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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 08 Dec 2014 21:13:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/08/t1418073366u016j4va1ozbfqy.htm/, Retrieved Tue, 28 May 2024 12:27:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264257, Retrieved Tue, 28 May 2024 12:27:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regressi...] [2014-12-08 21:13:42] [56a3e0974002d1c8d48b4dd203e70051] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
4 11 8 7 18 12 20 9 5 4 2 0 1 7.5
9 15 18 18 23 20 25 9 6 6 2 1 2 2.5
4 19 18 20 23 20 19 8 5 5 1 1 2 6.0
5 16 12 9 22 14 18 8 4 6 2 0 2 6.5
4 24 24 19 22 25 24 8 5 5 0 0 0 1.0
4 15 16 12 19 15 20 8 7 4 0 2 2 1.0
9 17 19 16 25 20 20 7 3 0 0 1 1 5.5
8 19 16 17 28 21 24 8 4 5 2 1 0 8.5
11 19 15 9 16 15 21 9 4 3 2 2 2 6.5
4 28 28 28 28 28 28 8 7 5 0 1 0 4.5
4 26 21 20 21 11 10 7 6 2 2 1 1 2.0
6 15 18 16 22 22 22 9 6 3 3 0 1 5.0
4 26 22 22 24 22 19 7 2 4 0 1 1 0.5
8 16 19 17 24 27 27 8 4 6 0 1 1 5.0
4 24 22 12 26 24 23 8 4 3 2 0 2 5.0
4 25 25 18 28 23 24 8 5 4 1 0 0 2.5
11 22 20 20 24 24 24 8 3 1 2 0 1 5.0
4 15 16 12 20 21 25 8 4 5 1 1 1 5.5
4 21 19 16 26 20 24 6 7 4 1 1 2 3.5
6 22 18 16 21 19 21 9 5 4 1 0 2 3.0
6 27 26 21 28 25 28 7 2 4 0 0 2 4.0
4 26 24 15 27 16 28 7 3 3 2 0 1 0.5
8 26 20 17 23 24 22 8 6 6 1 0 2 6.5
5 22 19 17 24 21 26 7 6 5 1 0 2 4.5
4 21 19 17 24 22 26 8 2 5 1 0 2 7.5
9 22 23 18 22 25 21 8 7 6 2 2 0 5.5
4 20 18 15 21 23 26 3 2 4 0 0 0 4.0
7 21 16 20 25 20 23 9 10 6 1 2 2 7.5
10 20 18 13 20 21 20 8 4 5 2 0 1 7.0
4 22 21 21 21 22 24 8 4 6 3 0 2 4.0
4 21 20 12 26 25 25 6 2 5 2 0 1 5.5
7 8 15 6 23 23 24 5 4 4 1 0 2 2.5
12 22 19 13 21 19 20 8 4 4 0 1 2 5.5
4 18 27 6 27 27 23 8 6 6 2 1 2 0.5
7 20 19 19 27 21 24 8 7 6 2 1 1 3.5
5 24 7 12 25 19 25 9 2 4 2 0 1 2.5
8 17 20 14 23 25 23 7 6 6 3 0 1 4.5
5 20 20 13 25 16 21 7 3 6 3 1 1 4.5
4 23 19 12 23 24 23 3 3 3 1 0 0 4.5
9 20 19 17 19 24 21 7 2 4 0 1 0 6.0
7 22 20 19 22 18 18 8 5 5 2 1 1 2.5
4 19 18 10 24 28 24 8 7 6 2 1 2 5.0
4 15 14 10 19 15 18 7 6 6 2 1 1 0.0
4 20 17 11 21 17 21 8 4 6 2 1 2 5.0
4 22 17 11 27 18 23 8 6 6 1 1 2 6.5
4 17 8 10 25 26 25 9 4 6 3 0 2 5.0
7 14 9 7 25 18 22 6 3 5 2 0 2 6.0
4 24 22 22 23 22 22 9 5 5 2 1 1 4.5
7 17 20 12 17 19 23 8 2 3 0 0 2 5.5
4 23 20 18 28 17 24 8 3 5 0 1 2 1.0
4 25 22 20 25 26 25 8 5 1 0 0 2 7.5
4 16 22 9 20 21 22 7 7 5 3 1 2 6.0
4 18 22 16 25 26 24 8 4 6 2 2 1 5.0
8 20 16 14 21 21 21 7 3 6 0 0 1 1.0
4 18 14 11 24 12 24 7 2 4 2 2 2 5.0
4 23 24 20 28 20 25 9 5 6 0 0 1 6.5
4 24 21 17 20 20 23 7 4 6 0 1 0 7.0
4 23 20 14 19 24 27 9 6 6 2 2 2 4.5
7 13 20 8 24 24 27 7 4 5 3 0 2 0.0
12 20 18 16 21 22 23 6 4 2 0 0 1 8.5
4 20 14 11 24 21 18 3 2 2 1 0 0 3.5
4 19 19 10 23 20 20 9 9 6 2 1 2 7.5
4 22 24 15 18 23 23 9 8 6 2 2 1 3.5
5 22 19 15 27 19 24 7 8 5 0 1 2 6.0
15 15 16 10 25 24 26 6 3 6 3 1 2 1.5
5 17 16 10 20 21 20 9 2 5 2 0 1 9.0
10 19 16 18 21 16 23 8 4 4 0 1 2 3.5
9 20 14 10 23 17 22 8 2 5 3 0 2 3.5
8 22 22 22 27 23 23 7 2 4 2 1 2 4.0
4 21 21 16 24 20 17 9 1 5 2 0 2 6.5
5 21 15 10 27 19 20 5 4 4 3 1 0 7.5
4 16 14 7 24 18 22 6 5 6 0 1 1 6.0
9 20 15 16 23 18 18 8 8 5 1 1 2 5.0
4 21 14 16 24 21 19 8 4 4 2 0 1 5.5
10 20 20 16 21 20 19 8 6 5 1 1 1 3.5
4 23 21 22 23 17 16 8 5 5 2 1 2 7.5
7 15 17 13 22 20 24 9 6 6 2 1 2 1.0
4 18 14 5 27 25 26 7 3 4 0 0 0 6.5
6 22 19 18 24 15 14 8 8 6 3 1 2 NA
7 16 16 10 25 17 25 9 4 2 0 1 0 6.5
5 17 13 8 19 17 23 9 6 5 2 1 1 6.5
4 24 26 16 24 24 18 8 4 6 1 0 1 7.0
4 13 13 8 25 21 22 4 3 5 0 0 0 3.5
4 19 18 16 23 22 26 7 8 5 0 2 2 1.5
4 20 15 14 23 18 25 8 6 3 1 2 2 4.0
4 22 18 15 25 22 26 6 3 3 0 0 0 7.5
4 19 21 9 26 20 26 7 5 5 2 1 2 4.5
6 21 17 21 26 21 24 7 4 6 1 0 2 0.0
10 15 18 7 16 21 22 3 3 2 2 0 0 3.5
7 21 20 17 23 20 21 8 7 6 1 0 1 5.5
4 24 18 18 26 18 22 8 2 4 1 1 1 5.0
4 22 25 16 25 25 28 8 4 5 3 0 2 4.5
7 20 20 16 23 23 22 8 6 6 2 1 1 2.5
4 21 19 14 26 21 26 5 6 5 0 0 2 7.5
8 19 18 15 22 20 20 6 6 5 2 1 1 7.0
11 14 12 8 20 21 24 6 4 6 1 1 2 0.0
6 25 22 22 27 20 21 7 6 5 0 0 2 4.5
14 11 16 5 20 22 23 7 5 6 1 1 2 3.0
5 17 18 13 22 15 23 7 5 5 0 0 2 1.5
4 22 23 22 24 24 23 8 6 4 0 0 2 3.5
8 20 20 18 21 22 22 9 8 5 1 1 2 2.5
9 22 20 15 24 21 23 8 5 5 2 2 1 5.5
4 15 16 11 26 17 21 8 6 5 2 1 2 8.0
4 23 22 19 24 23 27 7 4 5 2 1 2 1.0
5 20 19 19 24 22 23 9 3 4 2 1 2 5.0
4 22 23 21 27 23 26 7 3 5 3 0 1 4.5
5 16 6 4 25 16 27 6 2 0 0 0 0 3.0
4 25 19 17 27 18 27 7 4 5 0 0 1 3.0
4 18 24 10 19 25 23 8 5 6 0 0 1 8.0
7 19 19 13 22 18 23 6 3 1 0 1 0 2.5
10 25 15 15 22 14 23 2 4 1 0 1 0 7.0
4 21 18 11 25 20 28 4 5 3 3 0 0 0.0
5 22 18 20 23 19 24 8 3 3 2 0 2 1.0
4 21 22 13 24 18 20 6 5 6 0 0 1 3.5
4 22 23 18 24 22 23 8 4 4 2 0 1 5.5
4 23 18 20 23 21 22 6 4 5 2 0 2 5.5
6 20 17 15 22 14 15 7 6 6 0 2 2 0.5
4 6 6 4 24 5 27 7 3 6 2 2 2 7.5
8 15 22 9 19 25 23 7 4 6 1 2 1 9
5 18 20 18 25 21 23 9 3 6 3 2 2 9.5
4 24 16 12 26 11 20 7 10 6 3 2 2 8.5
17 22 16 17 18 20 18 6 4 6 0 0 1 7
4 21 17 12 24 9 22 8 8 5 3 1 2 8
4 23 20 16 28 15 20 8 3 6 2 2 2 10
8 20 23 17 23 23 21 9 5 5 2 0 2 7
4 20 18 14 19 21 25 7 4 6 0 0 1 8.5
7 18 13 13 19 9 19 6 3 5 2 0 2 9
4 25 22 20 27 24 25 8 5 5 3 0 2 9.5
4 16 20 16 24 16 24 6 3 6 2 0 2 4
5 20 20 15 26 20 22 6 3 4 0 0 2 6
7 14 13 10 21 15 28 9 4 5 0 0 2 8
4 22 16 16 25 18 22 6 3 6 0 0 1 5.5
4 26 25 21 28 22 21 9 6 6 1 1 1 9.5
7 20 16 15 19 21 23 8 6 5 2 2 2 7.5
11 17 15 16 20 21 19 8 4 6 3 2 2 7
7 22 19 19 26 21 21 9 4 6 0 0 0 7.5
4 22 19 9 27 20 25 6 4 6 2 0 1 8
4 20 24 19 23 24 23 4 3 4 2 1 2 7
4 17 9 7 18 15 28 8 2 6 1 2 0 7
4 22 22 23 23 24 14 5 5 5 2 0 2 6
4 17 15 14 21 18 23 7 4 6 2 2 2 10
4 22 22 10 23 24 24 9 4 6 2 0 0 2.5
6 21 22 16 22 24 25 9 4 5 2 0 2 9
8 25 24 12 21 15 15 8 3 4 2 1 1 8
23 11 12 10 14 19 23 6 4 5 2 2 1 6
4 19 21 7 24 20 26 8 2 6 1 1 2 8.5
8 24 25 20 26 26 21 3 0 0 0 0 0 6
6 17 26 9 24 26 26 8 4 6 2 1 2 9
4 22 19 14 26 18 15 7 3 4 0 0 0 8
4 22 21 12 22 23 23 7 6 6 0 2 2 8
7 17 14 10 20 13 15 9 4 4 2 0 1 9
4 26 28 19 20 16 16 4 4 6 0 0 1 5.5
4 19 16 16 20 19 20 7 2 4 0 0 0 5
4 20 21 11 18 22 20 6 4 5 0 1 0 7
4 19 16 15 18 21 20 3 2 1 0 1 0 5.5
10 21 16 14 25 11 21 8 4 5 3 2 2 9
6 24 25 11 28 23 28 8 3 5 0 0 1 2
5 21 21 14 23 18 19 9 6 5 2 2 0 8.5
5 19 22 15 20 19 21 8 6 5 3 0 2 9
4 13 9 7 22 15 22 8 4 5 0 0 2 8.5
4 24 20 22 27 8 27 9 5 6 2 2 1 9
5 28 19 19 24 15 20 8 4 5 0 1 2 7.5
5 27 24 22 23 21 17 9 6 6 3 2 2 10
5 22 22 11 20 25 26 7 6 5 2 1 2 9
5 23 22 19 22 14 21 7 9 6 2 1 2 7.5
4 19 12 9 21 21 24 6 4 5 2 1 0 6
6 18 17 11 24 18 21 8 8 6 3 1 2 10.5
4 23 18 17 26 18 25 6 5 5 3 0 2 8.5
4 21 10 12 24 12 22 7 4 5 3 0 0 8
4 22 22 17 18 24 17 8 4 6 2 2 1 10
9 17 24 10 17 17 14 8 7 6 3 2 1 10.5
18 15 18 17 23 20 23 7 4 6 1 2 2 6.5
6 21 18 13 21 24 28 9 8 6 2 1 2 9.5
5 20 23 11 21 22 24 9 4 6 3 2 1 8.5
4 26 21 19 24 15 22 9 3 6 2 0 1 7.5
11 19 21 21 22 22 24 6 5 6 2 1 2 5
4 28 28 24 24 26 25 8 8 6 2 2 2 8
10 21 17 13 24 17 21 9 4 5 1 0 1 10
6 19 21 16 24 23 22 9 10 6 3 1 0 7
8 22 21 13 23 19 16 8 5 6 2 2 2 7.5
8 21 20 15 21 21 18 8 5 6 2 2 2 7.5
6 20 18 15 24 23 27 8 3 6 1 0 2 9.5
8 19 17 11 19 19 17 8 3 5 1 1 2 6
4 11 7 7 19 18 25 8 3 3 0 0 2 10
4 17 17 13 23 16 24 9 4 4 1 1 1 7
9 19 14 13 25 23 21 6 5 6 1 0 2 3
9 20 18 12 24 13 21 9 5 4 2 1 2 6
5 17 14 8 21 18 19 8 4 6 0 0 0 7
4 21 23 7 18 23 27 8 7 6 3 1 0 10
4 21 20 17 23 21 28 8 5 3 1 0 1 7
15 12 14 9 20 23 19 8 4 4 1 2 0 3.5
10 23 17 18 23 16 23 9 7 4 3 0 2 8
9 22 21 17 23 17 25 9 7 4 3 0 2 10
7 22 23 17 23 20 26 9 7 4 3 0 2 5.5
9 21 24 18 23 18 25 8 7 4 3 0 2 6
6 20 21 12 27 20 25 8 7 4 0 0 0 6.5
4 18 14 14 19 19 24 8 7 6 2 1 2 6.5
7 21 24 22 25 26 24 3 1 4 1 1 0 8.5
4 24 16 19 25 9 24 6 2 4 2 1 2 4
7 22 21 21 21 23 22 5 3 2 1 0 2 9.5
4 20 8 10 25 9 21 4 6 5 1 0 1 8
15 17 17 16 17 13 17 9 8 6 3 2 2 8.5
4 19 18 11 22 27 23 8 8 6 1 1 1 5.5
9 16 17 15 23 22 17 3 0 1 0 0 0 7
4 19 16 12 27 12 25 6 3 4 1 0 2 9
4 23 22 21 27 18 19 6 6 5 1 1 2 8
28 8 17 22 5 6 8 9 5 5 2 0 2 10
4 22 21 20 19 17 14 7 7 6 1 0 1 8
4 23 20 15 24 22 22 6 3 5 0 1 2 6
4 15 20 9 23 22 25 9 3 6 2 0 0 8
5 17 19 15 28 23 28 7 4 6 2 0 1 5
4 21 8 14 25 19 25 8 4 5 3 0 2 9
4 25 19 11 27 20 24 8 1 5 0 0 2 4.5
12 18 11 9 16 17 15 8 5 6 2 0 2 8.5
5 23 15 18 23 18 25 7 3 4 1 0 1 7
4 20 13 12 25 24 24 0 0 0 0 0 0 9.5
6 21 18 11 26 20 28 6 4 6 1 1 0 8.5
6 21 19 14 24 18 24 9 6 5 2 2 1 7.5
5 24 23 10 23 23 25 9 4 6 1 1 2 7.5
4 22 20 18 24 27 23 6 1 2 0 1 2 5
4 22 22 11 27 25 26 8 3 5 0 0 2 7
4 23 19 14 25 24 26 8 7 5 2 0 2 8
10 17 16 16 19 12 22 5 3 1 0 0 2 5.5
7 15 11 11 19 16 25 6 5 5 1 1 0 8.5
4 24 11 8 14 16 20 6 3 4 1 0 0 7.5
4 22 21 16 24 24 22 9 3 5 2 2 2 9.5
7 19 14 13 20 23 26 9 6 4 2 1 2 7
4 18 21 12 21 24 20 9 9 6 3 0 2 8
4 21 20 17 28 24 26 6 4 5 0 1 2 8.5
12 20 21 23 26 26 26 4 3 6 0 1 1 3.5
5 19 20 14 19 19 21 8 9 6 2 2 2 6.5
8 19 19 10 23 28 21 4 5 6 0 1 0 6.5
6 16 19 16 23 23 24 5 3 6 3 1 1 10.5
17 18 18 11 21 21 21 8 6 5 2 0 1 8.5
4 23 20 16 26 19 18 6 2 6 1 0 1 8
5 22 21 19 25 23 23 8 4 5 3 1 2 10
4 23 22 17 25 23 26 9 5 5 2 1 1 10
5 20 19 12 24 20 23 7 4 5 2 0 1 9.5
5 24 23 17 23 18 25 4 0 0 0 0 0 9
6 25 16 11 22 20 20 8 2 6 1 1 2 10
4 25 23 19 27 28 25 8 5 6 2 1 2 7.5
4 20 18 12 26 21 26 8 3 6 2 0 1 4.5
4 23 23 8 23 25 19 4 0 0 0 0 0 4.5
6 21 20 17 22 18 21 9 5 5 3 0 2 0.5
8 23 20 13 26 24 23 8 6 5 1 0 2 6.5
10 23 23 17 22 28 24 6 3 5 0 1 1 4.5
4 11 13 7 17 9 6 3 0 0 0 0 0 5.5
5 21 21 23 25 22 22 7 3 4 0 1 0 5
4 27 26 18 22 26 21 8 5 6 2 1 2 6
4 19 18 13 28 28 28 7 4 4 0 0 2 4
4 21 19 17 22 18 24 7 5 5 2 0 1 8
16 16 18 13 21 23 14 8 7 6 3 2 1 10.5
4 22 19 13 21 22 17 8 4 5 3 1 2 8.5
7 21 18 8 24 15 20 7 8 6 2 1 2 6.5
4 22 19 16 26 24 28 7 6 6 1 1 2 8
4 16 13 14 26 12 19 6 4 5 1 0 1 8.5
14 18 10 13 24 12 24 8 5 5 1 1 0 5.5
5 23 21 19 27 20 21 8 5 6 0 1 2 7
5 24 24 15 22 25 21 7 3 6 1 0 2 5
5 20 21 15 23 24 26 9 6 6 0 1 2 3.5
5 20 23 8 22 23 24 9 3 4 2 0 1 5
7 18 18 14 23 18 26 7 6 5 3 1 1 9
19 4 11 7 15 20 25 7 3 2 1 0 2 8.5
16 14 16 11 20 22 23 8 7 6 2 2 2 5
4 22 20 17 22 20 24 8 7 6 3 0 2 9.5
4 17 20 19 25 25 24 6 6 4 3 1 2 3
7 23 26 17 27 28 26 9 5 6 1 1 0 1.5
9 20 21 12 24 25 23 6 5 5 1 0 1 6
5 18 12 12 21 14 20 5 4 4 0 0 2 0.5
14 19 15 18 17 16 16 7 4 6 1 2 2 6.5
4 20 18 16 26 24 24 9 7 6 3 0 2 7.5
16 15 14 15 20 13 20 6 2 1 0 1 0 4.5
10 24 18 20 22 19 23 7 5 5 2 0 1 8
5 21 16 16 24 18 23 5 4 5 2 1 0 9
6 19 19 12 23 16 18 9 2 6 2 2 2 7.5
4 19 7 10 22 8 21 8 5 4 2 0 0 8.5
4 27 21 28 28 27 25 4 4 3 0 0 2 7
4 23 24 19 21 23 23 9 7 4 3 2 2 9.5
5 23 21 18 24 20 26 8 6 5 2 2 0 6.5
4 20 20 19 28 20 26 7 4 5 0 0 0 9.5
4 17 22 8 25 26 24 8 5 6 2 2 2 6
5 21 17 17 24 23 23 1 0 1 0 0 0 8
4 23 19 16 24 24 21 8 7 6 2 1 2 9.5
4 22 20 18 21 21 23 8 4 4 2 0 2 8
5 16 16 12 20 15 20 9 5 4 3 0 2 8
8 20 20 17 26 22 23 8 6 5 2 0 1 9
15 16 16 13 16 25 24 9 8 3 2 1 1 5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 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 & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&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]12 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=264257&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=0

