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Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Wed, 10 Dec 2014 12:50:35 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418215874i5idouh0bq07ngo.htm/, Retrieved Sun, 19 May 2024 16:11:51 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265055, Retrieved Sun, 19 May 2024 16:11:51 +0000

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Estimated Impact

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

-       [Multiple Regression] [] [2014-12-10 12:50:35] [bfb0b3163eb17a9053d1f02c7e530193] [Current]

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Dataseries X:

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11 8 7 18 12 20 1.00 0.50 0.67 0.67 0.00 0.50 12.9 149 4 68
19 18 20 23 20 19 0.89 0.50 0.83 0.33 0.50 1.00 12.2 139 4 39
16 12 9 22 14 18 0.89 0.40 1.00 0.67 0.00 1.00 12.8 148 5 32
24 24 19 22 25 24 0.89 0.50 0.83 0.00 0.00 0.00 7.4 158 4 62
15 16 12 19 15 20 0.89 0.70 0.67 0.00 1.00 1.00 6.7 128 4 33
17 19 16 25 20 20 0.78 0.30 0.00 0.00 0.50 0.50 12.6 224 9 52
19 16 17 28 21 24 0.89 0.40 0.83 0.67 0.50 0.00 14.8 159 8 62
19 15 9 16 15 21 1.00 0.40 0.50 0.67 1.00 1.00 13.3 105 11 77
28 28 28 28 28 28 0.89 0.70 0.83 0.00 0.50 0.00 11.1 159 4 76
26 21 20 21 11 10 0.78 0.60 0.33 0.67 0.50 0.50 8.2 167 4 41
15 18 16 22 22 22 1.00 0.60 0.50 1.00 0.00 0.50 11.4 165 6 48
26 22 22 24 22 19 0.78 0.20 0.67 0.00 0.50 0.50 6.4 159 4 63
16 19 17 24 27 27 0.89 0.40 1.00 0.00 0.50 0.50 10.6 119 8 30
24 22 12 26 24 23 0.89 0.40 0.50 0.67 0.00 1.00 12.0 176 4 78
25 25 18 28 23 24 0.89 0.50 0.67 0.33 0.00 0.00 6.3 54 4 19
22 20 20 24 24 24 0.89 0.30 0.17 0.67 0.00 0.50 11.3 91 11 31
15 16 12 20 21 25 0.89 0.40 0.83 0.33 0.50 0.50 11.9 163 4 66
21 19 16 26 20 24 0.67 0.70 0.67 0.33 0.50 1.00 9.3 124 4 35
22 18 16 21 19 21 1.00 0.50 0.67 0.33 0.00 1.00 9.6 137 6 42
27 26 21 28 25 28 0.78 0.20 0.67 0.00 0.00 1.00 10.0 121 6 45
26 24 15 27 16 28 0.78 0.30 0.50 0.67 0.00 0.50 6.4 153 4 21
26 20 17 23 24 22 0.89 0.60 1.00 0.33 0.00 1.00 13.8 148 8 25
22 19 17 24 21 26 0.78 0.60 0.83 0.33 0.00 1.00 10.8 221 5 44
21 19 17 24 22 26 0.89 0.20 0.83 0.33 0.00 1.00 13.8 188 4 69
22 23 18 22 25 21 0.89 0.70 1.00 0.67 1.00 0.00 11.7 149 9 54
20 18 15 21 23 26 0.33 0.20 0.67 0.00 0.00 0.00 10.9 244 4 74
21 16 20 25 20 23 1.00 1.00 1.00 0.33 1.00 1.00 16.1 148 7 80
20 18 13 20 21 20 0.89 0.40 0.83 0.67 0.00 0.50 13.4 92 10 42
22 21 21 21 22 24 0.89 0.40 1.00 1.00 0.00 1.00 9.9 150 4 61
21 20 12 26 25 25 0.67 0.20 0.83 0.67 0.00 0.50 11.5 153 4 41
8 15 6 23 23 24 0.56 0.40 0.67 0.33 0.00 1.00 8.3 94 7 46
22 19 13 21 19 20 0.89 0.40 0.67 0.00 0.50 1.00 11.7 156 12 39
20 19 19 27 21 24 0.89 0.70 1.00 0.67 0.50 0.50 9.0 132 7 34
24 7 12 25 19 25 1.00 0.20 0.67 0.67 0.00 0.50 9.7 161 5 51
17 20 14 23 25 23 0.78 0.60 1.00 1.00 0.00 0.50 10.8 105 8 42
20 20 13 25 16 21 0.78 0.30 1.00 1.00 0.50 0.50 10.3 97 5 31
23 19 12 23 24 23 0.33 0.30 0.50 0.33 0.00 0.00 10.4 151 4 39
20 19 17 19 24 21 0.78 0.20 0.67 0.00 0.50 0.00 12.7 131 9 20
22 20 19 22 18 18 0.89 0.50 0.83 0.67 0.50 0.50 9.3 166 7 49
19 18 10 24 28 24 0.89 0.70 1.00 0.67 0.50 1.00 11.8 157 4 53
15 14 10 19 15 18 0.78 0.60 1.00 0.67 0.50 0.50 5.9 111 4 31
20 17 11 21 17 21 0.89 0.40 1.00 0.67 0.50 1.00 11.4 145 4 39
22 17 11 27 18 23 0.89 0.60 1.00 0.33 0.50 1.00 13.0 162 4 54
17 8 10 25 26 25 1.00 0.40 1.00 1.00 0.00 1.00 10.8 163 4 49
14 9 7 25 18 22 0.67 0.30 0.83 0.67 0.00 1.00 12.3 59 7 34
24 22 22 23 22 22 1.00 0.50 0.83 0.67 0.50 0.50 11.3 187 4 46
17 20 12 17 19 23 0.89 0.20 0.50 0.00 0.00 1.00 11.8 109 7 55
23 20 18 28 17 24 0.89 0.30 0.83 0.00 0.50 1.00 7.9 90 4 42
25 22 20 25 26 25 0.89 0.50 0.17 0.00 0.00 1.00 12.7 105 4 50
16 22 9 20 21 22 0.78 0.70 0.83 1.00 0.50 1.00 12.3 83 4 13
18 22 16 25 26 24 0.89 0.40 1.00 0.67 1.00 0.50 11.6 116 4 37
20 16 14 21 21 21 0.78 0.30 1.00 0.00 0.00 0.50 6.7 42 8 25
18 14 11 24 12 24 0.78 0.20 0.67 0.67 1.00 1.00 10.9 148 4 30
23 24 20 28 20 25 1.00 0.50 1.00 0.00 0.00 0.50 12.1 155 4 28
24 21 17 20 20 23 0.78 0.40 1.00 0.00 0.50 0.00 13.3 125 4 45
23 20 14 19 24 27 1.00 0.60 1.00 0.67 1.00 1.00 10.1 116 4 35
13 20 8 24 24 27 0.78 0.40 0.83 1.00 0.00 1.00 5.7 128 7 28
20 18 16 21 22 23 0.67 0.40 0.33 0.00 0.00 0.50 14.3 138 12 41
20 14 11 24 21 18 0.33 0.20 0.33 0.33 0.00 0.00 8.0 49 4 6
19 19 10 23 20 20 1.00 0.90 1.00 0.67 0.50 1.00 13.3 96 4 45
22 24 15 18 23 23 1.00 0.80 1.00 0.67 1.00 0.50 9.3 164 4 73
22 19 15 27 19 24 0.78 0.80 0.83 0.00 0.50 1.00 12.5 162 5 17
15 16 10 25 24 26 0.67 0.30 1.00 1.00 0.50 1.00 7.6 99 15 40
17 16 10 20 21 20 1.00 0.20 0.83 0.67 0.00 0.50 15.9 202 5 64
19 16 18 21 16 23 0.89 0.40 0.67 0.00 0.50 1.00 9.2 186 10 37
20 14 10 23 17 22 0.89 0.20 0.83 1.00 0.00 1.00 9.1 66 9 25
22 22 22 27 23 23 0.78 0.20 0.67 0.67 0.50 1.00 11.1 183 8 65
21 21 16 24 20 17 1.00 0.10 0.83 0.67 0.00 1.00 13.0 214 4 100
21 15 10 27 19 20 0.56 0.40 0.67 1.00 0.50 0.00 14.5 188 5 28
16 14 7 24 18 22 0.67 0.50 1.00 0.00 0.50 0.50 12.2 104 4 35
20 15 16 23 18 18 0.89 0.80 0.83 0.33 0.50 1.00 12.3 177 9 56
21 14 16 24 21 19 0.89 0.40 0.67 0.67 0.00 0.50 11.4 126 4 29
20 20 16 21 20 19 0.89 0.60 0.83 0.33 0.50 0.50 8.8 76 10 43
23 21 22 23 17 16 0.89 0.50 0.83 0.67 0.50 1.00 14.6 99 4 59
18 14 5 27 25 26 0.78 0.30 0.67 0.00 0.00 0.00 12.6 139 4 50
22 19 18 24 15 14 0.89 0.80 1.00 1.00 0.50 1.00 NA 78 6 3
16 16 10 25 17 25 1.00 0.40 0.33 0.00 0.50 0.00 13.0 162 7 59
17 13 8 19 17 23 1.00 0.60 0.83 0.67 0.50 0.50 12.6 108 5 27
24 26 16 24 24 18 0.89 0.40 1.00 0.33 0.00 0.50 13.2 159 4 61
13 13 8 25 21 22 0.44 0.30 0.83 0.00 0.00 0.00 9.9 74 4 28
19 18 16 23 22 26 0.78 0.80 0.83 0.00 1.00 1.00 7.7 110 4 51
20 15 14 23 18 25 0.89 0.60 0.50 0.33 1.00 1.00 10.5 96 4 35
22 18 15 25 22 26 0.67 0.30 0.50 0.00 0.00 0.00 13.4 116 4 29
19 21 9 26 20 26 0.78 0.50 0.83 0.67 0.50 1.00 10.9 87 4 48
21 17 21 26 21 24 0.78 0.40 1.00 0.33 0.00 1.00 4.3 97 6 25
15 18 7 16 21 22 0.33 0.30 0.33 0.67 0.00 0.00 10.3 127 10 44
21 20 17 23 20 21 0.89 0.70 1.00 0.33 0.00 0.50 11.8 106 7 64
24 18 18 26 18 22 0.89 0.20 0.67 0.33 0.50 0.50 11.2 80 4 32
22 25 16 25 25 28 0.89 0.40 0.83 1.00 0.00 1.00 11.4 74 4 20
20 20 16 23 23 22 0.89 0.60 1.00 0.67 0.50 0.50 8.6 91 7 28
21 19 14 26 21 26 0.56 0.60 0.83 0.00 0.00 1.00 13.2 133 4 34
19 18 15 22 20 20 0.67 0.60 0.83 0.67 0.50 0.50 12.6 74 8 31
14 12 8 20 21 24 0.67 0.40 1.00 0.33 0.50 1.00 5.6 114 11 26
25 22 22 27 20 21 0.78 0.60 0.83 0.00 0.00 1.00 9.9 140 6 58
11 16 5 20 22 23 0.78 0.50 1.00 0.33 0.50 1.00 8.8 95 14 23
17 18 13 22 15 23 0.78 0.50 0.83 0.00 0.00 1.00 7.7 98 5 21
22 23 22 24 24 23 0.89 0.60 0.67 0.00 0.00 1.00 9.0 121 4 21
20 20 18 21 22 22 1.00 0.80 0.83 0.33 0.50 1.00 7.3 126 8 33
22 20 15 24 21 23 0.89 0.50 0.83 0.67 1.00 0.50 11.4 98 9 16
15 16 11 26 17 21 0.89 0.60 0.83 0.67 0.50 1.00 13.6 95 4 20
23 22 19 24 23 27 0.78 0.40 0.83 0.67 0.50 1.00 7.9 110 4 37
20 19 19 24 22 23 1.00 0.30 0.67 0.67 0.50 1.00 10.7 70 5 35
22 23 21 27 23 26 0.78 0.30 0.83 1.00 0.00 0.50 10.3 102 4 33
16 6 4 25 16 27 0.67 0.20 0.00 0.00 0.00 0.00 8.3 86 5 27
25 19 17 27 18 27 0.78 0.40 0.83 0.00 0.00 0.50 9.6 130 4 41
18 24 10 19 25 23 0.89 0.50 1.00 0.00 0.00 0.50 14.2 96 4 40
19 19 13 22 18 23 0.67 0.30 0.17 0.00 0.50 0.00 8.5 102 7 35
25 15 15 22 14 23 0.22 0.40 0.17 0.00 0.50 0.00 13.5 100 10 28
21 18 11 25 20 28 0.44 0.50 0.50 1.00 0.00 0.00 4.9 94 4 32
22 18 20 23 19 24 0.89 0.30 0.50 0.67 0.00 1.00 6.4 52 5 22
21 22 13 24 18 20 0.67 0.50 1.00 0.00 0.00 0.50 9.6 98 4 44
22 23 18 24 22 23 0.89 0.40 0.67 0.67 0.00 0.50 11.6 118 4 27
23 18 20 23 21 22 0.67 0.40 0.83 0.67 0.00 1.00 11.1 99 4 17
20 17 15 22 14 15 0.78 0.60 1.00 0.00 1.00 1.00 4.35 48 6 12
6 6 4 24 5 27 0.78 0.30 1.00 0.67 1.00 1.00 12.7 50 4 45
15 22 9 19 25 23 0.78 0.40 1.00 0.33 1.00 0.50 18.1 150 8 37
18 20 18 25 21 23 1.00 0.30 1.00 1.00 1.00 1.00 17.85 154 5 37
24 16 12 26 11 20 0.78 1.00 1.00 1.00 1.00 1.00 16.6 109 4 108
22 16 17 18 20 18 0.67 0.40 1.00 0.00 0.00 0.50 12.6 68 17 10
21 17 12 24 9 22 0.89 0.80 0.83 1.00 0.50 1.00 17.1 194 4 68
23 20 16 28 15 20 0.89 0.30 1.00 0.67 1.00 1.00 19.1 158 4 72
20 23 17 23 23 21 1.00 0.50 0.83 0.67 0.00 1.00 16.1 159 8 143
20 18 14 19 21 25 0.78 0.40 1.00 0.00 0.00 0.50 13.35 67 4 9
18 13 13 19 9 19 0.67 0.30 0.83 0.67 0.00 1.00 18.4 147 7 55
25 22 20 27 24 25 0.89 0.50 0.83 1.00 0.00 1.00 14.7 39 4 17
16 20 16 24 16 24 0.67 0.30 1.00 0.67 0.00 1.00 10.6 100 4 37
20 20 15 26 20 22 0.67 0.30 0.67 0.00 0.00 1.00 12.6 111 5 27
14 13 10 21 15 28 1.00 0.40 0.83 0.00 0.00 1.00 16.2 138 7 37
22 16 16 25 18 22 0.67 0.30 1.00 0.00 0.00 0.50 13.6 101 4 58
26 25 21 28 22 21 1.00 0.60 1.00 0.33 0.50 0.50 18.9 131 4 66
20 16 15 19 21 23 0.89 0.60 0.83 0.67 1.00 1.00 14.1 101 7 21
17 15 16 20 21 19 0.89 0.40 1.00 1.00 1.00 1.00 14.5 114 11 19
22 19 19 26 21 21 1.00 0.40 1.00 0.00 0.00 0.00 16.15 165 7 78
22 19 9 27 20 25 0.67 0.40 1.00 0.67 0.00 0.50 14.75 114 4 35
20 24 19 23 24 23 0.44 0.30 0.67 0.67 0.50 1.00 14.8 111 4 48
17 9 7 18 15 28 0.89 0.20 1.00 0.33 1.00 0.00 12.45 75 4 27
22 22 23 23 24 14 0.56 0.50 0.83 0.67 0.00 1.00 12.65 82 4 43
17 15 14 21 18 23 0.78 0.40 1.00 0.67 1.00 1.00 17.35 121 4 30
22 22 10 23 24 24 1.00 0.40 1.00 0.67 0.00 0.00 8.6 32 4 25
21 22 16 22 24 25 1.00 0.40 0.83 0.67 0.00 1.00 18.4 150 6 69
25 24 12 21 15 15 0.89 0.30 0.67 0.67 0.50 0.50 16.1 117 8 72
11 12 10 14 19 23 0.67 0.40 0.83 0.67 1.00 0.50 11.6 71 23 23
19 21 7 24 20 26 0.89 0.20 1.00 0.33 0.50 1.00 17.75 165 4 13
24 25 20 26 26 21 0.33 0.00 0.00 0.00 0.00 0.00 15.25 154 8 61
17 26 9 24 26 26 0.89 0.40 1.00 0.67 0.50 1.00 17.65 126 6 43
22 21 12 22 23 23 0.78 0.60 1.00 0.00 1.00 1.00 16.35 149 4 51
17 14 10 20 13 15 1.00 0.40 0.67 0.67 0.00 0.50 17.65 145 7 67
26 28 19 20 16 16 0.44 0.40 1.00 0.00 0.00 0.50 13.6 120 4 36
20 21 11 18 22 20 0.67 0.40 0.83 0.00 0.50 0.00 14.35 109 4 44
19 16 15 18 21 20 0.33 0.20 0.17 0.00 0.50 0.00 14.75 132 4 45
21 16 14 25 11 21 0.89 0.40 0.83 1.00 1.00 1.00 18.25 172 10 34
24 25 11 28 23 28 0.89 0.30 0.83 0.00 0.00 0.50 9.9 169 6 36
21 21 14 23 18 19 1.00 0.60 0.83 0.67 1.00 0.00 16 114 5 72
19 22 15 20 19 21 0.89 0.60 0.83 1.00 0.00 1.00 18.25 156 5 39
13 9 7 22 15 22 0.89 0.40 0.83 0.00 0.00 1.00 16.85 172 4 43
24 20 22 27 8 27 1.00 0.50 1.00 0.67 1.00 0.50 14.6 68 4 25
28 19 19 24 15 20 0.89 0.40 0.83 0.00 0.50 1.00 13.85 89 5 56
27 24 22 23 21 17 1.00 0.60 1.00 1.00 1.00 1.00 18.95 167 5 80
22 22 11 20 25 26 0.78 0.60 0.83 0.67 0.50 1.00 15.6 113 5 40
23 22 19 22 14 21 0.78 0.90 1.00 0.67 0.50 1.00 14.85 115 5 73
19 12 9 21 21 24 0.67 0.40 0.83 0.67 0.50 0.00 11.75 78 4 34
18 17 11 24 18 21 0.89 0.80 1.00 1.00 0.50 1.00 18.45 118 6 72
23 18 17 26 18 25 0.67 0.50 0.83 1.00 0.00 1.00 15.9 87 4 42
21 10 12 24 12 22 0.78 0.40 0.83 1.00 0.00 0.00 17.1 173 4 61
22 22 17 18 24 17 0.89 0.40 1.00 0.67 1.00 0.50 16.1 2 4 23
17 24 10 17 17 14 0.89 0.70 1.00 1.00 1.00 0.50 19.9 162 9 74
15 18 17 23 20 23 0.78 0.40 1.00 0.33 1.00 1.00 10.95 49 18 16
21 18 13 21 24 28 1.00 0.80 1.00 0.67 0.50 1.00 18.45 122 6 66
20 23 11 21 22 24 1.00 0.40 1.00 1.00 1.00 0.50 15.1 96 5 9
26 21 19 24 15 22 1.00 0.30 1.00 0.67 0.00 0.50 15 100 4 41
19 21 21 22 22 24 0.67 0.50 1.00 0.67 0.50 1.00 11.35 82 11 57
28 28 24 24 26 25 0.89 0.80 1.00 0.67 1.00 1.00 15.95 100 4 48
21 17 13 24 17 21 1.00 0.40 0.83 0.33 0.00 0.50 18.1 115 10 51
19 21 16 24 23 22 1.00 1.00 1.00 1.00 0.50 0.00 14.6 141 6 53
22 21 13 23 19 16 0.89 0.50 1.00 0.67 1.00 1.00 15.4 165 8 29
21 20 15 21 21 18 0.89 0.50 1.00 0.67 1.00 1.00 15.4 165 8 29
20 18 15 24 23 27 0.89 0.30 1.00 0.33 0.00 1.00 17.6 110 6 55
19 17 11 19 19 17 0.89 0.30 0.83 0.33 0.50 1.00 13.35 118 8 54
11 7 7 19 18 25 0.89 0.30 0.50 0.00 0.00 1.00 19.1 158 4 43
17 17 13 23 16 24 1.00 0.40 0.67 0.33 0.50 0.50 15.35 146 4 51
19 14 13 25 23 21 0.67 0.50 1.00 0.33 0.00 1.00 7.6 49 9 20
20 18 12 24 13 21 1.00 0.50 0.67 0.67 0.50 1.00 13.4 90 9 79
17 14 8 21 18 19 0.89 0.40 1.00 0.00 0.00 0.00 13.9 121 5 39
21 23 7 18 23 27 0.89 0.70 1.00 1.00 0.50 0.00 19.1 155 4 61
21 20 17 23 21 28 0.89 0.50 0.50 0.33 0.00 0.50 15.25 104 4 55
12 14 9 20 23 19 0.89 0.40 0.67 0.33 1.00 0.00 12.9 147 15 30
23 17 18 23 16 23 1.00 0.70 0.67 1.00 0.00 1.00 16.1 110 10 55
22 21 17 23 17 25 1.00 0.70 0.67 1.00 0.00 1.00 17.35 108 9 22
22 23 17 23 20 26 1.00 0.70 0.67 1.00 0.00 1.00 13.15 113 7 37
21 24 18 23 18 25 0.89 0.70 0.67 1.00 0.00 1.00 12.15 115 9 2
20 21 12 27 20 25 0.89 0.70 0.67 0.00 0.00 0.00 12.6 61 6 38
18 14 14 19 19 24 0.89 0.70 1.00 0.67 0.50 1.00 10.35 60 4 27
21 24 22 25 26 24 0.33 0.10 0.67 0.33 0.50 0.00 15.4 109 7 56
24 16 19 25 9 24 0.67 0.20 0.67 0.67 0.50 1.00 9.6 68 4 25
22 21 21 21 23 22 0.56 0.30 0.33 0.33 0.00 1.00 18.2 111 7 39
20 8 10 25 9 21 0.44 0.60 0.83 0.33 0.00 0.50 13.6 77 4 33
17 17 16 17 13 17 1.00 0.80 1.00 1.00 1.00 1.00 14.85 73 15 43
19 18 11 22 27 23 0.89 0.80 1.00 0.33 0.50 0.50 14.75 151 4 57
16 17 15 23 22 17 0.33 0.00 0.17 0.00 0.00 0.00 14.1 89 9 43
19 16 12 27 12 25 0.67 0.30 0.67 0.33 0.00 1.00 14.9 78 4 23
23 22 21 27 18 19 0.67 0.60 0.83 0.33 0.50 1.00 16.25 110 4 44
8 17 22 5 6 8 1.00 0.50 0.83 0.67 0.00 1.00 19.25 220 28 54
22 21 20 19 17 14 0.78 0.70 1.00 0.33 0.00 0.50 13.6 65 4 28
23 20 15 24 22 22 0.67 0.30 0.83 0.00 0.50 1.00 13.6 141 4 36
15 20 9 23 22 25 1.00 0.30 1.00 0.67 0.00 0.00 15.65 117 4 39
17 19 15 28 23 28 0.78 0.40 1.00 0.67 0.00 0.50 12.75 122 5 16
21 8 14 25 19 25 0.89 0.40 0.83 1.00 0.00 1.00 14.6 63 4 23
25 19 11 27 20 24 0.89 0.10 0.83 0.00 0.00 1.00 9.85 44 4 40
18 11 9 16 17 15 0.89 0.50 1.00 0.67 0.00 1.00 12.65 52 12 24
20 13 12 25 24 24 0.00 0.00 0.00 0.00 0.00 0.00 19.2 131 4 78
21 18 11 26 20 28 0.67 0.40 1.00 0.33 0.50 0.00 16.6 101 6 57
21 19 14 24 18 24 1.00 0.60 0.83 0.67 1.00 0.50 11.2 42 6 37
24 23 10 23 23 25 1.00 0.40 1.00 0.33 0.50 1.00 15.25 152 5 27
22 20 18 24 27 23 0.67 0.10 0.33 0.00 0.50 1.00 11.9 107 4 61
22 22 11 27 25 26 0.89 0.30 0.83 0.00 0.00 1.00 13.2 77 4 27
23 19 14 25 24 26 0.89 0.70 0.83 0.67 0.00 1.00 16.35 154 4 69
17 16 16 19 12 22 0.56 0.30 0.17 0.00 0.00 1.00 12.4 103 10 34
15 11 11 19 16 25 0.67 0.50 0.83 0.33 0.50 0.00 15.85 96 7 44
22 21 16 24 24 22 1.00 0.30 0.83 0.67 1.00 1.00 18.15 175 4 34
19 14 13 20 23 26 1.00 0.60 0.67 0.67 0.50 1.00 11.15 57 7 39
18 21 12 21 24 20 1.00 0.90 1.00 1.00 0.00 1.00 15.65 112 4 51
21 20 17 28 24 26 0.67 0.40 0.83 0.00 0.50 1.00 17.75 143 4 34
20 21 23 26 26 26 0.44 0.30 1.00 0.00 0.50 0.50 7.65 49 12 31
19 20 14 19 19 21 0.89 0.90 1.00 0.67 1.00 1.00 12.35 110 5 13
19 19 10 23 28 21 0.44 0.50 1.00 0.00 0.50 0.00 15.6 131 8 12
16 19 16 23 23 24 0.56 0.30 1.00 1.00 0.50 0.50 19.3 167 6 51
18 18 11 21 21 21 0.89 0.60 0.83 0.67 0.00 0.50 15.2 56 17 24
23 20 16 26 19 18 0.67 0.20 1.00 0.33 0.00 0.50 17.1 137 4 19
22 21 19 25 23 23 0.89 0.40 0.83 1.00 0.50 1.00 15.6 86 5 30
23 22 17 25 23 26 1.00 0.50 0.83 0.67 0.50 0.50 18.4 121 4 81
20 19 12 24 20 23 0.78 0.40 0.83 0.67 0.00 0.50 19.05 149 5 42
24 23 17 23 18 25 0.44 0.00 0.00 0.00 0.00 0.00 18.55 168 5 22
25 16 11 22 20 20 0.89 0.20 1.00 0.33 0.50 1.00 19.1 140 6 85
25 23 19 27 28 25 0.89 0.50 1.00 0.67 0.50 1.00 13.1 88 4 27
20 18 12 26 21 26 0.89 0.30 1.00 0.67 0.00 0.50 12.85 168 4 25
23 23 8 23 25 19 0.44 0.00 0.00 0.00 0.00 0.00 9.5 94 4 22
21 20 17 22 18 21 1.00 0.50 0.83 1.00 0.00 1.00 4.5 51 6 19
23 20 13 26 24 23 0.89 0.60 0.83 0.33 0.00 1.00 11.85 48 8 14
23 23 17 22 28 24 0.67 0.30 0.83 0.00 0.50 0.50 13.6 145 10 45
11 13 7 17 9 6 0.33 0.00 0.00 0.00 0.00 0.00 11.7 66 4 45
21 21 23 25 22 22 0.78 0.30 0.67 0.00 0.50 0.00 12.4 85 5 28
27 26 18 22 26 21 0.89 0.50 1.00 0.67 0.50 1.00 13.35 109 4 51
19 18 13 28 28 28 0.78 0.40 0.67 0.00 0.00 1.00 11.4 63 4 41
21 19 17 22 18 24 0.78 0.50 0.83 0.67 0.00 0.50 14.9 102 4 31
16 18 13 21 23 14 0.89 0.70 1.00 1.00 1.00 0.50 19.9 162 16 74
21 18 8 24 15 20 0.78 0.80 1.00 0.67 0.50 1.00 11.2 86 7 19
22 19 16 26 24 28 0.78 0.60 1.00 0.33 0.50 1.00 14.6 114 4 51
16 13 14 26 12 19 0.67 0.40 0.83 0.33 0.00 0.50 17.6 164 4 73
18 10 13 24 12 24 0.89 0.50 0.83 0.33 0.50 0.00 14.05 119 14 24
23 21 19 27 20 21 0.89 0.50 1.00 0.00 0.50 1.00 16.1 126 5 61
24 24 15 22 25 21 0.78 0.30 1.00 0.33 0.00 1.00 13.35 132 5 23
20 21 15 23 24 26 1.00 0.60 1.00 0.00 0.50 1.00 11.85 142 5 14
20 23 8 22 23 24 1.00 0.30 0.67 0.67 0.00 0.50 11.95 83 5 54
18 18 14 23 18 26 0.78 0.60 0.83 1.00 0.50 0.50 14.75 94 7 51
4 11 7 15 20 25 0.78 0.30 0.33 0.33 0.00 1.00 15.15 81 19 62
14 16 11 20 22 23 0.89 0.70 1.00 0.67 1.00 1.00 13.2 166 16 36
22 20 17 22 20 24 0.89 0.70 1.00 1.00 0.00 1.00 16.85 110 4 59
17 20 19 25 25 24 0.67 0.60 0.67 1.00 0.50 1.00 7.85 64 4 24
23 26 17 27 28 26 1.00 0.50 1.00 0.33 0.50 0.00 7.7 93 7 26
20 21 12 24 25 23 0.67 0.50 0.83 0.33 0.00 0.50 12.6 104 9 54
18 12 12 21 14 20 0.56 0.40 0.67 0.00 0.00 1.00 7.85 105 5 39
19 15 18 17 16 16 0.78 0.40 1.00 0.33 1.00 1.00 10.95 49 14 16
20 18 16 26 24 24 1.00 0.70 1.00 1.00 0.00 1.00 12.35 88 4 36
15 14 15 20 13 20 0.67 0.20 0.17 0.00 0.50 0.00 9.95 95 16 31
24 18 20 22 19 23 0.78 0.50 0.83 0.67 0.00 0.50 14.9 102 10 31
21 16 16 24 18 23 0.56 0.40 0.83 0.67 0.50 0.00 16.65 99 5 42
19 19 12 23 16 18 1.00 0.20 1.00 0.67 1.00 1.00 13.4 63 6 39
19 7 10 22 8 21 0.89 0.50 0.67 0.67 0.00 0.00 13.95 76 4 25
27 21 28 28 27 25 0.44 0.40 0.50 0.00 0.00 1.00 15.7 109 4 31
23 24 19 21 23 23 1.00 0.70 0.67 1.00 1.00 1.00 16.85 117 4 38
23 21 18 24 20 26 0.89 0.60 0.83 0.67 1.00 0.00 10.95 57 5 31
20 20 19 28 20 26 0.78 0.40 0.83 0.00 0.00 0.00 15.35 120 4 17
17 22 8 25 26 24 0.89 0.50 1.00 0.67 1.00 1.00 12.2 73 4 22
21 17 17 24 23 23 0.11 0.00 0.17 0.00 0.00 0.00 15.1 91 5 55
23 19 16 24 24 21 0.89 0.70 1.00 0.67 0.50 1.00 17.75 108 4 62
22 20 18 21 21 23 0.89 0.40 0.67 0.67 0.00 1.00 15.2 105 4 51
16 16 12 20 15 20 1.00 0.50 0.67 1.00 0.00 1.00 14.6 117 5 30
20 20 17 26 22 23 0.89 0.60 0.83 0.67 0.00 0.50 16.65 119 8 49

