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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 12:56:27 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t14186493203k2804y3h8tbe30.htm/, Retrieved Fri, 17 May 2024 00:09:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268313, Retrieved Fri, 17 May 2024 00:09:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact47

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-15 12:56:27] [08b6b59c0a3564dc58beca6de73ddb7e] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
12.9 0 1 0 26 50 4 21 149 68 0 149 0
12.2 0 1 1 57 62 4 22 139 39 139 139 0
12.8 0 1 0 37 54 5 22 148 32 0 148 0
7.4 0 1 1 67 71 4 18 158 62 158 158 0
6.7 0 1 1 43 54 4 23 128 33 128 128 0
12.6 0 1 1 52 65 9 12 224 52 224 224 0
14.8 0 1 0 52 73 8 20 159 62 0 159 0
13.3 0 1 1 43 52 11 22 105 77 105 105 0
11.1 0 1 1 84 84 4 21 159 76 159 159 0
8.2 0 1 1 67 42 4 19 167 41 167 167 0
11.4 0 1 1 49 66 6 22 165 48 165 165 0
6.4 0 1 1 70 65 4 15 159 63 159 159 0
10.6 0 1 1 52 78 8 20 119 30 119 119 0
12 0 1 0 58 73 4 19 176 78 0 176 0
6.3 0 1 0 68 75 4 18 54 19 0 54 0
11.3 0 0 0 62 72 11 15 91 31 0 0 0
11.9 0 1 1 43 66 4 20 163 66 163 163 0
9.3 0 1 0 56 70 4 21 124 35 0 124 0
9.6 0 0 1 56 61 6 21 137 42 137 0 0
10 0 1 0 74 81 6 15 121 45 0 121 0
6.4 0 1 1 65 71 4 16 153 21 153 153 0
13.8 0 1 1 63 69 8 23 148 25 148 148 0
10.8 0 1 0 58 71 5 21 221 44 0 221 0
13.8 0 1 1 57 72 4 18 188 69 188 188 0
11.7 0 1 1 63 68 9 25 149 54 149 149 0
10.9 0 1 1 53 70 4 9 244 74 244 244 0
16.1 0 0 1 57 68 7 30 148 80 148 0 0
13.4 0 0 0 51 61 10 20 92 42 0 0 0
9.9 0 1 1 64 67 4 23 150 61 150 150 0
11.5 0 1 0 53 76 4 16 153 41 0 153 0
8.3 0 1 0 29 70 7 16 94 46 0 94 0
11.7 0 1 0 54 60 12 19 156 39 0 156 0
9 0 1 1 58 72 7 25 132 34 132 132 0
9.7 0 1 1 43 69 5 18 161 51 161 161 0
10.8 0 1 1 51 71 8 23 105 42 105 105 0
10.3 0 1 1 53 62 5 21 97 31 97 97 0
10.4 0 1 0 54 70 4 10 151 39 0 151 0
12.7 0 0 1 56 64 9 14 131 20 131 0 0
9.3 0 1 1 61 58 7 22 166 49 166 166 0
11.8 0 1 0 47 76 4 26 157 53 0 157 0
5.9 0 1 1 39 52 4 23 111 31 111 111 0
11.4 0 1 1 48 59 4 23 145 39 145 145 0
13 0 1 1 50 68 4 24 162 54 162 162 0
10.8 0 1 1 35 76 4 24 163 49 163 163 0
12.3 0 0 1 30 65 7 18 59 34 59 0 0
11.3 0 1 0 68 67 4 23 187 46 0 187 0
11.8 0 1 1 49 59 7 15 109 55 109 109 0
7.9 0 0 1 61 69 4 19 90 42 90 0 0
12.7 0 1 0 67 76 4 16 105 50 0 105 0
12.3 0 0 1 47 63 4 25 83 13 83 0 0
11.6 0 0 1 56 75 4 23 116 37 116 0 0
6.7 0 0 1 50 63 8 17 42 25 42 0 0
10.9 0 1 1 43 60 4 19 148 30 148 148 0
12.1 0 0 1 67 73 4 21 155 28 155 0 0
13.3 0 1 1 62 63 4 18 125 45 125 125 0
10.1 0 1 1 57 70 4 27 116 35 116 116 0
5.7 0 0 0 41 75 7 21 128 28 0 0 0
14.3 0 1 1 54 66 12 13 138 41 138 138 0
8 0 0 0 45 63 4 8 49 6 0 0 0
13.3 0 0 1 48 63 4 29 96 45 96 0 0
9.3 0 1 1 61 64 4 28 164 73 164 164 0
12.5 0 1 0 56 70 5 23 162 17 0 162 0
7.6 0 1 0 41 75 15 21 99 40 0 99 0
15.9 0 1 1 43 61 5 19 202 64 202 202 0
9.2 0 1 0 53 60 10 19 186 37 0 186 0
9.1 0 0 1 44 62 9 20 66 25 66 0 0
11.1 0 1 0 66 73 8 18 183 65 0 183 0
13 0 1 1 58 61 4 19 214 100 214 214 0
14.5 0 1 1 46 66 5 17 188 28 188 188 0
12.2 0 0 0 37 64 4 19 104 35 0 0 0
12.3 0 1 0 51 59 9 25 177 56 0 177 0
11.4 0 1 0 51 64 4 19 126 29 0 126 0
8.8 0 0 0 56 60 10 22 76 43 0 0 0
14.6 0 0 1 66 56 4 23 99 59 99 0 0
12.6 0 1 0 37 78 4 14 139 50 0 139 0
NA 0 1 1 59 53 6 28 78 3 78 78 0
13 0 1 0 42 67 7 16 162 59 0 162 0
12.6 0 0 1 38 59 5 24 108 27 108 0 0
13.2 0 1 0 66 66 4 20 159 61 0 159 0
9.9 0 0 0 34 68 4 12 74 28 0 0 0
7.7 0 1 1 53 71 4 24 110 51 110 110 0
10.5 0 0 0 49 66 4 22 96 35 0 0 0
13.4 0 0 0 55 73 4 12 116 29 0 0 0
10.9 0 0 0 49 72 4 22 87 48 0 0 0
4.3 0 0 1 59 71 6 20 97 25 97 0 0
10.3 0 0 0 40 59 10 10 127 44 0 0 0
11.8 0 0 1 58 64 7 23 106 64 106 0 0
11.2 0 0 1 60 66 4 17 80 32 80 0 0
11.4 0 0 0 63 78 4 22 74 20 0 0 0
8.6 0 0 0 56 68 7 24 91 28 0 0 0
13.2 0 0 0 54 73 4 18 133 34 0 0 0
12.6 0 0 1 52 62 8 21 74 31 74 0 0
5.6 0 0 1 34 65 11 20 114 26 114 0 0
9.9 0 0 1 69 68 6 20 140 58 140 0 0
8.8 0 0 0 32 65 14 22 95 23 0 0 0
7.7 0 0 1 48 60 5 19 98 21 98 0 0
9 0 0 0 67 71 4 20 121 21 0 0 0
7.3 0 0 1 58 65 8 26 126 33 126 0 0
11.4 0 0 1 57 68 9 23 98 16 98 0 0
13.6 0 0 1 42 64 4 24 95 20 95 0 0
7.9 0 0 1 64 74 4 21 110 37 110 0 0
10.7 0 0 1 58 69 5 21 70 35 70 0 0
10.3 0 0 0 66 76 4 19 102 33 0 0 0
8.3 0 0 1 26 68 5 8 86 27 86 0 0
9.6 0 0 1 61 72 4 17 130 41 130 0 0
14.2 0 0 1 52 67 4 20 96 40 96 0 0
8.5 0 0 0 51 63 7 11 102 35 0 0 0
13.5 0 0 0 55 59 10 8 100 28 0 0 0
4.9 0 0 0 50 73 4 15 94 32 0 0 0
6.4 0 0 0 60 66 5 18 52 22 0 0 0
9.6 0 0 0 56 62 4 18 98 44 0 0 0
11.6 0 0 0 63 69 4 19 118 27 0 0 0
11.1 0 0 1 61 66 4 19 99 17 99 0 0
4.35 1 1 1 52 51 6 23 48 12 48 48 48
12.7 1 1 1 16 56 4 22 50 45 50 50 50
18.1 1 1 1 46 67 8 21 150 37 150 150 150
17.85 1 1 1 56 69 5 25 154 37 154 154 154
16.6 1 0 0 52 57 4 30 109 108 0 0 109
12.6 1 0 1 55 56 17 17 68 10 68 0 68
17.1 1 1 1 50 55 4 27 194 68 194 194 194
19.1 1 1 0 59 63 4 23 158 72 0 158 158
16.1 1 1 1 60 67 8 23 159 143 159 159 159
13.35 1 1 0 52 65 4 18 67 9 0 67 67
18.4 1 1 0 44 47 7 18 147 55 0 147 147
14.7 1 1 1 67 76 4 23 39 17 39 39 39
10.6 1 1 1 52 64 4 19 100 37 100 100 100
12.6 1 1 1 55 68 5 15 111 27 111 111 111
16.2 1 1 1 37 64 7 20 138 37 138 138 138
13.6 1 1 1 54 65 4 16 101 58 101 101 101
18.9 1 0 1 72 71 4 24 131 66 131 0 131
14.1 1 1 1 51 63 7 25 101 21 101 101 101
14.5 1 1 1 48 60 11 25 114 19 114 114 114
16.15 1 1 0 60 68 7 19 165 78 0 165 165
14.75 1 1 1 50 72 4 19 114 35 114 114 114
14.8 1 1 1 63 70 4 16 111 48 111 111 111
12.45 1 1 1 33 61 4 19 75 27 75 75 75
12.65 1 1 1 67 61 4 19 82 43 82 82 82
17.35 1 1 1 46 62 4 23 121 30 121 121 121
8.6 1 1 1 54 71 4 21 32 25 32 32 32
18.4 1 1 0 59 71 6 22 150 69 0 150 150
16.1 1 1 1 61 51 8 19 117 72 117 117 117
11.6 1 0 1 33 56 23 20 71 23 71 0 71
17.75 1 1 1 47 70 4 20 165 13 165 165 165
15.25 1 1 1 69 73 8 3 154 61 154 154 154
17.65 1 1 1 52 76 6 23 126 43 126 126 126
16.35 1 1 0 55 68 4 23 149 51 0 149 149
17.65 1 1 0 41 48 7 20 145 67 0 145 145
13.6 1 1 1 73 52 4 15 120 36 120 120 120
14.35 1 1 0 52 60 4 16 109 44 0 109 109
14.75 1 1 0 50 59 4 7 132 45 0 132 132
18.25 1 1 1 51 57 10 24 172 34 172 172 172
9.9 1 1 0 60 79 6 17 169 36 0 169 169
16 1 1 1 56 60 5 24 114 72 114 114 114
18.25 1 1 1 56 60 5 24 156 39 156 156 156
16.85 1 1 0 29 59 4 19 172 43 0 172 172
14.6 1 0 1 66 62 4 25 68 25 68 0 68
13.85 1 0 1 66 59 5 20 89 56 89 0 89
18.95 1 1 1 73 61 5 28 167 80 167 167 167
15.6 1 1 0 55 71 5 23 113 40 0 113 113
14.85 1 0 0 64 57 5 27 115 73 0 0 115
11.75 1 0 0 40 66 4 18 78 34 0 0 78
18.45 1 0 0 46 63 6 28 118 72 0 0 118
15.9 1 0 1 58 69 4 21 87 42 87 0 87
17.1 1 1 0 43 58 4 19 173 61 0 173 173
16.1 1 1 1 61 59 4 23 2 23 2 2 2
19.9 1 0 0 51 48 9 27 162 74 0 0 162
10.95 1 0 1 50 66 18 22 49 16 49 0 49
18.45 1 0 0 52 73 6 28 122 66 0 0 122
15.1 1 0 1 54 67 5 25 96 9 96 0 96
15 1 0 0 66 61 4 21 100 41 0 0 100
11.35 1 0 0 61 68 11 22 82 57 0 0 82
15.95 1 0 1 80 75 4 28 100 48 100 0 100
18.1 1 0 0 51 62 10 20 115 51 0 0 115
14.6 1 0 1 56 69 6 29 141 53 141 0 141
15.4 1 1 1 56 58 8 25 165 29 165 165 165
15.4 1 1 1 56 60 8 25 165 29 165 165 165
17.6 1 0 1 53 74 6 20 110 55 110 0 110
13.35 1 1 1 47 55 8 20 118 54 118 118 118
19.1 1 1 0 25 62 4 16 158 43 0 158 158
15.35 1 0 1 47 63 4 20 146 51 146 0 146
7.6 1 1 0 46 69 9 20 49 20 0 49 49
13.4 1 0 0 50 58 9 23 90 79 0 0 90
13.9 1 0 0 39 58 5 18 121 39 0 0 121
19.1 1 1 1 51 68 4 25 155 61 155 155 155
15.25 1 0 0 58 72 4 18 104 55 0 0 104
12.9 1 0 1 35 62 15 19 147 30 147 0 147
16.1 1 0 0 58 62 10 25 110 55 0 0 110
17.35 1 0 0 60 65 9 25 108 22 0 0 108
13.15 1 0 0 62 69 7 25 113 37 0 0 113
12.15 1 0 0 63 66 9 24 115 2 0 0 115
12.6 1 0 1 53 72 6 19 61 38 61 0 61
10.35 1 0 1 46 62 4 26 60 27 60 0 60
15.4 1 0 1 67 75 7 10 109 56 109 0 109
9.6 1 0 1 59 58 4 17 68 25 68 0 68
18.2 1 0 0 64 66 7 13 111 39 0 0 111
13.6 1 0 0 38 55 4 17 77 33 0 0 77
14.85 1 0 1 50 47 15 30 73 43 73 0 73
14.75 1 1 0 48 72 4 25 151 57 0 151 151
14.1 1 0 0 48 62 9 4 89 43 0 0 89
14.9 1 0 0 47 64 4 16 78 23 0 0 78
16.25 1 0 0 66 64 4 21 110 44 0 0 110
19.25 1 1 1 47 19 28 23 220 54 220 220 220
13.6 1 0 1 63 50 4 22 65 28 65 0 65
13.6 1 1 0 58 68 4 17 141 36 0 141 141
15.65 1 0 0 44 70 4 20 117 39 0 0 117
12.75 1 1 1 51 79 5 20 122 16 122 122 122
14.6 1 0 0 43 69 4 22 63 23 0 0 63
9.85 1 1 1 55 71 4 16 44 40 44 44 44
12.65 1 0 1 38 48 12 23 52 24 52 0 52
19.2 1 0 0 45 73 4 0 131 78 0 0 131
16.6 1 0 1 50 74 6 18 101 57 101 0 101
11.2 1 0 1 54 66 6 25 42 37 42 0 42
15.25 1 1 1 57 71 5 23 152 27 152 152 152
11.9 1 1 0 60 74 4 12 107 61 0 107 107
13.2 1 0 0 55 78 4 18 77 27 0 0 77
16.35 1 1 0 56 75 4 24 154 69 0 154 154
12.4 1 1 1 49 53 10 11 103 34 103 103 103
15.85 1 0 1 37 60 7 18 96 44 96 0 96
18.15 1 1 1 59 70 4 23 175 34 175 175 175
11.15 1 0 1 46 69 7 24 57 39 57 0 57
15.65 1 0 0 51 65 4 29 112 51 0 0 112
17.75 1 1 0 58 78 4 18 143 34 0 143 143
7.65 1 0 0 64 78 12 15 49 31 0 0 49
12.35 1 1 1 53 59 5 29 110 13 110 110 110
15.6 1 1 1 48 72 8 16 131 12 131 131 131
19.3 1 1 0 51 70 6 19 167 51 0 167 167
15.2 1 0 0 47 63 17 22 56 24 0 0 56
17.1 1 1 0 59 63 4 16 137 19 0 137 137
15.6 1 0 1 62 71 5 23 86 30 86 0 86
18.4 1 1 1 62 74 4 23 121 81 121 121 121
19.05 1 1 0 51 67 5 19 149 42 0 149 149
18.55 1 1 0 64 66 5 4 168 22 0 168 168
19.1 1 1 0 52 62 6 20 140 85 0 140 140
13.1 1 0 1 67 80 4 24 88 27 88 0 88
12.85 1 1 1 50 73 4 20 168 25 168 168 168
9.5 1 1 1 54 67 4 4 94 22 94 94 94
4.5 1 1 1 58 61 6 24 51 19 51 51 51
11.85 1 0 0 56 73 8 22 48 14 0 0 48
13.6 1 1 1 63 74 10 16 145 45 145 145 145
11.7 1 1 1 31 32 4 3 66 45 66 66 66
12.4 1 0 1 65 69 5 15 85 28 85 0 85
13.35 1 1 0 71 69 4 24 109 51 0 109 109
11.4 1 0 0 50 84 4 17 63 41 0 0 63
14.9 1 0 1 57 64 4 20 102 31 102 0 102
19.9 1 0 0 47 58 16 27 162 74 0 0 162
11.2 1 0 1 47 59 7 26 86 19 86 0 86
14.6 1 0 1 57 78 4 23 114 51 114 0 114
17.6 1 1 0 43 57 4 17 164 73 0 164 164
14.05 1 1 1 41 60 14 20 119 24 119 119 119
16.1 1 1 0 63 68 5 22 126 61 0 126 126
13.35 1 1 1 63 68 5 19 132 23 132 132 132
11.85 1 1 1 56 73 5 24 142 14 142 142 142
11.95 1 1 0 51 69 5 19 83 54 0 83 83
14.75 1 0 1 50 67 7 23 94 51 94 0 94
15.15 1 0 0 22 60 19 15 81 62 0 0 81
13.2 1 1 1 41 65 16 27 166 36 166 166 166
16.85 1 0 0 59 66 4 26 110 59 0 0 110
7.85 1 0 1 56 74 4 22 64 24 64 0 64
7.7 1 1 0 66 81 7 22 93 26 0 93 93
12.6 1 0 0 53 72 9 18 104 54 0 0 104
7.85 1 0 1 42 55 5 15 105 39 105 0 105
10.95 1 0 1 52 49 14 22 49 16 49 0 49
12.35 1 0 0 54 74 4 27 88 36 0 0 88
9.95 1 0 1 44 53 16 10 95 31 95 0 95
14.9 1 0 1 62 64 10 20 102 31 102 0 102
16.65 1 0 0 53 65 5 17 99 42 0 0 99
13.4 1 0 1 50 57 6 23 63 39 63 0 63
13.95 1 0 0 36 51 4 19 76 25 0 0 76
15.7 1 0 0 76 80 4 13 109 31 0 0 109
16.85 1 0 1 66 67 4 27 117 38 117 0 117
10.95 1 0 1 62 70 5 23 57 31 57 0 57
15.35 1 0 0 59 74 4 16 120 17 0 0 120
12.2 1 0 1 47 75 4 25 73 22 73 0 73
15.1 1 0 0 55 70 5 2 91 55 0 0 91
17.75 1 0 0 58 69 4 26 108 62 0 0 108
15.2 1 0 1 60 65 4 20 105 51 105 0 105
14.6 1 1 0 44 55 5 23 117 30 0 117 117
16.65 1 0 0 57 71 8 22 119 49 0 0 119
8.1 1 0 1 45 65 15 24 31 16 31 0 31

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.06479 + 0.791615year_num[t] -0.714883group_num[t] + 0.647491gender[t] -0.00845122AMS.I[t] -0.0181652AMS.E[t] -0.0579353AMS.A[t] + 0.038751NUMERACYTOT[t] + 0.026867LFM[t] + 0.033395CH[t] -0.00906626Gender_LFM[t] -0.00283113Group_LFM[t] + 0.0297075Year_LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.06479 +  0.791615year_num[t] -0.714883group_num[t] +  0.647491gender[t] -0.00845122AMS.I[t] -0.0181652AMS.E[t] -0.0579353AMS.A[t] +  0.038751NUMERACYTOT[t] +  0.026867LFM[t] +  0.033395CH[t] -0.00906626Gender_LFM[t] -0.00283113Group_LFM[t] +  0.0297075Year_LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.06479 +  0.791615year_num[t] -0.714883group_num[t] +  0.647491gender[t] -0.00845122AMS.I[t] -0.0181652AMS.E[t] -0.0579353AMS.A[t] +  0.038751NUMERACYTOT[t] +  0.026867LFM[t] +  0.033395CH[t] -0.00906626Gender_LFM[t] -0.00283113Group_LFM[t] +  0.0297075Year_LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.06479 + 0.791615year_num[t] -0.714883group_num[t] + 0.647491gender[t] -0.00845122AMS.I[t] -0.0181652AMS.E[t] -0.0579353AMS.A[t] + 0.038751NUMERACYTOT[t] + 0.026867LFM[t] + 0.033395CH[t] -0.00906626Gender_LFM[t] -0.00283113Group_LFM[t] + 0.0297075Year_LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.064791.813414.4471.28044e-056.4022e-06
year_num0.7916150.9019730.87760.3809290.190465
group_num-0.7148831.00012-0.71480.4753630.237681
gender0.6474910.901590.71820.4732880.236644
AMS.I-0.008451220.0143018-0.59090.5550770.277539
AMS.E-0.01816520.0188052-0.9660.3349410.167471
AMS.A-0.05793530.0423314-1.3690.1722790.0861393
NUMERACYTOT0.0387510.02694331.4380.1515450.0757727
LFM0.0268670.01021872.6290.009058540.00452927
CH0.0333950.00806974.1384.70354e-052.35177e-05
Gender_LFM-0.009066260.00720528-1.2580.2093980.104699
Group_LFM-0.002831130.00879324-0.3220.7477320.373866
Year_LFM0.02970750.00714064.164.29715e-052.14857e-05

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 8.06479 & 1.81341 & 4.447 & 1.28044e-05 & 6.4022e-06 \tabularnewline
year_num & 0.791615 & 0.901973 & 0.8776 & 0.380929 & 0.190465 \tabularnewline
group_num & -0.714883 & 1.00012 & -0.7148 & 0.475363 & 0.237681 \tabularnewline
gender & 0.647491 & 0.90159 & 0.7182 & 0.473288 & 0.236644 \tabularnewline
AMS.I & -0.00845122 & 0.0143018 & -0.5909 & 0.555077 & 0.277539 \tabularnewline
AMS.E & -0.0181652 & 0.0188052 & -0.966 & 0.334941 & 0.167471 \tabularnewline
