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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 computationTue, 09 Dec 2014 13:18:32 +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/09/t1418131188evx7dl4j7w0cs9m.htm/, Retrieved Thu, 16 May 2024 06:56:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264581, Retrieved Thu, 16 May 2024 06:56:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Chi-Squared and McNemar Tests] [] [2010-11-16 15:17:18] [b98453cac15ba1066b407e146608df68]
- RM    [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [q1] [2014-11-05 13:43:53] [2568c9326b0361ae14a2b722dbd6de4e]
- RMPD      [Multiple Regression] [RFC multiple] [2014-12-09 13:18:32] [4475d2f35de7f19e7f9792645feacf86] [Current]
- R P         [Multiple Regression] [] [2014-12-09 13:24:41] [36c866d94170840abc594fd3e7d5794f]
- RMPD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-10 15:18:06] [36c866d94170840abc594fd3e7d5794f]
- RM D          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-10 15:19:24] [36c866d94170840abc594fd3e7d5794f]
- RMPD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-10 15:21:32] [36c866d94170840abc594fd3e7d5794f]
- RM D          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-10 15:23:12] [36c866d94170840abc594fd3e7d5794f]
- RM D            [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-13 19:52:37] [f12bfb29749f0c3f544bf278d0782c85]
- RMPD          [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-10 15:24:34] [36c866d94170840abc594fd3e7d5794f]
- RM D            [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-13 19:58:26] [f12bfb29749f0c3f544bf278d0782c85]
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Dataset

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

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'Gertrude Mary Cox' @ cox.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 & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&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]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.2405 + 0.0105454LFM[t] + 0.0278334BLOGS[t] + 0.00370288PRH[t] -0.0077767CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.2405 +  0.0105454LFM[t] +  0.0278334BLOGS[t] +  0.00370288PRH[t] -0.0077767CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.2405 +  0.0105454LFM[t] +  0.0278334BLOGS[t] +  0.00370288PRH[t] -0.0077767CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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] = + 8.2405 + 0.0105454LFM[t] + 0.0278334BLOGS[t] + 0.00370288PRH[t] -0.0077767CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.24050.54411215.144.99673e-382.49837e-38
LFM0.01054540.004818232.1890.02947040.0147352
BLOGS0.02783340.002915339.5477.96349e-193.98175e-19
PRH0.003702880.009452710.39170.6955660.347783
CH-0.00777670.0114743-0.67780.4985030.249251

\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) & 8.2405 & 0.544112 & 15.14 & 4.99673e-38 & 2.49837e-38 \tabularnewline
LFM & 0.0105454 & 0.00481823 & 2.189 & 0.0294704 & 0.0147352 \tabularnewline
BLOGS & 0.0278334 & 0.00291533 & 9.547 & 7.96349e-19 & 3.98175e-19 \tabularnewline
PRH & 0.00370288 & 0.00945271 & 0.3917 & 0.695566 & 0.347783 \tabularnewline
CH & -0.0077767 & 0.0114743 & -0.6778 & 0.498503 & 0.249251 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&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]8.2405[/C][C]0.544112[/C][C]15.14[/C][C]4.99673e-38[/C][C]2.49837e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.0105454[/C][C]0.00481823[/C][C]2.189[/C][C]0.0294704[/C][C]0.0147352[/C][/ROW]
[ROW][C]BLOGS[/C][C]0.0278334[/C][C]0.00291533[/C][C]9.547[/C][C]7.96349e-19[/C][C]3.98175e-19[/C][/ROW]
[ROW][C]PRH[/C][C]0.00370288[/C][C]0.00945271[/C][C]0.3917[/C][C]0.695566[/C][C]0.347783[/C][/ROW]
[ROW][C]CH[/C][C]-0.0077767[/C][C]0.0114743[/C][C]-0.6778[/C][C]0.498503[/C][C]0.249251[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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)8.24050.54411215.144.99673e-382.49837e-38
LFM0.01054540.004818232.1890.02947040.0147352
BLOGS0.02783340.002915339.5477.96349e-193.98175e-19
PRH0.003702880.009452710.39170.6955660.347783
CH-0.00777670.0114743-0.67780.4985030.249251






Multiple Linear Regression - Regression Statistics
Multiple R0.607307
R-squared0.368822
Adjusted R-squared0.359574
F-TEST (value)39.8811
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.71639
Sum Squared Residuals2014.41

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.607307 \tabularnewline
R-squared & 0.368822 \tabularnewline
Adjusted R-squared & 0.359574 \tabularnewline
F-TEST (value) & 39.8811 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.71639 \tabularnewline
Sum Squared Residuals & 2014.41 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.607307[/C][/ROW]
[ROW][C]R-squared[/C][C]0.368822[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.359574[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]39.8811[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/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]2.71639[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2014.41[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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 R0.607307
R-squared0.368822
Adjusted R-squared0.359574
F-TEST (value)39.8811
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.71639
Sum Squared Residuals2014.41






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.02160.878407
212.211.46610.733866
312.812.14610.653897
47.412.7678-5.36784
56.711.369-4.66896
612.615.345-2.74503
714.812.73772.06234
813.312.30930.990661
911.112.673-1.57297
108.214.2174-6.0174
1111.412.9544-1.55436
126.414.5984-8.19842
1310.611.546-0.945971
141213.6699-1.6699
156.39.71412-3.41412
1611.311.2820.0180104
1711.913.8768-1.97675
189.312.1091-2.80908
199.612.2696-2.66961
201011.5897-1.5897
216.411.7092-5.30919
2213.812.83270.967317
2310.813.3366-2.53662
2413.812.30981.4902
2511.712.6832-0.983184
2610.915.1346-4.2346
2716.113.39592.70414
2813.411.11612.28391
299.911.259-1.35898
