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Author

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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Mon, 15 Dec 2014 23:02:43 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418684738xvsv0kqp6bh67cm.htm/, Retrieved Thu, 16 May 2024 08:42:18 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=269098, Retrieved Thu, 16 May 2024 08:42:18 +0000

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Estimated Impact

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

-       [Multiple Regression] [] [2014-12-15 23:02:43] [37e054ac358b2aa7c2a1d0b751dfa890] [Current]

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 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 & 13 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&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]13 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=269098&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	13 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.25881 + 0.70396YearN[t] -0.681224GroupN[t] + 0.672392gender[t] + 0.0588095AMS.I1[t] -0.0577708AMS.I2[t] -0.0257743AMS.I3[t] -0.0590307AMS.E1[t] + 0.0242987AMS.E2[t] -0.0354835AMS.E3[t] -0.0582734AMS.A[t] + 0.041479NUMERACYTOT[t] + 0.027742LFM[t] + 0.0327447CH[t] -0.00914513Gender_LFM[t] -0.00369178Group_LFM[t] + 0.0306051Year_LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.25881 +  0.70396YearN[t] -0.681224GroupN[t] +  0.672392gender[t] +  0.0588095AMS.I1[t] -0.0577708AMS.I2[t] -0.0257743AMS.I3[t] -0.0590307AMS.E1[t] +  0.0242987AMS.E2[t] -0.0354835AMS.E3[t] -0.0582734AMS.A[t] +  0.041479NUMERACYTOT[t] +  0.027742LFM[t] +  0.0327447CH[t] -0.00914513Gender_LFM[t] -0.00369178Group_LFM[t] +  0.0306051Year_LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.25881 +  0.70396YearN[t] -0.681224GroupN[t] +  0.672392gender[t] +  0.0588095AMS.I1[t] -0.0577708AMS.I2[t] -0.0257743AMS.I3[t] -0.0590307AMS.E1[t] +  0.0242987AMS.E2[t] -0.0354835AMS.E3[t] -0.0582734AMS.A[t] +  0.041479NUMERACYTOT[t] +  0.027742LFM[t] +  0.0327447CH[t] -0.00914513Gender_LFM[t] -0.00369178Group_LFM[t] +  0.0306051Year_LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.25881 + 0.70396YearN[t] -0.681224GroupN[t] + 0.672392gender[t] + 0.0588095AMS.I1[t] -0.0577708AMS.I2[t] -0.0257743AMS.I3[t] -0.0590307AMS.E1[t] + 0.0242987AMS.E2[t] -0.0354835AMS.E3[t] -0.0582734AMS.A[t] + 0.041479NUMERACYTOT[t] + 0.027742LFM[t] + 0.0327447CH[t] -0.00914513Gender_LFM[t] -0.00369178Group_LFM[t] + 0.0306051Year_LFM[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	8.25881	2.02184	4.085	5.87315e-05	2.93658e-05
YearN	0.70396	0.912044	0.7718	0.440902	0.220451
GroupN	-0.681224	1.02434	-0.665	0.506614	0.253307
gender	0.672392	0.904808	0.7431	0.45807	0.229035
AMS.I1	0.0588095	0.0557988	1.054	0.292877	0.146439
AMS.I2	-0.0577708	0.0495729	-1.165	0.244933	0.122466
AMS.I3	-0.0257743	0.0419285	-0.6147	0.539276	0.269638
AMS.E1	-0.0590307	0.057773	-1.022	0.307836	0.153918
AMS.E2	0.0242987	0.0395321	0.6147	0.539316	0.269658
AMS.E3	-0.0354835	0.0476136	-0.7452	0.456798	0.228399
AMS.A	-0.0582734	0.0481585	-1.21	0.22736	0.11368
NUMERACYTOT	0.041479	0.0273771	1.515	0.130957	0.0654787
LFM	0.027742	0.0102679	2.702	0.00734811	0.00367406
CH	0.0327447	0.00811871	4.033	7.22807e-05	3.61404e-05
Gender_LFM	-0.00914513	0.00722934	-1.265	0.206999	0.103499
Group_LFM	-0.00369178	0.00894344	-0.4128	0.680098	0.340049
Year_LFM	0.0306051	0.00725058	4.221	3.35956e-05	1.67978e-05

\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) & 8.25881 & 2.02184 & 4.085 & 5.87315e-05 & 2.93658e-05 \tabularnewline
YearN & 0.70396 & 0.912044 & 0.7718 & 0.440902 & 0.220451 \tabularnewline
GroupN & -0.681224 & 1.02434 & -0.665 & 0.506614 & 0.253307 \tabularnewline
gender & 0.672392 & 0.904808 & 0.7431 & 0.45807 & 0.229035 \tabularnewline
AMS.I1 & 0.0588095 & 0.0557988 & 1.054 & 0.292877 & 0.146439 \tabularnewline
AMS.I2 & -0.0577708 & 0.0495729 & -1.165 & 0.244933 & 0.122466 \tabularnewline
AMS.I3 & -0.0257743 & 0.0419285 & -0.6147 & 0.539276 & 0.269638 \tabularnewline
AMS.E1 & -0.0590307 & 0.057773 & -1.022 & 0.307836 & 0.153918 \tabularnewline
AMS.E2 & 0.0242987 & 0.0395321 & 0.6147 & 0.539316 & 0.269658 \tabularnewline
AMS.E3 & -0.0354835 & 0.0476136 & -0.7452 & 0.456798 & 0.228399 \tabularnewline
AMS.A & -0.0582734 & 0.0481585 & -1.21 & 0.22736 & 0.11368 \tabularnewline
NUMERACYTOT & 0.041479 & 0.0273771 & 1.515 & 0.130957 & 0.0654787 \tabularnewline
LFM & 0.027742 & 0.0102679 & 2.702 & 0.00734811 & 0.00367406 \tabularnewline
CH & 0.0327447 & 0.00811871 & 4.033 & 7.22807e-05 & 3.61404e-05 \tabularnewline
Gender_LFM & -0.00914513 & 0.00722934 & -1.265 & 0.206999 & 0.103499 \tabularnewline
Group_LFM & -0.00369178 & 0.00894344 & -0.4128 & 0.680098 & 0.340049 \tabularnewline
Year_LFM & 0.0306051 & 0.00725058 & 4.221 & 3.35956e-05 & 1.67978e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&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]8.25881[/C][C]2.02184[/C][C]4.085[/C][C]5.87315e-05[/C][C]2.93658e-05[/C][/ROW]
[ROW][C]YearN[/C][C]0.70396[/C][C]0.912044[/C][C]0.7718[/C][C]0.440902[/C][C]0.220451[/C][/ROW]
[ROW][C]GroupN[/C][C]-0.681224[/C][C]1.02434[/C][C]-0.665[/C][C]0.506614[/C][C]0.253307[/C][/ROW]
[ROW][C]gender[/C][C]0.672392[/C][C]0.904808[/C][C]0.7431[/C][C]0.45807[/C][C]0.229035[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0588095[/C][C]0.0557988[/C][C]1.054[/C][C]0.292877[/C][C]0.146439[/C][/ROW]
[ROW][C]AMS.I2[/C][C]-0.0577708[/C][C]0.0495729[/C][C]-1.165[/C][C]0.244933[/C][C]0.122466[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0257743[/C][C]0.0419285[/C][C]-0.6147[/C][C]0.539276[/C][C]0.269638[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0590307[/C][C]0.057773[/C][C]-1.022[/C][C]0.307836[/C][C]0.153918[/C][/ROW]
[ROW][C]AMS.E2[/C][C]0.0242987[/C][C]0.0395321[/C][C]0.6147[/C][C]0.539316[/C][C]0.269658[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0354835[/C][C]0.0476136[/C][C]-0.7452[/C][C]0.456798[/C][C]0.228399[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0582734[/C][C]0.0481585[/C][C]-1.21[/C][C]0.22736[/C][C]0.11368[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.041479[/C][C]0.0273771[/C][C]1.515[/C][C]0.130957[/C][C]0.0654787[/C][/ROW]
[ROW][C]LFM[/C][C]0.027742[/C][C]0.0102679[/C][C]2.702[/C][C]0.00734811[/C][C]0.00367406[/C][/ROW]
[ROW][C]CH[/C][C]0.0327447[/C][C]0.00811871[/C][C]4.033[/C][C]7.22807e-05[/C][C]3.61404e-05[/C][/ROW]
[ROW][C]Gender_LFM[/C][C]-0.00914513[/C][C]0.00722934[/C][C]-1.265[/C][C]0.206999[/C][C]0.103499[/C][/ROW]
[ROW][C]Group_LFM[/C][C]-0.00369178[/C][C]0.00894344[/C][C]-0.4128[/C][C]0.680098[/C][C]0.340049[/C][/ROW]
[ROW][C]Year_LFM[/C][C]0.0306051[/C][C]0.00725058[/C][C]4.221[/C][C]3.35956e-05[/C][C]1.67978e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	8.25881	2.02184	4.085	5.87315e-05	2.93658e-05
YearN	0.70396	0.912044	0.7718	0.440902	0.220451
GroupN	-0.681224	1.02434	-0.665	0.506614	0.253307
gender	0.672392	0.904808	0.7431	0.45807	0.229035
AMS.I1	0.0588095	0.0557988	1.054	0.292877	0.146439
AMS.I2	-0.0577708	0.0495729	-1.165	0.244933	0.122466
AMS.I3	-0.0257743	0.0419285	-0.6147	0.539276	0.269638
AMS.E1	-0.0590307	0.057773	-1.022	0.307836	0.153918
AMS.E2	0.0242987	0.0395321	0.6147	0.539316	0.269658
AMS.E3	-0.0354835	0.0476136	-0.7452	0.456798	0.228399
AMS.A	-0.0582734	0.0481585	-1.21	0.22736	0.11368
NUMERACYTOT	0.041479	0.0273771	1.515	0.130957	0.0654787
LFM	0.027742	0.0102679	2.702	0.00734811	0.00367406
CH	0.0327447	0.00811871	4.033	7.22807e-05	3.61404e-05
Gender_LFM	-0.00914513	0.00722934	-1.265	0.206999	0.103499
Group_LFM	-0.00369178	0.00894344	-0.4128	0.680098	0.340049
Year_LFM	0.0306051	0.00725058	4.221	3.35956e-05	1.67978e-05

Multiple Linear Regression - Regression Statistics
Multiple R	0.771273
R-squared	0.594863
Adjusted R-squared	0.570027
F-TEST (value)	23.9516
F-TEST (DF numerator)	16
F-TEST (DF denominator)	261
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.22576
Sum Squared Residuals	1293

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.771273 \tabularnewline
R-squared & 0.594863 \tabularnewline
Adjusted R-squared & 0.570027 \tabularnewline
F-TEST (value) & 23.9516 \tabularnewline
F-TEST (DF numerator) & 16 \tabularnewline
F-TEST (DF denominator) & 261 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.22576 \tabularnewline
Sum Squared Residuals & 1293 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.771273[/C][/ROW]
[ROW][C]R-squared[/C][C]0.594863[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.570027[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]23.9516[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]16[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]261[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.22576[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1293[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.771273
R-squared	0.594863
Adjusted R-squared	0.570027
F-TEST (value)	23.9516
F-TEST (DF numerator)	16
F-TEST (DF denominator)	261
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.22576
Sum Squared Residuals	1293

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.5494	0.350642
2	12.2	10.2944	1.90562
3	12.8	11.2246	1.57544
4	7.4	11.1411	-3.74109
5	6.7	10.1411	-3.44108
6	12.6	11.055	1.545
7	14.8	11.5558	3.24417
8	13.3	11.3016	1.99843
9	11.1	11.0878	0.0121734
10	8.2	11.1099	-2.90985
11	11.4	10.7291	0.670895
12	6.4	11.2066	-4.8066
13	10.6	9.05584	1.54416
14	12	12.983	-0.982955
15	6.3	7.62841	-1.32841
16	11.3	9.71733	1.58267
17	11.9	11.5282	0.37176
18	9.3	10.1684	-0.868385
19	9.6	11.6941	-2.0941
20	10	9.73935	0.260651
21	6.4	9.20602	-2.80602
22	13.8	10.1427	3.65732
23	10.8	12.8421	-2.04212
24	13.8	11.7195	2.08049
25	11.7	10.8164	0.883648
26	10.9	12.5965	-1.69651
27	16.1	13.1288	2.97116
28	13.4	10.8544	2.54556
29	9.9	11.1868	-1.28678
30	11.5	10.9863	0.513748
31	8.3	9.39914	-1.09914
32	11.7	11.0687	0.631252
33	9	9.61351	-0.613509
34	9.7	11.5715	-1.8715
35	10.8	9.59527	1.20473
36	10.3	9.14412	1.15588
37	10.4	11.0229	-0.622938
38	12.7	10.4353	2.26465
39	9.3	10.982	-1.68202
40	11.8	12.1661	-0.366092
41	5.9	10.0603	-4.16026
42	11.4	10.748	0.651963
43	13	11.2508	1.74916
44	10.8	11.5952	-0.79517
45	12.3	9.78439	2.51561
46	11.3	12.2718	-0.971828
47	11.8	10.067	1.73305
48	7.9	10.1771	-2.27709
49	12.7	10.1234	2.57663
50	12.3	9.69135	2.60865
51	11.6	10.7005	0.89946
52	6.7	9.18634	-2.48634
53	10.9	9.98279	0.917209
54	12.1	10.7652	1.3348
55	13.3	10.3495	2.95052
56	10.1	10.3518	-0.25177
57	5.7	10.8011	-5.10108
58	14.3	9.6921	4.6079
59	8	8.45209	-0.452089
60	13.3	11.3404	1.9596
61	9.3	12.214	-2.91399
62	12.5	10.5188	1.98117
63	7.6	9.1502	-1.5502
64	15.9	12.2909	3.60912
65	9.2	11.53	-2.32998
66	9.1	9.66672	-0.566724
67	11.1	11.9924	-0.892362
68	13	13.3446	-0.344595
69	14.5	10.6516	3.84836
70	12.2	11.0368	1.1632
71	12.3	12.5189	-0.218906
72	11.4	10.5457	0.85431
73	8.8	10.2856	-1.48556
74	14.6	11.4852	3.11481
75	12.6	11.1174	1.48261
76	13	11.4705	1.52949
77	12.6	11.0458	1.55418
78	13.2	12.0202	1.17978
79	9.9	9.5544	0.345598
80	7.7	10.2413	-2.54134
81	10.5	10.8889	-0.388925
82	13.4	10.6947	2.70531
83	10.9	10.6244	0.275613
84	4.3	9.86916	-5.56916
85	10.3	11.5019	-1.20186
86	11.8	11.5688	0.231227
87	11.2	9.96839	1.23161
88	11.4	9.22137	2.17863
89	8.6	10.3167	-1.71668
90	13.2	11.4048	1.79523
91	12.6	9.89585	2.70415
92	5.6	10.4931	-4.89313
93	9.9	11.6931	-1.79314
94	8.8	9.87568	-1.07568
95	7.7	9.81258	-2.11258
96	9	10.6481	-1.64808
97	7.3	11.0384	-3.73838
98	11.4	9.73636	1.66364
99	13.6	9.92262	3.67738
100	7.9	10.6024	-2.70241
101	10.7	9.84929	0.850711
102	10.3	10.1904	0.109629
103	8.3	9.90129	-1.60129
104	9.6	10.9833	-1.3833
105	14.2	10.7069	3.49313
106	8.5	10.2902	-1.79017
107	13.5	10.1414	3.35859
108	4.9	10.2318	-5.33176
109	6.4	8.86785	-2.46785
110	9.6	10.8718	-1.27177
111	11.6	10.7743	0.825658
112	11.1	10.0532	1.04685
113	4.35	10.4525	-6.10247
114	12.7	11.0322	1.66776
115	18.1	15.4459	2.65412
116	17.85	15.5773	2.27272
117	16.6	18.0709	-1.47094
118	12.6	11.7389	0.861128
119	17.1	18.8613	-1.76132
120	19.1	17.7824	1.3176
121	16.1	19.2257	-3.1257
122	13.35	11.0288	2.32124
123	18.4	16.851	1.54904
124	14.7	9.79247	4.90753
125	10.6	12.7651	-2.16511
126	12.6	13.0252	-0.425197
127	16.2	14.8134	1.38656
128	13.6	14.0183	-0.418295
129	18.9	16.6843	2.21574
130	14.1	13.305	0.795017
131	14.5	13.5365	0.963495
132	16.15	18.1707	-2.02073
133	14.75	13.8124	0.93757
134	14.8	13.7172	1.08279
135	12.45	12.4141	0.0358868
136	12.65	12.8075	-0.157543
137	17.35	14.3179	3.03209
138	8.6	10.0058	-1.40581
139	18.4	17.2512	1.14881
140	16.1	15.3252	0.774801
141	11.6	11.886	-0.285961
142	17.75	15.3557	2.39427
143	15.25	15.4217	-0.171679