AMS.A & -0.0579353 & 0.0423314 & -1.369 & 0.172279 & 0.0861393 \tabularnewline
NUMERACYTOT & 0.038751 & 0.0269433 & 1.438 & 0.151545 & 0.0757727 \tabularnewline
LFM & 0.026867 & 0.0102187 & 2.629 & 0.00905854 & 0.00452927 \tabularnewline
CH & 0.033395 & 0.0080697 & 4.138 & 4.70354e-05 & 2.35177e-05 \tabularnewline
Gender_LFM & -0.00906626 & 0.00720528 & -1.258 & 0.209398 & 0.104699 \tabularnewline
Group_LFM & -0.00283113 & 0.00879324 & -0.322 & 0.747732 & 0.373866 \tabularnewline
Year_LFM & 0.0297075 & 0.0071406 & 4.16 & 4.29715e-05 & 2.14857e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]8.06479[/C][C]1.81341[/C][C]4.447[/C][C]1.28044e-05[/C][C]6.4022e-06[/C][/ROW]
[ROW][C]year_num[/C][C]0.791615[/C][C]0.901973[/C][C]0.8776[/C][C]0.380929[/C][C]0.190465[/C][/ROW]
[ROW][C]group_num[/C][C]-0.714883[/C][C]1.00012[/C][C]-0.7148[/C][C]0.475363[/C][C]0.237681[/C][/ROW]
[ROW][C]gender[/C][C]0.647491[/C][C]0.90159[/C][C]0.7182[/C][C]0.473288[/C][C]0.236644[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00845122[/C][C]0.0143018[/C][C]-0.5909[/C][C]0.555077[/C][C]0.277539[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0181652[/C][C]0.0188052[/C][C]-0.966[/C][C]0.334941[/C][C]0.167471[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0579353[/C][C]0.0423314[/C][C]-1.369[/C][C]0.172279[/C][C]0.0861393[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.038751[/C][C]0.0269433[/C][C]1.438[/C][C]0.151545[/C][C]0.0757727[/C][/ROW]
[ROW][C]LFM[/C][C]0.026867[/C][C]0.0102187[/C][C]2.629[/C][C]0.00905854[/C][C]0.00452927[/C][/ROW]
[ROW][C]CH[/C][C]0.033395[/C][C]0.0080697[/C][C]4.138[/C][C]4.70354e-05[/C][C]2.35177e-05[/C][/ROW]
[ROW][C]Gender_LFM[/C][C]-0.00906626[/C][C]0.00720528[/C][C]-1.258[/C][C]0.209398[/C][C]0.104699[/C][/ROW]
[ROW][C]Group_LFM[/C][C]-0.00283113[/C][C]0.00879324[/C][C]-0.322[/C][C]0.747732[/C][C]0.373866[/C][/ROW]
[ROW][C]Year_LFM[/C][C]0.0297075[/C][C]0.0071406[/C][C]4.16[/C][C]4.29715e-05[/C][C]2.14857e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.064791.813414.4471.28044e-056.4022e-06
year_num0.7916150.9019730.87760.3809290.190465
group_num-0.7148831.00012-0.71480.4753630.237681
gender0.6474910.901590.71820.4732880.236644
AMS.I-0.008451220.0143018-0.59090.5550770.277539
AMS.E-0.01816520.0188052-0.9660.3349410.167471
AMS.A-0.05793530.0423314-1.3690.1722790.0861393
NUMERACYTOT0.0387510.02694331.4380.1515450.0757727
LFM0.0268670.01021872.6290.009058540.00452927
CH0.0333950.00806974.1384.70354e-052.35177e-05
Gender_LFM-0.009066260.00720528-1.2580.2093980.104699
Group_LFM-0.002831130.00879324-0.3220.7477320.373866
Year_LFM0.02970750.00714064.164.29715e-052.14857e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.768477
R-squared0.590557
Adjusted R-squared0.572017
F-TEST (value)31.8518
F-TEST (DF numerator)12
F-TEST (DF denominator)265
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2206
Sum Squared Residuals1306.74

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.768477 \tabularnewline
R-squared & 0.590557 \tabularnewline
Adjusted R-squared & 0.572017 \tabularnewline
F-TEST (value) & 31.8518 \tabularnewline
F-TEST (DF numerator) & 12 \tabularnewline
F-TEST (DF denominator) & 265 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.2206 \tabularnewline
Sum Squared Residuals & 1306.74 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.768477[/C][/ROW]
[ROW][C]R-squared[/C][C]0.590557[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.572017[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]31.8518[/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]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.2206[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1306.74[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.768477
R-squared0.590557
Adjusted R-squared0.572017
F-TEST (value)31.8518
F-TEST (DF numerator)12
F-TEST (DF denominator)265
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2206
Sum Squared Residuals1306.74






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.65620.243843
212.210.39341.8066
312.811.24511.55491
47.411.0429-3.64291
56.710.3308-3.63076
612.611.41051.18947
714.811.78813.01188
813.311.04792.25213
911.111.2618-0.161844
108.211.0419-2.84188
1111.410.96220.437752
126.411.0587-4.65866
1310.69.235831.36417
141212.8733-0.873335
156.37.81106-1.51106
1611.39.657041.64296
1711.911.62250.277505
189.310.3364-1.03638
199.611.4384-1.83839
20109.897910.102091
216.49.53826-3.13826
2213.89.689754.11025
2310.812.8754-2.07541
2413.811.79212.00789
2511.710.71090.989096
2610.912.5188-1.61876
2716.113.05843.04157
2813.410.59572.80427
299.911.1815-1.28153
3011.510.95640.5436
318.39.84327-1.54327
3211.710.89670.803319
3399.87399-0.873985
349.710.9017-1.2017
3510.89.678851.12115
3610.39.434640.865362
3710.410.7096-0.309572
3812.710.09732.60266
399.310.9966-1.69658
4011.811.8915-0.0915022
415.910.0796-4.17962
4211.410.65250.747471
431311.26631.7337
4410.811.0957-0.295741
4512.39.755662.54434
4611.312.2486-0.948571
4711.810.15571.64432
487.910.4525-2.55255
4912.79.984922.71508
5012.39.81932.4807
5111.610.83670.763339
526.78.92311-2.22311
5310.910.2660.63403
5412.111.09621.0038
5513.310.16883.13123
5610.19.963960.136044
575.711.1382-5.43816
5814.39.585684.71432
5988.1352-0.135201
6013.311.26592.03409
619.312.0654-2.76545
6212.510.66821.8318
637.69.30111-1.70111
6415.912.13373.76634
659.211.6753-2.47529
669.19.47752-0.377516
6711.112.2693-1.16935
681313.4467-0.446684
6914.510.52823.97182
7012.211.0571.14295
7112.312.419-0.118981
7211.410.25781.14217
738.810.2527-1.45266
7414.611.52943.07063
7512.610.94181.65816
76NANA1.14352
771311.18391.81611
7812.611.39531.20469
7913.212.99870.201292
809.912.5078-2.60785
817.78.02062-0.32062
8210.57.692222.80778
8313.413.404-0.00396138
8410.916.5129-5.61289
854.35.34465-1.04465
8610.310.06940.230571
8711.810.5261.27396
8811.29.192322.00768
8911.413.0607-1.66073
908.66.856891.74311
9113.210.44942.75063
9212.617.2795-4.67949
935.67.45034-1.85034
949.911.0755-1.1755
958.811.2091-2.40908
967.79.40431-1.70431
97912.6303-3.63035
987.35.543981.75602
9911.48.052023.34798
10013.616.3029-2.70291
1017.97.107690.792312
10210.710.8735-0.173456
10310.311.7102-1.41018
1048.39.69919-1.39919
1059.66.04373.5563
10614.216.1193-1.91935
1078.54.880653.61935
10813.518.8598-5.35984
1094.97.39843-2.49843
1106.47.83341-1.43341
1119.68.855470.744532
11211.610.33241.26763
11311.117.262-6.16203
1144.353.643960.706039
11512.710.07072.62933
11618.116.10731.99266
11717.8519.3356-1.48561
11816.615.26021.33979
11912.614.6201-2.02013
12017.116.05391.04607
12119.122.3718-3.27182
12216.113.63852.46154
12313.3511.89491.45512
12418.413.51194.88811
12514.717.4948-2.79484
12610.611.2414-0.641383
12712.611.48431.11572
12816.216.5895-0.389491
12913.611.43162.16838
13018.917.79051.10949
13114.112.95261.14737
13214.516.5524-2.05241
13316.1515.22510.924891
13414.7513.88540.864575
13514.814.5090.290971
13612.4512.5187-0.0687477
13712.659.641333.00867
13817.3518.6395-1.2895
1398.67.423851.17615
14018.417.55150.848478
14116.116.2914-0.191439
14211.69.319392.28061
14317.7517.95-0.199969
14415.2512.1783.07203
14517.6518.1119-0.461919
14616.3516.02280.327171
14717.6518.1905-0.540489
14813.613.57780.0221634
14914.3514.8836-0.533638
15014.7512.99321.75684
15118.2525.1454-6.89541
1529.99.263820.636179
1531613.88822.11178
15418.2519.4091-1.15907
15516.8514.87231.97765
15614.615.2081-0.608074
15713.8512.8920.957962
15818.9517.74741.20262
15915.617.7306-2.13062
16014.8516.4335-1.58348
16111.7510.44091.3091
16218.4516.42822.02183
16315.917.3638-1.46377
16417.19.718727.38128
16516.115.91460.185368
16619.919.50430.395652
16710.959.434471.51553
16818.4516.72091.72909
16915.114.89920.20077
1701517.5135-2.51351
17111.3510.07251.27751
17215.9513.5542.39596
17318.120.522-2.422
17414.615.3076-0.707643
17515.416.0713-0.671313
17615.413.00182.3982
17717.619.0295-1.4295
17813.3511.36971.98028
17919.120.8949-1.79492
18015.3517.8043-2.4543
1817.69.68004-2.08004
18213.415.529-2.12899
18313.911.62192.27814
18419.119.09460.00540225
18515.2518.2847-3.03467
18612.912.48930.410658
18716.113.21072.88931
18817.3519.4708-2.1208
18913.1515.1065-1.95654
19012.1511.85380.296236
19112.614.7668-2.16685
19210.359.555760.794236
19315.418.2442-2.84416
1949.66.197023.40298
19518.218.02150.178523
19613.612.17521.42483
19714.8517.2838-2.43378
19814.7514.07920.670787
19914.112.06582.0342
20014.914.06070.839336
20116.2515.94810.301942
20219.2518.35710.892907
20313.615.6232-2.02319
20413.613.6279-0.0278953
20515.6516.2932-0.643228
20612.7510.34272.40733
20714.615.4743-0.874341
2089.858.978780.871216
20912.6510.38442.26562
21019.217.38891.81113
21116.617.1008-0.500758
21211.211.2618-0.0617553
21315.2517.6611-2.41114
21411.911.39840.501613
21513.214.4349-1.23489
21616.3516.9462-0.596236
21712.410.97341.42656
21815.8514.33231.51771
21918.1519.3966-1.2466
22011.1511.6762-0.52619
22115.6513.4212.22902
22217.7520.6921-2.94208
2237.658.75208-1.10208
22412.3510.23542.11456
22515.613.80591.7941
22619.315.25214.04793
22715.212.98412.21588
22817.114.87942.22065
22915.612.89132.70872
23018.415.70042.69961
23119.0516.53072.51935
23218.5516.81591.73412
23319.119.2651-0.165128
23413.116.1743-3.07431
23512.8515.3232-2.47319
2369.515.6862-6.18622
2374.53.279231.22077
23811.8513.184-1.33399
23913.614.1817-0.581722
24011.712.266-0.566024
24112.413.5976-1.19755
24213.3514.2184-0.868388
24311.410.7840.616024
24414.914.16120.738762
24519.922.0571-2.15714
24611.211.9839-0.783916
24714.615.4215-0.821487
24817.616.98460.61541
24914.0513.69550.354524
25016.116.8834-0.783417
25113.3515.9417-2.59172
25211.8513.0677-1.21774
25311.9511.71890.231079
25414.7513.31411.43591
25515.1517.9497-2.79972
25613.212.47820.721827
25716.8521.1492-4.2992
2587.8512.5757-4.72575
2597.710.0638-2.36378
26012.619.4822-6.88223
2617.857.978-0.127995
26210.9512.6511-1.70113
26312.3515.5784-3.22837
2649.958.944111.00589
26514.912.85032.04968
26616.6516.1350.514989
26713.412.71480.685193
26813.9512.48481.46521
26915.714.22111.47893
27016.8517.9532-1.10317
27110.9510.35850.591505
27215.3515.8341-0.484131
27312.210.99291.20714
27415.113.41921.68083
27517.7517.60090.149117
27615.215.262-0.0620108
27714.613.79270.807276
27816.6518.5609-1.91093
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.6562 & 0.243843 \tabularnewline
2 & 12.2 & 10.3934 & 1.8066 \tabularnewline
3 & 12.8 & 11.2451 & 1.55491 \tabularnewline
4 & 7.4 & 11.0429 & -3.64291 \tabularnewline
5 & 6.7 & 10.3308 & -3.63076 \tabularnewline
6 & 12.6 & 11.4105 & 1.18947 \tabularnewline
7 & 14.8 & 11.7881 & 3.01188 \tabularnewline
8 & 13.3 & 11.0479 & 2.25213 \tabularnewline
9 & 11.1 & 11.2618 & -0.161844 \tabularnewline
10 & 8.2 & 11.0419 & -2.84188 \tabularnewline
11 & 11.4 & 10.9622 & 0.437752 \tabularnewline
12 & 6.4 & 11.0587 & -4.65866 \tabularnewline
13 & 10.6 & 9.23583 & 1.36417 \tabularnewline
14 & 12 & 12.8733 & -0.873335 \tabularnewline
15 & 6.3 & 7.81106 & -1.51106 \tabularnewline
16 & 11.3 & 9.65704 & 1.64296 \tabularnewline
17 & 11.9 & 11.6225 & 0.277505 \tabularnewline
18 & 9.3 & 10.3364 & -1.03638 \tabularnewline
19 & 9.6 & 11.4384 & -1.83839 \tabularnewline
20 & 10 & 9.89791 & 0.102091 \tabularnewline
21 & 6.4 & 9.53826 & -3.13826 \tabularnewline
22 & 13.8 & 9.68975 & 4.11025 \tabularnewline
23 & 10.8 & 12.8754 & -2.07541 \tabularnewline
24 & 13.8 & 11.7921 & 2.00789 \tabularnewline
25 & 11.7 & 10.7109 & 0.989096 \tabularnewline
26 & 10.9 & 12.5188 & -1.61876 \tabularnewline
27 & 16.1 & 13.0584 & 3.04157 \tabularnewline
28 & 13.4 & 10.5957 & 2.80427 \tabularnewline
29 & 9.9 & 11.1815 & -1.28153 \tabularnewline
30 & 11.5 & 10.9564 & 0.5436 \tabularnewline
31 & 8.3 & 9.84327 & -1.54327 \tabularnewline
32 & 11.7 & 10.8967 & 0.803319 \tabularnewline
33 & 9 & 9.87399 & -0.873985 \tabularnewline
34 & 9.7 & 10.9017 & -1.2017 \tabularnewline
35 & 10.8 & 9.67885 & 1.12115 \tabularnewline
36 & 10.3 & 9.43464 & 0.865362 \tabularnewline
37 & 10.4 & 10.7096 & -0.309572 \tabularnewline
38 & 12.7 & 10.0973 & 2.60266 \tabularnewline
39 & 9.3 & 10.9966 & -1.69658 \tabularnewline
40 & 11.8 & 11.8915 & -0.0915022 \tabularnewline
41 & 5.9 & 10.0796 & -4.17962 \tabularnewline
42 & 11.4 & 10.6525 & 0.747471 \tabularnewline
43 & 13 & 11.2663 & 1.7337 \tabularnewline
44 & 10.8 & 11.0957 & -0.295741 \tabularnewline
45 & 12.3 & 9.75566 & 2.54434 \tabularnewline
46 & 11.3 & 12.2486 & -0.948571 \tabularnewline
47 & 11.8 & 10.1557 & 1.64432 \tabularnewline
48 & 7.9 & 10.4525 & -2.55255 \tabularnewline
49 & 12.7 & 9.98492 & 2.71508 \tabularnewline
50 & 12.3 & 9.8193 & 2.4807 \tabularnewline
51 & 11.6 & 10.8367 & 0.763339 \tabularnewline
52 & 6.7 & 8.92311 & -2.22311 \tabularnewline
53 & 10.9 & 10.266 & 0.63403 \tabularnewline
54 & 12.1 & 11.0962 & 1.0038 \tabularnewline
55 & 13.3 & 10.1688 & 3.13123 \tabularnewline
56 & 10.1 & 9.96396 & 0.136044 \tabularnewline
57 & 5.7 & 11.1382 & -5.43816 \tabularnewline
58 & 14.3 & 9.58568 & 4.71432 \tabularnewline
59 & 8 & 8.1352 & -0.135201 \tabularnewline
60 & 13.3 & 11.2659 & 2.03409 \tabularnewline
61 & 9.3 & 12.0654 & -2.76545 \tabularnewline
62 & 12.5 & 10.6682 & 1.8318 \tabularnewline
63 & 7.6 & 9.30111 & -1.70111 \tabularnewline
64 & 15.9 & 12.1337 & 3.76634 \tabularnewline
65 & 9.2 & 11.6753 & -2.47529 \tabularnewline
66 & 9.1 & 9.47752 & -0.377516 \tabularnewline
67 & 11.1 & 12.2693 & -1.16935 \tabularnewline
68 & 13 & 13.4467 & -0.446684 \tabularnewline
69 & 14.5 & 10.5282 & 3.97182 \tabularnewline
70 & 12.2 & 11.057 & 1.14295 \tabularnewline
71 & 12.3 & 12.419 & -0.118981 \tabularnewline
72 & 11.4 & 10.2578 & 1.14217 \tabularnewline
