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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 17:05:39 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t14182312297fvrnxo4yg9biib.htm/, Retrieved Sun, 19 May 2024 14:33:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265514, Retrieved Sun, 19 May 2024 14:33:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 17:05:39] [18673d63f90870b9c004059cd6229007] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0 0 26 50 4 1 21 13 12 21 149 96 18 68 7.5
0 0 57 62 4 0 22 8 8 22 139 70 31 39 6
0 0 37 54 5 1 21 14 11 22 148 88 39 32 6.5
0 0 67 71 4 0 21 16 13 18 158 114 46 62 1
0 0 43 54 4 1 21 14 11 23 128 69 31 33 1
0 0 52 65 9 1 21 13 10 12 224 176 67 52 5.5
0 0 52 73 8 1 21 15 7 20 159 114 35 62 8.5
0 0 43 52 11 0 23 13 10 22 105 121 52 77 6.5
0 0 84 84 4 1 22 20 15 21 159 110 77 76 4.5
0 0 67 42 4 1 25 17 12 19 167 158 37 41 2
0 0 49 66 6 1 21 15 12 22 165 116 32 48 5
0 0 70 65 4 1 23 16 10 15 159 181 36 63 0.5
0 0 52 78 8 1 22 12 10 20 119 77 38 30 5
0 0 58 73 4 1 21 17 14 19 176 141 69 78 5
0 0 68 75 4 0 21 11 6 18 54 35 21 19 2.5
0 1 62 72 11 0 25 16 12 15 91 80 26 31 5
0 0 43 66 4 0 21 16 14 20 163 152 54 66 5.5
0 0 56 70 4 1 21 15 11 21 124 97 36 35 3.5
0 1 56 61 6 0 20 13 8 21 137 99 42 42 3
0 0 74 81 6 1 24 14 12 15 121 84 23 45 4
0 0 65 71 4 0 23 19 15 16 153 68 34 21 0.5
0 0 63 69 8 1 21 16 13 23 148 101 112 25 6.5
0 0 58 71 5 1 24 17 11 21 221 107 35 44 4.5
0 0 57 72 4 0 23 10 12 18 188 88 47 69 7.5
0 0 63 68 9 1 21 15 7 25 149 112 47 54 5.5
0 0 53 70 4 1 22 14 11 9 244 171 37 74 4
0 1 57 68 7 1 20 14 7 30 148 137 109 80 7.5
0 1 51 61 10 1 18 16 12 20 92 77 24 42 7
0 0 64 67 4 0 21 15 12 23 150 66 20 61 4
0 0 53 76 4 1 22 17 13 16 153 93 22 41 5.5
0 0 29 70 7 0 22 14 9 16 94 105 23 46 2.5
0 0 54 60 12 0 21 16 11 19 156 131 32 39 5.5
0 0 58 72 7 1 21 15 12 25 132 102 30 34 3.5
0 0 43 69 5 1 25 16 15 18 161 161 92 51 2.5
0 0 51 71 8 1 22 16 12 23 105 120 43 42 4.5
0 0 53 62 5 1 22 10 6 21 97 127 55 31 4.5
0 0 54 70 4 1 20 8 5 10 151 77 16 39 4.5
0 1 56 64 9 0 21 17 13 14 131 108 49 20 6
0 0 61 58 7 1 21 14 11 22 166 85 71 49 2.5
0 0 47 76 4 1 21 10 6 26 157 168 43 53 5
0 0 39 52 4 0 22 14 12 23 111 48 29 31 0
0 0 48 59 4 1 21 12 10 23 145 152 56 39 5
0 0 50 68 4 1 24 16 6 24 162 75 46 54 6.5
0 0 35 76 4 1 22 16 12 24 163 107 19 49 5
0 1 30 65 7 1 22 16 11 18 59 62 23 34 6
0 0 68 67 4 1 21 8 6 23 187 121 59 46 4.5
0 0 49 59 7 0 22 16 12 15 109 124 30 55 5.5
0 1 61 69 4 1 19 15 12 19 90 72 61 42 1
0 0 67 76 4 1 22 8 8 16 105 40 7 50 7.5
0 1 47 63 4 0 23 13 10 25 83 58 38 13 6
0 1 56 75 4 1 20 14 11 23 116 97 32 37 5
0 1 50 63 8 1 20 13 7 17 42 88 16 25 1
0 0 43 60 4 1 23 16 12 19 148 126 19 30 5
0 1 67 73 4 1 20 19 13 21 155 104 22 28 6.5
0 0 62 63 4 1 23 19 14 18 125 148 48 45 7
0 0 57 70 4 1 21 14 12 27 116 146 23 35 4.5
0 1 41 75 7 1 22 15 6 21 128 80 26 28 0
0 0 54 66 12 0 21 13 14 13 138 97 33 41 8.5
0 1 45 63 4 1 21 10 10 8 49 25 9 6 3.5
0 1 48 63 4 0 19 16 12 29 96 99 24 45 7.5
0 0 61 64 4 1 22 15 11 28 164 118 34 73 3.5
0 0 56 70 5 1 21 11 10 23 162 58 48 17 6
0 0 41 75 15 0 21 9 7 21 99 63 18 40 1.5
0 0 43 61 5 0 21 16 12 19 202 139 43 64 9
0 0 53 60 10 1 21 12 7 19 186 50 33 37 3.5
0 1 44 62 9 0 21 12 12 20 66 60 28 25 3.5
0 0 66 73 8 1 21 14 12 18 183 152 71 65 4
0 0 58 61 4 0 22 14 10 19 214 142 26 100 6.5
0 0 46 66 5 1 22 13 10 17 188 94 67 28 7.5
0 1 37 64 4 1 18 15 12 19 104 66 34 35 6
0 0 51 59 9 0 21 17 12 25 177 127 80 56 5
0 0 51 64 4 0 23 14 12 19 126 67 29 29 5.5
0 1 56 60 10 0 19 11 8 22 76 90 16 43 3.5
0 1 66 56 4 0 19 9 10 23 99 75 59 59 7.5
0 0 37 78 4 1 21 7 5 14 139 128 32 50 6.5
0 0 42 67 7 1 21 15 10 16 162 146 43 59 6.5
0 1 38 59 5 0 21 12 12 24 108 69 38 27 6.5
0 0 66 66 4 1 20 15 11 20 159 186 29 61 7
0 1 34 68 4 0 19 14 9 12 74 81 36 28 3.5
0 0 53 71 4 0 21 16 12 24 110 85 32 51 1.5
0 1 49 66 4 1 19 14 11 22 96 54 35 35 4
0 1 55 73 4 0 19 13 10 12 116 46 21 29 7.5
0 1 49 72 4 0 19 16 12 22 87 106 29 48 4.5
0 1 59 71 6 0 20 13 10 20 97 34 12 25 0
0 1 40 59 10 1 19 16 9 10 127 60 37 44 3.5
0 1 58 64 7 0 19 16 11 23 106 95 37 64 5.5
0 1 60 66 4 1 19 16 12 17 80 57 47 32 5
0 1 63 78 4 1 20 10 7 22 74 62 51 20 4.5
0 1 56 68 7 0 19 12 11 24 91 36 32 28 2.5
0 1 54 73 4 0 18 12 12 18 133 56 21 34 7.5
0 1 52 62 8 0 19 12 6 21 74 54 13 31 7
0 1 34 65 11 1 21 12 9 20 114 64 14 26 0
0 1 69 68 6 1 18 19 15 20 140 76 -2 58 4.5
0 1 32 65 14 1 18 14 10 22 95 98 20 23 3
0 1 48 60 5 0 19 13 11 19 98 88 24 21 1.5
0 1 67 71 4 1 21 16 12 20 121 35 11 21 3.5
0 1 58 65 8 0 20 15 12 26 126 102 23 33 2.5
0 1 57 68 9 1 24 12 12 23 98 61 24 16 5.5
0 1 42 64 4 1 22 8 11 24 95 80 14 20 8
0 1 64 74 4 1 21 10 9 21 110 49 52 37 1
0 1 58 69 5 1 21 16 11 21 70 78 15 35 5
0 1 66 76 4 1 19 16 12 19 102 90 23 33 4.5
0 1 26 68 5 0 19 10 12 8 86 45 19 27 3
0 1 61 72 4 1 20 18 14 17 130 55 35 41 3
0 1 52 67 4 1 18 12 8 20 96 96 24 40 8
0 1 51 63 7 1 19 16 10 11 102 43 39 35 2.5
0 1 55 59 10 0 19 10 9 8 100 52 29 28 7
0 1 50 73 4 0 20 14 10 15 94 60 13 32 0
0 1 60 66 5 0 21 12 9 18 52 54 8 22 1
0 1 56 62 4 0 18 11 10 18 98 51 18 44 3.5
0 1 63 69 4 0 19 15 12 19 118 51 24 27 5.5
0 1 61 66 4 0 19 7 11 19 99 38 19 17 5.5
1 0 52 51 6 1 22 16 9 23 48 41 23 12 0.5
1 0 16 56 4 1 22 16 11 22 50 146 16 45 7.5
1 0 46 67 8 1 22 16 12 21 150 182 33 37 9
1 0 56 69 5 1 20 16 12 25 154 192 32 37 9.5
1 1 52 57 4 1 19 12 7 30 109 263 37 108 8.5
1 1 55 56 17 0 20 15 12 17 68 35 14 10 7
1 0 50 55 4 1 22 14 12 27 194 439 52 68 8
1 0 59 63 4 1 21 15 12 23 158 214 75 72 10
1 0 60 67 8 0 21 16 10 23 159 341 72 143 7
1 0 52 65 4 1 21 13 15 18 67 58 15 9 8.5
1 0 44 47 7 0 21 10 10 18 147 292 29 55 9
1 0 67 76 4 0 21 17 15 23 39 85 13 17 9.5
1 0 52 64 4 1 21 15 10 19 100 200 40 37 4
1 0 55 68 5 1 21 18 15 15 111 158 19 27 6
1 0 37 64 7 1 22 16 9 20 138 199 24 37 8
1 0 54 65 4 1 24 20 15 16 101 297 121 58 5.5
1 1 72 71 4 1 21 16 12 24 131 227 93 66 9.5
1 0 51 63 7 1 22 17 13 25 101 108 36 21 7.5
1 0 48 60 11 1 20 16 12 25 114 86 23 19 7
1 0 60 68 7 1 21 15 12 19 165 302 85 78 7.5
1 0 50 72 4 0 24 13 8 19 114 148 41 35 8
1 0 63 70 4 1 25 16 9 16 111 178 46 48 7
1 0 33 61 4 1 22 16 15 19 75 120 18 27 7
1 0 67 61 4 1 21 16 12 19 82 207 35 43 6
1 0 46 62 4 1 21 17 12 23 121 157 17 30 10
1 0 54 71 4 1 22 20 15 21 32 128 4 25 2.5
1 0 59 71 6 1 23 14 11 22 150 296 28 69 9
1 0 61 51 8 0 24 17 12 19 117 323 44 72 8
1 1 33 56 23 1 20 6 6 20 71 79 10 23 6
1 0 47 70 4 1 22 16 14 20 165 70 38 13 8.5
1 0 69 73 8 1 25 15 12 3 154 146 57 61 6
1 0 52 76 6 1 22 16 12 23 126 246 23 43 9
1 0 55 68 4 0 21 16 12 23 149 196 36 51 8
1 0 41 48 7 0 21 14 11 20 145 199 22 67 9
1 0 73 52 4 0 21 16 12 15 120 127 40 36 5.5
1 0 52 60 4 0 22 16 12 16 109 153 31 44 7
1 0 50 59 4 0 22 16 12 7 132 299 11 45 5.5
1 0 51 57 10 0 21 14 12 24 172 228 38 34 9
1 0 60 79 6 1 22 14 8 17 169 190 24 36 2
1 0 56 60 5 0 23 16 8 24 114 180 37 72 8.5
1 0 56 60 5 1 21 16 12 24 156 212 37 39 9
1 0 29 59 4 1 21 15 12 19 172 269 22 43 8.5
1 1 66 62 4 0 21 16 11 25 68 130 15 25 9
1 1 66 59 5 1 19 16 10 20 89 179 2 56 7.5
1 0 73 61 5 1 21 18 11 28 167 243 43 80 10
1 0 55 71 5 1 21 15 12 23 113 190 31 40 9
1 1 64 57 5 0 19 16 13 27 115 299 29 73 7.5
1 1 40 66 4 0 18 16 12 18 78 121 45 34 6
1 1 46 63 6 0 19 16 12 28 118 137 25 72 10.5
1 1 58 69 4 0 21 17 10 21 87 305 4 42 8.5
1 0 43 58 4 1 22 14 10 19 173 157 31 61 8
1 0 61 59 4 0 22 18 11 23 2 96 -4 23 10
1 1 51 48 9 1 19 9 8 27 162 183 66 74 10.5
1 1 50 66 18 0 20 15 12 22 49 52 61 16 6.5
1 1 52 73 6 1 19 14 9 28 122 238 32 66 9.5
1 1 54 67 5 0 21 15 12 25 96 40 31 9 8.5
1 1 66 61 4 1 19 13 9 21 100 226 39 41 7.5
1 1 61 68 11 0 20 16 11 22 82 190 19 57 5
1 1 80 75 4 0 21 20 15 28 100 214 31 48 8
1 1 51 62 10 1 19 14 8 20 115 145 36 51 10
1 1 56 69 6 0 21 12 8 29 141 119 42 53 7
1 0 56 58 8 1 21 15 11 25 165 222 21 29 7.5
1 0 56 60 8 1 21 15 11 25 165 222 21 29 7.5
1 1 53 74 6 1 19 15 11 20 110 159 25 55 9.5
1 0 47 55 8 1 25 16 13 20 118 165 32 54 6
1 0 25 62 4 1 21 11 7 16 158 249 26 43 10
1 1 47 63 4 0 20 16 12 20 146 125 28 51 7
1 0 46 69 9 1 25 7 8 20 49 122 32 20 3
1 1 50 58 9 0 19 11 8 23 90 186 41 79 6
1 1 39 58 5 0 20 9 4 18 121 148 29 39 7
1 0 51 68 4 0 22 15 11 25 155 274 33 61 10
1 1 58 72 4 1 19 16 10 18 104 172 17 55 7
1 1 35 62 15 0 20 14 7 19 147 84 13 30 3.5
1 1 58 62 10 1 19 15 12 25 110 168 32 55 8
1 1 60 65 9 0 19 13 11 25 108 102 30 22 10
1 1 62 69 7 0 18 13 9 25 113 106 34 37 5.5
1 1 63 66 9 0 19 12 10 24 115 2 59 2 6
1 1 53 72 6 0 21 16 8 19 61 139 13 38 6.5
1 1 46 62 4 1 19 14 8 26 60 95 23 27 6.5
1 1 67 75 7 1 20 16 11 10 109 130 10 56 8.5
1 1 59 58 4 1 20 14 12 17 68 72 5 25 4
1 1 64 66 7 1 19 15 10 13 111 141 31 39 9.5
1 1 38 55 4 0 19 10 10 17 77 113 19 33 8
1 1 50 47 15 0 22 16 12 30 73 206 32 43 8.5
1 0 48 72 4 1 21 14 8 25 151 268 30 57 5.5
1 1 48 62 9 0 19 16 11 4 89 175 25 43 7
1 1 47 64 4 0 19 12 8 16 78 77 48 23 9
1 1 66 64 4 0 19 16 10 21 110 125 35 44 8
1 0 47 19 28 0 23 16 14 23 220 255 67 54 10
1 1 63 50 4 1 19 15 9 22 65 111 15 28 8
1 0 58 68 4 1 20 14 9 17 141 132 22 36 6
1 1 44 70 4 0 19 16 10 20 117 211 18 39 8
1 0 51 79 5 0 22 11 13 20 122 92 33 16 5
1 1 43 69 4 1 19 15 12 22 63 76 46 23 9
1 0 55 71 4 0 25 18 13 16 44 171 24 40 4.5
1 1 38 48 12 1 19 13 8 23 52 83 14 24 8.5
1 1 45 73 4 1 19 7 3 0 131 266 12 78 9.5
1 1 50 74 6 0 19 7 8 18 101 186 38 57 8.5
1 1 54 66 6 1 20 17 12 25 42 50 12 37 7.5
1 0 57 71 5 1 20 18 11 23 152 117 28 27 7.5
1 0 60 74 4 1 21 15 9 12 107 219 41 61 5
1 1 55 78 4 0 19 8 12 18 77 246 12 27 7
1 0 56 75 4 0 21 13 12 24 154 279 31 69 8
1 0 49 53 10 0 23 13 12 11 103 148 33 34 5.5
1 1 37 60 7 1 19 15 10 18 96 137 34 44 8.5
1 0 59 70 4 0 22 18 13 23 175 181 21 34 9.5
1 1 46 69 7 1 20 16 9 24 57 98 20 39 7
1 1 51 65 4 1 18 14 12 29 112 226 44 51 8
1 0 58 78 4 0 21 15 11 18 143 234 52 34 8.5
1 1 64 78 12 0 20 19 14 15 49 138 7 31 3.5
1 0 53 59 5 0 21 16 11 29 110 85 29 13 6.5
1 0 48 72 8 1 21 12 9 16 131 66 11 12 6.5
1 0 51 70 6 1 21 16 12 19 167 236 26 51 10.5
1 1 47 63 17 0 19 11 8 22 56 106 24 24 8.5
1 0 59 63 4 0 21 16 15 16 137 135 7 19 8
1 1 62 71 5 0 19 15 12 23 86 122 60 30 10
1 0 62 74 4 1 21 19 14 23 121 218 13 81 10
1 0 51 67 5 1 21 15 12 19 149 199 20 42 9.5
1 0 64 66 5 0 22 14 9 4 168 112 52 22 9
1 0 52 62 6 0 21 14 9 20 140 278 28 85 10
1 1 67 80 4 0 22 17 13 24 88 94 25 27 7.5
1 0 50 73 4 1 22 16 13 20 168 113 39 25 4.5
1 0 54 67 4 1 22 20 15 4 94 84 9 22 4.5
1 0 58 61 6 1 22 16 11 24 51 86 19 19 0.5
1 1 56 73 8 1 21 9 7 22 48 62 13 14 6.5
1 0 63 74 10 0 22 13 10 16 145 222 60 45 4.5
1 0 31 32 4 1 23 15 11 3 66 167 19 45 5.5
1 1 65 69 5 1 19 19 14 15 85 82 34 28 5
1 0 71 69 4 1 22 16 14 24 109 207 14 51 6
1 1 50 84 4 0 21 17 13 17 63 184 17 41 4
1 1 57 64 4 0 19 16 12 20 102 83 45 31 8
1 1 47 58 16 1 19 9 8 27 162 183 66 74 10.5
1 1 47 59 7 1 20 11 13 26 86 89 48 19 6.5
1 1 57 78 4 1 18 14 9 23 114 225 29 51 8
1 0 43 57 4 1 21 19 12 17 164 237 -2 73 8.5
1 0 41 60 14 0 21 13 13 20 119 102 51 24 5.5
1 0 63 68 5 1 20 14 11 22 126 221 2 61 7
1 0 63 68 5 0 20 15 11 19 132 128 24 23 5
1 0 56 73 5 1 21 15 13 24 142 91 40 14 3.5
1 0 51 69 5 1 21 14 12 19 83 198 20 54 5
1 1 50 67 7 0 19 16 12 23 94 204 19 51 9
1 1 22 60 19 1 19 17 10 15 81 158 16 62 8.5
1 0 41 65 16 0 21 12 9 27 166 138 20 36 5
1 1 59 66 4 1 19 15 10 26 110 226 40 59 9.5
1 1 56 74 4 0 19 17 13 22 64 44 27 24 3
1 0 66 81 7 1 24 15 13 22 93 196 25 26 1.5
1 1 53 72 9 0 19 10 9 18 104 83 49 54 6
1 1 42 55 5 0 19 16 11 15 105 79 39 39 0.5
1 1 52 49 14 1 20 15 12 22 49 52 61 16 6.5
1 1 54 74 4 1 19 11 8 27 88 105 19 36 7.5
1 1 44 53 16 0 19 16 12 10 95 116 67 31 4.5
1 1 62 64 10 1 19 16 12 20 102 83 45 31 8
1 1 53 65 5 1 19 16 12 17 99 196 30 42 9
1 1 50 57 6 0 19 14 9 23 63 153 8 39 7.5
1 1 36 51 4 1 19 14 12 19 76 157 19 25 8.5
1 1 76 80 4 0 20 16 12 13 109 75 52 31 7
1 1 66 67 4 0 20 16 11 27 117 106 22 38 9.5
1 1 62 70 5 1 19 18 12 23 57 58 17 31 6.5
1 1 59 74 4 1 21 14 6 16 120 75 33 17 9.5
1 1 47 75 4 0 19 20 7 25 73 74 34 22 6
1 1 55 70 5 1 19 15 10 2 91 185 22 55 8
1 1 58 69 4 0 19 16 12 26 108 265 30 62 9.5
1 1 60 65 4 0 21 16 10 20 105 131 25 51 8
1 0 44 55 5 1 22 16 12 23 117 139 38 30 8
1 1 57 71 8 0 19 12 9 22 119 196 26 49 9
1 1 45 65 15 0 19 8 3 24 31 78 13 16 5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 11 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&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]11 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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 time11 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 6.5136 + 2.68856Jaar_Bin[t] + 0.654811ID_bin[t] -0.00921518AMS.I[t] -0.0214631AMS.E[t] -0.0512372AMS.A[t] + 0.0854394gender[t] -0.159503age[t] -0.100232CONFSTATTOT[t] + 0.085662CONFSOFTTOT[t] + 0.0504291NUMERACYTOT[t] + 0.0144178LFM[t] + 0.00337379Blogs[t] -0.00164822PRH[t] + 0.0158025CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  6.5136 +  2.68856Jaar_Bin[t] +  0.654811ID_bin[t] -0.00921518AMS.I[t] -0.0214631AMS.E[t] -0.0512372AMS.A[t] +  0.0854394gender[t] -0.159503age[t] -0.100232CONFSTATTOT[t] +  0.085662CONFSOFTTOT[t] +  0.0504291NUMERACYTOT[t] +  0.0144178LFM[t] +  0.00337379Blogs[t] -0.00164822PRH[t] +  0.0158025CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  6.5136 +  2.68856Jaar_Bin[t] +  0.654811ID_bin[t] -0.00921518AMS.I[t] -0.0214631AMS.E[t] -0.0512372AMS.A[t] +  0.0854394gender[t] -0.159503age[t] -0.100232CONFSTATTOT[t] +  0.085662CONFSOFTTOT[t] +  0.0504291NUMERACYTOT[t] +  0.0144178LFM[t] +  0.00337379Blogs[t] -0.00164822PRH[t] +  0.0158025CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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