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]12 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=0

As an alternative you can also use a QR Code:

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

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.95045 + 0.076843AMS.I1[t] + 0.0322279AMS.I2[t] -0.0537456AMS.I3[t] -0.0769117AMS.E1[t] -0.0598855AMS.E2[t] -0.00147953AMS.E3[t] -1.27032Calculation[t] -1.13912Algebraic_Reasoning[t] + 1.66661Graphical_Interpretation[t] + 1.48996Proportionality_and_Ratio[t] + 0.39136Probability_and_Sampling[t] -0.137082Estimation[t] + 0.015921LFM[t] + 0.0356839AMS.A[t] + 0.0501049CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  9.95045 +  0.076843AMS.I1[t] +  0.0322279AMS.I2[t] -0.0537456AMS.I3[t] -0.0769117AMS.E1[t] -0.0598855AMS.E2[t] -0.00147953AMS.E3[t] -1.27032Calculation[t] -1.13912Algebraic_Reasoning[t] +  1.66661Graphical_Interpretation[t] +  1.48996Proportionality_and_Ratio[t] +  0.39136Probability_and_Sampling[t] -0.137082Estimation[t] +  0.015921LFM[t] +  0.0356839AMS.A[t] +  0.0501049CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  9.95045 +  0.076843AMS.I1[t] +  0.0322279AMS.I2[t] -0.0537456AMS.I3[t] -0.0769117AMS.E1[t] -0.0598855AMS.E2[t] -0.00147953AMS.E3[t] -1.27032Calculation[t] -1.13912Algebraic_Reasoning[t] +  1.66661Graphical_Interpretation[t] +  1.48996Proportionality_and_Ratio[t] +  0.39136Probability_and_Sampling[t] -0.137082Estimation[t] +  0.015921LFM[t] +  0.0356839AMS.A[t] +  0.0501049CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 9.95045 + 0.076843AMS.I1[t] + 0.0322279AMS.I2[t] -0.0537456AMS.I3[t] -0.0769117AMS.E1[t] -0.0598855AMS.E2[t] -0.00147953AMS.E3[t] -1.27032Calculation[t] -1.13912Algebraic_Reasoning[t] + 1.66661Graphical_Interpretation[t] + 1.48996Proportionality_and_Ratio[t] + 0.39136Probability_and_Sampling[t] -0.137082Estimation[t] + 0.015921LFM[t] + 0.0356839AMS.A[t] + 0.0501049CH[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	9.95045	2.38083	4.179	3.99121e-05	1.9956e-05
AMS.I1	0.076843	0.077655	0.9895	0.323314	0.161657
AMS.I2	0.0322279	0.0674158	0.478	0.633017	0.316509
AMS.I3	-0.0537456	0.0580894	-0.9252	0.355705	0.177852
AMS.E1	-0.0769117	0.0805334	-0.955	0.340447	0.170223
AMS.E2	-0.0598855	0.0551612	-1.086	0.278637	0.139319
AMS.E3	-0.00147953	0.0666511	-0.0222	0.982307	0.491153
Calculation	-1.27032	1.2969	-0.9795	0.32824	0.16412
Algebraic_Reasoning	-1.13912	1.17459	-0.9698	0.333044	0.166522
Graphical_Interpretation	1.66661	0.959683	1.737	0.0836325	0.0418163
Proportionality_and_Ratio	1.48996	0.590901	2.521	0.0122816	0.00614082
Probability_and_Sampling	0.39136	0.545349	0.7176	0.473626	0.236813
Estimation	-0.137082	0.527339	-0.2599	0.795108	0.397554
LFM	0.015921	0.00532372	2.991	0.00305053	0.00152526
AMS.A	0.0356839	0.0657944	0.5424	0.588038	0.294019
CH	0.0501049	0.0111668	4.487	1.08411e-05	5.42057e-06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 9.95045 & 2.38083 & 4.179 & 3.99121e-05 & 1.9956e-05 \tabularnewline
AMS.I1 & 0.076843 & 0.077655 & 0.9895 & 0.323314 & 0.161657 \tabularnewline
AMS.I2 & 0.0322279 & 0.0674158 & 0.478 & 0.633017 & 0.316509 \tabularnewline
AMS.I3 & -0.0537456 & 0.0580894 & -0.9252 & 0.355705 & 0.177852 \tabularnewline
AMS.E1 & -0.0769117 & 0.0805334 & -0.955 & 0.340447 & 0.170223 \tabularnewline
AMS.E2 & -0.0598855 & 0.0551612 & -1.086 & 0.278637 & 0.139319 \tabularnewline
AMS.E3 & -0.00147953 & 0.0666511 & -0.0222 & 0.982307 & 0.491153 \tabularnewline
Calculation & -1.27032 & 1.2969 & -0.9795 & 0.32824 & 0.16412 \tabularnewline
Algebraic_Reasoning & -1.13912 & 1.17459 & -0.9698 & 0.333044 & 0.166522 \tabularnewline
Graphical_Interpretation & 1.66661 & 0.959683 & 1.737 & 0.0836325 & 0.0418163 \tabularnewline
Proportionality_and_Ratio & 1.48996 & 0.590901 & 2.521 & 0.0122816 & 0.00614082 \tabularnewline
Probability_and_Sampling & 0.39136 & 0.545349 & 0.7176 & 0.473626 & 0.236813 \tabularnewline
Estimation & -0.137082 & 0.527339 & -0.2599 & 0.795108 & 0.397554 \tabularnewline
LFM & 0.015921 & 0.00532372 & 2.991 & 0.00305053 & 0.00152526 \tabularnewline
AMS.A & 0.0356839 & 0.0657944 & 0.5424 & 0.588038 & 0.294019 \tabularnewline
CH & 0.0501049 & 0.0111668 & 4.487 & 1.08411e-05 & 5.42057e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]9.95045[/C][C]2.38083[/C][C]4.179[/C][C]3.99121e-05[/C][C]1.9956e-05[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.076843[/C][C]0.077655[/C][C]0.9895[/C][C]0.323314[/C][C]0.161657[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0322279[/C][C]0.0674158[/C][C]0.478[/C][C]0.633017[/C][C]0.316509[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0537456[/C][C]0.0580894[/C][C]-0.9252[/C][C]0.355705[/C][C]0.177852[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0769117[/C][C]0.0805334[/C][C]-0.955[/C][C]0.340447[/C][C]0.170223[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.0598855[/C][C]0.0551612[/C][C]-1.086[/C][C]0.278637[/C][C]0.139319[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.00147953[/C][C]0.0666511[/C][C]-0.0222[/C][C]0.982307[/C][C]0.491153[/C][/ROW]
[ROW][C]Calculation[/C][C]-1.27032[/C][C]1.2969[/C][C]-0.9795[/C][C]0.32824[/C][C]0.16412[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.13912[/C][C]1.17459[/C][C]-0.9698[/C][C]0.333044[/C][C]0.166522[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]1.66661[/C][C]0.959683[/C][C]1.737[/C][C]0.0836325[/C][C]0.0418163[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.48996[/C][C]0.590901[/C][C]2.521[/C][C]0.0122816[/C][C]0.00614082[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.39136[/C][C]0.545349[/C][C]0.7176[/C][C]0.473626[/C][C]0.236813[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.137082[/C][C]0.527339[/C][C]-0.2599[/C][C]0.795108[/C][C]0.397554[/C][/ROW]
[ROW][C]LFM[/C][C]0.015921[/C][C]0.00532372[/C][C]2.991[/C][C]0.00305053[/C][C]0.00152526[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.0356839[/C][C]0.0657944[/C][C]0.5424[/C][C]0.588038[/C][C]0.294019[/C][/ROW]
[ROW][C]CH[/C][C]0.0501049[/C][C]0.0111668[/C][C]4.487[/C][C]1.08411e-05[/C][C]5.42057e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	9.95045	2.38083	4.179	3.99121e-05	1.9956e-05
AMS.I1	0.076843	0.077655	0.9895	0.323314	0.161657
AMS.I2	0.0322279	0.0674158	0.478	0.633017	0.316509
AMS.I3	-0.0537456	0.0580894	-0.9252	0.355705	0.177852
AMS.E1	-0.0769117	0.0805334	-0.955	0.340447	0.170223
AMS.E2	-0.0598855	0.0551612	-1.086	0.278637	0.139319
AMS.E3	-0.00147953	0.0666511	-0.0222	0.982307	0.491153
Calculation	-1.27032	1.2969	-0.9795	0.32824	0.16412
Algebraic_Reasoning	-1.13912	1.17459	-0.9698	0.333044	0.166522
Graphical_Interpretation	1.66661	0.959683	1.737	0.0836325	0.0418163
Proportionality_and_Ratio	1.48996	0.590901	2.521	0.0122816	0.00614082
Probability_and_Sampling	0.39136	0.545349	0.7176	0.473626	0.236813
Estimation	-0.137082	0.527339	-0.2599	0.795108	0.397554
LFM	0.015921	0.00532372	2.991	0.00305053	0.00152526
AMS.A	0.0356839	0.0657944	0.5424	0.588038	0.294019
CH	0.0501049	0.0111668	4.487	1.08411e-05	5.42057e-06

Multiple Linear Regression - Regression Statistics
Multiple R	0.454435
R-squared	0.206511
Adjusted R-squared	0.160908
F-TEST (value)	4.52847
F-TEST (DF numerator)	15
F-TEST (DF denominator)	261
p-value	1.21408e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.10327
Sum Squared Residuals	2513.5

