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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Wed, 17 Nov 2010 09:14:55 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/17/t1289985300cxwbn0ak8zhqw31.htm/, Retrieved Thu, 25 Apr 2024 21:02:22 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=96544, Retrieved Thu, 25 Apr 2024 21:02:22 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

713

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-       [Multiple Regression] [] [2010-11-17 09:14:55] [d76b387543b13b5e3afd8ff9e5fdc89f] [Current]
-    D    [Multiple Regression] [Deterministic trend] [2010-11-19 12:13:34] [8a9a6f7c332640af31ddca253a8ded58] 
-   PD    [Multiple Regression] [deterministische ...] [2010-11-19 12:14:25] [74deae64b71f9d77c839af86f7c687b5] 
-   PD      [Multiple Regression] [] [2010-11-23 22:04:55] [8ef75e99f9f5061c72c54640f2f1c3e7] 
- R P       [Multiple Regression] [] [2011-11-21 20:29:39] [46d7ccc24e5d35a2decd922dfb3b3a39] 
-   PD    [Multiple Regression] [] [2010-11-19 12:14:29] [7789b9488494790f41ddb7f073cada1b] 
-    D      [Multiple Regression] [] [2010-11-19 14:12:16] [7789b9488494790f41ddb7f073cada1b] 
-    D      [Multiple Regression] [] [2010-11-19 14:22:18] [7789b9488494790f41ddb7f073cada1b] 
-   PD        [Multiple Regression] [multicoll. ] [2010-11-19 15:17:28] [74deae64b71f9d77c839af86f7c687b5] 
-   PD          [Multiple Regression] [] [2010-11-23 22:16:56] [8ef75e99f9f5061c72c54640f2f1c3e7] 
- R P           [Multiple Regression] [] [2011-11-21 20:38:13] [46d7ccc24e5d35a2decd922dfb3b3a39] 
-   PD    [Multiple Regression] [Workshop 7 - Incl...] [2010-11-19 13:07:40] [6f0e7a2d1a07390e3505a2db8288f975] 
-           [Multiple Regression] [W7] [2010-11-23 16:42:08] [5ddc7dfb25e070b079c4c8fcccc4d42e] 
- R PD    [Multiple Regression] [workshop 7 month-...] [2010-11-19 13:22:14] [4eaa304e6a28c475ba490fccf4c01ad3] 
-   PD    [Multiple Regression] [workshop 7 - tuto...] [2010-11-19 15:10:25] [956e8df26b41c50d9c6c2ec1b6a122a8] 
-    D      [Multiple Regression] [tutorial 7 - ] [2010-11-19 15:44:14] [74be16979710d4c4e7c6647856088456] 
-    D      [Multiple Regression] [workshop 7 - tuto...] [2010-11-19 15:44:14] [956e8df26b41c50d9c6c2ec1b6a122a8] 
F    D        [Multiple Regression] [WS7 comp 4] [2010-11-23 09:27:22] [dc30d19c3bc2be07fe595ad36c2cf923] 
-    D          [Multiple Regression] [ws 7] [2010-11-23 18:46:25] [4f85667043e8913570b3eb8f368f82b2] 
-               [Multiple Regression] [] [2010-12-02 15:17:23] [2e1e44f0ae3cb9513dc28781dfdb387b] 
-               [Multiple Regression] [] [2010-12-03 17:46:15] [b07cd1964830aab808142229b1166ece] 
-    D    [Multiple Regression] [Deterministic tre...] [2010-11-20 15:53:11] [95e8426e0df851c9330605aa1e892ab5] 
-   P       [Multiple Regression] [] [2010-12-01 15:02:43] [42a441ca3193af442aa2201743dfb347] 
- R PD      [Multiple Regression] [WS7 - determinist...] [2011-11-22 21:56:31] [74be16979710d4c4e7c6647856088456] 
- RMPD        [Structural Time Series Models] [] [2011-11-28 17:32:02] [c5b29addb16cc630d2ea8a9650ee6d6d] 
- RMP           [Exponential Smoothing] [] [2011-11-28 18:07:03] [c5b29addb16cc630d2ea8a9650ee6d6d] 
- R               [Exponential Smoothing] [] [2011-11-28 20:48:33] [74be16979710d4c4e7c6647856088456] 
- RMP             [Structural Time Series Models] [] [2011-11-28 21:17:27] [85c740202f6a07d51229b0a6b62ca11c] 
- R                 [Structural Time Series Models] [] [2011-12-06 16:14:27] [85c740202f6a07d51229b0a6b62ca11c] 
-  M                  [Structural Time Series Models] [] [2011-12-07 19:34:01] [d623f9be707a26b8ffaece1fc4d5a7ee] 
-  M                  [Structural Time Series Models] [] [2011-12-07 19:34:01] [d623f9be707a26b8ffaece1fc4d5a7ee] 
-  M                  [Structural Time Series Models] [] [2011-12-07 19:34:01] [d623f9be707a26b8ffaece1fc4d5a7ee] 
-                 [Exponential Smoothing] [] [2011-11-28 21:22:27] [85c740202f6a07d51229b0a6b62ca11c] 
- R               [Exponential Smoothing] [] [2011-12-06 16:15:42] [85c740202f6a07d51229b0a6b62ca11c] 
- RMP       [Multiple Regression] [] [2011-11-24 18:55:32] [7d86e24de0a0f8503ecffdef58e8c96c] 
- RMP       [Multiple Regression] [ws7 c)] [2011-11-24 20:03:00] [74be16979710d4c4e7c6647856088456] 
-   PD    [Multiple Regression] [Ws 7 - Determinis...] [2010-11-21 15:54:23] [603e2f5305d3a2a4e062624458fa1155] 
-    D      [Multiple Regression] [PAPER - Determini...] [2010-12-19 16:09:24] [603e2f5305d3a2a4e062624458fa1155] 
- R PD    [Multiple Regression] [ws7 Tutorial Popu...] [2010-11-22 11:00:33] [afe9379cca749d06b3d6872e02cc47ed] 
-           [Multiple Regression] [WS7 Determestic t...] [2010-11-23 10:32:25] [3fb95cad3bbcce10c72dbbcc5bec5662] 
-           [Multiple Regression] [WS 4: Toevoeging ...] [2010-12-02 17:54:13] [4f1a20f787b3465111b61213cdeef1a9] 
-           [Multiple Regression] [] [2010-12-02 19:08:37] [f47feae0308dca73181bb669fbad1c56] 
- RM          [Multiple Regression] [] [2012-11-20 16:55:39] [74be16979710d4c4e7c6647856088456] 
- RM          [Multiple Regression] [Workshop 7 (3)] [2012-11-20 19:44:33] [318be0e97d03618d227a3f8f0242bca0] 
- R           [Multiple Regression] [W7 ] [2012-11-20 19:55:43] [783d8509970888a6ec44a5a7a0d2a339] 
-   PD      [Multiple Regression] [] [2010-12-02 19:29:24] [94f4aa1c01e87d8321fffb341ed4df07] 
- R           [Multiple Regression] [] [2011-11-25 00:52:53] [74be16979710d4c4e7c6647856088456] 
- R P           [Multiple Regression] [] [2011-11-27 17:13:38] [3931071255a6f7f4a767409781cc5f7d] 
- RMPD          [Minimum Sample Size - Testing Mean] [] [2011-11-27 17:18:11] [3931071255a6f7f4a767409781cc5f7d] 

[Truncated]

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Dataseries X:

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Boxplots

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	16 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=96544&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=96544&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	16 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.00445406989737 + 0.161768138570369month[t] + 0.0339720452340411Connected[t] + 0.0426648655196235Separate[t] + 0.553914374083271Software[t] + 0.0693843908517855Happiness[t] -0.0309724601101621Depression[t] + 0.0210589104920521Belonging[t] -0.0218367544310276Belonging_Final[t] -0.00651732044274797t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  4.00445406989737 +  0.161768138570369month[t] +  0.0339720452340411Connected[t] +  0.0426648655196235Separate[t] +  0.553914374083271Software[t] +  0.0693843908517855Happiness[t] -0.0309724601101621Depression[t] +  0.0210589104920521Belonging[t] -0.0218367544310276Belonging_Final[t] -0.00651732044274797t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  4.00445406989737 +  0.161768138570369month[t] +  0.0339720452340411Connected[t] +  0.0426648655196235Separate[t] +  0.553914374083271Software[t] +  0.0693843908517855Happiness[t] -0.0309724601101621Depression[t] +  0.0210589104920521Belonging[t] -0.0218367544310276Belonging_Final[t] -0.00651732044274797t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.00445406989737 + 0.161768138570369month[t] + 0.0339720452340411Connected[t] + 0.0426648655196235Separate[t] + 0.553914374083271Software[t] + 0.0693843908517855Happiness[t] -0.0309724601101621Depression[t] + 0.0210589104920521Belonging[t] -0.0218367544310276Belonging_Final[t] -0.00651732044274797t + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.00445406989737	3.893744	1.0284	0.304725	0.152362
month	0.161768138570369	0.408738	0.3958	0.692604	0.346302
Connected	0.0339720452340411	0.034675	0.9797	0.328147	0.164074
Separate	0.0426648655196235	0.035196	1.2122	0.226558	0.113279
Software	0.553914374083271	0.054661	10.1337	0	0
Happiness	0.0693843908517855	0.058102	1.1942	0.233522	0.116761
Depression	-0.0309724601101621	0.042456	-0.7295	0.466353	0.233176
Belonging	0.0210589104920521	0.037979	0.5545	0.57973	0.289865
Belonging_Final	-0.0218367544310276	0.056419	-0.387	0.699047	0.349524
t	-0.00651732044274797	0.004332	-1.5043	0.13374	0.06687

\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) & 4.00445406989737 & 3.893744 & 1.0284 & 0.304725 & 0.152362 \tabularnewline
month & 0.161768138570369 & 0.408738 & 0.3958 & 0.692604 & 0.346302 \tabularnewline
Connected & 0.0339720452340411 & 0.034675 & 0.9797 & 0.328147 & 0.164074 \tabularnewline
Separate & 0.0426648655196235 & 0.035196 & 1.2122 & 0.226558 & 0.113279 \tabularnewline
Software & 0.553914374083271 & 0.054661 & 10.1337 & 0 & 0 \tabularnewline
Happiness & 0.0693843908517855 & 0.058102 & 1.1942 & 0.233522 & 0.116761 \tabularnewline
Depression & -0.0309724601101621 & 0.042456 & -0.7295 & 0.466353 & 0.233176 \tabularnewline
Belonging & 0.0210589104920521 & 0.037979 & 0.5545 & 0.57973 & 0.289865 \tabularnewline
Belonging_Final & -0.0218367544310276 & 0.056419 & -0.387 & 0.699047 & 0.349524 \tabularnewline
t & -0.00651732044274797 & 0.004332 & -1.5043 & 0.13374 & 0.06687 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&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]4.00445406989737[/C][C]3.893744[/C][C]1.0284[/C][C]0.304725[/C][C]0.152362[/C][/ROW]
[ROW][C]month[/C][C]0.161768138570369[/C][C]0.408738[/C][C]0.3958[/C][C]0.692604[/C][C]0.346302[/C][/ROW]
[ROW][C]Connected[/C][C]0.0339720452340411[/C][C]0.034675[/C][C]0.9797[/C][C]0.328147[/C][C]0.164074[/C][/ROW]
[ROW][C]Separate[/C][C]0.0426648655196235[/C][C]0.035196[/C][C]1.2122[/C][C]0.226558[/C][C]0.113279[/C][/ROW]
[ROW][C]Software[/C][C]0.553914374083271[/C][C]0.054661[/C][C]10.1337[/C][C]0[/C][C]0[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0693843908517855[/C][C]0.058102[/C][C]1.1942[/C][C]0.233522[/C][C]0.116761[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0309724601101621[/C][C]0.042456[/C][C]-0.7295[/C][C]0.466353[/C][C]0.233176[/C][/ROW]
[ROW][C]Belonging[/C][C]0.0210589104920521[/C][C]0.037979[/C][C]0.5545[/C][C]0.57973[/C][C]0.289865[/C][/ROW]
[ROW][C]Belonging_Final[/C][C]-0.0218367544310276[/C][C]0.056419[/C][C]-0.387[/C][C]0.699047[/C][C]0.349524[/C][/ROW]
[ROW][C]t[/C][C]-0.00651732044274797[/C][C]0.004332[/C][C]-1.5043[/C][C]0.13374[/C][C]0.06687[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	4.00445406989737	3.893744	1.0284	0.304725	0.152362
month	0.161768138570369	0.408738	0.3958	0.692604	0.346302
Connected	0.0339720452340411	0.034675	0.9797	0.328147	0.164074
Separate	0.0426648655196235	0.035196	1.2122	0.226558	0.113279
Software	0.553914374083271	0.054661	10.1337	0	0
Happiness	0.0693843908517855	0.058102	1.1942	0.233522	0.116761
Depression	-0.0309724601101621	0.042456	-0.7295	0.466353	0.233176
Belonging	0.0210589104920521	0.037979	0.5545	0.57973	0.289865
Belonging_Final	-0.0218367544310276	0.056419	-0.387	0.699047	0.349524
t	-0.00651732044274797	0.004332	-1.5043	0.13374	0.06687

Multiple Linear Regression - Regression Statistics
Multiple R	0.667804237836336
R-squared	0.445962500072170
Adjusted R-squared	0.426331250074727
F-TEST (value)	22.7169691247506
F-TEST (DF numerator)	9
F-TEST (DF denominator)	254
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	1.86017625008154
Sum Squared Residuals	878.904943067328

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.667804237836336 \tabularnewline
R-squared & 0.445962500072170 \tabularnewline
Adjusted R-squared & 0.426331250074727 \tabularnewline
F-TEST (value) & 22.7169691247506 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.86017625008154 \tabularnewline
Sum Squared Residuals & 878.904943067328 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.667804237836336[/C][/ROW]
[ROW][C]R-squared[/C][C]0.445962500072170[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.426331250074727[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]22.7169691247506[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/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]1.86017625008154[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]878.904943067328[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.667804237836336
R-squared	0.445962500072170
Adjusted R-squared	0.426331250074727
F-TEST (value)	22.7169691247506
F-TEST (DF numerator)	9
F-TEST (DF denominator)	254
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	1.86017625008154
Sum Squared Residuals	878.904943067328

