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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 14:22:42 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t14182214113u4y9c1hntw7chx.htm/, Retrieved Sun, 19 May 2024 13:04:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265260, Retrieved Sun, 19 May 2024 13:04:36 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2014-12-10 14:22:42] [6e8ac1d1765f9a3eaeef7407a694f46f] [Current]
- RMPD    [Central Tendency] [] [2014-12-17 13:43:11] [36781f05c04c55e165b348994b753b95]
- RMPD    [Skewness and Kurtosis Test] [] [2014-12-17 13:49:53] [36781f05c04c55e165b348994b753b95]
- RMPD    [Cronbach Alpha] [] [2014-12-17 15:32:19] [2ba32e9656c7c3fdddad3ba3f1588288]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11 8 7 18 12 20 4 0.5 1 0.67 0.67 0 0.5 12.9 149 68
19 18 20 23 20 19 4 0.5 0.89 0.83 0.33 0.5 1 12.2 139 39
16 12 9 22 14 18 5 0.4 0.89 1 0.67 0 1 12.8 148 32
24 24 19 22 25 24 4 0.5 0.89 0.83 0 0 0 7.4 158 62
15 16 12 19 15 20 4 0.7 0.89 0.67 0 1 1 6.7 128 33
17 19 16 25 20 20 9 0.3 0.78 0 0 0.5 0.5 12.6 224 52
19 16 17 28 21 24 8 0.4 0.89 0.83 0.67 0.5 0 14.8 159 62
19 15 9 16 15 21 11 0.4 1 0.5 0.67 1 1 13.3 105 77
28 28 28 28 28 28 4 0.7 0.89 0.83 0 0.5 0 11.1 159 76
26 21 20 21 11 10 4 0.6 0.78 0.33 0.67 0.5 0.5 8.2 167 41
15 18 16 22 22 22 6 0.6 1 0.5 1 0 0.5 11.4 165 48
26 22 22 24 22 19 4 0.2 0.78 0.67 0 0.5 0.5 6.4 159 63
16 19 17 24 27 27 8 0.4 0.89 1 0 0.5 0.5 10.6 119 30
24 22 12 26 24 23 4 0.4 0.89 0.5 0.67 0 1 12 176 78
25 25 18 28 23 24 4 0.5 0.89 0.67 0.33 0 0 6.3 54 19
22 20 20 24 24 24 11 0.3 0.89 0.17 0.67 0 0.5 11.3 91 31
15 16 12 20 21 25 4 0.4 0.89 0.83 0.33 0.5 0.5 11.9 163 66
21 19 16 26 20 24 4 0.7 0.67 0.67 0.33 0.5 1 9.3 124 35
22 18 16 21 19 21 6 0.5 1 0.67 0.33 0 1 9.6 137 42
27 26 21 28 25 28 6 0.2 0.78 0.67 0 0 1 10 121 45
26 24 15 27 16 28 4 0.3 0.78 0.5 0.67 0 0.5 6.4 153 21
26 20 17 23 24 22 8 0.6 0.89 1 0.33 0 1 13.8 148 25
22 19 17 24 21 26 5 0.6 0.78 0.83 0.33 0 1 10.8 221 44
21 19 17 24 22 26 4 0.2 0.89 0.83 0.33 0 1 13.8 188 69
22 23 18 22 25 21 9 0.7 0.89 1 0.67 1 0 11.7 149 54
20 18 15 21 23 26 4 0.2 0.33 0.67 0 0 0 10.9 244 74
21 16 20 25 20 23 7 1 1 1 0.33 1 1 16.1 148 80
20 18 13 20 21 20 10 0.4 0.89 0.83 0.67 0 0.5 13.4 92 42
22 21 21 21 22 24 4 0.4 0.89 1 1 0 1 9.9 150 61
21 20 12 26 25 25 4 0.2 0.67 0.83 0.67 0 0.5 11.5 153 41
8 15 6 23 23 24 7 0.4 0.56 0.67 0.33 0 1 8.3 94 46
22 19 13 21 19 20 12 0.4 0.89 0.67 0 0.5 1 11.7 156 39
20 19 19 27 21 24 7 0.7 0.89 1 0.67 0.5 0.5 9 132 34
24 7 12 25 19 25 5 0.2 1 0.67 0.67 0 0.5 9.7 161 51
17 20 14 23 25 23 8 0.6 0.78 1 1 0 0.5 10.8 105 42
20 20 13 25 16 21 5 0.3 0.78 1 1 0.5 0.5 10.3 97 31
23 19 12 23 24 23 4 0.3 0.33 0.5 0.33 0 0 10.4 151 39
20 19 17 19 24 21 9 0.2 0.78 0.67 0 0.5 0 12.7 131 20
22 20 19 22 18 18 7 0.5 0.89 0.83 0.67 0.5 0.5 9.3 166 49
19 18 10 24 28 24 4 0.7 0.89 1 0.67 0.5 1 11.8 157 53
15 14 10 19 15 18 4 0.6 0.78 1 0.67 0.5 0.5 5.9 111 31
20 17 11 21 17 21 4 0.4 0.89 1 0.67 0.5 1 11.4 145 39
22 17 11 27 18 23 4 0.6 0.89 1 0.33 0.5 1 13 162 54
17 8 10 25 26 25 4 0.4 1 1 1 0 1 10.8 163 49
14 9 7 25 18 22 7 0.3 0.67 0.83 0.67 0 1 12.3 59 34
24 22 22 23 22 22 4 0.5 1 0.83 0.67 0.5 0.5 11.3 187 46
17 20 12 17 19 23 7 0.2 0.89 0.5 0 0 1 11.8 109 55
23 20 18 28 17 24 4 0.3 0.89 0.83 0 0.5 1 7.9 90 42
25 22 20 25 26 25 4 0.5 0.89 0.17 0 0 1 12.7 105 50
16 22 9 20 21 22 4 0.7 0.78 0.83 1 0.5 1 12.3 83 13
18 22 16 25 26 24 4 0.4 0.89 1 0.67 1 0.5 11.6 116 37
20 16 14 21 21 21 8 0.3 0.78 1 0 0 0.5 6.7 42 25
18 14 11 24 12 24 4 0.2 0.78 0.67 0.67 1 1 10.9 148 30
23 24 20 28 20 25 4 0.5 1 1 0 0 0.5 12.1 155 28
24 21 17 20 20 23 4 0.4 0.78 1 0 0.5 0 13.3 125 45
23 20 14 19 24 27 4 0.6 1 1 0.67 1 1 10.1 116 35
13 20 8 24 24 27 7 0.4 0.78 0.83 1 0 1 5.7 128 28
20 18 16 21 22 23 12 0.4 0.67 0.33 0 0 0.5 14.3 138 41
20 14 11 24 21 18 4 0.2 0.33 0.33 0.33 0 0 8 49 6
19 19 10 23 20 20 4 0.9 1 1 0.67 0.5 1 13.3 96 45
22 24 15 18 23 23 4 0.8 1 1 0.67 1 0.5 9.3 164 73
22 19 15 27 19 24 5 0.8 0.78 0.83 0 0.5 1 12.5 162 17
15 16 10 25 24 26 15 0.3 0.67 1 1 0.5 1 7.6 99 40
17 16 10 20 21 20 5 0.2 1 0.83 0.67 0 0.5 15.9 202 64
19 16 18 21 16 23 10 0.4 0.89 0.67 0 0.5 1 9.2 186 37
20 14 10 23 17 22 9 0.2 0.89 0.83 1 0 1 9.1 66 25
22 22 22 27 23 23 8 0.2 0.78 0.67 0.67 0.5 1 11.1 183 65
21 21 16 24 20 17 4 0.1 1 0.83 0.67 0 1 13 214 100
21 15 10 27 19 20 5 0.4 0.56 0.67 1 0.5 0 14.5 188 28
16 14 7 24 18 22 4 0.5 0.67 1 0 0.5 0.5 12.2 104 35
20 15 16 23 18 18 9 0.8 0.89 0.83 0.33 0.5 1 12.3 177 56
21 14 16 24 21 19 4 0.4 0.89 0.67 0.67 0 0.5 11.4 126 29
20 20 16 21 20 19 10 0.6 0.89 0.83 0.33 0.5 0.5 8.8 76 43
23 21 22 23 17 16 4 0.5 0.89 0.83 0.67 0.5 1 14.6 99 59
18 14 5 27 25 26 4 0.3 0.78 0.67 0 0 0 12.6 139 50
22 19 18 24 15 14 6 0.8 0.89 1 1 0.5 1 NA 78 3
16 16 10 25 17 25 7 0.4 1 0.33 0 0.5 0 13 162 59
17 13 8 19 17 23 5 0.6 1 0.83 0.67 0.5 0.5 12.6 108 27
24 26 16 24 24 18 4 0.4 0.89 1 0.33 0 0.5 13.2 159 61
13 13 8 25 21 22 4 0.3 0.44 0.83 0 0 0 9.9 74 28
19 18 16 23 22 26 4 0.8 0.78 0.83 0 1 1 7.7 110 51
20 15 14 23 18 25 4 0.6 0.89 0.5 0.33 1 1 10.5 96 35
22 18 15 25 22 26 4 0.3 0.67 0.5 0 0 0 13.4 116 29
19 21 9 26 20 26 4 0.5 0.78 0.83 0.67 0.5 1 10.9 87 48
21 17 21 26 21 24 6 0.4 0.78 1 0.33 0 1 4.3 97 25
15 18 7 16 21 22 10 0.3 0.33 0.33 0.67 0 0 10.3 127 44
21 20 17 23 20 21 7 0.7 0.89 1 0.33 0 0.5 11.8 106 64
24 18 18 26 18 22 4 0.2 0.89 0.67 0.33 0.5 0.5 11.2 80 32
22 25 16 25 25 28 4 0.4 0.89 0.83 1 0 1 11.4 74 20
20 20 16 23 23 22 7 0.6 0.89 1 0.67 0.5 0.5 8.6 91 28
21 19 14 26 21 26 4 0.6 0.56 0.83 0 0 1 13.2 133 34
19 18 15 22 20 20 8 0.6 0.67 0.83 0.67 0.5 0.5 12.6 74 31
14 12 8 20 21 24 11 0.4 0.67 1 0.33 0.5 1 5.6 114 26
25 22 22 27 20 21 6 0.6 0.78 0.83 0 0 1 9.9 140 58
11 16 5 20 22 23 14 0.5 0.78 1 0.33 0.5 1 8.8 95 23
17 18 13 22 15 23 5 0.5 0.78 0.83 0 0 1 7.7 98 21
22 23 22 24 24 23 4 0.6 0.89 0.67 0 0 1 9 121 21
20 20 18 21 22 22 8 0.8 1 0.83 0.33 0.5 1 7.3 126 33
22 20 15 24 21 23 9 0.5 0.89 0.83 0.67 1 0.5 11.4 98 16
15 16 11 26 17 21 4 0.6 0.89 0.83 0.67 0.5 1 13.6 95 20
23 22 19 24 23 27 4 0.4 0.78 0.83 0.67 0.5 1 7.9 110 37
20 19 19 24 22 23 5 0.3 1 0.67 0.67 0.5 1 10.7 70 35
22 23 21 27 23 26 4 0.3 0.78 0.83 1 0 0.5 10.3 102 33
16 6 4 25 16 27 5 0.2 0.67 0 0 0 0 8.3 86 27
25 19 17 27 18 27 4 0.4 0.78 0.83 0 0 0.5 9.6 130 41
18 24 10 19 25 23 4 0.5 0.89 1 0 0 0.5 14.2 96 40
19 19 13 22 18 23 7 0.3 0.67 0.17 0 0.5 0 8.5 102 35
25 15 15 22 14 23 10 0.4 0.22 0.17 0 0.5 0 13.5 100 28
21 18 11 25 20 28 4 0.5 0.44 0.5 1 0 0 4.9 94 32
22 18 20 23 19 24 5 0.3 0.89 0.5 0.67 0 1 6.4 52 22
21 22 13 24 18 20 4 0.5 0.67 1 0 0 0.5 9.6 98 44
22 23 18 24 22 23 4 0.4 0.89 0.67 0.67 0 0.5 11.6 118 27
23 18 20 23 21 22 4 0.4 0.67 0.83 0.67 0 1 11.1 99 17
20 17 15 22 14 15 6 0.6 0.78 1 0 1 1 4.35 48 12
6 6 4 24 5 27 4 0.3 0.78 1 0.67 1 1 12.7 50 45
15 22 9 19 25 23 8 0.4 0.78 1 0.33 1 0.5 18.1 150 37
18 20 18 25 21 23 5 0.3 1 1 1 1 1 17.85 154 37
24 16 12 26 11 20 4 1 0.78 1 1 1 1 16.6 109 108
22 16 17 18 20 18 17 0.4 0.67 1 0 0 0.5 12.6 68 10
21 17 12 24 9 22 4 0.8 0.89 0.83 1 0.5 1 17.1 194 68
23 20 16 28 15 20 4 0.3 0.89 1 0.67 1 1 19.1 158 72
20 23 17 23 23 21 8 0.5 1 0.83 0.67 0 1 16.1 159 143
20 18 14 19 21 25 4 0.4 0.78 1 0 0 0.5 13.35 67 9
18 13 13 19 9 19 7 0.3 0.67 0.83 0.67 0 1 18.4 147 55
25 22 20 27 24 25 4 0.5 0.89 0.83 1 0 1 14.7 39 17
16 20 16 24 16 24 4 0.3 0.67 1 0.67 0 1 10.6 100 37
20 20 15 26 20 22 5 0.3 0.67 0.67 0 0 1 12.6 111 27
14 13 10 21 15 28 7 0.4 1 0.83 0 0 1 16.2 138 37
22 16 16 25 18 22 4 0.3 0.67 1 0 0 0.5 13.6 101 58
26 25 21 28 22 21 4 0.6 1 1 0.33 0.5 0.5 18.9 131 66
20 16 15 19 21 23 7 0.6 0.89 0.83 0.67 1 1 14.1 101 21
17 15 16 20 21 19 11 0.4 0.89 1 1 1 1 14.5 114 19
22 19 19 26 21 21 7 0.4 1 1 0 0 0 16.15 165 78
22 19 9 27 20 25 4 0.4 0.67 1 0.67 0 0.5 14.75 114 35
20 24 19 23 24 23 4 0.3 0.44 0.67 0.67 0.5 1 14.8 111 48
17 9 7 18 15 28 4 0.2 0.89 1 0.33 1 0 12.45 75 27
22 22 23 23 24 14 4 0.5 0.56 0.83 0.67 0 1 12.65 82 43
17 15 14 21 18 23 4 0.4 0.78 1 0.67 1 1 17.35 121 30
22 22 10 23 24 24 4 0.4 1 1 0.67 0 0 8.6 32 25
21 22 16 22 24 25 6 0.4 1 0.83 0.67 0 1 18.4 150 69
25 24 12 21 15 15 8 0.3 0.89 0.67 0.67 0.5 0.5 16.1 117 72
11 12 10 14 19 23 23 0.4 0.67 0.83 0.67 1 0.5 11.6 71 23
19 21 7 24 20 26 4 0.2 0.89 1 0.33 0.5 1 17.75 165 13
24 25 20 26 26 21 8 0 0.33 0 0 0 0 15.25 154 61
17 26 9 24 26 26 6 0.4 0.89 1 0.67 0.5 1 17.65 126 43
22 21 12 22 23 23 4 0.6 0.78 1 0 1 1 16.35 149 51
17 14 10 20 13 15 7 0.4 1 0.67 0.67 0 0.5 17.65 145 67
26 28 19 20 16 16 4 0.4 0.44 1 0 0 0.5 13.6 120 36
20 21 11 18 22 20 4 0.4 0.67 0.83 0 0.5 0 14.35 109 44
19 16 15 18 21 20 4 0.2 0.33 0.17 0 0.5 0 14.75 132 45
21 16 14 25 11 21 10 0.4 0.89 0.83 1 1 1 18.25 172 34
24 25 11 28 23 28 6 0.3 0.89 0.83 0 0 0.5 9.9 169 36
21 21 14 23 18 19 5 0.6 1 0.83 0.67 1 0 16 114 72
19 22 15 20 19 21 5 0.6 0.89 0.83 1 0 1 18.25 156 39
13 9 7 22 15 22 4 0.4 0.89 0.83 0 0 1 16.85 172 43
24 20 22 27 8 27 4 0.5 1 1 0.67 1 0.5 14.6 68 25
28 19 19 24 15 20 5 0.4 0.89 0.83 0 0.5 1 13.85 89 56
27 24 22 23 21 17 5 0.6 1 1 1 1 1 18.95 167 80
22 22 11 20 25 26 5 0.6 0.78 0.83 0.67 0.5 1 15.6 113 40
23 22 19 22 14 21 5 0.9 0.78 1 0.67 0.5 1 14.85 115 73
19 12 9 21 21 24 4 0.4 0.67 0.83 0.67 0.5 0 11.75 78 34
18 17 11 24 18 21 6 0.8 0.89 1 1 0.5 1 18.45 118 72
23 18 17 26 18 25 4 0.5 0.67 0.83 1 0 1 15.9 87 42
21 10 12 24 12 22 4 0.4 0.78 0.83 1 0 0 17.1 173 61
22 22 17 18 24 17 4 0.4 0.89 1 0.67 1 0.5 16.1 2 23
17 24 10 17 17 14 9 0.7 0.89 1 1 1 0.5 19.9 162 74
15 18 17 23 20 23 18 0.4 0.78 1 0.33 1 1 10.95 49 16
21 18 13 21 24 28 6 0.8 1 1 0.67 0.5 1 18.45 122 66
20 23 11 21 22 24 5 0.4 1 1 1 1 0.5 15.1 96 9
26 21 19 24 15 22 4 0.3 1 1 0.67 0 0.5 15 100 41
19 21 21 22 22 24 11 0.5 0.67 1 0.67 0.5 1 11.35 82 57
28 28 24 24 26 25 4 0.8 0.89 1 0.67 1 1 15.95 100 48
21 17 13 24 17 21 10 0.4 1 0.83 0.33 0 0.5 18.1 115 51
19 21 16 24 23 22 6 1 1 1 1 0.5 0 14.6 141 53
22 21 13 23 19 16 8 0.5 0.89 1 0.67 1 1 15.4 165 29
21 20 15 21 21 18 8 0.5 0.89 1 0.67 1 1 15.4 165 29
20 18 15 24 23 27 6 0.3 0.89 1 0.33 0 1 17.6 110 55
19 17 11 19 19 17 8 0.3 0.89 0.83 0.33 0.5 1 13.35 118 54
11 7 7 19 18 25 4 0.3 0.89 0.5 0 0 1 19.1 158 43
17 17 13 23 16 24 4 0.4 1 0.67 0.33 0.5 0.5 15.35 146 51
19 14 13 25 23 21 9 0.5 0.67 1 0.33 0 1 7.6 49 20
20 18 12 24 13 21 9 0.5 1 0.67 0.67 0.5 1 13.4 90 79
17 14 8 21 18 19 5 0.4 0.89 1 0 0 0 13.9 121 39
21 23 7 18 23 27 4 0.7 0.89 1 1 0.5 0 19.1 155 61
21 20 17 23 21 28 4 0.5 0.89 0.5 0.33 0 0.5 15.25 104 55
12 14 9 20 23 19 15 0.4 0.89 0.67 0.33 1 0 12.9 147 30
23 17 18 23 16 23 10 0.7 1 0.67 1 0 1 16.1 110 55
22 21 17 23 17 25 9 0.7 1 0.67 1 0 1 17.35 108 22
22 23 17 23 20 26 7 0.7 1 0.67 1 0 1 13.15 113 37
21 24 18 23 18 25 9 0.7 0.89 0.67 1 0 1 12.15 115 2
20 21 12 27 20 25 6 0.7 0.89 0.67 0 0 0 12.6 61 38
18 14 14 19 19 24 4 0.7 0.89 1 0.67 0.5 1 10.35 60 27
21 24 22 25 26 24 7 0.1 0.33 0.67 0.33 0.5 0 15.4 109 56
24 16 19 25 9 24 4 0.2 0.67 0.67 0.67 0.5 1 9.6 68 25
22 21 21 21 23 22 7 0.3 0.56 0.33 0.33 0 1 18.2 111 39
20 8 10 25 9 21 4 0.6 0.44 0.83 0.33 0 0.5 13.6 77 33
17 17 16 17 13 17 15 0.8 1 1 1 1 1 14.85 73 43
19 18 11 22 27 23 4 0.8 0.89 1 0.33 0.5 0.5 14.75 151 57
16 17 15 23 22 17 9 0 0.33 0.17 0 0 0 14.1 89 43
19 16 12 27 12 25 4 0.3 0.67 0.67 0.33 0 1 14.9 78 23
23 22 21 27 18 19 4 0.6 0.67 0.83 0.33 0.5 1 16.25 110 44
8 17 22 5 6 8 28 0.5 1 0.83 0.67 0 1 19.25 220 54
22 21 20 19 17 14 4 0.7 0.78 1 0.33 0 0.5 13.6 65 28
23 20 15 24 22 22 4 0.3 0.67 0.83 0 0.5 1 13.6 141 36
15 20 9 23 22 25 4 0.3 1 1 0.67 0 0 15.65 117 39
17 19 15 28 23 28 5 0.4 0.78 1 0.67 0 0.5 12.75 122 16
21 8 14 25 19 25 4 0.4 0.89 0.83 1 0 1 14.6 63 23
25 19 11 27 20 24 4 0.1 0.89 0.83 0 0 1 9.85 44 40
18 11 9 16 17 15 12 0.5 0.89 1 0.67 0 1 12.65 52 24
20 13 12 25 24 24 4 0 0 0 0 0 0 19.2 131 78
21 18 11 26 20 28 6 0.4 0.67 1 0.33 0.5 0 16.6 101 57
21 19 14 24 18 24 6 0.6 1 0.83 0.67 1 0.5 11.2 42 37
24 23 10 23 23 25 5 0.4 1 1 0.33 0.5 1 15.25 152 27
22 20 18 24 27 23 4 0.1 0.67 0.33 0 0.5 1 11.9 107 61
22 22 11 27 25 26 4 0.3 0.89 0.83 0 0 1 13.2 77 27
23 19 14 25 24 26 4 0.7 0.89 0.83 0.67 0 1 16.35 154 69
17 16 16 19 12 22 10 0.3 0.56 0.17 0 0 1 12.4 103 34
15 11 11 19 16 25 7 0.5 0.67 0.83 0.33 0.5 0 15.85 96 44
22 21 16 24 24 22 4 0.3 1 0.83 0.67 1 1 18.15 175 34
19 14 13 20 23 26 7 0.6 1 0.67 0.67 0.5 1 11.15 57 39
18 21 12 21 24 20 4 0.9 1 1 1 0 1 15.65 112 51
21 20 17 28 24 26 4 0.4 0.67 0.83 0 0.5 1 17.75 143 34
20 21 23 26 26 26 12 0.3 0.44 1 0 0.5 0.5 7.65 49 31
19 20 14 19 19 21 5 0.9 0.89 1 0.67 1 1 12.35 110 13
19 19 10 23 28 21 8 0.5 0.44 1 0 0.5 0 15.6 131 12
16 19 16 23 23 24 6 0.3 0.56 1 1 0.5 0.5 19.3 167 51
18 18 11 21 21 21 17 0.6 0.89 0.83 0.67 0 0.5 15.2 56 24
23 20 16 26 19 18 4 0.2 0.67 1 0.33 0 0.5 17.1 137 19
22 21 19 25 23 23 5 0.4 0.89 0.83 1 0.5 1 15.6 86 30
23 22 17 25 23 26 4 0.5 1 0.83 0.67 0.5 0.5 18.4 121 81
20 19 12 24 20 23 5 0.4 0.78 0.83 0.67 0 0.5 19.05 149 42
24 23 17 23 18 25 5 0 0.44 0 0 0 0 18.55 168 22
25 16 11 22 20 20 6 0.2 0.89 1 0.33 0.5 1 19.1 140 85
25 23 19 27 28 25 4 0.5 0.89 1 0.67 0.5 1 13.1 88 27
20 18 12 26 21 26 4 0.3 0.89 1 0.67 0 0.5 12.85 168 25
23 23 8 23 25 19 4 0 0.44 0 0 0 0 9.5 94 22
21 20 17 22 18 21 6 0.5 1 0.83 1 0 1 4.5 51 19
23 20 13 26 24 23 8 0.6 0.89 0.83 0.33 0 1 11.85 48 14
23 23 17 22 28 24 10 0.3 0.67 0.83 0 0.5 0.5 13.6 145 45
11 13 7 17 9 6 4 0 0.33 0 0 0 0 11.7 66 45
21 21 23 25 22 22 5 0.3 0.78 0.67 0 0.5 0 12.4 85 28
27 26 18 22 26 21 4 0.5 0.89 1 0.67 0.5 1 13.35 109 51
19 18 13 28 28 28 4 0.4 0.78 0.67 0 0 1 11.4 63 41
21 19 17 22 18 24 4 0.5 0.78 0.83 0.67 0 0.5 14.9 102 31
16 18 13 21 23 14 16 0.7 0.89 1 1 1 0.5 19.9 162 74
21 18 8 24 15 20 7 0.8 0.78 1 0.67 0.5 1 11.2 86 19
22 19 16 26 24 28 4 0.6 0.78 1 0.33 0.5 1 14.6 114 51
16 13 14 26 12 19 4 0.4 0.67 0.83 0.33 0 0.5 17.6 164 73
18 10 13 24 12 24 14 0.5 0.89 0.83 0.33 0.5 0 14.05 119 24
23 21 19 27 20 21 5 0.5 0.89 1 0 0.5 1 16.1 126 61
24 24 15 22 25 21 5 0.3 0.78 1 0.33 0 1 13.35 132 23
20 21 15 23 24 26 5 0.6 1 1 0 0.5 1 11.85 142 14
20 23 8 22 23 24 5 0.3 1 0.67 0.67 0 0.5 11.95 83 54
18 18 14 23 18 26 7 0.6 0.78 0.83 1 0.5 0.5 14.75 94 51
4 11 7 15 20 25 19 0.3 0.78 0.33 0.33 0 1 15.15 81 62
14 16 11 20 22 23 16 0.7 0.89 1 0.67 1 1 13.2 166 36
22 20 17 22 20 24 4 0.7 0.89 1 1 0 1 16.85 110 59
17 20 19 25 25 24 4 0.6 0.67 0.67 1 0.5 1 7.85 64 24
23 26 17 27 28 26 7 0.5 1 1 0.33 0.5 0 7.7 93 26
20 21 12 24 25 23 9 0.5 0.67 0.83 0.33 0 0.5 12.6 104 54