73 & 8.8 & 10.2527 & -1.45266 \tabularnewline
74 & 14.6 & 11.5294 & 3.07063 \tabularnewline
75 & 12.6 & 10.9418 & 1.65816 \tabularnewline
76 & NA & NA & 1.14352 \tabularnewline
77 & 13 & 11.1839 & 1.81611 \tabularnewline
78 & 12.6 & 11.3953 & 1.20469 \tabularnewline
79 & 13.2 & 12.9987 & 0.201292 \tabularnewline
80 & 9.9 & 12.5078 & -2.60785 \tabularnewline
81 & 7.7 & 8.02062 & -0.32062 \tabularnewline
82 & 10.5 & 7.69222 & 2.80778 \tabularnewline
83 & 13.4 & 13.404 & -0.00396138 \tabularnewline
84 & 10.9 & 16.5129 & -5.61289 \tabularnewline
85 & 4.3 & 5.34465 & -1.04465 \tabularnewline
86 & 10.3 & 10.0694 & 0.230571 \tabularnewline
87 & 11.8 & 10.526 & 1.27396 \tabularnewline
88 & 11.2 & 9.19232 & 2.00768 \tabularnewline
89 & 11.4 & 13.0607 & -1.66073 \tabularnewline
90 & 8.6 & 6.85689 & 1.74311 \tabularnewline
91 & 13.2 & 10.4494 & 2.75063 \tabularnewline
92 & 12.6 & 17.2795 & -4.67949 \tabularnewline
93 & 5.6 & 7.45034 & -1.85034 \tabularnewline
94 & 9.9 & 11.0755 & -1.1755 \tabularnewline
95 & 8.8 & 11.2091 & -2.40908 \tabularnewline
96 & 7.7 & 9.40431 & -1.70431 \tabularnewline
97 & 9 & 12.6303 & -3.63035 \tabularnewline
98 & 7.3 & 5.54398 & 1.75602 \tabularnewline
99 & 11.4 & 8.05202 & 3.34798 \tabularnewline
100 & 13.6 & 16.3029 & -2.70291 \tabularnewline
101 & 7.9 & 7.10769 & 0.792312 \tabularnewline
102 & 10.7 & 10.8735 & -0.173456 \tabularnewline
103 & 10.3 & 11.7102 & -1.41018 \tabularnewline
104 & 8.3 & 9.69919 & -1.39919 \tabularnewline
105 & 9.6 & 6.0437 & 3.5563 \tabularnewline
106 & 14.2 & 16.1193 & -1.91935 \tabularnewline
107 & 8.5 & 4.88065 & 3.61935 \tabularnewline
108 & 13.5 & 18.8598 & -5.35984 \tabularnewline
109 & 4.9 & 7.39843 & -2.49843 \tabularnewline
110 & 6.4 & 7.83341 & -1.43341 \tabularnewline
111 & 9.6 & 8.85547 & 0.744532 \tabularnewline
112 & 11.6 & 10.3324 & 1.26763 \tabularnewline
113 & 11.1 & 17.262 & -6.16203 \tabularnewline
114 & 4.35 & 3.64396 & 0.706039 \tabularnewline
115 & 12.7 & 10.0707 & 2.62933 \tabularnewline
116 & 18.1 & 16.1073 & 1.99266 \tabularnewline
117 & 17.85 & 19.3356 & -1.48561 \tabularnewline
118 & 16.6 & 15.2602 & 1.33979 \tabularnewline
119 & 12.6 & 14.6201 & -2.02013 \tabularnewline
120 & 17.1 & 16.0539 & 1.04607 \tabularnewline
121 & 19.1 & 22.3718 & -3.27182 \tabularnewline
122 & 16.1 & 13.6385 & 2.46154 \tabularnewline
123 & 13.35 & 11.8949 & 1.45512 \tabularnewline
124 & 18.4 & 13.5119 & 4.88811 \tabularnewline
125 & 14.7 & 17.4948 & -2.79484 \tabularnewline
126 & 10.6 & 11.2414 & -0.641383 \tabularnewline
127 & 12.6 & 11.4843 & 1.11572 \tabularnewline
128 & 16.2 & 16.5895 & -0.389491 \tabularnewline
129 & 13.6 & 11.4316 & 2.16838 \tabularnewline
130 & 18.9 & 17.7905 & 1.10949 \tabularnewline
131 & 14.1 & 12.9526 & 1.14737 \tabularnewline
132 & 14.5 & 16.5524 & -2.05241 \tabularnewline
133 & 16.15 & 15.2251 & 0.924891 \tabularnewline
134 & 14.75 & 13.8854 & 0.864575 \tabularnewline
135 & 14.8 & 14.509 & 0.290971 \tabularnewline
136 & 12.45 & 12.5187 & -0.0687477 \tabularnewline
137 & 12.65 & 9.64133 & 3.00867 \tabularnewline
138 & 17.35 & 18.6395 & -1.2895 \tabularnewline
139 & 8.6 & 7.42385 & 1.17615 \tabularnewline
140 & 18.4 & 17.5515 & 0.848478 \tabularnewline
141 & 16.1 & 16.2914 & -0.191439 \tabularnewline
142 & 11.6 & 9.31939 & 2.28061 \tabularnewline
143 & 17.75 & 17.95 & -0.199969 \tabularnewline
144 & 15.25 & 12.178 & 3.07203 \tabularnewline
145 & 17.65 & 18.1119 & -0.461919 \tabularnewline
146 & 16.35 & 16.0228 & 0.327171 \tabularnewline
147 & 17.65 & 18.1905 & -0.540489 \tabularnewline
148 & 13.6 & 13.5778 & 0.0221634 \tabularnewline
149 & 14.35 & 14.8836 & -0.533638 \tabularnewline
150 & 14.75 & 12.9932 & 1.75684 \tabularnewline
151 & 18.25 & 25.1454 & -6.89541 \tabularnewline
152 & 9.9 & 9.26382 & 0.636179 \tabularnewline
153 & 16 & 13.8882 & 2.11178 \tabularnewline
154 & 18.25 & 19.4091 & -1.15907 \tabularnewline
155 & 16.85 & 14.8723 & 1.97765 \tabularnewline
156 & 14.6 & 15.2081 & -0.608074 \tabularnewline
157 & 13.85 & 12.892 & 0.957962 \tabularnewline
158 & 18.95 & 17.7474 & 1.20262 \tabularnewline
159 & 15.6 & 17.7306 & -2.13062 \tabularnewline
160 & 14.85 & 16.4335 & -1.58348 \tabularnewline
161 & 11.75 & 10.4409 & 1.3091 \tabularnewline
162 & 18.45 & 16.4282 & 2.02183 \tabularnewline
163 & 15.9 & 17.3638 & -1.46377 \tabularnewline
164 & 17.1 & 9.71872 & 7.38128 \tabularnewline
165 & 16.1 & 15.9146 & 0.185368 \tabularnewline
166 & 19.9 & 19.5043 & 0.395652 \tabularnewline
167 & 10.95 & 9.43447 & 1.51553 \tabularnewline
168 & 18.45 & 16.7209 & 1.72909 \tabularnewline
169 & 15.1 & 14.8992 & 0.20077 \tabularnewline
170 & 15 & 17.5135 & -2.51351 \tabularnewline
171 & 11.35 & 10.0725 & 1.27751 \tabularnewline
172 & 15.95 & 13.554 & 2.39596 \tabularnewline
173 & 18.1 & 20.522 & -2.422 \tabularnewline
174 & 14.6 & 15.3076 & -0.707643 \tabularnewline
175 & 15.4 & 16.0713 & -0.671313 \tabularnewline
176 & 15.4 & 13.0018 & 2.3982 \tabularnewline
177 & 17.6 & 19.0295 & -1.4295 \tabularnewline
178 & 13.35 & 11.3697 & 1.98028 \tabularnewline
179 & 19.1 & 20.8949 & -1.79492 \tabularnewline
180 & 15.35 & 17.8043 & -2.4543 \tabularnewline
181 & 7.6 & 9.68004 & -2.08004 \tabularnewline
182 & 13.4 & 15.529 & -2.12899 \tabularnewline
183 & 13.9 & 11.6219 & 2.27814 \tabularnewline
184 & 19.1 & 19.0946 & 0.00540225 \tabularnewline
185 & 15.25 & 18.2847 & -3.03467 \tabularnewline
186 & 12.9 & 12.4893 & 0.410658 \tabularnewline
187 & 16.1 & 13.2107 & 2.88931 \tabularnewline
188 & 17.35 & 19.4708 & -2.1208 \tabularnewline
189 & 13.15 & 15.1065 & -1.95654 \tabularnewline
190 & 12.15 & 11.8538 & 0.296236 \tabularnewline
191 & 12.6 & 14.7668 & -2.16685 \tabularnewline
192 & 10.35 & 9.55576 & 0.794236 \tabularnewline
193 & 15.4 & 18.2442 & -2.84416 \tabularnewline
194 & 9.6 & 6.19702 & 3.40298 \tabularnewline
195 & 18.2 & 18.0215 & 0.178523 \tabularnewline
196 & 13.6 & 12.1752 & 1.42483 \tabularnewline
197 & 14.85 & 17.2838 & -2.43378 \tabularnewline
198 & 14.75 & 14.0792 & 0.670787 \tabularnewline
199 & 14.1 & 12.0658 & 2.0342 \tabularnewline
200 & 14.9 & 14.0607 & 0.839336 \tabularnewline
201 & 16.25 & 15.9481 & 0.301942 \tabularnewline
202 & 19.25 & 18.3571 & 0.892907 \tabularnewline
203 & 13.6 & 15.6232 & -2.02319 \tabularnewline
204 & 13.6 & 13.6279 & -0.0278953 \tabularnewline
205 & 15.65 & 16.2932 & -0.643228 \tabularnewline
206 & 12.75 & 10.3427 & 2.40733 \tabularnewline
207 & 14.6 & 15.4743 & -0.874341 \tabularnewline
208 & 9.85 & 8.97878 & 0.871216 \tabularnewline
209 & 12.65 & 10.3844 & 2.26562 \tabularnewline
210 & 19.2 & 17.3889 & 1.81113 \tabularnewline
211 & 16.6 & 17.1008 & -0.500758 \tabularnewline
212 & 11.2 & 11.2618 & -0.0617553 \tabularnewline
213 & 15.25 & 17.6611 & -2.41114 \tabularnewline
214 & 11.9 & 11.3984 & 0.501613 \tabularnewline
215 & 13.2 & 14.4349 & -1.23489 \tabularnewline
216 & 16.35 & 16.9462 & -0.596236 \tabularnewline
217 & 12.4 & 10.9734 & 1.42656 \tabularnewline
218 & 15.85 & 14.3323 & 1.51771 \tabularnewline
219 & 18.15 & 19.3966 & -1.2466 \tabularnewline
220 & 11.15 & 11.6762 & -0.52619 \tabularnewline
221 & 15.65 & 13.421 & 2.22902 \tabularnewline
222 & 17.75 & 20.6921 & -2.94208 \tabularnewline
223 & 7.65 & 8.75208 & -1.10208 \tabularnewline
224 & 12.35 & 10.2354 & 2.11456 \tabularnewline
225 & 15.6 & 13.8059 & 1.7941 \tabularnewline
226 & 19.3 & 15.2521 & 4.04793 \tabularnewline
227 & 15.2 & 12.9841 & 2.21588 \tabularnewline
228 & 17.1 & 14.8794 & 2.22065 \tabularnewline
229 & 15.6 & 12.8913 & 2.70872 \tabularnewline
230 & 18.4 & 15.7004 & 2.69961 \tabularnewline
231 & 19.05 & 16.5307 & 2.51935 \tabularnewline
232 & 18.55 & 16.8159 & 1.73412 \tabularnewline
233 & 19.1 & 19.2651 & -0.165128 \tabularnewline
234 & 13.1 & 16.1743 & -3.07431 \tabularnewline
235 & 12.85 & 15.3232 & -2.47319 \tabularnewline
236 & 9.5 & 15.6862 & -6.18622 \tabularnewline
237 & 4.5 & 3.27923 & 1.22077 \tabularnewline
238 & 11.85 & 13.184 & -1.33399 \tabularnewline
239 & 13.6 & 14.1817 & -0.581722 \tabularnewline
240 & 11.7 & 12.266 & -0.566024 \tabularnewline
241 & 12.4 & 13.5976 & -1.19755 \tabularnewline
242 & 13.35 & 14.2184 & -0.868388 \tabularnewline
243 & 11.4 & 10.784 & 0.616024 \tabularnewline
244 & 14.9 & 14.1612 & 0.738762 \tabularnewline
245 & 19.9 & 22.0571 & -2.15714 \tabularnewline
246 & 11.2 & 11.9839 & -0.783916 \tabularnewline
247 & 14.6 & 15.4215 & -0.821487 \tabularnewline
248 & 17.6 & 16.9846 & 0.61541 \tabularnewline
249 & 14.05 & 13.6955 & 0.354524 \tabularnewline
250 & 16.1 & 16.8834 & -0.783417 \tabularnewline
251 & 13.35 & 15.9417 & -2.59172 \tabularnewline
252 & 11.85 & 13.0677 & -1.21774 \tabularnewline
253 & 11.95 & 11.7189 & 0.231079 \tabularnewline
254 & 14.75 & 13.3141 & 1.43591 \tabularnewline
255 & 15.15 & 17.9497 & -2.79972 \tabularnewline
256 & 13.2 & 12.4782 & 0.721827 \tabularnewline
257 & 16.85 & 21.1492 & -4.2992 \tabularnewline
258 & 7.85 & 12.5757 & -4.72575 \tabularnewline
259 & 7.7 & 10.0638 & -2.36378 \tabularnewline
260 & 12.6 & 19.4822 & -6.88223 \tabularnewline
261 & 7.85 & 7.978 & -0.127995 \tabularnewline
262 & 10.95 & 12.6511 & -1.70113 \tabularnewline
263 & 12.35 & 15.5784 & -3.22837 \tabularnewline
264 & 9.95 & 8.94411 & 1.00589 \tabularnewline
265 & 14.9 & 12.8503 & 2.04968 \tabularnewline
266 & 16.65 & 16.135 & 0.514989 \tabularnewline
267 & 13.4 & 12.7148 & 0.685193 \tabularnewline
268 & 13.95 & 12.4848 & 1.46521 \tabularnewline
269 & 15.7 & 14.2211 & 1.47893 \tabularnewline
270 & 16.85 & 17.9532 & -1.10317 \tabularnewline
271 & 10.95 & 10.3585 & 0.591505 \tabularnewline
272 & 15.35 & 15.8341 & -0.484131 \tabularnewline
273 & 12.2 & 10.9929 & 1.20714 \tabularnewline
274 & 15.1 & 13.4192 & 1.68083 \tabularnewline
275 & 17.75 & 17.6009 & 0.149117 \tabularnewline
276 & 15.2 & 15.262 & -0.0620108 \tabularnewline
277 & 14.6 & 13.7927 & 0.807276 \tabularnewline
278 & 16.65 & 18.5609 & -1.91093 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.6562[/C][C]0.243843[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.3934[/C][C]1.8066[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.2451[/C][C]1.55491[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.0429[/C][C]-3.64291[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.3308[/C][C]-3.63076[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]11.4105[/C][C]1.18947[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.7881[/C][C]3.01188[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.0479[/C][C]2.25213[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.2618[/C][C]-0.161844[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.0419[/C][C]-2.84188[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]10.9622[/C][C]0.437752[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.0587[/C][C]-4.65866[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.23583[/C][C]1.36417[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.8733[/C][C]-0.873335[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.81106[/C][C]-1.51106[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.65704[/C][C]1.64296[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.6225[/C][C]0.277505[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.3364[/C][C]-1.03638[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.4384[/C][C]-1.83839[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.89791[/C][C]0.102091[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.53826[/C][C]-3.13826[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]9.68975[/C][C]4.11025[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.8754[/C][C]-2.07541[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.7921[/C][C]2.00789[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]10.7109[/C][C]0.989096[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.5188[/C][C]-1.61876[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.0584[/C][C]3.04157[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.5957[/C][C]2.80427[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.1815[/C][C]-1.28153[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.9564[/C][C]0.5436[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.84327[/C][C]-1.54327[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]10.8967[/C][C]0.803319[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.87399[/C][C]-0.873985[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]10.9017[/C][C]-1.2017[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.67885[/C][C]1.12115[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]9.43464[/C][C]0.865362[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.7096[/C][C]-0.309572[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.0973[/C][C]2.60266[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]10.9966[/C][C]-1.69658[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]11.8915[/C][C]-0.0915022[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.0796[/C][C]-4.17962[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.6525[/C][C]0.747471[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.2663[/C][C]1.7337[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.0957[/C][C]-0.295741[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]9.75566[/C][C]2.54434[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.2486[/C][C]-0.948571[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]10.1557[/C][C]1.64432[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]10.4525[/C][C]-2.55255[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.98492[/C][C]2.71508[