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	13	16.131999294817	-3.13199929481699
2	16	15.773013320795	0.226986679205006
3	19	17.0643208813592	1.93567911864081
4	15	12.195441484357	2.80455851564301
5	14	16.4180322249668	-2.41803222496677
6	13	14.8802268925994	-1.88022689259937
7	19	15.3073888497988	3.69261115020122
8	15	17.0994109702753	-2.09941097027535
9	14	16.0716945323483	-2.07169453234826
10	15	14.4709276632402	0.529072336759826
11	16	15.0048320881255	0.995167911874469
12	16	16.1898230324591	-0.189823032459148
13	16	15.5298829760843	0.47011702391567
14	16	15.5014616820547	0.498538317945331
15	17	17.9849723007825	-0.984972300782522
16	15	15.4711693679876	-0.471169367987593
17	15	14.6115173032805	0.388482696719519
18	20	16.4150676139934	3.58493238600663
19	18	15.4898912080503	2.51010879194969
20	16	15.5511175520187	0.448882447981341
21	16	15.3608695373747	0.639130462625267
22	16	15.1405055659748	0.859494434025239
23	19	16.4738106847532	2.52618931524677
24	16	15.0882424925316	0.911757507468418
25	17	16.1489849108884	0.851015089111614
26	17	16.2540261576059	0.745973842394144
27	16	14.9707572768000	1.02924272319996
28	15	16.7314032980079	-1.73140329800789
29	16	15.7144480582795	0.28555194172051
30	14	14.1776976706257	-0.177697670625716
31	15	15.7271570905493	-0.727157090549255
32	12	12.8196274232436	-0.81962742324364
33	14	14.7900282358008	-0.790028235800783
34	16	15.9092330167818	0.0907669832181634
35	14	15.5241842748814	-1.52418427488142
36	10	12.9949264320293	-2.99492643202928
37	10	13.0360177328080	-3.03601773280804
38	14	15.7159143656349	-1.71591436563490
39	16	14.5189322404391	1.48106775956085
40	16	14.4639740033125	1.53602599668751
41	16	14.6922614387991	1.30773856120088
42	14	15.6917393515645	-1.69173935156446
43	20	17.4239904078573	2.57600959214275
44	14	14.1268333106255	-0.126833310625486
45	14	14.4277755307962	-0.427775530796168
46	11	15.4769010866658	-4.47690108666582
47	14	16.5016700566974	-2.50167005669743
48	15	15.0872733557269	-0.087273355726934
49	16	15.4344986815598	0.565501318440216
50	14	15.5957515567831	-1.59575155678312
51	16	16.9470055618408	-0.947005561840803
52	14	14.1029056640276	-0.102905664027613
53	12	14.9814432966391	-2.98144329663915
54	16	15.785793299267	0.214206700732997
55	9	11.3563715377051	-2.35637153770508
56	14	12.3349345138998	1.66506548610016
57	16	15.7945814318002	0.205418568199844
58	16	15.4209469984546	0.579053001545421
59	15	15.0830124726959	-0.0830124726959017
60	16	14.1512679246356	1.84873207536441
61	12	11.5069610190735	0.493038980926456
62	16	15.6140188033833	0.385981196616663
63	16	16.4810046021701	-0.481004602170093
64	14	14.6386116076605	-0.638611607660451
65	16	15.2160664980086	0.7839335019914
66	17	16.1283594964296	0.871640503570416
67	18	16.3659810285842	1.63401897141582
68	18	14.5460652096084	3.45393479039163
69	12	15.9859557929281	-3.98595579292812
70	16	15.7235896801084	0.276410319891618
71	10	13.4364628729273	-3.43646287292727
72	14	14.9824764129632	-0.982476412963164
73	18	17.0158830121805	0.984116987819492
74	18	17.2454880935873	0.754511906412746
75	16	15.3257205980238	0.674279401976158
76	17	13.5757520187901	3.42424798120991
77	16	16.4687902994353	-0.468790299435257
78	16	14.5522158332352	1.44778416676477
79	13	15.2614002582591	-2.26140025825906
80	16	15.1964525622985	0.803547437701546
81	16	15.7574496667773	0.242550333222654
82	16	15.7768516930372	0.223148306962762
83	15	15.7298773413515	-0.729877341351537
84	15	14.9299702304001	0.0700297695999293
85	16	14.2149434227545	1.78505657724555
86	14	14.2366309572854	-0.236630957285364
87	16	15.4094170749233	0.590582925076748
88	16	14.9000272038213	1.09997279617871
89	15	14.5575243875150	0.442475612484963
90	12	13.9195769686057	-1.91957696860565
91	17	16.7800226813811	0.219977318618857
92	16	15.8629648187689	0.137035181231110
93	15	15.130179843395	-0.130179843395007
94	13	15.0948418111599	-2.09484181115993
95	16	14.8308172507294	1.16918274927061
96	16	15.7987332349023	0.201266765097668
97	16	13.7556058789697	2.24439412103031
98	16	15.8344267629732	0.165573237026833
99	14	14.4661328340413	-0.466132834041305
100	16	17.0397108174705	-1.03971081747049
101	16	14.6988800176282	1.30111998237180
102	20	17.4606549280590	2.53934507194103
103	15	14.2209068914829	0.77909310851712
104	16	15.0049324640879	0.995067535912096
105	13	14.8816285614617	-1.88162856146174
106	17	15.7060829213038	1.29391707869617
107	16	15.7299469725030	0.270053027497047
108	16	14.3734121615249	1.62658783847514
109	12	12.3059825583899	-0.305982558389886
110	16	15.2836170632319	0.716382936768055
111	16	16.0107716671885	-0.0107716671884995
112	17	15.0350812641786	1.96491873582139
113	13	14.5406112403526	-1.54061124035262
114	12	14.5772750204350	-2.57727502043505
115	18	16.1499158080540	1.85008419194603
116	14	15.8490205615627	-1.84902056156272
117	14	13.1714374137032	0.82856258629681
118	13	14.7890480129649	-1.78904801296490
119	16	15.5214947103640	0.478505289635981
120	13	14.4173866932526	-1.41738669325258
121	16	15.3732648403476	0.626735159652424
122	13	15.8239894208261	-2.82398942082606
123	16	16.8206727627472	-0.820672762747186
124	15	15.8151943614052	-0.815194361405174
125	16	16.7758864663847	-0.775886466384696
126	15	14.6563176955803	0.343682304419720
127	17	15.5135458446765	1.48645415532348
128	15	13.9561905870924	1.04380941290757
129	12	14.6649696205487	-2.66496962054875
130	16	13.9484125272074	2.05158747279264
131	10	13.6993457863953	-3.69934578639529
132	16	13.4787326491481	2.52126735085192
133	12	14.1171191044060	-2.11711910440598
134	14	15.4969825827167	-1.49698258271669
135	15	15.0228514514540	-0.0228514514539678
136	13	12.0782835373044	0.921716462695573
137	15	14.4179752062836	0.582024793716389
138	11	13.4148843246345	-2.41488432463447
139	12	12.9615388133991	-0.961538813399098
140	11	13.3294291078386	-2.32942910783858
141	16	12.8198286730183	3.18017132698169
142	15	13.6114765181638	1.38852348183617
143	17	16.7647361618203	0.235263838179739
144	16	14.0972664814835	1.90273351851650
145	10	13.2326063570416	-3.23260635704162
146	18	15.4231808220058	2.57681917799422
147	13	14.8643149057299	-1.86431490572987
148	16	14.7811040097575	1.21889599024249
149	13	12.7593738938659	0.240626106134064
150	10	12.8479456212172	-2.8479456212172
151	15	15.8571245856987	-0.85712458569868
152	16	13.8243203686565	2.17567963134345
153	16	11.817790540179	4.18220945982101
154	14	12.1796252670648	1.8203747329352
155	10	12.3603674449609	-2.3603674449609
156	17	16.3563968526025	0.643603147397474
157	13	11.6399592761047	1.36004072389525
158	15	13.76067097381	1.23932902619001
159	16	14.4777838001372	1.52221619986284
160	12	12.6712686826820	-0.671268682682037
161	13	12.5501583930836	0.449841606916437
162	13	12.6951856659235	0.304814334076526
163	12	12.5325265824158	-0.532526582415784
164	17	16.2944365499899	0.705563450010119
165	15	13.7802694966019	1.21973050339809
166	10	11.6960484317299	-1.69604843172991
167	14	14.4098138706111	-0.409813870611069
168	11	14.2824014929904	-3.28240149299045
169	13	14.8696564507497	-1.86965645074970
170	16	14.5277256233795	1.4722743766205
171	12	10.5781596972200	1.42184030277997
172	16	15.4053957124387	0.594604287561291
173	12	13.9507326026571	-1.95073260265711
174	9	11.4327559786395	-2.43275597863949
175	12	14.9708875013237	-2.97088750132369
176	15	14.6153118153365	0.384688184663523
177	12	12.3484847331071	-0.348484733107104
178	12	12.7410235452396	-0.741023545239609
179	14	13.8482569329381	0.151743067061868
180	12	13.4363825724819	-1.43638257248190
181	16	15.0574225512253	0.94257744877469
182	11	11.5290900782481	-0.52909007824815
183	19	16.7023934664027	2.29760653359726
184	15	15.1861080347248	-0.186108034724758
185	8	14.6098477634635	-6.60984776346354
186	16	14.7948754284262	1.20512457157383
187	17	14.4889678086466	2.51103219135342
188	12	12.4492788886035	-0.449278888603544
189	11	11.5258253233485	-0.525825323348466
190	11	10.4839919409227	0.51600805907726
191	14	14.7297291026958	-0.72972910269576
192	16	15.4573408606036	0.542659139396387
193	12	9.79494997958053	2.20505002041947
194	16	14.0582376070539	1.94176239294607
195	13	13.6671267744826	-0.667126774482572
196	15	15.0059615481752	-0.00596154817517691
197	16	12.9612756487799	3.03872435122008
198	16	15.0216959506926	0.978304049307385
199	14	12.4654951689653	1.53450483103466
200	16	14.5360348798980	1.46396512010202
201	16	14.0101773215679	1.98982267843206
202	14	13.3505146449400	0.64948535505996
203	11	13.4248894641780	-2.42488946417804
204	12	14.4629453484512	-2.46294534845120
205	15	12.7281807329234	2.27181926707665
206	15	14.4392077029054	0.560792297094569
207	16	14.4841958335770	1.51580416642298
208	16	14.8639174831779	1.13608251682205
209	11	13.5735507320522	-2.57355073205221
210	15	13.9329916342196	1.06700836578037
211	12	14.1909393598993	-2.19093935989935
212	12	15.7003657756719	-3.7003657756719
213	15	14.0984721484565	0.90152785154354
214	15	12.0898039545762	2.9101960454238
215	16	14.4861173675814	1.51388263241863
216	14	13.0447911555702	0.955208844429784
217	17	14.5703847036008	2.42961529639919
218	14	13.8898769613098	0.110123038690205
219	13	11.8763407163770	1.12365928362303
220	15	15.0824598206262	-0.0824598206262444
221	13	14.5750556822787	-1.57505568227875
222	14	13.9860332277979	0.0139667722021436
223	15	14.1866032608968	0.813396739103202
224	12	13.0451003628764	-1.04510036287638
225	13	12.5277927132757	0.472207286724271
226	8	11.6960459918855	-3.69604599188549
227	14	13.6561993287026	0.34380067129741
228	14	12.9000716996087	1.09992830039132
229	11	12.1551096302894	-1.15510963028936
230	12	12.8141987020800	-0.814198702080019
231	13	11.1927984749469	1.80720152505309
232	10	13.1324013386614	-3.13240133866138
233	16	11.3238724214746	4.67612757852538
234	18	15.7016623752784	2.29833762472164
235	13	13.6986247386433	-0.698624738643332
236	11	13.1953213217862	-2.19532132178623
237	4	10.9144168771812	-6.91441687718123
238	13	14.0863865432717	-1.08638654327175
239	16	14.1114446024490	1.88855539755096
240	10	11.5810420842532	-1.58104208425324
241	12	12.1457895056583	-0.145789505658296
242	12	13.3223330284657	-1.32233302846566
243	10	8.80195508184795	1.19804491815205
244	13	10.9675970396727	2.03240296032730
245	15	13.4825144280370	1.51748557196297
246	12	11.7701175979104	0.229882402089584
247	14	12.6701662045844	1.32983379541564
248	10	12.2934478887145	-2.29344788871453
249	12	10.6014073663047	1.39859263369527
250	12	11.5045860621479	0.495413937852056
251	11	11.6933270811220	-0.693327081122031
252	10	11.4970254698553	-1.49702546985534
253	12	11.2277722925804	0.772227707419619
254	16	12.6330294634868	3.36697053651322
255	12	13.1033064447535	-1.10330644475347
256	14	13.6115101268512	0.388489873148829
257	16	14.1380220385243	1.86197796147568
258	14	11.4512965204411	2.54870347955891
259	13	13.9883658481621	-0.988365848162086
260	4	9.27855351815033	-5.27855351815033
261	15	13.4908178141533	1.50918218584669
262	11	14.7054478781160	-3.70544787811602
263	11	11.1003815456158	-0.100381545615756
264	14	12.5759984379471	1.42400156205287

