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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 16:08:33 +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/t1418659738w8yjasnv6um5erd.htm/, Retrieved Thu, 16 May 2024 12:46:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268697, Retrieved Thu, 16 May 2024 12:46:59 +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 16:08:33] [afff6d6b458ee8576605d3685f592a9b] [Current]

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7.5 26 50 4 25 1.00 0.50 0.67 0.67 0.50 149 149 0
6.0 57 62 4 16 0.89 0.50 0.83 0.33 1.00 139 139 139
6.5 37 54 5 25 0.89 0.40 1.00 0.67 1.00 148 148 0
1.0 67 71 4 29 0.89 0.50 0.83 0.00 0.00 158 158 158
1.0 43 54 4 25 0.89 0.70 0.67 0.00 1.00 128 128 128
5.5 52 65 9 23 0.78 0.30 0.00 0.00 0.50 224 224 224
8.5 52 73 8 22 0.89 0.40 0.83 0.67 0.00 159 159 0
6.5 43 52 11 23 1.00 0.40 0.50 0.67 1.00 105 105 105
4.5 84 84 4 35 0.89 0.70 0.83 0.00 0.00 159 159 159
2.0 67 42 4 29 0.78 0.60 0.33 0.67 0.50 167 167 167
5.0 49 66 6 27 1.00 0.60 0.50 1.00 0.50 165 165 165
0.5 70 65 4 26 0.78 0.20 0.67 0.00 0.50 159 159 159
5.0 52 78 8 22 0.89 0.40 1.00 0.00 0.50 119 119 119
5.0 58 73 4 31 0.89 0.40 0.50 0.67 1.00 176 176 0
2.5 68 75 4 17 0.89 0.50 0.67 0.33 0.00 54 54 0
5.0 62 72 11 28 0.89 0.30 0.17 0.67 0.50 91 0 0
5.5 43 66 4 30 0.89 0.40 0.83 0.33 0.50 163 163 163
3.5 56 70 4 26 0.67 0.70 0.67 0.33 1.00 124 124 0
3.0 56 61 6 21 1.00 0.50 0.67 0.33 1.00 137 0 137
4.0 74 81 6 26 0.78 0.20 0.67 0.00 1.00 121 121 0
0.5 65 71 4 34 0.78 0.30 0.50 0.67 0.50 153 153 153
6.5 63 69 8 29 0.89 0.60 1.00 0.33 1.00 148 148 148
4.5 58 71 5 28 0.78 0.60 0.83 0.33 1.00 221 221 0
7.5 57 72 4 22 0.89 0.20 0.83 0.33 1.00 188 188 188
5.5 63 68 9 22 0.89 0.70 1.00 0.67 0.00 149 149 149
4.0 53 70 4 25 0.33 0.20 0.67 0.00 0.00 244 244 244
7.5 57 68 7 21 1.00 1.00 1.00 0.33 1.00 148 0 148
7.0 51 61 10 28 0.89 0.40 0.83 0.67 0.50 92 0 0
4.0 64 67 4 27 0.89 0.40 1.00 1.00 1.00 150 150 150
5.5 53 76 4 30 0.67 0.20 0.83 0.67 0.50 153 153 0
2.5 29 70 7 23 0.56 0.40 0.67 0.33 1.00 94 94 0
5.5 54 60 12 27 0.89 0.40 0.67 0.00 1.00 156 156 0
3.5 58 72 7 27 0.89 0.70 1.00 0.67 0.50 132 132 132
2.5 43 69 5 31 1.00 0.20 0.67 0.67 0.50 161 161 161
4.5 51 71 8 28 0.78 0.60 1.00 1.00 0.50 105 105 105
4.5 53 62 5 16 0.78 0.30 1.00 1.00 0.50 97 97 97
4.5 54 70 4 13 0.33 0.30 0.50 0.33 0.00 151 151 0
6.0 56 64 9 30 0.78 0.20 0.67 0.00 0.00 131 0 131
2.5 61 58 7 25 0.89 0.50 0.83 0.67 0.50 166 166 166
5.0 47 76 4 16 0.89 0.70 1.00 0.67 1.00 157 157 0
0.0 39 52 4 26 0.78 0.60 1.00 0.67 0.50 111 111 111
5.0 48 59 4 22 0.89 0.40 1.00 0.67 1.00 145 145 145
6.5 50 68 4 22 0.89 0.60 1.00 0.33 1.00 162 162 162
5.0 35 76 4 28 1.00 0.40 1.00 1.00 1.00 163 163 163
6.0 30 65 7 27 0.67 0.30 0.83 0.67 1.00 59 0 59
4.5 68 67 4 14 1.00 0.50 0.83 0.67 0.50 187 187 0
5.5 49 59 7 28 0.89 0.20 0.50 0.00 1.00 109 109 109
1.0 61 69 4 27 0.89 0.30 0.83 0.00 1.00 90 0 90
7.5 67 76 4 16 0.89 0.50 0.17 0.00 1.00 105 105 0
6.0 47 63 4 23 0.78 0.70 0.83 1.00 1.00 83 0 83
5.0 56 75 4 25 0.89 0.40 1.00 0.67 0.50 116 0 116
1.0 50 63 8 20 0.78 0.30 1.00 0.00 0.50 42 0 42
5.0 43 60 4 28 0.78 0.20 0.67 0.67 1.00 148 148 148
6.5 67 73 4 32 1.00 0.50 1.00 0.00 0.50 155 0 155
7.0 62 63 4 33 0.78 0.40 1.00 0.00 0.00 125 125 125
4.5 57 70 4 26 1.00 0.60 1.00 0.67 1.00 116 116 116
0.0 41 75 7 21 0.78 0.40 0.83 1.00 1.00 128 0 0
8.5 54 66 12 27 0.67 0.40 0.33 0.00 0.50 138 138 138
3.5 45 63 4 20 0.33 0.20 0.33 0.33 0.00 49 0 0
7.5 48 63 4 28 1.00 0.90 1.00 0.67 1.00 96 0 96
3.5 61 64 4 26 1.00 0.80 1.00 0.67 0.50 164 164 164
6.0 56 70 5 21 0.78 0.80 0.83 0.00 1.00 162 162 0
1.5 41 75 15 16 0.67 0.30 1.00 1.00 1.00 99 99 0
9.0 43 61 5 28 1.00 0.20 0.83 0.67 0.50 202 202 202
3.5 53 60 10 19 0.89 0.40 0.67 0.00 1.00 186 186 0
3.5 44 62 9 24 0.89 0.20 0.83 1.00 1.00 66 0 66
4.0 66 73 8 26 0.78 0.20 0.67 0.67 1.00 183 183 0
6.5 58 61 4 24 1.00 0.10 0.83 0.67 1.00 214 214 214
7.5 46 66 5 23 0.56 0.40 0.67 1.00 0.00 188 188 188
6.0 37 64 4 27 0.67 0.50 1.00 0.00 0.50 104 0 0
5.0 51 59 9 29 0.89 0.80 0.83 0.33 1.00 177 177 0
5.5 51 64 4 26 0.89 0.40 0.67 0.67 0.50 126 126 0
3.5 56 60 10 19 0.89 0.60 0.83 0.33 0.50 76 0 0
7.5 66 56 4 19 0.89 0.50 0.83 0.67 1.00 99 0 99
6.5 37 78 4 12 0.78 0.30 0.67 0.00 0.00 139 139 0
NA 59 53 6 23 0.89 0.80 1.00 1.00 1.00 78 78 78
6.5 42 67 7 25 1.00 0.40 0.33 0.00 0.00 162 162 0
6.5 38 59 5 24 1.00 0.60 0.83 0.67 0.50 108 0 108
7.0 66 66 4 26 0.89 0.40 1.00 0.33 0.50 159 159 0
3.5 34 68 4 23 0.44 0.30 0.83 0.00 0.00 74 0 0
1.5 53 71 4 28 0.78 0.80 0.83 0.00 1.00 110 110 110
4.0 49 66 4 25 0.89 0.60 0.50 0.33 1.00 96 0 0
7.5 55 73 4 23 0.67 0.30 0.50 0.00 0.00 116 0 0
4.5 49 72 4 28 0.78 0.50 0.83 0.67 1.00 87 0 0
0.0 59 71 6 23 0.78 0.40 1.00 0.33 1.00 97 0 97
3.5 40 59 10 25 0.33 0.30 0.33 0.67 0.00 127 0 0
5.5 58 64 7 27 0.89 0.70 1.00 0.33 0.50 106 0 106
5.0 60 66 4 28 0.89 0.20 0.67 0.33 0.50 80 0 80
4.5 63 78 4 17 0.89 0.40 0.83 1.00 1.00 74 0 0
2.5 56 68 7 23 0.89 0.60 1.00 0.67 0.50 91 0 0
7.5 54 73 4 24 0.56 0.60 0.83 0.00 1.00 133 0 0
7.0 52 62 8 18 0.67 0.60 0.83 0.67 0.50 74 0 74
0.0 34 65 11 21 0.67 0.40 1.00 0.33 1.00 114 0 114
4.5 69 68 6 34 0.78 0.60 0.83 0.00 1.00 140 0 140
3.0 32 65 14 24 0.78 0.50 1.00 0.33 1.00 95 0 0
1.5 48 60 5 24 0.78 0.50 0.83 0.00 1.00 98 0 98
3.5 67 71 4 28 0.89 0.60 0.67 0.00 1.00 121 0 0
2.5 58 65 8 27 1.00 0.80 0.83 0.33 1.00 126 0 126
5.5 57 68 9 24 0.89 0.50 0.83 0.67 0.50 98 0 98
8.0 42 64 4 19 0.89 0.60 0.83 0.67 1.00 95 0 95
1.0 64 74 4 19 0.78 0.40 0.83 0.67 1.00 110 0 110
5.0 58 69 5 27 1.00 0.30 0.67 0.67 1.00 70 0 70
4.5 66 76 4 28 0.78 0.30 0.83 1.00 0.50 102 0 0
3.0 26 68 5 22 0.67 0.20 0.00 0.00 0.00 86 0 86
3.0 61 72 4 32 0.78 0.40 0.83 0.00 0.50 130 0 130
8.0 52 67 4 20 0.89 0.50 1.00 0.00 0.50 96 0 96
2.5 51 63 7 26 0.67 0.30 0.17 0.00 0.00 102 0 0
7.0 55 59 10 19 0.22 0.40 0.17 0.00 0.00 100 0 0
0.0 50 73 4 24 0.44 0.50 0.50 1.00 0.00 94 0 0
1.0 60 66 5 21 0.89 0.30 0.50 0.67 1.00 52 0 0
3.5 56 62 4 21 0.67 0.50 1.00 0.00 0.50 98 0 0
5.5 63 69 4 27 0.89 0.40 0.67 0.67 0.50 118 0 0
5.5 61 66 4 18 0.67 0.40 0.83 0.67 1.00 99 0 99
0.5 52 51 6 25 0.78 0.60 1.00 0.00 1.00 0 48 48
7.5 16 56 4 27 0.78 0.30 1.00 0.67 1.00 0 50 50
9 46 67 8 28 0.78 0.40 1.00 0.33 0.50 0 150 150
9.5 56 69 5 28 1.00 0.30 1.00 1.00 1.00 0 154 154
8.5 52 57 4 19 0.78 1.00 1.00 1.00 1.00 0 0 0
7 55 56 17 27 0.67 0.40 1.00 0.00 0.50 0 0 68
8 50 55 4 26 0.89 0.80 0.83 1.00 1.00 0 194 194
10 59 63 4 27 0.89 0.30 1.00 0.67 1.00 0 158 0
7 60 67 8 26 1.00 0.50 0.83 0.67 1.00 0 159 159
8.5 52 65 4 28 0.78 0.40 1.00 0.00 0.50 0 67 0
9 44 47 7 20 0.67 0.30 0.83 0.67 1.00 0 147 0
9.5 67 76 4 32 0.89 0.50 0.83 1.00 1.00 0 39 39
4 52 64 4 25 0.67 0.30 1.00 0.67 1.00 0 100 100
6 55 68 5 33 0.67 0.30 0.67 0.00 1.00 0 111 111
8 37 64 7 25 1.00 0.40 0.83 0.00 1.00 0 138 138
5.5 54 65 4 35 0.67 0.30 1.00 0.00 0.50 0 101 101
9.5 72 71 4 28 1.00 0.60 1.00 0.33 0.50 0 0 131
7.5 51 63 7 30 0.89 0.60 0.83 0.67 1.00 0 101 101
7 48 60 11 28 0.89 0.40 1.00 1.00 1.00 0 114 114
7.5 60 68 7 27 1.00 0.40 1.00 0.00 0.00 0 165 0
8 50 72 4 21 0.67 0.40 1.00 0.67 0.50 0 114 114
7 63 70 4 25 0.44 0.30 0.67 0.67 1.00 0 111 111
7 33 61 4 31 0.89 0.20 1.00 0.33 0.00 0 75 75
6 67 61 4 28 0.56 0.50 0.83 0.67 1.00 0 82 82
10 46 62 4 29 0.78 0.40 1.00 0.67 1.00 0 121 121
2.5 54 71 4 35 1.00 0.40 1.00 0.67 0.00 0 32 32
9 59 71 6 25 1.00 0.40 0.83 0.67 1.00 0 150 0
8 61 51 8 29 0.89 0.30 0.67 0.67 0.50 0 117 117
6 33 56 23 12 0.67 0.40 0.83 0.67 0.50 0 0 71
8.5 47 70 4 30 0.89 0.20 1.00 0.33 1.00 0 165 165
6 69 73 8 27 0.33 0.00 0.00 0.00 0.00 0 154 154
9 52 76 6 28 0.89 0.40 1.00 0.67 1.00 0 126 126
8 55 68 4 28 0.78 0.60 1.00 0.00 1.00 0 149 0
9 41 48 7 25 1.00 0.40 0.67 0.67 0.50 0 145 0
5.5 73 52 4 28 0.44 0.40 1.00 0.00 0.50 0 120 120
7 52 60 4 28 0.67 0.40 0.83 0.00 0.00 0 109 0
5.5 50 59 4 28 0.33 0.20 0.17 0.00 0.00 0 132 0
9 51 57 10 26 0.89 0.40 0.83 1.00 1.00 0 172 172
2 60 79 6 22 0.89 0.30 0.83 0.00 0.50 0 169 0
8.5 56 60 5 24 1.00 0.60 0.83 0.67 0.00 0 114 114
9 56 60 5 28 0.89 0.60 0.83 1.00 1.00 0 156 156
8.5 29 59 4 27 0.89 0.40 0.83 0.00 1.00 0 172 0
9 66 62 4 27 1.00 0.50 1.00 0.67 0.50 0 0 68
7.5 66 59 5 26 0.89 0.40 0.83 0.00 1.00 0 0 89
10 73 61 5 29 1.00 0.60 1.00 1.00 1.00 0 167 167
9 55 71 5 27 0.78 0.60 0.83 0.67 1.00 0 113 0
7.5 64 57 5 29 0.78 0.90 1.00 0.67 1.00 0 0 0
6 40 66 4 28 0.67 0.40 0.83 0.67 0.00 0 0 0
10.5 46 63 6 28 0.89 0.80 1.00 1.00 1.00 0 0 0
8.5 58 69 4 27 0.67 0.50 0.83 1.00 1.00 0 0 87
8 43 58 4 24 0.78 0.40 0.83 1.00 0.00 0 173 0
10 61 59 4 29 0.89 0.40 1.00 0.67 0.50 0 2 2
10.5 51 48 9 17 0.89 0.70 1.00 1.00 0.50 0 0 0
6.5 50 66 18 27 0.78 0.40 1.00 0.33 1.00 0 0 49
9.5 52 73 6 23 1.00 0.80 1.00 0.67 1.00 0 0 0
8.5 54 67 5 27 1.00 0.40 1.00 1.00 0.50 0 0 96
7.5 66 61 4 22 1.00 0.30 1.00 0.67 0.50 0 0 0
5 61 68 11 27 0.67 0.50 1.00 0.67 1.00 0 0 0
8 80 75 4 35 0.89 0.80 1.00 0.67 1.00 0 0 100
10 51 62 10 22 1.00 0.40 0.83 0.33 0.50 0 0 0
7 56 69 6 20 1.00 1.00 1.00 1.00 0.00 0 0 141
7.5 56 58 8 26 0.89 0.50 1.00 0.67 1.00 0 165 165
7.5 56 60 8 26 0.89 0.50 1.00 0.67 1.00 0 165 165
9.5 53 74 6 26 0.89 0.30 1.00 0.33 1.00 0 0 110
6 47 55 8 29 0.89 0.30 0.83 0.33 1.00 0 118 118
10 25 62 4 18 0.89 0.30 0.50 0.00 1.00 0 158 0
7 47 63 4 28 1.00 0.40 0.67 0.33 0.50 0 0 146
3 46 69 9 15 0.67 0.50 1.00 0.33 1.00 0 49 0
6 50 58 9 19 1.00 0.50 0.67 0.67 1.00 0 0 0
7 39 58 5 13 0.89 0.40 1.00 0.00 0.00 0 0 0
10 51 68 4 26 0.89 0.70 1.00 1.00 0.00 0 155 155
7 58 72 4 26 0.89 0.50 0.50 0.33 0.50 0 0 0
3.5 35 62 15 21 0.89 0.40 0.67 0.33 0.00 0 0 147
8 58 62 10 27 1.00 0.70 0.67 1.00 1.00 0 0 0
10 60 65 9 24 1.00 0.70 0.67 1.00 1.00 0 0 0
5.5 62 69 7 22 1.00 0.70 0.67 1.00 1.00 0 0 0
6 63 66 9 22 0.89 0.70 0.67 1.00 1.00 0 0 0
6.5 53 72 6 24 0.89 0.70 0.67 0.00 0.00 0 0 61
6.5 46 62 4 22 0.89 0.70 1.00 0.67 1.00 0 0 60
8.5 67 75 7 27 0.33 0.10 0.67 0.33 0.00 0 0 109
4 59 58 4 26 0.67 0.20 0.67 0.67 1.00 0 0 68
9.5 64 66 7 25 0.56 0.30 0.33 0.33 1.00 0 0 0
8 38 55 4 20 0.44 0.60 0.83 0.33 0.50 0 0 0
8.5 50 47 15 28 1.00 0.80 1.00 1.00 1.00 0 0 73
5.5 48 72 4 22 0.89 0.80 1.00 0.33 0.50 0 151 0
7 48 62 9 27 0.33 0.00 0.17 0.00 0.00 0 0 0
9 47 64 4 20 0.67 0.30 0.67 0.33 1.00 0 0 0
8 66 64 4 26 0.67 0.60 0.83 0.33 1.00 0 0 0
10 47 19 28 30 1.00 0.50 0.83 0.67 1.00 0 220 220
8 63 50 4 24 0.78 0.70 1.00 0.33 0.50 0 0 65
6 58 68 4 23 0.67 0.30 0.83 0.00 1.00 0 141 0
8 44 70 4 26 1.00 0.30 1.00 0.67 0.00 0 0 0
5 51 79 5 24 0.78 0.40 1.00 0.67 0.50 0 122 122
9 43 69 4 27 0.89 0.40 0.83 1.00 1.00 0 0 0
4.5 55 71 4 31 0.89 0.10 0.83 0.00 1.00 0 44 44
8.5 38 48 12 21 0.89 0.50 1.00 0.67 1.00 0 0 52
9.5 45 73 4 10 0.00 0.00 0.00 0.00 0.00 0 0 0
8.5 50 74 6 15 0.67 0.40 1.00 0.33 0.00 0 0 101
7.5 54 66 6 29 1.00 0.60 0.83 0.67 0.50 0 0 42
7.5 57 71 5 29 1.00 0.40 1.00 0.33 1.00 0 152 152
5 60 74 4 24 0.67 0.10 0.33 0.00 1.00 0 107 0
7 55 78 4 20 0.89 0.30 0.83 0.00 1.00 0 0 0
8 56 75 4 25 0.89 0.70 0.83 0.67 1.00 0 154 0
5.5 49 53 10 25 0.56 0.30 0.17 0.00 1.00 0 103 103
8.5 37 60 7 25 0.67 0.50 0.83 0.33 0.00 0 0 96
9.5 59 70 4 31 1.00 0.30 0.83 0.67 1.00 0 175 175
7 46 69 7 25 1.00 0.60 0.67 0.67 1.00 0 0 57
8 51 65 4 26 1.00 0.90 1.00 1.00 1.00 0 0 0
8.5 58 78 4 26 0.67 0.40 0.83 0.00 1.00 0 143 0
3.5 64 78 12 33 0.44 0.30 1.00 0.00 0.50 0 0 0
6.5 53 59 5 27 0.89 0.90 1.00 0.67 1.00 0 110 110
6.5 48 72 8 21 0.44 0.50 1.00 0.00 0.00 0 131 131
10.5 51 70 6 28 0.56 0.30 1.00 1.00 0.50 0 167 0
8.5 47 63 17 19 0.89 0.60 0.83 0.67 0.50 0 0 0
8 59 63 4 31 0.67 0.20 1.00 0.33 0.50 0 137 0
10 62 71 5 27 0.89 0.40 0.83 1.00 1.00 0 0 86
10 62 74 4 33 1.00 0.50 0.83 0.67 0.50 0 121 121
9.5 51 67 5 27 0.78 0.40 0.83 0.67 0.50 0 149 0
9 64 66 5 23 0.44 0.00 0.00 0.00 0.00 0 168 0
10 52 62 6 23 0.89 0.20 1.00 0.33 1.00 0 140 0
7.5 67 80 4 30 0.89 0.50 1.00 0.67 1.00 0 0 88
4.5 50 73 4 29 0.89 0.30 1.00 0.67 0.50 0 168 168
4.5 54 67 4 35 0.44 0.00 0.00 0.00 0.00 0 94 94
0.5 58 61 6 27 1.00 0.50 0.83 1.00 1.00 0 51 51
6.5 56 73 8 16 0.89 0.60 0.83 0.33 1.00 0 0 0
4.5 63 74 10 23 0.67 0.30 0.83 0.00 0.50 0 145 145
5.5 31 32 4 26 0.33 0.00 0.00 0.00 0.00 0 66 66
5 65 69 5 33 0.78 0.30 0.67 0.00 0.00 0 0 85
6 71 69 4 30 0.89 0.50 1.00 0.67 1.00 0 109 0
4 50 84 4 30 0.78 0.40 0.67 0.00 1.00 0 0 0
8 57 64 4 28 0.78 0.50 0.83 0.67 0.50 0 0 102
10.5 47 58 16 17 0.89 0.70 1.00 1.00 0.50 0 0 0
6.5 47 59 7 24 0.78 0.80 1.00 0.67 1.00 0 0 86
8 57 78 4 23 0.78 0.60 1.00 0.33 1.00 0 0 114
8.5 43 57 4 31 0.67 0.40 0.83 0.33 0.50 0 164 0
5.5 41 60 14 26 0.89 0.50 0.83 0.33 0.00 0 119 119
7 63 68 5 25 0.89 0.50 1.00 0.00 1.00 0 126 0
5 63 68 5 26 0.78 0.30 1.00 0.33 1.00 0 132 132
3.5 56 73 5 28 1.00 0.60 1.00 0.00 1.00 0 142 142
5 51 69 5 26 1.00 0.30 0.67 0.67 0.50 0 83 0
9 50 67 7 28 0.78 0.60 0.83 1.00 0.50 0 0 94
8.5 22 60 19 27 0.78 0.30 0.33 0.33 1.00 0 0 0
5 41 65 16 21 0.89 0.70 1.00 0.67 1.00 0 166 166
9.5 59 66 4 25 0.89 0.70 1.00 1.00 1.00 0 0 0
3 56 74 4 30 0.67 0.60 0.67 1.00 1.00 0 0 64
1.5 66 81 7 28 1.00 0.50 1.00 0.33 0.00 0 93 0
6 53 72 9 19 0.67 0.50 0.83 0.33 0.50 0 0 0
0.5 42 55 5 27 0.56 0.40 0.67 0.00 1.00 0 0 105
6.5 52 49 14 27 0.78 0.40 1.00 0.33 1.00 0 0 49
7.5 54 74 4 19 1.00 0.70 1.00 1.00 1.00 0 0 0
4.5 44 53 16 28 0.67 0.20 0.17 0.00 0.00 0 0 95
8 62 64 10 28 0.78 0.50 0.83 0.67 0.50 0 0 102
9 53 65 5 28 0.56 0.40 0.83 0.67 0.00 0 0 0
7.5 50 57 6 23 1.00 0.20 1.00 0.67 1.00 0 0 63
8.5 36 51 4 26 0.89 0.50 0.67 0.67 0.00 0 0 0
7 76 80 4 28 0.44 0.40 0.50 0.00 1.00 0 0 0
9.5 66 67 4 27 1.00 0.70 0.67 1.00 1.00 0 0 117
6.5 62 70 5 30 0.89 0.60 0.83 0.67 0.00 0 0 57
9.5 59 74 4 20 0.78 0.40 0.83 0.00 0.00 0 0 0
6 47 75 4 27 0.89 0.50 1.00 0.67 1.00 0 0 73
8 55 70 5 25 0.11 0.00 0.17 0.00 0.00 0 0 0
9.5 58 69 4 28 0.89 0.70 1.00 0.67 1.00 0 0 0
8 60 65 4 26 0.89 0.40 0.67 0.67 1.00 0 0 105
8 44 55 5 28 1.00 0.50 0.67 1.00 1.00 0 117 0
9 57 71 8 21 0.89 0.60 0.83 0.67 0.50 0 0 0
5 45 65 15 11 1.00 0.80 0.50 0.67 0.50 0 0 31

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	12 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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	12 seconds
