Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Mon, 15 Dec 2014 16:27:37 +0000

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418660868kn7go03padobr0i.htm/, Retrieved Thu, 16 May 2024 09:28:15 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268720, Retrieved Thu, 16 May 2024 09:28:15 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

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

-       [Multiple Regression] [] [2014-12-15 16:27:37] [afff6d6b458ee8576605d3685f592a9b] [Current]

Feedback Forum

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

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

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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 12 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&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]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&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	'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 7.75402 + 0.00671591AMS.I[t] -0.028929AMS.E[t] -0.0444192AMS.A[t] -0.0197547SOFTSTATTOT[t] + 0.527661Calculation[t] -0.520772Algebraic_Reasoning[t] -0.613276Graphical_Interpretation[t] + 0.791933Proportionality_and_Ratio[t] -0.601538Estimation[t] -0.0181537lfm_year[t] + 0.00614936lfm_course[t] -0.00233953lfm_gender[t] + 0.0859061NUMERACYTOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  7.75402 +  0.00671591AMS.I[t] -0.028929AMS.E[t] -0.0444192AMS.A[t] -0.0197547SOFTSTATTOT[t] +  0.527661Calculation[t] -0.520772Algebraic_Reasoning[t] -0.613276Graphical_Interpretation[t] +  0.791933Proportionality_and_Ratio[t] -0.601538Estimation[t] -0.0181537lfm_year[t] +  0.00614936lfm_course[t] -0.00233953lfm_gender[t] +  0.0859061NUMERACYTOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  7.75402 +  0.00671591AMS.I[t] -0.028929AMS.E[t] -0.0444192AMS.A[t] -0.0197547SOFTSTATTOT[t] +  0.527661Calculation[t] -0.520772Algebraic_Reasoning[t] -0.613276Graphical_Interpretation[t] +  0.791933Proportionality_and_Ratio[t] -0.601538Estimation[t] -0.0181537lfm_year[t] +  0.00614936lfm_course[t] -0.00233953lfm_gender[t] +  0.0859061NUMERACYTOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 7.75402 + 0.00671591AMS.I[t] -0.028929AMS.E[t] -0.0444192AMS.A[t] -0.0197547SOFTSTATTOT[t] + 0.527661Calculation[t] -0.520772Algebraic_Reasoning[t] -0.613276Graphical_Interpretation[t] + 0.791933Proportionality_and_Ratio[t] -0.601538Estimation[t] -0.0181537lfm_year[t] + 0.00614936lfm_course[t] -0.00233953lfm_gender[t] + 0.0859061NUMERACYTOT[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	7.75402	1.62498	4.772	3.02627e-06	1.51313e-06
AMS.I	0.00671591	0.0145491	0.4616	0.644746	0.322373
AMS.E	-0.028929	0.0187617	-1.542	0.124291	0.0621457
AMS.A	-0.0444192	0.0420648	-1.056	0.291948	0.145974
SOFTSTATTOT	-0.0197547	0.0322715	-0.6121	0.540973	0.270486
Calculation	0.527661	2.026	0.2604	0.794723	0.397362
Algebraic_Reasoning	-0.520772	2.31622	-0.2248	0.82228	0.41114
Graphical_Interpretation	-0.613276	1.45152	-0.4225	0.672999	0.336499
Proportionality_and_Ratio	0.791933	0.741975	1.067	0.286797	0.143399
Estimation	-0.601538	0.539989	-1.114	0.2663	0.13315
lfm_year	-0.0181537	0.00223404	-8.126	1.72295e-14	8.61477e-15
lfm_course	0.00614936	0.00203785	3.018	0.0027971	0.00139855
lfm_gender	-0.00233953	0.00235372	-0.994	0.321147	0.160574
NUMERACYTOT	0.0859061	0.199592	0.4304	0.667249	0.333624

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 7.75402 & 1.62498 & 4.772 & 3.02627e-06 & 1.51313e-06 \tabularnewline
AMS.I & 0.00671591 & 0.0145491 & 0.4616 & 0.644746 & 0.322373 \tabularnewline
AMS.E & -0.028929 & 0.0187617 & -1.542 & 0.124291 & 0.0621457 \tabularnewline
AMS.A & -0.0444192 & 0.0420648 & -1.056 & 0.291948 & 0.145974 \tabularnewline
SOFTSTATTOT & -0.0197547 & 0.0322715 & -0.6121 & 0.540973 & 0.270486 \tabularnewline
Calculation & 0.527661 & 2.026 & 0.2604 & 0.794723 & 0.397362 \tabularnewline
Algebraic_Reasoning & -0.520772 & 2.31622 & -0.2248 & 0.82228 & 0.41114 \tabularnewline
Graphical_Interpretation & -0.613276 & 1.45152 & -0.4225 & 0.672999 & 0.336499 \tabularnewline
Proportionality_and_Ratio & 0.791933 & 0.741975 & 1.067 & 0.286797 & 0.143399 \tabularnewline
Estimation & -0.601538 & 0.539989 & -1.114 & 0.2663 & 0.13315 \tabularnewline
lfm_year & -0.0181537 & 0.00223404 & -8.126 & 1.72295e-14 & 8.61477e-15 \tabularnewline
lfm_course & 0.00614936 & 0.00203785 & 3.018 & 0.0027971 & 0.00139855 \tabularnewline
lfm_gender & -0.00233953 & 0.00235372 & -0.994 & 0.321147 & 0.160574 \tabularnewline
NUMERACYTOT & 0.0859061 & 0.199592 & 0.4304 & 0.667249 & 0.333624 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]7.75402[/C][C]1.62498[/C][C]4.772[/C][C]3.02627e-06[/C][C]1.51313e-06[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00671591[/C][C]0.0145491[/C][C]0.4616[/C][C]0.644746[/C][C]0.322373[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.028929[/C][C]0.0187617[/C][C]-1.542[/C][C]0.124291[/C][C]0.0621457[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0444192[/C][C]0.0420648[/C][C]-1.056[/C][C]0.291948[/C][C]0.145974[/C][/ROW]
[ROW][C]SOFTSTATTOT[/C][C]-0.0197547[/C][C]0.0322715[/C][C]-0.6121[/C][C]0.540973[/C][C]0.270486[/C][/ROW]
[ROW][C]Calculation[/C][C]0.527661[/C][C]2.026[/C][C]0.2604[/C][C]0.794723[/C][C]0.397362[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-0.520772[/C][C]2.31622[/C][C]-0.2248[/C][C]0.82228[/C][C]0.41114[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]-0.613276[/C][C]1.45152[/C][C]-0.4225[/C][C]0.672999[/C][C]0.336499[/C][/ROW]
[ROW][C]Proportionality_and_Ratio[/C][C]0.791933[/C][C]0.741975[/C][C]1.067[/C][C]0.286797[/C][C]0.143399[/C][/ROW]
[ROW][C]Estimation[/C][C]-0.601538[/C][C]0.539989[/C][C]-1.114[/C][C]0.2663[/C][C]0.13315[/C][/ROW]
[ROW][C]lfm_year[/C][C]-0.0181537[/C][C]0.00223404[/C][C]-8.126[/C][C]1.72295e-14[/C][C]8.61477e-15[/C][/ROW]
[ROW][C]lfm_course[/C][C]0.00614936[/C][C]0.00203785[/C][C]3.018[/C][C]0.0027971[/C][C]0.00139855[/C][/ROW]
[ROW][C]lfm_gender[/C][C]-0.00233953[/C][C]0.00235372[/C][C]-0.994[/C][C]0.321147[/C][C]0.160574[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0859061[/C][C]0.199592[/C][C]0.4304[/C][C]0.667249[/C][C]0.333624[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	7.75402	1.62498	4.772	3.02627e-06	1.51313e-06
AMS.I	0.00671591	0.0145491	0.4616	0.644746	0.322373
AMS.E	-0.028929	0.0187617	-1.542	0.124291	0.0621457
AMS.A	-0.0444192	0.0420648	-1.056	0.291948	0.145974
SOFTSTATTOT	-0.0197547	0.0322715	-0.6121	0.540973	0.270486
Calculation	0.527661	2.026	0.2604	0.794723	0.397362
Algebraic_Reasoning	-0.520772	2.31622	-0.2248	0.82228	0.41114
Graphical_Interpretation	-0.613276	1.45152	-0.4225	0.672999	0.336499
Proportionality_and_Ratio	0.791933	0.741975	1.067	0.286797	0.143399
Estimation	-0.601538	0.539989	-1.114	0.2663	0.13315
lfm_year	-0.0181537	0.00223404	-8.126	1.72295e-14	8.61477e-15
lfm_course	0.00614936	0.00203785	3.018	0.0027971	0.00139855
lfm_gender	-0.00233953	0.00235372	-0.994	0.321147	0.160574
NUMERACYTOT	0.0859061	0.199592	0.4304	0.667249	0.333624

Multiple Linear Regression - Regression Statistics
Multiple R	0.523831
R-squared	0.274399
Adjusted R-squared	0.238668
F-TEST (value)	7.6797
F-TEST (DF numerator)	13
F-TEST (DF denominator)	264
p-value	6.82787e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.2107
Sum Squared Residuals	1290.22

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.523831 \tabularnewline
R-squared & 0.274399 \tabularnewline
Adjusted R-squared & 0.238668 \tabularnewline
F-TEST (value) & 7.6797 \tabularnewline
F-TEST (DF numerator) & 13 \tabularnewline
F-TEST (DF denominator) & 264 \tabularnewline
p-value & 6.82787e-13 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.2107 \tabularnewline
Sum Squared Residuals & 1290.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.523831[/C][/ROW]
[ROW][C]R-squared[/C][C]0.274399[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.238668[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.6797[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]13[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]264[/C][/ROW]
[ROW][C]p-value[/C][C]6.82787e-13[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.2107[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1290.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&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	0.523831
R-squared	0.274399
Adjusted R-squared	0.238668
F-TEST (value)	7.6797
F-TEST (DF numerator)	13
F-TEST (DF denominator)	264
p-value	6.82787e-13
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.2107
Sum Squared Residuals	1290.22

