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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 06 Dec 2014 11:29:11 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/06/t1417865365cxhs7t6kpo45cnt.htm/, Retrieved Thu, 16 May 2024 13:35:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263586, Retrieved Thu, 16 May 2024 13:35:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact126

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-06 11:29:11] [42cc6d0d468769986f2f8c7c7fdc2d20] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
12.9 68 86 149 96 18 1.8 1.5
12.2 39 70 139 70 31 2.1 2.1
12.8 32 71 148 88 39 2.2 2.1
7.4 62 108 158 114 46 2.3 1.9
6.7 33 64 128 69 31 2.1 1.6
12.6 52 119 224 176 67 2.7 2.1
14.8 62 97 159 114 35 2.1 2.1
13.3 77 129 105 121 52 2.4 2.2
11.1 76 153 159 110 77 2.9 1.5
8.2 41 78 167 158 37 2.2 1.9
11.4 48 80 165 116 32 2.1 2.2
6.4 63 99 159 181 36 2.2 1.6
10.6 30 68 119 77 38 2.2 1.5
12 78 147 176 141 69 2.7 1.9
6.3 19 40 54 35 21 1.9 0.1
11.3 31 57 91 80 26 2 2.2
11.9 66 120 163 152 54 2.5 1.8
9.3 35 71 124 97 36 2.2 1.6
9.6 42 84 137 99 42 2.3 2.2
10 45 68 121 84 23 1.9 2.1
6.4 21 55 153 68 34 2.1 1.9
13.8 25 137 148 101 112 3.5 1.6
10.8 44 79 221 107 35 2.1 1.9
13.8 69 116 188 88 47 2.3 2.2
11.7 54 101 149 112 47 2.3 1.8
10.9 74 111 244 171 37 2.2 2.4
16.1 80 189 148 137 109 3.5 2.4
13.4 42 66 92 77 24 1.9 2.5
9.9 61 81 150 66 20 1.9 1.9
11.5 41 63 153 93 22 1.9 2.1
8.3 46 69 94 105 23 1.9 1.9
11.7 39 71 156 131 32 2.1 2.1
9 34 64 132 102 30 2 1.5
9.7 51 143 161 161 92 3.2 1.9
10.8 42 85 105 120 43 2.3 2.1
10.3 31 86 97 127 55 2.5 1.5
10.4 39 55 151 77 16 1.8 2.1
12.7 20 69 131 108 49 2.4 2.1
9.3 49 120 166 85 71 2.8 1.8
11.8 53 96 157 168 43 2.3 2.4
5.9 31 60 111 48 29 2 2.1
11.4 39 95 145 152 56 2.5 1.9
13 54 100 162 75 46 2.3 2.1
10.8 49 68 163 107 19 1.8 1.9
12.3 34 57 59 62 23 1.9 2.4
11.3 46 105 187 121 59 2.6 2.1
11.8 55 85 109 124 30 2 2.2
7.9 42 103 90 72 61 2.6 2.2
12.7 50 57 105 40 7 1.6 1.8
12.3 13 51 83 58 38 2.2 2.1
11.6 37 69 116 97 32 2.1 2.4
6.7 25 41 42 88 16 1.8 2.2
10.9 30 49 148 126 19 1.8 2.1
12.1 28 50 155 104 22 1.9 1.5
13.3 45 93 125 148 48 2.4 1.9
10.1 35 58 116 146 23 1.9 1.8
5.7 28 54 128 80 26 2 1.8
14.3 41 74 138 97 33 2.1 1.6
8 6 15 49 25 9 1.7 1.2
13.3 45 69 96 99 24 1.9 1.8
9.3 73 107 164 118 34 2.1 1.5
12.5 17 65 162 58 48 2.4 2.1
7.6 40 58 99 63 18 1.8 2.4
15.9 64 107 202 139 43 2.3 2.4
9.2 37 70 186 50 33 2.1 1.5
9.1 25 53 66 60 28 2 1.8
11.1 65 136 183 152 71 2.8 2.1
13 100 126 214 142 26 2 2.2
14.5 28 95 188 94 67 2.7 2.1
12.2 35 69 104 66 34 2.1 1.9
12.3 56 136 177 127 80 2.9 2.1
11.4 29 58 126 67 29 2 1.9
8.8 43 59 76 90 16 1.8 1.6
14.6 59 118 99 75 59 2.6 2.4
12.6 50 82 139 128 32 2.1 1.9
13 59 102 162 146 43 2.3 2.1
12.6 27 65 108 69 38 2.2 1.8
13.2 61 90 159 186 29 2 2.1
9.9 28 64 74 81 36 2.2 2.4
7.7 51 83 110 85 32 2.1 2.1
10.5 35 70 96 54 35 2.1 2.2
13.4 29 50 116 46 21 1.9 2.1
10.9 48 77 87 106 29 2 2.2
4.3 25 37 97 34 12 1.7 1.6
10.3 44 81 127 60 37 2.2 2.4
11.8 64 101 106 95 37 2.2 2.1
11.2 32 79 80 57 47 2.3 1.9
11.4 20 71 74 62 51 2.4 2.4
8.6 28 60 91 36 32 2.1 2.1
13.2 34 55 133 56 21 1.9 1.8
12.6 31 44 74 54 13 1.7 2.1
5.6 26 40 114 64 14 1.8 1.8
9.9 58 56 140 76 -2 1.5 1.9
8.8 23 43 95 98 20 1.9 1.9
7.7 21 45 98 88 24 1.9 2.4
9 21 32 121 35 11 1.7 1.8
7.3 33 56 126 102 23 1.9 1.8
11.4 16 40 98 61 24 1.9 2.1
13.6 20 34 95 80 14 1.8 2.1
7.9 37 89 110 49 52 2.4 2.4
10.7 35 50 70 78 15 1.8 1.9
10.3 33 56 102 90 23 1.9 1.8
8.3 27 46 86 45 19 1.8 1.8
9.6 41 76 130 55 35 2.1 2.2
14.2 40 64 96 96 24 1.9 2.4
8.5 35 74 102 43 39 2.2 1.8
13.5 28 57 100 52 29 2 2.4
4.9 32 45 94 60 13 1.7 1.8
6.4 22 30 52 54 8 1.7 1.9
9.6 44 62 98 51 18 1.8 2.4
11.6 27 51 118 51 24 1.9 2.1
11.1 17 36 99 38 19 1.8 1.9
4.35 12 34 48 41 23 1 2.1
12.7 45 61 50 146 16 1 2.7
18.1 37 70 150 182 33 4 2.1
17.85 37 69 154 192 32 4 2.1
16.6 108 145 109 263 37 3 2.1
12.6 10 23 68 35 14 2 2.1
17.1 68 120 194 439 52 4 2.1
19.1 72 147 158 214 75 4 2.1
16.1 143 215 159 341 72 4 2.1
13.35 9 24 67 58 15 2 2.1
18.4 55 84 147 292 29 4 2.4
14.7 17 30 39 85 13 1 1.95
10.6 37 77 100 200 40 3 2.1
12.6 27 46 111 158 19 3 2.1
16.2 37 61 138 199 24 4 1.95
13.6 58 178 101 297 121 3 2.1
18.9 66 160 131 227 93 4 2.4
14.1 21 57 101 108 36 3 2.1
14.5 19 42 114 86 23 3 2.25
16.15 78 163 165 302 85 4 2.4
14.75 35 75 114 148 41 3 2.25
14.8 48 94 111 178 46 3 2.55
12.45 27 45 75 120 18 2 1.95
12.65 43 78 82 207 35 2 2.4
17.35 30 47 121 157 17 3 2.1
8.6 25 29 32 128 4 1 2.1
18.4 69 97 150 296 28 4 2.4
16.1 72 116 117 323 44 3 2.1
11.6 23 32 71 79 10 2 2.1
17.75 13 50 165 70 38 4 2.25
15.25 61 118 154 146 57 4 2.25
17.65 43 66 126 246 23 4 2.4
16.35 51 86 149 196 36 4 2.1
17.65 67 89 145 199 22 4 2.4
13.6 36 76 120 127 40 3 2.1
14.35 44 75 109 153 31 3 2.1
14.75 45 57 132 299 11 4 2.25
18.25 34 72 172 228 38 4 2.25
9.9 36 60 169 190 24 4 2.4
16 72 109 114 180 37 3 2.25
18.25 39 76 156 212 37 4 2.25
16.85 43 65 172 269 22 4 2.1
14.6 25 40 68 130 15 2 2.1
13.85 56 58 89 179 2 2 2.1
18.95 80 123 167 243 43 4 2.7
15.6 40 71 113 190 31 3 2.1
14.85 73 102 115 299 29 3 2.1
11.75 34 80 78 121 45 2 2.25
18.45 72 97 118 137 25 3 2.7
15.9 42 46 87 305 4 2 2.4
17.1 61 93 173 157 31 4 2.1
16.1 23 19 2 96 -4 1 2.1
19.9 74 140 162 183 66 4 2.4
10.95 16 78 49 52 61 1 1.95
18.45 66 98 122 238 32 4 2.7
15.1 9 40 96 40 31 3 2.1
15 41 80 100 226 39 3 2.25
11.35 57 76 82 190 19 2 2.1
15.95 48 79 100 214 31 3 2.7
18.1 51 87 115 145 36 3 2.1
14.6 53 95 141 119 42 4 2.1
15.4 29 49 165 222 21 4 1.65
15.4 29 49 165 222 21 4 1.65
17.6 55 80 110 159 25 3 2.1
13.35 54 86 118 165 32 3 2.1
19.1 43 69 158 249 26 4 2.1
15.35 51 79 146 125 28 4 2.1
7.6 20 52 49 122 32 1 2.1
13.4 79 120 90 186 41 2 2.4
13.9 39 69 121 148 29 3 2.4
19.1 61 94 155 274 33 4 2.1
15.25 55 72 104 172 17 3 2.25
12.9 30 43 147 84 13 4 2.4
16.1 55 87 110 168 32 3 2.1
17.35 22 52 108 102 30 3 2.1
13.15 37 71 113 106 34 3 2.4
12.15 2 61 115 2 59 3 2.4
12.6 38 51 61 139 13 1 2.1
10.35 27 50 60 95 23 1 2.1
15.4 56 67 109 130 10 3 2.4
9.6 25 30 68 72 5 2 2.1
18.2 39 70 111 141 31 3 2.7
13.6 33 52 77 113 19 2 2.1
14.85 43 75 73 206 32 2 2.1
14.75 57 87 151 268 30 4 2.25
14.1 43 69 89 175 25 2 2.1
14.9 23 72 78 77 48 2 2.4
16.25 44 79 110 125 35 3 2.25
19.25 54 121 220 255 67 4 2.25
13.6 28 43 65 111 15 2 2.1
13.6 36 58 141 132 22 4 2.1
15.65 39 57 117 211 18 3 2.4
12.75 16 50 122 92 33 4 2.25
14.6 23 69 63 76 46 2 2.1
9.85 40 64 44 171 24 1 2.1
12.65 24 38 52 83 14 1 1.65
19.2 78 90 131 266 12 4 2.7
16.6 57 96 101 186 38 3 2.1
11.2 37 49 42 50 12 1 1.95
15.25 27 56 152 117 28 4 2.25
11.9 61 102 107 219 41 3 2.4
13.2 27 40 77 246 12 2 1.95
16.35 69 100 154 279 31 4 2.1
12.4 34 67 103 148 33 3 2.4
15.85 44 78 96 137 34 3 2.1
18.15 34 55 175 181 21 4 2.4
11.15 39 59 57 98 20 1 2.4
15.65 51 96 112 226 44 3 2.4
17.75 34 86 143 234 52 4 2.25
7.65 31 38 49 138 7 1 2.4
12.35 13 43 110 85 29 3 2.1
15.6 12 23 131 66 11 4 2.1
19.3 51 77 167 236 26 4 1.8
15.2 24 48 56 106 24 1 2.7
17.1 19 26 137 135 7 4 2.1
15.6 30 91 86 122 60 2 2.1
18.4 81 94 121 218 13 3 2.4
19.05 42 62 149 199 20 4 2.55
18.55 22 74 168 112 52 4 2.55
19.1 85 114 140 278 28 4 2.1
13.1 27 52 88 94 25 2 2.1
12.85 25 64 168 113 39 4 2.1
9.5 22 31 94 84 9 2 2.25
4.5 19 38 51 86 19 1 2.25
11.85 14 27 48 62 13 1 2.1
13.6 45 105 145 222 60 4 2.1
11.7 45 64 66 167 19 2 1.95
12.4 28 62 85 82 34 2 2.4
13.35 51 65 109 207 14 3 2.1
11.4 41 58 63 184 17 2 2.4
14.9 31 76 102 83 45 3 2.4
19.9 74 140 162 183 66 4 2.4
11.2 19 68 86 89 48 2 1.95
14.6 51 80 114 225 29 3 2.1
17.6 73 71 164 237 -2 4 2.1
14.05 24 76 119 102 51 3 2.55
16.1 61 63 126 221 2 4 2.1
13.35 23 46 132 128 24 4 2.1
11.85 14 53 142 91 40 4 2.1
11.95 54 74 83 198 20 2 1.95
14.75 51 70 94 204 19 2 2.25
15.15 62 78 81 158 16 2 2.4
13.2 36 56 166 138 20 4 1.95
16.85 59 100 110 226 40 3 2.1
7.85 24 51 64 44 27 2 2.1
7.7 26 52 93 196 25 2 1.95
12.6 54 102 104 83 49 3 2.1
7.85 39 78 105 79 39 3 2.1
10.95 16 78 49 52 61 1 1.95
12.35 36 55 88 105 19 2 2.1
9.95 31 98 95 116 67 2 1.95
14.9 31 76 102 83 45 3 2.4
16.65 42 73 99 196 30 3 2.4
13.4 39 47 63 153 8 2 2.4
13.95 25 45 76 157 19 2 1.95
15.7 31 83 109 75 52 3 2.7
16.85 38 60 117 106 22 3 2.1
10.95 31 48 57 58 17 1 1.95
15.35 17 50 120 75 33 3 2.1
12.2 22 56 73 74 34 2 1.95
15.1 55 77 91 185 22 2 2.1
17.75 62 91 108 265 30 3 2.25
15.2 51 76 105 131 25 3 2.7
14.6 30 68 117 139 38 3 2.1
16.65 49 74 119 196 26 3 2.4
8.1 16 29 31 78 13 1 1.35

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Herman Ole Andreas Wold' @ wold.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 & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 1.39076 -0.408212CH[t] + 0.421029Hours[t] -0.00887528LFM[t] + 0.0108214Blogs[t] -0.4312PRH[t] + 2.05136PR[t] + 2.69787PA[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  1.39076 -0.408212CH[t] +  0.421029Hours[t] -0.00887528LFM[t] +  0.0108214Blogs[t] -0.4312PRH[t] +  2.05136PR[t] +  2.69787PA[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  1.39076 -0.408212CH[t] +  0.421029Hours[t] -0.00887528LFM[t] +  0.0108214Blogs[t] -0.4312PRH[t] +  2.05136PR[t] +  2.69787PA[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 1.39076 -0.408212CH[t] + 0.421029Hours[t] -0.00887528LFM[t] + 0.0108214Blogs[t] -0.4312PRH[t] + 2.05136PR[t] + 2.69787PA[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.390761.064151.3070.1923540.096177
CH-0.4082120.366541-1.1140.2664030.133202
Hours0.4210290.3665851.1490.2517720.125886
LFM-0.008875280.00474958-1.8690.06275480.0313774
Blogs0.01082140.00285663.7880.0001870989.3549e-05
PRH-0.43120.367308-1.1740.2414510.120725
PR2.051360.2334948.7851.84231e-169.21153e-17
PA2.697870.4978755.4191.32985e-076.64924e-08

\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) & 1.39076 & 1.06415 & 1.307 & 0.192354 & 0.096177 \tabularnewline
CH & -0.408212 & 0.366541 & -1.114 & 0.266403 & 0.133202 \tabularnewline
Hours & 0.421029 & 0.366585 & 1.149 & 0.251772 & 0.125886 \tabularnewline
LFM & -0.00887528 & 0.00474958 & -1.869 & 0.0627548 & 0.0313774 \tabularnewline
Blogs & 0.0108214 & 0.0028566 & 3.788 & 0.000187098 & 9.3549e-05 \tabularnewline
PRH & -0.4312 & 0.367308 & -1.174 & 0.241451 & 0.120725 \tabularnewline
PR & 2.05136 & 0.233494 & 8.785 & 1.84231e-16 & 9.21153e-17 \tabularnewline
PA & 2.69787 & 0.497875 & 5.419 & 1.32985e-07 & 6.64924e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&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]1.39076[/C][C]1.06415[/C][C]1.307[/C][C]0.192354[/C][C]0.096177[/C][/ROW]
[ROW][C]CH[/C][C]-0.408212[/C][C]0.366541[/C][C]-1.114[/C][C]0.266403[/C][C]0.133202[/C][/ROW]
[ROW][C]Hours[/C][C]0.421029[/C][C]0.366585[/C][C]1.149[/C][C]0.251772[/C][C]0.125886[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00887528[/C][C]0.00474958[/C][C]-1.869[/C][C]0.0627548[/C][C]0.0313774[/C][/ROW]
[ROW][C]Blogs[/C][C]0.0108214[/C][C]0.0028566[/C][C]3.788[/C][C]0.000187098[/C][C]9.3549e-05[/C][/ROW]
[ROW][C]PRH[/C][C]-0.4312[/C][C]0.367308[/C][C]-1.174[/C][C]0.241451[/C][C]0.120725[/C][/ROW]
[ROW][C]PR[/C][C]2.05136[/C][C]0.233494[/C][C]8.785[/C][C]1.84231e-16[/C][C]9.21153e-17[/C][/ROW]
[ROW][C]PA[/C][C]2.69787[/C][C]0.497875[/C][C]5.419[/C][C]1.32985e-07[/C][C]6.64924e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)1.390761.064151.3070.1923540.096177
CH-0.4082120.366541-1.1140.2664030.133202
Hours0.4210290.3665851.1490.2517720.125886
LFM-0.008875280.00474958-1.8690.06275480.0313774
Blogs0.01082140.00285663.7880.0001870989.3549e-05
PRH-0.43120.367308-1.1740.2414510.120725
PR2.051360.2334948.7851.84231e-169.21153e-17
PA2.697870.4978755.4191.32985e-076.64924e-08






Multiple Linear Regression - Regression Statistics
Multiple R0.763097
R-squared0.582318
Adjusted R-squared0.571489
F-TEST (value)53.7749
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.22197
Sum Squared Residuals1333.04

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.763097 \tabularnewline
R-squared & 0.582318 \tabularnewline
Adjusted R-squared & 0.571489 \tabularnewline
F-TEST (value) & 53.7749 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.22197 \tabularnewline
Sum Squared Residuals & 1333.04 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.763097[/C][/ROW]
[ROW][C]R-squared[/C][C]0.582318[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.571489[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]53.7749[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.22197[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1333.04[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.763097
R-squared0.582318
Adjusted R-squared0.571489
F-TEST (value)53.7749
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.22197
Sum Squared Residuals1333.04






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.99.534913.36509
212.211.07251.12749
312.811.22151.57853
47.411.3929-3.99294
56.79.73349-3.03349
612.612.49640.103554
714.811.62533.17475
813.313.08480.2152
911.111.3566-0.25657
108.211.4065-3.20646
1111.411.7145-0.314507
126.411.2091-4.80913
1310.69.725630.874367
141212.317-0.317033
156.35.487530.812466
1611.311.6197-0.319714
1711.911.87020.0298427
189.310.2519-0.951898