144	17.65	14.2588	3.39116
145	16.35	17.0315	-0.681505
146	17.65	17.3584	0.29162
147	13.6	14.0452	-0.44525
148	14.35	14.5522	-0.202153
149	14.75	15.5713	-0.821309
150	18.25	16.304	1.94603
151	9.9	16.6487	-6.74873
152	16	15.2703	0.72969
153	18.25	16.0304	2.21958
154	16.85	17.9946	-1.14463
155	14.6	11.9349	2.66512
156	13.85	14.6834	-0.833441
157	18.95	18.2274	0.722559
158	15.6	14.6737	0.926343
159	14.85	16.7799	-1.92992
160	11.75	13.7519	-2.00188
161	18.45	17.0856	1.36444
162	15.9	13.8191	2.08095
163	17.1	18.7316	-1.63157
164	16.1	9.02109	7.07891
165	19.9	19.7019	0.198104
166	10.95	10.1498	0.800156
167	18.45	17.2641	1.18591
168	15.1	13.4061	1.69387
169	15	14.7712	0.228761
170	11.35	13.6324	-2.28244
171	15.95	14.7939	1.15613
172	18.1	15.7585	2.34146
173	14.6	17.0147	-2.41467
174	15.4	16.2653	-0.865302
175	15.4	16.3084	-0.908406
176	17.6	15.2621	2.33794
177	13.35	15.0444	-1.69438
178	19.1	17.2465	1.85352
179	15.35	16.9472	-1.59718
180	7.6	10.2311	-2.63114
181	13.4	15.2114	-1.81142
182	13.9	16.2634	-2.36339
183	19.1	17.0734	2.02655
184	15.25	15.1458	0.10419
185	12.9	16.1332	-3.23322
186	16.1	15.7577	0.342314
187	17.35	14.3079	3.0421
188	13.15	15.1292	-1.97923
189	12.15	13.7864	-1.63636
190	12.6	11.978	0.621987
191	10.35	12.6942	-2.34418
192	15.4	14.4246	0.975377
193	9.6	12.1603	-2.56027
194	18.2	14.9256	3.27439
195	13.6	13.4622	0.137828
196	14.85	13.3196	1.53039
197	14.75	17.5401	-2.79009
198	14.1	13.351	0.748977
199	14.9	12.392	2.50803
200	16.25	15.1695	1.08055
201	19.25	18.5449	0.705125
202	13.6	12.7895	0.810549
203	13.6	15.7866	-2.1866
204	15.65	15.4475	0.202548
205	12.75	12.9963	-0.246289
206	14.6	12.582	2.01797
207	9.85	10.8264	-0.976362
208	12.65	12.3617	0.288268
209	19.2	17.2989	1.90108
210	16.6	14.7372	1.86276
211	11.2	11.5461	-0.346085
212	15.25	15.5573	-0.307285
213	11.9	14.4894	-2.58942
214	13.2	12.6835	0.516463
215	16.35	17.7992	-1.44922
216	12.4	12.6808	-0.280751
217	15.85	14.4813	1.36871
218	18.15	16.8065	1.3435
219	11.15	12.7335	-1.58351
220	15.65	16.3074	-0.657375
221	17.75	15.3733	2.37673
222	7.65	10.3044	-2.65436
223	12.35	13.4933	-1.14333
224	15.6	13.8457	1.75431
225	19.3	17.2979	2.00209
226	15.2	11.1986	4.00137
227	17.1	14.895	2.20496
228	15.6	13.3694	2.23058
229	18.4	15.638	2.76205
230	19.05	16.3196	2.73042
231	18.55	15.8957	2.6543
232	19.1	17.9366	1.16345
233	13.1	13.4627	-0.362694
234	12.85	15.8947	-3.04469
235	9.5	12.2784	-2.77838
236	4.5	10.5779	-6.07793
237	11.85	10.7626	1.0874
238	13.6	15.2232	-1.62318
239	11.7	12.0402	-0.340196
240	12.4	12.7722	-0.372174
241	13.35	14.8812	-1.53118
242	11.4	12.2296	-0.829628
243	14.9	14.2516	0.648371
244	19.9	19.4141	0.485857
245	11.2	13.3862	-2.18623
246	14.6	15.4737	-0.873704
247	17.6	18.0191	-0.419131
248	14.05	13.3383	0.711678
249	16.1	15.5834	0.516568
250	13.35	14.4131	-1.0631
251	11.85	14.4582	-2.60823
252	11.95	13.1327	-1.18275
253	14.75	14.2912	0.458809
254	15.15	13.3668	1.78319
255	13.2	16.0283	-2.82833
256	16.85	16.1942	0.655821
257	7.85	11.8841	-4.03414
258	7.7	12.2969	-4.59686
259	12.6	15.0496	-2.44957
260	7.85	14.8561	-7.00613
261	10.95	11.2711	-0.321088
262	12.35	14.0837	-1.73366
263	9.95	12.9192	-2.96919
264	14.9	14.1186	0.781353
265	16.65	14.631	2.01901
266	13.4	12.7191	0.680877
267	13.95	13.3766	0.57342
268	15.7	14.4129	1.28706
269	16.85	15.5024	1.34755
270	10.95	11.9396	-0.989573
271	15.35	14.3933	0.956736
272	12.2	12.5782	-0.378178
273	15.1	14.0057	1.09434
274	17.75	16.4037	1.34634
275	15.2	15.1968	0.00319622
276	14.6	14.5027	0.0972613
277	16.65	15.7232	0.926814
278	8.1	10.2987	-2.19866

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.5494 & 0.350642 \tabularnewline
2 & 12.2 & 10.2944 & 1.90562 \tabularnewline
3 & 12.8 & 11.2246 & 1.57544 \tabularnewline
4 & 7.4 & 11.1411 & -3.74109 \tabularnewline
5 & 6.7 & 10.1411 & -3.44108 \tabularnewline
6 & 12.6 & 11.055 & 1.545 \tabularnewline
7 & 14.8 & 11.5558 & 3.24417 \tabularnewline
8 & 13.3 & 11.3016 & 1.99843 \tabularnewline
9 & 11.1 & 11.0878 & 0.0121734 \tabularnewline
10 & 8.2 & 11.1099 & -2.90985 \tabularnewline
11 & 11.4 & 10.7291 & 0.670895 \tabularnewline
12 & 6.4 & 11.2066 & -4.8066 \tabularnewline
13 & 10.6 & 9.05584 & 1.54416 \tabularnewline
14 & 12 & 12.983 & -0.982955 \tabularnewline
15 & 6.3 & 7.62841 & -1.32841 \tabularnewline
16 & 11.3 & 9.71733 & 1.58267 \tabularnewline
17 & 11.9 & 11.5282 & 0.37176 \tabularnewline
18 & 9.3 & 10.1684 & -0.868385 \tabularnewline
19 & 9.6 & 11.6941 & -2.0941 \tabularnewline
20 & 10 & 9.73935 & 0.260651 \tabularnewline
21 & 6.4 & 9.20602 & -2.80602 \tabularnewline
22 & 13.8 & 10.1427 & 3.65732 \tabularnewline
23 & 10.8 & 12.8421 & -2.04212 \tabularnewline
24 & 13.8 & 11.7195 & 2.08049 \tabularnewline
25 & 11.7 & 10.8164 & 0.883648 \tabularnewline
26 & 10.9 & 12.5965 & -1.69651 \tabularnewline
27 & 16.1 & 13.1288 & 2.97116 \tabularnewline
28 & 13.4 & 10.8544 & 2.54556 \tabularnewline
29 & 9.9 & 11.1868 & -1.28678 \tabularnewline
30 & 11.5 & 10.9863 & 0.513748 \tabularnewline
31 & 8.3 & 9.39914 & -1.09914 \tabularnewline
32 & 11.7 & 11.0687 & 0.631252 \tabularnewline
33 & 9 & 9.61351 & -0.613509 \tabularnewline
34 & 9.7 & 11.5715 & -1.8715 \tabularnewline
35 & 10.8 & 9.59527 & 1.20473 \tabularnewline
36 & 10.3 & 9.14412 & 1.15588 \tabularnewline
37 & 10.4 & 11.0229 & -0.622938 \tabularnewline
38 & 12.7 & 10.4353 & 2.26465 \tabularnewline
39 & 9.3 & 10.982 & -1.68202 \tabularnewline
40 & 11.8 & 12.1661 & -0.366092 \tabularnewline
41 & 5.9 & 10.0603 & -4.16026 \tabularnewline
42 & 11.4 & 10.748 & 0.651963 \tabularnewline
43 & 13 & 11.2508 & 1.74916 \tabularnewline
44 & 10.8 & 11.5952 & -0.79517 \tabularnewline
45 & 12.3 & 9.78439 & 2.51561 \tabularnewline
46 & 11.3 & 12.2718 & -0.971828 \tabularnewline
47 & 11.8 & 10.067 & 1.73305 \tabularnewline
48 & 7.9 & 10.1771 & -2.27709 \tabularnewline
49 & 12.7 & 10.1234 & 2.57663 \tabularnewline
50 & 12.3 & 9.69135 & 2.60865 \tabularnewline
51 & 11.6 & 10.7005 & 0.89946 \tabularnewline
52 & 6.7 & 9.18634 & -2.48634 \tabularnewline
53 & 10.9 & 9.98279 & 0.917209 \tabularnewline
54 & 12.1 & 10.7652 & 1.3348 \tabularnewline
55 & 13.3 & 10.3495 & 2.95052 \tabularnewline
56 & 10.1 & 10.3518 & -0.25177 \tabularnewline
57 & 5.7 & 10.8011 & -5.10108 \tabularnewline
58 & 14.3 & 9.6921 & 4.6079 \tabularnewline
59 & 8 & 8.45209 & -0.452089 \tabularnewline
60 & 13.3 & 11.3404 & 1.9596 \tabularnewline
61 & 9.3 & 12.214 & -2.91399 \tabularnewline
62 & 12.5 & 10.5188 & 1.98117 \tabularnewline
63 & 7.6 & 9.1502 & -1.5502 \tabularnewline
64 & 15.9 & 12.2909 & 3.60912 \tabularnewline
65 & 9.2 & 11.53 & -2.32998 \tabularnewline
66 & 9.1 & 9.66672 & -0.566724 \tabularnewline
67 & 11.1 & 11.9924 & -0.892362 \tabularnewline
68 & 13 & 13.3446 & -0.344595 \tabularnewline
69 & 14.5 & 10.6516 & 3.84836 \tabularnewline
70 & 12.2 & 11.0368 & 1.1632 \tabularnewline
71 & 12.3 & 12.5189 & -0.218906 \tabularnewline
72 & 11.4 & 10.5457 & 0.85431 \tabularnewline
73 & 8.8 & 10.2856 & -1.48556 \tabularnewline
74 & 14.6 & 11.4852 & 3.11481 \tabularnewline
75 & 12.6 & 11.1174 & 1.48261 \tabularnewline
76 & 13 & 11.4705 & 1.52949 \tabularnewline
77 & 12.6 & 11.0458 & 1.55418 \tabularnewline
78 & 13.2 & 12.0202 & 1.17978 \tabularnewline
79 & 9.9 & 9.5544 & 0.345598 \tabularnewline
80 & 7.7 & 10.2413 & -2.54134 \tabularnewline
81 & 10.5 & 10.8889 & -0.388925 \tabularnewline
82 & 13.4 & 10.6947 & 2.70531 \tabularnewline
83 & 10.9 & 10.6244 & 0.275613 \tabularnewline
84 & 4.3 & 9.86916 & -5.56916 \tabularnewline
85 & 10.3 & 11.5019 & -1.20186 \tabularnewline
86 & 11.8 & 11.5688 & 0.231227 \tabularnewline
87 & 11.2 & 9.96839 & 1.23161 \tabularnewline
88 & 11.4 & 9.22137 & 2.17863 \tabularnewline
89 & 8.6 & 10.3167 & -1.71668 \tabularnewline
90 & 13.2 & 11.4048 & 1.79523 \tabularnewline
91 & 12.6 & 9.89585 & 2.70415 \tabularnewline
92 & 5.6 & 10.4931 & -4.89313 \tabularnewline
93 & 9.9 & 11.6931 & -1.79314 \tabularnewline
94 & 8.8 & 9.87568 & -1.07568 \tabularnewline
95 & 7.7 & 9.81258 & -2.11258 \tabularnewline
96 & 9 & 10.6481 & -1.64808 \tabularnewline
97 & 7.3 & 11.0384 & -3.73838 \tabularnewline
98 & 11.4 & 9.73636 & 1.66364 \tabularnewline
99 & 13.6 & 9.92262 & 3.67738 \tabularnewline
100 & 7.9 & 10.6024 & -2.70241 \tabularnewline
101 & 10.7 & 9.84929 & 0.850711 \tabularnewline
102 & 10.3 & 10.1904 & 0.109629 \tabularnewline
103 & 8.3 & 9.90129 & -1.60129 \tabularnewline
104 & 9.6 & 10.9833 & -1.3833 \tabularnewline
105 & 14.2 & 10.7069 & 3.49313 \tabularnewline
106 & 8.5 & 10.2902 & -1.79017 \tabularnewline
107 & 13.5 & 10.1414 & 3.35859 \tabularnewline
108 & 4.9 & 10.2318 & -5.33176 \tabularnewline
109 & 6.4 & 8.86785 & -2.46785 \tabularnewline
110 & 9.6 & 10.8718 & -1.27177 \tabularnewline
111 & 11.6 & 10.7743 & 0.825658 \tabularnewline
112 & 11.1 & 10.0532 & 1.04685 \tabularnewline
113 & 4.35 & 10.4525 & -6.10247 \tabularnewline
114 & 12.7 & 11.0322 & 1.66776 \tabularnewline
115 & 18.1 & 15.4459 & 2.65412 \tabularnewline
116 & 17.85 & 15.5773 & 2.27272 \tabularnewline
117 & 16.6 & 18.0709 & -1.47094 \tabularnewline
118 & 12.6 & 11.7389 & 0.861128 \tabularnewline
119 & 17.1 & 18.8613 & -1.76132 \tabularnewline
120 & 19.1 & 17.7824 & 1.3176 \tabularnewline
121 & 16.1 & 19.2257 & -3.1257 \tabularnewline
122 & 13.35 & 11.0288 & 2.32124 \tabularnewline
123 & 18.4 & 16.851 & 1.54904 \tabularnewline
124 & 14.7 & 9.79247 & 4.90753 \tabularnewline
125 & 10.6 & 12.7651 & -2.16511 \tabularnewline
126 & 12.6 & 13.0252 & -0.425197 \tabularnewline
127 & 16.2 & 14.8134 & 1.38656 \tabularnewline
128 & 13.6 & 14.0183 & -0.418295 \tabularnewline
129 & 18.9 & 16.6843 & 2.21574 \tabularnewline
130 & 14.1 & 13.305 & 0.795017 \tabularnewline
131 & 14.5 & 13.5365 & 0.963495 \tabularnewline
132 & 16.15 & 18.1707 & -2.02073 \tabularnewline
133 & 14.75 & 13.8124 & 0.93757 \tabularnewline
134 & 14.8 & 13.7172 & 1.08279 \tabularnewline
135 & 12.45 & 12.4141 & 0.0358868 \tabularnewline
136 & 12.65 & 12.8075 & -0.157543 \tabularnewline
137 & 17.35 & 14.3179 & 3.03209 \tabularnewline
138 & 8.6 & 10.0058 & -1.40581 \tabularnewline
139 & 18.4 & 17.2512 & 1.14881 \tabularnewline
140 & 16.1 & 15.3252 & 0.774801 \tabularnewline
141 & 11.6 & 11.886 & -0.285961 \tabularnewline
142 & 17.75 & 15.3557 & 2.39427 \tabularnewline
143 & 15.25 & 15.4217 & -0.171679 \tabularnewline
144 & 17.65 & 14.2588 & 3.39116 \tabularnewline
145 & 16.35 & 17.0315 & -0.681505 \tabularnewline
146 & 17.65 & 17.3584 & 0.29162 \tabularnewline
147 & 13.6 & 14.0452 & -0.44525 \tabularnewline
148 & 14.35 & 14.5522 & -0.202153 \tabularnewline
149 & 14.75 & 15.5713 & -0.821309 \tabularnewline
150 & 18.25 & 16.304 & 1.94603 \tabularnewline
151 & 9.9 & 16.6487 & -6.74873 \tabularnewline
152 & 16 & 15.2703 & 0.72969 \tabularnewline
153 & 18.25 & 16.0304 & 2.21958 \tabularnewline
154 & 16.85 & 17.9946 & -1.14463 \tabularnewline
155 & 14.6 & 11.9349 & 2.66512 \tabularnewline
156 & 13.85 & 14.6834 & -0.833441 \tabularnewline
157 & 18.95 & 18.2274 & 0.722559 \tabularnewline
158 & 15.6 & 14.6737 & 0.926343 \tabularnewline
159 & 14.85 & 16.7799 & -1.92992 \tabularnewline
160 & 11.75 & 13.7519 & -2.00188 \tabularnewline
161 & 18.45 & 17.0856 & 1.36444 \tabularnewline
162 & 15.9 & 13.8191 & 2.08095 \tabularnewline
163 & 17.1 & 18.7316 & -1.63157 \tabularnewline
164 & 16.1 & 9.02109 & 7.07891 \tabularnewline
165 & 19.9 & 19.7019 & 0.198104 \tabularnewline
166 & 10.95 & 10.1498 & 0.800156 \tabularnewline
167 & 18.45 & 17.2641 & 1.18591 \tabularnewline
168 & 15.1 & 13.4061 & 1.69387 \tabularnewline
169 & 15 & 14.7712 & 0.228761 \tabularnewline
170 & 11.35 & 13.6324 & -2.28244 \tabularnewline
171 & 15.95 & 14.7939 & 1.15613 \tabularnewline
172 & 18.1 & 15.7585 & 2.34146 \tabularnewline
173 & 14.6 & 17.0147 & -2.41467 \tabularnewline
174 & 15.4 & 16.2653 & -0.865302 \tabularnewline
175 & 15.4 & 16.3084 & -0.908406 \tabularnewline
176 & 17.6 & 15.2621 & 2.33794 \tabularnewline
177 & 13.35 & 15.0444 & -1.69438 \tabularnewline
178 & 19.1 & 17.2465 & 1.85352 \tabularnewline
179 & 15.35 & 16.9472 & -1.59718 \tabularnewline
180 & 7.6 & 10.2311 & -2.63114 \tabularnewline
181 & 13.4 & 15.2114 & -1.81142 \tabularnewline
182 & 13.9 & 16.2634 & -2.36339 \tabularnewline
183 & 19.1 & 17.0734 & 2.02655 \tabularnewline
184 & 15.25 & 15.1458 & 0.10419 \tabularnewline
185 & 12.9 & 16.1332 & -3.23322 \tabularnewline
186 & 16.1 & 15.7577 & 0.342314 \tabularnewline
187 & 17.35 & 14.3079 & 3.0421 \tabularnewline
188 & 13.15 & 15.1292 & -1.97923 \tabularnewline
189 & 12.15 & 13.7864 & -1.63636 \tabularnewline
190 & 12.6 & 11.978 & 0.621987 \tabularnewline
191 & 10.35 & 12.6942 & -2.34418 \tabularnewline
192 & 15.4 & 14.4246 & 0.975377 \tabularnewline
193 & 9.6 & 12.1603 & -2.56027 \tabularnewline
194 & 18.2 & 14.9256 & 3.27439 \tabularnewline