18 12 12 21 14 20 5 0.4 0.56 0.67 0 0 1 7.85 105 39
19 15 18 17 16 16 14 0.4 0.78 1 0.33 1 1 10.95 49 16
20 18 16 26 24 24 4 0.7 1 1 1 0 1 12.35 88 36
15 14 15 20 13 20 16 0.2 0.67 0.17 0 0.5 0 9.95 95 31
24 18 20 22 19 23 10 0.5 0.78 0.83 0.67 0 0.5 14.9 102 31
21 16 16 24 18 23 5 0.4 0.56 0.83 0.67 0.5 0 16.65 99 42
19 19 12 23 16 18 6 0.2 1 1 0.67 1 1 13.4 63 39
19 7 10 22 8 21 4 0.5 0.89 0.67 0.67 0 0 13.95 76 25
27 21 28 28 27 25 4 0.4 0.44 0.5 0 0 1 15.7 109 31
23 24 19 21 23 23 4 0.7 1 0.67 1 1 1 16.85 117 38
23 21 18 24 20 26 5 0.6 0.89 0.83 0.67 1 0 10.95 57 31
20 20 19 28 20 26 4 0.4 0.78 0.83 0 0 0 15.35 120 17
17 22 8 25 26 24 4 0.5 0.89 1 0.67 1 1 12.2 73 22
21 17 17 24 23 23 5 0 0.11 0.17 0 0 0 15.1 91 55
23 19 16 24 24 21 4 0.7 0.89 1 0.67 0.5 1 17.75 108 62
22 20 18 21 21 23 4 0.4 0.89 0.67 0.67 0 1 15.2 105 51
16 16 12 20 15 20 5 0.5 1 0.67 1 0 1 14.6 117 30
20 20 17 26 22 23 8 0.6 0.89 0.83 0.67 0 0.5 16.65 119 49
16 16 13 16 25 24 15 0.8 1 0.5 0.67 0.5 0.5 8.1 31 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 21 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&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]21 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time21 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.93495 + 0.0758333AMS.I1[t] + 0.0342369AMS.I2[t] -0.0538298AMS.I3[t] -0.0732841AMS.E1[t] -0.0630887AMS.E2[t] -0.00278411AMS.E3[t] + 0.0326871AMS.A[t] -1.21463Algebraic_Reasoning[t] -1.33062Calculation[t] + 1.73841Graphical_Interpretation[t] + 1.48567Proportionality_and_Ratio[t] + 0.39162Probability_and_Sampling[t] -0.124836Estimation[t] + 0.0162099LFM[t] + 0.0503149CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  9.93495 +  0.0758333AMS.I1[t] +  0.0342369AMS.I2[t] -0.0538298AMS.I3[t] -0.0732841AMS.E1[t] -0.0630887AMS.E2[t] -0.00278411AMS.E3[t] +  0.0326871AMS.A[t] -1.21463Algebraic_Reasoning[t] -1.33062Calculation[t] +  1.73841Graphical_Interpretation[t] +  1.48567Proportionality_and_Ratio[t] +  0.39162Probability_and_Sampling[t] -0.124836Estimation[t] +  0.0162099LFM[t] +  0.0503149CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  9.93495 +  0.0758333AMS.I1[t] +  0.0342369AMS.I2[t] -0.0538298AMS.I3[t] -0.0732841AMS.E1[t] -0.0630887AMS.E2[t] -0.00278411AMS.E3[t] +  0.0326871AMS.A[t] -1.21463Algebraic_Reasoning[t] -1.33062Calculation[t] +  1.73841Graphical_Interpretation[t] +  1.48567Proportionality_and_Ratio[t] +  0.39162Probability_and_Sampling[t] -0.124836Estimation[t] +  0.0162099LFM[t] +  0.0503149CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.93495 + 0.0758333AMS.I1[t] + 0.0342369AMS.I2[t] -0.0538298AMS.I3[t] -0.0732841AMS.E1[t] -0.0630887AMS.E2[t] -0.00278411AMS.E3[t] + 0.0326871AMS.A[t] -1.21463Algebraic_Reasoning[t] -1.33062Calculation[t] + 1.73841Graphical_Interpretation[t] + 1.48567Proportionality_and_Ratio[t] + 0.39162Probability_and_Sampling[t] -0.124836Estimation[t] + 0.0162099LFM[t] + 0.0503149CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.934952.37744.1793.99468e-051.99734e-05
AMS.I10.07583330.07752580.97820.3288940.164447
AMS.I20.03423690.06721850.50930.6109450.305472
AMS.I3-0.05382980.0580098-0.92790.3542910.177146
AMS.E1-0.07328410.080136-0.91450.3612970.180648
AMS.E2-0.06308870.0547584-1.1520.2503180.125159
AMS.E3-0.002784110.0665152-0.041860.9666450.483322
AMS.A0.03268710.06546450.49930.617980.30899
Algebraic_Reasoning-1.214631.16444-1.0430.2978620.148931
Calculation-1.330621.2902-1.0310.3033370.151668
Graphical_Interpretation1.738410.9488971.8320.06808250.0340412
Proportionality_and_Ratio1.485670.5900392.5180.01240180.00620089
Probability_and_Sampling0.391620.5446040.71910.4727260.236363
Estimation-0.1248360.526119-0.23730.8126270.406314
LFM0.01620990.005288873.0650.002404850.00120243
CH0.05031490.01114464.5159.58867e-064.79434e-06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 9.93495 & 2.3774 & 4.179 & 3.99468e-05 & 1.99734e-05 \tabularnewline
AMS.I1 & 0.0758333 & 0.0775258 & 0.9782 & 0.328894 & 0.164447 \tabularnewline
AMS.I2 & 0.0342369 & 0.0672185 & 0.5093 & 0.610945 & 0.305472 \tabularnewline
AMS.I3 & -0.0538298 & 0.0580098 & -0.9279 & 0.354291 & 0.177146 \tabularnewline
AMS.E1 & -0.0732841 & 0.080136 & -0.9145 & 0.361297 & 0.180648 \tabularnewline
AMS.E2 & -0.0630887 & 0.0547584 & -1.152 & 0.250318 & 0.125159 \tabularnewline
AMS.E3 & -0.00278411 & 0.0665152 & -0.04186 & 0.966645 & 0.483322 \tabularnewline
AMS.A & 0.0326871 & 0.0654645 & 0.4993 & 0.61798 & 0.30899 \tabularnewline
Algebraic_Reasoning & -1.21463 & 1.16444 & -1.043 & 0.297862 & 0.148931 \tabularnewline
Calculation & -1.33062 & 1.2902 & -1.031 & 0.303337 & 0.151668 \tabularnewline
Graphical_Interpretation & 1.73841 & 0.948897 & 1.832 & 0.0680825 & 0.0340412 \tabularnewline
Proportionality_and_Ratio & 1.48567 & 0.590039 & 2.518 & 0.0124018 & 0.00620089 \tabularnewline
Probability_and_Sampling & 0.39162 & 0.544604 & 0.7191 & 0.472726 & 0.236363 \tabularnewline
Estimation & -0.124836 & 0.526119 & -0.2373 & 0.812627 & 0.406314 \tabularnewline
LFM & 0.0162099 & 0.00528887 & 3.065 & 0.00240485 & 0.00120243 \tabularnewline
CH & 0.0503149 & 0.0111446 & 4.515 & 9.58867e-06 & 4.79434e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]9.93495[/C][C]2.3774[/C][C]4.179[/C][C]3.99468e-05[/C][C]1.99734e-05[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0758333[/C][C]0.0775258[/C][C]0.9782[/C][C]0.328894[/C][C]0.164447[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0342369[/C][C]0.0672185[/C][C]0.5093[/C][C]0.610945[/C][C]0.305472[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0538298[/C][C]0.0580098[/C][C]-0.9279[/C][C]0.354291[/C][C]0.177146[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0732841[/C][C]0.080136[/C][C]-0.9145[/C][C]0.361297[/C][C]0.180648[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0630887[/C][C]0.0547584[/C][C]-1.152[/C][C]0.250318[/C][C]0.125159[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.00278411[/C][C]0.0665152[/C][C]-0.04186[/C][C]0.966645[/C][C]0.483322[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.0326871[/C][C]0.0654645[/C][C]0.4993[/C][C]0.61798[/C][C]0.30899[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.21463[/C][C]1.16444[/C][C]-1.043[/C][C]0.297862[/C][C]0.148931[/C][/ROW]
[ROW][C]Calculation[/C][C]-1.33062[/C][C]1.2902[/C][C]-1.031[/C][C]0.303337[/C][C]0.151668[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]1.73841[/C][C]0.948897[/C][C]1.832[/C][C]0.0680825[/C][C]0.0340412[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.48567[/C][C]0.590039[/C][C]2.518[/C][C]0.0124018[/C][C]0.00620089[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.39162[/C][C]0.544604[/C][C]0.7191[/C][C]0.472726[/C][C]0.236363[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.124836[/C][C]0.526119[/C][C]-0.2373[/C][C]0.812627[/C][C]0.406314[/C][/ROW]
[ROW][C]LFM[/C][C]0.0162099[/C][C]0.00528887[/C][C]3.065[/C][C]0.00240485[/C][C]0.00120243[/C][/ROW]
[ROW][C]CH[/C][C]0.0503149[/C][C]0.0111446[/C][C]4.515[/C][C]9.58867e-06[/C][C]4.79434e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)9.934952.37744.1793.99468e-051.99734e-05
AMS.I10.07583330.07752580.97820.3288940.164447
AMS.I20.03423690.06721850.50930.6109450.305472
AMS.I3-0.05382980.0580098-0.92790.3542910.177146
AMS.E1-0.07328410.080136-0.91450.3612970.180648
AMS.E2-0.06308870.0547584-1.1520.2503180.125159
AMS.E3-0.002784110.0665152-0.041860.9666450.483322
AMS.A0.03268710.06546450.49930.617980.30899
Algebraic_Reasoning-1.214631.16444-1.0430.2978620.148931
Calculation-1.330621.2902-1.0310.3033370.151668
Graphical_Interpretation1.738410.9488971.8320.06808250.0340412
Proportionality_and_Ratio1.485670.5900392.5180.01240180.00620089
Probability_and_Sampling0.391620.5446040.71910.4727260.236363
Estimation-0.1248360.526119-0.23730.8126270.406314
LFM0.01620990.005288873.0650.002404850.00120243
CH0.05031490.01114464.5159.58867e-064.79434e-06






Multiple Linear Regression - Regression Statistics
Multiple R0.459981
R-squared0.211583
Adjusted R-squared0.166444
F-TEST (value)4.68742
F-TEST (DF numerator)15
F-TEST (DF denominator)262
p-value5.55944e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.09903
Sum Squared Residuals2516.24

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.459981 \tabularnewline
R-squared & 0.211583 \tabularnewline
Adjusted R-squared & 0.166444 \tabularnewline
F-TEST (value) & 4.68742 \tabularnewline
F-TEST (DF numerator) & 15 \tabularnewline
F-TEST (DF denominator) & 262 \tabularnewline
p-value & 5.55944e-08 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.09903 \tabularnewline
Sum Squared Residuals & 2516.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.459981[/C][/ROW]
[ROW][C]R-squared[/C][C]0.211583[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.166444[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.68742[/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]5.55944e-08[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.09903[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2516.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.459981
R-squared0.211583
Adjusted R-squared0.166444
F-TEST (value)4.68742
F-TEST (DF numerator)15
F-TEST (DF denominator)262
p-value5.55944e-08
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.09903
Sum Squared Residuals2516.24






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.6616-1.76155
212.212.474-0.274001
312.813.6405-0.840489
47.413.7603-6.36032
56.711.8429-5.1429
612.613.1365-0.536469
714.814.48720.312798
813.315.4783-2.17828
911.113.7495-2.64953
108.214.1247-5.92472
1111.413.2849-1.88491
126.414.1712-7.77117
1310.611.2479-0.647903
141215.3566-3.35656
156.39.97345-3.67345
1611.310.94590.354056
1711.914.6043-2.70431
189.311.9687-2.66871
199.612.6845-3.08448
201012.2158-2.21583
216.412.9222-6.52219
2213.812.52461.27543
2310.814.1839-3.38393
2413.815.0748-1.27475
2511.714.6913-2.99125
2610.916.49-5.59
2716.114.4441.65599
2813.413.1590.240976
299.915.2587-5.35867
3011.513.9292-2.42921
318.311.895-3.59499
3211.713.2095-1.50953
33912.6209-3.62092
349.714.1117-4.41171
3510.813.3002-2.50021
3610.313.7873-3.48733
3710.413.5167-3.11666
3812.711.72570.974278
399.314.6325-5.33247
4011.813.9743-2.1743
415.913.215-7.31497
4211.414.3497-2.94971
431314.2753-1.27525
4410.813.9389-3.13886
4512.311.85240.447576
4611.314.2994-2.99938
4711.812.8345-1.03454
487.911.8717-3.97171
4912.710.6932.00696
5012.311.80690.493111
5111.612.9183-1.3183
526.710.7974-4.09739
5310.913.7898-2.8898
5412.111.8310.268979
5513.313.599-0.298959
5610.113.3418-3.24184
575.712.8192-7.11923
5814.312.04172.25834
5989.81384-1.81384
6013.312.81710.482946
619.316.0062-6.70617
6212.511.35121.14879
637.613.8101-6.21015
6415.915.84770.0523253
659.213.1114-3.91138
669.112.5718-3.47178
6711.115.1272-4.02716
681317.8097-4.80973
6914.514.5046-0.00458808
7012.212.2457-0.0456888
7112.314.0618-1.76178
7211.412.0688-0.668842
738.812.2973-3.49731
7414.613.8330.766965
7512.612.5440.0560349
76NANA0.0400395
771312.89450.10551
7812.614.1343-1.53425
7913.214.2491-1.04912
809.914.3649-4.46487
817.78.68196-0.981964
8210.58.303182.19682
8313.415.6909-2.29092
8410.917.8884-6.98844
854.38.11821-3.81821
8610.312.0903-1.79028
8711.812.2989-0.498873
8811.211.3808-0.180836
8911.414.9441-3.54414
908.67.363181.23682
9113.212.82710.372943
9212.619.5574-6.95741
935.68.73598-3.13598
949.913.0393-3.13934
958.812.0994-3.29943
967.78.84511-1.14511
97913.5454-4.54538
987.37.89656-0.596557
9911.49.064962.33504
10013.618.5855-4.98553
1017.98.66379-0.763789
10210.713.0666-2.36661
10310.312.0032-1.70324
1048.311.2344-2.9344
1059.67.53362.0664
10614.217.0933-2.89329
1078.57.046791.45321
10813.521.4064-7.90639
1094.98.99631-4.09631
1106.49.5411-3.1411
1119.610.0406-0.440614
11211.612.1741-0.574087
11311.117.2554-6.15545
1144.354.68435-0.334348
11512.78.496314.20369
11618.114.3623.73799
11717.8518.8217-0.971722
11816.615.06471.53532
11912.612.11610.483904
12017.114.21512.88486
12119.121.5383-2.43832
12216.113.09933.00071
12313.3510.41872.93134
12418.414.27544.12457
12514.717.2031-2.50314
12610.69.205721.39428
12712.68.569144.03086
12816.215.96710.232861
12913.68.711444.88856
13018.916.92531.97469
13114.112.61721.48283
13214.513.04221.45776
13316.1514.8931.25702
13414.7513.56321.18676
13514.815.0601-0.260148
13612.4512.26420.185755
13712.658.62394.0261
13817.3520.1264-2.77638
1398.65.01973.5803
14018.418.30510.0949421
14116.117.303-1.20302
14211.66.806914.79309
14317.7515.8181.93196
14415.2511.29513.95492
14517.6515.19962.45042
14616.3513.76912.58088
14717.6517.8648-0.214768
14813.612.43851.16149
14914.3512.36041.9896
15014.7511.5883.16202
15118.2521.3665-3.11654
1529.98.923310.97669
1531611.89394.10615
15418.2514.36263.8874
15516.8514.56282.28716
15614.613.94270.65732
15713.8511.78932.06071
15818.9516.74942.20059
15915.615.9799-0.379892
16014.8515.8341-0.984053
16111.758.507623.24238
16218.4515.77882.6712
16315.914.85581.0442
16417.112.27414.82587
16516.113.51252.58754
16619.919.87170.0283223
16710.956.809844.14016
16818.4515.91242.53758
16915.113.72741.37255
1701517.41-2.40998
17111.358.667762.68224
17215.9511.18124.76878
17318.117.48540.614586
17414.613.4981.10202
17515.414.09511.30492
17615.411.07714.32287
17717.618.324-0.724015
17813.356.335547.01446
17919.117.131.97004
18015.3518.2635-2.91348
1817.69.0056-1.4056
18213.412.20071.19926
18313.910.99062.90935
18419.116.14812.95189
18515.2514.97930.2707
18612.910.55522.3448
18716.110.8265.27401
18817.3516.92280.427189
18913.1512.23950.910514
19012.159.991722.15828
19112.613.8499-1.24988
19210.358.679221.67078
19315.418.2008-2.80081
1949.63.360536.23947
19518.216.92461.27537
19613.612.60730.992741
19714.8513.77271.07726
19814.7512.20892.54113
19914.110.49893.6011
20014.911.29633.60374
20116.2513.74612.50392
20219.2517.26311.98688
20313.612.8340.765992
20413.611.1082.49199
20515.6514.47991.17005
20612.759.540163.20984
20714.616.2008-1.60079
2089.859.365390.484611
20912.657.466495.18351
21019.216.65492.54514
21116.617.3098-0.709767
21211.29.216941.98306
21315.2515.7089-0.458917
21411.99.34292.5571
21513.211.38511.81487
21616.3515.41830.931733
21712.49.564452.83555
21815.8511.5154.33499
21918.1518.453-0.302963
22011.158.951962.19804
22115.659.854565.79544
22217.7521.0827-3.33265
2237.657.281140.368861
22412.358.45773.8923
22515.611.75133.84872
22619.315.63563.66439
22715.210.78774.41231
22817.113.84873.25134
22915.612.16313.43693
23018.413.26565.13441
23119.0512.64476.4053
23218.5515.92152.62852