199.612.0107-2.41071
201011.1318-1.13177
216.410.1258-3.72583
2213.811.84771.95225
2310.810.2290.571043
2413.811.73422.06577
2511.711.06870.631319
2610.912.6356-1.73563
2716.115.13110.968946
2813.412.34391.05607
299.910.3756-0.475612
3011.510.90410.595944
318.311.0719-2.77189
3211.711.57160.128433
3399.60316-0.603156
349.713.1123-3.41227
3510.812.242-1.44201
3610.310.9173-0.617269
3710.410.5789-0.178923
3812.711.74350.956469
399.311.3431-2.04311
4011.813.2503-1.45027
415.910.7956-4.89562
4211.411.9333-0.533301
431311.37241.62756
4410.810.35510.444857
4512.312.11230.18766
4611.312.029-0.728989
4711.812.203-0.403019
487.912.5578-4.65782
4912.79.599693.10031
5012.311.24041.05963
5111.612.3424-0.742378
526.711.7557-5.05572
5310.910.9899-0.0899311
5412.19.222.88
5513.312.02071.27934
5610.110.9095-0.809542
575.710.1737-4.47373
5814.310.02994.27008
5987.936520.0634832
6013.310.69642.60356
619.310.1566-0.856597
6212.510.8991.60095
637.611.6908-4.09077
6415.912.6783.22196
659.28.774250.425749
669.110.4488-1.34878
6711.112.9317-1.83169
681312.08330.916656
6914.511.6212.879
7012.210.71851.48149
7112.312.7126-0.412647
7211.410.30291.09711
738.810.0876-1.28758
7414.613.28821.31179
7512.611.29141.30861
761312.23540.76464
7712.610.50762.0924
7813.212.24750.952533
799.912.5911-2.6911
807.711.6358-3.93585
8110.511.4588-0.958842
8213.410.58022.81979
8310.912.1239-1.22394
844.38.90005-4.60005
8510.312.0884-1.78836
8611.812.1005-0.300462
8711.211.07370.126285
8811.412.5407-1.14066
898.610.9794-2.37944
9013.29.792263.40774
9112.610.73631.86373
925.69.81099-4.21099
939.99.93735-0.037355
948.810.723-1.923
957.711.8708-4.17077
9699.19634-0.196341
977.310.319-3.01901
9811.410.70510.694852
9913.610.88522.71477
1007.912.2882-4.38818
10110.710.728-0.0279733
10210.310.4022-0.102165
1038.39.81586-1.51586
1049.611.2448-1.64481
10514.212.21861.98139
1068.510.3719-1.87186
10713.511.70741.79255
1084.99.82715-4.92715
1096.410.3275-3.92746
1109.611.6211-2.02106
11111.610.56041.03959
11211.19.766351.33365
1134.358.62413-4.27413
11412.712.27650.423465
11518.116.03852.06151
11617.8516.12141.72862
11716.616.09690.503139
11812.610.4992.10103
11917.118.6331-1.53314
12019.116.33522.76484
12116.118.6411-2.54112
12213.3511.15482.19522
12318.418.33620.063779
12414.79.36235.3377
12510.614.5545-3.95448
12612.614.0878-1.48779
12716.216.01580.184177
12813.614.6195-1.01952
12918.917.68591.21412
13014.113.38570.714348
13114.513.54350.956522
13216.1518.0099-1.85987
13314.7513.81540.934641
13414.815.5128-0.712778
13512.4511.55020.899788
13612.6513.6757-1.02574
13717.3514.0473.303
1388.610.4885-1.8885
13918.418.5425-0.142488
14016.116.1425-0.0425349
14111.611.15580.444209
14217.7514.31863.43144
14315.2516.0816-0.831591
14417.6517.932-0.282044
14516.3515.92680.42324
14617.6517.57260.0774149
14713.613.57420.0258045
14814.3514.14730.202742
14914.7518.6164-3.86637
15018.2516.65641.59361
1519.916.8445-6.94452
1521615.09760.902417
15318.2516.69951.55049
15416.8516.9735-0.123485
15514.612.13012.46989
15613.8513.00350.846468
15718.9518.61580.334151
15815.614.46091.13912
15914.8516.066-1.21596
16011.7512.5799-0.829885
16118.4515.93292.51714
16215.914.99440.905641
16317.116.31280.787197
16416.110.46425.63578
16519.916.89073.00926
16610.958.836422.11358
16718.4518.8936-0.443579
16815.112.59122.50877
1691515.302-0.301955
17011.3513.0246-1.6746
17115.9516.5572-0.607228
17218.114.04634.0537
17314.615.5501-0.950149
17415.414.72270.677328
17515.414.72270.677328
17617.614.40533.19467
17713.3514.3152-0.965234
17819.116.84062.25938
17915.3515.6875-0.337468
1807.69.92381-2.32381
18113.413.7779-0.377868
18213.915.1733-1.2733
18319.117.29731.80271
18415.2515.08530.164693
18512.915.9277-3.02769
18616.114.43151.66848
18717.3513.33244.01756
18813.1514.2923-1.14228
18912.1512.4462-0.296227
19012.610.42522.17477
19110.359.715270.634733
19215.415.4962-0.0961583
1939.611.6042-2.00419
19418.215.55432.64571
19513.611.92811.67188
19614.8512.9661.88405
19714.7517.6518-2.90179
19814.112.98071.11929
19914.912.33692.56308
20016.2514.19942.05062
20119.2516.48392.76608
20213.611.98961.61042
20313.615.6764-2.07637
20415.6515.58140.068599
20512.7515.8696-3.11963
20614.611.24923.35081
2079.8510.8361-0.986145
20812.658.495464.15454
20919.219.4739-0.273932
21016.615.09181.50819
21111.29.223431.97657
21215.2516.0657-0.81575
21311.915.8048-3.90475
21413.213.378-0.178014
21516.3517.4831-1.13315
21612.414.8073-2.40725
21715.8514.0591.79102
21818.1516.69881.45124
21911.1510.7680.381966
22015.6516.0985-0.448472
22117.7516.83630.913696
2227.6511.3016-3.65159
22312.3513.4466-1.09658
22415.614.85520.744808
22519.315.91323.38676
22615.211.43993.7601
22717.115.6791.42098
22815.611.91123.68882
22918.416.21082.18918
23019.0517.64171.40831
23118.5515.94982.60023
23219.118.25320.846805
23313.111.4871.61304
23412.8514.9172-2.06723
2359.511.8288-2.32883
2364.510.0406-5.54058
23711.859.399762.45024
23813.616.3436-2.74363
23911.712.3592-0.659227
24012.412.11440.28564
24113.3514.9942-1.64425
24211.413.7529-2.35293
24314.913.95220.947772
24419.916.89073.00926
24511.211.13050.0695294
24614.614.9921-0.392082
24717.617.32680.273176
24814.0514.6819-0.631917
24916.117.2965-1.19645
25013.3515.105-1.75497
25111.8514.3377-2.48773
25211.9512.649-0.69899
25314.7513.39741.35263
25415.1513.59111.55885
25513.215.1351-1.93508
25616.8515.45011.39992
2577.8511.1001-3.2501
2587.712.5499-4.84989
25912.612.9582-0.35819
2607.8513.2365-5.38652
26110.958.836422.11358
26212.3511.78240.567627
2639.9510.8823-0.932286
26414.913.95220.947772
26516.6515.91630.733743
26613.413.4834-0.0833782
26713.9512.3271.62305
26815.714.54171.15831
26916.8513.58233.26771
27010.959.049121.90088
27115.3512.83922.51084
27212.210.84341.35665
27315.112.83452.26554
27417.7515.59272.15735
27515.215.7142-0.514156
27614.613.67410.92588
27716.6515.02711.6229
2788.17.726010.373985

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 9.53491 & 3.36509 \tabularnewline
2 & 12.2 & 11.0725 & 1.12749 \tabularnewline
3 & 12.8 & 11.2215 & 1.57853 \tabularnewline
4 & 7.4 & 11.3929 & -3.99294 \tabularnewline
5 & 6.7 & 9.73349 & -3.03349 \tabularnewline
6 & 12.6 & 12.4964 & 0.103554 \tabularnewline
7 & 14.8 & 11.6253 & 3.17475 \tabularnewline
8 & 13.3 & 13.0848 & 0.2152 \tabularnewline
9 & 11.1 & 11.3566 & -0.25657 \tabularnewline
10 & 8.2 & 11.4065 & -3.20646 \tabularnewline
11 & 11.4 & 11.7145 & -0.314507 \tabularnewline
12 & 6.4 & 11.2091 & -4.80913 \tabularnewline
13 & 10.6 & 9.72563 & 0.874367 \tabularnewline
14 & 12 & 12.317 & -0.317033 \tabularnewline
15 & 6.3 & 5.48753 & 0.812466 \tabularnewline
16 & 11.3 & 11.6197 & -0.319714 \tabularnewline
17 & 11.9 & 11.8702 & 0.0298427 \tabularnewline
18 & 9.3 & 10.2519 & -0.951898 \tabularnewline
19 & 9.6 & 12.0107 & -2.41071 \tabularnewline
20 & 10 & 11.1318 & -1.13177 \tabularnewline
21 & 6.4 & 10.1258 & -3.72583 \tabularnewline
22 & 13.8 & 11.8477 & 1.95225 \tabularnewline
23 & 10.8 & 10.229 & 0.571043 \tabularnewline
24 & 13.8 & 11.7342 & 2.06577 \tabularnewline
25 & 11.7 & 11.0687 & 0.631319 \tabularnewline
26 & 10.9 & 12.6356 & -1.73563 \tabularnewline
27 & 16.1 & 15.1311 & 0.968946 \tabularnewline
28 & 13.4 & 12.3439 & 1.05607 \tabularnewline
29 & 9.9 & 10.3756 & -0.475612 \tabularnewline
30 & 11.5 & 10.9041 & 0.595944 \tabularnewline
31 & 8.3 & 11.0719 & -2.77189 \tabularnewline
32 & 11.7 & 11.5716 & 0.128433 \tabularnewline
33 & 9 & 9.60316 & -0.603156 \tabularnewline
34 & 9.7 & 13.1123 & -3.41227 \tabularnewline
35 & 10.8 & 12.242 & -1.44201 \tabularnewline
36 & 10.3 & 10.9173 & -0.617269 \tabularnewline
37 & 10.4 & 10.5789 & -0.178923 \tabularnewline
38 & 12.7 & 11.7435 & 0.956469 \tabularnewline
39 & 9.3 & 11.3431 & -2.04311 \tabularnewline
40 & 11.8 & 13.2503 & -1.45027 \tabularnewline
41 & 5.9 & 10.7956 & -4.89562 \tabularnewline
42 & 11.4 & 11.9333 & -0.533301 \tabularnewline
43 & 13 & 11.3724 & 1.62756 \tabularnewline
44 & 10.8 & 10.3551 & 0.444857 \tabularnewline
45 & 12.3 & 12.1123 & 0.18766 \tabularnewline
46 & 11.3 & 12.029 & -0.728989 \tabularnewline
47 & 11.8 & 12.203 & -0.403019 \tabularnewline
48 & 7.9 & 12.5578 & -4.65782 \tabularnewline
49 & 12.7 & 9.59969 & 3.10031 \tabularnewline
50 & 12.3 & 11.2404 & 1.05963 \tabularnewline
51 & 11.6 & 12.3424 & -0.742378 \tabularnewline
52 & 6.7 & 11.7557 & -5.05572 \tabularnewline
53 & 10.9 & 10.9899 & -0.0899311 \tabularnewline
54 & 12.1 & 9.22 & 2.88 \tabularnewline
55 & 13.3 & 12.0207 & 1.27934 \tabularnewline
56 & 10.1 & 10.9095 & -0.809542 \tabularnewline
57 & 5.7 & 10.1737 & -4.47373 \tabularnewline
58 & 14.3 & 10.0299 & 4.27008 \tabularnewline
59 & 8 & 7.93652 & 0.0634832 \tabularnewline
60 & 13.3 & 10.6964 & 2.60356 \tabularnewline
61 & 9.3 & 10.1566 & -0.856597 \tabularnewline
62 & 12.5 & 10.899 & 1.60095 \tabularnewline
63 & 7.6 & 11.6908 & -4.09077 \tabularnewline
64 & 15.9 & 12.678 & 3.22196 \tabularnewline
65 & 9.2 & 8.77425 & 0.425749 \tabularnewline
66 & 9.1 & 10.4488 & -1.34878 \tabularnewline
67 & 11.1 & 12.9317 & -1.83169 \tabularnewline
68 & 13 & 12.0833 & 0.916656 \tabularnewline
69 & 14.5 & 11.621 & 2.879 \tabularnewline
70 & 12.2 & 10.7185 & 1.48149 \tabularnewline
71 & 12.3 & 12.7126 & -0.412647 \tabularnewline
72 & 11.4 & 10.3029 & 1.09711 \tabularnewline
73 & 8.8 & 10.0876 & -1.28758 \tabularnewline
74 & 14.6 & 13.2882 & 1.31179 \tabularnewline
75 & 12.6 & 11.2914 & 1.30861 \tabularnewline
76 & 13 & 12.2354 & 0.76464 \tabularnewline
77 & 12.6 & 10.5076 & 2.0924 \tabularnewline
78 & 13.2 & 12.2475 & 0.952533 \tabularnewline
79 & 9.9 & 12.5911 & -2.6911 \tabularnewline
80 & 7.7 & 11.6358 & -3.93585 \tabularnewline
81 & 10.5 & 11.4588 & -0.958842 \tabularnewline
82 & 13.4 & 10.5802 & 2.81979 \tabularnewline
83 & 10.9 & 12.1239 & -1.22394 \tabularnewline
84 & 4.3 & 8.90005 & -4.60005 \tabularnewline
85 & 10.3 & 12.0884 & -1.78836 \tabularnewline
86 & 11.8 & 12.1005 & -0.300462 \tabularnewline
87 & 11.2 & 11.0737 & 0.126285 \tabularnewline
88 & 11.4 & 12.5407 & -1.14066 \tabularnewline
89 & 8.6 & 10.9794 & -2.37944 \tabularnewline
90 & 13.2 & 9.79226 & 3.40774 \tabularnewline
91 & 12.6 & 10.7363 & 1.86373 \tabularnewline
92 & 5.6 & 9.81099 & -4.21099 \tabularnewline
93 & 9.9 & 9.93735 & -0.037355 \tabularnewline
94 & 8.8 & 10.723 & -1.923 \tabularnewline
95 & 7.7 & 11.8708 & -4.17077 \tabularnewline
96 & 9 & 9.19634 & -0.196341 \tabularnewline
97 & 7.3 & 10.319 & -3.01901 \tabularnewline
98 & 11.4 & 10.7051 & 0.694852 \tabularnewline
99 & 13.6 & 10.8852 & 2.71477 \tabularnewline
100 & 7.9 & 12.2882 & -4.38818 \tabularnewline
101 & 10.7 & 10.728 & -0.0279733 \tabularnewline
102 & 10.3 & 10.4022 & -0.102165 \tabularnewline
103 & 8.3 & 9.81586 & -1.51586 \tabularnewline
104 & 9.6 & 11.2448 & -1.64481 \tabularnewline
105 & 14.2 & 12.2186 & 1.98139 \tabularnewline
106 & 8.5 & 10.3719 & -1.87186 \tabularnewline
107 & 13.5 & 11.7074 & 1.79255 \tabularnewline
108 & 4.9 & 9.82715 & -4.92715 \tabularnewline
109 & 6.4 & 10.3275 & -3.92746 \tabularnewline
110 & 9.6 & 11.6211 & -2.02106 \tabularnewline
111 & 11.6 & 10.5604 & 1.03959 \tabularnewline
112 & 11.1 & 9.76635 & 1.33365 \tabularnewline
113 & 4.35 & 8.62413 & -4.27413 \tabularnewline
114 & 12.7 & 12.2765 & 0.423465 \tabularnewline
115 & 18.1 & 16.0385 & 2.06151 \tabularnewline
116 & 17.85 & 16.1214 & 1.72862 \tabularnewline
117 & 16.6 & 16.0969 & 0.503139 \tabularnewline
118 & 12.6 & 10.499 & 2.10103 \tabularnewline
119 & 17.1 & 18.6331 & -1.53314 \tabularnewline
120 & 19.1 & 16.3352 & 2.76484 \tabularnewline
121 & 16.1 & 18.6411 & -2.54112 \tabularnewline
122 & 13.35 & 11.1548 & 2.19522 \tabularnewline
123 & 18.4 & 18.3362 & 0.063779 \tabularnewline
124 & 14.7 & 9.3623 & 5.3377 \tabularnewline
125 & 10.6 & 14.5545 & -3.95448 \tabularnewline
126 & 12.6 & 14.0878 & -1.48779 \tabularnewline
127 & 16.2 & 16.0158 & 0.184177 \tabularnewline
128 & 13.6 & 14.6195 & -1.01952 \tabularnewline
129 & 18.9 & 17.6859 & 1.21412 \tabularnewline
130 & 14.1 & 13.3857 & 0.714348 \tabularnewline
131 & 14.5 & 13.5435 & 0.956522 \tabularnewline
132 & 16.15 & 18.0099 & -1.85987 \tabularnewline
133 & 14.75 & 13.8154 & 0.934641 \tabularnewline
134 & 14.8 & 15.5128 & -0.712778 \tabularnewline
135 & 12.45 & 11.5502 & 0.899788 \tabularnewline
136 & 12.65 & 13.6757 & -1.02574 \tabularnewline
137 & 17.35 & 14.047 & 3.303 \tabularnewline
138 & 8.6 & 10.4885 & -1.8885 \tabularnewline
139 & 18.4 & 18.5425 & -0.142488 \tabularnewline
140 & 16.1 & 16.1425 & -0.0425349 \tabularnewline
141 & 11.6 & 11.1558 & 0.444209 \tabularnewline
142 & 17.75 & 14.3186 & 3.43144 \tabularnewline
143 & 15.25 & 16.0816 & -0.831591 \tabularnewline
144 & 17.65 & 17.932 & -0.282044 \tabularnewline
145 & 16.35 & 15.9268 & 0.42324 \tabularnewline
146 & 17.65 & 17.5726 & 0.0774149 \tabularnewline
147 & 13.6 & 13.5742 & 0.0258045 \tabularnewline
148 & 14.35 & 14.1473 & 0.202742 \tabularnewline
149 & 14.75 & 18.6164 & -3.86637 \tabularnewline
150 & 18.25 & 16.6564 & 1.59361 \tabularnewline
151 & 9.9 & 16.8445 & -6.94452 \tabularnewline
152 & 16 & 15.0976 & 0.902417 \tabularnewline
153 & 18.25 & 16.6995 & 1.55049 \tabularnewline
154 & 16.85 & 16.9735 & -0.123485 \tabularnewline
155 & 14.6 & 12.1301 & 2.46989 \tabularnewline