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.91223	1.58777
2	6	5.10563	0.894374
3	6.5	5.41476	1.08524
4	1	4.37966	-3.37966
5	1	5.04156	-4.04156
6	5.5	3.14115	2.35885
7	8.5	5.29379	3.20621
8	6.5	5.92113	0.578872
9	4.5	4.13844	0.361558
10	2	5.60175	-3.60175
11	5	5.29681	-0.296814
12	0.5	4.25612	-3.75612
13	5	4.4153	0.584704
14	5	4.64483	0.355166
15	2.5	6.48527	-3.98527
16	5	5.12134	-0.121339
17	5.5	4.4561	1.0439
18	3.5	4.96717	-1.46717
19	3	4.19671	-1.19671
20	4	4.25867	-0.258667
21	0.5	4.64568	-4.14568
22	6.5	4.30941	2.19059
23	4.5	3.71532	0.784684
24	7.5	3.80756	3.69244
25	5.5	5.40839	0.0916118
26	4	2.34572	1.65428
27	7.5	4.04147	3.45853
28	7	5.36464	1.63536
29	4	5.19723	-1.19723
30	5.5	4.64906	0.850939
31	2.5	4.74064	-2.24064
32	5.5	4.32295	1.17705
33	3.5	5.19223	-1.69223
34	2.5	4.6916	-2.1916
35	4.5	5.58082	-1.08082
36	4.5	6.3241	-1.8241
37	4.5	4.67616	-0.176163
38	6	3.70084	2.29916
39	2.5	5.1199	-2.6199
40	5	5.14705	-0.147048
41	0	5.91967	-5.91967
42	5	5.23036	-0.230362
43	6.5	4.45208	2.04792
44	5	4.67983	0.320168
45	6	5.18535	0.814647
46	4.5	5.53733	-1.03733
47	5.5	4.69462	0.805378
48	1	4.44719	-3.44719
49	7.5	5.12911	2.37089
50	6	5.79023	0.209766
51	5	4.76538	0.234622
52	1	5.45783	-4.45783
53	5	4.91116	0.0888374
54	6.5	3.26315	3.23685
55	7	4.86162	2.13838
56	4.5	5.60705	-1.10705
57	0	4.49891	-4.49891
58	8.5	3.92036	4.57964
59	3.5	5.58759	-2.08759
60	7.5	5.42172	2.07828
61	3.5	5.40151	-1.90151
62	6	4.38367	1.61633
63	1.5	5.26735	-3.76735
64	9	4.38197	4.61803
65	3.5	4.20298	-0.702975
66	3.5	5.79445	-2.29445
67	4	4.39158	-0.391575
68	6.5	4.18533	2.31467
69	7.5	4.70916	2.79084
70	6	4.36333	1.63667
71	5	4.64373	0.356274
72	5.5	5.75369	-0.253687
73	3.5	5.6938	-2.1938
74	7.5	5.60051	1.89949
75	6.5	4.70984	1.79016
76	NA	NA	1.66019
77	6.5	5.39069	1.10931
78	6.5	4.51469	1.98531
79	7	8.13758	-1.13758
80	3.5	6.69352	-3.19352
81	1.5	2.65974	-1.15974
82	4	0.695251	3.30475
83	7.5	8.1512	-0.651195
84	4.5	8.8555	-4.3555
85	0	0.777438	-0.777438
86	3.5	2.70371	0.796294
87	5.5	5.75294	-0.252938
88	5	6.3964	-1.3964
89	4.5	7.58111	-3.08111
90	2.5	-1.64259	4.14259
91	7.5	6.14812	1.35188
92	7	10.7722	-3.77216
93	0	-1.3503	1.3503
94	4.5	5.85561	-1.35561
95	3	5.80895	-2.80895
96	1.5	2.08547	-0.585466
97	3.5	5.28766	-1.78766
98	2.5	2.19331	0.306685
99	5.5	2.8237	2.6763
100	8	11.6632	-3.66316
101	1	1.65107	-0.651065
102	5	5.78589	-0.785887
103	4.5	5.97897	-1.47897
104	3	3.46074	-0.460739
105	3	-0.361806	3.36181
106	8	10.1358	-2.13578
107	2.5	-0.227548	2.72755
108	7	12.3654	-5.36543
109	0	5.14884	-5.14884
110	1	2.19034	-1.19034
111	3.5	3.04029	0.459711
112	5.5	4.88976	0.610235
113	5.5	11.9105	-6.4105
114	0.5	0.181953	0.318047
115	7.5	5.64229	1.85771
116	9	7.5417	1.4583
117	9.5	8.94639	0.553611
118	8.5	7.24737	1.25263
119	7	7.60038	-0.600377
120	8	6.19329	1.80671
121	10	10.6187	-0.618679
122	7	5.2396	1.7604
123	8.5	7.55144	0.948561
124	9	6.71059	2.28941
125	9.5	12.6065	-3.10653
126	4	4.17858	-0.178579
127	6	4.79893	1.20107
128	8	8.90976	-0.909756
129	5.5	2.77056	2.72944
130	9.5	9.48007	0.0199262
131	7.5	8.21931	-0.719309
132	7	7.19843	-0.198434
133	7.5	6.74272	0.757281
134	8	7.87204	0.127956
135	7	7.35239	-0.352388
136	7	8.10828	-1.10828
137	6	3.47467	2.52533
138	10	14.8562	-4.85625
139	2.5	1.38765	1.11235
140	9	8.97036	0.0296383
141	8	8.51497	-0.514975
142	6	4.53306	1.46694
143	8.5	8.73544	-0.235437
144	6	4.11797	1.88203
145	9	8.20181	0.798186
146	8	7.58405	0.415953
147	9	10.3648	-1.36476
148	5.5	5.81769	-0.317687
149	7	8.53098	-1.53098
150	5.5	4.64949	0.850506
151	9	14.1737	-5.17372
152	2	1.93101	0.0689905
153	8.5	7.61376	0.886239
154	9	7.87158	1.12842
155	8.5	7.06501	1.43499
156	9	7.9154	1.0846
157	7.5	6.01857	1.48143
158	10	8.50384	1.49616
159	9	8.81803	0.181965
160	7.5	8.59565	-1.09565
161	6	2.95627	3.04373
162	10.5	8.81141	1.68859
163	8.5	9.39537	-0.895375
164	8	5.56764	2.43236
165	10	7.77477	2.22523
166	10.5	9.87267	0.627327
167	6.5	4.10276	2.39724
168	9.5	8.54327	0.956733
169	8.5	8.61233	-0.112334
170	7.5	8.9734	-1.4734
171	5	3.79273	1.20727
172	8	4.91317	3.08683
173	10	10.8194	-0.819356
174	7	7.38455	-0.384547
175	7.5	7.82669	-0.32669
176	7.5	4.00977	3.49023
177	9.5	10.6822	-1.18219
178	6	3.34637	2.65363
179	10	9.76191	0.238085
180	7	10.5299	-3.52987
181	3	4.3981	-1.3981
182	6	6.0535	-0.0534992
183	7	5.45998	1.54002
184	10	9.77883	0.221166
185	7	10.0144	-3.01441
186	3.5	2.96265	0.537345
187	8	5.49298	2.50702
188	10	12.019	-2.01905
189	5.5	6.87976	-1.37976
190	6	5.97014	0.0298594
191	6.5	7.17112	-0.671125
192	6.5	3.76655	2.73345
193	8.5	11.3499	-2.84994
194	4	0.683184	3.31682
195	9.5	8.17702	1.32298
196	8	7.1053	0.894702
197	8.5	10.8577	-2.35772
198	5.5	4.26314	1.23686
199	7	4.46615	2.53385
200	9	7.6504	1.3496
201	8	6.18496	1.81504
202	10	9.21108	0.78892
203	8	8.95855	-0.958549
204	6	5.34007	0.659933
205	8	10.1177	-2.11768
206	5	3.16827	1.83173
207	9	10.6285	-1.62848
208	4.5	3.05196	1.44804
209	8.5	4.5692	3.9308
210	9.5	7.48954	2.01046
211	8.5	8.35337	0.146633
212	7.5	7.2087	0.291297
213	7.5	9.05084	-1.55084
214	5	4.04331	0.956693
215	7	6.82276	0.177238
216	8	8.88265	-0.882652
217	5.5	3.62915	1.87085
218	8.5	6.76919	1.73081
219	9.5	9.42381	0.0761921
220	7	6.65222	0.347785
221	8	6.15612	1.84388
222	8.5	10.1929	-1.69293
223	3.5	4.87475	-1.37475
224	6.5	6.45539	0.0446062
225	6.5	3.92817	2.57183
226	10.5	8.88458	1.61542
227	8.5	7.8513	0.648704
228	8	5.07831	2.92169
229	10	7.625	2.375
230	10	8.37537	1.62463
231	9.5	7.70696	1.79304
232	9	6.5798	2.4202
233	10	9.00024	0.999764
234	7.5	10.5156	-3.01555
235	4.5	6.24327	-1.74327
236	4.5	11.7837	-7.28369
237	0.5	0.54474	-0.0447405
238	6.5	8.45227	-1.95227
239	4.5	6.02849	-1.52849
240	5.5	6.75464	-1.25464
241	5	6.72148	-1.72148
242	6	7.5407	-1.5407
243	4	2.90605	1.09395
244	8	5.14768	2.85232
245	10.5	10.9209	-0.420913
246	6.5	4.60311	1.89689
247	8	7.16946	0.830543
248	8.5	10.2912	-1.79119
249	5.5	5.65316	-0.153164
250	7	8.91122	-1.91122
251	5	8.3462	-3.3462
252	3.5	6.19769	-2.69769
253	5	3.12469	1.87531
254	9	6.29005	2.70995
255	8.5	10.8962	-2.39619
256	5	2.98516	2.01484
257	9.5	13.2798	-3.77983
258	3	8.86712	-5.86712
259	1.5	1.84297	-0.342975
260	6	11.3072	-5.30721
261	0.5	0.555574	-0.0555736
262	6.5	6.48263	0.0173731
263	7.5	9.03438	-1.53438
264	4.5	3.17312	1.32688
265	8	6.02352	1.97648
266	9	8.78773	0.212268
267	7.5	6.79027	0.709732
268	8.5	6.95177	1.54823
269	7	5.03634	1.96366
270	9.5	10.3519	-0.851864
271	6.5	3.50549	2.99451
272	9.5	10.1908	-0.690825
273	6	3.508	2.492
274	8	5.57106	2.42894
275	9.5	8.33724	1.16276
276	8	8.42529	-0.425294
277	8	6.08057	1.91943
278	9	11.3157	-2.31572
279	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.91223 & 1.58777 \tabularnewline
2 & 6 & 5.10563 & 0.894374 \tabularnewline
3 & 6.5 & 5.41476 & 1.08524 \tabularnewline
4 & 1 & 4.37966 & -3.37966 \tabularnewline
5 & 1 & 5.04156 & -4.04156 \tabularnewline
6 & 5.5 & 3.14115 & 2.35885 \tabularnewline
7 & 8.5 & 5.29379 & 3.20621 \tabularnewline
8 & 6.5 & 5.92113 & 0.578872 \tabularnewline
9 & 4.5 & 4.13844 & 0.361558 \tabularnewline
10 & 2 & 5.60175 & -3.60175 \tabularnewline
11 & 5 & 5.29681 & -0.296814 \tabularnewline
12 & 0.5 & 4.25612 & -3.75612 \tabularnewline
13 & 5 & 4.4153 & 0.584704 \tabularnewline
14 & 5 & 4.64483 & 0.355166 \tabularnewline
15 & 2.5 & 6.48527 & -3.98527 \tabularnewline
16 & 5 & 5.12134 & -0.121339 \tabularnewline
17 & 5.5 & 4.4561 & 1.0439 \tabularnewline
18 & 3.5 & 4.96717 & -1.46717 \tabularnewline
19 & 3 & 4.19671 & -1.19671 \tabularnewline
20 & 4 & 4.25867 & -0.258667 \tabularnewline
21 & 0.5 & 4.64568 & -4.14568 \tabularnewline
22 & 6.5 & 4.30941 & 2.19059 \tabularnewline
23 & 4.5 & 3.71532 & 0.784684 \tabularnewline
24 & 7.5 & 3.80756 & 3.69244 \tabularnewline
25 & 5.5 & 5.40839 & 0.0916118 \tabularnewline
26 & 4 & 2.34572 & 1.65428 \tabularnewline
27 & 7.5 & 4.04147 & 3.45853 \tabularnewline
28 & 7 & 5.36464 & 1.63536 \tabularnewline
29 & 4 & 5.19723 & -1.19723 \tabularnewline
30 & 5.5 & 4.64906 & 0.850939 \tabularnewline
31 & 2.5 & 4.74064 & -2.24064 \tabularnewline
32 & 5.5 & 4.32295 & 1.17705 \tabularnewline
33 & 3.5 & 5.19223 & -1.69223 \tabularnewline
34 & 2.5 & 4.6916 & -2.1916 \tabularnewline
35 & 4.5 & 5.58082 & -1.08082 \tabularnewline
36 & 4.5 & 6.3241 & -1.8241 \tabularnewline
37 & 4.5 & 4.67616 & -0.176163 \tabularnewline
38 & 6 & 3.70084 & 2.29916 \tabularnewline
39 & 2.5 & 5.1199 & -2.6199 \tabularnewline
40 & 5 & 5.14705 & -0.147048 \tabularnewline
41 & 0 & 5.91967 & -5.91967 \tabularnewline
42 & 5 & 5.23036 & -0.230362 \tabularnewline
43 & 6.5 & 4.45208 & 2.04792 \tabularnewline
44 & 5 & 4.67983 & 0.320168 \tabularnewline
45 & 6 & 5.18535 & 0.814647 \tabularnewline
46 & 4.5 & 5.53733 & -1.03733 \tabularnewline
47 & 5.5 & 4.69462 & 0.805378 \tabularnewline
48 & 1 & 4.44719 & -3.44719 \tabularnewline
49 & 7.5 & 5.12911 & 2.37089 \tabularnewline
50 & 6 & 5.79023 & 0.209766 \tabularnewline
51 & 5 & 4.76538 & 0.234622 \tabularnewline
52 & 1 & 5.45783 & -4.45783 \tabularnewline
53 & 5 & 4.91116 & 0.0888374 \tabularnewline
54 & 6.5 & 3.26315 & 3.23685 \tabularnewline
55 & 7 & 4.86162 & 2.13838 \tabularnewline
56 & 4.5 & 5.60705 & -1.10705 \tabularnewline
57 & 0 & 4.49891 & -4.49891 \tabularnewline
58 & 8.5 & 3.92036 & 4.57964 \tabularnewline
59 & 3.5 & 5.58759 & -2.08759 \tabularnewline
60 & 7.5 & 5.42172 & 2.07828 \tabularnewline
61 & 3.5 & 5.40151 & -1.90151 \tabularnewline
62 & 6 & 4.38367 & 1.61633 \tabularnewline
63 & 1.5 & 5.26735 & -3.76735 \tabularnewline
64 & 9 & 4.38197 & 4.61803 \tabularnewline
65 & 3.5 & 4.20298 & -0.702975 \tabularnewline
66 & 3.5 & 5.79445 & -2.29445 \tabularnewline
67 & 4 & 4.39158 & -0.391575 \tabularnewline
68 & 6.5 & 4.18533 & 2.31467 \tabularnewline
69 & 7.5 & 4.70916 & 2.79084 \tabularnewline
70 & 6 & 4.36333 & 1.63667 \tabularnewline
71 & 5 & 4.64373 & 0.356274 \tabularnewline
72 & 5.5 & 5.75369 & -0.253687 \tabularnewline
73 & 3.5 & 5.6938 & -2.1938 \tabularnewline
74 & 7.5 & 5.60051 & 1.89949 \tabularnewline
75 & 6.5 & 4.70984 & 1.79016 \tabularnewline
76 & NA & NA & 1.66019 \tabularnewline
77 & 6.5 & 5.39069 & 1.10931 \tabularnewline
78 & 6.5 & 4.51469 & 1.98531 \tabularnewline
79 & 7 & 8.13758 & -1.13758 \tabularnewline
80 & 3.5 & 6.69352 & -3.19352 \tabularnewline
81 & 1.5 & 2.65974 & -1.15974 \tabularnewline
82 & 4 & 0.695251 & 3.30475 \tabularnewline
83 & 7.5 & 8.1512 & -0.651195 \tabularnewline
84 & 4.5 & 8.8555 & -4.3555 \tabularnewline
85 & 0 & 0.777438 & -0.777438 \tabularnewline
86 & 3.5 & 2.70371 & 0.796294 \tabularnewline
87 & 5.5 & 5.75294 & -0.252938 \tabularnewline
88 & 5 & 6.3964 & -1.3964 \tabularnewline
89 & 4.5 & 7.58111 & -3.08111 \tabularnewline
90 & 2.5 & -1.64259 & 4.14259 \tabularnewline
91 & 7.5 & 6.14812 & 1.35188 \tabularnewline
92 & 7 & 10.7722 & -3.77216 \tabularnewline
93 & 0 & -1.3503 & 1.3503 \tabularnewline
94 & 4.5 & 5.85561 & -1.35561 \tabularnewline
95 & 3 & 5.80895 & -2.80895 \tabularnewline
96 & 1.5 & 2.08547 & -0.585466 \tabularnewline
97 & 3.5 & 5.28766 & -1.78766 \tabularnewline
98 & 2.5 & 2.19331 & 0.306685 \tabularnewline
99 & 5.5 & 2.8237 & 2.6763 \tabularnewline
100 & 8 & 11.6632 & -3.66316 \tabularnewline
101 & 1 & 1.65107 & -0.651065 \tabularnewline
102 & 5 & 5.78589 & -0.785887 \tabularnewline
103 & 4.5 & 5.97897 & -1.47897 \tabularnewline
104 & 3 & 3.46074 & -0.460739 \tabularnewline
105 & 3 & -0.361806 & 3.36181 \tabularnewline
106 & 8 & 10.1358 & -2.13578 \tabularnewline
107 & 2.5 & -0.227548 & 2.72755 \tabularnewline
108 & 7 & 12.3654 & -5.36543 \tabularnewline
109 & 0 & 5.14884 & -5.14884 \tabularnewline
110 & 1 & 2.19034 & -1.19034 \tabularnewline
111 & 3.5 & 3.04029 & 0.459711 \tabularnewline
112 & 5.5 & 4.88976 & 0.610235 \tabularnewline
113 & 5.5 & 11.9105 & -6.4105 \tabularnewline
114 & 0.5 & 0.181953 & 0.318047 \tabularnewline
115 & 7.5 & 5.64229 & 1.85771 \tabularnewline
116 & 9 & 7.5417 & 1.4583 \tabularnewline
117 & 9.5 & 8.94639 & 0.553611 \tabularnewline
118 & 8.5 & 7.24737 & 1.25263 \tabularnewline
119 & 7 & 7.60038 & -0.600377 \tabularnewline
120 & 8 & 6.19329 & 1.80671 \tabularnewline
121 & 10 & 10.6187 & -0.618679 \tabularnewline
122 & 7 & 5.2396 & 1.7604 \tabularnewline
123 & 8.5 & 7.55144 & 0.948561 \tabularnewline
124 & 9 & 6.71059 & 2.28941 \tabularnewline
125 & 9.5 & 12.6065 & -3.10653 \tabularnewline
126 & 4 & 4.17858 & -0.178579 \tabularnewline
127 & 6 & 4.79893 & 1.20107 \tabularnewline
128 & 8 & 8.90976 & -0.909756 \tabularnewline
129 & 5.5 & 2.77056 & 2.72944 \tabularnewline
130 & 9.5 & 9.48007 & 0.0199262 \tabularnewline
131 & 7.5 & 8.21931 & -0.719309 \tabularnewline
132 & 7 & 7.19843 & -0.198434 \tabularnewline
133 & 7.5 & 6.74272 & 0.757281 \tabularnewline
134 & 8 & 7.87204 & 0.127956 \tabularnewline
135 & 7 & 7.35239 & -0.352388 \tabularnewline
136 & 7 & 8.10828 & -1.10828 \tabularnewline
137 & 6 & 3.47467 & 2.52533 \tabularnewline
138 & 10 & 14.8562 & -4.85625 \tabularnewline
139 & 2.5 & 1.38765 & 1.11235 \tabularnewline
140 & 9 & 8.97036 & 0.0296383 \tabularnewline
141 & 8 & 8.51497 & -0.514975 \tabularnewline
142 & 6 & 4.53306 & 1.46694 \tabularnewline
143 & 8.5 & 8.73544 & -0.235437 \tabularnewline
144 & 6 & 4.11797 & 1.88203 \tabularnewline
145 & 9 & 8.20181 & 0.798186 \tabularnewline
146 & 8 & 7.58405 & 0.415953 \tabularnewline
147 & 9 & 10.3648 & -1.36476 \tabularnewline
148 & 5.5 & 5.81769 & -0.317687 \tabularnewline
149 & 7 & 8.53098 & -1.53098 \tabularnewline
150 & 5.5 & 4.64949 & 0.850506 \tabularnewline
151 & 9 & 14.1737 & -5.17372 \tabularnewline
152 & 2 & 1.93101 & 0.0689905 \tabularnewline
153 & 8.5 & 7.61376 & 0.886239 \tabularnewline
154 & 9 & 7.87158 & 1.12842 \tabularnewline
155 & 8.5 & 7.06501 & 1.43499 \tabularnewline
156 & 9 & 7.9154 & 1.0846 \tabularnewline