As an alternative you can also use a QR Code:  
QR Code


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 7.47112 -0.0101336AMS.A[t] + 0.0913186AMS.I1[t] -0.0325268AMS.I2[t] -0.0092723AMS.I3[t] -0.0754748AMS.E1[t] -0.0411171AMS.E2[t] -0.0399363AMS.E3[t] + 0.0279418Calculation[t] -0.0496649Algebraic_Reasoning[t] + 0.131552Graphical_Interpretation[t] + 0.457279Proportionality_and_Ratio[t] + 0.121246Probability_and_Sampling[t] -0.173159Estimation[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  7.47112 -0.0101336AMS.A[t] +  0.0913186AMS.I1[t] -0.0325268AMS.I2[t] -0.0092723AMS.I3[t] -0.0754748AMS.E1[t] -0.0411171AMS.E2[t] -0.0399363AMS.E3[t] +  0.0279418Calculation[t] -0.0496649Algebraic_Reasoning[t] +  0.131552Graphical_Interpretation[t] +  0.457279Proportionality_and_Ratio[t] +  0.121246Probability_and_Sampling[t] -0.173159Estimation[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  7.47112 -0.0101336AMS.A[t] +  0.0913186AMS.I1[t] -0.0325268AMS.I2[t] -0.0092723AMS.I3[t] -0.0754748AMS.E1[t] -0.0411171AMS.E2[t] -0.0399363AMS.E3[t] +  0.0279418Calculation[t] -0.0496649Algebraic_Reasoning[t] +  0.131552Graphical_Interpretation[t] +  0.457279Proportionality_and_Ratio[t] +  0.121246Probability_and_Sampling[t] -0.173159Estimation[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 7.47112 -0.0101336AMS.A[t] + 0.0913186AMS.I1[t] -0.0325268AMS.I2[t] -0.0092723AMS.I3[t] -0.0754748AMS.E1[t] -0.0411171AMS.E2[t] -0.0399363AMS.E3[t] + 0.0279418Calculation[t] -0.0496649Algebraic_Reasoning[t] + 0.131552Graphical_Interpretation[t] + 0.457279Proportionality_and_Ratio[t] + 0.121246Probability_and_Sampling[t] -0.173159Estimation[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.471121.8284.0875.75549e-052.87775e-05
AMS.A-0.01013360.052505-0.1930.8471010.42355
AMS.I10.09131860.06030151.5140.1310940.065547
AMS.I2-0.03252680.0528971-0.61490.5391310.269566
AMS.I3-0.00927230.0455728-0.20350.8389270.419463
AMS.E1-0.07547480.0620468-1.2160.2248810.11244
AMS.E2-0.04111710.0441933-0.93040.3529940.176497
AMS.E3-0.03993630.051927-0.76910.442510.221255
Calculation0.02794180.1140770.24490.806690.403345
Algebraic_Reasoning-0.04966490.0937928-0.52950.5968790.298439
Graphical_Interpretation0.1315520.1270741.0350.3014770.150739
Proportionality_and_Ratio0.4572790.1583832.8870.004199380.00209969
Probability_and_Sampling0.1212460.2200860.55090.5821530.291077
Estimation-0.1731590.210239-0.82360.4108720.205436

\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) & 7.47112 & 1.828 & 4.087 & 5.75549e-05 & 2.87775e-05 \tabularnewline
AMS.A & -0.0101336 & 0.052505 & -0.193 & 0.847101 & 0.42355 \tabularnewline
AMS.I1 & 0.0913186 & 0.0603015 & 1.514 & 0.131094 & 0.065547 \tabularnewline
AMS.I2 & -0.0325268 & 0.0528971 & -0.6149 & 0.539131 & 0.269566 \tabularnewline
AMS.I3 & -0.0092723 & 0.0455728 & -0.2035 & 0.838927 & 0.419463 \tabularnewline
AMS.E1 & -0.0754748 & 0.0620468 & -1.216 & 0.224881 & 0.11244 \tabularnewline
AMS.E2 & -0.0411171 & 0.0441933 & -0.9304 & 0.352994 & 0.176497 \tabularnewline
AMS.E3 & -0.0399363 & 0.051927 & -0.7691 & 0.44251 & 0.221255 \tabularnewline
Calculation & 0.0279418 & 0.114077 & 0.2449 & 0.80669 & 0.403345 \tabularnewline
Algebraic_Reasoning & -0.0496649 & 0.0937928 & -0.5295 & 0.596879 & 0.298439 \tabularnewline
Graphical_Interpretation & 0.131552 & 0.127074 & 1.035 & 0.301477 & 0.150739 \tabularnewline
Proportionality_and_Ratio & 0.457279 & 0.158383 & 2.887 & 0.00419938 & 0.00209969 \tabularnewline
Probability_and_Sampling & 0.121246 & 0.220086 & 0.5509 & 0.582153 & 0.291077 \tabularnewline
Estimation & -0.173159 & 0.210239 & -0.8236 & 0.410872 & 0.205436 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&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]7.47112[/C][C]1.828[/C][C]4.087[/C][C]5.75549e-05[/C][C]2.87775e-05[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0101336[/C][C]0.052505[/C][C]-0.193[/C][C]0.847101[/C][C]0.42355[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0913186[/C][C]0.0603015[/C][C]1.514[/C][C]0.131094[/C][C]0.065547[/C][/ROW]
[ROW][C]AMS.I2[/C][C]-0.0325268[/C][C]0.0528971[/C][C]-0.6149[/C][C]0.539131[/C][C]0.269566[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0092723[/C][C]0.0455728[/C][C]-0.2035[/C][C]0.838927[/C][C]0.419463[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0754748[/C][C]0.0620468[/C][C]-1.216[/C][C]0.224881[/C][C]0.11244[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0411171[/C][C]0.0441933[/C][C]-0.9304[/C][C]0.352994[/C][C]0.176497[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0399363[/C][C]0.051927[/C][C]-0.7691[/C][C]0.44251[/C][C]0.221255[/C][/ROW]
[ROW][C]Calculation[/C][C]0.0279418[/C][C]0.114077[/C][C]0.2449[/C][C]0.80669[/C][C]0.403345[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.0496649[/C][C]0.0937928[/C][C]-0.5295[/C][C]0.596879[/C][C]0.298439[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]0.131552[/C][C]0.127074[/C][C]1.035[/C][C]0.301477[/C][C]0.150739[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]0.457279[/C][C]0.158383[/C][C]2.887[/C][C]0.00419938[/C][C]0.00209969[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.121246[/C][C]0.220086[/C][C]0.5509[/C][C]0.582153[/C][C]0.291077[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.173159[/C][C]0.210239[/C][C]-0.8236[/C][C]0.410872[/C][C]0.205436[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=2

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.471121.8284.0875.75549e-052.87775e-05
AMS.A-0.01013360.052505-0.1930.8471010.42355
AMS.I10.09131860.06030151.5140.1310940.065547
AMS.I2-0.03252680.0528971-0.61490.5391310.269566
AMS.I3-0.00927230.0455728-0.20350.8389270.419463
AMS.E1-0.07547480.0620468-1.2160.2248810.11244
AMS.E2-0.04111710.0441933-0.93040.3529940.176497
AMS.E3-0.03993630.051927-0.76910.442510.221255
Calculation0.02794180.1140770.24490.806690.403345
Algebraic_Reasoning-0.04966490.0937928-0.52950.5968790.298439
Graphical_Interpretation0.1315520.1270741.0350.3014770.150739
Proportionality_and_Ratio0.4572790.1583832.8870.004199380.00209969
Probability_and_Sampling0.1212460.2200860.55090.5821530.291077
Estimation-0.1731590.210239-0.82360.4108720.205436






Multiple Linear Regression - Regression Statistics
Multiple R0.277728
R-squared0.0771326
Adjusted R-squared0.033025
F-TEST (value)1.74874
F-TEST (DF numerator)13
F-TEST (DF denominator)272
p-value0.0513182
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.51418
Sum Squared Residuals1719.33

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.277728 \tabularnewline
R-squared & 0.0771326 \tabularnewline
Adjusted R-squared & 0.033025 \tabularnewline
F-TEST (value) & 1.74874 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0.0513182 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.51418 \tabularnewline
Sum Squared Residuals & 1719.33 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.277728[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0771326[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.033025[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.74874[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/C][/ROW]
[ROW][C]p-value[/C][C]0.0513182[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.51418[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1719.33[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=3

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Regression Statistics
Multiple R0.277728
R-squared0.0771326
Adjusted R-squared0.033025
F-TEST (value)1.74874
F-TEST (DF numerator)13
F-TEST (DF denominator)272
p-value0.0513182
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.51418
Sum Squared Residuals1719.33