156 & 13.85 & 13.0035 & 0.846468 \tabularnewline
157 & 18.95 & 18.6158 & 0.334151 \tabularnewline
158 & 15.6 & 14.4609 & 1.13912 \tabularnewline
159 & 14.85 & 16.066 & -1.21596 \tabularnewline
160 & 11.75 & 12.5799 & -0.829885 \tabularnewline
161 & 18.45 & 15.9329 & 2.51714 \tabularnewline
162 & 15.9 & 14.9944 & 0.905641 \tabularnewline
163 & 17.1 & 16.3128 & 0.787197 \tabularnewline
164 & 16.1 & 10.4642 & 5.63578 \tabularnewline
165 & 19.9 & 16.8907 & 3.00926 \tabularnewline
166 & 10.95 & 8.83642 & 2.11358 \tabularnewline
167 & 18.45 & 18.8936 & -0.443579 \tabularnewline
168 & 15.1 & 12.5912 & 2.50877 \tabularnewline
169 & 15 & 15.302 & -0.301955 \tabularnewline
170 & 11.35 & 13.0246 & -1.6746 \tabularnewline
171 & 15.95 & 16.5572 & -0.607228 \tabularnewline
172 & 18.1 & 14.0463 & 4.0537 \tabularnewline
173 & 14.6 & 15.5501 & -0.950149 \tabularnewline
174 & 15.4 & 14.7227 & 0.677328 \tabularnewline
175 & 15.4 & 14.7227 & 0.677328 \tabularnewline
176 & 17.6 & 14.4053 & 3.19467 \tabularnewline
177 & 13.35 & 14.3152 & -0.965234 \tabularnewline
178 & 19.1 & 16.8406 & 2.25938 \tabularnewline
179 & 15.35 & 15.6875 & -0.337468 \tabularnewline
180 & 7.6 & 9.92381 & -2.32381 \tabularnewline
181 & 13.4 & 13.7779 & -0.377868 \tabularnewline
182 & 13.9 & 15.1733 & -1.2733 \tabularnewline
183 & 19.1 & 17.2973 & 1.80271 \tabularnewline
184 & 15.25 & 15.0853 & 0.164693 \tabularnewline
185 & 12.9 & 15.9277 & -3.02769 \tabularnewline
186 & 16.1 & 14.4315 & 1.66848 \tabularnewline
187 & 17.35 & 13.3324 & 4.01756 \tabularnewline
188 & 13.15 & 14.2923 & -1.14228 \tabularnewline
189 & 12.15 & 12.4462 & -0.296227 \tabularnewline
190 & 12.6 & 10.4252 & 2.17477 \tabularnewline
191 & 10.35 & 9.71527 & 0.634733 \tabularnewline
192 & 15.4 & 15.4962 & -0.0961583 \tabularnewline
193 & 9.6 & 11.6042 & -2.00419 \tabularnewline
194 & 18.2 & 15.5543 & 2.64571 \tabularnewline
195 & 13.6 & 11.9281 & 1.67188 \tabularnewline
196 & 14.85 & 12.966 & 1.88405 \tabularnewline
197 & 14.75 & 17.6518 & -2.90179 \tabularnewline
198 & 14.1 & 12.9807 & 1.11929 \tabularnewline
199 & 14.9 & 12.3369 & 2.56308 \tabularnewline
200 & 16.25 & 14.1994 & 2.05062 \tabularnewline
201 & 19.25 & 16.4839 & 2.76608 \tabularnewline
202 & 13.6 & 11.9896 & 1.61042 \tabularnewline
203 & 13.6 & 15.6764 & -2.07637 \tabularnewline
204 & 15.65 & 15.5814 & 0.068599 \tabularnewline
205 & 12.75 & 15.8696 & -3.11963 \tabularnewline
206 & 14.6 & 11.2492 & 3.35081 \tabularnewline
207 & 9.85 & 10.8361 & -0.986145 \tabularnewline
208 & 12.65 & 8.49546 & 4.15454 \tabularnewline
209 & 19.2 & 19.4739 & -0.273932 \tabularnewline
210 & 16.6 & 15.0918 & 1.50819 \tabularnewline
211 & 11.2 & 9.22343 & 1.97657 \tabularnewline
212 & 15.25 & 16.0657 & -0.81575 \tabularnewline
213 & 11.9 & 15.8048 & -3.90475 \tabularnewline
214 & 13.2 & 13.378 & -0.178014 \tabularnewline
215 & 16.35 & 17.4831 & -1.13315 \tabularnewline
216 & 12.4 & 14.8073 & -2.40725 \tabularnewline
217 & 15.85 & 14.059 & 1.79102 \tabularnewline
218 & 18.15 & 16.6988 & 1.45124 \tabularnewline
219 & 11.15 & 10.768 & 0.381966 \tabularnewline
220 & 15.65 & 16.0985 & -0.448472 \tabularnewline
221 & 17.75 & 16.8363 & 0.913696 \tabularnewline
222 & 7.65 & 11.3016 & -3.65159 \tabularnewline
223 & 12.35 & 13.4466 & -1.09658 \tabularnewline
224 & 15.6 & 14.8552 & 0.744808 \tabularnewline
225 & 19.3 & 15.9132 & 3.38676 \tabularnewline
226 & 15.2 & 11.4399 & 3.7601 \tabularnewline
227 & 17.1 & 15.679 & 1.42098 \tabularnewline
228 & 15.6 & 11.9112 & 3.68882 \tabularnewline
229 & 18.4 & 16.2108 & 2.18918 \tabularnewline
230 & 19.05 & 17.6417 & 1.40831 \tabularnewline
231 & 18.55 & 15.9498 & 2.60023 \tabularnewline
232 & 19.1 & 18.2532 & 0.846805 \tabularnewline
233 & 13.1 & 11.487 & 1.61304 \tabularnewline
234 & 12.85 & 14.9172 & -2.06723 \tabularnewline
235 & 9.5 & 11.8288 & -2.32883 \tabularnewline
236 & 4.5 & 10.0406 & -5.54058 \tabularnewline
237 & 11.85 & 9.39976 & 2.45024 \tabularnewline
238 & 13.6 & 16.3436 & -2.74363 \tabularnewline
239 & 11.7 & 12.3592 & -0.659227 \tabularnewline
240 & 12.4 & 12.1144 & 0.28564 \tabularnewline
241 & 13.35 & 14.9942 & -1.64425 \tabularnewline
242 & 11.4 & 13.7529 & -2.35293 \tabularnewline
243 & 14.9 & 13.9522 & 0.947772 \tabularnewline
244 & 19.9 & 16.8907 & 3.00926 \tabularnewline
245 & 11.2 & 11.1305 & 0.0695294 \tabularnewline
246 & 14.6 & 14.9921 & -0.392082 \tabularnewline
247 & 17.6 & 17.3268 & 0.273176 \tabularnewline
248 & 14.05 & 14.6819 & -0.631917 \tabularnewline
249 & 16.1 & 17.2965 & -1.19645 \tabularnewline
250 & 13.35 & 15.105 & -1.75497 \tabularnewline
251 & 11.85 & 14.3377 & -2.48773 \tabularnewline
252 & 11.95 & 12.649 & -0.69899 \tabularnewline
253 & 14.75 & 13.3974 & 1.35263 \tabularnewline
254 & 15.15 & 13.5911 & 1.55885 \tabularnewline
255 & 13.2 & 15.1351 & -1.93508 \tabularnewline
256 & 16.85 & 15.4501 & 1.39992 \tabularnewline
257 & 7.85 & 11.1001 & -3.2501 \tabularnewline
258 & 7.7 & 12.5499 & -4.84989 \tabularnewline
259 & 12.6 & 12.9582 & -0.35819 \tabularnewline
260 & 7.85 & 13.2365 & -5.38652 \tabularnewline
261 & 10.95 & 8.83642 & 2.11358 \tabularnewline
262 & 12.35 & 11.7824 & 0.567627 \tabularnewline
263 & 9.95 & 10.8823 & -0.932286 \tabularnewline
264 & 14.9 & 13.9522 & 0.947772 \tabularnewline
265 & 16.65 & 15.9163 & 0.733743 \tabularnewline
266 & 13.4 & 13.4834 & -0.0833782 \tabularnewline
267 & 13.95 & 12.327 & 1.62305 \tabularnewline
268 & 15.7 & 14.5417 & 1.15831 \tabularnewline
269 & 16.85 & 13.5823 & 3.26771 \tabularnewline
270 & 10.95 & 9.04912 & 1.90088 \tabularnewline
271 & 15.35 & 12.8392 & 2.51084 \tabularnewline
272 & 12.2 & 10.8434 & 1.35665 \tabularnewline
273 & 15.1 & 12.8345 & 2.26554 \tabularnewline
274 & 17.75 & 15.5927 & 2.15735 \tabularnewline
275 & 15.2 & 15.7142 & -0.514156 \tabularnewline
276 & 14.6 & 13.6741 & 0.92588 \tabularnewline
277 & 16.65 & 15.0271 & 1.6229 \tabularnewline
278 & 8.1 & 7.72601 & 0.373985 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]9.53491[/C][C]3.36509[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.0725[/C][C]1.12749[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.2215[/C][C]1.57853[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.3929[/C][C]-3.99294[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]9.73349[/C][C]-3.03349[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.4964[/C][C]0.103554[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.6253[/C][C]3.17475[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.0848[/C][C]0.2152[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.3566[/C][C]-0.25657[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.4065[/C][C]-3.20646[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.7145[/C][C]-0.314507[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.2091[/C][C]-4.80913[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.72563[/C][C]0.874367[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.317[/C][C]-0.317033[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]5.48753[/C][C]0.812466[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.6197[/C][C]-0.319714[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.8702[/C][C]0.0298427[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.2519[/C][C]-0.951898[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.0107[/C][C]-2.41071[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.1318[/C][C]-1.13177[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.1258[/C][C]-3.72583[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]11.8477[/C][C]1.95225[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]10.229[/C][C]0.571043[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]11.7342[/C][C]2.06577[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.0687[/C][C]0.631319[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.6356[/C][C]-1.73563[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]15.1311[/C][C]0.968946[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.3439[/C][C]1.05607[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]10.3756[/C][C]-0.475612[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]10.9041[/C][C]0.595944[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.0719[/C][C]-2.77189[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.5716[/C][C]0.128433[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.60316[/C][C]-0.603156[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.1123[/C][C]-3.41227[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.242[/C][C]-1.44201[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]10.9173[/C][C]-0.617269[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.5789[/C][C]-0.178923[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]11.7435[/C][C]0.956469[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.3431[/C][C]-2.04311[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]13.2503[/C][C]-1.45027[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.7956[/C][C]-4.89562[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.9333[/C][C]-0.533301[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.3724[/C][C]1.62756[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]10.3551[/C][C]0.444857[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.1123[/C][C]0.18766[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.029[/C][C]-0.728989[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.203[/C][C]-0.403019[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.5578[/C][C]-4.65782[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.59969[/C][C]3.10031[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.2404[/C][C]1.05963[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.3424[/C][C]-0.742378[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]11.7557[/C][C]-5.05572[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.9899[/C][C]-0.0899311[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]9.22[/C][C]2.88[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]12.0207[/C][C]1.27934[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.9095[/C][C]-0.809542[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.1737[/C][C]-4.47373[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.0299[/C][C]4.27008[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.93652[/C][C]0.0634832[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.6964[/C][C]2.60356[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]10.1566[/C][C]-0.856597[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]10.899[/C][C]1.60095[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.6908[/C][C]-4.09077[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.678[/C][C]3.22196[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]8.77425[/C][C]0.425749[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.4488[/C][C]-1.34878[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.9317[/C][C]-1.83169[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]12.0833[/C][C]0.916656[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.621[/C][C]2.879[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.7185[/C][C]1.48149[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]12.7126[/C][C]-0.412647[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.3029[/C][C]1.09711[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.0876[/C][C]-1.28758[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.2882[/C][C]1.31179[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.2914[/C][C]1.30861[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]12.2354[/C][C]0.76464[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]10.5076[/C][C]2.0924[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.2475[/C][C]0.952533[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.5911[/C][C]-2.6911[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.6358[/C][C]-3.93585[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]11.4588[/C][C]-0.958842[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.5802[/C][C]2.81979[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.1239[/C][C]-1.22394[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]8.90005[/C][C]-4.60005[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]12.0884[/C][C]-1.78836[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.1005[/C][C]-0.300462[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]11.0737[/C][C]0.126285[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]12.5407[/C][C]-1.14066[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.9794[/C][C]-2.37944[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]9.79226[/C][C]3.40774[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.7363[/C][C]1.86373[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]9.81099[/C][C]-4.21099[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]9.93735[/C][C]-0.037355[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.723[/C][C]-1.923[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]11.8708[/C][C]-4.17077[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]9.19634[/C][C]-0.196341[