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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, 16 Dec 2014 10:01:39 +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/16/t1418724157rrq0yvff94jnleh.htm/, Retrieved Thu, 31 Oct 2024 23:18:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269239, Retrieved Thu, 31 Oct 2024 23:18:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact146
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-16 10:01:39] [6c0da333d5967ad7c023c95d07a1face] [Current]
- RMP     [Multiple Regression] [] [2014-12-16 11:55:10] [a86b94943a9e798c2d09bb837c6a8141]
- RM      [Multiple Regression] [] [2014-12-16 18:53:33] [a86b94943a9e798c2d09bb837c6a8141]
- RMPD    [Central Tendency] [] [2014-12-17 08:51:24] [a86b94943a9e798c2d09bb837c6a8141]
- RMPD    [Central Tendency] [] [2014-12-17 08:59:08] [a86b94943a9e798c2d09bb837c6a8141]
- R  D      [Central Tendency] [] [2014-12-17 13:08:35] [a86b94943a9e798c2d09bb837c6a8141]
-    D        [Central Tendency] [] [2014-12-17 13:26:11] [a86b94943a9e798c2d09bb837c6a8141]
- RMPD    [Central Tendency] [] [2014-12-17 09:01:19] [a86b94943a9e798c2d09bb837c6a8141]
- RMPD    [Bootstrap Plot - Central Tendency] [] [2014-12-17 10:01:48] [a86b94943a9e798c2d09bb837c6a8141]
- RM        [Bootstrap Plot - Central Tendency] [] [2014-12-17 12:12:46] [a86b94943a9e798c2d09bb837c6a8141]
- RM      [Multiple Regression] [] [2014-12-17 08:48:29] [a86b94943a9e798c2d09bb837c6a8141]
- RM      [Multiple Regression] [] [2014-12-17 12:31:13] [a86b94943a9e798c2d09bb837c6a8141]
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Dataseries X:
12.9 2011 1 11 8 7 18 12 20 4 0 21 149 18 68 1.8
12.2 2011 1 19 18 20 23 20 19 4 1 22 139 31 39 2.1
12.8 2011 1 16 12 9 22 14 18 5 0 22 148 39 32 2.2
7.4 2011 1 24 24 19 22 25 24 4 1 18 158 46 62 2.3
6.7 2011 1 15 16 12 19 15 20 4 1 23 128 31 33 2.1
12.6 2011 1 17 19 16 25 20 20 9 1 12 224 67 52 2.7
14.8 2011 1 19 16 17 28 21 24 8 0 20 159 35 62 2.1
13.3 2011 1 19 15 9 16 15 21 11 1 22 105 52 77 2.4
11.1 2011 1 28 28 28 28 28 28 4 1 21 159 77 76 2.9
8.2 2011 1 26 21 20 21 11 10 4 1 19 167 37 41 2.2
11.4 2011 1 15 18 16 22 22 22 6 1 22 165 32 48 2.1
6.4 2011 1 26 22 22 24 22 19 4 1 15 159 36 63 2.2
10.6 2011 1 16 19 17 24 27 27 8 1 20 119 38 30 2.2
12 2011 1 24 22 12 26 24 23 4 0 19 176 69 78 2.7
6.3 2011 1 25 25 18 28 23 24 4 0 18 54 21 19 1.9
11.3 2011 0 22 20 20 24 24 24 11 0 15 91 26 31 2
11.9 2011 1 15 16 12 20 21 25 4 1 20 163 54 66 2.5
9.3 2011 1 21 19 16 26 20 24 4 0 21 124 36 35 2.2
9.6 2011 0 22 18 16 21 19 21 6 1 21 137 42 42 2.3
10 2011 1 27 26 21 28 25 28 6 0 15 121 23 45 1.9
6.4 2011 1 26 24 15 27 16 28 4 1 16 153 34 21 2.1
13.8 2011 1 26 20 17 23 24 22 8 1 23 148 112 25 3.5
10.8 2011 1 22 19 17 24 21 26 5 0 21 221 35 44 2.1
13.8 2011 1 21 19 17 24 22 26 4 1 18 188 47 69 2.3
11.7 2011 1 22 23 18 22 25 21 9 1 25 149 47 54 2.3
10.9 2011 1 20 18 15 21 23 26 4 1 9 244 37 74 2.2
16.1 2011 0 21 16 20 25 20 23 7 1 30 148 109 80 3.5
13.4 2011 0 20 18 13 20 21 20 10 0 20 92 24 42 1.9
9.9 2011 1 22 21 21 21 22 24 4 1 23 150 20 61 1.9
11.5 2011 1 21 20 12 26 25 25 4 0 16 153 22 41 1.9
8.3 2011 1 8 15 6 23 23 24 7 0 16 94 23 46 1.9
11.7 2011 1 22 19 13 21 19 20 12 0 19 156 32 39 2.1
9 2011 1 20 19 19 27 21 24 7 1 25 132 30 34 2
9.7 2011 1 24 7 12 25 19 25 5 1 18 161 92 51 3.2
10.8 2011 1 17 20 14 23 25 23 8 1 23 105 43 42 2.3
10.3 2011 1 20 20 13 25 16 21 5 1 21 97 55 31 2.5
10.4 2011 1 23 19 12 23 24 23 4 0 10 151 16 39 1.8
12.7 2011 0 20 19 17 19 24 21 9 1 14 131 49 20 2.4
9.3 2011 1 22 20 19 22 18 18 7 1 22 166 71 49 2.8
11.8 2011 1 19 18 10 24 28 24 4 0 26 157 43 53 2.3
5.9 2011 1 15 14 10 19 15 18 4 1 23 111 29 31 2
11.4 2011 1 20 17 11 21 17 21 4 1 23 145 56 39 2.5
13 2011 1 22 17 11 27 18 23 4 1 24 162 46 54 2.3
10.8 2011 1 17 8 10 25 26 25 4 1 24 163 19 49 1.8
12.3 2011 0 14 9 7 25 18 22 7 1 18 59 23 34 1.9
11.3 2011 1 24 22 22 23 22 22 4 0 23 187 59 46 2.6
11.8 2011 1 17 20 12 17 19 23 7 1 15 109 30 55 2
7.9 2011 0 23 20 18 28 17 24 4 1 19 90 61 42 2.6
12.7 2011 1 25 22 20 25 26 25 4 0 16 105 7 50 1.6
12.3 2011 0 16 22 9 20 21 22 4 1 25 83 38 13 2.2
11.6 2011 0 18 22 16 25 26 24 4 1 23 116 32 37 2.1
6.7 2011 0 20 16 14 21 21 21 8 1 17 42 16 25 1.8
10.9 2011 1 18 14 11 24 12 24 4 1 19 148 19 30 1.8
12.1 2011 0 23 24 20 28 20 25 4 1 21 155 22 28 1.9
13.3 2011 1 24 21 17 20 20 23 4 1 18 125 48 45 2.4
10.1 2011 1 23 20 14 19 24 27 4 1 27 116 23 35 1.9
5.7 2011 0 13 20 8 24 24 27 7 0 21 128 26 28 2
14.3 2011 1 20 18 16 21 22 23 12 1 13 138 33 41 2.1
8 2011 0 20 14 11 24 21 18 4 0 8 49 9 6 1.7
13.3 2011 0 19 19 10 23 20 20 4 1 29 96 24 45 1.9
9.3 2011 1 22 24 15 18 23 23 4 1 28 164 34 73 2.1
12.5 2011 1 22 19 15 27 19 24 5 0 23 162 48 17 2.4
7.6 2011 1 15 16 10 25 24 26 15 0 21 99 18 40 1.8
15.9 2011 1 17 16 10 20 21 20 5 1 19 202 43 64 2.3
9.2 2011 1 19 16 18 21 16 23 10 0 19 186 33 37 2.1
9.1 2011 0 20 14 10 23 17 22 9 1 20 66 28 25 2
11.1 2011 1 22 22 22 27 23 23 8 0 18 183 71 65 2.8
13 2011 1 21 21 16 24 20 17 4 1 19 214 26 100 2
14.5 2011 1 21 15 10 27 19 20 5 1 17 188 67 28 2.7
12.2 2011 0 16 14 7 24 18 22 4 0 19 104 34 35 2.1
12.3 2011 1 20 15 16 23 18 18 9 0 25 177 80 56 2.9
11.4 2011 1 21 14 16 24 21 19 4 0 19 126 29 29 2
8.8 2011 0 20 20 16 21 20 19 10 0 22 76 16 43 1.8
14.6 2011 0 23 21 22 23 17 16 4 1 23 99 59 59 2.6
12.6 2011 1 18 14 5 27 25 26 4 0 14 139 32 50 2.1
13 2011 1 16 16 10 25 17 25 7 0 16 162 43 59 2.3
12.6 2011 0 17 13 8 19 17 23 5 1 24 108 38 27 2.2
13.2 2011 1 24 26 16 24 24 18 4 0 20 159 29 61 2
9.9 2011 0 13 13 8 25 21 22 4 0 12 74 36 28 2.2
7.7 2011 1 19 18 16 23 22 26 4 1 24 110 32 51 2.1
10.5 2011 0 20 15 14 23 18 25 4 0 22 96 35 35 2.1
13.4 2011 0 22 18 15 25 22 26 4 0 12 116 21 29 1.9
10.9 2011 0 19 21 9 26 20 26 4 0 22 87 29 48 2
4.3 2011 0 21 17 21 26 21 24 6 1 20 97 12 25 1.7
10.3 2011 0 15 18 7 16 21 22 10 0 10 127 37 44 2.2
11.8 2011 0 21 20 17 23 20 21 7 1 23 106 37 64 2.2
11.2 2011 0 24 18 18 26 18 22 4 1 17 80 47 32 2.3
11.4 2011 0 22 25 16 25 25 28 4 0 22 74 51 20 2.4
8.6 2011 0 20 20 16 23 23 22 7 0 24 91 32 28 2.1
13.2 2011 0 21 19 14 26 21 26 4 0 18 133 21 34 1.9
12.6 2011 0 19 18 15 22 20 20 8 1 21 74 13 31 1.7
5.6 2011 0 14 12 8 20 21 24 11 1 20 114 14 26 1.8
9.9 2011 0 25 22 22 27 20 21 6 1 20 140 -2 58 1.5
8.8 2011 0 11 16 5 20 22 23 14 0 22 95 20 23 1.9
7.7 2011 0 17 18 13 22 15 23 5 1 19 98 24 21 1.9
9 2011 0 22 23 22 24 24 23 4 0 20 121 11 21 1.7
7.3 2011 0 20 20 18 21 22 22 8 1 26 126 23 33 1.9
11.4 2011 0 22 20 15 24 21 23 9 1 23 98 24 16 1.9
13.6 2011 0 15 16 11 26 17 21 4 1 24 95 14 20 1.8
7.9 2011 0 23 22 19 24 23 27 4 1 21 110 52 37 2.4
10.7 2011 0 20 19 19 24 22 23 5 1 21 70 15 35 1.8
10.3 2011 0 22 23 21 27 23 26 4 0 19 102 23 33 1.9
8.3 2011 0 16 6 4 25 16 27 5 1 8 86 19 27 1.8
9.6 2011 0 25 19 17 27 18 27 4 1 17 130 35 41 2.1
14.2 2011 0 18 24 10 19 25 23 4 1 20 96 24 40 1.9
8.5 2011 0 19 19 13 22 18 23 7 0 11 102 39 35 2.2
13.5 2011 0 25 15 15 22 14 23 10 0 8 100 29 28 2
4.9 2011 0 21 18 11 25 20 28 4 0 15 94 13 32 1.7
6.4 2011 0 22 18 20 23 19 24 5 0 18 52 8 22 1.7
9.6 2011 0 21 22 13 24 18 20 4 0 18 98 18 44 1.8
11.6 2011 0 22 23 18 24 22 23 4 0 19 118 24 27 1.9
11.1 2011 0 23 18 20 23 21 22 4 1 19 99 19 17 1.8
4.35 2012 1 20 17 15 22 14 15 6 1 23 48 23 12 1
12.7 2012 1 6 6 4 24 5 27 4 1 22 50 16 45 1
18.1 2012 1 15 22 9 19 25 23 8 1 21 150 33 37 4
17.85 2012 1 18 20 18 25 21 23 5 1 25 154 32 37 4
16.6 2012 0 24 16 12 26 11 20 4 0 30 109 37 108 3
12.6 2012 0 22 16 17 18 20 18 17 1 17 68 14 10 2
17.1 2012 1 21 17 12 24 9 22 4 1 27 194 52 68 4
19.1 2012 1 23 20 16 28 15 20 4 0 23 158 75 72 4
16.1 2012 1 20 23 17 23 23 21 8 1 23 159 72 143 4
13.35 2012 1 20 18 14 19 21 25 4 0 18 67 15 9 2
18.4 2012 1 18 13 13 19 9 19 7 0 18 147 29 55 4
14.7 2012 1 25 22 20 27 24 25 4 1 23 39 13 17 1
10.6 2012 1 16 20 16 24 16 24 4 1 19 100 40 37 3
12.6 2012 1 20 20 15 26 20 22 5 1 15 111 19 27 3
16.2 2012 1 14 13 10 21 15 28 7 1 20 138 24 37 4
13.6 2012 1 22 16 16 25 18 22 4 1 16 101 121 58 3
18.9 2012 0 26 25 21 28 22 21 4 1 24 131 93 66 4
14.1 2012 1 20 16 15 19 21 23 7 1 25 101 36 21 3
14.5 2012 1 17 15 16 20 21 19 11 1 25 114 23 19 3
16.15 2012 1 22 19 19 26 21 21 7 0 19 165 85 78 4
14.75 2012 1 22 19 9 27 20 25 4 1 19 114 41 35 3
14.8 2012 1 20 24 19 23 24 23 4 1 16 111 46 48 3
12.45 2012 1 17 9 7 18 15 28 4 1 19 75 18 27 2
12.65 2012 1 22 22 23 23 24 14 4 1 19 82 35 43 2
17.35 2012 1 17 15 14 21 18 23 4 1 23 121 17 30 3
8.6 2012 1 22 22 10 23 24 24 4 1 21 32 4 25 1
18.4 2012 1 21 22 16 22 24 25 6 0 22 150 28 69 4
16.1 2012 1 25 24 12 21 15 15 8 1 19 117 44 72 3
11.6 2012 0 11 12 10 14 19 23 23 1 20 71 10 23 2
17.75 2012 1 19 21 7 24 20 26 4 1 20 165 38 13 4
15.25 2012 1 24 25 20 26 26 21 8 1 3 154 57 61 4
17.65 2012 1 17 26 9 24 26 26 6 1 23 126 23 43 4
16.35 2012 1 22 21 12 22 23 23 4 0 23 149 36 51 4
17.65 2012 1 17 14 10 20 13 15 7 0 20 145 22 67 4
13.6 2012 1 26 28 19 20 16 16 4 1 15 120 40 36 3
14.35 2012 1 20 21 11 18 22 20 4 0 16 109 31 44 3
14.75 2012 1 19 16 15 18 21 20 4 0 7 132 11 45 4
18.25 2012 1 21 16 14 25 11 21 10 1 24 172 38 34 4
9.9 2012 1 24 25 11 28 23 28 6 0 17 169 24 36 4
16 2012 1 21 21 14 23 18 19 5 1 24 114 37 72 3
18.25 2012 1 19 22 15 20 19 21 5 1 24 156 37 39 4
16.85 2012 1 13 9 7 22 15 22 4 0 19 172 22 43 4
14.6 2012 0 24 20 22 27 8 27 4 1 25 68 15 25 2
13.85 2012 0 28 19 19 24 15 20 5 1 20 89 2 56 2
18.95 2012 1 27 24 22 23 21 17 5 1 28 167 43 80 4
15.6 2012 1 22 22 11 20 25 26 5 0 23 113 31 40 3
14.85 2012 0 23 22 19 22 14 21 5 0 27 115 29 73 3
11.75 2012 0 19 12 9 21 21 24 4 0 18 78 45 34 2
18.45 2012 0 18 17 11 24 18 21 6 0 28 118 25 72 3
15.9 2012 0 23 18 17 26 18 25 4 1 21 87 4 42 2
17.1 2012 1 21 10 12 24 12 22 4 0 19 173 31 61 4
16.1 2012 1 22 22 17 18 24 17 4 1 23 2 -4 23 1
19.9 2012 0 17 24 10 17 17 14 9 0 27 162 66 74 4
10.95 2012 0 15 18 17 23 20 23 18 1 22 49 61 16 1
18.45 2012 0 21 18 13 21 24 28 6 0 28 122 32 66 4
15.1 2012 0 20 23 11 21 22 24 5 1 25 96 31 9 3
15 2012 0 26 21 19 24 15 22 4 0 21 100 39 41 3
11.35 2012 0 19 21 21 22 22 24 11 0 22 82 19 57 2
15.95 2012 0 28 28 24 24 26 25 4 1 28 100 31 48 3
18.1 2012 0 21 17 13 24 17 21 10 0 20 115 36 51 3
14.6 2012 0 19 21 16 24 23 22 6 1 29 141 42 53 4
15.4 2012 1 22 21 13 23 19 16 8 1 25 165 21 29 4
15.4 2012 1 21 20 15 21 21 18 8 1 25 165 21 29 4
17.6 2012 0 20 18 15 24 23 27 6 1 20 110 25 55 3
13.35 2012 1 19 17 11 19 19 17 8 1 20 118 32 54 3
19.1 2012 1 11 7 7 19 18 25 4 0 16 158 26 43 4
15.35 2012 0 17 17 13 23 16 24 4 1 20 146 28 51 4
7.6 2012 1 19 14 13 25 23 21 9 0 20 49 32 20 1
13.4 2012 0 20 18 12 24 13 21 9 0 23 90 41 79 2
13.9 2012 0 17 14 8 21 18 19 5 0 18 121 29 39 3
19.1 2012 1 21 23 7 18 23 27 4 1 25 155 33 61 4
15.25 2012 0 21 20 17 23 21 28 4 0 18 104 17 55 3
12.9 2012 0 12 14 9 20 23 19 15 1 19 147 13 30 4
16.1 2012 0 23 17 18 23 16 23 10 0 25 110 32 55 3
17.35 2012 0 22 21 17 23 17 25 9 0 25 108 30 22 3
13.15 2012 0 22 23 17 23 20 26 7 0 25 113 34 37 3
12.15 2012 0 21 24 18 23 18 25 9 0 24 115 59 2 3
12.6 2012 0 20 21 12 27 20 25 6 1 19 61 13 38 1
10.35 2012 0 18 14 14 19 19 24 4 1 26 60 23 27 1
15.4 2012 0 21 24 22 25 26 24 7 1 10 109 10 56 3
9.6 2012 0 24 16 19 25 9 24 4 1 17 68 5 25 2
18.2 2012 0 22 21 21 21 23 22 7 0 13 111 31 39 3
13.6 2012 0 20 8 10 25 9 21 4 0 17 77 19 33 2
14.85 2012 0 17 17 16 17 13 17 15 1 30 73 32 43 2
14.75 2012 1 19 18 11 22 27 23 4 0 25 151 30 57 4
14.1 2012 0 16 17 15 23 22 17 9 0 4 89 25 43 2
14.9 2012 0 19 16 12 27 12 25 4 0 16 78 48 23 2
16.25 2012 0 23 22 21 27 18 19 4 0 21 110 35 44 3
19.25 2012 1 8 17 22 5 6 8 28 1 23 220 67 54 4
13.6 2012 0 22 21 20 19 17 14 4 1 22 65 15 28 2
13.6 2012 1 23 20 15 24 22 22 4 0 17 141 22 36 4
15.65 2012 0 15 20 9 23 22 25 4 0 20 117 18 39 3
12.75 2012 1 17 19 15 28 23 28 5 1 20 122 33 16 4
14.6 2012 0 21 8 14 25 19 25 4 0 22 63 46 23 2
9.85 2012 1 25 19 11 27 20 24 4 1 16 44 24 40 1
12.65 2012 0 18 11 9 16 17 15 12 1 23 52 14 24 1
19.2 2012 0 20 13 12 25 24 24 4 0 0 131 12 78 4
16.6 2012 0 21 18 11 26 20 28 6 1 18 101 38 57 3
11.2 2012 0 21 19 14 24 18 24 6 1 25 42 12 37 1
15.25 2012 1 24 23 10 23 23 25 5 1 23 152 28 27 4
11.9 2012 1 22 20 18 24 27 23 4 0 12 107 41 61 3
13.2 2012 0 22 22 11 27 25 26 4 0 18 77 12 27 2
16.35 2012 1 23 19 14 25 24 26 4 0 24 154 31 69 4
12.4 2012 1 17 16 16 19 12 22 10 1 11 103 33 34 3
15.85 2012 0 15 11 11 19 16 25 7 1 18 96 34 44 3
18.15 2012 1 22 21 16 24 24 22 4 1 23 175 21 34 4
11.15 2012 0 19 14 13 20 23 26 7 1 24 57 20 39 1
15.65 2012 0 18 21 12 21 24 20 4 0 29 112 44 51 3
17.75 2012 1 21 20 17 28 24 26 4 0 18 143 52 34 4
7.65 2012 0 20 21 23 26 26 26 12 0 15 49 7 31 1
12.35 2012 1 19 20 14 19 19 21 5 1 29 110 29 13 3
15.6 2012 1 19 19 10 23 28 21 8 1 16 131 11 12 4
19.3 2012 1 16 19 16 23 23 24 6 0 19 167 26 51 4
15.2 2012 0 18 18 11 21 21 21 17 0 22 56 24 24 1
17.1 2012 1 23 20 16 26 19 18 4 0 16 137 7 19 4
15.6 2012 0 22 21 19 25 23 23 5 1 23 86 60 30 2
18.4 2012 1 23 22 17 25 23 26 4 1 23 121 13 81 3
19.05 2012 1 20 19 12 24 20 23 5 0 19 149 20 42 4
18.55 2012 1 24 23 17 23 18 25 5 0 4 168 52 22 4
19.1 2012 1 25 16 11 22 20 20 6 0 20 140 28 85 4
13.1 2012 0 25 23 19 27 28 25 4 1 24 88 25 27 2
12.85 2012 1 20 18 12 26 21 26 4 1 20 168 39 25 4
9.5 2012 1 23 23 8 23 25 19 4 1 4 94 9 22 2
4.5 2012 1 21 20 17 22 18 21 6 1 24 51 19 19 1
11.85 2012 0 23 20 13 26 24 23 8 0 22 48 13 14 1
13.6 2012 1 23 23 17 22 28 24 10 1 16 145 60 45 4
11.7 2012 1 11 13 7 17 9 6 4 1 3 66 19 45 2
12.4 2012 0 21 21 23 25 22 22 5 1 15 85 34 28 2
13.35 2012 1 27 26 18 22 26 21 4 0 24 109 14 51 3
11.4 2012 0 19 18 13 28 28 28 4 0 17 63 17 41 2
14.9 2012 0 21 19 17 22 18 24 4 1 20 102 45 31 3
19.9 2012 0 16 18 13 21 23 14 16 0 27 162 66 74 4
11.2 2012 0 21 18 8 24 15 20 7 1 26 86 48 19 2
14.6 2012 0 22 19 16 26 24 28 4 1 23 114 29 51 3
17.6 2012 1 16 13 14 26 12 19 4 0 17 164 -2 73 4
14.05 2012 1 18 10 13 24 12 24 14 1 20 119 51 24 3
16.1 2012 1 23 21 19 27 20 21 5 0 22 126 2 61 4
13.35 2012 1 24 24 15 22 25 21 5 1 19 132 24 23 4
11.85 2012 1 20 21 15 23 24 26 5 1 24 142 40 14 4
11.95 2012 1 20 23 8 22 23 24 5 0 19 83 20 54 2