R Server	'Gwilym Jenkins' @ jenkins.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 7.74941 + 0.00673373AMS.I[t] -0.0293808AMS.E[t] -0.0425336AMS.A[t] -0.0195799SOFTSTATTOT[t] + 1.30492Calculation[t] + 0.406927Algebraic_Reasoning[t] -0.0600155Graphical_Interpretation[t] + 1.05479Proportionality_and_Ratio[t] -0.432901Estimation[t] -0.0182465lfm_year[t] + 0.00617639lfm_course[t] -0.00212972lfm_gender[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  7.74941 +  0.00673373AMS.I[t] -0.0293808AMS.E[t] -0.0425336AMS.A[t] -0.0195799SOFTSTATTOT[t] +  1.30492Calculation[t] +  0.406927Algebraic_Reasoning[t] -0.0600155Graphical_Interpretation[t] +  1.05479Proportionality_and_Ratio[t] -0.432901Estimation[t] -0.0182465lfm_year[t] +  0.00617639lfm_course[t] -0.00212972lfm_gender[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  7.74941 +  0.00673373AMS.I[t] -0.0293808AMS.E[t] -0.0425336AMS.A[t] -0.0195799SOFTSTATTOT[t] +  1.30492Calculation[t] +  0.406927Algebraic_Reasoning[t] -0.0600155Graphical_Interpretation[t] +  1.05479Proportionality_and_Ratio[t] -0.432901Estimation[t] -0.0182465lfm_year[t] +  0.00617639lfm_course[t] -0.00212972lfm_gender[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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
Ex[t] = + 7.74941 + 0.00673373AMS.I[t] -0.0293808AMS.E[t] -0.0425336AMS.A[t] -0.0195799SOFTSTATTOT[t] + 1.30492Calculation[t] + 0.406927Algebraic_Reasoning[t] -0.0600155Graphical_Interpretation[t] + 1.05479Proportionality_and_Ratio[t] -0.432901Estimation[t] -0.0182465lfm_year[t] + 0.00617639lfm_course[t] -0.00212972lfm_gender[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)	7.74941	1.62244	4.776	2.95775e-06	1.47887e-06
AMS.I	0.00673373	0.0145267	0.4635	0.643356	0.321678
AMS.E	-0.0293808	0.0187035	-1.571	0.117405	0.0587024
AMS.A	-0.0425336	0.0417717	-1.018	0.309493	0.154747
SOFTSTATTOT	-0.0195799	0.0322193	-0.6077	0.543902	0.271951
Calculation	1.30492	0.917021	1.423	0.155912	0.077956
Algebraic_Reasoning	0.406927	0.846733	0.4806	0.631208	0.315604
Graphical_Interpretation	-0.0600155	0.673184	-0.08915	0.929029	0.464514
Proportionality_and_Ratio	1.05479	0.420722	2.507	0.0127717	0.00638583
Estimation	-0.432901	0.371014	-1.167	0.244338	0.122169
lfm_year	-0.0182465	0.0022202	-8.218	9.2327e-15	4.61635e-15
lfm_course	0.00617639	0.00203375	3.037	0.00262822	0.00131411
lfm_gender	-0.00212972	0.00229915	-0.9263	0.355128	0.177564

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 7.74941 & 1.62244 & 4.776 & 2.95775e-06 & 1.47887e-06 \tabularnewline
AMS.I & 0.00673373 & 0.0145267 & 0.4635 & 0.643356 & 0.321678 \tabularnewline
AMS.E & -0.0293808 & 0.0187035 & -1.571 & 0.117405 & 0.0587024 \tabularnewline
AMS.A & -0.0425336 & 0.0417717 & -1.018 & 0.309493 & 0.154747 \tabularnewline
SOFTSTATTOT & -0.0195799 & 0.0322193 & -0.6077 & 0.543902 & 0.271951 \tabularnewline
Calculation & 1.30492 & 0.917021 & 1.423 & 0.155912 & 0.077956 \tabularnewline
Algebraic_Reasoning & 0.406927 & 0.846733 & 0.4806 & 0.631208 & 0.315604 \tabularnewline
Graphical_Interpretation & -0.0600155 & 0.673184 & -0.08915 & 0.929029 & 0.464514 \tabularnewline
Proportionality_and_Ratio & 1.05479 & 0.420722 & 2.507 & 0.0127717 & 0.00638583 \tabularnewline
Estimation & -0.432901 & 0.371014 & -1.167 & 0.244338 & 0.122169 \tabularnewline
lfm_year & -0.0182465 & 0.0022202 & -8.218 & 9.2327e-15 & 4.61635e-15 \tabularnewline
lfm_course & 0.00617639 & 0.00203375 & 3.037 & 0.00262822 & 0.00131411 \tabularnewline
lfm_gender & -0.00212972 & 0.00229915 & -0.9263 & 0.355128 & 0.177564 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]7.74941[/C][C]1.62244[/C][C]4.776[/C][C]2.95775e-06[/C][C]1.47887e-06[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00673373[/C][C]0.0145267[/C][C]0.4635[/C][C]0.643356[/C][C]0.321678[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0293808[/C][C]0.0187035[/C][C]-1.571[/C][C]0.117405[/C][C]0.0587024[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0425336[/C][C]0.0417717[/C][C]-1.018[/C][C]0.309493[/C][C]0.154747[/C][/ROW]
[ROW][C]SOFTSTATTOT[/C][C]-0.0195799[/C][C]0.0322193[/C][C]-0.6077[/C][C]0.543902[/C][C]0.271951[/C][/ROW]
[ROW][C]Calculation[/C][C]1.30492[/C][C]0.917021[/C][C]1.423[/C][C]0.155912[/C][C]0.077956[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]0.406927[/C][C]0.846733[/C][C]0.4806[/C][C]0.631208[/C][C]0.315604[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]-0.0600155[/C][C]0.673184[/C][C]-0.08915[/C][C]0.929029[/C][C]0.464514[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.05479[/C][C]0.420722[/C][C]2.507[/C][C]0.0127717[/C][C]0.00638583[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.432901[/C][C]0.371014[/C][C]-1.167[/C][C]0.244338[/C][C]0.122169[/C][/ROW]
[ROW][C]lfm_year[/C][C]-0.0182465[/C][C]0.0022202[/C][C]-8.218[/C][C]9.2327e-15[/C][C]4.61635e-15[/C][/ROW]
[ROW][C]lfm_course[/C][C]0.00617639[/C][C]0.00203375[/C][C]3.037[/C][C]0.00262822[/C][C]0.00131411[/C][/ROW]
[ROW][C]lfm_gender[/C][C]-0.00212972[/C][C]0.00229915[/C][C]-0.9263[/C][C]0.355128[/C][C]0.177564[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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)	7.74941	1.62244	4.776	2.95775e-06	1.47887e-06
AMS.I	0.00673373	0.0145267	0.4635	0.643356	0.321678
AMS.E	-0.0293808	0.0187035	-1.571	0.117405	0.0587024
AMS.A	-0.0425336	0.0417717	-1.018	0.309493	0.154747
SOFTSTATTOT	-0.0195799	0.0322193	-0.6077	0.543902	0.271951
Calculation	1.30492	0.917021	1.423	0.155912	0.077956
Algebraic_Reasoning	0.406927	0.846733	0.4806	0.631208	0.315604
Graphical_Interpretation	-0.0600155	0.673184	-0.08915	0.929029	0.464514
Proportionality_and_Ratio	1.05479	0.420722	2.507	0.0127717	0.00638583
Estimation	-0.432901	0.371014	-1.167	0.244338	0.122169
lfm_year	-0.0182465	0.0022202	-8.218	9.2327e-15	4.61635e-15
lfm_course	0.00617639	0.00203375	3.037	0.00262822	0.00131411
lfm_gender	-0.00212972	0.00229915	-0.9263	0.355128	0.177564

Multiple Linear Regression - Regression Statistics
Multiple R	0.523344
R-squared	0.273889
Adjusted R-squared	0.241009
F-TEST (value)	8.32985
F-TEST (DF numerator)	12
F-TEST (DF denominator)	265
p-value	2.4869e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.2073
Sum Squared Residuals	1291.13

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.523344 \tabularnewline
R-squared & 0.273889 \tabularnewline
Adjusted R-squared & 0.241009 \tabularnewline
F-TEST (value) & 8.32985 \tabularnewline
F-TEST (DF numerator) & 12 \tabularnewline
F-TEST (DF denominator) & 265 \tabularnewline
p-value & 2.4869e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.2073 \tabularnewline
Sum Squared Residuals & 1291.13 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.523344[/C][/ROW]
[ROW][C]R-squared[/C][C]0.273889[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.241009[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]8.32985[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]12[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]265[/C][/ROW]
[ROW][C]p-value[/C][C]2.4869e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.2073[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1291.13[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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	0.523344
R-squared	0.273889
Adjusted R-squared	0.241009
F-TEST (value)	8.32985
F-TEST (DF numerator)	12
F-TEST (DF denominator)	265
p-value	2.4869e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.2073
Sum Squared Residuals	1291.13

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.9558	1.5442
2	6	5.08464	0.915358
3	6.5	5.4614	1.0386
4	1	4.44804	-3.44804
5	1	4.9483	-3.9483
6	5.5	3.09937	2.40063
7	8.5	5.24564	3.25436
8	6.5	5.81346	0.68654
9	4.5	4.13027	0.369734
10	2	5.5897	-3.5897
11	5	5.37081	-0.370808
12	0.5	4.2166	-3.7166
13	5	4.39474	0.605263
14	5	4.66167	0.338332
15	2.5	6.52168	-4.02168
16	5	5.13846	-0.138458
17	5.5	4.43369	1.06631
18	3.5	4.92805	-1.42805
19	3	4.2597	-1.2597
20	4	4.26921	-0.269209
21	0.5	4.69281	-4.19281
22	6.5	4.3974	2.1026
23	4.5	3.75289	0.747109
24	7.5	3.85549	3.64451
25	5.5	5.33933	0.160673
26	4	2.39705	1.60295
27	7.5	3.97776	3.52224
28	7	5.41295	1.58705
29	4	5.26911	-1.26911
30	5.5	4.66523	0.834774
31	2.5	4.77386	-2.27386
32	5.5	4.27922	1.22078
33	3.5	5.20025	-1.70025
34	2.5	4.74222	-2.24222
35	4.5	5.66762	-1.16762
36	4.5	6.2996	-1.7996
37	4.5	4.67989	-0.179889
38	6	3.66565	2.33435
39	2.5	5.11697	-2.61697
40	5	5.11456	-0.114555
41	0	5.92107	-5.92107
42	5	5.21724	-0.217236
43	6.5	4.44764	2.05236
44	5	4.74877	0.25123
45	6	5.23345	0.766552
46	4.5	5.48626	-0.986257
47	5.5	4.732	0.768004
48	1	4.40098	-3.40098
49	7.5	5.13859	2.36141
50	6	5.77797	0.222032
51	5	4.65406	0.345943
52	1	5.51089	-4.51089
53	5	4.78899	0.211014
54	6.5	3.33268	3.16732
55	7	4.84525	2.15475
56	4.5	5.51305	-1.01305
57	0	4.53015	-4.53015
58	8.5	3.97607	4.52393
59	3.5	5.58591	-2.08591
60	7.5	5.4321	2.0679
61	3.5	5.33252	-1.83252
62	6	4.3513	1.6487
63	1.5	5.23396	-3.73396
64	9	4.44421	4.55579
65	3.5	4.15209	-0.652093
66	3.5	5.84137	-2.34137
67	4	4.32368	-0.323683
68	6.5	4.23853	2.26147
69	7.5	4.69556	2.80444
70	6	4.32305	1.67695
71	5	4.62462	0.375378
72	5.5	5.78661	-0.286611
73	3.5	5.66691	-2.16691
74	7.5	5.57795	1.92205
75	6.5	4.72372	1.77628
76	NA	NA	1.73099
77	6.5	5.37813	1.12187
78	6.5	4.55211	1.94789
79	7	8.15618	-1.15618
80	3.5	6.60057	-3.10057
81	1.5	2.51964	-1.01964
82	4	0.704266	3.29573
83	7.5	8.10342	-0.603423
84	4.5	8.9144	-4.4144
85	0	0.792758	-0.792758
86	3.5	2.79116	0.708835
87	5.5	5.70001	-0.200014
88	5	6.42492	-1.42492
89	4.5	7.55588	-3.05588
90	2.5	-1.60641	4.10641
91	7.5	6.1363	1.3637
92	7	10.7589	-3.7589
93	0	-1.27817	1.27817
94	4.5	5.8328	-1.3328
95	3	5.86891	-2.86891
96	1.5	2.12076	-0.620757
97	3.5	5.28971	-1.78971
98	2.5	2.09104	0.408964
99	5.5	2.80349	2.69651
100	8	11.6273	-3.62726
101	1	1.60563	-0.605625
102	5	5.80982	-0.809822
103	4.5	5.98649	-1.48649
104	3	3.51349	-0.513493
105	3	-0.298425	3.29842
106	8	10.0601	-2.06005
107	2.5	-0.296058	2.79606
108	7	12.3885	-5.38848
109	0	5.16889	-5.16889
110	1	2.23671	-1.23671
111	3.5	3.06868	0.431321
112	5.5	4.94228	0.557723
113	5.5	11.8198	-6.31976
114	0.5	0.0690728	0.430927
115	7.5	5.56136	1.93864
116	9	7.45038	1.54962
117	9.5	8.86934	0.630658
118	8.5	7.33849	1.16151
119	7	7.63499	-0.63499
120	8	6.07004	1.92996
121	10	10.7114	-0.711371
122	7	5.2894	1.7106
123	8.5	7.60376	0.896239
124	9	6.76567	2.23433
125	9.5	12.6744	-3.17439
126	4	4.23551	-0.235506
127	6	4.87437	1.12563
128	8	8.97647	-0.976467
129	5.5	2.77152	2.72848
130	9.5	9.39495	0.10505
131	7.5	8.14102	-0.641016
132	7	7.25592	-0.255924
133	7.5	6.81799	0.682005
134	8	7.83637	0.163635
135	7	7.23661	-0.23661
136	7	8.18001	-1.18001
137	6	3.38365	2.61635
138	10	14.9154	-4.91544
139	2.5	1.43411	1.06589
140	9	8.96062	0.0393753
141	8	8.43937	-0.439368
142	6	4.51733	1.48267
143	8.5	8.75412	-0.25412
144	6	4.111	1.889
145	9	8.09286	0.907144
146	8	7.6413	0.358704
147	9	10.4409	-1.44087
148	5.5	5.77882	-0.278822
149	7	8.45134	-1.45134
150	5.5	4.57596	0.924037
151	9	14.2074	-5.20739
152	2	1.84836	0.151643
153	8.5	7.71164	0.788364
154	9	7.9162	1.0838
155	8.5	6.96724	1.53276
156	9	7.89051	1.10949
157	7.5	5.955	1.545
158	10	8.47632	1.52368
159	9	8.82304	0.176959
160	7.5	8.55522	-1.05522
161	6	2.95352	3.04648
162	10.5	8.87845	1.62155
163	8.5	9.44892	-0.948922
164	8	5.45123	2.54877
165	10	7.69144	2.30856
166	10.5	9.78412	0.715885
167	6.5	4.09348	2.40652
168	9.5	8.44475	1.05525
169	8.5	8.65795	-0.157955
170	7.5	8.9573	-1.4573
171	5	3.71686	1.28314
172	8	4.96463	3.03537
173	10	10.8588	-0.858754
174	7	7.3194	-0.3194
175	7.5	7.76064	-0.260638
176	7.5	4.07219	3.42781
177	9.5	10.6682	-1.16819
178	6	3.36999	2.63001
179	10	9.7447	0.255298
180	7	10.5909	-3.59095
181	3	4.36917	-1.36917
182	6	6.10486	-0.104864
183	7	5.48396	1.51604
184	10	9.8118	0.188201
185	7	9.93325	-2.93325
186	3.5	3.03581	0.46419
187	8	5.56241	2.43759
188	10	12.0826	-2.08258
189	5.5	6.94885	-1.44885
190	6	6.04186	-0.0418623
191	6.5	7.16889	-0.668895
192	6.5	3.71766	2.78234
193	8.5	11.3079	-2.80786
194	4	0.702208	3.29779
195	9.5	8.22775	1.27225
196	8	7.05582	0.944178
197	8.5	10.8475	-2.34749
198	5.5	4.25998	1.24002
199	7	4.49513	2.50487
200	9	7.61807	1.38193
201	8	6.35197	1.64803
202	10	9.30041	0.69959
203	8	8.90613	-0.906128
204	6	5.38352	0.616484
205	8	10.1937	-2.1937
206	5	3.20912	1.79088
207	9	10.654	-1.65402
208	4.5	3.14132	1.35868
209	8.5	4.54169	3.95831
210	9.5	7.47304	2.02696
211	8.5	8.25095	0.249048
212	7.5	7.20466	0.295343
213	7.5	8.96236	-1.46236
214	5	4.06707	0.93293
215	7	6.88469	0.115308
216	8	8.93388	-0.93388
217	5.5	3.62005	1.87995
218	8.5	6.67209	1.82791
219	9.5	9.40593	0.0940684
220	7	6.73689	0.263107
221	8	6.10663	1.89337
222	8.5	10.1519	-1.6519
223	3.5	4.81804	-1.31804
224	6.5	6.45349	0.0465124
225	6.5	3.89535	2.60465
226	10.5	8.9658	1.5342
227	8.5	7.89206	0.607942
228	8	5.05261	2.94739
229	10	7.61493	2.38507
230	10	8.42433	1.57567
231	9.5	7.69003	1.80997
232	9	6.53504	2.46496
233	10	8.98379	1.01621
234	7.5	10.5969	-3.09688
235	4.5	6.24363	-1.74363
236	4.5	11.8507	-7.35072
237	0.5	0.599052	-0.0990524
238	6.5	8.44066	-1.94066
239	4.5	6.03646	-1.53646
240	5.5	6.7197	-1.2197
241	5	6.69456	-1.69456
242	6	7.56807	-1.56807
243	4	2.979	1.021
244	8	5.07296	2.92704
245	10.5	10.9388	-0.438789
246	6.5	4.59542	1.90458
247	8	7.21895	0.781046
248	8.5	10.3028	-1.80276
249	5.5	5.62372	-0.123723
250	7	8.98323	-1.98323
251	5	8.35158	-3.35158
252	3.5	6.23349	-2.73349
253	5	3.12194	1.87806
254	9	6.3332	2.6668
255	8.5	10.8558	-2.35579
256	5	3.05603	1.94397
257	9.5	13.2586	-3.75861
258	3	8.83887	-5.83887
259	1.5	1.89563	-0.395634
260	6	11.3717	-5.37175
261	0.5	0.467191	0.0328089
262	6.5	6.54834	-0.0483404
263	7.5	9.00289	-1.50289
264	4.5	3.25747	1.24253
265	8	5.98606	2.01394
266	9	8.67178	0.328225
267	7.5	6.84553	0.654469
268	8.5	6.96636	1.53364
269	7	4.9488	2.0512
270	9.5	10.2512	-0.751216
271	6.5	3.54158	2.95842
272	9.5	10.0867	-0.586706
273	6	3.49428	2.50572
274	8	5.55434	2.44566
275	9.5	8.39859	1.10141
276	8	8.48154	-0.481544
277	8	6.14173	1.85827
278	9	11.314	-2.31398
279	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.9558 & 1.5442 \tabularnewline
2 & 6 & 5.08464 & 0.915358 \tabularnewline
3 & 6.5 & 5.4614 & 1.0386 \tabularnewline
4 & 1 & 4.44804 & -3.44804 \tabularnewline
5 & 1 & 4.9483 & -3.9483 \tabularnewline
6 & 5.5 & 3.09937 & 2.40063 \tabularnewline
7 & 8.5 & 5.24564 & 3.25436 \tabularnewline
8 & 6.5 & 5.81346 & 0.68654 \tabularnewline
9 & 4.5 & 4.13027 & 0.369734 \tabularnewline
10 & 2 & 5.5897 & -3.5897 \tabularnewline
11 & 5 & 5.37081 & -0.370808 \tabularnewline