Ex[t] = + 6.5136 + 2.68856Jaar_Bin[t] + 0.654811ID_bin[t] -0.00921518AMS.I[t] -0.0214631AMS.E[t] -0.0512372AMS.A[t] + 0.0854394gender[t] -0.159503age[t] -0.100232CONFSTATTOT[t] + 0.085662CONFSOFTTOT[t] + 0.0504291NUMERACYTOT[t] + 0.0144178LFM[t] + 0.00337379Blogs[t] -0.00164822PRH[t] + 0.0158025CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)6.51362.781822.3410.01995380.00997692
Jaar_Bin2.688560.3412727.8788.80487e-144.40243e-14
ID_bin0.6548110.3809891.7190.08684370.0434219
AMS.I-0.009215180.013265-0.69470.4878560.243928
AMS.E-0.02146310.0166491-1.2890.198480.0992399
AMS.A-0.05123720.0385945-1.3280.1854690.0927343
gender0.08543940.251220.34010.7340540.367027
age-0.1595030.106392-1.4990.1350190.0675096
CONFSTATTOT-0.1002320.0591495-1.6950.09134220.0456711
CONFSOFTTOT0.0856620.07028611.2190.2240270.112014
NUMERACYTOT0.05042910.02384042.1150.0353470.0176735
LFM0.01441780.004254253.3890.0008089510.000404476
Blogs0.003373790.002879291.1720.2423610.12118
PRH-0.001648220.0071685-0.22990.8183280.409164
CH0.01580250.009206061.7170.08724190.0436209

\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) & 6.5136 & 2.78182 & 2.341 & 0.0199538 & 0.00997692 \tabularnewline
Jaar_Bin & 2.68856 & 0.341272 & 7.878 & 8.80487e-14 & 4.40243e-14 \tabularnewline
ID_bin & 0.654811 & 0.380989 & 1.719 & 0.0868437 & 0.0434219 \tabularnewline
AMS.I & -0.00921518 & 0.013265 & -0.6947 & 0.487856 & 0.243928 \tabularnewline
AMS.E & -0.0214631 & 0.0166491 & -1.289 & 0.19848 & 0.0992399 \tabularnewline
AMS.A & -0.0512372 & 0.0385945 & -1.328 & 0.185469 & 0.0927343 \tabularnewline
gender & 0.0854394 & 0.25122 & 0.3401 & 0.734054 & 0.367027 \tabularnewline
age & -0.159503 & 0.106392 & -1.499 & 0.135019 & 0.0675096 \tabularnewline
CONFSTATTOT & -0.100232 & 0.0591495 & -1.695 & 0.0913422 & 0.0456711 \tabularnewline
CONFSOFTTOT & 0.085662 & 0.0702861 & 1.219 & 0.224027 & 0.112014 \tabularnewline
NUMERACYTOT & 0.0504291 & 0.0238404 & 2.115 & 0.035347 & 0.0176735 \tabularnewline
LFM & 0.0144178 & 0.00425425 & 3.389 & 0.000808951 & 0.000404476 \tabularnewline
Blogs & 0.00337379 & 0.00287929 & 1.172 & 0.242361 & 0.12118 \tabularnewline
PRH & -0.00164822 & 0.0071685 & -0.2299 & 0.818328 & 0.409164 \tabularnewline
CH & 0.0158025 & 0.00920606 & 1.717 & 0.0872419 & 0.0436209 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&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]6.5136[/C][C]2.78182[/C][C]2.341[/C][C]0.0199538[/C][C]0.00997692[/C][/ROW]
[ROW][C]Jaar_Bin[/C][C]2.68856[/C][C]0.341272[/C][C]7.878[/C][C]8.80487e-14[/C][C]4.40243e-14[/C][/ROW]
[ROW][C]ID_bin[/C][C]0.654811[/C][C]0.380989[/C][C]1.719[/C][C]0.0868437[/C][C]0.0434219[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00921518[/C][C]0.013265[/C][C]-0.6947[/C][C]0.487856[/C][C]0.243928[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0214631[/C][C]0.0166491[/C][C]-1.289[/C][C]0.19848[/C][C]0.0992399[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0512372[/C][C]0.0385945[/C][C]-1.328[/C][C]0.185469[/C][C]0.0927343[/C][/ROW]
[ROW][C]gender[/C][C]0.0854394[/C][C]0.25122[/C][C]0.3401[/C][C]0.734054[/C][C]0.367027[/C][/ROW]
[ROW][C]age[/C][C]-0.159503[/C][C]0.106392[/C][C]-1.499[/C][C]0.135019[/C][C]0.0675096[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]-0.100232[/C][C]0.0591495[/C][C]-1.695[/C][C]0.0913422[/C][C]0.0456711[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]0.085662[/C][C]0.0702861[/C][C]1.219[/C][C]0.224027[/C][C]0.112014[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0504291[/C][C]0.0238404[/C][C]2.115[/C][C]0.035347[/C][C]0.0176735[/C][/ROW]
[ROW][C]LFM[/C][C]0.0144178[/C][C]0.00425425[/C][C]3.389[/C][C]0.000808951[/C][C]0.000404476[/C][/ROW]
[ROW][C]Blogs[/C][C]0.00337379[/C][C]0.00287929[/C][C]1.172[/C][C]0.242361[/C][C]0.12118[/C][/ROW]
[ROW][C]PRH[/C][C]-0.00164822[/C][C]0.0071685[/C][C]-0.2299[/C][C]0.818328[/C][C]0.409164[/C][/ROW]
[ROW][C]CH[/C][C]0.0158025[/C][C]0.00920606[/C][C]1.717[/C][C]0.0872419[/C][C]0.0436209[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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)6.51362.781822.3410.01995380.00997692
Jaar_Bin2.688560.3412727.8788.80487e-144.40243e-14
ID_bin0.6548110.3809891.7190.08684370.0434219
AMS.I-0.009215180.013265-0.69470.4878560.243928
AMS.E-0.02146310.0166491-1.2890.198480.0992399
AMS.A-0.05123720.0385945-1.3280.1854690.0927343
gender0.08543940.251220.34010.7340540.367027
age-0.1595030.106392-1.4990.1350190.0675096
CONFSTATTOT-0.1002320.0591495-1.6950.09134220.0456711
CONFSOFTTOT0.0856620.07028611.2190.2240270.112014
NUMERACYTOT0.05042910.02384042.1150.0353470.0176735
LFM0.01441780.004254253.3890.0008089510.000404476
Blogs0.003373790.002879291.1720.2423610.12118
PRH-0.001648220.0071685-0.22990.8183280.409164
CH0.01580250.009206061.7170.08724190.0436209






Multiple Linear Regression - Regression Statistics
Multiple R0.644211
R-squared0.415007
Adjusted R-squared0.383867
F-TEST (value)13.327
F-TEST (DF numerator)14
F-TEST (DF denominator)263
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.98875
Sum Squared Residuals1040.2

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.644211 \tabularnewline
R-squared & 0.415007 \tabularnewline
Adjusted R-squared & 0.383867 \tabularnewline
F-TEST (value) & 13.327 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 263 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.98875 \tabularnewline
Sum Squared Residuals & 1040.2 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.644211[/C][/ROW]
[ROW][C]R-squared[/C][C]0.415007[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.383867[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]13.327[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]263[/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]1.98875[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1040.2[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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 R0.644211
R-squared0.415007
Adjusted R-squared0.383867
F-TEST (value)13.327
F-TEST (DF numerator)14
F-TEST (DF denominator)263
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.98875
Sum Squared Residuals1040.2






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.56.032751.46725
264.741921.25808
36.55.013911.48609
414.80196-3.80196
514.73682-3.73682
65.55.60747-0.107468
78.54.497424.00258
86.54.485312.01469
94.54.384960.115039
1024.69754-2.69754
1155.18391-0.183912
120.54.534-4.034
1353.576121.42388
1455.52881-0.528811
152.52.204140.295863
1652.710152.28985
175.55.56728-0.0672764
183.54.13268-0.632679
1935.19063-2.19063
2043.125390.874613
210.53.41574-2.91574
226.54.132872.36713
234.54.93871-0.43871
247.55.523161.97684
255.54.407151.09285
2646.09035-2.09035
277.56.110211.38979
2874.734372.26563
2944.93194-0.93194
305.54.113271.38673
312.53.44931-0.949309
325.54.315191.18481
333.54.33129-0.831287
342.54.58574-2.08574
354.53.781870.718134
364.53.811550.688451
374.54.361530.138472
3864.072071.92793
392.55.06972-2.56972
4055.40007-0.400069
4104.31306-4.31306
4255.27697-0.276966
436.54.132552.36745
4455.01992-0.0199196
4563.520052.47995
464.55.58587-1.08587
475.53.918251.58175
4814.56155-3.56155
497.53.754123.74588
5063.859082.14092
5154.963620.0363765
5213.26599-2.26599
5354.425550.574453
546.54.934661.56534
5573.938123.06188
564.54.68333-0.183333
5703.98306-3.98306
588.54.097254.40275
593.53.0610.438997
607.55.414742.08526
613.55.66024-2.16024
6264.609641.39036
631.53.40682-1.90682
6495.906563.09344
653.54.69661-1.19661
663.53.95818-0.45818
6745.25839-1.25839
686.56.469260.0307449
697.54.763942.73606
7065.165020.834976
7155.28483-0.284825
725.53.832471.66753
733.54.56635-1.06635
747.55.752661.74734
756.54.635431.86457
766.54.915481.58452
776.55.135561.36444
7875.462751.53725
793.53.85628-0.356276
801.54.20724-2.70724
8144.86039-0.860394
827.54.269333.23067
834.54.79237-0.292371
8404.05405-4.05405
853.54.41533-0.915332
865.55.168680.331324
8754.104330.895671
884.53.818990.681008
892.54.57664-2.07664
907.55.370032.12997
9174.00582.9942
9204.45635-4.45635
934.55.56387-1.06387
9434.56911-1.56911
951.54.7511-3.2511
963.54.1672-0.667202
972.55.11882-2.61882
985.53.796931.70307
9985.062452.93755
10014.5992-3.5992
10153.8311.169
1024.54.419150.0808492
10334.39873-1.39873
10434.65383-1.65383
10585.052252.94775
1062.53.9546-1.4546
10774.036282.96372
10803.99759-3.99759
10913.33545-2.33545
1103.55.15808-1.65808
1115.54.614480.885525
1125.54.945910.554089
1130.55.20651-4.70651
1147.56.570420.929584
11597.296951.70305
1169.57.929361.57064
1178.510.0186-1.51857
11875.702311.29769
119810.1856-2.18564
120108.535711.46429
12179.44851-2.44851
1228.56.02762.4724
12398.767630.232374
1249.55.236164.26384
12546.82685-2.82685
12666.48149-0.481493
12787.087270.91273
1285.56.62433-1.12433
1299.58.379311.12069
1307.56.361191.13881
13176.684880.315118
1327.58.5399-1.0399
13386.131921.86808
13475.869821.13018
13576.482790.517212
13666.69125-0.691253
137107.182632.81737
1382.55.17306-2.67306
13998.098030.901967
14087.431470.568533
14166.62619-0.626189
1428.57.000091.49991
14365.946140.0538636
14497.233011.76699
14587.821520.178477
14698.417970.582032
1475.56.70109-1.20109
14876.684210.315794
1495.57.14319-1.64319
15098.205580.794419
15126.96891-4.96891
1528.57.093151.40685
15398.032270.967728
1548.58.71279-0.212793
15596.752182.24782
1567.57.81136-0.311363
157108.670941.32906
15897.18671.8133
1597.59.40113-1.90113
16067.32368-1.32368
16110.58.839241.66076
1628.57.439171.06083
16388.28081-0.280814
164104.680435.31957
16510.510.1090.391003
1666.55.535420.964578
1679.58.890310.609691
1688.56.710951.78905
1697.58.10428-0.60428
17057.22239-2.22239
17187.5190.480997
172107.783262.21674
17378.35063-1.35063
1747.58.01833-0.51833
1757.57.9754-0.475404
1769.57.925461.57454
17766.85358-0.853579
178108.230681.76932
17978.39598-1.39598
18035.30767-2.30767
18168.50822-2.50822
18277.96713-0.967128
183108.326941.67306
18477.70857-0.708567
1853.57.25511-3.75511
18688.28862-0.288623
187107.516712.48329
1885.57.81911-2.31911
18966.83144-0.831442
1906.56.133480.366523
1916.57.11983-0.619829
1928.56.887991.61201
19346.85098-2.85098
1949.57.196852.30315
19587.783980.216015
1968.57.421181.07882
1975.58.22074-2.72074
19876.644420.355582
19996.77282.2272
20087.596840.403158
201108.788591.21141
20287.15950.8405
20367.1345-1.1345
20487.960450.0395547
20556.55879-1.55879
20696.915962.08404
2074.54.89905-0.399052
2088.56.844681.65532
2099.58.279751.22025
2108.58.283190.216811
2117.56.454611.04539
2127.57.056930.443068
21356.64247-1.64247
21477.92133-0.921328
21588.65799-0.657992
2165.56.17902-0.679022
2178.57.670890.829108
2189.57.547771.95223
21976.602150.397846
22089.19914-1.19914
2218.57.088351.41165
2223.55.48985-1.98985
2236.56.67305-0.173054
2246.56.19840.301597
22510.58.007662.49234
2268.56.366992.13301
22786.959261.04074
228107.186052.81395
229107.766812.23319
2309.57.706841.79316
23196.0622.938
232108.365031.63497
2337.56.399811.10019
2344.57.1987-2.6987
2354.55.09143-0.591428
2360.55.47063-4.97063
2376.56.008110.491887
2384.56.82414-2.32414
2395.56.22647-0.726471
24056.51561-1.51561
24167.29697-1.29697
24246.45473-2.45473
24387.321720.678283
24410.59.572570.927435
2456.57.77779-1.27779
24688.35545-0.355455
2478.58.415250.084752
2485.56.64388-1.14388
24977.97268-0.972681
25056.77171-1.77171
2513.56.92906-3.42906
25256.99882-1.99882
25397.97121.0288
2548.57.011221.48878
25557.5845-2.5845
2569.58.625790.874212
25736.44218-3.44218
2581.55.84549-4.34549
25967.55994-1.55994
2600.57.43014-6.93014
2616.56.172250.327746
2627.57.72593-0.225929
2634.56.53262-2.03262
26487.053660.946343
26597.756561.24344
2667.57.390030.109968
2678.57.852570.647432
26876.353110.646892
2699.57.724621.77538
2706.56.444890.0551093
2719.56.370943.12906
27266.02811-0.0281069
27386.869461.13054
2749.58.72290.777102
27587.336490.663512
27687.087790.912215
27798.153430.84657
27855.85502-0.855017

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 6.03275 & 1.46725 \tabularnewline
2 & 6 & 4.74192 & 1.25808 \tabularnewline
3 & 6.5 & 5.01391 & 1.48609 \tabularnewline
4 & 1 & 4.80196 & -3.80196 \tabularnewline
5 & 1 & 4.73682 & -3.73682 \tabularnewline
6 & 5.5 & 5.60747 & -0.107468 \tabularnewline
7 & 8.5 & 4.49742 & 4.00258 \tabularnewline
8 & 6.5 & 4.48531 & 2.01469 \tabularnewline
9 & 4.5 & 4.38496 & 0.115039 \tabularnewline
10 & 2 & 4.69754 & -2.69754 \tabularnewline
11 & 5 & 5.18391 & -0.183912 \tabularnewline
12 & 0.5 & 4.534 & -4.034 \tabularnewline
13 & 5 & 3.57612 & 1.42388 \tabularnewline
14 & 5 & 5.52881 & -0.528811 \tabularnewline
15 & 2.5 & 2.20414 & 0.295863 \tabularnewline
16 & 5 & 2.71015 & 2.28985 \tabularnewline
17 & 5.5 & 5.56728 & -0.0672764 \tabularnewline
18 & 3.5 & 4.13268 & -0.632679 \tabularnewline
19 & 3 & 5.19063 & -2.19063 \tabularnewline
20 & 4 & 3.12539 & 0.874613 \tabularnewline
21 & 0.5 & 3.41574 & -2.91574 \tabularnewline
22 & 6.5 & 4.13287 & 2.36713 \tabularnewline
23 & 4.5 & 4.93871 & -0.43871 \tabularnewline
24 & 7.5 & 5.52316 & 1.97684 \tabularnewline
25 & 5.5 & 4.40715 & 1.09285 \tabularnewline
26 & 4 & 6.09035 & -2.09035 \tabularnewline
27 & 7.5 & 6.11021 & 1.38979 \tabularnewline
28 & 7 & 4.73437 & 2.26563 \tabularnewline
29 & 4 & 4.93194 & -0.93194 \tabularnewline
30 & 5.5 & 4.11327 & 1.38673 \tabularnewline
31 & 2.5 & 3.44931 & -0.949309 \tabularnewline
32 & 5.5 & 4.31519 & 1.18481 \tabularnewline
33 & 3.5 & 4.33129 & -0.831287 \tabularnewline
34 & 2.5 & 4.58574 & -2.08574 \tabularnewline
35 & 4.5 & 3.78187 & 0.718134 \tabularnewline
36 & 4.5 & 3.81155 & 0.688451 \tabularnewline
37 & 4.5 & 4.36153 & 0.138472 \tabularnewline
38 & 6 & 4.07207 & 1.92793 \tabularnewline