14.75 2012 0 18 18 14 23 18 26 7 1 23 94 19 51 2
15.15 2012 0 4 11 7 15 20 25 19 0 15 81 16 62 2
13.2 2012 1 14 16 11 20 22 23 16 1 27 166 20 36 4
16.85 2012 0 22 20 17 22 20 24 4 0 26 110 40 59 3
7.85 2012 0 17 20 19 25 25 24 4 1 22 64 27 24 2
7.7 2012 1 23 26 17 27 28 26 7 0 22 93 25 26 2
12.6 2012 0 20 21 12 24 25 23 9 0 18 104 49 54 3
7.85 2012 0 18 12 12 21 14 20 5 1 15 105 39 39 3
10.95 2012 0 19 15 18 17 16 16 14 1 22 49 61 16 1
12.35 2012 0 20 18 16 26 24 24 4 0 27 88 19 36 2
9.95 2012 0 15 14 15 20 13 20 16 1 10 95 67 31 2
14.9 2012 0 24 18 20 22 19 23 10 1 20 102 45 31 3
16.65 2012 0 21 16 16 24 18 23 5 0 17 99 30 42 3
13.4 2012 0 19 19 12 23 16 18 6 1 23 63 8 39 2
13.95 2012 0 19 7 10 22 8 21 4 0 19 76 19 25 2
15.7 2012 0 27 21 28 28 27 25 4 0 13 109 52 31 3
16.85 2012 0 23 24 19 21 23 23 4 1 27 117 22 38 3
10.95 2012 0 23 21 18 24 20 26 5 1 23 57 17 31 1
15.35 2012 0 20 20 19 28 20 26 4 0 16 120 33 17 3
12.2 2012 0 17 22 8 25 26 24 4 1 25 73 34 22 2
15.1 2012 0 21 17 17 24 23 23 5 0 2 91 22 55 2
17.75 2012 0 23 19 16 24 24 21 4 0 26 108 30 62 3
15.2 2012 0 22 20 18 21 21 23 4 1 20 105 25 51 3
14.6 2012 1 16 16 12 20 15 20 5 0 23 117 38 30 3
16.65 2012 0 20 20 17 26 22 23 8 0 22 119 26 49 3
8.1 2012 0 16 16 13 16 25 24 15 1 24 31 13 16 1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 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 & 12 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=0

As an alternative you can also use a QR Code:  

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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time12 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Multiple Linear Regression - Estimated Regression Equation
TOT[t] = -5750.73 + 2.86322year[t] -1.03265group[t] + 0.0378781AMS.I1[t] -0.0419523AMS.I2[t] -0.0245364AMS.I3[t] -0.0481988AMS.E1[t] + 0.000279591AMS.E2[t] -0.0412441AMS.E3[t] -0.0385653AMS.A[t] -0.456055gender[t] + 0.0426389NUMERACYTOT[t] + 0.0137004LFM[t] -0.00282769PRH[t] + 0.0316865CH[t] + 1.49115PR[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  -5750.73 +  2.86322year[t] -1.03265group[t] +  0.0378781AMS.I1[t] -0.0419523AMS.I2[t] -0.0245364AMS.I3[t] -0.0481988AMS.E1[t] +  0.000279591AMS.E2[t] -0.0412441AMS.E3[t] -0.0385653AMS.A[t] -0.456055gender[t] +  0.0426389NUMERACYTOT[t] +  0.0137004LFM[t] -0.00282769PRH[t] +  0.0316865CH[t] +  1.49115PR[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  -5750.73 +  2.86322year[t] -1.03265group[t] +  0.0378781AMS.I1[t] -0.0419523AMS.I2[t] -0.0245364AMS.I3[t] -0.0481988AMS.E1[t] +  0.000279591AMS.E2[t] -0.0412441AMS.E3[t] -0.0385653AMS.A[t] -0.456055gender[t] +  0.0426389NUMERACYTOT[t] +  0.0137004LFM[t] -0.00282769PRH[t] +  0.0316865CH[t] +  1.49115PR[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = -5750.73 + 2.86322year[t] -1.03265group[t] + 0.0378781AMS.I1[t] -0.0419523AMS.I2[t] -0.0245364AMS.I3[t] -0.0481988AMS.E1[t] + 0.000279591AMS.E2[t] -0.0412441AMS.E3[t] -0.0385653AMS.A[t] -0.456055gender[t] + 0.0426389NUMERACYTOT[t] + 0.0137004LFM[t] -0.00282769PRH[t] + 0.0316865CH[t] + 1.49115PR[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-5750.73782.902-7.3452.60072e-121.30036e-12
year2.863220.389267.3562.44226e-121.22113e-12
group-1.032650.320573-3.2210.001437570.000718787
AMS.I10.03787810.05422320.69860.4854470.242724
AMS.I2-0.04195230.0473392-0.88620.3763190.188159
AMS.I3-0.02453640.0408238-0.6010.5483380.274169
AMS.E1-0.04819880.0565925-0.85170.3951680.197584
AMS.E20.0002795910.03844940.0072720.9942040.497102
AMS.E3-0.04124410.0463422-0.890.3742880.187144
AMS.A-0.03856530.0474136-0.81340.4167380.208369
gender-0.4560550.281981-1.6170.1070110.0535056
NUMERACYTOT0.04263890.02666841.5990.1110580.0555289
LFM0.01370040.006079392.2540.02504980.0125249
PRH-0.002827690.00809893-0.34910.7272620.363631
CH0.03168650.007958923.9818.88377e-054.44189e-05
PR1.491150.2608115.7172.94097e-081.47048e-08

\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) & -5750.73 & 782.902 & -7.345 & 2.60072e-12 & 1.30036e-12 \tabularnewline
year & 2.86322 & 0.38926 & 7.356 & 2.44226e-12 & 1.22113e-12 \tabularnewline
group & -1.03265 & 0.320573 & -3.221 & 0.00143757 & 0.000718787 \tabularnewline
AMS.I1 & 0.0378781 & 0.0542232 & 0.6986 & 0.485447 & 0.242724 \tabularnewline
AMS.I2 & -0.0419523 & 0.0473392 & -0.8862 & 0.376319 & 0.188159 \tabularnewline
AMS.I3 & -0.0245364 & 0.0408238 & -0.601 & 0.548338 & 0.274169 \tabularnewline
AMS.E1 & -0.0481988 & 0.0565925 & -0.8517 & 0.395168 & 0.197584 \tabularnewline
AMS.E2 & 0.000279591 & 0.0384494 & 0.007272 & 0.994204 & 0.497102 \tabularnewline
AMS.E3 & -0.0412441 & 0.0463422 & -0.89 & 0.374288 & 0.187144 \tabularnewline
AMS.A & -0.0385653 & 0.0474136 & -0.8134 & 0.416738 & 0.208369 \tabularnewline
gender & -0.456055 & 0.281981 & -1.617 & 0.107011 & 0.0535056 \tabularnewline
NUMERACYTOT & 0.0426389 & 0.0266684 & 1.599 & 0.111058 & 0.0555289 \tabularnewline
LFM & 0.0137004 & 0.00607939 & 2.254 & 0.0250498 & 0.0125249 \tabularnewline
PRH & -0.00282769 & 0.00809893 & -0.3491 & 0.727262 & 0.363631 \tabularnewline
CH & 0.0316865 & 0.00795892 & 3.981 & 8.88377e-05 & 4.44189e-05 \tabularnewline
PR & 1.49115 & 0.260811 & 5.717 & 2.94097e-08 & 1.47048e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&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]-5750.73[/C][C]782.902[/C][C]-7.345[/C][C]2.60072e-12[/C][C]1.30036e-12[/C][/ROW]
[ROW][C]year[/C][C]2.86322[/C][C]0.38926[/C][C]7.356[/C][C]2.44226e-12[/C][C]1.22113e-12[/C][/ROW]
[ROW][C]group[/C][C]-1.03265[/C][C]0.320573[/C][C]-3.221[/C][C]0.00143757[/C][C]0.000718787[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0378781[/C][C]0.0542232[/C][C]0.6986[/C][C]0.485447[/C][C]0.242724[/C][/ROW]
[ROW][C]AMS.I2[/C][C]-0.0419523[/C][C]0.0473392[/C][C]-0.8862[/C][C]0.376319[/C][C]0.188159[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0245364[/C][C]0.0408238[/C][C]-0.601[/C][C]0.548338[/C][C]0.274169[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0481988[/C][C]0.0565925[/C][C]-0.8517[/C][C]0.395168[/C][C]0.197584[/C][/ROW]
[ROW][C]AMS.E2[/C][C]0.000279591[/C][C]0.0384494[/C][C]0.007272[/C][C]0.994204[/C][C]0.497102[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0412441[/C][C]0.0463422[/C][C]-0.89[/C][C]0.374288[/C][C]0.187144[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0385653[/C][C]0.0474136[/C][C]-0.8134[/C][C]0.416738[/C][C]0.208369[/C][/ROW]
[ROW][C]gender[/C][C]-0.456055[/C][C]0.281981[/C][C]-1.617[/C][C]0.107011[/C][C]0.0535056[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0426389[/C][C]0.0266684[/C][C]1.599[/C][C]0.111058[/C][C]0.0555289[/C][/ROW]
[ROW][C]LFM[/C][C]0.0137004[/C][C]0.00607939[/C][C]2.254[/C][C]0.0250498[/C][C]0.0125249[/C][/ROW]
[ROW][C]PRH[/C][C]-0.00282769[/C][C]0.00809893[/C][C]-0.3491[/C][C]0.727262[/C][C]0.363631[/C][/ROW]
[ROW][C]CH[/C][C]0.0316865[/C][C]0.00795892[/C][C]3.981[/C][C]8.88377e-05[/C][C]4.44189e-05[/C][/ROW]
[ROW][C]PR[/C][C]1.49115[/C][C]0.260811[/C][C]5.717[/C][C]2.94097e-08[/C][C]1.47048e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=2

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-5750.73782.902-7.3452.60072e-121.30036e-12
year2.863220.389267.3562.44226e-121.22113e-12
group-1.032650.320573-3.2210.001437570.000718787
AMS.I10.03787810.05422320.69860.4854470.242724
AMS.I2-0.04195230.0473392-0.88620.3763190.188159
AMS.I3-0.02453640.0408238-0.6010.5483380.274169
AMS.E1-0.04819880.0565925-0.85170.3951680.197584
AMS.E20.0002795910.03844940.0072720.9942040.497102
AMS.E3-0.04124410.0463422-0.890.3742880.187144
AMS.A-0.03856530.0474136-0.81340.4167380.208369
gender-0.4560550.281981-1.6170.1070110.0535056
NUMERACYTOT0.04263890.02666841.5990.1110580.0555289
LFM0.01370040.006079392.2540.02504980.0125249
PRH-0.002827690.00809893-0.34910.7272620.363631
CH0.03168650.007958923.9818.88377e-054.44189e-05
PR1.491150.2608115.7172.94097e-081.47048e-08







Multiple Linear Regression - Regression Statistics
Multiple R0.783761
R-squared0.614282
Adjusted R-squared0.592199
F-TEST (value)27.8169
F-TEST (DF numerator)15
F-TEST (DF denominator)262
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.16761
Sum Squared Residuals1231.02

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.783761 \tabularnewline
R-squared & 0.614282 \tabularnewline
Adjusted R-squared & 0.592199 \tabularnewline
F-TEST (value) & 27.8169 \tabularnewline
F-TEST (DF numerator) & 15 \tabularnewline
F-TEST (DF denominator) & 262 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.16761 \tabularnewline
Sum Squared Residuals & 1231.02 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.783761[/C][/ROW]
[ROW][C]R-squared[/C][C]0.614282[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.592199[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]27.8169[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]15[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]262[/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]2.16761[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1231.02[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.783761
R-squared0.614282
Adjusted R-squared0.592199
F-TEST (value)27.8169
F-TEST (DF numerator)15
F-TEST (DF denominator)262
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.16761
Sum Squared Residuals1231.02







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.95680.943151
212.210.26511.93488
312.811.20631.59365
47.411.1451-3.74507
56.710.2458-3.54577
612.611.8580.74195
714.811.18373.6163
813.311.77071.52934
911.111.8469-0.74687
108.211.3207-3.1207
1111.410.69820.701791
126.411.1367-4.73673
1310.69.137551.46245
141213.0326-1.0326
156.38.01871-1.71871
1611.39.915741.38426
1711.911.9217-0.0217053
189.310.2624-0.962395
199.611.7382-2.13819
20109.345550.654446
216.49.19326-2.79326
2213.811.8241.976
2310.811.7192-0.919187
2413.811.74052.05947
2511.710.98560.714447
2610.912.3596-1.45962
2716.114.7111.38903
2813.410.92312.47688
299.910.7424-0.842418
3011.510.24521.25478
318.39.52665-1.22665
3211.710.81310.886873
3399.49845-0.498445
349.712.7084-3.00844
3510.89.871020.928978
3610.39.829330.470671
3710.410.1110.289022
3812.710.62962.07041
399.311.91-2.61005
4011.811.8394-0.0394285
415.910.0215-4.1215
4211.411.22950.170541
431311.41471.5853
4410.810.8296-0.029606
4512.39.767912.53209
4611.312.159-0.858974
4711.89.961211.83879
487.910.923-3.02296
4912.79.387653.31235
5012.39.973542.32646
5111.610.55061.04938
526.79.03603-2.33603
5310.99.656021.24398
5412.110.26431.83566
5513.310.60892.69108
5610.19.839640.26036
575.710.5675-4.86749
5814.39.684874.61513
5988.76378-0.763781
6013.311.0812.21903
619.311.9938-2.69378
6212.510.53761.9624
637.69.12117-1.52117
6415.912.37543.52463
659.211-1.80004
669.19.76177-0.661775
6711.112.2935-1.19354
681313.045-0.0449652
6914.511.34173.15832
7012.211.21180.988177
7112.313.0725-0.77248
7211.410.24861.15138
738.810.5296-1.72964
7414.612.1922.408
7512.610.74371.85634
761311.43371.56628
7712.611.12431.47572
7813.211.40961.79037
799.910.2804-0.380415
807.710.1405-2.44049
8110.511.0896-0.589581
8213.410.27733.12272
8310.910.89390.00613861
844.39.31623-5.01623
8510.311.5183-1.21834
8611.811.67990.120117
8711.210.2770.922991
8811.410.1041.29604
898.610.6436-2.04363
9013.210.82072.37932
9112.69.540933.05907
925.610.0842-4.48424
939.910.6848-0.78483
948.810.1203-1.32035
957.79.6986-1.9986
9699.95442-0.954419
977.310.6465-3.3465
9811.49.518161.88184
9913.69.704213.89579
1007.910.8133-2.91334
10110.79.550241.14976
10210.310.05190.248063
1038.39.4974-1.1974
1049.610.749-1.14895
10514.210.36163.83839
1068.510.6744-2.1744
10713.510.25653.24349
1084.99.90046-5.00046
1096.49.18981-2.78981
1109.610.7591-1.1591
11111.610.41991.18015
11211.19.539381.56062
1134.359.78794-5.43794
11412.710.52252.17748
11518.115.82612.27391
11617.8515.85641.99363
11716.618.3398-1.73981
11812.612.00710.592852
11917.117.9268-0.826756
12019.117.52391.57612
12116.119.1234-3.02344
12213.3511.50361.84635
12318.417.28691.11307
12414.79.134795.56521
12510.613.3644-2.76439
12612.613.2117-0.611745
12716.215.69280.507194
12813.614.1165-0.516471
12918.917.27411.62592
13014.113.650.449954
13114.513.66780.832164
13216.1517.4827-1.33267
13314.7513.74621.00375
13414.813.72051.07947
13512.4512.12020.32981
13612.6512.26540.384627
13717.3514.1493.20101
1388.69.59832-0.998316
13918.417.25821.14183
14016.115.32750.772498
14111.612.2772-0.677209
14217.7515.2452.50498
14315.2515.4965-0.246527
14417.6515.42162.22841
14516.3517.0314-0.681449
14617.6517.8565-0.206509
14713.613.9285-0.328454
14814.3514.7512-0.401173
14914.7516.3354-1.58538
15018.2516.21482.03523
1519.915.9682-6.0682
1521615.29980.700179
15318.2516.24092.00912
15416.8517.2863-0.436312
15514.612.2992.301
15613.8514.0563-0.206327
15718.9517.91261.03738
15815.614.62990.970084
15914.8516.8602-2.01016
16011.7513.6757-1.9257
16118.4517.00631.44366
16215.913.26072.63928
16317.117.8861-0.786074
16416.19.589786.51022
16519.919.20820.691773
16610.959.691271.25873
16718.4518.22260.227441
16815.113.99231.10766
1691515.4134-0.41337
17011.3513.7135-2.36348
17115.9515.0390.911036
17218.115.83762.26237
17314.617.4566-2.85661
17415.416.2858-0.885784
17515.416.2553-0.855254
17617.615.25052.3495
17713.3514.9534-1.60338
17819.116.98512.11487
17915.3517.3241-1.97413
1807.69.98963-2.38963
18113.414.9871-1.58713
18213.915.9913-2.09133
18319.117.09692.00306
18415.2515.5501-0.300121
18512.916.6354-3.73535
18616.116.03890.0611127
18717.3514.74672.60331
18813.1515.232-2.082
18912.1513.8962-1.74623
19012.610.93431.66569
19110.3511.5148-1.16477
19215.414.53670.863274
1939.612.448-2.848
19418.215.01283.18724
19513.613.7699-0.169924
19614.8513.58251.26748
19714.7517.3891-2.63909
19814.113.10030.999662
19914.912.6592.24099
20016.2515.43210.817941
20119.2517.45541.79461
20213.613.08070.519313
20313.616.1811-2.58109
20415.6515.39670.253274
20512.7514.2639-1.51395
20614.613.17571.42435
2079.859.98931-0.139311
20812.6511.66290.987106
20919.217.83451.3655
21016.615.06611.53393
21111.211.1590.0410347
21215.2515.7503-0.500312
21311.914.598-2.69804
21413.212.8080.39202
21516.3517.5317-1.18175
21612.413.2858-0.885771