195 & 13.6 & 13.4622 & 0.137828 \tabularnewline
196 & 14.85 & 13.3196 & 1.53039 \tabularnewline
197 & 14.75 & 17.5401 & -2.79009 \tabularnewline
198 & 14.1 & 13.351 & 0.748977 \tabularnewline
199 & 14.9 & 12.392 & 2.50803 \tabularnewline
200 & 16.25 & 15.1695 & 1.08055 \tabularnewline
201 & 19.25 & 18.5449 & 0.705125 \tabularnewline
202 & 13.6 & 12.7895 & 0.810549 \tabularnewline
203 & 13.6 & 15.7866 & -2.1866 \tabularnewline
204 & 15.65 & 15.4475 & 0.202548 \tabularnewline
205 & 12.75 & 12.9963 & -0.246289 \tabularnewline
206 & 14.6 & 12.582 & 2.01797 \tabularnewline
207 & 9.85 & 10.8264 & -0.976362 \tabularnewline
208 & 12.65 & 12.3617 & 0.288268 \tabularnewline
209 & 19.2 & 17.2989 & 1.90108 \tabularnewline
210 & 16.6 & 14.7372 & 1.86276 \tabularnewline
211 & 11.2 & 11.5461 & -0.346085 \tabularnewline
212 & 15.25 & 15.5573 & -0.307285 \tabularnewline
213 & 11.9 & 14.4894 & -2.58942 \tabularnewline
214 & 13.2 & 12.6835 & 0.516463 \tabularnewline
215 & 16.35 & 17.7992 & -1.44922 \tabularnewline
216 & 12.4 & 12.6808 & -0.280751 \tabularnewline
217 & 15.85 & 14.4813 & 1.36871 \tabularnewline
218 & 18.15 & 16.8065 & 1.3435 \tabularnewline
219 & 11.15 & 12.7335 & -1.58351 \tabularnewline
220 & 15.65 & 16.3074 & -0.657375 \tabularnewline
221 & 17.75 & 15.3733 & 2.37673 \tabularnewline
222 & 7.65 & 10.3044 & -2.65436 \tabularnewline
223 & 12.35 & 13.4933 & -1.14333 \tabularnewline
224 & 15.6 & 13.8457 & 1.75431 \tabularnewline
225 & 19.3 & 17.2979 & 2.00209 \tabularnewline
226 & 15.2 & 11.1986 & 4.00137 \tabularnewline
227 & 17.1 & 14.895 & 2.20496 \tabularnewline
228 & 15.6 & 13.3694 & 2.23058 \tabularnewline
229 & 18.4 & 15.638 & 2.76205 \tabularnewline
230 & 19.05 & 16.3196 & 2.73042 \tabularnewline
231 & 18.55 & 15.8957 & 2.6543 \tabularnewline
232 & 19.1 & 17.9366 & 1.16345 \tabularnewline
233 & 13.1 & 13.4627 & -0.362694 \tabularnewline
234 & 12.85 & 15.8947 & -3.04469 \tabularnewline
235 & 9.5 & 12.2784 & -2.77838 \tabularnewline
236 & 4.5 & 10.5779 & -6.07793 \tabularnewline
237 & 11.85 & 10.7626 & 1.0874 \tabularnewline
238 & 13.6 & 15.2232 & -1.62318 \tabularnewline
239 & 11.7 & 12.0402 & -0.340196 \tabularnewline
240 & 12.4 & 12.7722 & -0.372174 \tabularnewline
241 & 13.35 & 14.8812 & -1.53118 \tabularnewline
242 & 11.4 & 12.2296 & -0.829628 \tabularnewline
243 & 14.9 & 14.2516 & 0.648371 \tabularnewline
244 & 19.9 & 19.4141 & 0.485857 \tabularnewline
245 & 11.2 & 13.3862 & -2.18623 \tabularnewline
246 & 14.6 & 15.4737 & -0.873704 \tabularnewline
247 & 17.6 & 18.0191 & -0.419131 \tabularnewline
248 & 14.05 & 13.3383 & 0.711678 \tabularnewline
249 & 16.1 & 15.5834 & 0.516568 \tabularnewline
250 & 13.35 & 14.4131 & -1.0631 \tabularnewline
251 & 11.85 & 14.4582 & -2.60823 \tabularnewline
252 & 11.95 & 13.1327 & -1.18275 \tabularnewline
253 & 14.75 & 14.2912 & 0.458809 \tabularnewline
254 & 15.15 & 13.3668 & 1.78319 \tabularnewline
255 & 13.2 & 16.0283 & -2.82833 \tabularnewline
256 & 16.85 & 16.1942 & 0.655821 \tabularnewline
257 & 7.85 & 11.8841 & -4.03414 \tabularnewline
258 & 7.7 & 12.2969 & -4.59686 \tabularnewline
259 & 12.6 & 15.0496 & -2.44957 \tabularnewline
260 & 7.85 & 14.8561 & -7.00613 \tabularnewline
261 & 10.95 & 11.2711 & -0.321088 \tabularnewline
262 & 12.35 & 14.0837 & -1.73366 \tabularnewline
263 & 9.95 & 12.9192 & -2.96919 \tabularnewline
264 & 14.9 & 14.1186 & 0.781353 \tabularnewline
265 & 16.65 & 14.631 & 2.01901 \tabularnewline
266 & 13.4 & 12.7191 & 0.680877 \tabularnewline
267 & 13.95 & 13.3766 & 0.57342 \tabularnewline
268 & 15.7 & 14.4129 & 1.28706 \tabularnewline
269 & 16.85 & 15.5024 & 1.34755 \tabularnewline
270 & 10.95 & 11.9396 & -0.989573 \tabularnewline
271 & 15.35 & 14.3933 & 0.956736 \tabularnewline
272 & 12.2 & 12.5782 & -0.378178 \tabularnewline
273 & 15.1 & 14.0057 & 1.09434 \tabularnewline
274 & 17.75 & 16.4037 & 1.34634 \tabularnewline
275 & 15.2 & 15.1968 & 0.00319622 \tabularnewline
276 & 14.6 & 14.5027 & 0.0972613 \tabularnewline
277 & 16.65 & 15.7232 & 0.926814 \tabularnewline
278 & 8.1 & 10.2987 & -2.19866 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&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]12.5494[/C][C]0.350642[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.2944[/C][C]1.90562[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.2246[/C][C]1.57544[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.1411[/C][C]-3.74109[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.1411[/C][C]-3.44108[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]11.055[/C][C]1.545[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.5558[/C][C]3.24417[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.3016[/C][C]1.99843[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.0878[/C][C]0.0121734[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.1099[/C][C]-2.90985[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.7291[/C][C]0.670895[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.2066[/C][C]-4.8066[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.05584[/C][C]1.54416[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.983[/C][C]-0.982955[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.62841[/C][C]-1.32841[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.71733[/C][C]1.58267[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.5282[/C][C]0.37176[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.1684[/C][C]-0.868385[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.6941[/C][C]-2.0941[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.73935[/C][C]0.260651[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.20602[/C][C]-2.80602[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.1427[/C][C]3.65732[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.8421[/C][C]-2.04212[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.7195[/C][C]2.08049[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.8164[/C][C]0.883648[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.5965[/C][C]-1.69651[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.1288[/C][C]2.97116[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.8544[/C][C]2.54556[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.1868[/C][C]-1.28678[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.9863[/C][C]0.513748[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.39914[/C][C]-1.09914[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.0687[/C][C]0.631252[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.61351[/C][C]-0.613509[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.5715[/C][C]-1.8715[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.59527[/C][C]1.20473[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]9.14412[/C][C]1.15588[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.0229[/C][C]-0.622938[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.4353[/C][C]2.26465[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]10.982[/C][C]-1.68202[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.1661[/C][C]-0.366092[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.0603[/C][C]-4.16026[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.748[/C][C]0.651963[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.2508[/C][C]1.74916[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.5952[/C][C]-0.79517[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.78439[/C][C]2.51561[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.2718[/C][C]-0.971828[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]10.067[/C][C]1.73305[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.1771[/C][C]-2.27709[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.1234[/C][C]2.57663[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.69135[/C][C]2.60865[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.7005[/C][C]0.89946[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]9.18634[/C][C]-2.48634[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]9.98279[/C][C]0.917209[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.7652[/C][C]1.3348[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.3495[/C][C]2.95052[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.3518[/C][C]-0.25177[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.8011[/C][C]-5.10108[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.6921[/C][C]4.6079[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.45209[/C][C]-0.452089[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.3404[/C][C]1.9596[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.214[/C][C]-2.91399[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.5188[/C][C]1.98117[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.1502[/C][C]-1.5502[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.2909[/C][C]3.60912[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.53[/C][C]-2.32998[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.66672[/C][C]-0.566724[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]11.9924[/C][C]-0.892362[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.3446[/C][C]-0.344595[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]10.6516[/C][C]3.84836[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.0368[/C][C]1.1632[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.5189[/C][C]-0.218906[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.5457[/C][C]0.85431[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.2856[/C][C]-1.48556[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.4852[/C][C]3.11481[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.1174[/C][C]1.48261[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]11.4705[/C][C]1.52949[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.0458[/C][C]1.55418[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.0202[/C][C]1.17978[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]9.5544[/C][C]0.345598[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]10.2413[/C][C]-2.54134[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.8889[/C][C]-0.388925[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.6947[/C][C]2.70531[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]10.6244[/C][C]0.275613[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]9.86916[/C][C]-5.56916[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.5019[/C][C]-1.20186[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.5688[/C][C]0.231227[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]9.96839[/C][C]1.23161[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]9.22137[/C][C]2.17863[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.3167[/C][C]-1.71668[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.4048[/C][C]1.79523[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]9.89585[/C][C]2.70415[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.4931[/C][C]-4.89313[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.6931[/C][C]-1.79314[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]9.87568[/C][C]-1.07568[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]9.81258[/C][C]-2.11258[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.6481[/C][C]-1.64808[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]11.0384[/C][C]-3.73838[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]9.73636[/C][C]1.66364[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]9.92262[/C][C]3.67738[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.6024[/C][C]-2.70241[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]9.84929[/C][C]0.850711[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.1904[/C][C]0.109629[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.90129[/C][C]-1.60129[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.9833[/C][C]-1.3833[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]10.7069[/C][C]3.49313[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.2902[/C][C]-1.79017[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.1414[/C][C]3.35859[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.2318[/C][C]-5.33176[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]8.86785[/C][C]-2.46785[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.8718[/C][C]-1.27177[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.7743[/C][C]0.825658[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.0532[/C][C]1.04685[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]10.4525[/C][C]-6.10247[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]11.0322[/C][C]1.66776[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]15.4459