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.730050.769945
22.55.87293-3.37293
365.942840.05716
46.56.83527-0.335269
515.65155-4.65155
615.61743-4.61743
75.54.652720.847279
88.56.230272.26973
96.57.11854-0.618544
104.55.08923-0.589234
1127.5231-5.5231
1256.14946-1.14946
130.55.98109-5.48109
1454.837950.162048
1555.91546-0.91546
162.55.67472-3.17472
1755.7235-0.723497
185.55.88531-0.385311
193.55.41717-1.91717
2036.12096-3.12096
2144.85223-0.852225
220.56.25389-5.75389
236.56.180660.319337
244.55.60695-1.10695
257.55.711251.78875
265.56.76912-1.26912
2745.47409-1.47409
287.55.881851.61815
2976.742490.25751
3046.9535-2.9535
315.56.06528-0.565277
322.54.52534-2.02534
335.55.78107-0.281071
340.55.47829-4.97829
353.56.10047-2.60047
362.57.0264-4.5264
374.56.36533-1.86533
384.57.24818-2.74818
394.55.94714-1.44714
4065.914880.0851207
412.56.9587-4.4587
4255.92097-0.920971
4307.0322-7.0322
4456.98306-1.98306
456.56.035250.46475
4656.54339-1.54339
4766.06008-0.0600813
484.56.70712-2.20712
495.55.380510.119486
5015.44995-4.44995
517.54.618642.88136
5266.49356-0.493557
5356.09407-1.09407
5415.94185-4.94185
5556.68689-1.68689
566.55.250091.24991
5776.438660.561337
584.56.80499-2.30499
5905.66634-5.66634
608.55.092913.40709
613.56.01076-2.51076
627.56.381211.11879
633.56.92446-3.42446
6465.125820.874182
651.56.11846-4.61846
6696.739342.26066
673.55.58214-2.08214
683.57.15217-3.65217
6945.88939-1.88939
706.56.63202-0.132018
717.57.100090.399908
7265.598030.40197
7356.09134-1.09134
745.56.60339-1.10339
753.56.21984-2.71984
767.56.892430.607572
7716.0875-5.0875
786.55.04131.4587
79NANA1.39897
806.56.89819-0.39819
816.55.709430.790569
8278.61231-1.61231
833.57.10517-3.60517
841.53.33847-1.83847
8541.798562.20144
867.58.87061-1.37061
874.510.1933-5.69327
8802.75202-2.75202
893.54.0621-0.562102
905.56.84458-1.34458
9156.65321-1.65321
924.58.44496-3.94496
932.5-0.1105262.61053
947.57.009090.490905
95712.8327-5.8327
9600.78393-0.78393
974.56.90315-2.40315
9836.82982-3.82982
991.52.87619-1.37619
1003.56.77497-3.27497
1012.53.62278-1.12278
1025.53.450742.04926
103813.148-5.14796
10412.13631-1.13631
10556.87794-1.87794
1064.56.5946-2.0946
10735.56324-2.56324
10830.4118392.58816
109810.8491-2.84906
1102.51.481171.01883
111713.4633-6.46331
11205.22036-5.22036
11313.1974-2.1974
1143.54.18256-0.682557
1155.56.477-0.977002
1165.511.2926-5.79261
1170.5-0.7023681.20237
1187.54.393173.10683
11996.237692.76231
1209.58.533450.966553
1218.57.815210.684794
12276.254750.745251
12384.877833.12217
124109.019560.980442
12574.358872.64113
1268.56.682331.81767
12795.947973.05203
1289.511.5413-2.04126
12942.992471.00753
13063.207392.79261
13188.40005-0.400046
1325.52.088623.41138
1339.58.745070.754931
1347.57.72626-0.226264
13575.292681.70732
1367.55.879271.62073
13786.837351.16265
13877.14513-0.145127
13977.34629-0.346292
14062.718653.28135
1411014.2068-4.20677
1422.5-0.402782.90278
14398.443730.556269
14488.61375-0.613746
14563.391322.60868
1468.57.296861.20314
14762.618483.38152
14896.963092.03691
14985.703682.29632
15086.081871.91813
15199.94086-0.94086
1525.56.52988-1.02988
15354.158050.841947
15477.22269-0.222693
1555.53.910061.58994
156912.0687-3.06874
15720.5587511.44125
1588.56.280282.21972
15995.94063.0594
1608.56.599031.90097
16197.913881.08612
1627.55.133942.36606
163107.280962.71904
16498.281680.71832
1657.58.44752-0.947525
16662.271233.72877
16710.58.689551.81045
1688.58.254880.245125
16985.340182.65982
170107.124162.87584
17110.59.578290.921713
1726.53.264953.23505
1739.58.2321.268
1748.58.272080.227921
1757.58.59156-1.09156
17653.401641.59836
17784.259633.74037
178109.715490.284509
17976.514590.485411
1807.56.92610.573904
1817.53.651573.84843
1829.510.0405-0.540501
18361.092844.90716
184108.941641.05836
18579.68743-2.68743
18633.54381-0.54381
18765.173640.826362
18874.311012.68899
189108.476511.52349
19079.41299-2.41299
1913.52.393481.10652
19284.570473.42953
1931010.8624-0.862395
1945.55.80324-0.303239
19564.485881.51412
1966.56.6701-0.170097
1976.53.557752.94225
1988.511.4943-2.99425
1994-0.01306554.01307
2009.58.06411.4359
20187.085190.914808
2028.58.80992-0.309917
2035.53.544941.95506
20473.660143.33986
20596.843522.15648
20685.446572.55343
207108.800341.19966
20887.598070.401928
20964.233831.76617
21088.56622-0.566219
21152.99992.0001
212910.1602-1.16023
2134.53.379141.12086
2148.57.748470.751529
21572.39074.6093
2169.57.074462.42554
2178.57.665360.834645
2187.56.165581.33442
2197.57.438090.0619108
22052.903912.09609
22174.972952.02705
22287.723340.276657
2235.53.375492.12451
2248.58.67916-0.179159
2257.54.502352.99765
2269.58.734970.765025
22775.528811.47119
22884.303353.69665
2298.59.91001-1.41001
2303.53.69785-0.197847
2316.55.462521.03748
2326.52.564923.93508
23310.58.292722.20728
2348.56.911351.58865
23584.648533.35147
236106.310353.68965
237106.861373.13863
2389.55.843693.65631
23995.935073.06493
240108.555771.44423
2417.59.30131-1.80131
2424.55.29775-0.797755
2434.510.9671-6.46706
2440.5-0.4541160.954116
2456.57.41868-0.918679
2464.55.13842-0.638423
2475.55.96583-0.465829
24855.76945-0.769449
24966.25366-0.253656
25042.560041.43996
25184.580653.41935
25210.59.361991.13801
2538.58.70841-0.208412
2546.54.024982.47502
25585.535362.46464
2568.59.4754-0.975404
2575.54.002171.49783
25878.11221-1.11221
25956.68133-1.68133
2603.54.73001-1.23001
26152.689542.31046
26295.188953.81105
2638.59.60834-1.10834
26452.380892.61911
2659.512.3257-2.82566
26637.14074-4.14074
2671.51.015310.484687
268611.2242-5.22421
2690.50.969275-0.469275
2706.55.334151.16585
2717.58.56268-1.06268
2724.53.276731.22327
27385.833942.16606
27498.555640.444358
2757.56.433161.06684
2768.56.193092.30691
27774.322942.67706
2789.59.73909-0.239094
2796.52.110974.38903
2809.59.354110.145894
28163.111432.88857
28284.982363.01764
2839.57.874521.62548
28486.879761.12024
28584.947513.05249
286910.0567-1.05671
2875NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.73005 & 0.769945 \tabularnewline
2 & 2.5 & 5.87293 & -3.37293 \tabularnewline
3 & 6 & 5.94284 & 0.05716 \tabularnewline
4 & 6.5 & 6.83527 & -0.335269 \tabularnewline
5 & 1 & 5.65155 & -4.65155 \tabularnewline
6 & 1 & 5.61743 & -4.61743 \tabularnewline
7 & 5.5 & 4.65272 & 0.847279 \tabularnewline
8 & 8.5 & 6.23027 & 2.26973 \tabularnewline
9 & 6.5 & 7.11854 & -0.618544 \tabularnewline
10 & 4.5 & 5.08923 & -0.589234 \tabularnewline
11 & 2 & 7.5231 & -5.5231 \tabularnewline
12 & 5 & 6.14946 & -1.14946 \tabularnewline
13 & 0.5 & 5.98109 & -5.48109 \tabularnewline
14 & 5 & 4.83795 & 0.162048 \tabularnewline
15 & 5 & 5.91546 & -0.91546 \tabularnewline
16 & 2.5 & 5.67472 & -3.17472 \tabularnewline
17 & 5 & 5.7235 & -0.723497 \tabularnewline
18 & 5.5 & 5.88531 & -0.385311 \tabularnewline
19 & 3.5 & 5.41717 & -1.91717 \tabularnewline
20 & 3 & 6.12096 & -3.12096 \tabularnewline
21 & 4 & 4.85223 & -0.852225 \tabularnewline
22 & 0.5 & 6.25389 & -5.75389 \tabularnewline
23 & 6.5 & 6.18066 & 0.319337 \tabularnewline
24 & 4.5 & 5.60695 & -1.10695 \tabularnewline
25 & 7.5 & 5.71125 & 1.78875 \tabularnewline
26 & 5.5 & 6.76912 & -1.26912 \tabularnewline
27 & 4 & 5.47409 & -1.47409 \tabularnewline
28 & 7.5 & 5.88185 & 1.61815 \tabularnewline
29 & 7 & 6.74249 & 0.25751 \tabularnewline
30 & 4 & 6.9535 & -2.9535 \tabularnewline
31 & 5.5 & 6.06528 & -0.565277 \tabularnewline
32 & 2.5 & 4.52534 & -2.02534 \tabularnewline
33 & 5.5 & 5.78107 & -0.281071 \tabularnewline
34 & 0.5 & 5.47829 & -4.97829 \tabularnewline
35 & 3.5 & 6.10047 & -2.60047 \tabularnewline
36 & 2.5 & 7.0264 & -4.5264 \tabularnewline
37 & 4.5 & 6.36533 & -1.86533 \tabularnewline
38 & 4.5 & 7.24818 & -2.74818 \tabularnewline
39 & 4.5 & 5.94714 & -1.44714 \tabularnewline
40 & 6 & 5.91488 & 0.0851207 \tabularnewline
41 & 2.5 & 6.9587 & -4.4587 \tabularnewline
42 & 5 & 5.92097 & -0.920971 \tabularnewline
43 & 0 & 7.0322 & -7.0322 \tabularnewline
44 & 5 & 6.98306 & -1.98306 \tabularnewline
45 & 6.5 & 6.03525 & 0.46475 \tabularnewline
46 & 5 & 6.54339 & -1.54339 \tabularnewline
47 & 6 & 6.06008 & -0.0600813 \tabularnewline
48 & 4.5 & 6.70712 & -2.20712 \tabularnewline
49 & 5.5 & 5.38051 & 0.119486 \tabularnewline
50 & 1 & 5.44995 & -4.44995 \tabularnewline
51 & 7.5 & 4.61864 & 2.88136 \tabularnewline
52 & 6 & 6.49356 & -0.493557 \tabularnewline
53 & 5 & 6.09407 & -1.09407 \tabularnewline
54 & 1 & 5.94185 & -4.94185 \tabularnewline
55 & 5 & 6.68689 & -1.68689 \tabularnewline
56 & 6.5 & 5.25009 & 1.24991 \tabularnewline
57 & 7 & 6.43866 & 0.561337 \tabularnewline
58 & 4.5 & 6.80499 & -2.30499 \tabularnewline
59 & 0 & 5.66634 & -5.66634 \tabularnewline
60 & 8.5 & 5.09291 & 3.40709 \tabularnewline
61 & 3.5 & 6.01076 & -2.51076 \tabularnewline
62 & 7.5 & 6.38121 & 1.11879 \tabularnewline
63 & 3.5 & 6.92446 & -3.42446 \tabularnewline
64 & 6 & 5.12582 & 0.874182 \tabularnewline
65 & 1.5 & 6.11846 & -4.61846 \tabularnewline
66 & 9 & 6.73934 & 2.26066 \tabularnewline
67 & 3.5 & 5.58214 & -2.08214 \tabularnewline
68 & 3.5 & 7.15217 & -3.65217 \tabularnewline
69 & 4 & 5.88939 & -1.88939 \tabularnewline
70 & 6.5 & 6.63202 & -0.132018 \tabularnewline
71 & 7.5 & 7.10009 & 0.399908 \tabularnewline
72 & 6 & 5.59803 & 0.40197 \tabularnewline
73 & 5 & 6.09134 & -1.09134 \tabularnewline
74 & 5.5 & 6.60339 & -1.10339 \tabularnewline
75 & 3.5 & 6.21984 & -2.71984 \tabularnewline
76 & 7.5 & 6.89243 & 0.607572 \tabularnewline
77 & 1 & 6.0875 & -5.0875 \tabularnewline
78 & 6.5 & 5.0413 & 1.4587 \tabularnewline
79 & NA & NA & 1.39897 \tabularnewline
80 & 6.5 & 6.89819 & -0.39819 \tabularnewline
81 & 6.5 & 5.70943 & 0.790569 \tabularnewline
82 & 7 & 8.61231 & -1.61231 \tabularnewline
83 & 3.5 & 7.10517 & -3.60517 \tabularnewline
84 & 1.5 & 3.33847 & -1.83847 \tabularnewline
85 & 4 & 1.79856 & 2.20144 \tabularnewline
86 & 7.5 & 8.87061 & -1.37061 \tabularnewline
87 & 4.5 & 10.1933 & -5.69327 \tabularnewline
88 & 0 & 2.75202 & -2.75202 \tabularnewline
89 & 3.5 & 4.0621 & -0.562102 \tabularnewline
90 & 5.5 & 6.84458 & -1.34458 \tabularnewline
91 & 5 & 6.65321 & -1.65321 \tabularnewline
92 & 4.5 & 8.44496 & -3.94496 \tabularnewline
93 & 2.5 & -0.110526 & 2.61053 \tabularnewline
94 & 7.5 & 7.00909 & 0.490905 \tabularnewline
95 & 7 & 12.8327 & -5.8327 \tabularnewline
96 & 0 & 0.78393 & -0.78393 \tabularnewline
97 & 4.5 & 6.90315 & -2.40315 \tabularnewline
98 & 3 & 6.82982 & -3.82982 \tabularnewline
99 & 1.5 & 2.87619 & -1.37619 \tabularnewline
100 & 3.5 & 6.77497 & -3.27497 \tabularnewline
101 & 2.5 & 3.62278 & -1.12278 \tabularnewline
102 & 5.5 & 3.45074 & 2.04926 \tabularnewline
103 & 8 & 13.148 & -5.14796 \tabularnewline
104 & 1 & 2.13631 & -1.13631 \tabularnewline
105 & 5 & 6.87794 & -1.87794 \tabularnewline
106 & 4.5 & 6.5946 & -2.0946 \tabularnewline
107 & 3 & 5.56324 & -2.56324 \tabularnewline
108 & 3 & 0.411839 & 2.58816 \tabularnewline
109 & 8 & 10.8491 & -2.84906 \tabularnewline
110 & 2.5 & 1.48117 & 1.01883 \tabularnewline
111 & 7 & 13.4633 & -6.46331 \tabularnewline
112 & 0 & 5.22036 & -5.22036 \tabularnewline
113 & 1 & 3.1974 & -2.1974 \tabularnewline
114 & 3.5 & 4.18256 & -0.682557 \tabularnewline
115 & 5.5 & 6.477 & -0.977002 \tabularnewline
116 & 5.5 & 11.2926 & -5.79261 \tabularnewline
117 & 0.5 & -0.702368 & 1.20237 \tabularnewline
118 & 7.5 & 4.39317 & 3.10683 \tabularnewline
119 & 9 & 6.23769 & 2.76231 \tabularnewline
120 & 9.5 & 8.53345 & 0.966553 \tabularnewline
121 & 8.5 & 7.81521 & 0.684794 \tabularnewline
122 & 7 & 6.25475 & 0.745251 \tabularnewline
123 & 8 & 4.87783 & 3.12217 \tabularnewline
124 & 10 & 9.01956 & 0.980442 \tabularnewline
125 & 7 & 4.35887 & 2.64113 \tabularnewline
126 & 8.5 & 6.68233 & 1.81767 \tabularnewline
127 & 9 & 5.94797 & 3.05203 \tabularnewline
128 & 9.5 & 11.5413 & -2.04126 \tabularnewline
129 & 4 & 2.99247 & 1.00753 \tabularnewline
130 & 6 & 3.20739 & 2.79261 \tabularnewline
131 & 8 & 8.40005 & -0.400046 \tabularnewline
132 & 5.5 & 2.08862 & 3.41138 \tabularnewline
133 & 9.5 & 8.74507 & 0.754931 \tabularnewline
134 & 7.5 & 7.72626 & -0.226264 \tabularnewline
135 & 7 & 5.29268 & 1.70732 \tabularnewline
136 & 7.5 & 5.87927 & 1.62073 \tabularnewline
137 & 8 & 6.83735 & 1.16265 \tabularnewline
138 & 7 & 7.14513 & -0.145127 \tabularnewline
139 & 7 & 7.34629 & -0.346292 \tabularnewline
140 & 6 & 2.71865 & 3.28135 \tabularnewline
141 & 10 & 14.2068 & -4.20677 \tabularnewline
142 & 2.5 & -0.40278 & 2.90278 \tabularnewline
143 & 9 & 8.44373 & 0.556269 \tabularnewline
144 & 8 & 8.61375 & -0.613746 \tabularnewline
145 & 6 & 3.39132 & 2.60868 \tabularnewline
146 & 8.5 & 7.29686 & 1.20314 \tabularnewline
147 & 6 & 2.61848 & 3.38152 \tabularnewline
148 & 9 & 6.96309 & 2.03691 \tabularnewline
149 & 8 & 5.70368 & 2.29632 \tabularnewline
150 & 8 & 6.08187 & 1.91813 \tabularnewline
151 & 9 & 9.94086 & -0.94086 \tabularnewline
152 & 5.5 & 6.52988 & -1.02988 \tabularnewline
153 & 5 & 4.15805 & 0.841947 \tabularnewline
154 & 7 & 7.22269 & -0.222693 \tabularnewline
155 & 5.5 & 3.91006 & 1.58994 \tabularnewline
156 & 9 & 12.0687 & -3.06874 \tabularnewline
157 & 2 & 0.558751 & 1.44125 \tabularnewline
158 & 8.5 & 6.28028 & 2.21972 \tabularnewline
159 & 9 & 5.9406 & 3.0594 \tabularnewline
160 & 8.5 & 6.59903 & 1.90097 \tabularnewline
161 & 9 & 7.91388 & 1.08612 \tabularnewline
162 & 7.5 & 5.13394 & 2.36606 \tabularnewline
163 & 10 & 7.28096 & 2.71904 \tabularnewline
164 & 9 & 8.28168 & 0.71832 \tabularnewline
165 & 7.5 & 8.44752 & -0.947525 \tabularnewline
166 & 6 & 2.27123 & 3.72877 \tabularnewline
167 & 10.5 & 8.68955 & 1.81045 \tabularnewline
168 & 8.5 & 8.25488 & 0.245125 \tabularnewline
169 & 8 & 5.34018 & 2.65982 \tabularnewline
170 & 10 & 7.12416 & 2.87584 \tabularnewline
171 & 10.5 & 9.57829 & 0.921713 \tabularnewline
172 & 6.5 & 3.26495 & 3.23505 \tabularnewline
173 & 9.5 & 8.232 & 1.268 \tabularnewline
174 & 8.5 & 8.27208 & 0.227921 \tabularnewline
175 & 7.5 & 8.59156 & -1.09156 \tabularnewline
176 & 5 & 3.40164 & 1.59836 \tabularnewline
177 & 8 & 4.25963 & 3.74037 \tabularnewline
178 & 10 & 9.71549 & 0.284509 \tabularnewline
179 & 7 & 6.51459 & 0.485411 \tabularnewline
180 & 7.5 & 6.9261 & 0.573904 \tabularnewline
181 & 7.5 & 3.65157 & 3.84843 \tabularnewline
182 & 9.5 & 10.0405 & -0.540501 \tabularnewline
183 & 6 & 1.09284 & 4.90716 \tabularnewline
184 & 10 & 8.94164 & 1.05836 \tabularnewline
185 & 7 & 9.68743 & -2.68743 \tabularnewline
186 & 3 & 3.54381 & -0.54381 \tabularnewline
187 & 6 & 5.17364 & 0.826362 \tabularnewline
188 & 7 & 4.31101 & 2.68899 \tabularnewline
189 & 10 & 8.47651 & 1.52349 \tabularnewline
190 & 7 & 9.41299 & -2.41299 \tabularnewline
191 & 3.5 & 2.39348 & 1.10652 \tabularnewline
192 & 8 & 4.57047 & 3.42953 \tabularnewline
193 & 10 & 10.8624 & -0.862395 \tabularnewline
194 & 5.5 & 5.80324 & -0.303239 \tabularnewline
195 & 6 & 4.48588 & 1.51412 \tabularnewline
196 & 6.5 & 6.6701 & -0.170097 \tabularnewline
197 & 6.5 & 3.55775 & 2.94225 \tabularnewline
198 & 8.5 & 11.4943 & -2.99425 \tabularnewline
199 & 4 & -0.0130655 & 4.01307 \tabularnewline
200 & 9.5 & 8.0641 & 1.4359 \tabularnewline
201 & 8 & 7.08519 & 0.914808 \tabularnewline
202 & 8.5 & 8.80992 & -0.309917 \tabularnewline
203 & 5.5 & 3.54494 & 1.95506 \tabularnewline
204 & 7 & 3.66014 & 3.33986 \tabularnewline
205 & 9 & 6.84352 & 2.15648 \tabularnewline
206 & 8 & 5.44657 & 2.55343 \tabularnewline
207 & 10 & 8.80034 & 1.19966 \tabularnewline
208 & 8 & 7.59807 & 0.401928 \tabularnewline
209 & 6 & 4.23383 & 1.76617 \tabularnewline
210 & 8 & 8.56622 & -0.566219 \tabularnewline
211 & 5 & 2.9999 & 2.0001 \tabularnewline
212 & 9 & 10.1602 & -1.16023 \tabularnewline
213 & 4.5 & 3.37914 & 1.12086 \tabularnewline
214 & 8.5 & 7.74847 & 0.751529 \tabularnewline
215 & 7 & 2.3907 & 4.6093 \tabularnewline
216 & 9.5 & 7.07446 & 2.42554 \tabularnewline
217 & 8.5 & 7.66536 & 0.834645 \tabularnewline
218 & 7.5 & 6.16558 & 1.33442 \tabularnewline
219 & 7.5 & 7.43809 & 0.0619108 \tabularnewline
220 & 5 & 2.90391 & 2.09609 \tabularnewline
221 & 7 & 4.97295 & 2.02705 \tabularnewline
222 & 8 & 7.72334 & 0.276657 \tabularnewline
223 & 5.5 & 3.37549 & 2.12451 \tabularnewline
224 & 8.5 & 8.67916 & -0.179159 \tabularnewline
225 & 7.5 & 4.50235 & 2.99765 \tabularnewline
226 & 9.5 & 8.73497 & 0.765025 \tabularnewline
227 & 7 & 5.52881 & 1.47119 \tabularnewline
228 & 8 & 4.30335 & 3.69665 \tabularnewline
229 & 8.5 & 9.91001 & -1.41001 \tabularnewline
230 & 3.5 & 3.69785 & -0.197847 \tabularnewline
231 & 6.5 & 5.46252 & 1.03748 \tabularnewline
232 & 6.5 & 2.56492 & 3.93508 \tabularnewline
233 & 10.5 & 8.29272 & 2.20728 \tabularnewline
234 & 8.5 & 6.91135 & 1.58865 \tabularnewline
235 & 8 & 4.64853 & 3.35147 \tabularnewline
236 & 10 & 6.31035 & 3.68965 \tabularnewline
237 & 10 & 6.86137 & 3.13863 \tabularnewline
238 & 9.5 & 5.84369 & 3.65631 \tabularnewline
239 & 9 & 5.93507 & 3.06493 \tabularnewline
240 & 10 & 8.55577 & 1.44423 \tabularnewline
241 & 7.5 & 9.30131 & -1.80131 \tabularnewline
242 & 4.5 & 5.29775 & -0.797755 \tabularnewline
243 & 4.5 & 10.9671 & -6.46706 \tabularnewline
244 & 0.5 & -0.454116 & 0.954116 \tabularnewline
245 & 6.5 & 7.41868 & -0.918679 \tabularnewline
246 & 4.5 & 5.13842 & -0.638423 \tabularnewline
247 & 5.5 & 5.96583 & -0.465829 \tabularnewline
248 & 5 & 5.76945 & -0.769449 \tabularnewline
249 & 6 & 6.25366 & -0.253656 \tabularnewline
250 & 4 & 2.56004 & 1.43996 \tabularnewline
251 & 8 & 4.58065 & 3.41935 \tabularnewline
252 & 10.5 & 9.36199 & 1.13801 \tabularnewline
253 & 8.5 & 8.70841 & -0.208412 \tabularnewline
254 & 6.5 & 4.02498 & 2.47502 \tabularnewline
255 & 8 & 5.53536 & 2.46464 \tabularnewline
256 & 8.5 & 9.4754 & -0.975404 \tabularnewline
257 & 5.5 & 4.00217 & 1.49783 \tabularnewline
258 & 7 & 8.11221 & -1.11221 \tabularnewline
259 & 5 & 6.68133 & -1.68133 \tabularnewline
260 & 3.5 & 4.73001 & -1.23001 \tabularnewline
261 & 5 & 2.68954 & 2.31046 \tabularnewline
262 & 9 & 5.18895 & 3.81105 \tabularnewline
263 & 8.5 & 9.60834 & -1.10834 \tabularnewline
264 & 5 & 2.38089 & 2.61911 \tabularnewline
265 & 9.5 & 12.3257 & -2.82566 \tabularnewline
266 & 3 & 7.14074 & -4.14074 \tabularnewline
267 & 1.5 & 1.01531 & 0.484687 \tabularnewline
268 & 6 & 11.2242 & -5.22421 \tabularnewline
269 & 0.5 & 0.969275 & -0.469275 \tabularnewline
270 & 6.5 & 5.33415 & 1.16585 \tabularnewline
271 & 7.5 & 8.56268 & -1.06268 \tabularnewline
272 & 4.5 & 3.27673 & 1.22327 \tabularnewline
273 & 8 & 5.83394 & 2.16606 \tabularnewline
274 & 9 & 8.55564 & 0.444358 \tabularnewline
275 & 7.5 & 6.43316 & 1.06684 \tabularnewline
276 & 8.5 & 6.19309 & 2.30691 \tabularnewline
277 & 7 & 4.32294 & 2.67706 \tabularnewline
278 & 9.5 & 9.73909 & -0.239094 \tabularnewline
279 & 6.5 & 2.11097 & 4.38903 \tabularnewline
280 & 9.5 & 9.35411 & 0.145894 \tabularnewline
281 & 6 & 3.11143 & 2.88857 \tabularnewline
282 & 8 & 4.98236 & 3.01764 \tabularnewline
283 & 9.5 & 7.87452 & 1.62548 \tabularnewline
284 & 8 & 6.87976 & 1.12024 \tabularnewline
285 & 8 & 4.94751 & 3.05249 \tabularnewline
286 & 9 & 10.0567 & -1.05671 \tabularnewline