157 & 7.5 & 6.01857 & 1.48143 \tabularnewline
158 & 10 & 8.50384 & 1.49616 \tabularnewline
159 & 9 & 8.81803 & 0.181965 \tabularnewline
160 & 7.5 & 8.59565 & -1.09565 \tabularnewline
161 & 6 & 2.95627 & 3.04373 \tabularnewline
162 & 10.5 & 8.81141 & 1.68859 \tabularnewline
163 & 8.5 & 9.39537 & -0.895375 \tabularnewline
164 & 8 & 5.56764 & 2.43236 \tabularnewline
165 & 10 & 7.77477 & 2.22523 \tabularnewline
166 & 10.5 & 9.87267 & 0.627327 \tabularnewline
167 & 6.5 & 4.10276 & 2.39724 \tabularnewline
168 & 9.5 & 8.54327 & 0.956733 \tabularnewline
169 & 8.5 & 8.61233 & -0.112334 \tabularnewline
170 & 7.5 & 8.9734 & -1.4734 \tabularnewline
171 & 5 & 3.79273 & 1.20727 \tabularnewline
172 & 8 & 4.91317 & 3.08683 \tabularnewline
173 & 10 & 10.8194 & -0.819356 \tabularnewline
174 & 7 & 7.38455 & -0.384547 \tabularnewline
175 & 7.5 & 7.82669 & -0.32669 \tabularnewline
176 & 7.5 & 4.00977 & 3.49023 \tabularnewline
177 & 9.5 & 10.6822 & -1.18219 \tabularnewline
178 & 6 & 3.34637 & 2.65363 \tabularnewline
179 & 10 & 9.76191 & 0.238085 \tabularnewline
180 & 7 & 10.5299 & -3.52987 \tabularnewline
181 & 3 & 4.3981 & -1.3981 \tabularnewline
182 & 6 & 6.0535 & -0.0534992 \tabularnewline
183 & 7 & 5.45998 & 1.54002 \tabularnewline
184 & 10 & 9.77883 & 0.221166 \tabularnewline
185 & 7 & 10.0144 & -3.01441 \tabularnewline
186 & 3.5 & 2.96265 & 0.537345 \tabularnewline
187 & 8 & 5.49298 & 2.50702 \tabularnewline
188 & 10 & 12.019 & -2.01905 \tabularnewline
189 & 5.5 & 6.87976 & -1.37976 \tabularnewline
190 & 6 & 5.97014 & 0.0298594 \tabularnewline
191 & 6.5 & 7.17112 & -0.671125 \tabularnewline
192 & 6.5 & 3.76655 & 2.73345 \tabularnewline
193 & 8.5 & 11.3499 & -2.84994 \tabularnewline
194 & 4 & 0.683184 & 3.31682 \tabularnewline
195 & 9.5 & 8.17702 & 1.32298 \tabularnewline
196 & 8 & 7.1053 & 0.894702 \tabularnewline
197 & 8.5 & 10.8577 & -2.35772 \tabularnewline
198 & 5.5 & 4.26314 & 1.23686 \tabularnewline
199 & 7 & 4.46615 & 2.53385 \tabularnewline
200 & 9 & 7.6504 & 1.3496 \tabularnewline
201 & 8 & 6.18496 & 1.81504 \tabularnewline
202 & 10 & 9.21108 & 0.78892 \tabularnewline
203 & 8 & 8.95855 & -0.958549 \tabularnewline
204 & 6 & 5.34007 & 0.659933 \tabularnewline
205 & 8 & 10.1177 & -2.11768 \tabularnewline
206 & 5 & 3.16827 & 1.83173 \tabularnewline
207 & 9 & 10.6285 & -1.62848 \tabularnewline
208 & 4.5 & 3.05196 & 1.44804 \tabularnewline
209 & 8.5 & 4.5692 & 3.9308 \tabularnewline
210 & 9.5 & 7.48954 & 2.01046 \tabularnewline
211 & 8.5 & 8.35337 & 0.146633 \tabularnewline
212 & 7.5 & 7.2087 & 0.291297 \tabularnewline
213 & 7.5 & 9.05084 & -1.55084 \tabularnewline
214 & 5 & 4.04331 & 0.956693 \tabularnewline
215 & 7 & 6.82276 & 0.177238 \tabularnewline
216 & 8 & 8.88265 & -0.882652 \tabularnewline
217 & 5.5 & 3.62915 & 1.87085 \tabularnewline
218 & 8.5 & 6.76919 & 1.73081 \tabularnewline
219 & 9.5 & 9.42381 & 0.0761921 \tabularnewline
220 & 7 & 6.65222 & 0.347785 \tabularnewline
221 & 8 & 6.15612 & 1.84388 \tabularnewline
222 & 8.5 & 10.1929 & -1.69293 \tabularnewline
223 & 3.5 & 4.87475 & -1.37475 \tabularnewline
224 & 6.5 & 6.45539 & 0.0446062 \tabularnewline
225 & 6.5 & 3.92817 & 2.57183 \tabularnewline
226 & 10.5 & 8.88458 & 1.61542 \tabularnewline
227 & 8.5 & 7.8513 & 0.648704 \tabularnewline
228 & 8 & 5.07831 & 2.92169 \tabularnewline
229 & 10 & 7.625 & 2.375 \tabularnewline
230 & 10 & 8.37537 & 1.62463 \tabularnewline
231 & 9.5 & 7.70696 & 1.79304 \tabularnewline
232 & 9 & 6.5798 & 2.4202 \tabularnewline
233 & 10 & 9.00024 & 0.999764 \tabularnewline
234 & 7.5 & 10.5156 & -3.01555 \tabularnewline
235 & 4.5 & 6.24327 & -1.74327 \tabularnewline
236 & 4.5 & 11.7837 & -7.28369 \tabularnewline
237 & 0.5 & 0.54474 & -0.0447405 \tabularnewline
238 & 6.5 & 8.45227 & -1.95227 \tabularnewline
239 & 4.5 & 6.02849 & -1.52849 \tabularnewline
240 & 5.5 & 6.75464 & -1.25464 \tabularnewline
241 & 5 & 6.72148 & -1.72148 \tabularnewline
242 & 6 & 7.5407 & -1.5407 \tabularnewline
243 & 4 & 2.90605 & 1.09395 \tabularnewline
244 & 8 & 5.14768 & 2.85232 \tabularnewline
245 & 10.5 & 10.9209 & -0.420913 \tabularnewline
246 & 6.5 & 4.60311 & 1.89689 \tabularnewline
247 & 8 & 7.16946 & 0.830543 \tabularnewline
248 & 8.5 & 10.2912 & -1.79119 \tabularnewline
249 & 5.5 & 5.65316 & -0.153164 \tabularnewline
250 & 7 & 8.91122 & -1.91122 \tabularnewline
251 & 5 & 8.3462 & -3.3462 \tabularnewline
252 & 3.5 & 6.19769 & -2.69769 \tabularnewline
253 & 5 & 3.12469 & 1.87531 \tabularnewline
254 & 9 & 6.29005 & 2.70995 \tabularnewline
255 & 8.5 & 10.8962 & -2.39619 \tabularnewline
256 & 5 & 2.98516 & 2.01484 \tabularnewline
257 & 9.5 & 13.2798 & -3.77983 \tabularnewline
258 & 3 & 8.86712 & -5.86712 \tabularnewline
259 & 1.5 & 1.84297 & -0.342975 \tabularnewline
260 & 6 & 11.3072 & -5.30721 \tabularnewline
261 & 0.5 & 0.555574 & -0.0555736 \tabularnewline
262 & 6.5 & 6.48263 & 0.0173731 \tabularnewline
263 & 7.5 & 9.03438 & -1.53438 \tabularnewline
264 & 4.5 & 3.17312 & 1.32688 \tabularnewline
265 & 8 & 6.02352 & 1.97648 \tabularnewline
266 & 9 & 8.78773 & 0.212268 \tabularnewline
267 & 7.5 & 6.79027 & 0.709732 \tabularnewline
268 & 8.5 & 6.95177 & 1.54823 \tabularnewline
269 & 7 & 5.03634 & 1.96366 \tabularnewline
270 & 9.5 & 10.3519 & -0.851864 \tabularnewline
271 & 6.5 & 3.50549 & 2.99451 \tabularnewline
272 & 9.5 & 10.1908 & -0.690825 \tabularnewline
273 & 6 & 3.508 & 2.492 \tabularnewline
274 & 8 & 5.57106 & 2.42894 \tabularnewline
275 & 9.5 & 8.33724 & 1.16276 \tabularnewline
276 & 8 & 8.42529 & -0.425294 \tabularnewline
277 & 8 & 6.08057 & 1.91943 \tabularnewline
278 & 9 & 11.3157 & -2.31572 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.91223[/C][C]1.58777[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.10563[/C][C]0.894374[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.41476[/C][C]1.08524[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]4.37966[/C][C]-3.37966[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.04156[/C][C]-4.04156[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]3.14115[/C][C]2.35885[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.29379[/C][C]3.20621[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]5.92113[/C][C]0.578872[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.13844[/C][C]0.361558[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]5.60175[/C][C]-3.60175[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.29681[/C][C]-0.296814[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.25612[/C][C]-3.75612[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]4.4153[/C][C]0.584704[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.64483[/C][C]0.355166[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]6.48527[/C][C]-3.98527[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.12134[/C][C]-0.121339[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]4.4561[/C][C]1.0439[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.96717[/C][C]-1.46717[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]4.19671[/C][C]-1.19671[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]4.25867[/C][C]-0.258667[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]4.64568[/C][C]-4.14568[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]4.30941[/C][C]2.19059[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]3.71532[/C][C]0.784684[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]3.80756[/C][C]3.69244[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.40839[/C][C]0.0916118[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]2.34572[/C][C]1.65428[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]4.04147[/C][C]3.45853[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.36464[/C][C]1.63536[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]5.19723[/C][C]-1.19723[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]4.64906[/C][C]0.850939[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]4.74064[/C][C]-2.24064[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]4.32295[/C][C]1.17705[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.19223[/C][C]-1.69223[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]4.6916[/C][C]-2.1916[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.58082[/C][C]-1.08082[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.3241[/C][C]-1.8241[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]4.67616[/C][C]-0.176163[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]3.70084[/C][C]2.29916[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.1199[/C][C]-2.6199[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]5.14705[/C][C]-0.147048[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]5.91967[/C][C]-5.91967[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]5.23036[/C][C]-0.230362[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]4.45208[/C][C]2.04792[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]4.67983[/C][C]0.320168[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.18535[/C][C]0.814647[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.53733[/C][C]-1.03733[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]4.69462[/C][C]0.805378[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]4.44719[/C][C]-3.44719[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]5.12911[/C][C]2.37089[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.79023[/C][C]0.209766[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]4.76538[/C][C]0.234622[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.45783[/C][C]-4.45783[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]4.91116[/C][C]0.0888374[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]3.26315[/C][C]3.23685[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]4.86162[/C][C]2.13838[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]5.60705[/C][C]-1.10705[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]4.49891[/C][C]-4.49891[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]3.92036[/C][C]4.57964[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.58759[/C][C]-2.08759[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.42172[/C][C]2.07828[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.40151[/C][C]-1.90151[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.38367[/C][C]1.61633[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.26735[/C][C]-3.76735[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]4.38197[/C][C]4.61803[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.20298[/C][C]-0.702975[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.79445[/C][C]-2.29445[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]4.39158[/C][C]-0.391575[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]4.18533[/C][C]2.31467[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]4.70916[/C][C]2.79084[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]4.36333[/C][C]1.63667[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]4.64373[/C][C]0.356274[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.75369[/C][C]-0.253687[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.6938[/C][C]-2.1938[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.60051[/C][C]1.89949[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]4.70984[/C][C]1.79016[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.66019[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.39069[/C][C]1.10931[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]4.51469[/C][C]1.98531[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]8.13758[/C][C]-1.13758[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]6.69352[/C][C]-3.19352[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]2.65974[/C][C]-1.15974[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]0.695251[/C][C]3.30475[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]8.1512[/C][C]-0.651195[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]8.8555[/C][C]-4.3555[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]0.777438[/C][C]-0.777438[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]2.70371[/C][C]0.796294[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]5.75294[/C][C]-0.252938[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]6.3964[/C][C]-1.3964[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]7.58111[/C][C]-3.08111[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]-1.64259[/C][C]4.14259[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]6.14812[/C][C]1.35188[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]10.7722[/C][C]-3.77216[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]-1.3503[/C][C]1.3503[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]5.85561[/C][C]-1.35561[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]5.80895[/C][C]-2.80895[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]2.08547[/C][C]-0.585466[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]5.28766[/C][C]-1.78766[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]2.19331[/C][C]0.306685[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]2.8237[/C][C]2.6763[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]11.6632[/C][C]-3.66316[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.65107[/C][C]-0.651065[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]5.78589[/C][C]-0.785887[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]5.97897[/C][C]-1.47897[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]3.46074[/C][C]-0.460739[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]-0.361806[/C][C]3.36181[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]10.1358[/C][C]-2.13578[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