12 & 0.5 & 4.2166 & -3.7166 \tabularnewline
13 & 5 & 4.39474 & 0.605263 \tabularnewline
14 & 5 & 4.66167 & 0.338332 \tabularnewline
15 & 2.5 & 6.52168 & -4.02168 \tabularnewline
16 & 5 & 5.13846 & -0.138458 \tabularnewline
17 & 5.5 & 4.43369 & 1.06631 \tabularnewline
18 & 3.5 & 4.92805 & -1.42805 \tabularnewline
19 & 3 & 4.2597 & -1.2597 \tabularnewline
20 & 4 & 4.26921 & -0.269209 \tabularnewline
21 & 0.5 & 4.69281 & -4.19281 \tabularnewline
22 & 6.5 & 4.3974 & 2.1026 \tabularnewline
23 & 4.5 & 3.75289 & 0.747109 \tabularnewline
24 & 7.5 & 3.85549 & 3.64451 \tabularnewline
25 & 5.5 & 5.33933 & 0.160673 \tabularnewline
26 & 4 & 2.39705 & 1.60295 \tabularnewline
27 & 7.5 & 3.97776 & 3.52224 \tabularnewline
28 & 7 & 5.41295 & 1.58705 \tabularnewline
29 & 4 & 5.26911 & -1.26911 \tabularnewline
30 & 5.5 & 4.66523 & 0.834774 \tabularnewline
31 & 2.5 & 4.77386 & -2.27386 \tabularnewline
32 & 5.5 & 4.27922 & 1.22078 \tabularnewline
33 & 3.5 & 5.20025 & -1.70025 \tabularnewline
34 & 2.5 & 4.74222 & -2.24222 \tabularnewline
35 & 4.5 & 5.66762 & -1.16762 \tabularnewline
36 & 4.5 & 6.2996 & -1.7996 \tabularnewline
37 & 4.5 & 4.67989 & -0.179889 \tabularnewline
38 & 6 & 3.66565 & 2.33435 \tabularnewline
39 & 2.5 & 5.11697 & -2.61697 \tabularnewline
40 & 5 & 5.11456 & -0.114555 \tabularnewline
41 & 0 & 5.92107 & -5.92107 \tabularnewline
42 & 5 & 5.21724 & -0.217236 \tabularnewline
43 & 6.5 & 4.44764 & 2.05236 \tabularnewline
44 & 5 & 4.74877 & 0.25123 \tabularnewline
45 & 6 & 5.23345 & 0.766552 \tabularnewline
46 & 4.5 & 5.48626 & -0.986257 \tabularnewline
47 & 5.5 & 4.732 & 0.768004 \tabularnewline
48 & 1 & 4.40098 & -3.40098 \tabularnewline
49 & 7.5 & 5.13859 & 2.36141 \tabularnewline
50 & 6 & 5.77797 & 0.222032 \tabularnewline
51 & 5 & 4.65406 & 0.345943 \tabularnewline
52 & 1 & 5.51089 & -4.51089 \tabularnewline
53 & 5 & 4.78899 & 0.211014 \tabularnewline
54 & 6.5 & 3.33268 & 3.16732 \tabularnewline
55 & 7 & 4.84525 & 2.15475 \tabularnewline
56 & 4.5 & 5.51305 & -1.01305 \tabularnewline
57 & 0 & 4.53015 & -4.53015 \tabularnewline
58 & 8.5 & 3.97607 & 4.52393 \tabularnewline
59 & 3.5 & 5.58591 & -2.08591 \tabularnewline
60 & 7.5 & 5.4321 & 2.0679 \tabularnewline
61 & 3.5 & 5.33252 & -1.83252 \tabularnewline
62 & 6 & 4.3513 & 1.6487 \tabularnewline
63 & 1.5 & 5.23396 & -3.73396 \tabularnewline
64 & 9 & 4.44421 & 4.55579 \tabularnewline
65 & 3.5 & 4.15209 & -0.652093 \tabularnewline
66 & 3.5 & 5.84137 & -2.34137 \tabularnewline
67 & 4 & 4.32368 & -0.323683 \tabularnewline
68 & 6.5 & 4.23853 & 2.26147 \tabularnewline
69 & 7.5 & 4.69556 & 2.80444 \tabularnewline
70 & 6 & 4.32305 & 1.67695 \tabularnewline
71 & 5 & 4.62462 & 0.375378 \tabularnewline
72 & 5.5 & 5.78661 & -0.286611 \tabularnewline
73 & 3.5 & 5.66691 & -2.16691 \tabularnewline
74 & 7.5 & 5.57795 & 1.92205 \tabularnewline
75 & 6.5 & 4.72372 & 1.77628 \tabularnewline
76 & NA & NA & 1.73099 \tabularnewline
77 & 6.5 & 5.37813 & 1.12187 \tabularnewline
78 & 6.5 & 4.55211 & 1.94789 \tabularnewline
79 & 7 & 8.15618 & -1.15618 \tabularnewline
80 & 3.5 & 6.60057 & -3.10057 \tabularnewline
81 & 1.5 & 2.51964 & -1.01964 \tabularnewline
82 & 4 & 0.704266 & 3.29573 \tabularnewline
83 & 7.5 & 8.10342 & -0.603423 \tabularnewline
84 & 4.5 & 8.9144 & -4.4144 \tabularnewline
85 & 0 & 0.792758 & -0.792758 \tabularnewline
86 & 3.5 & 2.79116 & 0.708835 \tabularnewline
87 & 5.5 & 5.70001 & -0.200014 \tabularnewline
88 & 5 & 6.42492 & -1.42492 \tabularnewline
89 & 4.5 & 7.55588 & -3.05588 \tabularnewline
90 & 2.5 & -1.60641 & 4.10641 \tabularnewline
91 & 7.5 & 6.1363 & 1.3637 \tabularnewline
92 & 7 & 10.7589 & -3.7589 \tabularnewline
93 & 0 & -1.27817 & 1.27817 \tabularnewline
94 & 4.5 & 5.8328 & -1.3328 \tabularnewline
95 & 3 & 5.86891 & -2.86891 \tabularnewline
96 & 1.5 & 2.12076 & -0.620757 \tabularnewline
97 & 3.5 & 5.28971 & -1.78971 \tabularnewline
98 & 2.5 & 2.09104 & 0.408964 \tabularnewline
99 & 5.5 & 2.80349 & 2.69651 \tabularnewline
100 & 8 & 11.6273 & -3.62726 \tabularnewline
101 & 1 & 1.60563 & -0.605625 \tabularnewline
102 & 5 & 5.80982 & -0.809822 \tabularnewline
103 & 4.5 & 5.98649 & -1.48649 \tabularnewline
104 & 3 & 3.51349 & -0.513493 \tabularnewline
105 & 3 & -0.298425 & 3.29842 \tabularnewline
106 & 8 & 10.0601 & -2.06005 \tabularnewline
107 & 2.5 & -0.296058 & 2.79606 \tabularnewline
108 & 7 & 12.3885 & -5.38848 \tabularnewline
109 & 0 & 5.16889 & -5.16889 \tabularnewline
110 & 1 & 2.23671 & -1.23671 \tabularnewline
111 & 3.5 & 3.06868 & 0.431321 \tabularnewline
112 & 5.5 & 4.94228 & 0.557723 \tabularnewline
113 & 5.5 & 11.8198 & -6.31976 \tabularnewline
114 & 0.5 & 0.0690728 & 0.430927 \tabularnewline
115 & 7.5 & 5.56136 & 1.93864 \tabularnewline
116 & 9 & 7.45038 & 1.54962 \tabularnewline
117 & 9.5 & 8.86934 & 0.630658 \tabularnewline
118 & 8.5 & 7.33849 & 1.16151 \tabularnewline
119 & 7 & 7.63499 & -0.63499 \tabularnewline
120 & 8 & 6.07004 & 1.92996 \tabularnewline
121 & 10 & 10.7114 & -0.711371 \tabularnewline
122 & 7 & 5.2894 & 1.7106 \tabularnewline
123 & 8.5 & 7.60376 & 0.896239 \tabularnewline
124 & 9 & 6.76567 & 2.23433 \tabularnewline
125 & 9.5 & 12.6744 & -3.17439 \tabularnewline
126 & 4 & 4.23551 & -0.235506 \tabularnewline
127 & 6 & 4.87437 & 1.12563 \tabularnewline
128 & 8 & 8.97647 & -0.976467 \tabularnewline
129 & 5.5 & 2.77152 & 2.72848 \tabularnewline
130 & 9.5 & 9.39495 & 0.10505 \tabularnewline
131 & 7.5 & 8.14102 & -0.641016 \tabularnewline
132 & 7 & 7.25592 & -0.255924 \tabularnewline
133 & 7.5 & 6.81799 & 0.682005 \tabularnewline
134 & 8 & 7.83637 & 0.163635 \tabularnewline
135 & 7 & 7.23661 & -0.23661 \tabularnewline
136 & 7 & 8.18001 & -1.18001 \tabularnewline
137 & 6 & 3.38365 & 2.61635 \tabularnewline
138 & 10 & 14.9154 & -4.91544 \tabularnewline
139 & 2.5 & 1.43411 & 1.06589 \tabularnewline
140 & 9 & 8.96062 & 0.0393753 \tabularnewline
141 & 8 & 8.43937 & -0.439368 \tabularnewline
142 & 6 & 4.51733 & 1.48267 \tabularnewline
143 & 8.5 & 8.75412 & -0.25412 \tabularnewline
144 & 6 & 4.111 & 1.889 \tabularnewline
145 & 9 & 8.09286 & 0.907144 \tabularnewline
146 & 8 & 7.6413 & 0.358704 \tabularnewline
147 & 9 & 10.4409 & -1.44087 \tabularnewline
148 & 5.5 & 5.77882 & -0.278822 \tabularnewline
149 & 7 & 8.45134 & -1.45134 \tabularnewline
150 & 5.5 & 4.57596 & 0.924037 \tabularnewline
151 & 9 & 14.2074 & -5.20739 \tabularnewline
152 & 2 & 1.84836 & 0.151643 \tabularnewline
153 & 8.5 & 7.71164 & 0.788364 \tabularnewline
154 & 9 & 7.9162 & 1.0838 \tabularnewline
155 & 8.5 & 6.96724 & 1.53276 \tabularnewline
156 & 9 & 7.89051 & 1.10949 \tabularnewline
157 & 7.5 & 5.955 & 1.545 \tabularnewline
158 & 10 & 8.47632 & 1.52368 \tabularnewline
159 & 9 & 8.82304 & 0.176959 \tabularnewline
160 & 7.5 & 8.55522 & -1.05522 \tabularnewline
161 & 6 & 2.95352 & 3.04648 \tabularnewline
162 & 10.5 & 8.87845 & 1.62155 \tabularnewline
163 & 8.5 & 9.44892 & -0.948922 \tabularnewline
164 & 8 & 5.45123 & 2.54877 \tabularnewline
165 & 10 & 7.69144 & 2.30856 \tabularnewline
166 & 10.5 & 9.78412 & 0.715885 \tabularnewline
167 & 6.5 & 4.09348 & 2.40652 \tabularnewline
168 & 9.5 & 8.44475 & 1.05525 \tabularnewline
169 & 8.5 & 8.65795 & -0.157955 \tabularnewline
170 & 7.5 & 8.9573 & -1.4573 \tabularnewline
171 & 5 & 3.71686 & 1.28314 \tabularnewline
172 & 8 & 4.96463 & 3.03537 \tabularnewline
173 & 10 & 10.8588 & -0.858754 \tabularnewline
174 & 7 & 7.3194 & -0.3194 \tabularnewline
175 & 7.5 & 7.76064 & -0.260638 \tabularnewline
176 & 7.5 & 4.07219 & 3.42781 \tabularnewline
177 & 9.5 & 10.6682 & -1.16819 \tabularnewline
178 & 6 & 3.36999 & 2.63001 \tabularnewline
179 & 10 & 9.7447 & 0.255298 \tabularnewline
180 & 7 & 10.5909 & -3.59095 \tabularnewline
181 & 3 & 4.36917 & -1.36917 \tabularnewline
182 & 6 & 6.10486 & -0.104864 \tabularnewline
183 & 7 & 5.48396 & 1.51604 \tabularnewline
184 & 10 & 9.8118 & 0.188201 \tabularnewline
185 & 7 & 9.93325 & -2.93325 \tabularnewline
186 & 3.5 & 3.03581 & 0.46419 \tabularnewline
187 & 8 & 5.56241 & 2.43759 \tabularnewline
188 & 10 & 12.0826 & -2.08258 \tabularnewline
189 & 5.5 & 6.94885 & -1.44885 \tabularnewline
190 & 6 & 6.04186 & -0.0418623 \tabularnewline
191 & 6.5 & 7.16889 & -0.668895 \tabularnewline
192 & 6.5 & 3.71766 & 2.78234 \tabularnewline
193 & 8.5 & 11.3079 & -2.80786 \tabularnewline
194 & 4 & 0.702208 & 3.29779 \tabularnewline
195 & 9.5 & 8.22775 & 1.27225 \tabularnewline
196 & 8 & 7.05582 & 0.944178 \tabularnewline
197 & 8.5 & 10.8475 & -2.34749 \tabularnewline
198 & 5.5 & 4.25998 & 1.24002 \tabularnewline
199 & 7 & 4.49513 & 2.50487 \tabularnewline
200 & 9 & 7.61807 & 1.38193 \tabularnewline
201 & 8 & 6.35197 & 1.64803 \tabularnewline
202 & 10 & 9.30041 & 0.69959 \tabularnewline
203 & 8 & 8.90613 & -0.906128 \tabularnewline
204 & 6 & 5.38352 & 0.616484 \tabularnewline
205 & 8 & 10.1937 & -2.1937 \tabularnewline
206 & 5 & 3.20912 & 1.79088 \tabularnewline
207 & 9 & 10.654 & -1.65402 \tabularnewline
208 & 4.5 & 3.14132 & 1.35868 \tabularnewline
209 & 8.5 & 4.54169 & 3.95831 \tabularnewline
210 & 9.5 & 7.47304 & 2.02696 \tabularnewline
211 & 8.5 & 8.25095 & 0.249048 \tabularnewline
212 & 7.5 & 7.20466 & 0.295343 \tabularnewline
213 & 7.5 & 8.96236 & -1.46236 \tabularnewline
214 & 5 & 4.06707 & 0.93293 \tabularnewline
215 & 7 & 6.88469 & 0.115308 \tabularnewline
216 & 8 & 8.93388 & -0.93388 \tabularnewline
217 & 5.5 & 3.62005 & 1.87995 \tabularnewline
218 & 8.5 & 6.67209 & 1.82791 \tabularnewline
219 & 9.5 & 9.40593 & 0.0940684 \tabularnewline
220 & 7 & 6.73689 & 0.263107 \tabularnewline
221 & 8 & 6.10663 & 1.89337 \tabularnewline
222 & 8.5 & 10.1519 & -1.6519 \tabularnewline
223 & 3.5 & 4.81804 & -1.31804 \tabularnewline
224 & 6.5 & 6.45349 & 0.0465124 \tabularnewline
225 & 6.5 & 3.89535 & 2.60465 \tabularnewline
226 & 10.5 & 8.9658 & 1.5342 \tabularnewline
227 & 8.5 & 7.89206 & 0.607942 \tabularnewline
228 & 8 & 5.05261 & 2.94739 \tabularnewline
229 & 10 & 7.61493 & 2.38507 \tabularnewline
230 & 10 & 8.42433 & 1.57567 \tabularnewline
231 & 9.5 & 7.69003 & 1.80997 \tabularnewline
232 & 9 & 6.53504 & 2.46496 \tabularnewline
233 & 10 & 8.98379 & 1.01621 \tabularnewline
234 & 7.5 & 10.5969 & -3.09688 \tabularnewline
235 & 4.5 & 6.24363 & -1.74363 \tabularnewline
236 & 4.5 & 11.8507 & -7.35072 \tabularnewline
237 & 0.5 & 0.599052 & -0.0990524 \tabularnewline
238 & 6.5 & 8.44066 & -1.94066 \tabularnewline
239 & 4.5 & 6.03646 & -1.53646 \tabularnewline
240 & 5.5 & 6.7197 & -1.2197 \tabularnewline
241 & 5 & 6.69456 & -1.69456 \tabularnewline
242 & 6 & 7.56807 & -1.56807 \tabularnewline
243 & 4 & 2.979 & 1.021 \tabularnewline
244 & 8 & 5.07296 & 2.92704 \tabularnewline
245 & 10.5 & 10.9388 & -0.438789 \tabularnewline
246 & 6.5 & 4.59542 & 1.90458 \tabularnewline
247 & 8 & 7.21895 & 0.781046 \tabularnewline
248 & 8.5 & 10.3028 & -1.80276 \tabularnewline
249 & 5.5 & 5.62372 & -0.123723 \tabularnewline
250 & 7 & 8.98323 & -1.98323 \tabularnewline
251 & 5 & 8.35158 & -3.35158 \tabularnewline
252 & 3.5 & 6.23349 & -2.73349 \tabularnewline
253 & 5 & 3.12194 & 1.87806 \tabularnewline
254 & 9 & 6.3332 & 2.6668 \tabularnewline
255 & 8.5 & 10.8558 & -2.35579 \tabularnewline
256 & 5 & 3.05603 & 1.94397 \tabularnewline
257 & 9.5 & 13.2586 & -3.75861 \tabularnewline
258 & 3 & 8.83887 & -5.83887 \tabularnewline
259 & 1.5 & 1.89563 & -0.395634 \tabularnewline
260 & 6 & 11.3717 & -5.37175 \tabularnewline
261 & 0.5 & 0.467191 & 0.0328089 \tabularnewline
262 & 6.5 & 6.54834 & -0.0483404 \tabularnewline
263 & 7.5 & 9.00289 & -1.50289 \tabularnewline
264 & 4.5 & 3.25747 & 1.24253 \tabularnewline
265 & 8 & 5.98606 & 2.01394 \tabularnewline
266 & 9 & 8.67178 & 0.328225 \tabularnewline
267 & 7.5 & 6.84553 & 0.654469 \tabularnewline
268 & 8.5 & 6.96636 & 1.53364 \tabularnewline
269 & 7 & 4.9488 & 2.0512 \tabularnewline
270 & 9.5 & 10.2512 & -0.751216 \tabularnewline
271 & 6.5 & 3.54158 & 2.95842 \tabularnewline
272 & 9.5 & 10.0867 & -0.586706 \tabularnewline
273 & 6 & 3.49428 & 2.50572 \tabularnewline
274 & 8 & 5.55434 & 2.44566 \tabularnewline
275 & 9.5 & 8.39859 & 1.10141 \tabularnewline
276 & 8 & 8.48154 & -0.481544 \tabularnewline
277 & 8 & 6.14173 & 1.85827 \tabularnewline
278 & 9 & 11.314 & -2.31398 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.9558[/C][C]1.5442[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.08464[/C][C]0.915358[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.4614[/C][C]1.0386[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]4.44804[/C][C]-3.44804[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.9483[/C][C]-3.9483[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]3.09937[/C][C]2.40063[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.24564[/C][C]3.25436[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]5.81346[/C][C]0.68654[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.13027[/C][C]0.369734[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]5.5897[/C][C]-3.5897[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.37081[/C][C]-0.370808[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.2166[/C][C]-3.7166[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]4.39474[/C][C]0.605263[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.66167[/C][C]0.338332[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]6.52168[/C][C]-4.02168[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.13846[/C][C]-0.138458[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]4.43369[/C][C]1.06631[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.92805[/C][C]-1.42805[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]4.2597[/C][C]-1.2597[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]4.26921[/C][C]-0.269209[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]4.69281[/C][C]-4.19281[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]4.3974[/C][C]2.1026[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]3.75289[/C][C]0.747109[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]3.85549[/C][C]3.64451[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.33933[/C][C]0.160673[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]2.39705[/C][C]1.60295[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]3.97776[/C][C]3.52224[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.41295[/C][C]1.58705[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]5.26911[/C][C]-1.26911[