287 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&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]7.5[/C][C]6.73005[/C][C]0.769945[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]5.87293[/C][C]-3.37293[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]5.94284[/C][C]0.05716[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]6.83527[/C][C]-0.335269[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.65155[/C][C]-4.65155[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]5.61743[/C][C]-4.61743[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]4.65272[/C][C]0.847279[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]6.23027[/C][C]2.26973[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]7.11854[/C][C]-0.618544[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.08923[/C][C]-0.589234[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]7.5231[/C][C]-5.5231[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]6.14946[/C][C]-1.14946[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]5.98109[/C][C]-5.48109[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.83795[/C][C]0.162048[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]5.91546[/C][C]-0.91546[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]5.67472[/C][C]-3.17472[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]5.7235[/C][C]-0.723497[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]5.88531[/C][C]-0.385311[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]5.41717[/C][C]-1.91717[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]6.12096[/C][C]-3.12096[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.85223[/C][C]-0.852225[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]6.25389[/C][C]-5.75389[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]6.18066[/C][C]0.319337[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.60695[/C][C]-1.10695[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]5.71125[/C][C]1.78875[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]6.76912[/C][C]-1.26912[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]5.47409[/C][C]-1.47409[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]5.88185[/C][C]1.61815[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]6.74249[/C][C]0.25751[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]6.9535[/C][C]-2.9535[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]6.06528[/C][C]-0.565277[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]4.52534[/C][C]-2.02534[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]5.78107[/C][C]-0.281071[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.47829[/C][C]-4.97829[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]6.10047[/C][C]-2.60047[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]7.0264[/C][C]-4.5264[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]6.36533[/C][C]-1.86533[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]7.24818[/C][C]-2.74818[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.94714[/C][C]-1.44714[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.91488[/C][C]0.0851207[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]6.9587[/C][C]-4.4587[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.92097[/C][C]-0.920971[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]7.0322[/C][C]-7.0322[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.98306[/C][C]-1.98306[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]6.03525[/C][C]0.46475[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]6.54339[/C][C]-1.54339[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]6.06008[/C][C]-0.0600813[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]6.70712[/C][C]-2.20712[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.38051[/C][C]0.119486[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]5.44995[/C][C]-4.44995[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]4.61864[/C][C]2.88136[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]6.49356[/C][C]-0.493557[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.09407[/C][C]-1.09407[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.94185[/C][C]-4.94185[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]6.68689[/C][C]-1.68689[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.25009[/C][C]1.24991[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]6.43866[/C][C]0.561337[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.80499[/C][C]-2.30499[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.66634[/C][C]-5.66634[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.09291[/C][C]3.40709[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]6.01076[/C][C]-2.51076[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]6.38121[/C][C]1.11879[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]6.92446[/C][C]-3.42446[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]5.12582[/C][C]0.874182[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]6.11846[/C][C]-4.61846[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]6.73934[/C][C]2.26066[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]5.58214[/C][C]-2.08214[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]7.15217[/C][C]-3.65217[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]5.88939[/C][C]-1.88939[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]6.63202[/C][C]-0.132018[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]7.10009[/C][C]0.399908[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]5.59803[/C][C]0.40197[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]6.09134[/C][C]-1.09134[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]6.60339[/C][C]-1.10339[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]6.21984[/C][C]-2.71984[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]6.89243[/C][C]0.607572[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]6.0875[/C][C]-5.0875[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.0413[/C][C]1.4587[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]1.39897[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]6.89819[/C][C]-0.39819[/C][/ROW]
[ROW][C]81[/C][C]6.5[/C][C]5.70943[/C][C]0.790569[/C][/ROW]
[ROW][C]82[/C][C]7[/C][C]8.61231[/C][C]-1.61231[/C][/ROW]
[ROW][C]83[/C][C]3.5[/C][C]7.10517[/C][C]-3.60517[/C][/ROW]
[ROW][C]84[/C][C]1.5[/C][C]3.33847[/C][C]-1.83847[/C][/ROW]
[ROW][C]85[/C][C]4[/C][C]1.79856[/C][C]2.20144[/C][/ROW]
[ROW][C]86[/C][C]7.5[/C][C]8.87061[/C][C]-1.37061[/C][/ROW]
[ROW][C]87[/C][C]4.5[/C][C]10.1933[/C][C]-5.69327[/C][/ROW]
[ROW][C]88[/C][C]0[/C][C]2.75202[/C][C]-2.75202[/C][/ROW]
[ROW][C]89[/C][C]3.5[/C][C]4.0621[/C][C]-0.562102[/C][/ROW]
[ROW][C]90[/C][C]5.5[/C][C]6.84458[/C][C]-1.34458[/C][/ROW]
[ROW][C]91[/C][C]5[/C][C]6.65321[/C][C]-1.65321[/C][/ROW]
[ROW][C]92[/C][C]4.5[/C][C]8.44496[/C][C]-3.94496[/C][/ROW]
[ROW][C]93[/C][C]2.5[/C][C]-0.110526[/C][C]2.61053[/C][/ROW]
[ROW][C]94[/C][C]7.5[/C][C]7.00909[/C][C]0.490905[/C][/ROW]
[ROW][C]95[/C][C]7[/C][C]12.8327[/C][C]-5.8327[/C][/ROW]
[ROW][C]96[/C][C]0[/C][C]0.78393[/C][C]-0.78393[/C][/ROW]
[ROW][C]97[/C][C]4.5[/C][C]6.90315[/C][C]-2.40315[/C][/ROW]
[ROW][C]98[/C][C]3[/C][C]6.82982[/C][C]-3.82982[/C][/ROW]
[ROW][C]99[/C][C]1.5[/C][C]2.87619[/C][C]-1.37619[/C][/ROW]
[ROW][C]100[/C][C]3.5[/C][C]6.77497[/C][C]-3.27497[/C][/ROW]
[ROW][C]101[/C][C]2.5[/C][C]3.62278[/C][C]-1.12278[/C][/ROW]
[ROW][C]102[/C][C]5.5[/C][C]3.45074[/C][C]2.04926[/C][/ROW]
[ROW][C]103[/C][C]8[/C][C]13.148[/C][C]-5.14796[/C][/ROW]
[ROW][C]104[/C][C]1[/C][C]2.13631[/C][C]-1.13631[/C][/ROW]
[ROW][C]105[/C][C]5[/C][C]6.87794[/C][C]-1.87794[/C][/ROW]
[ROW][C]106[/C][C]4.5[/C][C]6.5946[/C][C]-2.0946[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]5.56324[/C][C]-2.56324[/C][/ROW]
[ROW][C]108[/C][C]3[/C][C]0.411839[/C][C]2.58816[/C][/ROW]
[ROW][C]109[/C][C]8[/C][C]10.8491[/C][C]-2.84906[/C][/ROW]
[ROW][C]110[/C][C]2.5[/C][C]1.48117[/C][C]1.01883[/C][/ROW]
[ROW][C]111[/C][C]7[/C][C]13.4633[/C][C]-6.46331[/C][/ROW]
[ROW][C]112[/C][C]0[/C][C]5.22036[/C][C]-5.22036[/C][/ROW]
[ROW][C]113[/C][C]1[/C][C]3.1974[/C][C]-2.1974[/C][/ROW]
[ROW][C]114[/C][C]3.5[/C][C]4.18256[/C][C]-0.682557[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]6.477[/C][C]-0.977002[/C][/ROW]
[ROW][C]116[/C][C]5.5[/C][C]11.2926[/C][C]-5.79261[/C][/ROW]
[ROW][C]117[/C][C]0.5[/C][C]-0.702368[/C][C]1.20237[/C][/ROW]
[ROW][C]118[/C][C]7.5[/C][C]4.39317[/C][C]3.10683[/C][/ROW]
[ROW][C]119[/C][C]9[/C][C]6.23769[/C][C]2.76231[/C][/ROW]
[ROW][C]120[/C][C]9.5[/C][C]8.53345[/C][C]0.966553[/C][/ROW]
[ROW][C]121[/C][C]8.5[/C][C]7.81521[/C][C]0.684794[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]6.25475[/C][C]0.745251[/C][/ROW]
[ROW][C]123[/C][C]8[/C][C]4.87783[/C][C]3.12217[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]9.01956[/C][C]0.980442[/C][/ROW]
[ROW][C]125[/C][C]7[/C][C]4.35887[/C][C]2.64113[/C][/ROW]
[ROW][C]126[/C][C]8.5[/C][C]6.68233[/C][C]1.81767[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]5.94797[/C][C]3.05203[/C][/ROW]
[ROW][C]128[/C][C]9.5[/C][C]11.5413[/C][C]-2.04126[/C][/ROW]
[ROW][C]129[/C][C]4[/C][C]2.99247[/C][C]1.00753[/C][/ROW]
[ROW][C]130[/C][C]6[/C][C]3.20739[/C][C]2.79261[/C][/ROW]
[ROW][C]131[/C][C]8[/C][C]8.40005[/C][C]-0.400046[/C][/ROW]
[ROW][C]132[/C][C]5.5[/C][C]2.08862[/C][C]3.41138[/C][/ROW]
[ROW][C]133[/C][C]9.5[/C][C]8.74507[/C][C]0.754931[/C][/ROW]
[ROW][C]134[/C][C]7.5[/C][C]7.72626[/C][C]-0.226264[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]5.29268[/C][C]1.70732[/C][/ROW]
[ROW][C]136[/C][C]7.5[/C][C]5.87927[/C][C]1.62073[/C][/ROW]
[ROW][C]137[/C][C]8[/C][C]6.83735[/C][C]1.16265[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]7.14513[/C][C]-0.145127[/C][/ROW]
[ROW][C]139[/C][C]7[/C][C]7.34629[/C][C]-0.346292[/C][/ROW]
[ROW][C]140[/C][C]6[/C][C]2.71865[/C][C]3.28135[/C][/ROW]
[ROW][C]141[/C][C]10[/C][C]14.2068[/C][C]-4.20677[/C][/ROW]
[ROW][C]142[/C][C]2.5[/C][C]-0.40278[/C][C]2.90278[/C][/ROW]
[ROW][C]143[/C][C]9[/C][C]8.44373[/C][C]0.556269[/C][/ROW]
[ROW][C]144[/C][C]8[/C][C]8.61375[/C][C]-0.613746[/C][/ROW]
[ROW][C]145[/C][C]6[/C][C]3.39132[/C][C]2.60868[/C][/ROW]
[ROW][C]146[/C][C]8.5[/C][C]7.29686[/C][C]1.20314[/C][/ROW]
[ROW][C]147[/C][C]6[/C][C]2.61848[/C][C]3.38152[/C][/ROW]
[ROW][C]148[/C][C]9[/C][C]6.96309[/C][C]2.03691[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]5.70368[/C][C]2.29632[/C][/ROW]
[ROW][C]150[/C][C]8[/C][C]6.08187[/C][C]1.91813[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]9.94086[/C][C]-0.94086[/C][/ROW]
[ROW][C]152[/C][C]5.5[/C][C]6.52988[/C][C]-1.02988[/C][/ROW]
[ROW][C]153[/C][C]5[/C][C]4.15805[/C][C]0.841947[/C][/ROW]
[ROW][C]154[/C][C]7[/C][C]7.22269[/C][C]-0.222693[/C][/ROW]
[ROW][C]155[/C][C]5.5[/C][C]3.91006[/C][C]1.58994[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]12.0687[/C][C]-3.06874[/C][/ROW]
[ROW][C]157[/C][C]2[/C][C]0.558751[/C][C]1.44125[/C][/ROW]
[ROW][C]158[/C][C]8.5[/C][C]6.28028[/C][C]2.21972[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]5.9406[/C][C]3.0594[/C][/ROW]
[ROW][C]160[/C][C]8.5[/C][C]6.59903[/C][C]1.90097[/C][/ROW]
[ROW][C]161[/C][C]9[/C][C]7.91388[/C][C]1.08612[/C][/ROW]
[ROW][C]162[/C][C]7.5[/C][C]5.13394[/C][C]2.36606[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]7.28096[/C][C]2.71904[/C][/ROW]
[ROW][C]164[/C][C]9[/C][C]8.28168[/C][C]0.71832[/C][/ROW]
[ROW][C]165[/C][C]7.5[/C][C]8.44752[/C][C]-0.947525[/C][/ROW]
[ROW][C]166[/C][C]6[/C][C]2.27123[/C][C]3.72877[/C][/ROW]
[ROW][C]167[/C][C]10.5[/C][C]8.68955[/C][C]1.81045[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]8.25488[/C][C]0.245125[/C][/ROW]
[ROW][C]169[/C][C]8[/C][C]5.34018[/C][C]2.65982[/C][/ROW]
[ROW][C]170[/C][C]10[/C][C]7.12416[/C][C]2.87584[/C][/ROW]
[ROW][C]171[/C][C]10.5[/C][C]9.57829[/C][C]0.921713[/C][/ROW]
[ROW][C]172[/C][C]6.5[/C][C]3.26495[/C][C]3.23505[/C][/ROW]
[ROW][C]173[/C][C]9.5[/C][C]8.232[/C][C]1.268[/C][/ROW]
[ROW][C]174[/C][C]8.5[/C][C]8.27208[/C][C]0.227921[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]8.59156[/C][C]-1.09156[/C][/ROW]
[ROW][C]176[/C][C]5[/C][C]3.40164[/C][C]1.59836[/C][/ROW]
[ROW][C]177[/C][C]8[/C][C]4.25963[/C][C]3.74037[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]9.71549[/C][C]0.284509[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]6.51459[/C][C]0.485411[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]6.9261[/C][C]0.573904[/C][/ROW]
[ROW][C]181[/C][C]7.5[/C][C]3.65157[/C][C]3.84843[/C][/ROW]
[ROW][C]182[/C][C]9.5[/C][C]10.0405[/C][C]-0.540501[/C][/ROW]
[ROW][C]183[/C][C]6[/C][C]1.09284[/C][C]4.90716[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]8.94164[/C][C]1.05836[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]9.68743[/C][C]-2.68743[/C][/ROW]
[ROW][C]186[/C][C]3[/C][C]3.54381[/C][C]-0.54381[/C][/ROW]
[ROW][C]187[/C][C]6[/C][C]5.17364[/C][C]0.826362[/C][/ROW]
[ROW][C]188[/C][C]7[/C][C]4.31101[/C][C]2.68899[/C][/ROW]
[ROW][C]189[/C][C]10[/C][C]8.47651[/C][C]1.52349[/C][/ROW]
[ROW][C]190[/C][C]7[/C][C]9.41299[/C][C]-2.41299[/C][/ROW]
[ROW][C]191[/C][C]3.5[/C][C]2.39348[/C][C]1.10652[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]4.57047[/C][C]3.42953[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.8624[/C][C]-0.862395[/C][/ROW]
[ROW][C]194[/C][C]5.5[/C][C]5.80324[/C][C]-0.303239[/C][/ROW]
[ROW][C]195[/C][C]6[/C][C]4.48588[/C][C]1.51412[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]6.6701[/C][C]-0.170097[/C][/ROW]
[ROW][C]197[/C][C]6.5[/C][C]3.55775[/C][C]2.94225[/C][/ROW]
[ROW][C]198[/C][C]8.5[/C][C]11.4943[/C][C]-2.99425[/C][/ROW]
[ROW][C]199[/C][C]4[/C][C]-0.0130655[/C][C]4.01307[/C][/ROW]
[ROW][C]200[/C][C]9.5[/C][C]8.0641[/C][C]1.4359[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]7.08519[/C][C]0.914808[/C][/ROW]
[ROW][C]202[/C][C]8.5[/C][C]8.80992[/C][C]-0.309917[/C][/ROW]
[ROW][C]203[/C][C]5.5[/C][C]3.54494[/C][C]1.95506[/C][/ROW]
[ROW][C]204[/C][C]7[/C][C]3.66014[/C][C]3.33986[/C][/ROW]
[ROW][C]205[/C][C]9[/C][C]6.84352[/C][C]2.15648[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]5.44657[/C][C]2.55343[/C][/ROW]
[ROW][C]207[/C][C]10[/C][C]8.80034[/C][C]1.19966[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]7.59807[/C][C]0.401928[/C][/ROW]
[ROW][C]209[/C][C]6[/C][C]4.23383[/C][C]1.76617[/C][/ROW]
[ROW][C]210[/C][C]8[/C][C]8.56622[/C][C]-0.566219[/C][/ROW]
[ROW][C]211[/C][C]5[/C][C]2.9999[/C][C]2.0001[/C][/ROW]
[ROW][C]212[/C][C]9[/C][C]10.1602[/C][C]-1.16023[/C][/ROW]
[ROW][C]213[/C][C]4.5[/C][C]3.37914[/C][C]1.12086[/C][/ROW]
[ROW][C]214[/C][C]8.5[/C][C]7.74847[/C][C]0.751529[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]2.3907[/C][C]4.6093[/C][/ROW]
[ROW][C]216[/C][C]9.5[/C][C]7.07446[/C][C]2.42554[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]7.66536[/C][C]0.834645[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]6.16558[/C][C]1.33442[/C][/ROW]
[ROW][C]219[/C][C]7.5[/C][C]7.43809[/C][C]0.0619108[/C][/ROW]
[ROW][C]220[/C][C]5[/C][C]2.90391[/C][C]2.09609[/C][/ROW]
[ROW][C]221[/C][C]7[/C][C]4.97295[/C][C]2.02705[/C][/ROW]
[ROW][C]222[/C][C]8[/C][C]7.72334[/C][C]0.276657[/C][/ROW]
[ROW][C]223[/C][C]5.5[/C][C]3.37549[/C][C]2.12451[/C][/ROW]
[ROW][C]224[/C][C]8.5[/C][C]8.67916[/C][C]-0.179159[/C][/ROW]
[ROW][C]225[/C][C]7.5[/C][C]4.50235[/C][C]2.99765[/C][/ROW]
[ROW][C]226[/C][C]9.5[/C][C]8.73497[/C][C]0.765025[/C][/ROW]
[ROW][C]227[/C][C]7[/C][C]5.52881[/C][C]1.47119[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]4.30335[/C][C]3.69665[/C][/ROW]
[ROW][C]229[/C][C]8.5[/C][C]9.91001[/C][C]-1.41001[/C][/ROW]
[ROW][C]230[/C][C]3.5[/C][C]3.69785[/C][C]-0.197847[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]5.46252[/C][C]1.03748[/C][/ROW]
[ROW][C]232[/C][C]6.5[/C][C]2.56492[/C][C]3.93508[/C][/ROW]
[ROW][C]233[/C][C]10.5[/C][C]8.29272[/C][C]2.20728[/C][/ROW]
[ROW][C]234[/C][C]8.5[/C][C]6.91135[/C][C]1.58865[/C][/ROW]
[ROW][C]235[/C][C]8[/C][C]4.64853[/C][C]3.35147[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]6.31035[/C][C]3.68965[/C][/ROW]
[ROW][C]237[/C][C]10[/C][C]6.86137[/C][C]3.13863[/C][/ROW]
[ROW][C]238[/C][C]9.5[/C][C]5.84369[/C][C]3.65631[/C][/ROW]
[ROW][C]239[/C][C]9[/C][C]5.93507[/C][C]3.06493[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]8.55577[/C][C]1.44423[/C][/ROW]
[ROW][C]241[/C][C]7.5[/C][C]9.30131[/C][C]-1.80131[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]5.29775[/C][C]-0.797755[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]10.9671[/C][C]-6.46706[/C][/ROW]
[ROW][C]244[/C][C]0.5[/C][C]-0.454116[/C][C]0.954116[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]7.41868[/C][C]-0.918679[/C][/ROW]
[ROW][C]246[/C][C]4.5[/C][C]5.13842[/C][C]-0.638423[/C][/ROW]
[ROW][C]247[/C][C]5.5[/C][C]5.96583[/C][C]-0.465829[/C][/ROW]
[ROW][C]248[/C][C]5[/C][C]5.76945[/C][C]-0.769449[/C][/ROW]
[ROW][C]249[/C][C]6[/C][C]6.25366[/C][C]-0.253656[/C][/ROW]
[ROW][C]250[/C][C]4[/C][C]2.56004[/C][C]1.43996[/C][/ROW]
[ROW][C]251[/C][C]8[/C][C]4.58065[/C][C]3.41935[/C][/ROW]
[ROW][C]252[/C][C]10.5[/C][C]9.36199[/C][C]1.13801[/C][/ROW]
[ROW][C]253[/C][C]8.5[/C][C]8.70841[/C][C]-0.208412[/C][/ROW]
[ROW][C]254[/C][C]6.5[/C][C]4.02498[/C][C]2.47502[/C][/ROW]
[ROW][C]255[/C][C]8[/C][C]5.53536[/C][C]2.46464[/C][/ROW]
[ROW][C]256[/C][C]8.5[/C][C]9.4754[/C][C]-0.975404[/C][/ROW]
[ROW][C]257[/C][C]5.5[/C][C]4.00217[/C][C]1.49783[/C][/ROW]
[ROW][C]258[/C][C]7[/C][C]8.11221[/C][C]-1.11221[/C][/ROW]
[ROW][C]259[/C][C]5[/C][C]6.68133[/C][C]-1.68133[/C][/ROW]
[ROW][C]260[/C][C]3.5[/C][C]4.73001[/C][C]-1.23001[/C][/ROW]
[ROW][C]261[/C][C]5[/C][C]2.68954[/C][C]2.31046[/C][/ROW]
[ROW][C]262[/C][C]9[/C][C]5.18895[/C][C]3.81105[/C][/ROW]
[ROW][C]263[/C][C]8.5[/C][C]9.60834[/C][C]-1.10834[/C][/ROW]
[ROW][C]264[/C][C]5[/C][C]2.38089[/C][C]2.61911[/C][/ROW]
[ROW][C]265[/C][C]9.5[/C][C]12.3257[/C][C]-2.82566[/C][/ROW]
[ROW][C]266[/C][C]3[/C][C]7.14074[/C][C]-4.14074[/C][/ROW]
[ROW][C]267[/C][C]1.5[/C][C]1.01531[/C][C]0.484687[/C][/ROW]
[ROW][C]268[/C][C]6[/C][C]11.2242[/C][C]-5.22421[/C][/ROW]
[ROW][C]269[/C][C]0.5[/C][C]0.969275[/C][C]-0.469275[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]5.33415[/C][C]1.16585[/C][/ROW]
[ROW][C]271[/C][C]7.5[/C][C]8.56268[/C][C]-1.06268[/C][/ROW]
[ROW][C]272[/C][C]4.5[/C][C]3.27673[/C][C]1.22327[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]5.83394[/C][C]2.16606[/C][/ROW]
[ROW][C]274[/C][C]9[/C][C]8.55564[/C][C]0.444358[/C][/ROW]
[ROW][C]275[/C][C]7.5[/C][C]6.43316[/C][C]1.06684[/C][/ROW]
[ROW][C]276[/C][C]8.5[/C][C]6.19309[/C][C]2.30691[/C][/ROW]
[ROW][C]277[/C][C]7[/C][C]4.32294[/C][C]2.67706[/C][/ROW]
[ROW][C]278[/C][C]9.5[/C][C]9.73909[/C][C]-0.239094[/C][/ROW]
[ROW][C]279[/C][C]6.5[/C][C]2.11097[/C][C]4.38903[/C][/ROW]
[ROW][C]280[/C][C]9.5[/C][C]9.35411[/C][C]0.145894[/C][/ROW]
[ROW][C]281[/C][C]6[/C][C]3.11143[/C][C]2.88857[/C][/ROW]
[ROW][C]282[/C][C]8[/C][C]4.98236[/C][C]3.01764[/C][/ROW]
[ROW][C]283[/C][C]9.5[/C][C]7.87452[/C][C]1.62548[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.87976[/C][C]1.12024[/C][/ROW]
[ROW][C]285[/C][C]8[/C][C]4.94751[/C][C]3.05249[/C][/ROW]
[ROW][C]286[/C][C]9[/C][C]10.0567[/C][C]-1.05671[/C][/ROW]
[ROW][C]287[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=4