]-0.227548[/C][C]2.72755[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]12.3654[/C][C]-5.36543[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]5.14884[/C][C]-5.14884[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]2.19034[/C][C]-1.19034[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]3.04029[/C][C]0.459711[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.88976[/C][C]0.610235[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]11.9105[/C][C]-6.4105[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]0.181953[/C][C]0.318047[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]5.64229[/C][C]1.85771[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]7.5417[/C][C]1.4583[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]8.94639[/C][C]0.553611[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]7.24737[/C][C]1.25263[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]7.60038[/C][C]-0.600377[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]6.19329[/C][C]1.80671[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.6187[/C][C]-0.618679[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]5.2396[/C][C]1.7604[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]7.55144[/C][C]0.948561[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]6.71059[/C][C]2.28941[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]12.6065[/C][C]-3.10653[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]4.17858[/C][C]-0.178579[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]4.79893[/C][C]1.20107[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]8.90976[/C][C]-0.909756[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]2.77056[/C][C]2.72944[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]9.48007[/C][C]0.0199262[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]8.21931[/C][C]-0.719309[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]7.19843[/C][C]-0.198434[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]6.74272[/C][C]0.757281[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.87204[/C][C]0.127956[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]7.35239[/C][C]-0.352388[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]8.10828[/C][C]-1.10828[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]3.47467[/C][C]2.52533[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]14.8562[/C][C]-4.85625[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]1.38765[/C][C]1.11235[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.97036[/C][C]0.0296383[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]8.51497[/C][C]-0.514975[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]4.53306[/C][C]1.46694[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]8.73544[/C][C]-0.235437[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]4.11797[/C][C]1.88203[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]8.20181[/C][C]0.798186[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]7.58405[/C][C]0.415953[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]10.3648[/C][C]-1.36476[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]5.81769[/C][C]-0.317687[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.53098[/C][C]-1.53098[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]4.64949[/C][C]0.850506[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]14.1737[/C][C]-5.17372[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]1.93101[/C][C]0.0689905[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]7.61376[/C][C]0.886239[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]7.87158[/C][C]1.12842[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]7.06501[/C][C]1.43499[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]7.9154[/C][C]1.0846[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]6.01857[/C][C]1.48143[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]8.50384[/C][C]1.49616[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.81803[/C][C]0.181965[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]8.59565[/C][C]-1.09565[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]2.95627[/C][C]3.04373[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.81141[/C][C]1.68859[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]9.39537[/C][C]-0.895375[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]5.56764[/C][C]2.43236[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]7.77477[/C][C]2.22523[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]9.87267[/C][C]0.627327[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]4.10276[/C][C]2.39724[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]8.54327[/C][C]0.956733[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]8.61233[/C][C]-0.112334[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]8.9734[/C][C]-1.4734[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]3.79273[/C][C]1.20727[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]4.91317[/C][C]3.08683[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]10.8194[/C][C]-0.819356[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.38455[/C][C]-0.384547[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.82669[/C][C]-0.32669[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]4.00977[/C][C]3.49023[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]10.6822[/C][C]-1.18219[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]3.34637[/C][C]2.65363[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]9.76191[/C][C]0.238085[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]10.5299[/C][C]-3.52987[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]4.3981[/C][C]-1.3981[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]6.0535[/C][C]-0.0534992[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]5.45998[/C][C]1.54002[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]9.77883[/C][C]0.221166[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]10.0144[/C][C]-3.01441[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]2.96265[/C][C]0.537345[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]5.49298[/C][C]2.50702[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]12.019[/C][C]-2.01905[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]6.87976[/C][C]-1.37976[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]5.97014[/C][C]0.0298594[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]7.17112[/C][C]-0.671125[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]3.76655[/C][C]2.73345[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]11.3499[/C][C]-2.84994[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]0.683184[/C][C]3.31682[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]8.17702[/C][C]1.32298[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]7.1053[/C][C]0.894702[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]10.8577[/C][C]-2.35772[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]4.26314[/C][C]1.23686[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]4.46615[/C][C]2.53385[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]7.6504[/C][C]1.3496[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]6.18496[/C][C]1.81504[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]9.21108[/C][C]0.78892[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]8.95855[/C][C]-0.958549[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]5.34007[/C][C]0.659933[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]10.1177[/C][C]-2.11768[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]3.16827[/C][C]1.83173[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]10.6285[/C][C]-1.62848[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]3.05196[/C][C]1.44804[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]4.5692[/C][C]3.9308[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.48954[/C][C]2.01046[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]8.35337[/C][C]0.146633[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.2087[/C][C]0.291297[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]9.05084[/C][C]-1.55084[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]4.04331[/C][C]0.956693[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]6.82276[/C][C]0.177238[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]8.88265[/C][C]-0.882652[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.62915[/C][C]1.87085[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]6.76919[/C][C]1.73081[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]9.42381[/C][C]0.0761921[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]6.65222[/C][C]0.347785[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]6.15612[/C][C]1.84388[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]10.1929[/C][C]-1.69293[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]4.87475[/C][C]-1.37475[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]6.45539[/C][C]0.0446062[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]3.92817[/C][C]2.57183[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]8.88458[/C][C]1.61542[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]7.8513[/C][C]0.648704[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]5.07831[/C][C]2.92169[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.625[/C][C]2.375[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]8.37537[/C][C]1.62463[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]7.70696[/C][C]1.79304[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]6.5798[/C][C]2.4202[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]9.00024[/C][C]0.999764[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]10.5156[/C][C]-3.01555[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]6.24327[/C][C]-1.74327[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.7837[/C][C]-7.28369[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]0.54474[/C][C]-0.0447405[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]8.45227[/C][C]-1.95227[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]6.02849[/C][C]-1.52849[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.75464[/C][C]-1.25464[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]6.72148[/C][C]-1.72148[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]7.5407[/C][C]-1.5407[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]2.90605[/C][C]1.09395[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]5.14768[/C][C]2.85232[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]10.9209[/C][C]-0.420913[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]4.60311[/C][C]1.89689[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]7.16946[/C][C]0.830543[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]10.2912[/C][C]-1.79119[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]5.65316[/C][C]-0.153164[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]8.91122[/C][C]-1.91122[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]8.3462[/C][C]-3.3462[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]6.19769[/C][C]-2.69769[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]3.12469[/C][C]1.87531[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]6.29005[/C][C]2.70995[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]10.8962[/C][C]-2.39619[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]2.98516[/C][C]2.01484[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]13.2798[/C][C]-3.77983[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]8.86712[/C][C]-5.86712[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]1.84297[/C][C]-0.342975[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]11.3072[/C][C]-5.30721[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]0.555574[/C][C]-0.0555736[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]6.48263[/C][C]0.0173731[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]9.03438[/C][C]-1.53438[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]3.17312[/C][C]1.32688[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]6.02352[/C][C]1.97648[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]8.78773[/C][C]0.212268[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]6.79027[/C][C]0.709732[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]6.95177[/C][C]1.54823[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]5.03634[/C][C]1.96366[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]10.3519[/C][C]-0.851864[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]3.50549[/C][C]2.99451[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]10.1908[/C][C]-0.690825[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]3.508[/C][C]2.492[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.57106[/C][C]2.42894[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]8.33724[/C][C]1.16276[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]8.42529[/C][C]-0.425294[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]6.08057[/C][C]1.91943[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]11.3157[/C][C]-2.31572[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.91223	1.58777
2	6	5.10563	0.894374
3	6.5	5.41476	1.08524
4	1	4.37966	-3.37966
5	1	5.04156	-4.04156
6	5.5	3.14115	2.35885
7	8.5	5.29379	3.20621
8	6.5	5.92113	0.578872
9	4.5	4.13844	0.361558
10	2	5.60175	-3.60175
11	5	5.29681	-0.296814
12	0.5	4.25612	-3.75612
13	5	4.4153	0.584704
14	5	4.64483	0.355166
15	2.5	6.48527	-3.98527
16	5	5.12134	-0.121339
17	5.5	4.4561	1.0439
18	3.5	4.96717	-1.46717
19	3	4.19671	-1.19671
20	4	4.25867	-0.258667
21	0.5	4.64568	-4.14568