39 & 2.5 & 5.06972 & -2.56972 \tabularnewline
40 & 5 & 5.40007 & -0.400069 \tabularnewline
41 & 0 & 4.31306 & -4.31306 \tabularnewline
42 & 5 & 5.27697 & -0.276966 \tabularnewline
43 & 6.5 & 4.13255 & 2.36745 \tabularnewline
44 & 5 & 5.01992 & -0.0199196 \tabularnewline
45 & 6 & 3.52005 & 2.47995 \tabularnewline
46 & 4.5 & 5.58587 & -1.08587 \tabularnewline
47 & 5.5 & 3.91825 & 1.58175 \tabularnewline
48 & 1 & 4.56155 & -3.56155 \tabularnewline
49 & 7.5 & 3.75412 & 3.74588 \tabularnewline
50 & 6 & 3.85908 & 2.14092 \tabularnewline
51 & 5 & 4.96362 & 0.0363765 \tabularnewline
52 & 1 & 3.26599 & -2.26599 \tabularnewline
53 & 5 & 4.42555 & 0.574453 \tabularnewline
54 & 6.5 & 4.93466 & 1.56534 \tabularnewline
55 & 7 & 3.93812 & 3.06188 \tabularnewline
56 & 4.5 & 4.68333 & -0.183333 \tabularnewline
57 & 0 & 3.98306 & -3.98306 \tabularnewline
58 & 8.5 & 4.09725 & 4.40275 \tabularnewline
59 & 3.5 & 3.061 & 0.438997 \tabularnewline
60 & 7.5 & 5.41474 & 2.08526 \tabularnewline
61 & 3.5 & 5.66024 & -2.16024 \tabularnewline
62 & 6 & 4.60964 & 1.39036 \tabularnewline
63 & 1.5 & 3.40682 & -1.90682 \tabularnewline
64 & 9 & 5.90656 & 3.09344 \tabularnewline
65 & 3.5 & 4.69661 & -1.19661 \tabularnewline
66 & 3.5 & 3.95818 & -0.45818 \tabularnewline
67 & 4 & 5.25839 & -1.25839 \tabularnewline
68 & 6.5 & 6.46926 & 0.0307449 \tabularnewline
69 & 7.5 & 4.76394 & 2.73606 \tabularnewline
70 & 6 & 5.16502 & 0.834976 \tabularnewline
71 & 5 & 5.28483 & -0.284825 \tabularnewline
72 & 5.5 & 3.83247 & 1.66753 \tabularnewline
73 & 3.5 & 4.56635 & -1.06635 \tabularnewline
74 & 7.5 & 5.75266 & 1.74734 \tabularnewline
75 & 6.5 & 4.63543 & 1.86457 \tabularnewline
76 & 6.5 & 4.91548 & 1.58452 \tabularnewline
77 & 6.5 & 5.13556 & 1.36444 \tabularnewline
78 & 7 & 5.46275 & 1.53725 \tabularnewline
79 & 3.5 & 3.85628 & -0.356276 \tabularnewline
80 & 1.5 & 4.20724 & -2.70724 \tabularnewline
81 & 4 & 4.86039 & -0.860394 \tabularnewline
82 & 7.5 & 4.26933 & 3.23067 \tabularnewline
83 & 4.5 & 4.79237 & -0.292371 \tabularnewline
84 & 0 & 4.05405 & -4.05405 \tabularnewline
85 & 3.5 & 4.41533 & -0.915332 \tabularnewline
86 & 5.5 & 5.16868 & 0.331324 \tabularnewline
87 & 5 & 4.10433 & 0.895671 \tabularnewline
88 & 4.5 & 3.81899 & 0.681008 \tabularnewline
89 & 2.5 & 4.57664 & -2.07664 \tabularnewline
90 & 7.5 & 5.37003 & 2.12997 \tabularnewline
91 & 7 & 4.0058 & 2.9942 \tabularnewline
92 & 0 & 4.45635 & -4.45635 \tabularnewline
93 & 4.5 & 5.56387 & -1.06387 \tabularnewline
94 & 3 & 4.56911 & -1.56911 \tabularnewline
95 & 1.5 & 4.7511 & -3.2511 \tabularnewline
96 & 3.5 & 4.1672 & -0.667202 \tabularnewline
97 & 2.5 & 5.11882 & -2.61882 \tabularnewline
98 & 5.5 & 3.79693 & 1.70307 \tabularnewline
99 & 8 & 5.06245 & 2.93755 \tabularnewline
100 & 1 & 4.5992 & -3.5992 \tabularnewline
101 & 5 & 3.831 & 1.169 \tabularnewline
102 & 4.5 & 4.41915 & 0.0808492 \tabularnewline
103 & 3 & 4.39873 & -1.39873 \tabularnewline
104 & 3 & 4.65383 & -1.65383 \tabularnewline
105 & 8 & 5.05225 & 2.94775 \tabularnewline
106 & 2.5 & 3.9546 & -1.4546 \tabularnewline
107 & 7 & 4.03628 & 2.96372 \tabularnewline
108 & 0 & 3.99759 & -3.99759 \tabularnewline
109 & 1 & 3.33545 & -2.33545 \tabularnewline
110 & 3.5 & 5.15808 & -1.65808 \tabularnewline
111 & 5.5 & 4.61448 & 0.885525 \tabularnewline
112 & 5.5 & 4.94591 & 0.554089 \tabularnewline
113 & 0.5 & 5.20651 & -4.70651 \tabularnewline
114 & 7.5 & 6.57042 & 0.929584 \tabularnewline
115 & 9 & 7.29695 & 1.70305 \tabularnewline
116 & 9.5 & 7.92936 & 1.57064 \tabularnewline
117 & 8.5 & 10.0186 & -1.51857 \tabularnewline
118 & 7 & 5.70231 & 1.29769 \tabularnewline
119 & 8 & 10.1856 & -2.18564 \tabularnewline
120 & 10 & 8.53571 & 1.46429 \tabularnewline
121 & 7 & 9.44851 & -2.44851 \tabularnewline
122 & 8.5 & 6.0276 & 2.4724 \tabularnewline
123 & 9 & 8.76763 & 0.232374 \tabularnewline
124 & 9.5 & 5.23616 & 4.26384 \tabularnewline
125 & 4 & 6.82685 & -2.82685 \tabularnewline
126 & 6 & 6.48149 & -0.481493 \tabularnewline
127 & 8 & 7.08727 & 0.91273 \tabularnewline
128 & 5.5 & 6.62433 & -1.12433 \tabularnewline
129 & 9.5 & 8.37931 & 1.12069 \tabularnewline
130 & 7.5 & 6.36119 & 1.13881 \tabularnewline
131 & 7 & 6.68488 & 0.315118 \tabularnewline
132 & 7.5 & 8.5399 & -1.0399 \tabularnewline
133 & 8 & 6.13192 & 1.86808 \tabularnewline
134 & 7 & 5.86982 & 1.13018 \tabularnewline
135 & 7 & 6.48279 & 0.517212 \tabularnewline
136 & 6 & 6.69125 & -0.691253 \tabularnewline
137 & 10 & 7.18263 & 2.81737 \tabularnewline
138 & 2.5 & 5.17306 & -2.67306 \tabularnewline
139 & 9 & 8.09803 & 0.901967 \tabularnewline
140 & 8 & 7.43147 & 0.568533 \tabularnewline
141 & 6 & 6.62619 & -0.626189 \tabularnewline
142 & 8.5 & 7.00009 & 1.49991 \tabularnewline
143 & 6 & 5.94614 & 0.0538636 \tabularnewline
144 & 9 & 7.23301 & 1.76699 \tabularnewline
145 & 8 & 7.82152 & 0.178477 \tabularnewline
146 & 9 & 8.41797 & 0.582032 \tabularnewline
147 & 5.5 & 6.70109 & -1.20109 \tabularnewline
148 & 7 & 6.68421 & 0.315794 \tabularnewline
149 & 5.5 & 7.14319 & -1.64319 \tabularnewline
150 & 9 & 8.20558 & 0.794419 \tabularnewline
151 & 2 & 6.96891 & -4.96891 \tabularnewline
152 & 8.5 & 7.09315 & 1.40685 \tabularnewline
153 & 9 & 8.03227 & 0.967728 \tabularnewline
154 & 8.5 & 8.71279 & -0.212793 \tabularnewline
155 & 9 & 6.75218 & 2.24782 \tabularnewline
156 & 7.5 & 7.81136 & -0.311363 \tabularnewline
157 & 10 & 8.67094 & 1.32906 \tabularnewline
158 & 9 & 7.1867 & 1.8133 \tabularnewline
159 & 7.5 & 9.40113 & -1.90113 \tabularnewline
160 & 6 & 7.32368 & -1.32368 \tabularnewline
161 & 10.5 & 8.83924 & 1.66076 \tabularnewline
162 & 8.5 & 7.43917 & 1.06083 \tabularnewline
163 & 8 & 8.28081 & -0.280814 \tabularnewline
164 & 10 & 4.68043 & 5.31957 \tabularnewline
165 & 10.5 & 10.109 & 0.391003 \tabularnewline
166 & 6.5 & 5.53542 & 0.964578 \tabularnewline
167 & 9.5 & 8.89031 & 0.609691 \tabularnewline
168 & 8.5 & 6.71095 & 1.78905 \tabularnewline
169 & 7.5 & 8.10428 & -0.60428 \tabularnewline
170 & 5 & 7.22239 & -2.22239 \tabularnewline
171 & 8 & 7.519 & 0.480997 \tabularnewline
172 & 10 & 7.78326 & 2.21674 \tabularnewline
173 & 7 & 8.35063 & -1.35063 \tabularnewline
174 & 7.5 & 8.01833 & -0.51833 \tabularnewline
175 & 7.5 & 7.9754 & -0.475404 \tabularnewline
176 & 9.5 & 7.92546 & 1.57454 \tabularnewline
177 & 6 & 6.85358 & -0.853579 \tabularnewline
178 & 10 & 8.23068 & 1.76932 \tabularnewline
179 & 7 & 8.39598 & -1.39598 \tabularnewline
180 & 3 & 5.30767 & -2.30767 \tabularnewline
181 & 6 & 8.50822 & -2.50822 \tabularnewline
182 & 7 & 7.96713 & -0.967128 \tabularnewline
183 & 10 & 8.32694 & 1.67306 \tabularnewline
184 & 7 & 7.70857 & -0.708567 \tabularnewline
185 & 3.5 & 7.25511 & -3.75511 \tabularnewline
186 & 8 & 8.28862 & -0.288623 \tabularnewline
187 & 10 & 7.51671 & 2.48329 \tabularnewline
188 & 5.5 & 7.81911 & -2.31911 \tabularnewline
189 & 6 & 6.83144 & -0.831442 \tabularnewline
190 & 6.5 & 6.13348 & 0.366523 \tabularnewline
191 & 6.5 & 7.11983 & -0.619829 \tabularnewline
192 & 8.5 & 6.88799 & 1.61201 \tabularnewline
193 & 4 & 6.85098 & -2.85098 \tabularnewline
194 & 9.5 & 7.19685 & 2.30315 \tabularnewline
195 & 8 & 7.78398 & 0.216015 \tabularnewline
196 & 8.5 & 7.42118 & 1.07882 \tabularnewline
197 & 5.5 & 8.22074 & -2.72074 \tabularnewline
198 & 7 & 6.64442 & 0.355582 \tabularnewline
199 & 9 & 6.7728 & 2.2272 \tabularnewline
200 & 8 & 7.59684 & 0.403158 \tabularnewline
201 & 10 & 8.78859 & 1.21141 \tabularnewline
202 & 8 & 7.1595 & 0.8405 \tabularnewline
203 & 6 & 7.1345 & -1.1345 \tabularnewline
204 & 8 & 7.96045 & 0.0395547 \tabularnewline
205 & 5 & 6.55879 & -1.55879 \tabularnewline
206 & 9 & 6.91596 & 2.08404 \tabularnewline
207 & 4.5 & 4.89905 & -0.399052 \tabularnewline
208 & 8.5 & 6.84468 & 1.65532 \tabularnewline
209 & 9.5 & 8.27975 & 1.22025 \tabularnewline
210 & 8.5 & 8.28319 & 0.216811 \tabularnewline
211 & 7.5 & 6.45461 & 1.04539 \tabularnewline
212 & 7.5 & 7.05693 & 0.443068 \tabularnewline
213 & 5 & 6.64247 & -1.64247 \tabularnewline
214 & 7 & 7.92133 & -0.921328 \tabularnewline
215 & 8 & 8.65799 & -0.657992 \tabularnewline
216 & 5.5 & 6.17902 & -0.679022 \tabularnewline
217 & 8.5 & 7.67089 & 0.829108 \tabularnewline
218 & 9.5 & 7.54777 & 1.95223 \tabularnewline
219 & 7 & 6.60215 & 0.397846 \tabularnewline
220 & 8 & 9.19914 & -1.19914 \tabularnewline
221 & 8.5 & 7.08835 & 1.41165 \tabularnewline
222 & 3.5 & 5.48985 & -1.98985 \tabularnewline
223 & 6.5 & 6.67305 & -0.173054 \tabularnewline
224 & 6.5 & 6.1984 & 0.301597 \tabularnewline
225 & 10.5 & 8.00766 & 2.49234 \tabularnewline
226 & 8.5 & 6.36699 & 2.13301 \tabularnewline
227 & 8 & 6.95926 & 1.04074 \tabularnewline
228 & 10 & 7.18605 & 2.81395 \tabularnewline
229 & 10 & 7.76681 & 2.23319 \tabularnewline
230 & 9.5 & 7.70684 & 1.79316 \tabularnewline
231 & 9 & 6.062 & 2.938 \tabularnewline
232 & 10 & 8.36503 & 1.63497 \tabularnewline
233 & 7.5 & 6.39981 & 1.10019 \tabularnewline
234 & 4.5 & 7.1987 & -2.6987 \tabularnewline
235 & 4.5 & 5.09143 & -0.591428 \tabularnewline
236 & 0.5 & 5.47063 & -4.97063 \tabularnewline
237 & 6.5 & 6.00811 & 0.491887 \tabularnewline
238 & 4.5 & 6.82414 & -2.32414 \tabularnewline
239 & 5.5 & 6.22647 & -0.726471 \tabularnewline
240 & 5 & 6.51561 & -1.51561 \tabularnewline
241 & 6 & 7.29697 & -1.29697 \tabularnewline
242 & 4 & 6.45473 & -2.45473 \tabularnewline
243 & 8 & 7.32172 & 0.678283 \tabularnewline
244 & 10.5 & 9.57257 & 0.927435 \tabularnewline
245 & 6.5 & 7.77779 & -1.27779 \tabularnewline
246 & 8 & 8.35545 & -0.355455 \tabularnewline
247 & 8.5 & 8.41525 & 0.084752 \tabularnewline
248 & 5.5 & 6.64388 & -1.14388 \tabularnewline
249 & 7 & 7.97268 & -0.972681 \tabularnewline
250 & 5 & 6.77171 & -1.77171 \tabularnewline
251 & 3.5 & 6.92906 & -3.42906 \tabularnewline
252 & 5 & 6.99882 & -1.99882 \tabularnewline
253 & 9 & 7.9712 & 1.0288 \tabularnewline
254 & 8.5 & 7.01122 & 1.48878 \tabularnewline
255 & 5 & 7.5845 & -2.5845 \tabularnewline
256 & 9.5 & 8.62579 & 0.874212 \tabularnewline
257 & 3 & 6.44218 & -3.44218 \tabularnewline
258 & 1.5 & 5.84549 & -4.34549 \tabularnewline
259 & 6 & 7.55994 & -1.55994 \tabularnewline
260 & 0.5 & 7.43014 & -6.93014 \tabularnewline
261 & 6.5 & 6.17225 & 0.327746 \tabularnewline
262 & 7.5 & 7.72593 & -0.225929 \tabularnewline
263 & 4.5 & 6.53262 & -2.03262 \tabularnewline
264 & 8 & 7.05366 & 0.946343 \tabularnewline
265 & 9 & 7.75656 & 1.24344 \tabularnewline
266 & 7.5 & 7.39003 & 0.109968 \tabularnewline
267 & 8.5 & 7.85257 & 0.647432 \tabularnewline
268 & 7 & 6.35311 & 0.646892 \tabularnewline
269 & 9.5 & 7.72462 & 1.77538 \tabularnewline
270 & 6.5 & 6.44489 & 0.0551093 \tabularnewline
271 & 9.5 & 6.37094 & 3.12906 \tabularnewline
272 & 6 & 6.02811 & -0.0281069 \tabularnewline
273 & 8 & 6.86946 & 1.13054 \tabularnewline
274 & 9.5 & 8.7229 & 0.777102 \tabularnewline
275 & 8 & 7.33649 & 0.663512 \tabularnewline
276 & 8 & 7.08779 & 0.912215 \tabularnewline
277 & 9 & 8.15343 & 0.84657 \tabularnewline
278 & 5 & 5.85502 & -0.855017 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]6.03275[/C][C]1.46725[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]4.74192[/C][C]1.25808[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.01391[/C][C]1.48609[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]4.80196[/C][C]-3.80196[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.73682[/C][C]-3.73682[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]5.60747[/C][C]-0.107468[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]4.49742[/C][C]4.00258[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]4.48531[/C][C]2.01469[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.38496[/C][C]0.115039[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]4.69754[/C][C]-2.69754[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.18391[/C][C]-0.183912[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.534[/C][C]-4.034[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]3.57612[/C][C]1.42388[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.52881[/C][C]-0.528811[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]2.20414[/C][C]0.295863[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]2.71015[/C][C]2.28985[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]5.56728[/C][C]-0.0672764[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.13268[/C][C]-0.632679[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.19063[/C][C]-2.19063[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]3.12539[/C][C]0.874613[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]3.41574[/C][C]-2.91574[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]4.13287[/C][C]2.36713[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]4.93871[/C][C]-0.43871[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.52316[/C][C]1.97684[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]4.40715[/C][C]1.09285[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]6.09035[/C][C]-2.09035[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]6.11021[/C][C]1.38979[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]4.73437[/C][C]2.26563[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]4.93194[/C][C]-0.93194[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]4.11327[/C][C]1.38673[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]3.44931[/C][C]-0.949309[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]4.31519[/C][C]1.18481[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]4.33129[/C][C]-0.831287[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]4.58574[/C][C]-2.08574[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]3.78187[/C][C]0.718134[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