As an alternative you can also use a QR Code:  
QR Code


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.730050.769945
22.55.87293-3.37293
365.942840.05716
46.56.83527-0.335269
515.65155-4.65155
615.61743-4.61743
75.54.652720.847279
88.56.230272.26973
96.57.11854-0.618544
104.55.08923-0.589234
1127.5231-5.5231
1256.14946-1.14946
130.55.98109-5.48109
1454.837950.162048
1555.91546-0.91546
162.55.67472-3.17472
1755.7235-0.723497
185.55.88531-0.385311
193.55.41717-1.91717
2036.12096-3.12096
2144.85223-0.852225
220.56.25389-5.75389
236.56.180660.319337
244.55.60695-1.10695
257.55.711251.78875
265.56.76912-1.26912
2745.47409-1.47409
287.55.881851.61815
2976.742490.25751
3046.9535-2.9535
315.56.06528-0.565277
322.54.52534-2.02534
335.55.78107-0.281071
340.55.47829-4.97829
353.56.10047-2.60047
362.57.0264-4.5264
374.56.36533-1.86533
384.57.24818-2.74818
394.55.94714-1.44714
4065.914880.0851207
412.56.9587-4.4587
4255.92097-0.920971
4307.0322-7.0322
4456.98306-1.98306
456.56.035250.46475
4656.54339-1.54339
4766.06008-0.0600813
484.56.70712-2.20712
495.55.380510.119486
5015.44995-4.44995
517.54.618642.88136
5266.49356-0.493557
5356.09407-1.09407
5415.94185-4.94185
5556.68689-1.68689
566.55.250091.24991
5776.438660.561337
584.56.80499-2.30499
5905.66634-5.66634
608.55.092913.40709
613.56.01076-2.51076
627.56.381211.11879
633.56.92446-3.42446
6465.125820.874182
651.56.11846-4.61846
6696.739342.26066
673.55.58214-2.08214
683.57.15217-3.65217
6945.88939-1.88939
706.56.63202-0.132018
717.57.100090.399908
7265.598030.40197
7356.09134-1.09134
745.56.60339-1.10339
753.56.21984-2.71984
767.56.892430.607572
7716.0875-5.0875
786.55.04131.4587
79NANA1.39897
806.56.89819-0.39819
816.55.709430.790569
8278.61231-1.61231
833.57.10517-3.60517
841.53.33847-1.83847
8541.798562.20144
867.58.87061-1.37061
874.510.1933-5.69327
8802.75202-2.75202
893.54.0621-0.562102
905.56.84458-1.34458
9156.65321-1.65321
924.58.44496-3.94496
932.5-0.1105262.61053
947.57.009090.490905
95712.8327-5.8327
9600.78393-0.78393
974.56.90315-2.40315
9836.82982-3.82982
991.52.87619-1.37619
1003.56.77497-3.27497
1012.53.62278-1.12278
1025.53.450742.04926
103813.148-5.14796
10412.13631-1.13631
10556.87794-1.87794
1064.56.5946-2.0946
10735.56324-2.56324
10830.4118392.58816
109810.8491-2.84906
1102.51.481171.01883
111713.4633-6.46331
11205.22036-5.22036
11313.1974-2.1974
1143.54.18256-0.682557
1155.56.477-0.977002
1165.511.2926-5.79261
1170.5-0.7023681.20237
1187.54.393173.10683
11996.237692.76231
1209.58.533450.966553
1218.57.815210.684794
12276.254750.745251
12384.877833.12217
124109.019560.980442
12574.358872.64113
1268.56.682331.81767
12795.947973.05203
1289.511.5413-2.04126
12942.992471.00753
13063.207392.79261
13188.40005-0.400046
1325.52.088623.41138
1339.58.745070.754931
1347.57.72626-0.226264
13575.292681.70732
1367.55.879271.62073
13786.837351.16265
13877.14513-0.145127
13977.34629-0.346292
14062.718653.28135
1411014.2068-4.20677
1422.5-0.402782.90278
14398.443730.556269
14488.61375-0.613746
14563.391322.60868
1468.57.296861.20314
14762.618483.38152
14896.963092.03691
14985.703682.29632
15086.081871.91813
15199.94086-0.94086
1525.56.52988-1.02988
15354.158050.841947
15477.22269-0.222693
1555.53.910061.58994
156912.0687-3.06874
15720.5587511.44125
1588.56.280282.21972
15995.94063.0594
1608.56.599031.90097
16197.913881.08612
1627.55.133942.36606
163107.280962.71904
16498.281680.71832
1657.58.44752-0.947525
16662.271233.72877
16710.58.689551.81045
1688.58.254880.245125
16985.340182.65982
170107.124162.87584
17110.59.578290.921713
1726.53.264953.23505
1739.58.2321.268
1748.58.272080.227921
1757.58.59156-1.09156
17653.401641.59836
17784.259633.74037
178109.715490.284509
17976.514590.485411
1807.56.92610.573904
1817.53.651573.84843
1829.510.0405-0.540501
18361.092844.90716
184108.941641.05836
18579.68743-2.68743
18633.54381-0.54381
18765.173640.826362
18874.311012.68899
189108.476511.52349
19079.41299-2.41299
1913.52.393481.10652
19284.570473.42953
1931010.8624-0.862395
1945.55.80324-0.303239
19564.485881.51412
1966.56.6701-0.170097
1976.53.557752.94225
1988.511.4943-2.99425
1994-0.01306554.01307
2009.58.06411.4359
20187.085190.914808
2028.58.80992-0.309917
2035.53.544941.95506
20473.660143.33986
20596.843522.15648
20685.446572.55343
207108.800341.19966
20887.598070.401928
20964.233831.76617
21088.56622-0.566219
21152.99992.0001
212910.1602-1.16023
2134.53.379141.12086
2148.57.748470.751529
21572.39074.6093
2169.57.074462.42554
2178.57.665360.834645
2187.56.165581.33442
2197.57.438090.0619108
22052.903912.09609
22174.972952.02705
22287.723340.276657
2235.53.375492.12451
2248.58.67916-0.179159
2257.54.502352.99765
2269.58.734970.765025
22775.528811.47119
22884.303353.69665
2298.59.91001-1.41001
2303.53.69785-0.197847
2316.55.462521.03748
2326.52.564923.93508
23310.58.292722.20728
2348.56.911351.58865
23584.648533.35147
236106.310353.68965
237106.861373.13863
2389.55.843693.65631
23995.935073.06493
240108.555771.44423
2417.59.30131-1.80131
2424.55.29775-0.797755
2434.510.9671-6.46706
2440.5-0.4541160.954116
2456.57.41868-0.918679
2464.55.13842-0.638423
2475.55.96583-0.465829
24855.76945-0.769449
24966.25366-0.253656
25042.560041.43996
25184.580653.41935
25210.59.361991.13801
2538.58.70841-0.208412
2546.54.024982.47502
25585.535362.46464
2568.59.4754-0.975404
2575.54.002171.49783
25878.11221-1.11221
25956.68133-1.68133
2603.54.73001-1.23001
26152.689542.31046
26295.188953.81105
2638.59.60834-1.10834
26452.380892.61911
2659.512.3257-2.82566
26637.14074-4.14074
2671.51.015310.484687
268611.2242-5.22421
2690.50.969275-0.469275
2706.55.334151.16585
2717.58.56268-1.06268
2724.53.276731.22327
27385.833942.16606
27498.555640.444358
2757.56.433161.06684
2768.56.193092.30691
27774.322942.67706
2789.59.73909-0.239094
2796.52.110974.38903
2809.59.354110.145894
28163.111432.88857
28284.982363.01764
2839.57.874521.62548
28486.879761.12024
28584.947513.05249
286910.0567-1.05671
2875NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
170.214990.429980.78501
180.5498640.9002730.450136
190.4205670.8411330.579433
200.3221040.6442080.677896
210.3370220.6740450.662978
220.3129240.6258480.687076
230.2449580.4899160.755042
240.1738170.3476350.826183
250.2018670.4037350.798133
260.1714740.3429490.828526
270.1216850.2433710.878315
280.08317350.1663470.916826
290.06877480.137550.931225
300.04660220.09320440.953398
310.03147640.06295270.968524
320.02351820.04703640.976482
330.01642630.03285260.983574
340.01132330.02264650.988677
350.01208530.02417060.987915
360.3176670.6353340.682333
370.2750880.5501760.724912
380.2326020.4652050.767398
390.1973540.3947090.802646
400.1584130.3168260.841587
410.1666190.3332380.833381
420.132680.265360.86732
430.2317630.4635250.768237
440.2060390.4120770.793961
450.2087920.4175850.791208
460.2020180.4040350.797982
470.1656420.3312830.834358
480.141990.2839790.85801
490.1256860.2513730.874314
500.1435660.2871320.856434
510.17290.34580.8271
520.1784330.3568650.821567
530.1542070.3084140.845793
540.2075040.4150080.792496
550.1788810.3577630.821119
560.2301310.4602630.769869
570.2684340.5368680.731566
580.2432820.4865640.756718
590.3638770.7277540.636123
600.3850030.7700070.614997
610.3542780.7085560.645722
620.3784690.7569390.621531
630.3659610.7319210.634039
640.3333030.6666050.666697
650.3996960.7993920.600304
660.4693420.9386830.530658
670.448580.897160.55142
680.4410030.8820060.558997
690.412150.82430.58785
700.4059950.8119890.594005
710.4343960.8687920.565604
720.4038430.8076850.596157
730.3667860.7335720.633214
740.3337060.6674120.666294
750.3202460.6404930.679754
760.346270.692540.65373
770.4315510.8631030.568449
780.3950110.7900220.604989
790.3621320.7242630.637868
800.3311080.6622170.668892
810.324160.6483210.67584
820.3010550.6021090.698945
830.321610.643220.67839
840.2981180.5962360.701882
850.3028670.6057350.697133
860.2827770.5655530.717223
870.389220.7784410.61078
880.3718490.7436990.628151
890.3406020.6812030.659398
900.3126350.625270.687365
910.2970560.5941120.702944
920.3267150.653430.673285
930.3827630.7655260.617237
940.3878040.7756070.612196
950.5235140.9529730.476486
960.4881610.9763220.511839
970.4797870.9595730.520213
980.5152690.9694630.484731
990.4926680.9853360.507332
1000.5183650.9632690.481635
1010.4929890.9859770.507011
1020.517070.965860.48293
1030.6011620.7976750.398838
1040.581240.8375210.41876
1050.5750860.8498270.424914
1060.6069440.7861120.393056
1070.6026840.7946330.397316
1080.6197350.7605290.380265
1090.6348790.7302420.365121
1100.6618250.676350.338175
1110.8213830.3572350.178617
1120.9000630.1998740.0999371
1130.8960320.2079360.103968
1140.8883260.2233480.111674
1150.8873160.2253690.112684
1160.9504250.09915070.0495753
1170.9650020.06999580.0349979
1180.9761980.04760360.0238018
1190.9834610.03307810.016539
1200.9859990.02800110.0140006
1210.9854530.02909390.0145469
1220.9861150.02776950.0138848
1230.9900770.0198460.009923
1240.9889610.0220780.011039
1250.9916480.01670490.00835247
1260.9931480.01370490.00685246
1270.9953910.009218530.00460927
1280.9960340.007931440.00396572
1290.9952560.009487790.00474389
1300.9954270.009146020.00457301
1310.9943490.01130170.00565083
1320.995790.008420640.00421032
1330.9954230.009153580.00457679
1340.9947760.01044750.00522374
1350.9939980.01200340.00600172
1360.993440.01311960.00655979
1370.993980.01204080.00602039
1380.9926440.0147120.00735599
1390.9919160.01616860.00808432
1400.9937410.01251730.00625867
1410.9968630.006274830.00313741
1420.9973820.005236550.00261828
1430.9967750.00644940.0032247
1440.9961350.007730720.00386536
1450.9960280.007943230.00397162
1460.9953080.009383070.00469153
1470.9960060.007988170.00399409
1480.9956020.008796710.00439836
1490.9953990.009201390.00460069
1500.9949870.01002590.00501294
1510.9939260.01214890.00607443
1520.9930530.01389310.00694655
1530.9913910.01721820.00860909
1540.9901770.01964550.00982273
1550.9890860.02182840.0109142
1560.9917580.01648440.00824219
1570.9903080.01938470.00969237
1580.9904780.01904340.00952171
1590.9909780.01804450.00902223
1600.990260.019480.00974001
1610.9882680.02346370.0117319
1620.988290.02341930.0117097
1630.9889630.02207430.0110372
1640.9869040.02619220.0130961
1650.9860330.02793320.0139666
1660.9896070.02078690.0103935
1670.9887470.02250640.0112532
1680.9867550.02648980.0132449
1690.9865580.02688460.0134423
1700.9875870.02482690.0124135
1710.9849030.03019390.0150969
1720.9870040.02599150.0129958
1730.9840390.03192110.0159605
1740.9803680.03926450.0196323
1750.9794540.0410920.020546
1760.9764470.04710560.0235528
1770.9827030.03459450.0172972
1780.9787670.04246610.021233
1790.9739040.05219110.0260955
1800.9678930.06421360.0321068
1810.9739630.05207420.0260371
1820.9682530.06349490.0317474
1830.9832440.03351220.0167561
1840.9795590.04088130.0204407
1850.9843230.03135360.0156768
1860.9805390.03892140.0194607
1870.9761310.04773780.0238689
1880.9754380.04912360.0245618
1890.9714080.05718430.0285921
1900.9735010.05299830.0264991
1910.9681110.06377830.0318891
1920.9716880.05662410.028312
1930.9679560.0640880.032044
1940.9635130.0729730.0364865
1950.9578310.08433850.0421693
1960.9491190.1017620.0508811
1970.9493260.1013480.050674
1980.9700470.05990630.0299531
1990.975650.0486990.0243495
2000.9710690.05786160.0289308
2010.9640420.07191660.0359583
2020.9552360.08952760.0447638
2030.94910.1017990.0508997
2040.9492260.1015480.050774
2050.9428680.1142630.0571316
2060.9511460.09770730.0488536
2070.9464090.1071820.0535908
2080.9342060.1315890.0657944
2090.9253950.1492090.0746047
2100.9236390.1527230.0763615
2110.9153530.1692940.0846471
2120.9076330.1847330.0923666
2130.8927190.2145610.107281
2140.8732140.2535710.126786
2150.8794070.2411860.120593
2160.8643740.2712530.135626
2170.8398310.3203380.160169
2180.8202620.3594760.179738
2190.7953440.4093120.204656
2200.7822870.4354260.217713
2210.7571360.4857270.242864
2220.7208620.5582770.279138
2230.7003520.5992950.299648
2240.6596060.6807890.340394
2250.650740.698520.34926
2260.6079390.7841220.392061
2270.5781070.8437870.421893
2280.601860.7962810.39814
2290.6156950.7686090.384305
2300.5722020.8555970.427798
2310.5306590.9386820.469341
2320.5188270.9623460.481173
2330.4930230.9860460.506977
2340.450590.901180.54941
2350.4289240.8578470.571076
2360.4587680.9175360.541232
2370.4600250.9200490.539975
2380.5124970.9750060.487503
2390.5529710.8940590.447029
2400.5054450.9891090.494555
2410.4968450.9936910.503155
2420.4438330.8876660.556167
2430.847050.30590.15295
2440.8139710.3720570.186029
2450.7720840.4558330.227916
2460.724360.551280.27564
2470.6828380.6343250.317162
2480.6300090.7399810.369991
2490.5707050.8585910.429295
2500.5101410.9797170.489859
2510.5352790.9294430.464721
2520.4817270.9634540.518273
2530.4251560.8503130.574844
2540.3947890.7895790.605211
2550.3441910.6883810.655809
2560.308450.61690.69155
2570.2883080.5766160.711692
2580.2345430.4690870.765457
2590.1837260.3674520.816274
2600.1645350.329070.835465
2610.1225810.2451610.877419
2620.1669640.3339280.833036
2630.1409490.2818990.859051
2640.1097110.2194210.890289
2650.3206830.6413660.679317
2660.9335220.1329560.0664779
2670.8756330.2487340.124367
2680.965470.06906030.0345302
2690.9060750.1878490.0939246
2700.7575370.4849260.242463

