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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, 10 Dec 2014 14:12:48 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418221079sja6czouz1p63s7.htm/, Retrieved Sun, 19 May 2024 15:38:48 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265249, Retrieved Sun, 19 May 2024 15:38:48 +0000

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Estimated Impact

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

-       [Multiple Regression] [multiple regression] [2014-12-10 14:12:48] [6e8ac1d1765f9a3eaeef7407a694f46f] [Current]

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Dataseries X:

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Boxplots

11 8 7 18 12 20 4 0.5 1 0.67 0.67 0 0.5 12.9
19 18 20 23 20 19 4 0.5 0.89 0.83 0.33 0.5 1 12.2
16 12 9 22 14 18 5 0.4 0.89 1 0.67 0 1 12.8
24 24 19 22 25 24 4 0.5 0.89 0.83 0 0 0 7.4
15 16 12 19 15 20 4 0.7 0.89 0.67 0 1 1 6.7
17 19 16 25 20 20 9 0.3 0.78 0 0 0.5 0.5 12.6
19 16 17 28 21 24 8 0.4 0.89 0.83 0.67 0.5 0 14.8
19 15 9 16 15 21 11 0.4 1 0.5 0.67 1 1 13.3
28 28 28 28 28 28 4 0.7 0.89 0.83 0 0.5 0 11.1
26 21 20 21 11 10 4 0.6 0.78 0.33 0.67 0.5 0.5 8.2
15 18 16 22 22 22 6 0.6 1 0.5 1 0 0.5 11.4
26 22 22 24 22 19 4 0.2 0.78 0.67 0 0.5 0.5 6.4
16 19 17 24 27 27 8 0.4 0.89 1 0 0.5 0.5 10.6
24 22 12 26 24 23 4 0.4 0.89 0.5 0.67 0 1 12
25 25 18 28 23 24 4 0.5 0.89 0.67 0.33 0 0 6.3
22 20 20 24 24 24 11 0.3 0.89 0.17 0.67 0 0.5 11.3
15 16 12 20 21 25 4 0.4 0.89 0.83 0.33 0.5 0.5 11.9
21 19 16 26 20 24 4 0.7 0.67 0.67 0.33 0.5 1 9.3
22 18 16 21 19 21 6 0.5 1 0.67 0.33 0 1 9.6
27 26 21 28 25 28 6 0.2 0.78 0.67 0 0 1 10
26 24 15 27 16 28 4 0.3 0.78 0.5 0.67 0 0.5 6.4
26 20 17 23 24 22 8 0.6 0.89 1 0.33 0 1 13.8
22 19 17 24 21 26 5 0.6 0.78 0.83 0.33 0 1 10.8
21 19 17 24 22 26 4 0.2 0.89 0.83 0.33 0 1 13.8
22 23 18 22 25 21 9 0.7 0.89 1 0.67 1 0 11.7
20 18 15 21 23 26 4 0.2 0.33 0.67 0 0 0 10.9
21 16 20 25 20 23 7 1 1 1 0.33 1 1 16.1
20 18 13 20 21 20 10 0.4 0.89 0.83 0.67 0 0.5 13.4
22 21 21 21 22 24 4 0.4 0.89 1 1 0 1 9.9
21 20 12 26 25 25 4 0.2 0.67 0.83 0.67 0 0.5 11.5
8 15 6 23 23 24 7 0.4 0.56 0.67 0.33 0 1 8.3
22 19 13 21 19 20 12 0.4 0.89 0.67 0 0.5 1 11.7
20 19 19 27 21 24 7 0.7 0.89 1 0.67 0.5 0.5 9
24 7 12 25 19 25 5 0.2 1 0.67 0.67 0 0.5 9.7
17 20 14 23 25 23 8 0.6 0.78 1 1 0 0.5 10.8
20 20 13 25 16 21 5 0.3 0.78 1 1 0.5 0.5 10.3
23 19 12 23 24 23 4 0.3 0.33 0.5 0.33 0 0 10.4
20 19 17 19 24 21 9 0.2 0.78 0.67 0 0.5 0 12.7
22 20 19 22 18 18 7 0.5 0.89 0.83 0.67 0.5 0.5 9.3
19 18 10 24 28 24 4 0.7 0.89 1 0.67 0.5 1 11.8
15 14 10 19 15 18 4 0.6 0.78 1 0.67 0.5 0.5 5.9
20 17 11 21 17 21 4 0.4 0.89 1 0.67 0.5 1 11.4
22 17 11 27 18 23 4 0.6 0.89 1 0.33 0.5 1 13
17 8 10 25 26 25 4 0.4 1 1 1 0 1 10.8
14 9 7 25 18 22 7 0.3 0.67 0.83 0.67 0 1 12.3
24 22 22 23 22 22 4 0.5 1 0.83 0.67 0.5 0.5 11.3
17 20 12 17 19 23 7 0.2 0.89 0.5 0 0 1 11.8
23 20 18 28 17 24 4 0.3 0.89 0.83 0 0.5 1 7.9
25 22 20 25 26 25 4 0.5 0.89 0.17 0 0 1 12.7
16 22 9 20 21 22 4 0.7 0.78 0.83 1 0.5 1 12.3
18 22 16 25 26 24 4 0.4 0.89 1 0.67 1 0.5 11.6
20 16 14 21 21 21 8 0.3 0.78 1 0 0 0.5 6.7
18 14 11 24 12 24 4 0.2 0.78 0.67 0.67 1 1 10.9
23 24 20 28 20 25 4 0.5 1 1 0 0 0.5 12.1
24 21 17 20 20 23 4 0.4 0.78 1 0 0.5 0 13.3
23 20 14 19 24 27 4 0.6 1 1 0.67 1 1 10.1
13 20 8 24 24 27 7 0.4 0.78 0.83 1 0 1 5.7
20 18 16 21 22 23 12 0.4 0.67 0.33 0 0 0.5 14.3
20 14 11 24 21 18 4 0.2 0.33 0.33 0.33 0 0 8
19 19 10 23 20 20 4 0.9 1 1 0.67 0.5 1 13.3
22 24 15 18 23 23 4 0.8 1 1 0.67 1 0.5 9.3
22 19 15 27 19 24 5 0.8 0.78 0.83 0 0.5 1 12.5
15 16 10 25 24 26 15 0.3 0.67 1 1 0.5 1 7.6
17 16 10 20 21 20 5 0.2 1 0.83 0.67 0 0.5 15.9
19 16 18 21 16 23 10 0.4 0.89 0.67 0 0.5 1 9.2
20 14 10 23 17 22 9 0.2 0.89 0.83 1 0 1 9.1
22 22 22 27 23 23 8 0.2 0.78 0.67 0.67 0.5 1 11.1
21 21 16 24 20 17 4 0.1 1 0.83 0.67 0 1 13
21 15 10 27 19 20 5 0.4 0.56 0.67 1 0.5 0 14.5
16 14 7 24 18 22 4 0.5 0.67 1 0 0.5 0.5 12.2
20 15 16 23 18 18 9 0.8 0.89 0.83 0.33 0.5 1 12.3
21 14 16 24 21 19 4 0.4 0.89 0.67 0.67 0 0.5 11.4
20 20 16 21 20 19 10 0.6 0.89 0.83 0.33 0.5 0.5 8.8
23 21 22 23 17 16 4 0.5 0.89 0.83 0.67 0.5 1 14.6
18 14 5 27 25 26 4 0.3 0.78 0.67 0 0 0 12.6
22 19 18 24 15 14 6 0.8 0.89 1 1 0.5 1 NA
16 16 10 25 17 25 7 0.4 1 0.33 0 0.5 0 13
17 13 8 19 17 23 5 0.6 1 0.83 0.67 0.5 0.5 12.6
24 26 16 24 24 18 4 0.4 0.89 1 0.33 0 0.5 13.2
13 13 8 25 21 22 4 0.3 0.44 0.83 0 0 0 9.9
19 18 16 23 22 26 4 0.8 0.78 0.83 0 1 1 7.7
20 15 14 23 18 25 4 0.6 0.89 0.5 0.33 1 1 10.5
22 18 15 25 22 26 4 0.3 0.67 0.5 0 0 0 13.4
19 21 9 26 20 26 4 0.5 0.78 0.83 0.67 0.5 1 10.9
21 17 21 26 21 24 6 0.4 0.78 1 0.33 0 1 4.3
15 18 7 16 21 22 10 0.3 0.33 0.33 0.67 0 0 10.3
21 20 17 23 20 21 7 0.7 0.89 1 0.33 0 0.5 11.8
24 18 18 26 18 22 4 0.2 0.89 0.67 0.33 0.5 0.5 11.2
22 25 16 25 25 28 4 0.4 0.89 0.83 1 0 1 11.4
20 20 16 23 23 22 7 0.6 0.89 1 0.67 0.5 0.5 8.6
21 19 14 26 21 26 4 0.6 0.56 0.83 0 0 1 13.2
19 18 15 22 20 20 8 0.6 0.67 0.83 0.67 0.5 0.5 12.6
14 12 8 20 21 24 11 0.4 0.67 1 0.33 0.5 1 5.6
25 22 22 27 20 21 6 0.6 0.78 0.83 0 0 1 9.9
11 16 5 20 22 23 14 0.5 0.78 1 0.33 0.5 1 8.8
17 18 13 22 15 23 5 0.5 0.78 0.83 0 0 1 7.7
22 23 22 24 24 23 4 0.6 0.89 0.67 0 0 1 9
20 20 18 21 22 22 8 0.8 1 0.83 0.33 0.5 1 7.3
22 20 15 24 21 23 9 0.5 0.89 0.83 0.67 1 0.5 11.4
15 16 11 26 17 21 4 0.6 0.89 0.83 0.67 0.5 1 13.6
23 22 19 24 23 27 4 0.4 0.78 0.83 0.67 0.5 1 7.9
20 19 19 24 22 23 5 0.3 1 0.67 0.67 0.5 1 10.7
22 23 21 27 23 26 4 0.3 0.78 0.83 1 0 0.5 10.3
16 6 4 25 16 27 5 0.2 0.67 0 0 0 0 8.3
25 19 17 27 18 27 4 0.4 0.78 0.83 0 0 0.5 9.6
18 24 10 19 25 23 4 0.5 0.89 1 0 0 0.5 14.2
19 19 13 22 18 23 7 0.3 0.67 0.17 0 0.5 0 8.5
25 15 15 22 14 23 10 0.4 0.22 0.17 0 0.5 0 13.5
21 18 11 25 20 28 4 0.5 0.44 0.5 1 0 0 4.9
22 18 20 23 19 24 5 0.3 0.89 0.5 0.67 0 1 6.4
21 22 13 24 18 20 4 0.5 0.67 1 0 0 0.5 9.6
22 23 18 24 22 23 4 0.4 0.89 0.67 0.67 0 0.5 11.6
23 18 20 23 21 22 4 0.4 0.67 0.83 0.67 0 1 11.1
20 17 15 22 14 15 6 0.6 0.78 1 0 1 1 4.35
6 6 4 24 5 27 4 0.3 0.78 1 0.67 1 1 12.7
15 22 9 19 25 23 8 0.4 0.78 1 0.33 1 0.5 18.1
18 20 18 25 21 23 5 0.3 1 1 1 1 1 17.85
24 16 12 26 11 20 4 1 0.78 1 1 1 1 16.6
22 16 17 18 20 18 17 0.4 0.67 1 0 0 0.5 12.6
21 17 12 24 9 22 4 0.8 0.89 0.83 1 0.5 1 17.1
23 20 16 28 15 20 4 0.3 0.89 1 0.67 1 1 19.1
20 23 17 23 23 21 8 0.5 1 0.83 0.67 0 1 16.1
20 18 14 19 21 25 4 0.4 0.78 1 0 0 0.5 13.35
18 13 13 19 9 19 7 0.3 0.67 0.83 0.67 0 1 18.4
25 22 20 27 24 25 4 0.5 0.89 0.83 1 0 1 14.7
16 20 16 24 16 24 4 0.3 0.67 1 0.67 0 1 10.6
20 20 15 26 20 22 5 0.3 0.67 0.67 0 0 1 12.6
14 13 10 21 15 28 7 0.4 1 0.83 0 0 1 16.2
22 16 16 25 18 22 4 0.3 0.67 1 0 0 0.5 13.6
26 25 21 28 22 21 4 0.6 1 1 0.33 0.5 0.5 18.9
20 16 15 19 21 23 7 0.6 0.89 0.83 0.67 1 1 14.1
17 15 16 20 21 19 11 0.4 0.89 1 1 1 1 14.5
22 19 19 26 21 21 7 0.4 1 1 0 0 0 16.15
22 19 9 27 20 25 4 0.4 0.67 1 0.67 0 0.5 14.75
20 24 19 23 24 23 4 0.3 0.44 0.67 0.67 0.5 1 14.8
17 9 7 18 15 28 4 0.2 0.89 1 0.33 1 0 12.45
22 22 23 23 24 14 4 0.5 0.56 0.83 0.67 0 1 12.65
17 15 14 21 18 23 4 0.4 0.78 1 0.67 1 1 17.35
22 22 10 23 24 24 4 0.4 1 1 0.67 0 0 8.6
21 22 16 22 24 25 6 0.4 1 0.83 0.67 0 1 18.4
25 24 12 21 15 15 8 0.3 0.89 0.67 0.67 0.5 0.5 16.1
11 12 10 14 19 23 23 0.4 0.67 0.83 0.67 1 0.5 11.6
19 21 7 24 20 26 4 0.2 0.89 1 0.33 0.5 1 17.75
24 25 20 26 26 21 8 0 0.33 0 0 0 0 15.25
17 26 9 24 26 26 6 0.4 0.89 1 0.67 0.5 1 17.65
22 21 12 22 23 23 4 0.6 0.78 1 0 1 1 16.35
17 14 10 20 13 15 7 0.4 1 0.67 0.67 0 0.5 17.65
26 28 19 20 16 16 4 0.4 0.44 1 0 0 0.5 13.6
20 21 11 18 22 20 4 0.4 0.67 0.83 0 0.5 0 14.35
19 16 15 18 21 20 4 0.2 0.33 0.17 0 0.5 0 14.75
21 16 14 25 11 21 10 0.4 0.89 0.83 1 1 1 18.25
24 25 11 28 23 28 6 0.3 0.89 0.83 0 0 0.5 9.9
21 21 14 23 18 19 5 0.6 1 0.83 0.67 1 0 16
19 22 15 20 19 21 5 0.6 0.89 0.83 1 0 1 18.25
13 9 7 22 15 22 4 0.4 0.89 0.83 0 0 1 16.85
24 20 22 27 8 27 4 0.5 1 1 0.67 1 0.5 14.6
28 19 19 24 15 20 5 0.4 0.89 0.83 0 0.5 1 13.85
27 24 22 23 21 17 5 0.6 1 1 1 1 1 18.95
22 22 11 20 25 26 5 0.6 0.78 0.83 0.67 0.5 1 15.6
23 22 19 22 14 21 5 0.9 0.78 1 0.67 0.5 1 14.85
19 12 9 21 21 24 4 0.4 0.67 0.83 0.67 0.5 0 11.75
18 17 11 24 18 21 6 0.8 0.89 1 1 0.5 1 18.45
23 18 17 26 18 25 4 0.5 0.67 0.83 1 0 1 15.9
21 10 12 24 12 22 4 0.4 0.78 0.83 1 0 0 17.1
22 22 17 18 24 17 4 0.4 0.89 1 0.67 1 0.5 16.1
17 24 10 17 17 14 9 0.7 0.89 1 1 1 0.5 19.9
15 18 17 23 20 23 18 0.4 0.78 1 0.33 1 1 10.95
21 18 13 21 24 28 6 0.8 1 1 0.67 0.5 1 18.45
20 23 11 21 22 24 5 0.4 1 1 1 1 0.5 15.1
26 21 19 24 15 22 4 0.3 1 1 0.67 0 0.5 15
19 21 21 22 22 24 11 0.5 0.67 1 0.67 0.5 1 11.35
28 28 24 24 26 25 4 0.8 0.89 1 0.67 1 1 15.95
21 17 13 24 17 21 10 0.4 1 0.83 0.33 0 0.5 18.1
19 21 16 24 23 22 6 1 1 1 1 0.5 0 14.6
22 21 13 23 19 16 8 0.5 0.89 1 0.67 1 1 15.4
21 20 15 21 21 18 8 0.5 0.89 1 0.67 1 1 15.4
20 18 15 24 23 27 6 0.3 0.89 1 0.33 0 1 17.6
19 17 11 19 19 17 8 0.3 0.89 0.83 0.33 0.5 1 13.35
11 7 7 19 18 25 4 0.3 0.89 0.5 0 0 1 19.1
17 17 13 23 16 24 4 0.4 1 0.67 0.33 0.5 0.5 15.35
19 14 13 25 23 21 9 0.5 0.67 1 0.33 0 1 7.6
20 18 12 24 13 21 9 0.5 1 0.67 0.67 0.5 1 13.4
17 14 8 21 18 19 5 0.4 0.89 1 0 0 0 13.9
21 23 7 18 23 27 4 0.7 0.89 1 1 0.5 0 19.1
21 20 17 23 21 28 4 0.5 0.89 0.5 0.33 0 0.5 15.25
12 14 9 20 23 19 15 0.4 0.89 0.67 0.33 1 0 12.9
23 17 18 23 16 23 10 0.7 1 0.67 1 0 1 16.1
22 21 17 23 17 25 9 0.7 1 0.67 1 0 1 17.35
22 23 17 23 20 26 7 0.7 1 0.67 1 0 1 13.15
21 24 18 23 18 25 9 0.7 0.89 0.67 1 0 1 12.15
20 21 12 27 20 25 6 0.7 0.89 0.67 0 0 0 12.6
18 14 14 19 19 24 4 0.7 0.89 1 0.67 0.5 1 10.35
21 24 22 25 26 24 7 0.1 0.33 0.67 0.33 0.5 0 15.4
24 16 19 25 9 24 4 0.2 0.67 0.67 0.67 0.5 1 9.6
22 21 21 21 23 22 7 0.3 0.56 0.33 0.33 0 1 18.2
20 8 10 25 9 21 4 0.6 0.44 0.83 0.33 0 0.5 13.6
17 17 16 17 13 17 15 0.8 1 1 1 1 1 14.85
19 18 11 22 27 23 4 0.8 0.89 1 0.33 0.5 0.5 14.75
16 17 15 23 22 17 9 0 0.33 0.17 0 0 0 14.1
19 16 12 27 12 25 4 0.3 0.67 0.67 0.33 0 1 14.9
23 22 21 27 18 19 4 0.6 0.67 0.83 0.33 0.5 1 16.25
8 17 22 5 6 8 28 0.5 1 0.83 0.67 0 1 19.25
22 21 20 19 17 14 4 0.7 0.78 1 0.33 0 0.5 13.6
23 20 15 24 22 22 4 0.3 0.67 0.83 0 0.5 1 13.6
15 20 9 23 22 25 4 0.3 1 1 0.67 0 0 15.65
17 19 15 28 23 28 5 0.4 0.78 1 0.67 0 0.5 12.75
21 8 14 25 19 25 4 0.4 0.89 0.83 1 0 1 14.6
25 19 11 27 20 24 4 0.1 0.89 0.83 0 0 1 9.85
18 11 9 16 17 15 12 0.5 0.89 1 0.67 0 1 12.65
20 13 12 25 24 24 4 0 0 0 0 0 0 19.2
21 18 11 26 20 28 6 0.4 0.67 1 0.33 0.5 0 16.6
21 19 14 24 18 24 6 0.6 1 0.83 0.67 1 0.5 11.2
24 23 10 23 23 25 5 0.4 1 1 0.33 0.5 1 15.25
22 20 18 24 27 23 4 0.1 0.67 0.33 0 0.5 1 11.9
22 22 11 27 25 26 4 0.3 0.89 0.83 0 0 1 13.2
23 19 14 25 24 26 4 0.7 0.89 0.83 0.67 0 1 16.35
17 16 16 19 12 22 10 0.3 0.56 0.17 0 0 1 12.4
15 11 11 19 16 25 7 0.5 0.67 0.83 0.33 0.5 0 15.85
22 21 16 24 24 22 4 0.3 1 0.83 0.67 1 1 18.15
19 14 13 20 23 26 7 0.6 1 0.67 0.67 0.5 1 11.15
18 21 12 21 24 20 4 0.9 1 1 1 0 1 15.65
21 20 17 28 24 26 4 0.4 0.67 0.83 0 0.5 1 17.75
20 21 23 26 26 26 12 0.3 0.44 1 0 0.5 0.5 7.65
19 20 14 19 19 21 5 0.9 0.89 1 0.67 1 1 12.35
19 19 10 23 28 21 8 0.5 0.44 1 0 0.5 0 15.6
16 19 16 23 23 24 6 0.3 0.56 1 1 0.5 0.5 19.3
18 18 11 21 21 21 17 0.6 0.89 0.83 0.67 0 0.5 15.2
23 20 16 26 19 18 4 0.2 0.67 1 0.33 0 0.5 17.1
22 21 19 25 23 23 5 0.4 0.89 0.83 1 0.5 1 15.6
23 22 17 25 23 26 4 0.5 1 0.83 0.67 0.5 0.5 18.4
20 19 12 24 20 23 5 0.4 0.78 0.83 0.67 0 0.5 19.05
24 23 17 23 18 25 5 0 0.44 0 0 0 0 18.55
25 16 11 22 20 20 6 0.2 0.89 1 0.33 0.5 1 19.1
25 23 19 27 28 25 4 0.5 0.89 1 0.67 0.5 1 13.1
20 18 12 26 21 26 4 0.3 0.89 1 0.67 0 0.5 12.85
23 23 8 23 25 19 4 0 0.44 0 0 0 0 9.5
21 20 17 22 18 21 6 0.5 1 0.83 1 0 1 4.5
23 20 13 26 24 23 8 0.6 0.89 0.83 0.33 0 1 11.85
23 23 17 22 28 24 10 0.3 0.67 0.83 0 0.5 0.5 13.6
11 13 7 17 9 6 4 0 0.33 0 0 0 0 11.7
21 21 23 25 22 22 5 0.3 0.78 0.67 0 0.5 0 12.4
27 26 18 22 26 21 4 0.5 0.89 1 0.67 0.5 1 13.35
19 18 13 28 28 28 4 0.4 0.78 0.67 0 0 1 11.4
21 19 17 22 18 24 4 0.5 0.78 0.83 0.67 0 0.5 14.9
16 18 13 21 23 14 16 0.7 0.89 1 1 1 0.5 19.9
21 18 8 24 15 20 7 0.8 0.78 1 0.67 0.5 1 11.2
22 19 16 26 24 28 4 0.6 0.78 1 0.33 0.5 1 14.6
16 13 14 26 12 19 4 0.4 0.67 0.83 0.33 0 0.5 17.6
18 10 13 24 12 24 14 0.5 0.89 0.83 0.33 0.5 0 14.05
23 21 19 27 20 21 5 0.5 0.89 1 0 0.5 1 16.1
24 24 15 22 25 21 5 0.3 0.78 1 0.33 0 1 13.35
20 21 15 23 24 26 5 0.6 1 1 0 0.5 1 11.85
20 23 8 22 23 24 5 0.3 1 0.67 0.67 0 0.5 11.95
18 18 14 23 18 26 7 0.6 0.78 0.83 1 0.5 0.5 14.75
4 11 7 15 20 25 19 0.3 0.78 0.33 0.33 0 1 15.15
14 16 11 20 22 23 16 0.7 0.89 1 0.67 1 1 13.2
22 20 17 22 20 24 4 0.7 0.89 1 1 0 1 16.85
17 20 19 25 25 24 4 0.6 0.67 0.67 1 0.5 1 7.85
23 26 17 27 28 26 7 0.5 1 1 0.33 0.5 0 7.7
20 21 12 24 25 23 9 0.5 0.67 0.83 0.33 0 0.5 12.6
18 12 12 21 14 20 5 0.4 0.56 0.67 0 0 1 7.85
19 15 18 17 16 16 14 0.4 0.78 1 0.33 1 1 10.95
20 18 16 26 24 24 4 0.7 1 1 1 0 1 12.35
15 14 15 20 13 20 16 0.2 0.67 0.17 0 0.5 0 9.95
24 18 20 22 19 23 10 0.5 0.78 0.83 0.67 0 0.5 14.9
21 16 16 24 18 23 5 0.4 0.56 0.83 0.67 0.5 0 16.65
19 19 12 23 16 18 6 0.2 1 1 0.67 1 1 13.4
19 7 10 22 8 21 4 0.5 0.89 0.67 0.67 0 0 13.95
27 21 28 28 27 25 4 0.4 0.44 0.5 0 0 1 15.7
23 24 19 21 23 23 4 0.7 1 0.67 1 1 1 16.85
23 21 18 24 20 26 5 0.6 0.89 0.83 0.67 1 0 10.95
20 20 19 28 20 26 4 0.4 0.78 0.83 0 0 0 15.35
17 22 8 25 26 24 4 0.5 0.89 1 0.67 1 1 12.2
21 17 17 24 23 23 5 0 0.11 0.17 0 0 0 15.1
23 19 16 24 24 21 4 0.7 0.89 1 0.67 0.5 1 17.75
22 20 18 21 21 23 4 0.4 0.89 0.67 0.67 0 1 15.2
16 16 12 20 15 20 5 0.5 1 0.67 1 0 1 14.6
20 20 17 26 22 23 8 0.6 0.89 0.83 0.67 0 0.5 16.65
16 16 13 16 25 24 15 0.8 1 0.5 0.67 0.5 0.5 8.1