]3.81155[/C][C]0.688451[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]4.36153[/C][C]0.138472[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]4.07207[/C][C]1.92793[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.06972[/C][C]-2.56972[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]5.40007[/C][C]-0.400069[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.31306[/C][C]-4.31306[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.27697[/C][C]-0.276966[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]4.13255[/C][C]2.36745[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.01992[/C][C]-0.0199196[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]3.52005[/C][C]2.47995[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.58587[/C][C]-1.08587[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]3.91825[/C][C]1.58175[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]4.56155[/C][C]-3.56155[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]3.75412[/C][C]3.74588[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]3.85908[/C][C]2.14092[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]4.96362[/C][C]0.0363765[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]3.26599[/C][C]-2.26599[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]4.42555[/C][C]0.574453[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]4.93466[/C][C]1.56534[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]3.93812[/C][C]3.06188[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]4.68333[/C][C]-0.183333[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]3.98306[/C][C]-3.98306[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]4.09725[/C][C]4.40275[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]3.061[/C][C]0.438997[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.41474[/C][C]2.08526[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.66024[/C][C]-2.16024[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.60964[/C][C]1.39036[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]3.40682[/C][C]-1.90682[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]5.90656[/C][C]3.09344[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.69661[/C][C]-1.19661[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]3.95818[/C][C]-0.45818[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]5.25839[/C][C]-1.25839[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.46926[/C][C]0.0307449[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]4.76394[/C][C]2.73606[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.16502[/C][C]0.834976[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.28483[/C][C]-0.284825[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]3.83247[/C][C]1.66753[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]4.56635[/C][C]-1.06635[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.75266[/C][C]1.74734[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]4.63543[/C][C]1.86457[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]4.91548[/C][C]1.58452[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.13556[/C][C]1.36444[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]5.46275[/C][C]1.53725[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]3.85628[/C][C]-0.356276[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]4.20724[/C][C]-2.70724[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]4.86039[/C][C]-0.860394[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]4.26933[/C][C]3.23067[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]4.79237[/C][C]-0.292371[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]4.05405[/C][C]-4.05405[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]4.41533[/C][C]-0.915332[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]5.16868[/C][C]0.331324[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]4.10433[/C][C]0.895671[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]3.81899[/C][C]0.681008[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]4.57664[/C][C]-2.07664[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]5.37003[/C][C]2.12997[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]4.0058[/C][C]2.9942[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]4.45635[/C][C]-4.45635[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]5.56387[/C][C]-1.06387[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]4.56911[/C][C]-1.56911[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]4.7511[/C][C]-3.2511[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]4.1672[/C][C]-0.667202[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]5.11882[/C][C]-2.61882[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]3.79693[/C][C]1.70307[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]5.06245[/C][C]2.93755[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]4.5992[/C][C]-3.5992[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]3.831[/C][C]1.169[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]4.41915[/C][C]0.0808492[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]4.39873[/C][C]-1.39873[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.65383[/C][C]-1.65383[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]5.05225[/C][C]2.94775[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]3.9546[/C][C]-1.4546[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]4.03628[/C][C]2.96372[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]3.99759[/C][C]-3.99759[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]3.33545[/C][C]-2.33545[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]5.15808[/C][C]-1.65808[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]4.61448[/C][C]0.885525[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.94591[/C][C]0.554089[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]5.20651[/C][C]-4.70651[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.57042[/C][C]0.929584[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]7.29695[/C][C]1.70305[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]7.92936[/C][C]1.57064[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]10.0186[/C][C]-1.51857[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]5.70231[/C][C]1.29769[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]10.1856[/C][C]-2.18564[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]8.53571[/C][C]1.46429[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]9.44851[/C][C]-2.44851[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]6.0276[/C][C]2.4724[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]8.76763[/C][C]0.232374[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]5.23616[/C][C]4.26384[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]6.82685[/C][C]-2.82685[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]6.48149[/C][C]-0.481493[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]7.08727[/C][C]0.91273[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]6.62433[/C][C]-1.12433[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]8.37931[/C][C]1.12069[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]6.36119[/C][C]1.13881[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]6.68488[/C][C]0.315118[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]8.5399[/C][C]-1.0399[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]6.13192[/C][C]1.86808[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]5.86982[/C][C]1.13018[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.48279[/C][C]0.517212[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]6.69125[/C][C]-0.691253[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]7.18263[/C][C]2.81737[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]5.17306[/C][C]-2.67306[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.09803[/C][C]0.901967[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]7.43147[/C][C]0.568533[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]6.62619[/C][C]-0.626189[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]7.00009[/C][C]1.49991[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]5.94614[/C][C]0.0538636[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]7.23301[/C][C]1.76699[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]7.82152[/C][C]0.178477[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]8.41797[/C][C]0.582032[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]6.70109[/C][C]-1.20109[/C][/ROW]
[ROW][C]148[/C][C]7[/C][C]6.68421[/C][C]0.315794[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]7.14319[/C][C]-1.64319[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]8.20558[/C][C]0.794419[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]6.96891[/C][C]-4.96891[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]7.09315[/C][C]1.40685[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]8.03227[/C][C]0.967728[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]8.71279[/C][C]-0.212793[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.75218[/C][C]2.24782[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]7.81136[/C][C]-0.311363[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]8.67094[/C][C]1.32906[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]7.1867[/C][C]1.8133[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]9.40113[/C][C]-1.90113[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]7.32368[/C][C]-1.32368[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]8.83924[/C][C]1.66076[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]7.43917[/C][C]1.06083[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]8.28081[/C][C]-0.280814[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]4.68043[/C][C]5.31957[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]10.109[/C][C]0.391003[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]5.53542[/C][C]0.964578[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]8.89031[/C][C]0.609691[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]6.71095[/C][C]1.78905[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]8.10428[/C][C]-0.60428[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]7.22239[/C][C]-2.22239[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]7.519[/C][C]0.480997[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]7.78326[/C][C]2.21674[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]8.35063[/C][C]-1.35063[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]8.01833[/C][C]-0.51833[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.9754[/C][C]-0.475404[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]7.92546[/C][C]1.57454[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.85358[/C][C]-0.853579[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.23068[/C][C]1.76932[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]8.39598[/C][C]-1.39598[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]5.30767[/C][C]-2.30767[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]8.50822[/C][C]-2.50822[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]7.96713[/C][C]-0.967128[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]8.32694[/C][C]1.67306[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]7.70857[/C][C]-0.708567[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]7.25511[/C][C]-3.75511[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]8.28862[/C][C]-0.288623[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]7.51671[/C][C]2.48329[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]7.81911[/C][C]-2.31911[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]6.83144[/C][C]-0.831442[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]6.13348[/C][C]0.366523[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]7.11983[/C][C]-0.619829[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]6.88799[/C][C]1.61201[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]6.85098[/C][C]-2.85098[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]7.19685[/C][C]2.30315[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]7.78398[/C][C]0.216015[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]7.42118[/C][C]1.07882[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]8.22074[/C][C]-2.72074[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]6.64442[/C][C]0.355582[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]6.7728[/C][C]2.2272[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]7.59684[/C][C]0.403158[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]8.78859[/C][C]1.21141[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]7.1595[/C][C]0.8405[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]7.1345[/C][C]-1.1345[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]7.96045[/C][C]0.0395547[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]6.55879[/C][C]-1.55879[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]6.91596[/C][C]2.08404[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]4.89905[/C][C]-0.399052[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]6.84468[/C][C]1.65532[/C][/ROW]
[ROW][C]209[/C][C]9.5[/C][C]8.27975[/C][C]1.22025[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]8.28319[/C][C]0.216811[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]6.45461[/C][C]1.04539[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.05693[/C][C]0.443068[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]6.64247[/C][C]-1.64247[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]7.92133[/C][C]-0.921328[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]8.65799[/C][C]-0.657992[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.17902[/C][C]-0.679022[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]7.67089[/C][C]0.829108[/C][/ROW]