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.131999294817 & -3.13199929481699 \tabularnewline
2 & 16 & 15.773013320795 & 0.226986679205006 \tabularnewline
3 & 19 & 17.0643208813592 & 1.93567911864081 \tabularnewline
4 & 15 & 12.195441484357 & 2.80455851564301 \tabularnewline
5 & 14 & 16.4180322249668 & -2.41803222496677 \tabularnewline
6 & 13 & 14.8802268925994 & -1.88022689259937 \tabularnewline
7 & 19 & 15.3073888497988 & 3.69261115020122 \tabularnewline
8 & 15 & 17.0994109702753 & -2.09941097027535 \tabularnewline
9 & 14 & 16.0716945323483 & -2.07169453234826 \tabularnewline
10 & 15 & 14.4709276632402 & 0.529072336759826 \tabularnewline
11 & 16 & 15.0048320881255 & 0.995167911874469 \tabularnewline
12 & 16 & 16.1898230324591 & -0.189823032459148 \tabularnewline
13 & 16 & 15.5298829760843 & 0.47011702391567 \tabularnewline
14 & 16 & 15.5014616820547 & 0.498538317945331 \tabularnewline
15 & 17 & 17.9849723007825 & -0.984972300782522 \tabularnewline
16 & 15 & 15.4711693679876 & -0.471169367987593 \tabularnewline
17 & 15 & 14.6115173032805 & 0.388482696719519 \tabularnewline
18 & 20 & 16.4150676139934 & 3.58493238600663 \tabularnewline
19 & 18 & 15.4898912080503 & 2.51010879194969 \tabularnewline
20 & 16 & 15.5511175520187 & 0.448882447981341 \tabularnewline
21 & 16 & 15.3608695373747 & 0.639130462625267 \tabularnewline
22 & 16 & 15.1405055659748 & 0.859494434025239 \tabularnewline
23 & 19 & 16.4738106847532 & 2.52618931524677 \tabularnewline
24 & 16 & 15.0882424925316 & 0.911757507468418 \tabularnewline
25 & 17 & 16.1489849108884 & 0.851015089111614 \tabularnewline
26 & 17 & 16.2540261576059 & 0.745973842394144 \tabularnewline
27 & 16 & 14.9707572768000 & 1.02924272319996 \tabularnewline
28 & 15 & 16.7314032980079 & -1.73140329800789 \tabularnewline
29 & 16 & 15.7144480582795 & 0.28555194172051 \tabularnewline
30 & 14 & 14.1776976706257 & -0.177697670625716 \tabularnewline
31 & 15 & 15.7271570905493 & -0.727157090549255 \tabularnewline
32 & 12 & 12.8196274232436 & -0.81962742324364 \tabularnewline
33 & 14 & 14.7900282358008 & -0.790028235800783 \tabularnewline
34 & 16 & 15.9092330167818 & 0.0907669832181634 \tabularnewline
35 & 14 & 15.5241842748814 & -1.52418427488142 \tabularnewline
36 & 10 & 12.9949264320293 & -2.99492643202928 \tabularnewline
37 & 10 & 13.0360177328080 & -3.03601773280804 \tabularnewline
38 & 14 & 15.7159143656349 & -1.71591436563490 \tabularnewline
39 & 16 & 14.5189322404391 & 1.48106775956085 \tabularnewline
40 & 16 & 14.4639740033125 & 1.53602599668751 \tabularnewline
41 & 16 & 14.6922614387991 & 1.30773856120088 \tabularnewline
42 & 14 & 15.6917393515645 & -1.69173935156446 \tabularnewline
43 & 20 & 17.4239904078573 & 2.57600959214275 \tabularnewline
44 & 14 & 14.1268333106255 & -0.126833310625486 \tabularnewline
45 & 14 & 14.4277755307962 & -0.427775530796168 \tabularnewline
46 & 11 & 15.4769010866658 & -4.47690108666582 \tabularnewline
47 & 14 & 16.5016700566974 & -2.50167005669743 \tabularnewline
48 & 15 & 15.0872733557269 & -0.087273355726934 \tabularnewline
49 & 16 & 15.4344986815598 & 0.565501318440216 \tabularnewline
50 & 14 & 15.5957515567831 & -1.59575155678312 \tabularnewline
51 & 16 & 16.9470055618408 & -0.947005561840803 \tabularnewline
52 & 14 & 14.1029056640276 & -0.102905664027613 \tabularnewline
53 & 12 & 14.9814432966391 & -2.98144329663915 \tabularnewline
54 & 16 & 15.785793299267 & 0.214206700732997 \tabularnewline
55 & 9 & 11.3563715377051 & -2.35637153770508 \tabularnewline
56 & 14 & 12.3349345138998 & 1.66506548610016 \tabularnewline
57 & 16 & 15.7945814318002 & 0.205418568199844 \tabularnewline
58 & 16 & 15.4209469984546 & 0.579053001545421 \tabularnewline
59 & 15 & 15.0830124726959 & -0.0830124726959017 \tabularnewline
60 & 16 & 14.1512679246356 & 1.84873207536441 \tabularnewline
61 & 12 & 11.5069610190735 & 0.493038980926456 \tabularnewline
62 & 16 & 15.6140188033833 & 0.385981196616663 \tabularnewline
63 & 16 & 16.4810046021701 & -0.481004602170093 \tabularnewline
64 & 14 & 14.6386116076605 & -0.638611607660451 \tabularnewline
65 & 16 & 15.2160664980086 & 0.7839335019914 \tabularnewline
66 & 17 & 16.1283594964296 & 0.871640503570416 \tabularnewline
67 & 18 & 16.3659810285842 & 1.63401897141582 \tabularnewline
68 & 18 & 14.5460652096084 & 3.45393479039163 \tabularnewline
69 & 12 & 15.9859557929281 & -3.98595579292812 \tabularnewline
70 & 16 & 15.7235896801084 & 0.276410319891618 \tabularnewline
71 & 10 & 13.4364628729273 & -3.43646287292727 \tabularnewline
72 & 14 & 14.9824764129632 & -0.982476412963164 \tabularnewline
73 & 18 & 17.0158830121805 & 0.984116987819492 \tabularnewline
74 & 18 & 17.2454880935873 & 0.754511906412746 \tabularnewline
75 & 16 & 15.3257205980238 & 0.674279401976158 \tabularnewline
76 & 17 & 13.5757520187901 & 3.42424798120991 \tabularnewline
77 & 16 & 16.4687902994353 & -0.468790299435257 \tabularnewline
78 & 16 & 14.5522158332352 & 1.44778416676477 \tabularnewline
79 & 13 & 15.2614002582591 & -2.26140025825906 \tabularnewline
80 & 16 & 15.1964525622985 & 0.803547437701546 \tabularnewline
81 & 16 & 15.7574496667773 & 0.242550333222654 \tabularnewline
82 & 16 & 15.7768516930372 & 0.223148306962762 \tabularnewline
83 & 15 & 15.7298773413515 & -0.729877341351537 \tabularnewline
84 & 15 & 14.9299702304001 & 0.0700297695999293 \tabularnewline
85 & 16 & 14.2149434227545 & 1.78505657724555 \tabularnewline
86 & 14 & 14.2366309572854 & -0.236630957285364 \tabularnewline
87 & 16 & 15.4094170749233 & 0.590582925076748 \tabularnewline
88 & 16 & 14.9000272038213 & 1.09997279617871 \tabularnewline
89 & 15 & 14.5575243875150 & 0.442475612484963 \tabularnewline
90 & 12 & 13.9195769686057 & -1.91957696860565 \tabularnewline
91 & 17 & 16.7800226813811 & 0.219977318618857 \tabularnewline
92 & 16 & 15.8629648187689 & 0.137035181231110 \tabularnewline
93 & 15 & 15.130179843395 & -0.130179843395007 \tabularnewline
94 & 13 & 15.0948418111599 & -2.09484181115993 \tabularnewline
95 & 16 & 14.8308172507294 & 1.16918274927061 \tabularnewline
96 & 16 & 15.7987332349023 & 0.201266765097668 \tabularnewline
97 & 16 & 13.7556058789697 & 2.24439412103031 \tabularnewline
98 & 16 & 15.8344267629732 & 0.165573237026833 \tabularnewline
99 & 14 & 14.4661328340413 & -0.466132834041305 \tabularnewline
100 & 16 & 17.0397108174705 & -1.03971081747049 \tabularnewline
101 & 16 & 14.6988800176282 & 1.30111998237180 \tabularnewline
102 & 20 & 17.4606549280590 & 2.53934507194103 \tabularnewline
103 & 15 & 14.2209068914829 & 0.77909310851712 \tabularnewline
104 & 16 & 15.0049324640879 & 0.995067535912096 \tabularnewline
105 & 13 & 14.8816285614617 & -1.88162856146174 \tabularnewline
106 & 17 & 15.7060829213038 & 1.29391707869617 \tabularnewline
107 & 16 & 15.7299469725030 & 0.270053027497047 \tabularnewline
108 & 16 & 14.3734121615249 & 1.62658783847514 \tabularnewline
109 & 12 & 12.3059825583899 & -0.305982558389886 \tabularnewline
110 & 16 & 15.2836170632319 & 0.716382936768055 \tabularnewline
111 & 16 & 16.0107716671885 & -0.0107716671884995 \tabularnewline
112 & 17 & 15.0350812641786 & 1.96491873582139 \tabularnewline
113 & 13 & 14.5406112403526 & -1.54061124035262 \tabularnewline
114 & 12 & 14.5772750204350 & -2.57727502043505 \tabularnewline
115 & 18 & 16.1499158080540 & 1.85008419194603 \tabularnewline
116 & 14 & 15.8490205615627 & -1.84902056156272 \tabularnewline
117 & 14 & 13.1714374137032 & 0.82856258629681 \tabularnewline
118 & 13 & 14.7890480129649 & -1.78904801296490 \tabularnewline
119 & 16 & 15.5214947103640 & 0.478505289635981 \tabularnewline
120 & 13 & 14.4173866932526 & -1.41738669325258 \tabularnewline
121 & 16 & 15.3732648403476 & 0.626735159652424 \tabularnewline
122 & 13 & 15.8239894208261 & -2.82398942082606 \tabularnewline
123 & 16 & 16.8206727627472 & -0.820672762747186 \tabularnewline
124 & 15 & 15.8151943614052 & -0.815194361405174 \tabularnewline
125 & 16 & 16.7758864663847 & -0.775886466384696 \tabularnewline
126 & 15 & 14.6563176955803 & 0.343682304419720 \tabularnewline
127 & 17 & 15.5135458446765 & 1.48645415532348 \tabularnewline
128 & 15 & 13.9561905870924 & 1.04380941290757 \tabularnewline
129 & 12 & 14.6649696205487 & -2.66496962054875 \tabularnewline
130 & 16 & 13.9484125272074 & 2.05158747279264 \tabularnewline
131 & 10 & 13.6993457863953 & -3.69934578639529 \tabularnewline
132 & 16 & 13.4787326491481 & 2.52126735085192 \tabularnewline
133 & 12 & 14.1171191044060 & -2.11711910440598 \tabularnewline
134 & 14 & 15.4969825827167 & -1.49698258271669 \tabularnewline
135 & 15 & 15.0228514514540 & -0.0228514514539678 \tabularnewline
136 & 13 & 12.0782835373044 & 0.921716462695573 \tabularnewline
137 & 15 & 14.4179752062836 & 0.582024793716389 \tabularnewline
138 & 11 & 13.4148843246345 & -2.41488432463447 \tabularnewline
139 & 12 & 12.9615388133991 & -0.961538813399098 \tabularnewline
140 & 11 & 13.3294291078386 & -2.32942910783858 \tabularnewline
141 & 16 & 12.8198286730183 & 3.18017132698169 \tabularnewline
142 & 15 & 13.6114765181638 & 1.38852348183617 \tabularnewline
143 & 17 & 16.7647361618203 & 0.235263838179739 \tabularnewline
144 & 16 & 14.0972664814835 & 1.90273351851650 \tabularnewline
145 & 10 & 13.2326063570416 & -3.23260635704162 \tabularnewline
146 & 18 & 15.4231808220058 & 2.57681917799422 \tabularnewline
147 & 13 & 14.8643149057299 & -1.86431490572987 \tabularnewline
148 & 16 & 14.7811040097575 & 1.21889599024249 \tabularnewline
149 & 13 & 12.7593738938659 & 0.240626106134064 \tabularnewline
150 & 10 & 12.8479456212172 & -2.8479456212172 \tabularnewline
151 & 15 & 15.8571245856987 & -0.85712458569868 \tabularnewline
152 & 16 & 13.8243203686565 & 2.17567963134345 \tabularnewline
153 & 16 & 11.817790540179 & 4.18220945982101 \tabularnewline
154 & 14 & 12.1796252670648 & 1.8203747329352 \tabularnewline
155 & 10 & 12.3603674449609 & -2.3603674449609 \tabularnewline
156 & 17 & 16.3563968526025 & 0.643603147397474 \tabularnewline
157 & 13 & 11.6399592761047 & 1.36004072389525 \tabularnewline
158 & 15 & 13.76067097381 & 1.23932902619001 \tabularnewline
159 & 16 & 14.4777838001372 & 1.52221619986284 \tabularnewline
160 & 12 & 12.6712686826820 & -0.671268682682037 \tabularnewline
161 & 13 & 12.5501583930836 & 0.449841606916437 \tabularnewline
162 & 13 & 12.6951856659235 & 0.304814334076526 \tabularnewline
163 & 12 & 12.5325265824158 & -0.532526582415784 \tabularnewline
164 & 17 & 16.2944365499899 & 0.705563450010119 \tabularnewline
165 & 15 & 13.7802694966019 & 1.21973050339809 \tabularnewline
166 & 10 & 11.6960484317299 & -1.69604843172991 \tabularnewline
167 & 14 & 14.4098138706111 & -0.409813870611069 \tabularnewline
168 & 11 & 14.2824014929904 & -3.28240149299045 \tabularnewline
169 & 13 & 14.8696564507497 & -1.86965645074970 \tabularnewline
170 & 16 & 14.5277256233795 & 1.4722743766205 \tabularnewline
171 & 12 & 10.5781596972200 & 1.42184030277997 \tabularnewline
172 & 16 & 15.4053957124387 & 0.594604287561291 \tabularnewline
173 & 12 & 13.9507326026571 & -1.95073260265711 \tabularnewline
174 & 9 & 11.4327559786395 & -2.43275597863949 \tabularnewline
175 & 12 & 14.9708875013237 & -2.97088750132369 \tabularnewline
176 & 15 & 14.6153118153365 & 0.384688184663523 \tabularnewline
177 & 12 & 12.3484847331071 & -0.348484733107104 \tabularnewline
178 & 12 & 12.7410235452396 & -0.741023545239609 \tabularnewline
179 & 14 & 13.8482569329381 & 0.151743067061868 \tabularnewline
180 & 12 & 13.4363825724819 & -1.43638257248190 \tabularnewline
181 & 16 & 15.0574225512253 & 0.94257744877469 \tabularnewline
182 & 11 & 11.5290900782481 & -0.52909007824815 \tabularnewline
183 & 19 & 16.7023934664027 & 2.29760653359726 \tabularnewline
184 & 15 & 15.1861080347248 & -0.186108034724758 \tabularnewline
185 & 8 & 14.6098477634635 & -6.60984776346354 \tabularnewline
186 & 16 & 14.7948754284262 & 1.20512457157383 \tabularnewline
187 & 17 & 14.4889678086466 & 2.51103219135342 \tabularnewline
188 & 12 & 12.4492788886035 & -0.449278888603544 \tabularnewline
189 & 11 & 11.5258253233485 & -0.525825323348466 \tabularnewline
190 & 11 & 10.4839919409227 & 0.51600805907726 \tabularnewline
191 & 14 & 14.7297291026958 & -0.72972910269576 \tabularnewline
192 & 16 & 15.4573408606036 & 0.542659139396387 \tabularnewline
193 & 12 & 9.79494997958053 & 2.20505002041947 \tabularnewline
194 & 16 & 14.0582376070539 & 1.94176239294607 \tabularnewline
195 & 13 & 13.6671267744826 & -0.667126774482572 \tabularnewline
196 & 15 & 15.0059615481752 & -0.00596154817517691 \tabularnewline
197 & 16 & 12.9612756487799 & 3.03872435122008 \tabularnewline
198 & 16 & 15.0216959506926 & 0.978304049307385 \tabularnewline
199 & 14 & 12.4654951689653 & 1.53450483103466 \tabularnewline
200 & 16 & 14.5360348798980 & 1.46396512010202 \tabularnewline
201 & 16 & 14.0101773215679 & 1.98982267843206 \tabularnewline
202 & 14 & 13.3505146449400 & 0.64948535505996 \tabularnewline
203 & 11 & 13.4248894641780 & -2.42488946417804 \tabularnewline
204 & 12 & 14.4629453484512 & -2.46294534845120 \tabularnewline
205 & 15 & 12.7281807329234 & 2.27181926707665 \tabularnewline
206 & 15 & 14.4392077029054 & 0.560792297094569 \tabularnewline
207 & 16 & 14.4841958335770 & 1.51580416642298 \tabularnewline
208 & 16 & 14.8639174831779 & 1.13608251682205 \tabularnewline
209 & 11 & 13.5735507320522 & -2.57355073205221 \tabularnewline
210 & 15 & 13.9329916342196 & 1.06700836578037 \tabularnewline
211 & 12 & 14.1909393598993 & -2.19093935989935 \tabularnewline
212 & 12 & 15.7003657756719 & -3.7003657756719 \tabularnewline
213 & 15 & 14.0984721484565 & 0.90152785154354 \tabularnewline
214 & 15 & 12.0898039545762 & 2.9101960454238 \tabularnewline
215 & 16 & 14.4861173675814 & 1.51388263241863 \tabularnewline
216 & 14 & 13.0447911555702 & 0.955208844429784 \tabularnewline
217 & 17 & 14.5703847036008 & 2.42961529639919 \tabularnewline
218 & 14 & 13.8898769613098 & 0.110123038690205 \tabularnewline
219 & 13 & 11.8763407163770 & 1.12365928362303 \tabularnewline
220 & 15 & 15.0824598206262 & -0.0824598206262444 \tabularnewline
221 & 13 & 14.5750556822787 & -1.57505568227875 \tabularnewline
222 & 14 & 13.9860332277979 & 0.0139667722021436 \tabularnewline
223 & 15 & 14.1866032608968 & 0.813396739103202 \tabularnewline
224 & 12 & 13.0451003628764 & -1.04510036287638 \tabularnewline
225 & 13 & 12.5277927132757 & 0.472207286724271 \tabularnewline
226 & 8 & 11.6960459918855 & -3.69604599188549 \tabularnewline
227 & 14 & 13.6561993287026 & 0.34380067129741 \tabularnewline
228 & 14 & 12.9000716996087 & 1.09992830039132 \tabularnewline
229 & 11 & 12.1551096302894 & -1.15510963028936 \tabularnewline
230 & 12 & 12.8141987020800 & -0.814198702080019 \tabularnewline
231 & 13 & 11.1927984749469 & 1.80720152505309 \tabularnewline
232 & 10 & 13.1324013386614 & -3.13240133866138 \tabularnewline
233 & 16 & 11.3238724214746 & 4.67612757852538 \tabularnewline
234 & 18 & 15.7016623752784 & 2.29833762472164 \tabularnewline
235 & 13 & 13.6986247386433 & -0.698624738643332 \tabularnewline
236 & 11 & 13.1953213217862 & -2.19532132178623 \tabularnewline
237 & 4 & 10.9144168771812 & -6.91441687718123 \tabularnewline
238 & 13 & 14.0863865432717 & -1.08638654327175 \tabularnewline
239 & 16 & 14.1114446024490 & 1.88855539755096 \tabularnewline
240 & 10 & 11.5810420842532 & -1.58104208425324 \tabularnewline
241 & 12 & 12.1457895056583 & -0.145789505658296 \tabularnewline
242 & 12 & 13.3223330284657 & -1.32233302846566 \tabularnewline
243 & 10 & 8.80195508184795 & 1.19804491815205 \tabularnewline
244 & 13 & 10.9675970396727 & 2.03240296032730 \tabularnewline
245 & 15 & 13.4825144280370 & 1.51748557196297 \tabularnewline
246 & 12 & 11.7701175979104 & 0.229882402089584 \tabularnewline
247 & 14 & 12.6701662045844 & 1.32983379541564 \tabularnewline
248 & 10 & 12.2934478887145 & -2.29344788871453 \tabularnewline
249 & 12 & 10.6014073663047 & 1.39859263369527 \tabularnewline
250 & 12 & 11.5045860621479 & 0.495413937852056 \tabularnewline
251 & 11 & 11.6933270811220 & -0.693327081122031 \tabularnewline
252 & 10 & 11.4970254698553 & -1.49702546985534 \tabularnewline
253 & 12 & 11.2277722925804 & 0.772227707419619 \tabularnewline
254 & 16 & 12.6330294634868 & 3.36697053651322 \tabularnewline
255 & 12 & 13.1033064447535 & -1.10330644475347 \tabularnewline
256 & 14 & 13.6115101268512 & 0.388489873148829 \tabularnewline
257 & 16 & 14.1380220385243 & 1.86197796147568 \tabularnewline
258 & 14 & 11.4512965204411 & 2.54870347955891 \tabularnewline
259 & 13 & 13.9883658481621 & -0.988365848162086 \tabularnewline
260 & 4 & 9.27855351815033 & -5.27855351815033 \tabularnewline
261 & 15 & 13.4908178141533 & 1.50918218584669 \tabularnewline
262 & 11 & 14.7054478781160 & -3.70544787811602 \tabularnewline
263 & 11 & 11.1003815456158 & -0.100381545615756 \tabularnewline
264 & 14 & 12.5759984379471 & 1.42400156205287 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&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]16.131999294817[/C][C]-3.13199929481699[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.773013320795[/C][C]0.226986679205006[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.0643208813592[/C][C]1.93567911864081[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.195441484357[/C][C]2.80455851564301[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.4180322249668[/C][C]-2.41803222496677[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.8802268925994[/C][C]-1.88022689259937[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.3073888497988[/C][C]3.69261115020122[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]17.0994109702753[/C][C]-2.09941097027535[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]16.0716945323483[/C][C]-2.07169453234826[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.4709276632402[/C][C]0.529072336759826[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]15.0048320881255[/C][C]0.995167911874469[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1898230324591[/C][C]-0.189823032459148[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5298829760843[/C][C]0.47011702391567[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.5014616820547[/C][C]0.498538317945331[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]17.9849723007825[/C][C]-0.984972300782522[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.4711693679876[/C][C]-0.471169367987593[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.6115173032805[/C][C]0.388482696719519[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4150676139934[/C][C]3.58493238600663[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.4898912080503[/C][C]2.51010879194969[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.5511175520187[/C][C]0.448882447981341[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.3608695373747[/C][C]0.639130462625267[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]15.1405055659748[/C][C]0.859494434025239[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.4738106847532[/C][C]2.52618931524677[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]15.0882424925316[/C][C]0.911757507468418[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.1489849108884[/C][C]0.851015089111614[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.2540261576059[/C][C]0.745973842394144[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.9707572768000[/C][C]1.02924272319996[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]16.7314032980079[/C][C]-1.73140329800789[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.7144480582795[/C][C]0.28555194172051[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.1776976706257[/C][C]-0.177697670625716[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]15.7271570905493[/C][C]-0.727157090549255[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.8196274232436[/C][C]-0.81962742324364[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.7900282358008[/C][C]-0.790028235800783[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.9092330167818[/C][C]0.0907669832181634[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.5241842748814[/C][C]-1.52418427488142[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9949264320293[/C][C]-2.99492643202928[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.0360177328080[/C][C]-3.03601773280804[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.7159143656349[/C][C]-1.71591436563490[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.5189322404391[/C][C]1.48106775956085[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.4639740033125[/C][C]1.53602599668751[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.6922614387991[/C][C]1.30773856120088[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.6917393515645[/C][C]-1.69173935156446[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.4239904078573[/C][C]2.57600959214275[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]14.1268333106255[/C][C]-0.126833310625486[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.4277755307962[/C][C]-0.427775530796168[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.4769010866658[/C][C]-4.47690108666582[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.5016700566974[/C][C]-2.50167005669743[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]15.0872733557269[/C][C]-0.087273355726934[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.4344986815598[/C][C]0.565501318440216[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.5957515567831[/C][C]-1.59575155678312[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]16.9470055618408[/C][C]-0.947005561840803[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.1029056640276[/C][C]-0.102905664027613[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.9814432966391[/C][C]-2.98144329663915[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.785793299267[/C][C]0.214206700732997[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.3563715377051[/C][C]-2.35637153770508[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]12.3349345138998[/C][C]1.66506548610016[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.7945814318002[/C][C]0.205418568199844[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.4209469984546[/C][C]0.579053001545421[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]15.0830124726959[/C][C]-0.0830124726959017[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.1512679246356[/C][C]1.84873207536441[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.5069610190735[/C][C]0.493038980926456[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.6140188033833[/C][C]0.385981196616663[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.4810046021701[/C][C]-0.481004602170093[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]14.6386116076605[/C][C]-0.638611607660451[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.2160664980086[/C][C]0.7839335019914[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.1283594964296[/C][C]0.871640503570416[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.3659810285842[/C][C]1.63401897141582[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.5460652096084[/C][C]3.45393479039163[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.9859557929281[/C][C]-3.98595579292812[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.7235896801084[/C][C]0.276410319891618[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]13.4364628729273[/C][C]-3.43646287292727[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9824764129632[/C][C]-0.982476412963164[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.0158830121805[/C][C]0.984116987819492[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.2454880935873[/C][C]0.754511906412746[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.3257205980238[/C][C]0.674279401976158[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.5757520187901[/C][C]3.42424798120991[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.4687902994353[/C][C]-0.468790299435257[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.5522158332352[/C][C]1.44778416676477[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.2614002582591[/C][C]-2.26140025825906[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]15.1964525622985[/C][C]0.803547437701546[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.7574496667773[/C][C]0.242550333222654[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.7768516930372[/C][C]0.223148306962762[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.7298773413515[/C][C]-0.729877341351537[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.9299702304001[/C][C]0.0700297695999293[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.2149434227545[/C][C]1.78505657724555[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.2366309572854[/C][C]-0.236630957285364[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.4094170749233[/C][C]0.590582925076748[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]14.9000272038213[/C][C]1.09997279617871[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.5575243875150[/C][C]0.442475612484963[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]13.9195769686057[/C][C]-1.91957696860565[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]16.7800226813811[/C][C]0.219977318618857[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.8629648187689[/C][C]0.137035181231110[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]15.130179843395[/C][C]-0.130179843395007[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]15.0948418111599[/C][C]-2.09484181115993[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.8308172507294[/C][C]1.16918274927061[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.7987332349023[/C][C]0.201266765097668[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.7556058789697[/C][C]2.24439412103031[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]15.8344267629732[/C][C]0.165573237026833[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.4661328340413[/C][C]-0.466132834041305[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.0397108174705[/C][C]-1.03971081747049[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