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]10.319[/C][C]-3.01901[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]10.7051[/C][C]0.694852[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]10.8852[/C][C]2.71477[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.2882[/C][C]-4.38818[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]10.728[/C][C]-0.0279733[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.4022[/C][C]-0.102165[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]9.81586[/C][C]-1.51586[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]11.2448[/C][C]-1.64481[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.2186[/C][C]1.98139[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.3719[/C][C]-1.87186[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]11.7074[/C][C]1.79255[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]9.82715[/C][C]-4.92715[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.3275[/C][C]-3.92746[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]11.6211[/C][C]-2.02106[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.5604[/C][C]1.03959[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]9.76635[/C][C]1.33365[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]8.62413[/C][C]-4.27413[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.2765[/C][C]0.423465[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]16.0385[/C][C]2.06151[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]16.1214[/C][C]1.72862[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]16.0969[/C][C]0.503139[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]10.499[/C][C]2.10103[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]18.6331[/C][C]-1.53314[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]16.3352[/C][C]2.76484[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.6411[/C][C]-2.54112[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]11.1548[/C][C]2.19522[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]18.3362[/C][C]0.063779[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]9.3623[/C][C]5.3377[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.5545[/C][C]-3.95448[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]14.0878[/C][C]-1.48779[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]16.0158[/C][C]0.184177[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]14.6195[/C][C]-1.01952[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]17.6859[/C][C]1.21412[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.3857[/C][C]0.714348[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.5435[/C][C]0.956522[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]18.0099[/C][C]-1.85987[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.8154[/C][C]0.934641[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]15.5128[/C][C]-0.712778[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]11.5502[/C][C]0.899788[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.6757[/C][C]-1.02574[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]14.047[/C][C]3.303[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]10.4885[/C][C]-1.8885[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]18.5425[/C][C]-0.142488[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]16.1425[/C][C]-0.0425349[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]11.1558[/C][C]0.444209[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]14.3186[/C][C]3.43144[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]16.0816[/C][C]-0.831591[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]17.932[/C][C]-0.282044[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]15.9268[/C][C]0.42324[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]17.5726[/C][C]0.0774149[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]13.5742[/C][C]0.0258045[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.1473[/C][C]0.202742[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]18.6164[/C][C]-3.86637[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.6564[/C][C]1.59361[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]16.8445[/C][C]-6.94452[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.0976[/C][C]0.902417[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]16.6995[/C][C]1.55049[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]16.9735[/C][C]-0.123485[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.1301[/C][C]2.46989[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.0035[/C][C]0.846468[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]18.6158[/C][C]0.334151[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.4609[/C][C]1.13912[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]16.066[/C][C]-1.21596[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.5799[/C][C]-0.829885[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]15.9329[/C][C]2.51714[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]14.9944[/C][C]0.905641[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]16.3128[/C][C]0.787197[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]10.4642[/C][C]5.63578[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]16.8907[/C][C]3.00926[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]8.83642[/C][C]2.11358[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]18.8936[/C][C]-0.443579[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]12.5912[/C][C]2.50877[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.302[/C][C]-0.301955[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.0246[/C][C]-1.6746[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]16.5572[/C][C]-0.607228[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]14.0463[/C][C]4.0537[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]15.5501[/C][C]-0.950149[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]14.7227[/C][C]0.677328[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]14.7227[/C][C]0.677328[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]14.4053[/C][C]3.19467[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.3152[/C][C]-0.965234[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.8406[/C][C]2.25938[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]15.6875[/C][C]-0.337468[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]9.92381[/C][C]-2.32381[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.7779[/C][C]-0.377868[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]15.1733[/C][C]-1.2733[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.2973[/C][C]1.80271[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]15.0853[/C][C]0.164693[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]15.9277[/C][C]-3.02769[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]14.4315[/C][C]1.66848[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.3324[/C][C]4.01756[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]14.2923[/C][C]-1.14228[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]12.4462[/C][C]-0.296227[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]10.4252[/C][C]2.17477[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]9.71527[/C][C]0.634733[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]15.4962[/C][C]-0.0961583[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]11.6042[/C][C]-2.00419[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]15.5543[/C][C]2.64571[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]11.9281[/C][C]1.67188[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]12.966[/C][C]1.88405[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]17.6518[/C][C]-2.90179[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.9807[/C][C]1.11929[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.3369[/C][C]2.56308[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]14.1994[/C][C]2.05062[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]16.4839[/C][C]2.76608[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]11.9896[/C][C]1.61042[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.6764[/C][C]-2.07637[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.5814[/C][C]0.068599[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]15.8696[/C][C]-3.11963[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]11.2492[/C][C]3.35081[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]10.8361[/C][C]-0.986145[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]8.49546[/C][C]4.15454[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]19.4739[/C][C]-0.273932[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]15.0918[/C][C]1.50819[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]9.22343[/C][C]1.97657[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]16.0657[/C][C]-0.81575[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]15.8048[/C][C]-3.90475[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]13.378[/C][C]-0.178014[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.4831[/C][C]-1.13315[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]14.8073[/C][C]-2.40725[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]14.059[/C][C]1.79102[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]16.6988[/C][C]1.45124[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]10.768[/C][C]0.381966[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.0985[/C][C]-0.448472[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]16.8363[/C][C]0.913696[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]11.3016[/C][C]-3.65159[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.4466[/C][C]-1.09658[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]14.8552[/C][C]0.744808[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]15.9132[/C][C]3.38676[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.4399[/C][C]3.7601[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]15.679[/C][C]1.42098[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]11.9112[/C][C]3.68882[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]16.2108[/C][C]2.18918[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]17.6417[/C][C]1.40831[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.9498[/C][C]2.60023[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]18.2532[/C][C]0.846805[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.487[/C][C]1.61304[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]14.9172[/C][C]-2.06723[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.8288[/C][C]-2.32883[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]10.0406[/C][C]-5.54058[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]9.39976[/C][C]2.45024[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]16.3436[/C][C]-2.74363[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.3592[/C][C]-0.659227[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.1144[/C][C]0.28564[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.9942[/C][C]-1.64425[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.7529[/C][C]-2.35293[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]13.9522[/C][C]0.947772[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]16.8907[/C][C]3.00926[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]11.1305[/C][C]0.0695294[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]14.9921[/C][C]-0.392082[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]17.3268[/C][C]0.273176[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]14.6819[/C][C]-0.631917[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]17.2965[/C][C]-1.19645[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]15.105[/C][C]-1.75497[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.3377[/C][C]-2.48773[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]12.649[/C][C]-0.69899[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]13.3974[/C][C]1.35263[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.5911[/C][C]1.55885[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]15.1351[/C][C]-1.93508[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]15.4501[/C][C]1.39992[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]11.1001[/C][C]-3.2501[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.5499[/C][C]-4.84989[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.9582[/C][C]-0.35819[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.2365[/C][C]-5.38652[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]8.83642[/C][C]2.11358[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]11.7824[/C][C]0.567627[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]10.8823[/C][C]-0.932286[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]13.9522[/C][C]0.947772[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]15.9163[/C][C]0.733743[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.4834[/C][C]-0.0833782[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]12.327[/C][C]1.62305[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.5417[/C][C]1.15831[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]13.5823[/C][C]3.26771[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]9.04912[/C][C]1.90088[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.8392[/C][C]2.51084[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]10.8434[/C][C]1.35665[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.8345[/C][C]2.26554[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]15.5927[/C][C]2.15735[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]15.7142[/C][C]-0.514156[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.6741[/C][C]0.92588[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]15.0271[/C][C]1.6229[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]7.72601[/C][C]0.373985[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.99.534913.36509