22	6.5	4.30941	2.19059
23	4.5	3.71532	0.784684
24	7.5	3.80756	3.69244
25	5.5	5.40839	0.0916118
26	4	2.34572	1.65428
27	7.5	4.04147	3.45853
28	7	5.36464	1.63536
29	4	5.19723	-1.19723
30	5.5	4.64906	0.850939
31	2.5	4.74064	-2.24064
32	5.5	4.32295	1.17705
33	3.5	5.19223	-1.69223
34	2.5	4.6916	-2.1916
35	4.5	5.58082	-1.08082
36	4.5	6.3241	-1.8241
37	4.5	4.67616	-0.176163
38	6	3.70084	2.29916
39	2.5	5.1199	-2.6199
40	5	5.14705	-0.147048
41	0	5.91967	-5.91967
42	5	5.23036	-0.230362
43	6.5	4.45208	2.04792
44	5	4.67983	0.320168
45	6	5.18535	0.814647
46	4.5	5.53733	-1.03733
47	5.5	4.69462	0.805378
48	1	4.44719	-3.44719
49	7.5	5.12911	2.37089
50	6	5.79023	0.209766
51	5	4.76538	0.234622
52	1	5.45783	-4.45783
53	5	4.91116	0.0888374
54	6.5	3.26315	3.23685
55	7	4.86162	2.13838
56	4.5	5.60705	-1.10705
57	0	4.49891	-4.49891
58	8.5	3.92036	4.57964
59	3.5	5.58759	-2.08759
60	7.5	5.42172	2.07828
61	3.5	5.40151	-1.90151
62	6	4.38367	1.61633
63	1.5	5.26735	-3.76735
64	9	4.38197	4.61803
65	3.5	4.20298	-0.702975
66	3.5	5.79445	-2.29445
67	4	4.39158	-0.391575
68	6.5	4.18533	2.31467
69	7.5	4.70916	2.79084
70	6	4.36333	1.63667
71	5	4.64373	0.356274
72	5.5	5.75369	-0.253687
73	3.5	5.6938	-2.1938
74	7.5	5.60051	1.89949
75	6.5	4.70984	1.79016
76	NA	NA	1.66019
77	6.5	5.39069	1.10931
78	6.5	4.51469	1.98531
79	7	8.13758	-1.13758
80	3.5	6.69352	-3.19352
81	1.5	2.65974	-1.15974
82	4	0.695251	3.30475
83	7.5	8.1512	-0.651195
84	4.5	8.8555	-4.3555
85	0	0.777438	-0.777438
86	3.5	2.70371	0.796294
87	5.5	5.75294	-0.252938
88	5	6.3964	-1.3964
89	4.5	7.58111	-3.08111
90	2.5	-1.64259	4.14259
91	7.5	6.14812	1.35188
92	7	10.7722	-3.77216
93	0	-1.3503	1.3503
94	4.5	5.85561	-1.35561
95	3	5.80895	-2.80895
96	1.5	2.08547	-0.585466
97	3.5	5.28766	-1.78766
98	2.5	2.19331	0.306685
99	5.5	2.8237	2.6763
100	8	11.6632	-3.66316
101	1	1.65107	-0.651065
102	5	5.78589	-0.785887
103	4.5	5.97897	-1.47897
104	3	3.46074	-0.460739
105	3	-0.361806	3.36181
106	8	10.1358	-2.13578
107	2.5	-0.227548	2.72755
108	7	12.3654	-5.36543
109	0	5.14884	-5.14884
110	1	2.19034	-1.19034
111	3.5	3.04029	0.459711
112	5.5	4.88976	0.610235
113	5.5	11.9105	-6.4105
114	0.5	0.181953	0.318047
115	7.5	5.64229	1.85771
116	9	7.5417	1.4583
117	9.5	8.94639	0.553611
118	8.5	7.24737	1.25263
119	7	7.60038	-0.600377
120	8	6.19329	1.80671
121	10	10.6187	-0.618679
122	7	5.2396	1.7604
123	8.5	7.55144	0.948561
124	9	6.71059	2.28941
125	9.5	12.6065	-3.10653
126	4	4.17858	-0.178579
127	6	4.79893	1.20107
128	8	8.90976	-0.909756
129	5.5	2.77056	2.72944
130	9.5	9.48007	0.0199262
131	7.5	8.21931	-0.719309
132	7	7.19843	-0.198434
133	7.5	6.74272	0.757281
134	8	7.87204	0.127956
135	7	7.35239	-0.352388
136	7	8.10828	-1.10828
137	6	3.47467	2.52533
138	10	14.8562	-4.85625
139	2.5	1.38765	1.11235
140	9	8.97036	0.0296383
141	8	8.51497	-0.514975
142	6	4.53306	1.46694
143	8.5	8.73544	-0.235437
144	6	4.11797	1.88203
145	9	8.20181	0.798186
146	8	7.58405	0.415953
147	9	10.3648	-1.36476
148	5.5	5.81769	-0.317687
149	7	8.53098	-1.53098
150	5.5	4.64949	0.850506
151	9	14.1737	-5.17372
152	2	1.93101	0.0689905
153	8.5	7.61376	0.886239
154	9	7.87158	1.12842
155	8.5	7.06501	1.43499
156	9	7.9154	1.0846
157	7.5	6.01857	1.48143
158	10	8.50384	1.49616
159	9	8.81803	0.181965
160	7.5	8.59565	-1.09565
161	6	2.95627	3.04373
162	10.5	8.81141	1.68859
163	8.5	9.39537	-0.895375
164	8	5.56764	2.43236
165	10	7.77477	2.22523
166	10.5	9.87267	0.627327
167	6.5	4.10276	2.39724
168	9.5	8.54327	0.956733
169	8.5	8.61233	-0.112334
170	7.5	8.9734	-1.4734
171	5	3.79273	1.20727
172	8	4.91317	3.08683
173	10	10.8194	-0.819356
174	7	7.38455	-0.384547
175	7.5	7.82669	-0.32669
176	7.5	4.00977	3.49023
177	9.5	10.6822	-1.18219
178	6	3.34637	2.65363
179	10	9.76191	0.238085
180	7	10.5299	-3.52987
181	3	4.3981	-1.3981
182	6	6.0535	-0.0534992
183	7	5.45998	1.54002
184	10	9.77883	0.221166
185	7	10.0144	-3.01441
186	3.5	2.96265	0.537345
187	8	5.49298	2.50702
188	10	12.019	-2.01905
189	5.5	6.87976	-1.37976
190	6	5.97014	0.0298594
191	6.5	7.17112	-0.671125
192	6.5	3.76655	2.73345
193	8.5	11.3499	-2.84994
194	4	0.683184	3.31682
195	9.5	8.17702	1.32298
196	8	7.1053	0.894702
197	8.5	10.8577	-2.35772
198	5.5	4.26314	1.23686
199	7	4.46615	2.53385
200	9	7.6504	1.3496
201	8	6.18496	1.81504
202	10	9.21108	0.78892
203	8	8.95855	-0.958549
204	6	5.34007	0.659933
205	8	10.1177	-2.11768
206	5	3.16827	1.83173
207	9	10.6285	-1.62848
208	4.5	3.05196	1.44804
209	8.5	4.5692	3.9308
210	9.5	7.48954	2.01046
211	8.5	8.35337	0.146633
212	7.5	7.2087	0.291297
213	7.5	9.05084	-1.55084
214	5	4.04331	0.956693
215	7	6.82276	0.177238
216	8	8.88265	-0.882652
217	5.5	3.62915	1.87085
218	8.5	6.76919	1.73081
219	9.5	9.42381	0.0761921
220	7	6.65222	0.347785
221	8	6.15612	1.84388
222	8.5	10.1929	-1.69293
223	3.5	4.87475	-1.37475
224	6.5	6.45539	0.0446062
225	6.5	3.92817	2.57183
226	10.5	8.88458	1.61542
227	8.5	7.8513	0.648704
228	8	5.07831	2.92169
229	10	7.625	2.375
230	10	8.37537	1.62463
231	9.5	7.70696	1.79304
232	9	6.5798	2.4202
233	10	9.00024	0.999764
234	7.5	10.5156	-3.01555
235	4.5	6.24327	-1.74327
236	4.5	11.7837	-7.28369
237	0.5	0.54474	-0.0447405
238	6.5	8.45227	-1.95227
239	4.5	6.02849	-1.52849
240	5.5	6.75464	-1.25464
241	5	6.72148	-1.72148
242	6	7.5407	-1.5407
243	4	2.90605	1.09395
244	8	5.14768	2.85232
245	10.5	10.9209	-0.420913
246	6.5	4.60311	1.89689
247	8	7.16946	0.830543
248	8.5	10.2912	-1.79119
249	5.5	5.65316	-0.153164
250	7	8.91122	-1.91122
251	5	8.3462	-3.3462
252	3.5	6.19769	-2.69769
253	5	3.12469	1.87531
254	9	6.29005	2.70995
255	8.5	10.8962	-2.39619
256	5	2.98516	2.01484
257	9.5	13.2798	-3.77983
258	3	8.86712	-5.86712
259	1.5	1.84297	-0.342975
260	6	11.3072	-5.30721
261	0.5	0.555574	-0.0555736
262	6.5	6.48263	0.0173731
263	7.5	9.03438	-1.53438
264	4.5	3.17312	1.32688
265	8	6.02352	1.97648
266	9	8.78773	0.212268
267	7.5	6.79027	0.709732
268	8.5	6.95177	1.54823
269	7	5.03634	1.96366
270	9.5	10.3519	-0.851864
271	6.5	3.50549	2.99451
272	9.5	10.1908	-0.690825
273	6	3.508	2.492
274	8	5.57106	2.42894
275	9.5	8.33724	1.16276
276	8	8.42529	-0.425294
277	8	6.08057	1.91943
278	9	11.3157	-2.31572
279	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
17	0.697331	0.605339	0.302669
18	0.548649	0.902702	0.451351
19	0.443094	0.886188	0.556906
20	0.341926	0.683851	0.658074
21	0.273074	0.546149	0.726926
22	0.205574	0.411149	0.794426
23	0.283875	0.567749	0.716125
24	0.311489	0.622978	0.688511
25	0.267941	0.535881	0.732059
26	0.234213	0.468425	0.765787
27	0.220117	0.440234	0.779883
28	0.188369	0.376738	0.811631
29	0.151118	0.302236	0.848882
30	0.110861	0.221723	0.889139
31	0.106164	0.212328	0.893836
32	0.084586	0.169172	0.915414
33	0.0818289	0.163658	0.918171
34	0.103745	0.20749	0.896255
35	0.0757285	0.151457	0.924271
36	0.0573453	0.114691	0.942655
37	0.0405748	0.0811495	0.959425
38	0.0361925	0.0723849	0.963808
39	0.0477793	0.0955587	0.952221
40	0.0518964	0.103793	0.948104
41	0.0840854	0.168171	0.915915
42	0.0650374	0.130075	0.934963
43	0.0649022	0.129804	0.935098
44	0.0506869	0.101374	0.949313
45	0.0590976	0.118195	0.940902
46	0.0602943	0.120589	0.939706
47	0.0619987	0.123997	0.938001
48	0.0679608	0.135922	0.932039
49	0.116875	0.233749	0.883125
50	0.121577	0.243153	0.878423
51	0.0977281	0.195456	0.902272
52	0.125561	0.251123	0.874439
53	0.106284	0.212568	0.893716
54	0.112853	0.225707	0.887147
55	0.258023	0.516047	0.741977
56	0.221484	0.442968	0.778516
57	0.538154	0.923693	0.461846
58	0.622121	0.755758	0.377879
59	0.603898	0.792204	0.396102
60	0.638491	0.723017	0.361509
61	0.613085	0.77383	0.386915
62	0.576278	0.847443	0.423722
63	0.681623	0.636753	0.318377
64	0.751944	0.496111	0.248056
65	0.75319	0.493619	0.24681
66	0.729955	0.540089	0.270045
67	0.693209	0.613582	0.306791
68	0.682206	0.635587	0.317794
69	0.712811	0.574377	0.287189
70	0.689764	0.620473	0.310236
71	0.656056	0.687888	0.343944
72	0.620263	0.759473	0.379737
73	0.597373	0.805254	0.402627
74	0.657567	0.684865	0.342433
75	0.631572	0.736855	0.368428
76	0.61332	0.773359	0.38668
77	0.581595	0.83681	0.418405
78	0.600325	0.799349	0.399675
79	0.565311	0.869378	0.434689
80	0.559845	0.880311	0.440155
81	0.522083	0.955835	0.477917
82	0.553639	0.892721	0.446361
83	0.515675	0.968649	0.484325
84	0.61217	0.77566	0.38783
85	0.583766	0.832469	0.416234
86	0.553361	0.893278	0.446639
87	0.519575	0.96085	0.480425
88	0.486928	0.973856	0.513072
89	0.498888	0.997775	0.501112
90	0.577244	0.845513	0.422756
91	0.602759	0.794483	0.397241
92	0.698685	0.602631	0.301315
93	0.686176	0.627647	0.313824
94	0.660873	0.678253	0.339127
95	0.675721	0.648558	0.324279
96	0.652986	0.694028	0.347014
97	0.645748	0.708504	0.354252
98	0.619415	0.76117	0.380585
99	0.661034	0.677933	0.338966
100	0.696409	0.607182	0.303591
101	0.668141	0.663718	0.331859
102	0.634617	0.730767	0.365383
103	0.630987	0.738027	0.369013
104	0.605805	0.788391	0.394195
105	0.675542	0.648916	0.324458
106	0.662627	0.674746	0.337373
107	0.738518	0.522964	0.261482
108	0.820091	0.359818	0.179909
109	0.877546	0.244908	0.122454
110	0.862163	0.275674	0.137837
111	0.84199	0.316021	0.15801
112	0.829402	0.341197	0.170598
113	0.897194	0.205612	0.102806
114	0.924618	0.150763	0.0753816
115	0.960483	0.0790343	0.0395172
116	0.972398	0.0552035	0.0276017
117	0.976442	0.0471159	0.0235579
118	0.976563	0.0468733	0.0234366
119	0.972572	0.0548556	0.0274278
120	0.976633	0.0467337	0.0233669
121	0.971229	0.0575413	0.0287707
122	0.971454	0.0570928	0.0285464
123	0.968709	0.062582	0.031291
124	0.973503	0.0529947	0.0264974
125	0.978376	0.0432471	0.0216236
126	0.973382	0.0532359	0.026618
127	0.9708	0.0583992	0.0291996
128	0.964729	0.0705422	0.0352711
129	0.97234	0.0553197	0.0276598
130	0.966521	0.0669585	0.0334793
131	0.960934	0.078132	0.039066
132	0.955462	0.0890767	0.0445384
133	0.948063	0.103875	0.0519374
134	0.941868	0.116263	0.0581316
135	0.930918	0.138164	0.0690821
136	0.923476	0.153047	0.0765236
137	0.928171	0.143657	0.0718287
138	0.960367	0.0792651	0.0396325
139	0.955248	0.0895042	0.0447521
140	0.946657	0.106686	0.0533429
141	0.939779	0.120442	0.0602208
142	0.93498	0.130039	0.0650196
143	0.923168	0.153665	0.0768323
144	0.921025	0.15795	0.0789752
145	0.910955	0.178091	0.0890454
146	0.89707	0.20586	0.10293
147	0.885173	0.229654	0.114827
148	0.866718	0.266565	0.133282
149	0.855699	0.288601	0.144301
150	0.837824	0.324351	0.162176
151	0.912284	0.175432	0.0877158
152	0.897507	0.204986	0.102493
153	0.885703	0.228593	0.114297
154	0.878588	0.242825	0.121412
155	0.870985	0.25803	0.129015
156	0.859004	0.281992	0.140996
157	0.851554	0.296892	0.148446
158	0.842134	0.315732	0.157866
159	0.822232	0.355537	0.177768
160	0.812133	0.375733	0.187867
161	0.832754	0.334491	0.167246
162	0.822844	0.354312	0.177156
163	0.806902	0.386195	0.193098
164	0.809916	0.380168	0.190084
165	0.80476	0.390481	0.19524
166	0.779611	0.440779	0.220389
167	0.786412	0.427176	0.213588
168	0.762001	0.475999	0.237999
169	0.738793	0.522415	0.261207
170	0.736035	0.527931	0.263965
171	0.721604	0.556792	0.278396
172	0.748896	0.502207	0.251104
173	0.722082	0.555835	0.277918
174	0.691303	0.617394	0.308697
175	0.658968	0.682064	0.341032
176	0.719707	0.560587	0.280293
177	0.692826	0.614349	0.307174
178	0.740842	0.518316	0.259158
179	0.720107	0.559785	0.279893
180	0.793505	0.412991	0.206495
181	0.78135	0.4373	0.21865
182	0.752569	0.494862	0.247431
183	0.745652	0.508696	0.254348
184	0.716577	0.566845	0.283423
185	0.736369	0.527263	0.263631
186	0.704939	0.590121	0.295061
187	0.709568	0.580863	0.290432
188	0.713654	0.572692	0.286346
189	0.715293	0.569415	0.284707
190	0.693206	0.613587	0.306794
191	0.661828	0.676343	0.338172
192	0.660922	0.678156	0.339078
193	0.746648	0.506704	0.253352
194	0.765113	0.469774	0.234887
195	0.740787	0.518426	0.259213
196	0.708893	0.582214	0.291107
197	0.695572	0.608856	0.304428
198	0.665365	0.669271	0.334635
199	0.656493	0.687013	0.343507
200	0.625545	0.748909	0.374455
201	0.681742	0.636517	0.318258
202	0.65449	0.69102	0.34551
203	0.627342	0.745315	0.372658
204	0.588171	0.823658	0.411829
205	0.587493	0.825014	0.412507
206	0.555391	0.889218	0.444609
207	0.524721	0.950558	0.475279
208	0.49738	0.994759	0.50262
209	0.498021	0.996041	0.501979
210	0.465188	0.930376	0.534812
211	0.422133	0.844267	0.577867
212	0.407995	0.81599	0.592005
213	0.403284	0.806567	0.596716
214	0.364426	0.728853	0.635574
215	0.325223	0.650446	0.674777
216	0.291718	0.583435	0.708282
217	0.28292	0.565839	0.71708
218	0.304111	0.608221	0.695889
219	0.266845	0.533691	0.733155
220	0.231169	0.462337	0.768831
221	0.222443	0.444887	0.777557
222	0.240796	0.481591	0.759204
223	0.209375	0.418749	0.790625
224	0.177698	0.355396	0.822302
225	0.157159	0.314318	0.842841
226	0.135459	0.270918	0.864541
227	0.111329	0.222659	0.888671
228	0.113776	0.227552	0.886224
229	0.193765	0.387529	0.806235
230	0.184358	0.368716	0.815642
231	0.1887	0.377401	0.8113
232	0.217061	0.434122	0.782939
233	0.190762	0.381524	0.809238
234	0.168479	0.336959	0.831521
235	0.142829	0.285658	0.857171
236	0.535856	0.928289	0.464144
237	0.482217	0.964434	0.517783
238	0.432846	0.865693	0.567154
239	0.387651	0.775302	0.612349
240	0.33365	0.6673	0.66635
241	0.304256	0.608511	0.695744
242	0.25819	0.516379	0.74181
243	0.217142	0.434283	0.782858
244	0.189361	0.378721	0.810639
245	0.152233	0.304466	0.847767
246	0.167564	0.335127	0.832436
247	0.152422	0.304845	0.847578
248	0.125533	0.251067	0.874467
249	0.109496	0.218991	0.890504
250	0.0805682	0.161136	0.919432
251	0.0809332	0.161866	0.919067
252	0.074617	0.149234	0.925383
253	0.0604741	0.120948	0.939526
254	0.141977	0.283954	0.858023
255	0.380524	0.761047	0.619476
256	0.299984	0.599968	0.700016
257	0.457203	0.914407	0.542797
258	0.68868	0.62264	0.31132
259	0.566424	0.867153	0.433576
260	0.7319	0.536199	0.2681
261	0.592541	0.814919	0.407459
262	0.425491	0.850982	0.574509