[/C][C]2.65412[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]15.5773[/C][C]2.27272[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]18.0709[/C][C]-1.47094[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]11.7389[/C][C]0.861128[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]18.8613[/C][C]-1.76132[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]17.7824[/C][C]1.3176[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]19.2257[/C][C]-3.1257[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]11.0288[/C][C]2.32124[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]16.851[/C][C]1.54904[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]9.79247[/C][C]4.90753[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.7651[/C][C]-2.16511[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.0252[/C][C]-0.425197[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]14.8134[/C][C]1.38656[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.0183[/C][C]-0.418295[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]16.6843[/C][C]2.21574[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.305[/C][C]0.795017[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.5365[/C][C]0.963495[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]18.1707[/C][C]-2.02073[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.8124[/C][C]0.93757[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.7172[/C][C]1.08279[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.4141[/C][C]0.0358868[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]12.8075[/C][C]-0.157543[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]14.3179[/C][C]3.03209[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]10.0058[/C][C]-1.40581[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.2512[/C][C]1.14881[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]15.3252[/C][C]0.774801[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.886[/C][C]-0.285961[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]15.3557[/C][C]2.39427[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]15.4217[/C][C]-0.171679[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]14.2588[/C][C]3.39116[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]17.0315[/C][C]-0.681505[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]17.3584[/C][C]0.29162[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.0452[/C][C]-0.44525[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.5522[/C][C]-0.202153[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]15.5713[/C][C]-0.821309[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.304[/C][C]1.94603[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]16.6487[/C][C]-6.74873[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.2703[/C][C]0.72969[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]16.0304[/C][C]2.21958[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.9946[/C][C]-1.14463[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]11.9349[/C][C]2.66512[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]14.6834[/C][C]-0.833441[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]18.2274[/C][C]0.722559[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.6737[/C][C]0.926343[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]16.7799[/C][C]-1.92992[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.7519[/C][C]-2.00188[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]17.0856[/C][C]1.36444[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.8191[/C][C]2.08095[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]18.7316[/C][C]-1.63157[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]9.02109[/C][C]7.07891[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]19.7019[/C][C]0.198104[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]10.1498[/C][C]0.800156[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]17.2641[/C][C]1.18591[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.4061[/C][C]1.69387[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]14.7712[/C][C]0.228761[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.6324[/C][C]-2.28244[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]14.7939[/C][C]1.15613[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]15.7585[/C][C]2.34146[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]17.0147[/C][C]-2.41467[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]16.2653[/C][C]-0.865302[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.3084[/C][C]-0.908406[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]15.2621[/C][C]2.33794[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]15.0444[/C][C]-1.69438[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]17.2465[/C][C]1.85352[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]16.9472[/C][C]-1.59718[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]10.2311[/C][C]-2.63114[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]15.2114[/C][C]-1.81142[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]16.2634[/C][C]-2.36339[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.0734[/C][C]2.02655[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]15.1458[/C][C]0.10419[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]16.1332[/C][C]-3.23322[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]15.7577[/C][C]0.342314[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]14.3079[/C][C]3.0421[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]15.1292[/C][C]-1.97923[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.7864[/C][C]-1.63636[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]11.978[/C][C]0.621987[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.6942[/C][C]-2.34418[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]14.4246[/C][C]0.975377[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.1603[/C][C]-2.56027[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]14.9256[/C][C]3.27439[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]13.4622[/C][C]0.137828[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.3196[/C][C]1.53039[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]17.5401[/C][C]-2.79009[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.351[/C][C]0.748977[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.392[/C][C]2.50803[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]15.1695[/C][C]1.08055[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]18.5449[/C][C]0.705125[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.7895[/C][C]0.810549[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.7866[/C][C]-2.1866[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.4475[/C][C]0.202548[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.9963[/C][C]-0.246289[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]12.582[/C][C]2.01797[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]10.8264[/C][C]-0.976362[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]12.3617[/C][C]0.288268[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]17.2989[/C][C]1.90108[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]14.7372[/C][C]1.86276[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]11.5461[/C][C]-0.346085[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]15.5573[/C][C]-0.307285[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.4894[/C][C]-2.58942[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.6835[/C][C]0.516463[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.7992[/C][C]-1.44922[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]12.6808[/C][C]-0.280751[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]14.4813[/C][C]1.36871[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]16.8065[/C][C]1.3435[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.7335[/C][C]-1.58351[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.3074[/C][C]-0.657375[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]15.3733[/C][C]2.37673[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]10.3044[/C][C]-2.65436[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.4933[/C][C]-1.14333[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]13.8457[/C][C]1.75431[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]17.2979[/C][C]2.00209[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.1986[/C][C]4.00137[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]14.895[/C][C]2.20496[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]13.3694[/C][C]2.23058[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]15.638[/C][C]2.76205[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]16.3196[/C][C]2.73042[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.8957[/C][C]2.6543[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.9366[/C][C]1.16345[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]13.4627[/C][C]-0.362694[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]15.8947[/C][C]-3.04469[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]12.2784[/C][C]-2.77838[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]10.5779[/C][C]-6.07793[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.7626[/C][C]1.0874[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.2232[/C][C]-1.62318[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.0402[/C][C]-0.340196[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.7722[/C][C]-0.372174[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.8812[/C][C]-1.53118[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.2296[/C][C]-0.829628[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]14.2516[/C][C]0.648371[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]19.4141[/C][C]0.485857[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.3862[/C][C]-2.18623[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.4737[/C][C]-0.873704[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]18.0191[/C][C]-0.419131[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]13.3383[/C][C]0.711678[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.5834[/C][C]0.516568[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]14.4131[/C][C]-1.0631[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.4582[/C][C]-2.60823[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.1327[/C][C]-1.18275[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.2912[/C][C]0.458809[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.3668[/C][C]1.78319[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]16.0283[/C][C]-2.82833[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]16.1942[/C][C]0.655821[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]11.8841[/C][C]-4.03414[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.2969[/C][C]-4.59686[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]15.0496[/C][C]-2.44957[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]14.8561[/C][C]-7.00613[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]11.2711[/C][C]-0.321088[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]14.0837[/C][C]-1.73366[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.9192[/C][C]-2.96919[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]14.1186[/C][C]0.781353[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]14.631[/C][C]2.01901[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]12.7191[/C][C]0.680877[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.3766[/C][C]0.57342[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.4129[/C][C]1.28706[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]15.5024[/C][C]1.34755[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]11.9396[/C][C]-0.989573[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]14.3933[/C][C]0.956736[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.5782[/C][C]-0.378178[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]14.0057[/C][C]1.09434[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.4037[/C][C]1.34634[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]15.1968[/C][C]0.00319622[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]14.5027[/C][C]0.0972613[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]15.7232[/C][C]0.926814[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.2987[/C][C]-2.19866[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	12.5494	0.350642
2	12.2	10.2944	1.90562
3	12.8	11.2246	1.57544
4	7.4	11.1411	-3.74109
5	6.7	10.1411	-3.44108
6	12.6	11.055	1.545
7	14.8	11.5558	3.24417
8	13.3	11.3016	1.99843
9	11.1	11.0878	0.0121734
10	8.2	11.1099	-2.90985
11	11.4	10.7291	0.670895