23319.117.70961.39036
23413.113.6039-0.50391
23512.8514.2462-1.3962
2369.516.3354-6.83535
2374.52.469782.03022
23811.8511.61770.232259
23913.613.9327-0.33272
24011.79.935391.76461
24112.413.1195-0.719545
24213.3512.07691.27309
24311.49.022752.37725
24414.911.42693.47314
24519.921.0263-1.12628
24611.29.572761.62724
24714.612.07992.52009
24817.615.84141.75863
24914.0511.31932.73069
25016.115.43320.666799
25113.3512.51070.839281
25211.8513.2069-1.35688
25311.9511.0830.867045
25414.7511.99792.75214
25515.1515.9759-0.825875
25613.210.72922.47077
25716.8519.8868-3.03677
2587.8511.5177-3.66769
2597.78.29348-0.593477
26012.616.9736-4.37359
2617.858.54927-0.69927
26210.9510.60720.342798
26312.3513.7824-1.43239
2649.957.740352.20965
26514.911.793.10996
26616.6516.49190.158075
26713.411.34092.05915
26813.958.749675.20033
26915.711.94963.75041
27016.8517.8002-0.950201
27110.956.17794.7721
27215.3514.78750.562521
27312.29.575492.62451
27415.111.25823.84185
27517.7515.70532.04474
27615.213.33951.86051
27714.610.93263.6674
27816.6518.2232-1.57322
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.6616 & -1.76155 \tabularnewline
2 & 12.2 & 12.474 & -0.274001 \tabularnewline
3 & 12.8 & 13.6405 & -0.840489 \tabularnewline
4 & 7.4 & 13.7603 & -6.36032 \tabularnewline
5 & 6.7 & 11.8429 & -5.1429 \tabularnewline
6 & 12.6 & 13.1365 & -0.536469 \tabularnewline
7 & 14.8 & 14.4872 & 0.312798 \tabularnewline
8 & 13.3 & 15.4783 & -2.17828 \tabularnewline
9 & 11.1 & 13.7495 & -2.64953 \tabularnewline
10 & 8.2 & 14.1247 & -5.92472 \tabularnewline
11 & 11.4 & 13.2849 & -1.88491 \tabularnewline
12 & 6.4 & 14.1712 & -7.77117 \tabularnewline
13 & 10.6 & 11.2479 & -0.647903 \tabularnewline
14 & 12 & 15.3566 & -3.35656 \tabularnewline
15 & 6.3 & 9.97345 & -3.67345 \tabularnewline
16 & 11.3 & 10.9459 & 0.354056 \tabularnewline
17 & 11.9 & 14.6043 & -2.70431 \tabularnewline
18 & 9.3 & 11.9687 & -2.66871 \tabularnewline
19 & 9.6 & 12.6845 & -3.08448 \tabularnewline
20 & 10 & 12.2158 & -2.21583 \tabularnewline
21 & 6.4 & 12.9222 & -6.52219 \tabularnewline
22 & 13.8 & 12.5246 & 1.27543 \tabularnewline
23 & 10.8 & 14.1839 & -3.38393 \tabularnewline
24 & 13.8 & 15.0748 & -1.27475 \tabularnewline
25 & 11.7 & 14.6913 & -2.99125 \tabularnewline
26 & 10.9 & 16.49 & -5.59 \tabularnewline
27 & 16.1 & 14.444 & 1.65599 \tabularnewline
28 & 13.4 & 13.159 & 0.240976 \tabularnewline
29 & 9.9 & 15.2587 & -5.35867 \tabularnewline
30 & 11.5 & 13.9292 & -2.42921 \tabularnewline
31 & 8.3 & 11.895 & -3.59499 \tabularnewline
32 & 11.7 & 13.2095 & -1.50953 \tabularnewline
33 & 9 & 12.6209 & -3.62092 \tabularnewline
34 & 9.7 & 14.1117 & -4.41171 \tabularnewline
35 & 10.8 & 13.3002 & -2.50021 \tabularnewline
36 & 10.3 & 13.7873 & -3.48733 \tabularnewline
37 & 10.4 & 13.5167 & -3.11666 \tabularnewline
38 & 12.7 & 11.7257 & 0.974278 \tabularnewline
39 & 9.3 & 14.6325 & -5.33247 \tabularnewline
40 & 11.8 & 13.9743 & -2.1743 \tabularnewline
41 & 5.9 & 13.215 & -7.31497 \tabularnewline
42 & 11.4 & 14.3497 & -2.94971 \tabularnewline
43 & 13 & 14.2753 & -1.27525 \tabularnewline
44 & 10.8 & 13.9389 & -3.13886 \tabularnewline
45 & 12.3 & 11.8524 & 0.447576 \tabularnewline
46 & 11.3 & 14.2994 & -2.99938 \tabularnewline
47 & 11.8 & 12.8345 & -1.03454 \tabularnewline
48 & 7.9 & 11.8717 & -3.97171 \tabularnewline
49 & 12.7 & 10.693 & 2.00696 \tabularnewline
50 & 12.3 & 11.8069 & 0.493111 \tabularnewline
51 & 11.6 & 12.9183 & -1.3183 \tabularnewline
52 & 6.7 & 10.7974 & -4.09739 \tabularnewline
53 & 10.9 & 13.7898 & -2.8898 \tabularnewline
54 & 12.1 & 11.831 & 0.268979 \tabularnewline
55 & 13.3 & 13.599 & -0.298959 \tabularnewline
56 & 10.1 & 13.3418 & -3.24184 \tabularnewline
57 & 5.7 & 12.8192 & -7.11923 \tabularnewline
58 & 14.3 & 12.0417 & 2.25834 \tabularnewline
59 & 8 & 9.81384 & -1.81384 \tabularnewline
60 & 13.3 & 12.8171 & 0.482946 \tabularnewline
61 & 9.3 & 16.0062 & -6.70617 \tabularnewline
62 & 12.5 & 11.3512 & 1.14879 \tabularnewline
63 & 7.6 & 13.8101 & -6.21015 \tabularnewline
64 & 15.9 & 15.8477 & 0.0523253 \tabularnewline
65 & 9.2 & 13.1114 & -3.91138 \tabularnewline
66 & 9.1 & 12.5718 & -3.47178 \tabularnewline
67 & 11.1 & 15.1272 & -4.02716 \tabularnewline
68 & 13 & 17.8097 & -4.80973 \tabularnewline
69 & 14.5 & 14.5046 & -0.00458808 \tabularnewline
70 & 12.2 & 12.2457 & -0.0456888 \tabularnewline
71 & 12.3 & 14.0618 & -1.76178 \tabularnewline
72 & 11.4 & 12.0688 & -0.668842 \tabularnewline
73 & 8.8 & 12.2973 & -3.49731 \tabularnewline
74 & 14.6 & 13.833 & 0.766965 \tabularnewline
75 & 12.6 & 12.544 & 0.0560349 \tabularnewline
76 & NA & NA & 0.0400395 \tabularnewline
77 & 13 & 12.8945 & 0.10551 \tabularnewline
78 & 12.6 & 14.1343 & -1.53425 \tabularnewline
79 & 13.2 & 14.2491 & -1.04912 \tabularnewline
80 & 9.9 & 14.3649 & -4.46487 \tabularnewline
81 & 7.7 & 8.68196 & -0.981964 \tabularnewline
82 & 10.5 & 8.30318 & 2.19682 \tabularnewline
83 & 13.4 & 15.6909 & -2.29092 \tabularnewline
84 & 10.9 & 17.8884 & -6.98844 \tabularnewline
85 & 4.3 & 8.11821 & -3.81821 \tabularnewline
86 & 10.3 & 12.0903 & -1.79028 \tabularnewline
87 & 11.8 & 12.2989 & -0.498873 \tabularnewline
88 & 11.2 & 11.3808 & -0.180836 \tabularnewline
89 & 11.4 & 14.9441 & -3.54414 \tabularnewline
90 & 8.6 & 7.36318 & 1.23682 \tabularnewline
91 & 13.2 & 12.8271 & 0.372943 \tabularnewline
92 & 12.6 & 19.5574 & -6.95741 \tabularnewline
93 & 5.6 & 8.73598 & -3.13598 \tabularnewline
94 & 9.9 & 13.0393 & -3.13934 \tabularnewline
95 & 8.8 & 12.0994 & -3.29943 \tabularnewline
96 & 7.7 & 8.84511 & -1.14511 \tabularnewline
97 & 9 & 13.5454 & -4.54538 \tabularnewline
98 & 7.3 & 7.89656 & -0.596557 \tabularnewline
99 & 11.4 & 9.06496 & 2.33504 \tabularnewline
100 & 13.6 & 18.5855 & -4.98553 \tabularnewline
101 & 7.9 & 8.66379 & -0.763789 \tabularnewline
102 & 10.7 & 13.0666 & -2.36661 \tabularnewline
103 & 10.3 & 12.0032 & -1.70324 \tabularnewline
104 & 8.3 & 11.2344 & -2.9344 \tabularnewline
105 & 9.6 & 7.5336 & 2.0664 \tabularnewline
106 & 14.2 & 17.0933 & -2.89329 \tabularnewline
107 & 8.5 & 7.04679 & 1.45321 \tabularnewline
108 & 13.5 & 21.4064 & -7.90639 \tabularnewline
109 & 4.9 & 8.99631 & -4.09631 \tabularnewline
110 & 6.4 & 9.5411 & -3.1411 \tabularnewline
111 & 9.6 & 10.0406 & -0.440614 \tabularnewline
112 & 11.6 & 12.1741 & -0.574087 \tabularnewline
113 & 11.1 & 17.2554 & -6.15545 \tabularnewline
114 & 4.35 & 4.68435 & -0.334348 \tabularnewline
115 & 12.7 & 8.49631 & 4.20369 \tabularnewline
116 & 18.1 & 14.362 & 3.73799 \tabularnewline
117 & 17.85 & 18.8217 & -0.971722 \tabularnewline
118 & 16.6 & 15.0647 & 1.53532 \tabularnewline
119 & 12.6 & 12.1161 & 0.483904 \tabularnewline
120 & 17.1 & 14.2151 & 2.88486 \tabularnewline
121 & 19.1 & 21.5383 & -2.43832 \tabularnewline
122 & 16.1 & 13.0993 & 3.00071 \tabularnewline
123 & 13.35 & 10.4187 & 2.93134 \tabularnewline
124 & 18.4 & 14.2754 & 4.12457 \tabularnewline
125 & 14.7 & 17.2031 & -2.50314 \tabularnewline
126 & 10.6 & 9.20572 & 1.39428 \tabularnewline
127 & 12.6 & 8.56914 & 4.03086 \tabularnewline
128 & 16.2 & 15.9671 & 0.232861 \tabularnewline
129 & 13.6 & 8.71144 & 4.88856 \tabularnewline
130 & 18.9 & 16.9253 & 1.97469 \tabularnewline
131 & 14.1 & 12.6172 & 1.48283 \tabularnewline
132 & 14.5 & 13.0422 & 1.45776 \tabularnewline
133 & 16.15 & 14.893 & 1.25702 \tabularnewline
134 & 14.75 & 13.5632 & 1.18676 \tabularnewline
135 & 14.8 & 15.0601 & -0.260148 \tabularnewline
136 & 12.45 & 12.2642 & 0.185755 \tabularnewline
137 & 12.65 & 8.6239 & 4.0261 \tabularnewline
138 & 17.35 & 20.1264 & -2.77638 \tabularnewline
139 & 8.6 & 5.0197 & 3.5803 \tabularnewline
140 & 18.4 & 18.3051 & 0.0949421 \tabularnewline
141 & 16.1 & 17.303 & -1.20302 \tabularnewline
142 & 11.6 & 6.80691 & 4.79309 \tabularnewline
143 & 17.75 & 15.818 & 1.93196 \tabularnewline
144 & 15.25 & 11.2951 & 3.95492 \tabularnewline
145 & 17.65 & 15.1996 & 2.45042 \tabularnewline
146 & 16.35 & 13.7691 & 2.58088 \tabularnewline
147 & 17.65 & 17.8648 & -0.214768 \tabularnewline
148 & 13.6 & 12.4385 & 1.16149 \tabularnewline
149 & 14.35 & 12.3604 & 1.9896 \tabularnewline
150 & 14.75 & 11.588 & 3.16202 \tabularnewline
151 & 18.25 & 21.3665 & -3.11654 \tabularnewline
152 & 9.9 & 8.92331 & 0.97669 \tabularnewline
153 & 16 & 11.8939 & 4.10615 \tabularnewline
154 & 18.25 & 14.3626 & 3.8874 \tabularnewline
155 & 16.85 & 14.5628 & 2.28716 \tabularnewline
156 & 14.6 & 13.9427 & 0.65732 \tabularnewline
157 & 13.85 & 11.7893 & 2.06071 \tabularnewline
158 & 18.95 & 16.7494 & 2.20059 \tabularnewline
159 & 15.6 & 15.9799 & -0.379892 \tabularnewline
160 & 14.85 & 15.8341 & -0.984053 \tabularnewline
161 & 11.75 & 8.50762 & 3.24238 \tabularnewline
162 & 18.45 & 15.7788 & 2.6712 \tabularnewline
163 & 15.9 & 14.8558 & 1.0442 \tabularnewline
164 & 17.1 & 12.2741 & 4.82587 \tabularnewline
165 & 16.1 & 13.5125 & 2.58754 \tabularnewline
166 & 19.9 & 19.8717 & 0.0283223 \tabularnewline
167 & 10.95 & 6.80984 & 4.14016 \tabularnewline
168 & 18.45 & 15.9124 & 2.53758 \tabularnewline
169 & 15.1 & 13.7274 & 1.37255 \tabularnewline
170 & 15 & 17.41 & -2.40998 \tabularnewline
171 & 11.35 & 8.66776 & 2.68224 \tabularnewline
172 & 15.95 & 11.1812 & 4.76878 \tabularnewline
173 & 18.1 & 17.4854 & 0.614586 \tabularnewline
174 & 14.6 & 13.498 & 1.10202 \tabularnewline
175 & 15.4 & 14.0951 & 1.30492 \tabularnewline
176 & 15.4 & 11.0771 & 4.32287 \tabularnewline
177 & 17.6 & 18.324 & -0.724015 \tabularnewline
178 & 13.35 & 6.33554 & 7.01446 \tabularnewline
179 & 19.1 & 17.13 & 1.97004 \tabularnewline
180 & 15.35 & 18.2635 & -2.91348 \tabularnewline
181 & 7.6 & 9.0056 & -1.4056 \tabularnewline
182 & 13.4 & 12.2007 & 1.19926 \tabularnewline
183 & 13.9 & 10.9906 & 2.90935 \tabularnewline
184 & 19.1 & 16.1481 & 2.95189 \tabularnewline
185 & 15.25 & 14.9793 & 0.2707 \tabularnewline
186 & 12.9 & 10.5552 & 2.3448 \tabularnewline
187 & 16.1 & 10.826 & 5.27401 \tabularnewline
188 & 17.35 & 16.9228 & 0.427189 \tabularnewline
189 & 13.15 & 12.2395 & 0.910514 \tabularnewline
190 & 12.15 & 9.99172 & 2.15828 \tabularnewline
191 & 12.6 & 13.8499 & -1.24988 \tabularnewline
192 & 10.35 & 8.67922 & 1.67078 \tabularnewline
193 & 15.4 & 18.2008 & -2.80081 \tabularnewline
194 & 9.6 & 3.36053 & 6.23947 \tabularnewline
195 & 18.2 & 16.9246 & 1.27537 \tabularnewline
196 & 13.6 & 12.6073 & 0.992741 \tabularnewline
197 & 14.85 & 13.7727 & 1.07726 \tabularnewline
198 & 14.75 & 12.2089 & 2.54113 \tabularnewline
199 & 14.1 & 10.4989 & 3.6011 \tabularnewline
200 & 14.9 & 11.2963 & 3.60374 \tabularnewline
201 & 16.25 & 13.7461 & 2.50392 \tabularnewline
202 & 19.25 & 17.2631 & 1.98688 \tabularnewline
203 & 13.6 & 12.834 & 0.765992 \tabularnewline
204 & 13.6 & 11.108 & 2.49199 \tabularnewline
205 & 15.65 & 14.4799 & 1.17005 \tabularnewline
206 & 12.75 & 9.54016 & 3.20984 \tabularnewline
207 & 14.6 & 16.2008 & -1.60079 \tabularnewline
208 & 9.85 & 9.36539 & 0.484611 \tabularnewline
209 & 12.65 & 7.46649 & 5.18351 \tabularnewline
210 & 19.2 & 16.6549 & 2.54514 \tabularnewline
211 & 16.6 & 17.3098 & -0.709767 \tabularnewline
212 & 11.2 & 9.21694 & 1.98306 \tabularnewline
213 & 15.25 & 15.7089 & -0.458917 \tabularnewline
214 & 11.9 & 9.3429 & 2.5571 \tabularnewline
215 & 13.2 & 11.3851 & 1.81487 \tabularnewline
216 & 16.35 & 15.4183 & 0.931733 \tabularnewline
217 & 12.4 & 9.56445 & 2.83555 \tabularnewline
218 & 15.85 & 11.515 & 4.33499 \tabularnewline
219 & 18.15 & 18.453 & -0.302963 \tabularnewline
220 & 11.15 & 8.95196 & 2.19804 \tabularnewline
221 & 15.65 & 9.85456 & 5.79544 \tabularnewline
222 & 17.75 & 21.0827 & -3.33265 \tabularnewline
223 & 7.65 & 7.28114 & 0.368861 \tabularnewline
224 & 12.35 & 8.4577 & 3.8923 \tabularnewline
225 & 15.6 & 11.7513 & 3.84872 \tabularnewline
226 & 19.3 & 15.6356 & 3.66439 \tabularnewline
227 & 15.2 & 10.7877 & 4.41231 \tabularnewline
228 & 17.1 & 13.8487 & 3.25134 \tabularnewline
229 & 15.6 & 12.1631 & 3.43693 \tabularnewline
230 & 18.4 & 13.2656 & 5.13441 \tabularnewline
231 & 19.05 & 12.6447 & 6.4053 \tabularnewline
232 & 18.55 & 15.9215 & 2.62852 \tabularnewline
233 & 19.1 & 17.7096 & 1.39036 \tabularnewline
234 & 13.1 & 13.6039 & -0.50391 \tabularnewline
235 & 12.85 & 14.2462 & -1.3962 \tabularnewline
236 & 9.5 & 16.3354 & -6.83535 \tabularnewline
237 & 4.5 & 2.46978 & 2.03022 \tabularnewline
238 & 11.85 & 11.6177 & 0.232259 \tabularnewline
239 & 13.6 & 13.9327 & -0.33272 \tabularnewline
240 & 11.7 & 9.93539 & 1.76461 \tabularnewline
241 & 12.4 & 13.1195 & -0.719545 \tabularnewline
242 & 13.35 & 12.0769 & 1.27309 \tabularnewline
243 & 11.4 & 9.02275 & 2.37725 \tabularnewline
244 & 14.9 & 11.4269 & 3.47314 \tabularnewline
245 & 19.9 & 21.0263 & -1.12628 \tabularnewline
246 & 11.2 & 9.57276 & 1.62724 \tabularnewline
247 & 14.6 & 12.0799 & 2.52009 \tabularnewline
248 & 17.6 & 15.8414 & 1.75863 \tabularnewline
249 & 14.05 & 11.3193 & 2.73069 \tabularnewline
250 & 16.1 & 15.4332 & 0.666799 \tabularnewline
251 & 13.35 & 12.5107 & 0.839281 \tabularnewline
252 & 11.85 & 13.2069 & -1.35688 \tabularnewline
253 & 11.95 & 11.083 & 0.867045 \tabularnewline
254 & 14.75 & 11.9979 & 2.75214 \tabularnewline
255 & 15.15 & 15.9759 & -0.825875 \tabularnewline
256 & 13.2 & 10.7292 & 2.47077 \tabularnewline
257 & 16.85 & 19.8868 & -3.03677 \tabularnewline
258 & 7.85 & 11.5177 & -3.66769 \tabularnewline
259 & 7.7 & 8.29348 & -0.593477 \tabularnewline
260 & 12.6 & 16.9736 & -4.37359 \tabularnewline
261 & 7.85 & 8.54927 & -0.69927 \tabularnewline
262 & 10.95 & 10.6072 & 0.342798 \tabularnewline
263 & 12.35 & 13.7824 & -1.43239 \tabularnewline
264 & 9.95 & 7.74035 & 2.20965 \tabularnewline
265 & 14.9 & 11.79 & 3.10996 \tabularnewline
266 & 16.65 & 16.4919 & 0.158075 \tabularnewline
267 & 13.4 & 11.3409 & 2.05915 \tabularnewline
268 & 13.95 & 8.74967 & 5.20033 \tabularnewline
269 & 15.7 & 11.9496 & 3.75041 \tabularnewline
270 & 16.85 & 17.8002 & -0.950201 \tabularnewline
271 & 10.95 & 6.1779 & 4.7721 \tabularnewline
272 & 15.35 & 14.7875 & 0.562521 \tabularnewline
273 & 12.2 & 9.57549 & 2.62451 \tabularnewline
274 & 15.1 & 11.2582 & 3.84185 \tabularnewline
275 & 17.75 & 15.7053 & 2.04474 \tabularnewline
276 & 15.2 & 13.3395 & 1.86051 \tabularnewline
277 & 14.6 & 10.9326 & 3.6674 \tabularnewline