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	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 16 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 14.1716 + 0.0648186AMS.I1[t] + 0.0571967AMS.I2[t] -0.0443875AMS.I3[t] -0.056479AMS.E1[t] -0.0548109AMS.E2[t] -0.0702072AMS.E3[t] -0.0102076AMS.A[t] -1.10386Algebraic_Reasoning[t] + 0.110554Calculation[t] + 1.11973Graphical_Interpretation[t] + 1.46061Proportionality_and_Ratio[t] + 0.395394Probability_and_Sampling[t] -0.258948Estimation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  14.1716 +  0.0648186AMS.I1[t] +  0.0571967AMS.I2[t] -0.0443875AMS.I3[t] -0.056479AMS.E1[t] -0.0548109AMS.E2[t] -0.0702072AMS.E3[t] -0.0102076AMS.A[t] -1.10386Algebraic_Reasoning[t] +  0.110554Calculation[t] +  1.11973Graphical_Interpretation[t] +  1.46061Proportionality_and_Ratio[t] +  0.395394Probability_and_Sampling[t] -0.258948Estimation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  14.1716 +  0.0648186AMS.I1[t] +  0.0571967AMS.I2[t] -0.0443875AMS.I3[t] -0.056479AMS.E1[t] -0.0548109AMS.E2[t] -0.0702072AMS.E3[t] -0.0102076AMS.A[t] -1.10386Algebraic_Reasoning[t] +  0.110554Calculation[t] +  1.11973Graphical_Interpretation[t] +  1.46061Proportionality_and_Ratio[t] +  0.395394Probability_and_Sampling[t] -0.258948Estimation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 14.1716 + 0.0648186AMS.I1[t] + 0.0571967AMS.I2[t] -0.0443875AMS.I3[t] -0.056479AMS.E1[t] -0.0548109AMS.E2[t] -0.0702072AMS.E3[t] -0.0102076AMS.A[t] -1.10386Algebraic_Reasoning[t] + 0.110554Calculation[t] + 1.11973Graphical_Interpretation[t] + 1.46061Proportionality_and_Ratio[t] + 0.395394Probability_and_Sampling[t] -0.258948Estimation[t] + 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)	14.1716	2.50139	5.665	3.82825e-08	1.91413e-08
AMS.I1	0.0648186	0.0843179	0.7687	0.442735	0.221367
AMS.I2	0.0571967	0.0729879	0.7836	0.43395	0.216975
AMS.I3	-0.0443875	0.0631646	-0.7027	0.482845	0.241422
AMS.E1	-0.056479	0.0872422	-0.6474	0.517947	0.258974
AMS.E2	-0.0548109	0.0596202	-0.9193	0.35876	0.17938
AMS.E3	-0.0702072	0.0716483	-0.9799	0.32804	0.16402
AMS.A	-0.0102076	0.0709999	-0.1438	0.885792	0.442896
Algebraic_Reasoning	-1.10386	1.26473	-0.8728	0.383563	0.191782
Calculation	0.110554	1.38721	0.0797	0.93654	0.46827
Graphical_Interpretation	1.11973	1.02892	1.088	0.277473	0.138736
Proportionality_and_Ratio	1.46061	0.640874	2.279	0.0234606	0.0117303
Probability_and_Sampling	0.395394	0.593152	0.6666	0.505611	0.252805
Estimation	-0.258948	0.572653	-0.4522	0.651503	0.325752

\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) & 14.1716 & 2.50139 & 5.665 & 3.82825e-08 & 1.91413e-08 \tabularnewline
AMS.I1 & 0.0648186 & 0.0843179 & 0.7687 & 0.442735 & 0.221367 \tabularnewline
AMS.I2 & 0.0571967 & 0.0729879 & 0.7836 & 0.43395 & 0.216975 \tabularnewline
AMS.I3 & -0.0443875 & 0.0631646 & -0.7027 & 0.482845 & 0.241422 \tabularnewline
AMS.E1 & -0.056479 & 0.0872422 & -0.6474 & 0.517947 & 0.258974 \tabularnewline
AMS.E2 & -0.0548109 & 0.0596202 & -0.9193 & 0.35876 & 0.17938 \tabularnewline
AMS.E3 & -0.0702072 & 0.0716483 & -0.9799 & 0.32804 & 0.16402 \tabularnewline
AMS.A & -0.0102076 & 0.0709999 & -0.1438 & 0.885792 & 0.442896 \tabularnewline
Algebraic_Reasoning & -1.10386 & 1.26473 & -0.8728 & 0.383563 & 0.191782 \tabularnewline
Calculation & 0.110554 & 1.38721 & 0.0797 & 0.93654 & 0.46827 \tabularnewline
Graphical_Interpretation & 1.11973 & 1.02892 & 1.088 & 0.277473 & 0.138736 \tabularnewline
Proportionality_and_Ratio & 1.46061 & 0.640874 & 2.279 & 0.0234606 & 0.0117303 \tabularnewline
Probability_and_Sampling & 0.395394 & 0.593152 & 0.6666 & 0.505611 & 0.252805 \tabularnewline
Estimation & -0.258948 & 0.572653 & -0.4522 & 0.651503 & 0.325752 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&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]14.1716[/C][C]2.50139[/C][C]5.665[/C][C]3.82825e-08[/C][C]1.91413e-08[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0648186[/C][C]0.0843179[/C][C]0.7687[/C][C]0.442735[/C][C]0.221367[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0571967[/C][C]0.0729879[/C][C]0.7836[/C][C]0.43395[/C][C]0.216975[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0443875[/C][C]0.0631646[/C][C]-0.7027[/C][C]0.482845[/C][C]0.241422[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.056479[/C][C]0.0872422[/C][C]-0.6474[/C][C]0.517947[/C][C]0.258974[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0548109[/C][C]0.0596202[/C][C]-0.9193[/C][C]0.35876[/C][C]0.17938[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0702072[/C][C]0.0716483[/C][C]-0.9799[/C][C]0.32804[/C][C]0.16402[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0102076[/C][C]0.0709999[/C][C]-0.1438[/C][C]0.885792[/C][C]0.442896[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.10386[/C][C]1.26473[/C][C]-0.8728[/C][C]0.383563[/C][C]0.191782[/C][/ROW]
[ROW][C]Calculation[/C][C]0.110554[/C][C]1.38721[/C][C]0.0797[/C][C]0.93654[/C][C]0.46827[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]1.11973[/C][C]1.02892[/C][C]1.088[/C][C]0.277473[/C][C]0.138736[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.46061[/C][C]0.640874[/C][C]2.279[/C][C]0.0234606[/C][C]0.0117303[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.395394[/C][C]0.593152[/C][C]0.6666[/C][C]0.505611[/C][C]0.252805[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.258948[/C][C]0.572653[/C][C]-0.4522[/C][C]0.651503[/C][C]0.325752[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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)	14.1716	2.50139	5.665	3.82825e-08	1.91413e-08
AMS.I1	0.0648186	0.0843179	0.7687	0.442735	0.221367
AMS.I2	0.0571967	0.0729879	0.7836	0.43395	0.216975
AMS.I3	-0.0443875	0.0631646	-0.7027	0.482845	0.241422
AMS.E1	-0.056479	0.0872422	-0.6474	0.517947	0.258974
AMS.E2	-0.0548109	0.0596202	-0.9193	0.35876	0.17938
AMS.E3	-0.0702072	0.0716483	-0.9799	0.32804	0.16402
AMS.A	-0.0102076	0.0709999	-0.1438	0.885792	0.442896
Algebraic_Reasoning	-1.10386	1.26473	-0.8728	0.383563	0.191782
Calculation	0.110554	1.38721	0.0797	0.93654	0.46827
Graphical_Interpretation	1.11973	1.02892	1.088	0.277473	0.138736
Proportionality_and_Ratio	1.46061	0.640874	2.279	0.0234606	0.0117303
Probability_and_Sampling	0.395394	0.593152	0.6666	0.505611	0.252805
Estimation	-0.258948	0.572653	-0.4522	0.651503	0.325752

Multiple Linear Regression - Regression Statistics
Multiple R	0.240019
R-squared	0.0576093
Adjusted R-squared	0.0112037
F-TEST (value)	1.24143
F-TEST (DF numerator)	13
F-TEST (DF denominator)	264
p-value	0.249792
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.37529
Sum Squared Residuals	3007.64

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.240019 \tabularnewline
R-squared & 0.0576093 \tabularnewline
Adjusted R-squared & 0.0112037 \tabularnewline
F-TEST (value) & 1.24143 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 264 \tabularnewline
p-value & 0.249792 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.37529 \tabularnewline
Sum Squared Residuals & 3007.64 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.240019[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0576093[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0112037[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.24143[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]264[/C][/ROW]
[ROW][C]p-value[/C][C]0.249792[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.37529[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3007.64[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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	0.240019
R-squared	0.0576093
Adjusted R-squared	0.0112037
F-TEST (value)	1.24143
F-TEST (DF numerator)	13
F-TEST (DF denominator)	264
p-value	0.249792
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.37529
Sum Squared Residuals	3007.64

