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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 computationTue, 09 Dec 2014 17:32:58 +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/09/t1418146425g1hzm7hmmabre7m.htm/, Retrieved Thu, 16 May 2024 13:33:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264774, Retrieved Thu, 16 May 2024 13:33:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-09 17:32:58] [ec71b09431fe59ba6fc828a3f51756a9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 1.00 0.50 0.67 0.00 0.50 1 0
7.4 1.00 0.60 0.67 0.50 1.00 1 0
12.2 0.89 0.50 0.33 0.50 1.00 1 0
12.8 0.89 0.40 0.67 0.00 1.00 1 0
7.4 0.89 0.50 0.00 0.00 0.00 1 0
6.7 0.89 0.70 0.00 1.00 1.00 1 0
12.6 0.78 0.30 0.00 0.50 0.50 1 0
14.8 0.89 0.40 0.67 0.50 0.00 1 0
13.3 1.00 0.40 0.67 1.00 1.00 1 0
11.1 0.89 0.70 0.00 0.50 0.00 1 0
8.2 0.78 0.60 0.67 0.50 0.50 1 0
11.4 1.00 0.60 1.00 0.00 0.50 1 0
6.4 0.78 0.20 0.00 0.50 0.50 1 0
10.6 0.89 0.40 0.00 0.50 0.50 1 0
12.0 0.89 0.40 0.67 0.00 1.00 1 0
6.3 0.89 0.50 0.33 0.00 0.00 1 0
11.3 0.89 0.30 0.67 0.00 0.50 0 0
11.9 0.89 0.40 0.33 0.50 0.50 1 0
9.3 0.67 0.70 0.33 0.50 1.00 1 0
9.6 1.00 0.50 0.33 0.00 1.00 0 0
10.0 0.78 0.20 0.00 0.00 1.00 1 0
6.4 0.78 0.30 0.67 0.00 0.50 1 0
13.8 0.89 0.60 0.33 0.00 1.00 1 0
10.8 0.78 0.60 0.33 0.00 1.00 1 0
13.8 0.89 0.20 0.33 0.00 1.00 1 0
11.7 0.89 0.70 0.67 1.00 0.00 1 0
10.9 0.33 0.20 0.00 0.00 0.00 1 0
16.1 1.00 1.00 0.33 1.00 1.00 0 0
13.4 0.89 0.40 0.67 0.00 0.50 0 0
9.9 0.89 0.40 1.00 0.00 1.00 1 0
11.5 0.67 0.20 0.67 0.00 0.50 1 0
8.3 0.56 0.40 0.33 0.00 1.00 1 0
11.7 0.89 0.40 0.00 0.50 1.00 1 0
6.1 0.89 0.60 0.67 0.50 1.00 1 0
9.0 0.89 0.70 0.67 0.50 0.50 1 0
9.7 1.00 0.20 0.67 0.00 0.50 1 0
10.8 0.78 0.60 1.00 0.00 0.50 1 0
10.3 0.78 0.30 1.00 0.50 0.50 1 0
10.4 0.33 0.30 0.33 0.00 0.00 1 0
12.7 0.78 0.20 0.00 0.50 0.00 0 0
9.3 0.89 0.50 0.67 0.50 0.50 1 0
11.8 0.89 0.70 0.67 0.50 1.00 1 0
5.9 0.78 0.60 0.67 0.50 0.50 1 0
11.4 0.89 0.40 0.67 0.50 1.00 1 0
13.0 0.89 0.60 0.33 0.50 1.00 1 0
10.8 1.00 0.40 1.00 0.00 1.00 1 0
12.3 0.67 0.30 0.67 0.00 1.00 0 0
11.3 1.00 0.50 0.67 0.50 0.50 1 0
11.8 0.89 0.20 0.00 0.00 1.00 1 0
7.9 0.89 0.30 0.00 0.50 1.00 0 0
12.7 0.89 0.50 0.00 0.00 1.00 1 0
12.3 0.78 0.70 1.00 0.50 1.00 0 0
11.6 0.89 0.40 0.67 1.00 0.50 0 0
6.7 0.78 0.30 0.00 0.00 0.50 0 0
10.9 0.78 0.20 0.67 1.00 1.00 1 0
12.1 1.00 0.50 0.00 0.00 0.50 0 0
13.3 0.78 0.40 0.00 0.50 0.00 1 0
10.1 1.00 0.60 0.67 1.00 1.00 1 0
5.7 0.78 0.40 1.00 0.00 1.00 0 0
14.3 0.67 0.40 0.00 0.00 0.50 1 0
8.0 0.33 0.20 0.33 0.00 0.00 0 0
13.3 1.00 0.90 0.67 0.50 1.00 0 0
9.3 1.00 0.80 0.67 1.00 0.50 1 0
12.5 0.78 0.80 0.00 0.50 1.00 1 0
7.6 0.67 0.30 1.00 0.50 1.00 1 0
15.9 1.00 0.20 0.67 0.00 0.50 1 0
9.2 0.89 0.40 0.00 0.50 1.00 1 0
9.1 0.89 0.20 1.00 0.00 1.00 0 0
11.1 0.78 0.20 0.67 0.50 1.00 1 0
13.0 1.00 0.10 0.67 0.00 1.00 1 0
14.5 0.56 0.40 1.00 0.50 0.00 1 0
12.2 0.67 0.50 0.00 0.50 0.50 0 0
12.3 0.89 0.80 0.33 0.50 1.00 1 0
11.4 0.89 0.40 0.67 0.00 0.50 1 0
8.8 0.89 0.60 0.33 0.50 0.50 0 0
14.6 0.89 0.50 0.67 0.50 1.00 0 0
7.3 1.00 0.60 0.67 0.50 1.00 1 0
12.6 0.78 0.30 0.00 0.00 0.00 1 0
NA 0.89 0.80 1.00 0.50 1.00 1 0
13.0 1.00 0.40 0.00 0.50 0.00 1 0
12.6 1.00 0.60 0.67 0.50 0.50 0 0
13.2 0.89 0.40 0.33 0.00 0.50 1 0
9.9 0.44 0.30 0.00 0.00 0.00 0 0
7.7 0.78 0.80 0.00 1.00 1.00 1 0
10.5 0.89 0.60 0.33 1.00 1.00 0 0
13.4 0.67 0.30 0.00 0.00 0.00 0 0
10.9 0.78 0.50 0.67 0.50 1.00 0 0
4.3 0.78 0.40 0.33 0.00 1.00 0 0
10.3 0.33 0.30 0.67 0.00 0.00 0 0
11.8 0.89 0.70 0.33 0.00 0.50 0 0
11.2 0.89 0.20 0.33 0.50 0.50 0 0
11.4 0.89 0.40 1.00 0.00 1.00 0 0
8.6 0.89 0.60 0.67 0.50 0.50 0 0
13.2 0.56 0.60 0.00 0.00 1.00 0 0
12.6 0.67 0.60 0.67 0.50 0.50 0 0
5.6 0.67 0.40 0.33 0.50 1.00 0 0
9.9 0.78 0.60 0.00 0.00 1.00 0 0
8.8 0.78 0.50 0.33 0.50 1.00 0 0
7.7 0.78 0.50 0.00 0.00 1.00 0 0
9.0 0.89 0.60 0.00 0.00 1.00 0 0
7.3 1.00 0.80 0.33 0.50 1.00 0 0
11.4 0.89 0.50 0.67 1.00 0.50 0 0
13.6 0.89 0.60 0.67 0.50 1.00 0 0
7.9 0.78 0.40 0.67 0.50 1.00 0 0
10.7 1.00 0.30 0.67 0.50 1.00 0 0
10.3 0.78 0.30 1.00 0.00 0.50 0 0
8.3 0.67 0.20 0.00 0.00 0.00 0 0
9.6 0.78 0.40 0.00 0.00 0.50 0 0
14.2 0.89 0.50 0.00 0.00 0.50 0 0
8.5 0.67 0.30 0.00 0.50 0.00 0 0
13.5 0.22 0.40 0.00 0.50 0.00 0 0
4.9 0.44 0.50 1.00 0.00 0.00 0 0
6.4 0.89 0.30 0.67 0.00 1.00 0 0
9.6 0.67 0.50 0.00 0.00 0.50 0 0
11.6 0.89 0.40 0.67 0.00 0.50 0 0
11.1 0.67 0.40 0.67 0.00 1.00 0 0
4.35 0.78 0.60 0.00 1.00 1.00 1 1
12.7 0.78 0.30 0.67 1.00 1.00 1 1
18.1 0.78 0.40 0.33 1.00 0.50 1 1
17.85 1.00 0.30 1.00 1.00 1.00 1 1
16.6 0.78 1.00 1.00 1.00 1.00 0 1
12.6 0.67 0.40 0.00 0.00 0.50 0 1
17.1 0.89 0.80 1.00 0.50 1.00 1 1
19.1 0.89 0.30 0.67 1.00 1.00 1 1
16.1 1.00 0.50 0.67 0.00 1.00 1 1
13.35 0.78 0.40 0.00 0.00 0.50 1 1
18.4 0.67 0.30 0.67 0.00 1.00 1 1
14.7 0.89 0.50 1.00 0.00 1.00 1 1
10.6 0.67 0.30 0.67 0.00 1.00 1 1
12.6 0.67 0.30 0.00 0.00 1.00 1 1
16.2 1.00 0.40 0.00 0.00 1.00 1 1
13.6 0.67 0.30 0.00 0.00 0.50 1 1
18.9 1.00 0.60 0.33 0.50 0.50 0 1
14.1 0.89 0.60 0.67 1.00 1.00 1 1
14.5 0.89 0.40 1.00 1.00 1.00 1 1
16.15 1.00 0.40 0.00 0.00 0.00 1 1
14.75 0.67 0.40 0.67 0.00 0.50 1 1
14.8 0.44 0.30 0.67 0.50 1.00 1 1
12.45 0.89 0.20 0.33 1.00 0.00 1 1
12.65 0.56 0.50 0.67 0.00 1.00 1 1
17.35 0.78 0.40 0.67 1.00 1.00 1 1
8.6 1.00 0.40 0.67 0.00 0.00 1 1
18.4 1.00 0.40 0.67 0.00 1.00 1 1
16.1 0.89 0.30 0.67 0.50 0.50 1 1
11.6 0.67 0.40 0.67 1.00 0.50 0 1
17.75 0.89 0.20 0.33 0.50 1.00 1 1
15.25 0.33 0.00 0.00 0.00 0.00 1 1
17.65 0.89 0.40 0.67 0.50 1.00 1 1
15.6 0.78 0.30 0.00 0.00 0.00 1 1
16.35 0.78 0.60 0.00 1.00 1.00 1 1
17.65 1.00 0.40 0.67 0.00 0.50 1 1
13.6 0.44 0.40 0.00 0.00 0.50 1 1
11.7 0.78 0.20 0.00 0.00 0.00 1 1
14.35 0.67 0.40 0.00 0.50 0.00 1 1
14.75 0.33 0.20 0.00 0.50 0.00 1 1
18.25 0.89 0.40 1.00 1.00 1.00 1 1
9.9 0.89 0.30 0.00 0.00 0.50 1 1
16 1.00 0.60 0.67 1.00 0.00 1 1
18.25 0.89 0.60 1.00 0.00 1.00 1 1
16.85 0.89 0.40 0.00 0.00 1.00 1 1
14.6 1.00 0.50 0.67 1.00 0.50 0 1
13.85 0.89 0.40 0.00 0.50 1.00 0 1
18.95 1.00 0.60 1.00 1.00 1.00 1 1
15.6 0.78 0.60 0.67 0.50 1.00 1 1
14.85 0.78 0.90 0.67 0.50 1.00 0 1
11.75 0.67 0.40 0.67 0.50 0.00 0 1
18.45 0.89 0.80 1.00 0.50 1.00 0 1
15.9 0.67 0.50 1.00 0.00 1.00 0 1
17.1 0.78 0.40 1.00 0.00 0.00 1 1
16.1 0.89 0.40 0.67 1.00 0.50 1 1
19.9 0.89 0.70 1.00 1.00 0.50 0 1
10.95 0.78 0.40 0.33 1.00 1.00 0 1
18.45 1.00 0.80 0.67 0.50 1.00 0 1
15.1 1.00 0.40 1.00 1.00 0.50 0 1
15 1.00 0.30 0.67 0.00 0.50 0 1
11.35 0.67 0.50 0.67 0.50 1.00 0 1
15.95 0.89 0.80 0.67 1.00 1.00 0 1
18.1 1.00 0.40 0.33 0.00 0.50 0 1
14.6 1.00 1.00 1.00 0.50 0.00 0 1
15.4 0.89 0.50 0.67 1.00 1.00 1 1
15.4 0.89 0.50 0.67 1.00 1.00 1 1
17.6 0.89 0.30 0.33 0.00 1.00 0 1
13.35 0.89 0.30 0.33 0.50 1.00 1 1
19.1 0.89 0.30 0.00 0.00 1.00 1 1
15.35 1.00 0.40 0.33 0.50 0.50 0 1
7.6 0.67 0.50 0.33 0.00 1.00 1 1
13.4 1.00 0.50 0.67 0.50 1.00 0 1
13.9 0.89 0.40 0.00 0.00 0.00 0 1
19.1 0.89 0.70 1.00 0.50 0.00 1 1
15.25 0.89 0.50 0.33 0.00 0.50 0 1
12.9 0.89 0.40 0.33 1.00 0.00 0 1
16.1 1.00 0.70 1.00 0.00 1.00 0 1
17.35 1.00 0.70 1.00 0.00 1.00 0 1
13.15 1.00 0.70 1.00 0.00 1.00 0 1
12.15 0.89 0.70 1.00 0.00 1.00 0 1
12.6 0.89 0.70 0.00 0.00 0.00 0 1
10.35 0.89 0.70 0.67 0.50 1.00 0 1
15.4 0.33 0.10 0.33 0.50 0.00 0 1
9.6 0.67 0.20 0.67 0.50 1.00 0 1
18.2 0.56 0.30 0.33 0.00 1.00 0 1
13.6 0.44 0.60 0.33 0.00 0.50 0 1
14.85 1.00 0.80 1.00 1.00 1.00 0 1
14.75 0.89 0.80 0.33 0.50 0.50 1 1
14.1 0.33 0.00 0.00 0.00 0.00 0 1
14.9 0.67 0.30 0.33 0.00 1.00 0 1
16.25 0.67 0.60 0.33 0.50 1.00 0 1
19.25 1.00 0.50 0.67 0.00 1.00 1 1
13.6 0.78 0.70 0.33 0.00 0.50 0 1
13.6 0.67 0.30 0.00 0.50 1.00 1 1
15.65 1.00 0.30 0.67 0.00 0.00 0 1
12.75 0.78 0.40 0.67 0.00 0.50 1 1
14.6 0.89 0.40 1.00 0.00 1.00 0 1
9.85 0.89 0.10 0.00 0.00 1.00 1 1
12.65 0.89 0.50 0.67 0.00 1.00 0 1
11.9 0.78 0.30 0.33 0.00 0.50 0 1
19.2 0.00 0.00 0.00 0.00 0.00 0 1
16.6 0.67 0.40 0.33 0.50 0.00 0 1
11.2 1.00 0.60 0.67 1.00 0.50 0 1
15.25 1.00 0.40 0.33 0.50 1.00 1 1
11.9 0.67 0.10 0.00 0.50 1.00 1 1
13.2 0.89 0.30 0.00 0.00 1.00 0 1
16.35 0.89 0.70 0.67 0.00 1.00 1 1
12.4 0.56 0.30 0.00 0.00 1.00 1 1
15.85 0.67 0.50 0.33 0.50 0.00 0 1
14.35 0.67 0.30 0.33 0.00 0.00 1 1
18.15 1.00 0.30 0.67 1.00 1.00 1 1
11.15 1.00 0.60 0.67 0.50 1.00 0 1
15.65 1.00 0.90 1.00 0.00 1.00 0 1
17.75 0.67 0.40 0.00 0.50 1.00 1 1
7.65 0.44 0.30 0.00 0.50 0.50 0 1
12.35 0.89 0.90 0.67 1.00 1.00 1 1
15.6 0.44 0.50 0.00 0.50 0.00 1 1
19.3 0.56 0.30 1.00 0.50 0.50 1 1
15.2 0.89 0.60 0.67 0.00 0.50 0 1
17.1 0.67 0.20 0.33 0.00 0.50 1 1
15.6 0.89 0.40 1.00 0.50 1.00 0 1
18.4 1.00 0.50 0.67 0.50 0.50 1 1
19.05 0.78 0.40 0.67 0.00 0.50 1 1
18.55 0.44 0.00 0.00 0.00 0.00 1 1
19.1 0.89 0.20 0.33 0.50 1.00 1 1
13.1 0.89 0.50 0.67 0.50 1.00 0 1
12.85 0.89 0.30 0.67 0.00 0.50 1 1
9.5 0.44 0.00 0.00 0.00 0.00 1 1
4.5 1.00 0.50 1.00 0.00 1.00 1 1
11.85 0.89 0.60 0.33 0.00 1.00 0 1
13.6 0.67 0.30 0.00 0.50 0.50 1 1
11.7 0.33 0.00 0.00 0.00 0.00 1 1
12.4 0.78 0.30 0.00 0.50 0.00 0 1
13.35 0.89 0.50 0.67 0.50 1.00 1 1
11.4 0.78 0.40 0.00 0.00 1.00 0 1
14.9 0.78 0.50 0.67 0.00 0.50 0 1
19.9 0.89 0.70 1.00 1.00 0.50 0 1
17.75 0.89 0.40 1.00 0.50 1.00 1 1
11.2 0.78 0.80 0.67 0.50 1.00 0 1
14.6 0.78 0.60 0.33 0.50 1.00 0 1
17.6 0.67 0.40 0.33 0.00 0.50 1 1
14.05 0.89 0.50 0.33 0.50 0.00 1 1
16.1 0.89 0.50 0.00 0.50 1.00 1 1
13.35 0.78 0.30 0.33 0.00 1.00 1 1
11.85 1.00 0.60 0.00 0.50 1.00 1 1
11.95 1.00 0.30 0.67 0.00 0.50 1 1
14.75 0.78 0.60 1.00 0.50 0.50 0 1
15.15 0.78 0.30 0.33 0.00 1.00 0 1
13.2 0.89 0.70 0.67 1.00 1.00 1 1
16.85 0.89 0.70 1.00 0.00 1.00 0 1
7.85 0.67 0.60 1.00 0.50 1.00 0 1
7.7 1.00 0.50 0.33 0.50 0.00 1 1
12.6 0.67 0.50 0.33 0.00 0.50 0 1
7.85 0.56 0.40 0.00 0.00 1.00 0 1
10.95 0.78 0.40 0.33 1.00 1.00 0 1
12.35 1.00 0.70 1.00 0.00 1.00 0 1
9.95 0.67 0.20 0.00 0.50 0.00 0 1
14.9 0.78 0.50 0.67 0.00 0.50 0 1
16.65 0.56 0.40 0.67 0.50 0.00 0 1
13.4 1.00 0.20 0.67 1.00 1.00 0 1
13.95 0.89 0.50 0.67 0.00 0.00 0 1
15.7 0.44 0.40 0.00 0.00 1.00 0 1
16.85 1.00 0.70 1.00 1.00 1.00 0 1
10.95 0.89 0.60 0.67 1.00 0.00 0 1
15.35 0.78 0.40 0.00 0.00 0.00 0 1
12.2 0.89 0.50 0.67 1.00 1.00 0 1
15.1 0.11 0.00 0.00 0.00 0.00 0 1
17.75 0.89 0.70 0.67 0.50 1.00 0 1
15.2 0.89 0.40 0.67 0.00 1.00 0 1
14.6 1.00 0.50 1.00 0.00 1.00 1 1
16.65 0.89 0.60 0.67 0.00 0.50 0 1
8.1 1.00 0.80 0.67 0.50 0.50 0 1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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 time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.254 + 1.0665Calculation[t] -0.109419Algebraic_Reasoning[t] + 1.09292Proportionality_and_Ratio[t] + 0.0659268Probability_and_Sampling[t] -0.461067Estimation[t] + 0.587218Bin_Course_id[t] + 3.89492Bin_Year[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  9.254 +  1.0665Calculation[t] -0.109419Algebraic_Reasoning[t] +  1.09292Proportionality_and_Ratio[t] +  0.0659268Probability_and_Sampling[t] -0.461067Estimation[t] +  0.587218Bin_Course_id[t] +  3.89492Bin_Year[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  9.254 +  1.0665Calculation[t] -0.109419Algebraic_Reasoning[t] +  1.09292Proportionality_and_Ratio[t] +  0.0659268Probability_and_Sampling[t] -0.461067Estimation[t] +  0.587218Bin_Course_id[t] +  3.89492Bin_Year[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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
TOT[t] = + 9.254 + 1.0665Calculation[t] -0.109419Algebraic_Reasoning[t] + 1.09292Proportionality_and_Ratio[t] + 0.0659268Probability_and_Sampling[t] -0.461067Estimation[t] + 0.587218Bin_Course_id[t] + 3.89492Bin_Year[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.2540.82930711.163.87396e-241.93698e-24
Calculation1.06651.112670.95850.3386420.169321
Algebraic_Reasoning-0.1094191.03903-0.10530.9162070.458103
Proportionality_and_Ratio1.092920.5271242.0730.03905870.0195293
Probability_and_Sampling0.06592680.4817920.13680.8912590.44563
Estimation-0.4610670.461445-0.99920.3185760.159288
Bin_Course_id0.5872180.3450391.7020.08989440.0449472
Bin_Year3.894920.34259311.377.52739e-253.76369e-25

\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) & 9.254 & 0.829307 & 11.16 & 3.87396e-24 & 1.93698e-24 \tabularnewline
Calculation & 1.0665 & 1.11267 & 0.9585 & 0.338642 & 0.169321 \tabularnewline
Algebraic_Reasoning & -0.109419 & 1.03903 & -0.1053 & 0.916207 & 0.458103 \tabularnewline
Proportionality_and_Ratio & 1.09292 & 0.527124 & 2.073 & 0.0390587 & 0.0195293 \tabularnewline
Probability_and_Sampling & 0.0659268 & 0.481792 & 0.1368 & 0.891259 & 0.44563 \tabularnewline
Estimation & -0.461067 & 0.461445 & -0.9992 & 0.318576 & 0.159288 \tabularnewline
Bin_Course_id & 0.587218 & 0.345039 & 1.702 & 0.0898944 & 0.0449472 \tabularnewline
Bin_Year & 3.89492 & 0.342593 & 11.37 & 7.52739e-25 & 3.76369e-25 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&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]9.254[/C][C]0.829307[/C][C]11.16[/C][C]3.87396e-24[/C][C]1.93698e-24[/C][/ROW]
[ROW][C]Calculation[/C][C]1.0665[/C][C]1.11267[/C][C]0.9585[/C][C]0.338642[/C][C]0.169321[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.109419[/C][C]1.03903[/C][C]-0.1053[/C][C]0.916207[/C][C]0.458103[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.09292[/C][C]0.527124[/C][C]2.073[/C][C]0.0390587[/C][C]0.0195293[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.0659268[/C][C]0.481792[/C][C]0.1368[/C][C]0.891259[/C][C]0.44563[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.461067[/C][C]0.461445[/C][C]-0.9992[/C][C]0.318576[/C][C]0.159288[/C][/ROW]
[ROW][C]Bin_Course_id[/C][C]0.587218[/C][C]0.345039[/C][C]1.702[/C][C]0.0898944[/C][C]0.0449472[/C][/ROW]
[ROW][C]Bin_Year[/C][C]3.89492[/C][C]0.342593[/C][C]11.37[/C][C]7.52739e-25[/C][C]3.76369e-25[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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)9.2540.82930711.163.87396e-241.93698e-24
Calculation1.06651.112670.95850.3386420.169321
Algebraic_Reasoning-0.1094191.03903-0.10530.9162070.458103
Proportionality_and_Ratio1.092920.5271242.0730.03905870.0195293
