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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 12:30:35 +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/t1418215183sc4rlrisclt7ikc.htm/, Retrieved Fri, 17 May 2024 11:29:09 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265038, Retrieved Fri, 17 May 2024 11:29:09 +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 12:30:35] [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
19 18 20 23 20 19 0.89 0.50 0.83 0.33 0.50 1.00 12.2 139 4
16 12 9 22 14 18 0.89 0.40 1.00 0.67 0.00 1.00 12.8 148 5
24 24 19 22 25 24 0.89 0.50 0.83 0.00 0.00 0.00 7.4 158 4
15 16 12 19 15 20 0.89 0.70 0.67 0.00 1.00 1.00 6.7 128 4
17 19 16 25 20 20 0.78 0.30 0.00 0.00 0.50 0.50 12.6 224 9
19 16 17 28 21 24 0.89 0.40 0.83 0.67 0.50 0.00 14.8 159 8
19 15 9 16 15 21 1.00 0.40 0.50 0.67 1.00 1.00 13.3 105 11
28 28 28 28 28 28 0.89 0.70 0.83 0.00 0.50 0.00 11.1 159 4
26 21 20 21 11 10 0.78 0.60 0.33 0.67 0.50 0.50 8.2 167 4
15 18 16 22 22 22 1.00 0.60 0.50 1.00 0.00 0.50 11.4 165 6
26 22 22 24 22 19 0.78 0.20 0.67 0.00 0.50 0.50 6.4 159 4
16 19 17 24 27 27 0.89 0.40 1.00 0.00 0.50 0.50 10.6 119 8
24 22 12 26 24 23 0.89 0.40 0.50 0.67 0.00 1.00 12.0 176 4
25 25 18 28 23 24 0.89 0.50 0.67 0.33 0.00 0.00 6.3 54 4
22 20 20 24 24 24 0.89 0.30 0.17 0.67 0.00 0.50 11.3 91 11
15 16 12 20 21 25 0.89 0.40 0.83 0.33 0.50 0.50 11.9 163 4
21 19 16 26 20 24 0.67 0.70 0.67 0.33 0.50 1.00 9.3 124 4
22 18 16 21 19 21 1.00 0.50 0.67 0.33 0.00 1.00 9.6 137 6
27 26 21 28 25 28 0.78 0.20 0.67 0.00 0.00 1.00 10.0 121 6
26 24 15 27 16 28 0.78 0.30 0.50 0.67 0.00 0.50 6.4 153 4
26 20 17 23 24 22 0.89 0.60 1.00 0.33 0.00 1.00 13.8 148 8
22 19 17 24 21 26 0.78 0.60 0.83 0.33 0.00 1.00 10.8 221 5
21 19 17 24 22 26 0.89 0.20 0.83 0.33 0.00 1.00 13.8 188 4
22 23 18 22 25 21 0.89 0.70 1.00 0.67 1.00 0.00 11.7 149 9
20 18 15 21 23 26 0.33 0.20 0.67 0.00 0.00 0.00 10.9 244 4
21 16 20 25 20 23 1.00 1.00 1.00 0.33 1.00 1.00 16.1 148 7
20 18 13 20 21 20 0.89 0.40 0.83 0.67 0.00 0.50 13.4 92 10
22 21 21 21 22 24 0.89 0.40 1.00 1.00 0.00 1.00 9.9 150 4
21 20 12 26 25 25 0.67 0.20 0.83 0.67 0.00 0.50 11.5 153 4
8 15 6 23 23 24 0.56 0.40 0.67 0.33 0.00 1.00 8.3 94 7
22 19 13 21 19 20 0.89 0.40 0.67 0.00 0.50 1.00 11.7 156 12
20 19 19 27 21 24 0.89 0.70 1.00 0.67 0.50 0.50 9.0 132 7
24 7 12 25 19 25 1.00 0.20 0.67 0.67 0.00 0.50 9.7 161 5
17 20 14 23 25 23 0.78 0.60 1.00 1.00 0.00 0.50 10.8 105 8
20 20 13 25 16 21 0.78 0.30 1.00 1.00 0.50 0.50 10.3 97 5
23 19 12 23 24 23 0.33 0.30 0.50 0.33 0.00 0.00 10.4 151 4
20 19 17 19 24 21 0.78 0.20 0.67 0.00 0.50 0.00 12.7 131 9
22 20 19 22 18 18 0.89 0.50 0.83 0.67 0.50 0.50 9.3 166 7
19 18 10 24 28 24 0.89 0.70 1.00 0.67 0.50 1.00 11.8 157 4
15 14 10 19 15 18 0.78 0.60 1.00 0.67 0.50 0.50 5.9 111 4
20 17 11 21 17 21 0.89 0.40 1.00 0.67 0.50 1.00 11.4 145 4
22 17 11 27 18 23 0.89 0.60 1.00 0.33 0.50 1.00 13.0 162 4
17 8 10 25 26 25 1.00 0.40 1.00 1.00 0.00 1.00 10.8 163 4
14 9 7 25 18 22 0.67 0.30 0.83 0.67 0.00 1.00 12.3 59 7
24 22 22 23 22 22 1.00 0.50 0.83 0.67 0.50 0.50 11.3 187 4
17 20 12 17 19 23 0.89 0.20 0.50 0.00 0.00 1.00 11.8 109 7
23 20 18 28 17 24 0.89 0.30 0.83 0.00 0.50 1.00 7.9 90 4
25 22 20 25 26 25 0.89 0.50 0.17 0.00 0.00 1.00 12.7 105 4
16 22 9 20 21 22 0.78 0.70 0.83 1.00 0.50 1.00 12.3 83 4
18 22 16 25 26 24 0.89 0.40 1.00 0.67 1.00 0.50 11.6 116 4
20 16 14 21 21 21 0.78 0.30 1.00 0.00 0.00 0.50 6.7 42 8
18 14 11 24 12 24 0.78 0.20 0.67 0.67 1.00 1.00 10.9 148 4
23 24 20 28 20 25 1.00 0.50 1.00 0.00 0.00 0.50 12.1 155 4
24 21 17 20 20 23 0.78 0.40 1.00 0.00 0.50 0.00 13.3 125 4
23 20 14 19 24 27 1.00 0.60 1.00 0.67 1.00 1.00 10.1 116 4
13 20 8 24 24 27 0.78 0.40 0.83 1.00 0.00 1.00 5.7 128 7
20 18 16 21 22 23 0.67 0.40 0.33 0.00 0.00 0.50 14.3 138 12
20 14 11 24 21 18 0.33 0.20 0.33 0.33 0.00 0.00 8.0 49 4
19 19 10 23 20 20 1.00 0.90 1.00 0.67 0.50 1.00 13.3 96 4
22 24 15 18 23 23 1.00 0.80 1.00 0.67 1.00 0.50 9.3 164 4
22 19 15 27 19 24 0.78 0.80 0.83 0.00 0.50 1.00 12.5 162 5
15 16 10 25 24 26 0.67 0.30 1.00 1.00 0.50 1.00 7.6 99 15
17 16 10 20 21 20 1.00 0.20 0.83 0.67 0.00 0.50 15.9 202 5
19 16 18 21 16 23 0.89 0.40 0.67 0.00 0.50 1.00 9.2 186 10
20 14 10 23 17 22 0.89 0.20 0.83 1.00 0.00 1.00 9.1 66 9
22 22 22 27 23 23 0.78 0.20 0.67 0.67 0.50 1.00 11.1 183 8
21 21 16 24 20 17 1.00 0.10 0.83 0.67 0.00 1.00 13.0 214 4
21 15 10 27 19 20 0.56 0.40 0.67 1.00 0.50 0.00 14.5 188 5
16 14 7 24 18 22 0.67 0.50 1.00 0.00 0.50 0.50 12.2 104 4
20 15 16 23 18 18 0.89 0.80 0.83 0.33 0.50 1.00 12.3 177 9
21 14 16 24 21 19 0.89 0.40 0.67 0.67 0.00 0.50 11.4 126 4
20 20 16 21 20 19 0.89 0.60 0.83 0.33 0.50 0.50 8.8 76 10
23 21 22 23 17 16 0.89 0.50 0.83 0.67 0.50 1.00 14.6 99 4
18 14 5 27 25 26 0.78 0.30 0.67 0.00 0.00 0.00 12.6 139 4
22 19 18 24 15 14 0.89 0.80 1.00 1.00 0.50 1.00 NA 78 6
16 16 10 25 17 25 1.00 0.40 0.33 0.00 0.50 0.00 13.0 162 7
17 13 8 19 17 23 1.00 0.60 0.83 0.67 0.50 0.50 12.6 108 5
24 26 16 24 24 18 0.89 0.40 1.00 0.33 0.00 0.50 13.2 159 4
13 13 8 25 21 22 0.44 0.30 0.83 0.00 0.00 0.00 9.9 74 4
19 18 16 23 22 26 0.78 0.80 0.83 0.00 1.00 1.00 7.7 110 4
20 15 14 23 18 25 0.89 0.60 0.50 0.33 1.00 1.00 10.5 96 4
22 18 15 25 22 26 0.67 0.30 0.50 0.00 0.00 0.00 13.4 116 4
19 21 9 26 20 26 0.78 0.50 0.83 0.67 0.50 1.00 10.9 87 4
21 17 21 26 21 24 0.78 0.40 1.00 0.33 0.00 1.00 4.3 97 6
15 18 7 16 21 22 0.33 0.30 0.33 0.67 0.00 0.00 10.3 127 10
21 20 17 23 20 21 0.89 0.70 1.00 0.33 0.00 0.50 11.8 106 7
24 18 18 26 18 22 0.89 0.20 0.67 0.33 0.50 0.50 11.2 80 4
22 25 16 25 25 28 0.89 0.40 0.83 1.00 0.00 1.00 11.4 74 4
20 20 16 23 23 22 0.89 0.60 1.00 0.67 0.50 0.50 8.6 91 7
21 19 14 26 21 26 0.56 0.60 0.83 0.00 0.00 1.00 13.2 133 4
19 18 15 22 20 20 0.67 0.60 0.83 0.67 0.50 0.50 12.6 74 8
14 12 8 20 21 24 0.67 0.40 1.00 0.33 0.50 1.00 5.6 114 11
25 22 22 27 20 21 0.78 0.60 0.83 0.00 0.00 1.00 9.9 140 6
11 16 5 20 22 23 0.78 0.50 1.00 0.33 0.50 1.00 8.8 95 14
17 18 13 22 15 23 0.78 0.50 0.83 0.00 0.00 1.00 7.7 98 5
22 23 22 24 24 23 0.89 0.60 0.67 0.00 0.00 1.00 9.0 121 4
20 20 18 21 22 22 1.00 0.80 0.83 0.33 0.50 1.00 7.3 126 8
22 20 15 24 21 23 0.89 0.50 0.83 0.67 1.00 0.50 11.4 98 9
15 16 11 26 17 21 0.89 0.60 0.83 0.67 0.50 1.00 13.6 95 4
23 22 19 24 23 27 0.78 0.40 0.83 0.67 0.50 1.00 7.9 110 4
20 19 19 24 22 23 1.00 0.30 0.67 0.67 0.50 1.00 10.7 70 5
22 23 21 27 23 26 0.78 0.30 0.83 1.00 0.00 0.50 10.3 102 4
16 6 4 25 16 27 0.67 0.20 0.00 0.00 0.00 0.00 8.3 86 5
25 19 17 27 18 27 0.78 0.40 0.83 0.00 0.00 0.50 9.6 130 4
18 24 10 19 25 23 0.89 0.50 1.00 0.00 0.00 0.50 14.2 96 4
19 19 13 22 18 23 0.67 0.30 0.17 0.00 0.50 0.00 8.5 102 7
25 15 15 22 14 23 0.22 0.40 0.17 0.00 0.50 0.00 13.5 100 10
21 18 11 25 20 28 0.44 0.50 0.50 1.00 0.00 0.00 4.9 94 4
22 18 20 23 19 24 0.89 0.30 0.50 0.67 0.00 1.00 6.4 52 5
21 22 13 24 18 20 0.67 0.50 1.00 0.00 0.00 0.50 9.6 98 4
22 23 18 24 22 23 0.89 0.40 0.67 0.67 0.00 0.50 11.6 118 4
23 18 20 23 21 22 0.67 0.40 0.83 0.67 0.00 1.00 11.1 99 4
20 17 15 22 14 15 0.78 0.60 1.00 0.00 1.00 1.00 4.35 48 6
6 6 4 24 5 27 0.78 0.30 1.00 0.67 1.00 1.00 12.7 50 4
15 22 9 19 25 23 0.78 0.40 1.00 0.33 1.00 0.50 18.1 150 8
18 20 18 25 21 23 1.00 0.30 1.00 1.00 1.00 1.00 17.85 154 5
24 16 12 26 11 20 0.78 1.00 1.00 1.00 1.00 1.00 16.6 109 4
22 16 17 18 20 18 0.67 0.40 1.00 0.00 0.00 0.50 12.6 68 17
21 17 12 24 9 22 0.89 0.80 0.83 1.00 0.50 1.00 17.1 194 4
23 20 16 28 15 20 0.89 0.30 1.00 0.67 1.00 1.00 19.1 158 4
20 23 17 23 23 21 1.00 0.50 0.83 0.67 0.00 1.00 16.1 159 8
20 18 14 19 21 25 0.78 0.40 1.00 0.00 0.00 0.50 13.35 67 4
18 13 13 19 9 19 0.67 0.30 0.83 0.67 0.00 1.00 18.4 147 7
25 22 20 27 24 25 0.89 0.50 0.83 1.00 0.00 1.00 14.7 39 4
16 20 16 24 16 24 0.67 0.30 1.00 0.67 0.00 1.00 10.6 100 4
20 20 15 26 20 22 0.67 0.30 0.67 0.00 0.00 1.00 12.6 111 5
14 13 10 21 15 28 1.00 0.40 0.83 0.00 0.00 1.00 16.2 138 7
22 16 16 25 18 22 0.67 0.30 1.00 0.00 0.00 0.50 13.6 101 4
26 25 21 28 22 21 1.00 0.60 1.00 0.33 0.50 0.50 18.9 131 4
20 16 15 19 21 23 0.89 0.60 0.83 0.67 1.00 1.00 14.1 101 7
17 15 16 20 21 19 0.89 0.40 1.00 1.00 1.00 1.00 14.5 114 11
22 19 19 26 21 21 1.00 0.40 1.00 0.00 0.00 0.00 16.15 165 7
22 19 9 27 20 25 0.67 0.40 1.00 0.67 0.00 0.50 14.75 114 4
20 24 19 23 24 23 0.44 0.30 0.67 0.67 0.50 1.00 14.8 111 4
17 9 7 18 15 28 0.89 0.20 1.00 0.33 1.00 0.00 12.45 75 4
22 22 23 23 24 14 0.56 0.50 0.83 0.67 0.00 1.00 12.65 82 4
17 15 14 21 18 23 0.78 0.40 1.00 0.67 1.00 1.00 17.35 121 4
22 22 10 23 24 24 1.00 0.40 1.00 0.67 0.00 0.00 8.6 32 4
21 22 16 22 24 25 1.00 0.40 0.83 0.67 0.00 1.00 18.4 150 6
25 24 12 21 15 15 0.89 0.30 0.67 0.67 0.50 0.50 16.1 117 8
11 12 10 14 19 23 0.67 0.40 0.83 0.67 1.00 0.50 11.6 71 23
19 21 7 24 20 26 0.89 0.20 1.00 0.33 0.50 1.00 17.75 165 4
24 25 20 26 26 21 0.33 0.00 0.00 0.00 0.00 0.00 15.25 154 8
17 26 9 24 26 26 0.89 0.40 1.00 0.67 0.50 1.00 17.65 126 6
22 21 12 22 23 23 0.78 0.60 1.00 0.00 1.00 1.00 16.35 149 4
17 14 10 20 13 15 1.00 0.40 0.67 0.67 0.00 0.50 17.65 145 7
26 28 19 20 16 16 0.44 0.40 1.00 0.00 0.00 0.50 13.6 120 4
20 21 11 18 22 20 0.67 0.40 0.83 0.00 0.50 0.00 14.35 109 4
19 16 15 18 21 20 0.33 0.20 0.17 0.00 0.50 0.00 14.75 132 4
21 16 14 25 11 21 0.89 0.40 0.83 1.00 1.00 1.00 18.25 172 10
24 25 11 28 23 28 0.89 0.30 0.83 0.00 0.00 0.50 9.9 169 6
21 21 14 23 18 19 1.00 0.60 0.83 0.67 1.00 0.00 16 114 5
19 22 15 20 19 21 0.89 0.60 0.83 1.00 0.00 1.00 18.25 156 5
13 9 7 22 15 22 0.89 0.40 0.83 0.00 0.00 1.00 16.85 172 4
24 20 22 27 8 27 1.00 0.50 1.00 0.67 1.00 0.50 14.6 68 4
28 19 19 24 15 20 0.89 0.40 0.83 0.00 0.50 1.00 13.85 89 5
27 24 22 23 21 17 1.00 0.60 1.00 1.00 1.00 1.00 18.95 167 5
22 22 11 20 25 26 0.78 0.60 0.83 0.67 0.50 1.00 15.6 113 5
23 22 19 22 14 21 0.78 0.90 1.00 0.67 0.50 1.00 14.85 115 5
19 12 9 21 21 24 0.67 0.40 0.83 0.67 0.50 0.00 11.75 78 4
18 17 11 24 18 21 0.89 0.80 1.00 1.00 0.50 1.00 18.45 118 6
23 18 17 26 18 25 0.67 0.50 0.83 1.00 0.00 1.00 15.9 87 4
21 10 12 24 12 22 0.78 0.40 0.83 1.00 0.00 0.00 17.1 173 4
22 22 17 18 24 17 0.89 0.40 1.00 0.67 1.00 0.50 16.1 2 4
17 24 10 17 17 14 0.89 0.70 1.00 1.00 1.00 0.50 19.9 162 9
15 18 17 23 20 23 0.78 0.40 1.00 0.33 1.00 1.00 10.95 49 18
21 18 13 21 24 28 1.00 0.80 1.00 0.67 0.50 1.00 18.45 122 6
20 23 11 21 22 24 1.00 0.40 1.00 1.00 1.00 0.50 15.1 96 5
26 21 19 24 15 22 1.00 0.30 1.00 0.67 0.00 0.50 15 100 4
19 21 21 22 22 24 0.67 0.50 1.00 0.67 0.50 1.00 11.35 82 11
28 28 24 24 26 25 0.89 0.80 1.00 0.67 1.00 1.00 15.95 100 4
21 17 13 24 17 21 1.00 0.40 0.83 0.33 0.00 0.50 18.1 115 10
19 21 16 24 23 22 1.00 1.00 1.00 1.00 0.50 0.00 14.6 141 6
22 21 13 23 19 16 0.89 0.50 1.00 0.67 1.00 1.00 15.4 165 8
21 20 15 21 21 18 0.89 0.50 1.00 0.67 1.00 1.00 15.4 165 8
20 18 15 24 23 27 0.89 0.30 1.00 0.33 0.00 1.00 17.6 110 6
19 17 11 19 19 17 0.89 0.30 0.83 0.33 0.50 1.00 13.35 118 8
11 7 7 19 18 25 0.89 0.30 0.50 0.00 0.00 1.00 19.1 158 4
17 17 13 23 16 24 1.00 0.40 0.67 0.33 0.50 0.50 15.35 146 4
19 14 13 25 23 21 0.67 0.50 1.00 0.33 0.00 1.00 7.6 49 9
20 18 12 24 13 21 1.00 0.50 0.67 0.67 0.50 1.00 13.4 90 9
17 14 8 21 18 19 0.89 0.40 1.00 0.00 0.00 0.00 13.9 121 5
21 23 7 18 23 27 0.89 0.70 1.00 1.00 0.50 0.00 19.1 155 4
21 20 17 23 21 28 0.89 0.50 0.50 0.33 0.00 0.50 15.25 104 4
12 14 9 20 23 19 0.89 0.40 0.67 0.33 1.00 0.00 12.9 147 15
23 17 18 23 16 23 1.00 0.70 0.67 1.00 0.00 1.00 16.1 110 10
22 21 17 23 17 25 1.00 0.70 0.67 1.00 0.00 1.00 17.35 108 9
22 23 17 23 20 26 1.00 0.70 0.67 1.00 0.00 1.00 13.15 113 7
21 24 18 23 18 25 0.89 0.70 0.67 1.00 0.00 1.00 12.15 115 9
20 21 12 27 20 25 0.89 0.70 0.67 0.00 0.00 0.00 12.6 61 6
18 14 14 19 19 24 0.89 0.70 1.00 0.67 0.50 1.00 10.35 60 4
21 24 22 25 26 24 0.33 0.10 0.67 0.33 0.50 0.00 15.4 109 7
24 16 19 25 9 24 0.67 0.20 0.67 0.67 0.50 1.00 9.6 68 4
22 21 21 21 23 22 0.56 0.30 0.33 0.33 0.00 1.00 18.2 111 7
20 8 10 25 9 21 0.44 0.60 0.83 0.33 0.00 0.50 13.6 77 4
17 17 16 17 13 17 1.00 0.80 1.00 1.00 1.00 1.00 14.85 73 15
19 18 11 22 27 23 0.89 0.80 1.00 0.33 0.50 0.50 14.75 151 4
16 17 15 23 22 17 0.33 0.00 0.17 0.00 0.00 0.00 14.1 89 9
19 16 12 27 12 25 0.67 0.30 0.67 0.33 0.00 1.00 14.9 78 4
23 22 21 27 18 19 0.67 0.60 0.83 0.33 0.50 1.00 16.25 110 4
8 17 22 5 6 8 1.00 0.50 0.83 0.67 0.00 1.00 19.25 220 28
22 21 20 19 17 14 0.78 0.70 1.00 0.33 0.00 0.50 13.6 65 4
23 20 15 24 22 22 0.67 0.30 0.83 0.00 0.50 1.00 13.6 141 4
15 20 9 23 22 25 1.00 0.30 1.00 0.67 0.00 0.00 15.65 117 4
17 19 15 28 23 28 0.78 0.40 1.00 0.67 0.00 0.50 12.75 122 5
21 8 14 25 19 25 0.89 0.40 0.83 1.00 0.00 1.00 14.6 63 4
25 19 11 27 20 24 0.89 0.10 0.83 0.00 0.00 1.00 9.85 44 4
18 11 9 16 17 15 0.89 0.50 1.00 0.67 0.00 1.00 12.65 52 12
20 13 12 25 24 24 0.00 0.00 0.00 0.00 0.00 0.00 19.2 131 4
21 18 11 26 20 28 0.67 0.40 1.00 0.33 0.50 0.00 16.6 101 6
21 19 14 24 18 24 1.00 0.60 0.83 0.67 1.00 0.50 11.2 42 6
24 23 10 23 23 25 1.00 0.40 1.00 0.33 0.50 1.00 15.25 152 5
22 20 18 24 27 23 0.67 0.10 0.33 0.00 0.50 1.00 11.9 107 4
22 22 11 27 25 26 0.89 0.30 0.83 0.00 0.00 1.00 13.2 77 4
23 19 14 25 24 26 0.89 0.70 0.83 0.67 0.00 1.00 16.35 154 4
17 16 16 19 12 22 0.56 0.30 0.17 0.00 0.00 1.00 12.4 103 10
15 11 11 19 16 25 0.67 0.50 0.83 0.33 0.50 0.00 15.85 96 7
22 21 16 24 24 22 1.00 0.30 0.83 0.67 1.00 1.00 18.15 175 4
19 14 13 20 23 26 1.00 0.60 0.67 0.67 0.50 1.00 11.15 57 7
18 21 12 21 24 20 1.00 0.90 1.00 1.00 0.00 1.00 15.65 112 4
21 20 17 28 24 26 0.67 0.40 0.83 0.00 0.50 1.00 17.75 143 4
20 21 23 26 26 26 0.44 0.30 1.00 0.00 0.50 0.50 7.65 49 12
19 20 14 19 19 21 0.89 0.90 1.00 0.67 1.00 1.00 12.35 110 5
19 19 10 23 28 21 0.44 0.50 1.00 0.00 0.50 0.00 15.6 131 8
16 19 16 23 23 24 0.56 0.30 1.00 1.00 0.50 0.50 19.3 167 6
18 18 11 21 21 21 0.89 0.60 0.83 0.67 0.00 0.50 15.2 56 17
23 20 16 26 19 18 0.67 0.20 1.00 0.33 0.00 0.50 17.1 137 4
22 21 19 25 23 23 0.89 0.40 0.83 1.00 0.50 1.00 15.6 86 5
23 22 17 25 23 26 1.00 0.50 0.83 0.67 0.50 0.50 18.4 121 4
20 19 12 24 20 23 0.78 0.40 0.83 0.67 0.00 0.50 19.05 149 5
24 23 17 23 18 25 0.44 0.00 0.00 0.00 0.00 0.00 18.55 168 5
25 16 11 22 20 20 0.89 0.20 1.00 0.33 0.50 1.00 19.1 140 6
25 23 19 27 28 25 0.89 0.50 1.00 0.67 0.50 1.00 13.1 88 4
20 18 12 26 21 26 0.89 0.30 1.00 0.67 0.00 0.50 12.85 168 4
23 23 8 23 25 19 0.44 0.00 0.00 0.00 0.00 0.00 9.5 94 4
21 20 17 22 18 21 1.00 0.50 0.83 1.00 0.00 1.00 4.5 51 6
23 20 13 26 24 23 0.89 0.60 0.83 0.33 0.00 1.00 11.85 48 8
23 23 17 22 28 24 0.67 0.30 0.83 0.00 0.50 0.50 13.6 145 10
11 13 7 17 9 6 0.33 0.00 0.00 0.00 0.00 0.00 11.7 66 4
21 21 23 25 22 22 0.78 0.30 0.67 0.00 0.50 0.00 12.4 85 5
27 26 18 22 26 21 0.89 0.50 1.00 0.67 0.50 1.00 13.35 109 4
19 18 13 28 28 28 0.78 0.40 0.67 0.00 0.00 1.00 11.4 63 4
21 19 17 22 18 24 0.78 0.50 0.83 0.67 0.00 0.50 14.9 102 4
16 18 13 21 23 14 0.89 0.70 1.00 1.00 1.00 0.50 19.9 162 16
21 18 8 24 15 20 0.78 0.80 1.00 0.67 0.50 1.00 11.2 86 7
22 19 16 26 24 28 0.78 0.60 1.00 0.33 0.50 1.00 14.6 114 4
16 13 14 26 12 19 0.67 0.40 0.83 0.33 0.00 0.50 17.6 164 4
18 10 13 24 12 24 0.89 0.50 0.83 0.33 0.50 0.00 14.05 119 14