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	13.0701	-0.170075
2	12.2	12.6715	-0.471491
3	12.8	13.6671	-0.867111
4	7.4	12.3938	-4.99379
5	6.7	12.3985	-5.69845
6	12.6	11.4691	1.1309
7	14.8	12.8271	1.97287
8	13.3	13.893	-0.593042
9	11.1	11.6752	-0.575155
10	8.2	14.4786	-6.2786
11	11.4	12.7482	-1.34823
12	6.4	12.8864	-6.48645
13	10.6	11.573	-0.972965
14	12	12.9497	-0.949745
15	6.3	12.6338	-6.33378
16	11.3	12.1923	-0.892261
17	11.9	12.5862	-0.686166
18	9.3	12.0912	-2.79115
19	9.6	12.6857	-3.08574
20	10	11.8546	-1.85464
21	6.4	13.3193	-6.91928
22	13.8	12.7844	1.01565
23	10.8	12.1231	-1.32311
24	13.8	12.4674	1.3326
25	11.7	13.7545	-2.05451
26	10.9	12.0847	-1.18466
27	16.1	12.1106	3.98939
28	13.4	13.569	-0.168965
29	9.9	13.7271	-3.8271
30	11.5	13.1411	-1.64111
31	8.3	11.5593	-3.25928
32	11.7	12.699	-0.998985
33	9	12.7712	-3.77117
34	9.7	12.8245	-3.12447
35	10.8	13.305	-2.50505
36	10.3	14.6241	-4.32413
37	10.4	12.6936	-2.29359
38	12.7	12.6587	0.041323
39	9.3	13.8565	-4.55649
40	11.8	12.7356	-0.935552
41	5.9	13.8914	-7.99137
42	11.4	14.0129	-2.61292
43	13	12.8911	0.108917
44	10.8	12.6445	-1.84451
45	12.3	12.6604	-0.360443
46	11.3	13.4536	-2.15359
47	11.8	12.3755	-0.57553
48	7.9	12.4037	-4.50371
49	12.7	11.0074	1.6926
50	12.3	13.8438	-1.54376
51	11.6	13.3447	-1.74467
52	6.7	12.6139	-5.91389
53	10.9	13.6425	-2.74249
54	12.1	12.2226	-0.122599
55	13.3	13.2545	0.0455274
56	10.1	13.5429	-3.44293
57	5.7	12.9408	-7.24075
58	14.3	11.5307	2.76932
59	8	12.6366	-4.63656
60	13.3	13.3599	-0.0599326
61	9.3	13.9633	-4.66333
62	12.5	11.7874	0.712587
63	7.6	13.1712	-5.57117
64	15.9	13.6772	2.22275
65	9.2	12.0852	-2.88523
66	9.1	13.9662	-4.86624
67	11.1	12.9304	-1.8304
68	13	13.9868	-0.986818
69	14.5	13.9542	0.545806
70	12.2	12.4813	-0.281313
71	12.3	12.5399	-0.239902
72	11.4	12.9982	-1.59821
73	8.8	13.0991	-4.29905
74	14.6	13.8852	0.714759
75	12.6	11.661	0.939019
76	NA	NA	1.25425
77	13	13.8157	-0.815688
78	12.6	13.0577	-0.457709
79	13.2	15.2011	-2.00113
80	9.9	13.8203	-3.92035
81	7.7	9.43722	-1.73722
82	10.5	8.88004	1.61996
83	13.4	15.6549	-2.2549
84	10.9	18.7947	-7.89473
85	4.3	7.21478	-2.91478
86	10.3	11.279	-0.979006
87	11.8	13.6954	-1.8954
88	11.2	13.1163	-1.91629
89	11.4	16.1286	-4.72862
90	8.6	6.98238	1.61762
91	13.2	13.9302	-0.730242
92	12.6	19.5054	-6.90542
93	5.6	7.71142	-2.11142
94	9.9	13.6595	-3.75946
95	8.8	13.3002	-4.5002
96	7.7	10.2374	-2.53736
97	9	14.0724	-5.07236
98	7.3	9.4829	-2.1829
99	11.4	10.7381	0.661888
100	13.6	18.7162	-5.1162
101	7.9	10.1311	-2.23114
102	10.7	13.7447	-3.04474
103	10.3	12.992	-2.692
104	8.3	10.8208	-2.52081
105	9.6	8.10489	1.49511
106	14.2	17.8284	-3.62842
107	8.5	7.22826	1.27174
108	13.5	21.6764	-8.17639
109	4.9	11.2097	-6.30968
110	6.4	9.73937	-3.33937
111	9.6	11.1534	-1.55339
112	11.6	13.5503	-1.95031
113	11.1	20.0803	-8.98031
114	4.35	4.79998	-0.449985
115	12.7	7.97522	4.72478
116	18.1	14.2006	3.89937
117	17.85	15.5425	2.30749
118	16.6	16.8308	-0.230815
119	12.6	9.5823	3.0177
120	17.1	12.2496	4.85041
121	19.1	16.1208	2.97915
122	16.1	15.2409	0.859147
123	13.35	8.87497	4.47503
124	18.4	16.9037	1.4963
125	14.7	17.3664	-2.66642
126	10.6	10.02	0.58003
127	12.6	8.07266	4.52734
128	16.2	15.1517	1.04827
129	13.6	7.87038	5.72962
130	18.9	18.0874	0.812575
131	14.1	13.668	0.431969
132	14.5	10.8144	3.6856
133	16.15	14.869	1.28095
134	14.75	13.0623	1.68772
135	14.8	15.8569	-1.05686
136	12.45	13.1558	-0.70579
137	12.65	8.86122	3.78878
138	17.35	22.5891	-5.23909
139	8.6	3.2245	5.3755
140	18.4	17.3534	1.04661
141	16.1	17.7518	-1.65183
142	11.6	7.2437	4.3563
143	17.75	14.3563	3.39369
144	15.25	10.9878	4.26217
145	17.65	14.0874	3.56264
146	16.35	12.632	3.71797
147	17.65	18.0916	-0.441646
148	13.6	12.523	1.07703
149	14.35	11.8436	2.50641
150	14.75	10.9184	3.83157
151	18.25	20.7169	-2.46689
152	9.9	8.09348	1.80652
153	16	11.6164	4.38364
154	18.25	13.2954	4.95455
155	16.85	16.1677	0.682347
156	14.6	13.872	0.728011
157	13.85	9.68827	4.16173
158	18.95	16.612	2.338
159	15.6	14.4219	1.17808
160	14.85	16.4653	-1.6153
161	11.75	6.97908	4.77092
162	18.45	15.8895	2.56054
163	15.9	12.8081	3.09188
164	17.1	15.556	1.54402
165	16.1	11.6076	4.49243
166	19.9	21.5579	-1.65792
167	10.95	5.22124	5.72876
168	18.45	18.0326	0.417448
169	15.1	14.2998	0.800176
170	15	16.6357	-1.6357
171	11.35	8.79619	2.55381
172	15.95	10.8653	5.08474
173	18.1	16.9568	1.14318
174	14.6	13.6575	0.942491
175	15.4	14.1096	1.29036
176	15.4	10.1687	5.23131
177	17.6	17.8649	-0.264865
178	13.35	5.43667	7.91333
179	19.1	16.4864	2.61356
180	15.35	20.0029	-4.65291
181	7.6	7.75676	-0.156765
182	13.4	12.4381	0.96192
183	13.9	9.22759	4.67241
184	19.1	15.7743	3.32573
185	15.25	15.1078	0.142169
186	12.9	10.0327	2.86735
187	16.1	12.006	4.09401
188	17.35	17.3562	-0.0061607
189	13.15	14.2514	-1.1014
190	12.15	11.3247	0.825253
191	12.6	15.2901	-2.69009
192	10.35	7.64148	2.70852
193	15.4	19.4888	-4.08879
194	9.6	3.52716	6.07284
195	18.2	17.3294	0.870593
196	13.6	13.2105	0.38945
197	14.85	12.5516	2.29838
198	14.75	12.6018	2.14822
199	14.1	11.7231	2.37688
200	14.9	11.5142	3.38584
201	16.25	11.4349	4.81514
202	19.25	19.3181	-0.0681204
203	13.6	12.6048	0.995176
204	13.6	11.4152	2.18485
205	15.65	15.3491	0.30095
206	12.75	11.0574	1.69261
207	14.6	17.452	-2.85198
208	9.85	11.1428	-1.29278
209	12.65	4.6756	7.9744
210	19.2	15.5143	3.68573
211	16.6	18.9319	-2.33189
212	11.2	9.39246	1.80754
213	15.25	15.0735	0.176513
214	11.9	10.7439	1.15613
215	13.2	9.35877	3.84123
216	16.35	15.7131	0.636885
217	12.4	9.18925	3.21075
218	15.85	11.356	4.49402
219	18.15	19.4556	-1.30557
220	11.15	8.99875	2.15125
221	15.65	9.55966	6.09034
222	17.75	21.8122	-4.06217
223	7.65	8.92543	-1.27543
224	12.35	9.22038	3.12962
225	15.6	9.95862	5.64138
226	19.3	17.2092	2.09081
227	15.2	11.7073	3.49274
228	17.1	15.1025	1.99751
229	15.6	10.3621	5.23789
230	18.4	12.6777	5.7223
231	19.05	12.745	6.30504
232	18.55	13.2829	5.26713
233	19.1	18.9921	0.107912
234	13.1	13.4652	-0.365221
235	12.85	15.9774	-3.1274
236	9.5	18.847	-9.34703
237	4.5	4.98745	-0.487448
238	11.85	10.6495	1.20045
239	13.6	15.3384	-1.73838
240	11.7	11.5025	0.197451
241	12.4	13.0605	-0.660548
242	13.35	12.8188	0.531174
243	11.4	9.72277	1.67723
244	14.9	9.24018	5.65982
245	19.9	22.4942	-2.59417
246	11.2	8.74796	2.45204
247	14.6	9.74427	4.85573
248	17.6	16.1977	1.40234
249	14.05	10.4286	3.62144
250	16.1	16.1438	-0.0437723
251	13.35	13.5191	-0.169064
252	11.85	13.4679	-1.6179
253	11.95	10.6461	1.30392
254	14.75	10.8044	3.9456
255	15.15	14.9029	0.247127
256	13.2	9.91944	3.28056
257	16.85	21.6273	-4.77733
258	7.85	12.9465	-5.09649
259	7.7	7.60805	0.0919459
260	12.6	16.945	-4.34505
261	7.85	10.6416	-2.79162
262	10.95	11.5368	-0.586795
263	12.35	14.5105	-2.16054
264	9.95	8.23102	1.71898
265	14.9	11.7058	3.19415
266	16.65	17.8308	-1.1808
267	13.4	12.8887	0.511302
268	13.95	9.18064	4.76936
269	15.7	12.6246	3.07543
270	16.85	19.3759	-2.52586
271	10.95	7.39872	3.55128
272	15.35	16.5451	-1.19509
273	12.2	8.77107	3.42893
274	15.1	10.5656	4.53444
275	17.75	15.6266	2.12343
276	15.2	14.2947	0.905268
277	14.6	10.6511	3.94886
278	16.65	20.8189	-4.1689
279	8.1	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.0701 & -0.170075 \tabularnewline
2 & 12.2 & 12.6715 & -0.471491 \tabularnewline
3 & 12.8 & 13.6671 & -0.867111 \tabularnewline
4 & 7.4 & 12.3938 & -4.99379 \tabularnewline
5 & 6.7 & 12.3985 & -5.69845 \tabularnewline
6 & 12.6 & 11.4691 & 1.1309 \tabularnewline
7 & 14.8 & 12.8271 & 1.97287 \tabularnewline
8 & 13.3 & 13.893 & -0.593042 \tabularnewline
9 & 11.1 & 11.6752 & -0.575155 \tabularnewline
10 & 8.2 & 14.4786 & -6.2786 \tabularnewline
11 & 11.4 & 12.7482 & -1.34823 \tabularnewline
12 & 6.4 & 12.8864 & -6.48645 \tabularnewline
13 & 10.6 & 11.573 & -0.972965 \tabularnewline
14 & 12 & 12.9497 & -0.949745 \tabularnewline
15 & 6.3 & 12.6338 & -6.33378 \tabularnewline
16 & 11.3 & 12.1923 & -0.892261 \tabularnewline
17 & 11.9 & 12.5862 & -0.686166 \tabularnewline
18 & 9.3 & 12.0912 & -2.79115 \tabularnewline
19 & 9.6 & 12.6857 & -3.08574 \tabularnewline
20 & 10 & 11.8546 & -1.85464 \tabularnewline
21 & 6.4 & 13.3193 & -6.91928 \tabularnewline
22 & 13.8 & 12.7844 & 1.01565 \tabularnewline
23 & 10.8 & 12.1231 & -1.32311 \tabularnewline
24 & 13.8 & 12.4674 & 1.3326 \tabularnewline
25 & 11.7 & 13.7545 & -2.05451 \tabularnewline
26 & 10.9 & 12.0847 & -1.18466 \tabularnewline
27 & 16.1 & 12.1106 & 3.98939 \tabularnewline
28 & 13.4 & 13.569 & -0.168965 \tabularnewline
29 & 9.9 & 13.7271 & -3.8271 \tabularnewline
30 & 11.5 & 13.1411 & -1.64111 \tabularnewline
31 & 8.3 & 11.5593 & -3.25928 \tabularnewline
32 & 11.7 & 12.699 & -0.998985 \tabularnewline
33 & 9 & 12.7712 & -3.77117 \tabularnewline
34 & 9.7 & 12.8245 & -3.12447 \tabularnewline
35 & 10.8 & 13.305 & -2.50505 \tabularnewline
36 & 10.3 & 14.6241 & -4.32413 \tabularnewline
37 & 10.4 & 12.6936 & -2.29359 \tabularnewline
38 & 12.7 & 12.6587 & 0.041323 \tabularnewline
39 & 9.3 & 13.8565 & -4.55649 \tabularnewline
40 & 11.8 & 12.7356 & -0.935552 \tabularnewline
41 & 5.9 & 13.8914 & -7.99137 \tabularnewline
42 & 11.4 & 14.0129 & -2.61292 \tabularnewline
43 & 13 & 12.8911 & 0.108917 \tabularnewline
44 & 10.8 & 12.6445 & -1.84451 \tabularnewline
45 & 12.3 & 12.6604 & -0.360443 \tabularnewline
46 & 11.3 & 13.4536 & -2.15359 \tabularnewline
47 & 11.8 & 12.3755 & -0.57553 \tabularnewline
48 & 7.9 & 12.4037 & -4.50371 \tabularnewline
49 & 12.7 & 11.0074 & 1.6926 \tabularnewline
50 & 12.3 & 13.8438 & -1.54376 \tabularnewline
51 & 11.6 & 13.3447 & -1.74467 \tabularnewline
52 & 6.7 & 12.6139 & -5.91389 \tabularnewline
53 & 10.9 & 13.6425 & -2.74249 \tabularnewline
54 & 12.1 & 12.2226 & -0.122599 \tabularnewline
55 & 13.3 & 13.2545 & 0.0455274 \tabularnewline
56 & 10.1 & 13.5429 & -3.44293 \tabularnewline
57 & 5.7 & 12.9408 & -7.24075 \tabularnewline
58 & 14.3 & 11.5307 & 2.76932 \tabularnewline
59 & 8 & 12.6366 & -4.63656 \tabularnewline
60 & 13.3 & 13.3599 & -0.0599326 \tabularnewline
61 & 9.3 & 13.9633 & -4.66333 \tabularnewline
62 & 12.5 & 11.7874 & 0.712587 \tabularnewline
63 & 7.6 & 13.1712 & -5.57117 \tabularnewline
64 & 15.9 & 13.6772 & 2.22275 \tabularnewline
65 & 9.2 & 12.0852 & -2.88523 \tabularnewline
66 & 9.1 & 13.9662 & -4.86624 \tabularnewline
67 & 11.1 & 12.9304 & -1.8304 \tabularnewline
68 & 13 & 13.9868 & -0.986818 \tabularnewline
69 & 14.5 & 13.9542 & 0.545806 \tabularnewline
70 & 12.2 & 12.4813 & -0.281313 \tabularnewline
71 & 12.3 & 12.5399 & -0.239902 \tabularnewline
72 & 11.4 & 12.9982 & -1.59821 \tabularnewline
73 & 8.8 & 13.0991 & -4.29905 \tabularnewline
74 & 14.6 & 13.8852 & 0.714759 \tabularnewline
75 & 12.6 & 11.661 & 0.939019 \tabularnewline
76 & NA & NA & 1.25425 \tabularnewline
77 & 13 & 13.8157 & -0.815688 \tabularnewline
78 & 12.6 & 13.0577 & -0.457709 \tabularnewline
79 & 13.2 & 15.2011 & -2.00113 \tabularnewline
80 & 9.9 & 13.8203 & -3.92035 \tabularnewline
81 & 7.7 & 9.43722 & -1.73722 \tabularnewline
82 & 10.5 & 8.88004 & 1.61996 \tabularnewline
83 & 13.4 & 15.6549 & -2.2549 \tabularnewline
84 & 10.9 & 18.7947 & -7.89473 \tabularnewline
85 & 4.3 & 7.21478 & -2.91478 \tabularnewline
86 & 10.3 & 11.279 & -0.979006 \tabularnewline
87 & 11.8 & 13.6954 & -1.8954 \tabularnewline
88 & 11.2 & 13.1163 & -1.91629 \tabularnewline
89 & 11.4 & 16.1286 & -4.72862 \tabularnewline
90 & 8.6 & 6.98238 & 1.61762 \tabularnewline
91 & 13.2 & 13.9302 & -0.730242 \tabularnewline
92 & 12.6 & 19.5054 & -6.90542 \tabularnewline
93 & 5.6 & 7.71142 & -2.11142 \tabularnewline
94 & 9.9 & 13.6595 & -3.75946 \tabularnewline
95 & 8.8 & 13.3002 & -4.5002 \tabularnewline
96 & 7.7 & 10.2374 & -2.53736 \tabularnewline
97 & 9 & 14.0724 & -5.07236 \tabularnewline
98 & 7.3 & 9.4829 & -2.1829 \tabularnewline
99 & 11.4 & 10.7381 & 0.661888 \tabularnewline
100 & 13.6 & 18.7162 & -5.1162 \tabularnewline
101 & 7.9 & 10.1311 & -2.23114 \tabularnewline
102 & 10.7 & 13.7447 & -3.04474 \tabularnewline
103 & 10.3 & 12.992 & -2.692 \tabularnewline
104 & 8.3 & 10.8208 & -2.52081 \tabularnewline
105 & 9.6 & 8.10489 & 1.49511 \tabularnewline
106 & 14.2 & 17.8284 & -3.62842 \tabularnewline
107 & 8.5 & 7.22826 & 1.27174 \tabularnewline
108 & 13.5 & 21.6764 & -8.17639 \tabularnewline
109 & 4.9 & 11.2097 & -6.30968 \tabularnewline
110 & 6.4 & 9.73937 & -3.33937 \tabularnewline
111 & 9.6 & 11.1534 & -1.55339 \tabularnewline
112 & 11.6 & 13.5503 & -1.95031 \tabularnewline
113 & 11.1 & 20.0803 & -8.98031 \tabularnewline
114 & 4.35 & 4.79998 & -0.449985 \tabularnewline
115 & 12.7 & 7.97522 & 4.72478 \tabularnewline
116 & 18.1 & 14.2006 & 3.89937 \tabularnewline
117 & 17.85 & 15.5425 & 2.30749 \tabularnewline
118 & 16.6 & 16.8308 & -0.230815 \tabularnewline
119 & 12.6 & 9.5823 & 3.0177 \tabularnewline
120 & 17.1 & 12.2496 & 4.85041 \tabularnewline
121 & 19.1 & 16.1208 & 2.97915 \tabularnewline
122 & 16.1 & 15.2409 & 0.859147 \tabularnewline
123 & 13.35 & 8.87497 & 4.47503 \tabularnewline
124 & 18.4 & 16.9037 & 1.4963 \tabularnewline
125 & 14.7 & 17.3664 & -2.66642 \tabularnewline
126 & 10.6 & 10.02 & 0.58003 \tabularnewline
127 & 12.6 & 8.07266 & 4.52734 \tabularnewline
128 & 16.2 & 15.1517 & 1.04827 \tabularnewline
129 & 13.6 & 7.87038 & 5.72962 \tabularnewline
130 & 18.9 & 18.0874 & 0.812575 \tabularnewline
131 & 14.1 & 13.668 & 0.431969 \tabularnewline
132 & 14.5 & 10.8144 & 3.6856 \tabularnewline
133 & 16.15 & 14.869 & 1.28095 \tabularnewline
134 & 14.75 & 13.0623 & 1.68772 \tabularnewline
135 & 14.8 & 15.8569 & -1.05686 \tabularnewline
136 & 12.45 & 13.1558 & -0.70579 \tabularnewline
137 & 12.65 & 8.86122 & 3.78878 \tabularnewline
138 & 17.35 & 22.5891 & -5.23909 \tabularnewline
139 & 8.6 & 3.2245 & 5.3755 \tabularnewline
140 & 18.4 & 17.3534 & 1.04661 \tabularnewline
141 & 16.1 & 17.7518 & -1.65183 \tabularnewline
142 & 11.6 & 7.2437 & 4.3563 \tabularnewline
143 & 17.75 & 14.3563 & 3.39369 \tabularnewline
144 & 15.25 & 10.9878 & 4.26217 \tabularnewline
145 & 17.65 & 14.0874 & 3.56264 \tabularnewline
146 & 16.35 & 12.632 & 3.71797 \tabularnewline
147 & 17.65 & 18.0916 & -0.441646 \tabularnewline
148 & 13.6 & 12.523 & 1.07703 \tabularnewline
149 & 14.35 & 11.8436 & 2.50641 \tabularnewline
150 & 14.75 & 10.9184 & 3.83157 \tabularnewline
151 & 18.25 & 20.7169 & -2.46689 \tabularnewline
152 & 9.9 & 8.09348 & 1.80652 \tabularnewline
153 & 16 & 11.6164 & 4.38364 \tabularnewline
154 & 18.25 & 13.2954 & 4.95455 \tabularnewline
155 & 16.85 & 16.1677 & 0.682347 \tabularnewline
156 & 14.6 & 13.872 & 0.728011 \tabularnewline
157 & 13.85 & 9.68827 & 4.16173 \tabularnewline
158 & 18.95 & 16.612 & 2.338 \tabularnewline
159 & 15.6 & 14.4219 & 1.17808 \tabularnewline
160 & 14.85 & 16.4653 & -1.6153 \tabularnewline
161 & 11.75 & 6.97908 & 4.77092 \tabularnewline
162 & 18.45 & 15.8895 & 2.56054 \tabularnewline
163 & 15.9 & 12.8081 & 3.09188 \tabularnewline
164 & 17.1 & 15.556 & 1.54402 \tabularnewline
165 & 16.1 & 11.6076 & 4.49243 \tabularnewline
166 & 19.9 & 21.5579 & -1.65792 \tabularnewline
167 & 10.95 & 5.22124 & 5.72876 \tabularnewline
168 & 18.45 & 18.0326 & 0.417448 \tabularnewline
169 & 15.1 & 14.2998 & 0.800176 \tabularnewline
170 & 15 & 16.6357 & -1.6357 \tabularnewline
171 & 11.35 & 8.79619 & 2.55381 \tabularnewline
172 & 15.95 & 10.8653 & 5.08474 \tabularnewline
173 & 18.1 & 16.9568 & 1.14318 \tabularnewline
174 & 14.6 & 13.6575 & 0.942491 \tabularnewline
175 & 15.4 & 14.1096 & 1.29036 \tabularnewline
176 & 15.4 & 10.1687 & 5.23131 \tabularnewline
177 & 17.6 & 17.8649 & -0.264865 \tabularnewline
178 & 13.35 & 5.43667 & 7.91333 \tabularnewline
179 & 19.1 & 16.4864 & 2.61356 \tabularnewline
180 & 15.35 & 20.0029 & -4.65291 \tabularnewline
181 & 7.6 & 7.75676 & -0.156765 \tabularnewline
182 & 13.4 & 12.4381 & 0.96192 \tabularnewline
183 & 13.9 & 9.22759 & 4.67241 \tabularnewline
184 & 19.1 & 15.7743 & 3.32573 \tabularnewline
185 & 15.25 & 15.1078 & 0.142169 \tabularnewline
186 & 12.9 & 10.0327 & 2.86735 \tabularnewline
187 & 16.1 & 12.006 & 4.09401 \tabularnewline
188 & 17.35 & 17.3562 & -0.0061607 \tabularnewline
189 & 13.15 & 14.2514 & -1.1014 \tabularnewline
190 & 12.15 & 11.3247 & 0.825253 \tabularnewline
191 & 12.6 & 15.2901 & -2.69009 \tabularnewline
192 & 10.35 & 7.64148 & 2.70852 \tabularnewline
193 & 15.4 & 19.4888 & -4.08879 \tabularnewline
194 & 9.6 & 3.52716 & 6.07284 \tabularnewline
195 & 18.2 & 17.3294 & 0.870593 \tabularnewline
196 & 13.6 & 13.2105 & 0.38945 \tabularnewline
197 & 14.85 & 12.5516 & 2.29838 \tabularnewline
198 & 14.75 & 12.6018 & 2.14822 \tabularnewline
199 & 14.1 & 11.7231 & 2.37688 \tabularnewline
200 & 14.9 & 11.5142 & 3.38584 \tabularnewline
201 & 16.25 & 11.4349 & 4.81514 \tabularnewline
202 & 19.25 & 19.3181 & -0.0681204 \tabularnewline
203 & 13.6 & 12.6048 & 0.995176 \tabularnewline
204 & 13.6 & 11.4152 & 2.18485 \tabularnewline
205 & 15.65 & 15.3491 & 0.30095 \tabularnewline
206 & 12.75 & 11.0574 & 1.69261 \tabularnewline
207 & 14.6 & 17.452 & -2.85198 \tabularnewline
208 & 9.85 & 11.1428 & -1.29278 \tabularnewline
209 & 12.65 & 4.6756 & 7.9744 \tabularnewline
210 & 19.2 & 15.5143 & 3.68573 \tabularnewline
211 & 16.6 & 18.9319 & -2.33189 \tabularnewline
212 & 11.2 & 9.39246 & 1.80754 \tabularnewline
213 & 15.25 & 15.0735 & 0.176513 \tabularnewline
214 & 11.9 & 10.7439 & 1.15613 \tabularnewline
215 & 13.2 & 9.35877 & 3.84123 \tabularnewline
216 & 16.35 & 15.7131 & 0.636885 \tabularnewline
217 & 12.4 & 9.18925 & 3.21075 \tabularnewline
218 & 15.85 & 11.356 & 4.49402 \tabularnewline
219 & 18.15 & 19.4556 & -1.30557 \tabularnewline
220 & 11.15 & 8.99875 & 2.15125 \tabularnewline
221 & 15.65 & 9.55966 & 6.09034 \tabularnewline
222 & 17.75 & 21.8122 & -4.06217 \tabularnewline
223 & 7.65 & 8.92543 & -1.27543 \tabularnewline
224 & 12.35 & 9.22038 & 3.12962 \tabularnewline
225 & 15.6 & 9.95862 & 5.64138 \tabularnewline
226 & 19.3 & 17.2092 & 2.09081 \tabularnewline
227 & 15.2 & 11.7073 & 3.49274 \tabularnewline
228 & 17.1 & 15.1025 & 1.99751 \tabularnewline
229 & 15.6 & 10.3621 & 5.23789 \tabularnewline
230 & 18.4 & 12.6777 & 5.7223 \tabularnewline
231 & 19.05 & 12.745 & 6.30504 \tabularnewline
232 & 18.55 & 13.2829 & 5.26713 \tabularnewline
233 & 19.1 & 18.9921 & 0.107912 \tabularnewline
234 & 13.1 & 13.4652 & -0.365221 \tabularnewline
235 & 12.85 & 15.9774 & -3.1274 \tabularnewline
236 & 9.5 & 18.847 & -9.34703 \tabularnewline
237 & 4.5 & 4.98745 & -0.487448 \tabularnewline
238 & 11.85 & 10.6495 & 1.20045 \tabularnewline
239 & 13.6 & 15.3384 & -1.73838 \tabularnewline
240 & 11.7 & 11.5025 & 0.197451 \tabularnewline
241 & 12.4 & 13.0605 & -0.660548 \tabularnewline
242 & 13.35 & 12.8188 & 0.531174 \tabularnewline
243 & 11.4 & 9.72277 & 1.67723 \tabularnewline
244 & 14.9 & 9.24018 & 5.65982 \tabularnewline
245 & 19.9 & 22.4942 & -2.59417 \tabularnewline