3011.512.2051-0.705057
318.311.8817-3.5817
3211.713.3469-1.64694
33912.3182-3.31816
349.714.3635-4.66352
3510.812.5204-1.72036
3610.312.7608-2.46081
3710.411.732-1.33197
3812.712.65380.046152
399.312.2387-2.93871
4011.814.3192-2.51918
415.910.6133-4.71334
4211.413.9043-2.50431
431311.78671.21326
4410.812.6269-1.82686
4512.310.40911.8909
4611.313.4411-2.14106
4711.812.5246-0.724645
487.911.0928-3.19283
4912.710.09822.60182
5012.310.76971.53029
5111.611.9943-0.394348
526.710.9976-4.29757
5310.913.1453-2.24527
5412.112.6334-0.533412
5513.313.5058-0.20579
5610.113.3404-3.24041
575.711.6955-5.9955
5814.312.19892.10106
5989.43972-1.43972
6013.311.74731.55273
619.312.8125-3.51247
6212.511.60870.891287
637.610.7936-3.19357
6415.913.9011.99899
659.211.4281-2.22806
669.110.5158-1.41575
6711.114.1584-3.05839
681313.7681-0.768145
6914.512.86971.6303
7012.211.02791.17207
7112.313.5026-1.2026
7211.411.31590.0840945
738.811.2718-2.47179
7414.611.13163.46837
7512.612.9986-0.398628
76NANA-0.712913
771311.63061.36936
7812.614.1272-1.52722
7913.214.4909-1.29091
809.913.6882-3.7882
817.77.81327-0.113268
8210.57.696332.80367
8313.414.3424-0.94238
8410.916.6597-5.75975
854.35.04459-0.74459
8610.310.14180.158229
8711.811.19580.604193
8811.210.57980.620166
8911.412.9029-1.50287
908.66.415052.18495
9113.210.93092.26909
9212.618.0736-5.47365
935.67.07373-1.47373
949.912.9652-3.06517
958.812.7488-3.94884
967.79.06807-1.36807
97913.9367-4.93675
987.36.836220.463782
9911.49.165282.23472
10013.616.3691-2.76913
1017.98.13303-0.233032
10210.712.0497-1.34966
10310.312.2603-1.96028
1048.39.65298-1.35298
1059.67.102652.49735
10614.216.0852-1.88518
1078.55.6322.868
10813.519.301-5.80104
1094.98.65039-3.75039
1106.47.21792-0.817919
1119.68.783250.816752
11211.610.78030.819695
11311.116.6297-5.52969
1144.354.190730.159271
11512.79.322433.37757
11618.115.28922.81076
11717.8517.25720.592763
11816.613.90582.69418
11912.617.6689-5.06888
12017.113.58083.5192
12119.121.5629-2.46292
12216.113.29692.80308
12313.3512.54770.802329
12418.414.63353.76647
12514.718.8221-4.12208
12610.611.6691-1.06909
12712.611.43571.16427
12816.220.1691-3.96909
12913.610.47123.12878
13018.917.08161.81843
13114.111.37372.72626
13214.516.4443-1.94432
13316.1514.84161.30836
13414.7514.11240.63758
13514.814.57810.221918
13612.4514.4619-2.01192
13712.659.015973.63403
13817.3520.711-3.36101
1398.67.828060.771937
14018.420.3675-1.96748
14116.115.54620.553783
14211.65.818435.78157
14317.7516.16481.58516
14415.2513.7671.48301
14517.6516.30381.34621
14616.3513.56882.78116
14717.6516.95890.69107
14813.612.67110.928941
14914.3517.2454-2.89544
15014.7512.77661.97339
15118.2523.4699-5.21991
1529.97.929761.97024
1531613.372.63004
15418.2518.6885-0.438537
15516.8514.6872.16296
15614.614.48310.116885
15713.8511.20222.64783
15818.9517.87421.07582
15915.618.0651-2.46507
16014.8515.4331-0.583092
16111.756.130675.61933
16218.4519.8853-1.43531
16315.912.87513.02491
16417.111.73995.36009
16516.110.91135.18874
16619.919.2560.643998
16710.958.25662.6934
16818.4513.7614.68902
16915.115.5109-0.410939
1701517.6706-2.67064
17111.3510.39290.957121
17215.9511.07574.87426
17318.116.28291.81708
17414.615.2117-0.611723
17515.416.0117-0.611723
17615.411.29084.10916
17717.618.0259-0.425903
17813.3510.8492.50095
17919.116.71642.38364
18015.3519.8658-4.51585
1817.68.10404-0.504042
18213.412.93990.460086
18313.911.94921.95082
18419.117.60981.49022
18515.2514.29350.956498
18612.910.56732.33274
18716.110.90845.1916
18817.3516.42060.929382
18913.1510.71182.4382
19012.1512.05520.094777
19112.613.6426-1.04258
19210.357.559812.79019
19315.416.5857-1.18568
1949.64.547035.05297
19518.216.61141.58862
19613.613.27810.321926
19714.8517.06-2.21
19814.7514.4580.291955
19914.110.40513.69492
20014.911.31713.58292
20116.2514.48611.76387
20219.2517.50321.74676
20313.613.20290.397103
20413.613.06050.539497
20515.6514.98550.664533
20612.759.161663.58834
20714.617.9918-3.3918
2089.858.164221.68578
20912.659.913462.73654
21019.216.782.41998
21116.615.23181.36823
21211.28.94362.2564
21315.2518.4918-3.24179
21411.914.434-2.53396
21513.214.0582-0.858186
21616.3517.2538-0.903793
21712.49.399743.00026
21815.8512.63713.21288
21918.1518.34-0.190017
22011.1510.97820.171769
22115.6514.08961.56037
22217.7522.4831-4.73306
2237.657.072610.577392
22412.358.156354.19365
22515.612.56993.03009
22619.315.78363.5164
22715.211.42093.77912
22817.114.03193.06806
22915.612.20243.39762
23018.414.4483.95197
23119.0513.65095.39908
23218.5516.34722.20282
23319.117.66741.43258
23413.113.3573-0.257281
23512.8514.782-1.932
2369.516.0946-6.59458
2374.53.061611.43839
23811.8514.0708-2.2208
23913.615.2051-1.60506
24011.710.62731.07266
24112.413.8567-1.45667
24213.3515.7203-2.3703
24311.48.051843.34816
24414.99.711265.18874
24519.920.3545-0.454547
24611.212.0159-0.815945
24714.612.99131.60866
24817.615.88661.7134
24914.0513.20340.846589
25016.115.85520.244841
25113.3513.81-0.460014
25211.8514.1809-2.33088
25311.9511.78350.166491
25414.7512.66942.08057
25515.1515.5761-0.426126
25613.211.73011.46988
25716.8519.0534-2.2034
2587.8514.7169-6.86693
2597.76.508881.19112
26012.616.1377-3.53772
2617.857.2060.643998
26210.9510.48140.468616
26312.3514.878-2.52799
2649.956.601843.34816
26514.912.77432.12571
26616.6516.13970.51031
26713.412.73770.662282
26813.959.678914.27109
26915.711.06064.63941
27016.8516.17780.672212
27110.957.183433.76657
27215.3514.17481.17521
27312.211.1031.09696
27415.113.73421.36583
27517.7515.23992.51011
27615.213.85051.34945
27714.612.61591.98405
27816.6519.2121-2.56211
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.0216 & 0.878407 \tabularnewline
2 & 12.2 & 11.4661 & 0.733866 \tabularnewline
3 & 12.8 & 12.1461 & 0.653897 \tabularnewline
4 & 7.4 & 12.7678 & -5.36784 \tabularnewline
5 & 6.7 & 11.369 & -4.66896 \tabularnewline
6 & 12.6 & 15.345 & -2.74503 \tabularnewline
7 & 14.8 & 12.7377 & 2.06234 \tabularnewline
8 & 13.3 & 12.3093 & 0.990661 \tabularnewline
9 & 11.1 & 12.673 & -1.57297 \tabularnewline
10 & 8.2 & 14.2174 & -6.0174 \tabularnewline
11 & 11.4 & 12.9544 & -1.55436 \tabularnewline