Probability_and_Sampling0.06592680.4817920.13680.8912590.44563
Estimation-0.4610670.461445-0.99920.3185760.159288
Bin_Course_id0.5872180.3450391.7020.08989440.0449472
Bin_Year3.894920.34259311.377.52739e-253.76369e-25






Multiple Linear Regression - Regression Statistics
Multiple R0.584213
R-squared0.341304
Adjusted R-squared0.324718
F-TEST (value)20.578
F-TEST (DF numerator)7
F-TEST (DF denominator)278
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81144
Sum Squared Residuals2197.37

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.584213 \tabularnewline
R-squared & 0.341304 \tabularnewline
Adjusted R-squared & 0.324718 \tabularnewline
F-TEST (value) & 20.578 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 278 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.81144 \tabularnewline
Sum Squared Residuals & 2197.37 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.584213[/C][/ROW]
[ROW][C]R-squared[/C][C]0.341304[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.324718[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]20.578[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]278[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.81144[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2197.37[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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 R0.584213
R-squared0.341304
Adjusted R-squared0.324718
F-TEST (value)20.578
F-TEST (DF numerator)7
F-TEST (DF denominator)278
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.81144
Sum Squared Residuals2197.37






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.35471.54527
27.411.1462-3.74622
312.210.66831.53175
412.811.01781.78218
57.410.7357-3.33569
66.710.3187-3.61867
712.610.44272.15731
814.811.51193.28815
913.311.20112.09893
1011.110.74680.35323
118.211.1421-2.94212
1211.411.7045-0.304455
136.410.4536-4.05363
1410.610.54910.050938
151211.01780.982175
166.311.0964-4.79636
1711.310.67210.627918
1811.910.90970.990273
199.310.4117-1.11174
209.610.1654-0.565385
211010.1901-0.190134
226.411.142-4.74199
2313.810.62433.17565
2410.810.5070.292968
2513.810.66813.13189
2611.711.5120.188007
2710.910.17130.728724
2816.110.17665.9234
2913.410.66112.73886
309.911.3785-1.47849
3111.511.03560.464388
328.310.2943-1.99429
3311.710.31851.38147
346.111.0289-4.9289
35911.2485-2.2485
369.711.3876-1.68756
3710.811.4698-0.669825
3810.311.5356-1.23561
3910.410.521-0.120999
4012.710.09692.60305
419.311.2704-1.97038
4211.811.0180.782038
435.911.1421-5.24212
4411.411.05080.349212
451310.65732.34269
4610.811.4958-0.695805
4712.310.20692.09308
4811.311.3877-0.0876947
4911.810.30741.49255
507.99.74225-1.84225
5112.710.27462.42538
5212.310.67411.62591
5311.610.72710.872933
546.79.82251-3.12251
5510.910.9883-0.0883204
5612.110.03532.06475
5713.310.66232.63772
5810.111.1792-1.07918
595.710.674-4.97396
6014.310.28154.01853
6189.94472-1.94472
6213.310.52622.77382
639.311.3878-2.08783
6412.510.15742.34255
657.611.1878-3.58777
6615.911.38764.51244
679.210.3185-1.11853
689.110.8132-1.71316
6911.110.95540.144643
701311.1681.83203
7114.511.52062.97942
7212.29.716272.48373
7312.310.63541.66457
7411.411.24840.151642
758.810.3006-1.50063
7614.610.45264.14737
777.311.1462-3.84622
7812.610.64031.95974
79NANA2.10309
801311.18951.81047
8112.610.27682.32324
8213.212.99040.209569
839.912.3904-2.49041
847.77.303060.396945
8510.57.035733.46427
8613.412.83530.564687
8710.916.5417-5.6417
884.34.30538-0.00537525
8910.38.756721.54328
9011.810.94440.855607
9111.210.59130.608728
9211.413.4722-2.07222
938.64.724523.87548
9413.211.03762.16241
9512.616.8573-4.25735
965.65.259150.340852
979.911.0637-1.16372
988.810.6701-1.87009
997.78.37646-0.676463
100911.8655-2.86552
1017.36.616120.683875
10211.48.241693.15831
10313.616.0463-2.44626
1047.97.791830.108173
10510.711.3154-0.615432
10610.311.9467-1.64667
1078.38.51157-0.211565
1089.65.317944.28206
10914.215.6687-1.46869
1108.54.477824.02218
11113.519.3615-5.86147
1124.98.94155-4.04155
1136.46.48331-0.0833085
1149.68.661140.93886
11511.610.6960.904023
11611.120.8572-9.75721
1174.356.5223-2.1723
11812.79.320293.37971
11918.115.71762.38241
12017.8515.81922.03085
12116.617.5892-0.989169
12212.610.76261.8374
12317.112.98964.11039
12419.118.01911.08088
12516.117.0437-0.943702
12613.359.639063.71094
12718.418.9625-0.562466
12814.718.7891-4.08906
12910.611.9568-1.3568
13012.610.69781.9022
13116.216.7873-0.587329
13213.69.012864.58714
13318.919.7568-0.856786
13414.114.9393-0.839335
13514.513.10891.39113
13616.1516.3086-0.158647
13714.7514.42670.323276
13814.817.44-2.64003
13912.4514.3499-1.89986
14012.6510.16142.48864
14117.3524.2411-6.89112
1428.65.230063.36994
14318.417.48720.912818
14416.118.8874-2.78736
14511.68.4463.154
14617.7516.58811.16192
14715.2512.54572.70429
14817.6516.58521.06482
14915.613.35722.24279
15016.3513.96062.38941
15117.6517.9811-0.331092
15213.616.4461-2.84612
15311.711.7899-0.0898838
15414.3513.69920.650842
15514.7511.83932.91066
15618.2522.772-4.52196
1579.99.435170.464832
1581613.00152.99848
15918.2515.58052.66952
16016.8516.9784-0.128358
16114.614.37620.223771
16213.8510.33483.51523
16318.9518.15650.793492
16415.614.93650.663536
16514.8517.6849-2.83493
16611.757.975393.77461
16718.4516.99061.45938
16815.914.41721.48284
16917.116.20920.890797
17016.111.14984.95018
17119.922.8525-2.95254
17210.956.932044.01796
17318.4518.453.46848e-05
17415.114.78430.315685
1751517.7629-2.76292
17611.359.747681.60232
17715.9512.15183.79822
17818.118.7319-0.631884
17914.614.16770.432272
18015.414.96770.432272
18115.411.76493.63513
18217.618.8351-1.23505
18313.358.441434.90857
18419.118.08471.01526
18515.3522.0456-6.69558
1867.68.66486-1.06486
18713.413.5543-0.154332
18813.910.53463.36539
18919.118.02351.07648
19015.2516.8309-1.58092
19112.911.57071.32932
19216.113.52072.57932
19317.3518.9707-1.62068
19413.1515.6534-2.50336
19512.1513.5715-1.42151
19612.616.5757-3.97566
19710.358.833551.51645
19815.419.9457-4.54574
1999.65.012934.58707
20018.218.2827-0.0826552
20113.613.57570.0243357
20214.8514.8609-0.0108779
20314.7514.15090.59914
20414.112.93021.16976
20514.912.38042.51962
20616.2512.01914.23088
20719.2519.6843-0.434323
20813.613.9898-0.389759
20913.612.86480.735151
21015.6517.926-2.27596
21112.7512.8362-0.0861902
21214.618.9633-4.36331
2139.8511.5146-1.66458
21412.6514.8281-2.17809
21511.95.848916.05109
21619.216.81332.38667
21716.620.1174-3.51742
21811.210.64140.558573
21915.2517.3616-2.11164
22011.912.3042-0.404207
22113.211.72991.47008
22216.3517.7895-1.43948
22312.410.75241.64761
22415.8516.2785-0.428527
22514.3511.30693.04307
22618.1521.4539-3.30392
22711.1510.24880.901204
22815.6511.87883.77118
22917.7523.4878-5.73778
2307.6510.224-2.57396
23112.3510.93361.41635
23215.611.49594.1041
23319.318.63420.665825
23415.212.65892.54106
23517.116.21920.880846
23615.612.48263.11739
23718.414.3764.02404
23819.0514.70544.34461
23918.5514.0464.504
24019.120.3475-1.24755
24113.115.4042-2.30422
24212.8517.5554-4.70539
2439.520.3798-10.8798
2444.56.58205-2.08205
24511.8512.4703-0.620292
24613.615.9881-2.38808
24711.713.2809-1.58092
24812.413.9848-1.58476
24913.3515.426-2.07595
25011.410.92780.472199
25114.99.949824.95018
25219.917.45642.44363
25317.7520.7474-2.99741
25411.210.44770.752305
25514.611.53713.06295
25617.618.5742-0.974237
25714.0512.15251.89749
25816.117.1848-1.08478
25913.3515.8089-2.45888
26011.8515.1715-3.32153
26111.9512.0105-0.0604881
26214.7513.44761.30244
26315.1516.8958-1.74584
26413.211.00342.19664
26516.8523.4626-6.61264
2667.8515.2916-7.44155
2677.79.03889-1.33889
26812.617.9913-5.39132
2697.8510.8025-2.95254
27010.9513.3707-2.42068
27112.3516.2745-3.92455
2729.959.47780.472199
27314.912.71762.18239
27416.6517.7807-1.13065
27513.414.2256-0.82565
27613.9511.36332.58666
27715.713.68662.01339
27816.8520.7306-3.88063
27910.959.537021.41298
28015.3517.5305-2.18051
28112.210.36621.83377
28215.111.67573.42434
28317.7516.87550.874475
28415.215.9798-0.779781
28514.612.48422.11583
28616.6523.2126-6.56257
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.3547 & 1.54527 \tabularnewline
2 & 7.4 & 11.1462 & -3.74622 \tabularnewline
3 & 12.2 & 10.6683 & 1.53175 \tabularnewline
4 & 12.8 & 11.0178 & 1.78218 \tabularnewline
5 & 7.4 & 10.7357 & -3.33569 \tabularnewline
6 & 6.7 & 10.3187 & -3.61867 \tabularnewline
7 & 12.6 & 10.4427 & 2.15731 \tabularnewline
8 & 14.8 & 11.5119 & 3.28815 \tabularnewline
9 & 13.3 & 11.2011 & 2.09893 \tabularnewline
10 & 11.1 & 10.7468 & 0.35323 \tabularnewline
11 & 8.2 & 11.1421 & -2.94212 \tabularnewline
12 & 11.4 & 11.7045 & -0.304455 \tabularnewline
13 & 6.4 & 10.4536 & -4.05363 \tabularnewline
14 & 10.6 & 10.5491 & 0.050938 \tabularnewline
15 & 12 & 11.0178 & 0.982175 \tabularnewline
16 & 6.3 & 11.0964 & -4.79636 \tabularnewline
17 & 11.3 & 10.6721 & 0.627918 \tabularnewline
18 & 11.9 & 10.9097 & 0.990273 \tabularnewline
19 & 9.3 & 10.4117 & -1.11174 \tabularnewline
20 & 9.6 & 10.1654 & -0.565385 \tabularnewline
21 & 10 & 10.1901 & -0.190134 \tabularnewline
22 & 6.4 & 11.142 & -4.74199 \tabularnewline
23 & 13.8 & 10.6243 & 3.17565 \tabularnewline
24 & 10.8 & 10.507 & 0.292968 \tabularnewline
25 & 13.8 & 10.6681 & 3.13189 \tabularnewline
26 & 11.7 & 11.512 & 0.188007 \tabularnewline
27 & 10.9 & 10.1713 & 0.728724 \tabularnewline
28 & 16.1 & 10.1766 & 5.9234 \tabularnewline
29 & 13.4 & 10.6611 & 2.73886 \tabularnewline
30 & 9.9 & 11.3785 & -1.47849 \tabularnewline
31 & 11.5 & 11.0356 & 0.464388 \tabularnewline
32 & 8.3 & 10.2943 & -1.99429 \tabularnewline
33 & 11.7 & 10.3185 & 1.38147 \tabularnewline
34 & 6.1 & 11.0289 & -4.9289 \tabularnewline
35 & 9 & 11.2485 & -2.2485 \tabularnewline
36 & 9.7 & 11.3876 & -1.68756 \tabularnewline
37 & 10.8 & 11.4698 & -0.669825 \tabularnewline
38 & 10.3 & 11.5356 & -1.23561 \tabularnewline
39 & 10.4 & 10.521 & -0.120999 \tabularnewline
40 & 12.7 & 10.0969 & 2.60305 \tabularnewline
41 & 9.3 & 11.2704 & -1.97038 \tabularnewline
42 & 11.8 & 11.018 & 0.782038 \tabularnewline
43 & 5.9 & 11.1421 & -5.24212 \tabularnewline
44 & 11.4 & 11.0508 & 0.349212 \tabularnewline
45 & 13 & 10.6573 & 2.34269 \tabularnewline
46 & 10.8 & 11.4958 & -0.695805 \tabularnewline
47 & 12.3 & 10.2069 & 2.09308 \tabularnewline
48 & 11.3 & 11.3877 & -0.0876947 \tabularnewline
49 & 11.8 & 10.3074 & 1.49255 \tabularnewline
50 & 7.9 & 9.74225 & -1.84225 \tabularnewline
51 & 12.7 & 10.2746 & 2.42538 \tabularnewline
52 & 12.3 & 10.6741 & 1.62591 \tabularnewline
53 & 11.6 & 10.7271 & 0.872933 \tabularnewline
54 & 6.7 & 9.82251 & -3.12251 \tabularnewline
55 & 10.9 & 10.9883 & -0.0883204 \tabularnewline
56 & 12.1 & 10.0353 & 2.06475 \tabularnewline
57 & 13.3 & 10.6623 & 2.63772 \tabularnewline
58 & 10.1 & 11.1792 & -1.07918 \tabularnewline
59 & 5.7 & 10.674 & -4.97396 \tabularnewline
60 & 14.3 & 10.2815 & 4.01853 \tabularnewline
61 & 8 & 9.94472 & -1.94472 \tabularnewline
62 & 13.3 & 10.5262 & 2.77382 \tabularnewline
63 & 9.3 & 11.3878 & -2.08783 \tabularnewline
64 & 12.5 & 10.1574 & 2.34255 \tabularnewline
65 & 7.6 & 11.1878 & -3.58777 \tabularnewline
66 & 15.9 & 11.3876 & 4.51244 \tabularnewline
67 & 9.2 & 10.3185 & -1.11853 \tabularnewline
68 & 9.1 & 10.8132 & -1.71316 \tabularnewline
69 & 11.1 & 10.9554 & 0.144643 \tabularnewline
70 & 13 & 11.168 & 1.83203 \tabularnewline
71 & 14.5 & 11.5206 & 2.97942 \tabularnewline
72 & 12.2 & 9.71627 & 2.48373 \tabularnewline
73 & 12.3 & 10.6354 & 1.66457 \tabularnewline
74 & 11.4 & 11.2484 & 0.151642 \tabularnewline
75 & 8.8 & 10.3006 & -1.50063 \tabularnewline
76 & 14.6 & 10.4526 & 4.14737 \tabularnewline
77 & 7.3 & 11.1462 & -3.84622 \tabularnewline
78 & 12.6 & 10.6403 & 1.95974 \tabularnewline
79 & NA & NA & 2.10309 \tabularnewline
80 & 13 & 11.1895 & 1.81047 \tabularnewline
81 & 12.6 & 10.2768 & 2.32324 \tabularnewline
82 & 13.2 & 12.9904 & 0.209569 \tabularnewline
83 & 9.9 & 12.3904 & -2.49041 \tabularnewline
84 & 7.7 & 7.30306 & 0.396945 \tabularnewline
85 & 10.5 & 7.03573 & 3.46427 \tabularnewline
86 & 13.4 & 12.8353 & 0.564687 \tabularnewline
87 & 10.9 & 16.5417 & -5.6417 \tabularnewline
88 & 4.3 & 4.30538 & -0.00537525 \tabularnewline
89 & 10.3 & 8.75672 & 1.54328 \tabularnewline
90 & 11.8 & 10.9444 & 0.855607 \tabularnewline
91 & 11.2 & 10.5913 & 0.608728 \tabularnewline
92 & 11.4 & 13.4722 & -2.07222 \tabularnewline
93 & 8.6 & 4.72452 & 3.87548 \tabularnewline
94 & 13.2 & 11.0376 & 2.16241 \tabularnewline
95 & 12.6 & 16.8573 & -4.25735 \tabularnewline
96 & 5.6 & 5.25915 & 0.340852 \tabularnewline
97 & 9.9 & 11.0637 & -1.16372 \tabularnewline
98 & 8.8 & 10.6701 & -1.87009 \tabularnewline
99 & 7.7 & 8.37646 & -0.676463 \tabularnewline
100 & 9 & 11.8655 & -2.86552 \tabularnewline
101 & 7.3 & 6.61612 & 0.683875 \tabularnewline
102 & 11.4 & 8.24169 & 3.15831 \tabularnewline
103 & 13.6 & 16.0463 & -2.44626 \tabularnewline
104 & 7.9 & 7.79183 & 0.108173 \tabularnewline
105 & 10.7 & 11.3154 & -0.615432 \tabularnewline
106 & 10.3 & 11.9467 & -1.64667 \tabularnewline
107 & 8.3 & 8.51157 & -0.211565 \tabularnewline
108 & 9.6 & 5.31794 & 4.28206 \tabularnewline
109 & 14.2 & 15.6687 & -1.46869 \tabularnewline
110 & 8.5 & 4.47782 & 4.02218 \tabularnewline
111 & 13.5 & 19.3615 & -5.86147 \tabularnewline
112 & 4.9 & 8.94155 & -4.04155 \tabularnewline
113 & 6.4 & 6.48331 & -0.0833085 \tabularnewline
114 & 9.6 & 8.66114 & 0.93886 \tabularnewline
115 & 11.6 & 10.696 & 0.904023 \tabularnewline
116 & 11.1 & 20.8572 & -9.75721 \tabularnewline
117 & 4.35 & 6.5223 & -2.1723 \tabularnewline
118 & 12.7 & 9.32029 & 3.37971 \tabularnewline
119 & 18.1 & 15.7176 & 2.38241 \tabularnewline
120 & 17.85 & 15.8192 & 2.03085 \tabularnewline
121 & 16.6 & 17.5892 & -0.989169 \tabularnewline
122 & 12.6 & 10.7626 & 1.8374 \tabularnewline
123 & 17.1 & 12.9896 & 4.11039 \tabularnewline
124 & 19.1 & 18.0191 & 1.08088 \tabularnewline
125 & 16.1 & 17.0437 & -0.943702 \tabularnewline
126 & 13.35 & 9.63906 & 3.71094 \tabularnewline
127 & 18.4 & 18.9625 & -0.562466 \tabularnewline
128 & 14.7 & 18.7891 & -4.08906 \tabularnewline
129 & 10.6 & 11.9568 & -1.3568 \tabularnewline
130 & 12.6 & 10.6978 & 1.9022 \tabularnewline