21715.8515.08480.765205
21818.1516.28231.86767
21911.1511.5943-0.444265
22015.6516.3199-0.669942
22117.7515.62092.12911
2227.6510.3579-2.7079
22312.3513.6881-1.33812
22415.614.7660.833997
22519.316.72772.57231
22615.211.07994.12007
22717.115.63061.4694
22815.612.67442.92558
22918.415.32123.07882
23019.0516.49332.5567
23118.5515.2163.33401
23219.118.27390.826113
23313.112.63920.460824
23412.8515.6085-2.75847
2359.511.3563-1.85633
2364.59.7214-5.2214
23711.8510.76541.08458
23813.615.5242-1.92419
23911.712.441-0.741007
24012.412.23470.165304
24113.3515.0129-1.66287
24211.412.8783-1.47826
24314.914.56660.33342
24419.918.88741.01262
24511.212.9382-1.73816
24614.615.2442-0.644194
24717.617.8141-0.214059
24814.0513.40640.643578
24916.116.7549-0.654921
25013.3515.2394-1.88941
25111.8514.9788-3.12884
25211.9512.9733-1.02335
25314.7513.55651.19346
25415.1513.75011.39985
25513.216.1134-2.91341
25616.8516.28590.564083
2577.8512.084-4.23401
2587.711.7046-4.00464
25912.615.4371-2.83711
2607.8515.1412-7.29115
26110.9510.67510.274851
26212.3513.7076-1.3576
2639.9512.3197-2.36969
26414.914.45870.441311
26516.6515.30131.34874
26613.413.19570.20435
26713.9513.73640.213599
26815.714.34581.35418
26916.8515.26521.58484
27010.9510.92530.024722
27115.3514.1891.16102
27212.212.4383-0.238338
27315.113.43041.66962
27417.7516.51471.23533
27515.215.3596-0.159636
27614.614.59260.00736388
27716.6515.58041.06962
2788.110.2988-2.19884

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 11.9568 & 0.943151 \tabularnewline
2 & 12.2 & 10.2651 & 1.93488 \tabularnewline
3 & 12.8 & 11.2063 & 1.59365 \tabularnewline
4 & 7.4 & 11.1451 & -3.74507 \tabularnewline
5 & 6.7 & 10.2458 & -3.54577 \tabularnewline
6 & 12.6 & 11.858 & 0.74195 \tabularnewline
7 & 14.8 & 11.1837 & 3.6163 \tabularnewline
8 & 13.3 & 11.7707 & 1.52934 \tabularnewline
9 & 11.1 & 11.8469 & -0.74687 \tabularnewline
10 & 8.2 & 11.3207 & -3.1207 \tabularnewline
11 & 11.4 & 10.6982 & 0.701791 \tabularnewline
12 & 6.4 & 11.1367 & -4.73673 \tabularnewline
13 & 10.6 & 9.13755 & 1.46245 \tabularnewline
14 & 12 & 13.0326 & -1.0326 \tabularnewline
15 & 6.3 & 8.01871 & -1.71871 \tabularnewline
16 & 11.3 & 9.91574 & 1.38426 \tabularnewline
17 & 11.9 & 11.9217 & -0.0217053 \tabularnewline
18 & 9.3 & 10.2624 & -0.962395 \tabularnewline
19 & 9.6 & 11.7382 & -2.13819 \tabularnewline
20 & 10 & 9.34555 & 0.654446 \tabularnewline
21 & 6.4 & 9.19326 & -2.79326 \tabularnewline
22 & 13.8 & 11.824 & 1.976 \tabularnewline
23 & 10.8 & 11.7192 & -0.919187 \tabularnewline
24 & 13.8 & 11.7405 & 2.05947 \tabularnewline
25 & 11.7 & 10.9856 & 0.714447 \tabularnewline
26 & 10.9 & 12.3596 & -1.45962 \tabularnewline
27 & 16.1 & 14.711 & 1.38903 \tabularnewline
28 & 13.4 & 10.9231 & 2.47688 \tabularnewline
29 & 9.9 & 10.7424 & -0.842418 \tabularnewline
30 & 11.5 & 10.2452 & 1.25478 \tabularnewline
31 & 8.3 & 9.52665 & -1.22665 \tabularnewline
32 & 11.7 & 10.8131 & 0.886873 \tabularnewline
33 & 9 & 9.49845 & -0.498445 \tabularnewline
34 & 9.7 & 12.7084 & -3.00844 \tabularnewline
35 & 10.8 & 9.87102 & 0.928978 \tabularnewline
36 & 10.3 & 9.82933 & 0.470671 \tabularnewline
37 & 10.4 & 10.111 & 0.289022 \tabularnewline
38 & 12.7 & 10.6296 & 2.07041 \tabularnewline
39 & 9.3 & 11.91 & -2.61005 \tabularnewline
40 & 11.8 & 11.8394 & -0.0394285 \tabularnewline
41 & 5.9 & 10.0215 & -4.1215 \tabularnewline
42 & 11.4 & 11.2295 & 0.170541 \tabularnewline
43 & 13 & 11.4147 & 1.5853 \tabularnewline
44 & 10.8 & 10.8296 & -0.029606 \tabularnewline
45 & 12.3 & 9.76791 & 2.53209 \tabularnewline
46 & 11.3 & 12.159 & -0.858974 \tabularnewline
47 & 11.8 & 9.96121 & 1.83879 \tabularnewline
48 & 7.9 & 10.923 & -3.02296 \tabularnewline
49 & 12.7 & 9.38765 & 3.31235 \tabularnewline
50 & 12.3 & 9.97354 & 2.32646 \tabularnewline
51 & 11.6 & 10.5506 & 1.04938 \tabularnewline
52 & 6.7 & 9.03603 & -2.33603 \tabularnewline
53 & 10.9 & 9.65602 & 1.24398 \tabularnewline
54 & 12.1 & 10.2643 & 1.83566 \tabularnewline
55 & 13.3 & 10.6089 & 2.69108 \tabularnewline
56 & 10.1 & 9.83964 & 0.26036 \tabularnewline
57 & 5.7 & 10.5675 & -4.86749 \tabularnewline
58 & 14.3 & 9.68487 & 4.61513 \tabularnewline
59 & 8 & 8.76378 & -0.763781 \tabularnewline
60 & 13.3 & 11.081 & 2.21903 \tabularnewline
61 & 9.3 & 11.9938 & -2.69378 \tabularnewline
62 & 12.5 & 10.5376 & 1.9624 \tabularnewline
63 & 7.6 & 9.12117 & -1.52117 \tabularnewline
64 & 15.9 & 12.3754 & 3.52463 \tabularnewline
65 & 9.2 & 11 & -1.80004 \tabularnewline
66 & 9.1 & 9.76177 & -0.661775 \tabularnewline
67 & 11.1 & 12.2935 & -1.19354 \tabularnewline
68 & 13 & 13.045 & -0.0449652 \tabularnewline
69 & 14.5 & 11.3417 & 3.15832 \tabularnewline
70 & 12.2 & 11.2118 & 0.988177 \tabularnewline
71 & 12.3 & 13.0725 & -0.77248 \tabularnewline
72 & 11.4 & 10.2486 & 1.15138 \tabularnewline
73 & 8.8 & 10.5296 & -1.72964 \tabularnewline
74 & 14.6 & 12.192 & 2.408 \tabularnewline
75 & 12.6 & 10.7437 & 1.85634 \tabularnewline
76 & 13 & 11.4337 & 1.56628 \tabularnewline
77 & 12.6 & 11.1243 & 1.47572 \tabularnewline
78 & 13.2 & 11.4096 & 1.79037 \tabularnewline
79 & 9.9 & 10.2804 & -0.380415 \tabularnewline
80 & 7.7 & 10.1405 & -2.44049 \tabularnewline
81 & 10.5 & 11.0896 & -0.589581 \tabularnewline
82 & 13.4 & 10.2773 & 3.12272 \tabularnewline
83 & 10.9 & 10.8939 & 0.00613861 \tabularnewline
84 & 4.3 & 9.31623 & -5.01623 \tabularnewline
85 & 10.3 & 11.5183 & -1.21834 \tabularnewline
86 & 11.8 & 11.6799 & 0.120117 \tabularnewline
87 & 11.2 & 10.277 & 0.922991 \tabularnewline
88 & 11.4 & 10.104 & 1.29604 \tabularnewline
89 & 8.6 & 10.6436 & -2.04363 \tabularnewline
90 & 13.2 & 10.8207 & 2.37932 \tabularnewline
91 & 12.6 & 9.54093 & 3.05907 \tabularnewline
92 & 5.6 & 10.0842 & -4.48424 \tabularnewline
93 & 9.9 & 10.6848 & -0.78483 \tabularnewline
94 & 8.8 & 10.1203 & -1.32035 \tabularnewline
95 & 7.7 & 9.6986 & -1.9986 \tabularnewline
96 & 9 & 9.95442 & -0.954419 \tabularnewline
97 & 7.3 & 10.6465 & -3.3465 \tabularnewline
98 & 11.4 & 9.51816 & 1.88184 \tabularnewline
99 & 13.6 & 9.70421 & 3.89579 \tabularnewline
100 & 7.9 & 10.8133 & -2.91334 \tabularnewline
101 & 10.7 & 9.55024 & 1.14976 \tabularnewline
102 & 10.3 & 10.0519 & 0.248063 \tabularnewline
103 & 8.3 & 9.4974 & -1.1974 \tabularnewline
104 & 9.6 & 10.749 & -1.14895 \tabularnewline
105 & 14.2 & 10.3616 & 3.83839 \tabularnewline
106 & 8.5 & 10.6744 & -2.1744 \tabularnewline
107 & 13.5 & 10.2565 & 3.24349 \tabularnewline
108 & 4.9 & 9.90046 & -5.00046 \tabularnewline
109 & 6.4 & 9.18981 & -2.78981 \tabularnewline
110 & 9.6 & 10.7591 & -1.1591 \tabularnewline
111 & 11.6 & 10.4199 & 1.18015 \tabularnewline
112 & 11.1 & 9.53938 & 1.56062 \tabularnewline
113 & 4.35 & 9.78794 & -5.43794 \tabularnewline
114 & 12.7 & 10.5225 & 2.17748 \tabularnewline
115 & 18.1 & 15.8261 & 2.27391 \tabularnewline
116 & 17.85 & 15.8564 & 1.99363 \tabularnewline
117 & 16.6 & 18.3398 & -1.73981 \tabularnewline
118 & 12.6 & 12.0071 & 0.592852 \tabularnewline
119 & 17.1 & 17.9268 & -0.826756 \tabularnewline
120 & 19.1 & 17.5239 & 1.57612 \tabularnewline
121 & 16.1 & 19.1234 & -3.02344 \tabularnewline
122 & 13.35 & 11.5036 & 1.84635 \tabularnewline
123 & 18.4 & 17.2869 & 1.11307 \tabularnewline
124 & 14.7 & 9.13479 & 5.56521 \tabularnewline
125 & 10.6 & 13.3644 & -2.76439 \tabularnewline
126 & 12.6 & 13.2117 & -0.611745 \tabularnewline
127 & 16.2 & 15.6928 & 0.507194 \tabularnewline
128 & 13.6 & 14.1165 & -0.516471 \tabularnewline
129 & 18.9 & 17.2741 & 1.62592 \tabularnewline
130 & 14.1 & 13.65 & 0.449954 \tabularnewline
131 & 14.5 & 13.6678 & 0.832164 \tabularnewline
132 & 16.15 & 17.4827 & -1.33267 \tabularnewline
133 & 14.75 & 13.7462 & 1.00375 \tabularnewline
134 & 14.8 & 13.7205 & 1.07947 \tabularnewline
135 & 12.45 & 12.1202 & 0.32981 \tabularnewline
136 & 12.65 & 12.2654 & 0.384627 \tabularnewline
137 & 17.35 & 14.149 & 3.20101 \tabularnewline
138 & 8.6 & 9.59832 & -0.998316 \tabularnewline
139 & 18.4 & 17.2582 & 1.14183 \tabularnewline
140 & 16.1 & 15.3275 & 0.772498 \tabularnewline
141 & 11.6 & 12.2772 & -0.677209 \tabularnewline
142 & 17.75 & 15.245 & 2.50498 \tabularnewline
143 & 15.25 & 15.4965 & -0.246527 \tabularnewline
144 & 17.65 & 15.4216 & 2.22841 \tabularnewline
145 & 16.35 & 17.0314 & -0.681449 \tabularnewline
146 & 17.65 & 17.8565 & -0.206509 \tabularnewline
147 & 13.6 & 13.9285 & -0.328454 \tabularnewline
148 & 14.35 & 14.7512 & -0.401173 \tabularnewline
149 & 14.75 & 16.3354 & -1.58538 \tabularnewline
150 & 18.25 & 16.2148 & 2.03523 \tabularnewline
151 & 9.9 & 15.9682 & -6.0682 \tabularnewline
152 & 16 & 15.2998 & 0.700179 \tabularnewline
153 & 18.25 & 16.2409 & 2.00912 \tabularnewline
154 & 16.85 & 17.2863 & -0.436312 \tabularnewline
155 & 14.6 & 12.299 & 2.301 \tabularnewline
156 & 13.85 & 14.0563 & -0.206327 \tabularnewline
157 & 18.95 & 17.9126 & 1.03738 \tabularnewline
158 & 15.6 & 14.6299 & 0.970084 \tabularnewline
159 & 14.85 & 16.8602 & -2.01016 \tabularnewline
160 & 11.75 & 13.6757 & -1.9257 \tabularnewline
161 & 18.45 & 17.0063 & 1.44366 \tabularnewline
162 & 15.9 & 13.2607 & 2.63928 \tabularnewline
163 & 17.1 & 17.8861 & -0.786074 \tabularnewline
164 & 16.1 & 9.58978 & 6.51022 \tabularnewline
165 & 19.9 & 19.2082 & 0.691773 \tabularnewline
166 & 10.95 & 9.69127 & 1.25873 \tabularnewline
167 & 18.45 & 18.2226 & 0.227441 \tabularnewline
168 & 15.1 & 13.9923 & 1.10766 \tabularnewline
169 & 15 & 15.4134 & -0.41337 \tabularnewline
170 & 11.35 & 13.7135 & -2.36348 \tabularnewline
171 & 15.95 & 15.039 & 0.911036 \tabularnewline
172 & 18.1 & 15.8376 & 2.26237 \tabularnewline
173 & 14.6 & 17.4566 & -2.85661 \tabularnewline
174 & 15.4 & 16.2858 & -0.885784 \tabularnewline
175 & 15.4 & 16.2553 & -0.855254 \tabularnewline
176 & 17.6 & 15.2505 & 2.3495 \tabularnewline
177 & 13.35 & 14.9534 & -1.60338 \tabularnewline
178 & 19.1 & 16.9851 & 2.11487 \tabularnewline
179 & 15.35 & 17.3241 & -1.97413 \tabularnewline
180 & 7.6 & 9.98963 & -2.38963 \tabularnewline
181 & 13.4 & 14.9871 & -1.58713 \tabularnewline
182 & 13.9 & 15.9913 & -2.09133 \tabularnewline
183 & 19.1 & 17.0969 & 2.00306 \tabularnewline
184 & 15.25 & 15.5501 & -0.300121 \tabularnewline
185 & 12.9 & 16.6354 & -3.73535 \tabularnewline
186 & 16.1 & 16.0389 & 0.0611127 \tabularnewline
187 & 17.35 & 14.7467 & 2.60331 \tabularnewline
188 & 13.15 & 15.232 & -2.082 \tabularnewline
189 & 12.15 & 13.8962 & -1.74623 \tabularnewline
190 & 12.6 & 10.9343 & 1.66569 \tabularnewline
191 & 10.35 & 11.5148 & -1.16477 \tabularnewline
192 & 15.4 & 14.5367 & 0.863274 \tabularnewline
193 & 9.6 & 12.448 & -2.848 \tabularnewline
194 & 18.2 & 15.0128 & 3.18724 \tabularnewline
195 & 13.6 & 13.7699 & -0.169924 \tabularnewline
196 & 14.85 & 13.5825 & 1.26748 \tabularnewline
197 & 14.75 & 17.3891 & -2.63909 \tabularnewline
198 & 14.1 & 13.1003 & 0.999662 \tabularnewline
199 & 14.9 & 12.659 & 2.24099 \tabularnewline
200 & 16.25 & 15.4321 & 0.817941 \tabularnewline
201 & 19.25 & 17.4554 & 1.79461 \tabularnewline
202 & 13.6 & 13.0807 & 0.519313 \tabularnewline
203 & 13.6 & 16.1811 & -2.58109 \tabularnewline
204 & 15.65 & 15.3967 & 0.253274 \tabularnewline
205 & 12.75 & 14.2639 & -1.51395 \tabularnewline
206 & 14.6 & 13.1757 & 1.42435 \tabularnewline
207 & 9.85 & 9.98931 & -0.139311 \tabularnewline
208 & 12.65 & 11.6629 & 0.987106 \tabularnewline
209 & 19.2 & 17.8345 & 1.3655 \tabularnewline
210 & 16.6 & 15.0661 & 1.53393 \tabularnewline
211 & 11.2 & 11.159 & 0.0410347 \tabularnewline
212 & 15.25 & 15.7503 & -0.500312 \tabularnewline
213 & 11.9 & 14.598 & -2.69804 \tabularnewline
214 & 13.2 & 12.808 & 0.39202 \tabularnewline
215 & 16.35 & 17.5317 & -1.18175 \tabularnewline
216 & 12.4 & 13.2858 & -0.885771 \tabularnewline
217 & 15.85 & 15.0848 & 0.765205 \tabularnewline
218 & 18.15 & 16.2823 & 1.86767 \tabularnewline
219 & 11.15 & 11.5943 & -0.444265 \tabularnewline
220 & 15.65 & 16.3199 & -0.669942 \tabularnewline
221 & 17.75 & 15.6209 & 2.12911 \tabularnewline
222 & 7.65 & 10.3579 & -2.7079 \tabularnewline
223 & 12.35 & 13.6881 & -1.33812 \tabularnewline
224 & 15.6 & 14.766 & 0.833997 \tabularnewline
225 & 19.3 & 16.7277 & 2.57231 \tabularnewline
226 & 15.2 & 11.0799 & 4.12007 \tabularnewline
227 & 17.1 & 15.6306 & 1.4694 \tabularnewline
228 & 15.6 & 12.6744 & 2.92558 \tabularnewline
229 & 18.4 & 15.3212 & 3.07882 \tabularnewline
230 & 19.05 & 16.4933 & 2.5567 \tabularnewline
231 & 18.55 & 15.216 & 3.33401 \tabularnewline
232 & 19.1 & 18.2739 & 0.826113 \tabularnewline
233 & 13.1 & 12.6392 & 0.460824 \tabularnewline
234 & 12.85 & 15.6085 & -2.75847 \tabularnewline
235 & 9.5 & 11.3563 & -1.85633 \tabularnewline
236 & 4.5 & 9.7214 & -5.2214 \tabularnewline
237 & 11.85 & 10.7654 & 1.08458 \tabularnewline
238 & 13.6 & 15.5242 & -1.92419 \tabularnewline
239 & 11.7 & 12.441 & -0.741007 \tabularnewline
240 & 12.4 & 12.2347 & 0.165304 \tabularnewline
241 & 13.35 & 15.0129 & -1.66287 \tabularnewline
242 & 11.4 & 12.8783 & -1.47826 \tabularnewline
243 & 14.9 & 14.5666 & 0.33342 \tabularnewline
244 & 19.9 & 18.8874 & 1.01262 \tabularnewline
245 & 11.2 & 12.9382 & -1.73816 \tabularnewline
246 & 14.6 & 15.2442 & -0.644194 \tabularnewline
247 & 17.6 & 17.8141 & -0.214059 \tabularnewline
248 & 14.05 & 13.4064 & 0.643578 \tabularnewline
249 & 16.1 & 16.7549 & -0.654921 \tabularnewline
250 & 13.35 & 15.2394 & -1.88941 \tabularnewline
251 & 11.85 & 14.9788 & -3.12884 \tabularnewline
252 & 11.95 & 12.9733 & -1.02335 \tabularnewline
253 & 14.75 & 13.5565 & 1.19346 \tabularnewline
254 & 15.15 & 13.7501 & 1.39985 \tabularnewline
255 & 13.2 & 16.1134 & -2.91341 \tabularnewline
256 & 16.85 & 16.2859 & 0.564083 \tabularnewline
257 & 7.85 & 12.084 & -4.23401 \tabularnewline
258 & 7.7 & 11.7046 & -4.00464 \tabularnewline
259 & 12.6 & 15.4371 & -2.83711 \tabularnewline
260 & 7.85 & 15.1412 & -7.29115 \tabularnewline
261 & 10.95 & 10.6751 & 0.274851 \tabularnewline
262 & 12.35 & 13.7076 & -1.3576 \tabularnewline
263 & 9.95 & 12.3197 & -2.36969 \tabularnewline
264 & 14.9 & 14.4587 & 0.441311 \tabularnewline
265 & 16.65 & 15.3013 & 1.34874 \tabularnewline
266 & 13.4 & 13.1957 & 0.20435 \tabularnewline
267 & 13.95 & 13.7364 & 0.213599 \tabularnewline