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.21499 & 0.42998 & 0.78501 \tabularnewline
18 & 0.549864 & 0.900273 & 0.450136 \tabularnewline
19 & 0.420567 & 0.841133 & 0.579433 \tabularnewline
20 & 0.322104 & 0.644208 & 0.677896 \tabularnewline
21 & 0.337022 & 0.674045 & 0.662978 \tabularnewline
22 & 0.312924 & 0.625848 & 0.687076 \tabularnewline
23 & 0.244958 & 0.489916 & 0.755042 \tabularnewline
24 & 0.173817 & 0.347635 & 0.826183 \tabularnewline
25 & 0.201867 & 0.403735 & 0.798133 \tabularnewline
26 & 0.171474 & 0.342949 & 0.828526 \tabularnewline
27 & 0.121685 & 0.243371 & 0.878315 \tabularnewline
28 & 0.0831735 & 0.166347 & 0.916826 \tabularnewline
29 & 0.0687748 & 0.13755 & 0.931225 \tabularnewline
30 & 0.0466022 & 0.0932044 & 0.953398 \tabularnewline
31 & 0.0314764 & 0.0629527 & 0.968524 \tabularnewline
32 & 0.0235182 & 0.0470364 & 0.976482 \tabularnewline
33 & 0.0164263 & 0.0328526 & 0.983574 \tabularnewline
34 & 0.0113233 & 0.0226465 & 0.988677 \tabularnewline
35 & 0.0120853 & 0.0241706 & 0.987915 \tabularnewline
36 & 0.317667 & 0.635334 & 0.682333 \tabularnewline
37 & 0.275088 & 0.550176 & 0.724912 \tabularnewline
38 & 0.232602 & 0.465205 & 0.767398 \tabularnewline
39 & 0.197354 & 0.394709 & 0.802646 \tabularnewline
40 & 0.158413 & 0.316826 & 0.841587 \tabularnewline
41 & 0.166619 & 0.333238 & 0.833381 \tabularnewline
42 & 0.13268 & 0.26536 & 0.86732 \tabularnewline
43 & 0.231763 & 0.463525 & 0.768237 \tabularnewline
44 & 0.206039 & 0.412077 & 0.793961 \tabularnewline
45 & 0.208792 & 0.417585 & 0.791208 \tabularnewline
46 & 0.202018 & 0.404035 & 0.797982 \tabularnewline
47 & 0.165642 & 0.331283 & 0.834358 \tabularnewline
48 & 0.14199 & 0.283979 & 0.85801 \tabularnewline
49 & 0.125686 & 0.251373 & 0.874314 \tabularnewline
50 & 0.143566 & 0.287132 & 0.856434 \tabularnewline
51 & 0.1729 & 0.3458 & 0.8271 \tabularnewline
52 & 0.178433 & 0.356865 & 0.821567 \tabularnewline
53 & 0.154207 & 0.308414 & 0.845793 \tabularnewline
54 & 0.207504 & 0.415008 & 0.792496 \tabularnewline
55 & 0.178881 & 0.357763 & 0.821119 \tabularnewline
56 & 0.230131 & 0.460263 & 0.769869 \tabularnewline
57 & 0.268434 & 0.536868 & 0.731566 \tabularnewline
58 & 0.243282 & 0.486564 & 0.756718 \tabularnewline
59 & 0.363877 & 0.727754 & 0.636123 \tabularnewline
60 & 0.385003 & 0.770007 & 0.614997 \tabularnewline
61 & 0.354278 & 0.708556 & 0.645722 \tabularnewline
62 & 0.378469 & 0.756939 & 0.621531 \tabularnewline
63 & 0.365961 & 0.731921 & 0.634039 \tabularnewline
64 & 0.333303 & 0.666605 & 0.666697 \tabularnewline
65 & 0.399696 & 0.799392 & 0.600304 \tabularnewline
66 & 0.469342 & 0.938683 & 0.530658 \tabularnewline
67 & 0.44858 & 0.89716 & 0.55142 \tabularnewline
68 & 0.441003 & 0.882006 & 0.558997 \tabularnewline
69 & 0.41215 & 0.8243 & 0.58785 \tabularnewline
70 & 0.405995 & 0.811989 & 0.594005 \tabularnewline
71 & 0.434396 & 0.868792 & 0.565604 \tabularnewline
72 & 0.403843 & 0.807685 & 0.596157 \tabularnewline
73 & 0.366786 & 0.733572 & 0.633214 \tabularnewline
74 & 0.333706 & 0.667412 & 0.666294 \tabularnewline
75 & 0.320246 & 0.640493 & 0.679754 \tabularnewline
76 & 0.34627 & 0.69254 & 0.65373 \tabularnewline
77 & 0.431551 & 0.863103 & 0.568449 \tabularnewline
78 & 0.395011 & 0.790022 & 0.604989 \tabularnewline
79 & 0.362132 & 0.724263 & 0.637868 \tabularnewline
80 & 0.331108 & 0.662217 & 0.668892 \tabularnewline
81 & 0.32416 & 0.648321 & 0.67584 \tabularnewline
82 & 0.301055 & 0.602109 & 0.698945 \tabularnewline
83 & 0.32161 & 0.64322 & 0.67839 \tabularnewline
84 & 0.298118 & 0.596236 & 0.701882 \tabularnewline
85 & 0.302867 & 0.605735 & 0.697133 \tabularnewline
86 & 0.282777 & 0.565553 & 0.717223 \tabularnewline
87 & 0.38922 & 0.778441 & 0.61078 \tabularnewline
88 & 0.371849 & 0.743699 & 0.628151 \tabularnewline
89 & 0.340602 & 0.681203 & 0.659398 \tabularnewline
90 & 0.312635 & 0.62527 & 0.687365 \tabularnewline
91 & 0.297056 & 0.594112 & 0.702944 \tabularnewline
92 & 0.326715 & 0.65343 & 0.673285 \tabularnewline
93 & 0.382763 & 0.765526 & 0.617237 \tabularnewline
94 & 0.387804 & 0.775607 & 0.612196 \tabularnewline
95 & 0.523514 & 0.952973 & 0.476486 \tabularnewline
96 & 0.488161 & 0.976322 & 0.511839 \tabularnewline
97 & 0.479787 & 0.959573 & 0.520213 \tabularnewline
98 & 0.515269 & 0.969463 & 0.484731 \tabularnewline
99 & 0.492668 & 0.985336 & 0.507332 \tabularnewline
100 & 0.518365 & 0.963269 & 0.481635 \tabularnewline
101 & 0.492989 & 0.985977 & 0.507011 \tabularnewline
102 & 0.51707 & 0.96586 & 0.48293 \tabularnewline
103 & 0.601162 & 0.797675 & 0.398838 \tabularnewline
104 & 0.58124 & 0.837521 & 0.41876 \tabularnewline
105 & 0.575086 & 0.849827 & 0.424914 \tabularnewline
106 & 0.606944 & 0.786112 & 0.393056 \tabularnewline
107 & 0.602684 & 0.794633 & 0.397316 \tabularnewline
108 & 0.619735 & 0.760529 & 0.380265 \tabularnewline
109 & 0.634879 & 0.730242 & 0.365121 \tabularnewline
110 & 0.661825 & 0.67635 & 0.338175 \tabularnewline
111 & 0.821383 & 0.357235 & 0.178617 \tabularnewline
112 & 0.900063 & 0.199874 & 0.0999371 \tabularnewline
113 & 0.896032 & 0.207936 & 0.103968 \tabularnewline
114 & 0.888326 & 0.223348 & 0.111674 \tabularnewline
115 & 0.887316 & 0.225369 & 0.112684 \tabularnewline
116 & 0.950425 & 0.0991507 & 0.0495753 \tabularnewline
117 & 0.965002 & 0.0699958 & 0.0349979 \tabularnewline
118 & 0.976198 & 0.0476036 & 0.0238018 \tabularnewline
119 & 0.983461 & 0.0330781 & 0.016539 \tabularnewline
120 & 0.985999 & 0.0280011 & 0.0140006 \tabularnewline
121 & 0.985453 & 0.0290939 & 0.0145469 \tabularnewline
122 & 0.986115 & 0.0277695 & 0.0138848 \tabularnewline
123 & 0.990077 & 0.019846 & 0.009923 \tabularnewline
124 & 0.988961 & 0.022078 & 0.011039 \tabularnewline
125 & 0.991648 & 0.0167049 & 0.00835247 \tabularnewline
126 & 0.993148 & 0.0137049 & 0.00685246 \tabularnewline
127 & 0.995391 & 0.00921853 & 0.00460927 \tabularnewline
128 & 0.996034 & 0.00793144 & 0.00396572 \tabularnewline
129 & 0.995256 & 0.00948779 & 0.00474389 \tabularnewline
130 & 0.995427 & 0.00914602 & 0.00457301 \tabularnewline
131 & 0.994349 & 0.0113017 & 0.00565083 \tabularnewline
132 & 0.99579 & 0.00842064 & 0.00421032 \tabularnewline
133 & 0.995423 & 0.00915358 & 0.00457679 \tabularnewline
134 & 0.994776 & 0.0104475 & 0.00522374 \tabularnewline
135 & 0.993998 & 0.0120034 & 0.00600172 \tabularnewline
136 & 0.99344 & 0.0131196 & 0.00655979 \tabularnewline
137 & 0.99398 & 0.0120408 & 0.00602039 \tabularnewline
138 & 0.992644 & 0.014712 & 0.00735599 \tabularnewline
139 & 0.991916 & 0.0161686 & 0.00808432 \tabularnewline
140 & 0.993741 & 0.0125173 & 0.00625867 \tabularnewline
141 & 0.996863 & 0.00627483 & 0.00313741 \tabularnewline
142 & 0.997382 & 0.00523655 & 0.00261828 \tabularnewline
143 & 0.996775 & 0.0064494 & 0.0032247 \tabularnewline
144 & 0.996135 & 0.00773072 & 0.00386536 \tabularnewline
145 & 0.996028 & 0.00794323 & 0.00397162 \tabularnewline
146 & 0.995308 & 0.00938307 & 0.00469153 \tabularnewline
147 & 0.996006 & 0.00798817 & 0.00399409 \tabularnewline
148 & 0.995602 & 0.00879671 & 0.00439836 \tabularnewline
149 & 0.995399 & 0.00920139 & 0.00460069 \tabularnewline
150 & 0.994987 & 0.0100259 & 0.00501294 \tabularnewline
151 & 0.993926 & 0.0121489 & 0.00607443 \tabularnewline
152 & 0.993053 & 0.0138931 & 0.00694655 \tabularnewline
153 & 0.991391 & 0.0172182 & 0.00860909 \tabularnewline
154 & 0.990177 & 0.0196455 & 0.00982273 \tabularnewline
155 & 0.989086 & 0.0218284 & 0.0109142 \tabularnewline
156 & 0.991758 & 0.0164844 & 0.00824219 \tabularnewline
157 & 0.990308 & 0.0193847 & 0.00969237 \tabularnewline
158 & 0.990478 & 0.0190434 & 0.00952171 \tabularnewline
159 & 0.990978 & 0.0180445 & 0.00902223 \tabularnewline
160 & 0.99026 & 0.01948 & 0.00974001 \tabularnewline
161 & 0.988268 & 0.0234637 & 0.0117319 \tabularnewline
162 & 0.98829 & 0.0234193 & 0.0117097 \tabularnewline
163 & 0.988963 & 0.0220743 & 0.0110372 \tabularnewline
164 & 0.986904 & 0.0261922 & 0.0130961 \tabularnewline
165 & 0.986033 & 0.0279332 & 0.0139666 \tabularnewline
166 & 0.989607 & 0.0207869 & 0.0103935 \tabularnewline
167 & 0.988747 & 0.0225064 & 0.0112532 \tabularnewline
168 & 0.986755 & 0.0264898 & 0.0132449 \tabularnewline
169 & 0.986558 & 0.0268846 & 0.0134423 \tabularnewline
170 & 0.987587 & 0.0248269 & 0.0124135 \tabularnewline
171 & 0.984903 & 0.0301939 & 0.0150969 \tabularnewline
172 & 0.987004 & 0.0259915 & 0.0129958 \tabularnewline
173 & 0.984039 & 0.0319211 & 0.0159605 \tabularnewline
174 & 0.980368 & 0.0392645 & 0.0196323 \tabularnewline
175 & 0.979454 & 0.041092 & 0.020546 \tabularnewline
176 & 0.976447 & 0.0471056 & 0.0235528 \tabularnewline
177 & 0.982703 & 0.0345945 & 0.0172972 \tabularnewline
178 & 0.978767 & 0.0424661 & 0.021233 \tabularnewline
179 & 0.973904 & 0.0521911 & 0.0260955 \tabularnewline
180 & 0.967893 & 0.0642136 & 0.0321068 \tabularnewline
181 & 0.973963 & 0.0520742 & 0.0260371 \tabularnewline
182 & 0.968253 & 0.0634949 & 0.0317474 \tabularnewline
183 & 0.983244 & 0.0335122 & 0.0167561 \tabularnewline
184 & 0.979559 & 0.0408813 & 0.0204407 \tabularnewline
185 & 0.984323 & 0.0313536 & 0.0156768 \tabularnewline
186 & 0.980539 & 0.0389214 & 0.0194607 \tabularnewline
187 & 0.976131 & 0.0477378 & 0.0238689 \tabularnewline
188 & 0.975438 & 0.0491236 & 0.0245618 \tabularnewline
189 & 0.971408 & 0.0571843 & 0.0285921 \tabularnewline
190 & 0.973501 & 0.0529983 & 0.0264991 \tabularnewline
191 & 0.968111 & 0.0637783 & 0.0318891 \tabularnewline
192 & 0.971688 & 0.0566241 & 0.028312 \tabularnewline
193 & 0.967956 & 0.064088 & 0.032044 \tabularnewline
194 & 0.963513 & 0.072973 & 0.0364865 \tabularnewline
195 & 0.957831 & 0.0843385 & 0.0421693 \tabularnewline
196 & 0.949119 & 0.101762 & 0.0508811 \tabularnewline
197 & 0.949326 & 0.101348 & 0.050674 \tabularnewline
198 & 0.970047 & 0.0599063 & 0.0299531 \tabularnewline
199 & 0.97565 & 0.048699 & 0.0243495 \tabularnewline
200 & 0.971069 & 0.0578616 & 0.0289308 \tabularnewline
201 & 0.964042 & 0.0719166 & 0.0359583 \tabularnewline
202 & 0.955236 & 0.0895276 & 0.0447638 \tabularnewline
203 & 0.9491 & 0.101799 & 0.0508997 \tabularnewline
204 & 0.949226 & 0.101548 & 0.050774 \tabularnewline
205 & 0.942868 & 0.114263 & 0.0571316 \tabularnewline
206 & 0.951146 & 0.0977073 & 0.0488536 \tabularnewline
207 & 0.946409 & 0.107182 & 0.0535908 \tabularnewline
208 & 0.934206 & 0.131589 & 0.0657944 \tabularnewline
209 & 0.925395 & 0.149209 & 0.0746047 \tabularnewline
210 & 0.923639 & 0.152723 & 0.0763615 \tabularnewline
211 & 0.915353 & 0.169294 & 0.0846471 \tabularnewline
212 & 0.907633 & 0.184733 & 0.0923666 \tabularnewline
213 & 0.892719 & 0.214561 & 0.107281 \tabularnewline
214 & 0.873214 & 0.253571 & 0.126786 \tabularnewline
215 & 0.879407 & 0.241186 & 0.120593 \tabularnewline
216 & 0.864374 & 0.271253 & 0.135626 \tabularnewline
217 & 0.839831 & 0.320338 & 0.160169 \tabularnewline
218 & 0.820262 & 0.359476 & 0.179738 \tabularnewline
219 & 0.795344 & 0.409312 & 0.204656 \tabularnewline
220 & 0.782287 & 0.435426 & 0.217713 \tabularnewline
221 & 0.757136 & 0.485727 & 0.242864 \tabularnewline
222 & 0.720862 & 0.558277 & 0.279138 \tabularnewline
223 & 0.700352 & 0.599295 & 0.299648 \tabularnewline
224 & 0.659606 & 0.680789 & 0.340394 \tabularnewline
225 & 0.65074 & 0.69852 & 0.34926 \tabularnewline
226 & 0.607939 & 0.784122 & 0.392061 \tabularnewline
227 & 0.578107 & 0.843787 & 0.421893 \tabularnewline
228 & 0.60186 & 0.796281 & 0.39814 \tabularnewline
229 & 0.615695 & 0.768609 & 0.384305 \tabularnewline
230 & 0.572202 & 0.855597 & 0.427798 \tabularnewline
231 & 0.530659 & 0.938682 & 0.469341 \tabularnewline
232 & 0.518827 & 0.962346 & 0.481173 \tabularnewline
233 & 0.493023 & 0.986046 & 0.506977 \tabularnewline
234 & 0.45059 & 0.90118 & 0.54941 \tabularnewline
235 & 0.428924 & 0.857847 & 0.571076 \tabularnewline
236 & 0.458768 & 0.917536 & 0.541232 \tabularnewline
237 & 0.460025 & 0.920049 & 0.539975 \tabularnewline
238 & 0.512497 & 0.975006 & 0.487503 \tabularnewline
239 & 0.552971 & 0.894059 & 0.447029 \tabularnewline
240 & 0.505445 & 0.989109 & 0.494555 \tabularnewline
241 & 0.496845 & 0.993691 & 0.503155 \tabularnewline
242 & 0.443833 & 0.887666 & 0.556167 \tabularnewline
243 & 0.84705 & 0.3059 & 0.15295 \tabularnewline
244 & 0.813971 & 0.372057 & 0.186029 \tabularnewline
245 & 0.772084 & 0.455833 & 0.227916 \tabularnewline
246 & 0.72436 & 0.55128 & 0.27564 \tabularnewline
247 & 0.682838 & 0.634325 & 0.317162 \tabularnewline
248 & 0.630009 & 0.739981 & 0.369991 \tabularnewline
249 & 0.570705 & 0.858591 & 0.429295 \tabularnewline
250 & 0.510141 & 0.979717 & 0.489859 \tabularnewline
251 & 0.535279 & 0.929443 & 0.464721 \tabularnewline
252 & 0.481727 & 0.963454 & 0.518273 \tabularnewline
253 & 0.425156 & 0.850313 & 0.574844 \tabularnewline
254 & 0.394789 & 0.789579 & 0.605211 \tabularnewline
255 & 0.344191 & 0.688381 & 0.655809 \tabularnewline
256 & 0.30845 & 0.6169 & 0.69155 \tabularnewline
257 & 0.288308 & 0.576616 & 0.711692 \tabularnewline
258 & 0.234543 & 0.469087 & 0.765457 \tabularnewline
259 & 0.183726 & 0.367452 & 0.816274 \tabularnewline
260 & 0.164535 & 0.32907 & 0.835465 \tabularnewline
261 & 0.122581 & 0.245161 & 0.877419 \tabularnewline
262 & 0.166964 & 0.333928 & 0.833036 \tabularnewline
263 & 0.140949 & 0.281899 & 0.859051 \tabularnewline
264 & 0.109711 & 0.219421 & 0.890289 \tabularnewline
265 & 0.320683 & 0.641366 & 0.679317 \tabularnewline
266 & 0.933522 & 0.132956 & 0.0664779 \tabularnewline
267 & 0.875633 & 0.248734 & 0.124367 \tabularnewline
268 & 0.96547 & 0.0690603 & 0.0345302 \tabularnewline
269 & 0.906075 & 0.187849 & 0.0939246 \tabularnewline
270 & 0.757537 & 0.484926 & 0.242463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&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]0.21499[/C][C]0.42998[/C][C]0.78501[/C][/ROW]
[ROW][C]18[/C][C]0.549864[/C][C]0.900273[/C][C]0.450136[/C][/ROW]
[ROW][C]19[/C][C]0.420567[/C][C]0.841133[/C][C]0.579433[/C][/ROW]
[ROW][C]20[/C][C]0.322104[/C][C]0.644208[/C][C]0.677896[/C][/ROW]
[ROW][C]21[/C][C]0.337022[/C][C]0.674045[/C][C]0.662978[/C][/ROW]
[ROW][C]22[/C][C]0.312924[/C][C]0.625848[/C][C]0.687076[/C][/ROW]
[ROW][C]23[/C][C]0.244958[/C][C]0.489916[/C][C]0.755042[/C][/ROW]
[ROW][C]24[/C][C]0.173817[/C][C]0.347635[/C][C]0.826183[/C][/ROW]
[ROW][C]25[/C][C]0.201867[/C][C]0.403735[/C][C]0.798133[/C][/ROW]
[ROW][C]26[/C][C]0.171474[/C][C]0.342949[/C][C]0.828526[/C][/ROW]
[ROW][C]27[/C][C]0.121685[/C][C]0.243371[/C][C]0.878315[/C][/ROW]
[ROW][C]28[/C][C]0.0831735[/C][C]0.166347[/C][C]0.916826[/C][/ROW]
[ROW][C]29[/C][C]0.0687748[/C][C]0.13755[/C][C]0.931225[/C][/ROW]
[ROW][C]30[/C][C]0.0466022[/C][C]0.0932044[/C][C]0.953398[/C][/ROW]
[ROW][C]31[/C][C]0.0314764[/C][C]0.0629527[/C][C]0.968524[/C][/ROW]
[ROW][C]32[/C][C]0.0235182[/C][C]0.0470364[/C][C]0.976482[/C][/ROW]
[ROW][C]33[/C][C]0.0164263[/C][C]0.0328526[/C][C]0.983574[/C][/ROW]
[ROW][C]34[/C][C]0.0113233[/C][C]0.0226465[/C][C]0.988677[/C][/ROW]
[ROW][C]35[/C][C]0.0120853[/C][C]0.0241706[/C][C]0.987915[/C][/ROW]
[ROW][C]36[/C][C]0.317667[/C][C]0.635334[/C][C]0.682333[/C][/ROW]
[ROW][C]37[/C][C]0.275088[/C][C]0.550176[/C][C]0.724912[/C][/ROW]
[ROW][C]38[/C][C]0.232602[/C][C]0.465205[/C][C]0.767398[/C][/ROW]
[ROW][C]39[/C][C]0.197354[/C][C]0.394709[/C][C]0.802646[/C][/ROW]
[ROW][C]40[/C][C]0.158413[/C][C]0.316826[/C][C]0.841587[/C][/ROW]
[ROW][C]41[/C][C]0.166619[/C][C]0.333238[/C][C]0.833381[/C][/ROW]
[ROW][C]42[/C][C]0.13268[/C][C]0.26536[/C][C]0.86732[/C][/ROW]