23 21 19 27 20 21 0.89 0.50 1.00 0.00 0.50 1.00 16.1 126 5
24 24 15 22 25 21 0.78 0.30 1.00 0.33 0.00 1.00 13.35 132 5
20 21 15 23 24 26 1.00 0.60 1.00 0.00 0.50 1.00 11.85 142 5
20 23 8 22 23 24 1.00 0.30 0.67 0.67 0.00 0.50 11.95 83 5
18 18 14 23 18 26 0.78 0.60 0.83 1.00 0.50 0.50 14.75 94 7
4 11 7 15 20 25 0.78 0.30 0.33 0.33 0.00 1.00 15.15 81 19
14 16 11 20 22 23 0.89 0.70 1.00 0.67 1.00 1.00 13.2 166 16
22 20 17 22 20 24 0.89 0.70 1.00 1.00 0.00 1.00 16.85 110 4
17 20 19 25 25 24 0.67 0.60 0.67 1.00 0.50 1.00 7.85 64 4
23 26 17 27 28 26 1.00 0.50 1.00 0.33 0.50 0.00 7.7 93 7
20 21 12 24 25 23 0.67 0.50 0.83 0.33 0.00 0.50 12.6 104 9
18 12 12 21 14 20 0.56 0.40 0.67 0.00 0.00 1.00 7.85 105 5
19 15 18 17 16 16 0.78 0.40 1.00 0.33 1.00 1.00 10.95 49 14
20 18 16 26 24 24 1.00 0.70 1.00 1.00 0.00 1.00 12.35 88 4
15 14 15 20 13 20 0.67 0.20 0.17 0.00 0.50 0.00 9.95 95 16
24 18 20 22 19 23 0.78 0.50 0.83 0.67 0.00 0.50 14.9 102 10
21 16 16 24 18 23 0.56 0.40 0.83 0.67 0.50 0.00 16.65 99 5
19 19 12 23 16 18 1.00 0.20 1.00 0.67 1.00 1.00 13.4 63 6
19 7 10 22 8 21 0.89 0.50 0.67 0.67 0.00 0.00 13.95 76 4
27 21 28 28 27 25 0.44 0.40 0.50 0.00 0.00 1.00 15.7 109 4
23 24 19 21 23 23 1.00 0.70 0.67 1.00 1.00 1.00 16.85 117 4
23 21 18 24 20 26 0.89 0.60 0.83 0.67 1.00 0.00 10.95 57 5
20 20 19 28 20 26 0.78 0.40 0.83 0.00 0.00 0.00 15.35 120 4
17 22 8 25 26 24 0.89 0.50 1.00 0.67 1.00 1.00 12.2 73 4
21 17 17 24 23 23 0.11 0.00 0.17 0.00 0.00 0.00 15.1 91 5
23 19 16 24 24 21 0.89 0.70 1.00 0.67 0.50 1.00 17.75 108 4
22 20 18 21 21 23 0.89 0.40 0.67 0.67 0.00 1.00 15.2 105 4
16 16 12 20 15 20 1.00 0.50 0.67 1.00 0.00 1.00 14.6 117 5
20 20 17 26 22 23 0.89 0.60 0.83 0.67 0.00 0.50 16.65 119 8

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=265038&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=265038&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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] = + 11.0654 + 0.0860689AMS.I1[t] + 0.0262998AMS.I2[t] -0.0494687AMS.I3[t] -0.0708628AMS.E1[t] -0.052881AMS.E2[t] -0.0375933AMS.E3[t] -0.829315Calculation[t] -0.776169Algebraic_Reasoning[t] + 1.32535Graphical_Interpretation[t] + 1.633Proportionality_and_Ratio[t] + 0.394449Probability_and_Sampling[t] -0.187516Estimation[t] + 0.0260571LFM[t] + 0.0185255AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  11.0654 +  0.0860689AMS.I1[t] +  0.0262998AMS.I2[t] -0.0494687AMS.I3[t] -0.0708628AMS.E1[t] -0.052881AMS.E2[t] -0.0375933AMS.E3[t] -0.829315Calculation[t] -0.776169Algebraic_Reasoning[t] +  1.32535Graphical_Interpretation[t] +  1.633Proportionality_and_Ratio[t] +  0.394449Probability_and_Sampling[t] -0.187516Estimation[t] +  0.0260571LFM[t] +  0.0185255AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  11.0654 +  0.0860689AMS.I1[t] +  0.0262998AMS.I2[t] -0.0494687AMS.I3[t] -0.0708628AMS.E1[t] -0.052881AMS.E2[t] -0.0375933AMS.E3[t] -0.829315Calculation[t] -0.776169Algebraic_Reasoning[t] +  1.32535Graphical_Interpretation[t] +  1.633Proportionality_and_Ratio[t] +  0.394449Probability_and_Sampling[t] -0.187516Estimation[t] +  0.0260571LFM[t] +  0.0185255AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265038&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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] = + 11.0654 + 0.0860689AMS.I1[t] + 0.0262998AMS.I2[t] -0.0494687AMS.I3[t] -0.0708628AMS.E1[t] -0.052881AMS.E2[t] -0.0375933AMS.E3[t] -0.829315Calculation[t] -0.776169Algebraic_Reasoning[t] + 1.32535Graphical_Interpretation[t] + 1.633Proportionality_and_Ratio[t] + 0.394449Probability_and_Sampling[t] -0.187516Estimation[t] + 0.0260571LFM[t] + 0.0185255AMS.A[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)	11.0654	2.45276	4.511	9.72967e-06	4.86484e-06
AMS.I1	0.0860689	0.0804122	1.07	0.285449	0.142724
AMS.I2	0.0262998	0.0698206	0.3767	0.706719	0.353359
AMS.I3	-0.0494687	0.0601649	-0.8222	0.4117	0.20585
AMS.E1	-0.0708628	0.0834104	-0.8496	0.396341	0.19817
AMS.E2	-0.052881	0.0571169	-0.9258	0.355382	0.177691
AMS.E3	-0.0375933	0.0685366	-0.5485	0.583806	0.291903
Calculation	-0.829315	1.33956	-0.6191	0.536392	0.268196
Algebraic_Reasoning	-0.776169	1.21383	-0.6394	0.523098	0.261549
Graphical_Interpretation	1.32535	0.99098	1.337	0.182248	0.0911239
Proportionality_and_Ratio	1.633	0.611205	2.672	0.00801812	0.00400906
Probability_and_Sampling	0.394449	0.56491	0.6983	0.48564	0.24282
Estimation	-0.187516	0.546131	-0.3434	0.731608	0.365804
LFM	0.0260571	0.00499359	5.218	3.67882e-07	1.83941e-07
AMS.A	0.0185255	0.0680392	0.2723	0.785624	0.392812

\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) & 11.0654 & 2.45276 & 4.511 & 9.72967e-06 & 4.86484e-06 \tabularnewline
AMS.I1 & 0.0860689 & 0.0804122 & 1.07 & 0.285449 & 0.142724 \tabularnewline
AMS.I2 & 0.0262998 & 0.0698206 & 0.3767 & 0.706719 & 0.353359 \tabularnewline
AMS.I3 & -0.0494687 & 0.0601649 & -0.8222 & 0.4117 & 0.20585 \tabularnewline
AMS.E1 & -0.0708628 & 0.0834104 & -0.8496 & 0.396341 & 0.19817 \tabularnewline
AMS.E2 & -0.052881 & 0.0571169 & -0.9258 & 0.355382 & 0.177691 \tabularnewline
AMS.E3 & -0.0375933 & 0.0685366 & -0.5485 & 0.583806 & 0.291903 \tabularnewline
Calculation & -0.829315 & 1.33956 & -0.6191 & 0.536392 & 0.268196 \tabularnewline
Algebraic_Reasoning & -0.776169 & 1.21383 & -0.6394 & 0.523098 & 0.261549 \tabularnewline
Graphical_Interpretation & 1.32535 & 0.99098 & 1.337 & 0.182248 & 0.0911239 \tabularnewline
Proportionality_and_Ratio & 1.633 & 0.611205 & 2.672 & 0.00801812 & 0.00400906 \tabularnewline
Probability_and_Sampling & 0.394449 & 0.56491 & 0.6983 & 0.48564 & 0.24282 \tabularnewline
Estimation & -0.187516 & 0.546131 & -0.3434 & 0.731608 & 0.365804 \tabularnewline
LFM & 0.0260571 & 0.00499359 & 5.218 & 3.67882e-07 & 1.83941e-07 \tabularnewline
AMS.A & 0.0185255 & 0.0680392 & 0.2723 & 0.785624 & 0.392812 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&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]11.0654[/C][C]2.45276[/C][C]4.511[/C][C]9.72967e-06[/C][C]4.86484e-06[/C][/ROW]
[ROW][C]AMS.I1[/C][C]0.0860689[/C][C]0.0804122[/C][C]1.07[/C][C]0.285449[/C][C]0.142724[/C][/ROW]
[ROW][C]AMS.I2[/C][C]0.0262998[/C][C]0.0698206[/C][C]0.3767[/C][C]0.706719[/C][C]0.353359[/C][/ROW]
[ROW][C]AMS.I3[/C][C]-0.0494687[/C][C]0.0601649[/C][C]-0.8222[/C][C]0.4117[/C][C]0.20585[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0708628[/C][C]0.0834104[/C][C]-0.8496[/C][C]0.396341[/C][C]0.19817[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.052881[/C][C]0.0571169[/C][C]-0.9258[/C][C]0.355382[/C][C]0.177691[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0375933[/C][C]0.0685366[/C][C]-0.5485[/C][C]0.583806[/C][C]0.291903[/C][/ROW]
[ROW][C]Calculation[/C][C]-0.829315[/C][C]1.33956[/C][C]-0.6191[/C][C]0.536392[/C][C]0.268196[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.776169[/C][C]1.21383[/C][C]-0.6394[/C][C]0.523098[/C][C]0.261549[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]1.32535[/C][C]0.99098[/C][C]1.337[/C][C]0.182248[/C][C]0.0911239[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]1.633[/C][C]0.611205[/C][C]2.672[/C][C]0.00801812[/C][C]0.00400906[/C][/ROW]
[ROW][C]Probability_and_Sampling[/C][C]0.394449[/C][C]0.56491[/C][C]0.6983[/C][C]0.48564[/C][C]0.24282[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.187516[/C][C]0.546131[/C][C]-0.3434[/C][C]0.731608[/C][C]0.365804[/C][/ROW]
[ROW][C]LFM[/C][C]0.0260571[/C][C]0.00499359[/C][C]5.218[/C][C]3.67882e-07[/C][C]1.83941e-07[/C][/ROW]
[ROW][C]AMS.A[/C][C]0.0185255[/C][C]0.0680392[/C][C]0.2723[/C][C]0.785624[/C][C]0.392812[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265038&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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)	11.0654	2.45276	4.511	9.72967e-06	4.86484e-06
AMS.I1	0.0860689	0.0804122	1.07	0.285449	0.142724
AMS.I2	0.0262998	0.0698206	0.3767	0.706719	0.353359
AMS.I3	-0.0494687	0.0601649	-0.8222	0.4117	0.20585
AMS.E1	-0.0708628	0.0834104	-0.8496	0.396341	0.19817
AMS.E2	-0.052881	0.0571169	-0.9258	0.355382	0.177691
AMS.E3	-0.0375933	0.0685366	-0.5485	0.583806	0.291903
Calculation	-0.829315	1.33956	-0.6191	0.536392	0.268196
Algebraic_Reasoning	-0.776169	1.21383	-0.6394	0.523098	0.261549
Graphical_Interpretation	1.32535	0.99098	1.337	0.182248	0.0911239
Proportionality_and_Ratio	1.633	0.611205	2.672	0.00801812	0.00400906
Probability_and_Sampling	0.394449	0.56491	0.6983	0.48564	0.24282
Estimation	-0.187516	0.546131	-0.3434	0.731608	0.365804
LFM	0.0260571	0.00499359	5.218	3.67882e-07	1.83941e-07
AMS.A	0.0185255	0.0680392	0.2723	0.785624	0.392812

Multiple Linear Regression - Regression Statistics
Multiple R	0.381187
R-squared	0.145303
Adjusted R-squared	0.0996326
F-TEST (value)	3.18154
F-TEST (DF numerator)	14
F-TEST (DF denominator)	262
p-value	0.000120888
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.21458
Sum Squared Residuals	2707.38

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.381187 \tabularnewline
R-squared & 0.145303 \tabularnewline
Adjusted R-squared & 0.0996326 \tabularnewline
F-TEST (value) & 3.18154 \tabularnewline
F-TEST (DF numerator) & 14 \tabularnewline
F-TEST (DF denominator) & 262 \tabularnewline
p-value & 0.000120888 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.21458 \tabularnewline
Sum Squared Residuals & 2707.38 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.381187[/C][/ROW]
[ROW][C]R-squared[/C][C]0.145303[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0996326[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]3.18154[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]14[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]262[/C][/ROW]
[ROW][C]p-value[/C][C]0.000120888[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.21458[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2707.38[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265038&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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	0.381187
R-squared	0.145303
Adjusted R-squared	0.0996326
F-TEST (value)	3.18154
F-TEST (DF numerator)	14
F-TEST (DF denominator)	262
p-value	0.000120888
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	3.21458
Sum Squared Residuals	2707.38

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	12.9	13.8418	-0.94184
2	12.2	13.0015	-0.801483
3	12.8	14.4693	-1.66934
4	7.4	13.2041	-5.80407
5	6.7	12.515	-5.81504
6	12.6	13.883	-1.28297
7	14.8	13.9177	0.882275
8	13.3	13.6972	-0.397204
9	11.1	12.5422	-1.44219
10	8.2	15.3684	-7.16837
11	11.4	13.8064	-2.40638
12	6.4	13.6216	-7.22163
13	10.6	11.587	-0.98696
14	12	14.3207	-2.32065
15	6.3	10.6634	-4.36339
16	11.3	11.4531	-0.153128
17	11.9	13.7313	-1.83125
18	9.3	12.4215	-3.12154
19	9.6	13.0614	-3.46142
20	10	11.8378	-1.83783
21	6.4	14.2245	-7.82449
22	13.8	13.7398	0.0602484
23	10.8	15.0191	-4.21909
24	13.8	14.221	-0.420975
25	11.7	14.5846	-2.88463
26	10.9	15.7274	-4.82744
27	16.1	13.0622	3.03776
28	13.4	12.9718	0.428216
29	9.9	14.6236	-4.72356
30	11.5	14.1513	-2.65127
31	8.3	11.1468	-2.84679
32	11.7	13.7071	-2.00713
33	9	13.2313	-4.23125
34	9.7	14.197	-4.49698
35	10.8	13.1817	-2.3817
36	10.3	14.0648	-3.7648
37	10.4	13.8912	-3.49117
38	12.7	12.9038	-0.203815
39	9.3	14.9841	-5.68407
40	11.8	13.9086	-2.10862
41	5.9	13.7904	-7.89044
42	11.4	14.7461	-3.34614
43	13	14.0976	-1.09755
44	10.8	14.1104	-3.31042
45	12.3	11.4955	0.804526
46	11.3	15.028	-3.72804
47	11.8	11.9386	-0.138614
48	7.9	11.4532	-3.5532
49	12.7	10.4417	2.25826
50	12.3	13.0105	-0.710459
51	11.6	13.1213	-1.52132
52	6.7	10.7214	-4.02139
53	10.9	14.5186	-3.61863
54	12.1	12.8323	-0.732327
55	13.3	13.3993	-0.0993262
56	10.1	13.6759	-3.57595
57	5.7	13.3828	-7.68283
58	14.3	12.2482	2.0518
59	8	11.0212	-3.02116
60	13.3	12.7433	0.556744
61	9.3	15.109	-5.80899
62	12.5	13.0521	-0.552121
63	7.6	13.3015	-5.70149
64	15.9	15.6471	0.252949
65	9.2	13.9132	-4.71321
66	9.1	12.8431	-3.74309
67	11.1	14.5613	-3.46134
68	13	15.9862	-2.98624
69	14.5	16.0374	-1.53743
70	12.2	12.2539	-0.0539178
71	12.3	14.1998	-1.89983
72	11.4	13.1211	-1.72112
73	8.8	11.9654	-3.16545
74	14.6	13.1101	1.48992
75	12.6	12.227	0.372958
76	NA	NA	0.396043
77	13	13.6741	-0.674082
78	12.6	13.7159	-1.11591
79	13.2	14.2259	-1.02592
80	9.9	13.7915	-3.8915
81	7.7	8.94745	-1.24745
82	10.5	8.8488	1.6512
83	13.4	14.9403	-1.54027
84	10.9	18.384	-7.48399
85	4.3	7.93163	-3.63163
86	10.3	10.9617	-0.66174
87	11.8	12.4883	-0.688341
88	11.2	11.978	-0.77798
89	11.4	15.4681	-4.06811
90	8.6	7.67171	0.928288
91	13.2	13.0163	0.183706
92	12.6	19.9423	-7.34233
93	5.6	8.20612	-2.60612
94	9.9	13.4141	-3.51409
95	8.8	12.7658	-3.96582
96	7.7	10.0647	-2.36468
97	9	14.2736	-5.27356
98	7.3	9.056	-1.756
99	11.4	10.0518	1.34822
100	13.6	18.6386	-5.03858
101	7.9	8.66408	-0.764078
102	10.7	13.3095	-2.60946
103	10.3	12.3924	-2.09239
104	8.3	11.2061	-2.90614
105	9.6	7.29907	2.30093
106	14.2	17.3034	-3.10336
107	8.5	7.4262	1.0738
108	13.5	21.5864	-8.08643
109	4.9	9.45202	-4.55202
110	6.4	9.11947	-2.71947
111	9.6	10.9332	-1.33324
112	11.6	13.2559	-1.65587
113	11.1	18.1602	-7.06022
114	4.35	3.33522	1.01478
115	12.7	8.8211	3.8789
116	18.1	14.962	3.13799
117	17.85	15.6888	2.16121
118	16.6	15.9812	0.618802
119	12.6	11.7355	0.86448
120	17.1	13.0968	4.0032
121	19.1	16.9956	2.10436
122	16.1	14.0151	2.08494
123	13.35	9.90505	3.44495
124	18.4	14.8937	3.50627
125	14.7	16.9512	-2.2512
126	10.6	9.74057	0.859434
127	12.6	8.68192	3.91808
128	16.2	14.7867	1.41331
129	13.6	7.8451	5.7549
130	18.9	17.9027	0.997275
131	14.1	13.7805	0.319463
132	14.5	11.741	2.75903
133	16.15	15.0068	1.14317
134	14.75	13.0249	1.72509
135	14.8	15.0414	-0.241364
136	12.45	12.1393	0.310663
137	12.65	9.12194	3.52806
138	17.35	20.1792	-2.82918
139	8.6	3.97854	4.62146
140	18.4	17.0209	1.37905
141	16.1	17.3765	-1.27646
142	11.6	8.37511	3.22489
143	17.75	15.1797	2.57031
144	15.25	11.0891	4.16095
145	17.65	14.954	2.69599
146	16.35	13.09	3.26003
147	17.65	18.042	-0.392001
148	13.6	12.1996	1.40039
149	14.35	12.3488	2.00117
150	14.75	12.5168	2.23316
151	18.25	21.8915	-3.64149
152	9.9	7.69331	2.20669
153	16	12.5751	3.42493
154	18.25	14.7153	3.53466
155	16.85	14.8161	2.03391
156	14.6	13.0122	1.58778
157	13.85	10.7671	3.08287
158	18.95	16.755	2.195
159	15.6	14.5178	1.08217
160	14.85	15.802	-0.952035
161	11.75	7.17046	4.57954
162	18.45	15.4361	3.01386
163	15.9	14.5376	1.36244
164	17.1	12.3106	4.78943
165	16.1	12.6007	3.49927
166	19.9	20.1108	-0.21083
167	10.95	5.6623	5.2877
168	18.45	17.3571	1.09287
169	15.1	13.6379	1.46206
170	15	16.0654	-1.06545
171	11.35	8.35619	2.99381
172	15.95	10.7249	5.2251
173	18.1	17.5528	0.547239
174	14.6	14.7799	-0.179872
175	15.4	15.3293	0.0706575
176	15.4	10.0694	5.33064
177	17.6	17.7641	-0.164057
178	13.35	6.55722	6.79278
179	19.1	16.9734	2.12662
180	15.35	18.575	-3.22503
181	7.6	6.97519	0.624814
182	13.4	12.3691	1.03092
183	13.9	10.4118	3.48825
184	19.1	15.3806	3.71943
185	15.25	15.9044	-0.654442
186	12.9	10.0734	2.82659
187	16.1	11.8933	4.2067
188	17.35	17.2929	0.0570975
189	13.15	14.3074	-1.15741