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.454435 \tabularnewline
R-squared & 0.206511 \tabularnewline
Adjusted R-squared & 0.160908 \tabularnewline
F-TEST (value) & 4.52847 \tabularnewline
F-TEST (DF numerator) & 15 \tabularnewline
F-TEST (DF denominator) & 261 \tabularnewline
p-value & 1.21408e-07 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.10327 \tabularnewline
Sum Squared Residuals & 2513.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.454435[/C][/ROW]
[ROW][C]R-squared[/C][C]0.206511[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.160908[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.52847[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]15[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]261[/C][/ROW]
[ROW][C]p-value[/C][C]1.21408e-07[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.10327[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2513.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.454435
R-squared	0.206511
Adjusted R-squared	0.160908
F-TEST (value)	4.52847
F-TEST (DF numerator)	15
F-TEST (DF denominator)	261
p-value	1.21408e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.10327
Sum Squared Residuals	2513.5

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	14.6733	-1.77328
2	12.2	12.4641	-0.264145
3	12.8	13.6055	-0.805535
4	7.4	13.7702	-6.37019
5	6.7	11.8616	-5.16163
6	12.6	13.1466	-0.546563
7	14.8	14.4802	0.319767
8	13.3	15.5324	-2.23243
9	11.1	13.761	-2.66096
10	8.2	14.1185	-5.91848
11	11.4	13.3282	-1.92822
12	6.4	14.1394	-7.73939
13	10.6	11.2666	-0.666596
14	12	15.349	-3.34905
15	6.3	10.006	-3.70603
16	11.3	11.0273	0.272679
17	11.9	14.6016	-2.70165
18	9.3	11.9727	-2.67266
19	9.6	12.7082	-3.10817
20	10	12.1985	-2.19853
21	6.4	12.9007	-6.50075
22	13.8	12.542	1.25795
23	10.8	14.1629	-3.36286
24	13.8	15.0336	-1.23359
25	11.7	14.7219	-3.02188
26	10.9	16.4351	-5.53508
27	16.1	14.468	1.63201
28	13.4	13.1961	0.203936
29	9.9	15.2415	-5.34153
30	11.5	13.897	-2.39697
31	8.3	11.8997	-3.59969
32	11.7	13.227	-1.52705
33	9	12.6277	-3.62774
34	9.7	14.123	-4.423
35	10.8	13.3241	-2.52406
36	10.3	13.7483	-3.44828
37	10.4	13.5099	-3.10992
38	12.7	11.7589	0.941136
39	9.3	14.6241	-5.32413
40	11.8	13.9883	-2.18834
41	5.9	13.2115	-7.31152
42	11.4	14.3223	-2.92234
43	13	14.2395	-1.23953
44	10.8	13.9469	-3.14687
45	12.3	11.8511	0.448876
46	11.3	14.2959	-2.99591
47	11.8	12.8558	-1.0558
48	7.9	11.8375	-3.93749
49	12.7	10.7546	1.94539
50	12.3	11.836	0.463984
51	11.6	12.9123	-1.31231
52	6.7	10.819	-4.11897
53	10.9	13.7463	-2.8463
54	12.1	11.7998	0.300204
55	13.3	13.5912	-0.2912
56	10.1	13.3801	-3.28005
57	5.7	12.8212	-7.1212
58	14.3	12.0951	2.20489
59	8	9.83532	-1.83532
60	13.3	12.8429	0.457099
61	9.3	16.03	-6.73001
62	12.5	11.3463	1.15366
63	7.6	13.8207	-6.22073
64	15.9	15.8256	0.074391
65	9.2	13.1124	-3.91238
66	9.1	12.5838	-3.48379
67	11.1	15.0903	-3.99026
68	13	17.7328	-4.73284
69	14.5	14.4758	0.0241648
70	12.2	12.2238	-0.0238118
71	12.3	14.074	-1.774
72	11.4	12.0858	-0.685782
73	8.8	12.3404	-3.54038
74	14.6	13.8166	0.783353
75	12.6	12.5489	0.0510857
76	NA	NA	0.0148271
77	13	12.938	0.061996
78	12.6	14.097	-1.49702
79	13.2	14.2319	-1.03191
80	9.9	14.3905	-4.49054
81	7.7	8.72443	-1.02443
82	10.5	8.31925	2.18075
83	13.4	15.6803	-2.28031
84	10.9	17.8763	-6.97635
85	4.3	8.15698	-3.85698
86	10.3	12.1032	-1.80321
87	11.8	12.294	-0.493991
88	11.2	11.3983	-0.198326
89	11.4	14.9726	-3.57256
90	8.6	7.34343	1.25657
91	13.2	12.856	0.343982
92	12.6	19.5721	-6.97207
93	5.6	8.71376	-3.11376
94	9.9	13.0739	-3.17387
95	8.8	12.0905	-3.2905
96	7.7	8.86955	-1.16955
97	9	13.5962	-4.59621
98	7.3	7.92919	-0.629192
99	11.4	9.06214	2.33786
100	13.6	18.5841	-4.98408
101	7.9	8.68909	-0.789089
102	10.7	13.0534	-2.35339
103	10.3	12.0589	-1.75894
104	8.3	11.2107	-2.9107
105	9.6	7.55043	2.04957
106	14.2	17.1336	-2.93364
107	8.5	7.08004	1.41996
108	13.5	21.4286	-7.92855
109	4.9	9.03468	-4.13468
110	6.4	9.50607	-3.10607
111	9.6	10.0518	-0.451803
112	11.6	12.1723	-0.57233
113	11.1	17.2525	-6.15249
114	4.35	4.63472	-0.284722
115	12.7	8.49804	4.20196
116	18.1	14.3293	3.77072
117	17.85	18.7977	-0.947684
118	16.6	15.1158	1.48417
119	12.6	12.0782	0.521806
120	17.1	14.1337	2.96628
121	19.1	21.524	-2.42399
122	16.1	13.121	2.97897
123	13.35	10.3731	2.97693
124	18.4	14.3062	4.09377
125	14.7	17.1487	-2.44868
126	10.6	9.1809	1.4191
127	12.6	8.57391	4.02609
128	16.2	15.9255	0.274503
129	13.6	8.69029	4.90971
130	18.9	16.9756	1.92438
131	14.1	12.6405	1.45954
132	14.5	13.0194	1.48062
133	16.15	14.8593	1.29071
134	14.75	13.5372	1.21281
135	14.8	15.0774	-0.277388
136	12.45	12.2532	0.196765
137	12.65	8.60564	4.04436
138	17.35	20.1646	-2.81457
139	8.6	5.02495	3.57505
140	18.4	18.2899	0.110068
141	16.1	17.3975	-1.29753
142	11.6	6.75853	4.84147
143	17.75	15.8122	1.93783
144	15.25	11.2815	3.96846
145	17.65	15.1863	2.46373
146	16.35	13.7673	2.58266
147	17.65	17.8	-0.150027
148	13.6	12.4464	1.15364
149	14.35	12.3793	1.97066
150	14.75	11.5549	3.19513
151	18.25	21.3378	-3.08782
152	9.9	8.93358	0.96642
153	16	11.8945	4.10553
154	18.25	14.336	3.91401
155	16.85	14.537	2.313
156	14.6	13.9264	0.673616
157	13.85	11.7672	2.08276
158	18.95	16.7825	2.1675
159	15.6	15.9686	-0.368584
160	14.85	15.8639	-1.01386
161	11.75	8.50903	3.24097
162	18.45	15.7674	2.68261
163	15.9	14.8247	1.07535
164	17.1	12.318	4.78202
165	16.1	13.5061	2.59392
166	19.9	19.909	-0.00901039
167	10.95	6.857	4.093
168	18.45	15.9304	2.51958
169	15.1	13.7007	1.3993
170	15	17.4204	-2.42038
171	11.35	8.6918	2.6582
172	15.95	11.1919	4.7581
173	18.1	17.5289	0.571134
174	14.6	13.4731	1.12688
175	15.4	14.0877	1.31234
176	15.4	11.0681	4.33188
177	17.6	18.3239	-0.723911
178	13.35	6.35552	6.99448
179	19.1	17.1254	1.97464
180	15.35	18.2857	-2.93566
181	7.6	9.01296	-1.41296
182	13.4	12.1961	1.20385
183	13.9	11.0186	2.88137
184	19.1	16.1876	2.91236
185	15.25	15.0386	0.211425
186	12.9	10.6029	2.29715
187	16.1	10.8748	5.22517
188	17.35	16.968	0.382038
189	13.15	12.2801	0.869876
190	12.15	10.0358	2.11423
191	12.6	13.8941	-1.29406
192	10.35	8.65183	1.69817
193	15.4	18.1644	-2.76444
194	9.6	3.38664	6.21336
195	18.2	16.901	1.29902
196	13.6	12.6648	0.9352
197	14.85	13.8027	1.04728
198	14.75	12.2168	2.53322
199	14.1	10.4643	3.63569
200	14.9	11.2632	3.63682
201	16.25	13.787	2.463
202	19.25	17.2748	1.97516
203	13.6	12.8007	0.799285
204	13.6	11.1029	2.49708
205	15.65	14.4629	1.18709
206	12.75	9.57004	3.17996
207	14.6	16.182	-1.58198
208	9.85	9.41986	0.430139
209	12.65	7.45234	5.19766
210	19.2	16.6395	2.56046
211	16.6	17.352	-0.751971
212	11.2	9.20732	1.99268
213	15.25	15.7176	-0.467553
214	11.9	9.34196	2.55804
215	13.2	11.3975	1.80246
216	16.35	15.4434	0.906602
217	12.4	9.59272	2.80728
218	15.85	11.4984	4.35156
219	18.15	18.54	-0.389981
220	11.15	8.98868	2.16132
221	15.65	9.82392	5.82608
222	17.75	21.0874	-3.33741
223	7.65	7.31684	0.333164
224	12.35	8.46468	3.88532
225	15.6	11.7094	3.89065
226	19.3	15.7184	3.5816
227	15.2	10.725	4.47496
228	17.1	13.8588	3.24119
229	15.6	12.171	3.42895
230	18.4	13.2487	5.15135
231	19.05	12.6349	6.41513
232	18.55	15.8871	2.66293
233	19.1	17.7212	1.37884
234	13.1	13.5708	-0.470811
235	12.85	14.2676	-1.41758
236	9.5	16.3683	-6.86832
237	4.5	2.5177	1.9823
238	11.85	11.6287	0.221269
239	13.6	13.9122	-0.312158
240	11.7	9.94634	1.75366
241	12.4	13.1224	-0.72238
242	13.35	12.1032	1.24676
243	11.4	9.02984	2.37016
244	14.9	11.4575	3.44254
245	19.9	21.0329	-1.13286
246	11.2	9.57067	1.62933
247	14.6	12.0111	2.58886
248	17.6	15.8744	1.7256
249	14.05	11.284	2.766
250	16.1	15.4127	0.687259
251	13.35	12.5253	0.824683
252	11.85	13.2335	-1.38349
253	11.95	11.1037	0.846311
254	14.75	12.0938	2.65616
255	15.15	16.0198	-0.869756
256	13.2	10.7384	2.46164
257	16.85	19.9195	-3.06953
258	7.85	11.5475	-3.69748
259	7.7	8.31047	-0.610467
260	12.6	16.959	-4.35902
261	7.85	8.58459	-0.734587
262	10.95	10.6344	0.315636
263	12.35	13.8385	-1.48852
264	9.95	7.77261	2.17739
265	14.9	11.7812	3.11876
266	16.65	16.4663	0.183681
267	13.4	11.3665	2.03349
268	13.95	8.75271	5.19729
269	15.7	11.9962	3.70375
270	16.85	17.8432	-0.993178
271	10.95	6.16283	4.78717
272	15.35	14.7968	0.553199
273	12.2	9.56767	2.63233
274	15.1	11.2703	3.82974
275	17.75	15.7227	2.02726
276	15.2	13.3585	1.84152
277	14.6	10.9512	3.64885
278	16.65	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.6733 & -1.77328 \tabularnewline
2 & 12.2 & 12.4641 & -0.264145 \tabularnewline
3 & 12.8 & 13.6055 & -0.805535 \tabularnewline
4 & 7.4 & 13.7702 & -6.37019 \tabularnewline
5 & 6.7 & 11.8616 & -5.16163 \tabularnewline
6 & 12.6 & 13.1466 & -0.546563 \tabularnewline
7 & 14.8 & 14.4802 & 0.319767 \tabularnewline
8 & 13.3 & 15.5324 & -2.23243 \tabularnewline
9 & 11.1 & 13.761 & -2.66096 \tabularnewline
10 & 8.2 & 14.1185 & -5.91848 \tabularnewline
11 & 11.4 & 13.3282 & -1.92822 \tabularnewline
12 & 6.4 & 14.1394 & -7.73939 \tabularnewline
13 & 10.6 & 11.2666 & -0.666596 \tabularnewline
14 & 12 & 15.349 & -3.34905 \tabularnewline
15 & 6.3 & 10.006 & -3.70603 \tabularnewline
16 & 11.3 & 11.0273 & 0.272679 \tabularnewline
17 & 11.9 & 14.6016 & -2.70165 \tabularnewline
18 & 9.3 & 11.9727 & -2.67266 \tabularnewline
19 & 9.6 & 12.7082 & -3.10817 \tabularnewline
20 & 10 & 12.1985 & -2.19853 \tabularnewline
21 & 6.4 & 12.9007 & -6.50075 \tabularnewline
22 & 13.8 & 12.542 & 1.25795 \tabularnewline
23 & 10.8 & 14.1629 & -3.36286 \tabularnewline
24 & 13.8 & 15.0336 & -1.23359 \tabularnewline
25 & 11.7 & 14.7219 & -3.02188 \tabularnewline
26 & 10.9 & 16.4351 & -5.53508 \tabularnewline
27 & 16.1 & 14.468 & 1.63201 \tabularnewline
28 & 13.4 & 13.1961 & 0.203936 \tabularnewline
29 & 9.9 & 15.2415 & -5.34153 \tabularnewline
30 & 11.5 & 13.897 & -2.39697 \tabularnewline
31 & 8.3 & 11.8997 & -3.59969 \tabularnewline
32 & 11.7 & 13.227 & -1.52705 \tabularnewline
33 & 9 & 12.6277 & -3.62774 \tabularnewline
34 & 9.7 & 14.123 & -4.423 \tabularnewline
35 & 10.8 & 13.3241 & -2.52406 \tabularnewline
36 & 10.3 & 13.7483 & -3.44828 \tabularnewline
37 & 10.4 & 13.5099 & -3.10992 \tabularnewline
38 & 12.7 & 11.7589 & 0.941136 \tabularnewline
39 & 9.3 & 14.6241 & -5.32413 \tabularnewline
40 & 11.8 & 13.9883 & -2.18834 \tabularnewline
41 & 5.9 & 13.2115 & -7.31152 \tabularnewline
42 & 11.4 & 14.3223 & -2.92234 \tabularnewline
43 & 13 & 14.2395 & -1.23953 \tabularnewline
44 & 10.8 & 13.9469 & -3.14687 \tabularnewline
45 & 12.3 & 11.8511 & 0.448876 \tabularnewline
46 & 11.3 & 14.2959 & -2.99591 \tabularnewline
47 & 11.8 & 12.8558 & -1.0558 \tabularnewline
48 & 7.9 & 11.8375 & -3.93749 \tabularnewline
49 & 12.7 & 10.7546 & 1.94539 \tabularnewline
50 & 12.3 & 11.836 & 0.463984 \tabularnewline
51 & 11.6 & 12.9123 & -1.31231 \tabularnewline
52 & 6.7 & 10.819 & -4.11897 \tabularnewline
53 & 10.9 & 13.7463 & -2.8463 \tabularnewline
54 & 12.1 & 11.7998 & 0.300204 \tabularnewline
55 & 13.3 & 13.5912 & -0.2912 \tabularnewline
56 & 10.1 & 13.3801 & -3.28005 \tabularnewline
57 & 5.7 & 12.8212 & -7.1212 \tabularnewline
58 & 14.3 & 12.0951 & 2.20489 \tabularnewline
59 & 8 & 9.83532 & -1.83532 \tabularnewline
60 & 13.3 & 12.8429 & 0.457099 \tabularnewline
61 & 9.3 & 16.03 & -6.73001 \tabularnewline
62 & 12.5 & 11.3463 & 1.15366 \tabularnewline
63 & 7.6 & 13.8207 & -6.22073 \tabularnewline
64 & 15.9 & 15.8256 & 0.074391 \tabularnewline
65 & 9.2 & 13.1124 & -3.91238 \tabularnewline
66 & 9.1 & 12.5838 & -3.48379 \tabularnewline
67 & 11.1 & 15.0903 & -3.99026 \tabularnewline
68 & 13 & 17.7328 & -4.73284 \tabularnewline
69 & 14.5 & 14.4758 & 0.0241648 \tabularnewline
70 & 12.2 & 12.2238 & -0.0238118 \tabularnewline
71 & 12.3 & 14.074 & -1.774 \tabularnewline
72 & 11.4 & 12.0858 & -0.685782 \tabularnewline
73 & 8.8 & 12.3404 & -3.54038 \tabularnewline
74 & 14.6 & 13.8166 & 0.783353 \tabularnewline
75 & 12.6 & 12.5489 & 0.0510857 \tabularnewline
76 & NA & NA & 0.0148271 \tabularnewline
77 & 13 & 12.938 & 0.061996 \tabularnewline
78 & 12.6 & 14.097 & -1.49702 \tabularnewline
79 & 13.2 & 14.2319 & -1.03191 \tabularnewline
80 & 9.9 & 14.3905 & -4.49054 \tabularnewline
81 & 7.7 & 8.72443 & -1.02443 \tabularnewline
82 & 10.5 & 8.31925 & 2.18075 \tabularnewline
83 & 13.4 & 15.6803 & -2.28031 \tabularnewline
84 & 10.9 & 17.8763 & -6.97635 \tabularnewline
85 & 4.3 & 8.15698 & -3.85698 \tabularnewline
86 & 10.3 & 12.1032 & -1.80321 \tabularnewline
87 & 11.8 & 12.294 & -0.493991 \tabularnewline
88 & 11.2 & 11.3983 & -0.198326 \tabularnewline
89 & 11.4 & 14.9726 & -3.57256 \tabularnewline
90 & 8.6 & 7.34343 & 1.25657 \tabularnewline
91 & 13.2 & 12.856 & 0.343982 \tabularnewline
92 & 12.6 & 19.5721 & -6.97207 \tabularnewline
93 & 5.6 & 8.71376 & -3.11376 \tabularnewline
94 & 9.9 & 13.0739 & -3.17387 \tabularnewline
95 & 8.8 & 12.0905 & -3.2905 \tabularnewline
96 & 7.7 & 8.86955 & -1.16955 \tabularnewline
97 & 9 & 13.5962 & -4.59621 \tabularnewline
98 & 7.3 & 7.92919 & -0.629192 \tabularnewline
99 & 11.4 & 9.06214 & 2.33786 \tabularnewline
100 & 13.6 & 18.5841 & -4.98408 \tabularnewline
101 & 7.9 & 8.68909 & -0.789089 \tabularnewline
102 & 10.7 & 13.0534 & -2.35339 \tabularnewline
103 & 10.3 & 12.0589 & -1.75894 \tabularnewline
104 & 8.3 & 11.2107 & -2.9107 \tabularnewline
105 & 9.6 & 7.55043 & 2.04957 \tabularnewline
106 & 14.2 & 17.1336 & -2.93364 \tabularnewline
107 & 8.5 & 7.08004 & 1.41996 \tabularnewline
108 & 13.5 & 21.4286 & -7.92855 \tabularnewline
109 & 4.9 & 9.03468 & -4.13468 \tabularnewline
110 & 6.4 & 9.50607 & -3.10607 \tabularnewline
111 & 9.6 & 10.0518 & -0.451803 \tabularnewline
112 & 11.6 & 12.1723 & -0.57233 \tabularnewline
113 & 11.1 & 17.2525 & -6.15249 \tabularnewline
114 & 4.35 & 4.63472 & -0.284722 \tabularnewline
115 & 12.7 & 8.49804 & 4.20196 \tabularnewline
116 & 18.1 & 14.3293 & 3.77072 \tabularnewline
117 & 17.85 & 18.7977 & -0.947684 \tabularnewline
118 & 16.6 & 15.1158 & 1.48417 \tabularnewline
119 & 12.6 & 12.0782 & 0.521806 \tabularnewline
120 & 17.1 & 14.1337 & 2.96628 \tabularnewline
121 & 19.1 & 21.524 & -2.42399 \tabularnewline
122 & 16.1 & 13.121 & 2.97897 \tabularnewline
123 & 13.35 & 10.3731 & 2.97693 \tabularnewline
124 & 18.4 & 14.3062 & 4.09377 \tabularnewline
125 & 14.7 & 17.1487 & -2.44868 \tabularnewline
126 & 10.6 & 9.1809 & 1.4191 \tabularnewline
127 & 12.6 & 8.57391 & 4.02609 \tabularnewline
128 & 16.2 & 15.9255 & 0.274503 \tabularnewline
129 & 13.6 & 8.69029 & 4.90971 \tabularnewline
130 & 18.9 & 16.9756 & 1.92438 \tabularnewline
131 & 14.1 & 12.6405 & 1.45954 \tabularnewline
132 & 14.5 & 13.0194 & 1.48062 \tabularnewline
133 & 16.15 & 14.8593 & 1.29071 \tabularnewline
134 & 14.75 & 13.5372 & 1.21281 \tabularnewline
135 & 14.8 & 15.0774 & -0.277388 \tabularnewline
136 & 12.45 & 12.2532 & 0.196765 \tabularnewline
137 & 12.65 & 8.60564 & 4.04436 \tabularnewline
138 & 17.35 & 20.1646 & -2.81457 \tabularnewline
139 & 8.6 & 5.02495 & 3.57505 \tabularnewline
140 & 18.4 & 18.2899 & 0.110068 \tabularnewline
141 & 16.1 & 17.3975 & -1.29753 \tabularnewline
142 & 11.6 & 6.75853 & 4.84147 \tabularnewline
143 & 17.75 & 15.8122 & 1.93783 \tabularnewline
144 & 15.25 & 11.2815 & 3.96846 \tabularnewline
145 & 17.65 & 15.1863 & 2.46373 \tabularnewline
146 & 16.35 & 13.7673 & 2.58266 \tabularnewline
147 & 17.65 & 17.8 & -0.150027 \tabularnewline
148 & 13.6 & 12.4464 & 1.15364 \tabularnewline
149 & 14.35 & 12.3793 & 1.97066 \tabularnewline
150 & 14.75 & 11.5549 & 3.19513 \tabularnewline
151 & 18.25 & 21.3378 & -3.08782 \tabularnewline
152 & 9.9 & 8.93358 & 0.96642 \tabularnewline
153 & 16 & 11.8945 & 4.10553 \tabularnewline
154 & 18.25 & 14.336 & 3.91401 \tabularnewline
155 & 16.85 & 14.537 & 2.313 \tabularnewline
156 & 14.6 & 13.9264 & 0.673616 \tabularnewline
157 & 13.85 & 11.7672 & 2.08276 \tabularnewline
158 & 18.95 & 16.7825 & 2.1675 \tabularnewline
159 & 15.6 & 15.9686 & -0.368584 \tabularnewline
160 & 14.85 & 15.8639 & -1.01386 \tabularnewline
161 & 11.75 & 8.50903 & 3.24097 \tabularnewline
162 & 18.45 & 15.7674 & 2.68261 \tabularnewline
163 & 15.9 & 14.8247 & 1.07535 \tabularnewline
164 & 17.1 & 12.318 & 4.78202 \tabularnewline
165 & 16.1 & 13.5061 & 2.59392 \tabularnewline
166 & 19.9 & 19.909 & -0.00901039 \tabularnewline
167 & 10.95 & 6.857 & 4.093 \tabularnewline
168 & 18.45 & 15.9304 & 2.51958 \tabularnewline
169 & 15.1 & 13.7007 & 1.3993 \tabularnewline
170 & 15 & 17.4204 & -2.42038 \tabularnewline
171 & 11.35 & 8.6918 & 2.6582 \tabularnewline
172 & 15.95 & 11.1919 & 4.7581 \tabularnewline
173 & 18.1 & 17.5289 & 0.571134 \tabularnewline
174 & 14.6 & 13.4731 & 1.12688 \tabularnewline
175 & 15.4 & 14.0877 & 1.31234 \tabularnewline
176 & 15.4 & 11.0681 & 4.33188 \tabularnewline
177 & 17.6 & 18.3239 & -0.723911 \tabularnewline
178 & 13.35 & 6.35552 & 6.99448 \tabularnewline
179 & 19.1 & 17.1254 & 1.97464 \tabularnewline
180 & 15.35 & 18.2857 & -2.93566 \tabularnewline
181 & 7.6 & 9.01296 & -1.41296 \tabularnewline
182 & 13.4 & 12.1961 & 1.20385 \tabularnewline
183 & 13.9 & 11.0186 & 2.88137 \tabularnewline
184 & 19.1 & 16.1876 & 2.91236 \tabularnewline
185 & 15.25 & 15.0386 & 0.211425 \tabularnewline
186 & 12.9 & 10.6029 & 2.29715 \tabularnewline
187 & 16.1 & 10.8748 & 5.22517 \tabularnewline
188 & 17.35 & 16.968 & 0.382038 \tabularnewline
189 & 13.15 & 12.2801 & 0.869876 \tabularnewline
190 & 12.15 & 10.0358 & 2.11423 \tabularnewline
191 & 12.6 & 13.8941 & -1.29406 \tabularnewline
192 & 10.35 & 8.65183 & 1.69817 \tabularnewline
193 & 15.4 & 18.1644 & -2.76444 \tabularnewline
194 & 9.6 & 3.38664 & 6.21336 \tabularnewline
195 & 18.2 & 16.901 & 1.29902 \tabularnewline
196 & 13.6 & 12.6648 & 0.9352 \tabularnewline
197 & 14.85 & 13.8027 & 1.04728 \tabularnewline
198 & 14.75 & 12.2168 & 2.53322 \tabularnewline
199 & 14.1 & 10.4643 & 3.63569 \tabularnewline
200 & 14.9 & 11.2632 & 3.63682 \tabularnewline
201 & 16.25 & 13.787 & 2.463 \tabularnewline
202 & 19.25 & 17.2748 & 1.97516 \tabularnewline
203 & 13.6 & 12.8007 & 0.799285 \tabularnewline
204 & 13.6 & 11.1029 & 2.49708 \tabularnewline
205 & 15.65 & 14.4629 & 1.18709 \tabularnewline
206 & 12.75 & 9.57004 & 3.17996 \tabularnewline
207 & 14.6 & 16.182 & -1.58198 \tabularnewline
208 & 9.85 & 9.41986 & 0.430139 \tabularnewline
209 & 12.65 & 7.45234 & 5.19766 \tabularnewline
210 & 19.2 & 16.6395 & 2.56046 \tabularnewline
211 & 16.6 & 17.352 & -0.751971 \tabularnewline
212 & 11.2 & 9.20732 & 1.99268 \tabularnewline
213 & 15.25 & 15.7176 & -0.467553 \tabularnewline
214 & 11.9 & 9.34196 & 2.55804 \tabularnewline
215 & 13.2 & 11.3975 & 1.80246 \tabularnewline
216 & 16.35 & 15.4434 & 0.906602 \tabularnewline
217 & 12.4 & 9.59272 & 2.80728 \tabularnewline
218 & 15.85 & 11.4984 & 4.35156 \tabularnewline
219 & 18.15 & 18.54 & -0.389981 \tabularnewline
220 & 11.15 & 8.98868 & 2.16132 \tabularnewline
221 & 15.65 & 9.82392 & 5.82608 \tabularnewline
222 & 17.75 & 21.0874 & -3.33741 \tabularnewline
223 & 7.65 & 7.31684 & 0.333164 \tabularnewline
224 & 12.35 & 8.46468 & 3.88532 \tabularnewline
225 & 15.6 & 11.7094 & 3.89065 \tabularnewline
226 & 19.3 & 15.7184 & 3.5816 \tabularnewline
227 & 15.2 & 10.725 & 4.47496 \tabularnewline
228 & 17.1 & 13.8588 & 3.24119 \tabularnewline