246 & 11.2 & 8.74796 & 2.45204 \tabularnewline
247 & 14.6 & 9.74427 & 4.85573 \tabularnewline
248 & 17.6 & 16.1977 & 1.40234 \tabularnewline
249 & 14.05 & 10.4286 & 3.62144 \tabularnewline
250 & 16.1 & 16.1438 & -0.0437723 \tabularnewline
251 & 13.35 & 13.5191 & -0.169064 \tabularnewline
252 & 11.85 & 13.4679 & -1.6179 \tabularnewline
253 & 11.95 & 10.6461 & 1.30392 \tabularnewline
254 & 14.75 & 10.8044 & 3.9456 \tabularnewline
255 & 15.15 & 14.9029 & 0.247127 \tabularnewline
256 & 13.2 & 9.91944 & 3.28056 \tabularnewline
257 & 16.85 & 21.6273 & -4.77733 \tabularnewline
258 & 7.85 & 12.9465 & -5.09649 \tabularnewline
259 & 7.7 & 7.60805 & 0.0919459 \tabularnewline
260 & 12.6 & 16.945 & -4.34505 \tabularnewline
261 & 7.85 & 10.6416 & -2.79162 \tabularnewline
262 & 10.95 & 11.5368 & -0.586795 \tabularnewline
263 & 12.35 & 14.5105 & -2.16054 \tabularnewline
264 & 9.95 & 8.23102 & 1.71898 \tabularnewline
265 & 14.9 & 11.7058 & 3.19415 \tabularnewline
266 & 16.65 & 17.8308 & -1.1808 \tabularnewline
267 & 13.4 & 12.8887 & 0.511302 \tabularnewline
268 & 13.95 & 9.18064 & 4.76936 \tabularnewline
269 & 15.7 & 12.6246 & 3.07543 \tabularnewline
270 & 16.85 & 19.3759 & -2.52586 \tabularnewline
271 & 10.95 & 7.39872 & 3.55128 \tabularnewline
272 & 15.35 & 16.5451 & -1.19509 \tabularnewline
273 & 12.2 & 8.77107 & 3.42893 \tabularnewline
274 & 15.1 & 10.5656 & 4.53444 \tabularnewline
275 & 17.75 & 15.6266 & 2.12343 \tabularnewline
276 & 15.2 & 14.2947 & 0.905268 \tabularnewline
277 & 14.6 & 10.6511 & 3.94886 \tabularnewline
278 & 16.65 & 20.8189 & -4.1689 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.0701[/C][C]-0.170075[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.6715[/C][C]-0.471491[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.6671[/C][C]-0.867111[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.3938[/C][C]-4.99379[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.3985[/C][C]-5.69845[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]11.4691[/C][C]1.1309[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.8271[/C][C]1.97287[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.893[/C][C]-0.593042[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.6752[/C][C]-0.575155[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.4786[/C][C]-6.2786[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.7482[/C][C]-1.34823[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]12.8864[/C][C]-6.48645[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.573[/C][C]-0.972965[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.9497[/C][C]-0.949745[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.6338[/C][C]-6.33378[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.1923[/C][C]-0.892261[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.5862[/C][C]-0.686166[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.0912[/C][C]-2.79115[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.6857[/C][C]-3.08574[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.8546[/C][C]-1.85464[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]13.3193[/C][C]-6.91928[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.7844[/C][C]1.01565[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.1231[/C][C]-1.32311[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.4674[/C][C]1.3326[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.7545[/C][C]-2.05451[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.0847[/C][C]-1.18466[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.1106[/C][C]3.98939[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.569[/C][C]-0.168965[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.7271[/C][C]-3.8271[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.1411[/C][C]-1.64111[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.5593[/C][C]-3.25928[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]12.699[/C][C]-0.998985[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.7712[/C][C]-3.77117[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.8245[/C][C]-3.12447[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.305[/C][C]-2.50505[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]14.6241[/C][C]-4.32413[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.6936[/C][C]-2.29359[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6587[/C][C]0.041323[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.8565[/C][C]-4.55649[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.7356[/C][C]-0.935552[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.8914[/C][C]-7.99137[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.0129[/C][C]-2.61292[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]12.8911[/C][C]0.108917[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.6445[/C][C]-1.84451[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.6604[/C][C]-0.360443[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.4536[/C][C]-2.15359[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.3755[/C][C]-0.57553[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.4037[/C][C]-4.50371[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.0074[/C][C]1.6926[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.8438[/C][C]-1.54376[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.3447[/C][C]-1.74467[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.6139[/C][C]-5.91389[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.6425[/C][C]-2.74249[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.2226[/C][C]-0.122599[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.2545[/C][C]0.0455274[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.5429[/C][C]-3.44293[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.9408[/C][C]-7.24075[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]11.5307[/C][C]2.76932[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.6366[/C][C]-4.63656[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.3599[/C][C]-0.0599326[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.9633[/C][C]-4.66333[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.7874[/C][C]0.712587[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]13.1712[/C][C]-5.57117[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.6772[/C][C]2.22275[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.0852[/C][C]-2.88523[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]13.9662[/C][C]-4.86624[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.9304[/C][C]-1.8304[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.9868[/C][C]-0.986818[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.9542[/C][C]0.545806[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.4813[/C][C]-0.281313[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.5399[/C][C]-0.239902[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.9982[/C][C]-1.59821[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.0991[/C][C]-4.29905[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.8852[/C][C]0.714759[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.661[/C][C]0.939019[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.25425[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.8157[/C][C]-0.815688[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.0577[/C][C]-0.457709[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]15.2011[/C][C]-2.00113[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]13.8203[/C][C]-3.92035[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]9.43722[/C][C]-1.73722[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]8.88004[/C][C]1.61996[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.6549[/C][C]-2.2549[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]18.7947[/C][C]-7.89473[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.21478[/C][C]-2.91478[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]11.279[/C][C]-0.979006[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]13.6954[/C][C]-1.8954[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]13.1163[/C][C]-1.91629[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]16.1286[/C][C]-4.72862[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.98238[/C][C]1.61762[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]13.9302[/C][C]-0.730242[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.5054[/C][C]-6.90542[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.71142[/C][C]-2.11142[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.6595[/C][C]-3.75946[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]13.3002[/C][C]-4.5002[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.2374[/C][C]-2.53736[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.0724[/C][C]-5.07236[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]9.4829[/C][C]-2.1829[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.7381[/C][C]0.661888[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.7162[/C][C]-5.1162[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]10.1311[/C][C]-2.23114[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.7447[/C][C]-3.04474[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.992[/C][C]-2.692[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]10.8208[/C][C]-2.52081[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]8.10489[/C][C]1.49511[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]17.8284[/C][C]-3.62842[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.22826[/C][C]1.27174[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.6764[/C][C]-8.17639[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]11.2097[/C][C]-6.30968[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.73937[/C][C]-3.33937[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]11.1534[/C][C]-1.55339[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]13.5503[/C][C]-1.95031[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]20.0803[/C][C]-8.98031[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.79998[/C][C]-0.449985[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]7.97522[/C][C]4.72478[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]14.2006[/C][C]3.89937[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]15.5425[/C][C]2.30749[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.8308[/C][C]-0.230815[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]9.5823[/C][C]3.0177[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]12.2496[/C][C]4.85041[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]16.1208[/C][C]2.97915[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.2409[/C][C]0.859147[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]8.87497[/C][C]4.47503[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]16.9037[/C][C]1.4963[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.3664[/C][C]-2.66642[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]10.02[/C][C]0.58003[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]8.07266[/C][C]4.52734[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.1517[/C][C]1.04827[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]7.87038[/C][C]5.72962[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.0874[/C][C]0.812575[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.668[/C][C]0.431969[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]10.8144[/C][C]3.6856[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.869[/C][C]1.28095[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.0623[/C][C]1.68772[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.8569[/C][C]-1.05686[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.1558[/C][C]-0.70579[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.86122[/C][C]3.78878[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]22.5891[/C][C]-5.23909[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]3.2245[/C][C]5.3755[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.3534[/C][C]1.04661[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.7518[/C][C]-1.65183[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]7.2437[/C][C]4.3563[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]14.3563[/C][C]3.39369[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]10.9878[/C][C]4.26217[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.0874[/C][C]3.56264[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.632[/C][C]3.71797[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.0916[/C][C]-0.441646[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.523[/C][C]1.07703[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]11.8436[/C][C]2.50641[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]10.9184[/C][C]3.83157[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]20.7169[/C][C]-2.46689[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.09348[/C][C]1.80652[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.6164[/C][C]4.38364[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]13.2954[/C][C]4.95455[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]16.1677[/C][C]0.682347[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.872[/C][C]0.728011[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]9.68827[/C][C]4.16173[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.612[/C][C]2.338[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.4219[/C][C]1.17808[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]16.4653[/C][C]-1.6153[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.97908[/C][C]4.77092[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.8895[/C][C]2.56054[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]12.8081[/C][C]3.09188[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]15.556[/C][C]1.54402[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]11.6076[/C][C]4.49243[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.5579[/C][C]-1.65792[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]5.22124[/C][C]5.72876[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]18.0326[/C][C]0.417448[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]14.2998[/C][C]0.800176[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.6357[/C][C]-1.6357[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.79619[/C][C]2.55381[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]10.8653[/C][C]5.08474[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.9568[/C][C]1.14318[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]13.6575[/C][C]0.942491[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.1096[/C][C]1.29036[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.1687[/C][C]5.23131[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.8649[/C][C]-0.264865[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]5.43667[/C][C]7.91333[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.4864[/C][C]2.61356[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]20.0029[/C][C]-4.65291[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]7.75676[/C][C]-0.156765[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.4381[/C][C]0.96192[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]9.22759[/C][C]4.67241[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]15.7743[/C][C]3.32573[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.1078[/C][C]0.142169[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.0327[/C][C]2.86735[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]12.006[/C][C]4.09401[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.3562[/C][C]-0.0061607[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.2514[/C][C]-1.1014[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.3247[/C][C]0.825253[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.2901[/C][C]-2.69009[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.64148[/C][C]2.70852[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]19.4888[/C][C]-4.08879[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.52716[/C][C]6.07284[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]17.3294[/C][C]0.870593[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]13.2105[/C][C]0.38945[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]12.5516[/C][C]2.29838[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]12.6018[/C][C]2.14822[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]11.7231[/C][C]2.37688[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.5142[/C][C]3.38584[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]11.4349[/C][C]4.81514[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]19.3181[/C][C]-0.0681204[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.6048[/C][C]0.995176[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.4152[/C][C]2.18485[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]15.3491[/C][C]0.30095[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.0574[/C][C]1.69261[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.452[/C][C]-2.85198[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]11.1428[/C][C]-1.29278[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]4.6756[/C][C]7.9744[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]15.5143[/C][C]3.68573[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]18.9319[/C][C]-2.33189[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.39246[/C][C]1.80754[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]15.0735[/C][C]0.176513[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]10.7439[/C][C]1.15613[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]9.35877[/C][C]3.84123[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.7131[/C][C]0.636885[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.18925[/C][C]3.21075[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]11.356[/C][C]4.49402[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.4556[/C][C]-1.30557[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.99875[/C][C]2.15125[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]9.55966[/C][C]6.09034[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.8122[/C][C]-4.06217[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.92543[/C][C]-1.27543[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.22038[/C][C]3.12962[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]9.95862[/C][C]5.64138[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.2092[/C][C]2.09081[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.7073[/C][C]3.49274[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.1025[/C][C]1.99751[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