190	12.15	9.6919	2.4581
191	12.6	14.0722	-1.47217
192	10.35	7.55971	2.79029
193	15.4	18.3891	-2.9891
194	9.6	3.45441	6.14559
195	18.2	16.8606	1.33941
196	13.6	12.298	1.30197
197	14.85	13.4959	1.35407
198	14.75	11.8027	2.94731
199	14.1	10.7976	3.30241
200	14.9	11.223	3.67702
201	16.25	14.1809	2.06911
202	19.25	17.7483	1.50174
203	13.6	13.2072	0.392794
204	13.6	11.1342	2.46579
205	15.65	15.5731	0.0768502
206	12.75	10.0372	2.71281
207	14.6	15.3669	-0.766923
208	9.85	9.74506	0.104936
209	12.65	5.52967	7.12033
210	19.2	15.3877	3.81232
211	16.6	16.9305	-0.330534
212	11.2	10.1928	1.00722
213	15.25	14.6273	0.622651
214	11.9	9.50268	2.39732
215	13.2	10.4961	2.70391
216	16.35	15.5095	0.8405
217	12.4	9.04283	3.35717
218	15.85	12.5958	3.25419
219	18.15	18.1266	0.0234295
220	11.15	8.79963	2.35037
221	15.65	10.271	5.37896
222	17.75	20.4367	-2.68668
223	7.65	8.84219	-1.19219
224	12.35	9.88701	2.46299
225	15.6	11.5296	4.07042
226	19.3	15.9265	3.37348
227	15.2	12.0591	3.14085
228	17.1	14.2465	2.85346
229	15.6	10.3246	5.27543
230	18.4	13.5381	4.86194
231	19.05	13.9788	5.07124
232	18.55	13.9151	4.63495
233	19.1	18.2184	0.88158
234	13.1	14.7926	-1.69263
235	12.85	15.0965	-2.24655
236	9.5	17.0257	-7.52575
237	4.5	3.24821	1.25179
238	11.85	11.4956	0.35444
239	13.6	13.5218	0.0782003
240	11.7	10.3383	1.36168
241	12.4	12.7266	-0.326575
242	13.35	11.4224	1.92761
243	11.4	9.41585	1.98415
244	14.9	10.5374	4.36261
245	19.9	21.9366	-2.03665
246	11.2	8.9089	2.2911
247	14.6	10.9271	3.67292
248	17.6	16.6171	0.982856
249	14.05	10.4317	3.61831
250	16.1	16.4289	-0.32891
251	13.35	14.0534	-0.703394
252	11.85	12.3	-0.449961
253	11.95	10.3393	1.61069
254	14.75	10.2639	4.48609
255	15.15	16.6186	-1.46858
256	13.2	9.90489	3.29511
257	16.85	20.3699	-3.51992
258	7.85	12.0635	-4.21346
259	7.7	7.43617	0.263829
260	12.6	16.8605	-4.26049
261	7.85	9.10249	-1.25249
262	10.95	10.8202	0.129831
263	12.35	14.0095	-1.6595
264	9.95	8.14521	1.80479
265	14.9	11.5237	3.37631
266	16.65	16.0987	0.551263
267	13.4	11.979	1.42102
268	13.95	9.16876	4.78124
269	15.7	12.4953	3.2047
270	16.85	17.8338	-0.983762
271	10.95	7.29731	3.65269
272	15.35	15.2892	0.0608271
273	12.2	8.39525	3.80475
274	15.1	10.3799	4.72012
275	17.75	15.2373	2.51269
276	15.2	14.1647	1.0353
277	14.6	10.6969	3.90307
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 & 13.8418 & -0.94184 \tabularnewline
2 & 12.2 & 13.0015 & -0.801483 \tabularnewline
3 & 12.8 & 14.4693 & -1.66934 \tabularnewline
4 & 7.4 & 13.2041 & -5.80407 \tabularnewline
5 & 6.7 & 12.515 & -5.81504 \tabularnewline
6 & 12.6 & 13.883 & -1.28297 \tabularnewline
7 & 14.8 & 13.9177 & 0.882275 \tabularnewline
8 & 13.3 & 13.6972 & -0.397204 \tabularnewline
9 & 11.1 & 12.5422 & -1.44219 \tabularnewline
10 & 8.2 & 15.3684 & -7.16837 \tabularnewline
11 & 11.4 & 13.8064 & -2.40638 \tabularnewline
12 & 6.4 & 13.6216 & -7.22163 \tabularnewline
13 & 10.6 & 11.587 & -0.98696 \tabularnewline
14 & 12 & 14.3207 & -2.32065 \tabularnewline
15 & 6.3 & 10.6634 & -4.36339 \tabularnewline
16 & 11.3 & 11.4531 & -0.153128 \tabularnewline
17 & 11.9 & 13.7313 & -1.83125 \tabularnewline
18 & 9.3 & 12.4215 & -3.12154 \tabularnewline
19 & 9.6 & 13.0614 & -3.46142 \tabularnewline
20 & 10 & 11.8378 & -1.83783 \tabularnewline
21 & 6.4 & 14.2245 & -7.82449 \tabularnewline
22 & 13.8 & 13.7398 & 0.0602484 \tabularnewline
23 & 10.8 & 15.0191 & -4.21909 \tabularnewline
24 & 13.8 & 14.221 & -0.420975 \tabularnewline
25 & 11.7 & 14.5846 & -2.88463 \tabularnewline
26 & 10.9 & 15.7274 & -4.82744 \tabularnewline
27 & 16.1 & 13.0622 & 3.03776 \tabularnewline
28 & 13.4 & 12.9718 & 0.428216 \tabularnewline
29 & 9.9 & 14.6236 & -4.72356 \tabularnewline
30 & 11.5 & 14.1513 & -2.65127 \tabularnewline
31 & 8.3 & 11.1468 & -2.84679 \tabularnewline
32 & 11.7 & 13.7071 & -2.00713 \tabularnewline
33 & 9 & 13.2313 & -4.23125 \tabularnewline
34 & 9.7 & 14.197 & -4.49698 \tabularnewline
35 & 10.8 & 13.1817 & -2.3817 \tabularnewline
36 & 10.3 & 14.0648 & -3.7648 \tabularnewline
37 & 10.4 & 13.8912 & -3.49117 \tabularnewline
38 & 12.7 & 12.9038 & -0.203815 \tabularnewline
39 & 9.3 & 14.9841 & -5.68407 \tabularnewline
40 & 11.8 & 13.9086 & -2.10862 \tabularnewline
41 & 5.9 & 13.7904 & -7.89044 \tabularnewline
42 & 11.4 & 14.7461 & -3.34614 \tabularnewline
43 & 13 & 14.0976 & -1.09755 \tabularnewline
44 & 10.8 & 14.1104 & -3.31042 \tabularnewline
45 & 12.3 & 11.4955 & 0.804526 \tabularnewline
46 & 11.3 & 15.028 & -3.72804 \tabularnewline
47 & 11.8 & 11.9386 & -0.138614 \tabularnewline
48 & 7.9 & 11.4532 & -3.5532 \tabularnewline
49 & 12.7 & 10.4417 & 2.25826 \tabularnewline
50 & 12.3 & 13.0105 & -0.710459 \tabularnewline
51 & 11.6 & 13.1213 & -1.52132 \tabularnewline
52 & 6.7 & 10.7214 & -4.02139 \tabularnewline
53 & 10.9 & 14.5186 & -3.61863 \tabularnewline
54 & 12.1 & 12.8323 & -0.732327 \tabularnewline
55 & 13.3 & 13.3993 & -0.0993262 \tabularnewline
56 & 10.1 & 13.6759 & -3.57595 \tabularnewline
57 & 5.7 & 13.3828 & -7.68283 \tabularnewline
58 & 14.3 & 12.2482 & 2.0518 \tabularnewline
59 & 8 & 11.0212 & -3.02116 \tabularnewline
60 & 13.3 & 12.7433 & 0.556744 \tabularnewline
61 & 9.3 & 15.109 & -5.80899 \tabularnewline
62 & 12.5 & 13.0521 & -0.552121 \tabularnewline
63 & 7.6 & 13.3015 & -5.70149 \tabularnewline
64 & 15.9 & 15.6471 & 0.252949 \tabularnewline
65 & 9.2 & 13.9132 & -4.71321 \tabularnewline
66 & 9.1 & 12.8431 & -3.74309 \tabularnewline
67 & 11.1 & 14.5613 & -3.46134 \tabularnewline
68 & 13 & 15.9862 & -2.98624 \tabularnewline
69 & 14.5 & 16.0374 & -1.53743 \tabularnewline
70 & 12.2 & 12.2539 & -0.0539178 \tabularnewline
71 & 12.3 & 14.1998 & -1.89983 \tabularnewline
72 & 11.4 & 13.1211 & -1.72112 \tabularnewline
73 & 8.8 & 11.9654 & -3.16545 \tabularnewline
74 & 14.6 & 13.1101 & 1.48992 \tabularnewline
75 & 12.6 & 12.227 & 0.372958 \tabularnewline
76 & NA & NA & 0.396043 \tabularnewline
77 & 13 & 13.6741 & -0.674082 \tabularnewline
78 & 12.6 & 13.7159 & -1.11591 \tabularnewline
79 & 13.2 & 14.2259 & -1.02592 \tabularnewline
80 & 9.9 & 13.7915 & -3.8915 \tabularnewline
81 & 7.7 & 8.94745 & -1.24745 \tabularnewline
82 & 10.5 & 8.8488 & 1.6512 \tabularnewline
83 & 13.4 & 14.9403 & -1.54027 \tabularnewline
84 & 10.9 & 18.384 & -7.48399 \tabularnewline
85 & 4.3 & 7.93163 & -3.63163 \tabularnewline
86 & 10.3 & 10.9617 & -0.66174 \tabularnewline
87 & 11.8 & 12.4883 & -0.688341 \tabularnewline
88 & 11.2 & 11.978 & -0.77798 \tabularnewline
89 & 11.4 & 15.4681 & -4.06811 \tabularnewline
90 & 8.6 & 7.67171 & 0.928288 \tabularnewline
91 & 13.2 & 13.0163 & 0.183706 \tabularnewline
92 & 12.6 & 19.9423 & -7.34233 \tabularnewline
93 & 5.6 & 8.20612 & -2.60612 \tabularnewline
94 & 9.9 & 13.4141 & -3.51409 \tabularnewline
95 & 8.8 & 12.7658 & -3.96582 \tabularnewline
96 & 7.7 & 10.0647 & -2.36468 \tabularnewline
97 & 9 & 14.2736 & -5.27356 \tabularnewline
98 & 7.3 & 9.056 & -1.756 \tabularnewline
99 & 11.4 & 10.0518 & 1.34822 \tabularnewline
100 & 13.6 & 18.6386 & -5.03858 \tabularnewline
101 & 7.9 & 8.66408 & -0.764078 \tabularnewline
102 & 10.7 & 13.3095 & -2.60946 \tabularnewline
103 & 10.3 & 12.3924 & -2.09239 \tabularnewline
104 & 8.3 & 11.2061 & -2.90614 \tabularnewline
105 & 9.6 & 7.29907 & 2.30093 \tabularnewline
106 & 14.2 & 17.3034 & -3.10336 \tabularnewline
107 & 8.5 & 7.4262 & 1.0738 \tabularnewline
108 & 13.5 & 21.5864 & -8.08643 \tabularnewline
109 & 4.9 & 9.45202 & -4.55202 \tabularnewline
110 & 6.4 & 9.11947 & -2.71947 \tabularnewline
111 & 9.6 & 10.9332 & -1.33324 \tabularnewline
112 & 11.6 & 13.2559 & -1.65587 \tabularnewline
113 & 11.1 & 18.1602 & -7.06022 \tabularnewline
114 & 4.35 & 3.33522 & 1.01478 \tabularnewline
115 & 12.7 & 8.8211 & 3.8789 \tabularnewline
116 & 18.1 & 14.962 & 3.13799 \tabularnewline
117 & 17.85 & 15.6888 & 2.16121 \tabularnewline
118 & 16.6 & 15.9812 & 0.618802 \tabularnewline
119 & 12.6 & 11.7355 & 0.86448 \tabularnewline
120 & 17.1 & 13.0968 & 4.0032 \tabularnewline
121 & 19.1 & 16.9956 & 2.10436 \tabularnewline
122 & 16.1 & 14.0151 & 2.08494 \tabularnewline
123 & 13.35 & 9.90505 & 3.44495 \tabularnewline
124 & 18.4 & 14.8937 & 3.50627 \tabularnewline
125 & 14.7 & 16.9512 & -2.2512 \tabularnewline
126 & 10.6 & 9.74057 & 0.859434 \tabularnewline
127 & 12.6 & 8.68192 & 3.91808 \tabularnewline
128 & 16.2 & 14.7867 & 1.41331 \tabularnewline
129 & 13.6 & 7.8451 & 5.7549 \tabularnewline
130 & 18.9 & 17.9027 & 0.997275 \tabularnewline
131 & 14.1 & 13.7805 & 0.319463 \tabularnewline
132 & 14.5 & 11.741 & 2.75903 \tabularnewline
133 & 16.15 & 15.0068 & 1.14317 \tabularnewline
134 & 14.75 & 13.0249 & 1.72509 \tabularnewline
135 & 14.8 & 15.0414 & -0.241364 \tabularnewline
136 & 12.45 & 12.1393 & 0.310663 \tabularnewline
137 & 12.65 & 9.12194 & 3.52806 \tabularnewline
138 & 17.35 & 20.1792 & -2.82918 \tabularnewline
139 & 8.6 & 3.97854 & 4.62146 \tabularnewline
140 & 18.4 & 17.0209 & 1.37905 \tabularnewline
141 & 16.1 & 17.3765 & -1.27646 \tabularnewline
142 & 11.6 & 8.37511 & 3.22489 \tabularnewline
143 & 17.75 & 15.1797 & 2.57031 \tabularnewline
144 & 15.25 & 11.0891 & 4.16095 \tabularnewline
145 & 17.65 & 14.954 & 2.69599 \tabularnewline
146 & 16.35 & 13.09 & 3.26003 \tabularnewline
147 & 17.65 & 18.042 & -0.392001 \tabularnewline
148 & 13.6 & 12.1996 & 1.40039 \tabularnewline
149 & 14.35 & 12.3488 & 2.00117 \tabularnewline
150 & 14.75 & 12.5168 & 2.23316 \tabularnewline
151 & 18.25 & 21.8915 & -3.64149 \tabularnewline
152 & 9.9 & 7.69331 & 2.20669 \tabularnewline
153 & 16 & 12.5751 & 3.42493 \tabularnewline
154 & 18.25 & 14.7153 & 3.53466 \tabularnewline
155 & 16.85 & 14.8161 & 2.03391 \tabularnewline
156 & 14.6 & 13.0122 & 1.58778 \tabularnewline
157 & 13.85 & 10.7671 & 3.08287 \tabularnewline
158 & 18.95 & 16.755 & 2.195 \tabularnewline
159 & 15.6 & 14.5178 & 1.08217 \tabularnewline
160 & 14.85 & 15.802 & -0.952035 \tabularnewline
161 & 11.75 & 7.17046 & 4.57954 \tabularnewline
162 & 18.45 & 15.4361 & 3.01386 \tabularnewline
163 & 15.9 & 14.5376 & 1.36244 \tabularnewline
164 & 17.1 & 12.3106 & 4.78943 \tabularnewline
165 & 16.1 & 12.6007 & 3.49927 \tabularnewline
166 & 19.9 & 20.1108 & -0.21083 \tabularnewline
167 & 10.95 & 5.6623 & 5.2877 \tabularnewline
168 & 18.45 & 17.3571 & 1.09287 \tabularnewline
169 & 15.1 & 13.6379 & 1.46206 \tabularnewline
170 & 15 & 16.0654 & -1.06545 \tabularnewline
171 & 11.35 & 8.35619 & 2.99381 \tabularnewline
172 & 15.95 & 10.7249 & 5.2251 \tabularnewline
173 & 18.1 & 17.5528 & 0.547239 \tabularnewline
174 & 14.6 & 14.7799 & -0.179872 \tabularnewline
175 & 15.4 & 15.3293 & 0.0706575 \tabularnewline
176 & 15.4 & 10.0694 & 5.33064 \tabularnewline
177 & 17.6 & 17.7641 & -0.164057 \tabularnewline
178 & 13.35 & 6.55722 & 6.79278 \tabularnewline
179 & 19.1 & 16.9734 & 2.12662 \tabularnewline
180 & 15.35 & 18.575 & -3.22503 \tabularnewline
181 & 7.6 & 6.97519 & 0.624814 \tabularnewline
182 & 13.4 & 12.3691 & 1.03092 \tabularnewline
183 & 13.9 & 10.4118 & 3.48825 \tabularnewline
184 & 19.1 & 15.3806 & 3.71943 \tabularnewline
185 & 15.25 & 15.9044 & -0.654442 \tabularnewline
186 & 12.9 & 10.0734 & 2.82659 \tabularnewline
187 & 16.1 & 11.8933 & 4.2067 \tabularnewline
188 & 17.35 & 17.2929 & 0.0570975 \tabularnewline
189 & 13.15 & 14.3074 & -1.15741 \tabularnewline
190 & 12.15 & 9.6919 & 2.4581 \tabularnewline
191 & 12.6 & 14.0722 & -1.47217 \tabularnewline
192 & 10.35 & 7.55971 & 2.79029 \tabularnewline
193 & 15.4 & 18.3891 & -2.9891 \tabularnewline
194 & 9.6 & 3.45441 & 6.14559 \tabularnewline
195 & 18.2 & 16.8606 & 1.33941 \tabularnewline
196 & 13.6 & 12.298 & 1.30197 \tabularnewline
197 & 14.85 & 13.4959 & 1.35407 \tabularnewline
198 & 14.75 & 11.8027 & 2.94731 \tabularnewline
199 & 14.1 & 10.7976 & 3.30241 \tabularnewline
200 & 14.9 & 11.223 & 3.67702 \tabularnewline
201 & 16.25 & 14.1809 & 2.06911 \tabularnewline
202 & 19.25 & 17.7483 & 1.50174 \tabularnewline
203 & 13.6 & 13.2072 & 0.392794 \tabularnewline
204 & 13.6 & 11.1342 & 2.46579 \tabularnewline
205 & 15.65 & 15.5731 & 0.0768502 \tabularnewline
206 & 12.75 & 10.0372 & 2.71281 \tabularnewline
207 & 14.6 & 15.3669 & -0.766923 \tabularnewline
208 & 9.85 & 9.74506 & 0.104936 \tabularnewline
209 & 12.65 & 5.52967 & 7.12033 \tabularnewline
210 & 19.2 & 15.3877 & 3.81232 \tabularnewline
211 & 16.6 & 16.9305 & -0.330534 \tabularnewline
212 & 11.2 & 10.1928 & 1.00722 \tabularnewline
213 & 15.25 & 14.6273 & 0.622651 \tabularnewline
214 & 11.9 & 9.50268 & 2.39732 \tabularnewline
215 & 13.2 & 10.4961 & 2.70391 \tabularnewline
216 & 16.35 & 15.5095 & 0.8405 \tabularnewline
217 & 12.4 & 9.04283 & 3.35717 \tabularnewline
218 & 15.85 & 12.5958 & 3.25419 \tabularnewline
219 & 18.15 & 18.1266 & 0.0234295 \tabularnewline
220 & 11.15 & 8.79963 & 2.35037 \tabularnewline
221 & 15.65 & 10.271 & 5.37896 \tabularnewline
222 & 17.75 & 20.4367 & -2.68668 \tabularnewline
223 & 7.65 & 8.84219 & -1.19219 \tabularnewline
224 & 12.35 & 9.88701 & 2.46299 \tabularnewline
225 & 15.6 & 11.5296 & 4.07042 \tabularnewline
226 & 19.3 & 15.9265 & 3.37348 \tabularnewline
227 & 15.2 & 12.0591 & 3.14085 \tabularnewline
228 & 17.1 & 14.2465 & 2.85346 \tabularnewline
229 & 15.6 & 10.3246 & 5.27543 \tabularnewline
230 & 18.4 & 13.5381 & 4.86194 \tabularnewline
231 & 19.05 & 13.9788 & 5.07124 \tabularnewline
232 & 18.55 & 13.9151 & 4.63495 \tabularnewline
233 & 19.1 & 18.2184 & 0.88158 \tabularnewline
234 & 13.1 & 14.7926 & -1.69263 \tabularnewline
235 & 12.85 & 15.0965 & -2.24655 \tabularnewline
236 & 9.5 & 17.0257 & -7.52575 \tabularnewline
237 & 4.5 & 3.24821 & 1.25179 \tabularnewline
238 & 11.85 & 11.4956 & 0.35444 \tabularnewline
239 & 13.6 & 13.5218 & 0.0782003 \tabularnewline
240 & 11.7 & 10.3383 & 1.36168 \tabularnewline
241 & 12.4 & 12.7266 & -0.326575 \tabularnewline
242 & 13.35 & 11.4224 & 1.92761 \tabularnewline
243 & 11.4 & 9.41585 & 1.98415 \tabularnewline
244 & 14.9 & 10.5374 & 4.36261 \tabularnewline
245 & 19.9 & 21.9366 & -2.03665 \tabularnewline
246 & 11.2 & 8.9089 & 2.2911 \tabularnewline
247 & 14.6 & 10.9271 & 3.67292 \tabularnewline
248 & 17.6 & 16.6171 & 0.982856 \tabularnewline
249 & 14.05 & 10.4317 & 3.61831 \tabularnewline
250 & 16.1 & 16.4289 & -0.32891 \tabularnewline
251 & 13.35 & 14.0534 & -0.703394 \tabularnewline
252 & 11.85 & 12.3 & -0.449961 \tabularnewline
253 & 11.95 & 10.3393 & 1.61069 \tabularnewline
254 & 14.75 & 10.2639 & 4.48609 \tabularnewline
255 & 15.15 & 16.6186 & -1.46858 \tabularnewline
256 & 13.2 & 9.90489 & 3.29511 \tabularnewline
257 & 16.85 & 20.3699 & -3.51992 \tabularnewline
258 & 7.85 & 12.0635 & -4.21346 \tabularnewline
259 & 7.7 & 7.43617 & 0.263829 \tabularnewline
260 & 12.6 & 16.8605 & -4.26049 \tabularnewline
261 & 7.85 & 9.10249 & -1.25249 \tabularnewline
262 & 10.95 & 10.8202 & 0.129831 \tabularnewline
263 & 12.35 & 14.0095 & -1.6595 \tabularnewline
264 & 9.95 & 8.14521 & 1.80479 \tabularnewline
265 & 14.9 & 11.5237 & 3.37631 \tabularnewline
266 & 16.65 & 16.0987 & 0.551263 \tabularnewline
267 & 13.4 & 11.979 & 1.42102 \tabularnewline
268 & 13.95 & 9.16876 & 4.78124 \tabularnewline
269 & 15.7 & 12.4953 & 3.2047 \tabularnewline