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.8193[/C][C]2.4807[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.8367[/C][C]0.763339[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]8.92311[/C][C]-2.22311[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.266[/C][C]0.63403[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.0962[/C][C]1.0038[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.1688[/C][C]3.13123[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.96396[/C][C]0.136044[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.1382[/C][C]-5.43816[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.58568[/C][C]4.71432[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]8.1352[/C][C]-0.135201[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.2659[/C][C]2.03409[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.0654[/C][C]-2.76545[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.6682[/C][C]1.8318[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.30111[/C][C]-1.70111[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.1337[/C][C]3.76634[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.6753[/C][C]-2.47529[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]9.47752[/C][C]-0.377516[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.2693[/C][C]-1.16935[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.4467[/C][C]-0.446684[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]10.5282[/C][C]3.97182[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.057[/C][C]1.14295[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.419[/C][C]-0.118981[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.2578[/C][C]1.14217[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.2527[/C][C]-1.45266[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.5294[/C][C]3.07063[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.9418[/C][C]1.65816[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.14352[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.1839[/C][C]1.81611[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.3953[/C][C]1.20469[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]12.9987[/C][C]0.201292[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.5078[/C][C]-2.60785[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.02062[/C][C]-0.32062[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.69222[/C][C]2.80778[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]13.404[/C][C]-0.00396138[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.5129[/C][C]-5.61289[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.34465[/C][C]-1.04465[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]10.0694[/C][C]0.230571[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]10.526[/C][C]1.27396[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]9.19232[/C][C]2.00768[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]13.0607[/C][C]-1.66073[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.85689[/C][C]1.74311[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]10.4494[/C][C]2.75063[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]17.2795[/C][C]-4.67949[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.45034[/C][C]-1.85034[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.0755[/C][C]-1.1755[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]11.2091[/C][C]-2.40908[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.40431[/C][C]-1.70431[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.6303[/C][C]-3.63035[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.54398[/C][C]1.75602[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]8.05202[/C][C]3.34798[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]16.3029[/C][C]-2.70291[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]7.10769[/C][C]0.792312[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.8735[/C][C]-0.173456[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]11.7102[/C][C]-1.41018[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.69919[/C][C]-1.39919[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]6.0437[/C][C]3.5563[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.1193[/C][C]-1.91935[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.88065[/C][C]3.61935[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.8598[/C][C]-5.35984[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]7.39843[/C][C]-2.49843[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.83341[/C][C]-1.43341[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.85547[/C][C]0.744532[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.3324[/C][C]1.26763[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.262[/C][C]-6.16203[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.64396[/C][C]0.706039[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]10.0707[/C][C]2.62933[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]16.1073[/C][C]1.99266[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]19.3356[/C][C]-1.48561[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.2602[/C][C]1.33979[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]14.6201[/C][C]-2.02013[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]16.0539[/C][C]1.04607[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]22.3718[/C][C]-3.27182[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.6385[/C][C]2.46154[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]11.8949[/C][C]1.45512[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]13.5119[/C][C]4.88811[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.4948[/C][C]-2.79484[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.2414[/C][C]-0.641383[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.4843[/C][C]1.11572[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.5895[/C][C]-0.389491[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]11.4316[/C][C]2.16838[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.7905[/C][C]1.10949[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.9526[/C][C]1.14737[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]16.5524[/C][C]-2.05241[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.2251[/C][C]0.924891[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.8854[/C][C]0.864575[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.509[/C][C]0.290971[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.5187[/C][C]-0.0687477[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.64133[/C][C]3.00867[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]18.6395[/C][C]-1.2895[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.42385[/C][C]1.17615[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.5515[/C][C]0.848478[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.2914[/C][C]-0.191439[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]9.31939[/C][C]2.28061[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.95[/C][C]-0.199969[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]12.178[/C][C]3.07203[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]18.1119[/C][C]-0.461919[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]16.0228[/C][C]0.327171[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.1905[/C][C]-0.540489[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.5778[/C][C]0.0221634[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.8836[/C][C]-0.533638[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.9932[/C][C]1.75684[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]25.1454[/C][C]-6.89541[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.26382[/C][C]0.636179[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.8882[/C][C]2.11178[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]19.4091[/C][C]-1.15907[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.8723[/C][C]1.97765[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]15.2081[/C][C]-0.608074[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.892[/C][C]0.957962[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.7474[/C][C]1.20262[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]17.7306[/C][C]-2.13062[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]16.4335[/C][C]-1.58348[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]10.4409[/C][C]1.3091[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.4282[/C][C]2.02183[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]17.3638[/C][C]-1.46377[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]9.71872[/C][C]7.38128[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]15.9146[/C][C]0.185368[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.5043[/C][C]0.395652[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]9.43447[/C][C]1.51553[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.7209[/C][C]1.72909[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]14.8992[/C][C]0.20077[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.5135[/C][C]-2.51351[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.0725[/C][C]1.27751[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.554[/C][C]2.39596[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]20.522[/C][C]-2.422[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.3076[/C][C]-0.707643[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.0713[/C][C]-0.671313[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]13.0018[/C][C]2.3982[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]19.0295[/C][C]-1.4295[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]11.3697[/C][C]1.98028[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.8949[/C][C]-1.79492[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]17.8043[/C][C]-2.4543[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.68004[/C][C]-2.08004[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.529[/C][C]-2.12899[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.6219[/C][C]2.27814[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]19.0946[/C][C]0.00540225[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]18.2847[/C][C]-3.03467[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.4893[/C][C]0.410658[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]13.2107[/C][C]2.88931[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.4708[/C][C]-2.1208[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]15.1065[/C][C]-1.95654[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.8538[/C][C]0.296236[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.7668[/C][C]-2.16685[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.55576[/C][C]0.794236[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.2442[/C][C]-2.84416[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.19702[/C][C]3.40298[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.0215[/C][C]0.178523[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.1752[/C][C]1.42483[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]17.2838[/C][C]-2.43378[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.0792[/C][C]0.670787[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.0658[/C][C]2.0342[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.0607[/C][C]0.839336[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]15.9481[/C][C]0.301942[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.3571[/C][C]0.892907[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.6232[/C][C]-2.02319[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.6279[/C][C]-0.0278953[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.2932[/C][C]-0.643228[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.3427[/C][C]2.40733[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.4743[/C][C]-0.874341[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.97878[/C][C]0.871216[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]10.3844[/C][C]2.26562[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.3889[/C][C]1.81113[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.1008[/C][C]-0.500758[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.2618[/C][C]-0.0617553[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.6611[/C][C]-2.41114[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]11.3984[/C][C]0.501613[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]14.4349[/C][C]-1.23489[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]16.9462[/C][C]-0.596236[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]10.9734[/C][C]1.42656[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]14.3323[/C][C]1.51771[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.3966[/C][C]-1.2466[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.6762[/C][C]-0.52619[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]13.421[/C][C]2.22902[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]20.6921[/C][C]-2.94208[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.75208[/C][C]-1.10208[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]10.2354[/C][C]2.11456[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.8059[/C][C]1.7941[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.2521[/C][C]4.04793[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]12.9841[/C][C]2.21588[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.8794[/C][C]2.22065[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.8913[/C][C]2.70872[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