.6988800176282[/C][C]1.30111998237180[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4606549280590[/C][C]2.53934507194103[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.2209068914829[/C][C]0.77909310851712[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]15.0049324640879[/C][C]0.995067535912096[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.8816285614617[/C][C]-1.88162856146174[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.7060829213038[/C][C]1.29391707869617[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.7299469725030[/C][C]0.270053027497047[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.3734121615249[/C][C]1.62658783847514[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.3059825583899[/C][C]-0.305982558389886[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.2836170632319[/C][C]0.716382936768055[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.0107716671885[/C][C]-0.0107716671884995[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.0350812641786[/C][C]1.96491873582139[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5406112403526[/C][C]-1.54061124035262[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.5772750204350[/C][C]-2.57727502043505[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.1499158080540[/C][C]1.85008419194603[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.8490205615627[/C][C]-1.84902056156272[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.1714374137032[/C][C]0.82856258629681[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.7890480129649[/C][C]-1.78904801296490[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.5214947103640[/C][C]0.478505289635981[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.4173866932526[/C][C]-1.41738669325258[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.3732648403476[/C][C]0.626735159652424[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]15.8239894208261[/C][C]-2.82398942082606[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]16.8206727627472[/C][C]-0.820672762747186[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]15.8151943614052[/C][C]-0.815194361405174[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.7758864663847[/C][C]-0.775886466384696[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.6563176955803[/C][C]0.343682304419720[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.5135458446765[/C][C]1.48645415532348[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.9561905870924[/C][C]1.04380941290757[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.6649696205487[/C][C]-2.66496962054875[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.9484125272074[/C][C]2.05158747279264[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.6993457863953[/C][C]-3.69934578639529[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4787326491481[/C][C]2.52126735085192[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.1171191044060[/C][C]-2.11711910440598[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.4969825827167[/C][C]-1.49698258271669[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.0228514514540[/C][C]-0.0228514514539678[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.0782835373044[/C][C]0.921716462695573[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.4179752062836[/C][C]0.582024793716389[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.4148843246345[/C][C]-2.41488432463447[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]12.9615388133991[/C][C]-0.961538813399098[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]13.3294291078386[/C][C]-2.32942910783858[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.8198286730183[/C][C]3.18017132698169[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.6114765181638[/C][C]1.38852348183617[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.7647361618203[/C][C]0.235263838179739[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]14.0972664814835[/C][C]1.90273351851650[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.2326063570416[/C][C]-3.23260635704162[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.4231808220058[/C][C]2.57681917799422[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]14.8643149057299[/C][C]-1.86431490572987[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]14.7811040097575[/C][C]1.21889599024249[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.7593738938659[/C][C]0.240626106134064[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.8479456212172[/C][C]-2.8479456212172[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]15.8571245856987[/C][C]-0.85712458569868[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.8243203686565[/C][C]2.17567963134345[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.817790540179[/C][C]4.18220945982101[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]12.1796252670648[/C][C]1.8203747329352[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]12.3603674449609[/C][C]-2.3603674449609[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.3563968526025[/C][C]0.643603147397474[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.6399592761047[/C][C]1.36004072389525[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.76067097381[/C][C]1.23932902619001[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.4777838001372[/C][C]1.52221619986284[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]12.6712686826820[/C][C]-0.671268682682037[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.5501583930836[/C][C]0.449841606916437[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.6951856659235[/C][C]0.304814334076526[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.5325265824158[/C][C]-0.532526582415784[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]16.2944365499899[/C][C]0.705563450010119[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.7802694966019[/C][C]1.21973050339809[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.6960484317299[/C][C]-1.69604843172991[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.4098138706111[/C][C]-0.409813870611069[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.2824014929904[/C][C]-3.28240149299045[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.8696564507497[/C][C]-1.86965645074970[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.5277256233795[/C][C]1.4722743766205[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]10.5781596972200[/C][C]1.42184030277997[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.4053957124387[/C][C]0.594604287561291[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.9507326026571[/C][C]-1.95073260265711[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.4327559786395[/C][C]-2.43275597863949[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]14.9708875013237[/C][C]-2.97088750132369[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.6153118153365[/C][C]0.384688184663523[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.3484847331071[/C][C]-0.348484733107104[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.7410235452396[/C][C]-0.741023545239609[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.8482569329381[/C][C]0.151743067061868[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.4363825724819[/C][C]-1.43638257248190[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.0574225512253[/C][C]0.94257744877469[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.5290900782481[/C][C]-0.52909007824815[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]16.7023934664027[/C][C]2.29760653359726[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.1861080347248[/C][C]-0.186108034724758[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.6098477634635[/C][C]-6.60984776346354[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.7948754284262[/C][C]1.20512457157383[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.4889678086466[/C][C]2.51103219135342[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.4492788886035[/C][C]-0.449278888603544[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.5258253233485[/C][C]-0.525825323348466[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4839919409227[/C][C]0.51600805907726[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.7297291026958[/C][C]-0.72972910269576[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.4573408606036[/C][C]0.542659139396387[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]9.79494997958053[/C][C]2.20505002041947[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.0582376070539[/C][C]1.94176239294607[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]13.6671267744826[/C][C]-0.667126774482572[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.0059615481752[/C][C]-0.00596154817517691[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.9612756487799[/C][C]3.03872435122008[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0216959506926[/C][C]0.978304049307385[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.4654951689653[/C][C]1.53450483103466[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.5360348798980[/C][C]1.46396512010202[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]14.0101773215679[/C][C]1.98982267843206[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.3505146449400[/C][C]0.64948535505996[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.4248894641780[/C][C]-2.42488946417804[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.4629453484512[/C][C]-2.46294534845120[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.7281807329234[/C][C]2.27181926707665[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.4392077029054[/C][C]0.560792297094569[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.4841958335770[/C][C]1.51580416642298[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]14.8639174831779[/C][C]1.13608251682205[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.5735507320522[/C][C]-2.57355073205221[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]13.9329916342196[/C][C]1.06700836578037[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.1909393598993[/C][C]-2.19093935989935[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.7003657756719[/C][C]-3.7003657756719[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]14.0984721484565[/C][C]0.90152785154354[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]12.0898039545762[/C][C]2.9101960454238[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.4861173675814[/C][C]1.51388263241863[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]13.0447911555702[/C][C]0.955208844429784[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.5703847036008[/C][C]2.42961529639919[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.8898769613098[/C][C]0.110123038690205[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]11.8763407163770[/C][C]1.12365928362303[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.0824598206262[/C][C]-0.0824598206262444[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.5750556822787[/C][C]-1.57505568227875[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]13.9860332277979[/C][C]0.0139667722021436[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.1866032608968[/C][C]0.813396739103202[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]13.0451003628764[/C][C]-1.04510036287638[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.5277927132757[/C][C]0.472207286724271[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.6960459918855[/C][C]-3.69604599188549[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.6561993287026[/C][C]0.34380067129741[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.9000716996087[/C][C]1.09992830039132[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.1551096302894[/C][C]-1.15510963028936[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]12.8141987020800[/C][C]-0.814198702080019[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.1927984749469[/C][C]1.80720152505309[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.1324013386614[/C][C]-3.13240133866138[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.3238724214746[/C][C]4.67612757852538[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.7016623752784[/C][C]2.29833762472164[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]13.6986247386433[/C][C]-0.698624738643332[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.1953213217862[/C][C]-2.19532132178623[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.9144168771812[/C][C]-6.91441687718123[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]14.0863865432717[/C][C]-1.08638654327175[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]14.1114446024490[/C][C]1.88855539755096[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.5810420842532[/C][C]-1.58104208425324[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.1457895056583[/C][C]-0.145789505658296[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.3223330284657[/C][C]-1.32233302846566[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]8.80195508184795[/C][C]1.19804491815205[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]10.9675970396727[/C][C]2.03240296032730[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4825144280370[/C][C]1.51748557196297[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.7701175979104[/C][C]0.229882402089584[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.6701662045844[/C][C]1.32983379541564[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]12.2934478887145[/C][C]-2.29344788871453[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.6014073663047[/C][C]1.39859263369527[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.5045860621479[/C][C]0.495413937852056[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.6933270811220[/C][C]-0.693327081122031[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.4970254698553[/C][C]-1.49702546985534[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.2277722925804[/C][C]0.772227707419619[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.6330294634868[/C][C]3.36697053651322[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.1033064447535[/C][C]-1.10330644475347[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.6115101268512[/C][C]0.388489873148829[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]14.1380220385243[/C][C]1.86197796147568[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.4512965204411[/C][C]2.54870347955891[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]13.9883658481621[/C][C]-0.988365848162086[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]9.27855351815033[/C][C]-5.27855351815033[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.4908178141533[/C][C]1.50918218584669[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.7054478781160[/C][C]-3.70544787811602[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]11.1003815456158[/C][C]-0.100381545615756[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.5759984379471[/C][C]1.42400156205287[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	13	16.131999294817	-3.13199929481699
2	16	15.773013320795	0.226986679205006
3	19	17.0643208813592	1.93567911864081
4	15	12.195441484357	2.80455851564301
5	14	16.4180322249668	-2.41803222496677
6	13	14.8802268925994	-1.88022689259937
7	19	15.3073888497988	3.69261115020122
8	15	17.0994109702753	-2.09941097027535
9	14	16.0716945323483	-2.07169453234826
10	15	14.4709276632402	0.529072336759826
11	16	15.0048320881255	0.995167911874469
12	16	16.1898230324591	-0.189823032459148
13	16	15.5298829760843	0.47011702391567
14	16	15.5014616820547	0.498538317945331
15	17	17.9849723007825	-0.984972300782522
16	15	15.4711693679876	-0.471169367987593
17	15	14.6115173032805	0.388482696719519
18	20	16.4150676139934	3.58493238600663
19	18	15.4898912080503	2.51010879194969
20	16	15.5511175520187	0.448882447981341
21	16	15.3608695373747	0.639130462625267
22	16	15.1405055659748	0.859494434025239
23	19	16.4738106847532	2.52618931524677
24	16	15.0882424925316	0.911757507468418
25	17	16.1489849108884	0.851015089111614
26	17	16.2540261576059	0.745973842394144
27	16	14.9707572768000	1.02924272319996
28	15	16.7314032980079	-1.73140329800789
29	16	15.7144480582795	0.28555194172051
30	14	14.1776976706257	-0.177697670625716
31	15	15.7271570905493	-0.727157090549255
32	12	12.8196274232436	-0.81962742324364
33	14	14.7900282358008	-0.790028235800783
34	16	15.9092330167818	0.0907669832181634
35	14	15.5241842748814	-1.52418427488142
36	10	12.9949264320293	-2.99492643202928
37	10	13.0360177328080	-3.03601773280804
38	14	15.7159143656349	-1.71591436563490
39	16	14.5189322404391	1.48106775956085
40	16	14.4639740033125	1.53602599668751
41	16	14.6922614387991	1.30773856120088
42	14	15.6917393515645	-1.69173935156446
43	20	17.4239904078573	2.57600959214275
44	14	14.1268333106255	-0.126833310625486
45	14	14.4277755307962	-0.427775530796168
46	11	15.4769010866658	-4.47690108666582
47	14	16.5016700566974	-2.50167005669743
48	15	15.0872733557269	-0.087273355726934
49	16	15.4344986815598	0.565501318440216
50	14	15.5957515567831	-1.59575155678312
51	16	16.9470055618408	-0.947005561840803
52	14	14.1029056640276	-0.102905664027613
53	12	14.9814432966391	-2.98144329663915
54	16	15.785793299267	0.214206700732997
55	9	11.3563715377051	-2.35637153770508
56	14	12.3349345138998	1.66506548610016
57	16	15.7945814318002	0.205418568199844
58	16	15.4209469984546	0.579053001545421
59	15	15.0830124726959	-0.0830124726959017
60	16	14.1512679246356	1.84873207536441
61	12	11.5069610190735	0.493038980926456
62	16	15.6140188033833	0.385981196616663
63	16	16.4810046021701	-0.481004602170093
64	14	14.6386116076605	-0.638611607660451
65	16	15.2160664980086	0.7839335019914
66	17	16.1283594964296	0.871640503570416
67	18	16.3659810285842	1.63401897141582
68	18	14.5460652096084	3.45393479039163
69	12	15.9859557929281	-3.98595579292812
70	16	15.7235896801084	0.276410319891618
71	10	13.4364628729273	-3.43646287292727
72	14	14.9824764129632	-0.982476412963164
73	18	17.0158830121805	0.984116987819492
74	18	17.2454880935873	0.754511906412746
75	16	15.3257205980238	0.674279401976158
76	17	13.5757520187901	3.42424798120991
77	16	16.4687902994353	-0.468790299435257
78	16	14.5522158332352	1.44778416676477
79	13	15.2614002582591	-2.26140025825906
80	16	15.1964525622985	0.803547437701546
81	16	15.7574496667773	0.242550333222654
82	16	15.7768516930372	0.223148306962762
83	15	15.7298773413515	-0.729877341351537
84	15	14.9299702304001	0.0700297695999293
85	16	14.2149434227545	1.78505657724555
86	14	14.2366309572854	-0.236630957285364
87	16	15.4094170749233	0.590582925076748
88	16	14.9000272038213	1.09997279617871
89	15	14.5575243875150	0.442475612484963
90	12	13.9195769686057	-1.91957696860565
91	17	16.7800226813811	0.219977318618857
92	16	15.8629648187689	0.137035181231110
93	15	15.130179843395	-0.130179843395007
94	13	15.0948418111599	-2.09484181115993
95	16	14.8308172507294	1.16918274927061
96	16	15.7987332349023	0.201266765097668
97	16	13.7556058789697	2.24439412103031
98	16	15.8344267629732	0.165573237026833
99	14	14.4661328340413	-0.466132834041305
100	16	17.0397108174705	-1.03971081747049
101	16	14.6988800176282	1.30111998237180
102	20	17.4606549280590	2.53934507194103
103	15	14.2209068914829	0.77909310851712
104	16	15.0049324640879	0.995067535912096
105	13	14.8816285614617	-1.88162856146174
106	17	15.7060829213038	1.29391707869617
107	16	15.7299469725030	0.270053027497047
108	16	14.3734121615249	1.62658783847514
109	12	12.3059825583899	-0.305982558389886
110	16	15.2836170632319	0.716382936768055
111	16	16.0107716671885	-0.0107716671884995
112	17	15.0350812641786	1.96491873582139
113	13	14.5406112403526	-1.54061124035262
114	12	14.5772750204350	-2.57727502043505
115	18	16.1499158080540	1.85008419194603
116	14	15.8490205615627	-1.84902056156272
117	14	13.1714374137032	0.82856258629681
118	13	14.7890480129649	-1.78904801296490
119	16	15.5214947103640	0.478505289635981
120	13	14.4173866932526	-1.41738669325258
121	16	15.3732648403476	0.626735159652424
122	13	15.8239894208261	-2.82398942082606
123	16	16.8206727627472	-0.820672762747186
124	15	15.8151943614052	-0.815194361405174
125	16	16.7758864663847	-0.775886466384696
126	15	14.6563176955803	0.343682304419720
127	17	15.5135458446765	1.48645415532348
128	15	13.9561905870924	1.04380941290757
129	12	14.6649696205487	-2.66496962054875
130	16	13.9484125272074	2.05158747279264
131	10	13.6993457863953	-3.69934578639529
132	16	13.4787326491481	2.52126735085192
133	12	14.1171191044060	-2.11711910440598
134	14	15.4969825827167	-1.49698258271669
135	15	15.0228514514540	-0.0228514514539678
136	13	12.0782835373044	0.921716462695573
137	15	14.4179752062836	0.582024793716389
138	11	13.4148843246345	-2.41488432463447
139	12	12.9615388133991	-0.961538813399098
140	11	13.3294291078386	-2.32942910783858
141	16	12.8198286730183	3.18017132698169
142	15	13.6114765181638	1.38852348183617
143	17	16.7647361618203	0.235263838179739
144	16	14.0972664814835	1.90273351851650
145	10	13.2326063570416	-3.23260635704162
146	18	15.4231808220058	2.57681917799422
147	13	14.8643149057299	-1.86431490572987
148	16	14.7811040097575	1.21889599024249
149	13	12.7593738938659	0.240626106134064
150	10	12.8479456212172	-2.8479456212172
151	15	15.8571245856987	-0.85712458569868
152	16	13.8243203686565	2.17567963134345
153	16	11.817790540179	4.18220945982101
154	14	12.1796252670648	1.8203747329352
155	10	12.3603674449609	-2.3603674449609
156	17	16.3563968526025	0.643603147397474
157	13	11.6399592761047	1.36004072389525
158	15	13.76067097381	1.23932902619001
159	16	14.4777838001372	1.52221619986284
160	12	12.6712686826820	-0.671268682682037
161	13	12.5501583930836	0.449841606916437
162	13	12.6951856659235	0.304814334076526
163	12	12.5325265824158	-0.532526582415784
164	17	16.2944365499899	0.705563450010119
165	15	13.7802694966019	1.21973050339809
166	10	11.6960484317299	-1.69604843172991
167	14	14.4098138706111	-0.409813870611069
168	11	14.2824014929904	-3.28240149299045
169	13	14.8696564507497	-1.86965645074970
170	16	14.5277256233795	1.4722743766205
171	12	10.5781596972200	1.42184030277997
172	16	15.4053957124387	0.594604287561291
173	12	13.9507326026571	-1.95073260265711
174	9	11.4327559786395	-2.43275597863949
175	12	14.9708875013237	-2.97088750132369
176	15	14.6153118153365	0.384688184663523
177	12	12.3484847331071	-0.348484733107104
178	12	12.7410235452396	-0.741023545239609
179	14	13.8482569329381	0.151743067061868
180	12	13.4363825724819	-1.43638257248190
181	16	15.0574225512253	0.94257744877469
182	11	11.5290900782481	-0.52909007824815
183	19	16.7023934664027	2.29760653359726
184	15	15.1861080347248	-0.186108034724758
185	8	14.6098477634635	-6.60984776346354
186	16	14.7948754284262	1.20512457157383
187	17	14.4889678086466	2.51103219135342
188	12	12.4492788886035	-0.449278888603544
189	11	11.5258253233485	-0.525825323348466
190	11	10.4839919409227	0.51600805907726
191	14	14.7297291026958	-0.72972910269576
192	16	15.4573408606036	0.542659139396387
193	12	9.79494997958053	2.20505002041947
194	16	14.0582376070539	1.94176239294607
195	13	13.6671267744826	-0.667126774482572
196	15	15.0059615481752	-0.00596154817517691
197	16	12.9612756487799	3.03872435122008
198	16	15.0216959506926	0.978304049307385
199	14	12.4654951689653	1.53450483103466
200	16	14.5360348798980	1.46396512010202
201	16	14.0101773215679	1.98982267843206
202	14	13.3505146449400	0.64948535505996
203	11	13.4248894641780	-2.42488946417804
204	12	14.4629453484512	-2.46294534845120
205	15	12.7281807329234	2.27181926707665
206	15	14.4392077029054	0.560792297094569
207	16	14.4841958335770	1.51580416642298
208	16	14.8639174831779	1.13608251682205
209	11	13.5735507320522	-2.57355073205221
210	15	13.9329916342196	1.06700836578037
211	12	14.1909393598993	-2.19093935989935
212	12	15.7003657756719	-3.7003657756719
213	15	14.0984721484565	0.90152785154354
214	15	12.0898039545762	2.9101960454238
215	16	14.4861173675814	1.51388263241863
216	14	13.0447911555702	0.955208844429784
217	17	14.5703847036008	2.42961529639919
218	14	13.8898769613098	0.110123038690205
219	13	11.8763407163770	1.12365928362303
220	15	15.0824598206262	-0.0824598206262444
221	13	14.5750556822787	-1.57505568227875
222	14	13.9860332277979	0.0139667722021436
223	15	14.1866032608968	0.813396739103202
224	12	13.0451003628764	-1.04510036287638
225	13	12.5277927132757	0.472207286724271
226	8	11.6960459918855	-3.69604599188549
227	14	13.6561993287026	0.34380067129741
228	14	12.9000716996087	1.09992830039132
229	11	12.1551096302894	-1.15510963028936
230	12	12.8141987020800	-0.814198702080019
231	13	11.1927984749469	1.80720152505309
232	10	13.1324013386614	-3.13240133866138
233	16	11.3238724214746	4.67612757852538
234	18	15.7016623752784	2.29833762472164
235	13	13.6986247386433	-0.698624738643332
236	11	13.1953213217862	-2.19532132178623
237	4	10.9144168771812	-6.91441687718123
238	13	14.0863865432717	-1.08638654327175
239	16	14.1114446024490	1.88855539755096
240	10	11.5810420842532	-1.58104208425324
241	12	12.1457895056583	-0.145789505658296
242	12	13.3223330284657	-1.32233302846566
243	10	8.80195508184795	1.19804491815205
244	13	10.9675970396727	2.03240296032730
245	15	13.4825144280370	1.51748557196297
246	12	11.7701175979104	0.229882402089584
247	14	12.6701662045844	1.32983379541564
248	10	12.2934478887145	-2.29344788871453
249	12	10.6014073663047	1.39859263369527
250	12	11.5045860621479	0.495413937852056
251	11	11.6933270811220	-0.693327081122031
252	10	11.4970254698553	-1.49702546985534
253	12	11.2277722925804	0.772227707419619
254	16	12.6330294634868	3.36697053651322
255	12	13.1033064447535	-1.10330644475347
256	14	13.6115101268512	0.388489873148829
257	16	14.1380220385243	1.86197796147568
258	14	11.4512965204411	2.54870347955891
259	13	13.9883658481621	-0.988365848162086
260	4	9.27855351815033	-5.27855351815033
261	15	13.4908178141533	1.50918218584669
262	11	14.7054478781160	-3.70544787811602
263	11	11.1003815456158	-0.100381545615756
264	14	12.5759984379471	1.42400156205287