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]4.66523[/C][C]0.834774[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]4.77386[/C][C]-2.27386[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]4.27922[/C][C]1.22078[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.20025[/C][C]-1.70025[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]4.74222[/C][C]-2.24222[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.66762[/C][C]-1.16762[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.2996[/C][C]-1.7996[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]4.67989[/C][C]-0.179889[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]3.66565[/C][C]2.33435[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.11697[/C][C]-2.61697[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]5.11456[/C][C]-0.114555[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]5.92107[/C][C]-5.92107[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.21724[/C][C]-0.217236[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]4.44764[/C][C]2.05236[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]4.74877[/C][C]0.25123[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.23345[/C][C]0.766552[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.48626[/C][C]-0.986257[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]4.732[/C][C]0.768004[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]4.40098[/C][C]-3.40098[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]5.13859[/C][C]2.36141[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.77797[/C][C]0.222032[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]4.65406[/C][C]0.345943[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.51089[/C][C]-4.51089[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]4.78899[/C][C]0.211014[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]3.33268[/C][C]3.16732[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]4.84525[/C][C]2.15475[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]5.51305[/C][C]-1.01305[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]4.53015[/C][C]-4.53015[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]3.97607[/C][C]4.52393[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.58591[/C][C]-2.08591[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.4321[/C][C]2.0679[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.33252[/C][C]-1.83252[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.3513[/C][C]1.6487[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.23396[/C][C]-3.73396[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]4.44421[/C][C]4.55579[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.15209[/C][C]-0.652093[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.84137[/C][C]-2.34137[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]4.32368[/C][C]-0.323683[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]4.23853[/C][C]2.26147[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]4.69556[/C][C]2.80444[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]4.32305[/C][C]1.67695[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]4.62462[/C][C]0.375378[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.78661[/C][C]-0.286611[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.66691[/C][C]-2.16691[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.57795[/C][C]1.92205[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]4.72372[/C][C]1.77628[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.73099[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.37813[/C][C]1.12187[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]4.55211[/C][C]1.94789[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]8.15618[/C][C]-1.15618[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]6.60057[/C][C]-3.10057[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]2.51964[/C][C]-1.01964[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]0.704266[/C][C]3.29573[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]8.10342[/C][C]-0.603423[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]8.9144[/C][C]-4.4144[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]0.792758[/C][C]-0.792758[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]2.79116[/C][C]0.708835[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]5.70001[/C][C]-0.200014[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]6.42492[/C][C]-1.42492[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]7.55588[/C][C]-3.05588[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]-1.60641[/C][C]4.10641[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]6.1363[/C][C]1.3637[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]10.7589[/C][C]-3.7589[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]-1.27817[/C][C]1.27817[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]5.8328[/C][C]-1.3328[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]5.86891[/C][C]-2.86891[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]2.12076[/C][C]-0.620757[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]5.28971[/C][C]-1.78971[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]2.09104[/C][C]0.408964[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]2.80349[/C][C]2.69651[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]11.6273[/C][C]-3.62726[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.60563[/C][C]-0.605625[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]5.80982[/C][C]-0.809822[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]5.98649[/C][C]-1.48649[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]3.51349[/C][C]-0.513493[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]-0.298425[/C][C]3.29842[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.0601[/C][C]-2.06005[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]-0.296058[/C][C]2.79606[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]12.3885[/C][C]-5.38848[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]5.16889[/C][C]-5.16889[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]2.23671[/C][C]-1.23671[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]3.06868[/C][C]0.431321[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.94228[/C][C]0.557723[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]11.8198[/C][C]-6.31976[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]0.0690728[/C][C]0.430927[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]5.56136[/C][C]1.93864[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]7.45038[/C][C]1.54962[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]8.86934[/C][C]0.630658[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]7.33849[/C][C]1.16151[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]7.63499[/C][C]-0.63499[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]6.07004[/C][C]1.92996[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.7114[/C][C]-0.711371[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]5.2894[/C][C]1.7106[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]7.60376[/C][C]0.896239[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]6.76567[/C][C]2.23433[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]12.6744[/C][C]-3.17439[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]4.23551[/C][C]-0.235506[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]4.87437[/C][C]1.12563[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]8.97647[/C][C]-0.976467[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]2.77152[/C][C]2.72848[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]9.39495[/C][C]0.10505[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]8.14102[/C][C]-0.641016[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]7.25592[/C][C]-0.255924[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]6.81799[/C][C]0.682005[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.83637[/C][C]0.163635[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]7.23661[/C][C]-0.23661[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]8.18001[/C][C]-1.18001[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]3.38365[/C][C]2.61635[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]14.9154[/C][C]-4.91544[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]1.43411[/C][C]1.06589[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.96062[/C][C]0.0393753[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]8.43937[/C][C]-0.439368[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]4.51733[/C][C]1.48267[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]8.75412[/C][C]-0.25412[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]4.111[/C][C]1.889[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]8.09286[/C][C]0.907144[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]7.6413[/C][C]0.358704[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]10.4409[/C][C]-1.44087[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]5.77882[/C][C]-0.278822[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.45134[/C][C]-1.45134[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]4.57596[/C][C]0.924037[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]14.2074[/C][C]-5.20739[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]1.84836[/C][C]0.151643[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]7.71164[/C][C]0.788364[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]7.9162[/C][C]1.0838[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]6.96724[/C][C]1.53276[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]7.89051[/C][C]1.10949[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]5.955[/C][C]1.545[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]8.47632[/C][C]1.52368[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.82304[/C][C]0.176959[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]8.55522[/C][C]-1.05522[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]2.95352[/C][C]3.04648[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.87845[/C][C]1.62155[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]9.44892[/C][C]-0.948922[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]5.45123[/C][C]2.54877[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]7.69144[/C][C]2.30856[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]9.78412[/C][C]0.715885[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]4.09348[/C][C]2.40652[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]8.44475[/C][C]1.05525[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]8.65795[/C][C]-0.157955[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]8.9573[/C][C]-1.4573[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]3.71686[/C][C]1.28314[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]4.96463[/C][C]3.03537[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]10.8588[/C][C]-0.858754[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.3194[/C][C]-0.3194[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.76064[/C][C]-0.260638[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]4.07219[/C][C]3.42781[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]10.6682[/C][C]-1.16819[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]3.36999[/C][C]2.63001[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]9.7447[/C][C]0.255298[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]10.5909[/C][C]-3.59095[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]4.36917[/C][C]-1.36917[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]6.10486[/C][C]-0.104864[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]5.48396[/C][C]1.51604[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]9.8118[/C][C]0.188201[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]9.93325[/C][C]-2.93325[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]3.03581[/C][C]0.46419[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]5.56241[/C][C]2.43759[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]12.0826[/C][C]-2.08258[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]6.94885[/C][C]-1.44885[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]6.04186[/C][C]-0.0418623[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]7.16889[/C][C]-0.668895[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]3.71766[/C][C]2.78234[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]11.3079[/C][C]-2.80786[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]0.702208[/C][C]3.29779[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]8.22775[/C][C]1.27225[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]7.05582[/C][C]0.944178[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]10.8475[/C][C]-2.34749[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]4.25998[/C][C]1.24002[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]4.49513[/C][C]2.50487[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]7.61807[/C][C]1.38193[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]6.35197[/C][C]1.64803[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]9.30041[/C][C]0.69959[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]8.90613[/C][C]-0.906128[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]5.38352[/C][C]0.616484[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.1937[/C][C]-2.1937[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]3.20912[/C][C]1.79088[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]10.654[/C][C]-1.65402[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]3.14132[/C][C]1.35868[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]4.54169[/C][C]3.95831[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.47304[/C][C]2.02696[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]8.25095[/C][C]0.249048[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.20466[/C][C]0.295343[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]8.96236[/C][C]-1.46236[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]4.06707[/C][C]0.93293[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]6.88469[/C][C]0.115308[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]8.93388[/C][C]-0.93388[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.62005[/C][C]1.87995