229 & 15.6 & 12.171 & 3.42895 \tabularnewline
230 & 18.4 & 13.2487 & 5.15135 \tabularnewline
231 & 19.05 & 12.6349 & 6.41513 \tabularnewline
232 & 18.55 & 15.8871 & 2.66293 \tabularnewline
233 & 19.1 & 17.7212 & 1.37884 \tabularnewline
234 & 13.1 & 13.5708 & -0.470811 \tabularnewline
235 & 12.85 & 14.2676 & -1.41758 \tabularnewline
236 & 9.5 & 16.3683 & -6.86832 \tabularnewline
237 & 4.5 & 2.5177 & 1.9823 \tabularnewline
238 & 11.85 & 11.6287 & 0.221269 \tabularnewline
239 & 13.6 & 13.9122 & -0.312158 \tabularnewline
240 & 11.7 & 9.94634 & 1.75366 \tabularnewline
241 & 12.4 & 13.1224 & -0.72238 \tabularnewline
242 & 13.35 & 12.1032 & 1.24676 \tabularnewline
243 & 11.4 & 9.02984 & 2.37016 \tabularnewline
244 & 14.9 & 11.4575 & 3.44254 \tabularnewline
245 & 19.9 & 21.0329 & -1.13286 \tabularnewline
246 & 11.2 & 9.57067 & 1.62933 \tabularnewline
247 & 14.6 & 12.0111 & 2.58886 \tabularnewline
248 & 17.6 & 15.8744 & 1.7256 \tabularnewline
249 & 14.05 & 11.284 & 2.766 \tabularnewline
250 & 16.1 & 15.4127 & 0.687259 \tabularnewline
251 & 13.35 & 12.5253 & 0.824683 \tabularnewline
252 & 11.85 & 13.2335 & -1.38349 \tabularnewline
253 & 11.95 & 11.1037 & 0.846311 \tabularnewline
254 & 14.75 & 12.0938 & 2.65616 \tabularnewline
255 & 15.15 & 16.0198 & -0.869756 \tabularnewline
256 & 13.2 & 10.7384 & 2.46164 \tabularnewline
257 & 16.85 & 19.9195 & -3.06953 \tabularnewline
258 & 7.85 & 11.5475 & -3.69748 \tabularnewline
259 & 7.7 & 8.31047 & -0.610467 \tabularnewline
260 & 12.6 & 16.959 & -4.35902 \tabularnewline
261 & 7.85 & 8.58459 & -0.734587 \tabularnewline
262 & 10.95 & 10.6344 & 0.315636 \tabularnewline
263 & 12.35 & 13.8385 & -1.48852 \tabularnewline
264 & 9.95 & 7.77261 & 2.17739 \tabularnewline
265 & 14.9 & 11.7812 & 3.11876 \tabularnewline
266 & 16.65 & 16.4663 & 0.183681 \tabularnewline
267 & 13.4 & 11.3665 & 2.03349 \tabularnewline
268 & 13.95 & 8.75271 & 5.19729 \tabularnewline
269 & 15.7 & 11.9962 & 3.70375 \tabularnewline
270 & 16.85 & 17.8432 & -0.993178 \tabularnewline
271 & 10.95 & 6.16283 & 4.78717 \tabularnewline
272 & 15.35 & 14.7968 & 0.553199 \tabularnewline
273 & 12.2 & 9.56767 & 2.63233 \tabularnewline
274 & 15.1 & 11.2703 & 3.82974 \tabularnewline
275 & 17.75 & 15.7227 & 2.02726 \tabularnewline
276 & 15.2 & 13.3585 & 1.84152 \tabularnewline
277 & 14.6 & 10.9512 & 3.64885 \tabularnewline
278 & 16.65 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]14.6733[/C][C]-1.77328[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.4641[/C][C]-0.264145[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.6055[/C][C]-0.805535[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.7702[/C][C]-6.37019[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.8616[/C][C]-5.16163[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.1466[/C][C]-0.546563[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.4802[/C][C]0.319767[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]15.5324[/C][C]-2.23243[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]13.761[/C][C]-2.66096[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.1185[/C][C]-5.91848[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.3282[/C][C]-1.92822[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.1394[/C][C]-7.73939[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.2666[/C][C]-0.666596[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]15.349[/C][C]-3.34905[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.006[/C][C]-3.70603[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.0273[/C][C]0.272679[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.6016[/C][C]-2.70165[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]11.9727[/C][C]-2.67266[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.7082[/C][C]-3.10817[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.1985[/C][C]-2.19853[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9007[/C][C]-6.50075[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.542[/C][C]1.25795[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.1629[/C][C]-3.36286[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]15.0336[/C][C]-1.23359[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.7219[/C][C]-3.02188[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]16.4351[/C][C]-5.53508[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]14.468[/C][C]1.63201[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.1961[/C][C]0.203936[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]15.2415[/C][C]-5.34153[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.897[/C][C]-2.39697[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.8997[/C][C]-3.59969[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.227[/C][C]-1.52705[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.6277[/C][C]-3.62774[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.123[/C][C]-4.423[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.3241[/C][C]-2.52406[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.7483[/C][C]-3.44828[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.5099[/C][C]-3.10992[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.7589[/C][C]0.941136[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.6241[/C][C]-5.32413[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]13.9883[/C][C]-2.18834[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.2115[/C][C]-7.31152[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.3223[/C][C]-2.92234[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.2395[/C][C]-1.23953[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]13.9469[/C][C]-3.14687[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.8511[/C][C]0.448876[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.2959[/C][C]-2.99591[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.8558[/C][C]-1.0558[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.8375[/C][C]-3.93749[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.7546[/C][C]1.94539[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.836[/C][C]0.463984[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.9123[/C][C]-1.31231[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.819[/C][C]-4.11897[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.7463[/C][C]-2.8463[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.7998[/C][C]0.300204[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.5912[/C][C]-0.2912[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3801[/C][C]-3.28005[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.8212[/C][C]-7.1212[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.0951[/C][C]2.20489[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.83532[/C][C]-1.83532[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.8429[/C][C]0.457099[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]16.03[/C][C]-6.73001[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.3463[/C][C]1.15366[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]13.8207[/C][C]-6.22073[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.8256[/C][C]0.074391[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.1124[/C][C]-3.91238[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.5838[/C][C]-3.48379[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]15.0903[/C][C]-3.99026[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]17.7328[/C][C]-4.73284[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]14.4758[/C][C]0.0241648[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.2238[/C][C]-0.0238118[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.074[/C][C]-1.774[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]12.0858[/C][C]-0.685782[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.3404[/C][C]-3.54038[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.8166[/C][C]0.783353[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.5489[/C][C]0.0510857[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.0148271[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]12.938[/C][C]0.061996[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.097[/C][C]-1.49702[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.2319[/C][C]-1.03191[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.3905[/C][C]-4.49054[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.72443[/C][C]-1.02443[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]8.31925[/C][C]2.18075[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.6803[/C][C]-2.28031[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]17.8763[/C][C]-6.97635[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]8.15698[/C][C]-3.85698[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]12.1032[/C][C]-1.80321[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.294[/C][C]-0.493991[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.3983[/C][C]-0.198326[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]14.9726[/C][C]-3.57256[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.34343[/C][C]1.25657[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]12.856[/C][C]0.343982[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.5721[/C][C]-6.97207[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.71376[/C][C]-3.11376[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.0739[/C][C]-3.17387[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.0905[/C][C]-3.2905[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]8.86955[/C][C]-1.16955[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]13.5962[/C][C]-4.59621[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]7.92919[/C][C]-0.629192[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.06214[/C][C]2.33786[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.5841[/C][C]-4.98408[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.68909[/C][C]-0.789089[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.0534[/C][C]-2.35339[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.0589[/C][C]-1.75894[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.2107[/C][C]-2.9107[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.55043[/C][C]2.04957[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]17.1336[/C][C]-2.93364[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.08004[/C][C]1.41996[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.4286[/C][C]-7.92855[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.03468[/C][C]-4.13468[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.50607[/C][C]-3.10607[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.0518[/C][C]-0.451803[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]12.1723[/C][C]-0.57233[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.2525[/C][C]-6.15249[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.63472[/C][C]-0.284722[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]8.49804[/C][C]4.20196[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]14.3293[/C][C]3.77072[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]18.7977[/C][C]-0.947684[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.1158[/C][C]1.48417[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]12.0782[/C][C]0.521806[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.1337[/C][C]2.96628[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.524[/C][C]-2.42399[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.121[/C][C]2.97897[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]10.3731[/C][C]2.97693[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.3062[/C][C]4.09377[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.1487[/C][C]-2.44868[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.1809[/C][C]1.4191[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]8.57391[/C][C]4.02609[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.9255[/C][C]0.274503[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]8.69029[/C][C]4.90971[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]16.9756[/C][C]1.92438[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.6405[/C][C]1.45954[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]13.0194[/C][C]1.48062[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.8593[/C][C]1.29071[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.5372[/C][C]1.21281[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.0774[/C][C]-0.277388[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.2532[/C][C]0.196765[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.60564[/C][C]4.04436[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]20.1646[/C][C]-2.81457[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]5.02495[/C][C]3.57505[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]18.2899[/C][C]0.110068[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.3975[/C][C]-1.29753[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.75853[/C][C]4.84147[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.8122[/C][C]1.93783[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.2815[/C][C]3.96846[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]15.1863[/C][C]2.46373[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.7673[/C][C]2.58266[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.8[/C][C]-0.150027[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.4464[/C][C]1.15364[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.3793[/C][C]1.97066[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]11.5549[/C][C]3.19513[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.3378[/C][C]-3.08782[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.93358[/C][C]0.96642[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.8945[/C][C]4.10553[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.336[/C][C]3.91401[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.537[/C][C]2.313[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.9264[/C][C]0.673616[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.7672[/C][C]2.08276[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.7825[/C][C]2.1675[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]15.9686[/C][C]-0.368584[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.8639[/C][C]-1.01386[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]8.50903[/C][C]3.24097[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.7674[/C][C]2.68261[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]14.8247[/C][C]1.07535[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]12.318[/C][C]4.78202[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]13.5061[/C][C]2.59392[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.909[/C][C]-0.00901039[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]6.857[/C][C]4.093[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]15.9304[/C][C]2.51958[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.7007[/C][C]1.3993[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.4204[/C][C]-2.42038[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.6918[/C][C]2.6582[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.1919[/C][C]4.7581[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]17.5289[/C][C]0.571134[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]13.4731[/C][C]1.12688[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.0877[/C][C]1.31234[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.0681[/C][C]4.33188[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.3239[/C][C]-0.723911[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.35552[/C][C]6.99448[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]17.1254[/C][C]1.97464[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.2857[/C][C]-2.93566[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.01296[/C][C]-1.41296[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.1961[/C][C]1.20385[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.0186[/C][C]2.88137[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.1876[/C][C]2.91236[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.0386[/C][C]0.211425[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.6029[/C][C]2.29715[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.8748[/C][C]5.22517[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.968[/C][C]0.382038[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]12.2801[/C][C]0.869876[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]10.0358[/C][C]2.11423[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.8941[/C][C]-1.29406[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.65183[/C][C]1.69817[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.1644[/C][C]-2.76444[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.38664[/C][C]6.21336[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.901[/C][C]1.29902[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.6648[/C][C]0.9352[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]13.8027[/C][C]1.04728[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]12.2168[/C][C]2.53322[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.4643[/C][C]3.63569[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.2632[/C][C]3.63682[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]13.787[/C][C]2.463[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.2748[/C][C]1.97516[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.8007[/C][C]0.799285[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.1029[/C][C]2.49708[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.4629[/C][C]1.18709[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.57004[/C][C]3.17996[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]16.182[/C][C]-1.58198[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.41986[/C][C]0.430139[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]7.45234[/C][C]5.19766[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.6395[/C][C]2.56046[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.352[/C][C]-0.751971[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]9.20732[/C][C]1.99268[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]15.7176[/C][C]-0.467553[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]9.34196[/C][C]2.55804[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]11.3975[/C][C]1.80246[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.4434[/C][C]0.906602[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.59272[/C][C]2.80728[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]11.4984[/C][C]4.35156[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.54[/C][C]-0.389981[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.98868[/C][C]2.16132[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]9.82392[/C][C]5.82608[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.0874[/C][C]-3.33741[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]7.31684[/C][C]0.333164