[ROW][C]218[/C][C]9.5[/C][C]7.54777[/C][C]1.95223[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]6.60215[/C][C]0.397846[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]9.19914[/C][C]-1.19914[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]7.08835[/C][C]1.41165[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]5.48985[/C][C]-1.98985[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]6.67305[/C][C]-0.173054[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]6.1984[/C][C]0.301597[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]8.00766[/C][C]2.49234[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]6.36699[/C][C]2.13301[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]6.95926[/C][C]1.04074[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]7.18605[/C][C]2.81395[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.76681[/C][C]2.23319[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]7.70684[/C][C]1.79316[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]6.062[/C][C]2.938[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.36503[/C][C]1.63497[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]6.39981[/C][C]1.10019[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]7.1987[/C][C]-2.6987[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.09143[/C][C]-0.591428[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]5.47063[/C][C]-4.97063[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]6.00811[/C][C]0.491887[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]6.82414[/C][C]-2.32414[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]6.22647[/C][C]-0.726471[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]6.51561[/C][C]-1.51561[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]7.29697[/C][C]-1.29697[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]6.45473[/C][C]-2.45473[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]7.32172[/C][C]0.678283[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]9.57257[/C][C]0.927435[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]7.77779[/C][C]-1.27779[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]8.35545[/C][C]-0.355455[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]8.41525[/C][C]0.084752[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]6.64388[/C][C]-1.14388[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]7.97268[/C][C]-0.972681[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]6.77171[/C][C]-1.77171[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]6.92906[/C][C]-3.42906[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]6.99882[/C][C]-1.99882[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]7.9712[/C][C]1.0288[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]7.01122[/C][C]1.48878[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]7.5845[/C][C]-2.5845[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]8.62579[/C][C]0.874212[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]6.44218[/C][C]-3.44218[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]5.84549[/C][C]-4.34549[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]7.55994[/C][C]-1.55994[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]7.43014[/C][C]-6.93014[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]6.17225[/C][C]0.327746[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]7.72593[/C][C]-0.225929[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]6.53262[/C][C]-2.03262[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]7.05366[/C][C]0.946343[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]7.75656[/C][C]1.24344[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]7.39003[/C][C]0.109968[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]7.85257[/C][C]0.647432[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]6.35311[/C][C]0.646892[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]7.72462[/C][C]1.77538[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]6.44489[/C][C]0.0551093[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]6.37094[/C][C]3.12906[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]6.02811[/C][C]-0.0281069[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]6.86946[/C][C]1.13054[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]8.7229[/C][C]0.777102[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]7.33649[/C][C]0.663512[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]7.08779[/C][C]0.912215[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]8.15343[/C][C]0.84657[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]5.85502[/C][C]-0.855017[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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
17.56.032751.46725
264.741921.25808
36.55.013911.48609
414.80196-3.80196
514.73682-3.73682
65.55.60747-0.107468
78.54.497424.00258
86.54.485312.01469
94.54.384960.115039
1024.69754-2.69754
1155.18391-0.183912
120.54.534-4.034
1353.576121.42388
1455.52881-0.528811
152.52.204140.295863
1652.710152.28985
175.55.56728-0.0672764
183.54.13268-0.632679
1935.19063-2.19063
2043.125390.874613
210.53.41574-2.91574
226.54.132872.36713
234.54.93871-0.43871
247.55.523161.97684
255.54.407151.09285
2646.09035-2.09035
277.56.110211.38979
2874.734372.26563
2944.93194-0.93194
305.54.113271.38673
312.53.44931-0.949309
325.54.315191.18481
333.54.33129-0.831287
342.54.58574-2.08574
354.53.781870.718134
364.53.811550.688451
374.54.361530.138472
3864.072071.92793
392.55.06972-2.56972
4055.40007-0.400069
4104.31306-4.31306
4255.27697-0.276966
436.54.132552.36745
4455.01992-0.0199196
4563.520052.47995
464.55.58587-1.08587
475.53.918251.58175
4814.56155-3.56155
497.53.754123.74588
5063.859082.14092
5154.963620.0363765
5213.26599-2.26599
5354.425550.574453
546.54.934661.56534
5573.938123.06188
564.54.68333-0.183333
5703.98306-3.98306
588.54.097254.40275
593.53.0610.438997
607.55.414742.08526
613.55.66024-2.16024
6264.609641.39036
631.53.40682-1.90682
6495.906563.09344
653.54.69661-1.19661
663.53.95818-0.45818
6745.25839-1.25839
686.56.469260.0307449
697.54.763942.73606
7065.165020.834976
7155.28483-0.284825
725.53.832471.66753
733.54.56635-1.06635
747.55.752661.74734
756.54.635431.86457
766.54.915481.58452
776.55.135561.36444
7875.462751.53725
793.53.85628-0.356276
801.54.20724-2.70724
8144.86039-0.860394
827.54.269333.23067
834.54.79237-0.292371
8404.05405-4.05405
853.54.41533-0.915332
865.55.168680.331324
8754.104330.895671
884.53.818990.681008
892.54.57664-2.07664
907.55.370032.12997
9174.00582.9942
9204.45635-4.45635
934.55.56387-1.06387
9434.56911-1.56911
951.54.7511-3.2511
963.54.1672-0.667202
972.55.11882-2.61882
985.53.796931.70307
9985.062452.93755
10014.5992-3.5992
10153.8311.169
1024.54.419150.0808492
10334.39873-1.39873
10434.65383-1.65383
10585.052252.94775
1062.53.9546-1.4546
10774.036282.96372
10803.99759-3.99759
10913.33545-2.33545
1103.55.15808-1.65808
1115.54.614480.885525
1125.54.945910.554089
1130.55.20651-4.70651
1147.56.570420.929584
11597.296951.70305
1169.57.929361.57064
1178.510.0186-1.51857
11875.702311.29769
119810.1856-2.18564
120108.535711.46429
12179.44851-2.44851
1228.56.02762.4724
12398.767630.232374
1249.55.236164.26384
12546.82685-2.82685
12666.48149-0.481493
12787.087270.91273
1285.56.62433-1.12433
1299.58.379311.12069
1307.56.361191.13881
13176.684880.315118
1327.58.5399-1.0399
13386.131921.86808
13475.869821.13018
13576.482790.517212
13666.69125-0.691253
137107.182632.81737
1382.55.17306-2.67306
13998.098030.901967
14087.431470.568533
14166.62619-0.626189
1428.57.000091.49991
14365.946140.0538636
14497.233011.76699
14587.821520.178477
14698.417970.582032
1475.56.70109-1.20109
14876.684210.315794
1495.57.14319-1.64319
15098.205580.794419
15126.96891-4.96891
1528.57.093151.40685
15398.032270.967728
1548.58.71279-0.212793
15596.752182.24782
1567.57.81136-0.311363
157108.670941.32906
15897.18671.8133
1597.59.40113-1.90113
16067.32368-1.32368
16110.58.839241.66076
1628.57.439171.06083
16388.28081-0.280814
164104.680435.31957
16510.510.1090.391003
1666.55.535420.964578
1679.58.890310.609691
1688.56.710951.78905
1697.58.10428-0.60428
17057.22239-2.22239
17187.5190.480997
172107.783262.21674
17378.35063-1.35063
1747.58.01833-0.51833
1757.57.9754-0.475404
1769.57.925461.57454
17766.85358-0.853579
178108.230681.76932
17978.39598-1.39598
18035.30767-2.30767
18168.50822-2.50822
18277.96713-0.967128
183108.326941.67306
18477.70857-0.708567
1853.57.25511-3.75511
18688.28862-0.288623
187107.516712.48329
1885.57.81911-2.31911
18966.83144-0.831442
1906.56.133480.366523
1916.57.11983-0.619829
1928.56.887991.61201
19346.85098-2.85098
1949.57.196852.30315
19587.783980.216015
1968.57.421181.07882
1975.58.22074-2.72074
19876.644420.355582
19996.77282.2272
20087.596840.403158
201108.788591.21141
20287.15950.8405
20367.1345-1.1345
20487.960450.0395547
20556.55879-1.55879
20696.915962.08404
2074.54.89905-0.399052
2088.56.844681.65532
2099.58.279751.22025
2108.58.283190.216811
2117.56.454611.04539
2127.57.056930.443068
21356.64247-1.64247
21477.92133-0.921328
21588.65799-0.657992
2165.56.17902-0.679022
2178.57.670890.829108
2189.57.547771.95223
21976.602150.397846
22089.19914-1.19914
2218.57.088351.41165
2223.55.48985-1.98985
2236.56.67305-0.173054
2246.56.19840.301597
22510.58.007662.49234
2268.56.366992.13301
22786.959261.04074
228107.186052.81395
229107.766812.23319
2309.57.706841.79316
23196.0622.938
232108.365031.63497
2337.56.399811.10019
2344.57.1987-2.6987
2354.55.09143-0.591428
2360.55.47063-4.97063
2376.56.008110.491887
2384.56.82414-2.32414
2395.56.22647-0.726471
24056.51561-1.51561
24167.29697-1.29697
24246.45473-2.45473
24387.321720.678283
24410.59.572570.927435
2456.57.77779-1.27779
24688.35545-0.355455
2478.58.415250.084752
2485.56.64388-1.14388
24977.97268-0.972681
25056.77171-1.77171
2513.56.92906-3.42906
25256.99882-1.99882
25397.97121.0288
2548.57.011221.48878
25557.5845-2.5845
2569.58.625790.874212
25736.44218-3.44218
2581.55.84549-4.34549
25967.55994-1.55994
2600.57.43014-6.93014
2616.56.172250.327746
2627.57.72593-0.225929
2634.56.53262-2.03262
26487.053660.946343
26597.756561.24344
2667.57.390030.109968
2678.57.852570.647432
26876.353110.646892
2699.57.724621.77538
2706.56.444890.0551093
2719.56.370943.12906
27266.02811-0.0281069
27386.869461.13054
2749.58.72290.777102
27587.336490.663512
27687.087790.912215
27798.153430.84657
27855.85502-0.855017






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
180.7843270.4313460.215673
190.6551860.6896280.344814
200.5276060.9447890.472394
210.5163530.9672940.483647
220.4585580.9171150.541442
230.5682390.8635220.431761
240.4700160.9400330.529984
250.3753350.7506690.624665
260.3085410.6170810.691459
270.2934240.5868480.706576
280.3336870.6673750.666313
290.2620380.5240760.737962
300.2515460.5030920.748454
310.2563760.5127510.743624
320.2073210.4146420.792679
330.1855670.3711330.814433
340.1749970.3499940.825003
350.1341330.2682660.865867
360.120040.240080.87996
370.09358970.1871790.90641
380.1211740.2423480.878826
390.2325930.4651870.767407
400.1877350.375470.812265
410.2796420.5592830.720358
420.2485760.4971530.751424
430.2629110.5258230.737089
440.2196750.4393490.780325
450.1891530.3783070.810847
460.1601130.3202260.839887
470.1798960.3597920.820104
480.2372140.4744270.762786
490.2683680.5367370.731632
500.3053060.6106130.694694
510.261010.522020.73899
520.3273980.6547970.672602
530.3274790.6549570.672521
540.3851510.7703020.614849
550.6227640.7544730.377236
560.5766270.8467460.423373
570.7974420.4051170.202558
580.8240210.3519570.175979
590.7942260.4115480.205774
600.8149490.3701020.185051
610.8208120.3583760.179188
620.7982950.403410.201705
630.9165750.166850.0834252
640.9451130.1097750.0548874
650.9386650.122670.061335
660.9317770.1364460.068223
670.9254520.1490950.0745476
680.9094890.1810230.0905113
690.9237780.1524440.0762221
700.909680.1806390.0903195
710.8920540.2158930.107946
720.8856110.2287790.114389
730.8713020.2573960.128698
740.8672120.2655760.132788
750.861120.2777610.13888
760.8530770.2938470.146923
770.836520.3269590.16348
780.8404970.3190050.159503
790.8170490.3659020.182951
800.8288260.3423480.171174
810.8072650.3854710.192735
820.8430040.3139910.156996
830.8192840.3614310.180716
840.8862130.2275750.113787
850.8726820.2546360.127318
860.8531840.2936310.146816
870.8372620.3254760.162738
880.816430.367140.18357
890.8177580.3644840.182242
900.8213380.3573240.178662
910.860730.278540.13927
920.9284870.1430260.0715129
930.9156950.168610.0843048
940.9071960.1856080.0928041
950.9239170.1521670.0760833
960.9101820.1796350.0898176
970.9122230.1755530.0877766
980.9083420.1833160.0916582
990.9241370.1517250.0758627
1000.9489860.1020280.051014
1010.9436470.1127060.056353
1020.9326430.1347130.0673567
1030.9298170.1403660.0701832
1040.9226650.154670.0773349
1050.9411410.1177170.0588587
1060.932680.134640.0673202
1070.9501440.09971170.0498558
1080.9663260.06734840.0336742
1090.9668770.06624510.0331226
1100.9643330.07133440.0356672
1110.9592540.08149250.0407462
1120.950740.09851990.04926
1130.9658870.06822570.0341129
1140.9686980.06260460.0313023
1150.9690420.0619150.0309575
1160.9665630.06687310.0334366
1170.9644020.07119570.0355978
1180.9601580.07968470.0398423
1190.9631170.07376510.0368826
1200.960060.07987980.0399399
1210.9623550.07529070.0376453
1220.9666560.06668720.0333436