278 & 16.65 & 18.2232 & -1.57322 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&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]14.6616[/C][C]-1.76155[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.474[/C][C]-0.274001[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.6405[/C][C]-0.840489[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.7603[/C][C]-6.36032[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.8429[/C][C]-5.1429[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.1365[/C][C]-0.536469[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.4872[/C][C]0.312798[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]15.4783[/C][C]-2.17828[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]13.7495[/C][C]-2.64953[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.1247[/C][C]-5.92472[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.2849[/C][C]-1.88491[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.1712[/C][C]-7.77117[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.2479[/C][C]-0.647903[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]15.3566[/C][C]-3.35656[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.97345[/C][C]-3.67345[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]10.9459[/C][C]0.354056[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.6043[/C][C]-2.70431[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]11.9687[/C][C]-2.66871[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.6845[/C][C]-3.08448[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.2158[/C][C]-2.21583[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9222[/C][C]-6.52219[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.5246[/C][C]1.27543[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.1839[/C][C]-3.38393[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]15.0748[/C][C]-1.27475[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.6913[/C][C]-2.99125[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]16.49[/C][C]-5.59[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]14.444[/C][C]1.65599[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.159[/C][C]0.240976[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]15.2587[/C][C]-5.35867[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.9292[/C][C]-2.42921[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.895[/C][C]-3.59499[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.2095[/C][C]-1.50953[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.6209[/C][C]-3.62092[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.1117[/C][C]-4.41171[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.3002[/C][C]-2.50021[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.7873[/C][C]-3.48733[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.5167[/C][C]-3.11666[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.7257[/C][C]0.974278[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.6325[/C][C]-5.33247[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]13.9743[/C][C]-2.1743[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.215[/C][C]-7.31497[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.3497[/C][C]-2.94971[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.2753[/C][C]-1.27525[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]13.9389[/C][C]-3.13886[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.8524[/C][C]0.447576[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.2994[/C][C]-2.99938[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.8345[/C][C]-1.03454[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.8717[/C][C]-3.97171[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.693[/C][C]2.00696[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.8069[/C][C]0.493111[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.9183[/C][C]-1.3183[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.7974[/C][C]-4.09739[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.7898[/C][C]-2.8898[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.831[/C][C]0.268979[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.599[/C][C]-0.298959[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3418[/C][C]-3.24184[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.8192[/C][C]-7.11923[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.0417[/C][C]2.25834[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.81384[/C][C]-1.81384[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.8171[/C][C]0.482946[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]16.0062[/C][C]-6.70617[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.3512[/C][C]1.14879[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]13.8101[/C][C]-6.21015[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.8477[/C][C]0.0523253[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.1114[/C][C]-3.91138[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.5718[/C][C]-3.47178[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]15.1272[/C][C]-4.02716[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]17.8097[/C][C]-4.80973[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]14.5046[/C][C]-0.00458808[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.2457[/C][C]-0.0456888[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.0618[/C][C]-1.76178[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.0688[/C][C]-0.668842[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.2973[/C][C]-3.49731[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.833[/C][C]0.766965[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.544[/C][C]0.0560349[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.0400395[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]12.8945[/C][C]0.10551[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.1343[/C][C]-1.53425[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.2491[/C][C]-1.04912[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.3649[/C][C]-4.46487[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.68196[/C][C]-0.981964[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]8.30318[/C][C]2.19682[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.6909[/C][C]-2.29092[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]17.8884[/C][C]-6.98844[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]8.11821[/C][C]-3.81821[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]12.0903[/C][C]-1.79028[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.2989[/C][C]-0.498873[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.3808[/C][C]-0.180836[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]14.9441[/C][C]-3.54414[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.36318[/C][C]1.23682[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]12.8271[/C][C]0.372943[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.5574[/C][C]-6.95741[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.73598[/C][C]-3.13598[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.0393[/C][C]-3.13934[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.0994[/C][C]-3.29943[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]8.84511[/C][C]-1.14511[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]13.5454[/C][C]-4.54538[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]7.89656[/C][C]-0.596557[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.06496[/C][C]2.33504[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.5855[/C][C]-4.98553[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.66379[/C][C]-0.763789[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.0666[/C][C]-2.36661[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.0032[/C][C]-1.70324[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.2344[/C][C]-2.9344[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.5336[/C][C]2.0664[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]17.0933[/C][C]-2.89329[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.04679[/C][C]1.45321[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.4064[/C][C]-7.90639[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]8.99631[/C][C]-4.09631[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.5411[/C][C]-3.1411[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.0406[/C][C]-0.440614[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]12.1741[/C][C]-0.574087[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.2554[/C][C]-6.15545[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.68435[/C][C]-0.334348[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]8.49631[/C][C]4.20369[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]14.362[/C][C]3.73799[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]18.8217[/C][C]-0.971722[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.0647[/C][C]1.53532[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]12.1161[/C][C]0.483904[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.2151[/C][C]2.88486[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.5383[/C][C]-2.43832[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.0993[/C][C]3.00071[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]10.4187[/C][C]2.93134[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.2754[/C][C]4.12457[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.2031[/C][C]-2.50314[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.20572[/C][C]1.39428[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]8.56914[/C][C]4.03086[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.9671[/C][C]0.232861[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]8.71144[/C][C]4.88856[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]16.9253[/C][C]1.97469[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.6172[/C][C]1.48283[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]13.0422[/C][C]1.45776[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.893[/C][C]1.25702[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.5632[/C][C]1.18676[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.0601[/C][C]-0.260148[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.2642[/C][C]0.185755[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.6239[/C][C]4.0261[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]20.1264[/C][C]-2.77638[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]5.0197[/C][C]3.5803[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]18.3051[/C][C]0.0949421[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.303[/C][C]-1.20302[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.80691[/C][C]4.79309[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.818[/C][C]1.93196[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.2951[/C][C]3.95492[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]15.1996[/C][C]2.45042[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.7691[/C][C]2.58088[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.8648[/C][C]-0.214768[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.4385[/C][C]1.16149[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.3604[/C][C]1.9896[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]11.588[/C][C]3.16202[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.3665[/C][C]-3.11654[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.92331[/C][C]0.97669[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8939[/C][C]4.10615[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.3626[/C][C]3.8874[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.5628[/C][C]2.28716[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.9427[/C][C]0.65732[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.7893[/C][C]2.06071[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.7494[/C][C]2.20059[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]15.9799[/C][C]-0.379892[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.8341[/C][C]-0.984053[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]8.50762[/C][C]3.24238[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.7788[/C][C]2.6712[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]14.8558[/C][C]1.0442[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]12.2741[/C][C]4.82587[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]13.5125[/C][C]2.58754[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.8717[/C][C]0.0283223[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]6.80984[/C][C]4.14016[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]15.9124[/C][C]2.53758[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.7274[/C][C]1.37255[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.41[/C][C]-2.40998[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.66776[/C][C]2.68224[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.1812[/C][C]4.76878[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]17.4854[/C][C]0.614586[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]13.498[/C][C]1.10202[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.0951[/C][C]1.30492[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.0771[/C][C]4.32287[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.324[/C][C]-0.724015[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.33554[/C][C]7.01446[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.13[/C][C]1.97004[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.2635[/C][C]-2.91348[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.0056[/C][C]-1.4056[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.2007[/C][C]1.19926[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]10.9906[/C][C]2.90935[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.1481[/C][C]2.95189[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]14.9793[/C][C]0.2707[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.5552[/C][C]2.3448[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.826[/C][C]5.27401[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.9228[/C][C]0.427189[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]12.2395[/C][C]0.910514[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]9.99172[/C][C]2.15828[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.8499[/C][C]-1.24988[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.67922[/C][C]1.67078[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.2008[/C][C]-2.80081[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.36053[/C][C]6.23947[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.9246[/C][C]1.27537[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.6073[/C][C]0.992741[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]13.7727[/C][C]1.07726[