]10.3621[/C][C]5.23789[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.6777[/C][C]5.7223[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]12.745[/C][C]6.30504[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]13.2829[/C][C]5.26713[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.9921[/C][C]0.107912[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.4652[/C][C]-0.365221[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.9774[/C][C]-3.1274[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]18.847[/C][C]-9.34703[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]4.98745[/C][C]-0.487448[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]10.6495[/C][C]1.20045[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]15.3384[/C][C]-1.73838[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]11.5025[/C][C]0.197451[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.0605[/C][C]-0.660548[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]12.8188[/C][C]0.531174[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.72277[/C][C]1.67723[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]9.24018[/C][C]5.65982[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.4942[/C][C]-2.59417[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]8.74796[/C][C]2.45204[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]9.74427[/C][C]4.85573[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.1977[/C][C]1.40234[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.4286[/C][C]3.62144[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.1438[/C][C]-0.0437723[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]13.5191[/C][C]-0.169064[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.4679[/C][C]-1.6179[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.6461[/C][C]1.30392[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]10.8044[/C][C]3.9456[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]14.9029[/C][C]0.247127[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]9.91944[/C][C]3.28056[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.6273[/C][C]-4.77733[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.9465[/C][C]-5.09649[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.60805[/C][C]0.0919459[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.945[/C][C]-4.34505[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]10.6416[/C][C]-2.79162[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]11.5368[/C][C]-0.586795[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.5105[/C][C]-2.16054[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.23102[/C][C]1.71898[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.7058[/C][C]3.19415[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]17.8308[/C][C]-1.1808[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.8887[/C][C]0.511302[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]9.18064[/C][C]4.76936[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.6246[/C][C]3.07543[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]19.3759[/C][C]-2.52586[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.39872[/C][C]3.55128[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.5451[/C][C]-1.19509[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]8.77107[/C][C]3.42893[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.5656[/C][C]4.53444[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.6266[/C][C]2.12343[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]14.2947[/C][C]0.905268[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.6511[/C][C]3.94886[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]20.8189[/C][C]-4.1689[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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	12.9	13.0701	-0.170075
2	12.2	12.6715	-0.471491
3	12.8	13.6671	-0.867111
4	7.4	12.3938	-4.99379
5	6.7	12.3985	-5.69845
6	12.6	11.4691	1.1309
7	14.8	12.8271	1.97287
8	13.3	13.893	-0.593042
9	11.1	11.6752	-0.575155
10	8.2	14.4786	-6.2786
11	11.4	12.7482	-1.34823
12	6.4	12.8864	-6.48645
13	10.6	11.573	-0.972965
14	12	12.9497	-0.949745
15	6.3	12.6338	-6.33378
16	11.3	12.1923	-0.892261
17	11.9	12.5862	-0.686166
18	9.3	12.0912	-2.79115
19	9.6	12.6857	-3.08574
20	10	11.8546	-1.85464
21	6.4	13.3193	-6.91928
22	13.8	12.7844	1.01565
23	10.8	12.1231	-1.32311
24	13.8	12.4674	1.3326
25	11.7	13.7545	-2.05451
26	10.9	12.0847	-1.18466
27	16.1	12.1106	3.98939
28	13.4	13.569	-0.168965
29	9.9	13.7271	-3.8271
30	11.5	13.1411	-1.64111
31	8.3	11.5593	-3.25928
32	11.7	12.699	-0.998985
33	9	12.7712	-3.77117
34	9.7	12.8245	-3.12447
35	10.8	13.305	-2.50505
36	10.3	14.6241	-4.32413
37	10.4	12.6936	-2.29359
38	12.7	12.6587	0.041323
39	9.3	13.8565	-4.55649
40	11.8	12.7356	-0.935552
41	5.9	13.8914	-7.99137
42	11.4	14.0129	-2.61292
43	13	12.8911	0.108917
44	10.8	12.6445	-1.84451
45	12.3	12.6604	-0.360443
46	11.3	13.4536	-2.15359
47	11.8	12.3755	-0.57553
48	7.9	12.4037	-4.50371
49	12.7	11.0074	1.6926
50	12.3	13.8438	-1.54376
51	11.6	13.3447	-1.74467
52	6.7	12.6139	-5.91389
53	10.9	13.6425	-2.74249
54	12.1	12.2226	-0.122599
55	13.3	13.2545	0.0455274
56	10.1	13.5429	-3.44293
57	5.7	12.9408	-7.24075
58	14.3	11.5307	2.76932
59	8	12.6366	-4.63656
60	13.3	13.3599	-0.0599326
61	9.3	13.9633	-4.66333
62	12.5	11.7874	0.712587
63	7.6	13.1712	-5.57117
64	15.9	13.6772	2.22275
65	9.2	12.0852	-2.88523
66	9.1	13.9662	-4.86624
67	11.1	12.9304	-1.8304
68	13	13.9868	-0.986818
69	14.5	13.9542	0.545806
70	12.2	12.4813	-0.281313
71	12.3	12.5399	-0.239902
72	11.4	12.9982	-1.59821
73	8.8	13.0991	-4.29905
74	14.6	13.8852	0.714759
75	12.6	11.661	0.939019
76	NA	NA	1.25425
77	13	13.8157	-0.815688
78	12.6	13.0577	-0.457709
79	13.2	15.2011	-2.00113
80	9.9	13.8203	-3.92035
81	7.7	9.43722	-1.73722
82	10.5	8.88004	1.61996
83	13.4	15.6549	-2.2549
84	10.9	18.7947	-7.89473
85	4.3	7.21478	-2.91478
86	10.3	11.279	-0.979006
87	11.8	13.6954	-1.8954
88	11.2	13.1163	-1.91629
89	11.4	16.1286	-4.72862
90	8.6	6.98238	1.61762
91	13.2	13.9302	-0.730242
92	12.6	19.5054	-6.90542
93	5.6	7.71142	-2.11142
94	9.9	13.6595	-3.75946
95	8.8	13.3002	-4.5002
96	7.7	10.2374	-2.53736
97	9	14.0724	-5.07236
98	7.3	9.4829	-2.1829
99	11.4	10.7381	0.661888
100	13.6	18.7162	-5.1162
101	7.9	10.1311	-2.23114
102	10.7	13.7447	-3.04474
103	10.3	12.992	-2.692
104	8.3	10.8208	-2.52081
105	9.6	8.10489	1.49511
106	14.2	17.8284	-3.62842
107	8.5	7.22826	1.27174
108	13.5	21.6764	-8.17639
109	4.9	11.2097	-6.30968
110	6.4	9.73937	-3.33937
111	9.6	11.1534	-1.55339
112	11.6	13.5503	-1.95031
113	11.1	20.0803	-8.98031
114	4.35	4.79998	-0.449985
115	12.7	7.97522	4.72478
116	18.1	14.2006	3.89937
117	17.85	15.5425	2.30749
118	16.6	16.8308	-0.230815
119	12.6	9.5823	3.0177
120	17.1	12.2496	4.85041
121	19.1	16.1208	2.97915
122	16.1	15.2409	0.859147
123	13.35	8.87497	4.47503
124	18.4	16.9037	1.4963
125	14.7	17.3664	-2.66642
126	10.6	10.02	0.58003
127	12.6	8.07266	4.52734
128	16.2	15.1517	1.04827
129	13.6	7.87038	5.72962
130	18.9	18.0874	0.812575
131	14.1	13.668	0.431969
132	14.5	10.8144	3.6856
133	16.15	14.869	1.28095
134	14.75	13.0623	1.68772
135	14.8	15.8569	-1.05686
136	12.45	13.1558	-0.70579
137	12.65	8.86122	3.78878
138	17.35	22.5891	-5.23909
139	8.6	3.2245	5.3755
140	18.4	17.3534	1.04661
141	16.1	17.7518	-1.65183
142	11.6	7.2437	4.3563
143	17.75	14.3563	3.39369
144	15.25	10.9878	4.26217
145	17.65	14.0874	3.56264
146	16.35	12.632	3.71797
147	17.65	18.0916	-0.441646
148	13.6	12.523	1.07703
149	14.35	11.8436	2.50641
150	14.75	10.9184	3.83157
151	18.25	20.7169	-2.46689
152	9.9	8.09348	1.80652
153	16	11.6164	4.38364
154	18.25	13.2954	4.95455
155	16.85	16.1677	0.682347
156	14.6	13.872	0.728011
157	13.85	9.68827	4.16173
158	18.95	16.612	2.338
159	15.6	14.4219	1.17808
160	14.85	16.4653	-1.6153
161	11.75	6.97908	4.77092
162	18.45	15.8895	2.56054
163	15.9	12.8081	3.09188
164	17.1	15.556	1.54402
165	16.1	11.6076	4.49243
166	19.9	21.5579	-1.65792
167	10.95	5.22124	5.72876
168	18.45	18.0326	0.417448
169	15.1	14.2998	0.800176
170	15	16.6357	-1.6357
171	11.35	8.79619	2.55381
172	15.95	10.8653	5.08474
173	18.1	16.9568	1.14318
174	14.6	13.6575	0.942491
175	15.4	14.1096	1.29036
176	15.4	10.1687	5.23131
177	17.6	17.8649	-0.264865
178	13.35	5.43667	7.91333
179	19.1	16.4864	2.61356
180	15.35	20.0029	-4.65291
181	7.6	7.75676	-0.156765
182	13.4	12.4381	0.96192
183	13.9	9.22759	4.67241
184	19.1	15.7743	3.32573
185	15.25	15.1078	0.142169
186	12.9	10.0327	2.86735
187	16.1	12.006	4.09401
188	17.35	17.3562	-0.0061607
189	13.15	14.2514	-1.1014
190	12.15	11.3247	0.825253
191	12.6	15.2901	-2.69009
192	10.35	7.64148	2.70852
193	15.4	19.4888	-4.08879
194	9.6	3.52716	6.07284
195	18.2	17.3294	0.870593
196	13.6	13.2105	0.38945
197	14.85	12.5516	2.29838
198	14.75	12.6018	2.14822
199	14.1	11.7231	2.37688
200	14.9	11.5142	3.38584
201	16.25	11.4349	4.81514
202	19.25	19.3181	-0.0681204
203	13.6	12.6048	0.995176
204	13.6	11.4152	2.18485
205	15.65	15.3491	0.30095
206	12.75	11.0574	1.69261
207	14.6	17.452	-2.85198
208	9.85	11.1428	-1.29278
209	12.65	4.6756	7.9744
210	19.2	15.5143	3.68573
211	16.6	18.9319	-2.33189
212	11.2	9.39246	1.80754
213	15.25	15.0735	0.176513
214	11.9	10.7439	1.15613
215	13.2	9.35877	3.84123
216	16.35	15.7131	0.636885
217	12.4	9.18925	3.21075
218	15.85	11.356	4.49402
219	18.15	19.4556	-1.30557
220	11.15	8.99875	2.15125
221	15.65	9.55966	6.09034
222	17.75	21.8122	-4.06217
223	7.65	8.92543	-1.27543
224	12.35	9.22038	3.12962
225	15.6	9.95862	5.64138
226	19.3	17.2092	2.09081
227	15.2	11.7073	3.49274
228	17.1	15.1025	1.99751
229	15.6	10.3621	5.23789
230	18.4	12.6777	5.7223
231	19.05	12.745	6.30504
232	18.55	13.2829	5.26713
233	19.1	18.9921	0.107912
234	13.1	13.4652	-0.365221
235	12.85	15.9774	-3.1274
236	9.5	18.847	-9.34703
237	4.5	4.98745	-0.487448
238	11.85	10.6495	1.20045
239	13.6	15.3384	-1.73838
240	11.7	11.5025	0.197451
241	12.4	13.0605	-0.660548
242	13.35	12.8188	0.531174
243	11.4	9.72277	1.67723
244	14.9	9.24018	5.65982
245	19.9	22.4942	-2.59417
246	11.2	8.74796	2.45204
247	14.6	9.74427	4.85573
248	17.6	16.1977	1.40234
249	14.05	10.4286	3.62144
250	16.1	16.1438	-0.0437723
251	13.35	13.5191	-0.169064
252	11.85	13.4679	-1.6179
253	11.95	10.6461	1.30392
254	14.75	10.8044	3.9456
255	15.15	14.9029	0.247127
256	13.2	9.91944	3.28056
257	16.85	21.6273	-4.77733
258	7.85	12.9465	-5.09649
259	7.7	7.60805	0.0919459
260	12.6	16.945	-4.34505
261	7.85	10.6416	-2.79162
262	10.95	11.5368	-0.586795
263	12.35	14.5105	-2.16054
264	9.95	8.23102	1.71898
265	14.9	11.7058	3.19415
266	16.65	17.8308	-1.1808
267	13.4	12.8887	0.511302
268	13.95	9.18064	4.76936
269	15.7	12.6246	3.07543
270	16.85	19.3759	-2.52586
271	10.95	7.39872	3.55128
272	15.35	16.5451	-1.19509
273	12.2	8.77107	3.42893
274	15.1	10.5656	4.53444
275	17.75	15.6266	2.12343
276	15.2	14.2947	0.905268
277	14.6	10.6511	3.94886
278	16.65	20.8189	-4.1689
279	8.1	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.614646	0.770708	0.385354
18	0.49104	0.982079	0.50896
19	0.35809	0.716181	0.64191
20	0.258211	0.516423	0.741789
21	0.208582	0.417164	0.791418
22	0.156084	0.312168	0.843916
23	0.0984182	0.196836	0.901582
24	0.0928653	0.185731	0.907135
25	0.0603143	0.120629	0.939686
26	0.0435996	0.0871992	0.9564
27	0.0301115	0.0602231	0.969888
28	0.0195802	0.0391604	0.98042
29	0.012826	0.0256521	0.987174
30	0.00725508	0.0145102	0.992745
31	0.00552752	0.011055	0.994472
32	0.00304913	0.00609827	0.996951
33	0.00436266	0.00872532	0.995637
34	0.0505572	0.101114	0.949443
35	0.0387811	0.0775621	0.961219
36	0.0274938	0.0549876	0.972506
37	0.0202433	0.0404866	0.979757
38	0.0140589	0.0281179	0.985941
39	0.0115198	0.0230395	0.98848
40	0.00743383	0.0148677	0.992566
41	0.0144816	0.0289632	0.985518
42	0.0106426	0.0212852	0.989357
43	0.00953645	0.0190729	0.990464
44	0.0107753	0.0215505	0.989225
45	0.00718044	0.0143609	0.99282
46	0.0051953	0.0103906	0.994805
47	0.00384638	0.00769276	0.996154
48	0.00338582	0.00677164	0.996614
49	0.00277963	0.00555925	0.99722
50	0.00231454	0.00462908	0.997685
51	0.00155456	0.00310913	0.998445
52	0.00273852	0.00547705	0.997261
53	0.00186307	0.00372613	0.998137
54	0.00222596	0.00445192	0.997774
55	0.00319837	0.00639675	0.996802
56	0.00299899	0.00599798	0.997001
57	0.00836298	0.016726	0.991637
58	0.0072138	0.0144276	0.992786
59	0.00614651	0.012293	0.993853
60	0.00539402	0.010788	0.994606
61	0.00492074	0.00984148	0.995079
62	0.00362542	0.00725083	0.996375
63	0.00666239	0.0133248	0.993338
64	0.0109931	0.0219862	0.989007
65	0.00993653	0.0198731	0.990063
66	0.00940304	0.0188061	0.990597
67	0.00744835	0.0148967	0.992552
68	0.00650238	0.0130048	0.993498
69	0.00883106	0.0176621	0.991169
70	0.00682281	0.0136456	0.993177
71	0.00494328	0.00988655	0.995057
72	0.00374561	0.00749122	0.996254
73	0.00388042	0.00776084	0.99612
74	0.00480321	0.00960643	0.995197
75	0.00350773	0.00701546	0.996492
76	0.0026479	0.0052958	0.997352
77	0.00196201	0.00392402	0.998038
78	0.00162934	0.00325868	0.998371
79	0.00120794	0.00241588	0.998792
80	0.00129164	0.00258329	0.998708
81	0.000947267	0.00189453	0.999053
82	0.000916302	0.0018326	0.999084
83	0.000701003	0.00140201	0.999299
84	0.00246596	0.00493191	0.997534
85	0.0020262	0.00405241	0.997974
86	0.00152737	0.00305474	0.998473
87	0.00116026	0.00232052	0.99884
88	0.000962577	0.00192515	0.999037
89	0.00111915	0.00223829	0.998881
90	0.00132579	0.00265158	0.998674
91	0.00113862	0.00227723	0.998861
92	0.0026485	0.00529701	0.997351
93	0.0020483	0.00409659	0.997952
94	0.0019527	0.00390541	0.998047
95	0.00200704	0.00401407	0.997993
96	0.00176533	0.00353065	0.998235
97	0.00268119	0.00536237	0.997319
98	0.00211557	0.00423114	0.997884
99	0.00188183	0.00376365	0.998118
100	0.0021215	0.004243	0.997879
101	0.00178686	0.00357372	0.998213
102	0.00163687	0.00327374	0.998363
103	0.00202531	0.00405062	0.997975
104	0.00167459	0.00334918	0.998325
105	0.0015471	0.0030942	0.998453
106	0.00160709	0.00321417	0.998393
107	0.00234777	0.00469553	0.997652
108	0.00747739	0.0149548	0.992523
109	0.0139499	0.0278997	0.98605
110	0.0131849	0.0263698	0.986815
111	0.0119635	0.0239271	0.988036
112	0.0115072	0.0230144	0.988493
113	0.0500112	0.100022	0.949989
114	0.060319	0.120638	0.939681
115	0.107611	0.215222	0.892389
116	0.155013	0.310026	0.844987
117	0.192579	0.385159	0.807421
118	0.18163	0.363261	0.81837
119	0.228232	0.456465	0.771768
120	0.306888	0.613777	0.693112
121	0.329199	0.658399	0.670801
122	0.327866	0.655732	0.672134
123	0.450647	0.901294	0.549353
124	0.446415	0.89283	0.553585
125	0.450622	0.901245	0.549378
126	0.429468	0.858936	0.570532
127	0.466091	0.932181	0.533909
128	0.446813	0.893625	0.553187
129	0.537361	0.925278	0.462639
130	0.520663	0.958674	0.479337
131	0.49821	0.996419	0.50179
132	0.503081	0.993837	0.496919
133	0.482357	0.964714	0.517643
134	0.510525	0.978949	0.489475
135	0.487162	0.974324	0.512838
136	0.475006	0.950013	0.524994
137	0.504715	0.990571	0.495285
138	0.581113	0.837773	0.418887
139	0.65633	0.687341	0.34367
140	0.632927	0.734147	0.367073
141	0.609066	0.781868	0.390934
142	0.630325	0.739349	0.369675
143	0.649536	0.700927	0.350464
144	0.667443	0.665115	0.332557
145	0.671692	0.656615	0.328308
146	0.685459	0.629081	0.314541
147	0.660761	0.678477	0.339239
148	0.63472	0.73056	0.36528
149	0.633589	0.732821	0.366411
150	0.658093	0.683815	0.341907
151	0.653023	0.693955	0.346977
152	0.628949	0.742102	0.371051
153	0.66514	0.669719	0.33486
154	0.6964	0.607199	0.3036
155	0.668667	0.662667	0.331333
156	0.636233	0.727535	0.363767
157	0.659095	0.68181	0.340905
158	0.644192	0.711616	0.355808
159	0.620169	0.759661	0.379831
160	0.616017	0.767966	0.383983
161	0.65886	0.68228	0.34114
162	0.652147	0.695706	0.347853
163	0.649027	0.701946	0.350973
164	0.619002	0.761996	0.380998
165	0.651406	0.697189	0.348594
166	0.624387	0.751226	0.375613
167	0.683764	0.632472	0.316236
168	0.650228	0.699543	0.349772
169	0.618211	0.763577	0.381789
170	0.606892	0.786217	0.393108
171	0.590398	0.819205	0.409602
172	0.634041	0.731918	0.365959
173	0.602626	0.794748	0.397374
174	0.574214	0.851571	0.425786
175	0.543462	0.913076	0.456538
176	0.577419	0.845162	0.422581
177	0.54098	0.91804	0.45902
178	0.689295	0.62141	0.310705
179	0.675938	0.648125	0.324062
180	0.738369	0.523262	0.261631
181	0.707159	0.585682	0.292841
182	0.674489	0.651021	0.325511
183	0.695296	0.609407	0.304704
184	0.690689	0.618622	0.309311
185	0.656254	0.687491	0.343746
186	0.639993	0.720014	0.360007
187	0.654224	0.691552	0.345776
188	0.617625	0.764749	0.382375
189	0.588488	0.823024	0.411512
190	0.551585	0.89683	0.448415
191	0.55095	0.8981	0.44905
192	0.547353	0.905294	0.452647
193	0.59864	0.80272	0.40136
194	0.657161	0.685678	0.342839
195	0.63233	0.73534	0.36767
196	0.593937	0.812127	0.406063
197	0.573719	0.852563	0.426281
198	0.549559	0.900883	0.450441
199	0.518881	0.962238	0.481119
200	0.508759	0.982481	0.491241
201	0.590028	0.819945	0.409972
202	0.549461	0.901077	0.450539
203	0.510572	0.978855	0.489428
204	0.479324	0.958648	0.520676
205	0.455729	0.911459	0.544271
206	0.432695	0.865389	0.567305
207	0.451534	0.903069	0.548466
208	0.422767	0.845534	0.577233
209	0.491143	0.982286	0.508857
210	0.469885	0.939771	0.530115
211	0.448542	0.897085	0.551458
212	0.415331	0.830662	0.584669
213	0.377329	0.754658	0.622671
214	0.337386	0.674772	0.662614
215	0.32668	0.65336	0.67332
216	0.290394	0.580789	0.709606
217	0.27106	0.542121	0.72894
218	0.281951	0.563903	0.718049
219	0.253537	0.507074	0.746463
220	0.236916	0.473832	0.763084
221	0.280239	0.560478	0.719761
222	0.419231	0.838461	0.580769
223	0.376106	0.752211	0.623894
224	0.347436	0.694873	0.652564
225	0.344331	0.688662	0.655669
226	0.309106	0.618212	0.690894
227	0.279748	0.559496	0.720252
228	0.241965	0.48393	0.758035
229	0.288509	0.577018	0.711491
230	0.341434	0.682869	0.658566
231	0.49835	0.9967	0.50165
232	0.556937	0.886127	0.443063
233	0.50602	0.98796	0.49398
234	0.458357	0.916715	0.541643
235	0.411947	0.823894	0.588053
236	0.820977	0.358045	0.179023
237	0.785725	0.42855	0.214275
238	0.748929	0.502142	0.251071
239	0.69999	0.60002	0.30001
240	0.648387	0.703226	0.351613
241	0.589225	0.82155	0.410775
242	0.528396	0.943208	0.471604
243	0.468031	0.936062	0.531969
244	0.626611	0.746779	0.373389
245	0.591347	0.817306	0.408653
246	0.525203	0.949594	0.474797
247	0.528846	0.942308	0.471154
248	0.457564	0.915128	0.542436
249	0.445845	0.891691	0.554155
250	0.372968	0.745937	0.627032
251	0.301818	0.603637	0.698182
252	0.262904	0.525809	0.737096
253	0.202314	0.404629	0.797686
254	0.288584	0.577168	0.711416
255	0.394361	0.788721	0.605639
256	0.328229	0.656458	0.671771
257	0.614276	0.771448	0.385724
258	0.86446	0.27108	0.13554
259	0.816276	0.367447	0.183724
260	0.892464	0.215072	0.107536
261	0.84998	0.300041	0.15002
262	0.695517	0.608966	0.304483