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
13	0.309807656286817	0.619615312573634	0.690192343713183
14	0.2982458895084	0.5964917790168	0.7017541104916
15	0.180880645654023	0.361761291308045	0.819119354345977
16	0.137959527969735	0.275919055939470	0.862040472030265
17	0.143729595500073	0.287459191000146	0.856270404499927
18	0.295672611917276	0.591345223834551	0.704327388082725
19	0.245953051754568	0.491906103509136	0.754046948245432
20	0.197531582642351	0.395063165284702	0.802468417357649
21	0.154638598434060	0.309277196868121	0.84536140156594
22	0.181179794070588	0.362359588141176	0.818820205929412
23	0.292370722019794	0.584741444039587	0.707629277980206
24	0.413563053247267	0.827126106494533	0.586436946752734
25	0.343871514454900	0.687743028909799	0.6561284855451
26	0.292745395722881	0.585490791445763	0.707254604277119
27	0.280275008418916	0.560550016837832	0.719724991581084
28	0.396379429891148	0.792758859782295	0.603620570108852
29	0.342705495061225	0.68541099012245	0.657294504938775
30	0.453590892318243	0.907181784636485	0.546409107681757
31	0.4098203042314	0.8196406084628	0.5901796957686
32	0.379700407782805	0.75940081556561	0.620299592217195
33	0.362199175090739	0.724398350181479	0.637800824909261
34	0.323061419276707	0.646122838553414	0.676938580723293
35	0.27741937114134	0.55483874228268	0.72258062885866
36	0.412599374054753	0.825198748109507	0.587400625945247
37	0.440486741081803	0.880973482163606	0.559513258918197
38	0.414751240937735	0.82950248187547	0.585248759062265
39	0.458996581775578	0.917993163551155	0.541003418224423
40	0.438077281087412	0.876154562174824	0.561922718912588
41	0.397606632447526	0.795213264895052	0.602393367552474
42	0.357011020557362	0.714022041114724	0.642988979442638
43	0.375803323977979	0.751606647955958	0.624196676022021
44	0.32621919593697	0.65243839187394	0.67378080406303
45	0.297228597638108	0.594457195276217	0.702771402361892
46	0.477767576714707	0.955535153429414	0.522232423285293
47	0.566983009470338	0.866033981059324	0.433016990529662
48	0.523694345550082	0.952611308899836	0.476305654449918
49	0.547090628451313	0.905818743097374	0.452909371548687
50	0.519795954142248	0.960408091715505	0.480204045857752
51	0.4743618932566	0.9487237865132	0.5256381067434
52	0.432325414352373	0.864650828704747	0.567674585647627
53	0.432585256747916	0.865170513495831	0.567414743252084
54	0.389368675455909	0.778737350911817	0.610631324544092
55	0.377808513790590	0.755617027581181	0.622191486209410
56	0.373594207972992	0.747188415945983	0.626405792027008
57	0.332852275405684	0.665704550811369	0.667147724594316
58	0.312980767817856	0.625961535635712	0.687019232182144
59	0.281726108362702	0.563452216725403	0.718273891637298
60	0.301554968100597	0.603109936201195	0.698445031899403
61	0.276786835199114	0.553573670398227	0.723213164800886
62	0.250508189541221	0.501016379082442	0.749491810458779
63	0.220683000232985	0.44136600046597	0.779316999767015
64	0.191708281277336	0.383416562554672	0.808291718722664
65	0.16936819567674	0.33873639135348	0.83063180432326
66	0.143783931925017	0.287567863850034	0.856216068074983
67	0.124528037277648	0.249056074555296	0.875471962722352
68	0.150714126857997	0.301428253715993	0.849285873142003
69	0.343888668951922	0.687777337903845	0.656111331048078
70	0.305643256779926	0.611286513559851	0.694356743220074
71	0.456877585579658	0.913755171159316	0.543122414420342
72	0.419928697897371	0.839857395794743	0.580071302102628
73	0.410250267685324	0.820500535370647	0.589749732314676
74	0.389475787851003	0.778951575702005	0.610524212148997
75	0.353067153266133	0.706134306532266	0.646932846733867
76	0.402478661546027	0.804957323092054	0.597521338453973
77	0.367580301321666	0.735160602643333	0.632419698678334
78	0.338946911791492	0.677893823582983	0.661053088208508
79	0.36638716681708	0.73277433363416	0.63361283318292
80	0.334440607313753	0.668881214627506	0.665559392686247
81	0.30266028008657	0.60532056017314	0.69733971991343
82	0.268712181387127	0.537424362774254	0.731287818612873
83	0.243465165126896	0.486930330253792	0.756534834873104
84	0.213395170054051	0.426790340108102	0.786604829945949
85	0.204473723326668	0.408947446653337	0.795526276673332
86	0.177589055744589	0.355178111489177	0.822410944255412
87	0.155174073416449	0.310348146832897	0.844825926583551
88	0.141134380284515	0.28226876056903	0.858865619715485
89	0.120988634340955	0.24197726868191	0.879011365659045
90	0.120255159235721	0.240510318471442	0.879744840764279
91	0.102479154169644	0.204958308339289	0.897520845830356
92	0.0891461020230827	0.178292204046165	0.910853897976917
93	0.0755107869145351	0.151021573829070	0.924489213085465
94	0.079532704214503	0.159065408429006	0.920467295785497
95	0.0718327780761281	0.143665556152256	0.928167221923872
96	0.0597718811839649	0.119543762367930	0.940228118816035
97	0.0636513083515619	0.127302616703124	0.936348691648438
98	0.052572922589572	0.105145845179144	0.947427077410428
99	0.0433485278831651	0.0866970557663303	0.956651472116835
100	0.0375392408916114	0.0750784817832228	0.962460759108389
101	0.0329904108910570	0.0659808217821139	0.967009589108943
102	0.0398393796776781	0.0796787593553563	0.960160620322322
103	0.0335490789628814	0.0670981579257629	0.966450921037119
104	0.0305201746076184	0.0610403492152367	0.969479825392382
105	0.0357051447144569	0.0714102894289139	0.964294855285543
106	0.0312650391700154	0.0625300783400308	0.968734960829985
107	0.0253096768372012	0.0506193536744024	0.97469032316280
108	0.0246049676929592	0.0492099353859185	0.97539503230704
109	0.0198406477697905	0.0396812955395811	0.98015935223021
110	0.0162400714068859	0.0324801428137718	0.983759928593114
111	0.0128113236124551	0.0256226472249102	0.987188676387545
112	0.0132259030977173	0.0264518061954346	0.986774096902283
113	0.0121222773762483	0.0242445547524966	0.987877722623752
114	0.0169804189106440	0.0339608378212881	0.983019581089356
115	0.0161927520666967	0.0323855041333933	0.983807247933303
116	0.0154867349703439	0.0309734699406878	0.984513265029656
117	0.0127934248544036	0.0255868497088072	0.987206575145596
118	0.0126934873005723	0.0253869746011446	0.987306512699428
119	0.0101274243512959	0.0202548487025918	0.989872575648704
120	0.00894941565671435	0.0178988313134287	0.991050584343286
121	0.00713553477374165	0.0142710695474833	0.992864465226258
122	0.0103009170498025	0.0206018340996051	0.989699082950197
123	0.00841822557905408	0.0168364511581082	0.991581774420946
124	0.0070149585935322	0.0140299171870644	0.992985041406468
125	0.00561230814253774	0.0112246162850755	0.994387691857462
126	0.00437309194881369	0.00874618389762738	0.995626908051186
127	0.00411488230820626	0.00822976461641251	0.995885117691794
128	0.00337133624223543	0.00674267248447086	0.996628663757765
129	0.00459519241291721	0.00919038482583442	0.995404807587083
130	0.00520833343649414	0.0104166668729883	0.994791666563506
131	0.0106571654805978	0.0213143309611957	0.989342834519402
132	0.0131637837419432	0.0263275674838864	0.986836216258057
133	0.0140598613911444	0.0281197227822888	0.985940138608856
134	0.0130266352059284	0.0260532704118567	0.986973364794072
135	0.0102683003920224	0.0205366007840448	0.989731699607978
136	0.00869301337051336	0.0173860267410267	0.991306986629487
137	0.00691930633764624	0.0138386126752925	0.993080693662354
138	0.00873124414601983	0.0174624882920397	0.99126875585398
139	0.00744563128460002	0.0148912625692000	0.9925543687154
140	0.00911502152519438	0.0182300430503888	0.990884978474806
141	0.0149244978879686	0.0298489957759371	0.985075502112031
142	0.0142880269095094	0.0285760538190188	0.98571197309049
143	0.011787519191028	0.023575038382056	0.988212480808972
144	0.0117424736210715	0.0234849472421429	0.988257526378929
145	0.0208545078804271	0.0417090157608542	0.979145492119573
146	0.0248966680831226	0.0497933361662452	0.975103331916877
147	0.0264235823408604	0.0528471646817209	0.97357641765914
148	0.0230885578000696	0.0461771156001392	0.97691144219993
149	0.0185753774122757	0.0371507548245514	0.981424622587724
150	0.0265826413417606	0.0531652826835212	0.97341735865824
151	0.0226851778306609	0.0453703556613219	0.97731482216934
152	0.0252751966213975	0.050550393242795	0.974724803378602
153	0.0510143851879781	0.102028770375956	0.948985614812022
154	0.0499973342773527	0.0999946685547055	0.950002665722647
155	0.0590562582320646	0.118112516464129	0.940943741767935
156	0.0500529447297188	0.100105889459438	0.94994705527028
157	0.0442378578740246	0.0884757157480492	0.955762142125975
158	0.0379777226716838	0.0759554453433676	0.962022277328316
159	0.0367545381458568	0.0735090762917135	0.963245461854143
160	0.0310593851744151	0.0621187703488301	0.968940614825585
161	0.0251750377915537	0.0503500755831075	0.974824962208446
162	0.0203315323011701	0.0406630646023401	0.97966846769883
163	0.0168868472534704	0.0337736945069407	0.98311315274653
164	0.0140850690537459	0.0281701381074917	0.985914930946254
165	0.0120377696397923	0.0240755392795847	0.987962230360208
166	0.0127190399347612	0.0254380798695223	0.987280960065239
167	0.0101566261066436	0.0203132522132872	0.989843373893356
168	0.0157253938285429	0.0314507876570858	0.984274606171457
169	0.0160887007977170	0.0321774015954341	0.983911299202283
170	0.0150008269342025	0.0300016538684049	0.984999173065798
171	0.0135895026618326	0.0271790053236653	0.986410497338167
172	0.0108394207967232	0.0216788415934464	0.989160579203277
173	0.0108441625791383	0.0216883251582767	0.989155837420862
174	0.012596459523381	0.025192919046762	0.987403540476619
175	0.0166311203022962	0.0332622406045924	0.983368879697704
176	0.0132480745199596	0.0264961490399192	0.98675192548004
177	0.0104529209878134	0.0209058419756267	0.989547079012187
178	0.0087685983094409	0.0175371966188818	0.99123140169056
179	0.00675218099441613	0.0135043619888323	0.993247819005584
180	0.00595227577786152	0.0119045515557230	0.994047724222138
181	0.00482021255237906	0.00964042510475813	0.995179787447621
182	0.00370834631168027	0.00741669262336055	0.99629165368832
183	0.00398692399058354	0.00797384798116709	0.996013076009416
184	0.00300961008665678	0.00601922017331355	0.996990389913343
185	0.0853414771838382	0.170682954367676	0.914658522816162
186	0.0760215335305705	0.152043067061141	0.92397846646943
187	0.0837413923821005	0.167482784764201	0.9162586076179
188	0.07004031937687	0.14008063875374	0.92995968062313
189	0.0622875967513268	0.124575193502654	0.937712403248673
190	0.0517448100959109	0.103489620191822	0.94825518990409
191	0.0477314993313587	0.0954629986627174	0.952268500668641
192	0.0392257519398204	0.0784515038796408	0.96077424806018
193	0.0400243521800498	0.0800487043600997	0.95997564781995
194	0.0403047081110405	0.080609416222081	0.95969529188896
195	0.0347006081485536	0.0694012162971073	0.965299391851446
196	0.0277661518378843	0.0555323036757687	0.972233848162116
197	0.0351052014872313	0.0702104029744626	0.964894798512769
198	0.0285014184612945	0.0570028369225891	0.971498581538705
199	0.0255314443827536	0.0510628887655073	0.974468555617246
200	0.0218196101218239	0.0436392202436477	0.978180389878176
201	0.0203269456484067	0.0406538912968134	0.979673054351593
202	0.0170899582487389	0.0341799164974778	0.98291004175126
203	0.0224643847935013	0.0449287695870026	0.977535615206499
204	0.0261548877981559	0.0523097755963118	0.973845112201844
205	0.0273219956510728	0.0546439913021456	0.972678004348927
206	0.0212570119068145	0.0425140238136291	0.978742988093185
207	0.0202653106365932	0.0405306212731864	0.979734689363407
208	0.0164688259688203	0.0329376519376405	0.98353117403118
209	0.0183272916694650	0.0366545833389300	0.981672708330535
210	0.014501003799243	0.029002007598486	0.985498996200757
211	0.0166182867149888	0.0332365734299777	0.983381713285011
212	0.0270900954587140	0.0541801909174280	0.972909904541286
213	0.0209131162419586	0.0418262324839172	0.979086883758041
214	0.027113933494889	0.054227866989778	0.97288606650511
215	0.0228725494160244	0.0457450988320489	0.977127450583976
216	0.0175319782798157	0.0350639565596314	0.982468021720184
217	0.0192559593869288	0.0385119187738577	0.980744040613071
218	0.0160980713819302	0.0321961427638604	0.98390192861807
219	0.0148737932887074	0.0297475865774149	0.985126206711293
220	0.0112452282629419	0.0224904565258838	0.988754771737058
221	0.00926182737223425	0.0185236547444685	0.990738172627766
222	0.0065656275058431	0.0131312550116862	0.993434372494157
223	0.00498203627846982	0.00996407255693964	0.99501796372153
224	0.00370586623701994	0.00741173247403989	0.99629413376298
225	0.00312910572486035	0.00625821144972071	0.99687089427514
226	0.0073080238334571	0.0146160476669142	0.992691976166543
227	0.0056565869724856	0.0113131739449712	0.994343413027514
228	0.00413003590427982	0.00826007180855963	0.99586996409572
229	0.00290095626256910	0.00580191252513821	0.997099043737431
230	0.00210006526868233	0.00420013053736466	0.997899934731318
231	0.00187435006150138	0.00374870012300276	0.998125649938499
232	0.00445268431966201	0.00890536863932401	0.995547315680338
233	0.0186513607143556	0.0373027214287112	0.981348639285644
234	0.0287056236663921	0.0574112473327842	0.971294376333608
235	0.0202408156875338	0.0404816313750676	0.979759184312466
236	0.0166385178465637	0.0332770356931275	0.983361482153436
237	0.158811527145599	0.317623054291199	0.8411884728544
238	0.122053659592906	0.244107319185811	0.877946340407095
239	0.0996048696320387	0.199209739264077	0.900395130367961
240	0.0750857716468304	0.150171543293661	0.92491422835317
241	0.0646426417753595	0.129285283550719	0.93535735822464
242	0.102490655553289	0.204981311106577	0.897509344446711
243	0.081491720832899	0.162983441665798	0.9185082791671
244	0.0842682626125305	0.168536525225061	0.91573173738747
245	0.0665871193041568	0.133174238608314	0.933412880695843
246	0.0544356840043543	0.108871368008709	0.945564315995646
247	0.0329907544098212	0.0659815088196424	0.967009245590179
248	0.0266391640759625	0.053278328151925	0.973360835924038
249	0.0224913576759628	0.0449827153519257	0.977508642324037
250	0.0664473388463356	0.132894677692671	0.933552661153664
251	0.0486972483238257	0.0973944966476515	0.951302751676174