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]12.2089[/C][C]2.54113[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.4989[/C][C]3.6011[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.2963[/C][C]3.60374[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]13.7461[/C][C]2.50392[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.2631[/C][C]1.98688[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.834[/C][C]0.765992[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.108[/C][C]2.49199[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.4799[/C][C]1.17005[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.54016[/C][C]3.20984[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]16.2008[/C][C]-1.60079[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.36539[/C][C]0.484611[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]7.46649[/C][C]5.18351[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.6549[/C][C]2.54514[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.3098[/C][C]-0.709767[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.21694[/C][C]1.98306[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]15.7089[/C][C]-0.458917[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]9.3429[/C][C]2.5571[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]11.3851[/C][C]1.81487[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.4183[/C][C]0.931733[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.56445[/C][C]2.83555[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]11.515[/C][C]4.33499[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.453[/C][C]-0.302963[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.95196[/C][C]2.19804[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]9.85456[/C][C]5.79544[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.0827[/C][C]-3.33265[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]7.28114[/C][C]0.368861[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.4577[/C][C]3.8923[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]11.7513[/C][C]3.84872[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.6356[/C][C]3.66439[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]10.7877[/C][C]4.41231[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]13.8487[/C][C]3.25134[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.1631[/C][C]3.43693[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]13.2656[/C][C]5.13441[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]12.6447[/C][C]6.4053[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.9215[/C][C]2.62852[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]17.7096[/C][C]1.39036[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.6039[/C][C]-0.50391[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.2462[/C][C]-1.3962[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.3354[/C][C]-6.83535[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]2.46978[/C][C]2.03022[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.6177[/C][C]0.232259[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.9327[/C][C]-0.33272[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]9.93539[/C][C]1.76461[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.1195[/C][C]-0.719545[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]12.0769[/C][C]1.27309[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.02275[/C][C]2.37725[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]11.4269[/C][C]3.47314[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.0263[/C][C]-1.12628[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]9.57276[/C][C]1.62724[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.0799[/C][C]2.52009[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]15.8414[/C][C]1.75863[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]11.3193[/C][C]2.73069[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.4332[/C][C]0.666799[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]12.5107[/C][C]0.839281[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.2069[/C][C]-1.35688[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.083[/C][C]0.867045[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]11.9979[/C][C]2.75214[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.9759[/C][C]-0.825875[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]10.7292[/C][C]2.47077[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]19.8868[/C][C]-3.03677[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]11.5177[/C][C]-3.66769[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]8.29348[/C][C]-0.593477[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.9736[/C][C]-4.37359[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.54927[/C][C]-0.69927[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.6072[/C][C]0.342798[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]13.7824[/C][C]-1.43239[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.74035[/C][C]2.20965[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.79[/C][C]3.10996[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.4919[/C][C]0.158075[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]11.3409[/C][C]2.05915[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]8.74967[/C][C]5.20033[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.9496[/C][C]3.75041[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.8002[/C][C]-0.950201[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]6.1779[/C][C]4.7721[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.7875[/C][C]0.562521[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.57549[/C][C]2.62451[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]11.2582[/C][C]3.84185[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.7053[/C][C]2.04474[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.3395[/C][C]1.86051[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.9326[/C][C]3.6674[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]18.2232[/C][C]-1.57322[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.6616-1.76155
212.212.474-0.274001
312.813.6405-0.840489
47.413.7603-6.36032
56.711.8429-5.1429
612.613.1365-0.536469
714.814.48720.312798
813.315.4783-2.17828
911.113.7495-2.64953
108.214.1247-5.92472
1111.413.2849-1.88491
126.414.1712-7.77117
1310.611.2479-0.647903
141215.3566-3.35656
156.39.97345-3.67345
1611.310.94590.354056
1711.914.6043-2.70431
189.311.9687-2.66871
199.612.6845-3.08448
201012.2158-2.21583
216.412.9222-6.52219
2213.812.52461.27543
2310.814.1839-3.38393
2413.815.0748-1.27475
2511.714.6913-2.99125
2610.916.49-5.59
2716.114.4441.65599
2813.413.1590.240976
299.915.2587-5.35867
3011.513.9292-2.42921
318.311.895-3.59499
3211.713.2095-1.50953
33912.6209-3.62092
349.714.1117-4.41171
3510.813.3002-2.50021
3610.313.7873-3.48733
3710.413.5167-3.11666
3812.711.72570.974278
399.314.6325-5.33247
4011.813.9743-2.1743
415.913.215-7.31497
4211.414.3497-2.94971
431314.2753-1.27525
4410.813.9389-3.13886
4512.311.85240.447576
4611.314.2994-2.99938
4711.812.8345-1.03454
487.911.8717-3.97171
4912.710.6932.00696
5012.311.80690.493111
5111.612.9183-1.3183
526.710.7974-4.09739
5310.913.7898-2.8898
5412.111.8310.268979
5513.313.599-0.298959
5610.113.3418-3.24184
575.712.8192-7.11923
5814.312.04172.25834
5989.81384-1.81384
6013.312.81710.482946
619.316.0062-6.70617
6212.511.35121.14879
637.613.8101-6.21015
6415.915.84770.0523253
659.213.1114-3.91138
669.112.5718-3.47178
6711.115.1272-4.02716
681317.8097-4.80973
6914.514.5046-0.00458808
7012.212.2457-0.0456888
7112.314.0618-1.76178
7211.412.0688-0.668842
738.812.2973-3.49731
7414.613.8330.766965
7512.612.5440.0560349
76NANA0.0400395
771312.89450.10551
7812.614.1343-1.53425
7913.214.2491-1.04912
809.914.3649-4.46487
817.78.68196-0.981964
8210.58.303182.19682
8313.415.6909-2.29092
8410.917.8884-6.98844
854.38.11821-3.81821
8610.312.0903-1.79028
8711.812.2989-0.498873
8811.211.3808-0.180836
8911.414.9441-3.54414
908.67.363181.23682
9113.212.82710.372943
9212.619.5574-6.95741
935.68.73598-3.13598
949.913.0393-3.13934
958.812.0994-3.29943
967.78.84511-1.14511
97913.5454-4.54538
987.37.89656-0.596557
9911.49.064962.33504
10013.618.5855-4.98553
1017.98.66379-0.763789
10210.713.0666-2.36661
10310.312.0032-1.70324
1048.311.2344-2.9344
1059.67.53362.0664
10614.217.0933-2.89329
1078.57.046791.45321
10813.521.4064-7.90639
1094.98.99631-4.09631
1106.49.5411-3.1411
1119.610.0406-0.440614
11211.612.1741-0.574087
11311.117.2554-6.15545
1144.354.68435-0.334348
11512.78.496314.20369
11618.114.3623.73799
11717.8518.8217-0.971722
11816.615.06471.53532
11912.612.11610.483904
12017.114.21512.88486
12119.121.5383-2.43832
12216.113.09933.00071
12313.3510.41872.93134
12418.414.27544.12457
12514.717.2031-2.50314
12610.69.205721.39428
12712.68.569144.03086
12816.215.96710.232861
12913.68.711444.88856
13018.916.92531.97469
13114.112.61721.48283
13214.513.04221.45776
13316.1514.8931.25702
13414.7513.56321.18676
13514.815.0601-0.260148
13612.4512.26420.185755
13712.658.62394.0261
13817.3520.1264-2.77638
1398.65.01973.5803
14018.418.30510.0949421
14116.117.303-1.20302
14211.66.806914.79309
14317.7515.8181.93196
14415.2511.29513.95492
14517.6515.19962.45042
14616.3513.76912.58088
14717.6517.8648-0.214768
14813.612.43851.16149
14914.3512.36041.9896
15014.7511.5883.16202
15118.2521.3665-3.11654
1529.98.923310.97669
1531611.89394.10615
15418.2514.36263.8874
15516.8514.56282.28716
15614.613.94270.65732
15713.8511.78932.06071
15818.9516.74942.20059
15915.615.9799-0.379892
16014.8515.8341-0.984053
16111.758.507623.24238
16218.4515.77882.6712
16315.914.85581.0442
16417.112.27414.82587
16516.113.51252.58754
16619.919.87170.0283223
16710.956.809844.14016
16818.4515.91242.53758
16915.113.72741.37255
1701517.41-2.40998
17111.358.667762.68224
17215.9511.18124.76878
17318.117.48540.614586
17414.613.4981.10202
17515.414.09511.30492
17615.411.07714.32287
17717.618.324-0.724015
17813.356.335547.01446
17919.117.131.97004
18015.3518.2635-2.91348
1817.69.0056-1.4056
18213.412.20071.19926
18313.910.99062.90935
18419.116.14812.95189
18515.2514.97930.2707
18612.910.55522.3448
18716.110.8265.27401
18817.3516.92280.427189
18913.1512.23950.910514
19012.159.991722.15828
19112.613.8499-1.24988
19210.358.679221.67078
19315.418.2008-2.80081
1949.63.360536.23947
19518.216.92461.27537
19613.612.60730.992741
19714.8513.77271.07726
19814.7512.20892.54113
19914.110.49893.6011
20014.911.29633.60374
20116.2513.74612.50392
20219.2517.26311.98688
20313.612.8340.765992
20413.611.1082.49199
20515.6514.47991.17005
20612.759.540163.20984
20714.616.2008-1.60079
2089.859.365390.484611
20912.657.466495.18351
21019.216.65492.54514
21116.617.3098-0.709767
21211.29.216941.98306
21315.2515.7089-0.458917
21411.99.34292.5571
21513.211.38511.81487
21616.3515.41830.931733
21712.49.564452.83555
21815.8511.5154.33499
21918.1518.453-0.302963
22011.158.951962.19804
22115.659.854565.79544
22217.7521.0827-3.33265
2237.657.281140.368861
22412.358.45773.8923
22515.611.75133.84872
22619.315.63563.66439
22715.210.78774.41231
22817.113.84873.25134
22915.612.16313.43693
23018.413.26565.13441
23119.0512.64476.4053
23218.5515.92152.62852
23319.117.70961.39036
23413.113.6039-0.50391
23512.8514.2462-1.3962
2369.516.3354-6.83535
2374.52.469782.03022
23811.8511.61770.232259
23913.613.9327-0.33272
24011.79.935391.76461
24112.413.1195-0.719545
24213.3512.07691.27309
24311.49.022752.37725
24414.911.42693.47314
24519.921.0263-1.12628
24611.29.572761.62724
24714.612.07992.52009
24817.615.84141.75863
24914.0511.31932.73069
25016.115.43320.666799
25113.3512.51070.839281
25211.8513.2069-1.35688
25311.9511.0830.867045
25414.7511.99792.75214
25515.1515.9759-0.825875
25613.210.72922.47077
25716.8519.8868-3.03677
2587.8511.5177-3.66769
2597.78.29348-0.593477
26012.616.9736-4.37359
2617.858.54927-0.69927
26210.9510.60720.342798
26312.3513.7824-1.43239
2649.957.740352.20965
26514.911.793.10996
26616.6516.49190.158075
26713.411.34092.05915
26813.958.749675.20033
26915.711.94963.75041
27016.8517.8002-0.950201
27110.956.17794.7721
27215.3514.78750.562521
27312.29.575492.62451
27415.111.25823.84185
27517.7515.70532.04474
27615.213.33951.86051
27714.610.93263.6674
27816.6518.2232-1.57322
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.2239840.4479680.776016
200.162220.324440.83778
210.08369660.1673930.916303
220.08550240.1710050.914498
230.06194280.1238860.938057
240.04462380.08924750.955376
250.02349320.04698640.976507
260.01565130.03130260.984349
270.007891760.01578350.992108
280.003693510.007387020.996306
290.003496890.006993780.996503
300.002081720.004163440.997918
310.003401190.006802370.996599
320.001983830.003967670.998016
330.004417920.008835850.995582
340.02094860.04189720.979051
350.01536980.03073960.98463
360.01053930.02107870.989461
370.0152060.0304120.984794
380.02064360.04128720.979356
390.02379070.04758140.976209
400.01624780.03249550.983752
410.02386220.04772440.976138
420.01959830.03919670.980402
430.01523630.03047250.984764
440.01718660.03437320.982813
450.01231950.02463910.98768
460.01051290.02102570.989487
470.008629580.01725920.99137
480.00679890.01359780.993201
490.01080010.02160020.9892
500.01780070.03560150.982199
510.01406590.02813190.985934
520.01405150.0281030.985948
530.0110050.02201010.988995
540.01317730.02635460.986823
550.02616030.05232070.97384
560.02241050.04482090.97759
570.06854870.1370970.931451
580.06425390.1285080.935746
590.05263920.1052780.947361
600.04980560.09961110.950194
610.06963360.1392670.930366
620.05953090.1190620.940469
630.1120280.2240550.887972
640.1277480.2554960.872252
650.144310.2886190.85569
660.1281840.2563690.871816
670.1282910.2565820.871709
680.1516410.3032810.848359
690.1714680.3429360.828532
700.1507010.3014030.849299
710.1381070.2762130.861893
720.1221010.2442010.877899
730.1167780.2335570.883222
740.1631630.3263260.836837
750.1401080.2802160.859892
760.1213280.2426560.878672
770.1098560.2197120.890144
780.1032920.2065850.896708
790.08605710.1721140.913943
800.09874080.1974820.901259
810.08475020.16950.91525
820.09656020.193120.90344
830.08456460.1691290.915435
840.1666550.3333110.833345
850.1644980.3289950.835502
860.1470970.2941950.852903
870.132680.265360.86732
880.1367170.2734350.863283
890.1395950.2791890.860405
900.1522120.3044230.847788
910.153540.3070790.84646
920.2807490.5614990.719251
930.2857570.5715140.714243
940.2781180.5562360.721882
950.2737880.5475750.726212
960.2580180.5160370.741982