131 & 16.2 & 16.7873 & -0.587329 \tabularnewline
132 & 13.6 & 9.01286 & 4.58714 \tabularnewline
133 & 18.9 & 19.7568 & -0.856786 \tabularnewline
134 & 14.1 & 14.9393 & -0.839335 \tabularnewline
135 & 14.5 & 13.1089 & 1.39113 \tabularnewline
136 & 16.15 & 16.3086 & -0.158647 \tabularnewline
137 & 14.75 & 14.4267 & 0.323276 \tabularnewline
138 & 14.8 & 17.44 & -2.64003 \tabularnewline
139 & 12.45 & 14.3499 & -1.89986 \tabularnewline
140 & 12.65 & 10.1614 & 2.48864 \tabularnewline
141 & 17.35 & 24.2411 & -6.89112 \tabularnewline
142 & 8.6 & 5.23006 & 3.36994 \tabularnewline
143 & 18.4 & 17.4872 & 0.912818 \tabularnewline
144 & 16.1 & 18.8874 & -2.78736 \tabularnewline
145 & 11.6 & 8.446 & 3.154 \tabularnewline
146 & 17.75 & 16.5881 & 1.16192 \tabularnewline
147 & 15.25 & 12.5457 & 2.70429 \tabularnewline
148 & 17.65 & 16.5852 & 1.06482 \tabularnewline
149 & 15.6 & 13.3572 & 2.24279 \tabularnewline
150 & 16.35 & 13.9606 & 2.38941 \tabularnewline
151 & 17.65 & 17.9811 & -0.331092 \tabularnewline
152 & 13.6 & 16.4461 & -2.84612 \tabularnewline
153 & 11.7 & 11.7899 & -0.0898838 \tabularnewline
154 & 14.35 & 13.6992 & 0.650842 \tabularnewline
155 & 14.75 & 11.8393 & 2.91066 \tabularnewline
156 & 18.25 & 22.772 & -4.52196 \tabularnewline
157 & 9.9 & 9.43517 & 0.464832 \tabularnewline
158 & 16 & 13.0015 & 2.99848 \tabularnewline
159 & 18.25 & 15.5805 & 2.66952 \tabularnewline
160 & 16.85 & 16.9784 & -0.128358 \tabularnewline
161 & 14.6 & 14.3762 & 0.223771 \tabularnewline
162 & 13.85 & 10.3348 & 3.51523 \tabularnewline
163 & 18.95 & 18.1565 & 0.793492 \tabularnewline
164 & 15.6 & 14.9365 & 0.663536 \tabularnewline
165 & 14.85 & 17.6849 & -2.83493 \tabularnewline
166 & 11.75 & 7.97539 & 3.77461 \tabularnewline
167 & 18.45 & 16.9906 & 1.45938 \tabularnewline
168 & 15.9 & 14.4172 & 1.48284 \tabularnewline
169 & 17.1 & 16.2092 & 0.890797 \tabularnewline
170 & 16.1 & 11.1498 & 4.95018 \tabularnewline
171 & 19.9 & 22.8525 & -2.95254 \tabularnewline
172 & 10.95 & 6.93204 & 4.01796 \tabularnewline
173 & 18.45 & 18.45 & 3.46848e-05 \tabularnewline
174 & 15.1 & 14.7843 & 0.315685 \tabularnewline
175 & 15 & 17.7629 & -2.76292 \tabularnewline
176 & 11.35 & 9.74768 & 1.60232 \tabularnewline
177 & 15.95 & 12.1518 & 3.79822 \tabularnewline
178 & 18.1 & 18.7319 & -0.631884 \tabularnewline
179 & 14.6 & 14.1677 & 0.432272 \tabularnewline
180 & 15.4 & 14.9677 & 0.432272 \tabularnewline
181 & 15.4 & 11.7649 & 3.63513 \tabularnewline
182 & 17.6 & 18.8351 & -1.23505 \tabularnewline
183 & 13.35 & 8.44143 & 4.90857 \tabularnewline
184 & 19.1 & 18.0847 & 1.01526 \tabularnewline
185 & 15.35 & 22.0456 & -6.69558 \tabularnewline
186 & 7.6 & 8.66486 & -1.06486 \tabularnewline
187 & 13.4 & 13.5543 & -0.154332 \tabularnewline
188 & 13.9 & 10.5346 & 3.36539 \tabularnewline
189 & 19.1 & 18.0235 & 1.07648 \tabularnewline
190 & 15.25 & 16.8309 & -1.58092 \tabularnewline
191 & 12.9 & 11.5707 & 1.32932 \tabularnewline
192 & 16.1 & 13.5207 & 2.57932 \tabularnewline
193 & 17.35 & 18.9707 & -1.62068 \tabularnewline
194 & 13.15 & 15.6534 & -2.50336 \tabularnewline
195 & 12.15 & 13.5715 & -1.42151 \tabularnewline
196 & 12.6 & 16.5757 & -3.97566 \tabularnewline
197 & 10.35 & 8.83355 & 1.51645 \tabularnewline
198 & 15.4 & 19.9457 & -4.54574 \tabularnewline
199 & 9.6 & 5.01293 & 4.58707 \tabularnewline
200 & 18.2 & 18.2827 & -0.0826552 \tabularnewline
201 & 13.6 & 13.5757 & 0.0243357 \tabularnewline
202 & 14.85 & 14.8609 & -0.0108779 \tabularnewline
203 & 14.75 & 14.1509 & 0.59914 \tabularnewline
204 & 14.1 & 12.9302 & 1.16976 \tabularnewline
205 & 14.9 & 12.3804 & 2.51962 \tabularnewline
206 & 16.25 & 12.0191 & 4.23088 \tabularnewline
207 & 19.25 & 19.6843 & -0.434323 \tabularnewline
208 & 13.6 & 13.9898 & -0.389759 \tabularnewline
209 & 13.6 & 12.8648 & 0.735151 \tabularnewline
210 & 15.65 & 17.926 & -2.27596 \tabularnewline
211 & 12.75 & 12.8362 & -0.0861902 \tabularnewline
212 & 14.6 & 18.9633 & -4.36331 \tabularnewline
213 & 9.85 & 11.5146 & -1.66458 \tabularnewline
214 & 12.65 & 14.8281 & -2.17809 \tabularnewline
215 & 11.9 & 5.84891 & 6.05109 \tabularnewline
216 & 19.2 & 16.8133 & 2.38667 \tabularnewline
217 & 16.6 & 20.1174 & -3.51742 \tabularnewline
218 & 11.2 & 10.6414 & 0.558573 \tabularnewline
219 & 15.25 & 17.3616 & -2.11164 \tabularnewline
220 & 11.9 & 12.3042 & -0.404207 \tabularnewline
221 & 13.2 & 11.7299 & 1.47008 \tabularnewline
222 & 16.35 & 17.7895 & -1.43948 \tabularnewline
223 & 12.4 & 10.7524 & 1.64761 \tabularnewline
224 & 15.85 & 16.2785 & -0.428527 \tabularnewline
225 & 14.35 & 11.3069 & 3.04307 \tabularnewline
226 & 18.15 & 21.4539 & -3.30392 \tabularnewline
227 & 11.15 & 10.2488 & 0.901204 \tabularnewline
228 & 15.65 & 11.8788 & 3.77118 \tabularnewline
229 & 17.75 & 23.4878 & -5.73778 \tabularnewline
230 & 7.65 & 10.224 & -2.57396 \tabularnewline
231 & 12.35 & 10.9336 & 1.41635 \tabularnewline
232 & 15.6 & 11.4959 & 4.1041 \tabularnewline
233 & 19.3 & 18.6342 & 0.665825 \tabularnewline
234 & 15.2 & 12.6589 & 2.54106 \tabularnewline
235 & 17.1 & 16.2192 & 0.880846 \tabularnewline
236 & 15.6 & 12.4826 & 3.11739 \tabularnewline
237 & 18.4 & 14.376 & 4.02404 \tabularnewline
238 & 19.05 & 14.7054 & 4.34461 \tabularnewline
239 & 18.55 & 14.046 & 4.504 \tabularnewline
240 & 19.1 & 20.3475 & -1.24755 \tabularnewline
241 & 13.1 & 15.4042 & -2.30422 \tabularnewline
242 & 12.85 & 17.5554 & -4.70539 \tabularnewline
243 & 9.5 & 20.3798 & -10.8798 \tabularnewline
244 & 4.5 & 6.58205 & -2.08205 \tabularnewline
245 & 11.85 & 12.4703 & -0.620292 \tabularnewline
246 & 13.6 & 15.9881 & -2.38808 \tabularnewline
247 & 11.7 & 13.2809 & -1.58092 \tabularnewline
248 & 12.4 & 13.9848 & -1.58476 \tabularnewline
249 & 13.35 & 15.426 & -2.07595 \tabularnewline
250 & 11.4 & 10.9278 & 0.472199 \tabularnewline
251 & 14.9 & 9.94982 & 4.95018 \tabularnewline
252 & 19.9 & 17.4564 & 2.44363 \tabularnewline
253 & 17.75 & 20.7474 & -2.99741 \tabularnewline
254 & 11.2 & 10.4477 & 0.752305 \tabularnewline
255 & 14.6 & 11.5371 & 3.06295 \tabularnewline
256 & 17.6 & 18.5742 & -0.974237 \tabularnewline
257 & 14.05 & 12.1525 & 1.89749 \tabularnewline
258 & 16.1 & 17.1848 & -1.08478 \tabularnewline
259 & 13.35 & 15.8089 & -2.45888 \tabularnewline
260 & 11.85 & 15.1715 & -3.32153 \tabularnewline
261 & 11.95 & 12.0105 & -0.0604881 \tabularnewline
262 & 14.75 & 13.4476 & 1.30244 \tabularnewline
263 & 15.15 & 16.8958 & -1.74584 \tabularnewline
264 & 13.2 & 11.0034 & 2.19664 \tabularnewline
265 & 16.85 & 23.4626 & -6.61264 \tabularnewline
266 & 7.85 & 15.2916 & -7.44155 \tabularnewline
267 & 7.7 & 9.03889 & -1.33889 \tabularnewline
268 & 12.6 & 17.9913 & -5.39132 \tabularnewline
269 & 7.85 & 10.8025 & -2.95254 \tabularnewline
270 & 10.95 & 13.3707 & -2.42068 \tabularnewline
271 & 12.35 & 16.2745 & -3.92455 \tabularnewline
272 & 9.95 & 9.4778 & 0.472199 \tabularnewline
273 & 14.9 & 12.7176 & 2.18239 \tabularnewline
274 & 16.65 & 17.7807 & -1.13065 \tabularnewline
275 & 13.4 & 14.2256 & -0.82565 \tabularnewline
276 & 13.95 & 11.3633 & 2.58666 \tabularnewline
277 & 15.7 & 13.6866 & 2.01339 \tabularnewline
278 & 16.85 & 20.7306 & -3.88063 \tabularnewline
279 & 10.95 & 9.53702 & 1.41298 \tabularnewline
280 & 15.35 & 17.5305 & -2.18051 \tabularnewline
281 & 12.2 & 10.3662 & 1.83377 \tabularnewline
282 & 15.1 & 11.6757 & 3.42434 \tabularnewline
283 & 17.75 & 16.8755 & 0.874475 \tabularnewline
284 & 15.2 & 15.9798 & -0.779781 \tabularnewline
285 & 14.6 & 12.4842 & 2.11583 \tabularnewline
286 & 16.65 & 23.2126 & -6.56257 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]11.3547[/C][C]1.54527[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.1462[/C][C]-3.74622[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]10.6683[/C][C]1.53175[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]11.0178[/C][C]1.78218[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]10.7357[/C][C]-3.33569[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]10.3187[/C][C]-3.61867[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]10.4427[/C][C]2.15731[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]11.5119[/C][C]3.28815[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]11.2011[/C][C]2.09893[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]10.7468[/C][C]0.35323[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]11.1421[/C][C]-2.94212[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]11.7045[/C][C]-0.304455[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]10.4536[/C][C]-4.05363[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]10.5491[/C][C]0.050938[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]11.0178[/C][C]0.982175[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]11.0964[/C][C]-4.79636[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]10.6721[/C][C]0.627918[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]10.9097[/C][C]0.990273[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]10.4117[/C][C]-1.11174[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]10.1654[/C][C]-0.565385[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]10.1901[/C][C]-0.190134[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]11.142[/C][C]-4.74199[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]10.6243[/C][C]3.17565[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]10.507[/C][C]0.292968[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]10.6681[/C][C]3.13189[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]11.512[/C][C]0.188007[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]10.1713[/C][C]0.728724[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]10.1766[/C][C]5.9234[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]10.6611[/C][C]2.73886[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]11.3785[/C][C]-1.47849[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]11.0356[/C][C]0.464388[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]10.2943[/C][C]-1.99429[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]10.3185[/C][C]1.38147[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]11.0289[/C][C]-4.9289[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]11.2485[/C][C]-2.2485[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]11.3876[/C][C]-1.68756[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]11.4698[/C][C]-0.669825[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]11.5356[/C][C]-1.23561[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]10.521[/C][C]-0.120999[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]10.0969[/C][C]2.60305[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]11.2704[/C][C]-1.97038[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]11.018[/C][C]0.782038[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]11.1421[/C][C]-5.24212[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]11.0508[/C][C]0.349212[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]10.6573[/C][C]2.34269[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]11.4958[/C][C]-0.695805[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]10.2069[/C][C]2.09308[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]11.3877[/C][C]-0.0876947[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]10.3074[/C][C]1.49255[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]9.74225[/C][C]-1.84225[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]10.2746[/C][C]2.42538[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]10.6741[/C][C]1.62591[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]10.7271[/C][C]0.872933[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]9.82251[/C][C]-3.12251[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]10.9883[/C][C]-0.0883204[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]10.0353[/C][C]2.06475[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]10.6623[/C][C]2.63772[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]11.1792[/C][C]-1.07918[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]10.674[/C][C]-4.97396[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]10.2815[/C][C]4.01853[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]9.94472[/C][C]-1.94472[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]10.5262[/C][C]2.77382[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]11.3878[/C][C]-2.08783[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]10.1574[/C][C]2.34255[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]11.1878[/C][C]-3.58777[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]11.3876[/C][C]4.51244[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]10.3185[/C][C]-1.11853[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]10.8132[/C][C]-1.71316[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]10.9554[/C][C]0.144643[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]11.168[/C][C]1.83203[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]11.5206[/C][C]2.97942[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]9.71627[/C][C]2.48373[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]10.6354[/C][C]1.66457[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]11.2484[/C][C]0.151642[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]10.3006[/C][C]-1.50063[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]10.4526[/C][C]4.14737[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]11.1462[/C][C]-3.84622[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]10.6403[/C][C]1.95974[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]2.10309[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]11.1895[/C][C]1.81047[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]10.2768[/C][C]2.32324[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]12.9904[/C][C]0.209569[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]12.3904[/C][C]-2.49041[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]7.30306[/C][C]0.396945[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]7.03573[/C][C]3.46427[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