.7004[/C][C]2.69961[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]16.5307[/C][C]2.51935[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.8159[/C][C]1.73412[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.2651[/C][C]-0.165128[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]16.1743[/C][C]-3.07431[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.3232[/C][C]-2.47319[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]15.6862[/C][C]-6.18622[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.27923[/C][C]1.22077[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]13.184[/C][C]-1.33399[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]14.1817[/C][C]-0.581722[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.266[/C][C]-0.566024[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.5976[/C][C]-1.19755[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.2184[/C][C]-0.868388[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.784[/C][C]0.616024[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]14.1612[/C][C]0.738762[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.0571[/C][C]-2.15714[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.9839[/C][C]-0.783916[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]15.4215[/C][C]-0.821487[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.9846[/C][C]0.61541[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.6955[/C][C]0.354524[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.8834[/C][C]-0.783417[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]15.9417[/C][C]-2.59172[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.0677[/C][C]-1.21774[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.7189[/C][C]0.231079[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.3141[/C][C]1.43591[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]17.9497[/C][C]-2.79972[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.4782[/C][C]0.721827[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.1492[/C][C]-4.2992[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.5757[/C][C]-4.72575[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.0638[/C][C]-2.36378[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.4822[/C][C]-6.88223[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]7.978[/C][C]-0.127995[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]12.6511[/C][C]-1.70113[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.5784[/C][C]-3.22837[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.94411[/C][C]1.00589[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]12.8503[/C][C]2.04968[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.135[/C][C]0.514989[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.7148[/C][C]0.685193[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]12.4848[/C][C]1.46521[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]14.2211[/C][C]1.47893[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.9532[/C][C]-1.10317[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]10.3585[/C][C]0.591505[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.8341[/C][C]-0.484131[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.9929[/C][C]1.20714[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.4192[/C][C]1.68083[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.6009[/C][C]0.149117[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.262[/C][C]-0.0620108[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.7927[/C][C]0.807276[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]18.5609[/C][C]-1.91093[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.65620.243843
212.210.39341.8066
312.811.24511.55491
47.411.0429-3.64291
56.710.3308-3.63076
612.611.41051.18947
714.811.78813.01188
813.311.04792.25213
911.111.2618-0.161844
108.211.0419-2.84188
1111.410.96220.437752
126.411.0587-4.65866
1310.69.235831.36417
141212.8733-0.873335
156.37.81106-1.51106
1611.39.657041.64296
1711.911.62250.277505
189.310.3364-1.03638
199.611.4384-1.83839
20109.897910.102091
216.49.53826-3.13826
2213.89.689754.11025
2310.812.8754-2.07541
2413.811.79212.00789
2511.710.71090.989096
2610.912.5188-1.61876
2716.113.05843.04157
2813.410.59572.80427
299.911.1815-1.28153
3011.510.95640.5436
318.39.84327-1.54327
3211.710.89670.803319
3399.87399-0.873985
349.710.9017-1.2017
3510.89.678851.12115
3610.39.434640.865362
3710.410.7096-0.309572
3812.710.09732.60266
399.310.9966-1.69658
4011.811.8915-0.0915022
415.910.0796-4.17962
4211.410.65250.747471
431311.26631.7337
4410.811.0957-0.295741
4512.39.755662.54434
4611.312.2486-0.948571
4711.810.15571.64432
487.910.4525-2.55255
4912.79.984922.71508
5012.39.81932.4807
5111.610.83670.763339
526.78.92311-2.22311
5310.910.2660.63403
5412.111.09621.0038
5513.310.16883.13123
5610.19.963960.136044
575.711.1382-5.43816
5814.39.585684.71432
5988.1352-0.135201
6013.311.26592.03409
619.312.0654-2.76545
6212.510.66821.8318
637.69.30111-1.70111
6415.912.13373.76634
659.211.6753-2.47529
669.19.47752-0.377516
6711.112.2693-1.16935
681313.4467-0.446684
6914.510.52823.97182
7012.211.0571.14295
7112.312.419-0.118981
7211.410.25781.14217
738.810.2527-1.45266
7414.611.52943.07063
7512.610.94181.65816
76NANA1.14352
771311.18391.81611
7812.611.39531.20469
7913.212.99870.201292
809.912.5078-2.60785
817.78.02062-0.32062
8210.57.692222.80778
8313.413.404-0.00396138
8410.916.5129-5.61289
854.35.34465-1.04465
8610.310.06940.230571
8711.810.5261.27396
8811.29.192322.00768
8911.413.0607-1.66073
908.66.856891.74311
9113.210.44942.75063
9212.617.2795-4.67949
935.67.45034-1.85034
949.911.0755-1.1755
958.811.2091-2.40908
967.79.40431-1.70431
97912.6303-3.63035
987.35.543981.75602
9911.48.052023.34798
10013.616.3029-2.70291
1017.97.107690.792312
10210.710.8735-0.173456
10310.311.7102-1.41018
1048.39.69919-1.39919
1059.66.04373.5563
10614.216.1193-1.91935
1078.54.880653.61935
10813.518.8598-5.35984
1094.97.39843-2.49843
1106.47.83341-1.43341
1119.68.855470.744532
11211.610.33241.26763
11311.117.262-6.16203
1144.353.643960.706039
11512.710.07072.62933
11618.116.10731.99266
11717.8519.3356-1.48561
11816.615.26021.33979
11912.614.6201-2.02013
12017.116.05391.04607
12119.122.3718-3.27182
12216.113.63852.46154
12313.3511.89491.45512
12418.413.51194.88811
12514.717.4948-2.79484
12610.611.2414-0.641383
12712.611.48431.11572
12816.216.5895-0.389491
12913.611.43162.16838
13018.917.79051.10949
13114.112.95261.14737
13214.516.5524-2.05241
13316.1515.22510.924891
13414.7513.88540.864575
13514.814.5090.290971
13612.4512.5187-0.0687477
13712.659.641333.00867
13817.3518.6395-1.2895
1398.67.423851.17615
14018.417.55150.848478
14116.116.2914-0.191439
14211.69.319392.28061
14317.7517.95-0.199969
14415.2512.1783.07203
14517.6518.1119-0.461919
14616.3516.02280.327171
14717.6518.1905-0.540489
14813.613.57780.0221634
14914.3514.8836-0.533638
15014.7512.99321.75684
15118.2525.1454-6.89541
1529.99.263820.636179
1531613.88822.11178
15418.2519.4091-1.15907
15516.8514.87231.97765
15614.615.2081-0.608074
15713.8512.8920.957962
15818.9517.74741.20262
15915.617.7306-2.13062
16014.8516.4335-1.58348
16111.7510.44091.3091
16218.4516.42822.02183
16315.917.3638-1.46377
16417.19.718727.38128
16516.115.91460.185368
16619.919.50430.395652
16710.959.434471.51553
16818.4516.72091.72909
16915.114.89920.20077
1701517.5135-2.51351
17111.3510.07251.27751
17215.9513.5542.39596
17318.120.522-2.422
17414.615.3076-0.707643
17515.416.0713-0.671313
17615.413.00182.3982
17717.619.0295-1.4295
17813.3511.36971.98028
17919.120.8949-1.79492
18015.3517.8043-2.4543
1817.69.68004-2.08004
18213.415.529-2.12899
18313.911.62192.27814
18419.119.09460.00540225
18515.2518.2847-3.03467
18612.912.48930.410658
18716.113.21072.88931
18817.3519.4708-2.1208
18913.1515.1065-1.95654
19012.1511.85380.296236
19112.614.7668-2.16685
19210.359.555760.794236
19315.418.2442-2.84416
1949.66.197023.40298
19518.218.02150.178523
19613.612.17521.42483
19714.8517.2838-2.43378
19814.7514.07920.670787
19914.112.06582.0342
20014.914.06070.839336
20116.2515.94810.301942
20219.2518.35710.892907
20313.615.6232-2.02319
20413.613.6279-0.0278953
20515.6516.2932-0.643228
20612.7510.34272.40733
20714.615.4743-0.874341
2089.858.978780.871216
20912.6510.38442.26562
21019.217.38891.81113
21116.617.1008-0.500758
21211.211.2618-0.0617553
21315.2517.6611-2.41114
21411.911.39840.501613
21513.214.4349-1.23489
21616.3516.9462-0.596236
21712.410.97341.42656
21815.8514.33231.51771
21918.1519.3966-1.2466
22011.1511.6762-0.52619
22115.6513.4212.22902
22217.7520.6921-2.94208
2237.658.75208-1.10208
22412.3510.23542.11456
22515.613.80591.7941
22619.315.25214.04793
22715.212.98412.21588
22817.114.87942.22065
22915.612.89132.70872
23018.415.70042.69961
23119.0516.53072.51935
23218.5516.81591.73412
23319.119.2651-0.165128
23413.116.1743-3.07431
23512.8515.3232-2.47319
2369.515.6862-6.18622
2374.53.279231.22077
23811.8513.184-1.33399
23913.614.1817-0.581722
24011.712.266-0.566024
24112.413.5976-1.19755
24213.3514.2184-0.868388
24311.410.7840.616024
24414.914.16120.738762
24519.922.0571-2.15714
24611.211.9839-0.783916
24714.615.4215-0.821487
24817.616.98460.61541
24914.0513.69550.354524
25016.116.8834-0.783417
25113.3515.9417-2.59172
25211.8513.0677-1.21774
25311.9511.71890.231079
25414.7513.31411.43591
25515.1517.9497-2.79972
25613.212.47820.721827
25716.8521.1492-4.2992
2587.8512.5757-4.72575
2597.710.0638-2.36378
26012.619.4822-6.88223
2617.857.978-0.127995
26210.9512.6511-1.70113
26312.3515.5784-3.22837
2649.958.944111.00589
26514.912.85032.04968
26616.6516.1350.514989
26713.412.71480.685193
26813.9512.48481.46521
26915.714.22111.47893
27016.8517.9532-1.10317
27110.9510.35850.591505
27215.3515.8341-0.484131
27312.210.99291.20714
27415.113.41921.68083
27517.7517.60090.149117
27615.215.262-0.0620108
27714.613.79270.807276
27816.6518.5609-1.91093
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.6971510.6056980.302849
170.6054730.7890540.394527
180.5072170.9855660.492783
190.3786640.7573280.621336
200.3011610.6023210.698839
210.2130010.4260010.786999
220.162120.3242410.83788
230.2026350.4052690.797365
240.2237480.4474960.776252
250.3110830.6221670.688917
260.2432270.4864540.756773
270.1865930.3731850.813407
280.1399290.2798580.860071
290.1052140.2104290.894786
300.100360.2007190.89964
310.1543750.3087510.845625
320.1426080.2852160.857392
330.1608790.3217580.839121
340.1278860.2557720.872114
350.09831370.1966270.901686
360.1305320.2610640.869468
370.1475820.2951640.852418
380.1620340.3240690.837966
390.1486830.2973650.851317
400.121020.242040.87898
410.1515740.3031480.848426
420.1454870.2909740.854513
430.1386330.2772650.861367
440.1186420.2372830.881358
450.1035150.2070310.896485
460.08155480.163110.918445
470.08347480.166950.916525
480.08409170.1681830.915908
490.1361060.2722130.863894
500.1526950.305390.847305
510.1248030.2496060.875197
520.1438220.2876440.856178
530.1306460.2612910.869354
540.1072480.2144960.892752
550.2038860.4077730.796114
560.1710770.3421540.828923
570.5266860.9466290.473314
580.5693040.8613920.430696
590.5433540.9132910.456646
600.5370470.9259060.462953
610.5556790.8886410.444321
620.549530.900940.45047
630.6712130.6575740.328787
640.7397180.5205630.260282
650.7607070.4785850.239293
660.736180.527640.26382
670.7108830.5782330.289117
680.6767570.6464870.323243
690.7368520.5262960.263148
700.7121210.5757580.287879
710.6752450.649510.324755
720.6569870.6860260.343013
730.6390920.7218150.360908
740.6885160.6229690.311484
750.672870.6542590.32713
760.6473470.7053050.352653
770.6269260.7461480.373074
780.6233940.7532130.376606
790.5844510.8310970.415549
800.5933340.8133330.406666
810.554190.8916190.44581
820.574730.8505410.42527
830.5356140.9287710.464386
840.7392550.5214910.260745
850.7311330.5377340.268867
860.6996240.6007510.300376
870.6784640.6430720.321536
880.6726610.6546790.327339
890.658110.6837810.34189
900.6542890.6914210.345711
910.6616950.6766110.338305
920.7873630.4252730.212637
930.7736570.4526870.226343
940.7559140.4881720.244086
950.7549730.4900540.245027
960.7342470.5315070.265753
970.7684390.4631210.231561
980.7595960.4808080.240404
990.7970810.4058370.202919
1000.8033060.3933870.196694
1010.7843920.4312160.215608
1020.7561940.4876120.243806
1030.7397430.5205150.260257
1040.7258660.5482680.274134
1050.7779730.4440530.222027
1060.7654590.4690820.234541
1070.8175940.3648130.182406
1080.89270.21460.1073
1090.8859540.2280930.114046
1100.8751470.2497060.124853
1110.8596260.2807490.140374
1120.8435080.3129830.156492
1130.8936380.2127230.106362
1140.8772780.2454430.122722
1150.905830.188340.0941699
1160.8971140.2057720.102886
1170.8863060.2273890.113694
1180.8834210.2331570.116579
1190.8986610.2026770.101339
1200.884960.2300810.11504
1210.9056670.1886660.0943329
1220.9165430.1669130.0834566
1230.9081480.1837040.091852
1240.9512460.09750820.0487541
1250.9572510.08549710.0427486
1260.9495960.1008070.0504036
1270.9419040.1161930.0580965
1280.9311710.1376570.0688286
1290.9298090.1403820.0701909
1300.9199230.1601550.0800775
1310.9096750.180650.090325
1320.9078820.1842350.0921176
1330.8950780.2098440.104922
1340.880110.2397810.11989
1350.8628870.2742270.137113
1360.8423390.3153220.157661
1370.8587110.2825790.141289
1380.8448410.3103180.155159
1390.8273540.3452920.172646
1400.8067760.3864490.193224
1410.7866480.4267040.213352
1420.78770.42460.2123
1430.7623430.4753130.237657
1440.7878580.4242840.212142
1450.7635110.4729790.236489
1460.735630.528740.26437
1470.709040.5819210.29096
1480.6775760.6448480.322424