970.3399720.6799440.660028
980.315910.6318190.68409
990.3315860.6631720.668414
1000.3914660.7829320.608534
1010.3674270.7348540.632573
1020.3722450.7444910.627755
1030.3911890.7823780.608811
1040.4116790.8233570.588321
1050.4287730.8575450.571227
1060.4412870.8825730.558713
1070.5031160.9937670.496884
1080.7497180.5005640.250282
1090.7897890.4204220.210211
1100.7883630.4232750.211637
1110.7885320.4229370.211468
1120.8005170.3989660.199483
1130.8865440.2269120.113456
1140.8984070.2031850.101593
1150.9483520.1032970.0516483
1160.9698650.060270.030135
1170.9708770.05824690.0291235
1180.9743490.05130270.0256514
1190.9802720.03945690.0197284
1200.9853730.0292550.0146275
1210.98820.02360090.0118005
1220.9926890.01462270.00731137
1230.9960730.00785330.00392665
1240.99830.003399330.00169966
1250.9985250.002949980.00147499
1260.9983190.003361860.00168093
1270.9987370.002526690.00126334
1280.9985080.002984840.00149242
1290.9992670.001465270.000732633
1300.9992950.00140960.000704799
1310.9992270.001545560.000772779
1320.999110.001779090.000889544
1330.9989790.00204280.0010214
1340.9991330.001733260.000866628
1350.9988960.00220760.0011038
1360.998720.002559670.00127983
1370.999130.001739410.000869704
1380.9990390.001921850.000960925
1390.9992870.001425720.000712862
1400.9990840.001832990.000916497
1410.9987710.002457860.00122893
1420.9991750.001649510.000824754
1430.9991850.001630770.000815385
1440.9994020.001196450.000598226
1450.9993010.001398620.000699309
1460.9992740.001452690.000726345
1470.9990680.001863320.000931659
1480.998820.002360810.0011804
1490.9987830.002434710.00121735
1500.998790.002419070.00120953
1510.9994580.001083210.000541605
1520.9992950.001409910.000704957
1530.9994840.001031340.000515672
1540.9994780.001044940.000522468
1550.9994680.001063470.000531733
1560.9992810.001437690.000718847
1570.9991650.001669210.000834606
1580.9990660.001867960.000933979
1590.9989120.002175830.00108792
1600.9987390.002521480.00126074
1610.9988240.002352240.00117612
1620.9988350.00232960.0011648
1630.9989930.002014370.00100719
1640.9998290.0003425090.000171255
1650.9997980.000403670.000201835
1660.9997580.0004844010.0002422
1670.9998010.0003987620.000199381
1680.9998240.0003513350.000175667
1690.9997610.0004789030.000239452
1700.9997470.0005050280.000252514
1710.9997250.0005500090.000275004
1720.9998040.0003916880.000195844
1730.9997920.0004166690.000208334
1740.9997030.0005931510.000296576
1750.999590.0008193170.000409659
1760.9996910.0006176780.000308839
1770.99960.000799880.00039994
1780.9998480.0003042480.000152124
1790.9997930.0004140440.000207022
1800.9998050.0003898920.000194946
1810.9997810.0004384680.000219234
1820.9996890.0006212990.00031065
1830.9996160.0007672380.000383619
1840.9995450.0009109470.000455474
1850.9994310.001137860.000568929
1860.9992870.00142570.000712849
1870.999560.0008805880.000440294
1880.9994170.001165460.000582731
1890.9991910.001617510.000808757
1900.9989910.002017910.00100896
1910.9986270.002745330.00137266
1920.9983750.003250230.00162512
1930.9986940.002611180.00130559
1940.9994530.001093420.000546708
1950.999290.001419540.000709769
1960.999070.001859520.000929761
1970.9988550.002289380.00114469
1980.9986090.002781430.00139072
1990.9988380.002323090.00116155
2000.9987850.002430840.00121542
2010.9983140.003371410.0016857
2020.9980970.00380640.0019032
2030.997530.004939370.00246969
2040.99690.006200530.00310026
2050.9959960.008008310.00400415
2060.9951690.009661980.00483099
2070.9935830.01283490.00641746
2080.9918440.01631180.0081559
2090.9918280.01634470.00817236
2100.9899060.02018760.0100938
2110.9863750.027250.013625
2120.9822230.03555410.017777
2130.9817090.03658130.0182906
2140.9816630.03667380.0183369
2150.9801910.03961710.0198085
2160.9736330.05273370.0263668
2170.9710310.05793710.0289686
2180.9656990.06860150.0343007
2190.9554990.08900170.0445009
2200.9448660.1102690.0551343
2210.9533970.09320540.0466027
2220.9546180.09076340.0453817
2230.9424680.1150640.0575321
2240.9497620.1004760.0502382
2250.9410890.1178220.058911
2260.9644820.0710360.035518
2270.9696610.06067840.0303392
2280.9660180.0679630.0339815
2290.9562390.08752230.0437611
2300.9645370.07092690.0354635
2310.976370.04726030.0236302
2320.9680150.06397080.0319854
2330.9564580.08708330.0435417
2340.9493240.1013520.0506759
2350.9338460.1323080.0661542
2360.9869150.0261710.0130855
2370.9878710.0242570.0121285
2380.9825580.0348840.017442
2390.975930.048140.02407
2400.9648550.07029040.0351452
2410.9578630.08427350.0421367
2420.9403770.1192470.0596233
2430.9224060.1551880.0775939
2440.9005040.1989920.0994961
2450.9119510.1760980.0880491
2460.8818990.2362010.118101
2470.850280.2994390.14972
2480.7977820.4044350.202218
2490.7360740.5278510.263926
2500.6637680.6724630.336232
2510.5790950.841810.420905
2520.5037230.9925540.496277
2530.4089510.8179020.591049
2540.4317880.8635750.568212
2550.4294460.8588930.570554
2560.3516910.7033820.648309
2570.3767250.7534490.623275
2580.9574210.08515860.0425793
2590.9008370.1983250.0991627
2600.7925980.4148050.207402

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 & 0.223984 & 0.447968 & 0.776016 \tabularnewline
20 & 0.16222 & 0.32444 & 0.83778 \tabularnewline
21 & 0.0836966 & 0.167393 & 0.916303 \tabularnewline
22 & 0.0855024 & 0.171005 & 0.914498 \tabularnewline
23 & 0.0619428 & 0.123886 & 0.938057 \tabularnewline
24 & 0.0446238 & 0.0892475 & 0.955376 \tabularnewline
25 & 0.0234932 & 0.0469864 & 0.976507 \tabularnewline
26 & 0.0156513 & 0.0313026 & 0.984349 \tabularnewline
27 & 0.00789176 & 0.0157835 & 0.992108 \tabularnewline
28 & 0.00369351 & 0.00738702 & 0.996306 \tabularnewline
29 & 0.00349689 & 0.00699378 & 0.996503 \tabularnewline
30 & 0.00208172 & 0.00416344 & 0.997918 \tabularnewline
31 & 0.00340119 & 0.00680237 & 0.996599 \tabularnewline
32 & 0.00198383 & 0.00396767 & 0.998016 \tabularnewline
33 & 0.00441792 & 0.00883585 & 0.995582 \tabularnewline
34 & 0.0209486 & 0.0418972 & 0.979051 \tabularnewline
35 & 0.0153698 & 0.0307396 & 0.98463 \tabularnewline
36 & 0.0105393 & 0.0210787 & 0.989461 \tabularnewline
37 & 0.015206 & 0.030412 & 0.984794 \tabularnewline
38 & 0.0206436 & 0.0412872 & 0.979356 \tabularnewline
39 & 0.0237907 & 0.0475814 & 0.976209 \tabularnewline
40 & 0.0162478 & 0.0324955 & 0.983752 \tabularnewline
41 & 0.0238622 & 0.0477244 & 0.976138 \tabularnewline
42 & 0.0195983 & 0.0391967 & 0.980402 \tabularnewline
43 & 0.0152363 & 0.0304725 & 0.984764 \tabularnewline
44 & 0.0171866 & 0.0343732 & 0.982813 \tabularnewline
45 & 0.0123195 & 0.0246391 & 0.98768 \tabularnewline
46 & 0.0105129 & 0.0210257 & 0.989487 \tabularnewline
47 & 0.00862958 & 0.0172592 & 0.99137 \tabularnewline
48 & 0.0067989 & 0.0135978 & 0.993201 \tabularnewline
49 & 0.0108001 & 0.0216002 & 0.9892 \tabularnewline
50 & 0.0178007 & 0.0356015 & 0.982199 \tabularnewline
51 & 0.0140659 & 0.0281319 & 0.985934 \tabularnewline
52 & 0.0140515 & 0.028103 & 0.985948 \tabularnewline
53 & 0.011005 & 0.0220101 & 0.988995 \tabularnewline
54 & 0.0131773 & 0.0263546 & 0.986823 \tabularnewline
55 & 0.0261603 & 0.0523207 & 0.97384 \tabularnewline
56 & 0.0224105 & 0.0448209 & 0.97759 \tabularnewline
57 & 0.0685487 & 0.137097 & 0.931451 \tabularnewline
58 & 0.0642539 & 0.128508 & 0.935746 \tabularnewline
59 & 0.0526392 & 0.105278 & 0.947361 \tabularnewline
60 & 0.0498056 & 0.0996111 & 0.950194 \tabularnewline
61 & 0.0696336 & 0.139267 & 0.930366 \tabularnewline
62 & 0.0595309 & 0.119062 & 0.940469 \tabularnewline
63 & 0.112028 & 0.224055 & 0.887972 \tabularnewline
64 & 0.127748 & 0.255496 & 0.872252 \tabularnewline
65 & 0.14431 & 0.288619 & 0.85569 \tabularnewline
66 & 0.128184 & 0.256369 & 0.871816 \tabularnewline
67 & 0.128291 & 0.256582 & 0.871709 \tabularnewline
68 & 0.151641 & 0.303281 & 0.848359 \tabularnewline
69 & 0.171468 & 0.342936 & 0.828532 \tabularnewline
70 & 0.150701 & 0.301403 & 0.849299 \tabularnewline
71 & 0.138107 & 0.276213 & 0.861893 \tabularnewline
72 & 0.122101 & 0.244201 & 0.877899 \tabularnewline
73 & 0.116778 & 0.233557 & 0.883222 \tabularnewline
74 & 0.163163 & 0.326326 & 0.836837 \tabularnewline
75 & 0.140108 & 0.280216 & 0.859892 \tabularnewline
76 & 0.121328 & 0.242656 & 0.878672 \tabularnewline
77 & 0.109856 & 0.219712 & 0.890144 \tabularnewline
78 & 0.103292 & 0.206585 & 0.896708 \tabularnewline
79 & 0.0860571 & 0.172114 & 0.913943 \tabularnewline
80 & 0.0987408 & 0.197482 & 0.901259 \tabularnewline
81 & 0.0847502 & 0.1695 & 0.91525 \tabularnewline
82 & 0.0965602 & 0.19312 & 0.90344 \tabularnewline
83 & 0.0845646 & 0.169129 & 0.915435 \tabularnewline
84 & 0.166655 & 0.333311 & 0.833345 \tabularnewline
85 & 0.164498 & 0.328995 & 0.835502 \tabularnewline
86 & 0.147097 & 0.294195 & 0.852903 \tabularnewline
87 & 0.13268 & 0.26536 & 0.86732 \tabularnewline
88 & 0.136717 & 0.273435 & 0.863283 \tabularnewline
89 & 0.139595 & 0.279189 & 0.860405 \tabularnewline
90 & 0.152212 & 0.304423 & 0.847788 \tabularnewline
91 & 0.15354 & 0.307079 & 0.84646 \tabularnewline
92 & 0.280749 & 0.561499 & 0.719251 \tabularnewline
93 & 0.285757 & 0.571514 & 0.714243 \tabularnewline
94 & 0.278118 & 0.556236 & 0.721882 \tabularnewline
95 & 0.273788 & 0.547575 & 0.726212 \tabularnewline
96 & 0.258018 & 0.516037 & 0.741982 \tabularnewline
97 & 0.339972 & 0.679944 & 0.660028 \tabularnewline
98 & 0.31591 & 0.631819 & 0.68409 \tabularnewline
99 & 0.331586 & 0.663172 & 0.668414 \tabularnewline
100 & 0.391466 & 0.782932 & 0.608534 \tabularnewline
101 & 0.367427 & 0.734854 & 0.632573 \tabularnewline
102 & 0.372245 & 0.744491 & 0.627755 \tabularnewline
103 & 0.391189 & 0.782378 & 0.608811 \tabularnewline
104 & 0.411679 & 0.823357 & 0.588321 \tabularnewline
105 & 0.428773 & 0.857545 & 0.571227 \tabularnewline
106 & 0.441287 & 0.882573 & 0.558713 \tabularnewline
107 & 0.503116 & 0.993767 & 0.496884 \tabularnewline
108 & 0.749718 & 0.500564 & 0.250282 \tabularnewline
109 & 0.789789 & 0.420422 & 0.210211 \tabularnewline
110 & 0.788363 & 0.423275 & 0.211637 \tabularnewline
111 & 0.788532 & 0.422937 & 0.211468 \tabularnewline
112 & 0.800517 & 0.398966 & 0.199483 \tabularnewline
113 & 0.886544 & 0.226912 & 0.113456 \tabularnewline
114 & 0.898407 & 0.203185 & 0.101593 \tabularnewline
115 & 0.948352 & 0.103297 & 0.0516483 \tabularnewline
116 & 0.969865 & 0.06027 & 0.030135 \tabularnewline
117 & 0.970877 & 0.0582469 & 0.0291235 \tabularnewline
118 & 0.974349 & 0.0513027 & 0.0256514 \tabularnewline
119 & 0.980272 & 0.0394569 & 0.0197284 \tabularnewline
120 & 0.985373 & 0.029255 & 0.0146275 \tabularnewline
121 & 0.9882 & 0.0236009 & 0.0118005 \tabularnewline
122 & 0.992689 & 0.0146227 & 0.00731137 \tabularnewline
123 & 0.996073 & 0.0078533 & 0.00392665 \tabularnewline
124 & 0.9983 & 0.00339933 & 0.00169966 \tabularnewline
125 & 0.998525 & 0.00294998 & 0.00147499 \tabularnewline
126 & 0.998319 & 0.00336186 & 0.00168093 \tabularnewline
127 & 0.998737 & 0.00252669 & 0.00126334 \tabularnewline
128 & 0.998508 & 0.00298484 & 0.00149242 \tabularnewline
129 & 0.999267 & 0.00146527 & 0.000732633 \tabularnewline
130 & 0.999295 & 0.0014096 & 0.000704799 \tabularnewline
131 & 0.999227 & 0.00154556 & 0.000772779 \tabularnewline
132 & 0.99911 & 0.00177909 & 0.000889544 \tabularnewline
133 & 0.998979 & 0.0020428 & 0.0010214 \tabularnewline
134 & 0.999133 & 0.00173326 & 0.000866628 \tabularnewline
135 & 0.998896 & 0.0022076 & 0.0011038 \tabularnewline
136 & 0.99872 & 0.00255967 & 0.00127983 \tabularnewline
137 & 0.99913 & 0.00173941 & 0.000869704 \tabularnewline
138 & 0.999039 & 0.00192185 & 0.000960925 \tabularnewline
139 & 0.999287 & 0.00142572 & 0.000712862 \tabularnewline
140 & 0.999084 & 0.00183299 & 0.000916497 \tabularnewline
141 & 0.998771 & 0.00245786 & 0.00122893 \tabularnewline
142 & 0.999175 & 0.00164951 & 0.000824754 \tabularnewline
143 & 0.999185 & 0.00163077 & 0.000815385 \tabularnewline
144 & 0.999402 & 0.00119645 & 0.000598226 \tabularnewline
145 & 0.999301 & 0.00139862 & 0.000699309 \tabularnewline
146 & 0.999274 & 0.00145269 & 0.000726345 \tabularnewline
147 & 0.999068 & 0.00186332 & 0.000931659 \tabularnewline
148 & 0.99882 & 0.00236081 & 0.0011804 \tabularnewline
149 & 0.998783 & 0.00243471 & 0.00121735 \tabularnewline
150 & 0.99879 & 0.00241907 & 0.00120953 \tabularnewline
151 & 0.999458 & 0.00108321 & 0.000541605 \tabularnewline
152 & 0.999295 & 0.00140991 & 0.000704957 \tabularnewline
153 & 0.999484 & 0.00103134 & 0.000515672 \tabularnewline
154 & 0.999478 & 0.00104494 & 0.000522468 \tabularnewline
155 & 0.999468 & 0.00106347 & 0.000531733 \tabularnewline
156 & 0.999281 & 0.00143769 & 0.000718847 \tabularnewline
157 & 0.999165 & 0.00166921 & 0.000834606 \tabularnewline
158 & 0.999066 & 0.00186796 & 0.000933979 \tabularnewline
159 & 0.998912 & 0.00217583 & 0.00108792 \tabularnewline
160 & 0.998739 & 0.00252148 & 0.00126074 \tabularnewline
161 & 0.998824 & 0.00235224 & 0.00117612 \tabularnewline
162 & 0.998835 & 0.0023296 & 0.0011648 \tabularnewline
163 & 0.998993 & 0.00201437 & 0.00100719 \tabularnewline
164 & 0.999829 & 0.000342509 & 0.000171255 \tabularnewline
165 & 0.999798 & 0.00040367 & 0.000201835 \tabularnewline
166 & 0.999758 & 0.000484401 & 0.0002422 \tabularnewline
167 & 0.999801 & 0.000398762 & 0.000199381 \tabularnewline
168 & 0.999824 & 0.000351335 & 0.000175667 \tabularnewline
169 & 0.999761 & 0.000478903 & 0.000239452 \tabularnewline
170 & 0.999747 & 0.000505028 & 0.000252514 \tabularnewline
171 & 0.999725 & 0.000550009 & 0.000275004 \tabularnewline
172 & 0.999804 & 0.000391688 & 0.000195844 \tabularnewline
173 & 0.999792 & 0.000416669 & 0.000208334 \tabularnewline
174 & 0.999703 & 0.000593151 & 0.000296576 \tabularnewline
175 & 0.99959 & 0.000819317 & 0.000409659 \tabularnewline
176 & 0.999691 & 0.000617678 & 0.000308839 \tabularnewline
177 & 0.9996 & 0.00079988 & 0.00039994 \tabularnewline
178 & 0.999848 & 0.000304248 & 0.000152124 \tabularnewline
179 & 0.999793 & 0.000414044 & 0.000207022 \tabularnewline
180 & 0.999805 & 0.000389892 & 0.000194946 \tabularnewline
181 & 0.999781 & 0.000438468 & 0.000219234 \tabularnewline
182 & 0.999689 & 0.000621299 & 0.00031065 \tabularnewline
183 & 0.999616 & 0.000767238 & 0.000383619 \tabularnewline
184 & 0.999545 & 0.000910947 & 0.000455474 \tabularnewline
185 & 0.999431 & 0.00113786 & 0.000568929 \tabularnewline
186 & 0.999287 & 0.0014257 & 0.000712849 \tabularnewline
187 & 0.99956 & 0.000880588 & 0.000440294 \tabularnewline
188 & 0.999417 & 0.00116546 & 0.000582731 \tabularnewline
189 & 0.999191 & 0.00161751 & 0.000808757 \tabularnewline