270 & 16.85 & 17.8338 & -0.983762 \tabularnewline
271 & 10.95 & 7.29731 & 3.65269 \tabularnewline
272 & 15.35 & 15.2892 & 0.0608271 \tabularnewline
273 & 12.2 & 8.39525 & 3.80475 \tabularnewline
274 & 15.1 & 10.3799 & 4.72012 \tabularnewline
275 & 17.75 & 15.2373 & 2.51269 \tabularnewline
276 & 15.2 & 14.1647 & 1.0353 \tabularnewline
277 & 14.6 & 10.6969 & 3.90307 \tabularnewline
278 & 16.65 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&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]13.8418[/C][C]-0.94184[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.0015[/C][C]-0.801483[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]14.4693[/C][C]-1.66934[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.2041[/C][C]-5.80407[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.515[/C][C]-5.81504[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.883[/C][C]-1.28297[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]13.9177[/C][C]0.882275[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.6972[/C][C]-0.397204[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.5422[/C][C]-1.44219[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]15.3684[/C][C]-7.16837[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.8064[/C][C]-2.40638[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.6216[/C][C]-7.22163[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.587[/C][C]-0.98696[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]14.3207[/C][C]-2.32065[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]10.6634[/C][C]-4.36339[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.4531[/C][C]-0.153128[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.7313[/C][C]-1.83125[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.4215[/C][C]-3.12154[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.0614[/C][C]-3.46142[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.8378[/C][C]-1.83783[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]14.2245[/C][C]-7.82449[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]13.7398[/C][C]0.0602484[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]15.0191[/C][C]-4.21909[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]14.221[/C][C]-0.420975[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.5846[/C][C]-2.88463[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.7274[/C][C]-4.82744[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.0622[/C][C]3.03776[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.9718[/C][C]0.428216[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]14.6236[/C][C]-4.72356[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]14.1513[/C][C]-2.65127[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.1468[/C][C]-2.84679[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.7071[/C][C]-2.00713[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]13.2313[/C][C]-4.23125[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.197[/C][C]-4.49698[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]13.1817[/C][C]-2.3817[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]14.0648[/C][C]-3.7648[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]13.8912[/C][C]-3.49117[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.9038[/C][C]-0.203815[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]14.9841[/C][C]-5.68407[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]13.9086[/C][C]-2.10862[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.7904[/C][C]-7.89044[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]14.7461[/C][C]-3.34614[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.0976[/C][C]-1.09755[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]14.1104[/C][C]-3.31042[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]11.4955[/C][C]0.804526[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]15.028[/C][C]-3.72804[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]11.9386[/C][C]-0.138614[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.4532[/C][C]-3.5532[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.4417[/C][C]2.25826[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.0105[/C][C]-0.710459[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.1213[/C][C]-1.52132[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.7214[/C][C]-4.02139[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]14.5186[/C][C]-3.61863[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.8323[/C][C]-0.732327[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.3993[/C][C]-0.0993262[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.6759[/C][C]-3.57595[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]13.3828[/C][C]-7.68283[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.2482[/C][C]2.0518[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]11.0212[/C][C]-3.02116[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.7433[/C][C]0.556744[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]15.109[/C][C]-5.80899[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]13.0521[/C][C]-0.552121[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]13.3015[/C][C]-5.70149[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.6471[/C][C]0.252949[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.9132[/C][C]-4.71321[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.8431[/C][C]-3.74309[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.5613[/C][C]-3.46134[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.9862[/C][C]-2.98624[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]16.0374[/C][C]-1.53743[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.2539[/C][C]-0.0539178[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.1998[/C][C]-1.89983[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.1211[/C][C]-1.72112[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.9654[/C][C]-3.16545[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.1101[/C][C]1.48992[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.227[/C][C]0.372958[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.396043[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.6741[/C][C]-0.674082[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]13.7159[/C][C]-1.11591[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.2259[/C][C]-1.02592[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]13.7915[/C][C]-3.8915[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]8.94745[/C][C]-1.24745[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]8.8488[/C][C]1.6512[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]14.9403[/C][C]-1.54027[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]18.384[/C][C]-7.48399[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.93163[/C][C]-3.63163[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]10.9617[/C][C]-0.66174[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.4883[/C][C]-0.688341[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.978[/C][C]-0.77798[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.4681[/C][C]-4.06811[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.67171[/C][C]0.928288[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]13.0163[/C][C]0.183706[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.9423[/C][C]-7.34233[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.20612[/C][C]-2.60612[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.4141[/C][C]-3.51409[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.7658[/C][C]-3.96582[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.0647[/C][C]-2.36468[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.2736[/C][C]-5.27356[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]9.056[/C][C]-1.756[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.0518[/C][C]1.34822[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.6386[/C][C]-5.03858[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.66408[/C][C]-0.764078[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.3095[/C][C]-2.60946[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.3924[/C][C]-2.09239[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.2061[/C][C]-2.90614[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.29907[/C][C]2.30093[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]17.3034[/C][C]-3.10336[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]7.4262[/C][C]1.0738[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.5864[/C][C]-8.08643[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.45202[/C][C]-4.55202[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]9.11947[/C][C]-2.71947[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.9332[/C][C]-1.33324[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]13.2559[/C][C]-1.65587[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]18.1602[/C][C]-7.06022[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.33522[/C][C]1.01478[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]8.8211[/C][C]3.8789[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]14.962[/C][C]3.13799[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]15.6888[/C][C]2.16121[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.9812[/C][C]0.618802[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]11.7355[/C][C]0.86448[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]13.0968[/C][C]4.0032[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]16.9956[/C][C]2.10436[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]14.0151[/C][C]2.08494[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]9.90505[/C][C]3.44495[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.8937[/C][C]3.50627[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]16.9512[/C][C]-2.2512[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.74057[/C][C]0.859434[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]8.68192[/C][C]3.91808[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]14.7867[/C][C]1.41331[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]7.8451[/C][C]5.7549[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.9027[/C][C]0.997275[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.7805[/C][C]0.319463[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]11.741[/C][C]2.75903[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.0068[/C][C]1.14317[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.0249[/C][C]1.72509[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.0414[/C][C]-0.241364[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.1393[/C][C]0.310663[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.12194[/C][C]3.52806[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]20.1792[/C][C]-2.82918[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]3.97854[/C][C]4.62146[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.0209[/C][C]1.37905[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.3765[/C][C]-1.27646[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.37511[/C][C]3.22489[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.1797[/C][C]2.57031[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.0891[/C][C]4.16095[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.954[/C][C]2.69599[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.09[/C][C]3.26003[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.042[/C][C]-0.392001[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.1996[/C][C]1.40039[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.3488[/C][C]2.00117[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.5168[/C][C]2.23316[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.8915[/C][C]-3.64149[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.69331[/C][C]2.20669[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]12.5751[/C][C]3.42493[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.7153[/C][C]3.53466[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.8161[/C][C]2.03391[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]13.0122[/C][C]1.58778[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]10.7671[/C][C]3.08287[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.755[/C][C]2.195[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.5178[/C][C]1.08217[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.802[/C][C]-0.952035[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]7.17046[/C][C]4.57954[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.4361[/C][C]3.01386[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]14.5376[/C][C]1.36244[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]12.3106[/C][C]4.78943[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]12.6007[/C][C]3.49927[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.1108[/C][C]-0.21083[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]5.6623[/C][C]5.2877[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]17.3571[/C][C]1.09287[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.6379[/C][C]1.46206[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.0654[/C][C]-1.06545[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.35619[/C][C]2.99381[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]10.7249[/C][C]5.2251[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]17.5528[/C][C]0.547239[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.7799[/C][C]-0.179872[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.3293[/C][C]0.0706575[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.0694[/C][C]5.33064[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.7641[/C][C]-0.164057[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.55722[/C][C]6.79278[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.9734[/C][C]2.12662[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.575[/C][C]-3.22503[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]6.97519[/C][C]0.624814[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.3691[/C][C]1.03092[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]10.4118[/C][C]3.48825[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]15.3806[/C][C]3.71943[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.9044[/C][C]-0.654442[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.0734[/C][C]2.82659[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]11.8933[/C][C]4.2067[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.2929[/C][C]0.0570975[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.3074[/C][C]-1.15741[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]9.6919[/C][C]2.4581[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.0722[/C][C]-1.47217[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.55971[/C][C]2.79029[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.3891[/C][C]-2.9891[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.45441[/C][C]6.14559[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