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.309807656286817 & 0.619615312573634 & 0.690192343713183 \tabularnewline
14 & 0.2982458895084 & 0.5964917790168 & 0.7017541104916 \tabularnewline
15 & 0.180880645654023 & 0.361761291308045 & 0.819119354345977 \tabularnewline
16 & 0.137959527969735 & 0.275919055939470 & 0.862040472030265 \tabularnewline
17 & 0.143729595500073 & 0.287459191000146 & 0.856270404499927 \tabularnewline
18 & 0.295672611917276 & 0.591345223834551 & 0.704327388082725 \tabularnewline
19 & 0.245953051754568 & 0.491906103509136 & 0.754046948245432 \tabularnewline
20 & 0.197531582642351 & 0.395063165284702 & 0.802468417357649 \tabularnewline
21 & 0.154638598434060 & 0.309277196868121 & 0.84536140156594 \tabularnewline
22 & 0.181179794070588 & 0.362359588141176 & 0.818820205929412 \tabularnewline
23 & 0.292370722019794 & 0.584741444039587 & 0.707629277980206 \tabularnewline
24 & 0.413563053247267 & 0.827126106494533 & 0.586436946752734 \tabularnewline
25 & 0.343871514454900 & 0.687743028909799 & 0.6561284855451 \tabularnewline
26 & 0.292745395722881 & 0.585490791445763 & 0.707254604277119 \tabularnewline
27 & 0.280275008418916 & 0.560550016837832 & 0.719724991581084 \tabularnewline
28 & 0.396379429891148 & 0.792758859782295 & 0.603620570108852 \tabularnewline
29 & 0.342705495061225 & 0.68541099012245 & 0.657294504938775 \tabularnewline
30 & 0.453590892318243 & 0.907181784636485 & 0.546409107681757 \tabularnewline
31 & 0.4098203042314 & 0.8196406084628 & 0.5901796957686 \tabularnewline
32 & 0.379700407782805 & 0.75940081556561 & 0.620299592217195 \tabularnewline
33 & 0.362199175090739 & 0.724398350181479 & 0.637800824909261 \tabularnewline
34 & 0.323061419276707 & 0.646122838553414 & 0.676938580723293 \tabularnewline
35 & 0.27741937114134 & 0.55483874228268 & 0.72258062885866 \tabularnewline
36 & 0.412599374054753 & 0.825198748109507 & 0.587400625945247 \tabularnewline
37 & 0.440486741081803 & 0.880973482163606 & 0.559513258918197 \tabularnewline
38 & 0.414751240937735 & 0.82950248187547 & 0.585248759062265 \tabularnewline
39 & 0.458996581775578 & 0.917993163551155 & 0.541003418224423 \tabularnewline
40 & 0.438077281087412 & 0.876154562174824 & 0.561922718912588 \tabularnewline
41 & 0.397606632447526 & 0.795213264895052 & 0.602393367552474 \tabularnewline
42 & 0.357011020557362 & 0.714022041114724 & 0.642988979442638 \tabularnewline
43 & 0.375803323977979 & 0.751606647955958 & 0.624196676022021 \tabularnewline
44 & 0.32621919593697 & 0.65243839187394 & 0.67378080406303 \tabularnewline
45 & 0.297228597638108 & 0.594457195276217 & 0.702771402361892 \tabularnewline
46 & 0.477767576714707 & 0.955535153429414 & 0.522232423285293 \tabularnewline
47 & 0.566983009470338 & 0.866033981059324 & 0.433016990529662 \tabularnewline
48 & 0.523694345550082 & 0.952611308899836 & 0.476305654449918 \tabularnewline
49 & 0.547090628451313 & 0.905818743097374 & 0.452909371548687 \tabularnewline
50 & 0.519795954142248 & 0.960408091715505 & 0.480204045857752 \tabularnewline
51 & 0.4743618932566 & 0.9487237865132 & 0.5256381067434 \tabularnewline
52 & 0.432325414352373 & 0.864650828704747 & 0.567674585647627 \tabularnewline
53 & 0.432585256747916 & 0.865170513495831 & 0.567414743252084 \tabularnewline
54 & 0.389368675455909 & 0.778737350911817 & 0.610631324544092 \tabularnewline
55 & 0.377808513790590 & 0.755617027581181 & 0.622191486209410 \tabularnewline
56 & 0.373594207972992 & 0.747188415945983 & 0.626405792027008 \tabularnewline
57 & 0.332852275405684 & 0.665704550811369 & 0.667147724594316 \tabularnewline
58 & 0.312980767817856 & 0.625961535635712 & 0.687019232182144 \tabularnewline
59 & 0.281726108362702 & 0.563452216725403 & 0.718273891637298 \tabularnewline
60 & 0.301554968100597 & 0.603109936201195 & 0.698445031899403 \tabularnewline
61 & 0.276786835199114 & 0.553573670398227 & 0.723213164800886 \tabularnewline
62 & 0.250508189541221 & 0.501016379082442 & 0.749491810458779 \tabularnewline
63 & 0.220683000232985 & 0.44136600046597 & 0.779316999767015 \tabularnewline
64 & 0.191708281277336 & 0.383416562554672 & 0.808291718722664 \tabularnewline
65 & 0.16936819567674 & 0.33873639135348 & 0.83063180432326 \tabularnewline
66 & 0.143783931925017 & 0.287567863850034 & 0.856216068074983 \tabularnewline
67 & 0.124528037277648 & 0.249056074555296 & 0.875471962722352 \tabularnewline
68 & 0.150714126857997 & 0.301428253715993 & 0.849285873142003 \tabularnewline
69 & 0.343888668951922 & 0.687777337903845 & 0.656111331048078 \tabularnewline
70 & 0.305643256779926 & 0.611286513559851 & 0.694356743220074 \tabularnewline
71 & 0.456877585579658 & 0.913755171159316 & 0.543122414420342 \tabularnewline
72 & 0.419928697897371 & 0.839857395794743 & 0.580071302102628 \tabularnewline
73 & 0.410250267685324 & 0.820500535370647 & 0.589749732314676 \tabularnewline
74 & 0.389475787851003 & 0.778951575702005 & 0.610524212148997 \tabularnewline
75 & 0.353067153266133 & 0.706134306532266 & 0.646932846733867 \tabularnewline
76 & 0.402478661546027 & 0.804957323092054 & 0.597521338453973 \tabularnewline
77 & 0.367580301321666 & 0.735160602643333 & 0.632419698678334 \tabularnewline
78 & 0.338946911791492 & 0.677893823582983 & 0.661053088208508 \tabularnewline
79 & 0.36638716681708 & 0.73277433363416 & 0.63361283318292 \tabularnewline
80 & 0.334440607313753 & 0.668881214627506 & 0.665559392686247 \tabularnewline
81 & 0.30266028008657 & 0.60532056017314 & 0.69733971991343 \tabularnewline
82 & 0.268712181387127 & 0.537424362774254 & 0.731287818612873 \tabularnewline
83 & 0.243465165126896 & 0.486930330253792 & 0.756534834873104 \tabularnewline
84 & 0.213395170054051 & 0.426790340108102 & 0.786604829945949 \tabularnewline
85 & 0.204473723326668 & 0.408947446653337 & 0.795526276673332 \tabularnewline
86 & 0.177589055744589 & 0.355178111489177 & 0.822410944255412 \tabularnewline
87 & 0.155174073416449 & 0.310348146832897 & 0.844825926583551 \tabularnewline
88 & 0.141134380284515 & 0.28226876056903 & 0.858865619715485 \tabularnewline
89 & 0.120988634340955 & 0.24197726868191 & 0.879011365659045 \tabularnewline
90 & 0.120255159235721 & 0.240510318471442 & 0.879744840764279 \tabularnewline
91 & 0.102479154169644 & 0.204958308339289 & 0.897520845830356 \tabularnewline
92 & 0.0891461020230827 & 0.178292204046165 & 0.910853897976917 \tabularnewline
93 & 0.0755107869145351 & 0.151021573829070 & 0.924489213085465 \tabularnewline
94 & 0.079532704214503 & 0.159065408429006 & 0.920467295785497 \tabularnewline
95 & 0.0718327780761281 & 0.143665556152256 & 0.928167221923872 \tabularnewline
96 & 0.0597718811839649 & 0.119543762367930 & 0.940228118816035 \tabularnewline
97 & 0.0636513083515619 & 0.127302616703124 & 0.936348691648438 \tabularnewline
98 & 0.052572922589572 & 0.105145845179144 & 0.947427077410428 \tabularnewline
99 & 0.0433485278831651 & 0.0866970557663303 & 0.956651472116835 \tabularnewline
100 & 0.0375392408916114 & 0.0750784817832228 & 0.962460759108389 \tabularnewline
101 & 0.0329904108910570 & 0.0659808217821139 & 0.967009589108943 \tabularnewline
102 & 0.0398393796776781 & 0.0796787593553563 & 0.960160620322322 \tabularnewline
103 & 0.0335490789628814 & 0.0670981579257629 & 0.966450921037119 \tabularnewline
104 & 0.0305201746076184 & 0.0610403492152367 & 0.969479825392382 \tabularnewline
105 & 0.0357051447144569 & 0.0714102894289139 & 0.964294855285543 \tabularnewline
106 & 0.0312650391700154 & 0.0625300783400308 & 0.968734960829985 \tabularnewline
107 & 0.0253096768372012 & 0.0506193536744024 & 0.97469032316280 \tabularnewline
108 & 0.0246049676929592 & 0.0492099353859185 & 0.97539503230704 \tabularnewline
109 & 0.0198406477697905 & 0.0396812955395811 & 0.98015935223021 \tabularnewline
110 & 0.0162400714068859 & 0.0324801428137718 & 0.983759928593114 \tabularnewline
111 & 0.0128113236124551 & 0.0256226472249102 & 0.987188676387545 \tabularnewline
112 & 0.0132259030977173 & 0.0264518061954346 & 0.986774096902283 \tabularnewline
113 & 0.0121222773762483 & 0.0242445547524966 & 0.987877722623752 \tabularnewline
114 & 0.0169804189106440 & 0.0339608378212881 & 0.983019581089356 \tabularnewline
115 & 0.0161927520666967 & 0.0323855041333933 & 0.983807247933303 \tabularnewline
116 & 0.0154867349703439 & 0.0309734699406878 & 0.984513265029656 \tabularnewline
117 & 0.0127934248544036 & 0.0255868497088072 & 0.987206575145596 \tabularnewline
118 & 0.0126934873005723 & 0.0253869746011446 & 0.987306512699428 \tabularnewline
119 & 0.0101274243512959 & 0.0202548487025918 & 0.989872575648704 \tabularnewline
120 & 0.00894941565671435 & 0.0178988313134287 & 0.991050584343286 \tabularnewline
121 & 0.00713553477374165 & 0.0142710695474833 & 0.992864465226258 \tabularnewline
122 & 0.0103009170498025 & 0.0206018340996051 & 0.989699082950197 \tabularnewline
123 & 0.00841822557905408 & 0.0168364511581082 & 0.991581774420946 \tabularnewline
124 & 0.0070149585935322 & 0.0140299171870644 & 0.992985041406468 \tabularnewline
125 & 0.00561230814253774 & 0.0112246162850755 & 0.994387691857462 \tabularnewline
126 & 0.00437309194881369 & 0.00874618389762738 & 0.995626908051186 \tabularnewline
127 & 0.00411488230820626 & 0.00822976461641251 & 0.995885117691794 \tabularnewline
128 & 0.00337133624223543 & 0.00674267248447086 & 0.996628663757765 \tabularnewline
129 & 0.00459519241291721 & 0.00919038482583442 & 0.995404807587083 \tabularnewline
130 & 0.00520833343649414 & 0.0104166668729883 & 0.994791666563506 \tabularnewline
131 & 0.0106571654805978 & 0.0213143309611957 & 0.989342834519402 \tabularnewline
132 & 0.0131637837419432 & 0.0263275674838864 & 0.986836216258057 \tabularnewline
133 & 0.0140598613911444 & 0.0281197227822888 & 0.985940138608856 \tabularnewline
134 & 0.0130266352059284 & 0.0260532704118567 & 0.986973364794072 \tabularnewline
135 & 0.0102683003920224 & 0.0205366007840448 & 0.989731699607978 \tabularnewline
136 & 0.00869301337051336 & 0.0173860267410267 & 0.991306986629487 \tabularnewline
137 & 0.00691930633764624 & 0.0138386126752925 & 0.993080693662354 \tabularnewline
138 & 0.00873124414601983 & 0.0174624882920397 & 0.99126875585398 \tabularnewline
139 & 0.00744563128460002 & 0.0148912625692000 & 0.9925543687154 \tabularnewline
140 & 0.00911502152519438 & 0.0182300430503888 & 0.990884978474806 \tabularnewline
141 & 0.0149244978879686 & 0.0298489957759371 & 0.985075502112031 \tabularnewline
142 & 0.0142880269095094 & 0.0285760538190188 & 0.98571197309049 \tabularnewline
143 & 0.011787519191028 & 0.023575038382056 & 0.988212480808972 \tabularnewline
144 & 0.0117424736210715 & 0.0234849472421429 & 0.988257526378929 \tabularnewline
145 & 0.0208545078804271 & 0.0417090157608542 & 0.979145492119573 \tabularnewline
146 & 0.0248966680831226 & 0.0497933361662452 & 0.975103331916877 \tabularnewline
147 & 0.0264235823408604 & 0.0528471646817209 & 0.97357641765914 \tabularnewline
148 & 0.0230885578000696 & 0.0461771156001392 & 0.97691144219993 \tabularnewline
149 & 0.0185753774122757 & 0.0371507548245514 & 0.981424622587724 \tabularnewline
150 & 0.0265826413417606 & 0.0531652826835212 & 0.97341735865824 \tabularnewline
151 & 0.0226851778306609 & 0.0453703556613219 & 0.97731482216934 \tabularnewline
152 & 0.0252751966213975 & 0.050550393242795 & 0.974724803378602 \tabularnewline
153 & 0.0510143851879781 & 0.102028770375956 & 0.948985614812022 \tabularnewline
154 & 0.0499973342773527 & 0.0999946685547055 & 0.950002665722647 \tabularnewline
155 & 0.0590562582320646 & 0.118112516464129 & 0.940943741767935 \tabularnewline
156 & 0.0500529447297188 & 0.100105889459438 & 0.94994705527028 \tabularnewline
157 & 0.0442378578740246 & 0.0884757157480492 & 0.955762142125975 \tabularnewline
158 & 0.0379777226716838 & 0.0759554453433676 & 0.962022277328316 \tabularnewline
159 & 0.0367545381458568 & 0.0735090762917135 & 0.963245461854143 \tabularnewline
160 & 0.0310593851744151 & 0.0621187703488301 & 0.968940614825585 \tabularnewline
161 & 0.0251750377915537 & 0.0503500755831075 & 0.974824962208446 \tabularnewline
162 & 0.0203315323011701 & 0.0406630646023401 & 0.97966846769883 \tabularnewline
163 & 0.0168868472534704 & 0.0337736945069407 & 0.98311315274653 \tabularnewline
164 & 0.0140850690537459 & 0.0281701381074917 & 0.985914930946254 \tabularnewline
165 & 0.0120377696397923 & 0.0240755392795847 & 0.987962230360208 \tabularnewline
166 & 0.0127190399347612 & 0.0254380798695223 & 0.987280960065239 \tabularnewline
167 & 0.0101566261066436 & 0.0203132522132872 & 0.989843373893356 \tabularnewline
168 & 0.0157253938285429 & 0.0314507876570858 & 0.984274606171457 \tabularnewline
169 & 0.0160887007977170 & 0.0321774015954341 & 0.983911299202283 \tabularnewline
170 & 0.0150008269342025 & 0.0300016538684049 & 0.984999173065798 \tabularnewline
171 & 0.0135895026618326 & 0.0271790053236653 & 0.986410497338167 \tabularnewline
172 & 0.0108394207967232 & 0.0216788415934464 & 0.989160579203277 \tabularnewline
173 & 0.0108441625791383 & 0.0216883251582767 & 0.989155837420862 \tabularnewline
174 & 0.012596459523381 & 0.025192919046762 & 0.987403540476619 \tabularnewline
175 & 0.0166311203022962 & 0.0332622406045924 & 0.983368879697704 \tabularnewline
176 & 0.0132480745199596 & 0.0264961490399192 & 0.98675192548004 \tabularnewline
177 & 0.0104529209878134 & 0.0209058419756267 & 0.989547079012187 \tabularnewline
178 & 0.0087685983094409 & 0.0175371966188818 & 0.99123140169056 \tabularnewline
179 & 0.00675218099441613 & 0.0135043619888323 & 0.993247819005584 \tabularnewline
180 & 0.00595227577786152 & 0.0119045515557230 & 0.994047724222138 \tabularnewline
181 & 0.00482021255237906 & 0.00964042510475813 & 0.995179787447621 \tabularnewline
182 & 0.00370834631168027 & 0.00741669262336055 & 0.99629165368832 \tabularnewline
183 & 0.00398692399058354 & 0.00797384798116709 & 0.996013076009416 \tabularnewline
184 & 0.00300961008665678 & 0.00601922017331355 & 0.996990389913343 \tabularnewline
185 & 0.0853414771838382 & 0.170682954367676 & 0.914658522816162 \tabularnewline
186 & 0.0760215335305705 & 0.152043067061141 & 0.92397846646943 \tabularnewline
187 & 0.0837413923821005 & 0.167482784764201 & 0.9162586076179 \tabularnewline
188 & 0.07004031937687 & 0.14008063875374 & 0.92995968062313 \tabularnewline
189 & 0.0622875967513268 & 0.124575193502654 & 0.937712403248673 \tabularnewline
190 & 0.0517448100959109 & 0.103489620191822 & 0.94825518990409 \tabularnewline
191 & 0.0477314993313587 & 0.0954629986627174 & 0.952268500668641 \tabularnewline
192 & 0.0392257519398204 & 0.0784515038796408 & 0.96077424806018 \tabularnewline