1490.6472540.7054920.352746
1500.6344290.7311430.365571
1510.8786780.2426430.121322
1520.8617510.2764980.138249
1530.8628330.2743350.137167
1540.8478750.3042490.152125
1550.8394150.3211690.160585
1560.8195820.3608360.180418
1570.7994860.4010270.200514
1580.7811690.4376620.218831
1590.7881240.4237530.211876
1600.7744180.4511650.225582
1610.7555610.4888790.244439
1620.7496760.5006470.250324
1630.7403380.5193230.259662
1640.9745950.05081010.025405
1650.9691040.06179280.0308964
1660.9639930.07201420.0360071
1670.9594910.08101840.0405092
1680.9597370.08052530.0402627
1690.9511920.09761670.0488083
1700.9595420.08091520.0404576
1710.9542630.09147430.0457371
1720.9547490.09050210.045251
1730.9540530.09189350.0459468
1740.945310.109380.05469
1750.9350860.1298270.0649136
1760.9408010.1183990.0591995
1770.9318950.1362110.0681055
1780.9285470.1429070.0714534
1790.9213090.1573820.0786909
1800.9169210.1661580.0830788
1810.9263280.1473430.0736715
1820.9278620.1442770.0721383
1830.9308060.1383880.0691938
1840.9183840.1632320.0816159
1850.9220990.1558030.0779014
1860.90750.1850010.0925004
1870.9185020.1629960.0814982
1880.9216350.1567290.0783647
1890.9210410.1579190.0789594
1900.9077720.1844550.0922276
1910.9055950.1888110.0944053
1920.8894780.2210430.110522
1930.905790.188420.09421
1940.9177040.1645910.0822955
1950.9025870.1948250.0974126
1960.8956140.2087720.104386
1970.9059770.1880450.0940225
1980.8887520.2224970.111248
1990.8793640.2412730.120636
2000.8583790.2832420.141621
2010.8455540.3088930.154446
2020.8217780.3564440.178222
2030.8277380.3445230.172262
2040.8005110.3989780.199489
2050.7776780.4446430.222322
2060.7841330.4317330.215867
2070.7965380.4069240.203462
2080.7744040.4511920.225596
2090.7611610.4776790.238839
2100.772180.4556390.22782
2110.7404490.5191020.259551
2120.7040380.5919240.295962
2130.6997110.6005790.300289
2140.6624470.6751070.337553
2150.6566390.6867220.343361
2160.6186910.7626190.381309
2170.6209070.7581860.379093
2180.5871620.8256760.412838
2190.5476020.9047960.452398
2200.5103280.9793450.489672
2210.5057540.9884920.494246
2220.5957960.8084070.404204
2230.5608190.8783610.439181
2240.7010060.5979890.298994
2250.6725120.6549760.327488
2260.7379590.5240810.262041
2270.738210.523580.26179
2280.7728620.4542750.227138
2290.8376170.3247660.162383
2300.8632190.2735620.136781
2310.8612310.2775380.138769
2320.8444130.3111730.155587
2330.8245010.3509980.175499
2340.8092340.3815310.190766
2350.7841520.4316960.215848
2360.8360390.3279220.163961
2370.8059730.3880540.194027
2380.7650220.4699560.234978
2390.7362480.5275040.263752
2400.6853690.6292620.314631
2410.6532690.6934610.346731
2420.5951770.8096460.404823
2430.5583480.8833040.441652
2440.4959210.9918430.504079
2450.4478720.8957440.552128
2460.3887650.777530.611235
2470.3339630.6679250.666037
2480.4489460.8978920.551054
2490.3804550.760910.619545
2500.3418590.6837170.658141
2510.2924280.5848570.707572
2520.2616590.5233170.738341
2530.2368550.473710.763145
2540.382370.764740.61763
2550.3568130.7136260.643187
2560.2876060.5752110.712394
2570.3453920.6907850.654608
2580.2655080.5310160.734492
2590.2412820.4825650.758718
2600.7873310.4253380.212669
2610.6592460.6815080.340754
2620.7573250.485350.242675
2630.7553840.4892310.244616

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
16 & 0.697151 & 0.605698 & 0.302849 \tabularnewline
17 & 0.605473 & 0.789054 & 0.394527 \tabularnewline
18 & 0.507217 & 0.985566 & 0.492783 \tabularnewline
19 & 0.378664 & 0.757328 & 0.621336 \tabularnewline
20 & 0.301161 & 0.602321 & 0.698839 \tabularnewline
21 & 0.213001 & 0.426001 & 0.786999 \tabularnewline
22 & 0.16212 & 0.324241 & 0.83788 \tabularnewline
23 & 0.202635 & 0.405269 & 0.797365 \tabularnewline
24 & 0.223748 & 0.447496 & 0.776252 \tabularnewline
25 & 0.311083 & 0.622167 & 0.688917 \tabularnewline
26 & 0.243227 & 0.486454 & 0.756773 \tabularnewline
27 & 0.186593 & 0.373185 & 0.813407 \tabularnewline
28 & 0.139929 & 0.279858 & 0.860071 \tabularnewline
29 & 0.105214 & 0.210429 & 0.894786 \tabularnewline
30 & 0.10036 & 0.200719 & 0.89964 \tabularnewline
31 & 0.154375 & 0.308751 & 0.845625 \tabularnewline
32 & 0.142608 & 0.285216 & 0.857392 \tabularnewline
33 & 0.160879 & 0.321758 & 0.839121 \tabularnewline
34 & 0.127886 & 0.255772 & 0.872114 \tabularnewline
35 & 0.0983137 & 0.196627 & 0.901686 \tabularnewline
36 & 0.130532 & 0.261064 & 0.869468 \tabularnewline
37 & 0.147582 & 0.295164 & 0.852418 \tabularnewline
38 & 0.162034 & 0.324069 & 0.837966 \tabularnewline
39 & 0.148683 & 0.297365 & 0.851317 \tabularnewline
40 & 0.12102 & 0.24204 & 0.87898 \tabularnewline
41 & 0.151574 & 0.303148 & 0.848426 \tabularnewline
42 & 0.145487 & 0.290974 & 0.854513 \tabularnewline
43 & 0.138633 & 0.277265 & 0.861367 \tabularnewline
44 & 0.118642 & 0.237283 & 0.881358 \tabularnewline
45 & 0.103515 & 0.207031 & 0.896485 \tabularnewline
46 & 0.0815548 & 0.16311 & 0.918445 \tabularnewline
47 & 0.0834748 & 0.16695 & 0.916525 \tabularnewline
48 & 0.0840917 & 0.168183 & 0.915908 \tabularnewline
49 & 0.136106 & 0.272213 & 0.863894 \tabularnewline
50 & 0.152695 & 0.30539 & 0.847305 \tabularnewline
51 & 0.124803 & 0.249606 & 0.875197 \tabularnewline
52 & 0.143822 & 0.287644 & 0.856178 \tabularnewline
53 & 0.130646 & 0.261291 & 0.869354 \tabularnewline
54 & 0.107248 & 0.214496 & 0.892752 \tabularnewline
55 & 0.203886 & 0.407773 & 0.796114 \tabularnewline
56 & 0.171077 & 0.342154 & 0.828923 \tabularnewline
57 & 0.526686 & 0.946629 & 0.473314 \tabularnewline
58 & 0.569304 & 0.861392 & 0.430696 \tabularnewline
59 & 0.543354 & 0.913291 & 0.456646 \tabularnewline
60 & 0.537047 & 0.925906 & 0.462953 \tabularnewline
61 & 0.555679 & 0.888641 & 0.444321 \tabularnewline
62 & 0.54953 & 0.90094 & 0.45047 \tabularnewline
63 & 0.671213 & 0.657574 & 0.328787 \tabularnewline
64 & 0.739718 & 0.520563 & 0.260282 \tabularnewline
65 & 0.760707 & 0.478585 & 0.239293 \tabularnewline
66 & 0.73618 & 0.52764 & 0.26382 \tabularnewline
67 & 0.710883 & 0.578233 & 0.289117 \tabularnewline
68 & 0.676757 & 0.646487 & 0.323243 \tabularnewline
69 & 0.736852 & 0.526296 & 0.263148 \tabularnewline
70 & 0.712121 & 0.575758 & 0.287879 \tabularnewline
71 & 0.675245 & 0.64951 & 0.324755 \tabularnewline
72 & 0.656987 & 0.686026 & 0.343013 \tabularnewline
73 & 0.639092 & 0.721815 & 0.360908 \tabularnewline
74 & 0.688516 & 0.622969 & 0.311484 \tabularnewline
75 & 0.67287 & 0.654259 & 0.32713 \tabularnewline
76 & 0.647347 & 0.705305 & 0.352653 \tabularnewline
77 & 0.626926 & 0.746148 & 0.373074 \tabularnewline
78 & 0.623394 & 0.753213 & 0.376606 \tabularnewline
79 & 0.584451 & 0.831097 & 0.415549 \tabularnewline
80 & 0.593334 & 0.813333 & 0.406666 \tabularnewline
81 & 0.55419 & 0.891619 & 0.44581 \tabularnewline
82 & 0.57473 & 0.850541 & 0.42527 \tabularnewline
83 & 0.535614 & 0.928771 & 0.464386 \tabularnewline
84 & 0.739255 & 0.521491 & 0.260745 \tabularnewline
85 & 0.731133 & 0.537734 & 0.268867 \tabularnewline
86 & 0.699624 & 0.600751 & 0.300376 \tabularnewline
87 & 0.678464 & 0.643072 & 0.321536 \tabularnewline
88 & 0.672661 & 0.654679 & 0.327339 \tabularnewline
89 & 0.65811 & 0.683781 & 0.34189 \tabularnewline
90 & 0.654289 & 0.691421 & 0.345711 \tabularnewline
91 & 0.661695 & 0.676611 & 0.338305 \tabularnewline
92 & 0.787363 & 0.425273 & 0.212637 \tabularnewline
93 & 0.773657 & 0.452687 & 0.226343 \tabularnewline
94 & 0.755914 & 0.488172 & 0.244086 \tabularnewline
95 & 0.754973 & 0.490054 & 0.245027 \tabularnewline
96 & 0.734247 & 0.531507 & 0.265753 \tabularnewline
97 & 0.768439 & 0.463121 & 0.231561 \tabularnewline
98 & 0.759596 & 0.480808 & 0.240404 \tabularnewline
99 & 0.797081 & 0.405837 & 0.202919 \tabularnewline
100 & 0.803306 & 0.393387 & 0.196694 \tabularnewline
101 & 0.784392 & 0.431216 & 0.215608 \tabularnewline
102 & 0.756194 & 0.487612 & 0.243806 \tabularnewline
103 & 0.739743 & 0.520515 & 0.260257 \tabularnewline
104 & 0.725866 & 0.548268 & 0.274134 \tabularnewline
105 & 0.777973 & 0.444053 & 0.222027 \tabularnewline
106 & 0.765459 & 0.469082 & 0.234541 \tabularnewline
107 & 0.817594 & 0.364813 & 0.182406 \tabularnewline
108 & 0.8927 & 0.2146 & 0.1073 \tabularnewline
109 & 0.885954 & 0.228093 & 0.114046 \tabularnewline
110 & 0.875147 & 0.249706 & 0.124853 \tabularnewline
111 & 0.859626 & 0.280749 & 0.140374 \tabularnewline
112 & 0.843508 & 0.312983 & 0.156492 \tabularnewline
113 & 0.893638 & 0.212723 & 0.106362 \tabularnewline
114 & 0.877278 & 0.245443 & 0.122722 \tabularnewline
115 & 0.90583 & 0.18834 & 0.0941699 \tabularnewline
116 & 0.897114 & 0.205772 & 0.102886 \tabularnewline
117 & 0.886306 & 0.227389 & 0.113694 \tabularnewline
118 & 0.883421 & 0.233157 & 0.116579 \tabularnewline
119 & 0.898661 & 0.202677 & 0.101339 \tabularnewline
120 & 0.88496 & 0.230081 & 0.11504 \tabularnewline
121 & 0.905667 & 0.188666 & 0.0943329 \tabularnewline
122 & 0.916543 & 0.166913 & 0.0834566 \tabularnewline
123 & 0.908148 & 0.183704 & 0.091852 \tabularnewline
124 & 0.951246 & 0.0975082 & 0.0487541 \tabularnewline
125 & 0.957251 & 0.0854971 & 0.0427486 \tabularnewline
126 & 0.949596 & 0.100807 & 0.0504036 \tabularnewline
127 & 0.941904 & 0.116193 & 0.0580965 \tabularnewline
128 & 0.931171 & 0.137657 & 0.0688286 \tabularnewline
129 & 0.929809 & 0.140382 & 0.0701909 \tabularnewline
130 & 0.919923 & 0.160155 & 0.0800775 \tabularnewline
131 & 0.909675 & 0.18065 & 0.090325 \tabularnewline
132 & 0.907882 & 0.184235 & 0.0921176 \tabularnewline
133 & 0.895078 & 0.209844 & 0.104922 \tabularnewline
134 & 0.88011 & 0.239781 & 0.11989 \tabularnewline
135 & 0.862887 & 0.274227 & 0.137113 \tabularnewline
136 & 0.842339 & 0.315322 & 0.157661 \tabularnewline
137 & 0.858711 & 0.282579 & 0.141289 \tabularnewline
138 & 0.844841 & 0.310318 & 0.155159 \tabularnewline
139 & 0.827354 & 0.345292 & 0.172646 \tabularnewline
140 & 0.806776 & 0.386449 & 0.193224 \tabularnewline
141 & 0.786648 & 0.426704 & 0.213352 \tabularnewline
142 & 0.7877 & 0.4246 & 0.2123 \tabularnewline
143 & 0.762343 & 0.475313 & 0.237657 \tabularnewline
144 & 0.787858 & 0.424284 & 0.212142 \tabularnewline
145 & 0.763511 & 0.472979 & 0.236489 \tabularnewline
146 & 0.73563 & 0.52874 & 0.26437 \tabularnewline
147 & 0.70904 & 0.581921 & 0.29096 \tabularnewline
148 & 0.677576 & 0.644848 & 0.322424 \tabularnewline
149 & 0.647254 & 0.705492 & 0.352746 \tabularnewline
150 & 0.634429 & 0.731143 & 0.365571 \tabularnewline
151 & 0.878678 & 0.242643 & 0.121322 \tabularnewline
152 & 0.861751 & 0.276498 & 0.138249 \tabularnewline
153 & 0.862833 & 0.274335 & 0.137167 \tabularnewline
154 & 0.847875 & 0.304249 & 0.152125 \tabularnewline
155 & 0.839415 & 0.321169 & 0.160585 \tabularnewline
156 & 0.819582 & 0.360836 & 0.180418 \tabularnewline
157 & 0.799486 & 0.401027 & 0.200514 \tabularnewline
158 & 0.781169 & 0.437662 & 0.218831 \tabularnewline
159 & 0.788124 & 0.423753 & 0.211876 \tabularnewline
160 & 0.774418 & 0.451165 & 0.225582 \tabularnewline
161 & 0.755561 & 0.488879 & 0.244439 \tabularnewline
162 & 0.749676 & 0.500647 & 0.250324 \tabularnewline
163 & 0.740338 & 0.519323 & 0.259662 \tabularnewline
164 & 0.974595 & 0.0508101 & 0.025405 \tabularnewline
165 & 0.969104 & 0.0617928 & 0.0308964 \tabularnewline
166 & 0.963993 & 0.0720142 & 0.0360071 \tabularnewline
167 & 0.959491 & 0.0810184 & 0.0405092 \tabularnewline
168 & 0.959737 & 0.0805253 & 0.0402627 \tabularnewline
169 & 0.951192 & 0.0976167 & 0.0488083 \tabularnewline
170 & 0.959542 & 0.0809152 & 0.0404576 \tabularnewline
171 & 0.954263 & 0.0914743 & 0.0457371 \tabularnewline
172 & 0.954749 & 0.0905021 & 0.045251 \tabularnewline
173 & 0.954053 & 0.0918935 & 0.0459468 \tabularnewline
174 & 0.94531 & 0.10938 & 0.05469 \tabularnewline
175 & 0.935086 & 0.129827 & 0.0649136 \tabularnewline
176 & 0.940801 & 0.118399 & 0.0591995 \tabularnewline
177 & 0.931895 & 0.136211 & 0.0681055 \tabularnewline
178 & 0.928547 & 0.142907 & 0.0714534 \tabularnewline
179 & 0.921309 & 0.157382 & 0.0786909 \tabularnewline
180 & 0.916921 & 0.166158 & 0.0830788 \tabularnewline
181 & 0.926328 & 0.147343 & 0.0736715 \tabularnewline
182 & 0.927862 & 0.144277 & 0.0721383 \tabularnewline
183 & 0.930806 & 0.138388 & 0.0691938 \tabularnewline
184 & 0.918384 & 0.163232 & 0.0816159 \tabularnewline
185 & 0.922099 & 0.155803 & 0.0779014 \tabularnewline
186 & 0.9075 & 0.185001 & 0.0925004 \tabularnewline
187 & 0.918502 & 0.162996 & 0.0814982 \tabularnewline
188 & 0.921635 & 0.156729 & 0.0783647 \tabularnewline
189 & 0.921041 & 0.157919 & 0.0789594 \tabularnewline
190 & 0.907772 & 0.184455 & 0.0922276 \tabularnewline
191 & 0.905595 & 0.188811 & 0.0944053 \tabularnewline
192 & 0.889478 & 0.221043 & 0.110522 \tabularnewline
193 & 0.90579 & 0.18842 & 0.09421 \tabularnewline
194 & 0.917704 & 0.164591 & 0.0822955 \tabularnewline
195 & 0.902587 & 0.194825 & 0.0974126 \tabularnewline
196 & 0.895614 & 0.208772 & 0.104386 \tabularnewline
197 & 0.905977 & 0.188045 & 0.0940225 \tabularnewline
198 & 0.888752 & 0.222497 & 0.111248 \tabularnewline
199 & 0.879364 & 0.241273 & 0.120636 \tabularnewline
200 & 0.858379 & 0.283242 & 0.141621 \tabularnewline
201 & 0.845554 & 0.308893 & 0.154446 \tabularnewline
202 & 0.821778 & 0.356444 & 0.178222 \tabularnewline
203 & 0.827738 & 0.344523 & 0.172262 \tabularnewline
204 & 0.800511 & 0.398978 & 0.199489 \tabularnewline
205 & 0.777678 & 0.444643 & 0.222322 \tabularnewline
206 & 0.784133 & 0.431733 & 0.215867 \tabularnewline
207 & 0.796538 & 0.406924 & 0.203462 \tabularnewline
208 & 0.774404 & 0.451192 & 0.225596 \tabularnewline
209 & 0.761161 & 0.477679 & 0.238839 \tabularnewline