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
17 & 0.697331 & 0.605339 & 0.302669 \tabularnewline
18 & 0.548649 & 0.902702 & 0.451351 \tabularnewline
19 & 0.443094 & 0.886188 & 0.556906 \tabularnewline
20 & 0.341926 & 0.683851 & 0.658074 \tabularnewline
21 & 0.273074 & 0.546149 & 0.726926 \tabularnewline
22 & 0.205574 & 0.411149 & 0.794426 \tabularnewline
23 & 0.283875 & 0.567749 & 0.716125 \tabularnewline
24 & 0.311489 & 0.622978 & 0.688511 \tabularnewline
25 & 0.267941 & 0.535881 & 0.732059 \tabularnewline
26 & 0.234213 & 0.468425 & 0.765787 \tabularnewline
27 & 0.220117 & 0.440234 & 0.779883 \tabularnewline
28 & 0.188369 & 0.376738 & 0.811631 \tabularnewline
29 & 0.151118 & 0.302236 & 0.848882 \tabularnewline
30 & 0.110861 & 0.221723 & 0.889139 \tabularnewline
31 & 0.106164 & 0.212328 & 0.893836 \tabularnewline
32 & 0.084586 & 0.169172 & 0.915414 \tabularnewline
33 & 0.0818289 & 0.163658 & 0.918171 \tabularnewline
34 & 0.103745 & 0.20749 & 0.896255 \tabularnewline
35 & 0.0757285 & 0.151457 & 0.924271 \tabularnewline
36 & 0.0573453 & 0.114691 & 0.942655 \tabularnewline
37 & 0.0405748 & 0.0811495 & 0.959425 \tabularnewline
38 & 0.0361925 & 0.0723849 & 0.963808 \tabularnewline
39 & 0.0477793 & 0.0955587 & 0.952221 \tabularnewline
40 & 0.0518964 & 0.103793 & 0.948104 \tabularnewline
41 & 0.0840854 & 0.168171 & 0.915915 \tabularnewline
42 & 0.0650374 & 0.130075 & 0.934963 \tabularnewline
43 & 0.0649022 & 0.129804 & 0.935098 \tabularnewline
44 & 0.0506869 & 0.101374 & 0.949313 \tabularnewline
45 & 0.0590976 & 0.118195 & 0.940902 \tabularnewline
46 & 0.0602943 & 0.120589 & 0.939706 \tabularnewline
47 & 0.0619987 & 0.123997 & 0.938001 \tabularnewline
48 & 0.0679608 & 0.135922 & 0.932039 \tabularnewline
49 & 0.116875 & 0.233749 & 0.883125 \tabularnewline
50 & 0.121577 & 0.243153 & 0.878423 \tabularnewline
51 & 0.0977281 & 0.195456 & 0.902272 \tabularnewline
52 & 0.125561 & 0.251123 & 0.874439 \tabularnewline
53 & 0.106284 & 0.212568 & 0.893716 \tabularnewline
54 & 0.112853 & 0.225707 & 0.887147 \tabularnewline
55 & 0.258023 & 0.516047 & 0.741977 \tabularnewline
56 & 0.221484 & 0.442968 & 0.778516 \tabularnewline
57 & 0.538154 & 0.923693 & 0.461846 \tabularnewline
58 & 0.622121 & 0.755758 & 0.377879 \tabularnewline
59 & 0.603898 & 0.792204 & 0.396102 \tabularnewline
60 & 0.638491 & 0.723017 & 0.361509 \tabularnewline
61 & 0.613085 & 0.77383 & 0.386915 \tabularnewline
62 & 0.576278 & 0.847443 & 0.423722 \tabularnewline
63 & 0.681623 & 0.636753 & 0.318377 \tabularnewline
64 & 0.751944 & 0.496111 & 0.248056 \tabularnewline
65 & 0.75319 & 0.493619 & 0.24681 \tabularnewline
66 & 0.729955 & 0.540089 & 0.270045 \tabularnewline
67 & 0.693209 & 0.613582 & 0.306791 \tabularnewline
68 & 0.682206 & 0.635587 & 0.317794 \tabularnewline
69 & 0.712811 & 0.574377 & 0.287189 \tabularnewline
70 & 0.689764 & 0.620473 & 0.310236 \tabularnewline
71 & 0.656056 & 0.687888 & 0.343944 \tabularnewline
72 & 0.620263 & 0.759473 & 0.379737 \tabularnewline
73 & 0.597373 & 0.805254 & 0.402627 \tabularnewline
74 & 0.657567 & 0.684865 & 0.342433 \tabularnewline
75 & 0.631572 & 0.736855 & 0.368428 \tabularnewline
76 & 0.61332 & 0.773359 & 0.38668 \tabularnewline
77 & 0.581595 & 0.83681 & 0.418405 \tabularnewline
78 & 0.600325 & 0.799349 & 0.399675 \tabularnewline
79 & 0.565311 & 0.869378 & 0.434689 \tabularnewline
80 & 0.559845 & 0.880311 & 0.440155 \tabularnewline
81 & 0.522083 & 0.955835 & 0.477917 \tabularnewline
82 & 0.553639 & 0.892721 & 0.446361 \tabularnewline
83 & 0.515675 & 0.968649 & 0.484325 \tabularnewline
84 & 0.61217 & 0.77566 & 0.38783 \tabularnewline
85 & 0.583766 & 0.832469 & 0.416234 \tabularnewline
86 & 0.553361 & 0.893278 & 0.446639 \tabularnewline
87 & 0.519575 & 0.96085 & 0.480425 \tabularnewline
88 & 0.486928 & 0.973856 & 0.513072 \tabularnewline
89 & 0.498888 & 0.997775 & 0.501112 \tabularnewline
90 & 0.577244 & 0.845513 & 0.422756 \tabularnewline
91 & 0.602759 & 0.794483 & 0.397241 \tabularnewline
92 & 0.698685 & 0.602631 & 0.301315 \tabularnewline
93 & 0.686176 & 0.627647 & 0.313824 \tabularnewline
94 & 0.660873 & 0.678253 & 0.339127 \tabularnewline
95 & 0.675721 & 0.648558 & 0.324279 \tabularnewline
96 & 0.652986 & 0.694028 & 0.347014 \tabularnewline
97 & 0.645748 & 0.708504 & 0.354252 \tabularnewline
98 & 0.619415 & 0.76117 & 0.380585 \tabularnewline
99 & 0.661034 & 0.677933 & 0.338966 \tabularnewline
100 & 0.696409 & 0.607182 & 0.303591 \tabularnewline
101 & 0.668141 & 0.663718 & 0.331859 \tabularnewline
102 & 0.634617 & 0.730767 & 0.365383 \tabularnewline
103 & 0.630987 & 0.738027 & 0.369013 \tabularnewline
104 & 0.605805 & 0.788391 & 0.394195 \tabularnewline
105 & 0.675542 & 0.648916 & 0.324458 \tabularnewline
106 & 0.662627 & 0.674746 & 0.337373 \tabularnewline
107 & 0.738518 & 0.522964 & 0.261482 \tabularnewline
108 & 0.820091 & 0.359818 & 0.179909 \tabularnewline
109 & 0.877546 & 0.244908 & 0.122454 \tabularnewline
110 & 0.862163 & 0.275674 & 0.137837 \tabularnewline
111 & 0.84199 & 0.316021 & 0.15801 \tabularnewline
112 & 0.829402 & 0.341197 & 0.170598 \tabularnewline
113 & 0.897194 & 0.205612 & 0.102806 \tabularnewline
114 & 0.924618 & 0.150763 & 0.0753816 \tabularnewline
115 & 0.960483 & 0.0790343 & 0.0395172 \tabularnewline
116 & 0.972398 & 0.0552035 & 0.0276017 \tabularnewline
117 & 0.976442 & 0.0471159 & 0.0235579 \tabularnewline
118 & 0.976563 & 0.0468733 & 0.0234366 \tabularnewline
119 & 0.972572 & 0.0548556 & 0.0274278 \tabularnewline
120 & 0.976633 & 0.0467337 & 0.0233669 \tabularnewline
121 & 0.971229 & 0.0575413 & 0.0287707 \tabularnewline
122 & 0.971454 & 0.0570928 & 0.0285464 \tabularnewline
123 & 0.968709 & 0.062582 & 0.031291 \tabularnewline
124 & 0.973503 & 0.0529947 & 0.0264974 \tabularnewline
125 & 0.978376 & 0.0432471 & 0.0216236 \tabularnewline
126 & 0.973382 & 0.0532359 & 0.026618 \tabularnewline
127 & 0.9708 & 0.0583992 & 0.0291996 \tabularnewline
128 & 0.964729 & 0.0705422 & 0.0352711 \tabularnewline
129 & 0.97234 & 0.0553197 & 0.0276598 \tabularnewline
130 & 0.966521 & 0.0669585 & 0.0334793 \tabularnewline
131 & 0.960934 & 0.078132 & 0.039066 \tabularnewline
132 & 0.955462 & 0.0890767 & 0.0445384 \tabularnewline
133 & 0.948063 & 0.103875 & 0.0519374 \tabularnewline
134 & 0.941868 & 0.116263 & 0.0581316 \tabularnewline
135 & 0.930918 & 0.138164 & 0.0690821 \tabularnewline
136 & 0.923476 & 0.153047 & 0.0765236 \tabularnewline
137 & 0.928171 & 0.143657 & 0.0718287 \tabularnewline
138 & 0.960367 & 0.0792651 & 0.0396325 \tabularnewline
139 & 0.955248 & 0.0895042 & 0.0447521 \tabularnewline
140 & 0.946657 & 0.106686 & 0.0533429 \tabularnewline
141 & 0.939779 & 0.120442 & 0.0602208 \tabularnewline
142 & 0.93498 & 0.130039 & 0.0650196 \tabularnewline
143 & 0.923168 & 0.153665 & 0.0768323 \tabularnewline
144 & 0.921025 & 0.15795 & 0.0789752 \tabularnewline
145 & 0.910955 & 0.178091 & 0.0890454 \tabularnewline
146 & 0.89707 & 0.20586 & 0.10293 \tabularnewline
147 & 0.885173 & 0.229654 & 0.114827 \tabularnewline
148 & 0.866718 & 0.266565 & 0.133282 \tabularnewline
149 & 0.855699 & 0.288601 & 0.144301 \tabularnewline
150 & 0.837824 & 0.324351 & 0.162176 \tabularnewline
151 & 0.912284 & 0.175432 & 0.0877158 \tabularnewline
152 & 0.897507 & 0.204986 & 0.102493 \tabularnewline
153 & 0.885703 & 0.228593 & 0.114297 \tabularnewline
154 & 0.878588 & 0.242825 & 0.121412 \tabularnewline
155 & 0.870985 & 0.25803 & 0.129015 \tabularnewline
156 & 0.859004 & 0.281992 & 0.140996 \tabularnewline
157 & 0.851554 & 0.296892 & 0.148446 \tabularnewline
158 & 0.842134 & 0.315732 & 0.157866 \tabularnewline
159 & 0.822232 & 0.355537 & 0.177768 \tabularnewline
160 & 0.812133 & 0.375733 & 0.187867 \tabularnewline
161 & 0.832754 & 0.334491 & 0.167246 \tabularnewline
162 & 0.822844 & 0.354312 & 0.177156 \tabularnewline
163 & 0.806902 & 0.386195 & 0.193098 \tabularnewline
164 & 0.809916 & 0.380168 & 0.190084 \tabularnewline
165 & 0.80476 & 0.390481 & 0.19524 \tabularnewline
166 & 0.779611 & 0.440779 & 0.220389 \tabularnewline
167 & 0.786412 & 0.427176 & 0.213588 \tabularnewline
168 & 0.762001 & 0.475999 & 0.237999 \tabularnewline
169 & 0.738793 & 0.522415 & 0.261207 \tabularnewline
170 & 0.736035 & 0.527931 & 0.263965 \tabularnewline
171 & 0.721604 & 0.556792 & 0.278396 \tabularnewline
172 & 0.748896 & 0.502207 & 0.251104 \tabularnewline
173 & 0.722082 & 0.555835 & 0.277918 \tabularnewline
174 & 0.691303 & 0.617394 & 0.308697 \tabularnewline
175 & 0.658968 & 0.682064 & 0.341032 \tabularnewline
176 & 0.719707 & 0.560587 & 0.280293 \tabularnewline
177 & 0.692826 & 0.614349 & 0.307174 \tabularnewline
178 & 0.740842 & 0.518316 & 0.259158 \tabularnewline
179 & 0.720107 & 0.559785 & 0.279893 \tabularnewline
180 & 0.793505 & 0.412991 & 0.206495 \tabularnewline
181 & 0.78135 & 0.4373 & 0.21865 \tabularnewline
182 & 0.752569 & 0.494862 & 0.247431 \tabularnewline
183 & 0.745652 & 0.508696 & 0.254348 \tabularnewline
184 & 0.716577 & 0.566845 & 0.283423 \tabularnewline
185 & 0.736369 & 0.527263 & 0.263631 \tabularnewline
186 & 0.704939 & 0.590121 & 0.295061 \tabularnewline
187 & 0.709568 & 0.580863 & 0.290432 \tabularnewline
188 & 0.713654 & 0.572692 & 0.286346 \tabularnewline
189 & 0.715293 & 0.569415 & 0.284707 \tabularnewline
190 & 0.693206 & 0.613587 & 0.306794 \tabularnewline
191 & 0.661828 & 0.676343 & 0.338172 \tabularnewline
192 & 0.660922 & 0.678156 & 0.339078 \tabularnewline
193 & 0.746648 & 0.506704 & 0.253352 \tabularnewline
194 & 0.765113 & 0.469774 & 0.234887 \tabularnewline
195 & 0.740787 & 0.518426 & 0.259213 \tabularnewline
196 & 0.708893 & 0.582214 & 0.291107 \tabularnewline
197 & 0.695572 & 0.608856 & 0.304428 \tabularnewline
198 & 0.665365 & 0.669271 & 0.334635 \tabularnewline
199 & 0.656493 & 0.687013 & 0.343507 \tabularnewline
200 & 0.625545 & 0.748909 & 0.374455 \tabularnewline
201 & 0.681742 & 0.636517 & 0.318258 \tabularnewline
202 & 0.65449 & 0.69102 & 0.34551 \tabularnewline
203 & 0.627342 & 0.745315 & 0.372658 \tabularnewline
204 & 0.588171 & 0.823658 & 0.411829 \tabularnewline
205 & 0.587493 & 0.825014 & 0.412507 \tabularnewline
206 & 0.555391 & 0.889218 & 0.444609 \tabularnewline
207 & 0.524721 & 0.950558 & 0.475279 \tabularnewline
208 & 0.49738 & 0.994759 & 0.50262 \tabularnewline
209 & 0.498021 & 0.996041 & 0.501979 \tabularnewline
210 & 0.465188 & 0.930376 & 0.534812 \tabularnewline
211 & 0.422133 & 0.844267 & 0.577867 \tabularnewline
212 & 0.407995 & 0.81599 & 0.592005 \tabularnewline
213 & 0.403284 & 0.806567 & 0.596716 \tabularnewline
214 & 0.364426 & 0.728853 & 0.635574 \tabularnewline
215 & 0.325223 & 0.650446 & 0.674777 \tabularnewline
216 & 0.291718 & 0.583435 & 0.708282 \tabularnewline
217 & 0.28292 & 0.565839 & 0.71708 \tabularnewline
218 & 0.304111 & 0.608221 & 0.695889 \tabularnewline
219 & 0.266845 & 0.533691 & 0.733155 \tabularnewline
220 & 0.231169 & 0.462337 & 0.768831 \tabularnewline
221 & 0.222443 & 0.444887 & 0.777557 \tabularnewline
222 & 0.240796 & 0.481591 & 0.759204 \tabularnewline
223 & 0.209375 & 0.418749 & 0.790625 \tabularnewline
224 & 0.177698 & 0.355396 & 0.822302 \tabularnewline
225 & 0.157159 & 0.314318 & 0.842841 \tabularnewline
226 & 0.135459 & 0.270918 & 0.864541 \tabularnewline
227 & 0.111329 & 0.222659 & 0.888671 \tabularnewline
228 & 0.113776 & 0.227552 & 0.886224 \tabularnewline
229 & 0.193765 & 0.387529 & 0.806235 \tabularnewline
230 & 0.184358 & 0.368716 & 0.815642 \tabularnewline
231 & 0.1887 & 0.377401 & 0.8113 \tabularnewline
232 & 0.217061 & 0.434122 & 0.782939 \tabularnewline
233 & 0.190762 & 0.381524 & 0.809238 \tabularnewline
234 & 0.168479 & 0.336959 & 0.831521 \tabularnewline
235 & 0.142829 & 0.285658 & 0.857171 \tabularnewline
236 & 0.535856 & 0.928289 & 0.464144 \tabularnewline
237 & 0.482217 & 0.964434 & 0.517783 \tabularnewline
238 & 0.432846 & 0.865693 & 0.567154 \tabularnewline
239 & 0.387651 & 0.775302 & 0.612349 \tabularnewline
240 & 0.33365 & 0.6673 & 0.66635 \tabularnewline
241 & 0.304256 & 0.608511 & 0.695744 \tabularnewline
242 & 0.25819 & 0.516379 & 0.74181 \tabularnewline
243 & 0.217142 & 0.434283 & 0.782858 \tabularnewline
244 & 0.189361 & 0.378721 & 0.810639 \tabularnewline
245 & 0.152233 & 0.304466 & 0.847767 \tabularnewline
246 & 0.167564 & 0.335127 & 0.832436 \tabularnewline
247 & 0.152422 & 0.304845 & 0.847578 \tabularnewline
248 & 0.125533 & 0.251067 & 0.874467 \tabularnewline
249 & 0.109496 & 0.218991 & 0.890504 \tabularnewline
250 & 0.0805682 & 0.161136 & 0.919432 \tabularnewline
251 & 0.0809332 & 0.161866 & 0.919067 \tabularnewline
252 & 0.074617 & 0.149234 & 0.925383 \tabularnewline
253 & 0.0604741 & 0.120948 & 0.939526 \tabularnewline
254 & 0.141977 & 0.283954 & 0.858023 \tabularnewline
255 & 0.380524 & 0.761047 & 0.619476 \tabularnewline
256 & 0.299984 & 0.599968 & 0.700016 \tabularnewline