]12.8353[/C][C]0.564687[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]16.5417[/C][C]-5.6417[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]4.30538[/C][C]-0.00537525[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]8.75672[/C][C]1.54328[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]10.9444[/C][C]0.855607[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]10.5913[/C][C]0.608728[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]13.4722[/C][C]-2.07222[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]4.72452[/C][C]3.87548[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]11.0376[/C][C]2.16241[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]16.8573[/C][C]-4.25735[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]5.25915[/C][C]0.340852[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]11.0637[/C][C]-1.16372[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]10.6701[/C][C]-1.87009[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]8.37646[/C][C]-0.676463[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]11.8655[/C][C]-2.86552[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]6.61612[/C][C]0.683875[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]8.24169[/C][C]3.15831[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]16.0463[/C][C]-2.44626[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]7.79183[/C][C]0.108173[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]11.3154[/C][C]-0.615432[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]11.9467[/C][C]-1.64667[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]8.51157[/C][C]-0.211565[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]5.31794[/C][C]4.28206[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]15.6687[/C][C]-1.46869[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]4.47782[/C][C]4.02218[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]19.3615[/C][C]-5.86147[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]8.94155[/C][C]-4.04155[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]6.48331[/C][C]-0.0833085[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]8.66114[/C][C]0.93886[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]10.696[/C][C]0.904023[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]20.8572[/C][C]-9.75721[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]6.5223[/C][C]-2.1723[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]9.32029[/C][C]3.37971[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]15.7176[/C][C]2.38241[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]15.8192[/C][C]2.03085[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]17.5892[/C][C]-0.989169[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]10.7626[/C][C]1.8374[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]12.9896[/C][C]4.11039[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]18.0191[/C][C]1.08088[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]17.0437[/C][C]-0.943702[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]9.63906[/C][C]3.71094[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]18.9625[/C][C]-0.562466[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]18.7891[/C][C]-4.08906[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]11.9568[/C][C]-1.3568[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]10.6978[/C][C]1.9022[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]16.7873[/C][C]-0.587329[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]9.01286[/C][C]4.58714[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]19.7568[/C][C]-0.856786[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]14.9393[/C][C]-0.839335[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]13.1089[/C][C]1.39113[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]16.3086[/C][C]-0.158647[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]14.4267[/C][C]0.323276[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]17.44[/C][C]-2.64003[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]14.3499[/C][C]-1.89986[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]10.1614[/C][C]2.48864[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]24.2411[/C][C]-6.89112[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]5.23006[/C][C]3.36994[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]17.4872[/C][C]0.912818[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]18.8874[/C][C]-2.78736[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]8.446[/C][C]3.154[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]16.5881[/C][C]1.16192[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]12.5457[/C][C]2.70429[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]16.5852[/C][C]1.06482[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]13.3572[/C][C]2.24279[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]13.9606[/C][C]2.38941[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]17.9811[/C][C]-0.331092[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]16.4461[/C][C]-2.84612[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]11.7899[/C][C]-0.0898838[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]13.6992[/C][C]0.650842[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]11.8393[/C][C]2.91066[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]22.772[/C][C]-4.52196[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]9.43517[/C][C]0.464832[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]13.0015[/C][C]2.99848[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]15.5805[/C][C]2.66952[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]16.9784[/C][C]-0.128358[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]14.3762[/C][C]0.223771[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]10.3348[/C][C]3.51523[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]18.1565[/C][C]0.793492[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]14.9365[/C][C]0.663536[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]17.6849[/C][C]-2.83493[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]7.97539[/C][C]3.77461[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]16.9906[/C][C]1.45938[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]14.4172[/C][C]1.48284[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]16.2092[/C][C]0.890797[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]11.1498[/C][C]4.95018[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]22.8525[/C][C]-2.95254[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]6.93204[/C][C]4.01796[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]18.45[/C][C]3.46848e-05[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]14.7843[/C][C]0.315685[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]17.7629[/C][C]-2.76292[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]9.74768[/C][C]1.60232[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]12.1518[/C][C]3.79822[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]18.7319[/C][C]-0.631884[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]14.1677[/C][C]0.432272[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]14.9677[/C][C]0.432272[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]11.7649[/C][C]3.63513[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]18.8351[/C][C]-1.23505[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]8.44143[/C][C]4.90857[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]18.0847[/C][C]1.01526[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]22.0456[/C][C]-6.69558[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]8.66486[/C][C]-1.06486[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]13.5543[/C][C]-0.154332[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]10.5346[/C][C]3.36539[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]18.0235[/C][C]1.07648[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]16.8309[/C][C]-1.58092[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]11.5707[/C][C]1.32932[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]13.5207[/C][C]2.57932[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]18.9707[/C][C]-1.62068[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]15.6534[/C][C]-2.50336[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]13.5715[/C][C]-1.42151[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]16.5757[/C][C]-3.97566[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]8.83355[/C][C]1.51645[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]19.9457[/C][C]-4.54574[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]5.01293[/C][C]4.58707[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]18.2827[/C][C]-0.0826552[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]13.5757[/C][C]0.0243357[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]14.8609[/C][C]-0.0108779[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]14.1509[/C][C]0.59914[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]12.9302[/C][C]1.16976[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]12.3804[/C][C]2.51962[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]12.0191[/C][C]4.23088[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]19.6843[/C][C]-0.434323[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.9898[/C][C]-0.389759[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]12.8648[/C][C]0.735151[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]17.926[/C][C]-2.27596[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]12.8362[/C][C]-0.0861902[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]18.9633[/C][C]-4.36331[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]11.5146[/C][C]-1.66458[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]14.8281[/C][C]-2.17809[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]5.84891[/C][C]6.05109[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]16.8133[/C][C]2.38667[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]20.1174[/C][C]-3.51742[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]10.6414[/C][C]0.558573[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]17.3616[/C][C]-2.11164[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]12.3042[/C][C]-0.404207[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]11.7299[/C][C]1.47008[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]17.7895[/C][C]-1.43948[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]10.7524[/C][C]1.64761[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]16.2785[/C][C]-0.428527[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]11.3069[/C][C]3.04307[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]21.4539[/C][C]-3.30392[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]10.2488[/C][C]0.901204[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]11.8788[/C][C]3.77118[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]23.4878[/C][C]-5.73778[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]10.224[/C][C]-2.57396[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]10.9336[/C][C]1.41635[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]11.4959[/C][C]4.1041[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]18.6342[/C][C]0.665825[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]12.6589[/C][C]2.54106[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]16.2192[/C][C]0.880846[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]12.4826[/C][C]3.11739[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]14.376[/C][C]4.02404[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]14.7054[/C][C]4.34461[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]14.046[/C][C]4.504[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]20.3475[/C][C]-1.24755[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]15.4042[/C][C]-2.30422[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]17.5554[/C][C]-4.70539[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]20.3798[/C][C]-10.8798[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]6.58205[/C][C]-2.08205[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]12.4703[/C][C]-0.620292[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]15.9881[/C][C]-2.38808[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]13.2809[/C][C]-1.58092[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]13.9848[/C][C]-1.58476[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]15.426[/C][C]-2.07595[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]10.9278[/C][C]0.472199[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]9.94982[/C][C]4.95018[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]17.4564[/C][C]2.44363[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]20.7474[/C][C]-2.99741[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]10.4477[/C][C]0.752305[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]11.5371[/C][C]3.06295[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]18.5742[/C][C]-0.974237[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]12.1525[/C][C]1.89749[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]17.1848[/C][C]-1.08478[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]15.8089[/C][C]-2.45888[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]15.1715[/C][C]-3.32153[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]12.0105[/C][C]-0.0604881[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]13.4476[/C][C]1.30244[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]16.8958[/C][C]-1.74584[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]11.0034[/C][C]2.19664[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]23.4626[/C][C]-6.61264[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]15.2916[/C][C]-7.44155[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]9.03889[/C][C]-1.33889[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]17.9913[/C][C]-5.39132[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]10.8025[/C][C]-2.95254[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]13.3707[/C][C]-2.42068[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]16.2745[/C][C]-3.92455[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]9.4778[/C][C]0.472199[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]12.7176[/C][C]2.18239[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]17.7807[/C][C]-1.13065[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]14.2256[/C][C]-0.82565[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]11.3633[/C][C]2.58666[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]13.6866[/C][C]2.01339[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]20.7306[/C][C]-3.88063[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]9.53702[/C][C]1.41298[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]17.5305[/C][C]-2.18051[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]10.3662[/C][C]1.83377[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]11.6757[/C][C]3.42434[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]16.8755[/C][C]0.874475[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]15.9798[/C][C]-0.779781[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]12.4842[/C][C]2.11583[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]23.2126[/C][C]-6.56257[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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