210 & 0.77218 & 0.455639 & 0.22782 \tabularnewline
211 & 0.740449 & 0.519102 & 0.259551 \tabularnewline
212 & 0.704038 & 0.591924 & 0.295962 \tabularnewline
213 & 0.699711 & 0.600579 & 0.300289 \tabularnewline
214 & 0.662447 & 0.675107 & 0.337553 \tabularnewline
215 & 0.656639 & 0.686722 & 0.343361 \tabularnewline
216 & 0.618691 & 0.762619 & 0.381309 \tabularnewline
217 & 0.620907 & 0.758186 & 0.379093 \tabularnewline
218 & 0.587162 & 0.825676 & 0.412838 \tabularnewline
219 & 0.547602 & 0.904796 & 0.452398 \tabularnewline
220 & 0.510328 & 0.979345 & 0.489672 \tabularnewline
221 & 0.505754 & 0.988492 & 0.494246 \tabularnewline
222 & 0.595796 & 0.808407 & 0.404204 \tabularnewline
223 & 0.560819 & 0.878361 & 0.439181 \tabularnewline
224 & 0.701006 & 0.597989 & 0.298994 \tabularnewline
225 & 0.672512 & 0.654976 & 0.327488 \tabularnewline
226 & 0.737959 & 0.524081 & 0.262041 \tabularnewline
227 & 0.73821 & 0.52358 & 0.26179 \tabularnewline
228 & 0.772862 & 0.454275 & 0.227138 \tabularnewline
229 & 0.837617 & 0.324766 & 0.162383 \tabularnewline
230 & 0.863219 & 0.273562 & 0.136781 \tabularnewline
231 & 0.861231 & 0.277538 & 0.138769 \tabularnewline
232 & 0.844413 & 0.311173 & 0.155587 \tabularnewline
233 & 0.824501 & 0.350998 & 0.175499 \tabularnewline
234 & 0.809234 & 0.381531 & 0.190766 \tabularnewline
235 & 0.784152 & 0.431696 & 0.215848 \tabularnewline
236 & 0.836039 & 0.327922 & 0.163961 \tabularnewline
237 & 0.805973 & 0.388054 & 0.194027 \tabularnewline
238 & 0.765022 & 0.469956 & 0.234978 \tabularnewline
239 & 0.736248 & 0.527504 & 0.263752 \tabularnewline
240 & 0.685369 & 0.629262 & 0.314631 \tabularnewline
241 & 0.653269 & 0.693461 & 0.346731 \tabularnewline
242 & 0.595177 & 0.809646 & 0.404823 \tabularnewline
243 & 0.558348 & 0.883304 & 0.441652 \tabularnewline
244 & 0.495921 & 0.991843 & 0.504079 \tabularnewline
245 & 0.447872 & 0.895744 & 0.552128 \tabularnewline
246 & 0.388765 & 0.77753 & 0.611235 \tabularnewline
247 & 0.333963 & 0.667925 & 0.666037 \tabularnewline
248 & 0.448946 & 0.897892 & 0.551054 \tabularnewline
249 & 0.380455 & 0.76091 & 0.619545 \tabularnewline
250 & 0.341859 & 0.683717 & 0.658141 \tabularnewline
251 & 0.292428 & 0.584857 & 0.707572 \tabularnewline
252 & 0.261659 & 0.523317 & 0.738341 \tabularnewline
253 & 0.236855 & 0.47371 & 0.763145 \tabularnewline
254 & 0.38237 & 0.76474 & 0.61763 \tabularnewline
255 & 0.356813 & 0.713626 & 0.643187 \tabularnewline
256 & 0.287606 & 0.575211 & 0.712394 \tabularnewline
257 & 0.345392 & 0.690785 & 0.654608 \tabularnewline
258 & 0.265508 & 0.531016 & 0.734492 \tabularnewline
259 & 0.241282 & 0.482565 & 0.758718 \tabularnewline
260 & 0.787331 & 0.425338 & 0.212669 \tabularnewline
261 & 0.659246 & 0.681508 & 0.340754 \tabularnewline
262 & 0.757325 & 0.48535 & 0.242675 \tabularnewline
263 & 0.755384 & 0.489231 & 0.244616 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&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]0.697151[/C][C]0.605698[/C][C]0.302849[/C][/ROW]
[ROW][C]17[/C][C]0.605473[/C][C]0.789054[/C][C]0.394527[/C][/ROW]
[ROW][C]18[/C][C]0.507217[/C][C]0.985566[/C][C]0.492783[/C][/ROW]
[ROW][C]19[/C][C]0.378664[/C][C]0.757328[/C][C]0.621336[/C][/ROW]
[ROW][C]20[/C][C]0.301161[/C][C]0.602321[/C][C]0.698839[/C][/ROW]
[ROW][C]21[/C][C]0.213001[/C][C]0.426001[/C][C]0.786999[/C][/ROW]
[ROW][C]22[/C][C]0.16212[/C][C]0.324241[/C][C]0.83788[/C][/ROW]
[ROW][C]23[/C][C]0.202635[/C][C]0.405269[/C][C]0.797365[/C][/ROW]
[ROW][C]24[/C][C]0.223748[/C][C]0.447496[/C][C]0.776252[/C][/ROW]
[ROW][C]25[/C][C]0.311083[/C][C]0.622167[/C][C]0.688917[/C][/ROW]
[ROW][C]26[/C][C]0.243227[/C][C]0.486454[/C][C]0.756773[/C][/ROW]
[ROW][C]27[/C][C]0.186593[/C][C]0.373185[/C][C]0.813407[/C][/ROW]
[ROW][C]28[/C][C]0.139929[/C][C]0.279858[/C][C]0.860071[/C][/ROW]
[ROW][C]29[/C][C]0.105214[/C][C]0.210429[/C][C]0.894786[/C][/ROW]
[ROW][C]30[/C][C]0.10036[/C][C]0.200719[/C][C]0.89964[/C][/ROW]
[ROW][C]31[/C][C]0.154375[/C][C]0.308751[/C][C]0.845625[/C][/ROW]
[ROW][C]32[/C][C]0.142608[/C][C]0.285216[/C][C]0.857392[/C][/ROW]
[ROW][C]33[/C][C]0.160879[/C][C]0.321758[/C][C]0.839121[/C][/ROW]
[ROW][C]34[/C][C]0.127886[/C][C]0.255772[/C][C]0.872114[/C][/ROW]
[ROW][C]35[/C][C]0.0983137[/C][C]0.196627[/C][C]0.901686[/C][/ROW]
[ROW][C]36[/C][C]0.130532[/C][C]0.261064[/C][C]0.869468[/C][/ROW]
[ROW][C]37[/C][C]0.147582[/C][C]0.295164[/C][C]0.852418[/C][/ROW]
[ROW][C]38[/C][C]0.162034[/C][C]0.324069[/C][C]0.837966[/C][/ROW]
[ROW][C]39[/C][C]0.148683[/C][C]0.297365[/C][C]0.851317[/C][/ROW]
[ROW][C]40[/C][C]0.12102[/C][C]0.24204[/C][C]0.87898[/C][/ROW]
[ROW][C]41[/C][C]0.151574[/C][C]0.303148[/C][C]0.848426[/C][/ROW]
[ROW][C]42[/C][C]0.145487[/C][C]0.290974[/C][C]0.854513[/C][/ROW]
[ROW][C]43[/C][C]0.138633[/C][C]0.277265[/C][C]0.861367[/C][/ROW]
[ROW][C]44[/C][C]0.118642[/C][C]0.237283[/C][C]0.881358[/C][/ROW]
[ROW][C]45[/C][C]0.103515[/C][C]0.207031[/C][C]0.896485[/C][/ROW]
[ROW][C]46[/C][C]0.0815548[/C][C]0.16311[/C][C]0.918445[/C][/ROW]
[ROW][C]47[/C][C]0.0834748[/C][C]0.16695[/C][C]0.916525[/C][/ROW]
[ROW][C]48[/C][C]0.0840917[/C][C]0.168183[/C][C]0.915908[/C][/ROW]
[ROW][C]49[/C][C]0.136106[/C][C]0.272213[/C][C]0.863894[/C][/ROW]
[ROW][C]50[/C][C]0.152695[/C][C]0.30539[/C][C]0.847305[/C][/ROW]
[ROW][C]51[/C][C]0.124803[/C][C]0.249606[/C][C]0.875197[/C][/ROW]
[ROW][C]52[/C][C]0.143822[/C][C]0.287644[/C][C]0.856178[/C][/ROW]
[ROW][C]53[/C][C]0.130646[/C][C]0.261291[/C][C]0.869354[/C][/ROW]
[ROW][C]54[/C][C]0.107248[/C][C]0.214496[/C][C]0.892752[/C][/ROW]
[ROW][C]55[/C][C]0.203886[/C][C]0.407773[/C][C]0.796114[/C][/ROW]
[ROW][C]56[/C][C]0.171077[/C][C]0.342154[/C][C]0.828923[/C][/ROW]
[ROW][C]57[/C][C]0.526686[/C][C]0.946629[/C][C]0.473314[/C][/ROW]
[ROW][C]58[/C][C]0.569304[/C][C]0.861392[/C][C]0.430696[/C][/ROW]
[ROW][C]59[/C][C]0.543354[/C][C]0.913291[/C][C]0.456646[/C][/ROW]
[ROW][C]60[/C][C]0.537047[/C][C]0.925906[/C][C]0.462953[/C][/ROW]
[ROW][C]61[/C][C]0.555679[/C][C]0.888641[/C][C]0.444321[/C][/ROW]
[ROW][C]62[/C][C]0.54953[/C][C]0.90094[/C][C]0.45047[/C][/ROW]
[ROW][C]63[/C][C]0.671213[/C][C]0.657574[/C][C]0.328787[/C][/ROW]
[ROW][C]64[/C][C]0.739718[/C][C]0.520563[/C][C]0.260282[/C][/ROW]
[ROW][C]65[/C][C]0.760707[/C][C]0.478585[/C][C]0.239293[/C][/ROW]
[ROW][C]66[/C][C]0.73618[/C][C]0.52764[/C][C]0.26382[/C][/ROW]
[ROW][C]67[/C][C]0.710883[/C][C]0.578233[/C][C]0.289117[/C][/ROW]
[ROW][C]68[/C][C]0.676757[/C][C]0.646487[/C][C]0.323243[/C][/ROW]
[ROW][C]69[/C][C]0.736852[/C][C]0.526296[/C][C]0.263148[/C][/ROW]
[ROW][C]70[/C][C]0.712121[/C][C]0.575758[/C][C]0.287879[/C][/ROW]
[ROW][C]71[/C][C]0.675245[/C][C]0.64951[/C][C]0.324755[/C][/ROW]
[ROW][C]72[/C][C]0.656987[/C][C]0.686026[/C][C]0.343013[/C][/ROW]
[ROW][C]73[/C][C]0.639092[/C][C]0.721815[/C][C]0.360908[/C][/ROW]
[ROW][C]74[/C][C]0.688516[/C][C]0.622969[/C][C]0.311484[/C][/ROW]
[ROW][C]75[/C][C]0.67287[/C][C]0.654259[/C][C]0.32713[/C][/ROW]
[ROW][C]76[/C][C]0.647347[/C][C]0.705305[/C][C]0.352653[/C][/ROW]
[ROW][C]77[/C][C]0.626926[/C][C]0.746148[/C][C]0.373074[/C][/ROW]
[ROW][C]78[/C][C]0.623394[/C][C]0.753213[/C][C]0.376606[/C][/ROW]
[ROW][C]79[/C][C]0.584451[/C][C]0.831097[/C][C]0.415549[/C][/ROW]
[ROW][C]80[/C][C]0.593334[/C][C]0.813333[/C][C]0.406666[/C][/ROW]
[ROW][C]81[/C][C]0.55419[/C][C]0.891619[/C][C]0.44581[/C][/ROW]
[ROW][C]82[/C][C]0.57473[/C][C]0.850541[/C][C]0.42527[/C][/ROW]
[ROW][C]83[/C][C]0.535614[/C][C]0.928771[/C][C]0.464386[/C][/ROW]
[ROW][C]84[/C][C]0.739255[/C][C]0.521491[/C][C]0.260745[/C][/ROW]
[ROW][C]85[/C][C]0.731133[/C][C]0.537734[/C][C]0.268867[/C][/ROW]
[ROW][C]86[/C][C]0.699624[/C][C]0.600751[/C][C]0.300376[/C][/ROW]
[ROW][C]87[/C][C]0.678464[/C][C]0.643072[/C][C]0.321536[/C][/ROW]
[ROW][C]88[/C][C]0.672661[/C][C]0.654679[/C][C]0.327339[/C][/ROW]
[ROW][C]89[/C][C]0.65811[/C][C]0.683781[/C][C]0.34189[/C][/ROW]
[ROW][C]90[/C][C]0.654289[/C][C]0.691421[/C][C]0.345711[/C][/ROW]
[ROW][C]91[/C][C]0.661695[/C][C]0.676611[/C][C]0.338305[/C][/ROW]
[ROW][C]92[/C][C]0.787363[/C][C]0.425273[/C][C]0.212637[/C][/ROW]
[ROW][C]93[/C][C]0.773657[/C][C]0.452687[/C][C]0.226343[/C][/ROW]
[ROW][C]94[/C][C]0.755914[/C][C]0.488172[/C][C]0.244086[/C][/ROW]
[ROW][C]95[/C][C]0.754973[/C][C]0.490054[/C][C]0.245027[/C][/ROW]
[ROW][C]96[/C][C]0.734247[/C][C]0.531507[/C][C]0.265753[/C][/ROW]
[ROW][C]97[/C][C]0.768439[/C][C]0.463121[/C][C]0.231561[/C][/ROW]
[ROW][C]98[/C][C]0.759596[/C][C]0.480808[/C][C]0.240404[/C][/ROW]
[ROW][C]99[/C][C]0.797081[/C][C]0.405837[/C][C]0.202919[/C][/ROW]
[ROW][C]100[/C][C]0.803306[/C][C]0.393387[/C][C]0.196694[/C][/ROW]
[ROW][C]101[/C][C]0.784392[/C][C]0.431216[/C][C]0.215608[/C][/ROW]
[ROW][C]102[/C][C]0.756194[/C][C]0.487612[/C][C]0.243806[/C][/ROW]
[ROW][C]103[/C][C]0.739743[/C][C]0.520515[/C][C]0.260257[/C][/ROW]
[ROW][C]104[/C][C]0.725866[/C][C]0.548268[/C][C]0.274134[/C][/ROW]
[ROW][C]105[/C][C]0.777973[/C][C]0.444053[/C][C]0.222027[/C][/ROW]
[ROW][C]106[/C][C]0.765459[/C][C]0.469082[/C][C]0.234541[/C][/ROW]
[ROW][C]107[/C][C]0.817594[/C][C]0.364813[/C][C]0.182406[/C][/ROW]
[ROW][C]108[/C][C]0.8927[/C][C]0.2146[/C][C]0.1073[/C][/ROW]
[ROW][C]109[/C][C]0.885954[/C][C]0.228093[/C][C]0.114046[/C][/ROW]
[ROW][C]110[/C][C]0.875147[/C][C]0.249706[/C][C]0.124853[/C][/ROW]
[ROW][C]111[/C][C]0.859626[/C][C]0.280749[/C][C]0.140374[/C][/ROW]
[ROW][C]112[/C][C]0.843508[/C][C]0.312983[/C][C]0.156492[/C][/ROW]
[ROW][C]113[/C][C]0.893638[/C][C]0.212723[/C][C]0.106362[/C][/ROW]
[ROW][C]114[/C][C]0.877278[/C][C]0.245443[/C][C]0.122722[/C][/ROW]
[ROW][C]115[/C][C]0.90583[/C][C]0.18834[/C][C]0.0941699[/C][/ROW]
[ROW][C]116[/C][C]0.897114[/C][C]0.205772[/C][C]0.102886[/C][/ROW]
[ROW][C]117[/C][C]0.886306[/C][C]0.227389[/C][C]0.113694[/C][/ROW]
[ROW][C]118[/C][C]0.883421[/C][C]0.233157[/C][C]0.116579[/C][/ROW]
[ROW][C]119[/C][C]0.898661[/C][C]0.202677[/C][C]0.101339[/C][/ROW]
[ROW][C]120[/C][C]0.88496[/C][C]0.230081[/C][C]0.11504[/C][/ROW]
[ROW][C]121[/C][C]0.905667[/C][C]0.188666[/C][C]0.0943329[/C][/ROW]
[ROW][C]122[/C][C]0.916543[/C][C]0.166913[/C][C]0.0834566[/C][/ROW]
[ROW][C]123[/C][C]0.908148[/C][C]0.183704[/C][C]0.091852[/C][/ROW]
[ROW][C]124[/C][C]0.951246[/C][C]0.0975082[/C][C]0.0487541[/C][/ROW]
[ROW][C]125[/C][C]0.957251[/C][C]0.0854971[/C][C]0.0427486[/C][/ROW]
[ROW][C]126[/C][C]0.949596[/C][C]0.100807[/C][C]0.0504036[/C][/ROW]
[ROW][C]127[/C][C]0.941904[/C][C]0.116193[/C][C]0.0580965[/C][/ROW]
[ROW][C]128[/C][C]0.931171[/C][C]0.137657[/C][C]0.0688286[/C][/ROW]
[ROW][C]129[/C][C]0.929809[/C][C]0.140382[/C][C]0.0701909[/C][/ROW]
[ROW][C]130[/C][C]0.919923[/C][C]0.160155[/C][C]0.0800775[/C][/ROW]
[ROW][C]131[/C][C]0.909675[/C][C]0.18065[/C][C]0.090325[/C][/ROW]
[ROW][C]132[/C][C]0.907882[/C][C]0.184235[/C][C]0.0921176[/C][/ROW]
[ROW][C]133[/C][C]0.895078[/C][C]0.209844[/C][C]0.104922[/C][/ROW]
[ROW][C]134[/C][C]0.88011[/C][C]0.239781[/C][C]0.11989[/C][/ROW]
[ROW][C]135[/C][C]0.862887[/C][C]0.274227[/C][C]0.137113[/C][/ROW]
[ROW][C]136[/C][C]0.842339[/C][C]0.315322[/C][C]0.157661[/C][/ROW]
[ROW][C]137[/C][C]0.858711[/C][C]0.282579[/C][C]0.141289[/C][/ROW]
[ROW][C]138[/C][C]0.844841[/C][C]0.310318[/C][C]0.155159[/C][/ROW]
[ROW][C]139[/C][C]0.827354[/C][C]0.345292[/C][C]0.172646[/C][/ROW]
[ROW][C]140[/C][C]0.806776[/C][C]0.386449[/C][C]0.193224[/C][/ROW]
[ROW][C]141[/C][C]0.786648[/C][C]0.426704[/C][C]0.213352[/C][/ROW]
[ROW][C]142[/C][C]0.7877[/C][C]0.4246[/C][C]0.2123[/C][/ROW]
[ROW][C]143[/C][C]0.762343[/C][C]0.475313[/C][C]0.237657[/C][/ROW]
[ROW][C]144[/C][C]0.787858[/C][C]0.424284[/C][C]0.212142[/C][/ROW]
[ROW][C]145[/C][C]0.763511[/C][C]0.472979[/C][C]0.236489[/C][/ROW]
[ROW][C]146[/C][C]0.73563[/C][C]0.52874[/C][C]0.26437[/C][/ROW]
[ROW][C]147[/C][C]0.70904[/C][C]0.581921[/C][C]0.29096[/C][/ROW]
[ROW][C]148[/C][C]0.677576[/C][C]0.644848[/C][C]0.322424[/C][/ROW]
[ROW][C]149[/C][C]0.647254[/C][C]0.705492[/C][C]0.352746[/C][/ROW]
[ROW][C]150[/C][C]0.634429[/C][C]0.731143[/C][C]0.365571[/C][/ROW]
[ROW][C]151[/C][C]0.878678[/C][C]0.242643[/C][C]0.121322[/C][/ROW]
[ROW][C]152[/C][C]0.861751[/C][C]0.276498[/C][C]0.138249[/C][/ROW]
[ROW][C]153[/C][C]0.862833[/C][C]0.274335[/C][C]0.137167[/C][/ROW]
[ROW][C]154[/C][C]0.847875[/C][C]0.304249[/C][C]0.152125[/C][/ROW]
[ROW][C]155[/C][C]0.839415[/C][C]0.321169[/C][C]0.160585[/C][/ROW]
[ROW][C]156[/C][C]0.819582[/C][C]0.360836[/C][C]0.180418[/C][/ROW]
[ROW][C]157[/C][C]0.799486[/C][C]0.401027[/C][C]0.200514[/C][/ROW]
[ROW][C]158[/C][C]0.781169[/C][C]0.437662[/C][C]0.218831[/C][/ROW]
[ROW][C]159[/C][C]0.788124[/C][C]0.423753[/C][C]0.211876[/C][/ROW]
[ROW][C]160[/C][C]0.774418[/C][C]0.451165[/C][C]0.225582[/C][/ROW]
[ROW][C]161[/C][C]0.755561[/C][C]0.488879[/C][C]0.244439[/C][/ROW]
[ROW][C]162[/C][C]0.749676[/C][C]0.500647[/C][C]0.250324[/C][/ROW]
[ROW][C]163[/C][C]0.740338[/C][C]0.519323[/C][C]0.259662[/C][/ROW]
[ROW][C]164[/C][C]0.974595[/C][C]0.0508101[/C][C]0.025405[/C][/ROW]
[ROW][C]165[/C][C]0.969104[/C][C]0.0617928[/C][C]0.0308964[/C][/ROW]
[ROW][C]166[/C][C]0.963993[/C][C]0.0720142[/C][C]0.0360071[/C][/ROW]
[ROW][C]167[/C][C]0.959491[/C][C]0.0810184[/C][C]0.0405092[/C][/ROW]
[ROW][C]168[/C][C]0.959737[/C][C]0.0805253[/C][C]0.0402627[/C][/ROW]
[ROW][C]169[/C][C]0.951192[/C][C]0.0976167[/C][C]0.0488083[/C][/ROW]
[ROW][C]170[/C][C]0.959542[/C][C]0.0809152[/C][C]0.0404576[/C][/ROW]
[ROW][C]171[/C][C]0.954263[/C][C]0.0914743[/C][C]0.0457371[/C][/ROW]
[ROW][C]172[/C][C]0.954749[/C][C]0.0905021[/C][C]0.045251[/C][/ROW]
[ROW][C]173[/C][C]0.954053[/C][C]0.0918935[/C][C]0.0459468[/C][/ROW]
[ROW][C]174[/C][C]0.94531[/C][C]0.10938[/C][C]0.05469[/C][/ROW]