1230.9596160.08076770.0403839
1240.9815570.03688680.0184434
1250.9853050.02938990.0146949
1260.9819970.0360050.0180025
1270.9785840.04283290.0214165
1280.9759780.04804320.0240216
1290.9720270.0559460.027973
1300.9675220.06495580.0324779
1310.9611040.07779210.038896
1320.9561140.08777290.0438864
1330.9542570.09148550.0457428
1340.9471080.1057850.0528923
1350.9392580.1214830.0607417
1360.9289090.1421810.0710907
1370.9409470.1181070.0590533
1380.947520.1049590.0524795
1390.9391650.121670.0608348
1400.9296450.140710.0703549
1410.9227810.1544390.0772193
1420.9197640.1604720.0802362
1430.9076710.1846580.0923292
1440.905230.189540.0947702
1450.8895550.220890.110445
1460.8739320.2521360.126068
1470.8632870.2734270.136713
1480.8433290.3133410.156671
1490.8369140.3261710.163086
1500.8171870.3656250.182813
1510.9197110.1605770.0802885
1520.9126240.1747510.0873757
1530.9007830.1984350.0992173
1540.883940.2321190.11606
1550.8864090.2271820.113591
1560.8725790.2548420.127421
1570.8600120.2799760.139988
1580.8602960.2794080.139704
1590.8669470.2661050.133053
1600.8547830.2904340.145217
1610.8516470.2967060.148353
1620.8367460.3265080.163254
1630.8135080.3729840.186492
1640.9443240.1113510.0556755
1650.9335880.1328230.0664117
1660.9289360.1421280.071064
1670.9158570.1682860.0841428
1680.9155860.1688290.0844145
1690.9116390.1767220.088361
1700.9180280.1639450.0819725
1710.9029970.1940060.0970029
1720.9020430.1959130.0979565
1730.8958310.2083380.104169
1740.8826220.2347560.117378
1750.8686450.262710.131355
1760.8601250.279750.139875
1770.8412780.3174440.158722
1780.8363310.3273380.163669
1790.8265280.3469430.173472
1800.8268110.3463780.173189
1810.8412650.3174710.158735
1820.8335410.3329190.166459
1830.8249060.3501890.175094
1840.8087810.3824370.191219
1850.8985880.2028240.101412
1860.8820390.2359220.117961
1870.8910430.2179140.108957
1880.9043680.1912640.095632
1890.8905910.2188180.109409
1900.8712040.2575930.128796
1910.8517680.2964630.148232
1920.8359810.3280380.164019
1930.8717070.2565870.128293
1940.8663570.2672850.133643
1950.8435360.3129290.156464
1960.8210180.3579630.178982
1970.8564590.2870820.143541
1980.8322340.3355320.167766
1990.8445570.3108860.155443
2000.8198510.3602980.180149
2010.8001470.3997070.199853
2020.7731340.4537320.226866
2030.7513620.4972770.248638
2040.7236350.5527290.276365
2050.7062850.5874310.293715
2060.7765550.4468910.223445
2070.7647220.4705560.235278
2080.7456930.5086150.254307
2090.727220.5455610.27278
2100.6968660.6062690.303134
2110.7034860.5930280.296514
2120.6643160.6713690.335684
2130.6410690.7178620.358931
2140.6010090.7979830.398991
2150.557470.8850590.44253
2160.5152550.9694890.484745
2170.4767930.9535860.523207
2180.4527580.9055160.547242
2190.4168990.8337990.583101
2200.3963980.7927960.603602
2210.3897230.7794460.610277
2220.3804220.7608450.619578
2230.3549490.7098970.645051
2240.3279350.655870.672065
2250.341970.683940.65803
2260.3694710.7389420.630529
2270.3782790.7565580.621721
2280.5277920.9444160.472208
2290.6186610.7626780.381339
2300.6462570.7074860.353743
2310.7112340.5775320.288766
2320.7493910.5012180.250609
2330.7333980.5332040.266602
2340.7081790.5836420.291821
2350.6947880.6104230.305212
2360.7850550.429890.214945
2370.7415450.5169110.258455
2380.704780.590440.29522
2390.6497050.700590.350295
2400.6287260.7425480.371274
2410.5744140.8511720.425586
2420.5219340.9561320.478066
2430.5048140.9903710.495186
2440.4461980.8923970.553802
2450.382490.7649810.61751
2460.355810.7116210.64419
2470.2921490.5842980.707851
2480.425930.851860.57407
2490.3869880.7739760.613012
2500.3220660.6441310.677934
2510.2699530.5399060.730047
2520.2176920.4353840.782308
2530.1906340.3812690.809366
2540.2360810.4721620.763919
2550.1740150.3480310.825985
2560.2394330.4788650.760567
2570.2093430.4186860.790657
2580.5771330.8457340.422867
2590.7933080.4133850.206692
2600.9704330.05913470.0295673

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 0.784327 & 0.431346 & 0.215673 \tabularnewline
19 & 0.655186 & 0.689628 & 0.344814 \tabularnewline
20 & 0.527606 & 0.944789 & 0.472394 \tabularnewline
21 & 0.516353 & 0.967294 & 0.483647 \tabularnewline
22 & 0.458558 & 0.917115 & 0.541442 \tabularnewline
23 & 0.568239 & 0.863522 & 0.431761 \tabularnewline
24 & 0.470016 & 0.940033 & 0.529984 \tabularnewline
25 & 0.375335 & 0.750669 & 0.624665 \tabularnewline
26 & 0.308541 & 0.617081 & 0.691459 \tabularnewline
27 & 0.293424 & 0.586848 & 0.706576 \tabularnewline
28 & 0.333687 & 0.667375 & 0.666313 \tabularnewline
29 & 0.262038 & 0.524076 & 0.737962 \tabularnewline
30 & 0.251546 & 0.503092 & 0.748454 \tabularnewline
31 & 0.256376 & 0.512751 & 0.743624 \tabularnewline
32 & 0.207321 & 0.414642 & 0.792679 \tabularnewline
33 & 0.185567 & 0.371133 & 0.814433 \tabularnewline
34 & 0.174997 & 0.349994 & 0.825003 \tabularnewline
35 & 0.134133 & 0.268266 & 0.865867 \tabularnewline
36 & 0.12004 & 0.24008 & 0.87996 \tabularnewline
37 & 0.0935897 & 0.187179 & 0.90641 \tabularnewline
38 & 0.121174 & 0.242348 & 0.878826 \tabularnewline
39 & 0.232593 & 0.465187 & 0.767407 \tabularnewline
40 & 0.187735 & 0.37547 & 0.812265 \tabularnewline
41 & 0.279642 & 0.559283 & 0.720358 \tabularnewline
42 & 0.248576 & 0.497153 & 0.751424 \tabularnewline
43 & 0.262911 & 0.525823 & 0.737089 \tabularnewline
44 & 0.219675 & 0.439349 & 0.780325 \tabularnewline
45 & 0.189153 & 0.378307 & 0.810847 \tabularnewline
46 & 0.160113 & 0.320226 & 0.839887 \tabularnewline
47 & 0.179896 & 0.359792 & 0.820104 \tabularnewline
48 & 0.237214 & 0.474427 & 0.762786 \tabularnewline
49 & 0.268368 & 0.536737 & 0.731632 \tabularnewline
50 & 0.305306 & 0.610613 & 0.694694 \tabularnewline
51 & 0.26101 & 0.52202 & 0.73899 \tabularnewline
52 & 0.327398 & 0.654797 & 0.672602 \tabularnewline
53 & 0.327479 & 0.654957 & 0.672521 \tabularnewline
54 & 0.385151 & 0.770302 & 0.614849 \tabularnewline
55 & 0.622764 & 0.754473 & 0.377236 \tabularnewline
56 & 0.576627 & 0.846746 & 0.423373 \tabularnewline
57 & 0.797442 & 0.405117 & 0.202558 \tabularnewline
58 & 0.824021 & 0.351957 & 0.175979 \tabularnewline
59 & 0.794226 & 0.411548 & 0.205774 \tabularnewline
60 & 0.814949 & 0.370102 & 0.185051 \tabularnewline
61 & 0.820812 & 0.358376 & 0.179188 \tabularnewline
62 & 0.798295 & 0.40341 & 0.201705 \tabularnewline
63 & 0.916575 & 0.16685 & 0.0834252 \tabularnewline
64 & 0.945113 & 0.109775 & 0.0548874 \tabularnewline
65 & 0.938665 & 0.12267 & 0.061335 \tabularnewline
66 & 0.931777 & 0.136446 & 0.068223 \tabularnewline
67 & 0.925452 & 0.149095 & 0.0745476 \tabularnewline
68 & 0.909489 & 0.181023 & 0.0905113 \tabularnewline
69 & 0.923778 & 0.152444 & 0.0762221 \tabularnewline
70 & 0.90968 & 0.180639 & 0.0903195 \tabularnewline
71 & 0.892054 & 0.215893 & 0.107946 \tabularnewline
72 & 0.885611 & 0.228779 & 0.114389 \tabularnewline
73 & 0.871302 & 0.257396 & 0.128698 \tabularnewline
74 & 0.867212 & 0.265576 & 0.132788 \tabularnewline
75 & 0.86112 & 0.277761 & 0.13888 \tabularnewline
76 & 0.853077 & 0.293847 & 0.146923 \tabularnewline
77 & 0.83652 & 0.326959 & 0.16348 \tabularnewline
78 & 0.840497 & 0.319005 & 0.159503 \tabularnewline
79 & 0.817049 & 0.365902 & 0.182951 \tabularnewline
80 & 0.828826 & 0.342348 & 0.171174 \tabularnewline
81 & 0.807265 & 0.385471 & 0.192735 \tabularnewline
82 & 0.843004 & 0.313991 & 0.156996 \tabularnewline
83 & 0.819284 & 0.361431 & 0.180716 \tabularnewline
84 & 0.886213 & 0.227575 & 0.113787 \tabularnewline
85 & 0.872682 & 0.254636 & 0.127318 \tabularnewline
86 & 0.853184 & 0.293631 & 0.146816 \tabularnewline
87 & 0.837262 & 0.325476 & 0.162738 \tabularnewline
88 & 0.81643 & 0.36714 & 0.18357 \tabularnewline
89 & 0.817758 & 0.364484 & 0.182242 \tabularnewline
90 & 0.821338 & 0.357324 & 0.178662 \tabularnewline
91 & 0.86073 & 0.27854 & 0.13927 \tabularnewline
92 & 0.928487 & 0.143026 & 0.0715129 \tabularnewline
93 & 0.915695 & 0.16861 & 0.0843048 \tabularnewline
94 & 0.907196 & 0.185608 & 0.0928041 \tabularnewline
95 & 0.923917 & 0.152167 & 0.0760833 \tabularnewline
96 & 0.910182 & 0.179635 & 0.0898176 \tabularnewline
97 & 0.912223 & 0.175553 & 0.0877766 \tabularnewline
98 & 0.908342 & 0.183316 & 0.0916582 \tabularnewline
99 & 0.924137 & 0.151725 & 0.0758627 \tabularnewline
100 & 0.948986 & 0.102028 & 0.051014 \tabularnewline
101 & 0.943647 & 0.112706 & 0.056353 \tabularnewline
102 & 0.932643 & 0.134713 & 0.0673567 \tabularnewline
103 & 0.929817 & 0.140366 & 0.0701832 \tabularnewline
104 & 0.922665 & 0.15467 & 0.0773349 \tabularnewline
105 & 0.941141 & 0.117717 & 0.0588587 \tabularnewline
106 & 0.93268 & 0.13464 & 0.0673202 \tabularnewline
107 & 0.950144 & 0.0997117 & 0.0498558 \tabularnewline
108 & 0.966326 & 0.0673484 & 0.0336742 \tabularnewline
109 & 0.966877 & 0.0662451 & 0.0331226 \tabularnewline
110 & 0.964333 & 0.0713344 & 0.0356672 \tabularnewline
111 & 0.959254 & 0.0814925 & 0.0407462 \tabularnewline
112 & 0.95074 & 0.0985199 & 0.04926 \tabularnewline
113 & 0.965887 & 0.0682257 & 0.0341129 \tabularnewline
114 & 0.968698 & 0.0626046 & 0.0313023 \tabularnewline
115 & 0.969042 & 0.061915 & 0.0309575 \tabularnewline
116 & 0.966563 & 0.0668731 & 0.0334366 \tabularnewline
117 & 0.964402 & 0.0711957 & 0.0355978 \tabularnewline
118 & 0.960158 & 0.0796847 & 0.0398423 \tabularnewline
119 & 0.963117 & 0.0737651 & 0.0368826 \tabularnewline
120 & 0.96006 & 0.0798798 & 0.0399399 \tabularnewline
121 & 0.962355 & 0.0752907 & 0.0376453 \tabularnewline
122 & 0.966656 & 0.0666872 & 0.0333436 \tabularnewline
123 & 0.959616 & 0.0807677 & 0.0403839 \tabularnewline
124 & 0.981557 & 0.0368868 & 0.0184434 \tabularnewline
125 & 0.985305 & 0.0293899 & 0.0146949 \tabularnewline
126 & 0.981997 & 0.036005 & 0.0180025 \tabularnewline
127 & 0.978584 & 0.0428329 & 0.0214165 \tabularnewline
128 & 0.975978 & 0.0480432 & 0.0240216 \tabularnewline
129 & 0.972027 & 0.055946 & 0.027973 \tabularnewline
130 & 0.967522 & 0.0649558 & 0.0324779 \tabularnewline
131 & 0.961104 & 0.0777921 & 0.038896 \tabularnewline
132 & 0.956114 & 0.0877729 & 0.0438864 \tabularnewline
133 & 0.954257 & 0.0914855 & 0.0457428 \tabularnewline
134 & 0.947108 & 0.105785 & 0.0528923 \tabularnewline
135 & 0.939258 & 0.121483 & 0.0607417 \tabularnewline
136 & 0.928909 & 0.142181 & 0.0710907 \tabularnewline
137 & 0.940947 & 0.118107 & 0.0590533 \tabularnewline
138 & 0.94752 & 0.104959 & 0.0524795 \tabularnewline
139 & 0.939165 & 0.12167 & 0.0608348 \tabularnewline
140 & 0.929645 & 0.14071 & 0.0703549 \tabularnewline
141 & 0.922781 & 0.154439 & 0.0772193 \tabularnewline
142 & 0.919764 & 0.160472 & 0.0802362 \tabularnewline
143 & 0.907671 & 0.184658 & 0.0923292 \tabularnewline
144 & 0.90523 & 0.18954 & 0.0947702 \tabularnewline
145 & 0.889555 & 0.22089 & 0.110445 \tabularnewline
146 & 0.873932 & 0.252136 & 0.126068 \tabularnewline
147 & 0.863287 & 0.273427 & 0.136713 \tabularnewline
148 & 0.843329 & 0.313341 & 0.156671 \tabularnewline
149 & 0.836914 & 0.326171 & 0.163086 \tabularnewline
150 & 0.817187 & 0.365625 & 0.182813 \tabularnewline
151 & 0.919711 & 0.160577 & 0.0802885 \tabularnewline
152 & 0.912624 & 0.174751 & 0.0873757 \tabularnewline
153 & 0.900783 & 0.198435 & 0.0992173 \tabularnewline
154 & 0.88394 & 0.232119 & 0.11606 \tabularnewline
155 & 0.886409 & 0.227182 & 0.113591 \tabularnewline
156 & 0.872579 & 0.254842 & 0.127421 \tabularnewline
157 & 0.860012 & 0.279976 & 0.139988 \tabularnewline
158 & 0.860296 & 0.279408 & 0.139704 \tabularnewline
159 & 0.866947 & 0.266105 & 0.133053 \tabularnewline
160 & 0.854783 & 0.290434 & 0.145217 \tabularnewline
161 & 0.851647 & 0.296706 & 0.148353 \tabularnewline
162 & 0.836746 & 0.326508 & 0.163254 \tabularnewline
163 & 0.813508 & 0.372984 & 0.186492 \tabularnewline
164 & 0.944324 & 0.111351 & 0.0556755 \tabularnewline
165 & 0.933588 & 0.132823 & 0.0664117 \tabularnewline
166 & 0.928936 & 0.142128 & 0.071064 \tabularnewline
167 & 0.915857 & 0.168286 & 0.0841428 \tabularnewline
168 & 0.915586 & 0.168829 & 0.0844145 \tabularnewline
169 & 0.911639 & 0.176722 & 0.088361 \tabularnewline
170 & 0.918028 & 0.163945 & 0.0819725 \tabularnewline
171 & 0.902997 & 0.194006 & 0.0970029 \tabularnewline
172 & 0.902043 & 0.195913 & 0.0979565 \tabularnewline
173 & 0.895831 & 0.208338 & 0.104169 \tabularnewline
174 & 0.882622 & 0.234756 & 0.117378 \tabularnewline
175 & 0.868645 & 0.26271 & 0.131355 \tabularnewline
176 & 0.860125 & 0.27975 & 0.139875 \tabularnewline
177 & 0.841278 & 0.317444 & 0.158722 \tabularnewline
178 & 0.836331 & 0.327338 & 0.163669 \tabularnewline
179 & 0.826528 & 0.346943 & 0.173472 \tabularnewline
180 & 0.826811 & 0.346378 & 0.173189 \tabularnewline
181 & 0.841265 & 0.317471 & 0.158735 \tabularnewline
182 & 0.833541 & 0.332919 & 0.166459 \tabularnewline
183 & 0.824906 & 0.350189 & 0.175094 \tabularnewline
184 & 0.808781 & 0.382437 & 0.191219 \tabularnewline
185 & 0.898588 & 0.202824 & 0.101412 \tabularnewline
186 & 0.882039 & 0.235922 & 0.117961 \tabularnewline
187 & 0.891043 & 0.217914 & 0.108957 \tabularnewline
188 & 0.904368 & 0.191264 & 0.095632 \tabularnewline
189 & 0.890591 & 0.218818 & 0.109409 \tabularnewline
190 & 0.871204 & 0.257593 & 0.128796 \tabularnewline
191 & 0.851768 & 0.296463 & 0.148232 \tabularnewline
192 & 0.835981 & 0.328038 & 0.164019 \tabularnewline
193 & 0.871707 & 0.256587 & 0.128293 \tabularnewline
194 & 0.866357 & 0.267285 & 0.133643 \tabularnewline
195 & 0.843536 & 0.312929 & 0.156464 \tabularnewline
196 & 0.821018 & 0.357963 & 0.178982 \tabularnewline
197 & 0.856459 & 0.287082 & 0.143541 \tabularnewline
198 & 0.832234 & 0.335532 & 0.167766 \tabularnewline
199 & 0.844557 & 0.310886 & 0.155443 \tabularnewline
200 & 0.819851 & 0.360298 & 0.180149 \tabularnewline