190 & 0.998991 & 0.00201791 & 0.00100896 \tabularnewline
191 & 0.998627 & 0.00274533 & 0.00137266 \tabularnewline
192 & 0.998375 & 0.00325023 & 0.00162512 \tabularnewline
193 & 0.998694 & 0.00261118 & 0.00130559 \tabularnewline
194 & 0.999453 & 0.00109342 & 0.000546708 \tabularnewline
195 & 0.99929 & 0.00141954 & 0.000709769 \tabularnewline
196 & 0.99907 & 0.00185952 & 0.000929761 \tabularnewline
197 & 0.998855 & 0.00228938 & 0.00114469 \tabularnewline
198 & 0.998609 & 0.00278143 & 0.00139072 \tabularnewline
199 & 0.998838 & 0.00232309 & 0.00116155 \tabularnewline
200 & 0.998785 & 0.00243084 & 0.00121542 \tabularnewline
201 & 0.998314 & 0.00337141 & 0.0016857 \tabularnewline
202 & 0.998097 & 0.0038064 & 0.0019032 \tabularnewline
203 & 0.99753 & 0.00493937 & 0.00246969 \tabularnewline
204 & 0.9969 & 0.00620053 & 0.00310026 \tabularnewline
205 & 0.995996 & 0.00800831 & 0.00400415 \tabularnewline
206 & 0.995169 & 0.00966198 & 0.00483099 \tabularnewline
207 & 0.993583 & 0.0128349 & 0.00641746 \tabularnewline
208 & 0.991844 & 0.0163118 & 0.0081559 \tabularnewline
209 & 0.991828 & 0.0163447 & 0.00817236 \tabularnewline
210 & 0.989906 & 0.0201876 & 0.0100938 \tabularnewline
211 & 0.986375 & 0.02725 & 0.013625 \tabularnewline
212 & 0.982223 & 0.0355541 & 0.017777 \tabularnewline
213 & 0.981709 & 0.0365813 & 0.0182906 \tabularnewline
214 & 0.981663 & 0.0366738 & 0.0183369 \tabularnewline
215 & 0.980191 & 0.0396171 & 0.0198085 \tabularnewline
216 & 0.973633 & 0.0527337 & 0.0263668 \tabularnewline
217 & 0.971031 & 0.0579371 & 0.0289686 \tabularnewline
218 & 0.965699 & 0.0686015 & 0.0343007 \tabularnewline
219 & 0.955499 & 0.0890017 & 0.0445009 \tabularnewline
220 & 0.944866 & 0.110269 & 0.0551343 \tabularnewline
221 & 0.953397 & 0.0932054 & 0.0466027 \tabularnewline
222 & 0.954618 & 0.0907634 & 0.0453817 \tabularnewline
223 & 0.942468 & 0.115064 & 0.0575321 \tabularnewline
224 & 0.949762 & 0.100476 & 0.0502382 \tabularnewline
225 & 0.941089 & 0.117822 & 0.058911 \tabularnewline
226 & 0.964482 & 0.071036 & 0.035518 \tabularnewline
227 & 0.969661 & 0.0606784 & 0.0303392 \tabularnewline
228 & 0.966018 & 0.067963 & 0.0339815 \tabularnewline
229 & 0.956239 & 0.0875223 & 0.0437611 \tabularnewline
230 & 0.964537 & 0.0709269 & 0.0354635 \tabularnewline
231 & 0.97637 & 0.0472603 & 0.0236302 \tabularnewline
232 & 0.968015 & 0.0639708 & 0.0319854 \tabularnewline
233 & 0.956458 & 0.0870833 & 0.0435417 \tabularnewline
234 & 0.949324 & 0.101352 & 0.0506759 \tabularnewline
235 & 0.933846 & 0.132308 & 0.0661542 \tabularnewline
236 & 0.986915 & 0.026171 & 0.0130855 \tabularnewline
237 & 0.987871 & 0.024257 & 0.0121285 \tabularnewline
238 & 0.982558 & 0.034884 & 0.017442 \tabularnewline
239 & 0.97593 & 0.04814 & 0.02407 \tabularnewline
240 & 0.964855 & 0.0702904 & 0.0351452 \tabularnewline
241 & 0.957863 & 0.0842735 & 0.0421367 \tabularnewline
242 & 0.940377 & 0.119247 & 0.0596233 \tabularnewline
243 & 0.922406 & 0.155188 & 0.0775939 \tabularnewline
244 & 0.900504 & 0.198992 & 0.0994961 \tabularnewline
245 & 0.911951 & 0.176098 & 0.0880491 \tabularnewline
246 & 0.881899 & 0.236201 & 0.118101 \tabularnewline
247 & 0.85028 & 0.299439 & 0.14972 \tabularnewline
248 & 0.797782 & 0.404435 & 0.202218 \tabularnewline
249 & 0.736074 & 0.527851 & 0.263926 \tabularnewline
250 & 0.663768 & 0.672463 & 0.336232 \tabularnewline
251 & 0.579095 & 0.84181 & 0.420905 \tabularnewline
252 & 0.503723 & 0.992554 & 0.496277 \tabularnewline
253 & 0.408951 & 0.817902 & 0.591049 \tabularnewline
254 & 0.431788 & 0.863575 & 0.568212 \tabularnewline
255 & 0.429446 & 0.858893 & 0.570554 \tabularnewline
256 & 0.351691 & 0.703382 & 0.648309 \tabularnewline
257 & 0.376725 & 0.753449 & 0.623275 \tabularnewline
258 & 0.957421 & 0.0851586 & 0.0425793 \tabularnewline
259 & 0.900837 & 0.198325 & 0.0991627 \tabularnewline
260 & 0.792598 & 0.414805 & 0.207402 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&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]0.223984[/C][C]0.447968[/C][C]0.776016[/C][/ROW]
[ROW][C]20[/C][C]0.16222[/C][C]0.32444[/C][C]0.83778[/C][/ROW]
[ROW][C]21[/C][C]0.0836966[/C][C]0.167393[/C][C]0.916303[/C][/ROW]
[ROW][C]22[/C][C]0.0855024[/C][C]0.171005[/C][C]0.914498[/C][/ROW]
[ROW][C]23[/C][C]0.0619428[/C][C]0.123886[/C][C]0.938057[/C][/ROW]
[ROW][C]24[/C][C]0.0446238[/C][C]0.0892475[/C][C]0.955376[/C][/ROW]
[ROW][C]25[/C][C]0.0234932[/C][C]0.0469864[/C][C]0.976507[/C][/ROW]
[ROW][C]26[/C][C]0.0156513[/C][C]0.0313026[/C][C]0.984349[/C][/ROW]
[ROW][C]27[/C][C]0.00789176[/C][C]0.0157835[/C][C]0.992108[/C][/ROW]
[ROW][C]28[/C][C]0.00369351[/C][C]0.00738702[/C][C]0.996306[/C][/ROW]
[ROW][C]29[/C][C]0.00349689[/C][C]0.00699378[/C][C]0.996503[/C][/ROW]
[ROW][C]30[/C][C]0.00208172[/C][C]0.00416344[/C][C]0.997918[/C][/ROW]
[ROW][C]31[/C][C]0.00340119[/C][C]0.00680237[/C][C]0.996599[/C][/ROW]
[ROW][C]32[/C][C]0.00198383[/C][C]0.00396767[/C][C]0.998016[/C][/ROW]
[ROW][C]33[/C][C]0.00441792[/C][C]0.00883585[/C][C]0.995582[/C][/ROW]
[ROW][C]34[/C][C]0.0209486[/C][C]0.0418972[/C][C]0.979051[/C][/ROW]
[ROW][C]35[/C][C]0.0153698[/C][C]0.0307396[/C][C]0.98463[/C][/ROW]
[ROW][C]36[/C][C]0.0105393[/C][C]0.0210787[/C][C]0.989461[/C][/ROW]
[ROW][C]37[/C][C]0.015206[/C][C]0.030412[/C][C]0.984794[/C][/ROW]
[ROW][C]38[/C][C]0.0206436[/C][C]0.0412872[/C][C]0.979356[/C][/ROW]
[ROW][C]39[/C][C]0.0237907[/C][C]0.0475814[/C][C]0.976209[/C][/ROW]
[ROW][C]40[/C][C]0.0162478[/C][C]0.0324955[/C][C]0.983752[/C][/ROW]
[ROW][C]41[/C][C]0.0238622[/C][C]0.0477244[/C][C]0.976138[/C][/ROW]
[ROW][C]42[/C][C]0.0195983[/C][C]0.0391967[/C][C]0.980402[/C][/ROW]
[ROW][C]43[/C][C]0.0152363[/C][C]0.0304725[/C][C]0.984764[/C][/ROW]
[ROW][C]44[/C][C]0.0171866[/C][C]0.0343732[/C][C]0.982813[/C][/ROW]
[ROW][C]45[/C][C]0.0123195[/C][C]0.0246391[/C][C]0.98768[/C][/ROW]
[ROW][C]46[/C][C]0.0105129[/C][C]0.0210257[/C][C]0.989487[/C][/ROW]
[ROW][C]47[/C][C]0.00862958[/C][C]0.0172592[/C][C]0.99137[/C][/ROW]
[ROW][C]48[/C][C]0.0067989[/C][C]0.0135978[/C][C]0.993201[/C][/ROW]
[ROW][C]49[/C][C]0.0108001[/C][C]0.0216002[/C][C]0.9892[/C][/ROW]
[ROW][C]50[/C][C]0.0178007[/C][C]0.0356015[/C][C]0.982199[/C][/ROW]
[ROW][C]51[/C][C]0.0140659[/C][C]0.0281319[/C][C]0.985934[/C][/ROW]
[ROW][C]52[/C][C]0.0140515[/C][C]0.028103[/C][C]0.985948[/C][/ROW]
[ROW][C]53[/C][C]0.011005[/C][C]0.0220101[/C][C]0.988995[/C][/ROW]
[ROW][C]54[/C][C]0.0131773[/C][C]0.0263546[/C][C]0.986823[/C][/ROW]
[ROW][C]55[/C][C]0.0261603[/C][C]0.0523207[/C][C]0.97384[/C][/ROW]
[ROW][C]56[/C][C]0.0224105[/C][C]0.0448209[/C][C]0.97759[/C][/ROW]
[ROW][C]57[/C][C]0.0685487[/C][C]0.137097[/C][C]0.931451[/C][/ROW]
[ROW][C]58[/C][C]0.0642539[/C][C]0.128508[/C][C]0.935746[/C][/ROW]
[ROW][C]59[/C][C]0.0526392[/C][C]0.105278[/C][C]0.947361[/C][/ROW]
[ROW][C]60[/C][C]0.0498056[/C][C]0.0996111[/C][C]0.950194[/C][/ROW]
[ROW][C]61[/C][C]0.0696336[/C][C]0.139267[/C][C]0.930366[/C][/ROW]
[ROW][C]62[/C][C]0.0595309[/C][C]0.119062[/C][C]0.940469[/C][/ROW]
[ROW][C]63[/C][C]0.112028[/C][C]0.224055[/C][C]0.887972[/C][/ROW]
[ROW][C]64[/C][C]0.127748[/C][C]0.255496[/C][C]0.872252[/C][/ROW]
[ROW][C]65[/C][C]0.14431[/C][C]0.288619[/C][C]0.85569[/C][/ROW]
[ROW][C]66[/C][C]0.128184[/C][C]0.256369[/C][C]0.871816[/C][/ROW]
[ROW][C]67[/C][C]0.128291[/C][C]0.256582[/C][C]0.871709[/C][/ROW]
[ROW][C]68[/C][C]0.151641[/C][C]0.303281[/C][C]0.848359[/C][/ROW]
[ROW][C]69[/C][C]0.171468[/C][C]0.342936[/C][C]0.828532[/C][/ROW]
[ROW][C]70[/C][C]0.150701[/C][C]0.301403[/C][C]0.849299[/C][/ROW]
[ROW][C]71[/C][C]0.138107[/C][C]0.276213[/C][C]0.861893[/C][/ROW]
[ROW][C]72[/C][C]0.122101[/C][C]0.244201[/C][C]0.877899[/C][/ROW]
[ROW][C]73[/C][C]0.116778[/C][C]0.233557[/C][C]0.883222[/C][/ROW]
[ROW][C]74[/C][C]0.163163[/C][C]0.326326[/C][C]0.836837[/C][/ROW]
[ROW][C]75[/C][C]0.140108[/C][C]0.280216[/C][C]0.859892[/C][/ROW]
[ROW][C]76[/C][C]0.121328[/C][C]0.242656[/C][C]0.878672[/C][/ROW]
[ROW][C]77[/C][C]0.109856[/C][C]0.219712[/C][C]0.890144[/C][/ROW]
[ROW][C]78[/C][C]0.103292[/C][C]0.206585[/C][C]0.896708[/C][/ROW]
[ROW][C]79[/C][C]0.0860571[/C][C]0.172114[/C][C]0.913943[/C][/ROW]
[ROW][C]80[/C][C]0.0987408[/C][C]0.197482[/C][C]0.901259[/C][/ROW]
[ROW][C]81[/C][C]0.0847502[/C][C]0.1695[/C][C]0.91525[/C][/ROW]
[ROW][C]82[/C][C]0.0965602[/C][C]0.19312[/C][C]0.90344[/C][/ROW]
[ROW][C]83[/C][C]0.0845646[/C][C]0.169129[/C][C]0.915435[/C][/ROW]
[ROW][C]84[/C][C]0.166655[/C][C]0.333311[/C][C]0.833345[/C][/ROW]
[ROW][C]85[/C][C]0.164498[/C][C]0.328995[/C][C]0.835502[/C][/ROW]
[ROW][C]86[/C][C]0.147097[/C][C]0.294195[/C][C]0.852903[/C][/ROW]
[ROW][C]87[/C][C]0.13268[/C][C]0.26536[/C][C]0.86732[/C][/ROW]
[ROW][C]88[/C][C]0.136717[/C][C]0.273435[/C][C]0.863283[/C][/ROW]
[ROW][C]89[/C][C]0.139595[/C][C]0.279189[/C][C]0.860405[/C][/ROW]
[ROW][C]90[/C][C]0.152212[/C][C]0.304423[/C][C]0.847788[/C][/ROW]
[ROW][C]91[/C][C]0.15354[/C][C]0.307079[/C][C]0.84646[/C][/ROW]
[ROW][C]92[/C][C]0.280749[/C][C]0.561499[/C][C]0.719251[/C][/ROW]
[ROW][C]93[/C][C]0.285757[/C][C]0.571514[/C][C]0.714243[/C][/ROW]
[ROW][C]94[/C][C]0.278118[/C][C]0.556236[/C][C]0.721882[/C][/ROW]
[ROW][C]95[/C][C]0.273788[/C][C]0.547575[/C][C]0.726212[/C][/ROW]
[ROW][C]96[/C][C]0.258018[/C][C]0.516037[/C][C]0.741982[/C][/ROW]
[ROW][C]97[/C][C]0.339972[/C][C]0.679944[/C][C]0.660028[/C][/ROW]
[ROW][C]98[/C][C]0.31591[/C][C]0.631819[/C][C]0.68409[/C][/ROW]
[ROW][C]99[/C][C]0.331586[/C][C]0.663172[/C][C]0.668414[/C][/ROW]
[ROW][C]100[/C][C]0.391466[/C][C]0.782932[/C][C]0.608534[/C][/ROW]
[ROW][C]101[/C][C]0.367427[/C][C]0.734854[/C][C]0.632573[/C][/ROW]
[ROW][C]102[/C][C]0.372245[/C][C]0.744491[/C][C]0.627755[/C][/ROW]
[ROW][C]103[/C][C]0.391189[/C][C]0.782378[/C][C]0.608811[/C][/ROW]
[ROW][C]104[/C][C]0.411679[/C][C]0.823357[/C][C]0.588321[/C][/ROW]
[ROW][C]105[/C][C]0.428773[/C][C]0.857545[/C][C]0.571227[/C][/ROW]
[ROW][C]106[/C][C]0.441287[/C][C]0.882573[/C][C]0.558713[/C][/ROW]
[ROW][C]107[/C][C]0.503116[/C][C]0.993767[/C][C]0.496884[/C][/ROW]
[ROW][C]108[/C][C]0.749718[/C][C]0.500564[/C][C]0.250282[/C][/ROW]
[ROW][C]109[/C][C]0.789789[/C][C]0.420422[/C][C]0.210211[/C][/ROW]
[ROW][C]110[/C][C]0.788363[/C][C]0.423275[/C][C]0.211637[/C][/ROW]
[ROW][C]111[/C][C]0.788532[/C][C]0.422937[/C][C]0.211468[/C][/ROW]
[ROW][C]112[/C][C]0.800517[/C][C]0.398966[/C][C]0.199483[/C][/ROW]
[ROW][C]113[/C][C]0.886544[/C][C]0.226912[/C][C]0.113456[/C][/ROW]
[ROW][C]114[/C][C]0.898407[/C][C]0.203185[/C][C]0.101593[/C][/ROW]
[ROW][C]115[/C][C]0.948352[/C][C]0.103297[/C][C]0.0516483[/C][/ROW]
[ROW][C]116[/C][C]0.969865[/C][C]0.06027[/C][C]0.030135[/C][/ROW]
[ROW][C]117[/C][C]0.970877[/C][C]0.0582469[/C][C]0.0291235[/C][/ROW]
[ROW][C]118[/C][C]0.974349[/C][C]0.0513027[/C][C]0.0256514[/C][/ROW]
[ROW][C]119[/C][C]0.980272[/C][C]0.0394569[/C][C]0.0197284[/C][/ROW]
[ROW][C]120[/C][C]0.985373[/C][C]0.029255[/C][C]0.0146275[/C][/ROW]
[ROW][C]121[/C][C]0.9882[/C][C]0.0236009[/C][C]0.0118005[/C][/ROW]
[ROW][C]122[/C][C]0.992689[/C][C]0.0146227[/C][C]0.00731137[/C][/ROW]
[ROW][C]123[/C][C]0.996073[/C][C]0.0078533[/C][C]0.00392665[/C][/ROW]
[ROW][C]124[/C][C]0.9983[/C][C]0.00339933[/C][C]0.00169966[/C][/ROW]
[ROW][C]125[/C][C]0.998525[/C][C]0.00294998[/C][C]0.00147499[/C][/ROW]
[ROW][C]126[/C][C]0.998319[/C][C]0.00336186[/C][C]0.00168093[/C][/ROW]
[ROW][C]127[/C][C]0.998737[/C][C]0.00252669[/C][C]0.00126334[/C][/ROW]
[ROW][C]128[/C][C]0.998508[/C][C]0.00298484[/C][C]0.00149242[/C][/ROW]
[ROW][C]129[/C][C]0.999267[/C][C]0.00146527[/C][C]0.000732633[/C][/ROW]
[ROW][C]130[/C][C]0.999295[/C][C]0.0014096[/C][C]0.000704799[/C][/ROW]
[ROW][C]131[/C][C]0.999227[/C][C]0.00154556[/C][C]0.000772779[/C][/ROW]
[ROW][C]132[/C][C]0.99911[/C][C]0.00177909[/C][C]0.000889544[/C][/ROW]
[ROW][C]133[/C][C]0.998979[/C][C]0.0020428[/C][C]0.0010214[/C][/ROW]
[ROW][C]134[/C][C]0.999133[/C][C]0.00173326[/C][C]0.000866628[/C][/ROW]
[ROW][C]135[/C][C]0.998896[/C][C]0.0022076[/C][C]0.0011038[/C][/ROW]
[ROW][C]136[/C][C]0.99872[/C][C]0.00255967[/C][C]0.00127983[/C][/ROW]
[ROW][C]137[/C][C]0.99913[/C][C]0.00173941[/C][C]0.000869704[/C][/ROW]
[ROW][C]138[/C][C]0.999039[/C][C]0.00192185[/C][C]0.000960925[/C][/ROW]
[ROW][C]139[/C][C]0.999287[/C][C]0.00142572[/C][C]0.000712862[/C][/ROW]
[ROW][C]140[/C][C]0.999084[/C][C]0.00183299[/C][C]0.000916497[/C][/ROW]
[ROW][C]141[/C][C]0.998771[/C][C]0.00245786[/C][C]0.00122893[/C][/ROW]
[ROW][C]142[/C][C]0.999175[/C][C]0.00164951[/C][C]0.000824754[/C][/ROW]
[ROW][C]143[/C][C]0.999185[/C][C]0.00163077[/C][C]0.000815385[/C][/ROW]
[ROW][C]144[/C][C]0.999402[/C][C]0.00119645[/C][C]0.000598226[/C][/ROW]
[ROW][C]145[/C][C]0.999301[/C][C]0.00139862[/C][C]0.000699309[/C][/ROW]
[ROW][C]146[/C][C]0.999274[/C][C]0.00145269[/C][C]0.000726345[/C][/ROW]
[ROW][C]147[/C][C]0.999068[/C][C]0.00186332[/C][C]0.000931659[/C][/ROW]
[ROW][C]148[/C][C]0.99882[/C][C]0.00236081[/C][C]0.0011804[/C][/ROW]
[ROW][C]149[/C][C]0.998783[/C][C]0.00243471[/C][C]0.00121735[/C][/ROW]
[ROW][C]150[/C][C]0.99879[/C][C]0.00241907[/C][C]0.00120953[/C][/ROW]
[ROW][C]151[/C][C]0.999458[/C][C]0.00108321[/C][C]0.000541605[/C][/ROW]
[ROW][C]152[/C][C]0.999295[/C][C]0.00140991[/C][C]0.000704957[/C][/ROW]
[ROW][C]153[/C][C]0.999484[/C][C]0.00103134[/C][C]0.000515672[/C][/ROW]
[ROW][C]154[/C][C]0.999478[/C][C]0.00104494[/C][C]0.000522468[/C][/ROW]
[ROW][C]155[/C][C]0.999468[/C][C]0.00106347[/C][C]0.000531733[/C][/ROW]
[ROW][C]156[/C][C]0.999281[/C][C]0.00143769[/C][C]0.000718847[/C][/ROW]
[ROW][C]157[/C][C]0.999165[/C][C]0.00166921[/C][C]0.000834606[/C][/ROW]
[ROW][C]158[/C][C]0.999066[/C][C]0.00186796[/C][C]0.000933979[/C][/ROW]
[ROW][C]159[/C][C]0.998912[/C][C]0.00217583[/C][C]0.00108792[/C][/ROW]
[ROW][C]160[/C][C]0.998739[/C][C]0.00252148[/C][C]0.00126074[/C][/ROW]
[ROW][C]161[/C][C]0.998824[/C][C]0.00235224[/C][C]0.00117612[/C][/ROW]
[ROW][C]162[/C][C]0.998835[/C][C]0.0023296[/C][C]0.0011648[/C][/ROW]
[ROW][C]163[/C][C]0.998993[/C][C]0.00201437[/C][C]0.00100719[/C][/ROW]
[ROW][C]164[/C][C]0.999829[/C][C]0.000342509[/C][C]0.000171255[/C][/ROW]
[ROW][C]165[/C][C]0.999798[/C][C]0.00040367[/C][C]0.000201835[/C][/ROW]
[ROW][C]166[/C][C]0.999758[/C][C]0.000484401[/C][C]0.0002422[/C][/ROW]
[ROW][C]167[/C][C]0.999801[/C][C]0.000398762[/C][C]0.000199381[/C][/ROW]
[ROW][C]168[/C][C]0.999824[/C][C]0.000351335[/C][C]0.000175667[/C][/ROW]
[ROW][C]169[/C][C]0.999761[/C][C]0.000478903[/C][C]0.000239452[/C][/ROW]
[ROW][C]170[/C][C]0.999747[/C][C]0.000505028[/C][C]0.000252514[/C][/ROW]
[ROW][C]171[/C][C]0.999725[/C][C]0.000550009[/C][C]0.000275004[/C][/ROW]