12	6.4	11.2066	-4.8066
13	10.6	9.05584	1.54416
14	12	12.983	-0.982955
15	6.3	7.62841	-1.32841
16	11.3	9.71733	1.58267
17	11.9	11.5282	0.37176
18	9.3	10.1684	-0.868385
19	9.6	11.6941	-2.0941
20	10	9.73935	0.260651
21	6.4	9.20602	-2.80602
22	13.8	10.1427	3.65732
23	10.8	12.8421	-2.04212
24	13.8	11.7195	2.08049
25	11.7	10.8164	0.883648
26	10.9	12.5965	-1.69651
27	16.1	13.1288	2.97116
28	13.4	10.8544	2.54556
29	9.9	11.1868	-1.28678
30	11.5	10.9863	0.513748
31	8.3	9.39914	-1.09914
32	11.7	11.0687	0.631252
33	9	9.61351	-0.613509
34	9.7	11.5715	-1.8715
35	10.8	9.59527	1.20473
36	10.3	9.14412	1.15588
37	10.4	11.0229	-0.622938
38	12.7	10.4353	2.26465
39	9.3	10.982	-1.68202
40	11.8	12.1661	-0.366092
41	5.9	10.0603	-4.16026
42	11.4	10.748	0.651963
43	13	11.2508	1.74916
44	10.8	11.5952	-0.79517
45	12.3	9.78439	2.51561
46	11.3	12.2718	-0.971828
47	11.8	10.067	1.73305
48	7.9	10.1771	-2.27709
49	12.7	10.1234	2.57663
50	12.3	9.69135	2.60865
51	11.6	10.7005	0.89946
52	6.7	9.18634	-2.48634
53	10.9	9.98279	0.917209
54	12.1	10.7652	1.3348
55	13.3	10.3495	2.95052
56	10.1	10.3518	-0.25177
57	5.7	10.8011	-5.10108
58	14.3	9.6921	4.6079
59	8	8.45209	-0.452089
60	13.3	11.3404	1.9596
61	9.3	12.214	-2.91399
62	12.5	10.5188	1.98117
63	7.6	9.1502	-1.5502
64	15.9	12.2909	3.60912
65	9.2	11.53	-2.32998
66	9.1	9.66672	-0.566724
67	11.1	11.9924	-0.892362
68	13	13.3446	-0.344595
69	14.5	10.6516	3.84836
70	12.2	11.0368	1.1632
71	12.3	12.5189	-0.218906
72	11.4	10.5457	0.85431
73	8.8	10.2856	-1.48556
74	14.6	11.4852	3.11481
75	12.6	11.1174	1.48261
76	13	11.4705	1.52949
77	12.6	11.0458	1.55418
78	13.2	12.0202	1.17978
79	9.9	9.5544	0.345598
80	7.7	10.2413	-2.54134
81	10.5	10.8889	-0.388925
82	13.4	10.6947	2.70531
83	10.9	10.6244	0.275613
84	4.3	9.86916	-5.56916
85	10.3	11.5019	-1.20186
86	11.8	11.5688	0.231227
87	11.2	9.96839	1.23161
88	11.4	9.22137	2.17863
89	8.6	10.3167	-1.71668
90	13.2	11.4048	1.79523
91	12.6	9.89585	2.70415
92	5.6	10.4931	-4.89313
93	9.9	11.6931	-1.79314
94	8.8	9.87568	-1.07568
95	7.7	9.81258	-2.11258
96	9	10.6481	-1.64808
97	7.3	11.0384	-3.73838
98	11.4	9.73636	1.66364
99	13.6	9.92262	3.67738
100	7.9	10.6024	-2.70241
101	10.7	9.84929	0.850711
102	10.3	10.1904	0.109629
103	8.3	9.90129	-1.60129
104	9.6	10.9833	-1.3833
105	14.2	10.7069	3.49313
106	8.5	10.2902	-1.79017
107	13.5	10.1414	3.35859
108	4.9	10.2318	-5.33176
109	6.4	8.86785	-2.46785
110	9.6	10.8718	-1.27177
111	11.6	10.7743	0.825658
112	11.1	10.0532	1.04685
113	4.35	10.4525	-6.10247
114	12.7	11.0322	1.66776
115	18.1	15.4459	2.65412
116	17.85	15.5773	2.27272
117	16.6	18.0709	-1.47094
118	12.6	11.7389	0.861128
119	17.1	18.8613	-1.76132
120	19.1	17.7824	1.3176
121	16.1	19.2257	-3.1257
122	13.35	11.0288	2.32124
123	18.4	16.851	1.54904
124	14.7	9.79247	4.90753
125	10.6	12.7651	-2.16511
126	12.6	13.0252	-0.425197
127	16.2	14.8134	1.38656
128	13.6	14.0183	-0.418295
129	18.9	16.6843	2.21574
130	14.1	13.305	0.795017
131	14.5	13.5365	0.963495
132	16.15	18.1707	-2.02073
133	14.75	13.8124	0.93757
134	14.8	13.7172	1.08279
135	12.45	12.4141	0.0358868
136	12.65	12.8075	-0.157543
137	17.35	14.3179	3.03209
138	8.6	10.0058	-1.40581
139	18.4	17.2512	1.14881
140	16.1	15.3252	0.774801
141	11.6	11.886	-0.285961
142	17.75	15.3557	2.39427
143	15.25	15.4217	-0.171679
144	17.65	14.2588	3.39116
145	16.35	17.0315	-0.681505
146	17.65	17.3584	0.29162
147	13.6	14.0452	-0.44525
148	14.35	14.5522	-0.202153
149	14.75	15.5713	-0.821309
150	18.25	16.304	1.94603
151	9.9	16.6487	-6.74873
152	16	15.2703	0.72969
153	18.25	16.0304	2.21958
154	16.85	17.9946	-1.14463
155	14.6	11.9349	2.66512
156	13.85	14.6834	-0.833441
157	18.95	18.2274	0.722559
158	15.6	14.6737	0.926343
159	14.85	16.7799	-1.92992
160	11.75	13.7519	-2.00188
161	18.45	17.0856	1.36444
162	15.9	13.8191	2.08095
163	17.1	18.7316	-1.63157
164	16.1	9.02109	7.07891
165	19.9	19.7019	0.198104
166	10.95	10.1498	0.800156
167	18.45	17.2641	1.18591
168	15.1	13.4061	1.69387
169	15	14.7712	0.228761
170	11.35	13.6324	-2.28244
171	15.95	14.7939	1.15613
172	18.1	15.7585	2.34146
173	14.6	17.0147	-2.41467
174	15.4	16.2653	-0.865302
175	15.4	16.3084	-0.908406
176	17.6	15.2621	2.33794
177	13.35	15.0444	-1.69438
178	19.1	17.2465	1.85352
179	15.35	16.9472	-1.59718
180	7.6	10.2311	-2.63114
181	13.4	15.2114	-1.81142
182	13.9	16.2634	-2.36339
183	19.1	17.0734	2.02655
184	15.25	15.1458	0.10419
185	12.9	16.1332	-3.23322
186	16.1	15.7577	0.342314
187	17.35	14.3079	3.0421
188	13.15	15.1292	-1.97923
189	12.15	13.7864	-1.63636
190	12.6	11.978	0.621987
191	10.35	12.6942	-2.34418
192	15.4	14.4246	0.975377
193	9.6	12.1603	-2.56027
194	18.2	14.9256	3.27439
195	13.6	13.4622	0.137828
196	14.85	13.3196	1.53039
197	14.75	17.5401	-2.79009
198	14.1	13.351	0.748977
199	14.9	12.392	2.50803
200	16.25	15.1695	1.08055
201	19.25	18.5449	0.705125
202	13.6	12.7895	0.810549
203	13.6	15.7866	-2.1866
204	15.65	15.4475	0.202548
205	12.75	12.9963	-0.246289
206	14.6	12.582	2.01797
207	9.85	10.8264	-0.976362
208	12.65	12.3617	0.288268
209	19.2	17.2989	1.90108
210	16.6	14.7372	1.86276
211	11.2	11.5461	-0.346085
212	15.25	15.5573	-0.307285
213	11.9	14.4894	-2.58942
214	13.2	12.6835	0.516463
215	16.35	17.7992	-1.44922
216	12.4	12.6808	-0.280751
217	15.85	14.4813	1.36871
218	18.15	16.8065	1.3435
219	11.15	12.7335	-1.58351
220	15.65	16.3074	-0.657375
221	17.75	15.3733	2.37673
222	7.65	10.3044	-2.65436
223	12.35	13.4933	-1.14333
224	15.6	13.8457	1.75431
225	19.3	17.2979	2.00209
226	15.2	11.1986	4.00137
227	17.1	14.895	2.20496
228	15.6	13.3694	2.23058
229	18.4	15.638	2.76205
230	19.05	16.3196	2.73042
231	18.55	15.8957	2.6543
232	19.1	17.9366	1.16345
233	13.1	13.4627	-0.362694
234	12.85	15.8947	-3.04469
235	9.5	12.2784	-2.77838
236	4.5	10.5779	-6.07793
237	11.85	10.7626	1.0874
238	13.6	15.2232	-1.62318
239	11.7	12.0402	-0.340196
240	12.4	12.7722	-0.372174
241	13.35	14.8812	-1.53118
242	11.4	12.2296	-0.829628
243	14.9	14.2516	0.648371
244	19.9	19.4141	0.485857
245	11.2	13.3862	-2.18623
246	14.6	15.4737	-0.873704
247	17.6	18.0191	-0.419131
248	14.05	13.3383	0.711678
249	16.1	15.5834	0.516568
250	13.35	14.4131	-1.0631
251	11.85	14.4582	-2.60823
252	11.95	13.1327	-1.18275
253	14.75	14.2912	0.458809
254	15.15	13.3668	1.78319
255	13.2	16.0283	-2.82833
256	16.85	16.1942	0.655821
257	7.85	11.8841	-4.03414
258	7.7	12.2969	-4.59686
259	12.6	15.0496	-2.44957
260	7.85	14.8561	-7.00613
261	10.95	11.2711	-0.321088
262	12.35	14.0837	-1.73366
263	9.95	12.9192	-2.96919
264	14.9	14.1186	0.781353
265	16.65	14.631	2.01901
266	13.4	12.7191	0.680877
267	13.95	13.3766	0.57342
268	15.7	14.4129	1.28706
269	16.85	15.5024	1.34755
270	10.95	11.9396	-0.989573
271	15.35	14.3933	0.956736
272	12.2	12.5782	-0.378178
273	15.1	14.0057	1.09434
274	17.75	16.4037	1.34634
275	15.2	15.1968	0.00319622
276	14.6	14.5027	0.0972613
277	16.65	15.7232	0.926814
278	8.1	10.2987	-2.19866

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
20	0.716437	0.567127	0.283563
21	0.581498	0.837004	0.418502
22	0.443492	0.886984	0.556508
23	0.369547	0.739093	0.630453
24	0.29935	0.5987	0.70065
25	0.243873	0.487745	0.756127
26	0.172381	0.344761	0.827619
27	0.134846	0.269692	0.865154
28	0.095813	0.191626	0.904187
29	0.0615741	0.123148	0.938426
30	0.0565664	0.113133	0.943434
31	0.0464438	0.0928875	0.953556
32	0.0290795	0.058159	0.97092
33	0.0933369	0.186674	0.906663
34	0.274677	0.549354	0.725323
35	0.222552	0.445104	0.777448
36	0.253679	0.507359	0.746321
37	0.272521	0.545042	0.727479
38	0.29064	0.581279	0.70936
39	0.270189	0.540378	0.729811
40	0.231412	0.462825	0.768588
41	0.272332	0.544663	0.727668
42	0.267134	0.534267	0.732866
43	0.241042	0.482083	0.758958
44	0.227709	0.455417	0.772291
45	0.195223	0.390446	0.804777
46	0.159777	0.319554	0.840223
47	0.17321	0.34642	0.82679
48	0.171725	0.343449	0.828275
49	0.234625	0.46925	0.765375
50	0.261161	0.522322	0.738839
51	0.220402	0.440804	0.779598
52	0.248969	0.497937	0.751031
53	0.232694	0.465387	0.767306
54	0.197477	0.394954	0.802523
55	0.3126	0.6252	0.6874
56	0.270908	0.541816	0.729092
57	0.62658	0.746841	0.37342
58	0.65924	0.68152	0.34076
59	0.624491	0.751018	0.375509
60	0.619162	0.761676	0.380838
61	0.627761	0.744477	0.372239
62	0.620661	0.758679	0.379339
63	0.725309	0.549382	0.274691
64	0.78527	0.42946	0.21473
65	0.79079	0.418421	0.20921
66	0.768036	0.463927	0.231964
67	0.739996	0.520008	0.260004
68	0.706291	0.587419	0.293709
69	0.737927	0.524147	0.262073
70	0.713449	0.573102	0.286551
71	0.677323	0.645355	0.322677
72	0.644625	0.710751	0.355375
73	0.616601	0.766797	0.383399
74	0.661407	0.677187	0.338593
75	0.633853	0.732295	0.366147
76	0.620764	0.758471	0.379236
77	0.597945	0.804111	0.402055
78	0.58126	0.83748	0.41874
79	0.541647	0.916707	0.458353
80	0.538124	0.923752	0.461876
81	0.498909	0.997818	0.501091
82	0.5199	0.960201	0.4801
83	0.482625	0.96525	0.517375
84	0.677422	0.645156	0.322578
85	0.670491	0.659017	0.329509
86	0.635809	0.728382	0.364191
87	0.610822	0.778356	0.389178
88	0.629764	0.740471	0.370236
89	0.612663	0.774674	0.387337
90	0.607896	0.784208	0.392104
91	0.616317	0.767366	0.383683
92	0.763276	0.473448	0.236724
93	0.756487	0.487026	0.243513
94	0.735586	0.528827	0.264414
95	0.719821	0.560359	0.280179
96	0.693177	0.613646	0.306823
97	0.732963	0.534075	0.267037
98	0.718103	0.563794	0.281897
99	0.772059	0.455883	0.227941
100	0.773879	0.452242	0.226121
101	0.757096	0.485808	0.242904
102	0.72889	0.54222	0.27111
103	0.714343	0.571314	0.285657
104	0.700289	0.599421	0.299711
105	0.747364	0.505273	0.252636
106	0.727676	0.544649	0.272324
107	0.785903	0.428195	0.214097
108	0.864336	0.271327	0.135664
109	0.845811	0.308378	0.154189
110	0.831982	0.336035	0.168018
111	0.813393	0.373214	0.186607
112	0.793565	0.412869	0.206435
113	0.845893	0.308214	0.154107
114	0.827074	0.345852	0.172926
115	0.901371	0.197257	0.0986286
116	0.893585	0.212831	0.106415
117	0.885039	0.229922	0.114961
118	0.876709	0.246581	0.123291
119	0.884542	0.230917	0.115458
120	0.870416	0.259167	0.129584
121	0.895024	0.209951	0.104976
122	0.904611	0.190778	0.0953892
123	0.897357	0.205285	0.102643
124	0.940595	0.11881	0.0594049
125	0.941426	0.117148	0.0585741
126	0.932296	0.135407	0.0677037
127	0.923912	0.152177	0.0760885
128	0.911194	0.177611	0.0888056
129	0.906984	0.186032	0.0930161
130	0.892574	0.214851	0.107426
131	0.879543	0.240913	0.120457
132	0.877089	0.245823	0.122911
133	0.862324	0.275352	0.137676
134	0.844301	0.311398	0.155699
135	0.821805	0.35639	0.178195
136	0.79884	0.40232	0.20116
137	0.818186	0.363628	0.181814
138	0.808931	0.382139	0.191069
139	0.787459	0.425082	0.212541
140	0.761541	0.476917	0.238459
141	0.734105	0.531791	0.265895
142	0.734229	0.531542	0.265771
143	0.706801	0.586398	0.293199
144	0.744735	0.51053	0.255265
145	0.722184	0.555633	0.277816
146	0.691133	0.617734	0.308867
147	0.661304	0.677391	0.338696
148	0.628337	0.743326	0.371663
149	0.60062	0.798761	0.39938
150	0.596594	0.806813	0.403406
151	0.855645	0.28871	0.144355
152	0.837892	0.324216	0.162108
153	0.841172	0.317657	0.158828
154	0.823808	0.352383	0.176192
155	0.834177	0.331646	0.165823
156	0.816199	0.367602	0.183801
157	0.795111	0.409778	0.204889
158	0.770508	0.458985	0.229492
159	0.772021	0.455957	0.227979
160	0.769707	0.460585	0.230293
161	0.752225	0.495551	0.247775
162	0.749737	0.500526	0.250263
163	0.742432	0.515135	0.257568
164	0.971599	0.0568019	0.0284009
165	0.965083	0.0698347	0.0349173
166	0.960254	0.0794918	0.0397459
167	0.953375	0.0932499	0.046625
168	0.952154	0.0956926	0.0478463
169	0.94302	0.11396	0.0569798
170	0.947353	0.105295	0.0526474
171	0.940206	0.119588	0.0597938
172	0.93754	0.124919	0.0624597
173	0.936153	0.127694	0.0638472
174	0.926584	0.146832	0.073416
175	0.914794	0.170412	0.0852059
176	0.921009	0.157982	0.0789911
177	0.912291	0.175418	0.087709
178	0.910167	0.179665	0.0898325
179	0.898763	0.202473	0.101237
180	0.895695	0.208609	0.104305
181	0.911043	0.177915	0.0889575
182	0.916799	0.166401	0.0832006
183	0.913658	0.172684	0.0863418
184	0.89808	0.203841	0.10192
185	0.904754	0.190492	0.0952459
186	0.889098	0.221804	0.110902
187	0.90123	0.197539	0.0987697
188	0.903436	0.193127	0.0965637
189	0.901199	0.197601	0.0988007
190	0.884326	0.231349	0.115674
191	0.88071	0.23858	0.11929
192	0.864098	0.271804	0.135902
193	0.888638	0.222724	0.111362
194	0.903689	0.192622	0.0963108
195	0.892657	0.214685	0.107343
196	0.883294	0.233412	0.116706
197	0.893294	0.213411	0.106706
198	0.873561	0.252878	0.126439
199	0.863452	0.273095	0.136548
200	0.840738	0.318523	0.159262
201	0.818522	0.362957	0.181478
202	0.796129	0.407741	0.203871
203	0.809668	0.380665	0.190332
204	0.778709	0.442582	0.221291
205	0.762714	0.474572	0.237286
206	0.757317	0.485366	0.242683
207	0.750494	0.499011	0.249506
208	0.718929	0.562141	0.281071
209	0.695959	0.608082	0.304041
210	0.692348	0.615304	0.307652