201 & 0.800147 & 0.399707 & 0.199853 \tabularnewline
202 & 0.773134 & 0.453732 & 0.226866 \tabularnewline
203 & 0.751362 & 0.497277 & 0.248638 \tabularnewline
204 & 0.723635 & 0.552729 & 0.276365 \tabularnewline
205 & 0.706285 & 0.587431 & 0.293715 \tabularnewline
206 & 0.776555 & 0.446891 & 0.223445 \tabularnewline
207 & 0.764722 & 0.470556 & 0.235278 \tabularnewline
208 & 0.745693 & 0.508615 & 0.254307 \tabularnewline
209 & 0.72722 & 0.545561 & 0.27278 \tabularnewline
210 & 0.696866 & 0.606269 & 0.303134 \tabularnewline
211 & 0.703486 & 0.593028 & 0.296514 \tabularnewline
212 & 0.664316 & 0.671369 & 0.335684 \tabularnewline
213 & 0.641069 & 0.717862 & 0.358931 \tabularnewline
214 & 0.601009 & 0.797983 & 0.398991 \tabularnewline
215 & 0.55747 & 0.885059 & 0.44253 \tabularnewline
216 & 0.515255 & 0.969489 & 0.484745 \tabularnewline
217 & 0.476793 & 0.953586 & 0.523207 \tabularnewline
218 & 0.452758 & 0.905516 & 0.547242 \tabularnewline
219 & 0.416899 & 0.833799 & 0.583101 \tabularnewline
220 & 0.396398 & 0.792796 & 0.603602 \tabularnewline
221 & 0.389723 & 0.779446 & 0.610277 \tabularnewline
222 & 0.380422 & 0.760845 & 0.619578 \tabularnewline
223 & 0.354949 & 0.709897 & 0.645051 \tabularnewline
224 & 0.327935 & 0.65587 & 0.672065 \tabularnewline
225 & 0.34197 & 0.68394 & 0.65803 \tabularnewline
226 & 0.369471 & 0.738942 & 0.630529 \tabularnewline
227 & 0.378279 & 0.756558 & 0.621721 \tabularnewline
228 & 0.527792 & 0.944416 & 0.472208 \tabularnewline
229 & 0.618661 & 0.762678 & 0.381339 \tabularnewline
230 & 0.646257 & 0.707486 & 0.353743 \tabularnewline
231 & 0.711234 & 0.577532 & 0.288766 \tabularnewline
232 & 0.749391 & 0.501218 & 0.250609 \tabularnewline
233 & 0.733398 & 0.533204 & 0.266602 \tabularnewline
234 & 0.708179 & 0.583642 & 0.291821 \tabularnewline
235 & 0.694788 & 0.610423 & 0.305212 \tabularnewline
236 & 0.785055 & 0.42989 & 0.214945 \tabularnewline
237 & 0.741545 & 0.516911 & 0.258455 \tabularnewline
238 & 0.70478 & 0.59044 & 0.29522 \tabularnewline
239 & 0.649705 & 0.70059 & 0.350295 \tabularnewline
240 & 0.628726 & 0.742548 & 0.371274 \tabularnewline
241 & 0.574414 & 0.851172 & 0.425586 \tabularnewline
242 & 0.521934 & 0.956132 & 0.478066 \tabularnewline
243 & 0.504814 & 0.990371 & 0.495186 \tabularnewline
244 & 0.446198 & 0.892397 & 0.553802 \tabularnewline
245 & 0.38249 & 0.764981 & 0.61751 \tabularnewline
246 & 0.35581 & 0.711621 & 0.64419 \tabularnewline
247 & 0.292149 & 0.584298 & 0.707851 \tabularnewline
248 & 0.42593 & 0.85186 & 0.57407 \tabularnewline
249 & 0.386988 & 0.773976 & 0.613012 \tabularnewline
250 & 0.322066 & 0.644131 & 0.677934 \tabularnewline
251 & 0.269953 & 0.539906 & 0.730047 \tabularnewline
252 & 0.217692 & 0.435384 & 0.782308 \tabularnewline
253 & 0.190634 & 0.381269 & 0.809366 \tabularnewline
254 & 0.236081 & 0.472162 & 0.763919 \tabularnewline
255 & 0.174015 & 0.348031 & 0.825985 \tabularnewline
256 & 0.239433 & 0.478865 & 0.760567 \tabularnewline
257 & 0.209343 & 0.418686 & 0.790657 \tabularnewline
258 & 0.577133 & 0.845734 & 0.422867 \tabularnewline
259 & 0.793308 & 0.413385 & 0.206692 \tabularnewline
260 & 0.970433 & 0.0591347 & 0.0295673 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&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]18[/C][C]0.784327[/C][C]0.431346[/C][C]0.215673[/C][/ROW]
[ROW][C]19[/C][C]0.655186[/C][C]0.689628[/C][C]0.344814[/C][/ROW]
[ROW][C]20[/C][C]0.527606[/C][C]0.944789[/C][C]0.472394[/C][/ROW]
[ROW][C]21[/C][C]0.516353[/C][C]0.967294[/C][C]0.483647[/C][/ROW]
[ROW][C]22[/C][C]0.458558[/C][C]0.917115[/C][C]0.541442[/C][/ROW]
[ROW][C]23[/C][C]0.568239[/C][C]0.863522[/C][C]0.431761[/C][/ROW]
[ROW][C]24[/C][C]0.470016[/C][C]0.940033[/C][C]0.529984[/C][/ROW]
[ROW][C]25[/C][C]0.375335[/C][C]0.750669[/C][C]0.624665[/C][/ROW]
[ROW][C]26[/C][C]0.308541[/C][C]0.617081[/C][C]0.691459[/C][/ROW]
[ROW][C]27[/C][C]0.293424[/C][C]0.586848[/C][C]0.706576[/C][/ROW]
[ROW][C]28[/C][C]0.333687[/C][C]0.667375[/C][C]0.666313[/C][/ROW]
[ROW][C]29[/C][C]0.262038[/C][C]0.524076[/C][C]0.737962[/C][/ROW]
[ROW][C]30[/C][C]0.251546[/C][C]0.503092[/C][C]0.748454[/C][/ROW]
[ROW][C]31[/C][C]0.256376[/C][C]0.512751[/C][C]0.743624[/C][/ROW]
[ROW][C]32[/C][C]0.207321[/C][C]0.414642[/C][C]0.792679[/C][/ROW]
[ROW][C]33[/C][C]0.185567[/C][C]0.371133[/C][C]0.814433[/C][/ROW]
[ROW][C]34[/C][C]0.174997[/C][C]0.349994[/C][C]0.825003[/C][/ROW]
[ROW][C]35[/C][C]0.134133[/C][C]0.268266[/C][C]0.865867[/C][/ROW]
[ROW][C]36[/C][C]0.12004[/C][C]0.24008[/C][C]0.87996[/C][/ROW]
[ROW][C]37[/C][C]0.0935897[/C][C]0.187179[/C][C]0.90641[/C][/ROW]
[ROW][C]38[/C][C]0.121174[/C][C]0.242348[/C][C]0.878826[/C][/ROW]
[ROW][C]39[/C][C]0.232593[/C][C]0.465187[/C][C]0.767407[/C][/ROW]
[ROW][C]40[/C][C]0.187735[/C][C]0.37547[/C][C]0.812265[/C][/ROW]
[ROW][C]41[/C][C]0.279642[/C][C]0.559283[/C][C]0.720358[/C][/ROW]
[ROW][C]42[/C][C]0.248576[/C][C]0.497153[/C][C]0.751424[/C][/ROW]
[ROW][C]43[/C][C]0.262911[/C][C]0.525823[/C][C]0.737089[/C][/ROW]
[ROW][C]44[/C][C]0.219675[/C][C]0.439349[/C][C]0.780325[/C][/ROW]
[ROW][C]45[/C][C]0.189153[/C][C]0.378307[/C][C]0.810847[/C][/ROW]
[ROW][C]46[/C][C]0.160113[/C][C]0.320226[/C][C]0.839887[/C][/ROW]
[ROW][C]47[/C][C]0.179896[/C][C]0.359792[/C][C]0.820104[/C][/ROW]
[ROW][C]48[/C][C]0.237214[/C][C]0.474427[/C][C]0.762786[/C][/ROW]
[ROW][C]49[/C][C]0.268368[/C][C]0.536737[/C][C]0.731632[/C][/ROW]
[ROW][C]50[/C][C]0.305306[/C][C]0.610613[/C][C]0.694694[/C][/ROW]
[ROW][C]51[/C][C]0.26101[/C][C]0.52202[/C][C]0.73899[/C][/ROW]
[ROW][C]52[/C][C]0.327398[/C][C]0.654797[/C][C]0.672602[/C][/ROW]
[ROW][C]53[/C][C]0.327479[/C][C]0.654957[/C][C]0.672521[/C][/ROW]
[ROW][C]54[/C][C]0.385151[/C][C]0.770302[/C][C]0.614849[/C][/ROW]
[ROW][C]55[/C][C]0.622764[/C][C]0.754473[/C][C]0.377236[/C][/ROW]
[ROW][C]56[/C][C]0.576627[/C][C]0.846746[/C][C]0.423373[/C][/ROW]
[ROW][C]57[/C][C]0.797442[/C][C]0.405117[/C][C]0.202558[/C][/ROW]
[ROW][C]58[/C][C]0.824021[/C][C]0.351957[/C][C]0.175979[/C][/ROW]
[ROW][C]59[/C][C]0.794226[/C][C]0.411548[/C][C]0.205774[/C][/ROW]
[ROW][C]60[/C][C]0.814949[/C][C]0.370102[/C][C]0.185051[/C][/ROW]
[ROW][C]61[/C][C]0.820812[/C][C]0.358376[/C][C]0.179188[/C][/ROW]
[ROW][C]62[/C][C]0.798295[/C][C]0.40341[/C][C]0.201705[/C][/ROW]
[ROW][C]63[/C][C]0.916575[/C][C]0.16685[/C][C]0.0834252[/C][/ROW]
[ROW][C]64[/C][C]0.945113[/C][C]0.109775[/C][C]0.0548874[/C][/ROW]
[ROW][C]65[/C][C]0.938665[/C][C]0.12267[/C][C]0.061335[/C][/ROW]
[ROW][C]66[/C][C]0.931777[/C][C]0.136446[/C][C]0.068223[/C][/ROW]
[ROW][C]67[/C][C]0.925452[/C][C]0.149095[/C][C]0.0745476[/C][/ROW]
[ROW][C]68[/C][C]0.909489[/C][C]0.181023[/C][C]0.0905113[/C][/ROW]
[ROW][C]69[/C][C]0.923778[/C][C]0.152444[/C][C]0.0762221[/C][/ROW]
[ROW][C]70[/C][C]0.90968[/C][C]0.180639[/C][C]0.0903195[/C][/ROW]
[ROW][C]71[/C][C]0.892054[/C][C]0.215893[/C][C]0.107946[/C][/ROW]
[ROW][C]72[/C][C]0.885611[/C][C]0.228779[/C][C]0.114389[/C][/ROW]
[ROW][C]73[/C][C]0.871302[/C][C]0.257396[/C][C]0.128698[/C][/ROW]
[ROW][C]74[/C][C]0.867212[/C][C]0.265576[/C][C]0.132788[/C][/ROW]
[ROW][C]75[/C][C]0.86112[/C][C]0.277761[/C][C]0.13888[/C][/ROW]
[ROW][C]76[/C][C]0.853077[/C][C]0.293847[/C][C]0.146923[/C][/ROW]
[ROW][C]77[/C][C]0.83652[/C][C]0.326959[/C][C]0.16348[/C][/ROW]
[ROW][C]78[/C][C]0.840497[/C][C]0.319005[/C][C]0.159503[/C][/ROW]
[ROW][C]79[/C][C]0.817049[/C][C]0.365902[/C][C]0.182951[/C][/ROW]
[ROW][C]80[/C][C]0.828826[/C][C]0.342348[/C][C]0.171174[/C][/ROW]
[ROW][C]81[/C][C]0.807265[/C][C]0.385471[/C][C]0.192735[/C][/ROW]
[ROW][C]82[/C][C]0.843004[/C][C]0.313991[/C][C]0.156996[/C][/ROW]
[ROW][C]83[/C][C]0.819284[/C][C]0.361431[/C][C]0.180716[/C][/ROW]
[ROW][C]84[/C][C]0.886213[/C][C]0.227575[/C][C]0.113787[/C][/ROW]
[ROW][C]85[/C][C]0.872682[/C][C]0.254636[/C][C]0.127318[/C][/ROW]
[ROW][C]86[/C][C]0.853184[/C][C]0.293631[/C][C]0.146816[/C][/ROW]
[ROW][C]87[/C][C]0.837262[/C][C]0.325476[/C][C]0.162738[/C][/ROW]
[ROW][C]88[/C][C]0.81643[/C][C]0.36714[/C][C]0.18357[/C][/ROW]
[ROW][C]89[/C][C]0.817758[/C][C]0.364484[/C][C]0.182242[/C][/ROW]
[ROW][C]90[/C][C]0.821338[/C][C]0.357324[/C][C]0.178662[/C][/ROW]
[ROW][C]91[/C][C]0.86073[/C][C]0.27854[/C][C]0.13927[/C][/ROW]
[ROW][C]92[/C][C]0.928487[/C][C]0.143026[/C][C]0.0715129[/C][/ROW]
[ROW][C]93[/C][C]0.915695[/C][C]0.16861[/C][C]0.0843048[/C][/ROW]
[ROW][C]94[/C][C]0.907196[/C][C]0.185608[/C][C]0.0928041[/C][/ROW]
[ROW][C]95[/C][C]0.923917[/C][C]0.152167[/C][C]0.0760833[/C][/ROW]
[ROW][C]96[/C][C]0.910182[/C][C]0.179635[/C][C]0.0898176[/C][/ROW]
[ROW][C]97[/C][C]0.912223[/C][C]0.175553[/C][C]0.0877766[/C][/ROW]
[ROW][C]98[/C][C]0.908342[/C][C]0.183316[/C][C]0.0916582[/C][/ROW]
[ROW][C]99[/C][C]0.924137[/C][C]0.151725[/C][C]0.0758627[/C][/ROW]
[ROW][C]100[/C][C]0.948986[/C][C]0.102028[/C][C]0.051014[/C][/ROW]
[ROW][C]101[/C][C]0.943647[/C][C]0.112706[/C][C]0.056353[/C][/ROW]
[ROW][C]102[/C][C]0.932643[/C][C]0.134713[/C][C]0.0673567[/C][/ROW]
[ROW][C]103[/C][C]0.929817[/C][C]0.140366[/C][C]0.0701832[/C][/ROW]
[ROW][C]104[/C][C]0.922665[/C][C]0.15467[/C][C]0.0773349[/C][/ROW]
[ROW][C]105[/C][C]0.941141[/C][C]0.117717[/C][C]0.0588587[/C][/ROW]
[ROW][C]106[/C][C]0.93268[/C][C]0.13464[/C][C]0.0673202[/C][/ROW]
[ROW][C]107[/C][C]0.950144[/C][C]0.0997117[/C][C]0.0498558[/C][/ROW]
[ROW][C]108[/C][C]0.966326[/C][C]0.0673484[/C][C]0.0336742[/C][/ROW]
[ROW][C]109[/C][C]0.966877[/C][C]0.0662451[/C][C]0.0331226[/C][/ROW]
[ROW][C]110[/C][C]0.964333[/C][C]0.0713344[/C][C]0.0356672[/C][/ROW]
[ROW][C]111[/C][C]0.959254[/C][C]0.0814925[/C][C]0.0407462[/C][/ROW]
[ROW][C]112[/C][C]0.95074[/C][C]0.0985199[/C][C]0.04926[/C][/ROW]
[ROW][C]113[/C][C]0.965887[/C][C]0.0682257[/C][C]0.0341129[/C][/ROW]
[ROW][C]114[/C][C]0.968698[/C][C]0.0626046[/C][C]0.0313023[/C][/ROW]
[ROW][C]115[/C][C]0.969042[/C][C]0.061915[/C][C]0.0309575[/C][/ROW]
[ROW][C]116[/C][C]0.966563[/C][C]0.0668731[/C][C]0.0334366[/C][/ROW]
[ROW][C]117[/C][C]0.964402[/C][C]0.0711957[/C][C]0.0355978[/C][/ROW]
[ROW][C]118[/C][C]0.960158[/C][C]0.0796847[/C][C]0.0398423[/C][/ROW]
[ROW][C]119[/C][C]0.963117[/C][C]0.0737651[/C][C]0.0368826[/C][/ROW]
[ROW][C]120[/C][C]0.96006[/C][C]0.0798798[/C][C]0.0399399[/C][/ROW]
[ROW][C]121[/C][C]0.962355[/C][C]0.0752907[/C][C]0.0376453[/C][/ROW]
[ROW][C]122[/C][C]0.966656[/C][C]0.0666872[/C][C]0.0333436[/C][/ROW]
[ROW][C]123[/C][C]0.959616[/C][C]0.0807677[/C][C]0.0403839[/C][/ROW]
[ROW][C]124[/C][C]0.981557[/C][C]0.0368868[/C][C]0.0184434[/C][/ROW]
[ROW][C]125[/C][C]0.985305[/C][C]0.0293899[/C][C]0.0146949[/C][/ROW]
[ROW][C]126[/C][C]0.981997[/C][C]0.036005[/C][C]0.0180025[/C][/ROW]
[ROW][C]127[/C][C]0.978584[/C][C]0.0428329[/C][C]0.0214165[/C][/ROW]
[ROW][C]128[/C][C]0.975978[/C][C]0.0480432[/C][C]0.0240216[/C][/ROW]
[ROW][C]129[/C][C]0.972027[/C][C]0.055946[/C][C]0.027973[/C][/ROW]
[ROW][C]130[/C][C]0.967522[/C][C]0.0649558[/C][C]0.0324779[/C][/ROW]
[ROW][C]131[/C][C]0.961104[/C][C]0.0777921[/C][C]0.038896[/C][/ROW]
[ROW][C]132[/C][C]0.956114[/C][C]0.0877729[/C][C]0.0438864[/C][/ROW]
[ROW][C]133[/C][C]0.954257[/C][C]0.0914855[/C][C]0.0457428[/C][/ROW]
[ROW][C]134[/C][C]0.947108[/C][C]0.105785[/C][C]0.0528923[/C][/ROW]
[ROW][C]135[/C][C]0.939258[/C][C]0.121483[/C][C]0.0607417[/C][/ROW]
[ROW][C]136[/C][C]0.928909[/C][C]0.142181[/C][C]0.0710907[/C][/ROW]
[ROW][C]137[/C][C]0.940947[/C][C]0.118107[/C][C]0.0590533[/C][/ROW]
[ROW][C]138[/C][C]0.94752[/C][C]0.104959[/C][C]0.0524795[/C][/ROW]
[ROW][C]139[/C][C]0.939165[/C][C]0.12167[/C][C]0.0608348[/C][/ROW]
[ROW][C]140[/C][C]0.929645[/C][C]0.14071[/C][C]0.0703549[/C][/ROW]
[ROW][C]141[/C][C]0.922781[/C][C]0.154439[/C][C]0.0772193[/C][/ROW]
[ROW][C]142[/C][C]0.919764[/C][C]0.160472[/C][C]0.0802362[/C][/ROW]
[ROW][C]143[/C][C]0.907671[/C][C]0.184658[/C][C]0.0923292[/C][/ROW]
[ROW][C]144[/C][C]0.90523[/C][C]0.18954[/C][C]0.0947702[/C][/ROW]
[ROW][C]145[/C][C]0.889555[/C][C]0.22089[/C][C]0.110445[/C][/ROW]
[ROW][C]146[/C][C]0.873932[/C][C]0.252136[/C][C]0.126068[/C][/ROW]
[ROW][C]147[/C][C]0.863287[/C][C]0.273427[/C][C]0.136713[/C][/ROW]
[ROW][C]148[/C][C]0.843329[/C][C]0.313341[/C][C]0.156671[/C][/ROW]
[ROW][C]149[/C][C]0.836914[/C][C]0.326171[/C][C]0.163086[/C][/ROW]
[ROW][C]150[/C][C]0.817187[/C][C]0.365625[/C][C]0.182813[/C][/ROW]
[ROW][C]151[/C][C]0.919711[/C][C]0.160577[/C][C]0.0802885[/C][/ROW]
[ROW][C]152[/C][C]0.912624[/C][C]0.174751[/C][C]0.0873757[/C][/ROW]
[ROW][C]153[/C][C]0.900783[/C][C]0.198435[/C][C]0.0992173[/C][/ROW]
[ROW][C]154[/C][C]0.88394[/C][C]0.232119[/C][C]0.11606[/C][/ROW]
[ROW][C]155[/C][C]0.886409[/C][C]0.227182[/C][C]0.113591[/C][/ROW]
[ROW][C]156[/C][C]0.872579[/C][C]0.254842[/C][C]0.127421[/C][/ROW]
[ROW][C]157[/C][C]0.860012[/C][C]0.279976[/C][C]0.139988[/C][/ROW]
[ROW][C]158[/C][C]0.860296[/C][C]0.279408[/C][C]0.139704[/C][/ROW]
[ROW][C]159[/C][C]0.866947[/C][C]0.266105[/C][C]0.133053[/C][/ROW]
[ROW][C]160[/C][C]0.854783[/C][C]0.290434[/C][C]0.145217[/C][/ROW]
[ROW][C]161[/C][C]0.851647[/C][C]0.296706[/C][C]0.148353[/C][/ROW]
[ROW][C]162[/C][C]0.836746[/C][C]0.326508[/C][C]0.163254[/C][/ROW]
[ROW][C]163[/C][C]0.813508[/C][C]0.372984[/C][C]0.186492[/C][/ROW]
[ROW][C]164[/C][C]0.944324[/C][C]0.111351[/C][C]0.0556755[/C][/ROW]
[ROW][C]165[/C][C]0.933588[/C][C]0.132823[/C][C]0.0664117[/C][/ROW]
[ROW][C]166[/C][C]0.928936[/C][C]0.142128[/C][C]0.071064[/C][/ROW]
[ROW][C]167[/C][C]0.915857[/C][C]0.168286[/C][C]0.0841428[/C][/ROW]
[ROW][C]168[/C][C]0.915586[/C][C]0.168829[/C][C]0.0844145[/C][/ROW]
[ROW][C]169[/C][C]0.911639[/C][C]0.176722[/C][C]0.088361[/C][/ROW]
[ROW][C]170[/C][C]0.918028[/C][C]0.163945[/C][C]0.0819725[/C][/ROW]
[ROW][C]171[/C][C]0.902997[/C][C]0.194006[/C][C]0.0970029[/C][/ROW]
[ROW][C]172[/C][C]0.902043[/C][C]0.195913[/C][C]0.0979565[/C][/ROW]