[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]6.67209[/C][C]1.82791[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]9.40593[/C][C]0.0940684[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]6.73689[/C][C]0.263107[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]6.10663[/C][C]1.89337[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]10.1519[/C][C]-1.6519[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]4.81804[/C][C]-1.31804[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]6.45349[/C][C]0.0465124[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]3.89535[/C][C]2.60465[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]8.9658[/C][C]1.5342[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]7.89206[/C][C]0.607942[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]5.05261[/C][C]2.94739[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.61493[/C][C]2.38507[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]8.42433[/C][C]1.57567[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]7.69003[/C][C]1.80997[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]6.53504[/C][C]2.46496[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]8.98379[/C][C]1.01621[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]10.5969[/C][C]-3.09688[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]6.24363[/C][C]-1.74363[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.8507[/C][C]-7.35072[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]0.599052[/C][C]-0.0990524[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]8.44066[/C][C]-1.94066[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]6.03646[/C][C]-1.53646[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.7197[/C][C]-1.2197[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]6.69456[/C][C]-1.69456[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]7.56807[/C][C]-1.56807[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]2.979[/C][C]1.021[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]5.07296[/C][C]2.92704[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]10.9388[/C][C]-0.438789[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]4.59542[/C][C]1.90458[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]7.21895[/C][C]0.781046[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]10.3028[/C][C]-1.80276[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]5.62372[/C][C]-0.123723[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]8.98323[/C][C]-1.98323[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]8.35158[/C][C]-3.35158[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]6.23349[/C][C]-2.73349[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]3.12194[/C][C]1.87806[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]6.3332[/C][C]2.6668[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]10.8558[/C][C]-2.35579[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]3.05603[/C][C]1.94397[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]13.2586[/C][C]-3.75861[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]8.83887[/C][C]-5.83887[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]1.89563[/C][C]-0.395634[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]11.3717[/C][C]-5.37175[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]0.467191[/C][C]0.0328089[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]6.54834[/C][C]-0.0483404[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]9.00289[/C][C]-1.50289[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]3.25747[/C][C]1.24253[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]5.98606[/C][C]2.01394[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]8.67178[/C][C]0.328225[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]6.84553[/C][C]0.654469[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]6.96636[/C][C]1.53364[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]4.9488[/C][C]2.0512[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]10.2512[/C][C]-0.751216[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]3.54158[/C][C]2.95842[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]10.0867[/C][C]-0.586706[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]3.49428[/C][C]2.50572[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.55434[/C][C]2.44566[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]8.39859[/C][C]1.10141[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]8.48154[/C][C]-0.481544[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]6.14173[/C][C]1.85827[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]11.314[/C][C]-2.31398[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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	7.5	5.9558	1.5442
2	6	5.08464	0.915358
3	6.5	5.4614	1.0386
4	1	4.44804	-3.44804
5	1	4.9483	-3.9483
6	5.5	3.09937	2.40063
7	8.5	5.24564	3.25436
8	6.5	5.81346	0.68654
9	4.5	4.13027	0.369734
10	2	5.5897	-3.5897
11	5	5.37081	-0.370808
12	0.5	4.2166	-3.7166
13	5	4.39474	0.605263
14	5	4.66167	0.338332
15	2.5	6.52168	-4.02168
16	5	5.13846	-0.138458
17	5.5	4.43369	1.06631
18	3.5	4.92805	-1.42805
19	3	4.2597	-1.2597
20	4	4.26921	-0.269209
21	0.5	4.69281	-4.19281
22	6.5	4.3974	2.1026
23	4.5	3.75289	0.747109
24	7.5	3.85549	3.64451
25	5.5	5.33933	0.160673
26	4	2.39705	1.60295
27	7.5	3.97776	3.52224
28	7	5.41295	1.58705
29	4	5.26911	-1.26911
30	5.5	4.66523	0.834774
31	2.5	4.77386	-2.27386
32	5.5	4.27922	1.22078
33	3.5	5.20025	-1.70025
34	2.5	4.74222	-2.24222
35	4.5	5.66762	-1.16762
36	4.5	6.2996	-1.7996
37	4.5	4.67989	-0.179889
38	6	3.66565	2.33435
39	2.5	5.11697	-2.61697
40	5	5.11456	-0.114555
41	0	5.92107	-5.92107
42	5	5.21724	-0.217236
43	6.5	4.44764	2.05236
44	5	4.74877	0.25123
45	6	5.23345	0.766552
46	4.5	5.48626	-0.986257
47	5.5	4.732	0.768004
48	1	4.40098	-3.40098
49	7.5	5.13859	2.36141
50	6	5.77797	0.222032
51	5	4.65406	0.345943
52	1	5.51089	-4.51089
53	5	4.78899	0.211014
54	6.5	3.33268	3.16732
55	7	4.84525	2.15475
56	4.5	5.51305	-1.01305
57	0	4.53015	-4.53015
58	8.5	3.97607	4.52393
59	3.5	5.58591	-2.08591
60	7.5	5.4321	2.0679
61	3.5	5.33252	-1.83252
62	6	4.3513	1.6487
63	1.5	5.23396	-3.73396
64	9	4.44421	4.55579
65	3.5	4.15209	-0.652093
66	3.5	5.84137	-2.34137
67	4	4.32368	-0.323683
68	6.5	4.23853	2.26147
69	7.5	4.69556	2.80444
70	6	4.32305	1.67695
71	5	4.62462	0.375378
72	5.5	5.78661	-0.286611
73	3.5	5.66691	-2.16691
74	7.5	5.57795	1.92205
75	6.5	4.72372	1.77628
76	NA	NA	1.73099
77	6.5	5.37813	1.12187
78	6.5	4.55211	1.94789
79	7	8.15618	-1.15618
80	3.5	6.60057	-3.10057
81	1.5	2.51964	-1.01964
82	4	0.704266	3.29573
83	7.5	8.10342	-0.603423
84	4.5	8.9144	-4.4144
85	0	0.792758	-0.792758
86	3.5	2.79116	0.708835
87	5.5	5.70001	-0.200014
88	5	6.42492	-1.42492
89	4.5	7.55588	-3.05588
90	2.5	-1.60641	4.10641
91	7.5	6.1363	1.3637
92	7	10.7589	-3.7589
93	0	-1.27817	1.27817
94	4.5	5.8328	-1.3328
95	3	5.86891	-2.86891
96	1.5	2.12076	-0.620757
97	3.5	5.28971	-1.78971
98	2.5	2.09104	0.408964
99	5.5	2.80349	2.69651
100	8	11.6273	-3.62726
101	1	1.60563	-0.605625
102	5	5.80982	-0.809822
103	4.5	5.98649	-1.48649
104	3	3.51349	-0.513493
105	3	-0.298425	3.29842
106	8	10.0601	-2.06005
107	2.5	-0.296058	2.79606
108	7	12.3885	-5.38848
109	0	5.16889	-5.16889
110	1	2.23671	-1.23671
111	3.5	3.06868	0.431321
112	5.5	4.94228	0.557723
113	5.5	11.8198	-6.31976
114	0.5	0.0690728	0.430927
115	7.5	5.56136	1.93864
116	9	7.45038	1.54962
117	9.5	8.86934	0.630658
118	8.5	7.33849	1.16151
119	7	7.63499	-0.63499
120	8	6.07004	1.92996
121	10	10.7114	-0.711371
122	7	5.2894	1.7106
123	8.5	7.60376	0.896239
124	9	6.76567	2.23433
125	9.5	12.6744	-3.17439
126	4	4.23551	-0.235506
127	6	4.87437	1.12563
128	8	8.97647	-0.976467
129	5.5	2.77152	2.72848
130	9.5	9.39495	0.10505
131	7.5	8.14102	-0.641016
132	7	7.25592	-0.255924
133	7.5	6.81799	0.682005
134	8	7.83637	0.163635
135	7	7.23661	-0.23661
136	7	8.18001	-1.18001
137	6	3.38365	2.61635
138	10	14.9154	-4.91544
139	2.5	1.43411	1.06589
140	9	8.96062	0.0393753
141	8	8.43937	-0.439368
142	6	4.51733	1.48267
143	8.5	8.75412	-0.25412
144	6	4.111	1.889
145	9	8.09286	0.907144
146	8	7.6413	0.358704
147	9	10.4409	-1.44087
148	5.5	5.77882	-0.278822
149	7	8.45134	-1.45134
150	5.5	4.57596	0.924037
151	9	14.2074	-5.20739
152	2	1.84836	0.151643
153	8.5	7.71164	0.788364
154	9	7.9162	1.0838
155	8.5	6.96724	1.53276
156	9	7.89051	1.10949
157	7.5	5.955	1.545
158	10	8.47632	1.52368
159	9	8.82304	0.176959
160	7.5	8.55522	-1.05522
161	6	2.95352	3.04648
162	10.5	8.87845	1.62155
163	8.5	9.44892	-0.948922
164	8	5.45123	2.54877
165	10	7.69144	2.30856
166	10.5	9.78412	0.715885
167	6.5	4.09348	2.40652
168	9.5	8.44475	1.05525
169	8.5	8.65795	-0.157955
170	7.5	8.9573	-1.4573
171	5	3.71686	1.28314
172	8	4.96463	3.03537
173	10	10.8588	-0.858754
174	7	7.3194	-0.3194
175	7.5	7.76064	-0.260638
176	7.5	4.07219	3.42781
177	9.5	10.6682	-1.16819
178	6	3.36999	2.63001
179	10	9.7447	0.255298
180	7	10.5909	-3.59095
181	3	4.36917	-1.36917
182	6	6.10486	-0.104864
183	7	5.48396	1.51604
184	10	9.8118	0.188201
185	7	9.93325	-2.93325
186	3.5	3.03581	0.46419
187	8	5.56241	2.43759
188	10	12.0826	-2.08258
189	5.5	6.94885	-1.44885
190	6	6.04186	-0.0418623
191	6.5	7.16889	-0.668895
192	6.5	3.71766	2.78234
193	8.5	11.3079	-2.80786
194	4	0.702208	3.29779
195	9.5	8.22775	1.27225
196	8	7.05582	0.944178
197	8.5	10.8475	-2.34749
198	5.5	4.25998	1.24002
199	7	4.49513	2.50487
200	9	7.61807	1.38193
201	8	6.35197	1.64803
202	10	9.30041	0.69959
203	8	8.90613	-0.906128
204	6	5.38352	0.616484
205	8	10.1937	-2.1937
206	5	3.20912	1.79088
207	9	10.654	-1.65402
208	4.5	3.14132	1.35868
209	8.5	4.54169	3.95831
210	9.5	7.47304	2.02696
211	8.5	8.25095	0.249048
212	7.5	7.20466	0.295343
213	7.5	8.96236	-1.46236
214	5	4.06707	0.93293
215	7	6.88469	0.115308
216	8	8.93388	-0.93388
217	5.5	3.62005	1.87995
218	8.5	6.67209	1.82791
219	9.5	9.40593	0.0940684
220	7	6.73689	0.263107
221	8	6.10663	1.89337
222	8.5	10.1519	-1.6519
223	3.5	4.81804	-1.31804
224	6.5	6.45349	0.0465124
225	6.5	3.89535	2.60465
226	10.5	8.9658	1.5342
227	8.5	7.89206	0.607942
228	8	5.05261	2.94739
229	10	7.61493	2.38507
230	10	8.42433	1.57567
231	9.5	7.69003	1.80997
232	9	6.53504	2.46496
233	10	8.98379	1.01621
234	7.5	10.5969	-3.09688
235	4.5	6.24363	-1.74363
236	4.5	11.8507	-7.35072
237	0.5	0.599052	-0.0990524
238	6.5	8.44066	-1.94066
239	4.5	6.03646	-1.53646
240	5.5	6.7197	-1.2197
241	5	6.69456	-1.69456
242	6	7.56807	-1.56807
243	4	2.979	1.021
244	8	5.07296	2.92704
245	10.5	10.9388	-0.438789
246	6.5	4.59542	1.90458
247	8	7.21895	0.781046
248	8.5	10.3028	-1.80276
249	5.5	5.62372	-0.123723
250	7	8.98323	-1.98323
251	5	8.35158	-3.35158
252	3.5	6.23349	-2.73349
253	5	3.12194	1.87806
254	9	6.3332	2.6668
255	8.5	10.8558	-2.35579
256	5	3.05603	1.94397
257	9.5	13.2586	-3.75861
258	3	8.83887	-5.83887
259	1.5	1.89563	-0.395634
260	6	11.3717	-5.37175
261	0.5	0.467191	0.0328089
262	6.5	6.54834	-0.0483404
263	7.5	9.00289	-1.50289
264	4.5	3.25747	1.24253
265	8	5.98606	2.01394
266	9	8.67178	0.328225
267	7.5	6.84553	0.654469
268	8.5	6.96636	1.53364
269	7	4.9488	2.0512
270	9.5	10.2512	-0.751216
271	6.5	3.54158	2.95842
272	9.5	10.0867	-0.586706
273	6	3.49428	2.50572
274	8	5.55434	2.44566
275	9.5	8.39859	1.10141
276	8	8.48154	-0.481544
277	8	6.14173	1.85827
278	9	11.314	-2.31398
279	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
16	0.485855	0.971709	0.514145
17	0.602355	0.795291	0.397645
18	0.46058	0.92116	0.53942
19	0.360405	0.72081	0.639595
20	0.260225	0.520449	0.739775
21	0.207721	0.415442	0.792279
22	0.141841	0.283681	0.858159
23	0.216409	0.432818	0.783591
24	0.243296	0.486591	0.756704
25	0.202224	0.404447	0.797776
26	0.176083	0.352165	0.823917
27	0.16871	0.337421	0.83129
28	0.141967	0.283935	0.858033
29	0.112519	0.225038	0.887481
30	0.0815408	0.163082	0.918459
31	0.0826898	0.16538	0.91731
32	0.0665697	0.133139	0.93343
33	0.0654297	0.130859	0.93457
34	0.0837059	0.167412	0.916294
35	0.0609777	0.121955	0.939022
36	0.0447951	0.0895902	0.955205
37	0.0312646	0.0625292	0.968735
38	0.0297562	0.0595125	0.970244
39	0.0399944	0.0799888	0.960006
40	0.0413195	0.0826389	0.958681
41	0.0683566	0.136713	0.931643
42	0.052923	0.105846	0.947077
43	0.0532326	0.106465	0.946767
44	0.0412337	0.0824673	0.958766
45	0.0484549	0.0969098	0.951545
46	0.0488322	0.0976643	0.951168
47	0.0496509	0.0993019	0.950349
48	0.0553623	0.110725	0.944638
49	0.102928	0.205856	0.897072
50	0.104579	0.209158	0.895421
51	0.0827858	0.165572	0.917214
52	0.106898	0.213795	0.893102
53	0.0918447	0.183689	0.908155
54	0.0961705	0.192341	0.90383
55	0.234419	0.468838	0.765581
56	0.200712	0.401423	0.799288
57	0.514843	0.970314	0.485157
58	0.593831	0.812337	0.406169
59	0.576122	0.847757	0.423878
60	0.611005	0.77799	0.388995
61	0.583869	0.832263	0.416131
62	0.547287	0.905425	0.452713
63	0.655064	0.689873	0.344936
64	0.728873	0.542255	0.271127
65	0.731301	0.537398	0.268699
66	0.708025	0.58395	0.291975
67	0.670226	0.659547	0.329774
68	0.660423	0.679154	0.339577
69	0.690319	0.619362	0.309681
70	0.66631	0.667379	0.33369
71	0.632132	0.735737	0.367868
72	0.596224	0.807552	0.403776
73	0.572372	0.855256	0.427628
74	0.635124	0.729751	0.364876
75	0.608841	0.782318	0.391159
76	0.592786	0.814429	0.407214
77	0.561013	0.877974	0.438987
78	0.582273	0.835454	0.417727
79	0.54721	0.90558	0.45279
80	0.545929	0.908141	0.454071
81	0.510742	0.978516	0.489258
82	0.54397	0.91206	0.45603
83	0.505034	0.989932	0.494966
84	0.596327	0.807347	0.403673
85	0.567545	0.864909	0.432455
86	0.537925	0.924149	0.462075
87	0.502817	0.994366	0.497183
88	0.471169	0.942339	0.528831
89	0.483856	0.967711	0.516144
90	0.566402	0.867195	0.433598
91	0.592665	0.814669	0.407335
92	0.692334	0.615332	0.307666
93	0.678388	0.643223	0.321612
94	0.653691	0.692617	0.346309
95	0.664099	0.671802	0.335901
96	0.639501	0.720999	0.360499
97	0.631635	0.736729	0.368365
98	0.603835	0.79233	0.396165
99	0.647176	0.705647	0.352824
100	0.684061	0.631879	0.315939
101	0.654274	0.691452	0.345726
102	0.620643	0.758714	0.379357
103	0.616266	0.767468	0.383734
104	0.58985	0.820301	0.41015
105	0.661407	0.677185	0.338593
106	0.651719	0.696562	0.348281
107	0.731674	0.536652	0.268326
108	0.813006	0.373988	0.186994
109	0.870753	0.258494	0.129247
110	0.85449	0.29102	0.14551
111	0.833878	0.332245	0.166122
112	0.822033	0.355934	0.177967
113	0.885963	0.228073	0.114037
114	0.91295	0.174101	0.0870503