[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.46468[/C][C]3.88532[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]11.7094[/C][C]3.89065[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.7184[/C][C]3.5816[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]10.725[/C][C]4.47496[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]13.8588[/C][C]3.24119[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.171[/C][C]3.42895[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]13.2487[/C][C]5.15135[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]12.6349[/C][C]6.41513[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.8871[/C][C]2.66293[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]17.7212[/C][C]1.37884[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.5708[/C][C]-0.470811[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.2676[/C][C]-1.41758[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.3683[/C][C]-6.86832[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]2.5177[/C][C]1.9823[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.6287[/C][C]0.221269[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.9122[/C][C]-0.312158[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]9.94634[/C][C]1.75366[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.1224[/C][C]-0.72238[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]12.1032[/C][C]1.24676[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.02984[/C][C]2.37016[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]11.4575[/C][C]3.44254[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.0329[/C][C]-1.13286[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]9.57067[/C][C]1.62933[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.0111[/C][C]2.58886[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]15.8744[/C][C]1.7256[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]11.284[/C][C]2.766[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.4127[/C][C]0.687259[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]12.5253[/C][C]0.824683[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.2335[/C][C]-1.38349[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.1037[/C][C]0.846311[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.0938[/C][C]2.65616[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]16.0198[/C][C]-0.869756[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]10.7384[/C][C]2.46164[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]19.9195[/C][C]-3.06953[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]11.5475[/C][C]-3.69748[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]8.31047[/C][C]-0.610467[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.959[/C][C]-4.35902[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.58459[/C][C]-0.734587[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.6344[/C][C]0.315636[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]13.8385[/C][C]-1.48852[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.77261[/C][C]2.17739[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.7812[/C][C]3.11876[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.4663[/C][C]0.183681[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]11.3665[/C][C]2.03349[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]8.75271[/C][C]5.19729[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.9962[/C][C]3.70375[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.8432[/C][C]-0.993178[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]6.16283[/C][C]4.78717[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.7968[/C][C]0.553199[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.56767[/C][C]2.63233[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]11.2703[/C][C]3.82974[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.7227[/C][C]2.02726[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.3585[/C][C]1.84152[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.9512[/C][C]3.64885[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	14.6733	-1.77328
2	12.2	12.4641	-0.264145
3	12.8	13.6055	-0.805535
4	7.4	13.7702	-6.37019
5	6.7	11.8616	-5.16163
6	12.6	13.1466	-0.546563
7	14.8	14.4802	0.319767
8	13.3	15.5324	-2.23243
9	11.1	13.761	-2.66096
10	8.2	14.1185	-5.91848
11	11.4	13.3282	-1.92822
12	6.4	14.1394	-7.73939
13	10.6	11.2666	-0.666596
14	12	15.349	-3.34905
15	6.3	10.006	-3.70603
16	11.3	11.0273	0.272679
17	11.9	14.6016	-2.70165
18	9.3	11.9727	-2.67266
19	9.6	12.7082	-3.10817
20	10	12.1985	-2.19853
21	6.4	12.9007	-6.50075
22	13.8	12.542	1.25795
23	10.8	14.1629	-3.36286
24	13.8	15.0336	-1.23359
25	11.7	14.7219	-3.02188
26	10.9	16.4351	-5.53508
27	16.1	14.468	1.63201
28	13.4	13.1961	0.203936
29	9.9	15.2415	-5.34153
30	11.5	13.897	-2.39697
31	8.3	11.8997	-3.59969
32	11.7	13.227	-1.52705
33	9	12.6277	-3.62774
34	9.7	14.123	-4.423
35	10.8	13.3241	-2.52406
36	10.3	13.7483	-3.44828
37	10.4	13.5099	-3.10992
38	12.7	11.7589	0.941136
39	9.3	14.6241	-5.32413
40	11.8	13.9883	-2.18834
41	5.9	13.2115	-7.31152
42	11.4	14.3223	-2.92234
43	13	14.2395	-1.23953
44	10.8	13.9469	-3.14687
45	12.3	11.8511	0.448876
46	11.3	14.2959	-2.99591
47	11.8	12.8558	-1.0558
48	7.9	11.8375	-3.93749
49	12.7	10.7546	1.94539
50	12.3	11.836	0.463984
51	11.6	12.9123	-1.31231
52	6.7	10.819	-4.11897
53	10.9	13.7463	-2.8463
54	12.1	11.7998	0.300204
55	13.3	13.5912	-0.2912
56	10.1	13.3801	-3.28005
57	5.7	12.8212	-7.1212
58	14.3	12.0951	2.20489
59	8	9.83532	-1.83532
60	13.3	12.8429	0.457099
61	9.3	16.03	-6.73001
62	12.5	11.3463	1.15366
63	7.6	13.8207	-6.22073
64	15.9	15.8256	0.074391
65	9.2	13.1124	-3.91238
66	9.1	12.5838	-3.48379
67	11.1	15.0903	-3.99026
68	13	17.7328	-4.73284
69	14.5	14.4758	0.0241648
70	12.2	12.2238	-0.0238118
71	12.3	14.074	-1.774
72	11.4	12.0858	-0.685782
73	8.8	12.3404	-3.54038
74	14.6	13.8166	0.783353
75	12.6	12.5489	0.0510857
76	NA	NA	0.0148271
77	13	12.938	0.061996
78	12.6	14.097	-1.49702
79	13.2	14.2319	-1.03191
80	9.9	14.3905	-4.49054
81	7.7	8.72443	-1.02443
82	10.5	8.31925	2.18075
83	13.4	15.6803	-2.28031
84	10.9	17.8763	-6.97635
85	4.3	8.15698	-3.85698
86	10.3	12.1032	-1.80321
87	11.8	12.294	-0.493991
88	11.2	11.3983	-0.198326
89	11.4	14.9726	-3.57256
90	8.6	7.34343	1.25657
91	13.2	12.856	0.343982
92	12.6	19.5721	-6.97207
93	5.6	8.71376	-3.11376
94	9.9	13.0739	-3.17387
95	8.8	12.0905	-3.2905
96	7.7	8.86955	-1.16955
97	9	13.5962	-4.59621
98	7.3	7.92919	-0.629192
99	11.4	9.06214	2.33786
100	13.6	18.5841	-4.98408
101	7.9	8.68909	-0.789089
102	10.7	13.0534	-2.35339
103	10.3	12.0589	-1.75894
104	8.3	11.2107	-2.9107
105	9.6	7.55043	2.04957
106	14.2	17.1336	-2.93364
107	8.5	7.08004	1.41996
108	13.5	21.4286	-7.92855
109	4.9	9.03468	-4.13468
110	6.4	9.50607	-3.10607
111	9.6	10.0518	-0.451803
112	11.6	12.1723	-0.57233
113	11.1	17.2525	-6.15249
114	4.35	4.63472	-0.284722
115	12.7	8.49804	4.20196
116	18.1	14.3293	3.77072
117	17.85	18.7977	-0.947684
118	16.6	15.1158	1.48417
119	12.6	12.0782	0.521806
120	17.1	14.1337	2.96628
121	19.1	21.524	-2.42399
122	16.1	13.121	2.97897
123	13.35	10.3731	2.97693
124	18.4	14.3062	4.09377
125	14.7	17.1487	-2.44868
126	10.6	9.1809	1.4191
127	12.6	8.57391	4.02609
128	16.2	15.9255	0.274503
129	13.6	8.69029	4.90971
130	18.9	16.9756	1.92438
131	14.1	12.6405	1.45954
132	14.5	13.0194	1.48062
133	16.15	14.8593	1.29071
134	14.75	13.5372	1.21281
135	14.8	15.0774	-0.277388
136	12.45	12.2532	0.196765
137	12.65	8.60564	4.04436
138	17.35	20.1646	-2.81457
139	8.6	5.02495	3.57505
140	18.4	18.2899	0.110068
141	16.1	17.3975	-1.29753
142	11.6	6.75853	4.84147
143	17.75	15.8122	1.93783
144	15.25	11.2815	3.96846
145	17.65	15.1863	2.46373
146	16.35	13.7673	2.58266
147	17.65	17.8	-0.150027
148	13.6	12.4464	1.15364
149	14.35	12.3793	1.97066
150	14.75	11.5549	3.19513
151	18.25	21.3378	-3.08782
152	9.9	8.93358	0.96642
153	16	11.8945	4.10553
154	18.25	14.336	3.91401
155	16.85	14.537	2.313
156	14.6	13.9264	0.673616
157	13.85	11.7672	2.08276
158	18.95	16.7825	2.1675
159	15.6	15.9686	-0.368584
160	14.85	15.8639	-1.01386
161	11.75	8.50903	3.24097
162	18.45	15.7674	2.68261
163	15.9	14.8247	1.07535
164	17.1	12.318	4.78202
165	16.1	13.5061	2.59392
166	19.9	19.909	-0.00901039
167	10.95	6.857	4.093
168	18.45	15.9304	2.51958
169	15.1	13.7007	1.3993
170	15	17.4204	-2.42038
171	11.35	8.6918	2.6582
172	15.95	11.1919	4.7581
173	18.1	17.5289	0.571134
174	14.6	13.4731	1.12688
175	15.4	14.0877	1.31234
176	15.4	11.0681	4.33188
177	17.6	18.3239	-0.723911
178	13.35	6.35552	6.99448
179	19.1	17.1254	1.97464
180	15.35	18.2857	-2.93566
181	7.6	9.01296	-1.41296
182	13.4	12.1961	1.20385
183	13.9	11.0186	2.88137
184	19.1	16.1876	2.91236
185	15.25	15.0386	0.211425
186	12.9	10.6029	2.29715
187	16.1	10.8748	5.22517
188	17.35	16.968	0.382038
189	13.15	12.2801	0.869876
190	12.15	10.0358	2.11423
191	12.6	13.8941	-1.29406
192	10.35	8.65183	1.69817
193	15.4	18.1644	-2.76444
194	9.6	3.38664	6.21336
195	18.2	16.901	1.29902
196	13.6	12.6648	0.9352
197	14.85	13.8027	1.04728
198	14.75	12.2168	2.53322
199	14.1	10.4643	3.63569
200	14.9	11.2632	3.63682
201	16.25	13.787	2.463
202	19.25	17.2748	1.97516
203	13.6	12.8007	0.799285
204	13.6	11.1029	2.49708
205	15.65	14.4629	1.18709
206	12.75	9.57004	3.17996
207	14.6	16.182	-1.58198
208	9.85	9.41986	0.430139
209	12.65	7.45234	5.19766
210	19.2	16.6395	2.56046
211	16.6	17.352	-0.751971
212	11.2	9.20732	1.99268
213	15.25	15.7176	-0.467553
214	11.9	9.34196	2.55804
215	13.2	11.3975	1.80246
216	16.35	15.4434	0.906602
217	12.4	9.59272	2.80728
218	15.85	11.4984	4.35156
219	18.15	18.54	-0.389981
220	11.15	8.98868	2.16132
221	15.65	9.82392	5.82608
222	17.75	21.0874	-3.33741
223	7.65	7.31684	0.333164
224	12.35	8.46468	3.88532
225	15.6	11.7094	3.89065
226	19.3	15.7184	3.5816
227	15.2	10.725	4.47496
228	17.1	13.8588	3.24119
229	15.6	12.171	3.42895
230	18.4	13.2487	5.15135
231	19.05	12.6349	6.41513
232	18.55	15.8871	2.66293
233	19.1	17.7212	1.37884
234	13.1	13.5708	-0.470811
235	12.85	14.2676	-1.41758
236	9.5	16.3683	-6.86832
237	4.5	2.5177	1.9823
238	11.85	11.6287	0.221269
239	13.6	13.9122	-0.312158
240	11.7	9.94634	1.75366
241	12.4	13.1224	-0.72238
242	13.35	12.1032	1.24676
243	11.4	9.02984	2.37016
244	14.9	11.4575	3.44254
245	19.9	21.0329	-1.13286
246	11.2	9.57067	1.62933
247	14.6	12.0111	2.58886
248	17.6	15.8744	1.7256
249	14.05	11.284	2.766
250	16.1	15.4127	0.687259
251	13.35	12.5253	0.824683
252	11.85	13.2335	-1.38349
253	11.95	11.1037	0.846311
254	14.75	12.0938	2.65616
255	15.15	16.0198	-0.869756
256	13.2	10.7384	2.46164
257	16.85	19.9195	-3.06953
258	7.85	11.5475	-3.69748
259	7.7	8.31047	-0.610467
260	12.6	16.959	-4.35902
261	7.85	8.58459	-0.734587
262	10.95	10.6344	0.315636
263	12.35	13.8385	-1.48852
264	9.95	7.77261	2.17739
265	14.9	11.7812	3.11876
266	16.65	16.4663	0.183681
267	13.4	11.3665	2.03349
268	13.95	8.75271	5.19729
269	15.7	11.9962	3.70375
270	16.85	17.8432	-0.993178
271	10.95	6.16283	4.78717
272	15.35	14.7968	0.553199
273	12.2	9.56767	2.63233
274	15.1	11.2703	3.82974
275	17.75	15.7227	2.02726
276	15.2	13.3585	1.84152
277	14.6	10.9512	3.64885
278	16.65	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
19	0.223318	0.446636	0.776682
20	0.16158	0.32316	0.83842
21	0.0832518	0.166504	0.916748
22	0.0849814	0.169963	0.915019
23	0.0614909	0.122982	0.938509
24	0.0442422	0.0884843	0.955758
25	0.023271	0.046542	0.976729
26	0.0154636	0.0309272	0.984536
27	0.00778469	0.0155694	0.992215
28	0.00363754	0.00727508	0.996362
29	0.00343874	0.00687749	0.996561
30	0.00204321	0.00408642	0.997957
31	0.00333676	0.00667353	0.996663
32	0.0019437	0.0038874	0.998056
33	0.00432939	0.00865878	0.995671
34	0.0205692	0.0411384	0.979431
35	0.0150773	0.0301545	0.984923
36	0.0103166	0.0206333	0.989683
37	0.0148804	0.0297609	0.98512
38	0.0202009	0.0404018	0.979799
39	0.02327	0.04654	0.97673
40	0.0158709	0.0317417	0.984129
41	0.0233143	0.0466286	0.976686
42	0.0191129	0.0382258	0.980887
43	0.0148319	0.0296639	0.985168
44	0.0167291	0.0334582	0.983271
45	0.0119725	0.023945	0.988028
46	0.0102054	0.0204109	0.989795
47	0.00836876	0.0167375	0.991631
48	0.00657844	0.0131569	0.993422
49	0.0104515	0.0209031	0.989548
50	0.0172409	0.0344818	0.982759
51	0.0136025	0.027205	0.986397
52	0.0135876	0.0271752	0.986412
53	0.0106112	0.0212224	0.989389
54	0.0127021	0.0254042	0.987298
55	0.0252677	0.0505355	0.974732
56	0.021643	0.043286	0.978357
57	0.0665294	0.133059	0.933471
58	0.0622748	0.12455	0.937725
59	0.0509506	0.101901	0.949049
60	0.0481639	0.0963279	0.951836
61	0.0675633	0.135127	0.932437
62	0.0576818	0.115364	0.942318
63	0.108955	0.217909	0.891045
64	0.124249	0.248498	0.875751
65	0.140446	0.280892	0.859554
66	0.12463	0.249261	0.87537
67	0.124484	0.248967	0.875516
68	0.146774	0.293548	0.853226
69	0.166038	0.332077	0.833962
70	0.14568	0.291359	0.85432
71	0.133356	0.266712	0.866644
72	0.117734	0.235468	0.882266
73	0.112586	0.225173	0.887414
74	0.157745	0.31549	0.842255
75	0.135195	0.27039	0.864805
76	0.116899	0.233798	0.883101
77	0.105735	0.21147	0.894265
78	0.0992299	0.19846	0.90077
79	0.0824834	0.164967	0.917517
80	0.0948239	0.189648	0.905176
81	0.0813062	0.162612	0.918694
82	0.0926927	0.185385	0.907307
83	0.0810257	0.162051	0.918974
84	0.160601	0.321202	0.839399
85	0.158629	0.317258	0.841371
86	0.14166	0.283321	0.85834
87	0.127575	0.25515	0.872425
88	0.131452	0.262904	0.868548
89	0.134354	0.268708	0.865646
90	0.146581	0.293162	0.853419
91	0.1478	0.2956	0.8522
92	0.272466	0.544931	0.727534
93	0.277115	0.554229	0.722885
94	0.269789	0.539577	0.730211
95	0.265403	0.530805	0.734597
96	0.25008	0.500159	0.74992
97	0.332237	0.664475	0.667763
98	0.308546	0.617092	0.691454
99	0.323948	0.647895	0.676052
100	0.383283	0.766566	0.616717
101	0.359622	0.719243	0.640378
102	0.363974	0.727947	0.636026
103	0.383761	0.767523	0.616239
104	0.403537	0.807075	0.596463
105	0.420299	0.840599	0.579701
106	0.434135	0.868269	0.565865
107	0.495411	0.990822	0.504589
108	0.745092	0.509816	0.254908
109	0.787164	0.425673	0.212836
110	0.784973	0.430055	0.215027
111	0.785421	0.429158	0.214579
112	0.797393	0.405214	0.202607
113	0.884646	0.230707	0.115354
114	0.896613	0.206775	0.103387
115	0.947226	0.105547	0.0527737
116	0.969147	0.0617054	0.0308527
117	0.97012	0.0597594	0.0298797
118	0.973515	0.0529692	0.0264846
119	0.97945	0.0410998	0.0205499
120	0.984804	0.030392	0.015196
121	0.987602	0.0247964	0.0123982
122	0.99224	0.0155193	0.00775967
123	0.995819	0.00836147	0.00418073
124	0.99816	0.00367996	0.00183998
125	0.998364	0.0032712	0.0016356
126	0.998136	0.00372876	0.00186438
127	0.998593	0.00281409	0.00140705
128	0.998333	0.00333489	0.00166744
129	0.999178	0.00164426	0.000822131
130	0.999207	0.00158699	0.000793493
131	0.99913	0.0017403	0.000870151
132	0.998995	0.00200921	0.00100461
133	0.998847	0.00230646	0.00115323
134	0.999016	0.00196825	0.000984125
135	0.998751	0.00249808	0.00124904
136	0.99855	0.00289935	0.00144967
137	0.999012	0.00197536	0.000987678
138	0.998917	0.00216613	0.00108307
139	0.999193	0.00161454	0.00080727
140	0.998963	0.00207374	0.00103687
141	0.998619	0.00276153	0.00138077
142	0.999081	0.00183872	0.000919361
143	0.99909	0.00182005	0.000910023
144	0.999338	0.00132374	0.000661868
145	0.999227	0.00154555	0.000772775
146	0.999196	0.00160725	0.000803623
147	0.998962	0.00207525	0.00103762
148	0.998687	0.00262638	0.00131319
149	0.998651	0.00269737	0.00134869
150	0.998666	0.00266894	0.00133447
151	0.999383	0.0012334	0.000616698
152	0.999199	0.00160224	0.000801122
153	0.999412	0.00117536	0.000587682
154	0.999405	0.00118956	0.000594782
155	0.9994	0.00119978	0.000599892
156	0.99919	0.00162036	0.000810178
157	0.999056	0.00188801	0.000944004
158	0.99894	0.00211987	0.00105994
159	0.998755	0.00248904	0.00124452
160	0.998577	0.00284541	0.00142271
161	0.998678	0.0026438	0.0013219
162	0.998695	0.00261035	0.00130518
163	0.99885	0.00229917	0.00114958
164	0.999789	0.000422024	0.000211012
165	0.999753	0.000494025	0.000247013
166	0.999702	0.000595626	0.000297813
167	0.999752	0.00049633	0.000248165
168	0.999779	0.000441964	0.000220982
169	0.9997	0.000600816	0.000300408
170	0.999682	0.000635404	0.000317702
171	0.999653	0.000694415	0.000347207
172	0.999751	0.000497995	0.000248998
173	0.999737	0.000526888	0.000263444
174	0.999626	0.00074792	0.00037396
175	0.999485	0.00102982	0.00051491
176	0.999611	0.000778009	0.000389004
177	0.999497	0.00100602	0.000503011
178	0.999803	0.000394051	0.000197025
179	0.999733	0.00053471	0.000267355
180	0.999749	0.000501783	0.000250892
181	0.999716	0.000568607	0.000284304
182	0.999599	0.000801976	0.000400988
183	0.999505	0.000990361	0.000495181
184	0.999411	0.00117709	0.000588544
185	0.999275	0.00145038	0.000725191
186	0.999095	0.00181075	0.000905376
187	0.999428	0.00114338	0.000571688
188	0.999249	0.00150276	0.00075138
189	0.998964	0.00207176	0.00103588
190	0.998704	0.00259223	0.00129612
191	0.998252	0.0034964	0.0017482
192	0.997931	0.00413751	0.00206876
193	0.9983	0.00339981	0.0016999
194	0.999267	0.00146694	0.000733471
195	0.999051	0.00189897	0.000949486
196	0.99876	0.00247901	0.0012395
197	0.998481	0.00303758	0.00151879
198	0.998158	0.00368301	0.00184151
199	0.99847	0.00306028	0.00153014
200	0.998417	0.00316694	0.00158347
201	0.997816	0.00436855	0.00218427
202	0.997519	0.0049612	0.0024806
203	0.996781	0.0064387	0.00321935
204	0.99597	0.00806058	0.00403029
205	0.994804	0.010392	0.005196
206	0.993735	0.0125301	0.00626507
207	0.991708	0.0165837	0.00829186
208	0.989467	0.021065	0.0105325
209	0.989414	0.0211722	0.0105861
210	0.987006	0.0259882	0.0129941
211	0.982598	0.0348044	0.0174022
212	0.977463	0.0450736	0.0225368
213	0.976826	0.0463476	0.0231738
214	0.976786	0.0464272	0.0232136
215	0.97494	0.0501199	0.02506
216	0.966928	0.0661448	0.0330724
217	0.963464	0.0730716	0.0365358
218	0.956932	0.0861354	0.0430677
219	0.944843	0.110315	0.0551575
220	0.93197	0.136061	0.0680304
221	0.942566	0.114867	0.0574336
222	0.943219	0.113562	0.0567812
223	0.928389	0.143222	0.0716112
224	0.936644	0.126711	0.0633557
225	0.925974	0.148052	0.0740261
226	0.954987	0.0900255	0.0450127
227	0.960156	0.079688	0.039844
228	0.955388	0.0892233	0.0446116
229	0.943092	0.113817	0.0569084
230	0.953259	0.0934818	0.0467409
231	0.969311	0.061379	0.0306895
232	0.95864	0.082721	0.0413605
233	0.94433	0.11134	0.0556698
234	0.933509	0.132983	0.0664914
235	0.914239	0.171522	0.0857611
236	0.981174	0.0376516	0.0188258
237	0.981999	0.0360018	0.0180009
238	0.974464	0.0510724	0.0255362
239	0.965296	0.0694089	0.0347045
240	0.950251	0.0994978	0.0497489
241	0.940539	0.118923	0.0594614
242	0.91755	0.164899	0.0824497
243	0.894022	0.211955	0.105978
244	0.8669	0.266201	0.1331
245	0.881041	0.237918	0.118959
246	0.84474	0.31052	0.15526
247	0.81806	0.363881	0.18194
248	0.75722	0.485559	0.24278
249	0.68708	0.625839	0.31292
250	0.606421	0.787158	0.393579
251	0.514931	0.970139	0.485069
252	0.430182	0.860365	0.569818
253	0.334914	0.669829	0.665086
254	0.492441	0.984882	0.507559
255	0.451581	0.903162	0.548419
256	0.354098	0.708197	0.645902
257	0.327149	0.654298	0.672851
258	0.902253	0.195495	0.0977473
259	0.766698	0.466604	0.233302