268 & 15.7 & 14.3458 & 1.35418 \tabularnewline
269 & 16.85 & 15.2652 & 1.58484 \tabularnewline
270 & 10.95 & 10.9253 & 0.024722 \tabularnewline
271 & 15.35 & 14.189 & 1.16102 \tabularnewline
272 & 12.2 & 12.4383 & -0.238338 \tabularnewline
273 & 15.1 & 13.4304 & 1.66962 \tabularnewline
274 & 17.75 & 16.5147 & 1.23533 \tabularnewline
275 & 15.2 & 15.3596 & -0.159636 \tabularnewline
276 & 14.6 & 14.5926 & 0.00736388 \tabularnewline
277 & 16.65 & 15.5804 & 1.06962 \tabularnewline
278 & 8.1 & 10.2988 & -2.19884 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&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]11.9568[/C][C]0.943151[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.2651[/C][C]1.93488[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.2063[/C][C]1.59365[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.1451[/C][C]-3.74507[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.2458[/C][C]-3.54577[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]11.858[/C][C]0.74195[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.1837[/C][C]3.6163[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.7707[/C][C]1.52934[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.8469[/C][C]-0.74687[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.3207[/C][C]-3.1207[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.6982[/C][C]0.701791[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.1367[/C][C]-4.73673[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.13755[/C][C]1.46245[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.0326[/C][C]-1.0326[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]8.01871[/C][C]-1.71871[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.91574[/C][C]1.38426[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.9217[/C][C]-0.0217053[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.2624[/C][C]-0.962395[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.7382[/C][C]-2.13819[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.34555[/C][C]0.654446[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.19326[/C][C]-2.79326[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]11.824[/C][C]1.976[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]11.7192[/C][C]-0.919187[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.7405[/C][C]2.05947[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.9856[/C][C]0.714447[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.3596[/C][C]-1.45962[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]14.711[/C][C]1.38903[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.9231[/C][C]2.47688[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]10.7424[/C][C]-0.842418[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.2452[/C][C]1.25478[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.52665[/C][C]-1.22665[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]10.8131[/C][C]0.886873[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.49845[/C][C]-0.498445[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.7084[/C][C]-3.00844[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.87102[/C][C]0.928978[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]9.82933[/C][C]0.470671[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.111[/C][C]0.289022[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.6296[/C][C]2.07041[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.91[/C][C]-2.61005[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]11.8394[/C][C]-0.0394285[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.0215[/C][C]-4.1215[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.2295[/C][C]0.170541[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.4147[/C][C]1.5853[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.8296[/C][C]-0.029606[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.76791[/C][C]2.53209[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.159[/C][C]-0.858974[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.96121[/C][C]1.83879[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.923[/C][C]-3.02296[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.38765[/C][C]3.31235[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.97354[/C][C]2.32646[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.5506[/C][C]1.04938[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]9.03603[/C][C]-2.33603[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]9.65602[/C][C]1.24398[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.2643[/C][C]1.83566[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.6089[/C][C]2.69108[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.83964[/C][C]0.26036[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.5675[/C][C]-4.86749[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.68487[/C][C]4.61513[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.76378[/C][C]-0.763781[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.081[/C][C]2.21903[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]11.9938[/C][C]-2.69378[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.5376[/C][C]1.9624[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.12117[/C][C]-1.52117[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.3754[/C][C]3.52463[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11[/C][C]-1.80004[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.76177[/C][C]-0.661775[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.2935[/C][C]-1.19354[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.045[/C][C]-0.0449652[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.3417[/C][C]3.15832[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.2118[/C][C]0.988177[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0725[/C][C]-0.77248[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.2486[/C][C]1.15138[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.5296[/C][C]-1.72964[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]12.192[/C][C]2.408[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.7437[/C][C]1.85634[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.4337[/C][C]1.56628[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.1243[/C][C]1.47572[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]11.4096[/C][C]1.79037[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]10.2804[/C][C]-0.380415[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]10.1405[/C][C]-2.44049[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]11.0896[/C][C]-0.589581[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.2773[/C][C]3.12272[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]10.8939[/C][C]0.00613861[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]9.31623[/C][C]-5.01623[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.5183[/C][C]-1.21834[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.6799[/C][C]0.120117[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.277[/C][C]0.922991[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.104[/C][C]1.29604[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.6436[/C][C]-2.04363[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]10.8207[/C][C]2.37932[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]9.54093[/C][C]3.05907[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.0842[/C][C]-4.48424[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]10.6848[/C][C]-0.78483[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.1203[/C][C]-1.32035[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]9.6986[/C][C]-1.9986[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]9.95442[/C][C]-0.954419[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]10.6465[/C][C]-3.3465[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]9.51816[/C][C]1.88184[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]9.70421[/C][C]3.89579[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.8133[/C][C]-2.91334[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]9.55024[/C][C]1.14976[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.0519[/C][C]0.248063[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.4974[/C][C]-1.1974[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.749[/C][C]-1.14895[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]10.3616[/C][C]3.83839[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.6744[/C][C]-2.1744[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.2565[/C][C]3.24349[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]9.90046[/C][C]-5.00046[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]9.18981[/C][C]-2.78981[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.7591[/C][C]-1.1591[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.4199[/C][C]1.18015[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]9.53938[/C][C]1.56062[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]9.78794[/C][C]-5.43794[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]10.5225[/C][C]2.17748[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]15.8261[/C][C]2.27391[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]15.8564[/C][C]1.99363[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]18.3398[/C][C]-1.73981[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.0071[/C][C]0.592852[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]17.9268[/C][C]-0.826756[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]17.5239[/C][C]1.57612[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]19.1234[/C][C]-3.02344[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]11.5036[/C][C]1.84635[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.2869[/C][C]1.11307[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]9.13479[/C][C]5.56521[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]13.3644[/C][C]-2.76439[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.2117[/C][C]-0.611745[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]15.6928[/C][C]0.507194[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.1165[/C][C]-0.516471[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]17.2741[/C][C]1.62592[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.65[/C][C]0.449954[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.6678[/C][C]0.832164[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]17.4827[/C][C]-1.33267[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.7462[/C][C]1.00375[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.7205[/C][C]1.07947[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.1202[/C][C]0.32981[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]12.2654[/C][C]0.384627[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]14.149[/C][C]3.20101[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]9.59832[/C][C]-0.998316[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.2582[/C][C]1.14183[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]15.3275[/C][C]0.772498[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.2772[/C][C]-0.677209[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]15.245[/C][C]2.50498[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]15.4965[/C][C]-0.246527[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]15.4216[/C][C]2.22841[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]17.0314[/C][C]-0.681449[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]17.8565[/C][C]-0.206509[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]13.9285[/C][C]-0.328454[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.7512[/C][C]-0.401173[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]16.3354[/C][C]-1.58538[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.2148[/C][C]2.03523[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]15.9682[/C][C]-6.0682[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.2998[/C][C]0.700179[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]16.2409[/C][C]2.00912[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.2863[/C][C]-0.436312[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.299[/C][C]2.301[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]14.0563[/C][C]-0.206327[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]17.9126[/C][C]1.03738[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.6299[/C][C]0.970084[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]16.8602[/C][C]-2.01016[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.6757[/C][C]-1.9257[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]17.0063[/C][C]1.44366[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.2607[/C][C]2.63928[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]17.8861[/C][C]-0.786074[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]9.58978[/C][C]6.51022[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]19.2082[/C][C]0.691773[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]9.69127[/C][C]1.25873[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]18.2226[/C][C]0.227441[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.9923[/C][C]1.10766[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.4134[/C][C]-0.41337[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.7135[/C][C]-2.36348[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]15.039[/C][C]0.911036[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]15.8376[/C][C]2.26237[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]17.4566[/C][C]-2.85661[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]16.2858[/C][C]-0.885784[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.2553[/C][C]-0.855254[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]15.2505[/C][C]2.3495[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.9534[/C][C]-1.60338[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.9851[/C][C]2.11487[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]17.3241[/C][C]-1.97413[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]9.98963[