.8606[/C][C]1.33941[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.298[/C][C]1.30197[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]13.4959[/C][C]1.35407[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]11.8027[/C][C]2.94731[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.7976[/C][C]3.30241[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.223[/C][C]3.67702[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]14.1809[/C][C]2.06911[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.7483[/C][C]1.50174[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.2072[/C][C]0.392794[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.1342[/C][C]2.46579[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]15.5731[/C][C]0.0768502[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.0372[/C][C]2.71281[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.3669[/C][C]-0.766923[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.74506[/C][C]0.104936[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]5.52967[/C][C]7.12033[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]15.3877[/C][C]3.81232[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]16.9305[/C][C]-0.330534[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]10.1928[/C][C]1.00722[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]14.6273[/C][C]0.622651[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]9.50268[/C][C]2.39732[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]10.4961[/C][C]2.70391[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]15.5095[/C][C]0.8405[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.04283[/C][C]3.35717[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]12.5958[/C][C]3.25419[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.1266[/C][C]0.0234295[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.79963[/C][C]2.35037[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.271[/C][C]5.37896[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]20.4367[/C][C]-2.68668[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.84219[/C][C]-1.19219[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.88701[/C][C]2.46299[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]11.5296[/C][C]4.07042[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.9265[/C][C]3.37348[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]12.0591[/C][C]3.14085[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.2465[/C][C]2.85346[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]10.3246[/C][C]5.27543[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]13.5381[/C][C]4.86194[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.9788[/C][C]5.07124[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]13.9151[/C][C]4.63495[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.2184[/C][C]0.88158[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]14.7926[/C][C]-1.69263[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.0965[/C][C]-2.24655[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]17.0257[/C][C]-7.52575[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.24821[/C][C]1.25179[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.4956[/C][C]0.35444[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.5218[/C][C]0.0782003[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]10.3383[/C][C]1.36168[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.7266[/C][C]-0.326575[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]11.4224[/C][C]1.92761[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.41585[/C][C]1.98415[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]10.5374[/C][C]4.36261[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.9366[/C][C]-2.03665[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]8.9089[/C][C]2.2911[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]10.9271[/C][C]3.67292[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.6171[/C][C]0.982856[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.4317[/C][C]3.61831[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.4289[/C][C]-0.32891[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]14.0534[/C][C]-0.703394[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.3[/C][C]-0.449961[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.3393[/C][C]1.61069[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]10.2639[/C][C]4.48609[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]16.6186[/C][C]-1.46858[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]9.90489[/C][C]3.29511[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]20.3699[/C][C]-3.51992[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.0635[/C][C]-4.21346[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.43617[/C][C]0.263829[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.8605[/C][C]-4.26049[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]9.10249[/C][C]-1.25249[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.8202[/C][C]0.129831[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.0095[/C][C]-1.6595[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.14521[/C][C]1.80479[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.5237[/C][C]3.37631[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.0987[/C][C]0.551263[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]11.979[/C][C]1.42102[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]9.16876[/C][C]4.78124[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.4953[/C][C]3.2047[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.8338[/C][C]-0.983762[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.29731[/C][C]3.65269[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.2892[/C][C]0.0608271[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]8.39525[/C][C]3.80475[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.3799[/C][C]4.72012[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.2373[/C][C]2.51269[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]14.1647[/C][C]1.0353[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.6969[/C][C]3.90307[/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=265038&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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	13.8418	-0.94184
2	12.2	13.0015	-0.801483
3	12.8	14.4693	-1.66934
4	7.4	13.2041	-5.80407
5	6.7	12.515	-5.81504
6	12.6	13.883	-1.28297
7	14.8	13.9177	0.882275
8	13.3	13.6972	-0.397204
9	11.1	12.5422	-1.44219
10	8.2	15.3684	-7.16837
11	11.4	13.8064	-2.40638
12	6.4	13.6216	-7.22163
13	10.6	11.587	-0.98696
14	12	14.3207	-2.32065
15	6.3	10.6634	-4.36339
16	11.3	11.4531	-0.153128
17	11.9	13.7313	-1.83125
18	9.3	12.4215	-3.12154
19	9.6	13.0614	-3.46142
20	10	11.8378	-1.83783
21	6.4	14.2245	-7.82449
22	13.8	13.7398	0.0602484
23	10.8	15.0191	-4.21909
24	13.8	14.221	-0.420975
25	11.7	14.5846	-2.88463
26	10.9	15.7274	-4.82744
27	16.1	13.0622	3.03776
28	13.4	12.9718	0.428216
29	9.9	14.6236	-4.72356
30	11.5	14.1513	-2.65127
31	8.3	11.1468	-2.84679
32	11.7	13.7071	-2.00713
33	9	13.2313	-4.23125
34	9.7	14.197	-4.49698
35	10.8	13.1817	-2.3817
36	10.3	14.0648	-3.7648
37	10.4	13.8912	-3.49117
38	12.7	12.9038	-0.203815
39	9.3	14.9841	-5.68407
40	11.8	13.9086	-2.10862
41	5.9	13.7904	-7.89044
42	11.4	14.7461	-3.34614
43	13	14.0976	-1.09755
44	10.8	14.1104	-3.31042
45	12.3	11.4955	0.804526
46	11.3	15.028	-3.72804
47	11.8	11.9386	-0.138614
48	7.9	11.4532	-3.5532
49	12.7	10.4417	2.25826
50	12.3	13.0105	-0.710459
51	11.6	13.1213	-1.52132
52	6.7	10.7214	-4.02139
53	10.9	14.5186	-3.61863
54	12.1	12.8323	-0.732327
55	13.3	13.3993	-0.0993262
56	10.1	13.6759	-3.57595
57	5.7	13.3828	-7.68283
58	14.3	12.2482	2.0518
59	8	11.0212	-3.02116
60	13.3	12.7433	0.556744
61	9.3	15.109	-5.80899
62	12.5	13.0521	-0.552121
63	7.6	13.3015	-5.70149
64	15.9	15.6471	0.252949
65	9.2	13.9132	-4.71321
66	9.1	12.8431	-3.74309
67	11.1	14.5613	-3.46134
68	13	15.9862	-2.98624
69	14.5	16.0374	-1.53743
70	12.2	12.2539	-0.0539178
71	12.3	14.1998	-1.89983
72	11.4	13.1211	-1.72112
73	8.8	11.9654	-3.16545
74	14.6	13.1101	1.48992
75	12.6	12.227	0.372958
76	NA	NA	0.396043
77	13	13.6741	-0.674082
78	12.6	13.7159	-1.11591
79	13.2	14.2259	-1.02592
80	9.9	13.7915	-3.8915
81	7.7	8.94745	-1.24745
82	10.5	8.8488	1.6512
83	13.4	14.9403	-1.54027
84	10.9	18.384	-7.48399
85	4.3	7.93163	-3.63163
86	10.3	10.9617	-0.66174
87	11.8	12.4883	-0.688341
88	11.2	11.978	-0.77798
89	11.4	15.4681	-4.06811
90	8.6	7.67171	0.928288
91	13.2	13.0163	0.183706
92	12.6	19.9423	-7.34233
93	5.6	8.20612	-2.60612
94	9.9	13.4141	-3.51409
95	8.8	12.7658	-3.96582
96	7.7	10.0647	-2.36468
97	9	14.2736	-5.27356
98	7.3	9.056	-1.756
99	11.4	10.0518	1.34822
100	13.6	18.6386	-5.03858
101	7.9	8.66408	-0.764078
102	10.7	13.3095	-2.60946
103	10.3	12.3924	-2.09239
104	8.3	11.2061	-2.90614
105	9.6	7.29907	2.30093
106	14.2	17.3034	-3.10336
107	8.5	7.4262	1.0738
108	13.5	21.5864	-8.08643
109	4.9	9.45202	-4.55202
110	6.4	9.11947	-2.71947
111	9.6	10.9332	-1.33324
112	11.6	13.2559	-1.65587
113	11.1	18.1602	-7.06022
114	4.35	3.33522	1.01478
115	12.7	8.8211	3.8789
116	18.1	14.962	3.13799
117	17.85	15.6888	2.16121
118	16.6	15.9812	0.618802
119	12.6	11.7355	0.86448
120	17.1	13.0968	4.0032
121	19.1	16.9956	2.10436
122	16.1	14.0151	2.08494
123	13.35	9.90505	3.44495
124	18.4	14.8937	3.50627
125	14.7	16.9512	-2.2512
126	10.6	9.74057	0.859434
127	12.6	8.68192	3.91808
128	16.2	14.7867	1.41331
129	13.6	7.8451	5.7549
130	18.9	17.9027	0.997275
131	14.1	13.7805	0.319463
132	14.5	11.741	2.75903
133	16.15	15.0068	1.14317
134	14.75	13.0249	1.72509
135	14.8	15.0414	-0.241364
136	12.45	12.1393	0.310663
137	12.65	9.12194	3.52806
138	17.35	20.1792	-2.82918
139	8.6	3.97854	4.62146
140	18.4	17.0209	1.37905
141	16.1	17.3765	-1.27646
142	11.6	8.37511	3.22489
143	17.75	15.1797	2.57031
144	15.25	11.0891	4.16095
145	17.65	14.954	2.69599
146	16.35	13.09	3.26003
147	17.65	18.042	-0.392001
148	13.6	12.1996	1.40039
149	14.35	12.3488	2.00117
150	14.75	12.5168	2.23316
151	18.25	21.8915	-3.64149
152	9.9	7.69331	2.20669
153	16	12.5751	3.42493
154	18.25	14.7153	3.53466
155	16.85	14.8161	2.03391
156	14.6	13.0122	1.58778
157	13.85	10.7671	3.08287
158	18.95	16.755	2.195
159	15.6	14.5178	1.08217
160	14.85	15.802	-0.952035
161	11.75	7.17046	4.57954
162	18.45	15.4361	3.01386
163	15.9	14.5376	1.36244
164	17.1	12.3106	4.78943
165	16.1	12.6007	3.49927
166	19.9	20.1108	-0.21083
167	10.95	5.6623	5.2877
168	18.45	17.3571	1.09287
169	15.1	13.6379	1.46206
170	15	16.0654	-1.06545
171	11.35	8.35619	2.99381
172	15.95	10.7249	5.2251
173	18.1	17.5528	0.547239
174	14.6	14.7799	-0.179872
175	15.4	15.3293	0.0706575
176	15.4	10.0694	5.33064
177	17.6	17.7641	-0.164057
178	13.35	6.55722	6.79278
179	19.1	16.9734	2.12662
180	15.35	18.575	-3.22503
181	7.6	6.97519	0.624814
182	13.4	12.3691	1.03092
183	13.9	10.4118	3.48825
184	19.1	15.3806	3.71943
185	15.25	15.9044	-0.654442
186	12.9	10.0734	2.82659
187	16.1	11.8933	4.2067
188	17.35	17.2929	0.0570975
189	13.15	14.3074	-1.15741
190	12.15	9.6919	2.4581
191	12.6	14.0722	-1.47217
192	10.35	7.55971	2.79029
193	15.4	18.3891	-2.9891
194	9.6	3.45441	6.14559
195	18.2	16.8606	1.33941
196	13.6	12.298	1.30197
197	14.85	13.4959	1.35407
198	14.75	11.8027	2.94731
199	14.1	10.7976	3.30241
200	14.9	11.223	3.67702
201	16.25	14.1809	2.06911
202	19.25	17.7483	1.50174
203	13.6	13.2072	0.392794
204	13.6	11.1342	2.46579
205	15.65	15.5731	0.0768502
206	12.75	10.0372	2.71281
207	14.6	15.3669	-0.766923
208	9.85	9.74506	0.104936
209	12.65	5.52967	7.12033
210	19.2	15.3877	3.81232
211	16.6	16.9305	-0.330534
212	11.2	10.1928	1.00722
213	15.25	14.6273	0.622651
214	11.9	9.50268	2.39732
215	13.2	10.4961	2.70391
216	16.35	15.5095	0.8405
217	12.4	9.04283	3.35717
218	15.85	12.5958	3.25419
219	18.15	18.1266	0.0234295
220	11.15	8.79963	2.35037
221	15.65	10.271	5.37896
222	17.75	20.4367	-2.68668
223	7.65	8.84219	-1.19219
224	12.35	9.88701	2.46299
225	15.6	11.5296	4.07042
226	19.3	15.9265	3.37348
227	15.2	12.0591	3.14085
228	17.1	14.2465	2.85346
229	15.6	10.3246	5.27543
230	18.4	13.5381	4.86194
231	19.05	13.9788	5.07124
232	18.55	13.9151	4.63495
233	19.1	18.2184	0.88158
234	13.1	14.7926	-1.69263
235	12.85	15.0965	-2.24655
236	9.5	17.0257	-7.52575
237	4.5	3.24821	1.25179
238	11.85	11.4956	0.35444
239	13.6	13.5218	0.0782003
240	11.7	10.3383	1.36168
241	12.4	12.7266	-0.326575
242	13.35	11.4224	1.92761
243	11.4	9.41585	1.98415
244	14.9	10.5374	4.36261
245	19.9	21.9366	-2.03665
246	11.2	8.9089	2.2911
247	14.6	10.9271	3.67292
248	17.6	16.6171	0.982856
249	14.05	10.4317	3.61831
250	16.1	16.4289	-0.32891
251	13.35	14.0534	-0.703394
252	11.85	12.3	-0.449961
253	11.95	10.3393	1.61069
254	14.75	10.2639	4.48609
255	15.15	16.6186	-1.46858
256	13.2	9.90489	3.29511
257	16.85	20.3699	-3.51992
258	7.85	12.0635	-4.21346
259	7.7	7.43617	0.263829
260	12.6	16.8605	-4.26049
261	7.85	9.10249	-1.25249
262	10.95	10.8202	0.129831
263	12.35	14.0095	-1.6595
264	9.95	8.14521	1.80479
265	14.9	11.5237	3.37631
266	16.65	16.0987	0.551263
267	13.4	11.979	1.42102
268	13.95	9.16876	4.78124
269	15.7	12.4953	3.2047
270	16.85	17.8338	-0.983762
271	10.95	7.29731	3.65269
272	15.35	15.2892	0.0608271
273	12.2	8.39525	3.80475
274	15.1	10.3799	4.72012
275	17.75	15.2373	2.51269
276	15.2	14.1647	1.0353
277	14.6	10.6969	3.90307
278	16.65	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
18	0.250835	0.50167	0.749165
19	0.185714	0.371427	0.814286
20	0.111605	0.22321	0.888395
21	0.168625	0.33725	0.831375
22	0.0984528	0.196906	0.901547
23	0.0756924	0.151385	0.924308
24	0.0579922	0.115984	0.942008
25	0.0327096	0.0654192	0.96729
26	0.0282312	0.0564623	0.971769
27	0.0166804	0.0333607	0.98332
28	0.0147968	0.0295937	0.985203
29	0.00957494	0.0191499	0.990425
30	0.00521324	0.0104265	0.994787
31	0.0028397	0.00567941	0.99716
32	0.00160586	0.00321171	0.998394
33	0.00359745	0.0071949	0.996403
34	0.0385729	0.0771458	0.961427
35	0.0278583	0.0557166	0.972142
36	0.0198865	0.0397729	0.980114
37	0.0208312	0.0416624	0.979169
38	0.0165057	0.0330114	0.983494
39	0.018527	0.0370539	0.981473
40	0.0132222	0.0264445	0.986778
41	0.0218188	0.0436376	0.978181
42	0.0166197	0.0332395	0.98338
43	0.0136734	0.0273469	0.986327
44	0.0185381	0.0370762	0.981462
45	0.0150879	0.0301758	0.984912
46	0.0121146	0.0242292	0.987885
47	0.0111766	0.0223531	0.988823
48	0.00830904	0.0166181	0.991691
49	0.0121593	0.0243186	0.987841
50	0.0127802	0.0255605	0.98722
51	0.00952366	0.0190473	0.990476
52	0.00919913	0.0183983	0.990801
53	0.00705048	0.014101	0.99295
54	0.00725011	0.0145002	0.99275
55	0.0145414	0.0290827	0.985459
56	0.0132306	0.0264612	0.986769
57	0.0481909	0.0963818	0.951809
58	0.042945	0.08589	0.957055
59	0.0346543	0.0693085	0.965346
60	0.0342201	0.0684402	0.96578
61	0.0410137	0.0820274	0.958986
62	0.0324602	0.0649204	0.96754
63	0.0576464	0.115293	0.942354
64	0.0666399	0.13328	0.93336
65	0.0841874	0.168375	0.915813
66	0.0736934	0.147387	0.926307
67	0.0708012	0.141602	0.929199
68	0.0730674	0.146135	0.926933
69	0.0840093	0.168019	0.915991