[ROW][C]43[/C][C]0.231763[/C][C]0.463525[/C][C]0.768237[/C][/ROW]
[ROW][C]44[/C][C]0.206039[/C][C]0.412077[/C][C]0.793961[/C][/ROW]
[ROW][C]45[/C][C]0.208792[/C][C]0.417585[/C][C]0.791208[/C][/ROW]
[ROW][C]46[/C][C]0.202018[/C][C]0.404035[/C][C]0.797982[/C][/ROW]
[ROW][C]47[/C][C]0.165642[/C][C]0.331283[/C][C]0.834358[/C][/ROW]
[ROW][C]48[/C][C]0.14199[/C][C]0.283979[/C][C]0.85801[/C][/ROW]
[ROW][C]49[/C][C]0.125686[/C][C]0.251373[/C][C]0.874314[/C][/ROW]
[ROW][C]50[/C][C]0.143566[/C][C]0.287132[/C][C]0.856434[/C][/ROW]
[ROW][C]51[/C][C]0.1729[/C][C]0.3458[/C][C]0.8271[/C][/ROW]
[ROW][C]52[/C][C]0.178433[/C][C]0.356865[/C][C]0.821567[/C][/ROW]
[ROW][C]53[/C][C]0.154207[/C][C]0.308414[/C][C]0.845793[/C][/ROW]
[ROW][C]54[/C][C]0.207504[/C][C]0.415008[/C][C]0.792496[/C][/ROW]
[ROW][C]55[/C][C]0.178881[/C][C]0.357763[/C][C]0.821119[/C][/ROW]
[ROW][C]56[/C][C]0.230131[/C][C]0.460263[/C][C]0.769869[/C][/ROW]
[ROW][C]57[/C][C]0.268434[/C][C]0.536868[/C][C]0.731566[/C][/ROW]
[ROW][C]58[/C][C]0.243282[/C][C]0.486564[/C][C]0.756718[/C][/ROW]
[ROW][C]59[/C][C]0.363877[/C][C]0.727754[/C][C]0.636123[/C][/ROW]
[ROW][C]60[/C][C]0.385003[/C][C]0.770007[/C][C]0.614997[/C][/ROW]
[ROW][C]61[/C][C]0.354278[/C][C]0.708556[/C][C]0.645722[/C][/ROW]
[ROW][C]62[/C][C]0.378469[/C][C]0.756939[/C][C]0.621531[/C][/ROW]
[ROW][C]63[/C][C]0.365961[/C][C]0.731921[/C][C]0.634039[/C][/ROW]
[ROW][C]64[/C][C]0.333303[/C][C]0.666605[/C][C]0.666697[/C][/ROW]
[ROW][C]65[/C][C]0.399696[/C][C]0.799392[/C][C]0.600304[/C][/ROW]
[ROW][C]66[/C][C]0.469342[/C][C]0.938683[/C][C]0.530658[/C][/ROW]
[ROW][C]67[/C][C]0.44858[/C][C]0.89716[/C][C]0.55142[/C][/ROW]
[ROW][C]68[/C][C]0.441003[/C][C]0.882006[/C][C]0.558997[/C][/ROW]
[ROW][C]69[/C][C]0.41215[/C][C]0.8243[/C][C]0.58785[/C][/ROW]
[ROW][C]70[/C][C]0.405995[/C][C]0.811989[/C][C]0.594005[/C][/ROW]
[ROW][C]71[/C][C]0.434396[/C][C]0.868792[/C][C]0.565604[/C][/ROW]
[ROW][C]72[/C][C]0.403843[/C][C]0.807685[/C][C]0.596157[/C][/ROW]
[ROW][C]73[/C][C]0.366786[/C][C]0.733572[/C][C]0.633214[/C][/ROW]
[ROW][C]74[/C][C]0.333706[/C][C]0.667412[/C][C]0.666294[/C][/ROW]
[ROW][C]75[/C][C]0.320246[/C][C]0.640493[/C][C]0.679754[/C][/ROW]
[ROW][C]76[/C][C]0.34627[/C][C]0.69254[/C][C]0.65373[/C][/ROW]
[ROW][C]77[/C][C]0.431551[/C][C]0.863103[/C][C]0.568449[/C][/ROW]
[ROW][C]78[/C][C]0.395011[/C][C]0.790022[/C][C]0.604989[/C][/ROW]
[ROW][C]79[/C][C]0.362132[/C][C]0.724263[/C][C]0.637868[/C][/ROW]
[ROW][C]80[/C][C]0.331108[/C][C]0.662217[/C][C]0.668892[/C][/ROW]
[ROW][C]81[/C][C]0.32416[/C][C]0.648321[/C][C]0.67584[/C][/ROW]
[ROW][C]82[/C][C]0.301055[/C][C]0.602109[/C][C]0.698945[/C][/ROW]
[ROW][C]83[/C][C]0.32161[/C][C]0.64322[/C][C]0.67839[/C][/ROW]
[ROW][C]84[/C][C]0.298118[/C][C]0.596236[/C][C]0.701882[/C][/ROW]
[ROW][C]85[/C][C]0.302867[/C][C]0.605735[/C][C]0.697133[/C][/ROW]
[ROW][C]86[/C][C]0.282777[/C][C]0.565553[/C][C]0.717223[/C][/ROW]
[ROW][C]87[/C][C]0.38922[/C][C]0.778441[/C][C]0.61078[/C][/ROW]
[ROW][C]88[/C][C]0.371849[/C][C]0.743699[/C][C]0.628151[/C][/ROW]
[ROW][C]89[/C][C]0.340602[/C][C]0.681203[/C][C]0.659398[/C][/ROW]
[ROW][C]90[/C][C]0.312635[/C][C]0.62527[/C][C]0.687365[/C][/ROW]
[ROW][C]91[/C][C]0.297056[/C][C]0.594112[/C][C]0.702944[/C][/ROW]
[ROW][C]92[/C][C]0.326715[/C][C]0.65343[/C][C]0.673285[/C][/ROW]
[ROW][C]93[/C][C]0.382763[/C][C]0.765526[/C][C]0.617237[/C][/ROW]
[ROW][C]94[/C][C]0.387804[/C][C]0.775607[/C][C]0.612196[/C][/ROW]
[ROW][C]95[/C][C]0.523514[/C][C]0.952973[/C][C]0.476486[/C][/ROW]
[ROW][C]96[/C][C]0.488161[/C][C]0.976322[/C][C]0.511839[/C][/ROW]
[ROW][C]97[/C][C]0.479787[/C][C]0.959573[/C][C]0.520213[/C][/ROW]
[ROW][C]98[/C][C]0.515269[/C][C]0.969463[/C][C]0.484731[/C][/ROW]
[ROW][C]99[/C][C]0.492668[/C][C]0.985336[/C][C]0.507332[/C][/ROW]
[ROW][C]100[/C][C]0.518365[/C][C]0.963269[/C][C]0.481635[/C][/ROW]
[ROW][C]101[/C][C]0.492989[/C][C]0.985977[/C][C]0.507011[/C][/ROW]
[ROW][C]102[/C][C]0.51707[/C][C]0.96586[/C][C]0.48293[/C][/ROW]
[ROW][C]103[/C][C]0.601162[/C][C]0.797675[/C][C]0.398838[/C][/ROW]
[ROW][C]104[/C][C]0.58124[/C][C]0.837521[/C][C]0.41876[/C][/ROW]
[ROW][C]105[/C][C]0.575086[/C][C]0.849827[/C][C]0.424914[/C][/ROW]
[ROW][C]106[/C][C]0.606944[/C][C]0.786112[/C][C]0.393056[/C][/ROW]
[ROW][C]107[/C][C]0.602684[/C][C]0.794633[/C][C]0.397316[/C][/ROW]
[ROW][C]108[/C][C]0.619735[/C][C]0.760529[/C][C]0.380265[/C][/ROW]
[ROW][C]109[/C][C]0.634879[/C][C]0.730242[/C][C]0.365121[/C][/ROW]
[ROW][C]110[/C][C]0.661825[/C][C]0.67635[/C][C]0.338175[/C][/ROW]
[ROW][C]111[/C][C]0.821383[/C][C]0.357235[/C][C]0.178617[/C][/ROW]
[ROW][C]112[/C][C]0.900063[/C][C]0.199874[/C][C]0.0999371[/C][/ROW]
[ROW][C]113[/C][C]0.896032[/C][C]0.207936[/C][C]0.103968[/C][/ROW]
[ROW][C]114[/C][C]0.888326[/C][C]0.223348[/C][C]0.111674[/C][/ROW]
[ROW][C]115[/C][C]0.887316[/C][C]0.225369[/C][C]0.112684[/C][/ROW]
[ROW][C]116[/C][C]0.950425[/C][C]0.0991507[/C][C]0.0495753[/C][/ROW]
[ROW][C]117[/C][C]0.965002[/C][C]0.0699958[/C][C]0.0349979[/C][/ROW]
[ROW][C]118[/C][C]0.976198[/C][C]0.0476036[/C][C]0.0238018[/C][/ROW]
[ROW][C]119[/C][C]0.983461[/C][C]0.0330781[/C][C]0.016539[/C][/ROW]
[ROW][C]120[/C][C]0.985999[/C][C]0.0280011[/C][C]0.0140006[/C][/ROW]
[ROW][C]121[/C][C]0.985453[/C][C]0.0290939[/C][C]0.0145469[/C][/ROW]
[ROW][C]122[/C][C]0.986115[/C][C]0.0277695[/C][C]0.0138848[/C][/ROW]
[ROW][C]123[/C][C]0.990077[/C][C]0.019846[/C][C]0.009923[/C][/ROW]
[ROW][C]124[/C][C]0.988961[/C][C]0.022078[/C][C]0.011039[/C][/ROW]
[ROW][C]125[/C][C]0.991648[/C][C]0.0167049[/C][C]0.00835247[/C][/ROW]
[ROW][C]126[/C][C]0.993148[/C][C]0.0137049[/C][C]0.00685246[/C][/ROW]
[ROW][C]127[/C][C]0.995391[/C][C]0.00921853[/C][C]0.00460927[/C][/ROW]
[ROW][C]128[/C][C]0.996034[/C][C]0.00793144[/C][C]0.00396572[/C][/ROW]
[ROW][C]129[/C][C]0.995256[/C][C]0.00948779[/C][C]0.00474389[/C][/ROW]
[ROW][C]130[/C][C]0.995427[/C][C]0.00914602[/C][C]0.00457301[/C][/ROW]
[ROW][C]131[/C][C]0.994349[/C][C]0.0113017[/C][C]0.00565083[/C][/ROW]
[ROW][C]132[/C][C]0.99579[/C][C]0.00842064[/C][C]0.00421032[/C][/ROW]
[ROW][C]133[/C][C]0.995423[/C][C]0.00915358[/C][C]0.00457679[/C][/ROW]
[ROW][C]134[/C][C]0.994776[/C][C]0.0104475[/C][C]0.00522374[/C][/ROW]
[ROW][C]135[/C][C]0.993998[/C][C]0.0120034[/C][C]0.00600172[/C][/ROW]
[ROW][C]136[/C][C]0.99344[/C][C]0.0131196[/C][C]0.00655979[/C][/ROW]
[ROW][C]137[/C][C]0.99398[/C][C]0.0120408[/C][C]0.00602039[/C][/ROW]
[ROW][C]138[/C][C]0.992644[/C][C]0.014712[/C][C]0.00735599[/C][/ROW]
[ROW][C]139[/C][C]0.991916[/C][C]0.0161686[/C][C]0.00808432[/C][/ROW]
[ROW][C]140[/C][C]0.993741[/C][C]0.0125173[/C][C]0.00625867[/C][/ROW]
[ROW][C]141[/C][C]0.996863[/C][C]0.00627483[/C][C]0.00313741[/C][/ROW]
[ROW][C]142[/C][C]0.997382[/C][C]0.00523655[/C][C]0.00261828[/C][/ROW]
[ROW][C]143[/C][C]0.996775[/C][C]0.0064494[/C][C]0.0032247[/C][/ROW]
[ROW][C]144[/C][C]0.996135[/C][C]0.00773072[/C][C]0.00386536[/C][/ROW]
[ROW][C]145[/C][C]0.996028[/C][C]0.00794323[/C][C]0.00397162[/C][/ROW]
[ROW][C]146[/C][C]0.995308[/C][C]0.00938307[/C][C]0.00469153[/C][/ROW]
[ROW][C]147[/C][C]0.996006[/C][C]0.00798817[/C][C]0.00399409[/C][/ROW]
[ROW][C]148[/C][C]0.995602[/C][C]0.00879671[/C][C]0.00439836[/C][/ROW]
[ROW][C]149[/C][C]0.995399[/C][C]0.00920139[/C][C]0.00460069[/C][/ROW]
[ROW][C]150[/C][C]0.994987[/C][C]0.0100259[/C][C]0.00501294[/C][/ROW]
[ROW][C]151[/C][C]0.993926[/C][C]0.0121489[/C][C]0.00607443[/C][/ROW]
[ROW][C]152[/C][C]0.993053[/C][C]0.0138931[/C][C]0.00694655[/C][/ROW]
[ROW][C]153[/C][C]0.991391[/C][C]0.0172182[/C][C]0.00860909[/C][/ROW]
[ROW][C]154[/C][C]0.990177[/C][C]0.0196455[/C][C]0.00982273[/C][/ROW]
[ROW][C]155[/C][C]0.989086[/C][C]0.0218284[/C][C]0.0109142[/C][/ROW]
[ROW][C]156[/C][C]0.991758[/C][C]0.0164844[/C][C]0.00824219[/C][/ROW]
[ROW][C]157[/C][C]0.990308[/C][C]0.0193847[/C][C]0.00969237[/C][/ROW]
[ROW][C]158[/C][C]0.990478[/C][C]0.0190434[/C][C]0.00952171[/C][/ROW]
[ROW][C]159[/C][C]0.990978[/C][C]0.0180445[/C][C]0.00902223[/C][/ROW]
[ROW][C]160[/C][C]0.99026[/C][C]0.01948[/C][C]0.00974001[/C][/ROW]
[ROW][C]161[/C][C]0.988268[/C][C]0.0234637[/C][C]0.0117319[/C][/ROW]
[ROW][C]162[/C][C]0.98829[/C][C]0.0234193[/C][C]0.0117097[/C][/ROW]
[ROW][C]163[/C][C]0.988963[/C][C]0.0220743[/C][C]0.0110372[/C][/ROW]
[ROW][C]164[/C][C]0.986904[/C][C]0.0261922[/C][C]0.0130961[/C][/ROW]
[ROW][C]165[/C][C]0.986033[/C][C]0.0279332[/C][C]0.0139666[/C][/ROW]
[ROW][C]166[/C][C]0.989607[/C][C]0.0207869[/C][C]0.0103935[/C][/ROW]
[ROW][C]167[/C][C]0.988747[/C][C]0.0225064[/C][C]0.0112532[/C][/ROW]
[ROW][C]168[/C][C]0.986755[/C][C]0.0264898[/C][C]0.0132449[/C][/ROW]
[ROW][C]169[/C][C]0.986558[/C][C]0.0268846[/C][C]0.0134423[/C][/ROW]
[ROW][C]170[/C][C]0.987587[/C][C]0.0248269[/C][C]0.0124135[/C][/ROW]
[ROW][C]171[/C][C]0.984903[/C][C]0.0301939[/C][C]0.0150969[/C][/ROW]
[ROW][C]172[/C][C]0.987004[/C][C]0.0259915[/C][C]0.0129958[/C][/ROW]
[ROW][C]173[/C][C]0.984039[/C][C]0.0319211[/C][C]0.0159605[/C][/ROW]
[ROW][C]174[/C][C]0.980368[/C][C]0.0392645[/C][C]0.0196323[/C][/ROW]
[ROW][C]175[/C][C]0.979454[/C][C]0.041092[/C][C]0.020546[/C][/ROW]
[ROW][C]176[/C][C]0.976447[/C][C]0.0471056[/C][C]0.0235528[/C][/ROW]
[ROW][C]177[/C][C]0.982703[/C][C]0.0345945[/C][C]0.0172972[/C][/ROW]
[ROW][C]178[/C][C]0.978767[/C][C]0.0424661[/C][C]0.021233[/C][/ROW]
[ROW][C]179[/C][C]0.973904[/C][C]0.0521911[/C][C]0.0260955[/C][/ROW]
[ROW][C]180[/C][C]0.967893[/C][C]0.0642136[/C][C]0.0321068[/C][/ROW]
[ROW][C]181[/C][C]0.973963[/C][C]0.0520742[/C][C]0.0260371[/C][/ROW]
[ROW][C]182[/C][C]0.968253[/C][C]0.0634949[/C][C]0.0317474[/C][/ROW]
[ROW][C]183[/C][C]0.983244[/C][C]0.0335122[/C][C]0.0167561[/C][/ROW]
[ROW][C]184[/C][C]0.979559[/C][C]0.0408813[/C][C]0.0204407[/C][/ROW]
[ROW][C]185[/C][C]0.984323[/C][C]0.0313536[/C][C]0.0156768[/C][/ROW]
[ROW][C]186[/C][C]0.980539[/C][C]0.0389214[/C][C]0.0194607[/C][/ROW]
[ROW][C]187[/C][C]0.976131[/C][C]0.0477378[/C][C]0.0238689[/C][/ROW]
[ROW][C]188[/C][C]0.975438[/C][C]0.0491236[/C][C]0.0245618[/C][/ROW]
[ROW][C]189[/C][C]0.971408[/C][C]0.0571843[/C][C]0.0285921[/C][/ROW]
[ROW][C]190[/C][C]0.973501[/C][C]0.0529983[/C][C]0.0264991[/C][/ROW]
[ROW][C]191[/C][C]0.968111[/C][C]0.0637783[/C][C]0.0318891[/C][/ROW]
[ROW][C]192[/C][C]0.971688[/C][C]0.0566241[/C][C]0.028312[/C][/ROW]
[ROW][C]193[/C][C]0.967956[/C][C]0.064088[/C][C]0.032044[/C][/ROW]
[ROW][C]194[/C][C]0.963513[/C][C]0.072973[/C][C]0.0364865[/C][/ROW]
[ROW][C]195[/C][C]0.957831[/C][C]0.0843385[/C][C]0.0421693[/C][/ROW]
[ROW][C]196[/C][C]0.949119[/C][C]0.101762[/C][C]0.0508811[/C][/ROW]
[ROW][C]197[/C][C]0.949326[/C][C]0.101348[/C][C]0.050674[/C][/ROW]
[ROW][C]198[/C][C]0.970047[/C][C]0.0599063[/C][C]0.0299531[/C][/ROW]
[ROW][C]199[/C][C]0.97565[/C][C]0.048699[/C][C]0.0243495[/C][/ROW]
[ROW][C]200[/C][C]0.971069[/C][C]0.0578616[/C][C]0.0289308[/C][/ROW]
[ROW][C]201[/C][C]0.964042[/C][C]0.0719166[/C][C]0.0359583[/C][/ROW]
[ROW][C]202[/C][C]0.955236[/C][C]0.0895276[/C][C]0.0447638[/C][/ROW]
[ROW][C]203[/C][C]0.9491[/C][C]0.101799[/C][C]0.0508997[/C][/ROW]
[ROW][C]204[/C][C]0.949226[/C][C]0.101548[/C][C]0.050774[/C][/ROW]
[ROW][C]205[/C][C]0.942868[/C][C]0.114263[/C][C]0.0571316[/C][/ROW]
[ROW][C]206[/C][C]0.951146[/C][C]0.0977073[/C][C]0.0488536[/C][/ROW]
[ROW][C]207[/C][C]0.946409[/C][C]0.107182[/C][C]0.0535908[/C][/ROW]
[ROW][C]208[/C][C]0.934206[/C][C]0.131589[/C][C]0.0657944[/C][/ROW]
[ROW][C]209[/C][C]0.925395[/C][C]0.149209[/C][C]0.0746047[/C][/ROW]
[ROW][C]210[/C][C]0.923639[/C][C]0.152723[/C][C]0.0763615[/C][/ROW]
[ROW][C]211[/C][C]0.915353[/C][C]0.169294[/C][C]0.0846471[/C][/ROW]
[ROW][C]212[/C][C]0.907633[/C][C]0.184733[/C][C]0.0923666[/C][/ROW]
[ROW][C]213[/C][C]0.892719[/C][C]0.214561[/C][C]0.107281[/C][/ROW]
[ROW][C]214[/C][C]0.873214[/C][C]0.253571[/C][C]0.126786[/C][/ROW]
[ROW][C]215[/C][C]0.879407[/C][C]0.241186[/C][C]0.120593[/C][/ROW]
[ROW][C]216[/C][C]0.864374[/C][C]0.271253[/C][C]0.135626[/C][/ROW]
[ROW][C]217[/C][C]0.839831[/C][C]0.320338[/C][C]0.160169[/C][/ROW]
[ROW][C]218[/C][C]0.820262[/C][C]0.359476[/C][C]0.179738[/C][/ROW]
[ROW][C]219[/C][C]0.795344[/C][C]0.409312[/C][C]0.204656[/C][/ROW]
[ROW][C]220[/C][C]0.782287[/C][C]0.435426[/C][C]0.217713[/C][/ROW]
[ROW][C]221[/C][C]0.757136[/C][C]0.485727[/C][C]0.242864[/C][/ROW]
[ROW][C]222[/C][C]0.720862[/C][C]0.558277[/C][C]0.279138[/C][/ROW]
[ROW][C]223[/C][C]0.700352[/C][C]0.599295[/C][C]0.299648[/C][/ROW]
[ROW][C]224[/C][C]0.659606[/C][C]0.680789[/C][C]0.340394[/C][/ROW]
[ROW][C]225[/C][C]0.65074[/C][C]0.69852[/C][C]0.34926[/C][/ROW]
[ROW][C]226[/C][C]0.607939[/C][C]0.784122[/C][C]0.392061[/C][/ROW]
[ROW][C]227[/C][C]0.578107[/C][C]0.843787[/C][C]0.421893[/C][/ROW]
[ROW][C]228[/C][C]0.60186[/C][C]0.796281[/C][C]0.39814[/C][/ROW]
[ROW][C]229[/C][C]0.615695[/C][C]0.768609[/C][C]0.384305[/C][/ROW]
[ROW][C]230[/C][C]0.572202[/C][C]0.855597[/C][C]0.427798[/C][/ROW]
[ROW][C]231[/C][C]0.530659[/C][C]0.938682[/C][C]0.469341[/C][/ROW]
[ROW][C]232[/C][C]0.518827[/C][C]0.962346[/C][C]0.481173[/C][/ROW]
[ROW][C]233[/C][C]0.493023[/C][C]0.986046[/C][C]0.506977[/C][/ROW]
[ROW][C]234[/C][C]0.45059[/C][C]0.90118[/C][C]0.54941[/C][/ROW]
[ROW][C]235[/C][C]0.428924[/C][C]0.857847[/C][C]0.571076[/C][/ROW]
[ROW][C]236[/C][C]0.458768[/C][C]0.917536[/C][C]0.541232[/C][/ROW]
[ROW][C]237[/C][C]0.460025[/C][C]0.920049[/C][C]0.539975[/C][/ROW]
[ROW][C]238[/C][C]0.512497[/C][C]0.975006[/C][C]0.487503[/C][/ROW]
[ROW][C]239[/C][C]0.552971[/C][C]0.894059[/C][C]0.447029[/C][/ROW]
[ROW][C]240[/C][C]0.505445[/C][C]0.989109[/C][C]0.494555[/C][/ROW]
[ROW][C]241[/C][C]0.496845[/C][C]0.993691[/C][C]0.503155[/C][/ROW]
[ROW][C]242[/C][C]0.443833[/C][C]0.887666[/C][C]0.556167[/C][/ROW]
[ROW][C]243[/C][C]0.84705[/C][C]0.3059[/C][C]0.15295[/C][/ROW]
[ROW][C]244[/C][C]0.813971[/C][C]0.372057[/C][C]0.186029[/C][/ROW]
[ROW][C]245[/C][C]0.772084[/C][C]0.455833[/C][C]0.227916[/C][/ROW]
[ROW][C]246[/C][C]0.72436[/C][C]0.55128[/C][C]0.27564[/C][/ROW]
[ROW][C]247[/C][C]0.682838[/C][C]0.634325[/C][C]0.317162[/C][/ROW]
[ROW][C]248[/C][C]0.630009[/C][C]0.739981[/C][C]0.369991[/C][/ROW]
[ROW][C]249[/C][C]0.570705[/C][C]0.858591[/C][C]0.429295[/C][/ROW]
[ROW][C]250[/C][C]0.510141[/C][C]0.979717[/C][C]0.489859[/C][/ROW]
[ROW][C]251[/C][C]0.535279[/C][C]0.929443[/C][C]0.464721[/C][/ROW]
[ROW][C]252[/C][C]0.481727[/C][C]0.963454[/C][C]0.518273[/C][/ROW]
[ROW][C]253[/C][C]0.425156[/C][C]0.850313[/C][C]0.574844[/C][/ROW]
[ROW][C]254[/C][C]0.394789[/C][C]0.789579[/C][C]0.605211[/C][/ROW]
[ROW][C]255[/C][C]0.344191[/C][C]0.688381[/C][C]0.655809[/C][/ROW]
[ROW][C]256[/C][C]0.30845[/C][C]0.6169[/C][C]0.69155[/C][/ROW]
[ROW][C]257[/C][C]0.288308[/C][C]0.576616[/C][C]0.711692[/C][/ROW]
[ROW][C]258[/C][C]0.234543[/C][C]0.469087[/C][C]0.765457[/C][/ROW]
[ROW][C]259[/C][C]0.183726[/C][C]0.367452[/C][C]0.816274[/C][/ROW]
[ROW][C]260[/C][C]0.164535[/C][C]0.32907[/C][C]0.835465[/C][/ROW]
[ROW][C]261[/C][C]0.122581[/C][C]0.245161[/C][C]0.877419[/C][/ROW]
[ROW][C]262[/C][C]0.166964[/C][C]0.333928[/C][C]0.833036[/C][/ROW]
[ROW][C]263[/C][C]0.140949[/C][C]0.281899[/C][C]0.859051[/C][/ROW]
[ROW][C]264[/C][C]0.109711[/C][C]0.219421[/C][C]0.890289[/C][/ROW]
[ROW][C]265[/C][C]0.320683[/C][C]0.641366[/C][C]0.679317[/C][/ROW]
[ROW][C]266[/C][C]0.933522[/C][C]0.132956[/C][C]0.0664779[/C][/ROW]
[ROW][C]267[/C][C]0.875633[/C][C]0.248734[/C][C]0.124367[/C][/ROW]
[ROW][C]268[/C][C]0.96547[/C][C]0.0690603[/C][C]0.0345302[/C][/ROW]
[ROW][C]269[/C][C]0.906075[/C][C]0.187849[/C][C]0.0939246[/C][/ROW]
[ROW][C]270[/C][C]0.757537[/C][C]0.484926[/C][C]0.242463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=5