115	0.954462	0.0910767	0.0455384
116	0.968491	0.0630187	0.0315093
117	0.972863	0.0542736	0.0271368
118	0.972426	0.0551488	0.0275744
119	0.968083	0.0638331	0.0319166
120	0.973255	0.0534905	0.0267453
121	0.967306	0.0653871	0.0326935
122	0.967251	0.0654984	0.0327492
123	0.964511	0.0709772	0.0354886
124	0.969672	0.0606568	0.0303284
125	0.976022	0.0479553	0.0239777
126	0.970555	0.0588894	0.0294447
127	0.967194	0.0656115	0.0328058
128	0.960695	0.0786109	0.0393054
129	0.968734	0.0625319	0.0312659
130	0.962289	0.0754229	0.0377115
131	0.955562	0.0888762	0.0444381
132	0.948786	0.102429	0.0512143
133	0.940552	0.118896	0.0594478
134	0.933196	0.133608	0.0668041
135	0.921019	0.157963	0.0789815
136	0.914822	0.170356	0.0851778
137	0.921317	0.157367	0.0786835
138	0.958158	0.0836837	0.0418418
139	0.952583	0.0948346	0.0474173
140	0.943638	0.112725	0.0563624
141	0.935419	0.129161	0.0645807
142	0.930382	0.139237	0.0696184
143	0.917847	0.164306	0.0821532
144	0.915533	0.168934	0.0844672
145	0.907071	0.185858	0.092929
146	0.892634	0.214733	0.107366
147	0.882223	0.235553	0.117777
148	0.863539	0.272923	0.136461
149	0.850307	0.299385	0.149693
150	0.833063	0.333874	0.166937
151	0.910972	0.178055	0.0890276
152	0.896541	0.206919	0.103459
153	0.883476	0.233048	0.116524
154	0.876084	0.247831	0.123916
155	0.869901	0.260198	0.130099
156	0.858312	0.283377	0.141688
157	0.852529	0.294941	0.147471
158	0.844034	0.311933	0.155966
159	0.824227	0.351545	0.175773
160	0.813179	0.373643	0.186821
161	0.83437	0.33126	0.16563
162	0.823523	0.352954	0.176477
163	0.808461	0.383078	0.191539
164	0.815221	0.369557	0.184779
165	0.81202	0.375959	0.18798
166	0.788149	0.423701	0.211851
167	0.795261	0.409478	0.204739
168	0.772576	0.454847	0.227424
169	0.750025	0.499949	0.249975
170	0.747282	0.505435	0.252718
171	0.734515	0.53097	0.265485
172	0.759368	0.481265	0.240632
173	0.733857	0.532286	0.266143
174	0.703623	0.592754	0.296377
175	0.671832	0.656336	0.328168
176	0.728003	0.543994	0.271997
177	0.701533	0.596934	0.298467
178	0.749505	0.50099	0.250495
179	0.729558	0.540883	0.270442
180	0.804458	0.391084	0.195542
181	0.792132	0.415736	0.207868
182	0.764334	0.471331	0.235666
183	0.757398	0.485204	0.242602
184	0.728922	0.542155	0.271078
185	0.744575	0.51085	0.255425
186	0.713356	0.573287	0.286644
187	0.715334	0.569333	0.284666
188	0.722649	0.554701	0.277351
189	0.727425	0.545149	0.272575
190	0.704423	0.591155	0.295577
191	0.673345	0.653311	0.326655
192	0.674105	0.65179	0.325895
193	0.75353	0.49294	0.24647
194	0.770344	0.459313	0.229656
195	0.746187	0.507626	0.253813
196	0.715688	0.568624	0.284312
197	0.701507	0.596987	0.298493
198	0.671781	0.656438	0.328219
199	0.662196	0.675607	0.337804
200	0.632886	0.734228	0.367114
201	0.663334	0.673331	0.336666
202	0.629855	0.740291	0.370145
203	0.597086	0.805829	0.402914
204	0.557942	0.884115	0.442058
205	0.571885	0.856231	0.428115
206	0.539136	0.921728	0.460864
207	0.511234	0.977533	0.488766
208	0.47777	0.95554	0.52223
209	0.480607	0.961213	0.519393
210	0.449227	0.898453	0.550773
211	0.409979	0.819957	0.590021
212	0.393794	0.787588	0.606206
213	0.372911	0.745823	0.627089
214	0.335067	0.670134	0.664933
215	0.296419	0.592838	0.703581
216	0.262648	0.525296	0.737352
217	0.258785	0.51757	0.741215
218	0.299436	0.598873	0.700564
219	0.264506	0.529013	0.735494
220	0.228525	0.45705	0.771475
221	0.228414	0.456828	0.771586
222	0.246581	0.493163	0.753419
223	0.217058	0.434115	0.782942
224	0.185412	0.370824	0.814588
225	0.165767	0.331535	0.834233
226	0.140903	0.281805	0.859097
227	0.115978	0.231956	0.884022
228	0.120026	0.240053	0.879974
229	0.206356	0.412711	0.793644
230	0.19443	0.388861	0.80557
231	0.205398	0.410796	0.794602
232	0.24301	0.48602	0.75699
233	0.215425	0.430849	0.784575
234	0.191973	0.383945	0.808027
235	0.164728	0.329456	0.835272
236	0.574062	0.851876	0.425938
237	0.520573	0.958853	0.479427
238	0.471609	0.943218	0.528391
239	0.430295	0.86059	0.569705
240	0.37518	0.750361	0.62482
241	0.346425	0.69285	0.653575
242	0.298136	0.596273	0.701864
243	0.256492	0.512984	0.743508
244	0.225459	0.450919	0.774541
245	0.184637	0.369273	0.815363
246	0.203487	0.406975	0.796513
247	0.187115	0.37423	0.812885
248	0.158039	0.316079	0.841961
249	0.13606	0.272119	0.86394
250	0.103572	0.207145	0.896428
251	0.106356	0.212712	0.893644
252	0.0972648	0.19453	0.902735
253	0.0826803	0.165361	0.91732
254	0.189518	0.379035	0.810482
255	0.462326	0.924653	0.537674
256	0.377181	0.754362	0.622819
257	0.545764	0.908472	0.454236
258	0.780885	0.438229	0.219115
259	0.680361	0.639278	0.319639
260	0.812702	0.374597	0.187298
261	0.731898	0.536204	0.268102
262	0.58068	0.83864	0.41932
263	0.561757	0.876485	0.438243

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
16 & 0.485855 & 0.971709 & 0.514145 \tabularnewline
17 & 0.602355 & 0.795291 & 0.397645 \tabularnewline
18 & 0.46058 & 0.92116 & 0.53942 \tabularnewline
19 & 0.360405 & 0.72081 & 0.639595 \tabularnewline
20 & 0.260225 & 0.520449 & 0.739775 \tabularnewline
21 & 0.207721 & 0.415442 & 0.792279 \tabularnewline
22 & 0.141841 & 0.283681 & 0.858159 \tabularnewline
23 & 0.216409 & 0.432818 & 0.783591 \tabularnewline
24 & 0.243296 & 0.486591 & 0.756704 \tabularnewline
25 & 0.202224 & 0.404447 & 0.797776 \tabularnewline
26 & 0.176083 & 0.352165 & 0.823917 \tabularnewline
27 & 0.16871 & 0.337421 & 0.83129 \tabularnewline
28 & 0.141967 & 0.283935 & 0.858033 \tabularnewline
29 & 0.112519 & 0.225038 & 0.887481 \tabularnewline
30 & 0.0815408 & 0.163082 & 0.918459 \tabularnewline
31 & 0.0826898 & 0.16538 & 0.91731 \tabularnewline
32 & 0.0665697 & 0.133139 & 0.93343 \tabularnewline
33 & 0.0654297 & 0.130859 & 0.93457 \tabularnewline
34 & 0.0837059 & 0.167412 & 0.916294 \tabularnewline
35 & 0.0609777 & 0.121955 & 0.939022 \tabularnewline
36 & 0.0447951 & 0.0895902 & 0.955205 \tabularnewline
37 & 0.0312646 & 0.0625292 & 0.968735 \tabularnewline
38 & 0.0297562 & 0.0595125 & 0.970244 \tabularnewline
39 & 0.0399944 & 0.0799888 & 0.960006 \tabularnewline
40 & 0.0413195 & 0.0826389 & 0.958681 \tabularnewline
41 & 0.0683566 & 0.136713 & 0.931643 \tabularnewline
42 & 0.052923 & 0.105846 & 0.947077 \tabularnewline
43 & 0.0532326 & 0.106465 & 0.946767 \tabularnewline
44 & 0.0412337 & 0.0824673 & 0.958766 \tabularnewline
45 & 0.0484549 & 0.0969098 & 0.951545 \tabularnewline
46 & 0.0488322 & 0.0976643 & 0.951168 \tabularnewline
47 & 0.0496509 & 0.0993019 & 0.950349 \tabularnewline
48 & 0.0553623 & 0.110725 & 0.944638 \tabularnewline
49 & 0.102928 & 0.205856 & 0.897072 \tabularnewline
50 & 0.104579 & 0.209158 & 0.895421 \tabularnewline
51 & 0.0827858 & 0.165572 & 0.917214 \tabularnewline
52 & 0.106898 & 0.213795 & 0.893102 \tabularnewline
53 & 0.0918447 & 0.183689 & 0.908155 \tabularnewline
54 & 0.0961705 & 0.192341 & 0.90383 \tabularnewline
55 & 0.234419 & 0.468838 & 0.765581 \tabularnewline
56 & 0.200712 & 0.401423 & 0.799288 \tabularnewline
57 & 0.514843 & 0.970314 & 0.485157 \tabularnewline
58 & 0.593831 & 0.812337 & 0.406169 \tabularnewline
59 & 0.576122 & 0.847757 & 0.423878 \tabularnewline
60 & 0.611005 & 0.77799 & 0.388995 \tabularnewline
61 & 0.583869 & 0.832263 & 0.416131 \tabularnewline
62 & 0.547287 & 0.905425 & 0.452713 \tabularnewline
63 & 0.655064 & 0.689873 & 0.344936 \tabularnewline
64 & 0.728873 & 0.542255 & 0.271127 \tabularnewline
65 & 0.731301 & 0.537398 & 0.268699 \tabularnewline
66 & 0.708025 & 0.58395 & 0.291975 \tabularnewline
67 & 0.670226 & 0.659547 & 0.329774 \tabularnewline
68 & 0.660423 & 0.679154 & 0.339577 \tabularnewline
69 & 0.690319 & 0.619362 & 0.309681 \tabularnewline
70 & 0.66631 & 0.667379 & 0.33369 \tabularnewline
71 & 0.632132 & 0.735737 & 0.367868 \tabularnewline
72 & 0.596224 & 0.807552 & 0.403776 \tabularnewline
73 & 0.572372 & 0.855256 & 0.427628 \tabularnewline
74 & 0.635124 & 0.729751 & 0.364876 \tabularnewline
75 & 0.608841 & 0.782318 & 0.391159 \tabularnewline
76 & 0.592786 & 0.814429 & 0.407214 \tabularnewline
77 & 0.561013 & 0.877974 & 0.438987 \tabularnewline
78 & 0.582273 & 0.835454 & 0.417727 \tabularnewline
79 & 0.54721 & 0.90558 & 0.45279 \tabularnewline
80 & 0.545929 & 0.908141 & 0.454071 \tabularnewline
81 & 0.510742 & 0.978516 & 0.489258 \tabularnewline
82 & 0.54397 & 0.91206 & 0.45603 \tabularnewline
83 & 0.505034 & 0.989932 & 0.494966 \tabularnewline
84 & 0.596327 & 0.807347 & 0.403673 \tabularnewline
85 & 0.567545 & 0.864909 & 0.432455 \tabularnewline
86 & 0.537925 & 0.924149 & 0.462075 \tabularnewline
87 & 0.502817 & 0.994366 & 0.497183 \tabularnewline
88 & 0.471169 & 0.942339 & 0.528831 \tabularnewline
89 & 0.483856 & 0.967711 & 0.516144 \tabularnewline
90 & 0.566402 & 0.867195 & 0.433598 \tabularnewline
91 & 0.592665 & 0.814669 & 0.407335 \tabularnewline
92 & 0.692334 & 0.615332 & 0.307666 \tabularnewline
93 & 0.678388 & 0.643223 & 0.321612 \tabularnewline
94 & 0.653691 & 0.692617 & 0.346309 \tabularnewline
95 & 0.664099 & 0.671802 & 0.335901 \tabularnewline
96 & 0.639501 & 0.720999 & 0.360499 \tabularnewline
97 & 0.631635 & 0.736729 & 0.368365 \tabularnewline
98 & 0.603835 & 0.79233 & 0.396165 \tabularnewline
99 & 0.647176 & 0.705647 & 0.352824 \tabularnewline
100 & 0.684061 & 0.631879 & 0.315939 \tabularnewline
101 & 0.654274 & 0.691452 & 0.345726 \tabularnewline
102 & 0.620643 & 0.758714 & 0.379357 \tabularnewline
103 & 0.616266 & 0.767468 & 0.383734 \tabularnewline
104 & 0.58985 & 0.820301 & 0.41015 \tabularnewline
105 & 0.661407 & 0.677185 & 0.338593 \tabularnewline
106 & 0.651719 & 0.696562 & 0.348281 \tabularnewline
107 & 0.731674 & 0.536652 & 0.268326 \tabularnewline
108 & 0.813006 & 0.373988 & 0.186994 \tabularnewline
109 & 0.870753 & 0.258494 & 0.129247 \tabularnewline
110 & 0.85449 & 0.29102 & 0.14551 \tabularnewline
111 & 0.833878 & 0.332245 & 0.166122 \tabularnewline
112 & 0.822033 & 0.355934 & 0.177967 \tabularnewline
113 & 0.885963 & 0.228073 & 0.114037 \tabularnewline
114 & 0.91295 & 0.174101 & 0.0870503 \tabularnewline
115 & 0.954462 & 0.0910767 & 0.0455384 \tabularnewline
116 & 0.968491 & 0.0630187 & 0.0315093 \tabularnewline
117 & 0.972863 & 0.0542736 & 0.0271368 \tabularnewline
118 & 0.972426 & 0.0551488 & 0.0275744 \tabularnewline
119 & 0.968083 & 0.0638331 & 0.0319166 \tabularnewline
120 & 0.973255 & 0.0534905 & 0.0267453 \tabularnewline
121 & 0.967306 & 0.0653871 & 0.0326935 \tabularnewline
122 & 0.967251 & 0.0654984 & 0.0327492 \tabularnewline
123 & 0.964511 & 0.0709772 & 0.0354886 \tabularnewline
124 & 0.969672 & 0.0606568 & 0.0303284 \tabularnewline
125 & 0.976022 & 0.0479553 & 0.0239777 \tabularnewline
126 & 0.970555 & 0.0588894 & 0.0294447 \tabularnewline
127 & 0.967194 & 0.0656115 & 0.0328058 \tabularnewline
128 & 0.960695 & 0.0786109 & 0.0393054 \tabularnewline
129 & 0.968734 & 0.0625319 & 0.0312659 \tabularnewline
130 & 0.962289 & 0.0754229 & 0.0377115 \tabularnewline
131 & 0.955562 & 0.0888762 & 0.0444381 \tabularnewline
132 & 0.948786 & 0.102429 & 0.0512143 \tabularnewline
133 & 0.940552 & 0.118896 & 0.0594478 \tabularnewline
134 & 0.933196 & 0.133608 & 0.0668041 \tabularnewline
135 & 0.921019 & 0.157963 & 0.0789815 \tabularnewline
136 & 0.914822 & 0.170356 & 0.0851778 \tabularnewline
137 & 0.921317 & 0.157367 & 0.0786835 \tabularnewline
138 & 0.958158 & 0.0836837 & 0.0418418 \tabularnewline
139 & 0.952583 & 0.0948346 & 0.0474173 \tabularnewline
140 & 0.943638 & 0.112725 & 0.0563624 \tabularnewline
141 & 0.935419 & 0.129161 & 0.0645807 \tabularnewline
142 & 0.930382 & 0.139237 & 0.0696184 \tabularnewline
143 & 0.917847 & 0.164306 & 0.0821532 \tabularnewline
144 & 0.915533 & 0.168934 & 0.0844672 \tabularnewline
145 & 0.907071 & 0.185858 & 0.092929 \tabularnewline
146 & 0.892634 & 0.214733 & 0.107366 \tabularnewline
147 & 0.882223 & 0.235553 & 0.117777 \tabularnewline
148 & 0.863539 & 0.272923 & 0.136461 \tabularnewline
149 & 0.850307 & 0.299385 & 0.149693 \tabularnewline
150 & 0.833063 & 0.333874 & 0.166937 \tabularnewline
151 & 0.910972 & 0.178055 & 0.0890276 \tabularnewline
152 & 0.896541 & 0.206919 & 0.103459 \tabularnewline
153 & 0.883476 & 0.233048 & 0.116524 \tabularnewline
154 & 0.876084 & 0.247831 & 0.123916 \tabularnewline
155 & 0.869901 & 0.260198 & 0.130099 \tabularnewline
156 & 0.858312 & 0.283377 & 0.141688 \tabularnewline
157 & 0.852529 & 0.294941 & 0.147471 \tabularnewline
158 & 0.844034 & 0.311933 & 0.155966 \tabularnewline
159 & 0.824227 & 0.351545 & 0.175773 \tabularnewline
160 & 0.813179 & 0.373643 & 0.186821 \tabularnewline
161 & 0.83437 & 0.33126 & 0.16563 \tabularnewline
162 & 0.823523 & 0.352954 & 0.176477 \tabularnewline
163 & 0.808461 & 0.383078 & 0.191539 \tabularnewline
164 & 0.815221 & 0.369557 & 0.184779 \tabularnewline
165 & 0.81202 & 0.375959 & 0.18798 \tabularnewline
166 & 0.788149 & 0.423701 & 0.211851 \tabularnewline
167 & 0.795261 & 0.409478 & 0.204739 \tabularnewline
168 & 0.772576 & 0.454847 & 0.227424 \tabularnewline
169 & 0.750025 & 0.499949 & 0.249975 \tabularnewline
170 & 0.747282 & 0.505435 & 0.252718 \tabularnewline
171 & 0.734515 & 0.53097 & 0.265485 \tabularnewline
172 & 0.759368 & 0.481265 & 0.240632 \tabularnewline
173 & 0.733857 & 0.532286 & 0.266143 \tabularnewline
174 & 0.703623 & 0.592754 & 0.296377 \tabularnewline
175 & 0.671832 & 0.656336 & 0.328168 \tabularnewline
176 & 0.728003 & 0.543994 & 0.271997 \tabularnewline
177 & 0.701533 & 0.596934 & 0.298467 \tabularnewline
178 & 0.749505 & 0.50099 & 0.250495 \tabularnewline
179 & 0.729558 & 0.540883 & 0.270442 \tabularnewline
180 & 0.804458 & 0.391084 & 0.195542 \tabularnewline
181 & 0.792132 & 0.415736 & 0.207868 \tabularnewline
182 & 0.764334 & 0.471331 & 0.235666 \tabularnewline
183 & 0.757398 & 0.485204 & 0.242602 \tabularnewline
184 & 0.728922 & 0.542155 & 0.271078 \tabularnewline
185 & 0.744575 & 0.51085 & 0.255425 \tabularnewline
186 & 0.713356 & 0.573287 & 0.286644 \tabularnewline
187 & 0.715334 & 0.569333 & 0.284666 \tabularnewline
188 & 0.722649 & 0.554701 & 0.277351 \tabularnewline
189 & 0.727425 & 0.545149 & 0.272575 \tabularnewline
190 & 0.704423 & 0.591155 & 0.295577 \tabularnewline
191 & 0.673345 & 0.653311 & 0.326655 \tabularnewline
192 & 0.674105 & 0.65179 & 0.325895 \tabularnewline
193 & 0.75353 & 0.49294 & 0.24647 \tabularnewline
194 & 0.770344 & 0.459313 & 0.229656 \tabularnewline
195 & 0.746187 & 0.507626 & 0.253813 \tabularnewline
196 & 0.715688 & 0.568624 & 0.284312 \tabularnewline
197 & 0.701507 & 0.596987 & 0.298493 \tabularnewline