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
19 & 0.223318 & 0.446636 & 0.776682 \tabularnewline
20 & 0.16158 & 0.32316 & 0.83842 \tabularnewline
21 & 0.0832518 & 0.166504 & 0.916748 \tabularnewline
22 & 0.0849814 & 0.169963 & 0.915019 \tabularnewline
23 & 0.0614909 & 0.122982 & 0.938509 \tabularnewline
24 & 0.0442422 & 0.0884843 & 0.955758 \tabularnewline
25 & 0.023271 & 0.046542 & 0.976729 \tabularnewline
26 & 0.0154636 & 0.0309272 & 0.984536 \tabularnewline
27 & 0.00778469 & 0.0155694 & 0.992215 \tabularnewline
28 & 0.00363754 & 0.00727508 & 0.996362 \tabularnewline
29 & 0.00343874 & 0.00687749 & 0.996561 \tabularnewline
30 & 0.00204321 & 0.00408642 & 0.997957 \tabularnewline
31 & 0.00333676 & 0.00667353 & 0.996663 \tabularnewline
32 & 0.0019437 & 0.0038874 & 0.998056 \tabularnewline
33 & 0.00432939 & 0.00865878 & 0.995671 \tabularnewline
34 & 0.0205692 & 0.0411384 & 0.979431 \tabularnewline
35 & 0.0150773 & 0.0301545 & 0.984923 \tabularnewline
36 & 0.0103166 & 0.0206333 & 0.989683 \tabularnewline
37 & 0.0148804 & 0.0297609 & 0.98512 \tabularnewline
38 & 0.0202009 & 0.0404018 & 0.979799 \tabularnewline
39 & 0.02327 & 0.04654 & 0.97673 \tabularnewline
40 & 0.0158709 & 0.0317417 & 0.984129 \tabularnewline
41 & 0.0233143 & 0.0466286 & 0.976686 \tabularnewline
42 & 0.0191129 & 0.0382258 & 0.980887 \tabularnewline
43 & 0.0148319 & 0.0296639 & 0.985168 \tabularnewline
44 & 0.0167291 & 0.0334582 & 0.983271 \tabularnewline
45 & 0.0119725 & 0.023945 & 0.988028 \tabularnewline
46 & 0.0102054 & 0.0204109 & 0.989795 \tabularnewline
47 & 0.00836876 & 0.0167375 & 0.991631 \tabularnewline
48 & 0.00657844 & 0.0131569 & 0.993422 \tabularnewline
49 & 0.0104515 & 0.0209031 & 0.989548 \tabularnewline
50 & 0.0172409 & 0.0344818 & 0.982759 \tabularnewline
51 & 0.0136025 & 0.027205 & 0.986397 \tabularnewline
52 & 0.0135876 & 0.0271752 & 0.986412 \tabularnewline
53 & 0.0106112 & 0.0212224 & 0.989389 \tabularnewline
54 & 0.0127021 & 0.0254042 & 0.987298 \tabularnewline
55 & 0.0252677 & 0.0505355 & 0.974732 \tabularnewline
56 & 0.021643 & 0.043286 & 0.978357 \tabularnewline
57 & 0.0665294 & 0.133059 & 0.933471 \tabularnewline
58 & 0.0622748 & 0.12455 & 0.937725 \tabularnewline
59 & 0.0509506 & 0.101901 & 0.949049 \tabularnewline
60 & 0.0481639 & 0.0963279 & 0.951836 \tabularnewline
61 & 0.0675633 & 0.135127 & 0.932437 \tabularnewline
62 & 0.0576818 & 0.115364 & 0.942318 \tabularnewline
63 & 0.108955 & 0.217909 & 0.891045 \tabularnewline
64 & 0.124249 & 0.248498 & 0.875751 \tabularnewline
65 & 0.140446 & 0.280892 & 0.859554 \tabularnewline
66 & 0.12463 & 0.249261 & 0.87537 \tabularnewline
67 & 0.124484 & 0.248967 & 0.875516 \tabularnewline
68 & 0.146774 & 0.293548 & 0.853226 \tabularnewline
69 & 0.166038 & 0.332077 & 0.833962 \tabularnewline
70 & 0.14568 & 0.291359 & 0.85432 \tabularnewline
71 & 0.133356 & 0.266712 & 0.866644 \tabularnewline
72 & 0.117734 & 0.235468 & 0.882266 \tabularnewline
73 & 0.112586 & 0.225173 & 0.887414 \tabularnewline
74 & 0.157745 & 0.31549 & 0.842255 \tabularnewline
75 & 0.135195 & 0.27039 & 0.864805 \tabularnewline
76 & 0.116899 & 0.233798 & 0.883101 \tabularnewline
77 & 0.105735 & 0.21147 & 0.894265 \tabularnewline
78 & 0.0992299 & 0.19846 & 0.90077 \tabularnewline
79 & 0.0824834 & 0.164967 & 0.917517 \tabularnewline
80 & 0.0948239 & 0.189648 & 0.905176 \tabularnewline
81 & 0.0813062 & 0.162612 & 0.918694 \tabularnewline
82 & 0.0926927 & 0.185385 & 0.907307 \tabularnewline
83 & 0.0810257 & 0.162051 & 0.918974 \tabularnewline
84 & 0.160601 & 0.321202 & 0.839399 \tabularnewline
85 & 0.158629 & 0.317258 & 0.841371 \tabularnewline
86 & 0.14166 & 0.283321 & 0.85834 \tabularnewline
87 & 0.127575 & 0.25515 & 0.872425 \tabularnewline
88 & 0.131452 & 0.262904 & 0.868548 \tabularnewline
89 & 0.134354 & 0.268708 & 0.865646 \tabularnewline
90 & 0.146581 & 0.293162 & 0.853419 \tabularnewline
91 & 0.1478 & 0.2956 & 0.8522 \tabularnewline
92 & 0.272466 & 0.544931 & 0.727534 \tabularnewline
93 & 0.277115 & 0.554229 & 0.722885 \tabularnewline
94 & 0.269789 & 0.539577 & 0.730211 \tabularnewline
95 & 0.265403 & 0.530805 & 0.734597 \tabularnewline
96 & 0.25008 & 0.500159 & 0.74992 \tabularnewline
97 & 0.332237 & 0.664475 & 0.667763 \tabularnewline
98 & 0.308546 & 0.617092 & 0.691454 \tabularnewline
99 & 0.323948 & 0.647895 & 0.676052 \tabularnewline
100 & 0.383283 & 0.766566 & 0.616717 \tabularnewline
101 & 0.359622 & 0.719243 & 0.640378 \tabularnewline
102 & 0.363974 & 0.727947 & 0.636026 \tabularnewline
103 & 0.383761 & 0.767523 & 0.616239 \tabularnewline
104 & 0.403537 & 0.807075 & 0.596463 \tabularnewline
105 & 0.420299 & 0.840599 & 0.579701 \tabularnewline
106 & 0.434135 & 0.868269 & 0.565865 \tabularnewline
107 & 0.495411 & 0.990822 & 0.504589 \tabularnewline
108 & 0.745092 & 0.509816 & 0.254908 \tabularnewline
109 & 0.787164 & 0.425673 & 0.212836 \tabularnewline
110 & 0.784973 & 0.430055 & 0.215027 \tabularnewline
111 & 0.785421 & 0.429158 & 0.214579 \tabularnewline
112 & 0.797393 & 0.405214 & 0.202607 \tabularnewline
113 & 0.884646 & 0.230707 & 0.115354 \tabularnewline
114 & 0.896613 & 0.206775 & 0.103387 \tabularnewline
115 & 0.947226 & 0.105547 & 0.0527737 \tabularnewline
116 & 0.969147 & 0.0617054 & 0.0308527 \tabularnewline
117 & 0.97012 & 0.0597594 & 0.0298797 \tabularnewline
118 & 0.973515 & 0.0529692 & 0.0264846 \tabularnewline
119 & 0.97945 & 0.0410998 & 0.0205499 \tabularnewline
120 & 0.984804 & 0.030392 & 0.015196 \tabularnewline
121 & 0.987602 & 0.0247964 & 0.0123982 \tabularnewline
122 & 0.99224 & 0.0155193 & 0.00775967 \tabularnewline
123 & 0.995819 & 0.00836147 & 0.00418073 \tabularnewline
124 & 0.99816 & 0.00367996 & 0.00183998 \tabularnewline
125 & 0.998364 & 0.0032712 & 0.0016356 \tabularnewline
126 & 0.998136 & 0.00372876 & 0.00186438 \tabularnewline
127 & 0.998593 & 0.00281409 & 0.00140705 \tabularnewline
128 & 0.998333 & 0.00333489 & 0.00166744 \tabularnewline
129 & 0.999178 & 0.00164426 & 0.000822131 \tabularnewline
130 & 0.999207 & 0.00158699 & 0.000793493 \tabularnewline
131 & 0.99913 & 0.0017403 & 0.000870151 \tabularnewline
132 & 0.998995 & 0.00200921 & 0.00100461 \tabularnewline
133 & 0.998847 & 0.00230646 & 0.00115323 \tabularnewline
134 & 0.999016 & 0.00196825 & 0.000984125 \tabularnewline
135 & 0.998751 & 0.00249808 & 0.00124904 \tabularnewline
136 & 0.99855 & 0.00289935 & 0.00144967 \tabularnewline
137 & 0.999012 & 0.00197536 & 0.000987678 \tabularnewline
138 & 0.998917 & 0.00216613 & 0.00108307 \tabularnewline
139 & 0.999193 & 0.00161454 & 0.00080727 \tabularnewline
140 & 0.998963 & 0.00207374 & 0.00103687 \tabularnewline
141 & 0.998619 & 0.00276153 & 0.00138077 \tabularnewline
142 & 0.999081 & 0.00183872 & 0.000919361 \tabularnewline
143 & 0.99909 & 0.00182005 & 0.000910023 \tabularnewline
144 & 0.999338 & 0.00132374 & 0.000661868 \tabularnewline
145 & 0.999227 & 0.00154555 & 0.000772775 \tabularnewline
146 & 0.999196 & 0.00160725 & 0.000803623 \tabularnewline
147 & 0.998962 & 0.00207525 & 0.00103762 \tabularnewline
148 & 0.998687 & 0.00262638 & 0.00131319 \tabularnewline
149 & 0.998651 & 0.00269737 & 0.00134869 \tabularnewline
150 & 0.998666 & 0.00266894 & 0.00133447 \tabularnewline
151 & 0.999383 & 0.0012334 & 0.000616698 \tabularnewline
152 & 0.999199 & 0.00160224 & 0.000801122 \tabularnewline
153 & 0.999412 & 0.00117536 & 0.000587682 \tabularnewline
154 & 0.999405 & 0.00118956 & 0.000594782 \tabularnewline
155 & 0.9994 & 0.00119978 & 0.000599892 \tabularnewline
156 & 0.99919 & 0.00162036 & 0.000810178 \tabularnewline
157 & 0.999056 & 0.00188801 & 0.000944004 \tabularnewline
158 & 0.99894 & 0.00211987 & 0.00105994 \tabularnewline
159 & 0.998755 & 0.00248904 & 0.00124452 \tabularnewline
160 & 0.998577 & 0.00284541 & 0.00142271 \tabularnewline
161 & 0.998678 & 0.0026438 & 0.0013219 \tabularnewline
162 & 0.998695 & 0.00261035 & 0.00130518 \tabularnewline
163 & 0.99885 & 0.00229917 & 0.00114958 \tabularnewline
164 & 0.999789 & 0.000422024 & 0.000211012 \tabularnewline
165 & 0.999753 & 0.000494025 & 0.000247013 \tabularnewline
166 & 0.999702 & 0.000595626 & 0.000297813 \tabularnewline
167 & 0.999752 & 0.00049633 & 0.000248165 \tabularnewline
168 & 0.999779 & 0.000441964 & 0.000220982 \tabularnewline
169 & 0.9997 & 0.000600816 & 0.000300408 \tabularnewline
170 & 0.999682 & 0.000635404 & 0.000317702 \tabularnewline
171 & 0.999653 & 0.000694415 & 0.000347207 \tabularnewline
172 & 0.999751 & 0.000497995 & 0.000248998 \tabularnewline
173 & 0.999737 & 0.000526888 & 0.000263444 \tabularnewline
174 & 0.999626 & 0.00074792 & 0.00037396 \tabularnewline
175 & 0.999485 & 0.00102982 & 0.00051491 \tabularnewline
176 & 0.999611 & 0.000778009 & 0.000389004 \tabularnewline
177 & 0.999497 & 0.00100602 & 0.000503011 \tabularnewline
178 & 0.999803 & 0.000394051 & 0.000197025 \tabularnewline
179 & 0.999733 & 0.00053471 & 0.000267355 \tabularnewline
180 & 0.999749 & 0.000501783 & 0.000250892 \tabularnewline
181 & 0.999716 & 0.000568607 & 0.000284304 \tabularnewline
182 & 0.999599 & 0.000801976 & 0.000400988 \tabularnewline
183 & 0.999505 & 0.000990361 & 0.000495181 \tabularnewline
184 & 0.999411 & 0.00117709 & 0.000588544 \tabularnewline
185 & 0.999275 & 0.00145038 & 0.000725191 \tabularnewline
186 & 0.999095 & 0.00181075 & 0.000905376 \tabularnewline
187 & 0.999428 & 0.00114338 & 0.000571688 \tabularnewline
188 & 0.999249 & 0.00150276 & 0.00075138 \tabularnewline
189 & 0.998964 & 0.00207176 & 0.00103588 \tabularnewline
190 & 0.998704 & 0.00259223 & 0.00129612 \tabularnewline
191 & 0.998252 & 0.0034964 & 0.0017482 \tabularnewline
192 & 0.997931 & 0.00413751 & 0.00206876 \tabularnewline
193 & 0.9983 & 0.00339981 & 0.0016999 \tabularnewline
194 & 0.999267 & 0.00146694 & 0.000733471 \tabularnewline
195 & 0.999051 & 0.00189897 & 0.000949486 \tabularnewline
196 & 0.99876 & 0.00247901 & 0.0012395 \tabularnewline
197 & 0.998481 & 0.00303758 & 0.00151879 \tabularnewline
198 & 0.998158 & 0.00368301 & 0.00184151 \tabularnewline
199 & 0.99847 & 0.00306028 & 0.00153014 \tabularnewline
200 & 0.998417 & 0.00316694 & 0.00158347 \tabularnewline
201 & 0.997816 & 0.00436855 & 0.00218427 \tabularnewline
202 & 0.997519 & 0.0049612 & 0.0024806 \tabularnewline
203 & 0.996781 & 0.0064387 & 0.00321935 \tabularnewline
204 & 0.99597 & 0.00806058 & 0.00403029 \tabularnewline
205 & 0.994804 & 0.010392 & 0.005196 \tabularnewline
206 & 0.993735 & 0.0125301 & 0.00626507 \tabularnewline
207 & 0.991708 & 0.0165837 & 0.00829186 \tabularnewline
208 & 0.989467 & 0.021065 & 0.0105325 \tabularnewline
209 & 0.989414 & 0.0211722 & 0.0105861 \tabularnewline
210 & 0.987006 & 0.0259882 & 0.0129941 \tabularnewline
211 & 0.982598 & 0.0348044 & 0.0174022 \tabularnewline
212 & 0.977463 & 0.0450736 & 0.0225368 \tabularnewline
213 & 0.976826 & 0.0463476 & 0.0231738 \tabularnewline
214 & 0.976786 & 0.0464272 & 0.0232136 \tabularnewline
215 & 0.97494 & 0.0501199 & 0.02506 \tabularnewline
216 & 0.966928 & 0.0661448 & 0.0330724 \tabularnewline
217 & 0.963464 & 0.0730716 & 0.0365358 \tabularnewline
218 & 0.956932 & 0.0861354 & 0.0430677 \tabularnewline
219 & 0.944843 & 0.110315 & 0.0551575 \tabularnewline
220 & 0.93197 & 0.136061 & 0.0680304 \tabularnewline
221 & 0.942566 & 0.114867 & 0.0574336 \tabularnewline
222 & 0.943219 & 0.113562 & 0.0567812 \tabularnewline
223 & 0.928389 & 0.143222 & 0.0716112 \tabularnewline
224 & 0.936644 & 0.126711 & 0.0633557 \tabularnewline
225 & 0.925974 & 0.148052 & 0.0740261 \tabularnewline
226 & 0.954987 & 0.0900255 & 0.0450127 \tabularnewline
227 & 0.960156 & 0.079688 & 0.039844 \tabularnewline
228 & 0.955388 & 0.0892233 & 0.0446116 \tabularnewline
229 & 0.943092 & 0.113817 & 0.0569084 \tabularnewline
230 & 0.953259 & 0.0934818 & 0.0467409 \tabularnewline
231 & 0.969311 & 0.061379 & 0.0306895 \tabularnewline
232 & 0.95864 & 0.082721 & 0.0413605 \tabularnewline
233 & 0.94433 & 0.11134 & 0.0556698 \tabularnewline
234 & 0.933509 & 0.132983 & 0.0664914 \tabularnewline
235 & 0.914239 & 0.171522 & 0.0857611 \tabularnewline
236 & 0.981174 & 0.0376516 & 0.0188258 \tabularnewline
237 & 0.981999 & 0.0360018 & 0.0180009 \tabularnewline
238 & 0.974464 & 0.0510724 & 0.0255362 \tabularnewline
239 & 0.965296 & 0.0694089 & 0.0347045 \tabularnewline
240 & 0.950251 & 0.0994978 & 0.0497489 \tabularnewline
241 & 0.940539 & 0.118923 & 0.0594614 \tabularnewline
242 & 0.91755 & 0.164899 & 0.0824497 \tabularnewline
243 & 0.894022 & 0.211955 & 0.105978 \tabularnewline
244 & 0.8669 & 0.266201 & 0.1331 \tabularnewline
245 & 0.881041 & 0.237918 & 0.118959 \tabularnewline
246 & 0.84474 & 0.31052 & 0.15526 \tabularnewline
247 & 0.81806 & 0.363881 & 0.18194 \tabularnewline
248 & 0.75722 & 0.485559 & 0.24278 \tabularnewline
249 & 0.68708 & 0.625839 & 0.31292 \tabularnewline
250 & 0.606421 & 0.787158 & 0.393579 \tabularnewline
251 & 0.514931 & 0.970139 & 0.485069 \tabularnewline
252 & 0.430182 & 0.860365 & 0.569818 \tabularnewline
253 & 0.334914 & 0.669829 & 0.665086 \tabularnewline
254 & 0.492441 & 0.984882 & 0.507559 \tabularnewline
255 & 0.451581 & 0.903162 & 0.548419 \tabularnewline