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.614646 & 0.770708 & 0.385354 \tabularnewline
18 & 0.49104 & 0.982079 & 0.50896 \tabularnewline
19 & 0.35809 & 0.716181 & 0.64191 \tabularnewline
20 & 0.258211 & 0.516423 & 0.741789 \tabularnewline
21 & 0.208582 & 0.417164 & 0.791418 \tabularnewline
22 & 0.156084 & 0.312168 & 0.843916 \tabularnewline
23 & 0.0984182 & 0.196836 & 0.901582 \tabularnewline
24 & 0.0928653 & 0.185731 & 0.907135 \tabularnewline
25 & 0.0603143 & 0.120629 & 0.939686 \tabularnewline
26 & 0.0435996 & 0.0871992 & 0.9564 \tabularnewline
27 & 0.0301115 & 0.0602231 & 0.969888 \tabularnewline
28 & 0.0195802 & 0.0391604 & 0.98042 \tabularnewline
29 & 0.012826 & 0.0256521 & 0.987174 \tabularnewline
30 & 0.00725508 & 0.0145102 & 0.992745 \tabularnewline
31 & 0.00552752 & 0.011055 & 0.994472 \tabularnewline
32 & 0.00304913 & 0.00609827 & 0.996951 \tabularnewline
33 & 0.00436266 & 0.00872532 & 0.995637 \tabularnewline
34 & 0.0505572 & 0.101114 & 0.949443 \tabularnewline
35 & 0.0387811 & 0.0775621 & 0.961219 \tabularnewline
36 & 0.0274938 & 0.0549876 & 0.972506 \tabularnewline
37 & 0.0202433 & 0.0404866 & 0.979757 \tabularnewline
38 & 0.0140589 & 0.0281179 & 0.985941 \tabularnewline
39 & 0.0115198 & 0.0230395 & 0.98848 \tabularnewline
40 & 0.00743383 & 0.0148677 & 0.992566 \tabularnewline
41 & 0.0144816 & 0.0289632 & 0.985518 \tabularnewline
42 & 0.0106426 & 0.0212852 & 0.989357 \tabularnewline
43 & 0.00953645 & 0.0190729 & 0.990464 \tabularnewline
44 & 0.0107753 & 0.0215505 & 0.989225 \tabularnewline
45 & 0.00718044 & 0.0143609 & 0.99282 \tabularnewline
46 & 0.0051953 & 0.0103906 & 0.994805 \tabularnewline
47 & 0.00384638 & 0.00769276 & 0.996154 \tabularnewline
48 & 0.00338582 & 0.00677164 & 0.996614 \tabularnewline
49 & 0.00277963 & 0.00555925 & 0.99722 \tabularnewline
50 & 0.00231454 & 0.00462908 & 0.997685 \tabularnewline
51 & 0.00155456 & 0.00310913 & 0.998445 \tabularnewline
52 & 0.00273852 & 0.00547705 & 0.997261 \tabularnewline
53 & 0.00186307 & 0.00372613 & 0.998137 \tabularnewline
54 & 0.00222596 & 0.00445192 & 0.997774 \tabularnewline
55 & 0.00319837 & 0.00639675 & 0.996802 \tabularnewline
56 & 0.00299899 & 0.00599798 & 0.997001 \tabularnewline
57 & 0.00836298 & 0.016726 & 0.991637 \tabularnewline
58 & 0.0072138 & 0.0144276 & 0.992786 \tabularnewline
59 & 0.00614651 & 0.012293 & 0.993853 \tabularnewline
60 & 0.00539402 & 0.010788 & 0.994606 \tabularnewline
61 & 0.00492074 & 0.00984148 & 0.995079 \tabularnewline
62 & 0.00362542 & 0.00725083 & 0.996375 \tabularnewline
63 & 0.00666239 & 0.0133248 & 0.993338 \tabularnewline
64 & 0.0109931 & 0.0219862 & 0.989007 \tabularnewline
65 & 0.00993653 & 0.0198731 & 0.990063 \tabularnewline
66 & 0.00940304 & 0.0188061 & 0.990597 \tabularnewline
67 & 0.00744835 & 0.0148967 & 0.992552 \tabularnewline
68 & 0.00650238 & 0.0130048 & 0.993498 \tabularnewline
69 & 0.00883106 & 0.0176621 & 0.991169 \tabularnewline
70 & 0.00682281 & 0.0136456 & 0.993177 \tabularnewline
71 & 0.00494328 & 0.00988655 & 0.995057 \tabularnewline
72 & 0.00374561 & 0.00749122 & 0.996254 \tabularnewline
73 & 0.00388042 & 0.00776084 & 0.99612 \tabularnewline
74 & 0.00480321 & 0.00960643 & 0.995197 \tabularnewline
75 & 0.00350773 & 0.00701546 & 0.996492 \tabularnewline
76 & 0.0026479 & 0.0052958 & 0.997352 \tabularnewline
77 & 0.00196201 & 0.00392402 & 0.998038 \tabularnewline
78 & 0.00162934 & 0.00325868 & 0.998371 \tabularnewline
79 & 0.00120794 & 0.00241588 & 0.998792 \tabularnewline
80 & 0.00129164 & 0.00258329 & 0.998708 \tabularnewline
81 & 0.000947267 & 0.00189453 & 0.999053 \tabularnewline
82 & 0.000916302 & 0.0018326 & 0.999084 \tabularnewline
83 & 0.000701003 & 0.00140201 & 0.999299 \tabularnewline
84 & 0.00246596 & 0.00493191 & 0.997534 \tabularnewline
85 & 0.0020262 & 0.00405241 & 0.997974 \tabularnewline
86 & 0.00152737 & 0.00305474 & 0.998473 \tabularnewline
87 & 0.00116026 & 0.00232052 & 0.99884 \tabularnewline
88 & 0.000962577 & 0.00192515 & 0.999037 \tabularnewline
89 & 0.00111915 & 0.00223829 & 0.998881 \tabularnewline
90 & 0.00132579 & 0.00265158 & 0.998674 \tabularnewline
91 & 0.00113862 & 0.00227723 & 0.998861 \tabularnewline
92 & 0.0026485 & 0.00529701 & 0.997351 \tabularnewline
93 & 0.0020483 & 0.00409659 & 0.997952 \tabularnewline
94 & 0.0019527 & 0.00390541 & 0.998047 \tabularnewline
95 & 0.00200704 & 0.00401407 & 0.997993 \tabularnewline
96 & 0.00176533 & 0.00353065 & 0.998235 \tabularnewline
97 & 0.00268119 & 0.00536237 & 0.997319 \tabularnewline
98 & 0.00211557 & 0.00423114 & 0.997884 \tabularnewline
99 & 0.00188183 & 0.00376365 & 0.998118 \tabularnewline
100 & 0.0021215 & 0.004243 & 0.997879 \tabularnewline
101 & 0.00178686 & 0.00357372 & 0.998213 \tabularnewline
102 & 0.00163687 & 0.00327374 & 0.998363 \tabularnewline
103 & 0.00202531 & 0.00405062 & 0.997975 \tabularnewline
104 & 0.00167459 & 0.00334918 & 0.998325 \tabularnewline
105 & 0.0015471 & 0.0030942 & 0.998453 \tabularnewline
106 & 0.00160709 & 0.00321417 & 0.998393 \tabularnewline
107 & 0.00234777 & 0.00469553 & 0.997652 \tabularnewline
108 & 0.00747739 & 0.0149548 & 0.992523 \tabularnewline
109 & 0.0139499 & 0.0278997 & 0.98605 \tabularnewline
110 & 0.0131849 & 0.0263698 & 0.986815 \tabularnewline
111 & 0.0119635 & 0.0239271 & 0.988036 \tabularnewline
112 & 0.0115072 & 0.0230144 & 0.988493 \tabularnewline
113 & 0.0500112 & 0.100022 & 0.949989 \tabularnewline
114 & 0.060319 & 0.120638 & 0.939681 \tabularnewline
115 & 0.107611 & 0.215222 & 0.892389 \tabularnewline
116 & 0.155013 & 0.310026 & 0.844987 \tabularnewline
117 & 0.192579 & 0.385159 & 0.807421 \tabularnewline
118 & 0.18163 & 0.363261 & 0.81837 \tabularnewline
119 & 0.228232 & 0.456465 & 0.771768 \tabularnewline
120 & 0.306888 & 0.613777 & 0.693112 \tabularnewline
121 & 0.329199 & 0.658399 & 0.670801 \tabularnewline
122 & 0.327866 & 0.655732 & 0.672134 \tabularnewline
123 & 0.450647 & 0.901294 & 0.549353 \tabularnewline
124 & 0.446415 & 0.89283 & 0.553585 \tabularnewline
125 & 0.450622 & 0.901245 & 0.549378 \tabularnewline
126 & 0.429468 & 0.858936 & 0.570532 \tabularnewline
127 & 0.466091 & 0.932181 & 0.533909 \tabularnewline
128 & 0.446813 & 0.893625 & 0.553187 \tabularnewline
129 & 0.537361 & 0.925278 & 0.462639 \tabularnewline
130 & 0.520663 & 0.958674 & 0.479337 \tabularnewline
131 & 0.49821 & 0.996419 & 0.50179 \tabularnewline
132 & 0.503081 & 0.993837 & 0.496919 \tabularnewline
133 & 0.482357 & 0.964714 & 0.517643 \tabularnewline
134 & 0.510525 & 0.978949 & 0.489475 \tabularnewline
135 & 0.487162 & 0.974324 & 0.512838 \tabularnewline
136 & 0.475006 & 0.950013 & 0.524994 \tabularnewline
137 & 0.504715 & 0.990571 & 0.495285 \tabularnewline
138 & 0.581113 & 0.837773 & 0.418887 \tabularnewline
139 & 0.65633 & 0.687341 & 0.34367 \tabularnewline
140 & 0.632927 & 0.734147 & 0.367073 \tabularnewline
141 & 0.609066 & 0.781868 & 0.390934 \tabularnewline
142 & 0.630325 & 0.739349 & 0.369675 \tabularnewline
143 & 0.649536 & 0.700927 & 0.350464 \tabularnewline
144 & 0.667443 & 0.665115 & 0.332557 \tabularnewline
145 & 0.671692 & 0.656615 & 0.328308 \tabularnewline
146 & 0.685459 & 0.629081 & 0.314541 \tabularnewline
147 & 0.660761 & 0.678477 & 0.339239 \tabularnewline
148 & 0.63472 & 0.73056 & 0.36528 \tabularnewline
149 & 0.633589 & 0.732821 & 0.366411 \tabularnewline
150 & 0.658093 & 0.683815 & 0.341907 \tabularnewline
151 & 0.653023 & 0.693955 & 0.346977 \tabularnewline
152 & 0.628949 & 0.742102 & 0.371051 \tabularnewline
153 & 0.66514 & 0.669719 & 0.33486 \tabularnewline
154 & 0.6964 & 0.607199 & 0.3036 \tabularnewline
155 & 0.668667 & 0.662667 & 0.331333 \tabularnewline
156 & 0.636233 & 0.727535 & 0.363767 \tabularnewline
157 & 0.659095 & 0.68181 & 0.340905 \tabularnewline
158 & 0.644192 & 0.711616 & 0.355808 \tabularnewline
159 & 0.620169 & 0.759661 & 0.379831 \tabularnewline
160 & 0.616017 & 0.767966 & 0.383983 \tabularnewline
161 & 0.65886 & 0.68228 & 0.34114 \tabularnewline
162 & 0.652147 & 0.695706 & 0.347853 \tabularnewline
163 & 0.649027 & 0.701946 & 0.350973 \tabularnewline
164 & 0.619002 & 0.761996 & 0.380998 \tabularnewline
165 & 0.651406 & 0.697189 & 0.348594 \tabularnewline
166 & 0.624387 & 0.751226 & 0.375613 \tabularnewline
167 & 0.683764 & 0.632472 & 0.316236 \tabularnewline
168 & 0.650228 & 0.699543 & 0.349772 \tabularnewline
169 & 0.618211 & 0.763577 & 0.381789 \tabularnewline
170 & 0.606892 & 0.786217 & 0.393108 \tabularnewline
171 & 0.590398 & 0.819205 & 0.409602 \tabularnewline
172 & 0.634041 & 0.731918 & 0.365959 \tabularnewline
173 & 0.602626 & 0.794748 & 0.397374 \tabularnewline
174 & 0.574214 & 0.851571 & 0.425786 \tabularnewline
175 & 0.543462 & 0.913076 & 0.456538 \tabularnewline
176 & 0.577419 & 0.845162 & 0.422581 \tabularnewline
177 & 0.54098 & 0.91804 & 0.45902 \tabularnewline
178 & 0.689295 & 0.62141 & 0.310705 \tabularnewline
179 & 0.675938 & 0.648125 & 0.324062 \tabularnewline
180 & 0.738369 & 0.523262 & 0.261631 \tabularnewline
181 & 0.707159 & 0.585682 & 0.292841 \tabularnewline
182 & 0.674489 & 0.651021 & 0.325511 \tabularnewline
183 & 0.695296 & 0.609407 & 0.304704 \tabularnewline
184 & 0.690689 & 0.618622 & 0.309311 \tabularnewline
185 & 0.656254 & 0.687491 & 0.343746 \tabularnewline
186 & 0.639993 & 0.720014 & 0.360007 \tabularnewline
187 & 0.654224 & 0.691552 & 0.345776 \tabularnewline
188 & 0.617625 & 0.764749 & 0.382375 \tabularnewline
189 & 0.588488 & 0.823024 & 0.411512 \tabularnewline
190 & 0.551585 & 0.89683 & 0.448415 \tabularnewline
191 & 0.55095 & 0.8981 & 0.44905 \tabularnewline
192 & 0.547353 & 0.905294 & 0.452647 \tabularnewline
193 & 0.59864 & 0.80272 & 0.40136 \tabularnewline
194 & 0.657161 & 0.685678 & 0.342839 \tabularnewline
195 & 0.63233 & 0.73534 & 0.36767 \tabularnewline
196 & 0.593937 & 0.812127 & 0.406063 \tabularnewline
197 & 0.573719 & 0.852563 & 0.426281 \tabularnewline
198 & 0.549559 & 0.900883 & 0.450441 \tabularnewline
199 & 0.518881 & 0.962238 & 0.481119 \tabularnewline
200 & 0.508759 & 0.982481 & 0.491241 \tabularnewline
201 & 0.590028 & 0.819945 & 0.409972 \tabularnewline
202 & 0.549461 & 0.901077 & 0.450539 \tabularnewline
203 & 0.510572 & 0.978855 & 0.489428 \tabularnewline
204 & 0.479324 & 0.958648 & 0.520676 \tabularnewline
205 & 0.455729 & 0.911459 & 0.544271 \tabularnewline
206 & 0.432695 & 0.865389 & 0.567305 \tabularnewline
207 & 0.451534 & 0.903069 & 0.548466 \tabularnewline
208 & 0.422767 & 0.845534 & 0.577233 \tabularnewline
209 & 0.491143 & 0.982286 & 0.508857 \tabularnewline
210 & 0.469885 & 0.939771 & 0.530115 \tabularnewline
211 & 0.448542 & 0.897085 & 0.551458 \tabularnewline
212 & 0.415331 & 0.830662 & 0.584669 \tabularnewline
213 & 0.377329 & 0.754658 & 0.622671 \tabularnewline
214 & 0.337386 & 0.674772 & 0.662614 \tabularnewline
215 & 0.32668 & 0.65336 & 0.67332 \tabularnewline
216 & 0.290394 & 0.580789 & 0.709606 \tabularnewline
217 & 0.27106 & 0.542121 & 0.72894 \tabularnewline
218 & 0.281951 & 0.563903 & 0.718049 \tabularnewline
219 & 0.253537 & 0.507074 & 0.746463 \tabularnewline
220 & 0.236916 & 0.473832 & 0.763084 \tabularnewline
221 & 0.280239 & 0.560478 & 0.719761 \tabularnewline
222 & 0.419231 & 0.838461 & 0.580769 \tabularnewline
223 & 0.376106 & 0.752211 & 0.623894 \tabularnewline
224 & 0.347436 & 0.694873 & 0.652564 \tabularnewline
225 & 0.344331 & 0.688662 & 0.655669 \tabularnewline
226 & 0.309106 & 0.618212 & 0.690894 \tabularnewline
227 & 0.279748 & 0.559496 & 0.720252 \tabularnewline
228 & 0.241965 & 0.48393 & 0.758035 \tabularnewline
229 & 0.288509 & 0.577018 & 0.711491 \tabularnewline
230 & 0.341434 & 0.682869 & 0.658566 \tabularnewline
231 & 0.49835 & 0.9967 & 0.50165 \tabularnewline
232 & 0.556937 & 0.886127 & 0.443063 \tabularnewline
233 & 0.50602 & 0.98796 & 0.49398 \tabularnewline
234 & 0.458357 & 0.916715 & 0.541643 \tabularnewline
235 & 0.411947 & 0.823894 & 0.588053 \tabularnewline
236 & 0.820977 & 0.358045 & 0.179023 \tabularnewline
237 & 0.785725 & 0.42855 & 0.214275 \tabularnewline
238 & 0.748929 & 0.502142 & 0.251071 \tabularnewline
239 & 0.69999 & 0.60002 & 0.30001 \tabularnewline
240 & 0.648387 & 0.703226 & 0.351613 \tabularnewline
241 & 0.589225 & 0.82155 & 0.410775 \tabularnewline
242 & 0.528396 & 0.943208 & 0.471604 \tabularnewline
243 & 0.468031 & 0.936062 & 0.531969 \tabularnewline
244 & 0.626611 & 0.746779 & 0.373389 \tabularnewline
245 & 0.591347 & 0.817306 & 0.408653 \tabularnewline
246 & 0.525203 & 0.949594 & 0.474797 \tabularnewline
247 & 0.528846 & 0.942308 & 0.471154 \tabularnewline
248 & 0.457564 & 0.915128 & 0.542436 \tabularnewline
249 & 0.445845 & 0.891691 & 0.554155 \tabularnewline
250 & 0.372968 & 0.745937 & 0.627032 \tabularnewline
251 & 0.301818 & 0.603637 & 0.698182 \tabularnewline
252 & 0.262904 & 0.525809 & 0.737096 \tabularnewline
253 & 0.202314 & 0.404629 & 0.797686 \tabularnewline
254 & 0.288584 & 0.577168 & 0.711416 \tabularnewline
255 & 0.394361 & 0.788721 & 0.605639 \tabularnewline
256 & 0.328229 & 0.656458 & 0.671771 \tabularnewline
257 & 0.614276 & 0.771448 & 0.385724 \tabularnewline
258 & 0.86446 & 0.27108 & 0.13554 \tabularnewline