212.211.07251.12749
312.811.22151.57853
47.411.3929-3.99294
56.79.73349-3.03349
612.612.49640.103554
714.811.62533.17475
813.313.08480.2152
911.111.3566-0.25657
108.211.4065-3.20646
1111.411.7145-0.314507
126.411.2091-4.80913
1310.69.725630.874367
141212.317-0.317033
156.35.487530.812466
1611.311.6197-0.319714
1711.911.87020.0298427
189.310.2519-0.951898
199.612.0107-2.41071
201011.1318-1.13177
216.410.1258-3.72583
2213.811.84771.95225
2310.810.2290.571043
2413.811.73422.06577
2511.711.06870.631319
2610.912.6356-1.73563
2716.115.13110.968946
2813.412.34391.05607
299.910.3756-0.475612
3011.510.90410.595944
318.311.0719-2.77189
3211.711.57160.128433
3399.60316-0.603156
349.713.1123-3.41227
3510.812.242-1.44201
3610.310.9173-0.617269
3710.410.5789-0.178923
3812.711.74350.956469
399.311.3431-2.04311
4011.813.2503-1.45027
415.910.7956-4.89562
4211.411.9333-0.533301
431311.37241.62756
4410.810.35510.444857
4512.312.11230.18766
4611.312.029-0.728989
4711.812.203-0.403019
487.912.5578-4.65782
4912.79.599693.10031
5012.311.24041.05963
5111.612.3424-0.742378
526.711.7557-5.05572
5310.910.9899-0.0899311
5412.19.222.88
5513.312.02071.27934
5610.110.9095-0.809542
575.710.1737-4.47373
5814.310.02994.27008
5987.936520.0634832
6013.310.69642.60356
619.310.1566-0.856597
6212.510.8991.60095
637.611.6908-4.09077
6415.912.6783.22196
659.28.774250.425749
669.110.4488-1.34878
6711.112.9317-1.83169
681312.08330.916656
6914.511.6212.879
7012.210.71851.48149
7112.312.7126-0.412647
7211.410.30291.09711
738.810.0876-1.28758
7414.613.28821.31179
7512.611.29141.30861
761312.23540.76464
7712.610.50762.0924
7813.212.24750.952533
799.912.5911-2.6911
807.711.6358-3.93585
8110.511.4588-0.958842
8213.410.58022.81979
8310.912.1239-1.22394
844.38.90005-4.60005
8510.312.0884-1.78836
8611.812.1005-0.300462
8711.211.07370.126285
8811.412.5407-1.14066
898.610.9794-2.37944
9013.29.792263.40774
9112.610.73631.86373
925.69.81099-4.21099
939.99.93735-0.037355
948.810.723-1.923
957.711.8708-4.17077
9699.19634-0.196341
977.310.319-3.01901
9811.410.70510.694852
9913.610.88522.71477
1007.912.2882-4.38818
10110.710.728-0.0279733
10210.310.4022-0.102165
1038.39.81586-1.51586
1049.611.2448-1.64481
10514.212.21861.98139
1068.510.3719-1.87186
10713.511.70741.79255
1084.99.82715-4.92715
1096.410.3275-3.92746
1109.611.6211-2.02106
11111.610.56041.03959
11211.19.766351.33365
1134.358.62413-4.27413
11412.712.27650.423465
11518.116.03852.06151
11617.8516.12141.72862
11716.616.09690.503139
11812.610.4992.10103
11917.118.6331-1.53314
12019.116.33522.76484
12116.118.6411-2.54112
12213.3511.15482.19522
12318.418.33620.063779
12414.79.36235.3377
12510.614.5545-3.95448
12612.614.0878-1.48779
12716.216.01580.184177
12813.614.6195-1.01952
12918.917.68591.21412
13014.113.38570.714348
13114.513.54350.956522
13216.1518.0099-1.85987
13314.7513.81540.934641
13414.815.5128-0.712778
13512.4511.55020.899788
13612.6513.6757-1.02574
13717.3514.0473.303
1388.610.4885-1.8885
13918.418.5425-0.142488
14016.116.1425-0.0425349
14111.611.15580.444209
14217.7514.31863.43144
14315.2516.0816-0.831591
14417.6517.932-0.282044
14516.3515.92680.42324
14617.6517.57260.0774149
14713.613.57420.0258045
14814.3514.14730.202742
14914.7518.6164-3.86637
15018.2516.65641.59361
1519.916.8445-6.94452
1521615.09760.902417
15318.2516.69951.55049
15416.8516.9735-0.123485
15514.612.13012.46989
15613.8513.00350.846468
15718.9518.61580.334151
15815.614.46091.13912
15914.8516.066-1.21596
16011.7512.5799-0.829885
16118.4515.93292.51714
16215.914.99440.905641
16317.116.31280.787197
16416.110.46425.63578
16519.916.89073.00926
16610.958.836422.11358
16718.4518.8936-0.443579
16815.112.59122.50877
1691515.302-0.301955
17011.3513.0246-1.6746
17115.9516.5572-0.607228
17218.114.04634.0537
17314.615.5501-0.950149
17415.414.72270.677328
17515.414.72270.677328
17617.614.40533.19467
17713.3514.3152-0.965234
17819.116.84062.25938
17915.3515.6875-0.337468
1807.69.92381-2.32381
18113.413.7779-0.377868
18213.915.1733-1.2733
18319.117.29731.80271
18415.2515.08530.164693
18512.915.9277-3.02769
18616.114.43151.66848
18717.3513.33244.01756
18813.1514.2923-1.14228
18912.1512.4462-0.296227
19012.610.42522.17477
19110.359.715270.634733
19215.415.4962-0.0961583
1939.611.6042-2.00419
19418.215.55432.64571
19513.611.92811.67188
19614.8512.9661.88405
19714.7517.6518-2.90179
19814.112.98071.11929
19914.912.33692.56308
20016.2514.19942.05062
20119.2516.48392.76608
20213.611.98961.61042
20313.615.6764-2.07637
20415.6515.58140.068599
20512.7515.8696-3.11963
20614.611.24923.35081
2079.8510.8361-0.986145
20812.658.495464.15454
20919.219.4739-0.273932
21016.615.09181.50819
21111.29.223431.97657
21215.2516.0657-0.81575
21311.915.8048-3.90475
21413.213.378-0.178014
21516.3517.4831-1.13315
21612.414.8073-2.40725
21715.8514.0591.79102
21818.1516.69881.45124
21911.1510.7680.381966
22015.6516.0985-0.448472
22117.7516.83630.913696
2227.6511.3016-3.65159
22312.3513.4466-1.09658
22415.614.85520.744808
22519.315.91323.38676
22615.211.43993.7601
22717.115.6791.42098
22815.611.91123.68882
22918.416.21082.18918
23019.0517.64171.40831
23118.5515.94982.60023
23219.118.25320.846805
23313.111.4871.61304
23412.8514.9172-2.06723
2359.511.8288-2.32883
2364.510.0406-5.54058
23711.859.399762.45024
23813.616.3436-2.74363
23911.712.3592-0.659227
24012.412.11440.28564
24113.3514.9942-1.64425
24211.413.7529-2.35293
24314.913.95220.947772
24419.916.89073.00926
24511.211.13050.0695294
24614.614.9921-0.392082
24717.617.32680.273176
24814.0514.6819-0.631917
24916.117.2965-1.19645
25013.3515.105-1.75497
25111.8514.3377-2.48773
25211.9512.649-0.69899
25314.7513.39741.35263
25415.1513.59111.55885
25513.215.1351-1.93508
25616.8515.45011.39992
2577.8511.1001-3.2501
2587.712.5499-4.84989
25912.612.9582-0.35819
2607.8513.2365-5.38652
26110.958.836422.11358
26212.3511.78240.567627
2639.9510.8823-0.932286
26414.913.95220.947772
26516.6515.91630.733743
26613.413.4834-0.0833782
26713.9512.3271.62305
26815.714.54171.15831
26916.8513.58233.26771
27010.959.049121.90088
27115.3512.83922.51084
27212.210.84341.35665
27315.112.83452.26554
27417.7515.59272.15735
27515.215.7142-0.514156
27614.613.67410.92588
27716.6515.02711.6229
2788.17.726010.373985






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.9225810.1548380.0774188
120.8622440.2755110.137756
130.8690040.2619920.130996
140.8041250.391750.195875
150.7449230.5101530.255077
160.6598290.6803420.340171
170.6679210.6641590.332079
180.5839120.8321750.416088
190.5242940.9514130.475706
200.5139660.9720670.486034
210.7101570.5796860.289843
220.7088520.5822960.291148
230.6408210.7183570.359179
240.5732340.8535320.426766
250.5009110.9981780.499089
260.4341820.8683640.565818
270.3776630.7553260.622337
280.3213660.6427330.678634
290.2667970.5335930.733203
300.2275130.4550270.772487
310.2282660.4565320.771734
320.2179990.4359980.782001
330.1764560.3529120.823544
340.1713620.3427240.828638
350.1369420.2738840.863058
360.113830.227660.88617
370.08769970.1753990.9123
380.08602850.1720570.913972
390.09582950.1916590.90417
400.07637740.1527550.923623
410.2697940.5395880.730206
420.2298440.4596880.770156
430.198460.3969190.80154
440.1641540.3283080.835846
450.1349390.2698780.865061
460.1101460.2202910.889854
470.08805210.1761040.911948
480.1781060.3562130.821894
490.1917740.3835470.808226
500.1866840.3733680.813316
510.1573690.3147380.842631
520.214630.429260.78537
530.1824510.3649030.817549
540.222170.4443390.77783
550.2547760.5095530.745224
560.2205280.4410560.779472
570.2984490.5968980.701551
580.429510.859020.57049
590.3920210.7840430.607979
600.406490.8129810.59351
610.3827920.7655840.617208
620.3729050.745810.627095
630.4648920.9297830.535108
640.5420420.9159150.457958
650.504280.9914410.49572
660.4683410.9366830.531659
670.4455370.8910750.554463
680.4112940.8225880.588706
690.4211180.8422360.578882
700.4009130.8018250.599087
710.3693780.7387570.630622
720.3363510.6727010.663649
730.303320.6066410.69668
740.3045760.6091520.695424
750.2998020.5996040.700198
760.2802820.5605630.719718
770.2856890.5713790.714311
780.2701980.5403960.729802
790.2554670.5109330.744533
800.302240.6044810.69776
810.2755070.5510130.724493
820.307260.6145210.69274
830.2777280.5554570.722272
840.4172780.8345550.582722
850.3951250.790250.604875
860.3624720.7249450.637528
870.3273690.6547370.672631
880.2984090.5968180.701591
890.2930810.5861620.706919
900.343310.686620.65669
910.3402190.6804370.659781
920.4038570.8077140.596143
930.368370.7367390.63163
940.3443680.6887360.655632
950.4127590.8255170.587241
960.3779380.7558760.622062
970.4076080.8152160.592392
980.3787820.7575640.621218
990.4506510.9013020.549349
1000.5697260.8605480.430274
1010.5419240.9161520.458076
1020.5074180.9851640.492582
1030.4930450.9860890.506955
1040.489250.97850.51075
1050.4978550.995710.502145
1060.4963530.9927060.503647
1070.4901880.9803760.509812
1080.6565970.6868050.343403
1090.7013230.5973540.298677
1100.7067160.5865680.293284
1110.6817460.6365070.318254
1120.6580110.6839780.341989
1130.7142320.5715360.285768
1140.6941760.6116470.305824
1150.7461310.5077390.253869
1160.7284930.5430130.271507
1170.7009210.5981580.299079
1180.7156990.5686010.284301
1190.6973480.6053040.302652
1200.6987330.6025340.301267
1210.7261590.5476820.273841
1220.7348890.5302220.265111
1230.7084410.5831180.291559
1240.8781630.2436750.121837
1250.9038770.1922450.0961227
1260.8946720.2106570.105328
1270.8781620.2436760.121838
1280.8680020.2639960.131998
1290.8583750.283250.141625
1300.8406840.3186330.159316
1310.8217640.3564710.178236
1320.8189830.3620340.181017
1330.8005520.3988960.199448
1340.7778050.444390.222195
1350.7593460.4813080.240654
1360.7376370.5247270.262363
1370.7696570.4606860.230343
1380.7562430.4875140.243757
1390.7282720.5434570.271728
1400.7024320.5951360.297568
1410.6738250.6523490.326175
1420.6847890.6304220.315211
1430.6705520.6588970.329448
1440.6412410.7175190.358759
1450.6090530.7818950.390947
1460.5758870.8482260.424113
1470.5427280.9145450.457272
1480.5084540.9830920.491546
1490.5400190.9199630.459981
1500.5217150.956570.478285
1510.8133960.3732070.186604
1520.793890.412220.20611
1530.7813040.4373910.218696
1540.7544620.4910770.245538
1550.7724740.4550510.227526
1560.7510580.4978840.248942
1570.7233980.5532050.276602
1580.7026130.5947740.297387
1590.6842980.6314040.315702
1600.6623990.6752020.337601
1610.663440.673120.33656
1620.6471270.7057460.352873
1630.6157630.7684750.384237
1640.8389860.3220290.161014
1650.8384420.3231170.161558
1660.8379460.3241080.162054
1670.8152680.3694650.184732
1680.8296050.340790.170395
1690.8056810.3886380.194319
1700.8024980.3950040.197502
1710.7764230.4471540.223577
1720.8217910.3564180.178209
1730.8065650.386870.193435
1740.7811650.437670.218835
1750.7541660.4916680.245834
1760.7769820.4460370.223018
1770.761140.4777210.23886
1780.7628210.4743570.237179
1790.7365680.5268630.263432
1800.7460070.5079850.253993
1810.737640.524720.26236
1820.7201340.5597310.279866
1830.7058860.5882290.294114
1840.672950.65410.32705
1850.7019690.5960620.298031
1860.6817330.6365330.318267
1870.7654870.4690250.234513
1880.7483350.503330.251665
1890.7191490.5617010.280851
1900.7071210.5857590.292879
1910.6768520.6462960.323148
1920.6438650.7122690.356135
1930.6341330.7317340.365867
1940.6494060.7011880.350594
1950.6304560.7390880.369544
1960.6261810.7476380.373819
1970.6460830.7078340.353917
1980.614680.7706410.38532
1990.6182750.763450.381725
2000.604860.7902790.39514
2010.5812650.837470.418735
2020.5728080.8543830.427192
2030.5630650.873870.436935
2040.5243430.9513130.475657
2050.5305310.9389380.469469
2060.5925110.8149780.407489
2070.5600430.8799140.439957
2080.6409690.7180610.359031
2090.6016130.7967740.398387
2100.5762620.8474760.423738
2110.5599870.8800270.440013
2120.5282160.9435670.471784
2130.629060.7418810.37094
2140.5910590.8178820.408941
2150.573350.8532990.42665
2160.574280.851440.42572
2170.5651530.8696940.434847
2180.5275230.9449550.472477
2190.4848850.9697690.515115
2200.4506210.9012420.549379
2210.4169780.8339550.583022
2220.5039620.9920760.496038
2230.464630.9292610.53537
2240.4568520.9137040.543148
2250.5123820.9752350.487618
2260.543350.9132990.45665
2270.5859880.8280240.414012
2280.6304830.7390340.369517
2290.5938380.8123250.406162
2300.5785430.8429130.421457
2310.613310.7733810.38669
2320.5658340.8683330.434166
2330.5445360.9109280.455464
2340.5132950.9734110.486705
2350.5116990.9766010.488301