70	0.0725432	0.145086	0.927457
71	0.0649345	0.129869	0.935065
72	0.0578419	0.115684	0.942158
73	0.0523051	0.10461	0.947695
74	0.0869388	0.173878	0.913061
75	0.0722366	0.144473	0.927763
76	0.0608715	0.121743	0.939129
77	0.0528642	0.105728	0.947136
78	0.0482569	0.0965137	0.951743
79	0.0390341	0.0780682	0.960966
80	0.0411729	0.0823459	0.958827
81	0.0342748	0.0685496	0.965725
82	0.0384569	0.0769139	0.961543
83	0.0330371	0.0660742	0.966963
84	0.07795	0.1559	0.92205
85	0.0751713	0.150343	0.924829
86	0.0654839	0.130968	0.934516
87	0.0575346	0.115069	0.942465
88	0.0563347	0.112669	0.943665
89	0.060055	0.12011	0.939945
90	0.0663396	0.132679	0.93366
91	0.0674667	0.134933	0.932533
92	0.149137	0.298274	0.850863
93	0.144055	0.288109	0.855945
94	0.142704	0.285408	0.857296
95	0.144751	0.289502	0.855249
96	0.144068	0.288136	0.855932
97	0.219559	0.439119	0.780441
98	0.200836	0.401673	0.799164
99	0.200532	0.401063	0.799468
100	0.2399	0.4798	0.7601
101	0.219595	0.43919	0.780405
102	0.222766	0.445532	0.777234
103	0.239626	0.479252	0.760374
104	0.25129	0.502579	0.74871
105	0.262933	0.525866	0.737067
106	0.274842	0.549685	0.725158
107	0.336345	0.672691	0.663655
108	0.579503	0.840995	0.420497
109	0.635173	0.729654	0.364827
110	0.622641	0.754718	0.377359
111	0.627971	0.744059	0.372029
112	0.648258	0.703483	0.351742
113	0.791885	0.41623	0.208115
114	0.829869	0.340261	0.170131
115	0.891862	0.216276	0.108138
116	0.924149	0.151703	0.0758513
117	0.945557	0.108887	0.0544434
118	0.946595	0.106811	0.0534055
119	0.955962	0.0880758	0.0440379
120	0.970694	0.0586118	0.0293059
121	0.972943	0.054114	0.027057
122	0.978112	0.0437764	0.0218882
123	0.987973	0.0240542	0.0120271
124	0.992719	0.0145616	0.00728081
125	0.992628	0.0147441	0.00737207
126	0.99161	0.0167809	0.00839045
127	0.992892	0.0142167	0.00710837
128	0.9922	0.0156008	0.00780039
129	0.996504	0.00699146	0.00349573
130	0.996331	0.00733874	0.00366937
131	0.995857	0.00828601	0.00414301
132	0.995348	0.00930452	0.00465226
133	0.994626	0.0107485	0.00537427
134	0.995718	0.00856407	0.00428203
135	0.994732	0.0105361	0.00526804
136	0.994231	0.0115374	0.00576871
137	0.99532	0.00936079	0.0046804
138	0.99491	0.010179	0.00508952
139	0.996688	0.00662404	0.00331202
140	0.996157	0.00768517	0.00384259
141	0.995123	0.00975423	0.00487712
142	0.994986	0.010027	0.00501351
143	0.99531	0.00937952	0.00468976
144	0.996505	0.00699068	0.00349534
145	0.996104	0.0077917	0.00389585
146	0.996187	0.00762645	0.00381323
147	0.995186	0.00962871	0.00481436
148	0.994202	0.0115967	0.00579833
149	0.994438	0.0111248	0.00556239
150	0.993708	0.0125844	0.00629218
151	0.996792	0.00641631	0.00320816
152	0.996229	0.00754258	0.00377129
153	0.996633	0.00673422	0.00336711
154	0.996426	0.0071473	0.00357365
155	0.99619	0.00762029	0.00381015
156	0.99526	0.00948052	0.00474026
157	0.994813	0.0103731	0.00518654
158	0.994266	0.0114682	0.00573409
159	0.9931	0.0138002	0.00690008
160	0.992599	0.0148027	0.00740133
161	0.994825	0.0103499	0.00517494
162	0.995109	0.00978201	0.004891
163	0.995279	0.00944138	0.00472069
164	0.998561	0.00287821	0.00143911
165	0.998715	0.00257085	0.00128542
166	0.998377	0.00324561	0.0016228
167	0.998977	0.0020465	0.00102325
168	0.998714	0.00257273	0.00128636
169	0.998312	0.00337536	0.00168768
170	0.997821	0.00435834	0.00217917
171	0.997878	0.00424399	0.002122
172	0.998592	0.00281666	0.00140833
173	0.998336	0.00332807	0.00166403
174	0.997871	0.00425787	0.00212894
175	0.997378	0.00524468	0.00262234
176	0.998448	0.00310314	0.00155157
177	0.997927	0.00414538	0.00207269
178	0.998854	0.00229277	0.00114639
179	0.998499	0.00300189	0.00150094
180	0.998707	0.00258551	0.00129276
181	0.998224	0.00355118	0.00177559
182	0.997613	0.00477355	0.00238678
183	0.997418	0.00516487	0.00258244
184	0.997381	0.00523785	0.00261892
185	0.99747	0.00505938	0.00252969
186	0.996898	0.00620493	0.00310246
187	0.997244	0.00551284	0.00275642
188	0.996396	0.00720761	0.00360381
189	0.99597	0.00805997	0.00402998
190	0.995544	0.00891168	0.00445584
191	0.994351	0.0112982	0.00564912
192	0.994055	0.0118895	0.00594474
193	0.994927	0.0101451	0.00507255
194	0.997208	0.00558335	0.00279167
195	0.996501	0.00699831	0.00349916
196	0.995877	0.00824652	0.00412326
197	0.994804	0.0103928	0.00519638
198	0.99404	0.0119194	0.0059597
199	0.994249	0.0115017	0.00575086
200	0.994499	0.0110023	0.00550117
201	0.992677	0.0146466	0.00732331
202	0.991986	0.0160283	0.00801415
203	0.990113	0.0197747	0.00988737
204	0.988006	0.0239883	0.0119941
205	0.986672	0.0266554	0.0133277
206	0.983911	0.032178	0.016089
207	0.97885	0.0423003	0.0211501
208	0.972507	0.0549861	0.027493
209	0.97778	0.0444395	0.0222198
210	0.978313	0.0433746	0.0216873
211	0.972375	0.0552507	0.0276253
212	0.964294	0.0714121	0.0357061
213	0.95904	0.0819205	0.0409603
214	0.957251	0.0854976	0.0427488
215	0.949252	0.101495	0.0507475
216	0.935662	0.128676	0.0643378
217	0.933523	0.132954	0.0664769
218	0.92214	0.155721	0.0778604
219	0.904531	0.190939	0.0954693
220	0.889076	0.221849	0.110924
221	0.89427	0.21146	0.10573
222	0.880745	0.23851	0.119255
223	0.85433	0.291339	0.14567
224	0.831493	0.337014	0.168507
225	0.809416	0.381167	0.190584
226	0.852417	0.295166	0.147583
227	0.830331	0.339338	0.169669
228	0.802828	0.394344	0.197172
229	0.819381	0.361237	0.180619
230	0.822747	0.354507	0.177253
231	0.82591	0.348179	0.17409
232	0.826439	0.347123	0.173561
233	0.787393	0.425215	0.212607
234	0.827384	0.345232	0.172616
235	0.82272	0.354559	0.17728
236	0.954818	0.090364	0.045182
237	0.945115	0.109769	0.0548846
238	0.92765	0.144701	0.0723505
239	0.904752	0.190496	0.0952479
240	0.874263	0.251475	0.125737
241	0.840692	0.318617	0.159308
242	0.803296	0.393407	0.196704
243	0.756188	0.487624	0.243812
244	0.744194	0.511613	0.255806
245	0.68999	0.620021	0.31001
246	0.62444	0.751119	0.37556
247	0.560566	0.878869	0.439434
248	0.49166	0.983321	0.50834
249	0.51688	0.96624	0.48312
250	0.46496	0.929921	0.53504
251	0.398042	0.796084	0.601958
252	0.337132	0.674264	0.662868
253	0.264692	0.529384	0.735308
254	0.634443	0.731114	0.365557
255	0.580288	0.839424	0.419712
256	0.513353	0.973294	0.486647
257	0.498107	0.996214	0.501893
258	0.917734	0.164533	0.0822664
259	0.814543	0.370913	0.185457
260	0.91928	0.16144	0.0807201

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
18 & 0.250835 & 0.50167 & 0.749165 \tabularnewline
19 & 0.185714 & 0.371427 & 0.814286 \tabularnewline
20 & 0.111605 & 0.22321 & 0.888395 \tabularnewline
21 & 0.168625 & 0.33725 & 0.831375 \tabularnewline
22 & 0.0984528 & 0.196906 & 0.901547 \tabularnewline
23 & 0.0756924 & 0.151385 & 0.924308 \tabularnewline
24 & 0.0579922 & 0.115984 & 0.942008 \tabularnewline
25 & 0.0327096 & 0.0654192 & 0.96729 \tabularnewline
26 & 0.0282312 & 0.0564623 & 0.971769 \tabularnewline
27 & 0.0166804 & 0.0333607 & 0.98332 \tabularnewline
28 & 0.0147968 & 0.0295937 & 0.985203 \tabularnewline
29 & 0.00957494 & 0.0191499 & 0.990425 \tabularnewline
30 & 0.00521324 & 0.0104265 & 0.994787 \tabularnewline
31 & 0.0028397 & 0.00567941 & 0.99716 \tabularnewline
32 & 0.00160586 & 0.00321171 & 0.998394 \tabularnewline
33 & 0.00359745 & 0.0071949 & 0.996403 \tabularnewline
34 & 0.0385729 & 0.0771458 & 0.961427 \tabularnewline
35 & 0.0278583 & 0.0557166 & 0.972142 \tabularnewline
36 & 0.0198865 & 0.0397729 & 0.980114 \tabularnewline
37 & 0.0208312 & 0.0416624 & 0.979169 \tabularnewline
38 & 0.0165057 & 0.0330114 & 0.983494 \tabularnewline
39 & 0.018527 & 0.0370539 & 0.981473 \tabularnewline
40 & 0.0132222 & 0.0264445 & 0.986778 \tabularnewline
41 & 0.0218188 & 0.0436376 & 0.978181 \tabularnewline
42 & 0.0166197 & 0.0332395 & 0.98338 \tabularnewline
43 & 0.0136734 & 0.0273469 & 0.986327 \tabularnewline
44 & 0.0185381 & 0.0370762 & 0.981462 \tabularnewline
45 & 0.0150879 & 0.0301758 & 0.984912 \tabularnewline
46 & 0.0121146 & 0.0242292 & 0.987885 \tabularnewline
47 & 0.0111766 & 0.0223531 & 0.988823 \tabularnewline
48 & 0.00830904 & 0.0166181 & 0.991691 \tabularnewline
49 & 0.0121593 & 0.0243186 & 0.987841 \tabularnewline
50 & 0.0127802 & 0.0255605 & 0.98722 \tabularnewline
51 & 0.00952366 & 0.0190473 & 0.990476 \tabularnewline
52 & 0.00919913 & 0.0183983 & 0.990801 \tabularnewline
53 & 0.00705048 & 0.014101 & 0.99295 \tabularnewline
54 & 0.00725011 & 0.0145002 & 0.99275 \tabularnewline
55 & 0.0145414 & 0.0290827 & 0.985459 \tabularnewline
56 & 0.0132306 & 0.0264612 & 0.986769 \tabularnewline
57 & 0.0481909 & 0.0963818 & 0.951809 \tabularnewline
58 & 0.042945 & 0.08589 & 0.957055 \tabularnewline
59 & 0.0346543 & 0.0693085 & 0.965346 \tabularnewline
60 & 0.0342201 & 0.0684402 & 0.96578 \tabularnewline
61 & 0.0410137 & 0.0820274 & 0.958986 \tabularnewline
62 & 0.0324602 & 0.0649204 & 0.96754 \tabularnewline
63 & 0.0576464 & 0.115293 & 0.942354 \tabularnewline
64 & 0.0666399 & 0.13328 & 0.93336 \tabularnewline
65 & 0.0841874 & 0.168375 & 0.915813 \tabularnewline
66 & 0.0736934 & 0.147387 & 0.926307 \tabularnewline
67 & 0.0708012 & 0.141602 & 0.929199 \tabularnewline
68 & 0.0730674 & 0.146135 & 0.926933 \tabularnewline
69 & 0.0840093 & 0.168019 & 0.915991 \tabularnewline
70 & 0.0725432 & 0.145086 & 0.927457 \tabularnewline
71 & 0.0649345 & 0.129869 & 0.935065 \tabularnewline
72 & 0.0578419 & 0.115684 & 0.942158 \tabularnewline
73 & 0.0523051 & 0.10461 & 0.947695 \tabularnewline
74 & 0.0869388 & 0.173878 & 0.913061 \tabularnewline
75 & 0.0722366 & 0.144473 & 0.927763 \tabularnewline
76 & 0.0608715 & 0.121743 & 0.939129 \tabularnewline
77 & 0.0528642 & 0.105728 & 0.947136 \tabularnewline
78 & 0.0482569 & 0.0965137 & 0.951743 \tabularnewline
79 & 0.0390341 & 0.0780682 & 0.960966 \tabularnewline
80 & 0.0411729 & 0.0823459 & 0.958827 \tabularnewline
81 & 0.0342748 & 0.0685496 & 0.965725 \tabularnewline
82 & 0.0384569 & 0.0769139 & 0.961543 \tabularnewline
83 & 0.0330371 & 0.0660742 & 0.966963 \tabularnewline
84 & 0.07795 & 0.1559 & 0.92205 \tabularnewline
85 & 0.0751713 & 0.150343 & 0.924829 \tabularnewline
86 & 0.0654839 & 0.130968 & 0.934516 \tabularnewline
87 & 0.0575346 & 0.115069 & 0.942465 \tabularnewline
88 & 0.0563347 & 0.112669 & 0.943665 \tabularnewline
89 & 0.060055 & 0.12011 & 0.939945 \tabularnewline
90 & 0.0663396 & 0.132679 & 0.93366 \tabularnewline
91 & 0.0674667 & 0.134933 & 0.932533 \tabularnewline
92 & 0.149137 & 0.298274 & 0.850863 \tabularnewline
93 & 0.144055 & 0.288109 & 0.855945 \tabularnewline
94 & 0.142704 & 0.285408 & 0.857296 \tabularnewline
95 & 0.144751 & 0.289502 & 0.855249 \tabularnewline
96 & 0.144068 & 0.288136 & 0.855932 \tabularnewline
97 & 0.219559 & 0.439119 & 0.780441 \tabularnewline
98 & 0.200836 & 0.401673 & 0.799164 \tabularnewline
99 & 0.200532 & 0.401063 & 0.799468 \tabularnewline
100 & 0.2399 & 0.4798 & 0.7601 \tabularnewline
101 & 0.219595 & 0.43919 & 0.780405 \tabularnewline
102 & 0.222766 & 0.445532 & 0.777234 \tabularnewline
103 & 0.239626 & 0.479252 & 0.760374 \tabularnewline
104 & 0.25129 & 0.502579 & 0.74871 \tabularnewline
105 & 0.262933 & 0.525866 & 0.737067 \tabularnewline
106 & 0.274842 & 0.549685 & 0.725158 \tabularnewline
107 & 0.336345 & 0.672691 & 0.663655 \tabularnewline
108 & 0.579503 & 0.840995 & 0.420497 \tabularnewline
109 & 0.635173 & 0.729654 & 0.364827 \tabularnewline
110 & 0.622641 & 0.754718 & 0.377359 \tabularnewline
111 & 0.627971 & 0.744059 & 0.372029 \tabularnewline
112 & 0.648258 & 0.703483 & 0.351742 \tabularnewline
113 & 0.791885 & 0.41623 & 0.208115 \tabularnewline
114 & 0.829869 & 0.340261 & 0.170131 \tabularnewline
115 & 0.891862 & 0.216276 & 0.108138 \tabularnewline
116 & 0.924149 & 0.151703 & 0.0758513 \tabularnewline
117 & 0.945557 & 0.108887 & 0.0544434 \tabularnewline
118 & 0.946595 & 0.106811 & 0.0534055 \tabularnewline
119 & 0.955962 & 0.0880758 & 0.0440379 \tabularnewline
120 & 0.970694 & 0.0586118 & 0.0293059 \tabularnewline
121 & 0.972943 & 0.054114 & 0.027057 \tabularnewline
122 & 0.978112 & 0.0437764 & 0.0218882 \tabularnewline
123 & 0.987973 & 0.0240542 & 0.0120271 \tabularnewline
124 & 0.992719 & 0.0145616 & 0.00728081 \tabularnewline
125 & 0.992628 & 0.0147441 & 0.00737207 \tabularnewline
126 & 0.99161 & 0.0167809 & 0.00839045 \tabularnewline
127 & 0.992892 & 0.0142167 & 0.00710837 \tabularnewline
128 & 0.9922 & 0.0156008 & 0.00780039 \tabularnewline
129 & 0.996504 & 0.00699146 & 0.00349573 \tabularnewline
130 & 0.996331 & 0.00733874 & 0.00366937 \tabularnewline
131 & 0.995857 & 0.00828601 & 0.00414301 \tabularnewline
132 & 0.995348 & 0.00930452 & 0.00465226 \tabularnewline
133 & 0.994626 & 0.0107485 & 0.00537427 \tabularnewline
134 & 0.995718 & 0.00856407 & 0.00428203 \tabularnewline
135 & 0.994732 & 0.0105361 & 0.00526804 \tabularnewline
136 & 0.994231 & 0.0115374 & 0.00576871 \tabularnewline
137 & 0.99532 & 0.00936079 & 0.0046804 \tabularnewline
138 & 0.99491 & 0.010179 & 0.00508952 \tabularnewline
139 & 0.996688 & 0.00662404 & 0.00331202 \tabularnewline
140 & 0.996157 & 0.00768517 & 0.00384259 \tabularnewline
141 & 0.995123 & 0.00975423 & 0.00487712 \tabularnewline
142 & 0.994986 & 0.010027 & 0.00501351 \tabularnewline
143 & 0.99531 & 0.00937952 & 0.00468976 \tabularnewline
144 & 0.996505 & 0.00699068 & 0.00349534 \tabularnewline
145 & 0.996104 & 0.0077917 & 0.00389585 \tabularnewline
146 & 0.996187 & 0.00762645 & 0.00381323 \tabularnewline
147 & 0.995186 & 0.00962871 & 0.00481436 \tabularnewline
148 & 0.994202 & 0.0115967 & 0.00579833 \tabularnewline
149 & 0.994438 & 0.0111248 & 0.00556239 \tabularnewline
150 & 0.993708 & 0.0125844 & 0.00629218 \tabularnewline
151 & 0.996792 & 0.00641631 & 0.00320816 \tabularnewline
152 & 0.996229 & 0.00754258 & 0.00377129 \tabularnewline
153 & 0.996633 & 0.00673422 & 0.00336711 \tabularnewline
154 & 0.996426 & 0.0071473 & 0.00357365 \tabularnewline
155 & 0.99619 & 0.00762029 & 0.00381015 \tabularnewline
156 & 0.99526 & 0.00948052 & 0.00474026 \tabularnewline
157 & 0.994813 & 0.0103731 & 0.00518654 \tabularnewline
158 & 0.994266 & 0.0114682 & 0.00573409 \tabularnewline
159 & 0.9931 & 0.0138002 & 0.00690008 \tabularnewline
160 & 0.992599 & 0.0148027 & 0.00740133 \tabularnewline
161 & 0.994825 & 0.0103499 & 0.00517494 \tabularnewline
162 & 0.995109 & 0.00978201 & 0.004891 \tabularnewline
163 & 0.995279 & 0.00944138 & 0.00472069 \tabularnewline
164 & 0.998561 & 0.00287821 & 0.00143911 \tabularnewline
165 & 0.998715 & 0.00257085 & 0.00128542 \tabularnewline
166 & 0.998377 & 0.00324561 & 0.0016228 \tabularnewline
167 & 0.998977 & 0.0020465 & 0.00102325 \tabularnewline
168 & 0.998714 & 0.00257273 & 0.00128636 \tabularnewline
169 & 0.998312 & 0.00337536 & 0.00168768 \tabularnewline
170 & 0.997821 & 0.00435834 & 0.00217917 \tabularnewline
171 & 0.997878 & 0.00424399 & 0.002122 \tabularnewline
172 & 0.998592 & 0.00281666 & 0.00140833 \tabularnewline
173 & 0.998336 & 0.00332807 & 0.00166403 \tabularnewline
174 & 0.997871 & 0.00425787 & 0.00212894 \tabularnewline
175 & 0.997378 & 0.00524468 & 0.00262234 \tabularnewline
176 & 0.998448 & 0.00310314 & 0.00155157 \tabularnewline
177 & 0.997927 & 0.00414538 & 0.00207269 \tabularnewline
178 & 0.998854 & 0.00229277 & 0.00114639 \tabularnewline