/C][C]-2.38963[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]14.9871[/C][C]-1.58713[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]15.9913[/C][C]-2.09133[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.0969[/C][C]2.00306[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]15.5501[/C][C]-0.300121[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]16.6354[/C][C]-3.73535[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]16.0389[/C][C]0.0611127[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]14.7467[/C][C]2.60331[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]15.232[/C][C]-2.082[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.8962[/C][C]-1.74623[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]10.9343[/C][C]1.66569[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.5148[/C][C]-1.16477[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]14.5367[/C][C]0.863274[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.448[/C][C]-2.848[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]15.0128[/C][C]3.18724[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]13.7699[/C][C]-0.169924[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.5825[/C][C]1.26748[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]17.3891[/C][C]-2.63909[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.1003[/C][C]0.999662[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.659[/C][C]2.24099[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]15.4321[/C][C]0.817941[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]17.4554[/C][C]1.79461[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]13.0807[/C][C]0.519313[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]16.1811[/C][C]-2.58109[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.3967[/C][C]0.253274[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]14.2639[/C][C]-1.51395[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.1757[/C][C]1.42435[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]9.98931[/C][C]-0.139311[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]11.6629[/C][C]0.987106[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]17.8345[/C][C]1.3655[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]15.0661[/C][C]1.53393[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]11.159[/C][C]0.0410347[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]15.7503[/C][C]-0.500312[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.598[/C][C]-2.69804[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.808[/C][C]0.39202[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.5317[/C][C]-1.18175[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.2858[/C][C]-0.885771[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]15.0848[/C][C]0.765205[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]16.2823[/C][C]1.86767[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.5943[/C][C]-0.444265[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.3199[/C][C]-0.669942[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]15.6209[/C][C]2.12911[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]10.3579[/C][C]-2.7079[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.6881[/C][C]-1.33812[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]14.766[/C][C]0.833997[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.7277[/C][C]2.57231[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.0799[/C][C]4.12007[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]15.6306[/C][C]1.4694[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.6744[/C][C]2.92558[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]15.3212[/C][C]3.07882[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]16.4933[/C][C]2.5567[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.216[/C][C]3.33401[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]18.2739[/C][C]0.826113[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.6392[/C][C]0.460824[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]15.6085[/C][C]-2.75847[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.3563[/C][C]-1.85633[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]9.7214[/C][C]-5.2214[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.7654[/C][C]1.08458[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.5242[/C][C]-1.92419[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.441[/C][C]-0.741007[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.2347[/C][C]0.165304[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]15.0129[/C][C]-1.66287[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.8783[/C][C]-1.47826[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]14.5666[/C][C]0.33342[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]18.8874[/C][C]1.01262[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.9382[/C][C]-1.73816[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.2442[/C][C]-0.644194[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]17.8141[/C][C]-0.214059[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]13.4064[/C][C]0.643578[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]16.7549[/C][C]-0.654921[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]15.2394[/C][C]-1.88941[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.9788[/C][C]-3.12884[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]12.9733[/C][C]-1.02335[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]13.5565[/C][C]1.19346[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.7501[/C][C]1.39985[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]16.1134[/C][C]-2.91341[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]16.2859[/C][C]0.564083[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.084[/C][C]-4.23401[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]11.7046[/C][C]-4.00464[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]15.4371[/C][C]-2.83711[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]15.1412[/C][C]-7.29115[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]10.6751[/C][C]0.274851[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.7076[/C][C]-1.3576[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.3197[/C][C]-2.36969[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]14.4587[/C][C]0.441311[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]15.3013[/C][C]1.34874[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.1957[/C][C]0.20435[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.7364[/C][C]0.213599[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.3458[/C][C]1.35418[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]15.2652[/C][C]1.58484[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.9253[/C][C]0.024722[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]14.189[/C][C]1.16102[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.4383[/C][C]-0.238338[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.4304[/C][C]1.66962[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.5147[/C][C]1.23533[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]15.3596[/C][C]-0.159636[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]14.5926[/C][C]0.00736388[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]15.5804[/C][C]1.06962[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.2988[/C][C]-2.19884[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.911.95680.943151
212.210.26511.93488
312.811.20631.59365
47.411.1451-3.74507
56.710.2458-3.54577
612.611.8580.74195
714.811.18373.6163
813.311.77071.52934
911.111.8469-0.74687
108.211.3207-3.1207
1111.410.69820.701791
126.411.1367-4.73673
1310.69.137551.46245
141213.0326-1.0326
156.38.01871-1.71871
1611.39.915741.38426
1711.911.9217-0.0217053
189.310.2624-0.962395
199.611.7382-2.13819
20109.345550.654446
216.49.19326-2.79326
2213.811.8241.976
2310.811.7192-0.919187
2413.811.74052.05947
2511.710.98560.714447
2610.912.3596-1.45962
2716.114.7111.38903
2813.410.92312.47688
299.910.7424-0.842418
3011.510.24521.25478
318.39.52665-1.22665
3211.710.81310.886873
3399.49845-0.498445
349.712.7084-3.00844
3510.89.871020.928978
3610.39.829330.470671
3710.410.1110.289022
3812.710.62962.07041
399.311.91-2.61005
4011.811.8394-0.0394285
415.910.0215-4.1215
4211.411.22950.170541
431311.41471.5853
4410.810.8296-0.029606
4512.39.767912.53209
4611.312.159-0.858974
4711.89.961211.83879
487.910.923-3.02296
4912.79.387653.31235
5012.39.973542.32646
5111.610.55061.04938
526.79.03603-2.33603
5310.99.656021.24398
5412.110.26431.83566
5513.310.60892.69108
5610.19.839640.26036
575.710.5675-4.86749
5814.39.684874.61513
5988.76378-0.763781
6013.311.0812.21903
619.311.9938-2.69378
6212.510.53761.9624
637.69.12117-1.52117
6415.912.37543.52463
659.211-1.80004
669.19.76177-0.661775
6711.112.2935-1.19354
681313.045-0.0449652
6914.511.34173.15832
7012.211.21180.988177
7112.313.0725-0.77248
7211.410.24861.15138
738.810.5296-1.72964
7414.612.1922.408
7512.610.74371.85634
761311.43371.56628
7712.611.12431.47572
7813.211.40961.79037
799.910.2804-0.380415
807.710.1405-2.44049
8110.511.0896-0.589581
8213.410.27733.12272
8310.910.89390.00613861
844.39.31623-5.01623
8510.311.5183-1.21834
8611.811.67990.120117
8711.210.2770.922991
8811.410.1041.29604
898.610.6436-2.04363
9013.210.82072.37932
9112.69.540933.05907
925.610.0842-4.48424
939.910.6848-0.78483
948.810.1203-1.32035
957.79.6986-1.9986
9699.95442-0.954419
977.310.6465-3.3465
9811.49.518161.88184
9913.69.704213.89579
1007.910.8133-2.91334
10110.79.550241.14976
10210.310.05190.248063
1038.39.4974-1.1974
1049.610.749-1.14895
10514.210.36163.83839
1068.510.6744-2.1744
10713.510.25653.24349
1084.99.90046-5.00046
1096.49.18981-2.78981
1109.610.7591-1.1591
11111.610.41991.18015
11211.19.539381.56062
1134.359.78794-5.43794
11412.710.52252.17748
11518.115.82612.27391
11617.8515.85641.99363
11716.618.3398-1.73981
11812.612.00710.592852
11917.117.9268-0.826756
12019.117.52391.57612
12116.119.1234-3.02344
12213.3511.50361.84635
12318.417.28691.11307
12414.79.134795.56521
12510.613.3644-2.76439
12612.613.2117-0.611745
12716.215.69280.507194
12813.614.1165-0.516471
12918.917.27411.62592
13014.113.650.449954
13114.513.66780.832164
13216.1517.4827-1.33267
13314.7513.74621.00375
13414.813.72051.07947
13512.4512.12020.32981
13612.6512.26540.384627
13717.3514.1493.20101
1388.69.59832-0.998316
13918.417.25821.14183
14016.115.32750.772498
14111.612.2772-0.677209
14217.7515.2452.50498
14315.2515.4965-0.246527
14417.6515.42162.22841
14516.3517.0314-0.681449
14617.6517.8565-0.206509
14713.613.9285-0.328454
14814.3514.7512-0.401173
14914.7516.3354-1.58538
15018.2516.21482.03523
1519.915.9682-6.0682
1521615.29980.700179
15318.2516.24092.00912
15416.8517.2863-0.436312
15514.612.2992.301
15613.8514.0563-0.206327
15718.9517.91261.03738
15815.614.62990.970084
15914.8516.8602-2.01016
16011.7513.6757-1.9257
16118.4517.00631.44366
16215.913.26072.63928
16317.117.8861-0.786074
16416.19.589786.51022
16519.919.20820.691773
16610.959.691271.25873
16718.4518.22260.227441
16815.113.99231.10766
1691515.4134-0.41337
17011.3513.7135-2.36348
17115.9515.0390.911036
17218.115.83762.26237
17314.617.4566-2.85661
17415.416.2858-0.885784
17515.416.2553-0.855254
17617.615.25052.3495
17713.3514.9534-1.60338
17819.116.98512.11487
17915.3517.3241-1.97413
1807.69.98963-2.38963
18113.414.9871-1.58713
18213.915.9913-2.09133
18319.117.09692.00306
18415.2515.5501-0.300121
18512.916.6354-3.73535
18616.116.03890.0611127
18717.3514.74672.60331
18813.1515.232-2.082
18912.1513.8962-1.74623
19012.610.93431.66569
19110.3511.5148-1.16477
19215.414.53670.863274
1939.612.448-2.848
19418.215.01283.18724
19513.613.7699-0.169924
19614.8513.58251.26748
19714.7517.3891-2.63909
19814.113.10030.999662
19914.912.6592.24099
20016.2515.43210.817941
20119.2517.45541.79461
20213.613.08070.519313
20313.616.1811-2.58109
20415.6515.39670.253274
20512.7514.2639-1.51395
20614.613.17571.42435
2079.859.98931-0.139311
20812.6511.66290.987106
20919.217.83451.3655
21016.615.06611.53393
21111.211.1590.0410347
21215.2515.7503-0.500312
21311.914.598-2.69804
21413.212.8080.39202
21516.3517.5317-1.18175
21612.413.2858-0.885771
21715.8515.08480.765205
21818.1516.28231.86767
21911.1511.5943-0.444265
22015.6516.3199-0.669942
22117.7515.62092.12911
2227.6510.3579-2.7079
22312.3513.6881-1.33812
22415.614.7660.833997
22519.316.72772.57231
22615.211.07994.12007
22717.115.63061.4694
22815.612.67442.92558
22918.415.32123.07882
23019.0516.49332.5567
23118.5515.2163.33401
23219.118.27390.826113
23313.112.63920.460824
23412.8515.6085-2.75847
2359.511.3563-1.85633
2364.59.7214-5.2214
23711.8510.76541.08458
23813.615.5242-1.92419
23911.712.441-0.741007
24012.412.23470.165304
24113.3515.0129-1.66287
24211.412.8783-1.47826
24314.914.56660.33342
24419.918.88741.01262
24511.212.9382-1.73816
24614.615.2442-0.644194
24717.617.8141-0.214059
24814.0513.40640.643578
24916.116.7549-0.654921
25013.3515.2394-1.88941
25111.8514.9788-3.12884
25211.9512.9733-1.02335
25314.7513.55651.19346
25415.1513.75011.39985
25513.216.1134-2.91341
25616.8516.28590.564083
2577.8512.084-4.23401
2587.711.7046-4.00464
25912.615.4371-2.83711
2607.8515.1412-7.29115
26110.9510.67510.274851
26212.3513.7076-1.3576
2639.9512.3197-2.36969
26414.914.45870.441311
26516.6515.30131.34874
26613.413.19570.20435
26713.9513.73640.213599
26815.714.34581.35418
26916.8515.26521.58484
27010.9510.92530.024722
27115.3514.1891.16102
27212.212.4383-0.238338
27315.113.43041.66962
27417.7516.51471.23533
27515.215.3596-0.159636
27614.614.59260.00736388
27716.6515.58041.06962
2788.110.2988-2.19884







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.3320190.6640380.667981
200.5509280.8981450.449072
210.4167260.8334510.583274
220.2925410.5850830.707459
230.2171230.4342460.782877
240.2020470.4040940.797953
250.1340390.2680780.865961
260.140790.281580.85921
270.1001460.2002930.899854
280.08837290.1767460.911627
290.07073130.1414630.929269
300.06827230.1365450.931728
310.08782430.1756490.912176
320.0596060.1192120.940394