2360.8275630.3448730.172437
2370.8189640.3620710.181036
2380.8167620.3664760.183238
2390.7792350.441530.220765
2400.7377160.5245680.262284
2410.7099350.5801290.290065
2420.7323270.5353450.267673
2430.6933040.6133930.306696
2440.6931530.6136950.306847
2450.638650.72270.36135
2460.5829380.8341230.417062
2470.5229530.9540930.477047
2480.4662550.932510.533745
2490.4047970.8095930.595203
2500.3478120.6956230.652188
2510.3205980.6411970.679402
2520.2822730.5645450.717727
2530.2293090.4586180.770691
2540.18180.36360.8182
2550.1606930.3213870.839307
2560.1508070.3016140.849193
2570.2182520.4365040.781748
2580.7305540.5388920.269446
2590.7608790.4782430.239121
2600.9766240.04675190.023376
2610.990030.019940.00996999
2620.987290.02542040.0127102
2630.9949410.01011850.00505926
2640.9861460.02770760.0138538
2650.9638560.0722880.036144
2660.9184390.1631210.0815606
2670.9669620.06607680.0330384

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.922581 & 0.154838 & 0.0774188 \tabularnewline
12 & 0.862244 & 0.275511 & 0.137756 \tabularnewline
13 & 0.869004 & 0.261992 & 0.130996 \tabularnewline
14 & 0.804125 & 0.39175 & 0.195875 \tabularnewline
15 & 0.744923 & 0.510153 & 0.255077 \tabularnewline
16 & 0.659829 & 0.680342 & 0.340171 \tabularnewline
17 & 0.667921 & 0.664159 & 0.332079 \tabularnewline
18 & 0.583912 & 0.832175 & 0.416088 \tabularnewline
19 & 0.524294 & 0.951413 & 0.475706 \tabularnewline
20 & 0.513966 & 0.972067 & 0.486034 \tabularnewline
21 & 0.710157 & 0.579686 & 0.289843 \tabularnewline
22 & 0.708852 & 0.582296 & 0.291148 \tabularnewline
23 & 0.640821 & 0.718357 & 0.359179 \tabularnewline
24 & 0.573234 & 0.853532 & 0.426766 \tabularnewline
25 & 0.500911 & 0.998178 & 0.499089 \tabularnewline
26 & 0.434182 & 0.868364 & 0.565818 \tabularnewline
27 & 0.377663 & 0.755326 & 0.622337 \tabularnewline
28 & 0.321366 & 0.642733 & 0.678634 \tabularnewline
29 & 0.266797 & 0.533593 & 0.733203 \tabularnewline
30 & 0.227513 & 0.455027 & 0.772487 \tabularnewline
31 & 0.228266 & 0.456532 & 0.771734 \tabularnewline
32 & 0.217999 & 0.435998 & 0.782001 \tabularnewline
33 & 0.176456 & 0.352912 & 0.823544 \tabularnewline
34 & 0.171362 & 0.342724 & 0.828638 \tabularnewline
35 & 0.136942 & 0.273884 & 0.863058 \tabularnewline
36 & 0.11383 & 0.22766 & 0.88617 \tabularnewline
37 & 0.0876997 & 0.175399 & 0.9123 \tabularnewline
38 & 0.0860285 & 0.172057 & 0.913972 \tabularnewline
39 & 0.0958295 & 0.191659 & 0.90417 \tabularnewline
40 & 0.0763774 & 0.152755 & 0.923623 \tabularnewline
41 & 0.269794 & 0.539588 & 0.730206 \tabularnewline
42 & 0.229844 & 0.459688 & 0.770156 \tabularnewline
43 & 0.19846 & 0.396919 & 0.80154 \tabularnewline
44 & 0.164154 & 0.328308 & 0.835846 \tabularnewline
45 & 0.134939 & 0.269878 & 0.865061 \tabularnewline
46 & 0.110146 & 0.220291 & 0.889854 \tabularnewline
47 & 0.0880521 & 0.176104 & 0.911948 \tabularnewline
48 & 0.178106 & 0.356213 & 0.821894 \tabularnewline
49 & 0.191774 & 0.383547 & 0.808226 \tabularnewline
50 & 0.186684 & 0.373368 & 0.813316 \tabularnewline
51 & 0.157369 & 0.314738 & 0.842631 \tabularnewline
52 & 0.21463 & 0.42926 & 0.78537 \tabularnewline
53 & 0.182451 & 0.364903 & 0.817549 \tabularnewline
54 & 0.22217 & 0.444339 & 0.77783 \tabularnewline
55 & 0.254776 & 0.509553 & 0.745224 \tabularnewline
56 & 0.220528 & 0.441056 & 0.779472 \tabularnewline
57 & 0.298449 & 0.596898 & 0.701551 \tabularnewline
58 & 0.42951 & 0.85902 & 0.57049 \tabularnewline
59 & 0.392021 & 0.784043 & 0.607979 \tabularnewline
60 & 0.40649 & 0.812981 & 0.59351 \tabularnewline
61 & 0.382792 & 0.765584 & 0.617208 \tabularnewline
62 & 0.372905 & 0.74581 & 0.627095 \tabularnewline
63 & 0.464892 & 0.929783 & 0.535108 \tabularnewline
64 & 0.542042 & 0.915915 & 0.457958 \tabularnewline
65 & 0.50428 & 0.991441 & 0.49572 \tabularnewline
66 & 0.468341 & 0.936683 & 0.531659 \tabularnewline
67 & 0.445537 & 0.891075 & 0.554463 \tabularnewline
68 & 0.411294 & 0.822588 & 0.588706 \tabularnewline
69 & 0.421118 & 0.842236 & 0.578882 \tabularnewline
70 & 0.400913 & 0.801825 & 0.599087 \tabularnewline
71 & 0.369378 & 0.738757 & 0.630622 \tabularnewline
72 & 0.336351 & 0.672701 & 0.663649 \tabularnewline
73 & 0.30332 & 0.606641 & 0.69668 \tabularnewline
74 & 0.304576 & 0.609152 & 0.695424 \tabularnewline
75 & 0.299802 & 0.599604 & 0.700198 \tabularnewline
76 & 0.280282 & 0.560563 & 0.719718 \tabularnewline
77 & 0.285689 & 0.571379 & 0.714311 \tabularnewline
78 & 0.270198 & 0.540396 & 0.729802 \tabularnewline
79 & 0.255467 & 0.510933 & 0.744533 \tabularnewline
80 & 0.30224 & 0.604481 & 0.69776 \tabularnewline
81 & 0.275507 & 0.551013 & 0.724493 \tabularnewline
82 & 0.30726 & 0.614521 & 0.69274 \tabularnewline
83 & 0.277728 & 0.555457 & 0.722272 \tabularnewline
84 & 0.417278 & 0.834555 & 0.582722 \tabularnewline
85 & 0.395125 & 0.79025 & 0.604875 \tabularnewline
86 & 0.362472 & 0.724945 & 0.637528 \tabularnewline
87 & 0.327369 & 0.654737 & 0.672631 \tabularnewline
88 & 0.298409 & 0.596818 & 0.701591 \tabularnewline
89 & 0.293081 & 0.586162 & 0.706919 \tabularnewline
90 & 0.34331 & 0.68662 & 0.65669 \tabularnewline
91 & 0.340219 & 0.680437 & 0.659781 \tabularnewline
92 & 0.403857 & 0.807714 & 0.596143 \tabularnewline
93 & 0.36837 & 0.736739 & 0.63163 \tabularnewline
94 & 0.344368 & 0.688736 & 0.655632 \tabularnewline
95 & 0.412759 & 0.825517 & 0.587241 \tabularnewline
96 & 0.377938 & 0.755876 & 0.622062 \tabularnewline
97 & 0.407608 & 0.815216 & 0.592392 \tabularnewline
98 & 0.378782 & 0.757564 & 0.621218 \tabularnewline
99 & 0.450651 & 0.901302 & 0.549349 \tabularnewline
100 & 0.569726 & 0.860548 & 0.430274 \tabularnewline
101 & 0.541924 & 0.916152 & 0.458076 \tabularnewline
102 & 0.507418 & 0.985164 & 0.492582 \tabularnewline
103 & 0.493045 & 0.986089 & 0.506955 \tabularnewline
104 & 0.48925 & 0.9785 & 0.51075 \tabularnewline
105 & 0.497855 & 0.99571 & 0.502145 \tabularnewline
106 & 0.496353 & 0.992706 & 0.503647 \tabularnewline
107 & 0.490188 & 0.980376 & 0.509812 \tabularnewline
108 & 0.656597 & 0.686805 & 0.343403 \tabularnewline
109 & 0.701323 & 0.597354 & 0.298677 \tabularnewline
110 & 0.706716 & 0.586568 & 0.293284 \tabularnewline
111 & 0.681746 & 0.636507 & 0.318254 \tabularnewline
112 & 0.658011 & 0.683978 & 0.341989 \tabularnewline
113 & 0.714232 & 0.571536 & 0.285768 \tabularnewline
114 & 0.694176 & 0.611647 & 0.305824 \tabularnewline
115 & 0.746131 & 0.507739 & 0.253869 \tabularnewline
116 & 0.728493 & 0.543013 & 0.271507 \tabularnewline
117 & 0.700921 & 0.598158 & 0.299079 \tabularnewline
118 & 0.715699 & 0.568601 & 0.284301 \tabularnewline
119 & 0.697348 & 0.605304 & 0.302652 \tabularnewline
120 & 0.698733 & 0.602534 & 0.301267 \tabularnewline
121 & 0.726159 & 0.547682 & 0.273841 \tabularnewline
122 & 0.734889 & 0.530222 & 0.265111 \tabularnewline
123 & 0.708441 & 0.583118 & 0.291559 \tabularnewline
124 & 0.878163 & 0.243675 & 0.121837 \tabularnewline
125 & 0.903877 & 0.192245 & 0.0961227 \tabularnewline
126 & 0.894672 & 0.210657 & 0.105328 \tabularnewline
127 & 0.878162 & 0.243676 & 0.121838 \tabularnewline
128 & 0.868002 & 0.263996 & 0.131998 \tabularnewline
129 & 0.858375 & 0.28325 & 0.141625 \tabularnewline
130 & 0.840684 & 0.318633 & 0.159316 \tabularnewline
131 & 0.821764 & 0.356471 & 0.178236 \tabularnewline
132 & 0.818983 & 0.362034 & 0.181017 \tabularnewline
133 & 0.800552 & 0.398896 & 0.199448 \tabularnewline
134 & 0.777805 & 0.44439 & 0.222195 \tabularnewline
135 & 0.759346 & 0.481308 & 0.240654 \tabularnewline
136 & 0.737637 & 0.524727 & 0.262363 \tabularnewline
137 & 0.769657 & 0.460686 & 0.230343 \tabularnewline
138 & 0.756243 & 0.487514 & 0.243757 \tabularnewline
139 & 0.728272 & 0.543457 & 0.271728 \tabularnewline
140 & 0.702432 & 0.595136 & 0.297568 \tabularnewline
141 & 0.673825 & 0.652349 & 0.326175 \tabularnewline
142 & 0.684789 & 0.630422 & 0.315211 \tabularnewline
143 & 0.670552 & 0.658897 & 0.329448 \tabularnewline
144 & 0.641241 & 0.717519 & 0.358759 \tabularnewline
145 & 0.609053 & 0.781895 & 0.390947 \tabularnewline
146 & 0.575887 & 0.848226 & 0.424113 \tabularnewline
147 & 0.542728 & 0.914545 & 0.457272 \tabularnewline
148 & 0.508454 & 0.983092 & 0.491546 \tabularnewline
149 & 0.540019 & 0.919963 & 0.459981 \tabularnewline
150 & 0.521715 & 0.95657 & 0.478285 \tabularnewline
151 & 0.813396 & 0.373207 & 0.186604 \tabularnewline
152 & 0.79389 & 0.41222 & 0.20611 \tabularnewline
153 & 0.781304 & 0.437391 & 0.218696 \tabularnewline
154 & 0.754462 & 0.491077 & 0.245538 \tabularnewline
155 & 0.772474 & 0.455051 & 0.227526 \tabularnewline
156 & 0.751058 & 0.497884 & 0.248942 \tabularnewline
157 & 0.723398 & 0.553205 & 0.276602 \tabularnewline
158 & 0.702613 & 0.594774 & 0.297387 \tabularnewline
159 & 0.684298 & 0.631404 & 0.315702 \tabularnewline
160 & 0.662399 & 0.675202 & 0.337601 \tabularnewline
161 & 0.66344 & 0.67312 & 0.33656 \tabularnewline
162 & 0.647127 & 0.705746 & 0.352873 \tabularnewline
163 & 0.615763 & 0.768475 & 0.384237 \tabularnewline
164 & 0.838986 & 0.322029 & 0.161014 \tabularnewline
165 & 0.838442 & 0.323117 & 0.161558 \tabularnewline
166 & 0.837946 & 0.324108 & 0.162054 \tabularnewline
167 & 0.815268 & 0.369465 & 0.184732 \tabularnewline
168 & 0.829605 & 0.34079 & 0.170395 \tabularnewline
169 & 0.805681 & 0.388638 & 0.194319 \tabularnewline
170 & 0.802498 & 0.395004 & 0.197502 \tabularnewline
171 & 0.776423 & 0.447154 & 0.223577 \tabularnewline
172 & 0.821791 & 0.356418 & 0.178209 \tabularnewline
173 & 0.806565 & 0.38687 & 0.193435 \tabularnewline
174 & 0.781165 & 0.43767 & 0.218835 \tabularnewline
175 & 0.754166 & 0.491668 & 0.245834 \tabularnewline
176 & 0.776982 & 0.446037 & 0.223018 \tabularnewline
177 & 0.76114 & 0.477721 & 0.23886 \tabularnewline
178 & 0.762821 & 0.474357 & 0.237179 \tabularnewline
179 & 0.736568 & 0.526863 & 0.263432 \tabularnewline
180 & 0.746007 & 0.507985 & 0.253993 \tabularnewline
181 & 0.73764 & 0.52472 & 0.26236 \tabularnewline
182 & 0.720134 & 0.559731 & 0.279866 \tabularnewline
183 & 0.705886 & 0.588229 & 0.294114 \tabularnewline
184 & 0.67295 & 0.6541 & 0.32705 \tabularnewline
185 & 0.701969 & 0.596062 & 0.298031 \tabularnewline
186 & 0.681733 & 0.636533 & 0.318267 \tabularnewline
187 & 0.765487 & 0.469025 & 0.234513 \tabularnewline
188 & 0.748335 & 0.50333 & 0.251665 \tabularnewline
189 & 0.719149 & 0.561701 & 0.280851 \tabularnewline
190 & 0.707121 & 0.585759 & 0.292879 \tabularnewline
191 & 0.676852 & 0.646296 & 0.323148 \tabularnewline
192 & 0.643865 & 0.712269 & 0.356135 \tabularnewline
193 & 0.634133 & 0.731734 & 0.365867 \tabularnewline
194 & 0.649406 & 0.701188 & 0.350594 \tabularnewline
195 & 0.630456 & 0.739088 & 0.369544 \tabularnewline
196 & 0.626181 & 0.747638 & 0.373819 \tabularnewline
197 & 0.646083 & 0.707834 & 0.353917 \tabularnewline
198 & 0.61468 & 0.770641 & 0.38532 \tabularnewline
199 & 0.618275 & 0.76345 & 0.381725 \tabularnewline
200 & 0.60486 & 0.790279 & 0.39514 \tabularnewline
201 & 0.581265 & 0.83747 & 0.418735 \tabularnewline
202 & 0.572808 & 0.854383 & 0.427192 \tabularnewline
203 & 0.563065 & 0.87387 & 0.436935 \tabularnewline
204 & 0.524343 & 0.951313 & 0.475657 \tabularnewline
205 & 0.530531 & 0.938938 & 0.469469 \tabularnewline
206 & 0.592511 & 0.814978 & 0.407489 \tabularnewline
207 & 0.560043 & 0.879914 & 0.439957 \tabularnewline
208 & 0.640969 & 0.718061 & 0.359031 \tabularnewline
209 & 0.601613 & 0.796774 & 0.398387 \tabularnewline
210 & 0.576262 & 0.847476 & 0.423738 \tabularnewline
211 & 0.559987 & 0.880027 & 0.440013 \tabularnewline
212 & 0.528216 & 0.943567 & 0.471784 \tabularnewline
213 & 0.62906 & 0.741881 & 0.37094 \tabularnewline
214 & 0.591059 & 0.817882 & 0.408941 \tabularnewline
215 & 0.57335 & 0.853299 & 0.42665 \tabularnewline
216 & 0.57428 & 0.85144 & 0.42572 \tabularnewline
217 & 0.565153 & 0.869694 & 0.434847 \tabularnewline
218 & 0.527523 & 0.944955 & 0.472477 \tabularnewline
219 & 0.484885 & 0.969769 & 0.515115 \tabularnewline
220 & 0.450621 & 0.901242 & 0.549379 \tabularnewline
221 & 0.416978 & 0.833955 & 0.583022 \tabularnewline
222 & 0.503962 & 0.992076 & 0.496038 \tabularnewline
223 & 0.46463 & 0.929261 & 0.53537 \tabularnewline
224 & 0.456852 & 0.913704 & 0.543148 \tabularnewline
225 & 0.512382 & 0.975235 & 0.487618 \tabularnewline
226 & 0.54335 & 0.913299 & 0.45665 \tabularnewline
227 & 0.585988 & 0.828024 & 0.414012 \tabularnewline
228 & 0.630483 & 0.739034 & 0.369517 \tabularnewline
229 & 0.593838 & 0.812325 & 0.406162 \tabularnewline
230 & 0.578543 & 0.842913 & 0.421457 \tabularnewline
231 & 0.61331 & 0.773381 & 0.38669 \tabularnewline
232 & 0.565834 & 0.868333 & 0.434166 \tabularnewline
233 & 0.544536 & 0.910928 & 0.455464 \tabularnewline
234 & 0.513295 & 0.973411 & 0.486705 \tabularnewline
235 & 0.511699 & 0.976601 & 0.488301 \tabularnewline
236 & 0.827563 & 0.344873 & 0.172437 \tabularnewline
237 & 0.818964 & 0.362071 & 0.181036 \tabularnewline
238 & 0.816762 & 0.366476 & 0.183238 \tabularnewline
239 & 0.779235 & 0.44153 & 0.220765 \tabularnewline
240 & 0.737716 & 0.524568 & 0.262284 \tabularnewline
241 & 0.709935 & 0.580129 & 0.290065 \tabularnewline
242 & 0.732327 & 0.535345 & 0.267673 \tabularnewline
243 & 0.693304 & 0.613393 & 0.306696 \tabularnewline