[ROW][C]173[/C][C]0.895831[/C][C]0.208338[/C][C]0.104169[/C][/ROW]
[ROW][C]174[/C][C]0.882622[/C][C]0.234756[/C][C]0.117378[/C][/ROW]
[ROW][C]175[/C][C]0.868645[/C][C]0.26271[/C][C]0.131355[/C][/ROW]
[ROW][C]176[/C][C]0.860125[/C][C]0.27975[/C][C]0.139875[/C][/ROW]
[ROW][C]177[/C][C]0.841278[/C][C]0.317444[/C][C]0.158722[/C][/ROW]
[ROW][C]178[/C][C]0.836331[/C][C]0.327338[/C][C]0.163669[/C][/ROW]
[ROW][C]179[/C][C]0.826528[/C][C]0.346943[/C][C]0.173472[/C][/ROW]
[ROW][C]180[/C][C]0.826811[/C][C]0.346378[/C][C]0.173189[/C][/ROW]
[ROW][C]181[/C][C]0.841265[/C][C]0.317471[/C][C]0.158735[/C][/ROW]
[ROW][C]182[/C][C]0.833541[/C][C]0.332919[/C][C]0.166459[/C][/ROW]
[ROW][C]183[/C][C]0.824906[/C][C]0.350189[/C][C]0.175094[/C][/ROW]
[ROW][C]184[/C][C]0.808781[/C][C]0.382437[/C][C]0.191219[/C][/ROW]
[ROW][C]185[/C][C]0.898588[/C][C]0.202824[/C][C]0.101412[/C][/ROW]
[ROW][C]186[/C][C]0.882039[/C][C]0.235922[/C][C]0.117961[/C][/ROW]
[ROW][C]187[/C][C]0.891043[/C][C]0.217914[/C][C]0.108957[/C][/ROW]
[ROW][C]188[/C][C]0.904368[/C][C]0.191264[/C][C]0.095632[/C][/ROW]
[ROW][C]189[/C][C]0.890591[/C][C]0.218818[/C][C]0.109409[/C][/ROW]
[ROW][C]190[/C][C]0.871204[/C][C]0.257593[/C][C]0.128796[/C][/ROW]
[ROW][C]191[/C][C]0.851768[/C][C]0.296463[/C][C]0.148232[/C][/ROW]
[ROW][C]192[/C][C]0.835981[/C][C]0.328038[/C][C]0.164019[/C][/ROW]
[ROW][C]193[/C][C]0.871707[/C][C]0.256587[/C][C]0.128293[/C][/ROW]
[ROW][C]194[/C][C]0.866357[/C][C]0.267285[/C][C]0.133643[/C][/ROW]
[ROW][C]195[/C][C]0.843536[/C][C]0.312929[/C][C]0.156464[/C][/ROW]
[ROW][C]196[/C][C]0.821018[/C][C]0.357963[/C][C]0.178982[/C][/ROW]
[ROW][C]197[/C][C]0.856459[/C][C]0.287082[/C][C]0.143541[/C][/ROW]
[ROW][C]198[/C][C]0.832234[/C][C]0.335532[/C][C]0.167766[/C][/ROW]
[ROW][C]199[/C][C]0.844557[/C][C]0.310886[/C][C]0.155443[/C][/ROW]
[ROW][C]200[/C][C]0.819851[/C][C]0.360298[/C][C]0.180149[/C][/ROW]
[ROW][C]201[/C][C]0.800147[/C][C]0.399707[/C][C]0.199853[/C][/ROW]
[ROW][C]202[/C][C]0.773134[/C][C]0.453732[/C][C]0.226866[/C][/ROW]
[ROW][C]203[/C][C]0.751362[/C][C]0.497277[/C][C]0.248638[/C][/ROW]
[ROW][C]204[/C][C]0.723635[/C][C]0.552729[/C][C]0.276365[/C][/ROW]
[ROW][C]205[/C][C]0.706285[/C][C]0.587431[/C][C]0.293715[/C][/ROW]
[ROW][C]206[/C][C]0.776555[/C][C]0.446891[/C][C]0.223445[/C][/ROW]
[ROW][C]207[/C][C]0.764722[/C][C]0.470556[/C][C]0.235278[/C][/ROW]
[ROW][C]208[/C][C]0.745693[/C][C]0.508615[/C][C]0.254307[/C][/ROW]
[ROW][C]209[/C][C]0.72722[/C][C]0.545561[/C][C]0.27278[/C][/ROW]
[ROW][C]210[/C][C]0.696866[/C][C]0.606269[/C][C]0.303134[/C][/ROW]
[ROW][C]211[/C][C]0.703486[/C][C]0.593028[/C][C]0.296514[/C][/ROW]
[ROW][C]212[/C][C]0.664316[/C][C]0.671369[/C][C]0.335684[/C][/ROW]
[ROW][C]213[/C][C]0.641069[/C][C]0.717862[/C][C]0.358931[/C][/ROW]
[ROW][C]214[/C][C]0.601009[/C][C]0.797983[/C][C]0.398991[/C][/ROW]
[ROW][C]215[/C][C]0.55747[/C][C]0.885059[/C][C]0.44253[/C][/ROW]
[ROW][C]216[/C][C]0.515255[/C][C]0.969489[/C][C]0.484745[/C][/ROW]
[ROW][C]217[/C][C]0.476793[/C][C]0.953586[/C][C]0.523207[/C][/ROW]
[ROW][C]218[/C][C]0.452758[/C][C]0.905516[/C][C]0.547242[/C][/ROW]
[ROW][C]219[/C][C]0.416899[/C][C]0.833799[/C][C]0.583101[/C][/ROW]
[ROW][C]220[/C][C]0.396398[/C][C]0.792796[/C][C]0.603602[/C][/ROW]
[ROW][C]221[/C][C]0.389723[/C][C]0.779446[/C][C]0.610277[/C][/ROW]
[ROW][C]222[/C][C]0.380422[/C][C]0.760845[/C][C]0.619578[/C][/ROW]
[ROW][C]223[/C][C]0.354949[/C][C]0.709897[/C][C]0.645051[/C][/ROW]
[ROW][C]224[/C][C]0.327935[/C][C]0.65587[/C][C]0.672065[/C][/ROW]
[ROW][C]225[/C][C]0.34197[/C][C]0.68394[/C][C]0.65803[/C][/ROW]
[ROW][C]226[/C][C]0.369471[/C][C]0.738942[/C][C]0.630529[/C][/ROW]
[ROW][C]227[/C][C]0.378279[/C][C]0.756558[/C][C]0.621721[/C][/ROW]
[ROW][C]228[/C][C]0.527792[/C][C]0.944416[/C][C]0.472208[/C][/ROW]
[ROW][C]229[/C][C]0.618661[/C][C]0.762678[/C][C]0.381339[/C][/ROW]
[ROW][C]230[/C][C]0.646257[/C][C]0.707486[/C][C]0.353743[/C][/ROW]
[ROW][C]231[/C][C]0.711234[/C][C]0.577532[/C][C]0.288766[/C][/ROW]
[ROW][C]232[/C][C]0.749391[/C][C]0.501218[/C][C]0.250609[/C][/ROW]
[ROW][C]233[/C][C]0.733398[/C][C]0.533204[/C][C]0.266602[/C][/ROW]
[ROW][C]234[/C][C]0.708179[/C][C]0.583642[/C][C]0.291821[/C][/ROW]
[ROW][C]235[/C][C]0.694788[/C][C]0.610423[/C][C]0.305212[/C][/ROW]
[ROW][C]236[/C][C]0.785055[/C][C]0.42989[/C][C]0.214945[/C][/ROW]
[ROW][C]237[/C][C]0.741545[/C][C]0.516911[/C][C]0.258455[/C][/ROW]
[ROW][C]238[/C][C]0.70478[/C][C]0.59044[/C][C]0.29522[/C][/ROW]
[ROW][C]239[/C][C]0.649705[/C][C]0.70059[/C][C]0.350295[/C][/ROW]
[ROW][C]240[/C][C]0.628726[/C][C]0.742548[/C][C]0.371274[/C][/ROW]
[ROW][C]241[/C][C]0.574414[/C][C]0.851172[/C][C]0.425586[/C][/ROW]
[ROW][C]242[/C][C]0.521934[/C][C]0.956132[/C][C]0.478066[/C][/ROW]
[ROW][C]243[/C][C]0.504814[/C][C]0.990371[/C][C]0.495186[/C][/ROW]
[ROW][C]244[/C][C]0.446198[/C][C]0.892397[/C][C]0.553802[/C][/ROW]
[ROW][C]245[/C][C]0.38249[/C][C]0.764981[/C][C]0.61751[/C][/ROW]
[ROW][C]246[/C][C]0.35581[/C][C]0.711621[/C][C]0.64419[/C][/ROW]
[ROW][C]247[/C][C]0.292149[/C][C]0.584298[/C][C]0.707851[/C][/ROW]
[ROW][C]248[/C][C]0.42593[/C][C]0.85186[/C][C]0.57407[/C][/ROW]
[ROW][C]249[/C][C]0.386988[/C][C]0.773976[/C][C]0.613012[/C][/ROW]
[ROW][C]250[/C][C]0.322066[/C][C]0.644131[/C][C]0.677934[/C][/ROW]
[ROW][C]251[/C][C]0.269953[/C][C]0.539906[/C][C]0.730047[/C][/ROW]
[ROW][C]252[/C][C]0.217692[/C][C]0.435384[/C][C]0.782308[/C][/ROW]
[ROW][C]253[/C][C]0.190634[/C][C]0.381269[/C][C]0.809366[/C][/ROW]
[ROW][C]254[/C][C]0.236081[/C][C]0.472162[/C][C]0.763919[/C][/ROW]
[ROW][C]255[/C][C]0.174015[/C][C]0.348031[/C][C]0.825985[/C][/ROW]
[ROW][C]256[/C][C]0.239433[/C][C]0.478865[/C][C]0.760567[/C][/ROW]
[ROW][C]257[/C][C]0.209343[/C][C]0.418686[/C][C]0.790657[/C][/ROW]
[ROW][C]258[/C][C]0.577133[/C][C]0.845734[/C][C]0.422867[/C][/ROW]
[ROW][C]259[/C][C]0.793308[/C][C]0.413385[/C][C]0.206692[/C][/ROW]
[ROW][C]260[/C][C]0.970433[/C][C]0.0591347[/C][C]0.0295673[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&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
180.7843270.4313460.215673
190.6551860.6896280.344814
200.5276060.9447890.472394
210.5163530.9672940.483647
220.4585580.9171150.541442
230.5682390.8635220.431761
240.4700160.9400330.529984
250.3753350.7506690.624665
260.3085410.6170810.691459
270.2934240.5868480.706576
280.3336870.6673750.666313
290.2620380.5240760.737962
300.2515460.5030920.748454
310.2563760.5127510.743624
320.2073210.4146420.792679
330.1855670.3711330.814433
340.1749970.3499940.825003
350.1341330.2682660.865867
360.120040.240080.87996
370.09358970.1871790.90641
380.1211740.2423480.878826
390.2325930.4651870.767407
400.1877350.375470.812265
410.2796420.5592830.720358
420.2485760.4971530.751424
430.2629110.5258230.737089
440.2196750.4393490.780325
450.1891530.3783070.810847
460.1601130.3202260.839887
470.1798960.3597920.820104
480.2372140.4744270.762786
490.2683680.5367370.731632
500.3053060.6106130.694694
510.261010.522020.73899
520.3273980.6547970.672602
530.3274790.6549570.672521
540.3851510.7703020.614849
550.6227640.7544730.377236
560.5766270.8467460.423373
570.7974420.4051170.202558
580.8240210.3519570.175979
590.7942260.4115480.205774
600.8149490.3701020.185051
610.8208120.3583760.179188
620.7982950.403410.201705
630.9165750.166850.0834252
640.9451130.1097750.0548874
650.9386650.122670.061335
660.9317770.1364460.068223
670.9254520.1490950.0745476
680.9094890.1810230.0905113
690.9237780.1524440.0762221
700.909680.1806390.0903195
710.8920540.2158930.107946
720.8856110.2287790.114389
730.8713020.2573960.128698
740.8672120.2655760.132788
750.861120.2777610.13888
760.8530770.2938470.146923
770.836520.3269590.16348
780.8404970.3190050.159503
790.8170490.3659020.182951
800.8288260.3423480.171174
810.8072650.3854710.192735
820.8430040.3139910.156996
830.8192840.3614310.180716
840.8862130.2275750.113787
850.8726820.2546360.127318
860.8531840.2936310.146816
870.8372620.3254760.162738
880.816430.367140.18357
890.8177580.3644840.182242
900.8213380.3573240.178662
910.860730.278540.13927
920.9284870.1430260.0715129
930.9156950.168610.0843048
940.9071960.1856080.0928041
950.9239170.1521670.0760833
960.9101820.1796350.0898176
970.9122230.1755530.0877766
980.9083420.1833160.0916582
990.9241370.1517250.0758627
1000.9489860.1020280.051014
1010.9436470.1127060.056353
1020.9326430.1347130.0673567
1030.9298170.1403660.0701832
1040.9226650.154670.0773349
1050.9411410.1177170.0588587
1060.932680.134640.0673202
1070.9501440.09971170.0498558
1080.9663260.06734840.0336742
1090.9668770.06624510.0331226
1100.9643330.07133440.0356672
1110.9592540.08149250.0407462
1120.950740.09851990.04926
1130.9658870.06822570.0341129
1140.9686980.06260460.0313023
1150.9690420.0619150.0309575
1160.9665630.06687310.0334366
1170.9644020.07119570.0355978
1180.9601580.07968470.0398423
1190.9631170.07376510.0368826
1200.960060.07987980.0399399
1210.9623550.07529070.0376453
1220.9666560.06668720.0333436
1230.9596160.08076770.0403839
1240.9815570.03688680.0184434
1250.9853050.02938990.0146949
1260.9819970.0360050.0180025
1270.9785840.04283290.0214165
1280.9759780.04804320.0240216
1290.9720270.0559460.027973
1300.9675220.06495580.0324779
1310.9611040.07779210.038896
1320.9561140.08777290.0438864
1330.9542570.09148550.0457428
1340.9471080.1057850.0528923
1350.9392580.1214830.0607417
1360.9289090.1421810.0710907
1370.9409470.1181070.0590533
1380.947520.1049590.0524795
1390.9391650.121670.0608348
1400.9296450.140710.0703549
1410.9227810.1544390.0772193
1420.9197640.1604720.0802362
1430.9076710.1846580.0923292
1440.905230.189540.0947702
1450.8895550.220890.110445
1460.8739320.2521360.126068
1470.8632870.2734270.136713
1480.8433290.3133410.156671
1490.8369140.3261710.163086
1500.8171870.3656250.182813
1510.9197110.1605770.0802885
1520.9126240.1747510.0873757
1530.9007830.1984350.0992173
1540.883940.2321190.11606
1550.8864090.2271820.113591
1560.8725790.2548420.127421
1570.8600120.2799760.139988
1580.8602960.2794080.139704
1590.8669470.2661050.133053
1600.8547830.2904340.145217
1610.8516470.2967060.148353
1620.8367460.3265080.163254
1630.8135080.3729840.186492
1640.9443240.1113510.0556755
1650.9335880.1328230.0664117
1660.9289360.1421280.071064
1670.9158570.1682860.0841428
1680.9155860.1688290.0844145
1690.9116390.1767220.088361
1700.9180280.1639450.0819725
1710.9029970.1940060.0970029
1720.9020430.1959130.0979565
1730.8958310.2083380.104169
1740.8826220.2347560.117378
1750.8686450.262710.131355
1760.8601250.279750.139875
1770.8412780.3174440.158722
1780.8363310.3273380.163669
1790.8265280.3469430.173472
1800.8268110.3463780.173189
1810.8412650.3174710.158735
1820.8335410.3329190.166459
1830.8249060.3501890.175094
1840.8087810.3824370.191219
1850.8985880.2028240.101412
1860.8820390.2359220.117961
1870.8910430.2179140.108957
1880.9043680.1912640.095632
1890.8905910.2188180.109409
1900.8712040.2575930.128796
1910.8517680.2964630.148232
1920.8359810.3280380.164019
1930.8717070.2565870.128293
1940.8663570.2672850.133643
1950.8435360.3129290.156464
1960.8210180.3579630.178982
1970.8564590.2870820.143541
1980.8322340.3355320.167766
1990.8445570.3108860.155443
2000.8198510.3602980.180149
2010.8001470.3997070.199853
2020.7731340.4537320.226866
2030.7513620.4972770.248638
2040.7236350.5527290.276365
2050.7062850.5874310.293715
2060.7765550.4468910.223445
2070.7647220.4705560.235278
2080.7456930.5086150.254307
2090.727220.5455610.27278
2100.6968660.6062690.303134
2110.7034860.5930280.296514
2120.6643160.6713690.335684
2130.6410690.7178620.358931
2140.6010090.7979830.398991
2150.557470.8850590.44253
2160.5152550.9694890.484745
2170.4767930.9535860.523207
2180.4527580.9055160.547242
2190.4168990.8337990.583101
2200.3963980.7927960.603602
2210.3897230.7794460.610277
2220.3804220.7608450.619578
2230.3549490.7098970.645051
2240.3279350.655870.672065
2250.341970.683940.65803
2260.3694710.7389420.630529
2270.3782790.7565580.621721
2280.5277920.9444160.472208
2290.6186610.7626780.381339
2300.6462570.7074860.353743
2310.7112340.5775320.288766
2320.7493910.5012180.250609
2330.7333980.5332040.266602
2340.7081790.5836420.291821
2350.6947880.6104230.305212
2360.7850550.429890.214945
2370.7415450.5169110.258455
2380.704780.590440.29522
2390.6497050.700590.350295
2400.6287260.7425480.371274
2410.5744140.8511720.425586
2420.5219340.9561320.478066
2430.5048140.9903710.495186
2440.4461980.8923970.553802
2450.382490.7649810.61751
2460.355810.7116210.64419
2470.2921490.5842980.707851
2480.425930.851860.57407
2490.3869880.7739760.613012
2500.3220660.6441310.677934
2510.2699530.5399060.730047
2520.2176920.4353840.782308
2530.1906340.3812690.809366
2540.2360810.4721620.763919
2550.1740150.3480310.825985
2560.2394330.4788650.760567
2570.2093430.4186860.790657
2580.5771330.8457340.422867
2590.7933080.4133850.206692
2600.9704330.05913470.0295673






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0205761OK
10% type I error level280.115226NOK

\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 & 5 & 0.0205761 & OK \tabularnewline
10% type I error level & 28 & 0.115226 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265514&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]5[/C][C]0.0205761[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]28[/C][C]0.115226[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265514&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265514&T=6

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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 level50.0205761OK
10% type I error level280.115226NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 15 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 15 ; 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')
}