330.1029150.205830.897085
340.1995610.3991230.800439
350.1631270.3262550.836873
360.1642390.3284770.835761
370.1673530.3347060.832647
380.144990.2899790.85501
390.1567170.3134330.843283
400.120730.241460.87927
410.1828680.3657370.817132
420.1712790.3425570.828721
430.1772620.3545230.822738
440.1516410.3032810.848359
450.1350080.2700150.864992
460.1070140.2140290.892986
470.109020.218040.89098
480.1214610.2429220.878539
490.1653530.3307060.834647
500.1948060.3896120.805194
510.1627250.325450.837275
520.1880390.3760770.811961
530.1748310.3496610.825169
540.1592920.3185830.840708
550.2899470.5798940.710053
560.2489390.4978790.751061
570.5356190.9287620.464381
580.6122450.775510.387755
590.5669360.8661280.433064
600.5613210.8773590.438679
610.5730930.8538150.426907
620.58090.8381990.4191
630.6707590.6584830.329241
640.765290.4694210.23471
650.7675560.4648880.232444
660.7400170.5199660.259983
670.7126030.5747940.287397
680.6803830.6392330.319617
690.6981690.6036610.301831
700.6645630.6708740.335437
710.6480740.7038510.351926
720.6127660.7744690.387234
730.5931840.8136310.406816
740.6321430.7357150.367857
750.6237450.7525110.376255
760.6198140.7603730.380186
770.5994720.8010560.400528
780.5853520.8292960.414648
790.5469360.9061290.453064
800.5325750.934850.467425
810.49540.9907990.5046
820.5410320.9179360.458968
830.5014370.9971270.498563
840.6699180.6601630.330082
850.6552530.6894950.344747
860.619790.7604210.38021
870.5850.8300010.415
880.5572950.8854090.442705
890.5450630.9098750.454937
900.5637990.8724020.436201
910.5854590.8290830.414541
920.6728210.6543590.327179
930.6376510.7246990.362349
940.6066490.7867030.393351
950.6021980.7956040.397802
960.5696140.8607730.430386
970.6103050.7793910.389695
980.5964540.8070920.403546
990.7068770.5862450.293123
1000.7320450.5359090.267955
1010.7178460.5643080.282154
1020.6862140.6275730.313786
1030.6718460.6563070.328154
1040.6442590.7114830.355741
1050.6990310.6019390.300969
1060.6886770.6226450.311323
1070.7530190.4939620.246981
1080.8429580.3140830.157042
1090.8415340.3169330.158466
1100.8323090.3353830.167691
1110.8116110.3767780.188389
1120.7912520.4174950.208748
1130.8336490.3327020.166351
1140.9183210.1633580.0816788
1150.9212480.1575030.0787516
1160.9131520.1736950.0868475
1170.908410.1831790.0915895
1180.8953640.2092720.104636
1190.8820820.2358360.117918
1200.8714340.2571310.128566
1210.8914920.2170150.108508
1220.8900020.2199960.109998
1230.8743970.2512070.125603
1240.9463830.1072340.053617
1250.9539440.09211120.0460556
1260.9472750.105450.052725
1270.9371530.1256940.0628471
1280.9261430.1477150.0738574
1290.9182890.1634220.0817112
1300.9044550.1910890.0955445
1310.8912180.2175640.108782
1320.8811750.237650.118825
1330.8672520.2654960.132748
1340.8502810.2994380.149719
1350.8287390.3425230.171261
1360.8056370.3887260.194363
1370.8296930.3406140.170307
1380.8155740.3688530.184426
1390.7939990.4120030.206001
1400.7690160.4619690.230984
1410.7428220.5143560.257178
1420.7511120.4977760.248888
1430.7256490.5487030.274351
1440.7282990.5434020.271701
1450.7080940.5838120.291906
1460.677380.6452410.32262
1470.6460930.7078140.353907
1480.6145290.7709430.385471
1490.6047950.790410.395205
1500.6042730.7914530.395727
1510.8252640.3494730.174736
1520.8048320.3903370.195168
1530.8029130.3941750.197087
1540.7786750.442650.221325
1550.7850660.4298690.214934
1560.7614950.477010.238505
1570.738280.523440.26172
1580.7118360.5763290.288164
1590.7202460.5595090.279754
1600.7131710.5736570.286829
1610.6952940.6094130.304706
1620.7066840.5866330.293316
1630.6782040.6435920.321796
1640.9233340.1533330.0766663
1650.9100460.1799090.0899544
1660.9081330.1837340.0918671
1670.891810.2163810.10819
1680.8847630.2304730.115237
1690.8693530.2612930.130647
1700.8795250.240950.120475
1710.8635960.2728090.136404
1720.8578710.2842590.142129
1730.8697580.2604850.130242
1740.8547530.2904940.145247
1750.8364780.3270450.163522
1760.8407060.3185880.159294
1770.8269490.3461030.173051
1780.8341580.3316840.165842
1790.8321160.3357670.167884
1800.8295830.3408350.170417
1810.8422560.3154880.157744
1820.8523970.2952060.147603
1830.8514540.2970920.148546
1840.831040.337920.16896
1850.8767180.2465640.123282
1860.8608520.2782970.139148
1870.862860.2742790.13714
1880.8741770.2516450.125823
1890.8784770.2430450.121523
1900.8682040.2635910.131796
1910.8496390.3007210.150361
1920.827670.3446610.17233
1930.8679650.264070.132035
1940.8779130.2441740.122087
1950.8658350.2683310.134165
1960.8510880.2978240.148912
1970.8524340.2951320.147566
1980.8297770.3404460.170223
1990.8199380.3601240.180062
2000.7922720.4154560.207728
2010.7699020.4601960.230098
2020.7432540.5134930.256746
2030.7624840.4750330.237516
2040.7285180.5429640.271482
2050.7034330.5931330.296567
2060.6955510.6088980.304449
2070.6815990.6368020.318401
2080.6565320.6869360.343468
2090.6223460.7553090.377654
2100.6060320.7879350.393968
2110.5705490.8589010.429451
2120.5279630.9440730.472037
2130.517250.96550.48275
2140.4719310.9438610.528069
2150.4481120.8962240.551888
2160.40490.80980.5951
2170.382240.7644790.61776
2180.3611580.7223160.638842
2190.3245410.6490820.675459
2200.2909410.5818820.709059
2210.3197510.6395010.680249
2220.3739720.7479440.626028
2230.3383540.6767080.661646
2240.3965920.7931830.603408
2250.4133630.8267260.586637
2260.4851510.9703020.514849
2270.480570.961140.51943
2280.5955560.8088880.404444
2290.7137850.572430.286215
2300.7488850.502230.251115
2310.7575540.4848930.242446
2320.7310930.5378130.268907
2330.7092350.5815290.290765
2340.670770.658460.32923
2350.6266780.7466450.373322
2360.715380.569240.28462
2370.6871810.6256380.312819
2380.6428480.7143040.357152
2390.6485150.702970.351485
2400.5982210.8035580.401779
2410.5632760.8734480.436724
2420.5019020.9961960.498098
2430.448110.896220.55189
2440.3963910.7927820.603609
2450.3365640.6731280.663436
2460.2755850.5511710.724415
2470.2179260.4358510.782074
2480.406010.812020.59399
2490.3344190.6688370.665581
2500.2696850.5393690.730315
2510.2332050.4664110.766795
2520.1786440.3572890.821356
2530.1724010.3448010.827599
2540.160350.3206990.83965
2550.1791250.3582490.820875
2560.1346490.2692980.865351
2570.1063140.2126270.893686
2580.1680870.3361750.831913
2590.7094780.5810440.290522

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 & 0.332019 & 0.664038 & 0.667981 \tabularnewline
20 & 0.550928 & 0.898145 & 0.449072 \tabularnewline
21 & 0.416726 & 0.833451 & 0.583274 \tabularnewline
22 & 0.292541 & 0.585083 & 0.707459 \tabularnewline
23 & 0.217123 & 0.434246 & 0.782877 \tabularnewline
24 & 0.202047 & 0.404094 & 0.797953 \tabularnewline
25 & 0.134039 & 0.268078 & 0.865961 \tabularnewline
26 & 0.14079 & 0.28158 & 0.85921 \tabularnewline
27 & 0.100146 & 0.200293 & 0.899854 \tabularnewline
28 & 0.0883729 & 0.176746 & 0.911627 \tabularnewline
29 & 0.0707313 & 0.141463 & 0.929269 \tabularnewline
30 & 0.0682723 & 0.136545 & 0.931728 \tabularnewline
31 & 0.0878243 & 0.175649 & 0.912176 \tabularnewline
32 & 0.059606 & 0.119212 & 0.940394 \tabularnewline
33 & 0.102915 & 0.20583 & 0.897085 \tabularnewline
34 & 0.199561 & 0.399123 & 0.800439 \tabularnewline
35 & 0.163127 & 0.326255 & 0.836873 \tabularnewline
36 & 0.164239 & 0.328477 & 0.835761 \tabularnewline
37 & 0.167353 & 0.334706 & 0.832647 \tabularnewline
38 & 0.14499 & 0.289979 & 0.85501 \tabularnewline
39 & 0.156717 & 0.313433 & 0.843283 \tabularnewline
40 & 0.12073 & 0.24146 & 0.87927 \tabularnewline
41 & 0.182868 & 0.365737 & 0.817132 \tabularnewline
42 & 0.171279 & 0.342557 & 0.828721 \tabularnewline
43 & 0.177262 & 0.354523 & 0.822738 \tabularnewline
44 & 0.151641 & 0.303281 & 0.848359 \tabularnewline
45 & 0.135008 & 0.270015 & 0.864992 \tabularnewline
46 & 0.107014 & 0.214029 & 0.892986 \tabularnewline
47 & 0.10902 & 0.21804 & 0.89098 \tabularnewline
48 & 0.121461 & 0.242922 & 0.878539 \tabularnewline
49 & 0.165353 & 0.330706 & 0.834647 \tabularnewline
50 & 0.194806 & 0.389612 & 0.805194 \tabularnewline
51 & 0.162725 & 0.32545 & 0.837275 \tabularnewline
52 & 0.188039 & 0.376077 & 0.811961 \tabularnewline
53 & 0.174831 & 0.349661 & 0.825169 \tabularnewline
54 & 0.159292 & 0.318583 & 0.840708 \tabularnewline
55 & 0.289947 & 0.579894 & 0.710053 \tabularnewline
56 & 0.248939 & 0.497879 & 0.751061 \tabularnewline
57 & 0.535619 & 0.928762 & 0.464381 \tabularnewline
58 & 0.612245 & 0.77551 & 0.387755 \tabularnewline
59 & 0.566936 & 0.866128 & 0.433064 \tabularnewline
60 & 0.561321 & 0.877359 & 0.438679 \tabularnewline
61 & 0.573093 & 0.853815 & 0.426907 \tabularnewline
62 & 0.5809 & 0.838199 & 0.4191 \tabularnewline
63 & 0.670759 & 0.658483 & 0.329241 \tabularnewline
64 & 0.76529 & 0.469421 & 0.23471 \tabularnewline
65 & 0.767556 & 0.464888 & 0.232444 \tabularnewline
66 & 0.740017 & 0.519966 & 0.259983 \tabularnewline
67 & 0.712603 & 0.574794 & 0.287397 \tabularnewline
68 & 0.680383 & 0.639233 & 0.319617 \tabularnewline
69 & 0.698169 & 0.603661 & 0.301831 \tabularnewline
70 & 0.664563 & 0.670874 & 0.335437 \tabularnewline
71 & 0.648074 & 0.703851 & 0.351926 \tabularnewline
72 & 0.612766 & 0.774469 & 0.387234 \tabularnewline
73 & 0.593184 & 0.813631 & 0.406816 \tabularnewline
74 & 0.632143 & 0.735715 & 0.367857 \tabularnewline
75 & 0.623745 & 0.752511 & 0.376255 \tabularnewline
76 & 0.619814 & 0.760373 & 0.380186 \tabularnewline
77 & 0.599472 & 0.801056 & 0.400528 \tabularnewline
78 & 0.585352 & 0.829296 & 0.414648 \tabularnewline
79 & 0.546936 & 0.906129 & 0.453064 \tabularnewline
80 & 0.532575 & 0.93485 & 0.467425 \tabularnewline
81 & 0.4954 & 0.990799 & 0.5046 \tabularnewline
82 & 0.541032 & 0.917936 & 0.458968 \tabularnewline
83 & 0.501437 & 0.997127 & 0.498563 \tabularnewline
84 & 0.669918 & 0.660163 & 0.330082 \tabularnewline
85 & 0.655253 & 0.689495 & 0.344747 \tabularnewline
86 & 0.61979 & 0.760421 & 0.38021 \tabularnewline
87 & 0.585 & 0.830001 & 0.415 \tabularnewline
88 & 0.557295 & 0.885409 & 0.442705 \tabularnewline
89 & 0.545063 & 0.909875 & 0.454937 \tabularnewline
90 & 0.563799 & 0.872402 & 0.436201 \tabularnewline
91 & 0.585459 & 0.829083 & 0.414541 \tabularnewline
92 & 0.672821 & 0.654359 & 0.327179 \tabularnewline
93 & 0.637651 & 0.724699 & 0.362349 \tabularnewline
94 & 0.606649 & 0.786703 & 0.393351 \tabularnewline
95 & 0.602198 & 0.795604 & 0.397802 \tabularnewline
96 & 0.569614 & 0.860773 & 0.430386 \tabularnewline
97 & 0.610305 & 0.779391 & 0.389695 \tabularnewline
98 & 0.596454 & 0.807092 & 0.403546 \tabularnewline
99 & 0.706877 & 0.586245 & 0.293123 \tabularnewline
100 & 0.732045 & 0.535909 & 0.267955 \tabularnewline
101 & 0.717846 & 0.564308 & 0.282154 \tabularnewline
102 & 0.686214 & 0.627573 & 0.313786 \tabularnewline
103 & 0.671846 & 0.656307 & 0.328154 \tabularnewline
104 & 0.644259 & 0.711483 & 0.355741 \tabularnewline
105 & 0.699031 & 0.601939 & 0.300969 \tabularnewline
106 & 0.688677 & 0.622645 & 0.311323 \tabularnewline
107 & 0.753019 & 0.493962 & 0.246981 \tabularnewline
108 & 0.842958 & 0.314083 & 0.157042 \tabularnewline
109 & 0.841534 & 0.316933 & 0.158466 \tabularnewline
110 & 0.832309 & 0.335383 & 0.167691 \tabularnewline
111 & 0.811611 & 0.376778 & 0.188389 \tabularnewline
112 & 0.791252 & 0.417495 & 0.208748 \tabularnewline
113 & 0.833649 & 0.332702 & 0.166351 \tabularnewline
114 & 0.918321 & 0.163358 & 0.0816788 \tabularnewline
115 & 0.921248 & 0.157503 & 0.0787516 \tabularnewline
116 & 0.913152 & 0.173695 & 0.0868475 \tabularnewline
117 & 0.90841 & 0.183179 & 0.0915895 \tabularnewline
118 & 0.895364 & 0.209272 & 0.104636 \tabularnewline
119 & 0.882082 & 0.235836 & 0.117918 \tabularnewline
120 & 0.871434 & 0.257131 & 0.128566 \tabularnewline
121 & 0.891492 & 0.217015 & 0.108508 \tabularnewline
122 & 0.890002 & 0.219996 & 0.109998 \tabularnewline
123 & 0.874397 & 0.251207 & 0.125603 \tabularnewline
124 & 0.946383 & 0.107234 & 0.053617 \tabularnewline
125 & 0.953944 & 0.0921112 & 0.0460556 \tabularnewline
126 & 0.947275 & 0.10545 & 0.052725 \tabularnewline
127 & 0.937153 & 0.125694 & 0.0628471 \tabularnewline
128 & 0.926143 & 0.147715 & 0.0738574 \tabularnewline
129 & 0.918289 & 0.163422 & 0.0817112 \tabularnewline
130 & 0.904455 & 0.191089 & 0.0955445 \tabularnewline
131 & 0.891218 & 0.217564 & 0.108782 \tabularnewline
132 & 0.881175 & 0.23765 & 0.118825 \tabularnewline
133 & 0.867252 & 0.265496 & 0.132748 \tabularnewline
134 & 0.850281 & 0.299438 & 0.149719 \tabularnewline
135 & 0.828739 & 0.342523 & 0.171261 \tabularnewline
136 & 0.805637 & 0.388726 & 0.194363 \tabularnewline
137 & 0.829693 & 0.340614 & 0.170307 \tabularnewline
138 & 0.815574 & 0.368853 & 0.184426 \tabularnewline
139 & 0.793999 & 0.412003 & 0.206001 \tabularnewline
140 & 0.769016 & 0.461969 & 0.230984 \tabularnewline
141 & 0.742822 & 0.514356 & 0.257178 \tabularnewline
142 & 0.751112 & 0.497776 & 0.248888 \tabularnewline
143 & 0.725649 & 0.548703 & 0.274351 \tabularnewline
144 & 0.728299 & 0.543402 & 0.271701 \tabularnewline
145 & 0.708094 & 0.583812 & 0.291906 \tabularnewline
146 & 0.67738 & 0.645241 & 0.32262 \tabularnewline
147 & 0.646093 & 0.707814 & 0.353907 \tabularnewline
148 & 0.614529 & 0.770943 & 0.385471 \tabularnewline
149 & 0.604795 & 0.79041 & 0.395205 \tabularnewline
150 & 0.604273 & 0.791453 & 0.395727 \tabularnewline
151 & 0.825264 & 0.349473 & 0.174736 \tabularnewline
152 & 0.804832 & 0.390337 & 0.195168 \tabularnewline
153 & 0.802913 & 0.394175 & 0.197087 \tabularnewline
154 & 0.778675 & 0.44265 & 0.221325 \tabularnewline
155 & 0.785066 & 0.429869 & 0.214934 \tabularnewline
156 & 0.761495 & 0.47701 & 0.238505 \tabularnewline
157 & 0.73828 & 0.52344 & 0.26172 \tabularnewline
158 & 0.711836 & 0.576329 & 0.288164 \tabularnewline
159 & 0.720246 & 0.559509 & 0.279754 \tabularnewline
160 & 0.713171 & 0.573657 & 0.286829 \tabularnewline
161 & 0.695294 & 0.609413 & 0.304706 \tabularnewline
162 & 0.706684 & 0.586633 & 0.293316 \tabularnewline
163 & 0.678204 & 0.643592 & 0.321796 \tabularnewline
164 & 0.923334 & 0.153333 & 0.0766663 \tabularnewline
165 & 0.910046 & 0.179909 & 0.0899544 \tabularnewline
166 & 0.908133 & 0.183734 & 0.0918671 \tabularnewline
167 & 0.89181 & 0.216381 & 0.10819 \tabularnewline