193 & 0.0400243521800498 & 0.0800487043600997 & 0.95997564781995 \tabularnewline
194 & 0.0403047081110405 & 0.080609416222081 & 0.95969529188896 \tabularnewline
195 & 0.0347006081485536 & 0.0694012162971073 & 0.965299391851446 \tabularnewline
196 & 0.0277661518378843 & 0.0555323036757687 & 0.972233848162116 \tabularnewline
197 & 0.0351052014872313 & 0.0702104029744626 & 0.964894798512769 \tabularnewline
198 & 0.0285014184612945 & 0.0570028369225891 & 0.971498581538705 \tabularnewline
199 & 0.0255314443827536 & 0.0510628887655073 & 0.974468555617246 \tabularnewline
200 & 0.0218196101218239 & 0.0436392202436477 & 0.978180389878176 \tabularnewline
201 & 0.0203269456484067 & 0.0406538912968134 & 0.979673054351593 \tabularnewline
202 & 0.0170899582487389 & 0.0341799164974778 & 0.98291004175126 \tabularnewline
203 & 0.0224643847935013 & 0.0449287695870026 & 0.977535615206499 \tabularnewline
204 & 0.0261548877981559 & 0.0523097755963118 & 0.973845112201844 \tabularnewline
205 & 0.0273219956510728 & 0.0546439913021456 & 0.972678004348927 \tabularnewline
206 & 0.0212570119068145 & 0.0425140238136291 & 0.978742988093185 \tabularnewline
207 & 0.0202653106365932 & 0.0405306212731864 & 0.979734689363407 \tabularnewline
208 & 0.0164688259688203 & 0.0329376519376405 & 0.98353117403118 \tabularnewline
209 & 0.0183272916694650 & 0.0366545833389300 & 0.981672708330535 \tabularnewline
210 & 0.014501003799243 & 0.029002007598486 & 0.985498996200757 \tabularnewline
211 & 0.0166182867149888 & 0.0332365734299777 & 0.983381713285011 \tabularnewline
212 & 0.0270900954587140 & 0.0541801909174280 & 0.972909904541286 \tabularnewline
213 & 0.0209131162419586 & 0.0418262324839172 & 0.979086883758041 \tabularnewline
214 & 0.027113933494889 & 0.054227866989778 & 0.97288606650511 \tabularnewline
215 & 0.0228725494160244 & 0.0457450988320489 & 0.977127450583976 \tabularnewline
216 & 0.0175319782798157 & 0.0350639565596314 & 0.982468021720184 \tabularnewline
217 & 0.0192559593869288 & 0.0385119187738577 & 0.980744040613071 \tabularnewline
218 & 0.0160980713819302 & 0.0321961427638604 & 0.98390192861807 \tabularnewline
219 & 0.0148737932887074 & 0.0297475865774149 & 0.985126206711293 \tabularnewline
220 & 0.0112452282629419 & 0.0224904565258838 & 0.988754771737058 \tabularnewline
221 & 0.00926182737223425 & 0.0185236547444685 & 0.990738172627766 \tabularnewline
222 & 0.0065656275058431 & 0.0131312550116862 & 0.993434372494157 \tabularnewline
223 & 0.00498203627846982 & 0.00996407255693964 & 0.99501796372153 \tabularnewline
224 & 0.00370586623701994 & 0.00741173247403989 & 0.99629413376298 \tabularnewline
225 & 0.00312910572486035 & 0.00625821144972071 & 0.99687089427514 \tabularnewline
226 & 0.0073080238334571 & 0.0146160476669142 & 0.992691976166543 \tabularnewline
227 & 0.0056565869724856 & 0.0113131739449712 & 0.994343413027514 \tabularnewline
228 & 0.00413003590427982 & 0.00826007180855963 & 0.99586996409572 \tabularnewline
229 & 0.00290095626256910 & 0.00580191252513821 & 0.997099043737431 \tabularnewline
230 & 0.00210006526868233 & 0.00420013053736466 & 0.997899934731318 \tabularnewline
231 & 0.00187435006150138 & 0.00374870012300276 & 0.998125649938499 \tabularnewline
232 & 0.00445268431966201 & 0.00890536863932401 & 0.995547315680338 \tabularnewline
233 & 0.0186513607143556 & 0.0373027214287112 & 0.981348639285644 \tabularnewline
234 & 0.0287056236663921 & 0.0574112473327842 & 0.971294376333608 \tabularnewline
235 & 0.0202408156875338 & 0.0404816313750676 & 0.979759184312466 \tabularnewline
236 & 0.0166385178465637 & 0.0332770356931275 & 0.983361482153436 \tabularnewline
237 & 0.158811527145599 & 0.317623054291199 & 0.8411884728544 \tabularnewline
238 & 0.122053659592906 & 0.244107319185811 & 0.877946340407095 \tabularnewline
239 & 0.0996048696320387 & 0.199209739264077 & 0.900395130367961 \tabularnewline
240 & 0.0750857716468304 & 0.150171543293661 & 0.92491422835317 \tabularnewline
241 & 0.0646426417753595 & 0.129285283550719 & 0.93535735822464 \tabularnewline
242 & 0.102490655553289 & 0.204981311106577 & 0.897509344446711 \tabularnewline
243 & 0.081491720832899 & 0.162983441665798 & 0.9185082791671 \tabularnewline
244 & 0.0842682626125305 & 0.168536525225061 & 0.91573173738747 \tabularnewline
245 & 0.0665871193041568 & 0.133174238608314 & 0.933412880695843 \tabularnewline
246 & 0.0544356840043543 & 0.108871368008709 & 0.945564315995646 \tabularnewline
247 & 0.0329907544098212 & 0.0659815088196424 & 0.967009245590179 \tabularnewline
248 & 0.0266391640759625 & 0.053278328151925 & 0.973360835924038 \tabularnewline
249 & 0.0224913576759628 & 0.0449827153519257 & 0.977508642324037 \tabularnewline
250 & 0.0664473388463356 & 0.132894677692671 & 0.933552661153664 \tabularnewline
251 & 0.0486972483238257 & 0.0973944966476515 & 0.951302751676174 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]13[/C][C]0.309807656286817[/C][C]0.619615312573634[/C][C]0.690192343713183[/C][/ROW]
[ROW][C]14[/C][C]0.2982458895084[/C][C]0.5964917790168[/C][C]0.7017541104916[/C][/ROW]
[ROW][C]15[/C][C]0.180880645654023[/C][C]0.361761291308045[/C][C]0.819119354345977[/C][/ROW]
[ROW][C]16[/C][C]0.137959527969735[/C][C]0.275919055939470[/C][C]0.862040472030265[/C][/ROW]
[ROW][C]17[/C][C]0.143729595500073[/C][C]0.287459191000146[/C][C]0.856270404499927[/C][/ROW]
[ROW][C]18[/C][C]0.295672611917276[/C][C]0.591345223834551[/C][C]0.704327388082725[/C][/ROW]
[ROW][C]19[/C][C]0.245953051754568[/C][C]0.491906103509136[/C][C]0.754046948245432[/C][/ROW]
[ROW][C]20[/C][C]0.197531582642351[/C][C]0.395063165284702[/C][C]0.802468417357649[/C][/ROW]
[ROW][C]21[/C][C]0.154638598434060[/C][C]0.309277196868121[/C][C]0.84536140156594[/C][/ROW]
[ROW][C]22[/C][C]0.181179794070588[/C][C]0.362359588141176[/C][C]0.818820205929412[/C][/ROW]
[ROW][C]23[/C][C]0.292370722019794[/C][C]0.584741444039587[/C][C]0.707629277980206[/C][/ROW]
[ROW][C]24[/C][C]0.413563053247267[/C][C]0.827126106494533[/C][C]0.586436946752734[/C][/ROW]
[ROW][C]25[/C][C]0.343871514454900[/C][C]0.687743028909799[/C][C]0.6561284855451[/C][/ROW]
[ROW][C]26[/C][C]0.292745395722881[/C][C]0.585490791445763[/C][C]0.707254604277119[/C][/ROW]
[ROW][C]27[/C][C]0.280275008418916[/C][C]0.560550016837832[/C][C]0.719724991581084[/C][/ROW]
[ROW][C]28[/C][C]0.396379429891148[/C][C]0.792758859782295[/C][C]0.603620570108852[/C][/ROW]
[ROW][C]29[/C][C]0.342705495061225[/C][C]0.68541099012245[/C][C]0.657294504938775[/C][/ROW]
[ROW][C]30[/C][C]0.453590892318243[/C][C]0.907181784636485[/C][C]0.546409107681757[/C][/ROW]
[ROW][C]31[/C][C]0.4098203042314[/C][C]0.8196406084628[/C][C]0.5901796957686[/C][/ROW]
[ROW][C]32[/C][C]0.379700407782805[/C][C]0.75940081556561[/C][C]0.620299592217195[/C][/ROW]
[ROW][C]33[/C][C]0.362199175090739[/C][C]0.724398350181479[/C][C]0.637800824909261[/C][/ROW]
[ROW][C]34[/C][C]0.323061419276707[/C][C]0.646122838553414[/C][C]0.676938580723293[/C][/ROW]
[ROW][C]35[/C][C]0.27741937114134[/C][C]0.55483874228268[/C][C]0.72258062885866[/C][/ROW]
[ROW][C]36[/C][C]0.412599374054753[/C][C]0.825198748109507[/C][C]0.587400625945247[/C][/ROW]
[ROW][C]37[/C][C]0.440486741081803[/C][C]0.880973482163606[/C][C]0.559513258918197[/C][/ROW]
[ROW][C]38[/C][C]0.414751240937735[/C][C]0.82950248187547[/C][C]0.585248759062265[/C][/ROW]
[ROW][C]39[/C][C]0.458996581775578[/C][C]0.917993163551155[/C][C]0.541003418224423[/C][/ROW]
[ROW][C]40[/C][C]0.438077281087412[/C][C]0.876154562174824[/C][C]0.561922718912588[/C][/ROW]
[ROW][C]41[/C][C]0.397606632447526[/C][C]0.795213264895052[/C][C]0.602393367552474[/C][/ROW]
[ROW][C]42[/C][C]0.357011020557362[/C][C]0.714022041114724[/C][C]0.642988979442638[/C][/ROW]
[ROW][C]43[/C][C]0.375803323977979[/C][C]0.751606647955958[/C][C]0.624196676022021[/C][/ROW]
[ROW][C]44[/C][C]0.32621919593697[/C][C]0.65243839187394[/C][C]0.67378080406303[/C][/ROW]
[ROW][C]45[/C][C]0.297228597638108[/C][C]0.594457195276217[/C][C]0.702771402361892[/C][/ROW]
[ROW][C]46[/C][C]0.477767576714707[/C][C]0.955535153429414[/C][C]0.522232423285293[/C][/ROW]
[ROW][C]47[/C][C]0.566983009470338[/C][C]0.866033981059324[/C][C]0.433016990529662[/C][/ROW]
[ROW][C]48[/C][C]0.523694345550082[/C][C]0.952611308899836[/C][C]0.476305654449918[/C][/ROW]
[ROW][C]49[/C][C]0.547090628451313[/C][C]0.905818743097374[/C][C]0.452909371548687[/C][/ROW]
[ROW][C]50[/C][C]0.519795954142248[/C][C]0.960408091715505[/C][C]0.480204045857752[/C][/ROW]
[ROW][C]51[/C][C]0.4743618932566[/C][C]0.9487237865132[/C][C]0.5256381067434[/C][/ROW]
[ROW][C]52[/C][C]0.432325414352373[/C][C]0.864650828704747[/C][C]0.567674585647627[/C][/ROW]
[ROW][C]53[/C][C]0.432585256747916[/C][C]0.865170513495831[/C][C]0.567414743252084[/C][/ROW]
[ROW][C]54[/C][C]0.389368675455909[/C][C]0.778737350911817[/C][C]0.610631324544092[/C][/ROW]
[ROW][C]55[/C][C]0.377808513790590[/C][C]0.755617027581181[/C][C]0.622191486209410[/C][/ROW]
[ROW][C]56[/C][C]0.373594207972992[/C][C]0.747188415945983[/C][C]0.626405792027008[/C][/ROW]
[ROW][C]57[/C][C]0.332852275405684[/C][C]0.665704550811369[/C][C]0.667147724594316[/C][/ROW]
[ROW][C]58[/C][C]0.312980767817856[/C][C]0.625961535635712[/C][C]0.687019232182144[/C][/ROW]
[ROW][C]59[/C][C]0.281726108362702[/C][C]0.563452216725403[/C][C]0.718273891637298[/C][/ROW]
[ROW][C]60[/C][C]0.301554968100597[/C][C]0.603109936201195[/C][C]0.698445031899403[/C][/ROW]
[ROW][C]61[/C][C]0.276786835199114[/C][C]0.553573670398227[/C][C]0.723213164800886[/C][/ROW]
[ROW][C]62[/C][C]0.250508189541221[/C][C]0.501016379082442[/C][C]0.749491810458779[/C][/ROW]
[ROW][C]63[/C][C]0.220683000232985[/C][C]0.44136600046597[/C][C]0.779316999767015[/C][/ROW]
[ROW][C]64[/C][C]0.191708281277336[/C][C]0.383416562554672[/C][C]0.808291718722664[/C][/ROW]
[ROW][C]65[/C][C]0.16936819567674[/C][C]0.33873639135348[/C][C]0.83063180432326[/C][/ROW]
[ROW][C]66[/C][C]0.143783931925017[/C][C]0.287567863850034[/C][C]0.856216068074983[/C][/ROW]
[ROW][C]67[/C][C]0.124528037277648[/C][C]0.249056074555296[/C][C]0.875471962722352[/C][/ROW]
[ROW][C]68[/C][C]0.150714126857997[/C][C]0.301428253715993[/C][C]0.849285873142003[/C][/ROW]
[ROW][C]69[/C][C]0.343888668951922[/C][C]0.687777337903845[/C][C]0.656111331048078[/C][/ROW]
[ROW][C]70[/C][C]0.305643256779926[/C][C]0.611286513559851[/C][C]0.694356743220074[/C][/ROW]
[ROW][C]71[/C][C]0.456877585579658[/C][C]0.913755171159316[/C][C]0.543122414420342[/C][/ROW]
[ROW][C]72[/C][C]0.419928697897371[/C][C]0.839857395794743[/C][C]0.580071302102628[/C][/ROW]
[ROW][C]73[/C][C]0.410250267685324[/C][C]0.820500535370647[/C][C]0.589749732314676[/C][/ROW]
[ROW][C]74[/C][C]0.389475787851003[/C][C]0.778951575702005[/C][C]0.610524212148997[/C][/ROW]
[ROW][C]75[/C][C]0.353067153266133[/C][C]0.706134306532266[/C][C]0.646932846733867[/C][/ROW]
[ROW][C]76[/C][C]0.402478661546027[/C][C]0.804957323092054[/C][C]0.597521338453973[/C][/ROW]
[ROW][C]77[/C][C]0.367580301321666[/C][C]0.735160602643333[/C][C]0.632419698678334[/C][/ROW]
[ROW][C]78[/C][C]0.338946911791492[/C][C]0.677893823582983[/C][C]0.661053088208508[/C][/ROW]
[ROW][C]79[/C][C]0.36638716681708[/C][C]0.73277433363416[/C][C]0.63361283318292[/C][/ROW]
[ROW][C]80[/C][C]0.334440607313753[/C][C]0.668881214627506[/C][C]0.665559392686247[/C][/ROW]
[ROW][C]81[/C][C]0.30266028008657[/C][C]0.60532056017314[/C][C]0.69733971991343[/C][/ROW]
[ROW][C]82[/C][C]0.268712181387127[/C][C]0.537424362774254[/C][C]0.731287818612873[/C][/ROW]
[ROW][C]83[/C][C]0.243465165126896[/C][C]0.486930330253792[/C][C]0.756534834873104[/C][/ROW]
[ROW][C]84[/C][C]0.213395170054051[/C][C]0.426790340108102[/C][C]0.786604829945949[/C][/ROW]
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[ROW][C]228[/C][C]0.00413003590427982[/C][C]0.00826007180855963[/C][C]0.99586996409572[/C][/ROW]
[ROW][C]229[/C][C]0.00290095626256910[/C][C]0.00580191252513821[/C][C]0.997099043737431[/C][/ROW]
[ROW][C]230[/C][C]0.00210006526868233[/C][C]0.00420013053736466[/C][C]0.997899934731318[/C][/ROW]
[ROW][C]231[/C][C]0.00187435006150138[/C][C]0.00374870012300276[/C][C]0.998125649938499[/C][/ROW]
[ROW][C]232[/C][C]0.00445268431966201[/C][C]0.00890536863932401[/C][C]0.995547315680338[/C][/ROW]
[ROW][C]233[/C][C]0.0186513607143556[/C][C]0.0373027214287112[/C][C]0.981348639285644[/C][/ROW]
[ROW][C]234[/C][C]0.0287056236663921[/C][C]0.0574112473327842[/C][C]0.971294376333608[/C][/ROW]
[ROW][C]235[/C][C]0.0202408156875338[/C][C]0.0404816313750676[/C][C]0.979759184312466[/C][/ROW]
[ROW][C]236[/C][C]0.0166385178465637[/C][C]0.0332770356931275[/C][C]0.983361482153436[/C][/ROW]
[ROW][C]237[/C][C]0.158811527145599[/C][C]0.317623054291199[/C][C]0.8411884728544[/C][/ROW]
[ROW][C]238[/C][C]0.122053659592906[/C][C]0.244107319185811[/C][C]0.877946340407095[/C][/ROW]
[ROW][C]239[/C][C]0.0996048696320387[/C][C]0.199209739264077[/C][C]0.900395130367961[/C][/ROW]
[ROW][C]240[/C][C]0.0750857716468304[/C][C]0.150171543293661[/C][C]0.92491422835317[/C][/ROW]
[ROW][C]241[/C][C]0.0646426417753595[/C][C]0.129285283550719[/C][C]0.93535735822464[/C][/ROW]
[ROW][C]242[/C][C]0.102490655553289[/C][C]0.204981311106577[/C][C]0.897509344446711[/C][/ROW]
[ROW][C]243[/C][C]0.081491720832899[/C][C]0.162983441665798[/C][C]0.9185082791671[/C][/ROW]
[ROW][C]244[/C][C]0.0842682626125305[/C][C]0.168536525225061[/C][C]0.91573173738747[/C][/ROW]
[ROW][C]245[/C][C]0.0665871193041568[/C][C]0.133174238608314[/C][C]0.933412880695843[/C][/ROW]
[ROW][C]246[/C][C]0.0544356840043543[/C][C]0.108871368008709[/C][C]0.945564315995646[/C][/ROW]
[ROW][C]247[/C][C]0.0329907544098212[/C][C]0.0659815088196424[/C][C]0.967009245590179[/C][/ROW]
[ROW][C]248[/C][C]0.0266391640759625[/C][C]0.053278328151925[/C][C]0.973360835924038[/C][/ROW]
[ROW][C]249[/C][C]0.0224913576759628[/C][C]0.0449827153519257[/C][C]0.977508642324037[/C][/ROW]
[ROW][C]250[/C][C]0.0664473388463356[/C][C]0.132894677692671[/C][C]0.933552661153664[/C][/ROW]
[ROW][C]251[/C][C]0.0486972483238257[/C][C]0.0973944966476515[/C][C]0.951302751676174[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
13	0.309807656286817	0.619615312573634	0.690192343713183
14	0.2982458895084	0.5964917790168	0.7017541104916
15	0.180880645654023	0.361761291308045	0.819119354345977
16	0.137959527969735	0.275919055939470	0.862040472030265
17	0.143729595500073	0.287459191000146	0.856270404499927
18	0.295672611917276	0.591345223834551	0.704327388082725
19	0.245953051754568	0.491906103509136	0.754046948245432
20	0.197531582642351	0.395063165284702	0.802468417357649
21	0.154638598434060	0.309277196868121	0.84536140156594
22	0.181179794070588	0.362359588141176	0.818820205929412
23	0.292370722019794	0.584741444039587	0.707629277980206
24	0.413563053247267	0.827126106494533	0.586436946752734