259 & 0.816276 & 0.367447 & 0.183724 \tabularnewline
260 & 0.892464 & 0.215072 & 0.107536 \tabularnewline
261 & 0.84998 & 0.300041 & 0.15002 \tabularnewline
262 & 0.695517 & 0.608966 & 0.304483 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&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]17[/C][C]0.614646[/C][C]0.770708[/C][C]0.385354[/C][/ROW]
[ROW][C]18[/C][C]0.49104[/C][C]0.982079[/C][C]0.50896[/C][/ROW]
[ROW][C]19[/C][C]0.35809[/C][C]0.716181[/C][C]0.64191[/C][/ROW]
[ROW][C]20[/C][C]0.258211[/C][C]0.516423[/C][C]0.741789[/C][/ROW]
[ROW][C]21[/C][C]0.208582[/C][C]0.417164[/C][C]0.791418[/C][/ROW]
[ROW][C]22[/C][C]0.156084[/C][C]0.312168[/C][C]0.843916[/C][/ROW]
[ROW][C]23[/C][C]0.0984182[/C][C]0.196836[/C][C]0.901582[/C][/ROW]
[ROW][C]24[/C][C]0.0928653[/C][C]0.185731[/C][C]0.907135[/C][/ROW]
[ROW][C]25[/C][C]0.0603143[/C][C]0.120629[/C][C]0.939686[/C][/ROW]
[ROW][C]26[/C][C]0.0435996[/C][C]0.0871992[/C][C]0.9564[/C][/ROW]
[ROW][C]27[/C][C]0.0301115[/C][C]0.0602231[/C][C]0.969888[/C][/ROW]
[ROW][C]28[/C][C]0.0195802[/C][C]0.0391604[/C][C]0.98042[/C][/ROW]
[ROW][C]29[/C][C]0.012826[/C][C]0.0256521[/C][C]0.987174[/C][/ROW]
[ROW][C]30[/C][C]0.00725508[/C][C]0.0145102[/C][C]0.992745[/C][/ROW]
[ROW][C]31[/C][C]0.00552752[/C][C]0.011055[/C][C]0.994472[/C][/ROW]
[ROW][C]32[/C][C]0.00304913[/C][C]0.00609827[/C][C]0.996951[/C][/ROW]
[ROW][C]33[/C][C]0.00436266[/C][C]0.00872532[/C][C]0.995637[/C][/ROW]
[ROW][C]34[/C][C]0.0505572[/C][C]0.101114[/C][C]0.949443[/C][/ROW]
[ROW][C]35[/C][C]0.0387811[/C][C]0.0775621[/C][C]0.961219[/C][/ROW]
[ROW][C]36[/C][C]0.0274938[/C][C]0.0549876[/C][C]0.972506[/C][/ROW]
[ROW][C]37[/C][C]0.0202433[/C][C]0.0404866[/C][C]0.979757[/C][/ROW]
[ROW][C]38[/C][C]0.0140589[/C][C]0.0281179[/C][C]0.985941[/C][/ROW]
[ROW][C]39[/C][C]0.0115198[/C][C]0.0230395[/C][C]0.98848[/C][/ROW]
[ROW][C]40[/C][C]0.00743383[/C][C]0.0148677[/C][C]0.992566[/C][/ROW]
[ROW][C]41[/C][C]0.0144816[/C][C]0.0289632[/C][C]0.985518[/C][/ROW]
[ROW][C]42[/C][C]0.0106426[/C][C]0.0212852[/C][C]0.989357[/C][/ROW]
[ROW][C]43[/C][C]0.00953645[/C][C]0.0190729[/C][C]0.990464[/C][/ROW]
[ROW][C]44[/C][C]0.0107753[/C][C]0.0215505[/C][C]0.989225[/C][/ROW]
[ROW][C]45[/C][C]0.00718044[/C][C]0.0143609[/C][C]0.99282[/C][/ROW]
[ROW][C]46[/C][C]0.0051953[/C][C]0.0103906[/C][C]0.994805[/C][/ROW]
[ROW][C]47[/C][C]0.00384638[/C][C]0.00769276[/C][C]0.996154[/C][/ROW]
[ROW][C]48[/C][C]0.00338582[/C][C]0.00677164[/C][C]0.996614[/C][/ROW]
[ROW][C]49[/C][C]0.00277963[/C][C]0.00555925[/C][C]0.99722[/C][/ROW]
[ROW][C]50[/C][C]0.00231454[/C][C]0.00462908[/C][C]0.997685[/C][/ROW]
[ROW][C]51[/C][C]0.00155456[/C][C]0.00310913[/C][C]0.998445[/C][/ROW]
[ROW][C]52[/C][C]0.00273852[/C][C]0.00547705[/C][C]0.997261[/C][/ROW]
[ROW][C]53[/C][C]0.00186307[/C][C]0.00372613[/C][C]0.998137[/C][/ROW]
[ROW][C]54[/C][C]0.00222596[/C][C]0.00445192[/C][C]0.997774[/C][/ROW]
[ROW][C]55[/C][C]0.00319837[/C][C]0.00639675[/C][C]0.996802[/C][/ROW]
[ROW][C]56[/C][C]0.00299899[/C][C]0.00599798[/C][C]0.997001[/C][/ROW]
[ROW][C]57[/C][C]0.00836298[/C][C]0.016726[/C][C]0.991637[/C][/ROW]
[ROW][C]58[/C][C]0.0072138[/C][C]0.0144276[/C][C]0.992786[/C][/ROW]
[ROW][C]59[/C][C]0.00614651[/C][C]0.012293[/C][C]0.993853[/C][/ROW]
[ROW][C]60[/C][C]0.00539402[/C][C]0.010788[/C][C]0.994606[/C][/ROW]
[ROW][C]61[/C][C]0.00492074[/C][C]0.00984148[/C][C]0.995079[/C][/ROW]
[ROW][C]62[/C][C]0.00362542[/C][C]0.00725083[/C][C]0.996375[/C][/ROW]
[ROW][C]63[/C][C]0.00666239[/C][C]0.0133248[/C][C]0.993338[/C][/ROW]
[ROW][C]64[/C][C]0.0109931[/C][C]0.0219862[/C][C]0.989007[/C][/ROW]
[ROW][C]65[/C][C]0.00993653[/C][C]0.0198731[/C][C]0.990063[/C][/ROW]
[ROW][C]66[/C][C]0.00940304[/C][C]0.0188061[/C][C]0.990597[/C][/ROW]
[ROW][C]67[/C][C]0.00744835[/C][C]0.0148967[/C][C]0.992552[/C][/ROW]
[ROW][C]68[/C][C]0.00650238[/C][C]0.0130048[/C][C]0.993498[/C][/ROW]
[ROW][C]69[/C][C]0.00883106[/C][C]0.0176621[/C][C]0.991169[/C][/ROW]
[ROW][C]70[/C][C]0.00682281[/C][C]0.0136456[/C][C]0.993177[/C][/ROW]
[ROW][C]71[/C][C]0.00494328[/C][C]0.00988655[/C][C]0.995057[/C][/ROW]
[ROW][C]72[/C][C]0.00374561[/C][C]0.00749122[/C][C]0.996254[/C][/ROW]
[ROW][C]73[/C][C]0.00388042[/C][C]0.00776084[/C][C]0.99612[/C][/ROW]
[ROW][C]74[/C][C]0.00480321[/C][C]0.00960643[/C][C]0.995197[/C][/ROW]
[ROW][C]75[/C][C]0.00350773[/C][C]0.00701546[/C][C]0.996492[/C][/ROW]
[ROW][C]76[/C][C]0.0026479[/C][C]0.0052958[/C][C]0.997352[/C][/ROW]
[ROW][C]77[/C][C]0.00196201[/C][C]0.00392402[/C][C]0.998038[/C][/ROW]
[ROW][C]78[/C][C]0.00162934[/C][C]0.00325868[/C][C]0.998371[/C][/ROW]
[ROW][C]79[/C][C]0.00120794[/C][C]0.00241588[/C][C]0.998792[/C][/ROW]
[ROW][C]80[/C][C]0.00129164[/C][C]0.00258329[/C][C]0.998708[/C][/ROW]
[ROW][C]81[/C][C]0.000947267[/C][C]0.00189453[/C][C]0.999053[/C][/ROW]
[ROW][C]82[/C][C]0.000916302[/C][C]0.0018326[/C][C]0.999084[/C][/ROW]
[ROW][C]83[/C][C]0.000701003[/C][C]0.00140201[/C][C]0.999299[/C][/ROW]
[ROW][C]84[/C][C]0.00246596[/C][C]0.00493191[/C][C]0.997534[/C][/ROW]
[ROW][C]85[/C][C]0.0020262[/C][C]0.00405241[/C][C]0.997974[/C][/ROW]
[ROW][C]86[/C][C]0.00152737[/C][C]0.00305474[/C][C]0.998473[/C][/ROW]
[ROW][C]87[/C][C]0.00116026[/C][C]0.00232052[/C][C]0.99884[/C][/ROW]
[ROW][C]88[/C][C]0.000962577[/C][C]0.00192515[/C][C]0.999037[/C][/ROW]
[ROW][C]89[/C][C]0.00111915[/C][C]0.00223829[/C][C]0.998881[/C][/ROW]
[ROW][C]90[/C][C]0.00132579[/C][C]0.00265158[/C][C]0.998674[/C][/ROW]
[ROW][C]91[/C][C]0.00113862[/C][C]0.00227723[/C][C]0.998861[/C][/ROW]
[ROW][C]92[/C][C]0.0026485[/C][C]0.00529701[/C][C]0.997351[/C][/ROW]
[ROW][C]93[/C][C]0.0020483[/C][C]0.00409659[/C][C]0.997952[/C][/ROW]
[ROW][C]94[/C][C]0.0019527[/C][C]0.00390541[/C][C]0.998047[/C][/ROW]
[ROW][C]95[/C][C]0.00200704[/C][C]0.00401407[/C][C]0.997993[/C][/ROW]
[ROW][C]96[/C][C]0.00176533[/C][C]0.00353065[/C][C]0.998235[/C][/ROW]
[ROW][C]97[/C][C]0.00268119[/C][C]0.00536237[/C][C]0.997319[/C][/ROW]
[ROW][C]98[/C][C]0.00211557[/C][C]0.00423114[/C][C]0.997884[/C][/ROW]
[ROW][C]99[/C][C]0.00188183[/C][C]0.00376365[/C][C]0.998118[/C][/ROW]
[ROW][C]100[/C][C]0.0021215[/C][C]0.004243[/C][C]0.997879[/C][/ROW]
[ROW][C]101[/C][C]0.00178686[/C][C]0.00357372[/C][C]0.998213[/C][/ROW]
[ROW][C]102[/C][C]0.00163687[/C][C]0.00327374[/C][C]0.998363[/C][/ROW]
[ROW][C]103[/C][C]0.00202531[/C][C]0.00405062[/C][C]0.997975[/C][/ROW]
[ROW][C]104[/C][C]0.00167459[/C][C]0.00334918[/C][C]0.998325[/C][/ROW]
[ROW][C]105[/C][C]0.0015471[/C][C]0.0030942[/C][C]0.998453[/C][/ROW]
[ROW][C]106[/C][C]0.00160709[/C][C]0.00321417[/C][C]0.998393[/C][/ROW]
[ROW][C]107[/C][C]0.00234777[/C][C]0.00469553[/C][C]0.997652[/C][/ROW]
[ROW][C]108[/C][C]0.00747739[/C][C]0.0149548[/C][C]0.992523[/C][/ROW]
[ROW][C]109[/C][C]0.0139499[/C][C]0.0278997[/C][C]0.98605[/C][/ROW]
[ROW][C]110[/C][C]0.0131849[/C][C]0.0263698[/C][C]0.986815[/C][/ROW]
[ROW][C]111[/C][C]0.0119635[/C][C]0.0239271[/C][C]0.988036[/C][/ROW]
[ROW][C]112[/C][C]0.0115072[/C][C]0.0230144[/C][C]0.988493[/C][/ROW]
[ROW][C]113[/C][C]0.0500112[/C][C]0.100022[/C][C]0.949989[/C][/ROW]
[ROW][C]114[/C][C]0.060319[/C][C]0.120638[/C][C]0.939681[/C][/ROW]
[ROW][C]115[/C][C]0.107611[/C][C]0.215222[/C][C]0.892389[/C][/ROW]
[ROW][C]116[/C][C]0.155013[/C][C]0.310026[/C][C]0.844987[/C][/ROW]
[ROW][C]117[/C][C]0.192579[/C][C]0.385159[/C][C]0.807421[/C][/ROW]
[ROW][C]118[/C][C]0.18163[/C][C]0.363261[/C][C]0.81837[/C][/ROW]
[ROW][C]119[/C][C]0.228232[/C][C]0.456465[/C][C]0.771768[/C][/ROW]
[ROW][C]120[/C][C]0.306888[/C][C]0.613777[/C][C]0.693112[/C][/ROW]
[ROW][C]121[/C][C]0.329199[/C][C]0.658399[/C][C]0.670801[/C][/ROW]
[ROW][C]122[/C][C]0.327866[/C][C]0.655732[/C][C]0.672134[/C][/ROW]
[ROW][C]123[/C][C]0.450647[/C][C]0.901294[/C][C]0.549353[/C][/ROW]
[ROW][C]124[/C][C]0.446415[/C][C]0.89283[/C][C]0.553585[/C][/ROW]
[ROW][C]125[/C][C]0.450622[/C][C]0.901245[/C][C]0.549378[/C][/ROW]
[ROW][C]126[/C][C]0.429468[/C][C]0.858936[/C][C]0.570532[/C][/ROW]
[ROW][C]127[/C][C]0.466091[/C][C]0.932181[/C][C]0.533909[/C][/ROW]
[ROW][C]128[/C][C]0.446813[/C][C]0.893625[/C][C]0.553187[/C][/ROW]
[ROW][C]129[/C][C]0.537361[/C][C]0.925278[/C][C]0.462639[/C][/ROW]
[ROW][C]130[/C][C]0.520663[/C][C]0.958674[/C][C]0.479337[/C][/ROW]
[ROW][C]131[/C][C]0.49821[/C][C]0.996419[/C][C]0.50179[/C][/ROW]
[ROW][C]132[/C][C]0.503081[/C][C]0.993837[/C][C]0.496919[/C][/ROW]
[ROW][C]133[/C][C]0.482357[/C][C]0.964714[/C][C]0.517643[/C][/ROW]
[ROW][C]134[/C][C]0.510525[/C][C]0.978949[/C][C]0.489475[/C][/ROW]
[ROW][C]135[/C][C]0.487162[/C][C]0.974324[/C][C]0.512838[/C][/ROW]
[ROW][C]136[/C][C]0.475006[/C][C]0.950013[/C][C]0.524994[/C][/ROW]
[ROW][C]137[/C][C]0.504715[/C][C]0.990571[/C][C]0.495285[/C][/ROW]
[ROW][C]138[/C][C]0.581113[/C][C]0.837773[/C][C]0.418887[/C][/ROW]
[ROW][C]139[/C][C]0.65633[/C][C]0.687341[/C][C]0.34367[/C][/ROW]
[ROW][C]140[/C][C]0.632927[/C][C]0.734147[/C][C]0.367073[/C][/ROW]
[ROW][C]141[/C][C]0.609066[/C][C]0.781868[/C][C]0.390934[/C][/ROW]
[ROW][C]142[/C][C]0.630325[/C][C]0.739349[/C][C]0.369675[/C][/ROW]
[ROW][C]143[/C][C]0.649536[/C][C]0.700927[/C][C]0.350464[/C][/ROW]
[ROW][C]144[/C][C]0.667443[/C][C]0.665115[/C][C]0.332557[/C][/ROW]
[ROW][C]145[/C][C]0.671692[/C][C]0.656615[/C][C]0.328308[/C][/ROW]
[ROW][C]146[/C][C]0.685459[/C][C]0.629081[/C][C]0.314541[/C][/ROW]
[ROW][C]147[/C][C]0.660761[/C][C]0.678477[/C][C]0.339239[/C][/ROW]
[ROW][C]148[/C][C]0.63472[/C][C]0.73056[/C][C]0.36528[/C][/ROW]
[ROW][C]149[/C][C]0.633589[/C][C]0.732821[/C][C]0.366411[/C][/ROW]
[ROW][C]150[/C][C]0.658093[/C][C]0.683815[/C][C]0.341907[/C][/ROW]
[ROW][C]151[/C][C]0.653023[/C][C]0.693955[/C][C]0.346977[/C][/ROW]
[ROW][C]152[/C][C]0.628949[/C][C]0.742102[/C][C]0.371051[/C][/ROW]
[ROW][C]153[/C][C]0.66514[/C][C]0.669719[/C][C]0.33486[/C][/ROW]
[ROW][C]154[/C][C]0.6964[/C][C]0.607199[/C][C]0.3036[/C][/ROW]
[ROW][C]155[/C][C]0.668667[/C][C]0.662667[/C][C]0.331333[/C][/ROW]
[ROW][C]156[/C][C]0.636233[/C][C]0.727535[/C][C]0.363767[/C][/ROW]
[ROW][C]157[/C][C]0.659095[/C][C]0.68181[/C][C]0.340905[/C][/ROW]
[ROW][C]158[/C][C]0.644192[/C][C]0.711616[/C][C]0.355808[/C][/ROW]
[ROW][C]159[/C][C]0.620169[/C][C]0.759661[/C][C]0.379831[/C][/ROW]
[ROW][C]160[/C][C]0.616017[/C][C]0.767966[/C][C]0.383983[/C][/ROW]
[ROW][C]161[/C][C]0.65886[/C][C]0.68228[/C][C]0.34114[/C][/ROW]
[ROW][C]162[/C][C]0.652147[/C][C]0.695706[/C][C]0.347853[/C][/ROW]
[ROW][C]163[/C][C]0.649027[/C][C]0.701946[/C][C]0.350973[/C][/ROW]
[ROW][C]164[/C][C]0.619002[/C][C]0.761996[/C][C]0.380998[/C][/ROW]
[ROW][C]165[/C][C]0.651406[/C][C]0.697189[/C][C]0.348594[/C][/ROW]
[ROW][C]166[/C][C]0.624387[/C][C]0.751226[/C][C]0.375613[/C][/ROW]
[ROW][C]167[/C][C]0.683764[/C][C]0.632472[/C][C]0.316236[/C][/ROW]
[ROW][C]168[/C][C]0.650228[/C][C]0.699543[/C][C]0.349772[/C][/ROW]
[ROW][C]169[/C][C]0.618211[/C][C]0.763577[/C][C]0.381789[/C][/ROW]
[ROW][C]170[/C][C]0.606892[/C][C]0.786217[/C][C]0.393108[/C][/ROW]
[ROW][C]171[/C][C]0.590398[/C][C]0.819205[/C][C]0.409602[/C][/ROW]
[ROW][C]172[/C][C]0.634041[/C][C]0.731918[/C][C]0.365959[/C][/ROW]
[ROW][C]173[/C][C]0.602626[/C][C]0.794748[/C][C]0.397374[/C][/ROW]
[ROW][C]174[/C][C]0.574214[/C][C]0.851571[/C][C]0.425786[/C][/ROW]
[ROW][C]175[/C][C]0.543462[/C][C]0.913076[/C][C]0.456538[/C][/ROW]
[ROW][C]176[/C][C]0.577419[/C][C]0.845162[/C][C]0.422581[/C][/ROW]
[ROW][C]177[/C][C]0.54098[/C][C]0.91804[/C][C]0.45902[/C][/ROW]
[ROW][C]178[/C][C]0.689295[/C][C]0.62141[/C][C]0.310705[/C][/ROW]
[ROW][C]179[/C][C]0.675938[/C][C]0.648125[/C][C]0.324062[/C][/ROW]
[ROW][C]180[/C][C]0.738369[/C][C]0.523262[/C][C]0.261631[/C][/ROW]
[ROW][C]181[/C][C]0.707159[/C][C]0.585682[/C][C]0.292841[/C][/ROW]
[ROW][C]182[/C][C]0.674489[/C][C]0.651021[/C][C]0.325511[/C][/ROW]
[ROW][C]183[/C][C]0.695296[/C][C]0.609407[/C][C]0.304704[/C][/ROW]
[ROW][C]184[/C][C]0.690689[/C][C]0.618622[/C][C]0.309311[/C][/ROW]
[ROW][C]185[/C][C]0.656254[/C][C]0.687491[/C][C]0.343746[/C][/ROW]
[ROW][C]186[/C][C]0.639993[/C][C]0.720014[/C][C]0.360007[/C][/ROW]
[ROW][C]187[/C][C]0.654224[/C][C]0.691552[/C][C]0.345776[/C][/ROW]
[ROW][C]188[/C][C]0.617625[/C][C]0.764749[/C][C]0.382375[/C][/ROW]
[ROW][C]189[/C][C]0.588488[/C][C]0.823024[/C][C]0.411512[/C][/ROW]
[ROW][C]190[/C][C]0.551585[/C][C]0.89683[/C][C]0.448415[/C][/ROW]
[ROW][C]191[/C][C]0.55095[/C][C]0.8981[/C][C]0.44905[/C][/ROW]
[ROW][C]192[/C][C]0.547353[/C][C]0.905294[/C][C]0.452647[/C][/ROW]
[ROW][C]193[/C][C]0.59864[/C][C]0.80272[/C][C]0.40136[/C][/ROW]
[ROW][C]194[/C][C]0.657161[/C][C]0.685678[/C][C]0.342839[/C][/ROW]
[ROW][C]195[/C][C]0.63233[/C][C]0.73534[/C][C]0.36767[/C][/ROW]
[ROW][C]196[/C][C]0.593937[/C][C]0.812127[/C][C]0.406063[/C][/ROW]
[ROW][C]197[/C][C]0.573719[/C][C]0.852563[/C][C]0.426281[/C][/ROW]
[ROW][C]198[/C][C]0.549559[/C][C]0.900883[/C][C]0.450441[/C][/ROW]
[ROW][C]199[/C][C]0.518881[/C][C]0.962238[/C][C]0.481119[/C][/ROW]
[ROW][C]200[/C][C]0.508759[/C][C]0.982481[/C][C]0.491241[/C][/ROW]
[ROW][C]201[/C][C]0.590028[/C][C]0.819945[/C][C]0.409972[/C][/ROW]
[ROW][C]202[/C][C]0.549461[/C][C]0.901077[/C][C]0.450539[/C][/ROW]
[ROW][C]203[/C][C]0.510572[/C][C]0.978855[/C][C]0.489428[/C][/ROW]