12 & 6.4 & 14.5984 & -8.19842 \tabularnewline
13 & 10.6 & 11.546 & -0.945971 \tabularnewline
14 & 12 & 13.6699 & -1.6699 \tabularnewline
15 & 6.3 & 9.71412 & -3.41412 \tabularnewline
16 & 11.3 & 11.282 & 0.0180104 \tabularnewline
17 & 11.9 & 13.8768 & -1.97675 \tabularnewline
18 & 9.3 & 12.1091 & -2.80908 \tabularnewline
19 & 9.6 & 12.2696 & -2.66961 \tabularnewline
20 & 10 & 11.5897 & -1.5897 \tabularnewline
21 & 6.4 & 11.7092 & -5.30919 \tabularnewline
22 & 13.8 & 12.8327 & 0.967317 \tabularnewline
23 & 10.8 & 13.3366 & -2.53662 \tabularnewline
24 & 13.8 & 12.3098 & 1.4902 \tabularnewline
25 & 11.7 & 12.6832 & -0.983184 \tabularnewline
26 & 10.9 & 15.1346 & -4.2346 \tabularnewline
27 & 16.1 & 13.3959 & 2.70414 \tabularnewline
28 & 13.4 & 11.1161 & 2.28391 \tabularnewline
29 & 9.9 & 11.259 & -1.35898 \tabularnewline
30 & 11.5 & 12.2051 & -0.705057 \tabularnewline
31 & 8.3 & 11.8817 & -3.5817 \tabularnewline
32 & 11.7 & 13.3469 & -1.64694 \tabularnewline
33 & 9 & 12.3182 & -3.31816 \tabularnewline
34 & 9.7 & 14.3635 & -4.66352 \tabularnewline
35 & 10.8 & 12.5204 & -1.72036 \tabularnewline
36 & 10.3 & 12.7608 & -2.46081 \tabularnewline
37 & 10.4 & 11.732 & -1.33197 \tabularnewline
38 & 12.7 & 12.6538 & 0.046152 \tabularnewline
39 & 9.3 & 12.2387 & -2.93871 \tabularnewline
40 & 11.8 & 14.3192 & -2.51918 \tabularnewline
41 & 5.9 & 10.6133 & -4.71334 \tabularnewline
42 & 11.4 & 13.9043 & -2.50431 \tabularnewline
43 & 13 & 11.7867 & 1.21326 \tabularnewline
44 & 10.8 & 12.6269 & -1.82686 \tabularnewline
45 & 12.3 & 10.4091 & 1.8909 \tabularnewline
46 & 11.3 & 13.4411 & -2.14106 \tabularnewline
47 & 11.8 & 12.5246 & -0.724645 \tabularnewline
48 & 7.9 & 11.0928 & -3.19283 \tabularnewline
49 & 12.7 & 10.0982 & 2.60182 \tabularnewline
50 & 12.3 & 10.7697 & 1.53029 \tabularnewline
51 & 11.6 & 11.9943 & -0.394348 \tabularnewline
52 & 6.7 & 10.9976 & -4.29757 \tabularnewline
53 & 10.9 & 13.1453 & -2.24527 \tabularnewline
54 & 12.1 & 12.6334 & -0.533412 \tabularnewline
55 & 13.3 & 13.5058 & -0.20579 \tabularnewline
56 & 10.1 & 13.3404 & -3.24041 \tabularnewline
57 & 5.7 & 11.6955 & -5.9955 \tabularnewline
58 & 14.3 & 12.1989 & 2.10106 \tabularnewline
59 & 8 & 9.43972 & -1.43972 \tabularnewline
60 & 13.3 & 11.7473 & 1.55273 \tabularnewline
61 & 9.3 & 12.8125 & -3.51247 \tabularnewline
62 & 12.5 & 11.6087 & 0.891287 \tabularnewline
63 & 7.6 & 10.7936 & -3.19357 \tabularnewline
64 & 15.9 & 13.901 & 1.99899 \tabularnewline
65 & 9.2 & 11.4281 & -2.22806 \tabularnewline
66 & 9.1 & 10.5158 & -1.41575 \tabularnewline
67 & 11.1 & 14.1584 & -3.05839 \tabularnewline
68 & 13 & 13.7681 & -0.768145 \tabularnewline
69 & 14.5 & 12.8697 & 1.6303 \tabularnewline
70 & 12.2 & 11.0279 & 1.17207 \tabularnewline
71 & 12.3 & 13.5026 & -1.2026 \tabularnewline
72 & 11.4 & 11.3159 & 0.0840945 \tabularnewline
73 & 8.8 & 11.2718 & -2.47179 \tabularnewline
74 & 14.6 & 11.1316 & 3.46837 \tabularnewline
75 & 12.6 & 12.9986 & -0.398628 \tabularnewline
76 & NA & NA & -0.712913 \tabularnewline
77 & 13 & 11.6306 & 1.36936 \tabularnewline
78 & 12.6 & 14.1272 & -1.52722 \tabularnewline
79 & 13.2 & 14.4909 & -1.29091 \tabularnewline
80 & 9.9 & 13.6882 & -3.7882 \tabularnewline
81 & 7.7 & 7.81327 & -0.113268 \tabularnewline
82 & 10.5 & 7.69633 & 2.80367 \tabularnewline
83 & 13.4 & 14.3424 & -0.94238 \tabularnewline
84 & 10.9 & 16.6597 & -5.75975 \tabularnewline
85 & 4.3 & 5.04459 & -0.74459 \tabularnewline
86 & 10.3 & 10.1418 & 0.158229 \tabularnewline
87 & 11.8 & 11.1958 & 0.604193 \tabularnewline
88 & 11.2 & 10.5798 & 0.620166 \tabularnewline
89 & 11.4 & 12.9029 & -1.50287 \tabularnewline
90 & 8.6 & 6.41505 & 2.18495 \tabularnewline
91 & 13.2 & 10.9309 & 2.26909 \tabularnewline
92 & 12.6 & 18.0736 & -5.47365 \tabularnewline
93 & 5.6 & 7.07373 & -1.47373 \tabularnewline
94 & 9.9 & 12.9652 & -3.06517 \tabularnewline
95 & 8.8 & 12.7488 & -3.94884 \tabularnewline
96 & 7.7 & 9.06807 & -1.36807 \tabularnewline
97 & 9 & 13.9367 & -4.93675 \tabularnewline
98 & 7.3 & 6.83622 & 0.463782 \tabularnewline
99 & 11.4 & 9.16528 & 2.23472 \tabularnewline
100 & 13.6 & 16.3691 & -2.76913 \tabularnewline
101 & 7.9 & 8.13303 & -0.233032 \tabularnewline
102 & 10.7 & 12.0497 & -1.34966 \tabularnewline
103 & 10.3 & 12.2603 & -1.96028 \tabularnewline
104 & 8.3 & 9.65298 & -1.35298 \tabularnewline
105 & 9.6 & 7.10265 & 2.49735 \tabularnewline
106 & 14.2 & 16.0852 & -1.88518 \tabularnewline
107 & 8.5 & 5.632 & 2.868 \tabularnewline
108 & 13.5 & 19.301 & -5.80104 \tabularnewline
109 & 4.9 & 8.65039 & -3.75039 \tabularnewline
110 & 6.4 & 7.21792 & -0.817919 \tabularnewline
111 & 9.6 & 8.78325 & 0.816752 \tabularnewline
112 & 11.6 & 10.7803 & 0.819695 \tabularnewline
113 & 11.1 & 16.6297 & -5.52969 \tabularnewline
114 & 4.35 & 4.19073 & 0.159271 \tabularnewline
115 & 12.7 & 9.32243 & 3.37757 \tabularnewline
116 & 18.1 & 15.2892 & 2.81076 \tabularnewline
117 & 17.85 & 17.2572 & 0.592763 \tabularnewline
118 & 16.6 & 13.9058 & 2.69418 \tabularnewline
119 & 12.6 & 17.6689 & -5.06888 \tabularnewline
120 & 17.1 & 13.5808 & 3.5192 \tabularnewline
121 & 19.1 & 21.5629 & -2.46292 \tabularnewline
122 & 16.1 & 13.2969 & 2.80308 \tabularnewline
123 & 13.35 & 12.5477 & 0.802329 \tabularnewline
124 & 18.4 & 14.6335 & 3.76647 \tabularnewline
125 & 14.7 & 18.8221 & -4.12208 \tabularnewline
126 & 10.6 & 11.6691 & -1.06909 \tabularnewline
127 & 12.6 & 11.4357 & 1.16427 \tabularnewline
128 & 16.2 & 20.1691 & -3.96909 \tabularnewline
129 & 13.6 & 10.4712 & 3.12878 \tabularnewline
130 & 18.9 & 17.0816 & 1.81843 \tabularnewline
131 & 14.1 & 11.3737 & 2.72626 \tabularnewline
132 & 14.5 & 16.4443 & -1.94432 \tabularnewline
133 & 16.15 & 14.8416 & 1.30836 \tabularnewline
134 & 14.75 & 14.1124 & 0.63758 \tabularnewline
135 & 14.8 & 14.5781 & 0.221918 \tabularnewline
136 & 12.45 & 14.4619 & -2.01192 \tabularnewline
137 & 12.65 & 9.01597 & 3.63403 \tabularnewline
138 & 17.35 & 20.711 & -3.36101 \tabularnewline
139 & 8.6 & 7.82806 & 0.771937 \tabularnewline
140 & 18.4 & 20.3675 & -1.96748 \tabularnewline
141 & 16.1 & 15.5462 & 0.553783 \tabularnewline
142 & 11.6 & 5.81843 & 5.78157 \tabularnewline