25	0.343871514454900	0.687743028909799	0.6561284855451
26	0.292745395722881	0.585490791445763	0.707254604277119
27	0.280275008418916	0.560550016837832	0.719724991581084
28	0.396379429891148	0.792758859782295	0.603620570108852
29	0.342705495061225	0.68541099012245	0.657294504938775
30	0.453590892318243	0.907181784636485	0.546409107681757
31	0.4098203042314	0.8196406084628	0.5901796957686
32	0.379700407782805	0.75940081556561	0.620299592217195
33	0.362199175090739	0.724398350181479	0.637800824909261
34	0.323061419276707	0.646122838553414	0.676938580723293
35	0.27741937114134	0.55483874228268	0.72258062885866
36	0.412599374054753	0.825198748109507	0.587400625945247
37	0.440486741081803	0.880973482163606	0.559513258918197
38	0.414751240937735	0.82950248187547	0.585248759062265
39	0.458996581775578	0.917993163551155	0.541003418224423
40	0.438077281087412	0.876154562174824	0.561922718912588
41	0.397606632447526	0.795213264895052	0.602393367552474
42	0.357011020557362	0.714022041114724	0.642988979442638
43	0.375803323977979	0.751606647955958	0.624196676022021
44	0.32621919593697	0.65243839187394	0.67378080406303
45	0.297228597638108	0.594457195276217	0.702771402361892
46	0.477767576714707	0.955535153429414	0.522232423285293
47	0.566983009470338	0.866033981059324	0.433016990529662
48	0.523694345550082	0.952611308899836	0.476305654449918
49	0.547090628451313	0.905818743097374	0.452909371548687
50	0.519795954142248	0.960408091715505	0.480204045857752
51	0.4743618932566	0.9487237865132	0.5256381067434
52	0.432325414352373	0.864650828704747	0.567674585647627
53	0.432585256747916	0.865170513495831	0.567414743252084
54	0.389368675455909	0.778737350911817	0.610631324544092
55	0.377808513790590	0.755617027581181	0.622191486209410
56	0.373594207972992	0.747188415945983	0.626405792027008
57	0.332852275405684	0.665704550811369	0.667147724594316
58	0.312980767817856	0.625961535635712	0.687019232182144
59	0.281726108362702	0.563452216725403	0.718273891637298
60	0.301554968100597	0.603109936201195	0.698445031899403
61	0.276786835199114	0.553573670398227	0.723213164800886
62	0.250508189541221	0.501016379082442	0.749491810458779
63	0.220683000232985	0.44136600046597	0.779316999767015
64	0.191708281277336	0.383416562554672	0.808291718722664
65	0.16936819567674	0.33873639135348	0.83063180432326
66	0.143783931925017	0.287567863850034	0.856216068074983
67	0.124528037277648	0.249056074555296	0.875471962722352
68	0.150714126857997	0.301428253715993	0.849285873142003
69	0.343888668951922	0.687777337903845	0.656111331048078
70	0.305643256779926	0.611286513559851	0.694356743220074
71	0.456877585579658	0.913755171159316	0.543122414420342
72	0.419928697897371	0.839857395794743	0.580071302102628
73	0.410250267685324	0.820500535370647	0.589749732314676
74	0.389475787851003	0.778951575702005	0.610524212148997
75	0.353067153266133	0.706134306532266	0.646932846733867
76	0.402478661546027	0.804957323092054	0.597521338453973
77	0.367580301321666	0.735160602643333	0.632419698678334
78	0.338946911791492	0.677893823582983	0.661053088208508
79	0.36638716681708	0.73277433363416	0.63361283318292
80	0.334440607313753	0.668881214627506	0.665559392686247
81	0.30266028008657	0.60532056017314	0.69733971991343
82	0.268712181387127	0.537424362774254	0.731287818612873
83	0.243465165126896	0.486930330253792	0.756534834873104
84	0.213395170054051	0.426790340108102	0.786604829945949
85	0.204473723326668	0.408947446653337	0.795526276673332
86	0.177589055744589	0.355178111489177	0.822410944255412
87	0.155174073416449	0.310348146832897	0.844825926583551
88	0.141134380284515	0.28226876056903	0.858865619715485
89	0.120988634340955	0.24197726868191	0.879011365659045
90	0.120255159235721	0.240510318471442	0.879744840764279
91	0.102479154169644	0.204958308339289	0.897520845830356
92	0.0891461020230827	0.178292204046165	0.910853897976917
93	0.0755107869145351	0.151021573829070	0.924489213085465
94	0.079532704214503	0.159065408429006	0.920467295785497
95	0.0718327780761281	0.143665556152256	0.928167221923872
96	0.0597718811839649	0.119543762367930	0.940228118816035
97	0.0636513083515619	0.127302616703124	0.936348691648438
98	0.052572922589572	0.105145845179144	0.947427077410428
99	0.0433485278831651	0.0866970557663303	0.956651472116835
100	0.0375392408916114	0.0750784817832228	0.962460759108389
101	0.0329904108910570	0.0659808217821139	0.967009589108943
102	0.0398393796776781	0.0796787593553563	0.960160620322322
103	0.0335490789628814	0.0670981579257629	0.966450921037119
104	0.0305201746076184	0.0610403492152367	0.969479825392382
105	0.0357051447144569	0.0714102894289139	0.964294855285543
106	0.0312650391700154	0.0625300783400308	0.968734960829985
107	0.0253096768372012	0.0506193536744024	0.97469032316280
108	0.0246049676929592	0.0492099353859185	0.97539503230704
109	0.0198406477697905	0.0396812955395811	0.98015935223021
110	0.0162400714068859	0.0324801428137718	0.983759928593114
111	0.0128113236124551	0.0256226472249102	0.987188676387545
112	0.0132259030977173	0.0264518061954346	0.986774096902283
113	0.0121222773762483	0.0242445547524966	0.987877722623752
114	0.0169804189106440	0.0339608378212881	0.983019581089356
115	0.0161927520666967	0.0323855041333933	0.983807247933303
116	0.0154867349703439	0.0309734699406878	0.984513265029656
117	0.0127934248544036	0.0255868497088072	0.987206575145596
118	0.0126934873005723	0.0253869746011446	0.987306512699428
119	0.0101274243512959	0.0202548487025918	0.989872575648704
120	0.00894941565671435	0.0178988313134287	0.991050584343286
121	0.00713553477374165	0.0142710695474833	0.992864465226258
122	0.0103009170498025	0.0206018340996051	0.989699082950197
123	0.00841822557905408	0.0168364511581082	0.991581774420946
124	0.0070149585935322	0.0140299171870644	0.992985041406468
125	0.00561230814253774	0.0112246162850755	0.994387691857462
126	0.00437309194881369	0.00874618389762738	0.995626908051186
127	0.00411488230820626	0.00822976461641251	0.995885117691794
128	0.00337133624223543	0.00674267248447086	0.996628663757765
129	0.00459519241291721	0.00919038482583442	0.995404807587083
130	0.00520833343649414	0.0104166668729883	0.994791666563506
131	0.0106571654805978	0.0213143309611957	0.989342834519402
132	0.0131637837419432	0.0263275674838864	0.986836216258057
133	0.0140598613911444	0.0281197227822888	0.985940138608856
134	0.0130266352059284	0.0260532704118567	0.986973364794072
135	0.0102683003920224	0.0205366007840448	0.989731699607978
136	0.00869301337051336	0.0173860267410267	0.991306986629487
137	0.00691930633764624	0.0138386126752925	0.993080693662354
138	0.00873124414601983	0.0174624882920397	0.99126875585398
139	0.00744563128460002	0.0148912625692000	0.9925543687154
140	0.00911502152519438	0.0182300430503888	0.990884978474806
141	0.0149244978879686	0.0298489957759371	0.985075502112031
142	0.0142880269095094	0.0285760538190188	0.98571197309049
143	0.011787519191028	0.023575038382056	0.988212480808972
144	0.0117424736210715	0.0234849472421429	0.988257526378929
145	0.0208545078804271	0.0417090157608542	0.979145492119573
146	0.0248966680831226	0.0497933361662452	0.975103331916877
147	0.0264235823408604	0.0528471646817209	0.97357641765914
148	0.0230885578000696	0.0461771156001392	0.97691144219993
149	0.0185753774122757	0.0371507548245514	0.981424622587724
150	0.0265826413417606	0.0531652826835212	0.97341735865824
151	0.0226851778306609	0.0453703556613219	0.97731482216934
152	0.0252751966213975	0.050550393242795	0.974724803378602
153	0.0510143851879781	0.102028770375956	0.948985614812022
154	0.0499973342773527	0.0999946685547055	0.950002665722647
155	0.0590562582320646	0.118112516464129	0.940943741767935
156	0.0500529447297188	0.100105889459438	0.94994705527028
157	0.0442378578740246	0.0884757157480492	0.955762142125975
158	0.0379777226716838	0.0759554453433676	0.962022277328316
159	0.0367545381458568	0.0735090762917135	0.963245461854143
160	0.0310593851744151	0.0621187703488301	0.968940614825585
161	0.0251750377915537	0.0503500755831075	0.974824962208446
162	0.0203315323011701	0.0406630646023401	0.97966846769883
163	0.0168868472534704	0.0337736945069407	0.98311315274653
164	0.0140850690537459	0.0281701381074917	0.985914930946254
165	0.0120377696397923	0.0240755392795847	0.987962230360208
166	0.0127190399347612	0.0254380798695223	0.987280960065239
167	0.0101566261066436	0.0203132522132872	0.989843373893356
168	0.0157253938285429	0.0314507876570858	0.984274606171457
169	0.0160887007977170	0.0321774015954341	0.983911299202283
170	0.0150008269342025	0.0300016538684049	0.984999173065798
171	0.0135895026618326	0.0271790053236653	0.986410497338167
172	0.0108394207967232	0.0216788415934464	0.989160579203277
173	0.0108441625791383	0.0216883251582767	0.989155837420862
174	0.012596459523381	0.025192919046762	0.987403540476619
175	0.0166311203022962	0.0332622406045924	0.983368879697704
176	0.0132480745199596	0.0264961490399192	0.98675192548004
177	0.0104529209878134	0.0209058419756267	0.989547079012187
178	0.0087685983094409	0.0175371966188818	0.99123140169056
179	0.00675218099441613	0.0135043619888323	0.993247819005584
180	0.00595227577786152	0.0119045515557230	0.994047724222138
181	0.00482021255237906	0.00964042510475813	0.995179787447621
182	0.00370834631168027	0.00741669262336055	0.99629165368832
183	0.00398692399058354	0.00797384798116709	0.996013076009416
184	0.00300961008665678	0.00601922017331355	0.996990389913343
185	0.0853414771838382	0.170682954367676	0.914658522816162
186	0.0760215335305705	0.152043067061141	0.92397846646943
187	0.0837413923821005	0.167482784764201	0.9162586076179
188	0.07004031937687	0.14008063875374	0.92995968062313
189	0.0622875967513268	0.124575193502654	0.937712403248673
190	0.0517448100959109	0.103489620191822	0.94825518990409
191	0.0477314993313587	0.0954629986627174	0.952268500668641
192	0.0392257519398204	0.0784515038796408	0.96077424806018
193	0.0400243521800498	0.0800487043600997	0.95997564781995
194	0.0403047081110405	0.080609416222081	0.95969529188896
195	0.0347006081485536	0.0694012162971073	0.965299391851446
196	0.0277661518378843	0.0555323036757687	0.972233848162116
197	0.0351052014872313	0.0702104029744626	0.964894798512769
198	0.0285014184612945	0.0570028369225891	0.971498581538705
199	0.0255314443827536	0.0510628887655073	0.974468555617246
200	0.0218196101218239	0.0436392202436477	0.978180389878176
201	0.0203269456484067	0.0406538912968134	0.979673054351593
202	0.0170899582487389	0.0341799164974778	0.98291004175126
203	0.0224643847935013	0.0449287695870026	0.977535615206499
204	0.0261548877981559	0.0523097755963118	0.973845112201844
205	0.0273219956510728	0.0546439913021456	0.972678004348927
206	0.0212570119068145	0.0425140238136291	0.978742988093185
207	0.0202653106365932	0.0405306212731864	0.979734689363407
208	0.0164688259688203	0.0329376519376405	0.98353117403118
209	0.0183272916694650	0.0366545833389300	0.981672708330535
210	0.014501003799243	0.029002007598486	0.985498996200757
211	0.0166182867149888	0.0332365734299777	0.983381713285011
212	0.0270900954587140	0.0541801909174280	0.972909904541286
213	0.0209131162419586	0.0418262324839172	0.979086883758041
214	0.027113933494889	0.054227866989778	0.97288606650511
215	0.0228725494160244	0.0457450988320489	0.977127450583976
216	0.0175319782798157	0.0350639565596314	0.982468021720184
217	0.0192559593869288	0.0385119187738577	0.980744040613071
218	0.0160980713819302	0.0321961427638604	0.98390192861807
219	0.0148737932887074	0.0297475865774149	0.985126206711293
220	0.0112452282629419	0.0224904565258838	0.988754771737058
221	0.00926182737223425	0.0185236547444685	0.990738172627766
222	0.0065656275058431	0.0131312550116862	0.993434372494157
223	0.00498203627846982	0.00996407255693964	0.99501796372153
224	0.00370586623701994	0.00741173247403989	0.99629413376298
225	0.00312910572486035	0.00625821144972071	0.99687089427514
226	0.0073080238334571	0.0146160476669142	0.992691976166543
227	0.0056565869724856	0.0113131739449712	0.994343413027514
228	0.00413003590427982	0.00826007180855963	0.99586996409572
229	0.00290095626256910	0.00580191252513821	0.997099043737431
230	0.00210006526868233	0.00420013053736466	0.997899934731318
231	0.00187435006150138	0.00374870012300276	0.998125649938499
232	0.00445268431966201	0.00890536863932401	0.995547315680338
233	0.0186513607143556	0.0373027214287112	0.981348639285644
234	0.0287056236663921	0.0574112473327842	0.971294376333608
235	0.0202408156875338	0.0404816313750676	0.979759184312466
236	0.0166385178465637	0.0332770356931275	0.983361482153436
237	0.158811527145599	0.317623054291199	0.8411884728544
238	0.122053659592906	0.244107319185811	0.877946340407095
239	0.0996048696320387	0.199209739264077	0.900395130367961
240	0.0750857716468304	0.150171543293661	0.92491422835317
241	0.0646426417753595	0.129285283550719	0.93535735822464
242	0.102490655553289	0.204981311106577	0.897509344446711
243	0.081491720832899	0.162983441665798	0.9185082791671
244	0.0842682626125305	0.168536525225061	0.91573173738747
245	0.0665871193041568	0.133174238608314	0.933412880695843
246	0.0544356840043543	0.108871368008709	0.945564315995646
247	0.0329907544098212	0.0659815088196424	0.967009245590179
248	0.0266391640759625	0.053278328151925	0.973360835924038
249	0.0224913576759628	0.0449827153519257	0.977508642324037
250	0.0664473388463356	0.132894677692671	0.933552661153664
251	0.0486972483238257	0.0973944966476515	0.951302751676174

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	16	0.0669456066945607	NOK
5% type I error level	98	0.410041841004184	NOK
10% type I error level	133	0.556485355648536	NOK

\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 & 16 & 0.0669456066945607 & NOK \tabularnewline
5% type I error level & 98 & 0.410041841004184 & NOK \tabularnewline
10% type I error level & 133 & 0.556485355648536 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=96544&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]16[/C][C]0.0669456066945607[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]98[/C][C]0.410041841004184[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]133[/C][C]0.556485355648536[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=96544&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=96544&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	16	0.0669456066945607	NOK
5% type I error level	98	0.410041841004184	NOK
10% type I error level	133	0.556485355648536	NOK

Figure 1

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;

Parameters (R input):

par1 = 4 ; par2 = Do not include Seasonal Dummies ; par3 = 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code