[ROW][C]204[/C][C]0.479324[/C][C]0.958648[/C][C]0.520676[/C][/ROW]
[ROW][C]205[/C][C]0.455729[/C][C]0.911459[/C][C]0.544271[/C][/ROW]
[ROW][C]206[/C][C]0.432695[/C][C]0.865389[/C][C]0.567305[/C][/ROW]
[ROW][C]207[/C][C]0.451534[/C][C]0.903069[/C][C]0.548466[/C][/ROW]
[ROW][C]208[/C][C]0.422767[/C][C]0.845534[/C][C]0.577233[/C][/ROW]
[ROW][C]209[/C][C]0.491143[/C][C]0.982286[/C][C]0.508857[/C][/ROW]
[ROW][C]210[/C][C]0.469885[/C][C]0.939771[/C][C]0.530115[/C][/ROW]
[ROW][C]211[/C][C]0.448542[/C][C]0.897085[/C][C]0.551458[/C][/ROW]
[ROW][C]212[/C][C]0.415331[/C][C]0.830662[/C][C]0.584669[/C][/ROW]
[ROW][C]213[/C][C]0.377329[/C][C]0.754658[/C][C]0.622671[/C][/ROW]
[ROW][C]214[/C][C]0.337386[/C][C]0.674772[/C][C]0.662614[/C][/ROW]
[ROW][C]215[/C][C]0.32668[/C][C]0.65336[/C][C]0.67332[/C][/ROW]
[ROW][C]216[/C][C]0.290394[/C][C]0.580789[/C][C]0.709606[/C][/ROW]
[ROW][C]217[/C][C]0.27106[/C][C]0.542121[/C][C]0.72894[/C][/ROW]
[ROW][C]218[/C][C]0.281951[/C][C]0.563903[/C][C]0.718049[/C][/ROW]
[ROW][C]219[/C][C]0.253537[/C][C]0.507074[/C][C]0.746463[/C][/ROW]
[ROW][C]220[/C][C]0.236916[/C][C]0.473832[/C][C]0.763084[/C][/ROW]
[ROW][C]221[/C][C]0.280239[/C][C]0.560478[/C][C]0.719761[/C][/ROW]
[ROW][C]222[/C][C]0.419231[/C][C]0.838461[/C][C]0.580769[/C][/ROW]
[ROW][C]223[/C][C]0.376106[/C][C]0.752211[/C][C]0.623894[/C][/ROW]
[ROW][C]224[/C][C]0.347436[/C][C]0.694873[/C][C]0.652564[/C][/ROW]
[ROW][C]225[/C][C]0.344331[/C][C]0.688662[/C][C]0.655669[/C][/ROW]
[ROW][C]226[/C][C]0.309106[/C][C]0.618212[/C][C]0.690894[/C][/ROW]
[ROW][C]227[/C][C]0.279748[/C][C]0.559496[/C][C]0.720252[/C][/ROW]
[ROW][C]228[/C][C]0.241965[/C][C]0.48393[/C][C]0.758035[/C][/ROW]
[ROW][C]229[/C][C]0.288509[/C][C]0.577018[/C][C]0.711491[/C][/ROW]
[ROW][C]230[/C][C]0.341434[/C][C]0.682869[/C][C]0.658566[/C][/ROW]
[ROW][C]231[/C][C]0.49835[/C][C]0.9967[/C][C]0.50165[/C][/ROW]
[ROW][C]232[/C][C]0.556937[/C][C]0.886127[/C][C]0.443063[/C][/ROW]
[ROW][C]233[/C][C]0.50602[/C][C]0.98796[/C][C]0.49398[/C][/ROW]
[ROW][C]234[/C][C]0.458357[/C][C]0.916715[/C][C]0.541643[/C][/ROW]
[ROW][C]235[/C][C]0.411947[/C][C]0.823894[/C][C]0.588053[/C][/ROW]
[ROW][C]236[/C][C]0.820977[/C][C]0.358045[/C][C]0.179023[/C][/ROW]
[ROW][C]237[/C][C]0.785725[/C][C]0.42855[/C][C]0.214275[/C][/ROW]
[ROW][C]238[/C][C]0.748929[/C][C]0.502142[/C][C]0.251071[/C][/ROW]
[ROW][C]239[/C][C]0.69999[/C][C]0.60002[/C][C]0.30001[/C][/ROW]
[ROW][C]240[/C][C]0.648387[/C][C]0.703226[/C][C]0.351613[/C][/ROW]
[ROW][C]241[/C][C]0.589225[/C][C]0.82155[/C][C]0.410775[/C][/ROW]
[ROW][C]242[/C][C]0.528396[/C][C]0.943208[/C][C]0.471604[/C][/ROW]
[ROW][C]243[/C][C]0.468031[/C][C]0.936062[/C][C]0.531969[/C][/ROW]
[ROW][C]244[/C][C]0.626611[/C][C]0.746779[/C][C]0.373389[/C][/ROW]
[ROW][C]245[/C][C]0.591347[/C][C]0.817306[/C][C]0.408653[/C][/ROW]
[ROW][C]246[/C][C]0.525203[/C][C]0.949594[/C][C]0.474797[/C][/ROW]
[ROW][C]247[/C][C]0.528846[/C][C]0.942308[/C][C]0.471154[/C][/ROW]
[ROW][C]248[/C][C]0.457564[/C][C]0.915128[/C][C]0.542436[/C][/ROW]
[ROW][C]249[/C][C]0.445845[/C][C]0.891691[/C][C]0.554155[/C][/ROW]
[ROW][C]250[/C][C]0.372968[/C][C]0.745937[/C][C]0.627032[/C][/ROW]
[ROW][C]251[/C][C]0.301818[/C][C]0.603637[/C][C]0.698182[/C][/ROW]
[ROW][C]252[/C][C]0.262904[/C][C]0.525809[/C][C]0.737096[/C][/ROW]
[ROW][C]253[/C][C]0.202314[/C][C]0.404629[/C][C]0.797686[/C][/ROW]
[ROW][C]254[/C][C]0.288584[/C][C]0.577168[/C][C]0.711416[/C][/ROW]
[ROW][C]255[/C][C]0.394361[/C][C]0.788721[/C][C]0.605639[/C][/ROW]
[ROW][C]256[/C][C]0.328229[/C][C]0.656458[/C][C]0.671771[/C][/ROW]
[ROW][C]257[/C][C]0.614276[/C][C]0.771448[/C][C]0.385724[/C][/ROW]
[ROW][C]258[/C][C]0.86446[/C][C]0.27108[/C][C]0.13554[/C][/ROW]
[ROW][C]259[/C][C]0.816276[/C][C]0.367447[/C][C]0.183724[/C][/ROW]
[ROW][C]260[/C][C]0.892464[/C][C]0.215072[/C][C]0.107536[/C][/ROW]
[ROW][C]261[/C][C]0.84998[/C][C]0.300041[/C][C]0.15002[/C][/ROW]
[ROW][C]262[/C][C]0.695517[/C][C]0.608966[/C][C]0.304483[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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
17	0.614646	0.770708	0.385354
18	0.49104	0.982079	0.50896
19	0.35809	0.716181	0.64191
20	0.258211	0.516423	0.741789
21	0.208582	0.417164	0.791418
22	0.156084	0.312168	0.843916
23	0.0984182	0.196836	0.901582
24	0.0928653	0.185731	0.907135
25	0.0603143	0.120629	0.939686
26	0.0435996	0.0871992	0.9564
27	0.0301115	0.0602231	0.969888
28	0.0195802	0.0391604	0.98042
29	0.012826	0.0256521	0.987174
30	0.00725508	0.0145102	0.992745
31	0.00552752	0.011055	0.994472
32	0.00304913	0.00609827	0.996951
33	0.00436266	0.00872532	0.995637
34	0.0505572	0.101114	0.949443
35	0.0387811	0.0775621	0.961219
36	0.0274938	0.0549876	0.972506
37	0.0202433	0.0404866	0.979757
38	0.0140589	0.0281179	0.985941
39	0.0115198	0.0230395	0.98848
40	0.00743383	0.0148677	0.992566
41	0.0144816	0.0289632	0.985518
42	0.0106426	0.0212852	0.989357
43	0.00953645	0.0190729	0.990464
44	0.0107753	0.0215505	0.989225
45	0.00718044	0.0143609	0.99282
46	0.0051953	0.0103906	0.994805
47	0.00384638	0.00769276	0.996154
48	0.00338582	0.00677164	0.996614
49	0.00277963	0.00555925	0.99722
50	0.00231454	0.00462908	0.997685
51	0.00155456	0.00310913	0.998445
52	0.00273852	0.00547705	0.997261
53	0.00186307	0.00372613	0.998137
54	0.00222596	0.00445192	0.997774
55	0.00319837	0.00639675	0.996802
56	0.00299899	0.00599798	0.997001
57	0.00836298	0.016726	0.991637
58	0.0072138	0.0144276	0.992786
59	0.00614651	0.012293	0.993853
60	0.00539402	0.010788	0.994606
61	0.00492074	0.00984148	0.995079
62	0.00362542	0.00725083	0.996375
63	0.00666239	0.0133248	0.993338
64	0.0109931	0.0219862	0.989007
65	0.00993653	0.0198731	0.990063
66	0.00940304	0.0188061	0.990597
67	0.00744835	0.0148967	0.992552
68	0.00650238	0.0130048	0.993498
69	0.00883106	0.0176621	0.991169
70	0.00682281	0.0136456	0.993177
71	0.00494328	0.00988655	0.995057
72	0.00374561	0.00749122	0.996254
73	0.00388042	0.00776084	0.99612
74	0.00480321	0.00960643	0.995197
75	0.00350773	0.00701546	0.996492
76	0.0026479	0.0052958	0.997352
77	0.00196201	0.00392402	0.998038
78	0.00162934	0.00325868	0.998371
79	0.00120794	0.00241588	0.998792
80	0.00129164	0.00258329	0.998708
81	0.000947267	0.00189453	0.999053
82	0.000916302	0.0018326	0.999084
83	0.000701003	0.00140201	0.999299
84	0.00246596	0.00493191	0.997534
85	0.0020262	0.00405241	0.997974
86	0.00152737	0.00305474	0.998473
87	0.00116026	0.00232052	0.99884
88	0.000962577	0.00192515	0.999037
89	0.00111915	0.00223829	0.998881
90	0.00132579	0.00265158	0.998674
91	0.00113862	0.00227723	0.998861
92	0.0026485	0.00529701	0.997351
93	0.0020483	0.00409659	0.997952
94	0.0019527	0.00390541	0.998047
95	0.00200704	0.00401407	0.997993
96	0.00176533	0.00353065	0.998235
97	0.00268119	0.00536237	0.997319
98	0.00211557	0.00423114	0.997884
99	0.00188183	0.00376365	0.998118
100	0.0021215	0.004243	0.997879
101	0.00178686	0.00357372	0.998213
102	0.00163687	0.00327374	0.998363
103	0.00202531	0.00405062	0.997975
104	0.00167459	0.00334918	0.998325
105	0.0015471	0.0030942	0.998453
106	0.00160709	0.00321417	0.998393
107	0.00234777	0.00469553	0.997652
108	0.00747739	0.0149548	0.992523
109	0.0139499	0.0278997	0.98605
110	0.0131849	0.0263698	0.986815
111	0.0119635	0.0239271	0.988036
112	0.0115072	0.0230144	0.988493
113	0.0500112	0.100022	0.949989
114	0.060319	0.120638	0.939681
115	0.107611	0.215222	0.892389
116	0.155013	0.310026	0.844987
117	0.192579	0.385159	0.807421
118	0.18163	0.363261	0.81837
119	0.228232	0.456465	0.771768
120	0.306888	0.613777	0.693112
121	0.329199	0.658399	0.670801
122	0.327866	0.655732	0.672134
123	0.450647	0.901294	0.549353
124	0.446415	0.89283	0.553585
125	0.450622	0.901245	0.549378
126	0.429468	0.858936	0.570532
127	0.466091	0.932181	0.533909
128	0.446813	0.893625	0.553187
129	0.537361	0.925278	0.462639
130	0.520663	0.958674	0.479337
131	0.49821	0.996419	0.50179
132	0.503081	0.993837	0.496919
133	0.482357	0.964714	0.517643
134	0.510525	0.978949	0.489475
135	0.487162	0.974324	0.512838
136	0.475006	0.950013	0.524994
137	0.504715	0.990571	0.495285
138	0.581113	0.837773	0.418887
139	0.65633	0.687341	0.34367
140	0.632927	0.734147	0.367073
141	0.609066	0.781868	0.390934
142	0.630325	0.739349	0.369675
143	0.649536	0.700927	0.350464
144	0.667443	0.665115	0.332557
145	0.671692	0.656615	0.328308
146	0.685459	0.629081	0.314541
147	0.660761	0.678477	0.339239
148	0.63472	0.73056	0.36528
149	0.633589	0.732821	0.366411
150	0.658093	0.683815	0.341907
151	0.653023	0.693955	0.346977
152	0.628949	0.742102	0.371051
153	0.66514	0.669719	0.33486
154	0.6964	0.607199	0.3036
155	0.668667	0.662667	0.331333
156	0.636233	0.727535	0.363767
157	0.659095	0.68181	0.340905
158	0.644192	0.711616	0.355808
159	0.620169	0.759661	0.379831
160	0.616017	0.767966	0.383983
161	0.65886	0.68228	0.34114
162	0.652147	0.695706	0.347853
163	0.649027	0.701946	0.350973
164	0.619002	0.761996	0.380998
165	0.651406	0.697189	0.348594
166	0.624387	0.751226	0.375613
167	0.683764	0.632472	0.316236
168	0.650228	0.699543	0.349772
169	0.618211	0.763577	0.381789
170	0.606892	0.786217	0.393108
171	0.590398	0.819205	0.409602
172	0.634041	0.731918	0.365959
173	0.602626	0.794748	0.397374
174	0.574214	0.851571	0.425786
175	0.543462	0.913076	0.456538
176	0.577419	0.845162	0.422581
177	0.54098	0.91804	0.45902
178	0.689295	0.62141	0.310705
179	0.675938	0.648125	0.324062
180	0.738369	0.523262	0.261631
181	0.707159	0.585682	0.292841
182	0.674489	0.651021	0.325511
183	0.695296	0.609407	0.304704
184	0.690689	0.618622	0.309311
185	0.656254	0.687491	0.343746
186	0.639993	0.720014	0.360007
187	0.654224	0.691552	0.345776
188	0.617625	0.764749	0.382375
189	0.588488	0.823024	0.411512
190	0.551585	0.89683	0.448415
191	0.55095	0.8981	0.44905
192	0.547353	0.905294	0.452647
193	0.59864	0.80272	0.40136
194	0.657161	0.685678	0.342839
195	0.63233	0.73534	0.36767
196	0.593937	0.812127	0.406063
197	0.573719	0.852563	0.426281
198	0.549559	0.900883	0.450441
199	0.518881	0.962238	0.481119
200	0.508759	0.982481	0.491241
201	0.590028	0.819945	0.409972
202	0.549461	0.901077	0.450539
203	0.510572	0.978855	0.489428
204	0.479324	0.958648	0.520676
205	0.455729	0.911459	0.544271
206	0.432695	0.865389	0.567305
207	0.451534	0.903069	0.548466
208	0.422767	0.845534	0.577233
209	0.491143	0.982286	0.508857
210	0.469885	0.939771	0.530115
211	0.448542	0.897085	0.551458
212	0.415331	0.830662	0.584669
213	0.377329	0.754658	0.622671
214	0.337386	0.674772	0.662614
215	0.32668	0.65336	0.67332
216	0.290394	0.580789	0.709606
217	0.27106	0.542121	0.72894
218	0.281951	0.563903	0.718049
219	0.253537	0.507074	0.746463
220	0.236916	0.473832	0.763084
221	0.280239	0.560478	0.719761
222	0.419231	0.838461	0.580769
223	0.376106	0.752211	0.623894
224	0.347436	0.694873	0.652564
225	0.344331	0.688662	0.655669
226	0.309106	0.618212	0.690894
227	0.279748	0.559496	0.720252
228	0.241965	0.48393	0.758035
229	0.288509	0.577018	0.711491
230	0.341434	0.682869	0.658566
231	0.49835	0.9967	0.50165
232	0.556937	0.886127	0.443063
233	0.50602	0.98796	0.49398
234	0.458357	0.916715	0.541643
235	0.411947	0.823894	0.588053
236	0.820977	0.358045	0.179023
237	0.785725	0.42855	0.214275
238	0.748929	0.502142	0.251071
239	0.69999	0.60002	0.30001
240	0.648387	0.703226	0.351613
241	0.589225	0.82155	0.410775
242	0.528396	0.943208	0.471604
243	0.468031	0.936062	0.531969
244	0.626611	0.746779	0.373389
245	0.591347	0.817306	0.408653
246	0.525203	0.949594	0.474797
247	0.528846	0.942308	0.471154
248	0.457564	0.915128	0.542436
249	0.445845	0.891691	0.554155
250	0.372968	0.745937	0.627032
251	0.301818	0.603637	0.698182
252	0.262904	0.525809	0.737096
253	0.202314	0.404629	0.797686
254	0.288584	0.577168	0.711416
255	0.394361	0.788721	0.605639
256	0.328229	0.656458	0.671771
257	0.614276	0.771448	0.385724
258	0.86446	0.27108	0.13554
259	0.816276	0.367447	0.183724
260	0.892464	0.215072	0.107536
261	0.84998	0.300041	0.15002
262	0.695517	0.608966	0.304483

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	51	0.207317	NOK
5% type I error level	82	0.333333	NOK
10% type I error level	86	0.349593	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 & 51 & 0.207317 & NOK \tabularnewline
5% type I error level & 82 & 0.333333 & NOK \tabularnewline
10% type I error level & 86 & 0.349593 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265249&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]51[/C][C]0.207317[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]82[/C][C]0.333333[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]86[/C][C]0.349593[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265249&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265249&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	51	0.207317	NOK
5% type I error level	82	0.333333	NOK
10% type I error level	86	0.349593	NOK

Figure 1

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 14 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 14 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

R code (references can be found in the software module):

library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code