112.911.35471.54527
27.411.1462-3.74622
312.210.66831.53175
412.811.01781.78218
57.410.7357-3.33569
66.710.3187-3.61867
712.610.44272.15731
814.811.51193.28815
913.311.20112.09893
1011.110.74680.35323
118.211.1421-2.94212
1211.411.7045-0.304455
136.410.4536-4.05363
1410.610.54910.050938
151211.01780.982175
166.311.0964-4.79636
1711.310.67210.627918
1811.910.90970.990273
199.310.4117-1.11174
209.610.1654-0.565385
211010.1901-0.190134
226.411.142-4.74199
2313.810.62433.17565
2410.810.5070.292968
2513.810.66813.13189
2611.711.5120.188007
2710.910.17130.728724
2816.110.17665.9234
2913.410.66112.73886
309.911.3785-1.47849
3111.511.03560.464388
328.310.2943-1.99429
3311.710.31851.38147
346.111.0289-4.9289
35911.2485-2.2485
369.711.3876-1.68756
3710.811.4698-0.669825
3810.311.5356-1.23561
3910.410.521-0.120999
4012.710.09692.60305
419.311.2704-1.97038
4211.811.0180.782038
435.911.1421-5.24212
4411.411.05080.349212
451310.65732.34269
4610.811.4958-0.695805
4712.310.20692.09308
4811.311.3877-0.0876947
4911.810.30741.49255
507.99.74225-1.84225
5112.710.27462.42538
5212.310.67411.62591
5311.610.72710.872933
546.79.82251-3.12251
5510.910.9883-0.0883204
5612.110.03532.06475
5713.310.66232.63772
5810.111.1792-1.07918
595.710.674-4.97396
6014.310.28154.01853
6189.94472-1.94472
6213.310.52622.77382
639.311.3878-2.08783
6412.510.15742.34255
657.611.1878-3.58777
6615.911.38764.51244
679.210.3185-1.11853
689.110.8132-1.71316
6911.110.95540.144643
701311.1681.83203
7114.511.52062.97942
7212.29.716272.48373
7312.310.63541.66457
7411.411.24840.151642
758.810.3006-1.50063
7614.610.45264.14737
777.311.1462-3.84622
7812.610.64031.95974
79NANA2.10309
801311.18951.81047
8112.610.27682.32324
8213.212.99040.209569
839.912.3904-2.49041
847.77.303060.396945
8510.57.035733.46427
8613.412.83530.564687
8710.916.5417-5.6417
884.34.30538-0.00537525
8910.38.756721.54328
9011.810.94440.855607
9111.210.59130.608728
9211.413.4722-2.07222
938.64.724523.87548
9413.211.03762.16241
9512.616.8573-4.25735
965.65.259150.340852
979.911.0637-1.16372
988.810.6701-1.87009
997.78.37646-0.676463
100911.8655-2.86552
1017.36.616120.683875
10211.48.241693.15831
10313.616.0463-2.44626
1047.97.791830.108173
10510.711.3154-0.615432
10610.311.9467-1.64667
1078.38.51157-0.211565
1089.65.317944.28206
10914.215.6687-1.46869
1108.54.477824.02218
11113.519.3615-5.86147
1124.98.94155-4.04155
1136.46.48331-0.0833085
1149.68.661140.93886
11511.610.6960.904023
11611.120.8572-9.75721
1174.356.5223-2.1723
11812.79.320293.37971
11918.115.71762.38241
12017.8515.81922.03085
12116.617.5892-0.989169
12212.610.76261.8374
12317.112.98964.11039
12419.118.01911.08088
12516.117.0437-0.943702
12613.359.639063.71094
12718.418.9625-0.562466
12814.718.7891-4.08906
12910.611.9568-1.3568
13012.610.69781.9022
13116.216.7873-0.587329
13213.69.012864.58714
13318.919.7568-0.856786
13414.114.9393-0.839335
13514.513.10891.39113
13616.1516.3086-0.158647
13714.7514.42670.323276
13814.817.44-2.64003
13912.4514.3499-1.89986
14012.6510.16142.48864
14117.3524.2411-6.89112
1428.65.230063.36994
14318.417.48720.912818
14416.118.8874-2.78736
14511.68.4463.154
14617.7516.58811.16192
14715.2512.54572.70429
14817.6516.58521.06482
14915.613.35722.24279
15016.3513.96062.38941
15117.6517.9811-0.331092
15213.616.4461-2.84612
15311.711.7899-0.0898838
15414.3513.69920.650842
15514.7511.83932.91066
15618.2522.772-4.52196
1579.99.435170.464832
1581613.00152.99848
15918.2515.58052.66952
16016.8516.9784-0.128358
16114.614.37620.223771
16213.8510.33483.51523
16318.9518.15650.793492
16415.614.93650.663536
16514.8517.6849-2.83493
16611.757.975393.77461
16718.4516.99061.45938
16815.914.41721.48284
16917.116.20920.890797
17016.111.14984.95018
17119.922.8525-2.95254
17210.956.932044.01796
17318.4518.453.46848e-05
17415.114.78430.315685
1751517.7629-2.76292
17611.359.747681.60232
17715.9512.15183.79822
17818.118.7319-0.631884
17914.614.16770.432272
18015.414.96770.432272
18115.411.76493.63513
18217.618.8351-1.23505
18313.358.441434.90857
18419.118.08471.01526
18515.3522.0456-6.69558
1867.68.66486-1.06486
18713.413.5543-0.154332
18813.910.53463.36539
18919.118.02351.07648
19015.2516.8309-1.58092
19112.911.57071.32932
19216.113.52072.57932
19317.3518.9707-1.62068
19413.1515.6534-2.50336
19512.1513.5715-1.42151
19612.616.5757-3.97566
19710.358.833551.51645
19815.419.9457-4.54574
1999.65.012934.58707
20018.218.2827-0.0826552
20113.613.57570.0243357
20214.8514.8609-0.0108779
20314.7514.15090.59914
20414.112.93021.16976
20514.912.38042.51962
20616.2512.01914.23088
20719.2519.6843-0.434323
20813.613.9898-0.389759
20913.612.86480.735151
21015.6517.926-2.27596
21112.7512.8362-0.0861902
21214.618.9633-4.36331
2139.8511.5146-1.66458
21412.6514.8281-2.17809
21511.95.848916.05109
21619.216.81332.38667
21716.620.1174-3.51742
21811.210.64140.558573
21915.2517.3616-2.11164
22011.912.3042-0.404207
22113.211.72991.47008
22216.3517.7895-1.43948
22312.410.75241.64761
22415.8516.2785-0.428527
22514.3511.30693.04307
22618.1521.4539-3.30392
22711.1510.24880.901204
22815.6511.87883.77118
22917.7523.4878-5.73778
2307.6510.224-2.57396
23112.3510.93361.41635
23215.611.49594.1041
23319.318.63420.665825
23415.212.65892.54106
23517.116.21920.880846
23615.612.48263.11739
23718.414.3764.02404
23819.0514.70544.34461
23918.5514.0464.504
24019.120.3475-1.24755
24113.115.4042-2.30422
24212.8517.5554-4.70539
2439.520.3798-10.8798
2444.56.58205-2.08205
24511.8512.4703-0.620292
24613.615.9881-2.38808
24711.713.2809-1.58092
24812.413.9848-1.58476
24913.3515.426-2.07595
25011.410.92780.472199
25114.99.949824.95018
25219.917.45642.44363
25317.7520.7474-2.99741
25411.210.44770.752305
25514.611.53713.06295
25617.618.5742-0.974237
25714.0512.15251.89749
25816.117.1848-1.08478
25913.3515.8089-2.45888
26011.8515.1715-3.32153
26111.9512.0105-0.0604881
26214.7513.44761.30244
26315.1516.8958-1.74584
26413.211.00342.19664
26516.8523.4626-6.61264
2667.8515.2916-7.44155
2677.79.03889-1.33889
26812.617.9913-5.39132
2697.8510.8025-2.95254
27010.9513.3707-2.42068
27112.3516.2745-3.92455
2729.959.47780.472199
27314.912.71762.18239
27416.6517.7807-1.13065
27513.414.2256-0.82565
27613.9511.36332.58666
27715.713.68662.01339
27816.8520.7306-3.88063
27910.959.537021.41298
28015.3517.5305-2.18051
28112.210.36621.83377
28215.111.67573.42434
28317.7516.87550.874475
28415.215.9798-0.779781
28514.612.48422.11583
28616.6523.2126-6.56257
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7705370.4589260.229463
120.6375890.7248230.362411
130.8595170.2809670.140483
140.7842830.4314340.215717
150.7055650.5888690.294435
160.7724330.4551340.227567
170.6919860.6160280.308014
180.6122190.7755620.387781
190.5584120.8831760.441588
200.474050.94810.52595
210.3906530.7813050.609347
220.5341210.9317580.465879
230.6205990.7588010.379401
240.5638120.8723750.436188
250.531620.9367590.46838
260.486940.9738810.51306
270.4782460.9564920.521754
280.6272830.7454340.372717
290.575360.849280.42464
300.5348840.9302310.465116
310.4765970.9531940.523403
320.4368940.8737880.563106
330.3881080.7762160.611892
340.5093550.9812910.490645
350.468460.9369210.53154
360.4267020.8534040.573298
370.3754020.7508030.624598
380.3283840.6567670.671616
390.2867210.5734430.713279
400.2455760.4911520.754424
410.2163950.432790.783605
420.1863910.3727830.813609
430.2575810.5151620.742419
440.2185310.4370620.781469
450.2130560.4261130.786944
460.1782950.356590.821705
470.1489740.2979480.851026
480.1225460.2450920.877454
490.1025420.2050840.897458
500.1451620.2903250.854838
510.1376910.2753820.862309
520.1141190.2282380.885881
530.09311540.1862310.906885
540.1295270.2590530.870473
550.106240.2124790.89376
560.08943630.1788730.910564
570.09703370.1940670.902966
580.08142040.1628410.91858
590.1410.2820.859
600.1739730.3479470.826027
610.1566020.3132030.843398
620.1462320.2924640.853768
630.1337530.2675060.866247
640.1205620.2411230.879438
650.1188690.2377380.881131
660.16960.33920.8304
670.1538850.307770.846115
680.1391850.278370.860815
690.1193330.2386670.880667
700.1072990.2145980.892701
710.1432790.2865580.856721
720.1316140.2632270.868386
730.1168870.2337730.883113
740.09825560.1965110.901744
750.09162910.1832580.908371
760.1082920.2165840.891708
770.1271480.2542960.872852
780.1146890.2293770.885311
790.1024590.2049180.897541
800.08955720.1791140.910443
810.0838530.1677060.916147
820.06991940.1398390.930081
830.06782910.1356580.932171
840.05614930.1122990.943851
850.05602240.1120450.943978
860.04609660.09219330.953903
870.0979820.1959640.902018
880.08282290.1656460.917177
890.07120380.1424080.928796
900.05980850.1196170.940192
910.04976150.09952310.950238
920.04736640.09473270.952634
930.0548950.109790.945105
940.05135990.102720.94864
950.06835970.1367190.93164
960.05775770.1155150.942242
970.04984210.09968430.950158
980.04763410.09526820.952366
990.04112380.08224770.958876
1000.04361180.08722360.956388
1010.03611060.07222130.963889
1020.03932270.07864540.960677
1030.03677470.07354940.963225
1040.02999380.05998760.970006
1050.02449440.04898880.975506
1060.0229070.04581410.977093
1070.01874790.03749580.981252
1080.023910.04781990.97609
1090.02119220.04238430.978808
1100.03022630.06045260.969774
1110.05136050.1027210.94864
1120.06270680.1254140.937293
1130.05274750.1054950.947252
1140.0444010.0888020.955599
1150.03812290.07624570.961877
1160.06568450.1313690.934315
1170.09905220.1981040.900948
1180.1764640.3529290.823536
1190.1995490.3990990.800451
1200.2026660.4053310.797334
1210.1805710.3611420.819429
1220.1739430.3478860.826057
1230.2029250.405850.797075
1240.1810820.3621630.818918
1250.1633230.3266470.836677
1260.1792440.3584880.820756
1270.1592620.3185240.840738
1280.1855990.3711970.814401
1290.1679450.3358910.832055
1300.1551130.3102260.844887
1310.1364350.2728710.863565
1320.1619060.3238120.838094
1330.1440520.2881040.855948
1340.1280340.2560680.871966
1350.1160950.2321890.883905
1360.1005120.2010240.899488
1370.08920170.1784030.910798
1380.09154270.1830850.908457
1390.08601570.1720310.913984
1400.08285350.1657070.917147
1410.180340.3606790.81966
1420.1879440.3758880.812056
1430.1671410.3342820.832859
1440.168820.3376410.83118
1450.1730670.3461330.826933
1460.1555520.3111040.844448
1470.1516340.3032670.848366
1480.135230.270460.86477
1490.1294540.2589090.870546
1500.1223620.2447250.877638
1510.1061110.2122230.893889
1520.1077140.2154280.892286
1530.0927020.1854040.907298
1540.08000720.1600140.919993
1550.07849560.1569910.921504
1560.1006250.201250.899375
1570.08658920.1731780.913411
1580.08587550.1717510.914124
1590.08534890.1706980.914651
1600.07334570.1466910.926654
1610.06359830.1271970.936402
1620.06790720.1358140.932093
1630.05775290.1155060.942247
1640.04873370.09746740.951266
1650.05058150.1011630.949418
1660.05558070.1111610.944419
1670.04758460.09516930.952415
1680.04080870.08161730.959191
1690.03431660.06863310.965683
1700.04752780.09505560.952472
1710.04865470.09730940.951345
1720.0583530.1167060.941647
1730.04926760.09853510.950732
1740.04124050.0824810.95876
1750.04200770.08401550.957992
1760.0379230.0758460.962077
1770.04445870.08891740.955541
1780.03829590.07659180.961704
1790.03187150.06374310.968128
1800.02640410.05280820.973596
1810.03037680.06075350.969623
1820.02576370.05152730.974236
1830.042250.08450010.95775
1840.03798790.07597580.962012
1850.09146610.1829320.908534
1860.08069120.1613820.919309
1870.07086280.1417260.929137
1880.07255480.145110.927445
1890.0650830.1301660.934917
1900.05717020.114340.94283
1910.04996640.09993280.950034
1920.04919780.09839560.950802
1930.04396890.08793790.956031
1940.04324710.08649420.956753
1950.03754810.07509620.962452
1960.04393490.08786970.956065
1970.03749790.07499590.962502
1980.05467920.1093580.945321
1990.0684320.1368640.931568
2000.05759220.1151840.942408
2010.04801620.09603230.951984
2020.04021260.08042530.959787
2030.03297620.06595240.967024
2040.02749390.05498780.972506
2050.02655960.05311930.97344
2060.03725510.07451030.962745
2070.03068260.06136510.969317
2080.02470520.04941040.975295
2090.02137520.04275050.978625
2100.01993590.03987170.980064
2110.01575460.03150920.984245
2120.01841560.03683120.981584
2130.01537990.03075990.98462
2140.01326710.02653420.986733
2150.02097590.04195180.979024
2160.02065170.04130340.979348
2170.02051480.04102960.979485
2180.01681840.03363690.983182
2190.01484250.02968510.985157
2200.01189850.0237970.988102
2210.009973150.01994630.990027
2220.008127260.01625450.991873
2230.007283810.01456760.992716
2240.005474730.01094950.994525
2250.005739530.01147910.99426
2260.005407290.01081460.994593
2270.004353890.008707780.995646