179 & 0.998499 & 0.00300189 & 0.00150094 \tabularnewline
180 & 0.998707 & 0.00258551 & 0.00129276 \tabularnewline
181 & 0.998224 & 0.00355118 & 0.00177559 \tabularnewline
182 & 0.997613 & 0.00477355 & 0.00238678 \tabularnewline
183 & 0.997418 & 0.00516487 & 0.00258244 \tabularnewline
184 & 0.997381 & 0.00523785 & 0.00261892 \tabularnewline
185 & 0.99747 & 0.00505938 & 0.00252969 \tabularnewline
186 & 0.996898 & 0.00620493 & 0.00310246 \tabularnewline
187 & 0.997244 & 0.00551284 & 0.00275642 \tabularnewline
188 & 0.996396 & 0.00720761 & 0.00360381 \tabularnewline
189 & 0.99597 & 0.00805997 & 0.00402998 \tabularnewline
190 & 0.995544 & 0.00891168 & 0.00445584 \tabularnewline
191 & 0.994351 & 0.0112982 & 0.00564912 \tabularnewline
192 & 0.994055 & 0.0118895 & 0.00594474 \tabularnewline
193 & 0.994927 & 0.0101451 & 0.00507255 \tabularnewline
194 & 0.997208 & 0.00558335 & 0.00279167 \tabularnewline
195 & 0.996501 & 0.00699831 & 0.00349916 \tabularnewline
196 & 0.995877 & 0.00824652 & 0.00412326 \tabularnewline
197 & 0.994804 & 0.0103928 & 0.00519638 \tabularnewline
198 & 0.99404 & 0.0119194 & 0.0059597 \tabularnewline
199 & 0.994249 & 0.0115017 & 0.00575086 \tabularnewline
200 & 0.994499 & 0.0110023 & 0.00550117 \tabularnewline
201 & 0.992677 & 0.0146466 & 0.00732331 \tabularnewline
202 & 0.991986 & 0.0160283 & 0.00801415 \tabularnewline
203 & 0.990113 & 0.0197747 & 0.00988737 \tabularnewline
204 & 0.988006 & 0.0239883 & 0.0119941 \tabularnewline
205 & 0.986672 & 0.0266554 & 0.0133277 \tabularnewline
206 & 0.983911 & 0.032178 & 0.016089 \tabularnewline
207 & 0.97885 & 0.0423003 & 0.0211501 \tabularnewline
208 & 0.972507 & 0.0549861 & 0.027493 \tabularnewline
209 & 0.97778 & 0.0444395 & 0.0222198 \tabularnewline
210 & 0.978313 & 0.0433746 & 0.0216873 \tabularnewline
211 & 0.972375 & 0.0552507 & 0.0276253 \tabularnewline
212 & 0.964294 & 0.0714121 & 0.0357061 \tabularnewline
213 & 0.95904 & 0.0819205 & 0.0409603 \tabularnewline
214 & 0.957251 & 0.0854976 & 0.0427488 \tabularnewline
215 & 0.949252 & 0.101495 & 0.0507475 \tabularnewline
216 & 0.935662 & 0.128676 & 0.0643378 \tabularnewline
217 & 0.933523 & 0.132954 & 0.0664769 \tabularnewline
218 & 0.92214 & 0.155721 & 0.0778604 \tabularnewline
219 & 0.904531 & 0.190939 & 0.0954693 \tabularnewline
220 & 0.889076 & 0.221849 & 0.110924 \tabularnewline
221 & 0.89427 & 0.21146 & 0.10573 \tabularnewline
222 & 0.880745 & 0.23851 & 0.119255 \tabularnewline
223 & 0.85433 & 0.291339 & 0.14567 \tabularnewline
224 & 0.831493 & 0.337014 & 0.168507 \tabularnewline
225 & 0.809416 & 0.381167 & 0.190584 \tabularnewline
226 & 0.852417 & 0.295166 & 0.147583 \tabularnewline
227 & 0.830331 & 0.339338 & 0.169669 \tabularnewline
228 & 0.802828 & 0.394344 & 0.197172 \tabularnewline
229 & 0.819381 & 0.361237 & 0.180619 \tabularnewline
230 & 0.822747 & 0.354507 & 0.177253 \tabularnewline
231 & 0.82591 & 0.348179 & 0.17409 \tabularnewline
232 & 0.826439 & 0.347123 & 0.173561 \tabularnewline
233 & 0.787393 & 0.425215 & 0.212607 \tabularnewline
234 & 0.827384 & 0.345232 & 0.172616 \tabularnewline
235 & 0.82272 & 0.354559 & 0.17728 \tabularnewline
236 & 0.954818 & 0.090364 & 0.045182 \tabularnewline
237 & 0.945115 & 0.109769 & 0.0548846 \tabularnewline
238 & 0.92765 & 0.144701 & 0.0723505 \tabularnewline
239 & 0.904752 & 0.190496 & 0.0952479 \tabularnewline
240 & 0.874263 & 0.251475 & 0.125737 \tabularnewline
241 & 0.840692 & 0.318617 & 0.159308 \tabularnewline
242 & 0.803296 & 0.393407 & 0.196704 \tabularnewline
243 & 0.756188 & 0.487624 & 0.243812 \tabularnewline
244 & 0.744194 & 0.511613 & 0.255806 \tabularnewline
245 & 0.68999 & 0.620021 & 0.31001 \tabularnewline
246 & 0.62444 & 0.751119 & 0.37556 \tabularnewline
247 & 0.560566 & 0.878869 & 0.439434 \tabularnewline
248 & 0.49166 & 0.983321 & 0.50834 \tabularnewline
249 & 0.51688 & 0.96624 & 0.48312 \tabularnewline
250 & 0.46496 & 0.929921 & 0.53504 \tabularnewline
251 & 0.398042 & 0.796084 & 0.601958 \tabularnewline
252 & 0.337132 & 0.674264 & 0.662868 \tabularnewline
253 & 0.264692 & 0.529384 & 0.735308 \tabularnewline
254 & 0.634443 & 0.731114 & 0.365557 \tabularnewline
255 & 0.580288 & 0.839424 & 0.419712 \tabularnewline
256 & 0.513353 & 0.973294 & 0.486647 \tabularnewline
257 & 0.498107 & 0.996214 & 0.501893 \tabularnewline
258 & 0.917734 & 0.164533 & 0.0822664 \tabularnewline
259 & 0.814543 & 0.370913 & 0.185457 \tabularnewline
260 & 0.91928 & 0.16144 & 0.0807201 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]18[/C][C]0.250835[/C][C]0.50167[/C][C]0.749165[/C][/ROW]
[ROW][C]19[/C][C]0.185714[/C][C]0.371427[/C][C]0.814286[/C][/ROW]
[ROW][C]20[/C][C]0.111605[/C][C]0.22321[/C][C]0.888395[/C][/ROW]
[ROW][C]21[/C][C]0.168625[/C][C]0.33725[/C][C]0.831375[/C][/ROW]
[ROW][C]22[/C][C]0.0984528[/C][C]0.196906[/C][C]0.901547[/C][/ROW]
[ROW][C]23[/C][C]0.0756924[/C][C]0.151385[/C][C]0.924308[/C][/ROW]
[ROW][C]24[/C][C]0.0579922[/C][C]0.115984[/C][C]0.942008[/C][/ROW]
[ROW][C]25[/C][C]0.0327096[/C][C]0.0654192[/C][C]0.96729[/C][/ROW]
[ROW][C]26[/C][C]0.0282312[/C][C]0.0564623[/C][C]0.971769[/C][/ROW]
[ROW][C]27[/C][C]0.0166804[/C][C]0.0333607[/C][C]0.98332[/C][/ROW]
[ROW][C]28[/C][C]0.0147968[/C][C]0.0295937[/C][C]0.985203[/C][/ROW]
[ROW][C]29[/C][C]0.00957494[/C][C]0.0191499[/C][C]0.990425[/C][/ROW]
[ROW][C]30[/C][C]0.00521324[/C][C]0.0104265[/C][C]0.994787[/C][/ROW]
[ROW][C]31[/C][C]0.0028397[/C][C]0.00567941[/C][C]0.99716[/C][/ROW]
[ROW][C]32[/C][C]0.00160586[/C][C]0.00321171[/C][C]0.998394[/C][/ROW]
[ROW][C]33[/C][C]0.00359745[/C][C]0.0071949[/C][C]0.996403[/C][/ROW]
[ROW][C]34[/C][C]0.0385729[/C][C]0.0771458[/C][C]0.961427[/C][/ROW]
[ROW][C]35[/C][C]0.0278583[/C][C]0.0557166[/C][C]0.972142[/C][/ROW]
[ROW][C]36[/C][C]0.0198865[/C][C]0.0397729[/C][C]0.980114[/C][/ROW]
[ROW][C]37[/C][C]0.0208312[/C][C]0.0416624[/C][C]0.979169[/C][/ROW]
[ROW][C]38[/C][C]0.0165057[/C][C]0.0330114[/C][C]0.983494[/C][/ROW]
[ROW][C]39[/C][C]0.018527[/C][C]0.0370539[/C][C]0.981473[/C][/ROW]
[ROW][C]40[/C][C]0.0132222[/C][C]0.0264445[/C][C]0.986778[/C][/ROW]
[ROW][C]41[/C][C]0.0218188[/C][C]0.0436376[/C][C]0.978181[/C][/ROW]
[ROW][C]42[/C][C]0.0166197[/C][C]0.0332395[/C][C]0.98338[/C][/ROW]
[ROW][C]43[/C][C]0.0136734[/C][C]0.0273469[/C][C]0.986327[/C][/ROW]
[ROW][C]44[/C][C]0.0185381[/C][C]0.0370762[/C][C]0.981462[/C][/ROW]
[ROW][C]45[/C][C]0.0150879[/C][C]0.0301758[/C][C]0.984912[/C][/ROW]
[ROW][C]46[/C][C]0.0121146[/C][C]0.0242292[/C][C]0.987885[/C][/ROW]
[ROW][C]47[/C][C]0.0111766[/C][C]0.0223531[/C][C]0.988823[/C][/ROW]
[ROW][C]48[/C][C]0.00830904[/C][C]0.0166181[/C][C]0.991691[/C][/ROW]
[ROW][C]49[/C][C]0.0121593[/C][C]0.0243186[/C][C]0.987841[/C][/ROW]
[ROW][C]50[/C][C]0.0127802[/C][C]0.0255605[/C][C]0.98722[/C][/ROW]
[ROW][C]51[/C][C]0.00952366[/C][C]0.0190473[/C][C]0.990476[/C][/ROW]
[ROW][C]52[/C][C]0.00919913[/C][C]0.0183983[/C][C]0.990801[/C][/ROW]
[ROW][C]53[/C][C]0.00705048[/C][C]0.014101[/C][C]0.99295[/C][/ROW]
[ROW][C]54[/C][C]0.00725011[/C][C]0.0145002[/C][C]0.99275[/C][/ROW]
[ROW][C]55[/C][C]0.0145414[/C][C]0.0290827[/C][C]0.985459[/C][/ROW]
[ROW][C]56[/C][C]0.0132306[/C][C]0.0264612[/C][C]0.986769[/C][/ROW]
[ROW][C]57[/C][C]0.0481909[/C][C]0.0963818[/C][C]0.951809[/C][/ROW]
[ROW][C]58[/C][C]0.042945[/C][C]0.08589[/C][C]0.957055[/C][/ROW]
[ROW][C]59[/C][C]0.0346543[/C][C]0.0693085[/C][C]0.965346[/C][/ROW]
[ROW][C]60[/C][C]0.0342201[/C][C]0.0684402[/C][C]0.96578[/C][/ROW]
[ROW][C]61[/C][C]0.0410137[/C][C]0.0820274[/C][C]0.958986[/C][/ROW]
[ROW][C]62[/C][C]0.0324602[/C][C]0.0649204[/C][C]0.96754[/C][/ROW]
[ROW][C]63[/C][C]0.0576464[/C][C]0.115293[/C][C]0.942354[/C][/ROW]
[ROW][C]64[/C][C]0.0666399[/C][C]0.13328[/C][C]0.93336[/C][/ROW]
[ROW][C]65[/C][C]0.0841874[/C][C]0.168375[/C][C]0.915813[/C][/ROW]
[ROW][C]66[/C][C]0.0736934[/C][C]0.147387[/C][C]0.926307[/C][/ROW]
[ROW][C]67[/C][C]0.0708012[/C][C]0.141602[/C][C]0.929199[/C][/ROW]
[ROW][C]68[/C][C]0.0730674[/C][C]0.146135[/C][C]0.926933[/C][/ROW]
[ROW][C]69[/C][C]0.0840093[/C][C]0.168019[/C][C]0.915991[/C][/ROW]
[ROW][C]70[/C][C]0.0725432[/C][C]0.145086[/C][C]0.927457[/C][/ROW]
[ROW][C]71[/C][C]0.0649345[/C][C]0.129869[/C][C]0.935065[/C][/ROW]
[ROW][C]72[/C][C]0.0578419[/C][C]0.115684[/C][C]0.942158[/C][/ROW]
[ROW][C]73[/C][C]0.0523051[/C][C]0.10461[/C][C]0.947695[/C][/ROW]
[ROW][C]74[/C][C]0.0869388[/C][C]0.173878[/C][C]0.913061[/C][/ROW]
[ROW][C]75[/C][C]0.0722366[/C][C]0.144473[/C][C]0.927763[/C][/ROW]
[ROW][C]76[/C][C]0.0608715[/C][C]0.121743[/C][C]0.939129[/C][/ROW]
[ROW][C]77[/C][C]0.0528642[/C][C]0.105728[/C][C]0.947136[/C][/ROW]
[ROW][C]78[/C][C]0.0482569[/C][C]0.0965137[/C][C]0.951743[/C][/ROW]
[ROW][C]79[/C][C]0.0390341[/C][C]0.0780682[/C][C]0.960966[/C][/ROW]
[ROW][C]80[/C][C]0.0411729[/C][C]0.0823459[/C][C]0.958827[/C][/ROW]
[ROW][C]81[/C][C]0.0342748[/C][C]0.0685496[/C][C]0.965725[/C][/ROW]
[ROW][C]82[/C][C]0.0384569[/C][C]0.0769139[/C][C]0.961543[/C][/ROW]
[ROW][C]83[/C][C]0.0330371[/C][C]0.0660742[/C][C]0.966963[/C][/ROW]
[ROW][C]84[/C][C]0.07795[/C][C]0.1559[/C][C]0.92205[/C][/ROW]
[ROW][C]85[/C][C]0.0751713[/C][C]0.150343[/C][C]0.924829[/C][/ROW]
[ROW][C]86[/C][C]0.0654839[/C][C]0.130968[/C][C]0.934516[/C][/ROW]
[ROW][C]87[/C][C]0.0575346[/C][C]0.115069[/C][C]0.942465[/C][/ROW]
[ROW][C]88[/C][C]0.0563347[/C][C]0.112669[/C][C]0.943665[/C][/ROW]
[ROW][C]89[/C][C]0.060055[/C][C]0.12011[/C][C]0.939945[/C][/ROW]
[ROW][C]90[/C][C]0.0663396[/C][C]0.132679[/C][C]0.93366[/C][/ROW]
[ROW][C]91[/C][C]0.0674667[/C][C]0.134933[/C][C]0.932533[/C][/ROW]
[ROW][C]92[/C][C]0.149137[/C][C]0.298274[/C][C]0.850863[/C][/ROW]
[ROW][C]93[/C][C]0.144055[/C][C]0.288109[/C][C]0.855945[/C][/ROW]
[ROW][C]94[/C][C]0.142704[/C][C]0.285408[/C][C]0.857296[/C][/ROW]
[ROW][C]95[/C][C]0.144751[/C][C]0.289502[/C][C]0.855249[/C][/ROW]
[ROW][C]96[/C][C]0.144068[/C][C]0.288136[/C][C]0.855932[/C][/ROW]
[ROW][C]97[/C][C]0.219559[/C][C]0.439119[/C][C]0.780441[/C][/ROW]
[ROW][C]98[/C][C]0.200836[/C][C]0.401673[/C][C]0.799164[/C][/ROW]
[ROW][C]99[/C][C]0.200532[/C][C]0.401063[/C][C]0.799468[/C][/ROW]
[ROW][C]100[/C][C]0.2399[/C][C]0.4798[/C][C]0.7601[/C][/ROW]
[ROW][C]101[/C][C]0.219595[/C][C]0.43919[/C][C]0.780405[/C][/ROW]
[ROW][C]102[/C][C]0.222766[/C][C]0.445532[/C][C]0.777234[/C][/ROW]
[ROW][C]103[/C][C]0.239626[/C][C]0.479252[/C][C]0.760374[/C][/ROW]
[ROW][C]104[/C][C]0.25129[/C][C]0.502579[/C][C]0.74871[/C][/ROW]
[ROW][C]105[/C][C]0.262933[/C][C]0.525866[/C][C]0.737067[/C][/ROW]
[ROW][C]106[/C][C]0.274842[/C][C]0.549685[/C][C]0.725158[/C][/ROW]
[ROW][C]107[/C][C]0.336345[/C][C]0.672691[/C][C]0.663655[/C][/ROW]
[ROW][C]108[/C][C]0.579503[/C][C]0.840995[/C][C]0.420497[/C][/ROW]
[ROW][C]109[/C][C]0.635173[/C][C]0.729654[/C][C]0.364827[/C][/ROW]
[ROW][C]110[/C][C]0.622641[/C][C]0.754718[/C][C]0.377359[/C][/ROW]
[ROW][C]111[/C][C]0.627971[/C][C]0.744059[/C][C]0.372029[/C][/ROW]
[ROW][C]112[/C][C]0.648258[/C][C]0.703483[/C][C]0.351742[/C][/ROW]
[ROW][C]113[/C][C]0.791885[/C][C]0.41623[/C][C]0.208115[/C][/ROW]
[ROW][C]114[/C][C]0.829869[/C][C]0.340261[/C][C]0.170131[/C][/ROW]
[ROW][C]115[/C][C]0.891862[/C][C]0.216276[/C][C]0.108138[/C][/ROW]
[ROW][C]116[/C][C]0.924149[/C][C]0.151703[/C][C]0.0758513[/C][/ROW]
[ROW][C]117[/C][C]0.945557[/C][C]0.108887[/C][C]0.0544434[/C][/ROW]
[ROW][C]118[/C][C]0.946595[/C][C]0.106811[/C][C]0.0534055[/C][/ROW]
[ROW][C]119[/C][C]0.955962[/C][C]0.0880758[/C][C]0.0440379[/C][/ROW]
[ROW][C]120[/C][C]0.970694[/C][C]0.0586118[/C][C]0.0293059[/C][/ROW]
[ROW][C]121[/C][C]0.972943[/C][C]0.054114[/C][C]0.027057[/C][/ROW]
[ROW][C]122[/C][C]0.978112[/C][C]0.0437764[/C][C]0.0218882[/C][/ROW]
[ROW][C]123[/C][C]0.987973[/C][C]0.0240542[/C][C]0.0120271[/C][/ROW]
[ROW][C]124[/C][C]0.992719[/C][C]0.0145616[/C][C]0.00728081[/C][/ROW]
[ROW][C]125[/C][C]0.992628[/C][C]0.0147441[/C][C]0.00737207[/C][/ROW]
[ROW][C]126[/C][C]0.99161[/C][C]0.0167809[/C][C]0.00839045[/C][/ROW]
[ROW][C]127[/C][C]0.992892[/C][C]0.0142167[/C][C]0.00710837[/C][/ROW]
[ROW][C]128[/C][C]0.9922[/C][C]0.0156008[/C][C]0.00780039[/C][/ROW]
[ROW][C]129[/C][C]0.996504[/C][C]0.00699146[/C][C]0.00349573[/C][/ROW]
[ROW][C]130[/C][C]0.996331[/C][C]0.00733874[/C][C]0.00366937[/C][/ROW]
[ROW][C]131[/C][C]0.995857[/C][C]0.00828601[/C][C]0.00414301[/C][/ROW]
[ROW][C]132[/C][C]0.995348[/C][C]0.00930452[/C][C]0.00465226[/C][/ROW]
[ROW][C]133[/C][C]0.994626[/C][C]0.0107485[/C][C]0.00537427[/C][/ROW]
[ROW][C]134[/C][C]0.995718[/C][C]0.00856407[/C][C]0.00428203[/C][/ROW]
[ROW][C]135[/C][C]0.994732[/C][C]0.0105361[/C][C]0.00526804[/C][/ROW]
[ROW][C]136[/C][C]0.994231[/C][C]0.0115374[/C][C]0.00576871[/C][/ROW]
[ROW][C]137[/C][C]0.99532[/C][C]0.00936079[/C][C]0.0046804[/C][/ROW]
[ROW][C]138[/C][C]0.99491[/C][C]0.010179[/C][C]0.00508952[/C][/ROW]
[ROW][C]139[/C][C]0.996688[/C][C]0.00662404[/C][C]0.00331202[/C][/ROW]
[ROW][C]140[/C][C]0.996157[/C][C]0.00768517[/C][C]0.00384259[/C][/ROW]
[ROW][C]141[/C][C]0.995123[/C][C]0.00975423[/C][C]0.00487712[/C][/ROW]
[ROW][C]142[/C][C]0.994986[/C][C]0.010027[/C][C]0.00501351[/C][/ROW]
[ROW][C]143[/C][C]0.99531[/C][C]0.00937952[/C][C]0.00468976[/C][/ROW]
[ROW][C]144[/C][C]0.996505[/C][C]0.00699068[/C][C]0.00349534[/C][/ROW]
[ROW][C]145[/C][C]0.996104[/C][C]0.0077917[/C][C]0.00389585[/C][/ROW]
[ROW][C]146[/C][C]0.996187[/C][C]0.00762645[/C][C]0.00381323[/C][/ROW]
[ROW][C]147[/C][C]0.995186[/C][C]0.00962871[/C][C]0.00481436[/C][/ROW]
[ROW][C]148[/C][C]0.994202[/C][C]0.0115967[/C][C]0.00579833[/C][/ROW]
[ROW][C]149[/C][C]0.994438[/C][C]0.0111248[/C][C]0.00556239[/C][/ROW]
[ROW][C]150[/C][C]0.993708[/C][C]0.0125844[/C][C]0.00629218[/C][/ROW]
[ROW][C]151[/C][C]0.996792[/C][C]0.00641631[/C][C]0.00320816[/C][/ROW]
[ROW][C]152[/C][C]0.996229[/C][C]0.00754258[/C][C]0.00377129[/C][/ROW]
[ROW][C]153[/C][C]0.996633[/C][C]0.00673422[/C][C]0.00336711[/C][/ROW]
[ROW][C]154[/C][C]0.996426[/C][C]0.0071473[/C][C]0.00357365[/C][/ROW]
[ROW][C]155[/C][C]0.99619[/C][C]0.00762029[/C][C]0.00381015[/C][/ROW]
[ROW][C]156[/C][C]0.99526[/C][C]0.00948052[/C][C]0.00474026[/C][/ROW]
[ROW][C]157[/C][C]0.994813[/C][C]0.0103731[/C][C]0.00518654[/C][/ROW]
[ROW][C]158[/C][C]0.994266[/C][C]0.0114682[/C][C]0.00573409[/C][/ROW]
[ROW][C]159[/C][C]0.9931[/C][C]0.0138002[/C][C]0.00690008[/C][/ROW]
[ROW][C]160[/C][C]0.992599[/C][C]0.0148027[/C][C]0.00740133[/C][/ROW]
[ROW][C]161[/C][C]0.994825[/C][C]0.0103499[/C][C]0.00517494[/C][/ROW]
[ROW][C]162[/C][C]0.995109[/C][C]0.00978201[/C][C]0.004891[/C][/ROW]
[ROW][C]163[/C][C]0.995279[/C][C]0.00944138[/C][C]0.00472069[/C][/ROW]
[ROW][C]164[/C][C]0.998561[/C][C]0.00287821[/C][C]0.00143911[/C][/ROW]
[ROW][C]165[/C][C]0.998715[/C][C]0.00257085[/C][C]0.00128542[/C][/ROW]
[ROW][C]166[/C][C]0.998377[/C][C]0.00324561[/C][C]0.0016228[/C][/ROW]
[ROW][C]167[/C][C]0.998977[/C][C]0.0020465[/C][C]0.00102325[/C][/ROW]
[ROW][C]168[/C][C]0.998714[/C][C]0.00257273[/C][C]0.00128636[/C][/ROW]
[ROW][C]169[/C][C]0.998312[/C][C]0.00337536[/C][C]0.00168768[/C][/ROW]
[ROW][C]170[/C][C]0.997821[/C][C]0.00435834[/C][C]0.00217917[/C][/ROW]
[ROW][C]171[/C][C]0.997878[/C][C]0.00424399[/C][C]0.002122[/C][/ROW]