[ROW][C]172[/C][C]0.999804[/C][C]0.000391688[/C][C]0.000195844[/C][/ROW]
[ROW][C]173[/C][C]0.999792[/C][C]0.000416669[/C][C]0.000208334[/C][/ROW]
[ROW][C]174[/C][C]0.999703[/C][C]0.000593151[/C][C]0.000296576[/C][/ROW]
[ROW][C]175[/C][C]0.99959[/C][C]0.000819317[/C][C]0.000409659[/C][/ROW]
[ROW][C]176[/C][C]0.999691[/C][C]0.000617678[/C][C]0.000308839[/C][/ROW]
[ROW][C]177[/C][C]0.9996[/C][C]0.00079988[/C][C]0.00039994[/C][/ROW]
[ROW][C]178[/C][C]0.999848[/C][C]0.000304248[/C][C]0.000152124[/C][/ROW]
[ROW][C]179[/C][C]0.999793[/C][C]0.000414044[/C][C]0.000207022[/C][/ROW]
[ROW][C]180[/C][C]0.999805[/C][C]0.000389892[/C][C]0.000194946[/C][/ROW]
[ROW][C]181[/C][C]0.999781[/C][C]0.000438468[/C][C]0.000219234[/C][/ROW]
[ROW][C]182[/C][C]0.999689[/C][C]0.000621299[/C][C]0.00031065[/C][/ROW]
[ROW][C]183[/C][C]0.999616[/C][C]0.000767238[/C][C]0.000383619[/C][/ROW]
[ROW][C]184[/C][C]0.999545[/C][C]0.000910947[/C][C]0.000455474[/C][/ROW]
[ROW][C]185[/C][C]0.999431[/C][C]0.00113786[/C][C]0.000568929[/C][/ROW]
[ROW][C]186[/C][C]0.999287[/C][C]0.0014257[/C][C]0.000712849[/C][/ROW]
[ROW][C]187[/C][C]0.99956[/C][C]0.000880588[/C][C]0.000440294[/C][/ROW]
[ROW][C]188[/C][C]0.999417[/C][C]0.00116546[/C][C]0.000582731[/C][/ROW]
[ROW][C]189[/C][C]0.999191[/C][C]0.00161751[/C][C]0.000808757[/C][/ROW]
[ROW][C]190[/C][C]0.998991[/C][C]0.00201791[/C][C]0.00100896[/C][/ROW]
[ROW][C]191[/C][C]0.998627[/C][C]0.00274533[/C][C]0.00137266[/C][/ROW]
[ROW][C]192[/C][C]0.998375[/C][C]0.00325023[/C][C]0.00162512[/C][/ROW]
[ROW][C]193[/C][C]0.998694[/C][C]0.00261118[/C][C]0.00130559[/C][/ROW]
[ROW][C]194[/C][C]0.999453[/C][C]0.00109342[/C][C]0.000546708[/C][/ROW]
[ROW][C]195[/C][C]0.99929[/C][C]0.00141954[/C][C]0.000709769[/C][/ROW]
[ROW][C]196[/C][C]0.99907[/C][C]0.00185952[/C][C]0.000929761[/C][/ROW]
[ROW][C]197[/C][C]0.998855[/C][C]0.00228938[/C][C]0.00114469[/C][/ROW]
[ROW][C]198[/C][C]0.998609[/C][C]0.00278143[/C][C]0.00139072[/C][/ROW]
[ROW][C]199[/C][C]0.998838[/C][C]0.00232309[/C][C]0.00116155[/C][/ROW]
[ROW][C]200[/C][C]0.998785[/C][C]0.00243084[/C][C]0.00121542[/C][/ROW]
[ROW][C]201[/C][C]0.998314[/C][C]0.00337141[/C][C]0.0016857[/C][/ROW]
[ROW][C]202[/C][C]0.998097[/C][C]0.0038064[/C][C]0.0019032[/C][/ROW]
[ROW][C]203[/C][C]0.99753[/C][C]0.00493937[/C][C]0.00246969[/C][/ROW]
[ROW][C]204[/C][C]0.9969[/C][C]0.00620053[/C][C]0.00310026[/C][/ROW]
[ROW][C]205[/C][C]0.995996[/C][C]0.00800831[/C][C]0.00400415[/C][/ROW]
[ROW][C]206[/C][C]0.995169[/C][C]0.00966198[/C][C]0.00483099[/C][/ROW]
[ROW][C]207[/C][C]0.993583[/C][C]0.0128349[/C][C]0.00641746[/C][/ROW]
[ROW][C]208[/C][C]0.991844[/C][C]0.0163118[/C][C]0.0081559[/C][/ROW]
[ROW][C]209[/C][C]0.991828[/C][C]0.0163447[/C][C]0.00817236[/C][/ROW]
[ROW][C]210[/C][C]0.989906[/C][C]0.0201876[/C][C]0.0100938[/C][/ROW]
[ROW][C]211[/C][C]0.986375[/C][C]0.02725[/C][C]0.013625[/C][/ROW]
[ROW][C]212[/C][C]0.982223[/C][C]0.0355541[/C][C]0.017777[/C][/ROW]
[ROW][C]213[/C][C]0.981709[/C][C]0.0365813[/C][C]0.0182906[/C][/ROW]
[ROW][C]214[/C][C]0.981663[/C][C]0.0366738[/C][C]0.0183369[/C][/ROW]
[ROW][C]215[/C][C]0.980191[/C][C]0.0396171[/C][C]0.0198085[/C][/ROW]
[ROW][C]216[/C][C]0.973633[/C][C]0.0527337[/C][C]0.0263668[/C][/ROW]
[ROW][C]217[/C][C]0.971031[/C][C]0.0579371[/C][C]0.0289686[/C][/ROW]
[ROW][C]218[/C][C]0.965699[/C][C]0.0686015[/C][C]0.0343007[/C][/ROW]
[ROW][C]219[/C][C]0.955499[/C][C]0.0890017[/C][C]0.0445009[/C][/ROW]
[ROW][C]220[/C][C]0.944866[/C][C]0.110269[/C][C]0.0551343[/C][/ROW]
[ROW][C]221[/C][C]0.953397[/C][C]0.0932054[/C][C]0.0466027[/C][/ROW]
[ROW][C]222[/C][C]0.954618[/C][C]0.0907634[/C][C]0.0453817[/C][/ROW]
[ROW][C]223[/C][C]0.942468[/C][C]0.115064[/C][C]0.0575321[/C][/ROW]
[ROW][C]224[/C][C]0.949762[/C][C]0.100476[/C][C]0.0502382[/C][/ROW]
[ROW][C]225[/C][C]0.941089[/C][C]0.117822[/C][C]0.058911[/C][/ROW]
[ROW][C]226[/C][C]0.964482[/C][C]0.071036[/C][C]0.035518[/C][/ROW]
[ROW][C]227[/C][C]0.969661[/C][C]0.0606784[/C][C]0.0303392[/C][/ROW]
[ROW][C]228[/C][C]0.966018[/C][C]0.067963[/C][C]0.0339815[/C][/ROW]
[ROW][C]229[/C][C]0.956239[/C][C]0.0875223[/C][C]0.0437611[/C][/ROW]
[ROW][C]230[/C][C]0.964537[/C][C]0.0709269[/C][C]0.0354635[/C][/ROW]
[ROW][C]231[/C][C]0.97637[/C][C]0.0472603[/C][C]0.0236302[/C][/ROW]
[ROW][C]232[/C][C]0.968015[/C][C]0.0639708[/C][C]0.0319854[/C][/ROW]
[ROW][C]233[/C][C]0.956458[/C][C]0.0870833[/C][C]0.0435417[/C][/ROW]
[ROW][C]234[/C][C]0.949324[/C][C]0.101352[/C][C]0.0506759[/C][/ROW]
[ROW][C]235[/C][C]0.933846[/C][C]0.132308[/C][C]0.0661542[/C][/ROW]
[ROW][C]236[/C][C]0.986915[/C][C]0.026171[/C][C]0.0130855[/C][/ROW]
[ROW][C]237[/C][C]0.987871[/C][C]0.024257[/C][C]0.0121285[/C][/ROW]
[ROW][C]238[/C][C]0.982558[/C][C]0.034884[/C][C]0.017442[/C][/ROW]
[ROW][C]239[/C][C]0.97593[/C][C]0.04814[/C][C]0.02407[/C][/ROW]
[ROW][C]240[/C][C]0.964855[/C][C]0.0702904[/C][C]0.0351452[/C][/ROW]
[ROW][C]241[/C][C]0.957863[/C][C]0.0842735[/C][C]0.0421367[/C][/ROW]
[ROW][C]242[/C][C]0.940377[/C][C]0.119247[/C][C]0.0596233[/C][/ROW]
[ROW][C]243[/C][C]0.922406[/C][C]0.155188[/C][C]0.0775939[/C][/ROW]
[ROW][C]244[/C][C]0.900504[/C][C]0.198992[/C][C]0.0994961[/C][/ROW]
[ROW][C]245[/C][C]0.911951[/C][C]0.176098[/C][C]0.0880491[/C][/ROW]
[ROW][C]246[/C][C]0.881899[/C][C]0.236201[/C][C]0.118101[/C][/ROW]
[ROW][C]247[/C][C]0.85028[/C][C]0.299439[/C][C]0.14972[/C][/ROW]
[ROW][C]248[/C][C]0.797782[/C][C]0.404435[/C][C]0.202218[/C][/ROW]
[ROW][C]249[/C][C]0.736074[/C][C]0.527851[/C][C]0.263926[/C][/ROW]
[ROW][C]250[/C][C]0.663768[/C][C]0.672463[/C][C]0.336232[/C][/ROW]
[ROW][C]251[/C][C]0.579095[/C][C]0.84181[/C][C]0.420905[/C][/ROW]
[ROW][C]252[/C][C]0.503723[/C][C]0.992554[/C][C]0.496277[/C][/ROW]
[ROW][C]253[/C][C]0.408951[/C][C]0.817902[/C][C]0.591049[/C][/ROW]
[ROW][C]254[/C][C]0.431788[/C][C]0.863575[/C][C]0.568212[/C][/ROW]
[ROW][C]255[/C][C]0.429446[/C][C]0.858893[/C][C]0.570554[/C][/ROW]
[ROW][C]256[/C][C]0.351691[/C][C]0.703382[/C][C]0.648309[/C][/ROW]
[ROW][C]257[/C][C]0.376725[/C][C]0.753449[/C][C]0.623275[/C][/ROW]
[ROW][C]258[/C][C]0.957421[/C][C]0.0851586[/C][C]0.0425793[/C][/ROW]
[ROW][C]259[/C][C]0.900837[/C][C]0.198325[/C][C]0.0991627[/C][/ROW]
[ROW][C]260[/C][C]0.792598[/C][C]0.414805[/C][C]0.207402[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
190.2239840.4479680.776016
200.162220.324440.83778
210.08369660.1673930.916303
220.08550240.1710050.914498
230.06194280.1238860.938057
240.04462380.08924750.955376
250.02349320.04698640.976507
260.01565130.03130260.984349
270.007891760.01578350.992108
280.003693510.007387020.996306
290.003496890.006993780.996503
300.002081720.004163440.997918
310.003401190.006802370.996599
320.001983830.003967670.998016
330.004417920.008835850.995582
340.02094860.04189720.979051
350.01536980.03073960.98463
360.01053930.02107870.989461
370.0152060.0304120.984794
380.02064360.04128720.979356
390.02379070.04758140.976209
400.01624780.03249550.983752
410.02386220.04772440.976138
420.01959830.03919670.980402
430.01523630.03047250.984764
440.01718660.03437320.982813
450.01231950.02463910.98768
460.01051290.02102570.989487
470.008629580.01725920.99137
480.00679890.01359780.993201
490.01080010.02160020.9892
500.01780070.03560150.982199
510.01406590.02813190.985934
520.01405150.0281030.985948
530.0110050.02201010.988995
540.01317730.02635460.986823
550.02616030.05232070.97384
560.02241050.04482090.97759
570.06854870.1370970.931451
580.06425390.1285080.935746
590.05263920.1052780.947361
600.04980560.09961110.950194
610.06963360.1392670.930366
620.05953090.1190620.940469
630.1120280.2240550.887972
640.1277480.2554960.872252
650.144310.2886190.85569
660.1281840.2563690.871816
670.1282910.2565820.871709
680.1516410.3032810.848359
690.1714680.3429360.828532
700.1507010.3014030.849299
710.1381070.2762130.861893
720.1221010.2442010.877899
730.1167780.2335570.883222
740.1631630.3263260.836837
750.1401080.2802160.859892
760.1213280.2426560.878672
770.1098560.2197120.890144
780.1032920.2065850.896708
790.08605710.1721140.913943
800.09874080.1974820.901259
810.08475020.16950.91525
820.09656020.193120.90344
830.08456460.1691290.915435
840.1666550.3333110.833345
850.1644980.3289950.835502
860.1470970.2941950.852903
870.132680.265360.86732
880.1367170.2734350.863283
890.1395950.2791890.860405
900.1522120.3044230.847788
910.153540.3070790.84646
920.2807490.5614990.719251
930.2857570.5715140.714243
940.2781180.5562360.721882
950.2737880.5475750.726212
960.2580180.5160370.741982
970.3399720.6799440.660028
980.315910.6318190.68409
990.3315860.6631720.668414
1000.3914660.7829320.608534
1010.3674270.7348540.632573
1020.3722450.7444910.627755
1030.3911890.7823780.608811
1040.4116790.8233570.588321
1050.4287730.8575450.571227
1060.4412870.8825730.558713
1070.5031160.9937670.496884
1080.7497180.5005640.250282
1090.7897890.4204220.210211
1100.7883630.4232750.211637
1110.7885320.4229370.211468
1120.8005170.3989660.199483
1130.8865440.2269120.113456
1140.8984070.2031850.101593
1150.9483520.1032970.0516483
1160.9698650.060270.030135
1170.9708770.05824690.0291235
1180.9743490.05130270.0256514
1190.9802720.03945690.0197284
1200.9853730.0292550.0146275
1210.98820.02360090.0118005
1220.9926890.01462270.00731137
1230.9960730.00785330.00392665
1240.99830.003399330.00169966
1250.9985250.002949980.00147499
1260.9983190.003361860.00168093
1270.9987370.002526690.00126334
1280.9985080.002984840.00149242
1290.9992670.001465270.000732633
1300.9992950.00140960.000704799
1310.9992270.001545560.000772779
1320.999110.001779090.000889544
1330.9989790.00204280.0010214
1340.9991330.001733260.000866628
1350.9988960.00220760.0011038
1360.998720.002559670.00127983
1370.999130.001739410.000869704
1380.9990390.001921850.000960925
1390.9992870.001425720.000712862
1400.9990840.001832990.000916497
1410.9987710.002457860.00122893
1420.9991750.001649510.000824754
1430.9991850.001630770.000815385
1440.9994020.001196450.000598226
1450.9993010.001398620.000699309
1460.9992740.001452690.000726345
1470.9990680.001863320.000931659
1480.998820.002360810.0011804
1490.9987830.002434710.00121735
1500.998790.002419070.00120953
1510.9994580.001083210.000541605
1520.9992950.001409910.000704957
1530.9994840.001031340.000515672
1540.9994780.001044940.000522468
1550.9994680.001063470.000531733
1560.9992810.001437690.000718847
1570.9991650.001669210.000834606
1580.9990660.001867960.000933979
1590.9989120.002175830.00108792
1600.9987390.002521480.00126074
1610.9988240.002352240.00117612
1620.9988350.00232960.0011648
1630.9989930.002014370.00100719
1640.9998290.0003425090.000171255
1650.9997980.000403670.000201835
1660.9997580.0004844010.0002422
1670.9998010.0003987620.000199381
1680.9998240.0003513350.000175667
1690.9997610.0004789030.000239452
1700.9997470.0005050280.000252514
1710.9997250.0005500090.000275004
1720.9998040.0003916880.000195844
1730.9997920.0004166690.000208334
1740.9997030.0005931510.000296576
1750.999590.0008193170.000409659
1760.9996910.0006176780.000308839
1770.99960.000799880.00039994
1780.9998480.0003042480.000152124
1790.9997930.0004140440.000207022
1800.9998050.0003898920.000194946
1810.9997810.0004384680.000219234
1820.9996890.0006212990.00031065
1830.9996160.0007672380.000383619
1840.9995450.0009109470.000455474
1850.9994310.001137860.000568929
1860.9992870.00142570.000712849
1870.999560.0008805880.000440294
1880.9994170.001165460.000582731
1890.9991910.001617510.000808757
1900.9989910.002017910.00100896
1910.9986270.002745330.00137266
1920.9983750.003250230.00162512
1930.9986940.002611180.00130559
1940.9994530.001093420.000546708
1950.999290.001419540.000709769
1960.999070.001859520.000929761
1970.9988550.002289380.00114469
1980.9986090.002781430.00139072
1990.9988380.002323090.00116155
2000.9987850.002430840.00121542
2010.9983140.003371410.0016857
2020.9980970.00380640.0019032
2030.997530.004939370.00246969
2040.99690.006200530.00310026
2050.9959960.008008310.00400415
2060.9951690.009661980.00483099
2070.9935830.01283490.00641746
2080.9918440.01631180.0081559
2090.9918280.01634470.00817236
2100.9899060.02018760.0100938
2110.9863750.027250.013625
2120.9822230.03555410.017777
2130.9817090.03658130.0182906
2140.9816630.03667380.0183369
2150.9801910.03961710.0198085
2160.9736330.05273370.0263668
2170.9710310.05793710.0289686
2180.9656990.06860150.0343007
2190.9554990.08900170.0445009
2200.9448660.1102690.0551343
2210.9533970.09320540.0466027
2220.9546180.09076340.0453817
2230.9424680.1150640.0575321
2240.9497620.1004760.0502382
2250.9410890.1178220.058911
2260.9644820.0710360.035518
2270.9696610.06067840.0303392
2280.9660180.0679630.0339815
2290.9562390.08752230.0437611
2300.9645370.07092690.0354635
2310.976370.04726030.0236302
2320.9680150.06397080.0319854
2330.9564580.08708330.0435417
2340.9493240.1013520.0506759
2350.9338460.1323080.0661542
2360.9869150.0261710.0130855
2370.9878710.0242570.0121285
2380.9825580.0348840.017442
2390.975930.048140.02407
2400.9648550.07029040.0351452
2410.9578630.08427350.0421367
2420.9403770.1192470.0596233
2430.9224060.1551880.0775939
2440.9005040.1989920.0994961
2450.9119510.1760980.0880491
2460.8818990.2362010.118101
2470.850280.2994390.14972
2480.7977820.4044350.202218
2490.7360740.5278510.263926
2500.6637680.6724630.336232
2510.5790950.841810.420905
2520.5037230.9925540.496277
2530.4089510.8179020.591049
2540.4317880.8635750.568212
2550.4294460.8588930.570554
2560.3516910.7033820.648309
2570.3767250.7534490.623275
2580.9574210.08515860.0425793
2590.9008370.1983250.0991627
2600.7925980.4148050.207402






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level900.371901NOK
5% type I error level1330.549587NOK
10% type I error level1550.640496NOK

\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 & 90 & 0.371901 & NOK \tabularnewline
5% type I error level & 133 & 0.549587 & NOK \tabularnewline
10% type I error level & 155 & 0.640496 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265260&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]90[/C][C]0.371901[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]133[/C][C]0.549587[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]155[/C][C]0.640496[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265260&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265260&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level900.371901NOK
5% type I error level1330.549587NOK
10% type I error level1550.640496NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 14 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 14 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}