143 & 17.75 & 16.1648 & 1.58516 \tabularnewline
144 & 15.25 & 13.767 & 1.48301 \tabularnewline
145 & 17.65 & 16.3038 & 1.34621 \tabularnewline
146 & 16.35 & 13.5688 & 2.78116 \tabularnewline
147 & 17.65 & 16.9589 & 0.69107 \tabularnewline
148 & 13.6 & 12.6711 & 0.928941 \tabularnewline
149 & 14.35 & 17.2454 & -2.89544 \tabularnewline
150 & 14.75 & 12.7766 & 1.97339 \tabularnewline
151 & 18.25 & 23.4699 & -5.21991 \tabularnewline
152 & 9.9 & 7.92976 & 1.97024 \tabularnewline
153 & 16 & 13.37 & 2.63004 \tabularnewline
154 & 18.25 & 18.6885 & -0.438537 \tabularnewline
155 & 16.85 & 14.687 & 2.16296 \tabularnewline
156 & 14.6 & 14.4831 & 0.116885 \tabularnewline
157 & 13.85 & 11.2022 & 2.64783 \tabularnewline
158 & 18.95 & 17.8742 & 1.07582 \tabularnewline
159 & 15.6 & 18.0651 & -2.46507 \tabularnewline
160 & 14.85 & 15.4331 & -0.583092 \tabularnewline
161 & 11.75 & 6.13067 & 5.61933 \tabularnewline
162 & 18.45 & 19.8853 & -1.43531 \tabularnewline
163 & 15.9 & 12.8751 & 3.02491 \tabularnewline
164 & 17.1 & 11.7399 & 5.36009 \tabularnewline
165 & 16.1 & 10.9113 & 5.18874 \tabularnewline
166 & 19.9 & 19.256 & 0.643998 \tabularnewline
167 & 10.95 & 8.2566 & 2.6934 \tabularnewline
168 & 18.45 & 13.761 & 4.68902 \tabularnewline
169 & 15.1 & 15.5109 & -0.410939 \tabularnewline
170 & 15 & 17.6706 & -2.67064 \tabularnewline
171 & 11.35 & 10.3929 & 0.957121 \tabularnewline
172 & 15.95 & 11.0757 & 4.87426 \tabularnewline
173 & 18.1 & 16.2829 & 1.81708 \tabularnewline
174 & 14.6 & 15.2117 & -0.611723 \tabularnewline
175 & 15.4 & 16.0117 & -0.611723 \tabularnewline
176 & 15.4 & 11.2908 & 4.10916 \tabularnewline
177 & 17.6 & 18.0259 & -0.425903 \tabularnewline
178 & 13.35 & 10.849 & 2.50095 \tabularnewline
179 & 19.1 & 16.7164 & 2.38364 \tabularnewline
180 & 15.35 & 19.8658 & -4.51585 \tabularnewline
181 & 7.6 & 8.10404 & -0.504042 \tabularnewline
182 & 13.4 & 12.9399 & 0.460086 \tabularnewline
183 & 13.9 & 11.9492 & 1.95082 \tabularnewline
184 & 19.1 & 17.6098 & 1.49022 \tabularnewline
185 & 15.25 & 14.2935 & 0.956498 \tabularnewline
186 & 12.9 & 10.5673 & 2.33274 \tabularnewline
187 & 16.1 & 10.9084 & 5.1916 \tabularnewline
188 & 17.35 & 16.4206 & 0.929382 \tabularnewline
189 & 13.15 & 10.7118 & 2.4382 \tabularnewline
190 & 12.15 & 12.0552 & 0.094777 \tabularnewline
191 & 12.6 & 13.6426 & -1.04258 \tabularnewline
192 & 10.35 & 7.55981 & 2.79019 \tabularnewline
193 & 15.4 & 16.5857 & -1.18568 \tabularnewline
194 & 9.6 & 4.54703 & 5.05297 \tabularnewline
195 & 18.2 & 16.6114 & 1.58862 \tabularnewline
196 & 13.6 & 13.2781 & 0.321926 \tabularnewline
197 & 14.85 & 17.06 & -2.21 \tabularnewline
198 & 14.75 & 14.458 & 0.291955 \tabularnewline
199 & 14.1 & 10.4051 & 3.69492 \tabularnewline
200 & 14.9 & 11.3171 & 3.58292 \tabularnewline
201 & 16.25 & 14.4861 & 1.76387 \tabularnewline
202 & 19.25 & 17.5032 & 1.74676 \tabularnewline
203 & 13.6 & 13.2029 & 0.397103 \tabularnewline
204 & 13.6 & 13.0605 & 0.539497 \tabularnewline
205 & 15.65 & 14.9855 & 0.664533 \tabularnewline
206 & 12.75 & 9.16166 & 3.58834 \tabularnewline
207 & 14.6 & 17.9918 & -3.3918 \tabularnewline
208 & 9.85 & 8.16422 & 1.68578 \tabularnewline
209 & 12.65 & 9.91346 & 2.73654 \tabularnewline
210 & 19.2 & 16.78 & 2.41998 \tabularnewline
211 & 16.6 & 15.2318 & 1.36823 \tabularnewline
212 & 11.2 & 8.9436 & 2.2564 \tabularnewline
213 & 15.25 & 18.4918 & -3.24179 \tabularnewline
214 & 11.9 & 14.434 & -2.53396 \tabularnewline
215 & 13.2 & 14.0582 & -0.858186 \tabularnewline
216 & 16.35 & 17.2538 & -0.903793 \tabularnewline
217 & 12.4 & 9.39974 & 3.00026 \tabularnewline
218 & 15.85 & 12.6371 & 3.21288 \tabularnewline
219 & 18.15 & 18.34 & -0.190017 \tabularnewline
220 & 11.15 & 10.9782 & 0.171769 \tabularnewline
221 & 15.65 & 14.0896 & 1.56037 \tabularnewline
222 & 17.75 & 22.4831 & -4.73306 \tabularnewline
223 & 7.65 & 7.07261 & 0.577392 \tabularnewline
224 & 12.35 & 8.15635 & 4.19365 \tabularnewline
225 & 15.6 & 12.5699 & 3.03009 \tabularnewline
226 & 19.3 & 15.7836 & 3.5164 \tabularnewline
227 & 15.2 & 11.4209 & 3.77912 \tabularnewline
228 & 17.1 & 14.0319 & 3.06806 \tabularnewline
229 & 15.6 & 12.2024 & 3.39762 \tabularnewline
230 & 18.4 & 14.448 & 3.95197 \tabularnewline
231 & 19.05 & 13.6509 & 5.39908 \tabularnewline
232 & 18.55 & 16.3472 & 2.20282 \tabularnewline
233 & 19.1 & 17.6674 & 1.43258 \tabularnewline
234 & 13.1 & 13.3573 & -0.257281 \tabularnewline
235 & 12.85 & 14.782 & -1.932 \tabularnewline
236 & 9.5 & 16.0946 & -6.59458 \tabularnewline
237 & 4.5 & 3.06161 & 1.43839 \tabularnewline
238 & 11.85 & 14.0708 & -2.2208 \tabularnewline
239 & 13.6 & 15.2051 & -1.60506 \tabularnewline
240 & 11.7 & 10.6273 & 1.07266 \tabularnewline
241 & 12.4 & 13.8567 & -1.45667 \tabularnewline
242 & 13.35 & 15.7203 & -2.3703 \tabularnewline
243 & 11.4 & 8.05184 & 3.34816 \tabularnewline
244 & 14.9 & 9.71126 & 5.18874 \tabularnewline
245 & 19.9 & 20.3545 & -0.454547 \tabularnewline
246 & 11.2 & 12.0159 & -0.815945 \tabularnewline
247 & 14.6 & 12.9913 & 1.60866 \tabularnewline
248 & 17.6 & 15.8866 & 1.7134 \tabularnewline
249 & 14.05 & 13.2034 & 0.846589 \tabularnewline
250 & 16.1 & 15.8552 & 0.244841 \tabularnewline
251 & 13.35 & 13.81 & -0.460014 \tabularnewline
252 & 11.85 & 14.1809 & -2.33088 \tabularnewline
253 & 11.95 & 11.7835 & 0.166491 \tabularnewline
254 & 14.75 & 12.6694 & 2.08057 \tabularnewline
255 & 15.15 & 15.5761 & -0.426126 \tabularnewline
256 & 13.2 & 11.7301 & 1.46988 \tabularnewline
257 & 16.85 & 19.0534 & -2.2034 \tabularnewline
258 & 7.85 & 14.7169 & -6.86693 \tabularnewline
259 & 7.7 & 6.50888 & 1.19112 \tabularnewline
260 & 12.6 & 16.1377 & -3.53772 \tabularnewline
261 & 7.85 & 7.206 & 0.643998 \tabularnewline
262 & 10.95 & 10.4814 & 0.468616 \tabularnewline
263 & 12.35 & 14.878 & -2.52799 \tabularnewline
264 & 9.95 & 6.60184 & 3.34816 \tabularnewline
265 & 14.9 & 12.7743 & 2.12571 \tabularnewline
266 & 16.65 & 16.1397 & 0.51031 \tabularnewline
267 & 13.4 & 12.7377 & 0.662282 \tabularnewline
268 & 13.95 & 9.67891 & 4.27109 \tabularnewline
269 & 15.7 & 11.0606 & 4.63941 \tabularnewline