As an alternative you can also use a QR Code:  
QR Code


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
170.214990.429980.78501
180.5498640.9002730.450136
190.4205670.8411330.579433
200.3221040.6442080.677896
210.3370220.6740450.662978
220.3129240.6258480.687076
230.2449580.4899160.755042
240.1738170.3476350.826183
250.2018670.4037350.798133
260.1714740.3429490.828526
270.1216850.2433710.878315
280.08317350.1663470.916826
290.06877480.137550.931225
300.04660220.09320440.953398
310.03147640.06295270.968524
320.02351820.04703640.976482
330.01642630.03285260.983574
340.01132330.02264650.988677
350.01208530.02417060.987915
360.3176670.6353340.682333
370.2750880.5501760.724912
380.2326020.4652050.767398
390.1973540.3947090.802646
400.1584130.3168260.841587
410.1666190.3332380.833381
420.132680.265360.86732
430.2317630.4635250.768237
440.2060390.4120770.793961
450.2087920.4175850.791208
460.2020180.4040350.797982
470.1656420.3312830.834358
480.141990.2839790.85801
490.1256860.2513730.874314
500.1435660.2871320.856434
510.17290.34580.8271
520.1784330.3568650.821567
530.1542070.3084140.845793
540.2075040.4150080.792496
550.1788810.3577630.821119
560.2301310.4602630.769869
570.2684340.5368680.731566
580.2432820.4865640.756718
590.3638770.7277540.636123
600.3850030.7700070.614997
610.3542780.7085560.645722
620.3784690.7569390.621531
630.3659610.7319210.634039
640.3333030.6666050.666697
650.3996960.7993920.600304
660.4693420.9386830.530658
670.448580.897160.55142
680.4410030.8820060.558997
690.412150.82430.58785
700.4059950.8119890.594005
710.4343960.8687920.565604
720.4038430.8076850.596157
730.3667860.7335720.633214
740.3337060.6674120.666294
750.3202460.6404930.679754
760.346270.692540.65373
770.4315510.8631030.568449
780.3950110.7900220.604989
790.3621320.7242630.637868
800.3311080.6622170.668892
810.324160.6483210.67584
820.3010550.6021090.698945
830.321610.643220.67839
840.2981180.5962360.701882
850.3028670.6057350.697133
860.2827770.5655530.717223
870.389220.7784410.61078
880.3718490.7436990.628151
890.3406020.6812030.659398
900.3126350.625270.687365
910.2970560.5941120.702944
920.3267150.653430.673285
930.3827630.7655260.617237
940.3878040.7756070.612196
950.5235140.9529730.476486
960.4881610.9763220.511839
970.4797870.9595730.520213
980.5152690.9694630.484731
990.4926680.9853360.507332
1000.5183650.9632690.481635
1010.4929890.9859770.507011
1020.517070.965860.48293
1030.6011620.7976750.398838
1040.581240.8375210.41876
1050.5750860.8498270.424914
1060.6069440.7861120.393056
1070.6026840.7946330.397316
1080.6197350.7605290.380265
1090.6348790.7302420.365121
1100.6618250.676350.338175
1110.8213830.3572350.178617
1120.9000630.1998740.0999371
1130.8960320.2079360.103968
1140.8883260.2233480.111674
1150.8873160.2253690.112684
1160.9504250.09915070.0495753
1170.9650020.06999580.0349979
1180.9761980.04760360.0238018
1190.9834610.03307810.016539
1200.9859990.02800110.0140006
1210.9854530.02909390.0145469
1220.9861150.02776950.0138848
1230.9900770.0198460.009923
1240.9889610.0220780.011039
1250.9916480.01670490.00835247
1260.9931480.01370490.00685246
1270.9953910.009218530.00460927
1280.9960340.007931440.00396572
1290.9952560.009487790.00474389
1300.9954270.009146020.00457301
1310.9943490.01130170.00565083
1320.995790.008420640.00421032
1330.9954230.009153580.00457679
1340.9947760.01044750.00522374
1350.9939980.01200340.00600172
1360.993440.01311960.00655979
1370.993980.01204080.00602039
1380.9926440.0147120.00735599
1390.9919160.01616860.00808432
1400.9937410.01251730.00625867
1410.9968630.006274830.00313741
1420.9973820.005236550.00261828
1430.9967750.00644940.0032247
1440.9961350.007730720.00386536
1450.9960280.007943230.00397162
1460.9953080.009383070.00469153
1470.9960060.007988170.00399409
1480.9956020.008796710.00439836
1490.9953990.009201390.00460069
1500.9949870.01002590.00501294
1510.9939260.01214890.00607443
1520.9930530.01389310.00694655
1530.9913910.01721820.00860909
1540.9901770.01964550.00982273
1550.9890860.02182840.0109142
1560.9917580.01648440.00824219
1570.9903080.01938470.00969237
1580.9904780.01904340.00952171
1590.9909780.01804450.00902223
1600.990260.019480.00974001
1610.9882680.02346370.0117319
1620.988290.02341930.0117097
1630.9889630.02207430.0110372
1640.9869040.02619220.0130961
1650.9860330.02793320.0139666
1660.9896070.02078690.0103935
1670.9887470.02250640.0112532
1680.9867550.02648980.0132449
1690.9865580.02688460.0134423
1700.9875870.02482690.0124135
1710.9849030.03019390.0150969
1720.9870040.02599150.0129958
1730.9840390.03192110.0159605
1740.9803680.03926450.0196323
1750.9794540.0410920.020546
1760.9764470.04710560.0235528
1770.9827030.03459450.0172972
1780.9787670.04246610.021233
1790.9739040.05219110.0260955
1800.9678930.06421360.0321068
1810.9739630.05207420.0260371
1820.9682530.06349490.0317474
1830.9832440.03351220.0167561
1840.9795590.04088130.0204407
1850.9843230.03135360.0156768
1860.9805390.03892140.0194607
1870.9761310.04773780.0238689
1880.9754380.04912360.0245618
1890.9714080.05718430.0285921
1900.9735010.05299830.0264991
1910.9681110.06377830.0318891
1920.9716880.05662410.028312
1930.9679560.0640880.032044
1940.9635130.0729730.0364865
1950.9578310.08433850.0421693
1960.9491190.1017620.0508811
1970.9493260.1013480.050674
1980.9700470.05990630.0299531
1990.975650.0486990.0243495
2000.9710690.05786160.0289308
2010.9640420.07191660.0359583
2020.9552360.08952760.0447638
2030.94910.1017990.0508997
2040.9492260.1015480.050774
2050.9428680.1142630.0571316
2060.9511460.09770730.0488536
2070.9464090.1071820.0535908
2080.9342060.1315890.0657944
2090.9253950.1492090.0746047
2100.9236390.1527230.0763615
2110.9153530.1692940.0846471
2120.9076330.1847330.0923666
2130.8927190.2145610.107281
2140.8732140.2535710.126786
2150.8794070.2411860.120593
2160.8643740.2712530.135626
2170.8398310.3203380.160169
2180.8202620.3594760.179738
2190.7953440.4093120.204656
2200.7822870.4354260.217713
2210.7571360.4857270.242864
2220.7208620.5582770.279138
2230.7003520.5992950.299648
2240.6596060.6807890.340394
2250.650740.698520.34926
2260.6079390.7841220.392061
2270.5781070.8437870.421893
2280.601860.7962810.39814
2290.6156950.7686090.384305
2300.5722020.8555970.427798
2310.5306590.9386820.469341
2320.5188270.9623460.481173
2330.4930230.9860460.506977
2340.450590.901180.54941
2350.4289240.8578470.571076
2360.4587680.9175360.541232
2370.4600250.9200490.539975
2380.5124970.9750060.487503
2390.5529710.8940590.447029
2400.5054450.9891090.494555
2410.4968450.9936910.503155
2420.4438330.8876660.556167
2430.847050.30590.15295
2440.8139710.3720570.186029
2450.7720840.4558330.227916
2460.724360.551280.27564
2470.6828380.6343250.317162
2480.6300090.7399810.369991
2490.5707050.8585910.429295
2500.5101410.9797170.489859
2510.5352790.9294430.464721
2520.4817270.9634540.518273
2530.4251560.8503130.574844
2540.3947890.7895790.605211
2550.3441910.6883810.655809
2560.308450.61690.69155
2570.2883080.5766160.711692
2580.2345430.4690870.765457
2590.1837260.3674520.816274
2600.1645350.329070.835465
2610.1225810.2451610.877419
2620.1669640.3339280.833036
2630.1409490.2818990.859051
2640.1097110.2194210.890289
2650.3206830.6413660.679317
2660.9335220.1329560.0664779
2670.8756330.2487340.124367
2680.965470.06906030.0345302
2690.9060750.1878490.0939246
2700.7575370.4849260.242463






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level150.0590551NOK
5% type I error level720.283465NOK
10% type I error level930.366142NOK

\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 & 15 & 0.0590551 & NOK \tabularnewline
5% type I error level & 72 & 0.283465 & NOK \tabularnewline
10% type I error level & 93 & 0.366142 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264257&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]15[/C][C]0.0590551[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]72[/C][C]0.283465[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]93[/C][C]0.366142[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264257&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264257&T=6

As an alternative you can also use a QR Code:  
QR Code


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level150.0590551NOK
5% type I error level720.283465NOK
10% type I error level930.366142NOK


Figures (Output of Computation)

Figure 1
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Figure 6
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Figure 7
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Figure 8
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Figure 10
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Input Parameters & R Code

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')
}