257 & 0.457203 & 0.914407 & 0.542797 \tabularnewline
258 & 0.68868 & 0.62264 & 0.31132 \tabularnewline
259 & 0.566424 & 0.867153 & 0.433576 \tabularnewline
260 & 0.7319 & 0.536199 & 0.2681 \tabularnewline
261 & 0.592541 & 0.814919 & 0.407459 \tabularnewline
262 & 0.425491 & 0.850982 & 0.574509 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&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]17[/C][C]0.697331[/C][C]0.605339[/C][C]0.302669[/C][/ROW]
[ROW][C]18[/C][C]0.548649[/C][C]0.902702[/C][C]0.451351[/C][/ROW]
[ROW][C]19[/C][C]0.443094[/C][C]0.886188[/C][C]0.556906[/C][/ROW]
[ROW][C]20[/C][C]0.341926[/C][C]0.683851[/C][C]0.658074[/C][/ROW]
[ROW][C]21[/C][C]0.273074[/C][C]0.546149[/C][C]0.726926[/C][/ROW]
[ROW][C]22[/C][C]0.205574[/C][C]0.411149[/C][C]0.794426[/C][/ROW]
[ROW][C]23[/C][C]0.283875[/C][C]0.567749[/C][C]0.716125[/C][/ROW]
[ROW][C]24[/C][C]0.311489[/C][C]0.622978[/C][C]0.688511[/C][/ROW]
[ROW][C]25[/C][C]0.267941[/C][C]0.535881[/C][C]0.732059[/C][/ROW]
[ROW][C]26[/C][C]0.234213[/C][C]0.468425[/C][C]0.765787[/C][/ROW]
[ROW][C]27[/C][C]0.220117[/C][C]0.440234[/C][C]0.779883[/C][/ROW]
[ROW][C]28[/C][C]0.188369[/C][C]0.376738[/C][C]0.811631[/C][/ROW]
[ROW][C]29[/C][C]0.151118[/C][C]0.302236[/C][C]0.848882[/C][/ROW]
[ROW][C]30[/C][C]0.110861[/C][C]0.221723[/C][C]0.889139[/C][/ROW]
[ROW][C]31[/C][C]0.106164[/C][C]0.212328[/C][C]0.893836[/C][/ROW]
[ROW][C]32[/C][C]0.084586[/C][C]0.169172[/C][C]0.915414[/C][/ROW]
[ROW][C]33[/C][C]0.0818289[/C][C]0.163658[/C][C]0.918171[/C][/ROW]
[ROW][C]34[/C][C]0.103745[/C][C]0.20749[/C][C]0.896255[/C][/ROW]
[ROW][C]35[/C][C]0.0757285[/C][C]0.151457[/C][C]0.924271[/C][/ROW]
[ROW][C]36[/C][C]0.0573453[/C][C]0.114691[/C][C]0.942655[/C][/ROW]
[ROW][C]37[/C][C]0.0405748[/C][C]0.0811495[/C][C]0.959425[/C][/ROW]
[ROW][C]38[/C][C]0.0361925[/C][C]0.0723849[/C][C]0.963808[/C][/ROW]
[ROW][C]39[/C][C]0.0477793[/C][C]0.0955587[/C][C]0.952221[/C][/ROW]
[ROW][C]40[/C][C]0.0518964[/C][C]0.103793[/C][C]0.948104[/C][/ROW]
[ROW][C]41[/C][C]0.0840854[/C][C]0.168171[/C][C]0.915915[/C][/ROW]
[ROW][C]42[/C][C]0.0650374[/C][C]0.130075[/C][C]0.934963[/C][/ROW]
[ROW][C]43[/C][C]0.0649022[/C][C]0.129804[/C][C]0.935098[/C][/ROW]
[ROW][C]44[/C][C]0.0506869[/C][C]0.101374[/C][C]0.949313[/C][/ROW]
[ROW][C]45[/C][C]0.0590976[/C][C]0.118195[/C][C]0.940902[/C][/ROW]
[ROW][C]46[/C][C]0.0602943[/C][C]0.120589[/C][C]0.939706[/C][/ROW]
[ROW][C]47[/C][C]0.0619987[/C][C]0.123997[/C][C]0.938001[/C][/ROW]
[ROW][C]48[/C][C]0.0679608[/C][C]0.135922[/C][C]0.932039[/C][/ROW]
[ROW][C]49[/C][C]0.116875[/C][C]0.233749[/C][C]0.883125[/C][/ROW]
[ROW][C]50[/C][C]0.121577[/C][C]0.243153[/C][C]0.878423[/C][/ROW]
[ROW][C]51[/C][C]0.0977281[/C][C]0.195456[/C][C]0.902272[/C][/ROW]
[ROW][C]52[/C][C]0.125561[/C][C]0.251123[/C][C]0.874439[/C][/ROW]
[ROW][C]53[/C][C]0.106284[/C][C]0.212568[/C][C]0.893716[/C][/ROW]
[ROW][C]54[/C][C]0.112853[/C][C]0.225707[/C][C]0.887147[/C][/ROW]
[ROW][C]55[/C][C]0.258023[/C][C]0.516047[/C][C]0.741977[/C][/ROW]
[ROW][C]56[/C][C]0.221484[/C][C]0.442968[/C][C]0.778516[/C][/ROW]
[ROW][C]57[/C][C]0.538154[/C][C]0.923693[/C][C]0.461846[/C][/ROW]
[ROW][C]58[/C][C]0.622121[/C][C]0.755758[/C][C]0.377879[/C][/ROW]
[ROW][C]59[/C][C]0.603898[/C][C]0.792204[/C][C]0.396102[/C][/ROW]
[ROW][C]60[/C][C]0.638491[/C][C]0.723017[/C][C]0.361509[/C][/ROW]
[ROW][C]61[/C][C]0.613085[/C][C]0.77383[/C][C]0.386915[/C][/ROW]
[ROW][C]62[/C][C]0.576278[/C][C]0.847443[/C][C]0.423722[/C][/ROW]
[ROW][C]63[/C][C]0.681623[/C][C]0.636753[/C][C]0.318377[/C][/ROW]
[ROW][C]64[/C][C]0.751944[/C][C]0.496111[/C][C]0.248056[/C][/ROW]
[ROW][C]65[/C][C]0.75319[/C][C]0.493619[/C][C]0.24681[/C][/ROW]
[ROW][C]66[/C][C]0.729955[/C][C]0.540089[/C][C]0.270045[/C][/ROW]
[ROW][C]67[/C][C]0.693209[/C][C]0.613582[/C][C]0.306791[/C][/ROW]
[ROW][C]68[/C][C]0.682206[/C][C]0.635587[/C][C]0.317794[/C][/ROW]
[ROW][C]69[/C][C]0.712811[/C][C]0.574377[/C][C]0.287189[/C][/ROW]
[ROW][C]70[/C][C]0.689764[/C][C]0.620473[/C][C]0.310236[/C][/ROW]
[ROW][C]71[/C][C]0.656056[/C][C]0.687888[/C][C]0.343944[/C][/ROW]
[ROW][C]72[/C][C]0.620263[/C][C]0.759473[/C][C]0.379737[/C][/ROW]
[ROW][C]73[/C][C]0.597373[/C][C]0.805254[/C][C]0.402627[/C][/ROW]
[ROW][C]74[/C][C]0.657567[/C][C]0.684865[/C][C]0.342433[/C][/ROW]
[ROW][C]75[/C][C]0.631572[/C][C]0.736855[/C][C]0.368428[/C][/ROW]
[ROW][C]76[/C][C]0.61332[/C][C]0.773359[/C][C]0.38668[/C][/ROW]
[ROW][C]77[/C][C]0.581595[/C][C]0.83681[/C][C]0.418405[/C][/ROW]
[ROW][C]78[/C][C]0.600325[/C][C]0.799349[/C][C]0.399675[/C][/ROW]
[ROW][C]79[/C][C]0.565311[/C][C]0.869378[/C][C]0.434689[/C][/ROW]
[ROW][C]80[/C][C]0.559845[/C][C]0.880311[/C][C]0.440155[/C][/ROW]
[ROW][C]81[/C][C]0.522083[/C][C]0.955835[/C][C]0.477917[/C][/ROW]
[ROW][C]82[/C][C]0.553639[/C][C]0.892721[/C][C]0.446361[/C][/ROW]
[ROW][C]83[/C][C]0.515675[/C][C]0.968649[/C][C]0.484325[/C][/ROW]
[ROW][C]84[/C][C]0.61217[/C][C]0.77566[/C][C]0.38783[/C][/ROW]
[ROW][C]85[/C][C]0.583766[/C][C]0.832469[/C][C]0.416234[/C][/ROW]
[ROW][C]86[/C][C]0.553361[/C][C]0.893278[/C][C]0.446639[/C][/ROW]
[ROW][C]87[/C][C]0.519575[/C][C]0.96085[/C][C]0.480425[/C][/ROW]
[ROW][C]88[/C][C]0.486928[/C][C]0.973856[/C][C]0.513072[/C][/ROW]
[ROW][C]89[/C][C]0.498888[/C][C]0.997775[/C][C]0.501112[/C][/ROW]
[ROW][C]90[/C][C]0.577244[/C][C]0.845513[/C][C]0.422756[/C][/ROW]
[ROW][C]91[/C][C]0.602759[/C][C]0.794483[/C][C]0.397241[/C][/ROW]
[ROW][C]92[/C][C]0.698685[/C][C]0.602631[/C][C]0.301315[/C][/ROW]
[ROW][C]93[/C][C]0.686176[/C][C]0.627647[/C][C]0.313824[/C][/ROW]
[ROW][C]94[/C][C]0.660873[/C][C]0.678253[/C][C]0.339127[/C][/ROW]
[ROW][C]95[/C][C]0.675721[/C][C]0.648558[/C][C]0.324279[/C][/ROW]
[ROW][C]96[/C][C]0.652986[/C][C]0.694028[/C][C]0.347014[/C][/ROW]
[ROW][C]97[/C][C]0.645748[/C][C]0.708504[/C][C]0.354252[/C][/ROW]
[ROW][C]98[/C][C]0.619415[/C][C]0.76117[/C][C]0.380585[/C][/ROW]
[ROW][C]99[/C][C]0.661034[/C][C]0.677933[/C][C]0.338966[/C][/ROW]
[ROW][C]100[/C][C]0.696409[/C][C]0.607182[/C][C]0.303591[/C][/ROW]
[ROW][C]101[/C][C]0.668141[/C][C]0.663718[/C][C]0.331859[/C][/ROW]
[ROW][C]102[/C][C]0.634617[/C][C]0.730767[/C][C]0.365383[/C][/ROW]
[ROW][C]103[/C][C]0.630987[/C][C]0.738027[/C][C]0.369013[/C][/ROW]
[ROW][C]104[/C][C]0.605805[/C][C]0.788391[/C][C]0.394195[/C][/ROW]
[ROW][C]105[/C][C]0.675542[/C][C]0.648916[/C][C]0.324458[/C][/ROW]
[ROW][C]106[/C][C]0.662627[/C][C]0.674746[/C][C]0.337373[/C][/ROW]
[ROW][C]107[/C][C]0.738518[/C][C]0.522964[/C][C]0.261482[/C][/ROW]
[ROW][C]108[/C][C]0.820091[/C][C]0.359818[/C][C]0.179909[/C][/ROW]
[ROW][C]109[/C][C]0.877546[/C][C]0.244908[/C][C]0.122454[/C][/ROW]
[ROW][C]110[/C][C]0.862163[/C][C]0.275674[/C][C]0.137837[/C][/ROW]
[ROW][C]111[/C][C]0.84199[/C][C]0.316021[/C][C]0.15801[/C][/ROW]
[ROW][C]112[/C][C]0.829402[/C][C]0.341197[/C][C]0.170598[/C][/ROW]
[ROW][C]113[/C][C]0.897194[/C][C]0.205612[/C][C]0.102806[/C][/ROW]
[ROW][C]114[/C][C]0.924618[/C][C]0.150763[/C][C]0.0753816[/C][/ROW]
[ROW][C]115[/C][C]0.960483[/C][C]0.0790343[/C][C]0.0395172[/C][/ROW]
[ROW][C]116[/C][C]0.972398[/C][C]0.0552035[/C][C]0.0276017[/C][/ROW]
[ROW][C]117[/C][C]0.976442[/C][C]0.0471159[/C][C]0.0235579[/C][/ROW]
[ROW][C]118[/C][C]0.976563[/C][C]0.0468733[/C][C]0.0234366[/C][/ROW]
[ROW][C]119[/C][C]0.972572[/C][C]0.0548556[/C][C]0.0274278[/C][/ROW]
[ROW][C]120[/C][C]0.976633[/C][C]0.0467337[/C][C]0.0233669[/C][/ROW]
[ROW][C]121[/C][C]0.971229[/C][C]0.0575413[/C][C]0.0287707[/C][/ROW]
[ROW][C]122[/C][C]0.971454[/C][C]0.0570928[/C][C]0.0285464[/C][/ROW]
[ROW][C]123[/C][C]0.968709[/C][C]0.062582[/C][C]0.031291[/C][/ROW]
[ROW][C]124[/C][C]0.973503[/C][C]0.0529947[/C][C]0.0264974[/C][/ROW]
[ROW][C]125[/C][C]0.978376[/C][C]0.0432471[/C][C]0.0216236[/C][/ROW]
[ROW][C]126[/C][C]0.973382[/C][C]0.0532359[/C][C]0.026618[/C][/ROW]
[ROW][C]127[/C][C]0.9708[/C][C]0.0583992[/C][C]0.0291996[/C][/ROW]
[ROW][C]128[/C][C]0.964729[/C][C]0.0705422[/C][C]0.0352711[/C][/ROW]
[ROW][C]129[/C][C]0.97234[/C][C]0.0553197[/C][C]0.0276598[/C][/ROW]
[ROW][C]130[/C][C]0.966521[/C][C]0.0669585[/C][C]0.0334793[/C][/ROW]
[ROW][C]131[/C][C]0.960934[/C][C]0.078132[/C][C]0.039066[/C][/ROW]
[ROW][C]132[/C][C]0.955462[/C][C]0.0890767[/C][C]0.0445384[/C][/ROW]
[ROW][C]133[/C][C]0.948063[/C][C]0.103875[/C][C]0.0519374[/C][/ROW]
[ROW][C]134[/C][C]0.941868[/C][C]0.116263[/C][C]0.0581316[/C][/ROW]
[ROW][C]135[/C][C]0.930918[/C][C]0.138164[/C][C]0.0690821[/C][/ROW]
[ROW][C]136[/C][C]0.923476[/C][C]0.153047[/C][C]0.0765236[/C][/ROW]
[ROW][C]137[/C][C]0.928171[/C][C]0.143657[/C][C]0.0718287[/C][/ROW]
[ROW][C]138[/C][C]0.960367[/C][C]0.0792651[/C][C]0.0396325[/C][/ROW]
[ROW][C]139[/C][C]0.955248[/C][C]0.0895042[/C][C]0.0447521[/C][/ROW]
[ROW][C]140[/C][C]0.946657[/C][C]0.106686[/C][C]0.0533429[/C][/ROW]
[ROW][C]141[/C][C]0.939779[/C][C]0.120442[/C][C]0.0602208[/C][/ROW]
[ROW][C]142[/C][C]0.93498[/C][C]0.130039[/C][C]0.0650196[/C][/ROW]
[ROW][C]143[/C][C]0.923168[/C][C]0.153665[/C][C]0.0768323[/C][/ROW]
[ROW][C]144[/C][C]0.921025[/C][C]0.15795[/C][C]0.0789752[/C][/ROW]
[ROW][C]145[/C][C]0.910955[/C][C]0.178091[/C][C]0.0890454[/C][/ROW]
[ROW][C]146[/C][C]0.89707[/C][C]0.20586[/C][C]0.10293[/C][/ROW]
[ROW][C]147[/C][C]0.885173[/C][C]0.229654[/C][C]0.114827[/C][/ROW]
[ROW][C]148[/C][C]0.866718[/C][C]0.266565[/C][C]0.133282[/C][/ROW]
[ROW][C]149[/C][C]0.855699[/C][C]0.288601[/C][C]0.144301[/C][/ROW]
[ROW][C]150[/C][C]0.837824[/C][C]0.324351[/C][C]0.162176[/C][/ROW]
[ROW][C]151[/C][C]0.912284[/C][C]0.175432[/C][C]0.0877158[/C][/ROW]
[ROW][C]152[/C][C]0.897507[/C][C]0.204986[/C][C]0.102493[/C][/ROW]
[ROW][C]153[/C][C]0.885703[/C][C]0.228593[/C][C]0.114297[/C][/ROW]
[ROW][C]154[/C][C]0.878588[/C][C]0.242825[/C][C]0.121412[/C][/ROW]
[ROW][C]155[/C][C]0.870985[/C][C]0.25803[/C][C]0.129015[/C][/ROW]
[ROW][C]156[/C][C]0.859004[/C][C]0.281992[/C][C]0.140996[/C][/ROW]
[ROW][C]157[/C][C]0.851554[/C][C]0.296892[/C][C]0.148446[/C][/ROW]
[ROW][C]158[/C][C]0.842134[/C][C]0.315732[/C][C]0.157866[/C][/ROW]
[ROW][C]159[/C][C]0.822232[/C][C]0.355537[/C][C]0.177768[/C][/ROW]
[ROW][C]160[/C][C]0.812133[/C][C]0.375733[/C][C]0.187867[/C][/ROW]
[ROW][C]161[/C][C]0.832754[/C][C]0.334491[/C][C]0.167246[/C][/ROW]
[ROW][C]162[/C][C]0.822844[/C][C]0.354312[/C][C]0.177156[/C][/ROW]
[ROW][C]163[/C][C]0.806902[/C][C]0.386195[/C][C]0.193098[/C][/ROW]
[ROW][C]164[/C][C]0.809916[/C][C]0.380168[/C][C]0.190084[/C][/ROW]
[ROW][C]165[/C][C]0.80476[/C][C]0.390481[/C][C]0.19524[/C][/ROW]
[ROW][C]166[/C][C]0.779611[/C][C]0.440779[/C][C]0.220389[/C][/ROW]
[ROW][C]167[/C][C]0.786412[/C][C]0.427176[/C][C]0.213588[/C][/ROW]
[ROW][C]168[/C][C]0.762001[/C][C]0.475999[/C][C]0.237999[/C][/ROW]
[ROW][C]169[/C][C]0.738793[/C][C]0.522415[/C][C]0.261207[/C][/ROW]
[ROW][C]170[/C][C]0.736035[/C][C]0.527931[/C][C]0.263965[/C][/ROW]
[ROW][C]171[/C][C]0.721604[/C][C]0.556792[/C][C]0.278396[/C][/ROW]
[ROW][C]172[/C][C]0.748896[/C][C]0.502207[/C][C]0.251104[/C][/ROW]
[ROW][C]173[/C][C]0.722082[/C][C]0.555835[/C][C]0.277918[/C][/ROW]
[ROW][C]174[/C][C]0.691303[/C][C]0.617394[/C][C]0.308697[/C][/ROW]
[ROW][C]175[/C][C]0.658968[/C][C]0.682064[/C][C]0.341032[/C][/ROW]
[ROW][C]176[/C][C]0.719707[/C][C]0.560587[/C][C]0.280293[/C][/ROW]
[ROW][C]177[/C][C]0.692826[/C][C]0.614349[/C][C]0.307174[/C][/ROW]
[ROW][C]178[/C][C]0.740842[/C][C]0.518316[/C][C]0.259158[/C][/ROW]
[ROW][C]179[/C][C]0.720107[/C][C]0.559785[/C][C]0.279893[/C][/ROW]
[ROW][C]180[/C][C]0.793505[/C][C]0.412991[/C][C]0.206495[/C][/ROW]
[ROW][C]181[/C][C]0.78135[/C][C]0.4373[/C][C]0.21865[/C][/ROW]
[ROW][C]182[/C][C]0.752569[/C][C]0.494862[/C][C]0.247431[/C][/ROW]
[ROW][C]183[/C][C]0.745652[/C][C]0.508696[/C][C]0.254348[/C][/ROW]
[ROW][C]184[/C][C]0.716577[/C][C]0.566845[/C][C]0.283423[/C][/ROW]
[ROW][C]185[/C][C]0.736369[/C][C]0.527263[/C][C]0.263631[/C][/ROW]
[ROW][C]186[/C][C]0.704939[/C][C]0.590121[/C][C]0.295061[/C][/ROW]
[ROW][C]187[/C][C]0.709568[/C][C]0.580863[/C][C]0.290432[/C][/ROW]
[ROW][C]188[/C][C]0.713654[/C][C]0.572692[/C][C]0.286346[/C][/ROW]
[ROW][C]189[/C][C]0.715293[/C][C]0.569415[/C][C]0.284707[/C][/ROW]
[ROW][C]190[/C][C]0.693206[/C][C]0.613587[/C][C]0.306794[/C][/ROW]
[ROW][C]191[/C][C]0.661828[/C][C]0.676343[/C][C]0.338172[/C][/ROW]
[ROW][C]192[/C][C]0.660922[/C][C]0.678156[/C][C]0.339078[/C][/ROW]
[ROW][C]193[/C][C]0.746648[/C][C]0.506704[/C][C]0.253352[/C][/ROW]
[ROW][C]194[/C][C]0.765113[/C][C]0.469774[/C][C]0.234887[/C][/ROW]
[ROW][C]195[/C][C]0.740787[/C][C]0.518426[/C][C]0.259213[/C][/ROW]
[ROW][C]196[/C][C]0.708893[/C][C]0.582214[/C][C]0.291107[/C][/ROW]
[ROW][C]197[/C][C]0.695572[/C][C]0.608856[/C][C]0.304428[/C][/ROW]
[ROW][C]198[/C][C]0.665365[/C][C]0.669271[/C][C]0.334635[/C][/ROW]
[ROW][C]199[/C][C]0.656493[/C][C]0.687013[/C][C]0.343507[/C][/ROW]
[ROW][C]200[/C][C]0.625545[/C][C]0.748909[/C][C]0.374455[/C][/ROW]
[ROW][C]201[/C][C]0.681742[/C][C]0.636517[/C][C]0.318258[/C][/ROW]