168 & 0.884763 & 0.230473 & 0.115237 \tabularnewline
169 & 0.869353 & 0.261293 & 0.130647 \tabularnewline
170 & 0.879525 & 0.24095 & 0.120475 \tabularnewline
171 & 0.863596 & 0.272809 & 0.136404 \tabularnewline
172 & 0.857871 & 0.284259 & 0.142129 \tabularnewline
173 & 0.869758 & 0.260485 & 0.130242 \tabularnewline
174 & 0.854753 & 0.290494 & 0.145247 \tabularnewline
175 & 0.836478 & 0.327045 & 0.163522 \tabularnewline
176 & 0.840706 & 0.318588 & 0.159294 \tabularnewline
177 & 0.826949 & 0.346103 & 0.173051 \tabularnewline
178 & 0.834158 & 0.331684 & 0.165842 \tabularnewline
179 & 0.832116 & 0.335767 & 0.167884 \tabularnewline
180 & 0.829583 & 0.340835 & 0.170417 \tabularnewline
181 & 0.842256 & 0.315488 & 0.157744 \tabularnewline
182 & 0.852397 & 0.295206 & 0.147603 \tabularnewline
183 & 0.851454 & 0.297092 & 0.148546 \tabularnewline
184 & 0.83104 & 0.33792 & 0.16896 \tabularnewline
185 & 0.876718 & 0.246564 & 0.123282 \tabularnewline
186 & 0.860852 & 0.278297 & 0.139148 \tabularnewline
187 & 0.86286 & 0.274279 & 0.13714 \tabularnewline
188 & 0.874177 & 0.251645 & 0.125823 \tabularnewline
189 & 0.878477 & 0.243045 & 0.121523 \tabularnewline
190 & 0.868204 & 0.263591 & 0.131796 \tabularnewline
191 & 0.849639 & 0.300721 & 0.150361 \tabularnewline
192 & 0.82767 & 0.344661 & 0.17233 \tabularnewline
193 & 0.867965 & 0.26407 & 0.132035 \tabularnewline
194 & 0.877913 & 0.244174 & 0.122087 \tabularnewline
195 & 0.865835 & 0.268331 & 0.134165 \tabularnewline
196 & 0.851088 & 0.297824 & 0.148912 \tabularnewline
197 & 0.852434 & 0.295132 & 0.147566 \tabularnewline
198 & 0.829777 & 0.340446 & 0.170223 \tabularnewline
199 & 0.819938 & 0.360124 & 0.180062 \tabularnewline
200 & 0.792272 & 0.415456 & 0.207728 \tabularnewline
201 & 0.769902 & 0.460196 & 0.230098 \tabularnewline
202 & 0.743254 & 0.513493 & 0.256746 \tabularnewline
203 & 0.762484 & 0.475033 & 0.237516 \tabularnewline
204 & 0.728518 & 0.542964 & 0.271482 \tabularnewline
205 & 0.703433 & 0.593133 & 0.296567 \tabularnewline
206 & 0.695551 & 0.608898 & 0.304449 \tabularnewline
207 & 0.681599 & 0.636802 & 0.318401 \tabularnewline
208 & 0.656532 & 0.686936 & 0.343468 \tabularnewline
209 & 0.622346 & 0.755309 & 0.377654 \tabularnewline
210 & 0.606032 & 0.787935 & 0.393968 \tabularnewline
211 & 0.570549 & 0.858901 & 0.429451 \tabularnewline
212 & 0.527963 & 0.944073 & 0.472037 \tabularnewline
213 & 0.51725 & 0.9655 & 0.48275 \tabularnewline
214 & 0.471931 & 0.943861 & 0.528069 \tabularnewline
215 & 0.448112 & 0.896224 & 0.551888 \tabularnewline
216 & 0.4049 & 0.8098 & 0.5951 \tabularnewline
217 & 0.38224 & 0.764479 & 0.61776 \tabularnewline
218 & 0.361158 & 0.722316 & 0.638842 \tabularnewline
219 & 0.324541 & 0.649082 & 0.675459 \tabularnewline
220 & 0.290941 & 0.581882 & 0.709059 \tabularnewline
221 & 0.319751 & 0.639501 & 0.680249 \tabularnewline
222 & 0.373972 & 0.747944 & 0.626028 \tabularnewline
223 & 0.338354 & 0.676708 & 0.661646 \tabularnewline
224 & 0.396592 & 0.793183 & 0.603408 \tabularnewline
225 & 0.413363 & 0.826726 & 0.586637 \tabularnewline
226 & 0.485151 & 0.970302 & 0.514849 \tabularnewline
227 & 0.48057 & 0.96114 & 0.51943 \tabularnewline
228 & 0.595556 & 0.808888 & 0.404444 \tabularnewline
229 & 0.713785 & 0.57243 & 0.286215 \tabularnewline
230 & 0.748885 & 0.50223 & 0.251115 \tabularnewline
231 & 0.757554 & 0.484893 & 0.242446 \tabularnewline
232 & 0.731093 & 0.537813 & 0.268907 \tabularnewline
233 & 0.709235 & 0.581529 & 0.290765 \tabularnewline
234 & 0.67077 & 0.65846 & 0.32923 \tabularnewline
235 & 0.626678 & 0.746645 & 0.373322 \tabularnewline
236 & 0.71538 & 0.56924 & 0.28462 \tabularnewline
237 & 0.687181 & 0.625638 & 0.312819 \tabularnewline
238 & 0.642848 & 0.714304 & 0.357152 \tabularnewline
239 & 0.648515 & 0.70297 & 0.351485 \tabularnewline
240 & 0.598221 & 0.803558 & 0.401779 \tabularnewline
241 & 0.563276 & 0.873448 & 0.436724 \tabularnewline
242 & 0.501902 & 0.996196 & 0.498098 \tabularnewline
243 & 0.44811 & 0.89622 & 0.55189 \tabularnewline
244 & 0.396391 & 0.792782 & 0.603609 \tabularnewline
245 & 0.336564 & 0.673128 & 0.663436 \tabularnewline
246 & 0.275585 & 0.551171 & 0.724415 \tabularnewline
247 & 0.217926 & 0.435851 & 0.782074 \tabularnewline
248 & 0.40601 & 0.81202 & 0.59399 \tabularnewline
249 & 0.334419 & 0.668837 & 0.665581 \tabularnewline
250 & 0.269685 & 0.539369 & 0.730315 \tabularnewline
251 & 0.233205 & 0.466411 & 0.766795 \tabularnewline
252 & 0.178644 & 0.357289 & 0.821356 \tabularnewline
253 & 0.172401 & 0.344801 & 0.827599 \tabularnewline
254 & 0.16035 & 0.320699 & 0.83965 \tabularnewline
255 & 0.179125 & 0.358249 & 0.820875 \tabularnewline
256 & 0.134649 & 0.269298 & 0.865351 \tabularnewline
257 & 0.106314 & 0.212627 & 0.893686 \tabularnewline
258 & 0.168087 & 0.336175 & 0.831913 \tabularnewline
259 & 0.709478 & 0.581044 & 0.290522 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&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]19[/C][C]0.332019[/C][C]0.664038[/C][C]0.667981[/C][/ROW]
[ROW][C]20[/C][C]0.550928[/C][C]0.898145[/C][C]0.449072[/C][/ROW]
[ROW][C]21[/C][C]0.416726[/C][C]0.833451[/C][C]0.583274[/C][/ROW]
[ROW][C]22[/C][C]0.292541[/C][C]0.585083[/C][C]0.707459[/C][/ROW]
[ROW][C]23[/C][C]0.217123[/C][C]0.434246[/C][C]0.782877[/C][/ROW]
[ROW][C]24[/C][C]0.202047[/C][C]0.404094[/C][C]0.797953[/C][/ROW]
[ROW][C]25[/C][C]0.134039[/C][C]0.268078[/C][C]0.865961[/C][/ROW]
[ROW][C]26[/C][C]0.14079[/C][C]0.28158[/C][C]0.85921[/C][/ROW]
[ROW][C]27[/C][C]0.100146[/C][C]0.200293[/C][C]0.899854[/C][/ROW]
[ROW][C]28[/C][C]0.0883729[/C][C]0.176746[/C][C]0.911627[/C][/ROW]
[ROW][C]29[/C][C]0.0707313[/C][C]0.141463[/C][C]0.929269[/C][/ROW]
[ROW][C]30[/C][C]0.0682723[/C][C]0.136545[/C][C]0.931728[/C][/ROW]
[ROW][C]31[/C][C]0.0878243[/C][C]0.175649[/C][C]0.912176[/C][/ROW]
[ROW][C]32[/C][C]0.059606[/C][C]0.119212[/C][C]0.940394[/C][/ROW]
[ROW][C]33[/C][C]0.102915[/C][C]0.20583[/C][C]0.897085[/C][/ROW]
[ROW][C]34[/C][C]0.199561[/C][C]0.399123[/C][C]0.800439[/C][/ROW]
[ROW][C]35[/C][C]0.163127[/C][C]0.326255[/C][C]0.836873[/C][/ROW]
[ROW][C]36[/C][C]0.164239[/C][C]0.328477[/C][C]0.835761[/C][/ROW]
[ROW][C]37[/C][C]0.167353[/C][C]0.334706[/C][C]0.832647[/C][/ROW]
[ROW][C]38[/C][C]0.14499[/C][C]0.289979[/C][C]0.85501[/C][/ROW]
[ROW][C]39[/C][C]0.156717[/C][C]0.313433[/C][C]0.843283[/C][/ROW]
[ROW][C]40[/C][C]0.12073[/C][C]0.24146[/C][C]0.87927[/C][/ROW]
[ROW][C]41[/C][C]0.182868[/C][C]0.365737[/C][C]0.817132[/C][/ROW]
[ROW][C]42[/C][C]0.171279[/C][C]0.342557[/C][C]0.828721[/C][/ROW]
[ROW][C]43[/C][C]0.177262[/C][C]0.354523[/C][C]0.822738[/C][/ROW]
[ROW][C]44[/C][C]0.151641[/C][C]0.303281[/C][C]0.848359[/C][/ROW]
[ROW][C]45[/C][C]0.135008[/C][C]0.270015[/C][C]0.864992[/C][/ROW]
[ROW][C]46[/C][C]0.107014[/C][C]0.214029[/C][C]0.892986[/C][/ROW]
[ROW][C]47[/C][C]0.10902[/C][C]0.21804[/C][C]0.89098[/C][/ROW]
[ROW][C]48[/C][C]0.121461[/C][C]0.242922[/C][C]0.878539[/C][/ROW]
[ROW][C]49[/C][C]0.165353[/C][C]0.330706[/C][C]0.834647[/C][/ROW]
[ROW][C]50[/C][C]0.194806[/C][C]0.389612[/C][C]0.805194[/C][/ROW]
[ROW][C]51[/C][C]0.162725[/C][C]0.32545[/C][C]0.837275[/C][/ROW]
[ROW][C]52[/C][C]0.188039[/C][C]0.376077[/C][C]0.811961[/C][/ROW]
[ROW][C]53[/C][C]0.174831[/C][C]0.349661[/C][C]0.825169[/C][/ROW]
[ROW][C]54[/C][C]0.159292[/C][C]0.318583[/C][C]0.840708[/C][/ROW]
[ROW][C]55[/C][C]0.289947[/C][C]0.579894[/C][C]0.710053[/C][/ROW]
[ROW][C]56[/C][C]0.248939[/C][C]0.497879[/C][C]0.751061[/C][/ROW]
[ROW][C]57[/C][C]0.535619[/C][C]0.928762[/C][C]0.464381[/C][/ROW]
[ROW][C]58[/C][C]0.612245[/C][C]0.77551[/C][C]0.387755[/C][/ROW]
[ROW][C]59[/C][C]0.566936[/C][C]0.866128[/C][C]0.433064[/C][/ROW]
[ROW][C]60[/C][C]0.561321[/C][C]0.877359[/C][C]0.438679[/C][/ROW]
[ROW][C]61[/C][C]0.573093[/C][C]0.853815[/C][C]0.426907[/C][/ROW]
[ROW][C]62[/C][C]0.5809[/C][C]0.838199[/C][C]0.4191[/C][/ROW]
[ROW][C]63[/C][C]0.670759[/C][C]0.658483[/C][C]0.329241[/C][/ROW]
[ROW][C]64[/C][C]0.76529[/C][C]0.469421[/C][C]0.23471[/C][/ROW]
[ROW][C]65[/C][C]0.767556[/C][C]0.464888[/C][C]0.232444[/C][/ROW]
[ROW][C]66[/C][C]0.740017[/C][C]0.519966[/C][C]0.259983[/C][/ROW]
[ROW][C]67[/C][C]0.712603[/C][C]0.574794[/C][C]0.287397[/C][/ROW]
[ROW][C]68[/C][C]0.680383[/C][C]0.639233[/C][C]0.319617[/C][/ROW]
[ROW][C]69[/C][C]0.698169[/C][C]0.603661[/C][C]0.301831[/C][/ROW]
[ROW][C]70[/C][C]0.664563[/C][C]0.670874[/C][C]0.335437[/C][/ROW]
[ROW][C]71[/C][C]0.648074[/C][C]0.703851[/C][C]0.351926[/C][/ROW]
[ROW][C]72[/C][C]0.612766[/C][C]0.774469[/C][C]0.387234[/C][/ROW]
[ROW][C]73[/C][C]0.593184[/C][C]0.813631[/C][C]0.406816[/C][/ROW]
[ROW][C]74[/C][C]0.632143[/C][C]0.735715[/C][C]0.367857[/C][/ROW]
[ROW][C]75[/C][C]0.623745[/C][C]0.752511[/C][C]0.376255[/C][/ROW]
[ROW][C]76[/C][C]0.619814[/C][C]0.760373[/C][C]0.380186[/C][/ROW]
[ROW][C]77[/C][C]0.599472[/C][C]0.801056[/C][C]0.400528[/C][/ROW]
[ROW][C]78[/C][C]0.585352[/C][C]0.829296[/C][C]0.414648[/C][/ROW]
[ROW][C]79[/C][C]0.546936[/C][C]0.906129[/C][C]0.453064[/C][/ROW]
[ROW][C]80[/C][C]0.532575[/C][C]0.93485[/C][C]0.467425[/C][/ROW]
[ROW][C]81[/C][C]0.4954[/C][C]0.990799[/C][C]0.5046[/C][/ROW]
[ROW][C]82[/C][C]0.541032[/C][C]0.917936[/C][C]0.458968[/C][/ROW]
[ROW][C]83[/C][C]0.501437[/C][C]0.997127[/C][C]0.498563[/C][/ROW]
[ROW][C]84[/C][C]0.669918[/C][C]0.660163[/C][C]0.330082[/C][/ROW]
[ROW][C]85[/C][C]0.655253[/C][C]0.689495[/C][C]0.344747[/C][/ROW]
[ROW][C]86[/C][C]0.61979[/C][C]0.760421[/C][C]0.38021[/C][/ROW]
[ROW][C]87[/C][C]0.585[/C][C]0.830001[/C][C]0.415[/C][/ROW]
[ROW][C]88[/C][C]0.557295[/C][C]0.885409[/C][C]0.442705[/C][/ROW]
[ROW][C]89[/C][C]0.545063[/C][C]0.909875[/C][C]0.454937[/C][/ROW]
[ROW][C]90[/C][C]0.563799[/C][C]0.872402[/C][C]0.436201[/C][/ROW]
[ROW][C]91[/C][C]0.585459[/C][C]0.829083[/C][C]0.414541[/C][/ROW]
[ROW][C]92[/C][C]0.672821[/C][C]0.654359[/C][C]0.327179[/C][/ROW]
[ROW][C]93[/C][C]0.637651[/C][C]0.724699[/C][C]0.362349[/C][/ROW]
[ROW][C]94[/C][C]0.606649[/C][C]0.786703[/C][C]0.393351[/C][/ROW]
[ROW][C]95[/C][C]0.602198[/C][C]0.795604[/C][C]0.397802[/C][/ROW]
[ROW][C]96[/C][C]0.569614[/C][C]0.860773[/C][C]0.430386[/C][/ROW]
[ROW][C]97[/C][C]0.610305[/C][C]0.779391[/C][C]0.389695[/C][/ROW]
[ROW][C]98[/C][C]0.596454[/C][C]0.807092[/C][C]0.403546[/C][/ROW]
[ROW][C]99[/C][C]0.706877[/C][C]0.586245[/C][C]0.293123[/C][/ROW]
[ROW][C]100[/C][C]0.732045[/C][C]0.535909[/C][C]0.267955[/C][/ROW]
[ROW][C]101[/C][C]0.717846[/C][C]0.564308[/C][C]0.282154[/C][/ROW]
[ROW][C]102[/C][C]0.686214[/C][C]0.627573[/C][C]0.313786[/C][/ROW]
[ROW][C]103[/C][C]0.671846[/C][C]0.656307[/C][C]0.328154[/C][/ROW]
[ROW][C]104[/C][C]0.644259[/C][C]0.711483[/C][C]0.355741[/C][/ROW]
[ROW][C]105[/C][C]0.699031[/C][C]0.601939[/C][C]0.300969[/C][/ROW]
[ROW][C]106[/C][C]0.688677[/C][C]0.622645[/C][C]0.311323[/C][/ROW]
[ROW][C]107[/C][C]0.753019[/C][C]0.493962[/C][C]0.246981[/C][/ROW]
[ROW][C]108[/C][C]0.842958[/C][C]0.314083[/C][C]0.157042[/C][/ROW]
[ROW][C]109[/C][C]0.841534[/C][C]0.316933[/C][C]0.158466[/C][/ROW]
[ROW][C]110[/C][C]0.832309[/C][C]0.335383[/C][C]0.167691[/C][/ROW]
[ROW][C]111[/C][C]0.811611[/C][C]0.376778[/C][C]0.188389[/C][/ROW]
[ROW][C]112[/C][C]0.791252[/C][C]0.417495[/C][C]0.208748[/C][/ROW]
[ROW][C]113[/C][C]0.833649[/C][C]0.332702[/C][C]0.166351[/C][/ROW]
[ROW][C]114[/C][C]0.918321[/C][C]0.163358[/C][C]0.0816788[/C][/ROW]
[ROW][C]115[/C][C]0.921248[/C][C]0.157503[/C][C]0.0787516[/C][/ROW]
[ROW][C]116[/C][C]0.913152[/C][C]0.173695[/C][C]0.0868475[/C][/ROW]
[ROW][C]117[/C][C]0.90841[/C][C]0.183179[/C][C]0.0915895[/C][/ROW]
[ROW][C]118[/C][C]0.895364[/C][C]0.209272[/C][C]0.104636[/C][/ROW]
[ROW][C]119[/C][C]0.882082[/C][C]0.235836[/C][C]0.117918[/C][/ROW]
[ROW][C]120[/C][C]0.871434[/C][C]0.257131[/C][C]0.128566[/C][/ROW]
[ROW][C]121[/C][C]0.891492[/C][C]0.217015[/C][C]0.108508[/C][/ROW]
[ROW][C]122[/C][C]0.890002[/C][C]0.219996[/C][C]0.109998[/C][/ROW]
[ROW][C]123[/C][C]0.874397[/C][C]0.251207[/C][C]0.125603[/C][/ROW]
[ROW][C]124[/C][C]0.946383[/C][C]0.107234[/C][C]0.053617[/C][/ROW]
[ROW][C]125[/C][C]0.953944[/C][C]0.0921112[/C][C]0.0460556[/C][/ROW]
[ROW][C]126[/C][C]0.947275[/C][C]0.10545[/C][C]0.052725[/C][/ROW]
[ROW][C]127[/C][C]0.937153[/C][C]0.125694[/C][C]0.0628471[/C][/ROW]
[ROW][C]128[/C][C]0.926143[/C][C]0.147715[/C][C]0.0738574[/C][/ROW]
[ROW][C]129[/C][C]0.918289[/C][C]0.163422[/C][C]0.0817112[/C][/ROW]
[ROW][C]130[/C][C]0.904455[/C][C]0.191089[/C][C]0.0955445[/C][/ROW]
[ROW][C]131[/C][C]0.891218[/C][C]0.217564[/C][C]0.108782[/C][/ROW]
[ROW][C]132[/C][C]0.881175[/C][C]0.23765[/C][C]0.118825[/C][/ROW]
[ROW][C]133[/C][C]0.867252[/C][C]0.265496[/C][C]0.132748[/C][/ROW]
[ROW][C]134[/C][C]0.850281[/C][C]0.299438[/C][C]0.149719[/C][/ROW]
[ROW][C]135[/C][C]0.828739[/C][C]0.342523[/C][C]0.171261[/C][/ROW]
[ROW][C]136[/C][C]0.805637[/C][C]0.388726[/C][C]0.194363[/C][/ROW]
[ROW][C]137[/C][C]0.829693[/C][C]0.340614[/C][C]0.170307[/C][/ROW]
[ROW][C]138[/C][C]0.815574[/C][C]0.368853[/C][C]0.184426[/C][/ROW]
[ROW][C]139[/C][C]0.793999[/C][C]0.412003[/C][C]0.206001[/C][/ROW]
[ROW][C]140[/C][C]0.769016[/C][C]0.461969[/C][C]0.230984[/C][/ROW]
[ROW][C]141[/C][C]0.742822[/C][C]0.514356[/C][C]0.257178[/C][/ROW]
[ROW][C]142[/C][C]0.751112[/C][C]0.497776[/C][C]0.248888[/C][/ROW]
[ROW][C]143[/C][C]0.725649[/C][C]0.548703[/C][C]0.274351[/C][/ROW]
[ROW][C]144[/C][C]0.728299[/C][C]0.543402[/C][C]0.271701[/C][/ROW]
[ROW][C]145[/C][C]0.708094[/C][C]0.583812[/C][C]0.291906[/C][/ROW]
[ROW][C]146[/C][C]0.67738[/C][C]0.645241[/C][C]0.32262[/C][/ROW]
[ROW][C]147[/C][C]0.646093[/C][C]0.707814[/C][C]0.353907[/C][/ROW]
[ROW][C]148[/C][C]0.614529[/C][C]0.770943[/C][C]0.385471[/C][/ROW]
[ROW][C]149[/C][C]0.604795[/C][C]0.79041[/C][C]0.395205[/C][/ROW]
[ROW][C]150[/C][C]0.604273[/C][C]0.791453[/C][C]0.395727[/C][/ROW]
[ROW][C]151[/C][C]0.825264[/C][C]0.349473[/C][C]0.174736[/C][/ROW]
[ROW][C]152[/C][C]0.804832[/C][C]0.390337[/C][C]0.195168[/C][/ROW]
[ROW][C]153[/C][C]0.802913[/C][C]0.394175[/C][C]0.197087[/C][/ROW]
[ROW][C]154[/C][C]0.778675[/C][C]0.44265[/C][C]0.221325[/C][/ROW]
[ROW][C]155[/C][C]0.785066[/C][C]0.429869[/C][C]0.214934[/C][/ROW]
[ROW][C]156[/C][C]0.761495[/C][C]0.47701[/C][C]0.238505[/C][/ROW]