2280.005764670.01152930.994235
2290.01248680.02497350.987513
2300.01078250.0215650.989218
2310.008622160.01724430.991378
2320.008948920.01789780.991051
2330.007138380.01427680.992862
2340.006678750.01335750.993321
2350.005000120.01000020.995
2360.006817670.01363530.993182
2370.01081090.02162180.989189
2380.01768340.03536670.982317
2390.03880520.07761040.961195
2400.03052640.06105270.969474
2410.02439110.04878210.975609
2420.02848240.05696480.971518
2430.2793350.558670.720665
2440.2476720.4953450.752328
2450.2129270.4258530.787073
2460.2025650.405130.797435
2470.1708150.341630.829185
2480.1439960.2879920.856004
2490.1205480.2410950.879452
2500.09619810.1923960.903802
2510.2046380.4092750.795362
2520.1997030.3994060.800297
2530.1872630.3745250.812737
2540.1586120.3172240.841388
2550.1754440.3508890.824556
2560.1577180.3154360.842282
2570.2140560.4281120.785944
2580.1719440.3438880.828056
2590.1539320.3078640.846068
2600.1281770.2563540.871823
2610.09652820.1930560.903472
2620.0735150.147030.926485
2630.07947330.1589470.920527
2640.06337620.1267520.936624
2650.2905910.5811820.709409
2660.2551280.5102560.744872
2670.1986980.3973950.801302
2680.3884840.7769670.611516
2690.3401860.6803730.659814
2700.4240.8480.576
2710.3549390.7098780.645061
2720.2675920.5351830.732408
2730.2190390.4380790.780961
2740.1371150.2742290.862885
2750.07251670.1450330.927483
2760.0326570.06531390.967343

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.770537 & 0.458926 & 0.229463 \tabularnewline
12 & 0.637589 & 0.724823 & 0.362411 \tabularnewline
13 & 0.859517 & 0.280967 & 0.140483 \tabularnewline
14 & 0.784283 & 0.431434 & 0.215717 \tabularnewline
15 & 0.705565 & 0.588869 & 0.294435 \tabularnewline
16 & 0.772433 & 0.455134 & 0.227567 \tabularnewline
17 & 0.691986 & 0.616028 & 0.308014 \tabularnewline
18 & 0.612219 & 0.775562 & 0.387781 \tabularnewline
19 & 0.558412 & 0.883176 & 0.441588 \tabularnewline
20 & 0.47405 & 0.9481 & 0.52595 \tabularnewline
21 & 0.390653 & 0.781305 & 0.609347 \tabularnewline
22 & 0.534121 & 0.931758 & 0.465879 \tabularnewline
23 & 0.620599 & 0.758801 & 0.379401 \tabularnewline
24 & 0.563812 & 0.872375 & 0.436188 \tabularnewline
25 & 0.53162 & 0.936759 & 0.46838 \tabularnewline
26 & 0.48694 & 0.973881 & 0.51306 \tabularnewline
27 & 0.478246 & 0.956492 & 0.521754 \tabularnewline
28 & 0.627283 & 0.745434 & 0.372717 \tabularnewline
29 & 0.57536 & 0.84928 & 0.42464 \tabularnewline
30 & 0.534884 & 0.930231 & 0.465116 \tabularnewline
31 & 0.476597 & 0.953194 & 0.523403 \tabularnewline
32 & 0.436894 & 0.873788 & 0.563106 \tabularnewline
33 & 0.388108 & 0.776216 & 0.611892 \tabularnewline
34 & 0.509355 & 0.981291 & 0.490645 \tabularnewline
35 & 0.46846 & 0.936921 & 0.53154 \tabularnewline
36 & 0.426702 & 0.853404 & 0.573298 \tabularnewline
37 & 0.375402 & 0.750803 & 0.624598 \tabularnewline
38 & 0.328384 & 0.656767 & 0.671616 \tabularnewline
39 & 0.286721 & 0.573443 & 0.713279 \tabularnewline
40 & 0.245576 & 0.491152 & 0.754424 \tabularnewline
41 & 0.216395 & 0.43279 & 0.783605 \tabularnewline
42 & 0.186391 & 0.372783 & 0.813609 \tabularnewline
43 & 0.257581 & 0.515162 & 0.742419 \tabularnewline
44 & 0.218531 & 0.437062 & 0.781469 \tabularnewline
45 & 0.213056 & 0.426113 & 0.786944 \tabularnewline
46 & 0.178295 & 0.35659 & 0.821705 \tabularnewline
47 & 0.148974 & 0.297948 & 0.851026 \tabularnewline
48 & 0.122546 & 0.245092 & 0.877454 \tabularnewline
49 & 0.102542 & 0.205084 & 0.897458 \tabularnewline
50 & 0.145162 & 0.290325 & 0.854838 \tabularnewline
51 & 0.137691 & 0.275382 & 0.862309 \tabularnewline
52 & 0.114119 & 0.228238 & 0.885881 \tabularnewline
53 & 0.0931154 & 0.186231 & 0.906885 \tabularnewline
54 & 0.129527 & 0.259053 & 0.870473 \tabularnewline
55 & 0.10624 & 0.212479 & 0.89376 \tabularnewline
56 & 0.0894363 & 0.178873 & 0.910564 \tabularnewline
57 & 0.0970337 & 0.194067 & 0.902966 \tabularnewline
58 & 0.0814204 & 0.162841 & 0.91858 \tabularnewline
59 & 0.141 & 0.282 & 0.859 \tabularnewline
60 & 0.173973 & 0.347947 & 0.826027 \tabularnewline
61 & 0.156602 & 0.313203 & 0.843398 \tabularnewline
62 & 0.146232 & 0.292464 & 0.853768 \tabularnewline
63 & 0.133753 & 0.267506 & 0.866247 \tabularnewline
64 & 0.120562 & 0.241123 & 0.879438 \tabularnewline
65 & 0.118869 & 0.237738 & 0.881131 \tabularnewline
66 & 0.1696 & 0.3392 & 0.8304 \tabularnewline
67 & 0.153885 & 0.30777 & 0.846115 \tabularnewline
68 & 0.139185 & 0.27837 & 0.860815 \tabularnewline
69 & 0.119333 & 0.238667 & 0.880667 \tabularnewline
70 & 0.107299 & 0.214598 & 0.892701 \tabularnewline
71 & 0.143279 & 0.286558 & 0.856721 \tabularnewline
72 & 0.131614 & 0.263227 & 0.868386 \tabularnewline
73 & 0.116887 & 0.233773 & 0.883113 \tabularnewline
74 & 0.0982556 & 0.196511 & 0.901744 \tabularnewline
75 & 0.0916291 & 0.183258 & 0.908371 \tabularnewline
76 & 0.108292 & 0.216584 & 0.891708 \tabularnewline
77 & 0.127148 & 0.254296 & 0.872852 \tabularnewline
78 & 0.114689 & 0.229377 & 0.885311 \tabularnewline
79 & 0.102459 & 0.204918 & 0.897541 \tabularnewline
80 & 0.0895572 & 0.179114 & 0.910443 \tabularnewline
81 & 0.083853 & 0.167706 & 0.916147 \tabularnewline
82 & 0.0699194 & 0.139839 & 0.930081 \tabularnewline
83 & 0.0678291 & 0.135658 & 0.932171 \tabularnewline
84 & 0.0561493 & 0.112299 & 0.943851 \tabularnewline
85 & 0.0560224 & 0.112045 & 0.943978 \tabularnewline
86 & 0.0460966 & 0.0921933 & 0.953903 \tabularnewline
87 & 0.097982 & 0.195964 & 0.902018 \tabularnewline
88 & 0.0828229 & 0.165646 & 0.917177 \tabularnewline
89 & 0.0712038 & 0.142408 & 0.928796 \tabularnewline
90 & 0.0598085 & 0.119617 & 0.940192 \tabularnewline
91 & 0.0497615 & 0.0995231 & 0.950238 \tabularnewline
92 & 0.0473664 & 0.0947327 & 0.952634 \tabularnewline
93 & 0.054895 & 0.10979 & 0.945105 \tabularnewline
94 & 0.0513599 & 0.10272 & 0.94864 \tabularnewline
95 & 0.0683597 & 0.136719 & 0.93164 \tabularnewline
96 & 0.0577577 & 0.115515 & 0.942242 \tabularnewline
97 & 0.0498421 & 0.0996843 & 0.950158 \tabularnewline
98 & 0.0476341 & 0.0952682 & 0.952366 \tabularnewline
99 & 0.0411238 & 0.0822477 & 0.958876 \tabularnewline
100 & 0.0436118 & 0.0872236 & 0.956388 \tabularnewline
101 & 0.0361106 & 0.0722213 & 0.963889 \tabularnewline
102 & 0.0393227 & 0.0786454 & 0.960677 \tabularnewline
103 & 0.0367747 & 0.0735494 & 0.963225 \tabularnewline
104 & 0.0299938 & 0.0599876 & 0.970006 \tabularnewline
105 & 0.0244944 & 0.0489888 & 0.975506 \tabularnewline
106 & 0.022907 & 0.0458141 & 0.977093 \tabularnewline
107 & 0.0187479 & 0.0374958 & 0.981252 \tabularnewline
108 & 0.02391 & 0.0478199 & 0.97609 \tabularnewline
109 & 0.0211922 & 0.0423843 & 0.978808 \tabularnewline
110 & 0.0302263 & 0.0604526 & 0.969774 \tabularnewline
111 & 0.0513605 & 0.102721 & 0.94864 \tabularnewline
112 & 0.0627068 & 0.125414 & 0.937293 \tabularnewline
113 & 0.0527475 & 0.105495 & 0.947252 \tabularnewline
114 & 0.044401 & 0.088802 & 0.955599 \tabularnewline
115 & 0.0381229 & 0.0762457 & 0.961877 \tabularnewline
116 & 0.0656845 & 0.131369 & 0.934315 \tabularnewline
117 & 0.0990522 & 0.198104 & 0.900948 \tabularnewline
118 & 0.176464 & 0.352929 & 0.823536 \tabularnewline
119 & 0.199549 & 0.399099 & 0.800451 \tabularnewline
120 & 0.202666 & 0.405331 & 0.797334 \tabularnewline
121 & 0.180571 & 0.361142 & 0.819429 \tabularnewline
122 & 0.173943 & 0.347886 & 0.826057 \tabularnewline
123 & 0.202925 & 0.40585 & 0.797075 \tabularnewline
124 & 0.181082 & 0.362163 & 0.818918 \tabularnewline
125 & 0.163323 & 0.326647 & 0.836677 \tabularnewline
126 & 0.179244 & 0.358488 & 0.820756 \tabularnewline
127 & 0.159262 & 0.318524 & 0.840738 \tabularnewline
128 & 0.185599 & 0.371197 & 0.814401 \tabularnewline
129 & 0.167945 & 0.335891 & 0.832055 \tabularnewline
130 & 0.155113 & 0.310226 & 0.844887 \tabularnewline
131 & 0.136435 & 0.272871 & 0.863565 \tabularnewline
132 & 0.161906 & 0.323812 & 0.838094 \tabularnewline
133 & 0.144052 & 0.288104 & 0.855948 \tabularnewline
134 & 0.128034 & 0.256068 & 0.871966 \tabularnewline
135 & 0.116095 & 0.232189 & 0.883905 \tabularnewline
136 & 0.100512 & 0.201024 & 0.899488 \tabularnewline
137 & 0.0892017 & 0.178403 & 0.910798 \tabularnewline
138 & 0.0915427 & 0.183085 & 0.908457 \tabularnewline
139 & 0.0860157 & 0.172031 & 0.913984 \tabularnewline
140 & 0.0828535 & 0.165707 & 0.917147 \tabularnewline
141 & 0.18034 & 0.360679 & 0.81966 \tabularnewline
142 & 0.187944 & 0.375888 & 0.812056 \tabularnewline
143 & 0.167141 & 0.334282 & 0.832859 \tabularnewline
144 & 0.16882 & 0.337641 & 0.83118 \tabularnewline
145 & 0.173067 & 0.346133 & 0.826933 \tabularnewline
146 & 0.155552 & 0.311104 & 0.844448 \tabularnewline
147 & 0.151634 & 0.303267 & 0.848366 \tabularnewline
148 & 0.13523 & 0.27046 & 0.86477 \tabularnewline
149 & 0.129454 & 0.258909 & 0.870546 \tabularnewline
150 & 0.122362 & 0.244725 & 0.877638 \tabularnewline
151 & 0.106111 & 0.212223 & 0.893889 \tabularnewline
152 & 0.107714 & 0.215428 & 0.892286 \tabularnewline
153 & 0.092702 & 0.185404 & 0.907298 \tabularnewline
154 & 0.0800072 & 0.160014 & 0.919993 \tabularnewline
155 & 0.0784956 & 0.156991 & 0.921504 \tabularnewline
156 & 0.100625 & 0.20125 & 0.899375 \tabularnewline
157 & 0.0865892 & 0.173178 & 0.913411 \tabularnewline
158 & 0.0858755 & 0.171751 & 0.914124 \tabularnewline
159 & 0.0853489 & 0.170698 & 0.914651 \tabularnewline
160 & 0.0733457 & 0.146691 & 0.926654 \tabularnewline
161 & 0.0635983 & 0.127197 & 0.936402 \tabularnewline
162 & 0.0679072 & 0.135814 & 0.932093 \tabularnewline
163 & 0.0577529 & 0.115506 & 0.942247 \tabularnewline
164 & 0.0487337 & 0.0974674 & 0.951266 \tabularnewline
165 & 0.0505815 & 0.101163 & 0.949418 \tabularnewline
166 & 0.0555807 & 0.111161 & 0.944419 \tabularnewline
167 & 0.0475846 & 0.0951693 & 0.952415 \tabularnewline
168 & 0.0408087 & 0.0816173 & 0.959191 \tabularnewline
169 & 0.0343166 & 0.0686331 & 0.965683 \tabularnewline
170 & 0.0475278 & 0.0950556 & 0.952472 \tabularnewline
171 & 0.0486547 & 0.0973094 & 0.951345 \tabularnewline
172 & 0.058353 & 0.116706 & 0.941647 \tabularnewline
173 & 0.0492676 & 0.0985351 & 0.950732 \tabularnewline
174 & 0.0412405 & 0.082481 & 0.95876 \tabularnewline
175 & 0.0420077 & 0.0840155 & 0.957992 \tabularnewline
176 & 0.037923 & 0.075846 & 0.962077 \tabularnewline
177 & 0.0444587 & 0.0889174 & 0.955541 \tabularnewline
178 & 0.0382959 & 0.0765918 & 0.961704 \tabularnewline
179 & 0.0318715 & 0.0637431 & 0.968128 \tabularnewline
180 & 0.0264041 & 0.0528082 & 0.973596 \tabularnewline
181 & 0.0303768 & 0.0607535 & 0.969623 \tabularnewline
182 & 0.0257637 & 0.0515273 & 0.974236 \tabularnewline
183 & 0.04225 & 0.0845001 & 0.95775 \tabularnewline
184 & 0.0379879 & 0.0759758 & 0.962012 \tabularnewline
185 & 0.0914661 & 0.182932 & 0.908534 \tabularnewline
186 & 0.0806912 & 0.161382 & 0.919309 \tabularnewline
187 & 0.0708628 & 0.141726 & 0.929137 \tabularnewline
188 & 0.0725548 & 0.14511 & 0.927445 \tabularnewline
189 & 0.065083 & 0.130166 & 0.934917 \tabularnewline
190 & 0.0571702 & 0.11434 & 0.94283 \tabularnewline
191 & 0.0499664 & 0.0999328 & 0.950034 \tabularnewline
192 & 0.0491978 & 0.0983956 & 0.950802 \tabularnewline
193 & 0.0439689 & 0.0879379 & 0.956031 \tabularnewline
194 & 0.0432471 & 0.0864942 & 0.956753 \tabularnewline
195 & 0.0375481 & 0.0750962 & 0.962452 \tabularnewline
196 & 0.0439349 & 0.0878697 & 0.956065 \tabularnewline
197 & 0.0374979 & 0.0749959 & 0.962502 \tabularnewline
198 & 0.0546792 & 0.109358 & 0.945321 \tabularnewline
199 & 0.068432 & 0.136864 & 0.931568 \tabularnewline
200 & 0.0575922 & 0.115184 & 0.942408 \tabularnewline
201 & 0.0480162 & 0.0960323 & 0.951984 \tabularnewline
202 & 0.0402126 & 0.0804253 & 0.959787 \tabularnewline
203 & 0.0329762 & 0.0659524 & 0.967024 \tabularnewline
204 & 0.0274939 & 0.0549878 & 0.972506 \tabularnewline
205 & 0.0265596 & 0.0531193 & 0.97344 \tabularnewline
206 & 0.0372551 & 0.0745103 & 0.962745 \tabularnewline
207 & 0.0306826 & 0.0613651 & 0.969317 \tabularnewline
208 & 0.0247052 & 0.0494104 & 0.975295 \tabularnewline
209 & 0.0213752 & 0.0427505 & 0.978625 \tabularnewline
210 & 0.0199359 & 0.0398717 & 0.980064 \tabularnewline
211 & 0.0157546 & 0.0315092 & 0.984245 \tabularnewline
212 & 0.0184156 & 0.0368312 & 0.981584 \tabularnewline
213 & 0.0153799 & 0.0307599 & 0.98462 \tabularnewline
214 & 0.0132671 & 0.0265342 & 0.986733 \tabularnewline
215 & 0.0209759 & 0.0419518 & 0.979024 \tabularnewline
216 & 0.0206517 & 0.0413034 & 0.979348 \tabularnewline
217 & 0.0205148 & 0.0410296 & 0.979485 \tabularnewline
218 & 0.0168184 & 0.0336369 & 0.983182 \tabularnewline
219 & 0.0148425 & 0.0296851 & 0.985157 \tabularnewline
220 & 0.0118985 & 0.023797 & 0.988102 \tabularnewline
221 & 0.00997315 & 0.0199463 & 0.990027 \tabularnewline
222 & 0.00812726 & 0.0162545 & 0.991873 \tabularnewline
223 & 0.00728381 & 0.0145676 & 0.992716 \tabularnewline
224 & 0.00547473 & 0.0109495 & 0.994525 \tabularnewline
225 & 0.00573953 & 0.0114791 & 0.99426 \tabularnewline
226 & 0.00540729 & 0.0108146 & 0.994593 \tabularnewline
227 & 0.00435389 & 0.00870778 & 0.995646 \tabularnewline
228 & 0.00576467 & 0.0115293 & 0.994235 \tabularnewline
229 & 0.0124868 & 0.0249735 & 0.987513 \tabularnewline
230 & 0.0107825 & 0.021565 & 0.989218 \tabularnewline
231 & 0.00862216 & 0.0172443 & 0.991378 \tabularnewline
232 & 0.00894892 & 0.0178978 & 0.991051 \tabularnewline
233 & 0.00713838 & 0.0142768 & 0.992862 \tabularnewline
234 & 0.00667875 & 0.0133575 & 0.993321 \tabularnewline
235 & 0.00500012 & 0.0100002 & 0.995 \tabularnewline
236 & 0.00681767 & 0.0136353 & 0.993182 \tabularnewline
237 & 0.0108109 & 0.0216218 & 0.989189 \tabularnewline
238 & 0.0176834 & 0.0353667 & 0.982317 \tabularnewline
239 & 0.0388052 & 0.0776104 & 0.961195 \tabularnewline
240 & 0.0305264 & 0.0610527 & 0.969474 \tabularnewline
241 & 0.0243911 & 0.0487821 & 0.975609 \tabularnewline
242 & 0.0284824 & 0.0569648 & 0.971518 \tabularnewline
243 & 0.279335 & 0.55867 & 0.720665 \tabularnewline
244 & 0.247672 & 0.495345 & 0.752328 \tabularnewline
245 & 0.212927 & 0.425853 & 0.787073 \tabularnewline
246 & 0.202565 & 0.40513 & 0.797435 \tabularnewline