198 & 0.671781 & 0.656438 & 0.328219 \tabularnewline
199 & 0.662196 & 0.675607 & 0.337804 \tabularnewline
200 & 0.632886 & 0.734228 & 0.367114 \tabularnewline
201 & 0.663334 & 0.673331 & 0.336666 \tabularnewline
202 & 0.629855 & 0.740291 & 0.370145 \tabularnewline
203 & 0.597086 & 0.805829 & 0.402914 \tabularnewline
204 & 0.557942 & 0.884115 & 0.442058 \tabularnewline
205 & 0.571885 & 0.856231 & 0.428115 \tabularnewline
206 & 0.539136 & 0.921728 & 0.460864 \tabularnewline
207 & 0.511234 & 0.977533 & 0.488766 \tabularnewline
208 & 0.47777 & 0.95554 & 0.52223 \tabularnewline
209 & 0.480607 & 0.961213 & 0.519393 \tabularnewline
210 & 0.449227 & 0.898453 & 0.550773 \tabularnewline
211 & 0.409979 & 0.819957 & 0.590021 \tabularnewline
212 & 0.393794 & 0.787588 & 0.606206 \tabularnewline
213 & 0.372911 & 0.745823 & 0.627089 \tabularnewline
214 & 0.335067 & 0.670134 & 0.664933 \tabularnewline
215 & 0.296419 & 0.592838 & 0.703581 \tabularnewline
216 & 0.262648 & 0.525296 & 0.737352 \tabularnewline
217 & 0.258785 & 0.51757 & 0.741215 \tabularnewline
218 & 0.299436 & 0.598873 & 0.700564 \tabularnewline
219 & 0.264506 & 0.529013 & 0.735494 \tabularnewline
220 & 0.228525 & 0.45705 & 0.771475 \tabularnewline
221 & 0.228414 & 0.456828 & 0.771586 \tabularnewline
222 & 0.246581 & 0.493163 & 0.753419 \tabularnewline
223 & 0.217058 & 0.434115 & 0.782942 \tabularnewline
224 & 0.185412 & 0.370824 & 0.814588 \tabularnewline
225 & 0.165767 & 0.331535 & 0.834233 \tabularnewline
226 & 0.140903 & 0.281805 & 0.859097 \tabularnewline
227 & 0.115978 & 0.231956 & 0.884022 \tabularnewline
228 & 0.120026 & 0.240053 & 0.879974 \tabularnewline
229 & 0.206356 & 0.412711 & 0.793644 \tabularnewline
230 & 0.19443 & 0.388861 & 0.80557 \tabularnewline
231 & 0.205398 & 0.410796 & 0.794602 \tabularnewline
232 & 0.24301 & 0.48602 & 0.75699 \tabularnewline
233 & 0.215425 & 0.430849 & 0.784575 \tabularnewline
234 & 0.191973 & 0.383945 & 0.808027 \tabularnewline
235 & 0.164728 & 0.329456 & 0.835272 \tabularnewline
236 & 0.574062 & 0.851876 & 0.425938 \tabularnewline
237 & 0.520573 & 0.958853 & 0.479427 \tabularnewline
238 & 0.471609 & 0.943218 & 0.528391 \tabularnewline
239 & 0.430295 & 0.86059 & 0.569705 \tabularnewline
240 & 0.37518 & 0.750361 & 0.62482 \tabularnewline
241 & 0.346425 & 0.69285 & 0.653575 \tabularnewline
242 & 0.298136 & 0.596273 & 0.701864 \tabularnewline
243 & 0.256492 & 0.512984 & 0.743508 \tabularnewline
244 & 0.225459 & 0.450919 & 0.774541 \tabularnewline
245 & 0.184637 & 0.369273 & 0.815363 \tabularnewline
246 & 0.203487 & 0.406975 & 0.796513 \tabularnewline
247 & 0.187115 & 0.37423 & 0.812885 \tabularnewline
248 & 0.158039 & 0.316079 & 0.841961 \tabularnewline
249 & 0.13606 & 0.272119 & 0.86394 \tabularnewline
250 & 0.103572 & 0.207145 & 0.896428 \tabularnewline
251 & 0.106356 & 0.212712 & 0.893644 \tabularnewline
252 & 0.0972648 & 0.19453 & 0.902735 \tabularnewline
253 & 0.0826803 & 0.165361 & 0.91732 \tabularnewline
254 & 0.189518 & 0.379035 & 0.810482 \tabularnewline
255 & 0.462326 & 0.924653 & 0.537674 \tabularnewline
256 & 0.377181 & 0.754362 & 0.622819 \tabularnewline
257 & 0.545764 & 0.908472 & 0.454236 \tabularnewline
258 & 0.780885 & 0.438229 & 0.219115 \tabularnewline
259 & 0.680361 & 0.639278 & 0.319639 \tabularnewline
260 & 0.812702 & 0.374597 & 0.187298 \tabularnewline
261 & 0.731898 & 0.536204 & 0.268102 \tabularnewline
262 & 0.58068 & 0.83864 & 0.41932 \tabularnewline
263 & 0.561757 & 0.876485 & 0.438243 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&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]16[/C][C]0.485855[/C][C]0.971709[/C][C]0.514145[/C][/ROW]
[ROW][C]17[/C][C]0.602355[/C][C]0.795291[/C][C]0.397645[/C][/ROW]
[ROW][C]18[/C][C]0.46058[/C][C]0.92116[/C][C]0.53942[/C][/ROW]
[ROW][C]19[/C][C]0.360405[/C][C]0.72081[/C][C]0.639595[/C][/ROW]
[ROW][C]20[/C][C]0.260225[/C][C]0.520449[/C][C]0.739775[/C][/ROW]
[ROW][C]21[/C][C]0.207721[/C][C]0.415442[/C][C]0.792279[/C][/ROW]
[ROW][C]22[/C][C]0.141841[/C][C]0.283681[/C][C]0.858159[/C][/ROW]
[ROW][C]23[/C][C]0.216409[/C][C]0.432818[/C][C]0.783591[/C][/ROW]
[ROW][C]24[/C][C]0.243296[/C][C]0.486591[/C][C]0.756704[/C][/ROW]
[ROW][C]25[/C][C]0.202224[/C][C]0.404447[/C][C]0.797776[/C][/ROW]
[ROW][C]26[/C][C]0.176083[/C][C]0.352165[/C][C]0.823917[/C][/ROW]
[ROW][C]27[/C][C]0.16871[/C][C]0.337421[/C][C]0.83129[/C][/ROW]
[ROW][C]28[/C][C]0.141967[/C][C]0.283935[/C][C]0.858033[/C][/ROW]
[ROW][C]29[/C][C]0.112519[/C][C]0.225038[/C][C]0.887481[/C][/ROW]
[ROW][C]30[/C][C]0.0815408[/C][C]0.163082[/C][C]0.918459[/C][/ROW]
[ROW][C]31[/C][C]0.0826898[/C][C]0.16538[/C][C]0.91731[/C][/ROW]
[ROW][C]32[/C][C]0.0665697[/C][C]0.133139[/C][C]0.93343[/C][/ROW]
[ROW][C]33[/C][C]0.0654297[/C][C]0.130859[/C][C]0.93457[/C][/ROW]
[ROW][C]34[/C][C]0.0837059[/C][C]0.167412[/C][C]0.916294[/C][/ROW]
[ROW][C]35[/C][C]0.0609777[/C][C]0.121955[/C][C]0.939022[/C][/ROW]
[ROW][C]36[/C][C]0.0447951[/C][C]0.0895902[/C][C]0.955205[/C][/ROW]
[ROW][C]37[/C][C]0.0312646[/C][C]0.0625292[/C][C]0.968735[/C][/ROW]
[ROW][C]38[/C][C]0.0297562[/C][C]0.0595125[/C][C]0.970244[/C][/ROW]
[ROW][C]39[/C][C]0.0399944[/C][C]0.0799888[/C][C]0.960006[/C][/ROW]
[ROW][C]40[/C][C]0.0413195[/C][C]0.0826389[/C][C]0.958681[/C][/ROW]
[ROW][C]41[/C][C]0.0683566[/C][C]0.136713[/C][C]0.931643[/C][/ROW]
[ROW][C]42[/C][C]0.052923[/C][C]0.105846[/C][C]0.947077[/C][/ROW]
[ROW][C]43[/C][C]0.0532326[/C][C]0.106465[/C][C]0.946767[/C][/ROW]
[ROW][C]44[/C][C]0.0412337[/C][C]0.0824673[/C][C]0.958766[/C][/ROW]
[ROW][C]45[/C][C]0.0484549[/C][C]0.0969098[/C][C]0.951545[/C][/ROW]
[ROW][C]46[/C][C]0.0488322[/C][C]0.0976643[/C][C]0.951168[/C][/ROW]
[ROW][C]47[/C][C]0.0496509[/C][C]0.0993019[/C][C]0.950349[/C][/ROW]
[ROW][C]48[/C][C]0.0553623[/C][C]0.110725[/C][C]0.944638[/C][/ROW]
[ROW][C]49[/C][C]0.102928[/C][C]0.205856[/C][C]0.897072[/C][/ROW]
[ROW][C]50[/C][C]0.104579[/C][C]0.209158[/C][C]0.895421[/C][/ROW]
[ROW][C]51[/C][C]0.0827858[/C][C]0.165572[/C][C]0.917214[/C][/ROW]
[ROW][C]52[/C][C]0.106898[/C][C]0.213795[/C][C]0.893102[/C][/ROW]
[ROW][C]53[/C][C]0.0918447[/C][C]0.183689[/C][C]0.908155[/C][/ROW]
[ROW][C]54[/C][C]0.0961705[/C][C]0.192341[/C][C]0.90383[/C][/ROW]
[ROW][C]55[/C][C]0.234419[/C][C]0.468838[/C][C]0.765581[/C][/ROW]
[ROW][C]56[/C][C]0.200712[/C][C]0.401423[/C][C]0.799288[/C][/ROW]
[ROW][C]57[/C][C]0.514843[/C][C]0.970314[/C][C]0.485157[/C][/ROW]
[ROW][C]58[/C][C]0.593831[/C][C]0.812337[/C][C]0.406169[/C][/ROW]
[ROW][C]59[/C][C]0.576122[/C][C]0.847757[/C][C]0.423878[/C][/ROW]
[ROW][C]60[/C][C]0.611005[/C][C]0.77799[/C][C]0.388995[/C][/ROW]
[ROW][C]61[/C][C]0.583869[/C][C]0.832263[/C][C]0.416131[/C][/ROW]
[ROW][C]62[/C][C]0.547287[/C][C]0.905425[/C][C]0.452713[/C][/ROW]
[ROW][C]63[/C][C]0.655064[/C][C]0.689873[/C][C]0.344936[/C][/ROW]
[ROW][C]64[/C][C]0.728873[/C][C]0.542255[/C][C]0.271127[/C][/ROW]
[ROW][C]65[/C][C]0.731301[/C][C]0.537398[/C][C]0.268699[/C][/ROW]
[ROW][C]66[/C][C]0.708025[/C][C]0.58395[/C][C]0.291975[/C][/ROW]
[ROW][C]67[/C][C]0.670226[/C][C]0.659547[/C][C]0.329774[/C][/ROW]
[ROW][C]68[/C][C]0.660423[/C][C]0.679154[/C][C]0.339577[/C][/ROW]
[ROW][C]69[/C][C]0.690319[/C][C]0.619362[/C][C]0.309681[/C][/ROW]
[ROW][C]70[/C][C]0.66631[/C][C]0.667379[/C][C]0.33369[/C][/ROW]
[ROW][C]71[/C][C]0.632132[/C][C]0.735737[/C][C]0.367868[/C][/ROW]
[ROW][C]72[/C][C]0.596224[/C][C]0.807552[/C][C]0.403776[/C][/ROW]
[ROW][C]73[/C][C]0.572372[/C][C]0.855256[/C][C]0.427628[/C][/ROW]
[ROW][C]74[/C][C]0.635124[/C][C]0.729751[/C][C]0.364876[/C][/ROW]
[ROW][C]75[/C][C]0.608841[/C][C]0.782318[/C][C]0.391159[/C][/ROW]
[ROW][C]76[/C][C]0.592786[/C][C]0.814429[/C][C]0.407214[/C][/ROW]
[ROW][C]77[/C][C]0.561013[/C][C]0.877974[/C][C]0.438987[/C][/ROW]
[ROW][C]78[/C][C]0.582273[/C][C]0.835454[/C][C]0.417727[/C][/ROW]
[ROW][C]79[/C][C]0.54721[/C][C]0.90558[/C][C]0.45279[/C][/ROW]
[ROW][C]80[/C][C]0.545929[/C][C]0.908141[/C][C]0.454071[/C][/ROW]
[ROW][C]81[/C][C]0.510742[/C][C]0.978516[/C][C]0.489258[/C][/ROW]
[ROW][C]82[/C][C]0.54397[/C][C]0.91206[/C][C]0.45603[/C][/ROW]
[ROW][C]83[/C][C]0.505034[/C][C]0.989932[/C][C]0.494966[/C][/ROW]
[ROW][C]84[/C][C]0.596327[/C][C]0.807347[/C][C]0.403673[/C][/ROW]
[ROW][C]85[/C][C]0.567545[/C][C]0.864909[/C][C]0.432455[/C][/ROW]
[ROW][C]86[/C][C]0.537925[/C][C]0.924149[/C][C]0.462075[/C][/ROW]
[ROW][C]87[/C][C]0.502817[/C][C]0.994366[/C][C]0.497183[/C][/ROW]
[ROW][C]88[/C][C]0.471169[/C][C]0.942339[/C][C]0.528831[/C][/ROW]
[ROW][C]89[/C][C]0.483856[/C][C]0.967711[/C][C]0.516144[/C][/ROW]
[ROW][C]90[/C][C]0.566402[/C][C]0.867195[/C][C]0.433598[/C][/ROW]
[ROW][C]91[/C][C]0.592665[/C][C]0.814669[/C][C]0.407335[/C][/ROW]
[ROW][C]92[/C][C]0.692334[/C][C]0.615332[/C][C]0.307666[/C][/ROW]
[ROW][C]93[/C][C]0.678388[/C][C]0.643223[/C][C]0.321612[/C][/ROW]
[ROW][C]94[/C][C]0.653691[/C][C]0.692617[/C][C]0.346309[/C][/ROW]
[ROW][C]95[/C][C]0.664099[/C][C]0.671802[/C][C]0.335901[/C][/ROW]
[ROW][C]96[/C][C]0.639501[/C][C]0.720999[/C][C]0.360499[/C][/ROW]
[ROW][C]97[/C][C]0.631635[/C][C]0.736729[/C][C]0.368365[/C][/ROW]
[ROW][C]98[/C][C]0.603835[/C][C]0.79233[/C][C]0.396165[/C][/ROW]
[ROW][C]99[/C][C]0.647176[/C][C]0.705647[/C][C]0.352824[/C][/ROW]
[ROW][C]100[/C][C]0.684061[/C][C]0.631879[/C][C]0.315939[/C][/ROW]
[ROW][C]101[/C][C]0.654274[/C][C]0.691452[/C][C]0.345726[/C][/ROW]
[ROW][C]102[/C][C]0.620643[/C][C]0.758714[/C][C]0.379357[/C][/ROW]
[ROW][C]103[/C][C]0.616266[/C][C]0.767468[/C][C]0.383734[/C][/ROW]
[ROW][C]104[/C][C]0.58985[/C][C]0.820301[/C][C]0.41015[/C][/ROW]
[ROW][C]105[/C][C]0.661407[/C][C]0.677185[/C][C]0.338593[/C][/ROW]
[ROW][C]106[/C][C]0.651719[/C][C]0.696562[/C][C]0.348281[/C][/ROW]
[ROW][C]107[/C][C]0.731674[/C][C]0.536652[/C][C]0.268326[/C][/ROW]
[ROW][C]108[/C][C]0.813006[/C][C]0.373988[/C][C]0.186994[/C][/ROW]
[ROW][C]109[/C][C]0.870753[/C][C]0.258494[/C][C]0.129247[/C][/ROW]
[ROW][C]110[/C][C]0.85449[/C][C]0.29102[/C][C]0.14551[/C][/ROW]
[ROW][C]111[/C][C]0.833878[/C][C]0.332245[/C][C]0.166122[/C][/ROW]
[ROW][C]112[/C][C]0.822033[/C][C]0.355934[/C][C]0.177967[/C][/ROW]
[ROW][C]113[/C][C]0.885963[/C][C]0.228073[/C][C]0.114037[/C][/ROW]
[ROW][C]114[/C][C]0.91295[/C][C]0.174101[/C][C]0.0870503[/C][/ROW]
[ROW][C]115[/C][C]0.954462[/C][C]0.0910767[/C][C]0.0455384[/C][/ROW]
[ROW][C]116[/C][C]0.968491[/C][C]0.0630187[/C][C]0.0315093[/C][/ROW]
[ROW][C]117[/C][C]0.972863[/C][C]0.0542736[/C][C]0.0271368[/C][/ROW]
[ROW][C]118[/C][C]0.972426[/C][C]0.0551488[/C][C]0.0275744[/C][/ROW]
[ROW][C]119[/C][C]0.968083[/C][C]0.0638331[/C][C]0.0319166[/C][/ROW]
[ROW][C]120[/C][C]0.973255[/C][C]0.0534905[/C][C]0.0267453[/C][/ROW]
[ROW][C]121[/C][C]0.967306[/C][C]0.0653871[/C][C]0.0326935[/C][/ROW]
[ROW][C]122[/C][C]0.967251[/C][C]0.0654984[/C][C]0.0327492[/C][/ROW]
[ROW][C]123[/C][C]0.964511[/C][C]0.0709772[/C][C]0.0354886[/C][/ROW]
[ROW][C]124[/C][C]0.969672[/C][C]0.0606568[/C][C]0.0303284[/C][/ROW]
[ROW][C]125[/C][C]0.976022[/C][C]0.0479553[/C][C]0.0239777[/C][/ROW]
[ROW][C]126[/C][C]0.970555[/C][C]0.0588894[/C][C]0.0294447[/C][/ROW]
[ROW][C]127[/C][C]0.967194[/C][C]0.0656115[/C][C]0.0328058[/C][/ROW]
[ROW][C]128[/C][C]0.960695[/C][C]0.0786109[/C][C]0.0393054[/C][/ROW]
[ROW][C]129[/C][C]0.968734[/C][C]0.0625319[/C][C]0.0312659[/C][/ROW]
[ROW][C]130[/C][C]0.962289[/C][C]0.0754229[/C][C]0.0377115[/C][/ROW]
[ROW][C]131[/C][C]0.955562[/C][C]0.0888762[/C][C]0.0444381[/C][/ROW]
[ROW][C]132[/C][C]0.948786[/C][C]0.102429[/C][C]0.0512143[/C][/ROW]
[ROW][C]133[/C][C]0.940552[/C][C]0.118896[/C][C]0.0594478[/C][/ROW]
[ROW][C]134[/C][C]0.933196[/C][C]0.133608[/C][C]0.0668041[/C][/ROW]
[ROW][C]135[/C][C]0.921019[/C][C]0.157963[/C][C]0.0789815[/C][/ROW]
[ROW][C]136[/C][C]0.914822[/C][C]0.170356[/C][C]0.0851778[/C][/ROW]
[ROW][C]137[/C][C]0.921317[/C][C]0.157367[/C][C]0.0786835[/C][/ROW]
[ROW][C]138[/C][C]0.958158[/C][C]0.0836837[/C][C]0.0418418[/C][/ROW]
[ROW][C]139[/C][C]0.952583[/C][C]0.0948346[/C][C]0.0474173[/C][/ROW]
[ROW][C]140[/C][C]0.943638[/C][C]0.112725[/C][C]0.0563624[/C][/ROW]
[ROW][C]141[/C][C]0.935419[/C][C]0.129161[/C][C]0.0645807[/C][/ROW]
[ROW][C]142[/C][C]0.930382[/C][C]0.139237[/C][C]0.0696184[/C][/ROW]
[ROW][C]143[/C][C]0.917847[/C][C]0.164306[/C][C]0.0821532[/C][/ROW]
[ROW][C]144[/C][C]0.915533[/C][C]0.168934[/C][C]0.0844672[/C][/ROW]
[ROW][C]145[/C][C]0.907071[/C][C]0.185858[/C][C]0.092929[/C][/ROW]
[ROW][C]146[/C][C]0.892634[/C][C]0.214733[/C][C]0.107366[/C][/ROW]
[ROW][C]147[/C][C]0.882223[/C][C]0.235553[/C][C]0.117777[/C][/ROW]
[ROW][C]148[/C][C]0.863539[/C][C]0.272923[/C][C]0.136461[/C][/ROW]
[ROW][C]149[/C][C]0.850307[/C][C]0.299385[/C][C]0.149693[/C][/ROW]
[ROW][C]150[/C][C]0.833063[/C][C]0.333874[/C][C]0.166937[/C][/ROW]
[ROW][C]151[/C][C]0.910972[/C][C]0.178055[/C][C]0.0890276[/C][/ROW]
[ROW][C]152[/C][C]0.896541[/C][C]0.206919[/C][C]0.103459[/C][/ROW]
[ROW][C]153[/C][C]0.883476[/C][C]0.233048[/C][C]0.116524[/C][/ROW]
[ROW][C]154[/C][C]0.876084[/C][C]0.247831[/C][C]0.123916[/C][/ROW]
[ROW][C]155[/C][C]0.869901[/C][C]0.260198[/C][C]0.130099[/C][/ROW]
[ROW][C]156[/C][C]0.858312[/C][C]0.283377[/C][C]0.141688[/C][/ROW]
[ROW][C]157[/C][C]0.852529[/C][C]0.294941[/C][C]0.147471[/C][/ROW]
[ROW][C]158[/C][C]0.844034[/C][C]0.311933[/C][C]0.155966[/C][/ROW]
[ROW][C]159[/C][C]0.824227[/C][C]0.351545[/C][C]0.175773[/C][/ROW]
[ROW][C]160[/C][C]0.813179[/C][C]0.373643[/C][C]0.186821[/C][/ROW]
[ROW][C]161[/C][C]0.83437[/C][C]0.33126[/C][C]0.16563[/C][/ROW]
[ROW][C]162[/C][C]0.823523[/C][C]0.352954[/C][C]0.176477[/C][/ROW]
[ROW][C]163[/C][C]0.808461[/C][C]0.383078[/C][C]0.191539[/C][/ROW]
[ROW][C]164[/C][C]0.815221[/C][C]0.369557[/C][C]0.184779[/C][/ROW]
[ROW][C]165[/C][C]0.81202[/C][C]0.375959[/C][C]0.18798[/C][/ROW]
[ROW][C]166[/C][C]0.788149[/C][C]0.423701[/C][C]0.211851[/C][/ROW]
[ROW][C]167[/C][C]0.795261[/C][C]0.409478[/C][C]0.204739[/C][/ROW]
[ROW][C]168[/C][C]0.772576[/C][C]0.454847[/C][C]0.227424[/C][/ROW]
[ROW][C]169[/C][C]0.750025[/C][C]0.499949[/C][C]0.249975[/C][/ROW]
[ROW][C]170[/C][C]0.747282[/C][C]0.505435[/C][C]0.252718[/C][/ROW]
[ROW][C]171[/C][C]0.734515[/C][C]0.53097[/C][C]0.265485[/C][/ROW]
[ROW][C]172[/C][C]0.759368[/C][C]0.481265[/C][C]0.240632[/C][/ROW]
[ROW][C]173[/C][C]0.733857[/C][C]0.532286[/C][C]0.266143[/C][/ROW]
[ROW][C]174[/C][C]0.703623[/C][C]0.592754[/C][C]0.296377[/C][/ROW]
[ROW][C]175[/C][C]0.671832[/C][C]0.656336[/C][C]0.328168[/C][/ROW]
[ROW][C]176[/C][C]0.728003[/C][C]0.543994[/C][C]0.271997[/C][/ROW]