256 & 0.354098 & 0.708197 & 0.645902 \tabularnewline
257 & 0.327149 & 0.654298 & 0.672851 \tabularnewline
258 & 0.902253 & 0.195495 & 0.0977473 \tabularnewline
259 & 0.766698 & 0.466604 & 0.233302 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]19[/C][C]0.223318[/C][C]0.446636[/C][C]0.776682[/C][/ROW]
[ROW][C]20[/C][C]0.16158[/C][C]0.32316[/C][C]0.83842[/C][/ROW]
[ROW][C]21[/C][C]0.0832518[/C][C]0.166504[/C][C]0.916748[/C][/ROW]
[ROW][C]22[/C][C]0.0849814[/C][C]0.169963[/C][C]0.915019[/C][/ROW]
[ROW][C]23[/C][C]0.0614909[/C][C]0.122982[/C][C]0.938509[/C][/ROW]
[ROW][C]24[/C][C]0.0442422[/C][C]0.0884843[/C][C]0.955758[/C][/ROW]
[ROW][C]25[/C][C]0.023271[/C][C]0.046542[/C][C]0.976729[/C][/ROW]
[ROW][C]26[/C][C]0.0154636[/C][C]0.0309272[/C][C]0.984536[/C][/ROW]
[ROW][C]27[/C][C]0.00778469[/C][C]0.0155694[/C][C]0.992215[/C][/ROW]
[ROW][C]28[/C][C]0.00363754[/C][C]0.00727508[/C][C]0.996362[/C][/ROW]
[ROW][C]29[/C][C]0.00343874[/C][C]0.00687749[/C][C]0.996561[/C][/ROW]
[ROW][C]30[/C][C]0.00204321[/C][C]0.00408642[/C][C]0.997957[/C][/ROW]
[ROW][C]31[/C][C]0.00333676[/C][C]0.00667353[/C][C]0.996663[/C][/ROW]
[ROW][C]32[/C][C]0.0019437[/C][C]0.0038874[/C][C]0.998056[/C][/ROW]
[ROW][C]33[/C][C]0.00432939[/C][C]0.00865878[/C][C]0.995671[/C][/ROW]
[ROW][C]34[/C][C]0.0205692[/C][C]0.0411384[/C][C]0.979431[/C][/ROW]
[ROW][C]35[/C][C]0.0150773[/C][C]0.0301545[/C][C]0.984923[/C][/ROW]
[ROW][C]36[/C][C]0.0103166[/C][C]0.0206333[/C][C]0.989683[/C][/ROW]
[ROW][C]37[/C][C]0.0148804[/C][C]0.0297609[/C][C]0.98512[/C][/ROW]
[ROW][C]38[/C][C]0.0202009[/C][C]0.0404018[/C][C]0.979799[/C][/ROW]
[ROW][C]39[/C][C]0.02327[/C][C]0.04654[/C][C]0.97673[/C][/ROW]
[ROW][C]40[/C][C]0.0158709[/C][C]0.0317417[/C][C]0.984129[/C][/ROW]
[ROW][C]41[/C][C]0.0233143[/C][C]0.0466286[/C][C]0.976686[/C][/ROW]
[ROW][C]42[/C][C]0.0191129[/C][C]0.0382258[/C][C]0.980887[/C][/ROW]
[ROW][C]43[/C][C]0.0148319[/C][C]0.0296639[/C][C]0.985168[/C][/ROW]
[ROW][C]44[/C][C]0.0167291[/C][C]0.0334582[/C][C]0.983271[/C][/ROW]
[ROW][C]45[/C][C]0.0119725[/C][C]0.023945[/C][C]0.988028[/C][/ROW]
[ROW][C]46[/C][C]0.0102054[/C][C]0.0204109[/C][C]0.989795[/C][/ROW]
[ROW][C]47[/C][C]0.00836876[/C][C]0.0167375[/C][C]0.991631[/C][/ROW]
[ROW][C]48[/C][C]0.00657844[/C][C]0.0131569[/C][C]0.993422[/C][/ROW]
[ROW][C]49[/C][C]0.0104515[/C][C]0.0209031[/C][C]0.989548[/C][/ROW]
[ROW][C]50[/C][C]0.0172409[/C][C]0.0344818[/C][C]0.982759[/C][/ROW]
[ROW][C]51[/C][C]0.0136025[/C][C]0.027205[/C][C]0.986397[/C][/ROW]
[ROW][C]52[/C][C]0.0135876[/C][C]0.0271752[/C][C]0.986412[/C][/ROW]
[ROW][C]53[/C][C]0.0106112[/C][C]0.0212224[/C][C]0.989389[/C][/ROW]
[ROW][C]54[/C][C]0.0127021[/C][C]0.0254042[/C][C]0.987298[/C][/ROW]
[ROW][C]55[/C][C]0.0252677[/C][C]0.0505355[/C][C]0.974732[/C][/ROW]
[ROW][C]56[/C][C]0.021643[/C][C]0.043286[/C][C]0.978357[/C][/ROW]
[ROW][C]57[/C][C]0.0665294[/C][C]0.133059[/C][C]0.933471[/C][/ROW]
[ROW][C]58[/C][C]0.0622748[/C][C]0.12455[/C][C]0.937725[/C][/ROW]
[ROW][C]59[/C][C]0.0509506[/C][C]0.101901[/C][C]0.949049[/C][/ROW]
[ROW][C]60[/C][C]0.0481639[/C][C]0.0963279[/C][C]0.951836[/C][/ROW]
[ROW][C]61[/C][C]0.0675633[/C][C]0.135127[/C][C]0.932437[/C][/ROW]
[ROW][C]62[/C][C]0.0576818[/C][C]0.115364[/C][C]0.942318[/C][/ROW]
[ROW][C]63[/C][C]0.108955[/C][C]0.217909[/C][C]0.891045[/C][/ROW]
[ROW][C]64[/C][C]0.124249[/C][C]0.248498[/C][C]0.875751[/C][/ROW]
[ROW][C]65[/C][C]0.140446[/C][C]0.280892[/C][C]0.859554[/C][/ROW]
[ROW][C]66[/C][C]0.12463[/C][C]0.249261[/C][C]0.87537[/C][/ROW]
[ROW][C]67[/C][C]0.124484[/C][C]0.248967[/C][C]0.875516[/C][/ROW]
[ROW][C]68[/C][C]0.146774[/C][C]0.293548[/C][C]0.853226[/C][/ROW]
[ROW][C]69[/C][C]0.166038[/C][C]0.332077[/C][C]0.833962[/C][/ROW]
[ROW][C]70[/C][C]0.14568[/C][C]0.291359[/C][C]0.85432[/C][/ROW]
[ROW][C]71[/C][C]0.133356[/C][C]0.266712[/C][C]0.866644[/C][/ROW]
[ROW][C]72[/C][C]0.117734[/C][C]0.235468[/C][C]0.882266[/C][/ROW]
[ROW][C]73[/C][C]0.112586[/C][C]0.225173[/C][C]0.887414[/C][/ROW]
[ROW][C]74[/C][C]0.157745[/C][C]0.31549[/C][C]0.842255[/C][/ROW]
[ROW][C]75[/C][C]0.135195[/C][C]0.27039[/C][C]0.864805[/C][/ROW]
[ROW][C]76[/C][C]0.116899[/C][C]0.233798[/C][C]0.883101[/C][/ROW]
[ROW][C]77[/C][C]0.105735[/C][C]0.21147[/C][C]0.894265[/C][/ROW]
[ROW][C]78[/C][C]0.0992299[/C][C]0.19846[/C][C]0.90077[/C][/ROW]
[ROW][C]79[/C][C]0.0824834[/C][C]0.164967[/C][C]0.917517[/C][/ROW]
[ROW][C]80[/C][C]0.0948239[/C][C]0.189648[/C][C]0.905176[/C][/ROW]
[ROW][C]81[/C][C]0.0813062[/C][C]0.162612[/C][C]0.918694[/C][/ROW]
[ROW][C]82[/C][C]0.0926927[/C][C]0.185385[/C][C]0.907307[/C][/ROW]
[ROW][C]83[/C][C]0.0810257[/C][C]0.162051[/C][C]0.918974[/C][/ROW]
[ROW][C]84[/C][C]0.160601[/C][C]0.321202[/C][C]0.839399[/C][/ROW]
[ROW][C]85[/C][C]0.158629[/C][C]0.317258[/C][C]0.841371[/C][/ROW]
[ROW][C]86[/C][C]0.14166[/C][C]0.283321[/C][C]0.85834[/C][/ROW]
[ROW][C]87[/C][C]0.127575[/C][C]0.25515[/C][C]0.872425[/C][/ROW]
[ROW][C]88[/C][C]0.131452[/C][C]0.262904[/C][C]0.868548[/C][/ROW]
[ROW][C]89[/C][C]0.134354[/C][C]0.268708[/C][C]0.865646[/C][/ROW]
[ROW][C]90[/C][C]0.146581[/C][C]0.293162[/C][C]0.853419[/C][/ROW]
[ROW][C]91[/C][C]0.1478[/C][C]0.2956[/C][C]0.8522[/C][/ROW]
[ROW][C]92[/C][C]0.272466[/C][C]0.544931[/C][C]0.727534[/C][/ROW]
[ROW][C]93[/C][C]0.277115[/C][C]0.554229[/C][C]0.722885[/C][/ROW]
[ROW][C]94[/C][C]0.269789[/C][C]0.539577[/C][C]0.730211[/C][/ROW]
[ROW][C]95[/C][C]0.265403[/C][C]0.530805[/C][C]0.734597[/C][/ROW]
[ROW][C]96[/C][C]0.25008[/C][C]0.500159[/C][C]0.74992[/C][/ROW]
[ROW][C]97[/C][C]0.332237[/C][C]0.664475[/C][C]0.667763[/C][/ROW]
[ROW][C]98[/C][C]0.308546[/C][C]0.617092[/C][C]0.691454[/C][/ROW]
[ROW][C]99[/C][C]0.323948[/C][C]0.647895[/C][C]0.676052[/C][/ROW]
[ROW][C]100[/C][C]0.383283[/C][C]0.766566[/C][C]0.616717[/C][/ROW]
[ROW][C]101[/C][C]0.359622[/C][C]0.719243[/C][C]0.640378[/C][/ROW]
[ROW][C]102[/C][C]0.363974[/C][C]0.727947[/C][C]0.636026[/C][/ROW]
[ROW][C]103[/C][C]0.383761[/C][C]0.767523[/C][C]0.616239[/C][/ROW]
[ROW][C]104[/C][C]0.403537[/C][C]0.807075[/C][C]0.596463[/C][/ROW]
[ROW][C]105[/C][C]0.420299[/C][C]0.840599[/C][C]0.579701[/C][/ROW]
[ROW][C]106[/C][C]0.434135[/C][C]0.868269[/C][C]0.565865[/C][/ROW]
[ROW][C]107[/C][C]0.495411[/C][C]0.990822[/C][C]0.504589[/C][/ROW]
[ROW][C]108[/C][C]0.745092[/C][C]0.509816[/C][C]0.254908[/C][/ROW]
[ROW][C]109[/C][C]0.787164[/C][C]0.425673[/C][C]0.212836[/C][/ROW]
[ROW][C]110[/C][C]0.784973[/C][C]0.430055[/C][C]0.215027[/C][/ROW]
[ROW][C]111[/C][C]0.785421[/C][C]0.429158[/C][C]0.214579[/C][/ROW]
[ROW][C]112[/C][C]0.797393[/C][C]0.405214[/C][C]0.202607[/C][/ROW]
[ROW][C]113[/C][C]0.884646[/C][C]0.230707[/C][C]0.115354[/C][/ROW]
[ROW][C]114[/C][C]0.896613[/C][C]0.206775[/C][C]0.103387[/C][/ROW]
[ROW][C]115[/C][C]0.947226[/C][C]0.105547[/C][C]0.0527737[/C][/ROW]
[ROW][C]116[/C][C]0.969147[/C][C]0.0617054[/C][C]0.0308527[/C][/ROW]
[ROW][C]117[/C][C]0.97012[/C][C]0.0597594[/C][C]0.0298797[/C][/ROW]
[ROW][C]118[/C][C]0.973515[/C][C]0.0529692[/C][C]0.0264846[/C][/ROW]
[ROW][C]119[/C][C]0.97945[/C][C]0.0410998[/C][C]0.0205499[/C][/ROW]
[ROW][C]120[/C][C]0.984804[/C][C]0.030392[/C][C]0.015196[/C][/ROW]
[ROW][C]121[/C][C]0.987602[/C][C]0.0247964[/C][C]0.0123982[/C][/ROW]
[ROW][C]122[/C][C]0.99224[/C][C]0.0155193[/C][C]0.00775967[/C][/ROW]
[ROW][C]123[/C][C]0.995819[/C][C]0.00836147[/C][C]0.00418073[/C][/ROW]
[ROW][C]124[/C][C]0.99816[/C][C]0.00367996[/C][C]0.00183998[/C][/ROW]
[ROW][C]125[/C][C]0.998364[/C][C]0.0032712[/C][C]0.0016356[/C][/ROW]
[ROW][C]126[/C][C]0.998136[/C][C]0.00372876[/C][C]0.00186438[/C][/ROW]
[ROW][C]127[/C][C]0.998593[/C][C]0.00281409[/C][C]0.00140705[/C][/ROW]
[ROW][C]128[/C][C]0.998333[/C][C]0.00333489[/C][C]0.00166744[/C][/ROW]
[ROW][C]129[/C][C]0.999178[/C][C]0.00164426[/C][C]0.000822131[/C][/ROW]
[ROW][C]130[/C][C]0.999207[/C][C]0.00158699[/C][C]0.000793493[/C][/ROW]
[ROW][C]131[/C][C]0.99913[/C][C]0.0017403[/C][C]0.000870151[/C][/ROW]
[ROW][C]132[/C][C]0.998995[/C][C]0.00200921[/C][C]0.00100461[/C][/ROW]
[ROW][C]133[/C][C]0.998847[/C][C]0.00230646[/C][C]0.00115323[/C][/ROW]
[ROW][C]134[/C][C]0.999016[/C][C]0.00196825[/C][C]0.000984125[/C][/ROW]
[ROW][C]135[/C][C]0.998751[/C][C]0.00249808[/C][C]0.00124904[/C][/ROW]
[ROW][C]136[/C][C]0.99855[/C][C]0.00289935[/C][C]0.00144967[/C][/ROW]
[ROW][C]137[/C][C]0.999012[/C][C]0.00197536[/C][C]0.000987678[/C][/ROW]
[ROW][C]138[/C][C]0.998917[/C][C]0.00216613[/C][C]0.00108307[/C][/ROW]
[ROW][C]139[/C][C]0.999193[/C][C]0.00161454[/C][C]0.00080727[/C][/ROW]
[ROW][C]140[/C][C]0.998963[/C][C]0.00207374[/C][C]0.00103687[/C][/ROW]
[ROW][C]141[/C][C]0.998619[/C][C]0.00276153[/C][C]0.00138077[/C][/ROW]
[ROW][C]142[/C][C]0.999081[/C][C]0.00183872[/C][C]0.000919361[/C][/ROW]
[ROW][C]143[/C][C]0.99909[/C][C]0.00182005[/C][C]0.000910023[/C][/ROW]
[ROW][C]144[/C][C]0.999338[/C][C]0.00132374[/C][C]0.000661868[/C][/ROW]
[ROW][C]145[/C][C]0.999227[/C][C]0.00154555[/C][C]0.000772775[/C][/ROW]
[ROW][C]146[/C][C]0.999196[/C][C]0.00160725[/C][C]0.000803623[/C][/ROW]
[ROW][C]147[/C][C]0.998962[/C][C]0.00207525[/C][C]0.00103762[/C][/ROW]
[ROW][C]148[/C][C]0.998687[/C][C]0.00262638[/C][C]0.00131319[/C][/ROW]
[ROW][C]149[/C][C]0.998651[/C][C]0.00269737[/C][C]0.00134869[/C][/ROW]
[ROW][C]150[/C][C]0.998666[/C][C]0.00266894[/C][C]0.00133447[/C][/ROW]
[ROW][C]151[/C][C]0.999383[/C][C]0.0012334[/C][C]0.000616698[/C][/ROW]
[ROW][C]152[/C][C]0.999199[/C][C]0.00160224[/C][C]0.000801122[/C][/ROW]
[ROW][C]153[/C][C]0.999412[/C][C]0.00117536[/C][C]0.000587682[/C][/ROW]
[ROW][C]154[/C][C]0.999405[/C][C]0.00118956[/C][C]0.000594782[/C][/ROW]
[ROW][C]155[/C][C]0.9994[/C][C]0.00119978[/C][C]0.000599892[/C][/ROW]
[ROW][C]156[/C][C]0.99919[/C][C]0.00162036[/C][C]0.000810178[/C][/ROW]
[ROW][C]157[/C][C]0.999056[/C][C]0.00188801[/C][C]0.000944004[/C][/ROW]
[ROW][C]158[/C][C]0.99894[/C][C]0.00211987[/C][C]0.00105994[/C][/ROW]
[ROW][C]159[/C][C]0.998755[/C][C]0.00248904[/C][C]0.00124452[/C][/ROW]
[ROW][C]160[/C][C]0.998577[/C][C]0.00284541[/C][C]0.00142271[/C][/ROW]
[ROW][C]161[/C][C]0.998678[/C][C]0.0026438[/C][C]0.0013219[/C][/ROW]
[ROW][C]162[/C][C]0.998695[/C][C]0.00261035[/C][C]0.00130518[/C][/ROW]
[ROW][C]163[/C][C]0.99885[/C][C]0.00229917[/C][C]0.00114958[/C][/ROW]
[ROW][C]164[/C][C]0.999789[/C][C]0.000422024[/C][C]0.000211012[/C][/ROW]
[ROW][C]165[/C][C]0.999753[/C][C]0.000494025[/C][C]0.000247013[/C][/ROW]
[ROW][C]166[/C][C]0.999702[/C][C]0.000595626[/C][C]0.000297813[/C][/ROW]
[ROW][C]167[/C][C]0.999752[/C][C]0.00049633[/C][C]0.000248165[/C][/ROW]
[ROW][C]168[/C][C]0.999779[/C][C]0.000441964[/C][C]0.000220982[/C][/ROW]
[ROW][C]169[/C][C]0.9997[/C][C]0.000600816[/C][C]0.000300408[/C][/ROW]
[ROW][C]170[/C][C]0.999682[/C][C]0.000635404[/C][C]0.000317702[/C][/ROW]
[ROW][C]171[/C][C]0.999653[/C][C]0.000694415[/C][C]0.000347207[/C][/ROW]
[ROW][C]172[/C][C]0.999751[/C][C]0.000497995[/C][C]0.000248998[/C][/ROW]
[ROW][C]173[/C][C]0.999737[/C][C]0.000526888[/C][C]0.000263444[/C][/ROW]
[ROW][C]174[/C][C]0.999626[/C][C]0.00074792[/C][C]0.00037396[/C][/ROW]
[ROW][C]175[/C][C]0.999485[/C][C]0.00102982[/C][C]0.00051491[/C][/ROW]
[ROW][C]176[/C][C]0.999611[/C][C]0.000778009[/C][C]0.000389004[/C][/ROW]
[ROW][C]177[/C][C]0.999497[/C][C]0.00100602[/C][C]0.000503011[/C][/ROW]
[ROW][C]178[/C][C]0.999803[/C][C]0.000394051[/C][C]0.000197025[/C][/ROW]
[ROW][C]179[/C][C]0.999733[/C][C]0.00053471[/C][C]0.000267355[/C][/ROW]
[ROW][C]180[/C][C]0.999749[/C][C]0.000501783[/C][C]0.000250892[/C][/ROW]
[ROW][C]181[/C][C]0.999716[/C][C]0.000568607[/C][C]0.000284304[/C][/ROW]
[ROW][C]182[/C][C]0.999599[/C][C]0.000801976[/C][C]0.000400988[/C][/ROW]
[ROW][C]183[/C][C]0.999505[/C][C]0.000990361[/C][C]0.000495181[/C][/ROW]
[ROW][C]184[/C][C]0.999411[/C][C]0.00117709[/C][C]0.000588544[/C][/ROW]
[ROW][C]185[/C][C]0.999275[/C][C]0.00145038[/C][C]0.000725191[/C][/ROW]
[ROW][C]186[/C][C]0.999095[/C][C]0.00181075[/C][C]0.000905376[/C][/ROW]
[ROW][C]187[/C][C]0.999428[/C][C]0.00114338[/C][C]0.000571688[/C][/ROW]
[ROW][C]188[/C][C]0.999249[/C][C]0.00150276[/C][C]0.00075138[/C][/ROW]
[ROW][C]189[/C][C]0.998964[/C][C]0.00207176[/C][C]0.00103588[/C][/ROW]
[ROW][C]190[/C][C]0.998704[/C][C]0.00259223[/C][C]0.00129612[/C][/ROW]
[ROW][C]191[/C][C]0.998252[/C][C]0.0034964[/C][C]0.0017482[/C][/ROW]
[ROW][C]192[/C][C]0.997931[/C][C]0.00413751[/C][C]0.00206876[/C][/ROW]
[ROW][C]193[/C][C]0.9983[/C][C]0.00339981[/C][C]0.0016999[/C][/ROW]
[ROW][C]194[/C][C]0.999267[/C][C]0.00146694[/C][C]0.000733471[/C][/ROW]
[ROW][C]195[/C][C]0.999051[/C][C]0.00189897[/C][C]0.000949486[/C][/ROW]
[ROW][C]196[/C][C]0.99876[/C][C]0.00247901[/C][C]0.0012395[/C][/ROW]
[ROW][C]197[/C][C]0.998481[/C][C]0.00303758[/C][C]0.00151879[/C][/ROW]
[ROW][C]198[/C][C]0.998158[/C][C]0.00368301[/C][C]0.00184151[/C][/ROW]
[ROW][C]199[/C][C]0.99847[/C][C]0.00306028[/C][C]0.00153014[/C][/ROW]
[ROW][C]200[/C][C]0.998417[/C][C]0.00316694[/C][C]0.00158347[/C][/ROW]
[ROW][C]201[/C][C]0.997816[/C][C]0.00436855[/C][C]0.00218427[/C][/ROW]
[ROW][C]202[/C][C]0.997519[/C][C]0.0049612[/C][C]0.0024806[/C][/ROW]
[ROW][C]203[/C][C]0.996781[/C][C]0.0064387[/C][C]0.00321935[/C][/ROW]