244 & 0.693153 & 0.613695 & 0.306847 \tabularnewline
245 & 0.63865 & 0.7227 & 0.36135 \tabularnewline
246 & 0.582938 & 0.834123 & 0.417062 \tabularnewline
247 & 0.522953 & 0.954093 & 0.477047 \tabularnewline
248 & 0.466255 & 0.93251 & 0.533745 \tabularnewline
249 & 0.404797 & 0.809593 & 0.595203 \tabularnewline
250 & 0.347812 & 0.695623 & 0.652188 \tabularnewline
251 & 0.320598 & 0.641197 & 0.679402 \tabularnewline
252 & 0.282273 & 0.564545 & 0.717727 \tabularnewline
253 & 0.229309 & 0.458618 & 0.770691 \tabularnewline
254 & 0.1818 & 0.3636 & 0.8182 \tabularnewline
255 & 0.160693 & 0.321387 & 0.839307 \tabularnewline
256 & 0.150807 & 0.301614 & 0.849193 \tabularnewline
257 & 0.218252 & 0.436504 & 0.781748 \tabularnewline
258 & 0.730554 & 0.538892 & 0.269446 \tabularnewline
259 & 0.760879 & 0.478243 & 0.239121 \tabularnewline
260 & 0.976624 & 0.0467519 & 0.023376 \tabularnewline
261 & 0.99003 & 0.01994 & 0.00996999 \tabularnewline
262 & 0.98729 & 0.0254204 & 0.0127102 \tabularnewline
263 & 0.994941 & 0.0101185 & 0.00505926 \tabularnewline
264 & 0.986146 & 0.0277076 & 0.0138538 \tabularnewline
265 & 0.963856 & 0.072288 & 0.036144 \tabularnewline
266 & 0.918439 & 0.163121 & 0.0815606 \tabularnewline
267 & 0.966962 & 0.0660768 & 0.0330384 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&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]11[/C][C]0.922581[/C][C]0.154838[/C][C]0.0774188[/C][/ROW]
[ROW][C]12[/C][C]0.862244[/C][C]0.275511[/C][C]0.137756[/C][/ROW]
[ROW][C]13[/C][C]0.869004[/C][C]0.261992[/C][C]0.130996[/C][/ROW]
[ROW][C]14[/C][C]0.804125[/C][C]0.39175[/C][C]0.195875[/C][/ROW]
[ROW][C]15[/C][C]0.744923[/C][C]0.510153[/C][C]0.255077[/C][/ROW]
[ROW][C]16[/C][C]0.659829[/C][C]0.680342[/C][C]0.340171[/C][/ROW]
[ROW][C]17[/C][C]0.667921[/C][C]0.664159[/C][C]0.332079[/C][/ROW]
[ROW][C]18[/C][C]0.583912[/C][C]0.832175[/C][C]0.416088[/C][/ROW]
[ROW][C]19[/C][C]0.524294[/C][C]0.951413[/C][C]0.475706[/C][/ROW]
[ROW][C]20[/C][C]0.513966[/C][C]0.972067[/C][C]0.486034[/C][/ROW]
[ROW][C]21[/C][C]0.710157[/C][C]0.579686[/C][C]0.289843[/C][/ROW]
[ROW][C]22[/C][C]0.708852[/C][C]0.582296[/C][C]0.291148[/C][/ROW]
[ROW][C]23[/C][C]0.640821[/C][C]0.718357[/C][C]0.359179[/C][/ROW]
[ROW][C]24[/C][C]0.573234[/C][C]0.853532[/C][C]0.426766[/C][/ROW]
[ROW][C]25[/C][C]0.500911[/C][C]0.998178[/C][C]0.499089[/C][/ROW]
[ROW][C]26[/C][C]0.434182[/C][C]0.868364[/C][C]0.565818[/C][/ROW]
[ROW][C]27[/C][C]0.377663[/C][C]0.755326[/C][C]0.622337[/C][/ROW]
[ROW][C]28[/C][C]0.321366[/C][C]0.642733[/C][C]0.678634[/C][/ROW]
[ROW][C]29[/C][C]0.266797[/C][C]0.533593[/C][C]0.733203[/C][/ROW]
[ROW][C]30[/C][C]0.227513[/C][C]0.455027[/C][C]0.772487[/C][/ROW]
[ROW][C]31[/C][C]0.228266[/C][C]0.456532[/C][C]0.771734[/C][/ROW]
[ROW][C]32[/C][C]0.217999[/C][C]0.435998[/C][C]0.782001[/C][/ROW]
[ROW][C]33[/C][C]0.176456[/C][C]0.352912[/C][C]0.823544[/C][/ROW]
[ROW][C]34[/C][C]0.171362[/C][C]0.342724[/C][C]0.828638[/C][/ROW]
[ROW][C]35[/C][C]0.136942[/C][C]0.273884[/C][C]0.863058[/C][/ROW]
[ROW][C]36[/C][C]0.11383[/C][C]0.22766[/C][C]0.88617[/C][/ROW]
[ROW][C]37[/C][C]0.0876997[/C][C]0.175399[/C][C]0.9123[/C][/ROW]
[ROW][C]38[/C][C]0.0860285[/C][C]0.172057[/C][C]0.913972[/C][/ROW]
[ROW][C]39[/C][C]0.0958295[/C][C]0.191659[/C][C]0.90417[/C][/ROW]
[ROW][C]40[/C][C]0.0763774[/C][C]0.152755[/C][C]0.923623[/C][/ROW]
[ROW][C]41[/C][C]0.269794[/C][C]0.539588[/C][C]0.730206[/C][/ROW]
[ROW][C]42[/C][C]0.229844[/C][C]0.459688[/C][C]0.770156[/C][/ROW]
[ROW][C]43[/C][C]0.19846[/C][C]0.396919[/C][C]0.80154[/C][/ROW]
[ROW][C]44[/C][C]0.164154[/C][C]0.328308[/C][C]0.835846[/C][/ROW]
[ROW][C]45[/C][C]0.134939[/C][C]0.269878[/C][C]0.865061[/C][/ROW]
[ROW][C]46[/C][C]0.110146[/C][C]0.220291[/C][C]0.889854[/C][/ROW]
[ROW][C]47[/C][C]0.0880521[/C][C]0.176104[/C][C]0.911948[/C][/ROW]
[ROW][C]48[/C][C]0.178106[/C][C]0.356213[/C][C]0.821894[/C][/ROW]
[ROW][C]49[/C][C]0.191774[/C][C]0.383547[/C][C]0.808226[/C][/ROW]
[ROW][C]50[/C][C]0.186684[/C][C]0.373368[/C][C]0.813316[/C][/ROW]
[ROW][C]51[/C][C]0.157369[/C][C]0.314738[/C][C]0.842631[/C][/ROW]
[ROW][C]52[/C][C]0.21463[/C][C]0.42926[/C][C]0.78537[/C][/ROW]
[ROW][C]53[/C][C]0.182451[/C][C]0.364903[/C][C]0.817549[/C][/ROW]
[ROW][C]54[/C][C]0.22217[/C][C]0.444339[/C][C]0.77783[/C][/ROW]
[ROW][C]55[/C][C]0.254776[/C][C]0.509553[/C][C]0.745224[/C][/ROW]
[ROW][C]56[/C][C]0.220528[/C][C]0.441056[/C][C]0.779472[/C][/ROW]
[ROW][C]57[/C][C]0.298449[/C][C]0.596898[/C][C]0.701551[/C][/ROW]
[ROW][C]58[/C][C]0.42951[/C][C]0.85902[/C][C]0.57049[/C][/ROW]
[ROW][C]59[/C][C]0.392021[/C][C]0.784043[/C][C]0.607979[/C][/ROW]
[ROW][C]60[/C][C]0.40649[/C][C]0.812981[/C][C]0.59351[/C][/ROW]
[ROW][C]61[/C][C]0.382792[/C][C]0.765584[/C][C]0.617208[/C][/ROW]
[ROW][C]62[/C][C]0.372905[/C][C]0.74581[/C][C]0.627095[/C][/ROW]
[ROW][C]63[/C][C]0.464892[/C][C]0.929783[/C][C]0.535108[/C][/ROW]
[ROW][C]64[/C][C]0.542042[/C][C]0.915915[/C][C]0.457958[/C][/ROW]
[ROW][C]65[/C][C]0.50428[/C][C]0.991441[/C][C]0.49572[/C][/ROW]
[ROW][C]66[/C][C]0.468341[/C][C]0.936683[/C][C]0.531659[/C][/ROW]
[ROW][C]67[/C][C]0.445537[/C][C]0.891075[/C][C]0.554463[/C][/ROW]
[ROW][C]68[/C][C]0.411294[/C][C]0.822588[/C][C]0.588706[/C][/ROW]
[ROW][C]69[/C][C]0.421118[/C][C]0.842236[/C][C]0.578882[/C][/ROW]
[ROW][C]70[/C][C]0.400913[/C][C]0.801825[/C][C]0.599087[/C][/ROW]
[ROW][C]71[/C][C]0.369378[/C][C]0.738757[/C][C]0.630622[/C][/ROW]
[ROW][C]72[/C][C]0.336351[/C][C]0.672701[/C][C]0.663649[/C][/ROW]
[ROW][C]73[/C][C]0.30332[/C][C]0.606641[/C][C]0.69668[/C][/ROW]
[ROW][C]74[/C][C]0.304576[/C][C]0.609152[/C][C]0.695424[/C][/ROW]
[ROW][C]75[/C][C]0.299802[/C][C]0.599604[/C][C]0.700198[/C][/ROW]
[ROW][C]76[/C][C]0.280282[/C][C]0.560563[/C][C]0.719718[/C][/ROW]
[ROW][C]77[/C][C]0.285689[/C][C]0.571379[/C][C]0.714311[/C][/ROW]
[ROW][C]78[/C][C]0.270198[/C][C]0.540396[/C][C]0.729802[/C][/ROW]
[ROW][C]79[/C][C]0.255467[/C][C]0.510933[/C][C]0.744533[/C][/ROW]
[ROW][C]80[/C][C]0.30224[/C][C]0.604481[/C][C]0.69776[/C][/ROW]
[ROW][C]81[/C][C]0.275507[/C][C]0.551013[/C][C]0.724493[/C][/ROW]
[ROW][C]82[/C][C]0.30726[/C][C]0.614521[/C][C]0.69274[/C][/ROW]
[ROW][C]83[/C][C]0.277728[/C][C]0.555457[/C][C]0.722272[/C][/ROW]
[ROW][C]84[/C][C]0.417278[/C][C]0.834555[/C][C]0.582722[/C][/ROW]
[ROW][C]85[/C][C]0.395125[/C][C]0.79025[/C][C]0.604875[/C][/ROW]
[ROW][C]86[/C][C]0.362472[/C][C]0.724945[/C][C]0.637528[/C][/ROW]
[ROW][C]87[/C][C]0.327369[/C][C]0.654737[/C][C]0.672631[/C][/ROW]
[ROW][C]88[/C][C]0.298409[/C][C]0.596818[/C][C]0.701591[/C][/ROW]
[ROW][C]89[/C][C]0.293081[/C][C]0.586162[/C][C]0.706919[/C][/ROW]
[ROW][C]90[/C][C]0.34331[/C][C]0.68662[/C][C]0.65669[/C][/ROW]
[ROW][C]91[/C][C]0.340219[/C][C]0.680437[/C][C]0.659781[/C][/ROW]
[ROW][C]92[/C][C]0.403857[/C][C]0.807714[/C][C]0.596143[/C][/ROW]
[ROW][C]93[/C][C]0.36837[/C][C]0.736739[/C][C]0.63163[/C][/ROW]
[ROW][C]94[/C][C]0.344368[/C][C]0.688736[/C][C]0.655632[/C][/ROW]
[ROW][C]95[/C][C]0.412759[/C][C]0.825517[/C][C]0.587241[/C][/ROW]
[ROW][C]96[/C][C]0.377938[/C][C]0.755876[/C][C]0.622062[/C][/ROW]
[ROW][C]97[/C][C]0.407608[/C][C]0.815216[/C][C]0.592392[/C][/ROW]
[ROW][C]98[/C][C]0.378782[/C][C]0.757564[/C][C]0.621218[/C][/ROW]
[ROW][C]99[/C][C]0.450651[/C][C]0.901302[/C][C]0.549349[/C][/ROW]
[ROW][C]100[/C][C]0.569726[/C][C]0.860548[/C][C]0.430274[/C][/ROW]
[ROW][C]101[/C][C]0.541924[/C][C]0.916152[/C][C]0.458076[/C][/ROW]
[ROW][C]102[/C][C]0.507418[/C][C]0.985164[/C][C]0.492582[/C][/ROW]
[ROW][C]103[/C][C]0.493045[/C][C]0.986089[/C][C]0.506955[/C][/ROW]
[ROW][C]104[/C][C]0.48925[/C][C]0.9785[/C][C]0.51075[/C][/ROW]
[ROW][C]105[/C][C]0.497855[/C][C]0.99571[/C][C]0.502145[/C][/ROW]
[ROW][C]106[/C][C]0.496353[/C][C]0.992706[/C][C]0.503647[/C][/ROW]
[ROW][C]107[/C][C]0.490188[/C][C]0.980376[/C][C]0.509812[/C][/ROW]
[ROW][C]108[/C][C]0.656597[/C][C]0.686805[/C][C]0.343403[/C][/ROW]
[ROW][C]109[/C][C]0.701323[/C][C]0.597354[/C][C]0.298677[/C][/ROW]
[ROW][C]110[/C][C]0.706716[/C][C]0.586568[/C][C]0.293284[/C][/ROW]
[ROW][C]111[/C][C]0.681746[/C][C]0.636507[/C][C]0.318254[/C][/ROW]
[ROW][C]112[/C][C]0.658011[/C][C]0.683978[/C][C]0.341989[/C][/ROW]
[ROW][C]113[/C][C]0.714232[/C][C]0.571536[/C][C]0.285768[/C][/ROW]
[ROW][C]114[/C][C]0.694176[/C][C]0.611647[/C][C]0.305824[/C][/ROW]
[ROW][C]115[/C][C]0.746131[/C][C]0.507739[/C][C]0.253869[/C][/ROW]
[ROW][C]116[/C][C]0.728493[/C][C]0.543013[/C][C]0.271507[/C][/ROW]
[ROW][C]117[/C][C]0.700921[/C][C]0.598158[/C][C]0.299079[/C][/ROW]
[ROW][C]118[/C][C]0.715699[/C][C]0.568601[/C][C]0.284301[/C][/ROW]
[ROW][C]119[/C][C]0.697348[/C][C]0.605304[/C][C]0.302652[/C][/ROW]
[ROW][C]120[/C][C]0.698733[/C][C]0.602534[/C][C]0.301267[/C][/ROW]
[ROW][C]121[/C][C]0.726159[/C][C]0.547682[/C][C]0.273841[/C][/ROW]
[ROW][C]122[/C][C]0.734889[/C][C]0.530222[/C][C]0.265111[/C][/ROW]
[ROW][C]123[/C][C]0.708441[/C][C]0.583118[/C][C]0.291559[/C][/ROW]
[ROW][C]124[/C][C]0.878163[/C][C]0.243675[/C][C]0.121837[/C][/ROW]
[ROW][C]125[/C][C]0.903877[/C][C]0.192245[/C][C]0.0961227[/C][/ROW]
[ROW][C]126[/C][C]0.894672[/C][C]0.210657[/C][C]0.105328[/C][/ROW]
[ROW][C]127[/C][C]0.878162[/C][C]0.243676[/C][C]0.121838[/C][/ROW]
[ROW][C]128[/C][C]0.868002[/C][C]0.263996[/C][C]0.131998[/C][/ROW]
[ROW][C]129[/C][C]0.858375[/C][C]0.28325[/C][C]0.141625[/C][/ROW]
[ROW][C]130[/C][C]0.840684[/C][C]0.318633[/C][C]0.159316[/C][/ROW]
[ROW][C]131[/C][C]0.821764[/C][C]0.356471[/C][C]0.178236[/C][/ROW]
[ROW][C]132[/C][C]0.818983[/C][C]0.362034[/C][C]0.181017[/C][/ROW]
[ROW][C]133[/C][C]0.800552[/C][C]0.398896[/C][C]0.199448[/C][/ROW]
[ROW][C]134[/C][C]0.777805[/C][C]0.44439[/C][C]0.222195[/C][/ROW]
[ROW][C]135[/C][C]0.759346[/C][C]0.481308[/C][C]0.240654[/C][/ROW]
[ROW][C]136[/C][C]0.737637[/C][C]0.524727[/C][C]0.262363[/C][/ROW]
[ROW][C]137[/C][C]0.769657[/C][C]0.460686[/C][C]0.230343[/C][/ROW]
[ROW][C]138[/C][C]0.756243[/C][C]0.487514[/C][C]0.243757[/C][/ROW]
[ROW][C]139[/C][C]0.728272[/C][C]0.543457[/C][C]0.271728[/C][/ROW]
[ROW][C]140[/C][C]0.702432[/C][C]0.595136[/C][C]0.297568[/C][/ROW]
[ROW][C]141[/C][C]0.673825[/C][C]0.652349[/C][C]0.326175[/C][/ROW]
[ROW][C]142[/C][C]0.684789[/C][C]0.630422[/C][C]0.315211[/C][/ROW]
[ROW][C]143[/C][C]0.670552[/C][C]0.658897[/C][C]0.329448[/C][/ROW]
[ROW][C]144[/C][C]0.641241[/C][C]0.717519[/C][C]0.358759[/C][/ROW]
[ROW][C]145[/C][C]0.609053[/C][C]0.781895[/C][C]0.390947[/C][/ROW]
[ROW][C]146[/C][C]0.575887[/C][C]0.848226[/C][C]0.424113[/C][/ROW]
[ROW][C]147[/C][C]0.542728[/C][C]0.914545[/C][C]0.457272[/C][/ROW]
[ROW][C]148[/C][C]0.508454[/C][C]0.983092[/C][C]0.491546[/C][/ROW]
[ROW][C]149[/C][C]0.540019[/C][C]0.919963[/C][C]0.459981[/C][/ROW]
[ROW][C]150[/C][C]0.521715[/C][C]0.95657[/C][C]0.478285[/C][/ROW]
[ROW][C]151[/C][C]0.813396[/C][C]0.373207[/C][C]0.186604[/C][/ROW]
[ROW][C]152[/C][C]0.79389[/C][C]0.41222[/C][C]0.20611[/C][/ROW]
[ROW][C]153[/C][C]0.781304[/C][C]0.437391[/C][C]0.218696[/C][/ROW]
[ROW][C]154[/C][C]0.754462[/C][C]0.491077[/C][C]0.245538[/C][/ROW]
[ROW][C]155[/C][C]0.772474[/C][C]0.455051[/C][C]0.227526[/C][/ROW]
[ROW][C]156[/C][C]0.751058[/C][C]0.497884[/C][C]0.248942[/C][/ROW]
[ROW][C]157[/C][C]0.723398[/C][C]0.553205[/C][C]0.276602[/C][/ROW]
[ROW][C]158[/C][C]0.702613[/C][C]0.594774[/C][C]0.297387[/C][/ROW]
[ROW][C]159[/C][C]0.684298[/C][C]0.631404[/C][C]0.315702[/C][/ROW]
[ROW][C]160[/C][C]0.662399[/C][C]0.675202[/C][C]0.337601[/C][/ROW]
[ROW][C]161[/C][C]0.66344[/C][C]0.67312[/C][C]0.33656[/C][/ROW]
[ROW][C]162[/C][C]0.647127[/C][C]0.705746[/C][C]0.352873[/C][/ROW]
[ROW][C]163[/C][C]0.615763[/C][C]0.768475[/C][C]0.384237[/C][/ROW]
[ROW][C]164[/C][C]0.838986[/C][C]0.322029[/C][C]0.161014[/C][/ROW]
[ROW][C]165[/C][C]0.838442[/C][C]0.323117[/C][C]0.161558[/C][/ROW]
[ROW][C]166[/C][C]0.837946[/C][C]0.324108[/C][C]0.162054[/C][/ROW]
[ROW][C]167[/C][C]0.815268[/C][C]0.369465[/C][C]0.184732[/C][/ROW]
[ROW][C]168[/C][C]0.829605[/C][C]0.34079[/C][C]0.170395[/C][/ROW]
[ROW][C]169[/C][C]0.805681[/C][C]0.388638[/C][C]0.194319[/C][/ROW]
[ROW][C]170[/C][C]0.802498[/C][C]0.395004[/C][C]0.197502[/C][/ROW]
[ROW][C]171[/C][C]0.776423[/C][C]0.447154[/C][C]0.223577[/C][/ROW]
[ROW][C]172[/C][C]0.821791[/C][C]0.356418[/C][C]0.178209[/C][/ROW]
[ROW][C]173[/C][C]0.806565[/C][C]0.38687[/C][C]0.193435[/C][/ROW]
[ROW][C]174[/C][C]0.781165[/C][C]0.43767[/C][C]0.218835[/C][/ROW]
[ROW][C]175[/C][C]0.754166[/C][C]0.491668[/C][C]0.245834[/C][/ROW]
[ROW][C]176[/C][C]0.776982[/C][C]0.446037[/C][C]0.223018[/C][/ROW]
[ROW][C]177[/C][C]0.76114[/C][C]0.477721[/C][C]0.23886[/C][/ROW]
[ROW][C]178[/C][C]0.762821[/C][C]0.474357[/C][C]0.237179[/C][/ROW]
[ROW][C]179[/C][C]0.736568[/C][C]0.526863[/C][C]0.263432[/C][/ROW]
[ROW][C]180[/C][C]0.746007[/C][C]0.507985[/C][C]0.253993[/C][/ROW]
[ROW][C]181[/C][C]0.73764[/C][C]0.52472[/C][C]0.26236[/C][/ROW]
[ROW][C]182[/C][C]0.720134[/C][C]0.559731[/C][C]0.279866[/C][/ROW]
[ROW][C]183[/C][C]0.705886[/C][C]0.588229[/C][C]0.294114[/C][/ROW]
[ROW][C]184[/C][C]0.67295[/C][C]0.6541[/C][C]0.32705[/C][/ROW]
[ROW][C]185[/C][C]0.701969[/C][C]0.596062[/C][C]0.298031[/C][/ROW]
[ROW][C]186[/C][C]0.681733[/C][C]0.636533[/C][C]0.318267[/C][/ROW]
[ROW][C]187[/C][C]0.765487[/C][C]0.469025[/C][C]0.234513[/C][/ROW]