211	0.653935	0.69213	0.346065
212	0.612107	0.775786	0.387893
213	0.604397	0.791206	0.395603
214	0.56028	0.879439	0.43972
215	0.563905	0.872191	0.436095
216	0.52443	0.951139	0.47557
217	0.521451	0.957099	0.478549
218	0.485535	0.971069	0.514465
219	0.447552	0.895104	0.552448
220	0.412442	0.824884	0.587558
221	0.415987	0.831974	0.584013
222	0.463526	0.927053	0.536474
223	0.428488	0.856976	0.571512
224	0.577389	0.845223	0.422611
225	0.552219	0.895562	0.447781
226	0.603733	0.792533	0.396267
227	0.61234	0.775321	0.38766
228	0.66286	0.67428	0.33714
229	0.737935	0.52413	0.262065
230	0.762311	0.475378	0.237689
231	0.737659	0.524681	0.262341
232	0.702573	0.594854	0.297427
233	0.676316	0.647368	0.323684
234	0.651616	0.696767	0.348384
235	0.62008	0.75984	0.37992
236	0.69303	0.613939	0.30697
237	0.663921	0.672159	0.336079
238	0.611213	0.777574	0.388787
239	0.619175	0.76165	0.380825
240	0.564069	0.871862	0.435931
241	0.525804	0.948392	0.474196
242	0.46352	0.927039	0.53648
243	0.408667	0.817334	0.591333
244	0.351828	0.703657	0.648172
245	0.300856	0.601711	0.699144
246	0.241835	0.48367	0.758165
247	0.199105	0.398211	0.800895
248	0.420748	0.841496	0.579252
249	0.358483	0.716965	0.641517
250	0.291156	0.582312	0.708844
251	0.225465	0.45093	0.774535
252	0.185158	0.370316	0.814842
253	0.181512	0.363024	0.818488
254	0.307272	0.614543	0.692728
255	0.272957	0.545913	0.727043
256	0.197478	0.394957	0.802522
257	0.126681	0.253363	0.873319
258	0.0696005	0.139201	0.930399

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
20 & 0.716437 & 0.567127 & 0.283563 \tabularnewline
21 & 0.581498 & 0.837004 & 0.418502 \tabularnewline
22 & 0.443492 & 0.886984 & 0.556508 \tabularnewline
23 & 0.369547 & 0.739093 & 0.630453 \tabularnewline
24 & 0.29935 & 0.5987 & 0.70065 \tabularnewline
25 & 0.243873 & 0.487745 & 0.756127 \tabularnewline
26 & 0.172381 & 0.344761 & 0.827619 \tabularnewline
27 & 0.134846 & 0.269692 & 0.865154 \tabularnewline
28 & 0.095813 & 0.191626 & 0.904187 \tabularnewline
29 & 0.0615741 & 0.123148 & 0.938426 \tabularnewline
30 & 0.0565664 & 0.113133 & 0.943434 \tabularnewline
31 & 0.0464438 & 0.0928875 & 0.953556 \tabularnewline
32 & 0.0290795 & 0.058159 & 0.97092 \tabularnewline
33 & 0.0933369 & 0.186674 & 0.906663 \tabularnewline
34 & 0.274677 & 0.549354 & 0.725323 \tabularnewline
35 & 0.222552 & 0.445104 & 0.777448 \tabularnewline
36 & 0.253679 & 0.507359 & 0.746321 \tabularnewline
37 & 0.272521 & 0.545042 & 0.727479 \tabularnewline
38 & 0.29064 & 0.581279 & 0.70936 \tabularnewline
39 & 0.270189 & 0.540378 & 0.729811 \tabularnewline
40 & 0.231412 & 0.462825 & 0.768588 \tabularnewline
41 & 0.272332 & 0.544663 & 0.727668 \tabularnewline
42 & 0.267134 & 0.534267 & 0.732866 \tabularnewline
43 & 0.241042 & 0.482083 & 0.758958 \tabularnewline
44 & 0.227709 & 0.455417 & 0.772291 \tabularnewline
45 & 0.195223 & 0.390446 & 0.804777 \tabularnewline
46 & 0.159777 & 0.319554 & 0.840223 \tabularnewline
47 & 0.17321 & 0.34642 & 0.82679 \tabularnewline
48 & 0.171725 & 0.343449 & 0.828275 \tabularnewline
49 & 0.234625 & 0.46925 & 0.765375 \tabularnewline
50 & 0.261161 & 0.522322 & 0.738839 \tabularnewline
51 & 0.220402 & 0.440804 & 0.779598 \tabularnewline
52 & 0.248969 & 0.497937 & 0.751031 \tabularnewline
53 & 0.232694 & 0.465387 & 0.767306 \tabularnewline
54 & 0.197477 & 0.394954 & 0.802523 \tabularnewline
55 & 0.3126 & 0.6252 & 0.6874 \tabularnewline
56 & 0.270908 & 0.541816 & 0.729092 \tabularnewline
57 & 0.62658 & 0.746841 & 0.37342 \tabularnewline
58 & 0.65924 & 0.68152 & 0.34076 \tabularnewline
59 & 0.624491 & 0.751018 & 0.375509 \tabularnewline
60 & 0.619162 & 0.761676 & 0.380838 \tabularnewline
61 & 0.627761 & 0.744477 & 0.372239 \tabularnewline
62 & 0.620661 & 0.758679 & 0.379339 \tabularnewline
63 & 0.725309 & 0.549382 & 0.274691 \tabularnewline
64 & 0.78527 & 0.42946 & 0.21473 \tabularnewline
65 & 0.79079 & 0.418421 & 0.20921 \tabularnewline
66 & 0.768036 & 0.463927 & 0.231964 \tabularnewline
67 & 0.739996 & 0.520008 & 0.260004 \tabularnewline
68 & 0.706291 & 0.587419 & 0.293709 \tabularnewline
69 & 0.737927 & 0.524147 & 0.262073 \tabularnewline
70 & 0.713449 & 0.573102 & 0.286551 \tabularnewline
71 & 0.677323 & 0.645355 & 0.322677 \tabularnewline
72 & 0.644625 & 0.710751 & 0.355375 \tabularnewline
73 & 0.616601 & 0.766797 & 0.383399 \tabularnewline
74 & 0.661407 & 0.677187 & 0.338593 \tabularnewline
75 & 0.633853 & 0.732295 & 0.366147 \tabularnewline
76 & 0.620764 & 0.758471 & 0.379236 \tabularnewline
77 & 0.597945 & 0.804111 & 0.402055 \tabularnewline
78 & 0.58126 & 0.83748 & 0.41874 \tabularnewline
79 & 0.541647 & 0.916707 & 0.458353 \tabularnewline
80 & 0.538124 & 0.923752 & 0.461876 \tabularnewline
81 & 0.498909 & 0.997818 & 0.501091 \tabularnewline
82 & 0.5199 & 0.960201 & 0.4801 \tabularnewline
83 & 0.482625 & 0.96525 & 0.517375 \tabularnewline
84 & 0.677422 & 0.645156 & 0.322578 \tabularnewline
85 & 0.670491 & 0.659017 & 0.329509 \tabularnewline
86 & 0.635809 & 0.728382 & 0.364191 \tabularnewline
87 & 0.610822 & 0.778356 & 0.389178 \tabularnewline
88 & 0.629764 & 0.740471 & 0.370236 \tabularnewline
89 & 0.612663 & 0.774674 & 0.387337 \tabularnewline
90 & 0.607896 & 0.784208 & 0.392104 \tabularnewline
91 & 0.616317 & 0.767366 & 0.383683 \tabularnewline
92 & 0.763276 & 0.473448 & 0.236724 \tabularnewline
93 & 0.756487 & 0.487026 & 0.243513 \tabularnewline
94 & 0.735586 & 0.528827 & 0.264414 \tabularnewline
95 & 0.719821 & 0.560359 & 0.280179 \tabularnewline
96 & 0.693177 & 0.613646 & 0.306823 \tabularnewline
97 & 0.732963 & 0.534075 & 0.267037 \tabularnewline
98 & 0.718103 & 0.563794 & 0.281897 \tabularnewline
99 & 0.772059 & 0.455883 & 0.227941 \tabularnewline
100 & 0.773879 & 0.452242 & 0.226121 \tabularnewline
101 & 0.757096 & 0.485808 & 0.242904 \tabularnewline
102 & 0.72889 & 0.54222 & 0.27111 \tabularnewline
103 & 0.714343 & 0.571314 & 0.285657 \tabularnewline
104 & 0.700289 & 0.599421 & 0.299711 \tabularnewline
105 & 0.747364 & 0.505273 & 0.252636 \tabularnewline
106 & 0.727676 & 0.544649 & 0.272324 \tabularnewline
107 & 0.785903 & 0.428195 & 0.214097 \tabularnewline
108 & 0.864336 & 0.271327 & 0.135664 \tabularnewline
109 & 0.845811 & 0.308378 & 0.154189 \tabularnewline
110 & 0.831982 & 0.336035 & 0.168018 \tabularnewline
111 & 0.813393 & 0.373214 & 0.186607 \tabularnewline
112 & 0.793565 & 0.412869 & 0.206435 \tabularnewline
113 & 0.845893 & 0.308214 & 0.154107 \tabularnewline
114 & 0.827074 & 0.345852 & 0.172926 \tabularnewline
115 & 0.901371 & 0.197257 & 0.0986286 \tabularnewline
116 & 0.893585 & 0.212831 & 0.106415 \tabularnewline
117 & 0.885039 & 0.229922 & 0.114961 \tabularnewline
118 & 0.876709 & 0.246581 & 0.123291 \tabularnewline
119 & 0.884542 & 0.230917 & 0.115458 \tabularnewline
120 & 0.870416 & 0.259167 & 0.129584 \tabularnewline
121 & 0.895024 & 0.209951 & 0.104976 \tabularnewline
122 & 0.904611 & 0.190778 & 0.0953892 \tabularnewline
123 & 0.897357 & 0.205285 & 0.102643 \tabularnewline
124 & 0.940595 & 0.11881 & 0.0594049 \tabularnewline
125 & 0.941426 & 0.117148 & 0.0585741 \tabularnewline
126 & 0.932296 & 0.135407 & 0.0677037 \tabularnewline
127 & 0.923912 & 0.152177 & 0.0760885 \tabularnewline
128 & 0.911194 & 0.177611 & 0.0888056 \tabularnewline
129 & 0.906984 & 0.186032 & 0.0930161 \tabularnewline
130 & 0.892574 & 0.214851 & 0.107426 \tabularnewline
131 & 0.879543 & 0.240913 & 0.120457 \tabularnewline
132 & 0.877089 & 0.245823 & 0.122911 \tabularnewline
133 & 0.862324 & 0.275352 & 0.137676 \tabularnewline
134 & 0.844301 & 0.311398 & 0.155699 \tabularnewline
135 & 0.821805 & 0.35639 & 0.178195 \tabularnewline
136 & 0.79884 & 0.40232 & 0.20116 \tabularnewline
137 & 0.818186 & 0.363628 & 0.181814 \tabularnewline
138 & 0.808931 & 0.382139 & 0.191069 \tabularnewline
139 & 0.787459 & 0.425082 & 0.212541 \tabularnewline
140 & 0.761541 & 0.476917 & 0.238459 \tabularnewline
141 & 0.734105 & 0.531791 & 0.265895 \tabularnewline
142 & 0.734229 & 0.531542 & 0.265771 \tabularnewline
143 & 0.706801 & 0.586398 & 0.293199 \tabularnewline
144 & 0.744735 & 0.51053 & 0.255265 \tabularnewline
145 & 0.722184 & 0.555633 & 0.277816 \tabularnewline
146 & 0.691133 & 0.617734 & 0.308867 \tabularnewline
147 & 0.661304 & 0.677391 & 0.338696 \tabularnewline
148 & 0.628337 & 0.743326 & 0.371663 \tabularnewline
149 & 0.60062 & 0.798761 & 0.39938 \tabularnewline
150 & 0.596594 & 0.806813 & 0.403406 \tabularnewline
151 & 0.855645 & 0.28871 & 0.144355 \tabularnewline
152 & 0.837892 & 0.324216 & 0.162108 \tabularnewline
153 & 0.841172 & 0.317657 & 0.158828 \tabularnewline
154 & 0.823808 & 0.352383 & 0.176192 \tabularnewline
155 & 0.834177 & 0.331646 & 0.165823 \tabularnewline
156 & 0.816199 & 0.367602 & 0.183801 \tabularnewline
157 & 0.795111 & 0.409778 & 0.204889 \tabularnewline
158 & 0.770508 & 0.458985 & 0.229492 \tabularnewline
159 & 0.772021 & 0.455957 & 0.227979 \tabularnewline
160 & 0.769707 & 0.460585 & 0.230293 \tabularnewline
161 & 0.752225 & 0.495551 & 0.247775 \tabularnewline
162 & 0.749737 & 0.500526 & 0.250263 \tabularnewline
163 & 0.742432 & 0.515135 & 0.257568 \tabularnewline
164 & 0.971599 & 0.0568019 & 0.0284009 \tabularnewline
165 & 0.965083 & 0.0698347 & 0.0349173 \tabularnewline
166 & 0.960254 & 0.0794918 & 0.0397459 \tabularnewline
167 & 0.953375 & 0.0932499 & 0.046625 \tabularnewline
168 & 0.952154 & 0.0956926 & 0.0478463 \tabularnewline
169 & 0.94302 & 0.11396 & 0.0569798 \tabularnewline
170 & 0.947353 & 0.105295 & 0.0526474 \tabularnewline
171 & 0.940206 & 0.119588 & 0.0597938 \tabularnewline
172 & 0.93754 & 0.124919 & 0.0624597 \tabularnewline
173 & 0.936153 & 0.127694 & 0.0638472 \tabularnewline
174 & 0.926584 & 0.146832 & 0.073416 \tabularnewline
175 & 0.914794 & 0.170412 & 0.0852059 \tabularnewline
176 & 0.921009 & 0.157982 & 0.0789911 \tabularnewline
177 & 0.912291 & 0.175418 & 0.087709 \tabularnewline
178 & 0.910167 & 0.179665 & 0.0898325 \tabularnewline
179 & 0.898763 & 0.202473 & 0.101237 \tabularnewline
180 & 0.895695 & 0.208609 & 0.104305 \tabularnewline
181 & 0.911043 & 0.177915 & 0.0889575 \tabularnewline
182 & 0.916799 & 0.166401 & 0.0832006 \tabularnewline
183 & 0.913658 & 0.172684 & 0.0863418 \tabularnewline
184 & 0.89808 & 0.203841 & 0.10192 \tabularnewline
185 & 0.904754 & 0.190492 & 0.0952459 \tabularnewline
186 & 0.889098 & 0.221804 & 0.110902 \tabularnewline
187 & 0.90123 & 0.197539 & 0.0987697 \tabularnewline
188 & 0.903436 & 0.193127 & 0.0965637 \tabularnewline
189 & 0.901199 & 0.197601 & 0.0988007 \tabularnewline
190 & 0.884326 & 0.231349 & 0.115674 \tabularnewline
191 & 0.88071 & 0.23858 & 0.11929 \tabularnewline
192 & 0.864098 & 0.271804 & 0.135902 \tabularnewline
193 & 0.888638 & 0.222724 & 0.111362 \tabularnewline
194 & 0.903689 & 0.192622 & 0.0963108 \tabularnewline
195 & 0.892657 & 0.214685 & 0.107343 \tabularnewline
196 & 0.883294 & 0.233412 & 0.116706 \tabularnewline
197 & 0.893294 & 0.213411 & 0.106706 \tabularnewline
198 & 0.873561 & 0.252878 & 0.126439 \tabularnewline
199 & 0.863452 & 0.273095 & 0.136548 \tabularnewline
200 & 0.840738 & 0.318523 & 0.159262 \tabularnewline
201 & 0.818522 & 0.362957 & 0.181478 \tabularnewline
202 & 0.796129 & 0.407741 & 0.203871 \tabularnewline
203 & 0.809668 & 0.380665 & 0.190332 \tabularnewline
204 & 0.778709 & 0.442582 & 0.221291 \tabularnewline
205 & 0.762714 & 0.474572 & 0.237286 \tabularnewline
206 & 0.757317 & 0.485366 & 0.242683 \tabularnewline
207 & 0.750494 & 0.499011 & 0.249506 \tabularnewline
208 & 0.718929 & 0.562141 & 0.281071 \tabularnewline
209 & 0.695959 & 0.608082 & 0.304041 \tabularnewline
210 & 0.692348 & 0.615304 & 0.307652 \tabularnewline
211 & 0.653935 & 0.69213 & 0.346065 \tabularnewline
212 & 0.612107 & 0.775786 & 0.387893 \tabularnewline
213 & 0.604397 & 0.791206 & 0.395603 \tabularnewline
214 & 0.56028 & 0.879439 & 0.43972 \tabularnewline
215 & 0.563905 & 0.872191 & 0.436095 \tabularnewline
216 & 0.52443 & 0.951139 & 0.47557 \tabularnewline
217 & 0.521451 & 0.957099 & 0.478549 \tabularnewline
218 & 0.485535 & 0.971069 & 0.514465 \tabularnewline
219 & 0.447552 & 0.895104 & 0.552448 \tabularnewline
220 & 0.412442 & 0.824884 & 0.587558 \tabularnewline
221 & 0.415987 & 0.831974 & 0.584013 \tabularnewline
222 & 0.463526 & 0.927053 & 0.536474 \tabularnewline
223 & 0.428488 & 0.856976 & 0.571512 \tabularnewline
224 & 0.577389 & 0.845223 & 0.422611 \tabularnewline
225 & 0.552219 & 0.895562 & 0.447781 \tabularnewline
226 & 0.603733 & 0.792533 & 0.396267 \tabularnewline
227 & 0.61234 & 0.775321 & 0.38766 \tabularnewline
228 & 0.66286 & 0.67428 & 0.33714 \tabularnewline
229 & 0.737935 & 0.52413 & 0.262065 \tabularnewline
230 & 0.762311 & 0.475378 & 0.237689 \tabularnewline
231 & 0.737659 & 0.524681 & 0.262341 \tabularnewline