[ROW][C]202[/C][C]0.65449[/C][C]0.69102[/C][C]0.34551[/C][/ROW]
[ROW][C]203[/C][C]0.627342[/C][C]0.745315[/C][C]0.372658[/C][/ROW]
[ROW][C]204[/C][C]0.588171[/C][C]0.823658[/C][C]0.411829[/C][/ROW]
[ROW][C]205[/C][C]0.587493[/C][C]0.825014[/C][C]0.412507[/C][/ROW]
[ROW][C]206[/C][C]0.555391[/C][C]0.889218[/C][C]0.444609[/C][/ROW]
[ROW][C]207[/C][C]0.524721[/C][C]0.950558[/C][C]0.475279[/C][/ROW]
[ROW][C]208[/C][C]0.49738[/C][C]0.994759[/C][C]0.50262[/C][/ROW]
[ROW][C]209[/C][C]0.498021[/C][C]0.996041[/C][C]0.501979[/C][/ROW]
[ROW][C]210[/C][C]0.465188[/C][C]0.930376[/C][C]0.534812[/C][/ROW]
[ROW][C]211[/C][C]0.422133[/C][C]0.844267[/C][C]0.577867[/C][/ROW]
[ROW][C]212[/C][C]0.407995[/C][C]0.81599[/C][C]0.592005[/C][/ROW]
[ROW][C]213[/C][C]0.403284[/C][C]0.806567[/C][C]0.596716[/C][/ROW]
[ROW][C]214[/C][C]0.364426[/C][C]0.728853[/C][C]0.635574[/C][/ROW]
[ROW][C]215[/C][C]0.325223[/C][C]0.650446[/C][C]0.674777[/C][/ROW]
[ROW][C]216[/C][C]0.291718[/C][C]0.583435[/C][C]0.708282[/C][/ROW]
[ROW][C]217[/C][C]0.28292[/C][C]0.565839[/C][C]0.71708[/C][/ROW]
[ROW][C]218[/C][C]0.304111[/C][C]0.608221[/C][C]0.695889[/C][/ROW]
[ROW][C]219[/C][C]0.266845[/C][C]0.533691[/C][C]0.733155[/C][/ROW]
[ROW][C]220[/C][C]0.231169[/C][C]0.462337[/C][C]0.768831[/C][/ROW]
[ROW][C]221[/C][C]0.222443[/C][C]0.444887[/C][C]0.777557[/C][/ROW]
[ROW][C]222[/C][C]0.240796[/C][C]0.481591[/C][C]0.759204[/C][/ROW]
[ROW][C]223[/C][C]0.209375[/C][C]0.418749[/C][C]0.790625[/C][/ROW]
[ROW][C]224[/C][C]0.177698[/C][C]0.355396[/C][C]0.822302[/C][/ROW]
[ROW][C]225[/C][C]0.157159[/C][C]0.314318[/C][C]0.842841[/C][/ROW]
[ROW][C]226[/C][C]0.135459[/C][C]0.270918[/C][C]0.864541[/C][/ROW]
[ROW][C]227[/C][C]0.111329[/C][C]0.222659[/C][C]0.888671[/C][/ROW]
[ROW][C]228[/C][C]0.113776[/C][C]0.227552[/C][C]0.886224[/C][/ROW]
[ROW][C]229[/C][C]0.193765[/C][C]0.387529[/C][C]0.806235[/C][/ROW]
[ROW][C]230[/C][C]0.184358[/C][C]0.368716[/C][C]0.815642[/C][/ROW]
[ROW][C]231[/C][C]0.1887[/C][C]0.377401[/C][C]0.8113[/C][/ROW]
[ROW][C]232[/C][C]0.217061[/C][C]0.434122[/C][C]0.782939[/C][/ROW]
[ROW][C]233[/C][C]0.190762[/C][C]0.381524[/C][C]0.809238[/C][/ROW]
[ROW][C]234[/C][C]0.168479[/C][C]0.336959[/C][C]0.831521[/C][/ROW]
[ROW][C]235[/C][C]0.142829[/C][C]0.285658[/C][C]0.857171[/C][/ROW]
[ROW][C]236[/C][C]0.535856[/C][C]0.928289[/C][C]0.464144[/C][/ROW]
[ROW][C]237[/C][C]0.482217[/C][C]0.964434[/C][C]0.517783[/C][/ROW]
[ROW][C]238[/C][C]0.432846[/C][C]0.865693[/C][C]0.567154[/C][/ROW]
[ROW][C]239[/C][C]0.387651[/C][C]0.775302[/C][C]0.612349[/C][/ROW]
[ROW][C]240[/C][C]0.33365[/C][C]0.6673[/C][C]0.66635[/C][/ROW]
[ROW][C]241[/C][C]0.304256[/C][C]0.608511[/C][C]0.695744[/C][/ROW]
[ROW][C]242[/C][C]0.25819[/C][C]0.516379[/C][C]0.74181[/C][/ROW]
[ROW][C]243[/C][C]0.217142[/C][C]0.434283[/C][C]0.782858[/C][/ROW]
[ROW][C]244[/C][C]0.189361[/C][C]0.378721[/C][C]0.810639[/C][/ROW]
[ROW][C]245[/C][C]0.152233[/C][C]0.304466[/C][C]0.847767[/C][/ROW]
[ROW][C]246[/C][C]0.167564[/C][C]0.335127[/C][C]0.832436[/C][/ROW]
[ROW][C]247[/C][C]0.152422[/C][C]0.304845[/C][C]0.847578[/C][/ROW]
[ROW][C]248[/C][C]0.125533[/C][C]0.251067[/C][C]0.874467[/C][/ROW]
[ROW][C]249[/C][C]0.109496[/C][C]0.218991[/C][C]0.890504[/C][/ROW]
[ROW][C]250[/C][C]0.0805682[/C][C]0.161136[/C][C]0.919432[/C][/ROW]
[ROW][C]251[/C][C]0.0809332[/C][C]0.161866[/C][C]0.919067[/C][/ROW]
[ROW][C]252[/C][C]0.074617[/C][C]0.149234[/C][C]0.925383[/C][/ROW]
[ROW][C]253[/C][C]0.0604741[/C][C]0.120948[/C][C]0.939526[/C][/ROW]
[ROW][C]254[/C][C]0.141977[/C][C]0.283954[/C][C]0.858023[/C][/ROW]
[ROW][C]255[/C][C]0.380524[/C][C]0.761047[/C][C]0.619476[/C][/ROW]
[ROW][C]256[/C][C]0.299984[/C][C]0.599968[/C][C]0.700016[/C][/ROW]
[ROW][C]257[/C][C]0.457203[/C][C]0.914407[/C][C]0.542797[/C][/ROW]
[ROW][C]258[/C][C]0.68868[/C][C]0.62264[/C][C]0.31132[/C][/ROW]
[ROW][C]259[/C][C]0.566424[/C][C]0.867153[/C][C]0.433576[/C][/ROW]
[ROW][C]260[/C][C]0.7319[/C][C]0.536199[/C][C]0.2681[/C][/ROW]
[ROW][C]261[/C][C]0.592541[/C][C]0.814919[/C][C]0.407459[/C][/ROW]
[ROW][C]262[/C][C]0.425491[/C][C]0.850982[/C][C]0.574509[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&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
17	0.697331	0.605339	0.302669
18	0.548649	0.902702	0.451351
19	0.443094	0.886188	0.556906
20	0.341926	0.683851	0.658074
21	0.273074	0.546149	0.726926
22	0.205574	0.411149	0.794426
23	0.283875	0.567749	0.716125
24	0.311489	0.622978	0.688511
25	0.267941	0.535881	0.732059
26	0.234213	0.468425	0.765787
27	0.220117	0.440234	0.779883
28	0.188369	0.376738	0.811631
29	0.151118	0.302236	0.848882
30	0.110861	0.221723	0.889139
31	0.106164	0.212328	0.893836
32	0.084586	0.169172	0.915414
33	0.0818289	0.163658	0.918171
34	0.103745	0.20749	0.896255
35	0.0757285	0.151457	0.924271
36	0.0573453	0.114691	0.942655
37	0.0405748	0.0811495	0.959425
38	0.0361925	0.0723849	0.963808
39	0.0477793	0.0955587	0.952221
40	0.0518964	0.103793	0.948104
41	0.0840854	0.168171	0.915915
42	0.0650374	0.130075	0.934963
43	0.0649022	0.129804	0.935098
44	0.0506869	0.101374	0.949313
45	0.0590976	0.118195	0.940902
46	0.0602943	0.120589	0.939706
47	0.0619987	0.123997	0.938001
48	0.0679608	0.135922	0.932039
49	0.116875	0.233749	0.883125
50	0.121577	0.243153	0.878423
51	0.0977281	0.195456	0.902272
52	0.125561	0.251123	0.874439
53	0.106284	0.212568	0.893716
54	0.112853	0.225707	0.887147
55	0.258023	0.516047	0.741977
56	0.221484	0.442968	0.778516
57	0.538154	0.923693	0.461846
58	0.622121	0.755758	0.377879
59	0.603898	0.792204	0.396102
60	0.638491	0.723017	0.361509
61	0.613085	0.77383	0.386915
62	0.576278	0.847443	0.423722
63	0.681623	0.636753	0.318377
64	0.751944	0.496111	0.248056
65	0.75319	0.493619	0.24681
66	0.729955	0.540089	0.270045
67	0.693209	0.613582	0.306791
68	0.682206	0.635587	0.317794
69	0.712811	0.574377	0.287189
70	0.689764	0.620473	0.310236
71	0.656056	0.687888	0.343944
72	0.620263	0.759473	0.379737
73	0.597373	0.805254	0.402627
74	0.657567	0.684865	0.342433
75	0.631572	0.736855	0.368428
76	0.61332	0.773359	0.38668
77	0.581595	0.83681	0.418405
78	0.600325	0.799349	0.399675
79	0.565311	0.869378	0.434689
80	0.559845	0.880311	0.440155
81	0.522083	0.955835	0.477917
82	0.553639	0.892721	0.446361
83	0.515675	0.968649	0.484325
84	0.61217	0.77566	0.38783
85	0.583766	0.832469	0.416234
86	0.553361	0.893278	0.446639
87	0.519575	0.96085	0.480425
88	0.486928	0.973856	0.513072
89	0.498888	0.997775	0.501112
90	0.577244	0.845513	0.422756
91	0.602759	0.794483	0.397241
92	0.698685	0.602631	0.301315
93	0.686176	0.627647	0.313824
94	0.660873	0.678253	0.339127
95	0.675721	0.648558	0.324279
96	0.652986	0.694028	0.347014
97	0.645748	0.708504	0.354252
98	0.619415	0.76117	0.380585
99	0.661034	0.677933	0.338966
100	0.696409	0.607182	0.303591
101	0.668141	0.663718	0.331859
102	0.634617	0.730767	0.365383
103	0.630987	0.738027	0.369013
104	0.605805	0.788391	0.394195
105	0.675542	0.648916	0.324458
106	0.662627	0.674746	0.337373
107	0.738518	0.522964	0.261482
108	0.820091	0.359818	0.179909
109	0.877546	0.244908	0.122454
110	0.862163	0.275674	0.137837
111	0.84199	0.316021	0.15801
112	0.829402	0.341197	0.170598
113	0.897194	0.205612	0.102806
114	0.924618	0.150763	0.0753816
115	0.960483	0.0790343	0.0395172
116	0.972398	0.0552035	0.0276017
117	0.976442	0.0471159	0.0235579
118	0.976563	0.0468733	0.0234366
119	0.972572	0.0548556	0.0274278
120	0.976633	0.0467337	0.0233669
121	0.971229	0.0575413	0.0287707
122	0.971454	0.0570928	0.0285464
123	0.968709	0.062582	0.031291
124	0.973503	0.0529947	0.0264974
125	0.978376	0.0432471	0.0216236
126	0.973382	0.0532359	0.026618
127	0.9708	0.0583992	0.0291996
128	0.964729	0.0705422	0.0352711
129	0.97234	0.0553197	0.0276598
130	0.966521	0.0669585	0.0334793
131	0.960934	0.078132	0.039066
132	0.955462	0.0890767	0.0445384
133	0.948063	0.103875	0.0519374
134	0.941868	0.116263	0.0581316
135	0.930918	0.138164	0.0690821
136	0.923476	0.153047	0.0765236
137	0.928171	0.143657	0.0718287
138	0.960367	0.0792651	0.0396325
139	0.955248	0.0895042	0.0447521
140	0.946657	0.106686	0.0533429
141	0.939779	0.120442	0.0602208
142	0.93498	0.130039	0.0650196
143	0.923168	0.153665	0.0768323
144	0.921025	0.15795	0.0789752
145	0.910955	0.178091	0.0890454
146	0.89707	0.20586	0.10293
147	0.885173	0.229654	0.114827
148	0.866718	0.266565	0.133282
149	0.855699	0.288601	0.144301
150	0.837824	0.324351	0.162176
151	0.912284	0.175432	0.0877158
152	0.897507	0.204986	0.102493
153	0.885703	0.228593	0.114297
154	0.878588	0.242825	0.121412
155	0.870985	0.25803	0.129015
156	0.859004	0.281992	0.140996
157	0.851554	0.296892	0.148446
158	0.842134	0.315732	0.157866
159	0.822232	0.355537	0.177768
160	0.812133	0.375733	0.187867
161	0.832754	0.334491	0.167246
162	0.822844	0.354312	0.177156
163	0.806902	0.386195	0.193098
164	0.809916	0.380168	0.190084
165	0.80476	0.390481	0.19524
166	0.779611	0.440779	0.220389
167	0.786412	0.427176	0.213588
168	0.762001	0.475999	0.237999
169	0.738793	0.522415	0.261207
170	0.736035	0.527931	0.263965
171	0.721604	0.556792	0.278396
172	0.748896	0.502207	0.251104
173	0.722082	0.555835	0.277918
174	0.691303	0.617394	0.308697
175	0.658968	0.682064	0.341032
176	0.719707	0.560587	0.280293
177	0.692826	0.614349	0.307174
178	0.740842	0.518316	0.259158
179	0.720107	0.559785	0.279893
180	0.793505	0.412991	0.206495
181	0.78135	0.4373	0.21865
182	0.752569	0.494862	0.247431
183	0.745652	0.508696	0.254348
184	0.716577	0.566845	0.283423
185	0.736369	0.527263	0.263631
186	0.704939	0.590121	0.295061
187	0.709568	0.580863	0.290432
188	0.713654	0.572692	0.286346
189	0.715293	0.569415	0.284707
190	0.693206	0.613587	0.306794
191	0.661828	0.676343	0.338172
192	0.660922	0.678156	0.339078
193	0.746648	0.506704	0.253352
194	0.765113	0.469774	0.234887
195	0.740787	0.518426	0.259213
196	0.708893	0.582214	0.291107
197	0.695572	0.608856	0.304428
198	0.665365	0.669271	0.334635
199	0.656493	0.687013	0.343507
200	0.625545	0.748909	0.374455
201	0.681742	0.636517	0.318258
202	0.65449	0.69102	0.34551
203	0.627342	0.745315	0.372658
204	0.588171	0.823658	0.411829
205	0.587493	0.825014	0.412507
206	0.555391	0.889218	0.444609
207	0.524721	0.950558	0.475279
208	0.49738	0.994759	0.50262
209	0.498021	0.996041	0.501979
210	0.465188	0.930376	0.534812
211	0.422133	0.844267	0.577867
212	0.407995	0.81599	0.592005
213	0.403284	0.806567	0.596716
214	0.364426	0.728853	0.635574
215	0.325223	0.650446	0.674777
216	0.291718	0.583435	0.708282
217	0.28292	0.565839	0.71708
218	0.304111	0.608221	0.695889
219	0.266845	0.533691	0.733155
220	0.231169	0.462337	0.768831
221	0.222443	0.444887	0.777557
222	0.240796	0.481591	0.759204
223	0.209375	0.418749	0.790625
224	0.177698	0.355396	0.822302
225	0.157159	0.314318	0.842841
226	0.135459	0.270918	0.864541
227	0.111329	0.222659	0.888671
228	0.113776	0.227552	0.886224
229	0.193765	0.387529	0.806235
230	0.184358	0.368716	0.815642
231	0.1887	0.377401	0.8113
232	0.217061	0.434122	0.782939
233	0.190762	0.381524	0.809238
234	0.168479	0.336959	0.831521
235	0.142829	0.285658	0.857171
236	0.535856	0.928289	0.464144
237	0.482217	0.964434	0.517783
238	0.432846	0.865693	0.567154
239	0.387651	0.775302	0.612349
240	0.33365	0.6673	0.66635
241	0.304256	0.608511	0.695744
242	0.25819	0.516379	0.74181
243	0.217142	0.434283	0.782858
244	0.189361	0.378721	0.810639
245	0.152233	0.304466	0.847767
246	0.167564	0.335127	0.832436
247	0.152422	0.304845	0.847578
248	0.125533	0.251067	0.874467
249	0.109496	0.218991	0.890504
250	0.0805682	0.161136	0.919432
251	0.0809332	0.161866	0.919067
252	0.074617	0.149234	0.925383
253	0.0604741	0.120948	0.939526
254	0.141977	0.283954	0.858023
255	0.380524	0.761047	0.619476
256	0.299984	0.599968	0.700016
257	0.457203	0.914407	0.542797
258	0.68868	0.62264	0.31132
259	0.566424	0.867153	0.433576
260	0.7319	0.536199	0.2681
261	0.592541	0.814919	0.407459
262	0.425491	0.850982	0.574509

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	4	0.0162602	OK
10% type I error level	23	0.0934959	OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 4 & 0.0162602 & OK \tabularnewline
10% type I error level & 23 & 0.0934959 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268720&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]4[/C][C]0.0162602[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]23[/C][C]0.0934959[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268720&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268720&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	4	0.0162602	OK
10% type I error level	23	0.0934959	OK

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

Figure 9

PNG link

Postscript link

PDF link

Figure 10

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

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

par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '1'
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