270 & 16.85 & 16.1778 & 0.672212 \tabularnewline
271 & 10.95 & 7.18343 & 3.76657 \tabularnewline
272 & 15.35 & 14.1748 & 1.17521 \tabularnewline
273 & 12.2 & 11.103 & 1.09696 \tabularnewline
274 & 15.1 & 13.7342 & 1.36583 \tabularnewline
275 & 17.75 & 15.2399 & 2.51011 \tabularnewline
276 & 15.2 & 13.8505 & 1.34945 \tabularnewline
277 & 14.6 & 12.6159 & 1.98405 \tabularnewline
278 & 16.65 & 19.2121 & -2.56211 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&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]12.0216[/C][C]0.878407[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.4661[/C][C]0.733866[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.1461[/C][C]0.653897[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.7678[/C][C]-5.36784[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.369[/C][C]-4.66896[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.345[/C][C]-2.74503[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.7377[/C][C]2.06234[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.3093[/C][C]0.990661[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.673[/C][C]-1.57297[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.2174[/C][C]-6.0174[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.9544[/C][C]-1.55436[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.5984[/C][C]-8.19842[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.546[/C][C]-0.945971[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.6699[/C][C]-1.6699[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.71412[/C][C]-3.41412[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.282[/C][C]0.0180104[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.8768[/C][C]-1.97675[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.1091[/C][C]-2.80908[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.2696[/C][C]-2.66961[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.5897[/C][C]-1.5897[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.7092[/C][C]-5.30919[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.8327[/C][C]0.967317[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3366[/C][C]-2.53662[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.3098[/C][C]1.4902[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.6832[/C][C]-0.983184[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.1346[/C][C]-4.2346[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.3959[/C][C]2.70414[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.1161[/C][C]2.28391[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.259[/C][C]-1.35898[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.2051[/C][C]-0.705057[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.8817[/C][C]-3.5817[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3469[/C][C]-1.64694[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.3182[/C][C]-3.31816[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.3635[/C][C]-4.66352[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.5204[/C][C]-1.72036[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.7608[/C][C]-2.46081[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.732[/C][C]-1.33197[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6538[/C][C]0.046152[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.2387[/C][C]-2.93871[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.3192[/C][C]-2.51918[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.6133[/C][C]-4.71334[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.9043[/C][C]-2.50431[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.7867[/C][C]1.21326[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.6269[/C][C]-1.82686[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.4091[/C][C]1.8909[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.4411[/C][C]-2.14106[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.5246[/C][C]-0.724645[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.0928[/C][C]-3.19283[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.0982[/C][C]2.60182[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.7697[/C][C]1.53029[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.9943[/C][C]-0.394348[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9976[/C][C]-4.29757[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.1453[/C][C]-2.24527[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.6334[/C][C]-0.533412[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.5058[/C][C]-0.20579[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3404[/C][C]-3.24041[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.6955[/C][C]-5.9955[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.1989[/C][C]2.10106[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.43972[/C][C]-1.43972[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.7473[/C][C]1.55273[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.8125[/C][C]-3.51247[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.6087[/C][C]0.891287[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.7936[/C][C]-3.19357[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.901[/C][C]1.99899[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.4281[/C][C]-2.22806[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.5158[/C][C]-1.41575[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.1584[/C][C]-3.05839[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.7681[/C][C]-0.768145[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.8697[/C][C]1.6303[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.0279[/C][C]1.17207[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.5026[/C][C]-1.2026[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.3159[/C][C]0.0840945[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.2718[/C][C]-2.47179[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.1316[/C][C]3.46837[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.9986[/C][C]-0.398628[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-0.712913[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