[ROW][C]204[/C][C]0.99597[/C][C]0.00806058[/C][C]0.00403029[/C][/ROW]
[ROW][C]205[/C][C]0.994804[/C][C]0.010392[/C][C]0.005196[/C][/ROW]
[ROW][C]206[/C][C]0.993735[/C][C]0.0125301[/C][C]0.00626507[/C][/ROW]
[ROW][C]207[/C][C]0.991708[/C][C]0.0165837[/C][C]0.00829186[/C][/ROW]
[ROW][C]208[/C][C]0.989467[/C][C]0.021065[/C][C]0.0105325[/C][/ROW]
[ROW][C]209[/C][C]0.989414[/C][C]0.0211722[/C][C]0.0105861[/C][/ROW]
[ROW][C]210[/C][C]0.987006[/C][C]0.0259882[/C][C]0.0129941[/C][/ROW]
[ROW][C]211[/C][C]0.982598[/C][C]0.0348044[/C][C]0.0174022[/C][/ROW]
[ROW][C]212[/C][C]0.977463[/C][C]0.0450736[/C][C]0.0225368[/C][/ROW]
[ROW][C]213[/C][C]0.976826[/C][C]0.0463476[/C][C]0.0231738[/C][/ROW]
[ROW][C]214[/C][C]0.976786[/C][C]0.0464272[/C][C]0.0232136[/C][/ROW]
[ROW][C]215[/C][C]0.97494[/C][C]0.0501199[/C][C]0.02506[/C][/ROW]
[ROW][C]216[/C][C]0.966928[/C][C]0.0661448[/C][C]0.0330724[/C][/ROW]
[ROW][C]217[/C][C]0.963464[/C][C]0.0730716[/C][C]0.0365358[/C][/ROW]
[ROW][C]218[/C][C]0.956932[/C][C]0.0861354[/C][C]0.0430677[/C][/ROW]
[ROW][C]219[/C][C]0.944843[/C][C]0.110315[/C][C]0.0551575[/C][/ROW]
[ROW][C]220[/C][C]0.93197[/C][C]0.136061[/C][C]0.0680304[/C][/ROW]
[ROW][C]221[/C][C]0.942566[/C][C]0.114867[/C][C]0.0574336[/C][/ROW]
[ROW][C]222[/C][C]0.943219[/C][C]0.113562[/C][C]0.0567812[/C][/ROW]
[ROW][C]223[/C][C]0.928389[/C][C]0.143222[/C][C]0.0716112[/C][/ROW]
[ROW][C]224[/C][C]0.936644[/C][C]0.126711[/C][C]0.0633557[/C][/ROW]
[ROW][C]225[/C][C]0.925974[/C][C]0.148052[/C][C]0.0740261[/C][/ROW]
[ROW][C]226[/C][C]0.954987[/C][C]0.0900255[/C][C]0.0450127[/C][/ROW]
[ROW][C]227[/C][C]0.960156[/C][C]0.079688[/C][C]0.039844[/C][/ROW]
[ROW][C]228[/C][C]0.955388[/C][C]0.0892233[/C][C]0.0446116[/C][/ROW]
[ROW][C]229[/C][C]0.943092[/C][C]0.113817[/C][C]0.0569084[/C][/ROW]
[ROW][C]230[/C][C]0.953259[/C][C]0.0934818[/C][C]0.0467409[/C][/ROW]
[ROW][C]231[/C][C]0.969311[/C][C]0.061379[/C][C]0.0306895[/C][/ROW]
[ROW][C]232[/C][C]0.95864[/C][C]0.082721[/C][C]0.0413605[/C][/ROW]
[ROW][C]233[/C][C]0.94433[/C][C]0.11134[/C][C]0.0556698[/C][/ROW]
[ROW][C]234[/C][C]0.933509[/C][C]0.132983[/C][C]0.0664914[/C][/ROW]
[ROW][C]235[/C][C]0.914239[/C][C]0.171522[/C][C]0.0857611[/C][/ROW]
[ROW][C]236[/C][C]0.981174[/C][C]0.0376516[/C][C]0.0188258[/C][/ROW]
[ROW][C]237[/C][C]0.981999[/C][C]0.0360018[/C][C]0.0180009[/C][/ROW]
[ROW][C]238[/C][C]0.974464[/C][C]0.0510724[/C][C]0.0255362[/C][/ROW]
[ROW][C]239[/C][C]0.965296[/C][C]0.0694089[/C][C]0.0347045[/C][/ROW]
[ROW][C]240[/C][C]0.950251[/C][C]0.0994978[/C][C]0.0497489[/C][/ROW]
[ROW][C]241[/C][C]0.940539[/C][C]0.118923[/C][C]0.0594614[/C][/ROW]
[ROW][C]242[/C][C]0.91755[/C][C]0.164899[/C][C]0.0824497[/C][/ROW]
[ROW][C]243[/C][C]0.894022[/C][C]0.211955[/C][C]0.105978[/C][/ROW]
[ROW][C]244[/C][C]0.8669[/C][C]0.266201[/C][C]0.1331[/C][/ROW]
[ROW][C]245[/C][C]0.881041[/C][C]0.237918[/C][C]0.118959[/C][/ROW]
[ROW][C]246[/C][C]0.84474[/C][C]0.31052[/C][C]0.15526[/C][/ROW]
[ROW][C]247[/C][C]0.81806[/C][C]0.363881[/C][C]0.18194[/C][/ROW]
[ROW][C]248[/C][C]0.75722[/C][C]0.485559[/C][C]0.24278[/C][/ROW]
[ROW][C]249[/C][C]0.68708[/C][C]0.625839[/C][C]0.31292[/C][/ROW]
[ROW][C]250[/C][C]0.606421[/C][C]0.787158[/C][C]0.393579[/C][/ROW]
[ROW][C]251[/C][C]0.514931[/C][C]0.970139[/C][C]0.485069[/C][/ROW]
[ROW][C]252[/C][C]0.430182[/C][C]0.860365[/C][C]0.569818[/C][/ROW]
[ROW][C]253[/C][C]0.334914[/C][C]0.669829[/C][C]0.665086[/C][/ROW]
[ROW][C]254[/C][C]0.492441[/C][C]0.984882[/C][C]0.507559[/C][/ROW]
[ROW][C]255[/C][C]0.451581[/C][C]0.903162[/C][C]0.548419[/C][/ROW]
[ROW][C]256[/C][C]0.354098[/C][C]0.708197[/C][C]0.645902[/C][/ROW]
[ROW][C]257[/C][C]0.327149[/C][C]0.654298[/C][C]0.672851[/C][/ROW]
[ROW][C]258[/C][C]0.902253[/C][C]0.195495[/C][C]0.0977473[/C][/ROW]
[ROW][C]259[/C][C]0.766698[/C][C]0.466604[/C][C]0.233302[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
19	0.223318	0.446636	0.776682
20	0.16158	0.32316	0.83842
21	0.0832518	0.166504	0.916748
22	0.0849814	0.169963	0.915019
23	0.0614909	0.122982	0.938509
24	0.0442422	0.0884843	0.955758
25	0.023271	0.046542	0.976729
26	0.0154636	0.0309272	0.984536
27	0.00778469	0.0155694	0.992215
28	0.00363754	0.00727508	0.996362
29	0.00343874	0.00687749	0.996561
30	0.00204321	0.00408642	0.997957
31	0.00333676	0.00667353	0.996663
32	0.0019437	0.0038874	0.998056
33	0.00432939	0.00865878	0.995671
34	0.0205692	0.0411384	0.979431
35	0.0150773	0.0301545	0.984923
36	0.0103166	0.0206333	0.989683
37	0.0148804	0.0297609	0.98512
38	0.0202009	0.0404018	0.979799
39	0.02327	0.04654	0.97673
40	0.0158709	0.0317417	0.984129
41	0.0233143	0.0466286	0.976686
42	0.0191129	0.0382258	0.980887
43	0.0148319	0.0296639	0.985168
44	0.0167291	0.0334582	0.983271
45	0.0119725	0.023945	0.988028
46	0.0102054	0.0204109	0.989795
47	0.00836876	0.0167375	0.991631
48	0.00657844	0.0131569	0.993422
49	0.0104515	0.0209031	0.989548
50	0.0172409	0.0344818	0.982759
51	0.0136025	0.027205	0.986397
52	0.0135876	0.0271752	0.986412
53	0.0106112	0.0212224	0.989389
54	0.0127021	0.0254042	0.987298
55	0.0252677	0.0505355	0.974732
56	0.021643	0.043286	0.978357
57	0.0665294	0.133059	0.933471
58	0.0622748	0.12455	0.937725
59	0.0509506	0.101901	0.949049
60	0.0481639	0.0963279	0.951836
61	0.0675633	0.135127	0.932437
62	0.0576818	0.115364	0.942318
63	0.108955	0.217909	0.891045
64	0.124249	0.248498	0.875751
65	0.140446	0.280892	0.859554
66	0.12463	0.249261	0.87537
67	0.124484	0.248967	0.875516
68	0.146774	0.293548	0.853226
69	0.166038	0.332077	0.833962
70	0.14568	0.291359	0.85432
71	0.133356	0.266712	0.866644
72	0.117734	0.235468	0.882266
73	0.112586	0.225173	0.887414
74	0.157745	0.31549	0.842255
75	0.135195	0.27039	0.864805
76	0.116899	0.233798	0.883101
77	0.105735	0.21147	0.894265
78	0.0992299	0.19846	0.90077
79	0.0824834	0.164967	0.917517
80	0.0948239	0.189648	0.905176
81	0.0813062	0.162612	0.918694
82	0.0926927	0.185385	0.907307
83	0.0810257	0.162051	0.918974
84	0.160601	0.321202	0.839399
85	0.158629	0.317258	0.841371
86	0.14166	0.283321	0.85834
87	0.127575	0.25515	0.872425
88	0.131452	0.262904	0.868548
89	0.134354	0.268708	0.865646
90	0.146581	0.293162	0.853419
91	0.1478	0.2956	0.8522
92	0.272466	0.544931	0.727534
93	0.277115	0.554229	0.722885
94	0.269789	0.539577	0.730211
95	0.265403	0.530805	0.734597
96	0.25008	0.500159	0.74992
97	0.332237	0.664475	0.667763
98	0.308546	0.617092	0.691454
99	0.323948	0.647895	0.676052
100	0.383283	0.766566	0.616717
101	0.359622	0.719243	0.640378
102	0.363974	0.727947	0.636026
103	0.383761	0.767523	0.616239
104	0.403537	0.807075	0.596463
105	0.420299	0.840599	0.579701
106	0.434135	0.868269	0.565865
107	0.495411	0.990822	0.504589
108	0.745092	0.509816	0.254908
109	0.787164	0.425673	0.212836
110	0.784973	0.430055	0.215027
111	0.785421	0.429158	0.214579
112	0.797393	0.405214	0.202607
113	0.884646	0.230707	0.115354
114	0.896613	0.206775	0.103387
115	0.947226	0.105547	0.0527737
116	0.969147	0.0617054	0.0308527
117	0.97012	0.0597594	0.0298797
118	0.973515	0.0529692	0.0264846
119	0.97945	0.0410998	0.0205499
120	0.984804	0.030392	0.015196
121	0.987602	0.0247964	0.0123982
122	0.99224	0.0155193	0.00775967
123	0.995819	0.00836147	0.00418073
124	0.99816	0.00367996	0.00183998
125	0.998364	0.0032712	0.0016356
126	0.998136	0.00372876	0.00186438
127	0.998593	0.00281409	0.00140705
128	0.998333	0.00333489	0.00166744
129	0.999178	0.00164426	0.000822131
130	0.999207	0.00158699	0.000793493
131	0.99913	0.0017403	0.000870151
132	0.998995	0.00200921	0.00100461
133	0.998847	0.00230646	0.00115323
134	0.999016	0.00196825	0.000984125
135	0.998751	0.00249808	0.00124904
136	0.99855	0.00289935	0.00144967
137	0.999012	0.00197536	0.000987678
138	0.998917	0.00216613	0.00108307
139	0.999193	0.00161454	0.00080727
140	0.998963	0.00207374	0.00103687
141	0.998619	0.00276153	0.00138077
142	0.999081	0.00183872	0.000919361
143	0.99909	0.00182005	0.000910023
144	0.999338	0.00132374	0.000661868
145	0.999227	0.00154555	0.000772775
146	0.999196	0.00160725	0.000803623
147	0.998962	0.00207525	0.00103762
148	0.998687	0.00262638	0.00131319
149	0.998651	0.00269737	0.00134869
150	0.998666	0.00266894	0.00133447
151	0.999383	0.0012334	0.000616698
152	0.999199	0.00160224	0.000801122
153	0.999412	0.00117536	0.000587682
154	0.999405	0.00118956	0.000594782
155	0.9994	0.00119978	0.000599892
156	0.99919	0.00162036	0.000810178
157	0.999056	0.00188801	0.000944004
158	0.99894	0.00211987	0.00105994
159	0.998755	0.00248904	0.00124452
160	0.998577	0.00284541	0.00142271
161	0.998678	0.0026438	0.0013219
162	0.998695	0.00261035	0.00130518
163	0.99885	0.00229917	0.00114958
164	0.999789	0.000422024	0.000211012
165	0.999753	0.000494025	0.000247013
166	0.999702	0.000595626	0.000297813
167	0.999752	0.00049633	0.000248165
168	0.999779	0.000441964	0.000220982
169	0.9997	0.000600816	0.000300408
170	0.999682	0.000635404	0.000317702
171	0.999653	0.000694415	0.000347207
172	0.999751	0.000497995	0.000248998
173	0.999737	0.000526888	0.000263444
174	0.999626	0.00074792	0.00037396
175	0.999485	0.00102982	0.00051491
176	0.999611	0.000778009	0.000389004
177	0.999497	0.00100602	0.000503011
178	0.999803	0.000394051	0.000197025
179	0.999733	0.00053471	0.000267355
180	0.999749	0.000501783	0.000250892
181	0.999716	0.000568607	0.000284304
182	0.999599	0.000801976	0.000400988
183	0.999505	0.000990361	0.000495181
184	0.999411	0.00117709	0.000588544
185	0.999275	0.00145038	0.000725191
186	0.999095	0.00181075	0.000905376
187	0.999428	0.00114338	0.000571688
188	0.999249	0.00150276	0.00075138
189	0.998964	0.00207176	0.00103588
190	0.998704	0.00259223	0.00129612
191	0.998252	0.0034964	0.0017482
192	0.997931	0.00413751	0.00206876
193	0.9983	0.00339981	0.0016999
194	0.999267	0.00146694	0.000733471
195	0.999051	0.00189897	0.000949486
196	0.99876	0.00247901	0.0012395
197	0.998481	0.00303758	0.00151879
198	0.998158	0.00368301	0.00184151
199	0.99847	0.00306028	0.00153014
200	0.998417	0.00316694	0.00158347
201	0.997816	0.00436855	0.00218427
202	0.997519	0.0049612	0.0024806
203	0.996781	0.0064387	0.00321935
204	0.99597	0.00806058	0.00403029
205	0.994804	0.010392	0.005196
206	0.993735	0.0125301	0.00626507
207	0.991708	0.0165837	0.00829186
208	0.989467	0.021065	0.0105325
209	0.989414	0.0211722	0.0105861
210	0.987006	0.0259882	0.0129941
211	0.982598	0.0348044	0.0174022
212	0.977463	0.0450736	0.0225368
213	0.976826	0.0463476	0.0231738
214	0.976786	0.0464272	0.0232136
215	0.97494	0.0501199	0.02506
216	0.966928	0.0661448	0.0330724
217	0.963464	0.0730716	0.0365358
218	0.956932	0.0861354	0.0430677
219	0.944843	0.110315	0.0551575
220	0.93197	0.136061	0.0680304
221	0.942566	0.114867	0.0574336
222	0.943219	0.113562	0.0567812
223	0.928389	0.143222	0.0716112
224	0.936644	0.126711	0.0633557
225	0.925974	0.148052	0.0740261
226	0.954987	0.0900255	0.0450127
227	0.960156	0.079688	0.039844
228	0.955388	0.0892233	0.0446116
229	0.943092	0.113817	0.0569084
230	0.953259	0.0934818	0.0467409
231	0.969311	0.061379	0.0306895
232	0.95864	0.082721	0.0413605
233	0.94433	0.11134	0.0556698
234	0.933509	0.132983	0.0664914
235	0.914239	0.171522	0.0857611
236	0.981174	0.0376516	0.0188258
237	0.981999	0.0360018	0.0180009
238	0.974464	0.0510724	0.0255362
239	0.965296	0.0694089	0.0347045
240	0.950251	0.0994978	0.0497489
241	0.940539	0.118923	0.0594614
242	0.91755	0.164899	0.0824497
243	0.894022	0.211955	0.105978
244	0.8669	0.266201	0.1331
245	0.881041	0.237918	0.118959
246	0.84474	0.31052	0.15526
247	0.81806	0.363881	0.18194
248	0.75722	0.485559	0.24278
249	0.68708	0.625839	0.31292
250	0.606421	0.787158	0.393579
251	0.514931	0.970139	0.485069
252	0.430182	0.860365	0.569818
253	0.334914	0.669829	0.665086
254	0.492441	0.984882	0.507559
255	0.451581	0.903162	0.548419
256	0.354098	0.708197	0.645902
257	0.327149	0.654298	0.672851
258	0.902253	0.195495	0.0977473
259	0.766698	0.466604	0.233302

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	88	0.365145	NOK
5% type I error level	129	0.53527	NOK
10% type I error level	148	0.614108	NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 88 & 0.365145 & NOK \tabularnewline
5% type I error level & 129 & 0.53527 & NOK \tabularnewline
10% type I error level & 148 & 0.614108 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265055&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]88[/C][C]0.365145[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]129[/C][C]0.53527[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]148[/C][C]0.614108[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265055&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265055&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	88	0.365145	NOK
5% type I error level	129	0.53527	NOK
10% type I error level	148	0.614108	NOK

Figure 1

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

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Parameters (Session):

par1 = 13 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 13 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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

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

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code