247 & 0.170815 & 0.34163 & 0.829185 \tabularnewline
248 & 0.143996 & 0.287992 & 0.856004 \tabularnewline
249 & 0.120548 & 0.241095 & 0.879452 \tabularnewline
250 & 0.0961981 & 0.192396 & 0.903802 \tabularnewline
251 & 0.204638 & 0.409275 & 0.795362 \tabularnewline
252 & 0.199703 & 0.399406 & 0.800297 \tabularnewline
253 & 0.187263 & 0.374525 & 0.812737 \tabularnewline
254 & 0.158612 & 0.317224 & 0.841388 \tabularnewline
255 & 0.175444 & 0.350889 & 0.824556 \tabularnewline
256 & 0.157718 & 0.315436 & 0.842282 \tabularnewline
257 & 0.214056 & 0.428112 & 0.785944 \tabularnewline
258 & 0.171944 & 0.343888 & 0.828056 \tabularnewline
259 & 0.153932 & 0.307864 & 0.846068 \tabularnewline
260 & 0.128177 & 0.256354 & 0.871823 \tabularnewline
261 & 0.0965282 & 0.193056 & 0.903472 \tabularnewline
262 & 0.073515 & 0.14703 & 0.926485 \tabularnewline
263 & 0.0794733 & 0.158947 & 0.920527 \tabularnewline
264 & 0.0633762 & 0.126752 & 0.936624 \tabularnewline
265 & 0.290591 & 0.581182 & 0.709409 \tabularnewline
266 & 0.255128 & 0.510256 & 0.744872 \tabularnewline
267 & 0.198698 & 0.397395 & 0.801302 \tabularnewline
268 & 0.388484 & 0.776967 & 0.611516 \tabularnewline
269 & 0.340186 & 0.680373 & 0.659814 \tabularnewline
270 & 0.424 & 0.848 & 0.576 \tabularnewline
271 & 0.354939 & 0.709878 & 0.645061 \tabularnewline
272 & 0.267592 & 0.535183 & 0.732408 \tabularnewline
273 & 0.219039 & 0.438079 & 0.780961 \tabularnewline
274 & 0.137115 & 0.274229 & 0.862885 \tabularnewline
275 & 0.0725167 & 0.145033 & 0.927483 \tabularnewline
276 & 0.032657 & 0.0653139 & 0.967343 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]11[/C][C]0.770537[/C][C]0.458926[/C][C]0.229463[/C][/ROW]
[ROW][C]12[/C][C]0.637589[/C][C]0.724823[/C][C]0.362411[/C][/ROW]
[ROW][C]13[/C][C]0.859517[/C][C]0.280967[/C][C]0.140483[/C][/ROW]
[ROW][C]14[/C][C]0.784283[/C][C]0.431434[/C][C]0.215717[/C][/ROW]
[ROW][C]15[/C][C]0.705565[/C][C]0.588869[/C][C]0.294435[/C][/ROW]
[ROW][C]16[/C][C]0.772433[/C][C]0.455134[/C][C]0.227567[/C][/ROW]
[ROW][C]17[/C][C]0.691986[/C][C]0.616028[/C][C]0.308014[/C][/ROW]
[ROW][C]18[/C][C]0.612219[/C][C]0.775562[/C][C]0.387781[/C][/ROW]
[ROW][C]19[/C][C]0.558412[/C][C]0.883176[/C][C]0.441588[/C][/ROW]
[ROW][C]20[/C][C]0.47405[/C][C]0.9481[/C][C]0.52595[/C][/ROW]
[ROW][C]21[/C][C]0.390653[/C][C]0.781305[/C][C]0.609347[/C][/ROW]
[ROW][C]22[/C][C]0.534121[/C][C]0.931758[/C][C]0.465879[/C][/ROW]
[ROW][C]23[/C][C]0.620599[/C][C]0.758801[/C][C]0.379401[/C][/ROW]
[ROW][C]24[/C][C]0.563812[/C][C]0.872375[/C][C]0.436188[/C][/ROW]
[ROW][C]25[/C][C]0.53162[/C][C]0.936759[/C][C]0.46838[/C][/ROW]
[ROW][C]26[/C][C]0.48694[/C][C]0.973881[/C][C]0.51306[/C][/ROW]
[ROW][C]27[/C][C]0.478246[/C][C]0.956492[/C][C]0.521754[/C][/ROW]
[ROW][C]28[/C][C]0.627283[/C][C]0.745434[/C][C]0.372717[/C][/ROW]
[ROW][C]29[/C][C]0.57536[/C][C]0.84928[/C][C]0.42464[/C][/ROW]
[ROW][C]30[/C][C]0.534884[/C][C]0.930231[/C][C]0.465116[/C][/ROW]
[ROW][C]31[/C][C]0.476597[/C][C]0.953194[/C][C]0.523403[/C][/ROW]
[ROW][C]32[/C][C]0.436894[/C][C]0.873788[/C][C]0.563106[/C][/ROW]
[ROW][C]33[/C][C]0.388108[/C][C]0.776216[/C][C]0.611892[/C][/ROW]
[ROW][C]34[/C][C]0.509355[/C][C]0.981291[/C][C]0.490645[/C][/ROW]
[ROW][C]35[/C][C]0.46846[/C][C]0.936921[/C][C]0.53154[/C][/ROW]
[ROW][C]36[/C][C]0.426702[/C][C]0.853404[/C][C]0.573298[/C][/ROW]
[ROW][C]37[/C][C]0.375402[/C][C]0.750803[/C][C]0.624598[/C][/ROW]
[ROW][C]38[/C][C]0.328384[/C][C]0.656767[/C][C]0.671616[/C][/ROW]
[ROW][C]39[/C][C]0.286721[/C][C]0.573443[/C][C]0.713279[/C][/ROW]
[ROW][C]40[/C][C]0.245576[/C][C]0.491152[/C][C]0.754424[/C][/ROW]
[ROW][C]41[/C][C]0.216395[/C][C]0.43279[/C][C]0.783605[/C][/ROW]
[ROW][C]42[/C][C]0.186391[/C][C]0.372783[/C][C]0.813609[/C][/ROW]
[ROW][C]43[/C][C]0.257581[/C][C]0.515162[/C][C]0.742419[/C][/ROW]
[ROW][C]44[/C][C]0.218531[/C][C]0.437062[/C][C]0.781469[/C][/ROW]
[ROW][C]45[/C][C]0.213056[/C][C]0.426113[/C][C]0.786944[/C][/ROW]
[ROW][C]46[/C][C]0.178295[/C][C]0.35659[/C][C]0.821705[/C][/ROW]
[ROW][C]47[/C][C]0.148974[/C][C]0.297948[/C][C]0.851026[/C][/ROW]
[ROW][C]48[/C][C]0.122546[/C][C]0.245092[/C][C]0.877454[/C][/ROW]
[ROW][C]49[/C][C]0.102542[/C][C]0.205084[/C][C]0.897458[/C][/ROW]
[ROW][C]50[/C][C]0.145162[/C][C]0.290325[/C][C]0.854838[/C][/ROW]
[ROW][C]51[/C][C]0.137691[/C][C]0.275382[/C][C]0.862309[/C][/ROW]
[ROW][C]52[/C][C]0.114119[/C][C]0.228238[/C][C]0.885881[/C][/ROW]
[ROW][C]53[/C][C]0.0931154[/C][C]0.186231[/C][C]0.906885[/C][/ROW]
[ROW][C]54[/C][C]0.129527[/C][C]0.259053[/C][C]0.870473[/C][/ROW]
[ROW][C]55[/C][C]0.10624[/C][C]0.212479[/C][C]0.89376[/C][/ROW]
[ROW][C]56[/C][C]0.0894363[/C][C]0.178873[/C][C]0.910564[/C][/ROW]
[ROW][C]57[/C][C]0.0970337[/C][C]0.194067[/C][C]0.902966[/C][/ROW]
[ROW][C]58[/C][C]0.0814204[/C][C]0.162841[/C][C]0.91858[/C][/ROW]
[ROW][C]59[/C][C]0.141[/C][C]0.282[/C][C]0.859[/C][/ROW]
[ROW][C]60[/C][C]0.173973[/C][C]0.347947[/C][C]0.826027[/C][/ROW]
[ROW][C]61[/C][C]0.156602[/C][C]0.313203[/C][C]0.843398[/C][/ROW]
[ROW][C]62[/C][C]0.146232[/C][C]0.292464[/C][C]0.853768[/C][/ROW]
[ROW][C]63[/C][C]0.133753[/C][C]0.267506[/C][C]0.866247[/C][/ROW]
[ROW][C]64[/C][C]0.120562[/C][C]0.241123[/C][C]0.879438[/C][/ROW]
[ROW][C]65[/C][C]0.118869[/C][C]0.237738[/C][C]0.881131[/C][/ROW]
[ROW][C]66[/C][C]0.1696[/C][C]0.3392[/C][C]0.8304[/C][/ROW]
[ROW][C]67[/C][C]0.153885[/C][C]0.30777[/C][C]0.846115[/C][/ROW]
[ROW][C]68[/C][C]0.139185[/C][C]0.27837[/C][C]0.860815[/C][/ROW]
[ROW][C]69[/C][C]0.119333[/C][C]0.238667[/C][C]0.880667[/C][/ROW]
[ROW][C]70[/C][C]0.107299[/C][C]0.214598[/C][C]0.892701[/C][/ROW]
[ROW][C]71[/C][C]0.143279[/C][C]0.286558[/C][C]0.856721[/C][/ROW]
[ROW][C]72[/C][C]0.131614[/C][C]0.263227[/C][C]0.868386[/C][/ROW]
[ROW][C]73[/C][C]0.116887[/C][C]0.233773[/C][C]0.883113[/C][/ROW]
[ROW][C]74[/C][C]0.0982556[/C][C]0.196511[/C][C]0.901744[/C][/ROW]
[ROW][C]75[/C][C]0.0916291[/C][C]0.183258[/C][C]0.908371[/C][/ROW]
[ROW][C]76[/C][C]0.108292[/C][C]0.216584[/C][C]0.891708[/C][/ROW]
[ROW][C]77[/C][C]0.127148[/C][C]0.254296[/C][C]0.872852[/C][/ROW]
[ROW][C]78[/C][C]0.114689[/C][C]0.229377[/C][C]0.885311[/C][/ROW]
[ROW][C]79[/C][C]0.102459[/C][C]0.204918[/C][C]0.897541[/C][/ROW]
[ROW][C]80[/C][C]0.0895572[/C][C]0.179114[/C][C]0.910443[/C][/ROW]
[ROW][C]81[/C][C]0.083853[/C][C]0.167706[/C][C]0.916147[/C][/ROW]
[ROW][C]82[/C][C]0.0699194[/C][C]0.139839[/C][C]0.930081[/C][/ROW]
[ROW][C]83[/C][C]0.0678291[/C][C]0.135658[/C][C]0.932171[/C][/ROW]
[ROW][C]84[/C][C]0.0561493[/C][C]0.112299[/C][C]0.943851[/C][/ROW]
[ROW][C]85[/C][C]0.0560224[/C][C]0.112045[/C][C]0.943978[/C][/ROW]
[ROW][C]86[/C][C]0.0460966[/C][C]0.0921933[/C][C]0.953903[/C][/ROW]
[ROW][C]87[/C][C]0.097982[/C][C]0.195964[/C][C]0.902018[/C][/ROW]
[ROW][C]88[/C][C]0.0828229[/C][C]0.165646[/C][C]0.917177[/C][/ROW]
[ROW][C]89[/C][C]0.0712038[/C][C]0.142408[/C][C]0.928796[/C][/ROW]
[ROW][C]90[/C][C]0.0598085[/C][C]0.119617[/C][C]0.940192[/C][/ROW]
[ROW][C]91[/C][C]0.0497615[/C][C]0.0995231[/C][C]0.950238[/C][/ROW]
[ROW][C]92[/C][C]0.0473664[/C][C]0.0947327[/C][C]0.952634[/C][/ROW]
[ROW][C]93[/C][C]0.054895[/C][C]0.10979[/C][C]0.945105[/C][/ROW]
[ROW][C]94[/C][C]0.0513599[/C][C]0.10272[/C][C]0.94864[/C][/ROW]
[ROW][C]95[/C][C]0.0683597[/C][C]0.136719[/C][C]0.93164[/C][/ROW]
[ROW][C]96[/C][C]0.0577577[/C][C]0.115515[/C][C]0.942242[/C][/ROW]
[ROW][C]97[/C][C]0.0498421[/C][C]0.0996843[/C][C]0.950158[/C][/ROW]
[ROW][C]98[/C][C]0.0476341[/C][C]0.0952682[/C][C]0.952366[/C][/ROW]
[ROW][C]99[/C][C]0.0411238[/C][C]0.0822477[/C][C]0.958876[/C][/ROW]
[ROW][C]100[/C][C]0.0436118[/C][C]0.0872236[/C][C]0.956388[/C][/ROW]
[ROW][C]101[/C][C]0.0361106[/C][C]0.0722213[/C][C]0.963889[/C][/ROW]
[ROW][C]102[/C][C]0.0393227[/C][C]0.0786454[/C][C]0.960677[/C][/ROW]
[ROW][C]103[/C][C]0.0367747[/C][C]0.0735494[/C][C]0.963225[/C][/ROW]
[ROW][C]104[/C][C]0.0299938[/C][C]0.0599876[/C][C]0.970006[/C][/ROW]
[ROW][C]105[/C][C]0.0244944[/C][C]0.0489888[/C][C]0.975506[/C][/ROW]
[ROW][C]106[/C][C]0.022907[/C][C]0.0458141[/C][C]0.977093[/C][/ROW]
[ROW][C]107[/C][C]0.0187479[/C][C]0.0374958[/C][C]0.981252[/C][/ROW]
[ROW][C]108[/C][C]0.02391[/C][C]0.0478199[/C][C]0.97609[/C][/ROW]
[ROW][C]109[/C][C]0.0211922[/C][C]0.0423843[/C][C]0.978808[/C][/ROW]
[ROW][C]110[/C][C]0.0302263[/C][C]0.0604526[/C][C]0.969774[/C][/ROW]
[ROW][C]111[/C][C]0.0513605[/C][C]0.102721[/C][C]0.94864[/C][/ROW]
[ROW][C]112[/C][C]0.0627068[/C][C]0.125414[/C][C]0.937293[/C][/ROW]
[ROW][C]113[/C][C]0.0527475[/C][C]0.105495[/C][C]0.947252[/C][/ROW]
[ROW][C]114[/C][C]0.044401[/C][C]0.088802[/C][C]0.955599[/C][/ROW]
[ROW][C]115[/C][C]0.0381229[/C][C]0.0762457[/C][C]0.961877[/C][/ROW]
[ROW][C]116[/C][C]0.0656845[/C][C]0.131369[/C][C]0.934315[/C][/ROW]
[ROW][C]117[/C][C]0.0990522[/C][C]0.198104[/C][C]0.900948[/C][/ROW]
[ROW][C]118[/C][C]0.176464[/C][C]0.352929[/C][C]0.823536[/C][/ROW]
[ROW][C]119[/C][C]0.199549[/C][C]0.399099[/C][C]0.800451[/C][/ROW]
[ROW][C]120[/C][C]0.202666[/C][C]0.405331[/C][C]0.797334[/C][/ROW]
[ROW][C]121[/C][C]0.180571[/C][C]0.361142[/C][C]0.819429[/C][/ROW]
[ROW][C]122[/C][C]0.173943[/C][C]0.347886[/C][C]0.826057[/C][/ROW]
[ROW][C]123[/C][C]0.202925[/C][C]0.40585[/C][C]0.797075[/C][/ROW]
[ROW][C]124[/C][C]0.181082[/C][C]0.362163[/C][C]0.818918[/C][/ROW]
[ROW][C]125[/C][C]0.163323[/C][C]0.326647[/C][C]0.836677[/C][/ROW]
[ROW][C]126[/C][C]0.179244[/C][C]0.358488[/C][C]0.820756[/C][/ROW]
[ROW][C]127[/C][C]0.159262[/C][C]0.318524[/C][C]0.840738[/C][/ROW]
[ROW][C]128[/C][C]0.185599[/C][C]0.371197[/C][C]0.814401[/C][/ROW]
[ROW][C]129[/C][C]0.167945[/C][C]0.335891[/C][C]0.832055[/C][/ROW]
[ROW][C]130[/C][C]0.155113[/C][C]0.310226[/C][C]0.844887[/C][/ROW]
[ROW][C]131[/C][C]0.136435[/C][C]0.272871[/C][C]0.863565[/C][/ROW]
[ROW][C]132[/C][C]0.161906[/C][C]0.323812[/C][C]0.838094[/C][/ROW]
[ROW][C]133[/C][C]0.144052[/C][C]0.288104[/C][C]0.855948[/C][/ROW]
[ROW][C]134[/C][C]0.128034[/C][C]0.256068[/C][C]0.871966[/C][/ROW]
[ROW][C]135[/C][C]0.116095[/C][C]0.232189[/C][C]0.883905[/C][/ROW]
[ROW][C]136[/C][C]0.100512[/C][C]0.201024[/C][C]0.899488[/C][/ROW]
[ROW][C]137[/C][C]0.0892017[/C][C]0.178403[/C][C]0.910798[/C][/ROW]
[ROW][C]138[/C][C]0.0915427[/C][C]0.183085[/C][C]0.908457[/C][/ROW]
[ROW][C]139[/C][C]0.0860157[/C][C]0.172031[/C][C]0.913984[/C][/ROW]
[ROW][C]140[/C][C]0.0828535[/C][C]0.165707[/C][C]0.917147[/C][/ROW]
[ROW][C]141[/C][C]0.18034[/C][C]0.360679[/C][C]0.81966[/C][/ROW]
[ROW][C]142[/C][C]0.187944[/C][C]0.375888[/C][C]0.812056[/C][/ROW]
[ROW][C]143[/C][C]0.167141[/C][C]0.334282[/C][C]0.832859[/C][/ROW]
[ROW][C]144[/C][C]0.16882[/C][C]0.337641[/C][C]0.83118[/C][/ROW]
[ROW][C]145[/C][C]0.173067[/C][C]0.346133[/C][C]0.826933[/C][/ROW]
[ROW][C]146[/C][C]0.155552[/C][C]0.311104[/C][C]0.844448[/C][/ROW]
[ROW][C]147[/C][C]0.151634[/C][C]0.303267[/C][C]0.848366[/C][/ROW]
[ROW][C]148[/C][C]0.13523[/C][C]0.27046[/C][C]0.86477[/C][/ROW]
[ROW][C]149[/C][C]0.129454[/C][C]0.258909[/C][C]0.870546[/C][/ROW]
[ROW][C]150[/C][C]0.122362[/C][C]0.244725[/C][C]0.877638[/C][/ROW]
[ROW][C]151[/C][C]0.106111[/C][C]0.212223[/C][C]0.893889[/C][/ROW]
[ROW][C]152[/C][C]0.107714[/C][C]0.215428[/C][C]0.892286[/C][/ROW]
[ROW][C]153[/C][C]0.092702[/C][C]0.185404[/C][C]0.907298[/C][/ROW]
[ROW][C]154[/C][C]0.0800072[/C][C]0.160014[/C][C]0.919993[/C][/ROW]
[ROW][C]155[/C][C]0.0784956[/C][C]0.156991[/C][C]0.921504[/C][/ROW]
[ROW][C]156[/C][C]0.100625[/C][C]0.20125[/C][C]0.899375[/C][/ROW]
[ROW][C]157[/C][C]0.0865892[/C][C]0.173178[/C][C]0.913411[/C][/ROW]
[ROW][C]158[/C][C]0.0858755[/C][C]0.171751[/C][C]0.914124[/C][/ROW]
[ROW][C]159[/C][C]0.0853489[/C][C]0.170698[/C][C]0.914651[/C][/ROW]
[ROW][C]160[/C][C]0.0733457[/C][C]0.146691[/C][C]0.926654[/C][/ROW]
[ROW][C]161[/C][C]0.0635983[/C][C]0.127197[/C][C]0.936402[/C][/ROW]
[ROW][C]162[/C][C]0.0679072[/C][C]0.135814[/C][C]0.932093[/C][/ROW]
[ROW][C]163[/C][C]0.0577529[/C][C]0.115506[/C][C]0.942247[/C][/ROW]
[ROW][C]164[/C][C]0.0487337[/C][C]0.0974674[/C][C]0.951266[/C][/ROW]
[ROW][C]165[/C][C]0.0505815[/C][C]0.101163[/C][C]0.949418[/C][/ROW]
[ROW][C]166[/C][C]0.0555807[/C][C]0.111161[/C][C]0.944419[/C][/ROW]
[ROW][C]167[/C][C]0.0475846[/C][C]0.0951693[/C][C]0.952415[/C][/ROW]
[ROW][C]168[/C][C]0.0408087[/C][C]0.0816173[/C][C]0.959191[/C][/ROW]
[ROW][C]169[/C][C]0.0343166[/C][C]0.0686331[/C][C]0.965683[/C][/ROW]
[ROW][C]170[/C][C]0.0475278[/C][C]0.0950556[/C][C]0.952472[/C][/ROW]
[ROW][C]171[/C][C]0.0486547[/C][C]0.0973094[/C][C]0.951345[/C][/ROW]
[ROW][C]172[/C][C]0.058353[/C][C]0.116706[/C][C]0.941647[/C][/ROW]
[ROW][C]173[/C][C]0.0492676[/C][C]0.0985351[/C][C]0.950732[/C][/ROW]
[ROW][C]174[/C][C]0.0412405[/C][C]0.082481[/C][C]0.95876[/C][/ROW]
[ROW][C]175[/C][C]0.0420077[/C][C]0.0840155[/C][C]0.957992[/C][/ROW]
[ROW][C]176[/C][C]0.037923[/C][C]0.075846[/C][C]0.962077[/C][/ROW]
[ROW][C]177[/C][C]0.0444587[/C][C]0.0889174[/C][C]0.955541[/C][/ROW]
[ROW][C]178[/C][C]0.0382959[/C][C]0.0765918[/C][C]0.961704[/C][/ROW]
[ROW][C]179[/C][C]0.0318715[/C][C]0.0637431[/C][C]0.968128[/C][/ROW]
[ROW][C]180[/C][C]0.0264041[/C][C]0.0528082[/C][C]0.973596[/C][/ROW]
[ROW][C]181[/C][C]0.0303768[/C][C]0.0607535[/C][C]0.969623[/C][/ROW]
[ROW][C]182[/C][C]0.0257637[/C][C]0.0515273[/C][C]0.974236[/C][/ROW]
[ROW][C]183[/C][C]0.04225[/C][C]0.0845001[/C][C]0.95775[/C][/ROW]
[ROW][C]184[/C][C]0.0379879[/C][C]0.0759758[/C][C]0.962012[/C][/ROW]
[ROW][C]185[/C][C]0.0914661[/C][C]0.182932[/C][C]0.908534[/C][/ROW]
[ROW][C]186[/C][C]0.0806912[/C][C]0.161382[/C][C]0.919309[/C][/ROW]
[ROW][C]187[/C][C]0.0708628[/C][C]0.141726[/C][C]0.929137[/C][/ROW]
[ROW][C]188[/C][C]0.0725548[/C][C]0.14511[/C][C]0.927445[/C][/ROW]
[ROW][C]189[/C][C]0.065083[/C][C]0.130166[/C][C]0.934917[/C][/ROW]
[ROW][C]190[/C][C]0.0571702[/C][C]0.11434[/C][C]0.94283[/C][/ROW]
[ROW][C]191[/C][C]0.0499664[/C][C]0.0999328[/C][C]0.950034[/C][/ROW]
[ROW][C]192[/C][C]0.0491978[/C][C]0.0983956[/C][C]0.950802[/C][/ROW]
[ROW][C]193[/C][C]0.0439689[/C][C]0.0879379[/C][C]0.956031[/C][/ROW]
[ROW][C]194[/C][C]0.0432471[/C][C]0.0864942[/C][C]0.956753[/C][/ROW]
[ROW][C]195[/C][C]0.0375481[/C][C]0.0750962[/C][C]0.962452[/C][/ROW]
[ROW][C]196[/C][C]0.0439349[/C][C]0.0878697[/C][C]0.956065[/C][/ROW]