]11.6306[/C][C]1.36936[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.1272[/C][C]-1.52722[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]14.4909[/C][C]-1.29091[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]13.6882[/C][C]-3.7882[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.81327[/C][C]-0.113268[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.69633[/C][C]2.80367[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]14.3424[/C][C]-0.94238[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.6597[/C][C]-5.75975[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.04459[/C][C]-0.74459[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]10.1418[/C][C]0.158229[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]11.1958[/C][C]0.604193[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]10.5798[/C][C]0.620166[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]12.9029[/C][C]-1.50287[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.41505[/C][C]2.18495[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]10.9309[/C][C]2.26909[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]18.0736[/C][C]-5.47365[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.07373[/C][C]-1.47373[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]12.9652[/C][C]-3.06517[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]12.7488[/C][C]-3.94884[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.06807[/C][C]-1.36807[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]13.9367[/C][C]-4.93675[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]6.83622[/C][C]0.463782[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.16528[/C][C]2.23472[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]16.3691[/C][C]-2.76913[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]8.13303[/C][C]-0.233032[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]12.0497[/C][C]-1.34966[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.2603[/C][C]-1.96028[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.65298[/C][C]-1.35298[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]7.10265[/C][C]2.49735[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]16.0852[/C][C]-1.88518[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]5.632[/C][C]2.868[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]19.301[/C][C]-5.80104[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]8.65039[/C][C]-3.75039[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.21792[/C][C]-0.817919[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.78325[/C][C]0.816752[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.7803[/C][C]0.819695[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]16.6297[/C][C]-5.52969[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.19073[/C][C]0.159271[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.32243[/C][C]3.37757[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.2892[/C][C]2.81076[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.2572[/C][C]0.592763[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]13.9058[/C][C]2.69418[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]17.6689[/C][C]-5.06888[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]13.5808[/C][C]3.5192[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.5629[/C][C]-2.46292[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.2969[/C][C]2.80308[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]12.5477[/C][C]0.802329[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.6335[/C][C]3.76647[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]18.8221[/C][C]-4.12208[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.6691[/C][C]-1.06909[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.4357[/C][C]1.16427[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]20.1691[/C][C]-3.96909[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.4712[/C][C]3.12878[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.0816[/C][C]1.81843[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]11.3737[/C][C]2.72626[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]16.4443[/C][C]-1.94432[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.8416[/C][C]1.30836[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]14.1124[/C][C]0.63758[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.5781[/C][C]0.221918[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]14.4619[/C][C]-2.01192[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.01597[/C][C]3.63403[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]20.711[/C][C]-3.36101[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.82806[/C][C]0.771937[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]20.3675[/C][C]-1.96748[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]15.5462[/C][C]0.553783[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]5.81843[/C][C]5.78157[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]16.1648[/C][C]1.58516[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]13.767[/C][C]1.48301[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]16.3038[/C][C]1.34621[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]13.5688[/C][C]2.78116[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.9589[/C][C]0.69107[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.6711[/C][C]0.928941[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]17.2454[/C][C]-2.89544[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.7766[/C][C]1.97339[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]23.4699[/C][C]-5.21991[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.92976[/C][C]1.97024[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.37[/C][C]2.63004[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.6885[/C][C]-0.438537[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.687[/C][C]2.16296[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.4831[/C][C]0.116885[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.2022[/C][C]2.64783[