232 & 0.702573 & 0.594854 & 0.297427 \tabularnewline
233 & 0.676316 & 0.647368 & 0.323684 \tabularnewline
234 & 0.651616 & 0.696767 & 0.348384 \tabularnewline
235 & 0.62008 & 0.75984 & 0.37992 \tabularnewline
236 & 0.69303 & 0.613939 & 0.30697 \tabularnewline
237 & 0.663921 & 0.672159 & 0.336079 \tabularnewline
238 & 0.611213 & 0.777574 & 0.388787 \tabularnewline
239 & 0.619175 & 0.76165 & 0.380825 \tabularnewline
240 & 0.564069 & 0.871862 & 0.435931 \tabularnewline
241 & 0.525804 & 0.948392 & 0.474196 \tabularnewline
242 & 0.46352 & 0.927039 & 0.53648 \tabularnewline
243 & 0.408667 & 0.817334 & 0.591333 \tabularnewline
244 & 0.351828 & 0.703657 & 0.648172 \tabularnewline
245 & 0.300856 & 0.601711 & 0.699144 \tabularnewline
246 & 0.241835 & 0.48367 & 0.758165 \tabularnewline
247 & 0.199105 & 0.398211 & 0.800895 \tabularnewline
248 & 0.420748 & 0.841496 & 0.579252 \tabularnewline
249 & 0.358483 & 0.716965 & 0.641517 \tabularnewline
250 & 0.291156 & 0.582312 & 0.708844 \tabularnewline
251 & 0.225465 & 0.45093 & 0.774535 \tabularnewline
252 & 0.185158 & 0.370316 & 0.814842 \tabularnewline
253 & 0.181512 & 0.363024 & 0.818488 \tabularnewline
254 & 0.307272 & 0.614543 & 0.692728 \tabularnewline
255 & 0.272957 & 0.545913 & 0.727043 \tabularnewline
256 & 0.197478 & 0.394957 & 0.802522 \tabularnewline
257 & 0.126681 & 0.253363 & 0.873319 \tabularnewline
258 & 0.0696005 & 0.139201 & 0.930399 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&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]20[/C][C]0.716437[/C][C]0.567127[/C][C]0.283563[/C][/ROW]
[ROW][C]21[/C][C]0.581498[/C][C]0.837004[/C][C]0.418502[/C][/ROW]
[ROW][C]22[/C][C]0.443492[/C][C]0.886984[/C][C]0.556508[/C][/ROW]
[ROW][C]23[/C][C]0.369547[/C][C]0.739093[/C][C]0.630453[/C][/ROW]
[ROW][C]24[/C][C]0.29935[/C][C]0.5987[/C][C]0.70065[/C][/ROW]
[ROW][C]25[/C][C]0.243873[/C][C]0.487745[/C][C]0.756127[/C][/ROW]
[ROW][C]26[/C][C]0.172381[/C][C]0.344761[/C][C]0.827619[/C][/ROW]
[ROW][C]27[/C][C]0.134846[/C][C]0.269692[/C][C]0.865154[/C][/ROW]
[ROW][C]28[/C][C]0.095813[/C][C]0.191626[/C][C]0.904187[/C][/ROW]
[ROW][C]29[/C][C]0.0615741[/C][C]0.123148[/C][C]0.938426[/C][/ROW]
[ROW][C]30[/C][C]0.0565664[/C][C]0.113133[/C][C]0.943434[/C][/ROW]
[ROW][C]31[/C][C]0.0464438[/C][C]0.0928875[/C][C]0.953556[/C][/ROW]
[ROW][C]32[/C][C]0.0290795[/C][C]0.058159[/C][C]0.97092[/C][/ROW]
[ROW][C]33[/C][C]0.0933369[/C][C]0.186674[/C][C]0.906663[/C][/ROW]
[ROW][C]34[/C][C]0.274677[/C][C]0.549354[/C][C]0.725323[/C][/ROW]
[ROW][C]35[/C][C]0.222552[/C][C]0.445104[/C][C]0.777448[/C][/ROW]
[ROW][C]36[/C][C]0.253679[/C][C]0.507359[/C][C]0.746321[/C][/ROW]
[ROW][C]37[/C][C]0.272521[/C][C]0.545042[/C][C]0.727479[/C][/ROW]
[ROW][C]38[/C][C]0.29064[/C][C]0.581279[/C][C]0.70936[/C][/ROW]
[ROW][C]39[/C][C]0.270189[/C][C]0.540378[/C][C]0.729811[/C][/ROW]
[ROW][C]40[/C][C]0.231412[/C][C]0.462825[/C][C]0.768588[/C][/ROW]
[ROW][C]41[/C][C]0.272332[/C][C]0.544663[/C][C]0.727668[/C][/ROW]
[ROW][C]42[/C][C]0.267134[/C][C]0.534267[/C][C]0.732866[/C][/ROW]
[ROW][C]43[/C][C]0.241042[/C][C]0.482083[/C][C]0.758958[/C][/ROW]
[ROW][C]44[/C][C]0.227709[/C][C]0.455417[/C][C]0.772291[/C][/ROW]
[ROW][C]45[/C][C]0.195223[/C][C]0.390446[/C][C]0.804777[/C][/ROW]
[ROW][C]46[/C][C]0.159777[/C][C]0.319554[/C][C]0.840223[/C][/ROW]
[ROW][C]47[/C][C]0.17321[/C][C]0.34642[/C][C]0.82679[/C][/ROW]
[ROW][C]48[/C][C]0.171725[/C][C]0.343449[/C][C]0.828275[/C][/ROW]
[ROW][C]49[/C][C]0.234625[/C][C]0.46925[/C][C]0.765375[/C][/ROW]
[ROW][C]50[/C][C]0.261161[/C][C]0.522322[/C][C]0.738839[/C][/ROW]
[ROW][C]51[/C][C]0.220402[/C][C]0.440804[/C][C]0.779598[/C][/ROW]
[ROW][C]52[/C][C]0.248969[/C][C]0.497937[/C][C]0.751031[/C][/ROW]
[ROW][C]53[/C][C]0.232694[/C][C]0.465387[/C][C]0.767306[/C][/ROW]
[ROW][C]54[/C][C]0.197477[/C][C]0.394954[/C][C]0.802523[/C][/ROW]
[ROW][C]55[/C][C]0.3126[/C][C]0.6252[/C][C]0.6874[/C][/ROW]
[ROW][C]56[/C][C]0.270908[/C][C]0.541816[/C][C]0.729092[/C][/ROW]
[ROW][C]57[/C][C]0.62658[/C][C]0.746841[/C][C]0.37342[/C][/ROW]
[ROW][C]58[/C][C]0.65924[/C][C]0.68152[/C][C]0.34076[/C][/ROW]
[ROW][C]59[/C][C]0.624491[/C][C]0.751018[/C][C]0.375509[/C][/ROW]
[ROW][C]60[/C][C]0.619162[/C][C]0.761676[/C][C]0.380838[/C][/ROW]
[ROW][C]61[/C][C]0.627761[/C][C]0.744477[/C][C]0.372239[/C][/ROW]
[ROW][C]62[/C][C]0.620661[/C][C]0.758679[/C][C]0.379339[/C][/ROW]
[ROW][C]63[/C][C]0.725309[/C][C]0.549382[/C][C]0.274691[/C][/ROW]
[ROW][C]64[/C][C]0.78527[/C][C]0.42946[/C][C]0.21473[/C][/ROW]
[ROW][C]65[/C][C]0.79079[/C][C]0.418421[/C][C]0.20921[/C][/ROW]
[ROW][C]66[/C][C]0.768036[/C][C]0.463927[/C][C]0.231964[/C][/ROW]
[ROW][C]67[/C][C]0.739996[/C][C]0.520008[/C][C]0.260004[/C][/ROW]
[ROW][C]68[/C][C]0.706291[/C][C]0.587419[/C][C]0.293709[/C][/ROW]
[ROW][C]69[/C][C]0.737927[/C][C]0.524147[/C][C]0.262073[/C][/ROW]
[ROW][C]70[/C][C]0.713449[/C][C]0.573102[/C][C]0.286551[/C][/ROW]
[ROW][C]71[/C][C]0.677323[/C][C]0.645355[/C][C]0.322677[/C][/ROW]
[ROW][C]72[/C][C]0.644625[/C][C]0.710751[/C][C]0.355375[/C][/ROW]
[ROW][C]73[/C][C]0.616601[/C][C]0.766797[/C][C]0.383399[/C][/ROW]
[ROW][C]74[/C][C]0.661407[/C][C]0.677187[/C][C]0.338593[/C][/ROW]
[ROW][C]75[/C][C]0.633853[/C][C]0.732295[/C][C]0.366147[/C][/ROW]
[ROW][C]76[/C][C]0.620764[/C][C]0.758471[/C][C]0.379236[/C][/ROW]
[ROW][C]77[/C][C]0.597945[/C][C]0.804111[/C][C]0.402055[/C][/ROW]
[ROW][C]78[/C][C]0.58126[/C][C]0.83748[/C][C]0.41874[/C][/ROW]
[ROW][C]79[/C][C]0.541647[/C][C]0.916707[/C][C]0.458353[/C][/ROW]
[ROW][C]80[/C][C]0.538124[/C][C]0.923752[/C][C]0.461876[/C][/ROW]
[ROW][C]81[/C][C]0.498909[/C][C]0.997818[/C][C]0.501091[/C][/ROW]
[ROW][C]82[/C][C]0.5199[/C][C]0.960201[/C][C]0.4801[/C][/ROW]
[ROW][C]83[/C][C]0.482625[/C][C]0.96525[/C][C]0.517375[/C][/ROW]
[ROW][C]84[/C][C]0.677422[/C][C]0.645156[/C][C]0.322578[/C][/ROW]
[ROW][C]85[/C][C]0.670491[/C][C]0.659017[/C][C]0.329509[/C][/ROW]
[ROW][C]86[/C][C]0.635809[/C][C]0.728382[/C][C]0.364191[/C][/ROW]
[ROW][C]87[/C][C]0.610822[/C][C]0.778356[/C][C]0.389178[/C][/ROW]
[ROW][C]88[/C][C]0.629764[/C][C]0.740471[/C][C]0.370236[/C][/ROW]
[ROW][C]89[/C][C]0.612663[/C][C]0.774674[/C][C]0.387337[/C][/ROW]
[ROW][C]90[/C][C]0.607896[/C][C]0.784208[/C][C]0.392104[/C][/ROW]
[ROW][C]91[/C][C]0.616317[/C][C]0.767366[/C][C]0.383683[/C][/ROW]
[ROW][C]92[/C][C]0.763276[/C][C]0.473448[/C][C]0.236724[/C][/ROW]
[ROW][C]93[/C][C]0.756487[/C][C]0.487026[/C][C]0.243513[/C][/ROW]
[ROW][C]94[/C][C]0.735586[/C][C]0.528827[/C][C]0.264414[/C][/ROW]
[ROW][C]95[/C][C]0.719821[/C][C]0.560359[/C][C]0.280179[/C][/ROW]
[ROW][C]96[/C][C]0.693177[/C][C]0.613646[/C][C]0.306823[/C][/ROW]
[ROW][C]97[/C][C]0.732963[/C][C]0.534075[/C][C]0.267037[/C][/ROW]
[ROW][C]98[/C][C]0.718103[/C][C]0.563794[/C][C]0.281897[/C][/ROW]
[ROW][C]99[/C][C]0.772059[/C][C]0.455883[/C][C]0.227941[/C][/ROW]
[ROW][C]100[/C][C]0.773879[/C][C]0.452242[/C][C]0.226121[/C][/ROW]
[ROW][C]101[/C][C]0.757096[/C][C]0.485808[/C][C]0.242904[/C][/ROW]
[ROW][C]102[/C][C]0.72889[/C][C]0.54222[/C][C]0.27111[/C][/ROW]
[ROW][C]103[/C][C]0.714343[/C][C]0.571314[/C][C]0.285657[/C][/ROW]
[ROW][C]104[/C][C]0.700289[/C][C]0.599421[/C][C]0.299711[/C][/ROW]
[ROW][C]105[/C][C]0.747364[/C][C]0.505273[/C][C]0.252636[/C][/ROW]
[ROW][C]106[/C][C]0.727676[/C][C]0.544649[/C][C]0.272324[/C][/ROW]
[ROW][C]107[/C][C]0.785903[/C][C]0.428195[/C][C]0.214097[/C][/ROW]
[ROW][C]108[/C][C]0.864336[/C][C]0.271327[/C][C]0.135664[/C][/ROW]
[ROW][C]109[/C][C]0.845811[/C][C]0.308378[/C][C]0.154189[/C][/ROW]
[ROW][C]110[/C][C]0.831982[/C][C]0.336035[/C][C]0.168018[/C][/ROW]
[ROW][C]111[/C][C]0.813393[/C][C]0.373214[/C][C]0.186607[/C][/ROW]
[ROW][C]112[/C][C]0.793565[/C][C]0.412869[/C][C]0.206435[/C][/ROW]
[ROW][C]113[/C][C]0.845893[/C][C]0.308214[/C][C]0.154107[/C][/ROW]
[ROW][C]114[/C][C]0.827074[/C][C]0.345852[/C][C]0.172926[/C][/ROW]
[ROW][C]115[/C][C]0.901371[/C][C]0.197257[/C][C]0.0986286[/C][/ROW]
[ROW][C]116[/C][C]0.893585[/C][C]0.212831[/C][C]0.106415[/C][/ROW]
[ROW][C]117[/C][C]0.885039[/C][C]0.229922[/C][C]0.114961[/C][/ROW]
[ROW][C]118[/C][C]0.876709[/C][C]0.246581[/C][C]0.123291[/C][/ROW]
[ROW][C]119[/C][C]0.884542[/C][C]0.230917[/C][C]0.115458[/C][/ROW]
[ROW][C]120[/C][C]0.870416[/C][C]0.259167[/C][C]0.129584[/C][/ROW]
[ROW][C]121[/C][C]0.895024[/C][C]0.209951[/C][C]0.104976[/C][/ROW]
[ROW][C]122[/C][C]0.904611[/C][C]0.190778[/C][C]0.0953892[/C][/ROW]
[ROW][C]123[/C][C]0.897357[/C][C]0.205285[/C][C]0.102643[/C][/ROW]
[ROW][C]124[/C][C]0.940595[/C][C]0.11881[/C][C]0.0594049[/C][/ROW]
[ROW][C]125[/C][C]0.941426[/C][C]0.117148[/C][C]0.0585741[/C][/ROW]
[ROW][C]126[/C][C]0.932296[/C][C]0.135407[/C][C]0.0677037[/C][/ROW]
[ROW][C]127[/C][C]0.923912[/C][C]0.152177[/C][C]0.0760885[/C][/ROW]
[ROW][C]128[/C][C]0.911194[/C][C]0.177611[/C][C]0.0888056[/C][/ROW]
[ROW][C]129[/C][C]0.906984[/C][C]0.186032[/C][C]0.0930161[/C][/ROW]
[ROW][C]130[/C][C]0.892574[/C][C]0.214851[/C][C]0.107426[/C][/ROW]
[ROW][C]131[/C][C]0.879543[/C][C]0.240913[/C][C]0.120457[/C][/ROW]
[ROW][C]132[/C][C]0.877089[/C][C]0.245823[/C][C]0.122911[/C][/ROW]
[ROW][C]133[/C][C]0.862324[/C][C]0.275352[/C][C]0.137676[/C][/ROW]
[ROW][C]134[/C][C]0.844301[/C][C]0.311398[/C][C]0.155699[/C][/ROW]
[ROW][C]135[/C][C]0.821805[/C][C]0.35639[/C][C]0.178195[/C][/ROW]
[ROW][C]136[/C][C]0.79884[/C][C]0.40232[/C][C]0.20116[/C][/ROW]
[ROW][C]137[/C][C]0.818186[/C][C]0.363628[/C][C]0.181814[/C][/ROW]
[ROW][C]138[/C][C]0.808931[/C][C]0.382139[/C][C]0.191069[/C][/ROW]
[ROW][C]139[/C][C]0.787459[/C][C]0.425082[/C][C]0.212541[/C][/ROW]
[ROW][C]140[/C][C]0.761541[/C][C]0.476917[/C][C]0.238459[/C][/ROW]
[ROW][C]141[/C][C]0.734105[/C][C]0.531791[/C][C]0.265895[/C][/ROW]
[ROW][C]142[/C][C]0.734229[/C][C]0.531542[/C][C]0.265771[/C][/ROW]
[ROW][C]143[/C][C]0.706801[/C][C]0.586398[/C][C]0.293199[/C][/ROW]
[ROW][C]144[/C][C]0.744735[/C][C]0.51053[/C][C]0.255265[/C][/ROW]
[ROW][C]145[/C][C]0.722184[/C][C]0.555633[/C][C]0.277816[/C][/ROW]
[ROW][C]146[/C][C]0.691133[/C][C]0.617734[/C][C]0.308867[/C][/ROW]
[ROW][C]147[/C][C]0.661304[/C][C]0.677391[/C][C]0.338696[/C][/ROW]
[ROW][C]148[/C][C]0.628337[/C][C]0.743326[/C][C]0.371663[/C][/ROW]
[ROW][C]149[/C][C]0.60062[/C][C]0.798761[/C][C]0.39938[/C][/ROW]
[ROW][C]150[/C][C]0.596594[/C][C]0.806813[/C][C]0.403406[/C][/ROW]
[ROW][C]151[/C][C]0.855645[/C][C]0.28871[/C][C]0.144355[/C][/ROW]
[ROW][C]152[/C][C]0.837892[/C][C]0.324216[/C][C]0.162108[/C][/ROW]
[ROW][C]153[/C][C]0.841172[/C][C]0.317657[/C][C]0.158828[/C][/ROW]
[ROW][C]154[/C][C]0.823808[/C][C]0.352383[/C][C]0.176192[/C][/ROW]
[ROW][C]155[/C][C]0.834177[/C][C]0.331646[/C][C]0.165823[/C][/ROW]
[ROW][C]156[/C][C]0.816199[/C][C]0.367602[/C][C]0.183801[/C][/ROW]
[ROW][C]157[/C][C]0.795111[/C][C]0.409778[/C][C]0.204889[/C][/ROW]
[ROW][C]158[/C][C]0.770508[/C][C]0.458985[/C][C]0.229492[/C][/ROW]
[ROW][C]159[/C][C]0.772021[/C][C]0.455957[/C][C]0.227979[/C][/ROW]
[ROW][C]160[/C][C]0.769707[/C][C]0.460585[/C][C]0.230293[/C][/ROW]
[ROW][C]161[/C][C]0.752225[/C][C]0.495551[/C][C]0.247775[/C][/ROW]
[ROW][C]162[/C][C]0.749737[/C][C]0.500526[/C][C]0.250263[/C][/ROW]
[ROW][C]163[/C][C]0.742432[/C][C]0.515135[/C][C]0.257568[/C][/ROW]
[ROW][C]164[/C][C]0.971599[/C][C]0.0568019[/C][C]0.0284009[/C][/ROW]
[ROW][C]165[/C][C]0.965083[/C][C]0.0698347[/C][C]0.0349173[/C][/ROW]
[ROW][C]166[/C][C]0.960254[/C][C]0.0794918[/C][C]0.0397459[/C][/ROW]
[ROW][C]167[/C][C]0.953375[/C][C]0.0932499[/C][C]0.046625[/C][/ROW]
[ROW][C]168[/C][C]0.952154[/C][C]0.0956926[/C][C]0.0478463[/C][/ROW]
[ROW][C]169[/C][C]0.94302[/C][C]0.11396[/C][C]0.0569798[/C][/ROW]
[ROW][C]170[/C][C]0.947353[/C][C]0.105295[/C][C]0.0526474[/C][/ROW]
[ROW][C]171[/C][C]0.940206[/C][C]0.119588[/C][C]0.0597938[/C][/ROW]
[ROW][C]172[/C][C]0.93754[/C][C]0.124919[/C][C]0.0624597[/C][/ROW]
[ROW][C]173[/C][C]0.936153[/C][C]0.127694[/C][C]0.0638472[/C][/ROW]
[ROW][C]174[/C][C]0.926584[/C][C]0.146832[/C][C]0.073416[/C][/ROW]
[ROW][C]175[/C][C]0.914794[/C][C]0.170412[/C][C]0.0852059[/C][/ROW]
[ROW][C]176[/C][C]0.921009[/C][C]0.157982[/C][C]0.0789911[/C][/ROW]
[ROW][C]177[/C][C]0.912291[/C][C]0.175418[/C][C]0.087709[/C][/ROW]
[ROW][C]178[/C][C]0.910167[/C][C]0.179665[/C][C]0.0898325[/C][/ROW]
[ROW][C]179[/C][C]0.898763[/C][C]0.202473[/C][C]0.101237[/C][/ROW]
[ROW][C]180[/C][C]0.895695[/C][C]0.208609[/C][C]0.104305[/C][/ROW]
[ROW][C]181[/C][C]0.911043[/C][C]0.177915[/C][C]0.0889575[/C][/ROW]
[ROW][C]182[/C][C]0.916799[/C][C]0.166401[/C][C]0.0832006[/C][/ROW]
[ROW][C]183[/C][C]0.913658[/C][C]0.172684[/C][C]0.0863418[/C][/ROW]
[ROW][C]184[/C][C]0.89808[/C][C]0.203841[/C][C]0.10192[/C][/ROW]
[ROW][C]185[/C][C]0.904754[/C][C]0.190492[/C][C]0.0952459[/C][/ROW]
[ROW][C]186[/C][C]0.889098[/C][C]0.221804[/C][C]0.110902[/C][/ROW]
[ROW][C]187[/C][C]0.90123[/C][C]0.197539[/C][C]0.0987697[/C][/ROW]