[ROW][C]197[/C][C]0.0374979[/C][C]0.0749959[/C][C]0.962502[/C][/ROW]
[ROW][C]198[/C][C]0.0546792[/C][C]0.109358[/C][C]0.945321[/C][/ROW]
[ROW][C]199[/C][C]0.068432[/C][C]0.136864[/C][C]0.931568[/C][/ROW]
[ROW][C]200[/C][C]0.0575922[/C][C]0.115184[/C][C]0.942408[/C][/ROW]
[ROW][C]201[/C][C]0.0480162[/C][C]0.0960323[/C][C]0.951984[/C][/ROW]
[ROW][C]202[/C][C]0.0402126[/C][C]0.0804253[/C][C]0.959787[/C][/ROW]
[ROW][C]203[/C][C]0.0329762[/C][C]0.0659524[/C][C]0.967024[/C][/ROW]
[ROW][C]204[/C][C]0.0274939[/C][C]0.0549878[/C][C]0.972506[/C][/ROW]
[ROW][C]205[/C][C]0.0265596[/C][C]0.0531193[/C][C]0.97344[/C][/ROW]
[ROW][C]206[/C][C]0.0372551[/C][C]0.0745103[/C][C]0.962745[/C][/ROW]
[ROW][C]207[/C][C]0.0306826[/C][C]0.0613651[/C][C]0.969317[/C][/ROW]
[ROW][C]208[/C][C]0.0247052[/C][C]0.0494104[/C][C]0.975295[/C][/ROW]
[ROW][C]209[/C][C]0.0213752[/C][C]0.0427505[/C][C]0.978625[/C][/ROW]
[ROW][C]210[/C][C]0.0199359[/C][C]0.0398717[/C][C]0.980064[/C][/ROW]
[ROW][C]211[/C][C]0.0157546[/C][C]0.0315092[/C][C]0.984245[/C][/ROW]
[ROW][C]212[/C][C]0.0184156[/C][C]0.0368312[/C][C]0.981584[/C][/ROW]
[ROW][C]213[/C][C]0.0153799[/C][C]0.0307599[/C][C]0.98462[/C][/ROW]
[ROW][C]214[/C][C]0.0132671[/C][C]0.0265342[/C][C]0.986733[/C][/ROW]
[ROW][C]215[/C][C]0.0209759[/C][C]0.0419518[/C][C]0.979024[/C][/ROW]
[ROW][C]216[/C][C]0.0206517[/C][C]0.0413034[/C][C]0.979348[/C][/ROW]
[ROW][C]217[/C][C]0.0205148[/C][C]0.0410296[/C][C]0.979485[/C][/ROW]
[ROW][C]218[/C][C]0.0168184[/C][C]0.0336369[/C][C]0.983182[/C][/ROW]
[ROW][C]219[/C][C]0.0148425[/C][C]0.0296851[/C][C]0.985157[/C][/ROW]
[ROW][C]220[/C][C]0.0118985[/C][C]0.023797[/C][C]0.988102[/C][/ROW]
[ROW][C]221[/C][C]0.00997315[/C][C]0.0199463[/C][C]0.990027[/C][/ROW]
[ROW][C]222[/C][C]0.00812726[/C][C]0.0162545[/C][C]0.991873[/C][/ROW]
[ROW][C]223[/C][C]0.00728381[/C][C]0.0145676[/C][C]0.992716[/C][/ROW]
[ROW][C]224[/C][C]0.00547473[/C][C]0.0109495[/C][C]0.994525[/C][/ROW]
[ROW][C]225[/C][C]0.00573953[/C][C]0.0114791[/C][C]0.99426[/C][/ROW]
[ROW][C]226[/C][C]0.00540729[/C][C]0.0108146[/C][C]0.994593[/C][/ROW]
[ROW][C]227[/C][C]0.00435389[/C][C]0.00870778[/C][C]0.995646[/C][/ROW]
[ROW][C]228[/C][C]0.00576467[/C][C]0.0115293[/C][C]0.994235[/C][/ROW]
[ROW][C]229[/C][C]0.0124868[/C][C]0.0249735[/C][C]0.987513[/C][/ROW]
[ROW][C]230[/C][C]0.0107825[/C][C]0.021565[/C][C]0.989218[/C][/ROW]
[ROW][C]231[/C][C]0.00862216[/C][C]0.0172443[/C][C]0.991378[/C][/ROW]
[ROW][C]232[/C][C]0.00894892[/C][C]0.0178978[/C][C]0.991051[/C][/ROW]
[ROW][C]233[/C][C]0.00713838[/C][C]0.0142768[/C][C]0.992862[/C][/ROW]
[ROW][C]234[/C][C]0.00667875[/C][C]0.0133575[/C][C]0.993321[/C][/ROW]
[ROW][C]235[/C][C]0.00500012[/C][C]0.0100002[/C][C]0.995[/C][/ROW]
[ROW][C]236[/C][C]0.00681767[/C][C]0.0136353[/C][C]0.993182[/C][/ROW]
[ROW][C]237[/C][C]0.0108109[/C][C]0.0216218[/C][C]0.989189[/C][/ROW]
[ROW][C]238[/C][C]0.0176834[/C][C]0.0353667[/C][C]0.982317[/C][/ROW]
[ROW][C]239[/C][C]0.0388052[/C][C]0.0776104[/C][C]0.961195[/C][/ROW]
[ROW][C]240[/C][C]0.0305264[/C][C]0.0610527[/C][C]0.969474[/C][/ROW]
[ROW][C]241[/C][C]0.0243911[/C][C]0.0487821[/C][C]0.975609[/C][/ROW]
[ROW][C]242[/C][C]0.0284824[/C][C]0.0569648[/C][C]0.971518[/C][/ROW]
[ROW][C]243[/C][C]0.279335[/C][C]0.55867[/C][C]0.720665[/C][/ROW]
[ROW][C]244[/C][C]0.247672[/C][C]0.495345[/C][C]0.752328[/C][/ROW]
[ROW][C]245[/C][C]0.212927[/C][C]0.425853[/C][C]0.787073[/C][/ROW]
[ROW][C]246[/C][C]0.202565[/C][C]0.40513[/C][C]0.797435[/C][/ROW]
[ROW][C]247[/C][C]0.170815[/C][C]0.34163[/C][C]0.829185[/C][/ROW]
[ROW][C]248[/C][C]0.143996[/C][C]0.287992[/C][C]0.856004[/C][/ROW]
[ROW][C]249[/C][C]0.120548[/C][C]0.241095[/C][C]0.879452[/C][/ROW]
[ROW][C]250[/C][C]0.0961981[/C][C]0.192396[/C][C]0.903802[/C][/ROW]
[ROW][C]251[/C][C]0.204638[/C][C]0.409275[/C][C]0.795362[/C][/ROW]
[ROW][C]252[/C][C]0.199703[/C][C]0.399406[/C][C]0.800297[/C][/ROW]
[ROW][C]253[/C][C]0.187263[/C][C]0.374525[/C][C]0.812737[/C][/ROW]
[ROW][C]254[/C][C]0.158612[/C][C]0.317224[/C][C]0.841388[/C][/ROW]
[ROW][C]255[/C][C]0.175444[/C][C]0.350889[/C][C]0.824556[/C][/ROW]
[ROW][C]256[/C][C]0.157718[/C][C]0.315436[/C][C]0.842282[/C][/ROW]
[ROW][C]257[/C][C]0.214056[/C][C]0.428112[/C][C]0.785944[/C][/ROW]
[ROW][C]258[/C][C]0.171944[/C][C]0.343888[/C][C]0.828056[/C][/ROW]
[ROW][C]259[/C][C]0.153932[/C][C]0.307864[/C][C]0.846068[/C][/ROW]
[ROW][C]260[/C][C]0.128177[/C][C]0.256354[/C][C]0.871823[/C][/ROW]
[ROW][C]261[/C][C]0.0965282[/C][C]0.193056[/C][C]0.903472[/C][/ROW]
[ROW][C]262[/C][C]0.073515[/C][C]0.14703[/C][C]0.926485[/C][/ROW]
[ROW][C]263[/C][C]0.0794733[/C][C]0.158947[/C][C]0.920527[/C][/ROW]
[ROW][C]264[/C][C]0.0633762[/C][C]0.126752[/C][C]0.936624[/C][/ROW]
[ROW][C]265[/C][C]0.290591[/C][C]0.581182[/C][C]0.709409[/C][/ROW]
[ROW][C]266[/C][C]0.255128[/C][C]0.510256[/C][C]0.744872[/C][/ROW]
[ROW][C]267[/C][C]0.198698[/C][C]0.397395[/C][C]0.801302[/C][/ROW]
[ROW][C]268[/C][C]0.388484[/C][C]0.776967[/C][C]0.611516[/C][/ROW]
[ROW][C]269[/C][C]0.340186[/C][C]0.680373[/C][C]0.659814[/C][/ROW]
[ROW][C]270[/C][C]0.424[/C][C]0.848[/C][C]0.576[/C][/ROW]
[ROW][C]271[/C][C]0.354939[/C][C]0.709878[/C][C]0.645061[/C][/ROW]
[ROW][C]272[/C][C]0.267592[/C][C]0.535183[/C][C]0.732408[/C][/ROW]
[ROW][C]273[/C][C]0.219039[/C][C]0.438079[/C][C]0.780961[/C][/ROW]
[ROW][C]274[/C][C]0.137115[/C][C]0.274229[/C][C]0.862885[/C][/ROW]
[ROW][C]275[/C][C]0.0725167[/C][C]0.145033[/C][C]0.927483[/C][/ROW]
[ROW][C]276[/C][C]0.032657[/C][C]0.0653139[/C][C]0.967343[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.7705370.4589260.229463
120.6375890.7248230.362411
130.8595170.2809670.140483
140.7842830.4314340.215717
150.7055650.5888690.294435
160.7724330.4551340.227567
170.6919860.6160280.308014
180.6122190.7755620.387781
190.5584120.8831760.441588
200.474050.94810.52595
210.3906530.7813050.609347
220.5341210.9317580.465879
230.6205990.7588010.379401
240.5638120.8723750.436188
250.531620.9367590.46838
260.486940.9738810.51306
270.4782460.9564920.521754
280.6272830.7454340.372717
290.575360.849280.42464
300.5348840.9302310.465116
310.4765970.9531940.523403
320.4368940.8737880.563106
330.3881080.7762160.611892
340.5093550.9812910.490645
350.468460.9369210.53154
360.4267020.8534040.573298
370.3754020.7508030.624598
380.3283840.6567670.671616
390.2867210.5734430.713279
400.2455760.4911520.754424
410.2163950.432790.783605
420.1863910.3727830.813609
430.2575810.5151620.742419
440.2185310.4370620.781469
450.2130560.4261130.786944
460.1782950.356590.821705
470.1489740.2979480.851026
480.1225460.2450920.877454
490.1025420.2050840.897458
500.1451620.2903250.854838
510.1376910.2753820.862309
520.1141190.2282380.885881
530.09311540.1862310.906885
540.1295270.2590530.870473
550.106240.2124790.89376
560.08943630.1788730.910564
570.09703370.1940670.902966
580.08142040.1628410.91858
590.1410.2820.859
600.1739730.3479470.826027
610.1566020.3132030.843398
620.1462320.2924640.853768
630.1337530.2675060.866247
640.1205620.2411230.879438
650.1188690.2377380.881131
660.16960.33920.8304
670.1538850.307770.846115
680.1391850.278370.860815
690.1193330.2386670.880667
700.1072990.2145980.892701
710.1432790.2865580.856721
720.1316140.2632270.868386
730.1168870.2337730.883113
740.09825560.1965110.901744
750.09162910.1832580.908371
760.1082920.2165840.891708
770.1271480.2542960.872852
780.1146890.2293770.885311
790.1024590.2049180.897541
800.08955720.1791140.910443
810.0838530.1677060.916147
820.06991940.1398390.930081
830.06782910.1356580.932171
840.05614930.1122990.943851
850.05602240.1120450.943978
860.04609660.09219330.953903
870.0979820.1959640.902018
880.08282290.1656460.917177
890.07120380.1424080.928796
900.05980850.1196170.940192
910.04976150.09952310.950238
920.04736640.09473270.952634
930.0548950.109790.945105
940.05135990.102720.94864
950.06835970.1367190.93164
960.05775770.1155150.942242
970.04984210.09968430.950158
980.04763410.09526820.952366
990.04112380.08224770.958876
1000.04361180.08722360.956388
1010.03611060.07222130.963889
1020.03932270.07864540.960677
1030.03677470.07354940.963225
1040.02999380.05998760.970006
1050.02449440.04898880.975506
1060.0229070.04581410.977093
1070.01874790.03749580.981252
1080.023910.04781990.97609
1090.02119220.04238430.978808
1100.03022630.06045260.969774
1110.05136050.1027210.94864
1120.06270680.1254140.937293
1130.05274750.1054950.947252
1140.0444010.0888020.955599
1150.03812290.07624570.961877
1160.06568450.1313690.934315
1170.09905220.1981040.900948
1180.1764640.3529290.823536
1190.1995490.3990990.800451
1200.2026660.4053310.797334
1210.1805710.3611420.819429
1220.1739430.3478860.826057
1230.2029250.405850.797075
1240.1810820.3621630.818918
1250.1633230.3266470.836677
1260.1792440.3584880.820756
1270.1592620.3185240.840738
1280.1855990.3711970.814401
1290.1679450.3358910.832055
1300.1551130.3102260.844887
1310.1364350.2728710.863565
1320.1619060.3238120.838094
1330.1440520.2881040.855948
1340.1280340.2560680.871966
1350.1160950.2321890.883905
1360.1005120.2010240.899488
1370.08920170.1784030.910798
1380.09154270.1830850.908457
1390.08601570.1720310.913984
1400.08285350.1657070.917147
1410.180340.3606790.81966
1420.1879440.3758880.812056
1430.1671410.3342820.832859
1440.168820.3376410.83118
1450.1730670.3461330.826933
1460.1555520.3111040.844448
1470.1516340.3032670.848366
1480.135230.270460.86477
1490.1294540.2589090.870546
1500.1223620.2447250.877638
1510.1061110.2122230.893889
1520.1077140.2154280.892286
1530.0927020.1854040.907298
1540.08000720.1600140.919993
1550.07849560.1569910.921504
1560.1006250.201250.899375
1570.08658920.1731780.913411
1580.08587550.1717510.914124
1590.08534890.1706980.914651
1600.07334570.1466910.926654
1610.06359830.1271970.936402
1620.06790720.1358140.932093
1630.05775290.1155060.942247
1640.04873370.09746740.951266
1650.05058150.1011630.949418
1660.05558070.1111610.944419
1670.04758460.09516930.952415
1680.04080870.08161730.959191
1690.03431660.06863310.965683
1700.04752780.09505560.952472
1710.04865470.09730940.951345
1720.0583530.1167060.941647
1730.04926760.09853510.950732
1740.04124050.0824810.95876
1750.04200770.08401550.957992
1760.0379230.0758460.962077
1770.04445870.08891740.955541
1780.03829590.07659180.961704
1790.03187150.06374310.968128
1800.02640410.05280820.973596
1810.03037680.06075350.969623
1820.02576370.05152730.974236
1830.042250.08450010.95775
1840.03798790.07597580.962012
1850.09146610.1829320.908534
1860.08069120.1613820.919309
1870.07086280.1417260.929137
1880.07255480.145110.927445
1890.0650830.1301660.934917
1900.05717020.114340.94283
1910.04996640.09993280.950034
1920.04919780.09839560.950802
1930.04396890.08793790.956031
1940.04324710.08649420.956753
1950.03754810.07509620.962452
1960.04393490.08786970.956065
1970.03749790.07499590.962502
1980.05467920.1093580.945321
1990.0684320.1368640.931568
2000.05759220.1151840.942408
2010.04801620.09603230.951984
2020.04021260.08042530.959787
2030.03297620.06595240.967024
2040.02749390.05498780.972506
2050.02655960.05311930.97344
2060.03725510.07451030.962745
2070.03068260.06136510.969317
2080.02470520.04941040.975295
2090.02137520.04275050.978625
2100.01993590.03987170.980064
2110.01575460.03150920.984245
2120.01841560.03683120.981584
2130.01537990.03075990.98462
2140.01326710.02653420.986733
2150.02097590.04195180.979024
2160.02065170.04130340.979348
2170.02051480.04102960.979485
2180.01681840.03363690.983182
2190.01484250.02968510.985157
2200.01189850.0237970.988102
2210.009973150.01994630.990027
2220.008127260.01625450.991873
2230.007283810.01456760.992716
2240.005474730.01094950.994525
2250.005739530.01147910.99426
2260.005407290.01081460.994593
2270.004353890.008707780.995646
2280.005764670.01152930.994235
2290.01248680.02497350.987513
2300.01078250.0215650.989218
2310.008622160.01724430.991378
2320.008948920.01789780.991051
2330.007138380.01427680.992862
2340.006678750.01335750.993321
2350.005000120.01000020.995
2360.006817670.01363530.993182
2370.01081090.02162180.989189
2380.01768340.03536670.982317
2390.03880520.07761040.961195
2400.03052640.06105270.969474
2410.02439110.04878210.975609
2420.02848240.05696480.971518
2430.2793350.558670.720665
2440.2476720.4953450.752328
2450.2129270.4258530.787073
2460.2025650.405130.797435
2470.1708150.341630.829185
2480.1439960.2879920.856004
2490.1205480.2410950.879452
2500.09619810.1923960.903802
2510.2046380.4092750.795362
2520.1997030.3994060.800297
2530.1872630.3745250.812737
2540.1586120.3172240.841388
2550.1754440.3508890.824556
2560.1577180.3154360.842282
2570.2140560.4281120.785944
2580.1719440.3438880.828056
2590.1539320.3078640.846068
2600.1281770.2563540.871823
2610.09652820.1930560.903472
2620.0735150.147030.926485
2630.07947330.1589470.920527
2640.06337620.1267520.936624
2650.2905910.5811820.709409
2660.2551280.5102560.744872
2670.1986980.3973950.801302
2680.3884840.7769670.611516
2690.3401860.6803730.659814
2700.4240.8480.576
2710.3549390.7098780.645061
2720.2675920.5351830.732408
2730.2190390.4380790.780961
2740.1371150.2742290.862885
2750.07251670.1450330.927483
2760.0326570.06531390.967343






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level10.0037594OK
5% type I error level370.139098NOK
10% type I error level870.327068NOK

\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 & 1 & 0.0037594 & OK \tabularnewline
5% type I error level & 37 & 0.139098 & NOK \tabularnewline
10% type I error level & 87 & 0.327068 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264774&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]1[/C][C]0.0037594[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]37[/C][C]0.139098[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]87[/C][C]0.327068[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264774&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264774&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 level10.0037594OK
5% type I error level370.139098NOK
10% type I error level870.327068NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 1 ; 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')
}