[ROW][C]177[/C][C]0.701533[/C][C]0.596934[/C][C]0.298467[/C][/ROW]
[ROW][C]178[/C][C]0.749505[/C][C]0.50099[/C][C]0.250495[/C][/ROW]
[ROW][C]179[/C][C]0.729558[/C][C]0.540883[/C][C]0.270442[/C][/ROW]
[ROW][C]180[/C][C]0.804458[/C][C]0.391084[/C][C]0.195542[/C][/ROW]
[ROW][C]181[/C][C]0.792132[/C][C]0.415736[/C][C]0.207868[/C][/ROW]
[ROW][C]182[/C][C]0.764334[/C][C]0.471331[/C][C]0.235666[/C][/ROW]
[ROW][C]183[/C][C]0.757398[/C][C]0.485204[/C][C]0.242602[/C][/ROW]
[ROW][C]184[/C][C]0.728922[/C][C]0.542155[/C][C]0.271078[/C][/ROW]
[ROW][C]185[/C][C]0.744575[/C][C]0.51085[/C][C]0.255425[/C][/ROW]
[ROW][C]186[/C][C]0.713356[/C][C]0.573287[/C][C]0.286644[/C][/ROW]
[ROW][C]187[/C][C]0.715334[/C][C]0.569333[/C][C]0.284666[/C][/ROW]
[ROW][C]188[/C][C]0.722649[/C][C]0.554701[/C][C]0.277351[/C][/ROW]
[ROW][C]189[/C][C]0.727425[/C][C]0.545149[/C][C]0.272575[/C][/ROW]
[ROW][C]190[/C][C]0.704423[/C][C]0.591155[/C][C]0.295577[/C][/ROW]
[ROW][C]191[/C][C]0.673345[/C][C]0.653311[/C][C]0.326655[/C][/ROW]
[ROW][C]192[/C][C]0.674105[/C][C]0.65179[/C][C]0.325895[/C][/ROW]
[ROW][C]193[/C][C]0.75353[/C][C]0.49294[/C][C]0.24647[/C][/ROW]
[ROW][C]194[/C][C]0.770344[/C][C]0.459313[/C][C]0.229656[/C][/ROW]
[ROW][C]195[/C][C]0.746187[/C][C]0.507626[/C][C]0.253813[/C][/ROW]
[ROW][C]196[/C][C]0.715688[/C][C]0.568624[/C][C]0.284312[/C][/ROW]
[ROW][C]197[/C][C]0.701507[/C][C]0.596987[/C][C]0.298493[/C][/ROW]
[ROW][C]198[/C][C]0.671781[/C][C]0.656438[/C][C]0.328219[/C][/ROW]
[ROW][C]199[/C][C]0.662196[/C][C]0.675607[/C][C]0.337804[/C][/ROW]
[ROW][C]200[/C][C]0.632886[/C][C]0.734228[/C][C]0.367114[/C][/ROW]
[ROW][C]201[/C][C]0.663334[/C][C]0.673331[/C][C]0.336666[/C][/ROW]
[ROW][C]202[/C][C]0.629855[/C][C]0.740291[/C][C]0.370145[/C][/ROW]
[ROW][C]203[/C][C]0.597086[/C][C]0.805829[/C][C]0.402914[/C][/ROW]
[ROW][C]204[/C][C]0.557942[/C][C]0.884115[/C][C]0.442058[/C][/ROW]
[ROW][C]205[/C][C]0.571885[/C][C]0.856231[/C][C]0.428115[/C][/ROW]
[ROW][C]206[/C][C]0.539136[/C][C]0.921728[/C][C]0.460864[/C][/ROW]
[ROW][C]207[/C][C]0.511234[/C][C]0.977533[/C][C]0.488766[/C][/ROW]
[ROW][C]208[/C][C]0.47777[/C][C]0.95554[/C][C]0.52223[/C][/ROW]
[ROW][C]209[/C][C]0.480607[/C][C]0.961213[/C][C]0.519393[/C][/ROW]
[ROW][C]210[/C][C]0.449227[/C][C]0.898453[/C][C]0.550773[/C][/ROW]
[ROW][C]211[/C][C]0.409979[/C][C]0.819957[/C][C]0.590021[/C][/ROW]
[ROW][C]212[/C][C]0.393794[/C][C]0.787588[/C][C]0.606206[/C][/ROW]
[ROW][C]213[/C][C]0.372911[/C][C]0.745823[/C][C]0.627089[/C][/ROW]
[ROW][C]214[/C][C]0.335067[/C][C]0.670134[/C][C]0.664933[/C][/ROW]
[ROW][C]215[/C][C]0.296419[/C][C]0.592838[/C][C]0.703581[/C][/ROW]
[ROW][C]216[/C][C]0.262648[/C][C]0.525296[/C][C]0.737352[/C][/ROW]
[ROW][C]217[/C][C]0.258785[/C][C]0.51757[/C][C]0.741215[/C][/ROW]
[ROW][C]218[/C][C]0.299436[/C][C]0.598873[/C][C]0.700564[/C][/ROW]
[ROW][C]219[/C][C]0.264506[/C][C]0.529013[/C][C]0.735494[/C][/ROW]
[ROW][C]220[/C][C]0.228525[/C][C]0.45705[/C][C]0.771475[/C][/ROW]
[ROW][C]221[/C][C]0.228414[/C][C]0.456828[/C][C]0.771586[/C][/ROW]
[ROW][C]222[/C][C]0.246581[/C][C]0.493163[/C][C]0.753419[/C][/ROW]
[ROW][C]223[/C][C]0.217058[/C][C]0.434115[/C][C]0.782942[/C][/ROW]
[ROW][C]224[/C][C]0.185412[/C][C]0.370824[/C][C]0.814588[/C][/ROW]
[ROW][C]225[/C][C]0.165767[/C][C]0.331535[/C][C]0.834233[/C][/ROW]
[ROW][C]226[/C][C]0.140903[/C][C]0.281805[/C][C]0.859097[/C][/ROW]
[ROW][C]227[/C][C]0.115978[/C][C]0.231956[/C][C]0.884022[/C][/ROW]
[ROW][C]228[/C][C]0.120026[/C][C]0.240053[/C][C]0.879974[/C][/ROW]
[ROW][C]229[/C][C]0.206356[/C][C]0.412711[/C][C]0.793644[/C][/ROW]
[ROW][C]230[/C][C]0.19443[/C][C]0.388861[/C][C]0.80557[/C][/ROW]
[ROW][C]231[/C][C]0.205398[/C][C]0.410796[/C][C]0.794602[/C][/ROW]
[ROW][C]232[/C][C]0.24301[/C][C]0.48602[/C][C]0.75699[/C][/ROW]
[ROW][C]233[/C][C]0.215425[/C][C]0.430849[/C][C]0.784575[/C][/ROW]
[ROW][C]234[/C][C]0.191973[/C][C]0.383945[/C][C]0.808027[/C][/ROW]
[ROW][C]235[/C][C]0.164728[/C][C]0.329456[/C][C]0.835272[/C][/ROW]
[ROW][C]236[/C][C]0.574062[/C][C]0.851876[/C][C]0.425938[/C][/ROW]
[ROW][C]237[/C][C]0.520573[/C][C]0.958853[/C][C]0.479427[/C][/ROW]
[ROW][C]238[/C][C]0.471609[/C][C]0.943218[/C][C]0.528391[/C][/ROW]
[ROW][C]239[/C][C]0.430295[/C][C]0.86059[/C][C]0.569705[/C][/ROW]
[ROW][C]240[/C][C]0.37518[/C][C]0.750361[/C][C]0.62482[/C][/ROW]
[ROW][C]241[/C][C]0.346425[/C][C]0.69285[/C][C]0.653575[/C][/ROW]
[ROW][C]242[/C][C]0.298136[/C][C]0.596273[/C][C]0.701864[/C][/ROW]
[ROW][C]243[/C][C]0.256492[/C][C]0.512984[/C][C]0.743508[/C][/ROW]
[ROW][C]244[/C][C]0.225459[/C][C]0.450919[/C][C]0.774541[/C][/ROW]
[ROW][C]245[/C][C]0.184637[/C][C]0.369273[/C][C]0.815363[/C][/ROW]
[ROW][C]246[/C][C]0.203487[/C][C]0.406975[/C][C]0.796513[/C][/ROW]
[ROW][C]247[/C][C]0.187115[/C][C]0.37423[/C][C]0.812885[/C][/ROW]
[ROW][C]248[/C][C]0.158039[/C][C]0.316079[/C][C]0.841961[/C][/ROW]
[ROW][C]249[/C][C]0.13606[/C][C]0.272119[/C][C]0.86394[/C][/ROW]
[ROW][C]250[/C][C]0.103572[/C][C]0.207145[/C][C]0.896428[/C][/ROW]
[ROW][C]251[/C][C]0.106356[/C][C]0.212712[/C][C]0.893644[/C][/ROW]
[ROW][C]252[/C][C]0.0972648[/C][C]0.19453[/C][C]0.902735[/C][/ROW]
[ROW][C]253[/C][C]0.0826803[/C][C]0.165361[/C][C]0.91732[/C][/ROW]
[ROW][C]254[/C][C]0.189518[/C][C]0.379035[/C][C]0.810482[/C][/ROW]
[ROW][C]255[/C][C]0.462326[/C][C]0.924653[/C][C]0.537674[/C][/ROW]
[ROW][C]256[/C][C]0.377181[/C][C]0.754362[/C][C]0.622819[/C][/ROW]
[ROW][C]257[/C][C]0.545764[/C][C]0.908472[/C][C]0.454236[/C][/ROW]
[ROW][C]258[/C][C]0.780885[/C][C]0.438229[/C][C]0.219115[/C][/ROW]
[ROW][C]259[/C][C]0.680361[/C][C]0.639278[/C][C]0.319639[/C][/ROW]
[ROW][C]260[/C][C]0.812702[/C][C]0.374597[/C][C]0.187298[/C][/ROW]
[ROW][C]261[/C][C]0.731898[/C][C]0.536204[/C][C]0.268102[/C][/ROW]
[ROW][C]262[/C][C]0.58068[/C][C]0.83864[/C][C]0.41932[/C][/ROW]
[ROW][C]263[/C][C]0.561757[/C][C]0.876485[/C][C]0.438243[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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
16	0.485855	0.971709	0.514145
17	0.602355	0.795291	0.397645
18	0.46058	0.92116	0.53942
19	0.360405	0.72081	0.639595
20	0.260225	0.520449	0.739775
21	0.207721	0.415442	0.792279
22	0.141841	0.283681	0.858159
23	0.216409	0.432818	0.783591
24	0.243296	0.486591	0.756704
25	0.202224	0.404447	0.797776
26	0.176083	0.352165	0.823917
27	0.16871	0.337421	0.83129
28	0.141967	0.283935	0.858033
29	0.112519	0.225038	0.887481
30	0.0815408	0.163082	0.918459
31	0.0826898	0.16538	0.91731
32	0.0665697	0.133139	0.93343
33	0.0654297	0.130859	0.93457
34	0.0837059	0.167412	0.916294
35	0.0609777	0.121955	0.939022
36	0.0447951	0.0895902	0.955205
37	0.0312646	0.0625292	0.968735
38	0.0297562	0.0595125	0.970244
39	0.0399944	0.0799888	0.960006
40	0.0413195	0.0826389	0.958681
41	0.0683566	0.136713	0.931643
42	0.052923	0.105846	0.947077
43	0.0532326	0.106465	0.946767
44	0.0412337	0.0824673	0.958766
45	0.0484549	0.0969098	0.951545
46	0.0488322	0.0976643	0.951168
47	0.0496509	0.0993019	0.950349
48	0.0553623	0.110725	0.944638
49	0.102928	0.205856	0.897072
50	0.104579	0.209158	0.895421
51	0.0827858	0.165572	0.917214
52	0.106898	0.213795	0.893102
53	0.0918447	0.183689	0.908155
54	0.0961705	0.192341	0.90383
55	0.234419	0.468838	0.765581
56	0.200712	0.401423	0.799288
57	0.514843	0.970314	0.485157
58	0.593831	0.812337	0.406169
59	0.576122	0.847757	0.423878
60	0.611005	0.77799	0.388995
61	0.583869	0.832263	0.416131
62	0.547287	0.905425	0.452713
63	0.655064	0.689873	0.344936
64	0.728873	0.542255	0.271127
65	0.731301	0.537398	0.268699
66	0.708025	0.58395	0.291975
67	0.670226	0.659547	0.329774
68	0.660423	0.679154	0.339577
69	0.690319	0.619362	0.309681
70	0.66631	0.667379	0.33369
71	0.632132	0.735737	0.367868
72	0.596224	0.807552	0.403776
73	0.572372	0.855256	0.427628
74	0.635124	0.729751	0.364876
75	0.608841	0.782318	0.391159
76	0.592786	0.814429	0.407214
77	0.561013	0.877974	0.438987
78	0.582273	0.835454	0.417727
79	0.54721	0.90558	0.45279
80	0.545929	0.908141	0.454071
81	0.510742	0.978516	0.489258
82	0.54397	0.91206	0.45603
83	0.505034	0.989932	0.494966
84	0.596327	0.807347	0.403673
85	0.567545	0.864909	0.432455
86	0.537925	0.924149	0.462075
87	0.502817	0.994366	0.497183
88	0.471169	0.942339	0.528831
89	0.483856	0.967711	0.516144
90	0.566402	0.867195	0.433598
91	0.592665	0.814669	0.407335
92	0.692334	0.615332	0.307666
93	0.678388	0.643223	0.321612
94	0.653691	0.692617	0.346309
95	0.664099	0.671802	0.335901
96	0.639501	0.720999	0.360499
97	0.631635	0.736729	0.368365
98	0.603835	0.79233	0.396165
99	0.647176	0.705647	0.352824
100	0.684061	0.631879	0.315939
101	0.654274	0.691452	0.345726
102	0.620643	0.758714	0.379357
103	0.616266	0.767468	0.383734
104	0.58985	0.820301	0.41015
105	0.661407	0.677185	0.338593
106	0.651719	0.696562	0.348281
107	0.731674	0.536652	0.268326
108	0.813006	0.373988	0.186994
109	0.870753	0.258494	0.129247
110	0.85449	0.29102	0.14551
111	0.833878	0.332245	0.166122
112	0.822033	0.355934	0.177967
113	0.885963	0.228073	0.114037
114	0.91295	0.174101	0.0870503
115	0.954462	0.0910767	0.0455384
116	0.968491	0.0630187	0.0315093
117	0.972863	0.0542736	0.0271368
118	0.972426	0.0551488	0.0275744
119	0.968083	0.0638331	0.0319166
120	0.973255	0.0534905	0.0267453
121	0.967306	0.0653871	0.0326935
122	0.967251	0.0654984	0.0327492
123	0.964511	0.0709772	0.0354886
124	0.969672	0.0606568	0.0303284
125	0.976022	0.0479553	0.0239777
126	0.970555	0.0588894	0.0294447
127	0.967194	0.0656115	0.0328058
128	0.960695	0.0786109	0.0393054
129	0.968734	0.0625319	0.0312659
130	0.962289	0.0754229	0.0377115
131	0.955562	0.0888762	0.0444381
132	0.948786	0.102429	0.0512143
133	0.940552	0.118896	0.0594478
134	0.933196	0.133608	0.0668041
135	0.921019	0.157963	0.0789815
136	0.914822	0.170356	0.0851778
137	0.921317	0.157367	0.0786835
138	0.958158	0.0836837	0.0418418
139	0.952583	0.0948346	0.0474173
140	0.943638	0.112725	0.0563624
141	0.935419	0.129161	0.0645807
142	0.930382	0.139237	0.0696184
143	0.917847	0.164306	0.0821532
144	0.915533	0.168934	0.0844672
145	0.907071	0.185858	0.092929
146	0.892634	0.214733	0.107366
147	0.882223	0.235553	0.117777
148	0.863539	0.272923	0.136461
149	0.850307	0.299385	0.149693
150	0.833063	0.333874	0.166937
151	0.910972	0.178055	0.0890276
152	0.896541	0.206919	0.103459
153	0.883476	0.233048	0.116524
154	0.876084	0.247831	0.123916
155	0.869901	0.260198	0.130099
156	0.858312	0.283377	0.141688
157	0.852529	0.294941	0.147471
158	0.844034	0.311933	0.155966
159	0.824227	0.351545	0.175773
160	0.813179	0.373643	0.186821
161	0.83437	0.33126	0.16563
162	0.823523	0.352954	0.176477
163	0.808461	0.383078	0.191539
164	0.815221	0.369557	0.184779
165	0.81202	0.375959	0.18798
166	0.788149	0.423701	0.211851
167	0.795261	0.409478	0.204739
168	0.772576	0.454847	0.227424
169	0.750025	0.499949	0.249975
170	0.747282	0.505435	0.252718
171	0.734515	0.53097	0.265485
172	0.759368	0.481265	0.240632
173	0.733857	0.532286	0.266143
174	0.703623	0.592754	0.296377
175	0.671832	0.656336	0.328168
176	0.728003	0.543994	0.271997
177	0.701533	0.596934	0.298467
178	0.749505	0.50099	0.250495
179	0.729558	0.540883	0.270442
180	0.804458	0.391084	0.195542
181	0.792132	0.415736	0.207868
182	0.764334	0.471331	0.235666
183	0.757398	0.485204	0.242602
184	0.728922	0.542155	0.271078
185	0.744575	0.51085	0.255425
186	0.713356	0.573287	0.286644
187	0.715334	0.569333	0.284666
188	0.722649	0.554701	0.277351
189	0.727425	0.545149	0.272575
190	0.704423	0.591155	0.295577
191	0.673345	0.653311	0.326655
192	0.674105	0.65179	0.325895
193	0.75353	0.49294	0.24647
194	0.770344	0.459313	0.229656
195	0.746187	0.507626	0.253813
196	0.715688	0.568624	0.284312
197	0.701507	0.596987	0.298493
198	0.671781	0.656438	0.328219
199	0.662196	0.675607	0.337804
200	0.632886	0.734228	0.367114
201	0.663334	0.673331	0.336666
202	0.629855	0.740291	0.370145
203	0.597086	0.805829	0.402914
204	0.557942	0.884115	0.442058
205	0.571885	0.856231	0.428115
206	0.539136	0.921728	0.460864
207	0.511234	0.977533	0.488766
208	0.47777	0.95554	0.52223
209	0.480607	0.961213	0.519393
210	0.449227	0.898453	0.550773
211	0.409979	0.819957	0.590021
212	0.393794	0.787588	0.606206
213	0.372911	0.745823	0.627089
214	0.335067	0.670134	0.664933
215	0.296419	0.592838	0.703581
216	0.262648	0.525296	0.737352
217	0.258785	0.51757	0.741215
218	0.299436	0.598873	0.700564
219	0.264506	0.529013	0.735494
220	0.228525	0.45705	0.771475
221	0.228414	0.456828	0.771586
222	0.246581	0.493163	0.753419
223	0.217058	0.434115	0.782942
224	0.185412	0.370824	0.814588
225	0.165767	0.331535	0.834233
226	0.140903	0.281805	0.859097
227	0.115978	0.231956	0.884022
228	0.120026	0.240053	0.879974
229	0.206356	0.412711	0.793644
230	0.19443	0.388861	0.80557
231	0.205398	0.410796	0.794602
232	0.24301	0.48602	0.75699
233	0.215425	0.430849	0.784575
234	0.191973	0.383945	0.808027
235	0.164728	0.329456	0.835272
236	0.574062	0.851876	0.425938
237	0.520573	0.958853	0.479427
238	0.471609	0.943218	0.528391
239	0.430295	0.86059	0.569705
240	0.37518	0.750361	0.62482
241	0.346425	0.69285	0.653575
242	0.298136	0.596273	0.701864
243	0.256492	0.512984	0.743508
244	0.225459	0.450919	0.774541
245	0.184637	0.369273	0.815363
246	0.203487	0.406975	0.796513
247	0.187115	0.37423	0.812885
248	0.158039	0.316079	0.841961
249	0.13606	0.272119	0.86394
250	0.103572	0.207145	0.896428
251	0.106356	0.212712	0.893644
252	0.0972648	0.19453	0.902735
253	0.0826803	0.165361	0.91732
254	0.189518	0.379035	0.810482
255	0.462326	0.924653	0.537674
256	0.377181	0.754362	0.622819
257	0.545764	0.908472	0.454236
258	0.780885	0.438229	0.219115
259	0.680361	0.639278	0.319639
260	0.812702	0.374597	0.187298
261	0.731898	0.536204	0.268102
262	0.58068	0.83864	0.41932
263	0.561757	0.876485	0.438243

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	1	0.00403226	OK
10% type I error level	28	0.112903	NOK

\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 & 1 & 0.00403226 & OK \tabularnewline
10% type I error level & 28 & 0.112903 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268697&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]1[/C][C]0.00403226[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.112903[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268697&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268697&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	1	0.00403226	OK
10% type I error level	28	0.112903	NOK

Figure 1

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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