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.8742[/C][C]1.07582[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]18.0651[/C][C]-2.46507[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.4331[/C][C]-0.583092[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.13067[/C][C]5.61933[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]19.8853[/C][C]-1.43531[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]12.8751[/C][C]3.02491[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.7399[/C][C]5.36009[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]10.9113[/C][C]5.18874[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]19.256[/C][C]0.643998[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]8.2566[/C][C]2.6934[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]13.761[/C][C]4.68902[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.5109[/C][C]-0.410939[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.6706[/C][C]-2.67064[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.3929[/C][C]0.957121[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.0757[/C][C]4.87426[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.2829[/C][C]1.81708[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.2117[/C][C]-0.611723[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.0117[/C][C]-0.611723[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]11.2908[/C][C]4.10916[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.0259[/C][C]-0.425903[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.849[/C][C]2.50095[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.7164[/C][C]2.38364[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]19.8658[/C][C]-4.51585[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.10404[/C][C]-0.504042[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.9399[/C][C]0.460086[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.9492[/C][C]1.95082[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.6098[/C][C]1.49022[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]14.2935[/C][C]0.956498[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.5673[/C][C]2.33274[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.9084[/C][C]5.1916[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.4206[/C][C]0.929382[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]10.7118[/C][C]2.4382[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.0552[/C][C]0.094777[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.6426[/C][C]-1.04258[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.55981[/C][C]2.79019[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]16.5857[/C][C]-1.18568[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.54703[/C][C]5.05297[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.6114[/C][C]1.58862[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]13.2781[/C][C]0.321926[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]17.06[/C][C]-2.21[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.458[/C][C]0.291955[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.4051[/C][C]3.69492[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.3171[/C][C]3.58292[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]14.4861[/C][C]1.76387[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.5032[/C][C]1.74676[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.2029[/C][C]0.397103[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.0605[/C][C]0.539497[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.9855[/C][C]0.664533[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.16166[/C][C]3.58834[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.9918[/C][C]-3.3918[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.16422[/C][C]1.68578[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]9.91346[/C][C]2.73654[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.78[/C][C]2.41998[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]15.2318[/C][C]1.36823[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]8.9436[/C][C]2.2564[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]18.4918[/C][C]-3.24179[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]14.434[/C][C]-2.53396[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]14.0582[/C][C]-0.858186[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.2538[/C][C]-0.903793[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.39974[/C][C]3.00026[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]12.6371[/C][C]3.21288[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.34[/C][C]-0.190017[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]10.9782[/C][C]0.171769[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]14.0896[/C][C]1.56037[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.4831[/C][C]-4.73306[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]7.07261[/C][C]0.577392[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.15635[/C][C]4.19365[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]12.5699[/C][C]3.03009[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.7836[/C][C]3.5164[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.4209[/C][C]3.77912[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.0319[/C][C]3.06806[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.2024[/C][C]3.39762[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]14.448[/C][C]3.95197[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.6509[/C][C]5.39908[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.3472[/C][C]2.20282[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]17.6674[/C][C]1.43258[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.3573[/C][C]-0.257281[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]14.782[/C][C]-1.932[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.0946[/C][C]-6.59458[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.06161[/C][C]1.43839[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]14.0708[/C][C]-2.2208[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]15.2051[/C][C]-1.60506[