[ROW][C]188[/C][C]0.748335[/C][C]0.50333[/C][C]0.251665[/C][/ROW]
[ROW][C]189[/C][C]0.719149[/C][C]0.561701[/C][C]0.280851[/C][/ROW]
[ROW][C]190[/C][C]0.707121[/C][C]0.585759[/C][C]0.292879[/C][/ROW]
[ROW][C]191[/C][C]0.676852[/C][C]0.646296[/C][C]0.323148[/C][/ROW]
[ROW][C]192[/C][C]0.643865[/C][C]0.712269[/C][C]0.356135[/C][/ROW]
[ROW][C]193[/C][C]0.634133[/C][C]0.731734[/C][C]0.365867[/C][/ROW]
[ROW][C]194[/C][C]0.649406[/C][C]0.701188[/C][C]0.350594[/C][/ROW]
[ROW][C]195[/C][C]0.630456[/C][C]0.739088[/C][C]0.369544[/C][/ROW]
[ROW][C]196[/C][C]0.626181[/C][C]0.747638[/C][C]0.373819[/C][/ROW]
[ROW][C]197[/C][C]0.646083[/C][C]0.707834[/C][C]0.353917[/C][/ROW]
[ROW][C]198[/C][C]0.61468[/C][C]0.770641[/C][C]0.38532[/C][/ROW]
[ROW][C]199[/C][C]0.618275[/C][C]0.76345[/C][C]0.381725[/C][/ROW]
[ROW][C]200[/C][C]0.60486[/C][C]0.790279[/C][C]0.39514[/C][/ROW]
[ROW][C]201[/C][C]0.581265[/C][C]0.83747[/C][C]0.418735[/C][/ROW]
[ROW][C]202[/C][C]0.572808[/C][C]0.854383[/C][C]0.427192[/C][/ROW]
[ROW][C]203[/C][C]0.563065[/C][C]0.87387[/C][C]0.436935[/C][/ROW]
[ROW][C]204[/C][C]0.524343[/C][C]0.951313[/C][C]0.475657[/C][/ROW]
[ROW][C]205[/C][C]0.530531[/C][C]0.938938[/C][C]0.469469[/C][/ROW]
[ROW][C]206[/C][C]0.592511[/C][C]0.814978[/C][C]0.407489[/C][/ROW]
[ROW][C]207[/C][C]0.560043[/C][C]0.879914[/C][C]0.439957[/C][/ROW]
[ROW][C]208[/C][C]0.640969[/C][C]0.718061[/C][C]0.359031[/C][/ROW]
[ROW][C]209[/C][C]0.601613[/C][C]0.796774[/C][C]0.398387[/C][/ROW]
[ROW][C]210[/C][C]0.576262[/C][C]0.847476[/C][C]0.423738[/C][/ROW]
[ROW][C]211[/C][C]0.559987[/C][C]0.880027[/C][C]0.440013[/C][/ROW]
[ROW][C]212[/C][C]0.528216[/C][C]0.943567[/C][C]0.471784[/C][/ROW]
[ROW][C]213[/C][C]0.62906[/C][C]0.741881[/C][C]0.37094[/C][/ROW]
[ROW][C]214[/C][C]0.591059[/C][C]0.817882[/C][C]0.408941[/C][/ROW]
[ROW][C]215[/C][C]0.57335[/C][C]0.853299[/C][C]0.42665[/C][/ROW]
[ROW][C]216[/C][C]0.57428[/C][C]0.85144[/C][C]0.42572[/C][/ROW]
[ROW][C]217[/C][C]0.565153[/C][C]0.869694[/C][C]0.434847[/C][/ROW]
[ROW][C]218[/C][C]0.527523[/C][C]0.944955[/C][C]0.472477[/C][/ROW]
[ROW][C]219[/C][C]0.484885[/C][C]0.969769[/C][C]0.515115[/C][/ROW]
[ROW][C]220[/C][C]0.450621[/C][C]0.901242[/C][C]0.549379[/C][/ROW]
[ROW][C]221[/C][C]0.416978[/C][C]0.833955[/C][C]0.583022[/C][/ROW]
[ROW][C]222[/C][C]0.503962[/C][C]0.992076[/C][C]0.496038[/C][/ROW]
[ROW][C]223[/C][C]0.46463[/C][C]0.929261[/C][C]0.53537[/C][/ROW]
[ROW][C]224[/C][C]0.456852[/C][C]0.913704[/C][C]0.543148[/C][/ROW]
[ROW][C]225[/C][C]0.512382[/C][C]0.975235[/C][C]0.487618[/C][/ROW]
[ROW][C]226[/C][C]0.54335[/C][C]0.913299[/C][C]0.45665[/C][/ROW]
[ROW][C]227[/C][C]0.585988[/C][C]0.828024[/C][C]0.414012[/C][/ROW]
[ROW][C]228[/C][C]0.630483[/C][C]0.739034[/C][C]0.369517[/C][/ROW]
[ROW][C]229[/C][C]0.593838[/C][C]0.812325[/C][C]0.406162[/C][/ROW]
[ROW][C]230[/C][C]0.578543[/C][C]0.842913[/C][C]0.421457[/C][/ROW]
[ROW][C]231[/C][C]0.61331[/C][C]0.773381[/C][C]0.38669[/C][/ROW]
[ROW][C]232[/C][C]0.565834[/C][C]0.868333[/C][C]0.434166[/C][/ROW]
[ROW][C]233[/C][C]0.544536[/C][C]0.910928[/C][C]0.455464[/C][/ROW]
[ROW][C]234[/C][C]0.513295[/C][C]0.973411[/C][C]0.486705[/C][/ROW]
[ROW][C]235[/C][C]0.511699[/C][C]0.976601[/C][C]0.488301[/C][/ROW]
[ROW][C]236[/C][C]0.827563[/C][C]0.344873[/C][C]0.172437[/C][/ROW]
[ROW][C]237[/C][C]0.818964[/C][C]0.362071[/C][C]0.181036[/C][/ROW]
[ROW][C]238[/C][C]0.816762[/C][C]0.366476[/C][C]0.183238[/C][/ROW]
[ROW][C]239[/C][C]0.779235[/C][C]0.44153[/C][C]0.220765[/C][/ROW]
[ROW][C]240[/C][C]0.737716[/C][C]0.524568[/C][C]0.262284[/C][/ROW]
[ROW][C]241[/C][C]0.709935[/C][C]0.580129[/C][C]0.290065[/C][/ROW]
[ROW][C]242[/C][C]0.732327[/C][C]0.535345[/C][C]0.267673[/C][/ROW]
[ROW][C]243[/C][C]0.693304[/C][C]0.613393[/C][C]0.306696[/C][/ROW]
[ROW][C]244[/C][C]0.693153[/C][C]0.613695[/C][C]0.306847[/C][/ROW]
[ROW][C]245[/C][C]0.63865[/C][C]0.7227[/C][C]0.36135[/C][/ROW]
[ROW][C]246[/C][C]0.582938[/C][C]0.834123[/C][C]0.417062[/C][/ROW]
[ROW][C]247[/C][C]0.522953[/C][C]0.954093[/C][C]0.477047[/C][/ROW]
[ROW][C]248[/C][C]0.466255[/C][C]0.93251[/C][C]0.533745[/C][/ROW]
[ROW][C]249[/C][C]0.404797[/C][C]0.809593[/C][C]0.595203[/C][/ROW]
[ROW][C]250[/C][C]0.347812[/C][C]0.695623[/C][C]0.652188[/C][/ROW]
[ROW][C]251[/C][C]0.320598[/C][C]0.641197[/C][C]0.679402[/C][/ROW]
[ROW][C]252[/C][C]0.282273[/C][C]0.564545[/C][C]0.717727[/C][/ROW]
[ROW][C]253[/C][C]0.229309[/C][C]0.458618[/C][C]0.770691[/C][/ROW]
[ROW][C]254[/C][C]0.1818[/C][C]0.3636[/C][C]0.8182[/C][/ROW]
[ROW][C]255[/C][C]0.160693[/C][C]0.321387[/C][C]0.839307[/C][/ROW]
[ROW][C]256[/C][C]0.150807[/C][C]0.301614[/C][C]0.849193[/C][/ROW]
[ROW][C]257[/C][C]0.218252[/C][C]0.436504[/C][C]0.781748[/C][/ROW]
[ROW][C]258[/C][C]0.730554[/C][C]0.538892[/C][C]0.269446[/C][/ROW]
[ROW][C]259[/C][C]0.760879[/C][C]0.478243[/C][C]0.239121[/C][/ROW]
[ROW][C]260[/C][C]0.976624[/C][C]0.0467519[/C][C]0.023376[/C][/ROW]
[ROW][C]261[/C][C]0.99003[/C][C]0.01994[/C][C]0.00996999[/C][/ROW]
[ROW][C]262[/C][C]0.98729[/C][C]0.0254204[/C][C]0.0127102[/C][/ROW]
[ROW][C]263[/C][C]0.994941[/C][C]0.0101185[/C][C]0.00505926[/C][/ROW]
[ROW][C]264[/C][C]0.986146[/C][C]0.0277076[/C][C]0.0138538[/C][/ROW]
[ROW][C]265[/C][C]0.963856[/C][C]0.072288[/C][C]0.036144[/C][/ROW]
[ROW][C]266[/C][C]0.918439[/C][C]0.163121[/C][C]0.0815606[/C][/ROW]
[ROW][C]267[/C][C]0.966962[/C][C]0.0660768[/C][C]0.0330384[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.9225810.1548380.0774188
120.8622440.2755110.137756
130.8690040.2619920.130996
140.8041250.391750.195875
150.7449230.5101530.255077
160.6598290.6803420.340171
170.6679210.6641590.332079
180.5839120.8321750.416088
190.5242940.9514130.475706
200.5139660.9720670.486034
210.7101570.5796860.289843
220.7088520.5822960.291148
230.6408210.7183570.359179
240.5732340.8535320.426766
250.5009110.9981780.499089
260.4341820.8683640.565818
270.3776630.7553260.622337
280.3213660.6427330.678634
290.2667970.5335930.733203
300.2275130.4550270.772487
310.2282660.4565320.771734
320.2179990.4359980.782001
330.1764560.3529120.823544
340.1713620.3427240.828638
350.1369420.2738840.863058
360.113830.227660.88617
370.08769970.1753990.9123
380.08602850.1720570.913972
390.09582950.1916590.90417
400.07637740.1527550.923623
410.2697940.5395880.730206
420.2298440.4596880.770156
430.198460.3969190.80154
440.1641540.3283080.835846
450.1349390.2698780.865061
460.1101460.2202910.889854
470.08805210.1761040.911948
480.1781060.3562130.821894
490.1917740.3835470.808226
500.1866840.3733680.813316
510.1573690.3147380.842631
520.214630.429260.78537
530.1824510.3649030.817549
540.222170.4443390.77783
550.2547760.5095530.745224
560.2205280.4410560.779472
570.2984490.5968980.701551
580.429510.859020.57049
590.3920210.7840430.607979
600.406490.8129810.59351
610.3827920.7655840.617208
620.3729050.745810.627095
630.4648920.9297830.535108
640.5420420.9159150.457958
650.504280.9914410.49572
660.4683410.9366830.531659
670.4455370.8910750.554463
680.4112940.8225880.588706
690.4211180.8422360.578882
700.4009130.8018250.599087
710.3693780.7387570.630622
720.3363510.6727010.663649
730.303320.6066410.69668
740.3045760.6091520.695424
750.2998020.5996040.700198
760.2802820.5605630.719718
770.2856890.5713790.714311
780.2701980.5403960.729802
790.2554670.5109330.744533
800.302240.6044810.69776
810.2755070.5510130.724493
820.307260.6145210.69274
830.2777280.5554570.722272
840.4172780.8345550.582722
850.3951250.790250.604875
860.3624720.7249450.637528
870.3273690.6547370.672631
880.2984090.5968180.701591
890.2930810.5861620.706919
900.343310.686620.65669
910.3402190.6804370.659781
920.4038570.8077140.596143
930.368370.7367390.63163
940.3443680.6887360.655632
950.4127590.8255170.587241
960.3779380.7558760.622062
970.4076080.8152160.592392
980.3787820.7575640.621218
990.4506510.9013020.549349
1000.5697260.8605480.430274
1010.5419240.9161520.458076
1020.5074180.9851640.492582
1030.4930450.9860890.506955
1040.489250.97850.51075
1050.4978550.995710.502145
1060.4963530.9927060.503647
1070.4901880.9803760.509812
1080.6565970.6868050.343403
1090.7013230.5973540.298677
1100.7067160.5865680.293284
1110.6817460.6365070.318254
1120.6580110.6839780.341989
1130.7142320.5715360.285768
1140.6941760.6116470.305824
1150.7461310.5077390.253869
1160.7284930.5430130.271507
1170.7009210.5981580.299079
1180.7156990.5686010.284301
1190.6973480.6053040.302652
1200.6987330.6025340.301267
1210.7261590.5476820.273841
1220.7348890.5302220.265111
1230.7084410.5831180.291559
1240.8781630.2436750.121837
1250.9038770.1922450.0961227
1260.8946720.2106570.105328
1270.8781620.2436760.121838
1280.8680020.2639960.131998
1290.8583750.283250.141625
1300.8406840.3186330.159316
1310.8217640.3564710.178236
1320.8189830.3620340.181017
1330.8005520.3988960.199448
1340.7778050.444390.222195
1350.7593460.4813080.240654
1360.7376370.5247270.262363
1370.7696570.4606860.230343
1380.7562430.4875140.243757
1390.7282720.5434570.271728
1400.7024320.5951360.297568
1410.6738250.6523490.326175
1420.6847890.6304220.315211
1430.6705520.6588970.329448
1440.6412410.7175190.358759
1450.6090530.7818950.390947
1460.5758870.8482260.424113
1470.5427280.9145450.457272
1480.5084540.9830920.491546
1490.5400190.9199630.459981
1500.5217150.956570.478285
1510.8133960.3732070.186604
1520.793890.412220.20611
1530.7813040.4373910.218696
1540.7544620.4910770.245538
1550.7724740.4550510.227526
1560.7510580.4978840.248942
1570.7233980.5532050.276602
1580.7026130.5947740.297387
1590.6842980.6314040.315702
1600.6623990.6752020.337601
1610.663440.673120.33656
1620.6471270.7057460.352873
1630.6157630.7684750.384237
1640.8389860.3220290.161014
1650.8384420.3231170.161558
1660.8379460.3241080.162054
1670.8152680.3694650.184732
1680.8296050.340790.170395
1690.8056810.3886380.194319
1700.8024980.3950040.197502
1710.7764230.4471540.223577
1720.8217910.3564180.178209
1730.8065650.386870.193435
1740.7811650.437670.218835
1750.7541660.4916680.245834
1760.7769820.4460370.223018
1770.761140.4777210.23886
1780.7628210.4743570.237179
1790.7365680.5268630.263432
1800.7460070.5079850.253993
1810.737640.524720.26236
1820.7201340.5597310.279866
1830.7058860.5882290.294114
1840.672950.65410.32705
1850.7019690.5960620.298031
1860.6817330.6365330.318267
1870.7654870.4690250.234513
1880.7483350.503330.251665
1890.7191490.5617010.280851
1900.7071210.5857590.292879
1910.6768520.6462960.323148
1920.6438650.7122690.356135
1930.6341330.7317340.365867
1940.6494060.7011880.350594
1950.6304560.7390880.369544
1960.6261810.7476380.373819
1970.6460830.7078340.353917
1980.614680.7706410.38532
1990.6182750.763450.381725
2000.604860.7902790.39514
2010.5812650.837470.418735
2020.5728080.8543830.427192
2030.5630650.873870.436935
2040.5243430.9513130.475657
2050.5305310.9389380.469469
2060.5925110.8149780.407489
2070.5600430.8799140.439957
2080.6409690.7180610.359031
2090.6016130.7967740.398387
2100.5762620.8474760.423738
2110.5599870.8800270.440013
2120.5282160.9435670.471784
2130.629060.7418810.37094
2140.5910590.8178820.408941
2150.573350.8532990.42665
2160.574280.851440.42572
2170.5651530.8696940.434847
2180.5275230.9449550.472477
2190.4848850.9697690.515115
2200.4506210.9012420.549379
2210.4169780.8339550.583022
2220.5039620.9920760.496038
2230.464630.9292610.53537
2240.4568520.9137040.543148
2250.5123820.9752350.487618
2260.543350.9132990.45665
2270.5859880.8280240.414012
2280.6304830.7390340.369517
2290.5938380.8123250.406162
2300.5785430.8429130.421457
2310.613310.7733810.38669
2320.5658340.8683330.434166
2330.5445360.9109280.455464
2340.5132950.9734110.486705
2350.5116990.9766010.488301
2360.8275630.3448730.172437
2370.8189640.3620710.181036
2380.8167620.3664760.183238
2390.7792350.441530.220765
2400.7377160.5245680.262284
2410.7099350.5801290.290065
2420.7323270.5353450.267673
2430.6933040.6133930.306696
2440.6931530.6136950.306847
2450.638650.72270.36135
2460.5829380.8341230.417062
2470.5229530.9540930.477047
2480.4662550.932510.533745
2490.4047970.8095930.595203
2500.3478120.6956230.652188
2510.3205980.6411970.679402
2520.2822730.5645450.717727
2530.2293090.4586180.770691
2540.18180.36360.8182
2550.1606930.3213870.839307
2560.1508070.3016140.849193
2570.2182520.4365040.781748
2580.7305540.5388920.269446
2590.7608790.4782430.239121
2600.9766240.04675190.023376
2610.990030.019940.00996999
2620.987290.02542040.0127102
2630.9949410.01011850.00505926
2640.9861460.02770760.0138538
2650.9638560.0722880.036144
2660.9184390.1631210.0815606
2670.9669620.06607680.0330384






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0194553OK
10% type I error level70.0272374OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 5 & 0.0194553 & OK \tabularnewline
10% type I error level & 7 & 0.0272374 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263586&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]5[/C][C]0.0194553[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]7[/C][C]0.0272374[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263586&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263586&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level50.0194553OK
10% type I error level70.0272374OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}