[ROW][C]172[/C][C]0.998592[/C][C]0.00281666[/C][C]0.00140833[/C][/ROW]
[ROW][C]173[/C][C]0.998336[/C][C]0.00332807[/C][C]0.00166403[/C][/ROW]
[ROW][C]174[/C][C]0.997871[/C][C]0.00425787[/C][C]0.00212894[/C][/ROW]
[ROW][C]175[/C][C]0.997378[/C][C]0.00524468[/C][C]0.00262234[/C][/ROW]
[ROW][C]176[/C][C]0.998448[/C][C]0.00310314[/C][C]0.00155157[/C][/ROW]
[ROW][C]177[/C][C]0.997927[/C][C]0.00414538[/C][C]0.00207269[/C][/ROW]
[ROW][C]178[/C][C]0.998854[/C][C]0.00229277[/C][C]0.00114639[/C][/ROW]
[ROW][C]179[/C][C]0.998499[/C][C]0.00300189[/C][C]0.00150094[/C][/ROW]
[ROW][C]180[/C][C]0.998707[/C][C]0.00258551[/C][C]0.00129276[/C][/ROW]
[ROW][C]181[/C][C]0.998224[/C][C]0.00355118[/C][C]0.00177559[/C][/ROW]
[ROW][C]182[/C][C]0.997613[/C][C]0.00477355[/C][C]0.00238678[/C][/ROW]
[ROW][C]183[/C][C]0.997418[/C][C]0.00516487[/C][C]0.00258244[/C][/ROW]
[ROW][C]184[/C][C]0.997381[/C][C]0.00523785[/C][C]0.00261892[/C][/ROW]
[ROW][C]185[/C][C]0.99747[/C][C]0.00505938[/C][C]0.00252969[/C][/ROW]
[ROW][C]186[/C][C]0.996898[/C][C]0.00620493[/C][C]0.00310246[/C][/ROW]
[ROW][C]187[/C][C]0.997244[/C][C]0.00551284[/C][C]0.00275642[/C][/ROW]
[ROW][C]188[/C][C]0.996396[/C][C]0.00720761[/C][C]0.00360381[/C][/ROW]
[ROW][C]189[/C][C]0.99597[/C][C]0.00805997[/C][C]0.00402998[/C][/ROW]
[ROW][C]190[/C][C]0.995544[/C][C]0.00891168[/C][C]0.00445584[/C][/ROW]
[ROW][C]191[/C][C]0.994351[/C][C]0.0112982[/C][C]0.00564912[/C][/ROW]
[ROW][C]192[/C][C]0.994055[/C][C]0.0118895[/C][C]0.00594474[/C][/ROW]
[ROW][C]193[/C][C]0.994927[/C][C]0.0101451[/C][C]0.00507255[/C][/ROW]
[ROW][C]194[/C][C]0.997208[/C][C]0.00558335[/C][C]0.00279167[/C][/ROW]
[ROW][C]195[/C][C]0.996501[/C][C]0.00699831[/C][C]0.00349916[/C][/ROW]
[ROW][C]196[/C][C]0.995877[/C][C]0.00824652[/C][C]0.00412326[/C][/ROW]
[ROW][C]197[/C][C]0.994804[/C][C]0.0103928[/C][C]0.00519638[/C][/ROW]
[ROW][C]198[/C][C]0.99404[/C][C]0.0119194[/C][C]0.0059597[/C][/ROW]
[ROW][C]199[/C][C]0.994249[/C][C]0.0115017[/C][C]0.00575086[/C][/ROW]
[ROW][C]200[/C][C]0.994499[/C][C]0.0110023[/C][C]0.00550117[/C][/ROW]
[ROW][C]201[/C][C]0.992677[/C][C]0.0146466[/C][C]0.00732331[/C][/ROW]
[ROW][C]202[/C][C]0.991986[/C][C]0.0160283[/C][C]0.00801415[/C][/ROW]
[ROW][C]203[/C][C]0.990113[/C][C]0.0197747[/C][C]0.00988737[/C][/ROW]
[ROW][C]204[/C][C]0.988006[/C][C]0.0239883[/C][C]0.0119941[/C][/ROW]
[ROW][C]205[/C][C]0.986672[/C][C]0.0266554[/C][C]0.0133277[/C][/ROW]
[ROW][C]206[/C][C]0.983911[/C][C]0.032178[/C][C]0.016089[/C][/ROW]
[ROW][C]207[/C][C]0.97885[/C][C]0.0423003[/C][C]0.0211501[/C][/ROW]
[ROW][C]208[/C][C]0.972507[/C][C]0.0549861[/C][C]0.027493[/C][/ROW]
[ROW][C]209[/C][C]0.97778[/C][C]0.0444395[/C][C]0.0222198[/C][/ROW]
[ROW][C]210[/C][C]0.978313[/C][C]0.0433746[/C][C]0.0216873[/C][/ROW]
[ROW][C]211[/C][C]0.972375[/C][C]0.0552507[/C][C]0.0276253[/C][/ROW]
[ROW][C]212[/C][C]0.964294[/C][C]0.0714121[/C][C]0.0357061[/C][/ROW]
[ROW][C]213[/C][C]0.95904[/C][C]0.0819205[/C][C]0.0409603[/C][/ROW]
[ROW][C]214[/C][C]0.957251[/C][C]0.0854976[/C][C]0.0427488[/C][/ROW]
[ROW][C]215[/C][C]0.949252[/C][C]0.101495[/C][C]0.0507475[/C][/ROW]
[ROW][C]216[/C][C]0.935662[/C][C]0.128676[/C][C]0.0643378[/C][/ROW]
[ROW][C]217[/C][C]0.933523[/C][C]0.132954[/C][C]0.0664769[/C][/ROW]
[ROW][C]218[/C][C]0.92214[/C][C]0.155721[/C][C]0.0778604[/C][/ROW]
[ROW][C]219[/C][C]0.904531[/C][C]0.190939[/C][C]0.0954693[/C][/ROW]
[ROW][C]220[/C][C]0.889076[/C][C]0.221849[/C][C]0.110924[/C][/ROW]
[ROW][C]221[/C][C]0.89427[/C][C]0.21146[/C][C]0.10573[/C][/ROW]
[ROW][C]222[/C][C]0.880745[/C][C]0.23851[/C][C]0.119255[/C][/ROW]
[ROW][C]223[/C][C]0.85433[/C][C]0.291339[/C][C]0.14567[/C][/ROW]
[ROW][C]224[/C][C]0.831493[/C][C]0.337014[/C][C]0.168507[/C][/ROW]
[ROW][C]225[/C][C]0.809416[/C][C]0.381167[/C][C]0.190584[/C][/ROW]
[ROW][C]226[/C][C]0.852417[/C][C]0.295166[/C][C]0.147583[/C][/ROW]
[ROW][C]227[/C][C]0.830331[/C][C]0.339338[/C][C]0.169669[/C][/ROW]
[ROW][C]228[/C][C]0.802828[/C][C]0.394344[/C][C]0.197172[/C][/ROW]
[ROW][C]229[/C][C]0.819381[/C][C]0.361237[/C][C]0.180619[/C][/ROW]
[ROW][C]230[/C][C]0.822747[/C][C]0.354507[/C][C]0.177253[/C][/ROW]
[ROW][C]231[/C][C]0.82591[/C][C]0.348179[/C][C]0.17409[/C][/ROW]
[ROW][C]232[/C][C]0.826439[/C][C]0.347123[/C][C]0.173561[/C][/ROW]
[ROW][C]233[/C][C]0.787393[/C][C]0.425215[/C][C]0.212607[/C][/ROW]
[ROW][C]234[/C][C]0.827384[/C][C]0.345232[/C][C]0.172616[/C][/ROW]
[ROW][C]235[/C][C]0.82272[/C][C]0.354559[/C][C]0.17728[/C][/ROW]
[ROW][C]236[/C][C]0.954818[/C][C]0.090364[/C][C]0.045182[/C][/ROW]
[ROW][C]237[/C][C]0.945115[/C][C]0.109769[/C][C]0.0548846[/C][/ROW]
[ROW][C]238[/C][C]0.92765[/C][C]0.144701[/C][C]0.0723505[/C][/ROW]
[ROW][C]239[/C][C]0.904752[/C][C]0.190496[/C][C]0.0952479[/C][/ROW]
[ROW][C]240[/C][C]0.874263[/C][C]0.251475[/C][C]0.125737[/C][/ROW]
[ROW][C]241[/C][C]0.840692[/C][C]0.318617[/C][C]0.159308[/C][/ROW]
[ROW][C]242[/C][C]0.803296[/C][C]0.393407[/C][C]0.196704[/C][/ROW]
[ROW][C]243[/C][C]0.756188[/C][C]0.487624[/C][C]0.243812[/C][/ROW]
[ROW][C]244[/C][C]0.744194[/C][C]0.511613[/C][C]0.255806[/C][/ROW]
[ROW][C]245[/C][C]0.68999[/C][C]0.620021[/C][C]0.31001[/C][/ROW]
[ROW][C]246[/C][C]0.62444[/C][C]0.751119[/C][C]0.37556[/C][/ROW]
[ROW][C]247[/C][C]0.560566[/C][C]0.878869[/C][C]0.439434[/C][/ROW]
[ROW][C]248[/C][C]0.49166[/C][C]0.983321[/C][C]0.50834[/C][/ROW]
[ROW][C]249[/C][C]0.51688[/C][C]0.96624[/C][C]0.48312[/C][/ROW]
[ROW][C]250[/C][C]0.46496[/C][C]0.929921[/C][C]0.53504[/C][/ROW]
[ROW][C]251[/C][C]0.398042[/C][C]0.796084[/C][C]0.601958[/C][/ROW]
[ROW][C]252[/C][C]0.337132[/C][C]0.674264[/C][C]0.662868[/C][/ROW]
[ROW][C]253[/C][C]0.264692[/C][C]0.529384[/C][C]0.735308[/C][/ROW]
[ROW][C]254[/C][C]0.634443[/C][C]0.731114[/C][C]0.365557[/C][/ROW]
[ROW][C]255[/C][C]0.580288[/C][C]0.839424[/C][C]0.419712[/C][/ROW]
[ROW][C]256[/C][C]0.513353[/C][C]0.973294[/C][C]0.486647[/C][/ROW]
[ROW][C]257[/C][C]0.498107[/C][C]0.996214[/C][C]0.501893[/C][/ROW]
[ROW][C]258[/C][C]0.917734[/C][C]0.164533[/C][C]0.0822664[/C][/ROW]
[ROW][C]259[/C][C]0.814543[/C][C]0.370913[/C][C]0.185457[/C][/ROW]
[ROW][C]260[/C][C]0.91928[/C][C]0.16144[/C][C]0.0807201[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265038&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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
18	0.250835	0.50167	0.749165
19	0.185714	0.371427	0.814286
20	0.111605	0.22321	0.888395
21	0.168625	0.33725	0.831375
22	0.0984528	0.196906	0.901547
23	0.0756924	0.151385	0.924308
24	0.0579922	0.115984	0.942008
25	0.0327096	0.0654192	0.96729
26	0.0282312	0.0564623	0.971769
27	0.0166804	0.0333607	0.98332
28	0.0147968	0.0295937	0.985203
29	0.00957494	0.0191499	0.990425
30	0.00521324	0.0104265	0.994787
31	0.0028397	0.00567941	0.99716
32	0.00160586	0.00321171	0.998394
33	0.00359745	0.0071949	0.996403
34	0.0385729	0.0771458	0.961427
35	0.0278583	0.0557166	0.972142
36	0.0198865	0.0397729	0.980114
37	0.0208312	0.0416624	0.979169
38	0.0165057	0.0330114	0.983494
39	0.018527	0.0370539	0.981473
40	0.0132222	0.0264445	0.986778
41	0.0218188	0.0436376	0.978181
42	0.0166197	0.0332395	0.98338
43	0.0136734	0.0273469	0.986327
44	0.0185381	0.0370762	0.981462
45	0.0150879	0.0301758	0.984912
46	0.0121146	0.0242292	0.987885
47	0.0111766	0.0223531	0.988823
48	0.00830904	0.0166181	0.991691
49	0.0121593	0.0243186	0.987841
50	0.0127802	0.0255605	0.98722
51	0.00952366	0.0190473	0.990476
52	0.00919913	0.0183983	0.990801
53	0.00705048	0.014101	0.99295
54	0.00725011	0.0145002	0.99275
55	0.0145414	0.0290827	0.985459
56	0.0132306	0.0264612	0.986769
57	0.0481909	0.0963818	0.951809
58	0.042945	0.08589	0.957055
59	0.0346543	0.0693085	0.965346
60	0.0342201	0.0684402	0.96578
61	0.0410137	0.0820274	0.958986
62	0.0324602	0.0649204	0.96754
63	0.0576464	0.115293	0.942354
64	0.0666399	0.13328	0.93336
65	0.0841874	0.168375	0.915813
66	0.0736934	0.147387	0.926307
67	0.0708012	0.141602	0.929199
68	0.0730674	0.146135	0.926933
69	0.0840093	0.168019	0.915991
70	0.0725432	0.145086	0.927457
71	0.0649345	0.129869	0.935065
72	0.0578419	0.115684	0.942158
73	0.0523051	0.10461	0.947695
74	0.0869388	0.173878	0.913061
75	0.0722366	0.144473	0.927763
76	0.0608715	0.121743	0.939129
77	0.0528642	0.105728	0.947136
78	0.0482569	0.0965137	0.951743
79	0.0390341	0.0780682	0.960966
80	0.0411729	0.0823459	0.958827
81	0.0342748	0.0685496	0.965725
82	0.0384569	0.0769139	0.961543
83	0.0330371	0.0660742	0.966963
84	0.07795	0.1559	0.92205
85	0.0751713	0.150343	0.924829
86	0.0654839	0.130968	0.934516
87	0.0575346	0.115069	0.942465
88	0.0563347	0.112669	0.943665
89	0.060055	0.12011	0.939945
90	0.0663396	0.132679	0.93366
91	0.0674667	0.134933	0.932533
92	0.149137	0.298274	0.850863
93	0.144055	0.288109	0.855945
94	0.142704	0.285408	0.857296
95	0.144751	0.289502	0.855249
96	0.144068	0.288136	0.855932
97	0.219559	0.439119	0.780441
98	0.200836	0.401673	0.799164
99	0.200532	0.401063	0.799468
100	0.2399	0.4798	0.7601
101	0.219595	0.43919	0.780405
102	0.222766	0.445532	0.777234
103	0.239626	0.479252	0.760374
104	0.25129	0.502579	0.74871
105	0.262933	0.525866	0.737067
106	0.274842	0.549685	0.725158
107	0.336345	0.672691	0.663655
108	0.579503	0.840995	0.420497
109	0.635173	0.729654	0.364827
110	0.622641	0.754718	0.377359
111	0.627971	0.744059	0.372029
112	0.648258	0.703483	0.351742
113	0.791885	0.41623	0.208115
114	0.829869	0.340261	0.170131
115	0.891862	0.216276	0.108138
116	0.924149	0.151703	0.0758513
117	0.945557	0.108887	0.0544434
118	0.946595	0.106811	0.0534055
119	0.955962	0.0880758	0.0440379
120	0.970694	0.0586118	0.0293059
121	0.972943	0.054114	0.027057
122	0.978112	0.0437764	0.0218882
123	0.987973	0.0240542	0.0120271
124	0.992719	0.0145616	0.00728081
125	0.992628	0.0147441	0.00737207
126	0.99161	0.0167809	0.00839045
127	0.992892	0.0142167	0.00710837
128	0.9922	0.0156008	0.00780039
129	0.996504	0.00699146	0.00349573
130	0.996331	0.00733874	0.00366937
131	0.995857	0.00828601	0.00414301
132	0.995348	0.00930452	0.00465226
133	0.994626	0.0107485	0.00537427
134	0.995718	0.00856407	0.00428203
135	0.994732	0.0105361	0.00526804
136	0.994231	0.0115374	0.00576871
137	0.99532	0.00936079	0.0046804
138	0.99491	0.010179	0.00508952
139	0.996688	0.00662404	0.00331202
140	0.996157	0.00768517	0.00384259
141	0.995123	0.00975423	0.00487712
142	0.994986	0.010027	0.00501351
143	0.99531	0.00937952	0.00468976
144	0.996505	0.00699068	0.00349534
145	0.996104	0.0077917	0.00389585
146	0.996187	0.00762645	0.00381323
147	0.995186	0.00962871	0.00481436
148	0.994202	0.0115967	0.00579833
149	0.994438	0.0111248	0.00556239
150	0.993708	0.0125844	0.00629218
151	0.996792	0.00641631	0.00320816
152	0.996229	0.00754258	0.00377129
153	0.996633	0.00673422	0.00336711
154	0.996426	0.0071473	0.00357365
155	0.99619	0.00762029	0.00381015
156	0.99526	0.00948052	0.00474026
157	0.994813	0.0103731	0.00518654
158	0.994266	0.0114682	0.00573409
159	0.9931	0.0138002	0.00690008
160	0.992599	0.0148027	0.00740133
161	0.994825	0.0103499	0.00517494
162	0.995109	0.00978201	0.004891
163	0.995279	0.00944138	0.00472069
164	0.998561	0.00287821	0.00143911
165	0.998715	0.00257085	0.00128542
166	0.998377	0.00324561	0.0016228
167	0.998977	0.0020465	0.00102325
168	0.998714	0.00257273	0.00128636
169	0.998312	0.00337536	0.00168768
170	0.997821	0.00435834	0.00217917
171	0.997878	0.00424399	0.002122
172	0.998592	0.00281666	0.00140833
173	0.998336	0.00332807	0.00166403
174	0.997871	0.00425787	0.00212894
175	0.997378	0.00524468	0.00262234
176	0.998448	0.00310314	0.00155157
177	0.997927	0.00414538	0.00207269
178	0.998854	0.00229277	0.00114639
179	0.998499	0.00300189	0.00150094
180	0.998707	0.00258551	0.00129276
181	0.998224	0.00355118	0.00177559
182	0.997613	0.00477355	0.00238678
183	0.997418	0.00516487	0.00258244
184	0.997381	0.00523785	0.00261892
185	0.99747	0.00505938	0.00252969
186	0.996898	0.00620493	0.00310246
187	0.997244	0.00551284	0.00275642
188	0.996396	0.00720761	0.00360381
189	0.99597	0.00805997	0.00402998
190	0.995544	0.00891168	0.00445584
191	0.994351	0.0112982	0.00564912
192	0.994055	0.0118895	0.00594474
193	0.994927	0.0101451	0.00507255
194	0.997208	0.00558335	0.00279167
195	0.996501	0.00699831	0.00349916
196	0.995877	0.00824652	0.00412326
197	0.994804	0.0103928	0.00519638
198	0.99404	0.0119194	0.0059597
199	0.994249	0.0115017	0.00575086
200	0.994499	0.0110023	0.00550117
201	0.992677	0.0146466	0.00732331
202	0.991986	0.0160283	0.00801415
203	0.990113	0.0197747	0.00988737
204	0.988006	0.0239883	0.0119941
205	0.986672	0.0266554	0.0133277
206	0.983911	0.032178	0.016089
207	0.97885	0.0423003	0.0211501
208	0.972507	0.0549861	0.027493
209	0.97778	0.0444395	0.0222198
210	0.978313	0.0433746	0.0216873
211	0.972375	0.0552507	0.0276253
212	0.964294	0.0714121	0.0357061
213	0.95904	0.0819205	0.0409603
214	0.957251	0.0854976	0.0427488
215	0.949252	0.101495	0.0507475
216	0.935662	0.128676	0.0643378
217	0.933523	0.132954	0.0664769
218	0.92214	0.155721	0.0778604
219	0.904531	0.190939	0.0954693
220	0.889076	0.221849	0.110924
221	0.89427	0.21146	0.10573
222	0.880745	0.23851	0.119255
223	0.85433	0.291339	0.14567
224	0.831493	0.337014	0.168507
225	0.809416	0.381167	0.190584
226	0.852417	0.295166	0.147583
227	0.830331	0.339338	0.169669
228	0.802828	0.394344	0.197172
229	0.819381	0.361237	0.180619
230	0.822747	0.354507	0.177253
231	0.82591	0.348179	0.17409
232	0.826439	0.347123	0.173561
233	0.787393	0.425215	0.212607
234	0.827384	0.345232	0.172616
235	0.82272	0.354559	0.17728
236	0.954818	0.090364	0.045182
237	0.945115	0.109769	0.0548846
238	0.92765	0.144701	0.0723505
239	0.904752	0.190496	0.0952479
240	0.874263	0.251475	0.125737
241	0.840692	0.318617	0.159308
242	0.803296	0.393407	0.196704
243	0.756188	0.487624	0.243812
244	0.744194	0.511613	0.255806
245	0.68999	0.620021	0.31001
246	0.62444	0.751119	0.37556
247	0.560566	0.878869	0.439434
248	0.49166	0.983321	0.50834
249	0.51688	0.96624	0.48312
250	0.46496	0.929921	0.53504
251	0.398042	0.796084	0.601958
252	0.337132	0.674264	0.662868
253	0.264692	0.529384	0.735308
254	0.634443	0.731114	0.365557
255	0.580288	0.839424	0.419712
256	0.513353	0.973294	0.486647
257	0.498107	0.996214	0.501893
258	0.917734	0.164533	0.0822664
259	0.814543	0.370913	0.185457
260	0.91928	0.16144	0.0807201

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	55	0.226337	NOK
5% type I error level	116	0.477366	NOK
10% type I error level	141	0.580247	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 & 55 & 0.226337 & NOK \tabularnewline
5% type I error level & 116 & 0.477366 & NOK \tabularnewline
10% type I error level & 141 & 0.580247 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265038&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]55[/C][C]0.226337[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]116[/C][C]0.477366[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]141[/C][C]0.580247[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265038&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265038&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	55	0.226337	NOK
5% type I error level	116	0.477366	NOK
10% type I error level	141	0.580247	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