[ROW][C]188[/C][C]0.903436[/C][C]0.193127[/C][C]0.0965637[/C][/ROW]
[ROW][C]189[/C][C]0.901199[/C][C]0.197601[/C][C]0.0988007[/C][/ROW]
[ROW][C]190[/C][C]0.884326[/C][C]0.231349[/C][C]0.115674[/C][/ROW]
[ROW][C]191[/C][C]0.88071[/C][C]0.23858[/C][C]0.11929[/C][/ROW]
[ROW][C]192[/C][C]0.864098[/C][C]0.271804[/C][C]0.135902[/C][/ROW]
[ROW][C]193[/C][C]0.888638[/C][C]0.222724[/C][C]0.111362[/C][/ROW]
[ROW][C]194[/C][C]0.903689[/C][C]0.192622[/C][C]0.0963108[/C][/ROW]
[ROW][C]195[/C][C]0.892657[/C][C]0.214685[/C][C]0.107343[/C][/ROW]
[ROW][C]196[/C][C]0.883294[/C][C]0.233412[/C][C]0.116706[/C][/ROW]
[ROW][C]197[/C][C]0.893294[/C][C]0.213411[/C][C]0.106706[/C][/ROW]
[ROW][C]198[/C][C]0.873561[/C][C]0.252878[/C][C]0.126439[/C][/ROW]
[ROW][C]199[/C][C]0.863452[/C][C]0.273095[/C][C]0.136548[/C][/ROW]
[ROW][C]200[/C][C]0.840738[/C][C]0.318523[/C][C]0.159262[/C][/ROW]
[ROW][C]201[/C][C]0.818522[/C][C]0.362957[/C][C]0.181478[/C][/ROW]
[ROW][C]202[/C][C]0.796129[/C][C]0.407741[/C][C]0.203871[/C][/ROW]
[ROW][C]203[/C][C]0.809668[/C][C]0.380665[/C][C]0.190332[/C][/ROW]
[ROW][C]204[/C][C]0.778709[/C][C]0.442582[/C][C]0.221291[/C][/ROW]
[ROW][C]205[/C][C]0.762714[/C][C]0.474572[/C][C]0.237286[/C][/ROW]
[ROW][C]206[/C][C]0.757317[/C][C]0.485366[/C][C]0.242683[/C][/ROW]
[ROW][C]207[/C][C]0.750494[/C][C]0.499011[/C][C]0.249506[/C][/ROW]
[ROW][C]208[/C][C]0.718929[/C][C]0.562141[/C][C]0.281071[/C][/ROW]
[ROW][C]209[/C][C]0.695959[/C][C]0.608082[/C][C]0.304041[/C][/ROW]
[ROW][C]210[/C][C]0.692348[/C][C]0.615304[/C][C]0.307652[/C][/ROW]
[ROW][C]211[/C][C]0.653935[/C][C]0.69213[/C][C]0.346065[/C][/ROW]
[ROW][C]212[/C][C]0.612107[/C][C]0.775786[/C][C]0.387893[/C][/ROW]
[ROW][C]213[/C][C]0.604397[/C][C]0.791206[/C][C]0.395603[/C][/ROW]
[ROW][C]214[/C][C]0.56028[/C][C]0.879439[/C][C]0.43972[/C][/ROW]
[ROW][C]215[/C][C]0.563905[/C][C]0.872191[/C][C]0.436095[/C][/ROW]
[ROW][C]216[/C][C]0.52443[/C][C]0.951139[/C][C]0.47557[/C][/ROW]
[ROW][C]217[/C][C]0.521451[/C][C]0.957099[/C][C]0.478549[/C][/ROW]
[ROW][C]218[/C][C]0.485535[/C][C]0.971069[/C][C]0.514465[/C][/ROW]
[ROW][C]219[/C][C]0.447552[/C][C]0.895104[/C][C]0.552448[/C][/ROW]
[ROW][C]220[/C][C]0.412442[/C][C]0.824884[/C][C]0.587558[/C][/ROW]
[ROW][C]221[/C][C]0.415987[/C][C]0.831974[/C][C]0.584013[/C][/ROW]
[ROW][C]222[/C][C]0.463526[/C][C]0.927053[/C][C]0.536474[/C][/ROW]
[ROW][C]223[/C][C]0.428488[/C][C]0.856976[/C][C]0.571512[/C][/ROW]
[ROW][C]224[/C][C]0.577389[/C][C]0.845223[/C][C]0.422611[/C][/ROW]
[ROW][C]225[/C][C]0.552219[/C][C]0.895562[/C][C]0.447781[/C][/ROW]
[ROW][C]226[/C][C]0.603733[/C][C]0.792533[/C][C]0.396267[/C][/ROW]
[ROW][C]227[/C][C]0.61234[/C][C]0.775321[/C][C]0.38766[/C][/ROW]
[ROW][C]228[/C][C]0.66286[/C][C]0.67428[/C][C]0.33714[/C][/ROW]
[ROW][C]229[/C][C]0.737935[/C][C]0.52413[/C][C]0.262065[/C][/ROW]
[ROW][C]230[/C][C]0.762311[/C][C]0.475378[/C][C]0.237689[/C][/ROW]
[ROW][C]231[/C][C]0.737659[/C][C]0.524681[/C][C]0.262341[/C][/ROW]
[ROW][C]232[/C][C]0.702573[/C][C]0.594854[/C][C]0.297427[/C][/ROW]
[ROW][C]233[/C][C]0.676316[/C][C]0.647368[/C][C]0.323684[/C][/ROW]
[ROW][C]234[/C][C]0.651616[/C][C]0.696767[/C][C]0.348384[/C][/ROW]
[ROW][C]235[/C][C]0.62008[/C][C]0.75984[/C][C]0.37992[/C][/ROW]
[ROW][C]236[/C][C]0.69303[/C][C]0.613939[/C][C]0.30697[/C][/ROW]
[ROW][C]237[/C][C]0.663921[/C][C]0.672159[/C][C]0.336079[/C][/ROW]
[ROW][C]238[/C][C]0.611213[/C][C]0.777574[/C][C]0.388787[/C][/ROW]
[ROW][C]239[/C][C]0.619175[/C][C]0.76165[/C][C]0.380825[/C][/ROW]
[ROW][C]240[/C][C]0.564069[/C][C]0.871862[/C][C]0.435931[/C][/ROW]
[ROW][C]241[/C][C]0.525804[/C][C]0.948392[/C][C]0.474196[/C][/ROW]
[ROW][C]242[/C][C]0.46352[/C][C]0.927039[/C][C]0.53648[/C][/ROW]
[ROW][C]243[/C][C]0.408667[/C][C]0.817334[/C][C]0.591333[/C][/ROW]
[ROW][C]244[/C][C]0.351828[/C][C]0.703657[/C][C]0.648172[/C][/ROW]
[ROW][C]245[/C][C]0.300856[/C][C]0.601711[/C][C]0.699144[/C][/ROW]
[ROW][C]246[/C][C]0.241835[/C][C]0.48367[/C][C]0.758165[/C][/ROW]
[ROW][C]247[/C][C]0.199105[/C][C]0.398211[/C][C]0.800895[/C][/ROW]
[ROW][C]248[/C][C]0.420748[/C][C]0.841496[/C][C]0.579252[/C][/ROW]
[ROW][C]249[/C][C]0.358483[/C][C]0.716965[/C][C]0.641517[/C][/ROW]
[ROW][C]250[/C][C]0.291156[/C][C]0.582312[/C][C]0.708844[/C][/ROW]
[ROW][C]251[/C][C]0.225465[/C][C]0.45093[/C][C]0.774535[/C][/ROW]
[ROW][C]252[/C][C]0.185158[/C][C]0.370316[/C][C]0.814842[/C][/ROW]
[ROW][C]253[/C][C]0.181512[/C][C]0.363024[/C][C]0.818488[/C][/ROW]
[ROW][C]254[/C][C]0.307272[/C][C]0.614543[/C][C]0.692728[/C][/ROW]
[ROW][C]255[/C][C]0.272957[/C][C]0.545913[/C][C]0.727043[/C][/ROW]
[ROW][C]256[/C][C]0.197478[/C][C]0.394957[/C][C]0.802522[/C][/ROW]
[ROW][C]257[/C][C]0.126681[/C][C]0.253363[/C][C]0.873319[/C][/ROW]
[ROW][C]258[/C][C]0.0696005[/C][C]0.139201[/C][C]0.930399[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
20	0.716437	0.567127	0.283563
21	0.581498	0.837004	0.418502
22	0.443492	0.886984	0.556508
23	0.369547	0.739093	0.630453
24	0.29935	0.5987	0.70065
25	0.243873	0.487745	0.756127
26	0.172381	0.344761	0.827619
27	0.134846	0.269692	0.865154
28	0.095813	0.191626	0.904187
29	0.0615741	0.123148	0.938426
30	0.0565664	0.113133	0.943434
31	0.0464438	0.0928875	0.953556
32	0.0290795	0.058159	0.97092
33	0.0933369	0.186674	0.906663
34	0.274677	0.549354	0.725323
35	0.222552	0.445104	0.777448
36	0.253679	0.507359	0.746321
37	0.272521	0.545042	0.727479
38	0.29064	0.581279	0.70936
39	0.270189	0.540378	0.729811
40	0.231412	0.462825	0.768588
41	0.272332	0.544663	0.727668
42	0.267134	0.534267	0.732866
43	0.241042	0.482083	0.758958
44	0.227709	0.455417	0.772291
45	0.195223	0.390446	0.804777
46	0.159777	0.319554	0.840223
47	0.17321	0.34642	0.82679
48	0.171725	0.343449	0.828275
49	0.234625	0.46925	0.765375
50	0.261161	0.522322	0.738839
51	0.220402	0.440804	0.779598
52	0.248969	0.497937	0.751031
53	0.232694	0.465387	0.767306
54	0.197477	0.394954	0.802523
55	0.3126	0.6252	0.6874
56	0.270908	0.541816	0.729092
57	0.62658	0.746841	0.37342
58	0.65924	0.68152	0.34076
59	0.624491	0.751018	0.375509
60	0.619162	0.761676	0.380838
61	0.627761	0.744477	0.372239
62	0.620661	0.758679	0.379339
63	0.725309	0.549382	0.274691
64	0.78527	0.42946	0.21473
65	0.79079	0.418421	0.20921
66	0.768036	0.463927	0.231964
67	0.739996	0.520008	0.260004
68	0.706291	0.587419	0.293709
69	0.737927	0.524147	0.262073
70	0.713449	0.573102	0.286551
71	0.677323	0.645355	0.322677
72	0.644625	0.710751	0.355375
73	0.616601	0.766797	0.383399
74	0.661407	0.677187	0.338593
75	0.633853	0.732295	0.366147
76	0.620764	0.758471	0.379236
77	0.597945	0.804111	0.402055
78	0.58126	0.83748	0.41874
79	0.541647	0.916707	0.458353
80	0.538124	0.923752	0.461876
81	0.498909	0.997818	0.501091
82	0.5199	0.960201	0.4801
83	0.482625	0.96525	0.517375
84	0.677422	0.645156	0.322578
85	0.670491	0.659017	0.329509
86	0.635809	0.728382	0.364191
87	0.610822	0.778356	0.389178
88	0.629764	0.740471	0.370236
89	0.612663	0.774674	0.387337
90	0.607896	0.784208	0.392104
91	0.616317	0.767366	0.383683
92	0.763276	0.473448	0.236724
93	0.756487	0.487026	0.243513
94	0.735586	0.528827	0.264414
95	0.719821	0.560359	0.280179
96	0.693177	0.613646	0.306823
97	0.732963	0.534075	0.267037
98	0.718103	0.563794	0.281897
99	0.772059	0.455883	0.227941
100	0.773879	0.452242	0.226121
101	0.757096	0.485808	0.242904
102	0.72889	0.54222	0.27111
103	0.714343	0.571314	0.285657
104	0.700289	0.599421	0.299711
105	0.747364	0.505273	0.252636
106	0.727676	0.544649	0.272324
107	0.785903	0.428195	0.214097
108	0.864336	0.271327	0.135664
109	0.845811	0.308378	0.154189
110	0.831982	0.336035	0.168018
111	0.813393	0.373214	0.186607
112	0.793565	0.412869	0.206435
113	0.845893	0.308214	0.154107
114	0.827074	0.345852	0.172926
115	0.901371	0.197257	0.0986286
116	0.893585	0.212831	0.106415
117	0.885039	0.229922	0.114961
118	0.876709	0.246581	0.123291
119	0.884542	0.230917	0.115458
120	0.870416	0.259167	0.129584
121	0.895024	0.209951	0.104976
122	0.904611	0.190778	0.0953892
123	0.897357	0.205285	0.102643
124	0.940595	0.11881	0.0594049
125	0.941426	0.117148	0.0585741
126	0.932296	0.135407	0.0677037
127	0.923912	0.152177	0.0760885
128	0.911194	0.177611	0.0888056
129	0.906984	0.186032	0.0930161
130	0.892574	0.214851	0.107426
131	0.879543	0.240913	0.120457
132	0.877089	0.245823	0.122911
133	0.862324	0.275352	0.137676
134	0.844301	0.311398	0.155699
135	0.821805	0.35639	0.178195
136	0.79884	0.40232	0.20116
137	0.818186	0.363628	0.181814
138	0.808931	0.382139	0.191069
139	0.787459	0.425082	0.212541
140	0.761541	0.476917	0.238459
141	0.734105	0.531791	0.265895
142	0.734229	0.531542	0.265771
143	0.706801	0.586398	0.293199
144	0.744735	0.51053	0.255265
145	0.722184	0.555633	0.277816
146	0.691133	0.617734	0.308867
147	0.661304	0.677391	0.338696
148	0.628337	0.743326	0.371663
149	0.60062	0.798761	0.39938
150	0.596594	0.806813	0.403406
151	0.855645	0.28871	0.144355
152	0.837892	0.324216	0.162108
153	0.841172	0.317657	0.158828
154	0.823808	0.352383	0.176192
155	0.834177	0.331646	0.165823
156	0.816199	0.367602	0.183801
157	0.795111	0.409778	0.204889
158	0.770508	0.458985	0.229492
159	0.772021	0.455957	0.227979
160	0.769707	0.460585	0.230293
161	0.752225	0.495551	0.247775
162	0.749737	0.500526	0.250263
163	0.742432	0.515135	0.257568
164	0.971599	0.0568019	0.0284009
165	0.965083	0.0698347	0.0349173
166	0.960254	0.0794918	0.0397459
167	0.953375	0.0932499	0.046625
168	0.952154	0.0956926	0.0478463
169	0.94302	0.11396	0.0569798
170	0.947353	0.105295	0.0526474
171	0.940206	0.119588	0.0597938
172	0.93754	0.124919	0.0624597
173	0.936153	0.127694	0.0638472
174	0.926584	0.146832	0.073416
175	0.914794	0.170412	0.0852059
176	0.921009	0.157982	0.0789911
177	0.912291	0.175418	0.087709
178	0.910167	0.179665	0.0898325
179	0.898763	0.202473	0.101237
180	0.895695	0.208609	0.104305
181	0.911043	0.177915	0.0889575
182	0.916799	0.166401	0.0832006
183	0.913658	0.172684	0.0863418
184	0.89808	0.203841	0.10192
185	0.904754	0.190492	0.0952459
186	0.889098	0.221804	0.110902
187	0.90123	0.197539	0.0987697
188	0.903436	0.193127	0.0965637
189	0.901199	0.197601	0.0988007
190	0.884326	0.231349	0.115674
191	0.88071	0.23858	0.11929
192	0.864098	0.271804	0.135902
193	0.888638	0.222724	0.111362
194	0.903689	0.192622	0.0963108
195	0.892657	0.214685	0.107343
196	0.883294	0.233412	0.116706
197	0.893294	0.213411	0.106706
198	0.873561	0.252878	0.126439
199	0.863452	0.273095	0.136548
200	0.840738	0.318523	0.159262
201	0.818522	0.362957	0.181478
202	0.796129	0.407741	0.203871
203	0.809668	0.380665	0.190332
204	0.778709	0.442582	0.221291
205	0.762714	0.474572	0.237286
206	0.757317	0.485366	0.242683
207	0.750494	0.499011	0.249506
208	0.718929	0.562141	0.281071
209	0.695959	0.608082	0.304041
210	0.692348	0.615304	0.307652
211	0.653935	0.69213	0.346065
212	0.612107	0.775786	0.387893
213	0.604397	0.791206	0.395603
214	0.56028	0.879439	0.43972
215	0.563905	0.872191	0.436095
216	0.52443	0.951139	0.47557
217	0.521451	0.957099	0.478549
218	0.485535	0.971069	0.514465
219	0.447552	0.895104	0.552448
220	0.412442	0.824884	0.587558
221	0.415987	0.831974	0.584013
222	0.463526	0.927053	0.536474
223	0.428488	0.856976	0.571512
224	0.577389	0.845223	0.422611
225	0.552219	0.895562	0.447781
226	0.603733	0.792533	0.396267
227	0.61234	0.775321	0.38766
228	0.66286	0.67428	0.33714
229	0.737935	0.52413	0.262065
230	0.762311	0.475378	0.237689
231	0.737659	0.524681	0.262341
232	0.702573	0.594854	0.297427
233	0.676316	0.647368	0.323684
234	0.651616	0.696767	0.348384
235	0.62008	0.75984	0.37992
236	0.69303	0.613939	0.30697
237	0.663921	0.672159	0.336079
238	0.611213	0.777574	0.388787
239	0.619175	0.76165	0.380825
240	0.564069	0.871862	0.435931
241	0.525804	0.948392	0.474196
242	0.46352	0.927039	0.53648
243	0.408667	0.817334	0.591333
244	0.351828	0.703657	0.648172
245	0.300856	0.601711	0.699144
246	0.241835	0.48367	0.758165
247	0.199105	0.398211	0.800895
248	0.420748	0.841496	0.579252
249	0.358483	0.716965	0.641517
250	0.291156	0.582312	0.708844
251	0.225465	0.45093	0.774535
252	0.185158	0.370316	0.814842
253	0.181512	0.363024	0.818488
254	0.307272	0.614543	0.692728
255	0.272957	0.545913	0.727043
256	0.197478	0.394957	0.802522
257	0.126681	0.253363	0.873319
258	0.0696005	0.139201	0.930399

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	7	0.0292887	OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 7 & 0.0292887 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=269098&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]7[/C][C]0.0292887[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=269098&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=269098&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	0	0	OK
10% type I error level	7	0.0292887	OK

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code