[ROW][C]157[/C][C]0.73828[/C][C]0.52344[/C][C]0.26172[/C][/ROW]
[ROW][C]158[/C][C]0.711836[/C][C]0.576329[/C][C]0.288164[/C][/ROW]
[ROW][C]159[/C][C]0.720246[/C][C]0.559509[/C][C]0.279754[/C][/ROW]
[ROW][C]160[/C][C]0.713171[/C][C]0.573657[/C][C]0.286829[/C][/ROW]
[ROW][C]161[/C][C]0.695294[/C][C]0.609413[/C][C]0.304706[/C][/ROW]
[ROW][C]162[/C][C]0.706684[/C][C]0.586633[/C][C]0.293316[/C][/ROW]
[ROW][C]163[/C][C]0.678204[/C][C]0.643592[/C][C]0.321796[/C][/ROW]
[ROW][C]164[/C][C]0.923334[/C][C]0.153333[/C][C]0.0766663[/C][/ROW]
[ROW][C]165[/C][C]0.910046[/C][C]0.179909[/C][C]0.0899544[/C][/ROW]
[ROW][C]166[/C][C]0.908133[/C][C]0.183734[/C][C]0.0918671[/C][/ROW]
[ROW][C]167[/C][C]0.89181[/C][C]0.216381[/C][C]0.10819[/C][/ROW]
[ROW][C]168[/C][C]0.884763[/C][C]0.230473[/C][C]0.115237[/C][/ROW]
[ROW][C]169[/C][C]0.869353[/C][C]0.261293[/C][C]0.130647[/C][/ROW]
[ROW][C]170[/C][C]0.879525[/C][C]0.24095[/C][C]0.120475[/C][/ROW]
[ROW][C]171[/C][C]0.863596[/C][C]0.272809[/C][C]0.136404[/C][/ROW]
[ROW][C]172[/C][C]0.857871[/C][C]0.284259[/C][C]0.142129[/C][/ROW]
[ROW][C]173[/C][C]0.869758[/C][C]0.260485[/C][C]0.130242[/C][/ROW]
[ROW][C]174[/C][C]0.854753[/C][C]0.290494[/C][C]0.145247[/C][/ROW]
[ROW][C]175[/C][C]0.836478[/C][C]0.327045[/C][C]0.163522[/C][/ROW]
[ROW][C]176[/C][C]0.840706[/C][C]0.318588[/C][C]0.159294[/C][/ROW]
[ROW][C]177[/C][C]0.826949[/C][C]0.346103[/C][C]0.173051[/C][/ROW]
[ROW][C]178[/C][C]0.834158[/C][C]0.331684[/C][C]0.165842[/C][/ROW]
[ROW][C]179[/C][C]0.832116[/C][C]0.335767[/C][C]0.167884[/C][/ROW]
[ROW][C]180[/C][C]0.829583[/C][C]0.340835[/C][C]0.170417[/C][/ROW]
[ROW][C]181[/C][C]0.842256[/C][C]0.315488[/C][C]0.157744[/C][/ROW]
[ROW][C]182[/C][C]0.852397[/C][C]0.295206[/C][C]0.147603[/C][/ROW]
[ROW][C]183[/C][C]0.851454[/C][C]0.297092[/C][C]0.148546[/C][/ROW]
[ROW][C]184[/C][C]0.83104[/C][C]0.33792[/C][C]0.16896[/C][/ROW]
[ROW][C]185[/C][C]0.876718[/C][C]0.246564[/C][C]0.123282[/C][/ROW]
[ROW][C]186[/C][C]0.860852[/C][C]0.278297[/C][C]0.139148[/C][/ROW]
[ROW][C]187[/C][C]0.86286[/C][C]0.274279[/C][C]0.13714[/C][/ROW]
[ROW][C]188[/C][C]0.874177[/C][C]0.251645[/C][C]0.125823[/C][/ROW]
[ROW][C]189[/C][C]0.878477[/C][C]0.243045[/C][C]0.121523[/C][/ROW]
[ROW][C]190[/C][C]0.868204[/C][C]0.263591[/C][C]0.131796[/C][/ROW]
[ROW][C]191[/C][C]0.849639[/C][C]0.300721[/C][C]0.150361[/C][/ROW]
[ROW][C]192[/C][C]0.82767[/C][C]0.344661[/C][C]0.17233[/C][/ROW]
[ROW][C]193[/C][C]0.867965[/C][C]0.26407[/C][C]0.132035[/C][/ROW]
[ROW][C]194[/C][C]0.877913[/C][C]0.244174[/C][C]0.122087[/C][/ROW]
[ROW][C]195[/C][C]0.865835[/C][C]0.268331[/C][C]0.134165[/C][/ROW]
[ROW][C]196[/C][C]0.851088[/C][C]0.297824[/C][C]0.148912[/C][/ROW]
[ROW][C]197[/C][C]0.852434[/C][C]0.295132[/C][C]0.147566[/C][/ROW]
[ROW][C]198[/C][C]0.829777[/C][C]0.340446[/C][C]0.170223[/C][/ROW]
[ROW][C]199[/C][C]0.819938[/C][C]0.360124[/C][C]0.180062[/C][/ROW]
[ROW][C]200[/C][C]0.792272[/C][C]0.415456[/C][C]0.207728[/C][/ROW]
[ROW][C]201[/C][C]0.769902[/C][C]0.460196[/C][C]0.230098[/C][/ROW]
[ROW][C]202[/C][C]0.743254[/C][C]0.513493[/C][C]0.256746[/C][/ROW]
[ROW][C]203[/C][C]0.762484[/C][C]0.475033[/C][C]0.237516[/C][/ROW]
[ROW][C]204[/C][C]0.728518[/C][C]0.542964[/C][C]0.271482[/C][/ROW]
[ROW][C]205[/C][C]0.703433[/C][C]0.593133[/C][C]0.296567[/C][/ROW]
[ROW][C]206[/C][C]0.695551[/C][C]0.608898[/C][C]0.304449[/C][/ROW]
[ROW][C]207[/C][C]0.681599[/C][C]0.636802[/C][C]0.318401[/C][/ROW]
[ROW][C]208[/C][C]0.656532[/C][C]0.686936[/C][C]0.343468[/C][/ROW]
[ROW][C]209[/C][C]0.622346[/C][C]0.755309[/C][C]0.377654[/C][/ROW]
[ROW][C]210[/C][C]0.606032[/C][C]0.787935[/C][C]0.393968[/C][/ROW]
[ROW][C]211[/C][C]0.570549[/C][C]0.858901[/C][C]0.429451[/C][/ROW]
[ROW][C]212[/C][C]0.527963[/C][C]0.944073[/C][C]0.472037[/C][/ROW]
[ROW][C]213[/C][C]0.51725[/C][C]0.9655[/C][C]0.48275[/C][/ROW]
[ROW][C]214[/C][C]0.471931[/C][C]0.943861[/C][C]0.528069[/C][/ROW]
[ROW][C]215[/C][C]0.448112[/C][C]0.896224[/C][C]0.551888[/C][/ROW]
[ROW][C]216[/C][C]0.4049[/C][C]0.8098[/C][C]0.5951[/C][/ROW]
[ROW][C]217[/C][C]0.38224[/C][C]0.764479[/C][C]0.61776[/C][/ROW]
[ROW][C]218[/C][C]0.361158[/C][C]0.722316[/C][C]0.638842[/C][/ROW]
[ROW][C]219[/C][C]0.324541[/C][C]0.649082[/C][C]0.675459[/C][/ROW]
[ROW][C]220[/C][C]0.290941[/C][C]0.581882[/C][C]0.709059[/C][/ROW]
[ROW][C]221[/C][C]0.319751[/C][C]0.639501[/C][C]0.680249[/C][/ROW]
[ROW][C]222[/C][C]0.373972[/C][C]0.747944[/C][C]0.626028[/C][/ROW]
[ROW][C]223[/C][C]0.338354[/C][C]0.676708[/C][C]0.661646[/C][/ROW]
[ROW][C]224[/C][C]0.396592[/C][C]0.793183[/C][C]0.603408[/C][/ROW]
[ROW][C]225[/C][C]0.413363[/C][C]0.826726[/C][C]0.586637[/C][/ROW]
[ROW][C]226[/C][C]0.485151[/C][C]0.970302[/C][C]0.514849[/C][/ROW]
[ROW][C]227[/C][C]0.48057[/C][C]0.96114[/C][C]0.51943[/C][/ROW]
[ROW][C]228[/C][C]0.595556[/C][C]0.808888[/C][C]0.404444[/C][/ROW]
[ROW][C]229[/C][C]0.713785[/C][C]0.57243[/C][C]0.286215[/C][/ROW]
[ROW][C]230[/C][C]0.748885[/C][C]0.50223[/C][C]0.251115[/C][/ROW]
[ROW][C]231[/C][C]0.757554[/C][C]0.484893[/C][C]0.242446[/C][/ROW]
[ROW][C]232[/C][C]0.731093[/C][C]0.537813[/C][C]0.268907[/C][/ROW]
[ROW][C]233[/C][C]0.709235[/C][C]0.581529[/C][C]0.290765[/C][/ROW]
[ROW][C]234[/C][C]0.67077[/C][C]0.65846[/C][C]0.32923[/C][/ROW]
[ROW][C]235[/C][C]0.626678[/C][C]0.746645[/C][C]0.373322[/C][/ROW]
[ROW][C]236[/C][C]0.71538[/C][C]0.56924[/C][C]0.28462[/C][/ROW]
[ROW][C]237[/C][C]0.687181[/C][C]0.625638[/C][C]0.312819[/C][/ROW]
[ROW][C]238[/C][C]0.642848[/C][C]0.714304[/C][C]0.357152[/C][/ROW]
[ROW][C]239[/C][C]0.648515[/C][C]0.70297[/C][C]0.351485[/C][/ROW]
[ROW][C]240[/C][C]0.598221[/C][C]0.803558[/C][C]0.401779[/C][/ROW]
[ROW][C]241[/C][C]0.563276[/C][C]0.873448[/C][C]0.436724[/C][/ROW]
[ROW][C]242[/C][C]0.501902[/C][C]0.996196[/C][C]0.498098[/C][/ROW]
[ROW][C]243[/C][C]0.44811[/C][C]0.89622[/C][C]0.55189[/C][/ROW]
[ROW][C]244[/C][C]0.396391[/C][C]0.792782[/C][C]0.603609[/C][/ROW]
[ROW][C]245[/C][C]0.336564[/C][C]0.673128[/C][C]0.663436[/C][/ROW]
[ROW][C]246[/C][C]0.275585[/C][C]0.551171[/C][C]0.724415[/C][/ROW]
[ROW][C]247[/C][C]0.217926[/C][C]0.435851[/C][C]0.782074[/C][/ROW]
[ROW][C]248[/C][C]0.40601[/C][C]0.81202[/C][C]0.59399[/C][/ROW]
[ROW][C]249[/C][C]0.334419[/C][C]0.668837[/C][C]0.665581[/C][/ROW]
[ROW][C]250[/C][C]0.269685[/C][C]0.539369[/C][C]0.730315[/C][/ROW]
[ROW][C]251[/C][C]0.233205[/C][C]0.466411[/C][C]0.766795[/C][/ROW]
[ROW][C]252[/C][C]0.178644[/C][C]0.357289[/C][C]0.821356[/C][/ROW]
[ROW][C]253[/C][C]0.172401[/C][C]0.344801[/C][C]0.827599[/C][/ROW]
[ROW][C]254[/C][C]0.16035[/C][C]0.320699[/C][C]0.83965[/C][/ROW]
[ROW][C]255[/C][C]0.179125[/C][C]0.358249[/C][C]0.820875[/C][/ROW]
[ROW][C]256[/C][C]0.134649[/C][C]0.269298[/C][C]0.865351[/C][/ROW]
[ROW][C]257[/C][C]0.106314[/C][C]0.212627[/C][C]0.893686[/C][/ROW]
[ROW][C]258[/C][C]0.168087[/C][C]0.336175[/C][C]0.831913[/C][/ROW]
[ROW][C]259[/C][C]0.709478[/C][C]0.581044[/C][C]0.290522[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.3320190.6640380.667981
200.5509280.8981450.449072
210.4167260.8334510.583274
220.2925410.5850830.707459
230.2171230.4342460.782877
240.2020470.4040940.797953
250.1340390.2680780.865961
260.140790.281580.85921
270.1001460.2002930.899854
280.08837290.1767460.911627
290.07073130.1414630.929269
300.06827230.1365450.931728
310.08782430.1756490.912176
320.0596060.1192120.940394
330.1029150.205830.897085
340.1995610.3991230.800439
350.1631270.3262550.836873
360.1642390.3284770.835761
370.1673530.3347060.832647
380.144990.2899790.85501
390.1567170.3134330.843283
400.120730.241460.87927
410.1828680.3657370.817132
420.1712790.3425570.828721
430.1772620.3545230.822738
440.1516410.3032810.848359
450.1350080.2700150.864992
460.1070140.2140290.892986
470.109020.218040.89098
480.1214610.2429220.878539
490.1653530.3307060.834647
500.1948060.3896120.805194
510.1627250.325450.837275
520.1880390.3760770.811961
530.1748310.3496610.825169
540.1592920.3185830.840708
550.2899470.5798940.710053
560.2489390.4978790.751061
570.5356190.9287620.464381
580.6122450.775510.387755
590.5669360.8661280.433064
600.5613210.8773590.438679
610.5730930.8538150.426907
620.58090.8381990.4191
630.6707590.6584830.329241
640.765290.4694210.23471
650.7675560.4648880.232444
660.7400170.5199660.259983
670.7126030.5747940.287397
680.6803830.6392330.319617
690.6981690.6036610.301831
700.6645630.6708740.335437
710.6480740.7038510.351926
720.6127660.7744690.387234
730.5931840.8136310.406816
740.6321430.7357150.367857
750.6237450.7525110.376255
760.6198140.7603730.380186
770.5994720.8010560.400528
780.5853520.8292960.414648
790.5469360.9061290.453064
800.5325750.934850.467425
810.49540.9907990.5046
820.5410320.9179360.458968
830.5014370.9971270.498563
840.6699180.6601630.330082
850.6552530.6894950.344747
860.619790.7604210.38021
870.5850.8300010.415
880.5572950.8854090.442705
890.5450630.9098750.454937
900.5637990.8724020.436201
910.5854590.8290830.414541
920.6728210.6543590.327179
930.6376510.7246990.362349
940.6066490.7867030.393351
950.6021980.7956040.397802
960.5696140.8607730.430386
970.6103050.7793910.389695
980.5964540.8070920.403546
990.7068770.5862450.293123
1000.7320450.5359090.267955
1010.7178460.5643080.282154
1020.6862140.6275730.313786
1030.6718460.6563070.328154
1040.6442590.7114830.355741
1050.6990310.6019390.300969
1060.6886770.6226450.311323
1070.7530190.4939620.246981
1080.8429580.3140830.157042
1090.8415340.3169330.158466
1100.8323090.3353830.167691
1110.8116110.3767780.188389
1120.7912520.4174950.208748
1130.8336490.3327020.166351
1140.9183210.1633580.0816788
1150.9212480.1575030.0787516
1160.9131520.1736950.0868475
1170.908410.1831790.0915895
1180.8953640.2092720.104636
1190.8820820.2358360.117918
1200.8714340.2571310.128566
1210.8914920.2170150.108508
1220.8900020.2199960.109998
1230.8743970.2512070.125603
1240.9463830.1072340.053617
1250.9539440.09211120.0460556
1260.9472750.105450.052725
1270.9371530.1256940.0628471
1280.9261430.1477150.0738574
1290.9182890.1634220.0817112
1300.9044550.1910890.0955445
1310.8912180.2175640.108782
1320.8811750.237650.118825
1330.8672520.2654960.132748
1340.8502810.2994380.149719
1350.8287390.3425230.171261
1360.8056370.3887260.194363
1370.8296930.3406140.170307
1380.8155740.3688530.184426
1390.7939990.4120030.206001
1400.7690160.4619690.230984
1410.7428220.5143560.257178
1420.7511120.4977760.248888
1430.7256490.5487030.274351
1440.7282990.5434020.271701
1450.7080940.5838120.291906
1460.677380.6452410.32262
1470.6460930.7078140.353907
1480.6145290.7709430.385471
1490.6047950.790410.395205
1500.6042730.7914530.395727
1510.8252640.3494730.174736
1520.8048320.3903370.195168
1530.8029130.3941750.197087
1540.7786750.442650.221325
1550.7850660.4298690.214934
1560.7614950.477010.238505
1570.738280.523440.26172
1580.7118360.5763290.288164
1590.7202460.5595090.279754
1600.7131710.5736570.286829
1610.6952940.6094130.304706
1620.7066840.5866330.293316
1630.6782040.6435920.321796
1640.9233340.1533330.0766663
1650.9100460.1799090.0899544
1660.9081330.1837340.0918671
1670.891810.2163810.10819
1680.8847630.2304730.115237
1690.8693530.2612930.130647
1700.8795250.240950.120475
1710.8635960.2728090.136404
1720.8578710.2842590.142129
1730.8697580.2604850.130242
1740.8547530.2904940.145247
1750.8364780.3270450.163522
1760.8407060.3185880.159294
1770.8269490.3461030.173051
1780.8341580.3316840.165842
1790.8321160.3357670.167884
1800.8295830.3408350.170417
1810.8422560.3154880.157744
1820.8523970.2952060.147603
1830.8514540.2970920.148546
1840.831040.337920.16896
1850.8767180.2465640.123282
1860.8608520.2782970.139148
1870.862860.2742790.13714
1880.8741770.2516450.125823
1890.8784770.2430450.121523
1900.8682040.2635910.131796
1910.8496390.3007210.150361
1920.827670.3446610.17233
1930.8679650.264070.132035
1940.8779130.2441740.122087
1950.8658350.2683310.134165
1960.8510880.2978240.148912
1970.8524340.2951320.147566
1980.8297770.3404460.170223
1990.8199380.3601240.180062
2000.7922720.4154560.207728
2010.7699020.4601960.230098
2020.7432540.5134930.256746
2030.7624840.4750330.237516
2040.7285180.5429640.271482
2050.7034330.5931330.296567
2060.6955510.6088980.304449
2070.6815990.6368020.318401
2080.6565320.6869360.343468
2090.6223460.7553090.377654
2100.6060320.7879350.393968
2110.5705490.8589010.429451
2120.5279630.9440730.472037
2130.517250.96550.48275
2140.4719310.9438610.528069
2150.4481120.8962240.551888
2160.40490.80980.5951
2170.382240.7644790.61776
2180.3611580.7223160.638842
2190.3245410.6490820.675459
2200.2909410.5818820.709059
2210.3197510.6395010.680249
2220.3739720.7479440.626028
2230.3383540.6767080.661646
2240.3965920.7931830.603408
2250.4133630.8267260.586637
2260.4851510.9703020.514849
2270.480570.961140.51943
2280.5955560.8088880.404444
2290.7137850.572430.286215
2300.7488850.502230.251115
2310.7575540.4848930.242446
2320.7310930.5378130.268907
2330.7092350.5815290.290765
2340.670770.658460.32923
2350.6266780.7466450.373322
2360.715380.569240.28462
2370.6871810.6256380.312819
2380.6428480.7143040.357152
2390.6485150.702970.351485
2400.5982210.8035580.401779
2410.5632760.8734480.436724
2420.5019020.9961960.498098
2430.448110.896220.55189
2440.3963910.7927820.603609
2450.3365640.6731280.663436
2460.2755850.5511710.724415
2470.2179260.4358510.782074
2480.406010.812020.59399
2490.3344190.6688370.665581
2500.2696850.5393690.730315
2510.2332050.4664110.766795
2520.1786440.3572890.821356
2530.1724010.3448010.827599
2540.160350.3206990.83965
2550.1791250.3582490.820875
2560.1346490.2692980.865351
2570.1063140.2126270.893686
2580.1680870.3361750.831913
2590.7094780.5810440.290522







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level10.00414938OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 1 & 0.00414938 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269239&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]1[/C][C]0.00414938[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269239&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269239&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level10.00414938OK



Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')
}