[ROW][C]175[/C][C]0.935086[/C][C]0.129827[/C][C]0.0649136[/C][/ROW]
[ROW][C]176[/C][C]0.940801[/C][C]0.118399[/C][C]0.0591995[/C][/ROW]
[ROW][C]177[/C][C]0.931895[/C][C]0.136211[/C][C]0.0681055[/C][/ROW]
[ROW][C]178[/C][C]0.928547[/C][C]0.142907[/C][C]0.0714534[/C][/ROW]
[ROW][C]179[/C][C]0.921309[/C][C]0.157382[/C][C]0.0786909[/C][/ROW]
[ROW][C]180[/C][C]0.916921[/C][C]0.166158[/C][C]0.0830788[/C][/ROW]
[ROW][C]181[/C][C]0.926328[/C][C]0.147343[/C][C]0.0736715[/C][/ROW]
[ROW][C]182[/C][C]0.927862[/C][C]0.144277[/C][C]0.0721383[/C][/ROW]
[ROW][C]183[/C][C]0.930806[/C][C]0.138388[/C][C]0.0691938[/C][/ROW]
[ROW][C]184[/C][C]0.918384[/C][C]0.163232[/C][C]0.0816159[/C][/ROW]
[ROW][C]185[/C][C]0.922099[/C][C]0.155803[/C][C]0.0779014[/C][/ROW]
[ROW][C]186[/C][C]0.9075[/C][C]0.185001[/C][C]0.0925004[/C][/ROW]
[ROW][C]187[/C][C]0.918502[/C][C]0.162996[/C][C]0.0814982[/C][/ROW]
[ROW][C]188[/C][C]0.921635[/C][C]0.156729[/C][C]0.0783647[/C][/ROW]
[ROW][C]189[/C][C]0.921041[/C][C]0.157919[/C][C]0.0789594[/C][/ROW]
[ROW][C]190[/C][C]0.907772[/C][C]0.184455[/C][C]0.0922276[/C][/ROW]
[ROW][C]191[/C][C]0.905595[/C][C]0.188811[/C][C]0.0944053[/C][/ROW]
[ROW][C]192[/C][C]0.889478[/C][C]0.221043[/C][C]0.110522[/C][/ROW]
[ROW][C]193[/C][C]0.90579[/C][C]0.18842[/C][C]0.09421[/C][/ROW]
[ROW][C]194[/C][C]0.917704[/C][C]0.164591[/C][C]0.0822955[/C][/ROW]
[ROW][C]195[/C][C]0.902587[/C][C]0.194825[/C][C]0.0974126[/C][/ROW]
[ROW][C]196[/C][C]0.895614[/C][C]0.208772[/C][C]0.104386[/C][/ROW]
[ROW][C]197[/C][C]0.905977[/C][C]0.188045[/C][C]0.0940225[/C][/ROW]
[ROW][C]198[/C][C]0.888752[/C][C]0.222497[/C][C]0.111248[/C][/ROW]
[ROW][C]199[/C][C]0.879364[/C][C]0.241273[/C][C]0.120636[/C][/ROW]
[ROW][C]200[/C][C]0.858379[/C][C]0.283242[/C][C]0.141621[/C][/ROW]
[ROW][C]201[/C][C]0.845554[/C][C]0.308893[/C][C]0.154446[/C][/ROW]
[ROW][C]202[/C][C]0.821778[/C][C]0.356444[/C][C]0.178222[/C][/ROW]
[ROW][C]203[/C][C]0.827738[/C][C]0.344523[/C][C]0.172262[/C][/ROW]
[ROW][C]204[/C][C]0.800511[/C][C]0.398978[/C][C]0.199489[/C][/ROW]
[ROW][C]205[/C][C]0.777678[/C][C]0.444643[/C][C]0.222322[/C][/ROW]
[ROW][C]206[/C][C]0.784133[/C][C]0.431733[/C][C]0.215867[/C][/ROW]
[ROW][C]207[/C][C]0.796538[/C][C]0.406924[/C][C]0.203462[/C][/ROW]
[ROW][C]208[/C][C]0.774404[/C][C]0.451192[/C][C]0.225596[/C][/ROW]
[ROW][C]209[/C][C]0.761161[/C][C]0.477679[/C][C]0.238839[/C][/ROW]
[ROW][C]210[/C][C]0.77218[/C][C]0.455639[/C][C]0.22782[/C][/ROW]
[ROW][C]211[/C][C]0.740449[/C][C]0.519102[/C][C]0.259551[/C][/ROW]
[ROW][C]212[/C][C]0.704038[/C][C]0.591924[/C][C]0.295962[/C][/ROW]
[ROW][C]213[/C][C]0.699711[/C][C]0.600579[/C][C]0.300289[/C][/ROW]
[ROW][C]214[/C][C]0.662447[/C][C]0.675107[/C][C]0.337553[/C][/ROW]
[ROW][C]215[/C][C]0.656639[/C][C]0.686722[/C][C]0.343361[/C][/ROW]
[ROW][C]216[/C][C]0.618691[/C][C]0.762619[/C][C]0.381309[/C][/ROW]
[ROW][C]217[/C][C]0.620907[/C][C]0.758186[/C][C]0.379093[/C][/ROW]
[ROW][C]218[/C][C]0.587162[/C][C]0.825676[/C][C]0.412838[/C][/ROW]
[ROW][C]219[/C][C]0.547602[/C][C]0.904796[/C][C]0.452398[/C][/ROW]
[ROW][C]220[/C][C]0.510328[/C][C]0.979345[/C][C]0.489672[/C][/ROW]
[ROW][C]221[/C][C]0.505754[/C][C]0.988492[/C][C]0.494246[/C][/ROW]
[ROW][C]222[/C][C]0.595796[/C][C]0.808407[/C][C]0.404204[/C][/ROW]
[ROW][C]223[/C][C]0.560819[/C][C]0.878361[/C][C]0.439181[/C][/ROW]
[ROW][C]224[/C][C]0.701006[/C][C]0.597989[/C][C]0.298994[/C][/ROW]
[ROW][C]225[/C][C]0.672512[/C][C]0.654976[/C][C]0.327488[/C][/ROW]
[ROW][C]226[/C][C]0.737959[/C][C]0.524081[/C][C]0.262041[/C][/ROW]
[ROW][C]227[/C][C]0.73821[/C][C]0.52358[/C][C]0.26179[/C][/ROW]
[ROW][C]228[/C][C]0.772862[/C][C]0.454275[/C][C]0.227138[/C][/ROW]
[ROW][C]229[/C][C]0.837617[/C][C]0.324766[/C][C]0.162383[/C][/ROW]
[ROW][C]230[/C][C]0.863219[/C][C]0.273562[/C][C]0.136781[/C][/ROW]
[ROW][C]231[/C][C]0.861231[/C][C]0.277538[/C][C]0.138769[/C][/ROW]
[ROW][C]232[/C][C]0.844413[/C][C]0.311173[/C][C]0.155587[/C][/ROW]
[ROW][C]233[/C][C]0.824501[/C][C]0.350998[/C][C]0.175499[/C][/ROW]
[ROW][C]234[/C][C]0.809234[/C][C]0.381531[/C][C]0.190766[/C][/ROW]
[ROW][C]235[/C][C]0.784152[/C][C]0.431696[/C][C]0.215848[/C][/ROW]
[ROW][C]236[/C][C]0.836039[/C][C]0.327922[/C][C]0.163961[/C][/ROW]
[ROW][C]237[/C][C]0.805973[/C][C]0.388054[/C][C]0.194027[/C][/ROW]
[ROW][C]238[/C][C]0.765022[/C][C]0.469956[/C][C]0.234978[/C][/ROW]
[ROW][C]239[/C][C]0.736248[/C][C]0.527504[/C][C]0.263752[/C][/ROW]
[ROW][C]240[/C][C]0.685369[/C][C]0.629262[/C][C]0.314631[/C][/ROW]
[ROW][C]241[/C][C]0.653269[/C][C]0.693461[/C][C]0.346731[/C][/ROW]
[ROW][C]242[/C][C]0.595177[/C][C]0.809646[/C][C]0.404823[/C][/ROW]
[ROW][C]243[/C][C]0.558348[/C][C]0.883304[/C][C]0.441652[/C][/ROW]
[ROW][C]244[/C][C]0.495921[/C][C]0.991843[/C][C]0.504079[/C][/ROW]
[ROW][C]245[/C][C]0.447872[/C][C]0.895744[/C][C]0.552128[/C][/ROW]
[ROW][C]246[/C][C]0.388765[/C][C]0.77753[/C][C]0.611235[/C][/ROW]
[ROW][C]247[/C][C]0.333963[/C][C]0.667925[/C][C]0.666037[/C][/ROW]
[ROW][C]248[/C][C]0.448946[/C][C]0.897892[/C][C]0.551054[/C][/ROW]
[ROW][C]249[/C][C]0.380455[/C][C]0.76091[/C][C]0.619545[/C][/ROW]
[ROW][C]250[/C][C]0.341859[/C][C]0.683717[/C][C]0.658141[/C][/ROW]
[ROW][C]251[/C][C]0.292428[/C][C]0.584857[/C][C]0.707572[/C][/ROW]
[ROW][C]252[/C][C]0.261659[/C][C]0.523317[/C][C]0.738341[/C][/ROW]
[ROW][C]253[/C][C]0.236855[/C][C]0.47371[/C][C]0.763145[/C][/ROW]
[ROW][C]254[/C][C]0.38237[/C][C]0.76474[/C][C]0.61763[/C][/ROW]
[ROW][C]255[/C][C]0.356813[/C][C]0.713626[/C][C]0.643187[/C][/ROW]
[ROW][C]256[/C][C]0.287606[/C][C]0.575211[/C][C]0.712394[/C][/ROW]
[ROW][C]257[/C][C]0.345392[/C][C]0.690785[/C][C]0.654608[/C][/ROW]
[ROW][C]258[/C][C]0.265508[/C][C]0.531016[/C][C]0.734492[/C][/ROW]
[ROW][C]259[/C][C]0.241282[/C][C]0.482565[/C][C]0.758718[/C][/ROW]
[ROW][C]260[/C][C]0.787331[/C][C]0.425338[/C][C]0.212669[/C][/ROW]
[ROW][C]261[/C][C]0.659246[/C][C]0.681508[/C][C]0.340754[/C][/ROW]
[ROW][C]262[/C][C]0.757325[/C][C]0.48535[/C][C]0.242675[/C][/ROW]
[ROW][C]263[/C][C]0.755384[/C][C]0.489231[/C][C]0.244616[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
160.6971510.6056980.302849
170.6054730.7890540.394527
180.5072170.9855660.492783
190.3786640.7573280.621336
200.3011610.6023210.698839
210.2130010.4260010.786999
220.162120.3242410.83788
230.2026350.4052690.797365
240.2237480.4474960.776252
250.3110830.6221670.688917
260.2432270.4864540.756773
270.1865930.3731850.813407
280.1399290.2798580.860071
290.1052140.2104290.894786
300.100360.2007190.89964
310.1543750.3087510.845625
320.1426080.2852160.857392
330.1608790.3217580.839121
340.1278860.2557720.872114
350.09831370.1966270.901686
360.1305320.2610640.869468
370.1475820.2951640.852418
380.1620340.3240690.837966
390.1486830.2973650.851317
400.121020.242040.87898
410.1515740.3031480.848426
420.1454870.2909740.854513
430.1386330.2772650.861367
440.1186420.2372830.881358
450.1035150.2070310.896485
460.08155480.163110.918445
470.08347480.166950.916525
480.08409170.1681830.915908
490.1361060.2722130.863894
500.1526950.305390.847305
510.1248030.2496060.875197
520.1438220.2876440.856178
530.1306460.2612910.869354
540.1072480.2144960.892752
550.2038860.4077730.796114
560.1710770.3421540.828923
570.5266860.9466290.473314
580.5693040.8613920.430696
590.5433540.9132910.456646
600.5370470.9259060.462953
610.5556790.8886410.444321
620.549530.900940.45047
630.6712130.6575740.328787
640.7397180.5205630.260282
650.7607070.4785850.239293
660.736180.527640.26382
670.7108830.5782330.289117
680.6767570.6464870.323243
690.7368520.5262960.263148
700.7121210.5757580.287879
710.6752450.649510.324755
720.6569870.6860260.343013
730.6390920.7218150.360908
740.6885160.6229690.311484
750.672870.6542590.32713
760.6473470.7053050.352653
770.6269260.7461480.373074
780.6233940.7532130.376606
790.5844510.8310970.415549
800.5933340.8133330.406666
810.554190.8916190.44581
820.574730.8505410.42527
830.5356140.9287710.464386
840.7392550.5214910.260745
850.7311330.5377340.268867
860.6996240.6007510.300376
870.6784640.6430720.321536
880.6726610.6546790.327339
890.658110.6837810.34189
900.6542890.6914210.345711
910.6616950.6766110.338305
920.7873630.4252730.212637
930.7736570.4526870.226343
940.7559140.4881720.244086
950.7549730.4900540.245027
960.7342470.5315070.265753
970.7684390.4631210.231561
980.7595960.4808080.240404
990.7970810.4058370.202919
1000.8033060.3933870.196694
1010.7843920.4312160.215608
1020.7561940.4876120.243806
1030.7397430.5205150.260257
1040.7258660.5482680.274134
1050.7779730.4440530.222027
1060.7654590.4690820.234541
1070.8175940.3648130.182406
1080.89270.21460.1073
1090.8859540.2280930.114046
1100.8751470.2497060.124853
1110.8596260.2807490.140374
1120.8435080.3129830.156492
1130.8936380.2127230.106362
1140.8772780.2454430.122722
1150.905830.188340.0941699
1160.8971140.2057720.102886
1170.8863060.2273890.113694
1180.8834210.2331570.116579
1190.8986610.2026770.101339
1200.884960.2300810.11504
1210.9056670.1886660.0943329
1220.9165430.1669130.0834566
1230.9081480.1837040.091852
1240.9512460.09750820.0487541
1250.9572510.08549710.0427486
1260.9495960.1008070.0504036
1270.9419040.1161930.0580965
1280.9311710.1376570.0688286
1290.9298090.1403820.0701909
1300.9199230.1601550.0800775
1310.9096750.180650.090325
1320.9078820.1842350.0921176
1330.8950780.2098440.104922
1340.880110.2397810.11989
1350.8628870.2742270.137113
1360.8423390.3153220.157661
1370.8587110.2825790.141289
1380.8448410.3103180.155159
1390.8273540.3452920.172646
1400.8067760.3864490.193224
1410.7866480.4267040.213352
1420.78770.42460.2123
1430.7623430.4753130.237657
1440.7878580.4242840.212142
1450.7635110.4729790.236489
1460.735630.528740.26437
1470.709040.5819210.29096
1480.6775760.6448480.322424
1490.6472540.7054920.352746
1500.6344290.7311430.365571
1510.8786780.2426430.121322
1520.8617510.2764980.138249
1530.8628330.2743350.137167
1540.8478750.3042490.152125
1550.8394150.3211690.160585
1560.8195820.3608360.180418
1570.7994860.4010270.200514
1580.7811690.4376620.218831
1590.7881240.4237530.211876
1600.7744180.4511650.225582
1610.7555610.4888790.244439
1620.7496760.5006470.250324
1630.7403380.5193230.259662
1640.9745950.05081010.025405
1650.9691040.06179280.0308964
1660.9639930.07201420.0360071
1670.9594910.08101840.0405092
1680.9597370.08052530.0402627
1690.9511920.09761670.0488083
1700.9595420.08091520.0404576
1710.9542630.09147430.0457371
1720.9547490.09050210.045251
1730.9540530.09189350.0459468
1740.945310.109380.05469
1750.9350860.1298270.0649136
1760.9408010.1183990.0591995
1770.9318950.1362110.0681055
1780.9285470.1429070.0714534
1790.9213090.1573820.0786909
1800.9169210.1661580.0830788
1810.9263280.1473430.0736715
1820.9278620.1442770.0721383
1830.9308060.1383880.0691938
1840.9183840.1632320.0816159
1850.9220990.1558030.0779014
1860.90750.1850010.0925004
1870.9185020.1629960.0814982
1880.9216350.1567290.0783647
1890.9210410.1579190.0789594
1900.9077720.1844550.0922276
1910.9055950.1888110.0944053
1920.8894780.2210430.110522
1930.905790.188420.09421
1940.9177040.1645910.0822955
1950.9025870.1948250.0974126
1960.8956140.2087720.104386
1970.9059770.1880450.0940225
1980.8887520.2224970.111248
1990.8793640.2412730.120636
2000.8583790.2832420.141621
2010.8455540.3088930.154446
2020.8217780.3564440.178222
2030.8277380.3445230.172262
2040.8005110.3989780.199489
2050.7776780.4446430.222322
2060.7841330.4317330.215867
2070.7965380.4069240.203462
2080.7744040.4511920.225596
2090.7611610.4776790.238839
2100.772180.4556390.22782
2110.7404490.5191020.259551
2120.7040380.5919240.295962
2130.6997110.6005790.300289
2140.6624470.6751070.337553
2150.6566390.6867220.343361
2160.6186910.7626190.381309
2170.6209070.7581860.379093
2180.5871620.8256760.412838
2190.5476020.9047960.452398
2200.5103280.9793450.489672
2210.5057540.9884920.494246
2220.5957960.8084070.404204
2230.5608190.8783610.439181
2240.7010060.5979890.298994
2250.6725120.6549760.327488
2260.7379590.5240810.262041
2270.738210.523580.26179
2280.7728620.4542750.227138
2290.8376170.3247660.162383
2300.8632190.2735620.136781
2310.8612310.2775380.138769
2320.8444130.3111730.155587
2330.8245010.3509980.175499
2340.8092340.3815310.190766
2350.7841520.4316960.215848
2360.8360390.3279220.163961
2370.8059730.3880540.194027
2380.7650220.4699560.234978
2390.7362480.5275040.263752
2400.6853690.6292620.314631
2410.6532690.6934610.346731
2420.5951770.8096460.404823
2430.5583480.8833040.441652
2440.4959210.9918430.504079
2450.4478720.8957440.552128
2460.3887650.777530.611235
2470.3339630.6679250.666037
2480.4489460.8978920.551054
2490.3804550.760910.619545
2500.3418590.6837170.658141
2510.2924280.5848570.707572
2520.2616590.5233170.738341
2530.2368550.473710.763145
2540.382370.764740.61763
2550.3568130.7136260.643187
2560.2876060.5752110.712394
2570.3453920.6907850.654608
2580.2655080.5310160.734492
2590.2412820.4825650.758718
2600.7873310.4253380.212669
2610.6592460.6815080.340754
2620.7573250.485350.242675
2630.7553840.4892310.244616






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level120.0483871OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 12 & 0.0483871 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268313&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]12[/C][C]0.0483871[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268313&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268313&T=6

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level120.0483871OK


Figures (Output of Computation)

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Input Parameters & R Code

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')
}