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]10.6273[/C][C]1.07266[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.8567[/C][C]-1.45667[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.7203[/C][C]-2.3703[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]8.05184[/C][C]3.34816[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]9.71126[/C][C]5.18874[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]20.3545[/C][C]-0.454547[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]12.0159[/C][C]-0.815945[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.9913[/C][C]1.60866[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]15.8866[/C][C]1.7134[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.2034[/C][C]0.846589[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.8552[/C][C]0.244841[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]13.81[/C][C]-0.460014[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]14.1809[/C][C]-2.33088[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.7835[/C][C]0.166491[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.6694[/C][C]2.08057[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.5761[/C][C]-0.426126[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]11.7301[/C][C]1.46988[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]19.0534[/C][C]-2.2034[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]14.7169[/C][C]-6.86693[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]6.50888[/C][C]1.19112[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]16.1377[/C][C]-3.53772[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]7.206[/C][C]0.643998[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]10.4814[/C][C]0.468616[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]14.878[/C][C]-2.52799[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]6.60184[/C][C]3.34816[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]12.7743[/C][C]2.12571[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.1397[/C][C]0.51031[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.7377[/C][C]0.662282[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]9.67891[/C][C]4.27109[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.0606[/C][C]4.63941[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]16.1778[/C][C]0.672212[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.18343[/C][C]3.76657[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.1748[/C][C]1.17521[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]11.103[/C][C]1.09696[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.7342[/C][C]1.36583[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.2399[/C][C]2.51011[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.8505[/C][C]1.34945[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]12.6159[/C][C]1.98405[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.2121[/C][C]-2.56211[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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
112.912.02160.878407
212.211.46610.733866
312.812.14610.653897
47.412.7678-5.36784
56.711.369-4.66896
612.615.345-2.74503
714.812.73772.06234
813.312.30930.990661
911.112.673-1.57297
108.214.2174-6.0174
1111.412.9544-1.55436
126.414.5984-8.19842
1310.611.546-0.945971
141213.6699-1.6699
156.39.71412-3.41412
1611.311.2820.0180104
1711.913.8768-1.97675
189.312.1091-2.80908
199.612.2696-2.66961
201011.5897-1.5897
216.411.7092-5.30919
2213.812.83270.967317
2310.813.3366-2.53662
2413.812.30981.4902
2511.712.6832-0.983184
2610.915.1346-4.2346
2716.113.39592.70414
2813.411.11612.28391
299.911.259-1.35898
3011.512.2051-0.705057
318.311.8817-3.5817
3211.713.3469-1.64694
33912.3182-3.31816
349.714.3635-4.66352
3510.812.5204-1.72036
3610.312.7608-2.46081
3710.411.732-1.33197
3812.712.65380.046152
399.312.2387-2.93871
4011.814.3192-2.51918
415.910.6133-4.71334
4211.413.9043-2.50431
431311.78671.21326
4410.812.6269-1.82686
4512.310.40911.8909
4611.313.4411-2.14106
4711.812.5246-0.724645
487.911.0928-3.19283
4912.710.09822.60182
5012.310.76971.53029
5111.611.9943-0.394348
526.710.9976-4.29757
5310.913.1453-2.24527
5412.112.6334-0.533412
5513.313.5058-0.20579
5610.113.3404-3.24041
575.711.6955-5.9955
5814.312.19892.10106
5989.43972-1.43972
6013.311.74731.55273
619.312.8125-3.51247
6212.511.60870.891287
637.610.7936-3.19357
6415.913.9011.99899
659.211.4281-2.22806
669.110.5158-1.41575
6711.114.1584-3.05839
681313.7681-0.768145
6914.512.86971.6303
7012.211.02791.17207
7112.313.5026-1.2026
7211.411.31590.0840945
738.811.2718-2.47179
7414.611.13163.46837
7512.612.9986-0.398628
76NANA-0.712913
771311.63061.36936
7812.614.1272-1.52722
7913.214.4909-1.29091
809.913.6882-3.7882
817.77.81327-0.113268
8210.57.696332.80367
8313.414.3424-0.94238
8410.916.6597-5.75975
854.35.04459-0.74459
8610.310.14180.158229
8711.811.19580.604193
8811.210.57980.620166
8911.412.9029-1.50287
908.66.415052.18495
9113.210.93092.26909
9212.618.0736-5.47365
935.67.07373-1.47373
949.912.9652-3.06517
958.812.7488-3.94884
967.79.06807-1.36807
97913.9367-4.93675
987.36.836220.463782
9911.49.165282.23472
10013.616.3691-2.76913
1017.98.13303-0.233032
10210.712.0497-1.34966
10310.312.2603-1.96028
1048.39.65298-1.35298
1059.67.102652.49735
10614.216.0852-1.88518
1078.55.6322.868
10813.519.301-5.80104
1094.98.65039-3.75039
1106.47.21792-0.817919
1119.68.783250.816752
11211.610.78030.819695
11311.116.6297-5.52969
1144.354.190730.159271
11512.79.322433.37757
11618.115.28922.81076
11717.8517.25720.592763
11816.613.90582.69418
11912.617.6689-5.06888
12017.113.58083.5192
12119.121.5629-2.46292
12216.113.29692.80308
12313.3512.54770.802329
12418.414.63353.76647
12514.718.8221-4.12208
12610.611.6691-1.06909
12712.611.43571.16427
12816.220.1691-3.96909
12913.610.47123.12878
13018.917.08161.81843
13114.111.37372.72626
13214.516.4443-1.94432
13316.1514.84161.30836
13414.7514.11240.63758
13514.814.57810.221918
13612.4514.4619-2.01192
13712.659.015973.63403
13817.3520.711-3.36101
1398.67.828060.771937
14018.420.3675-1.96748
14116.115.54620.553783
14211.65.818435.78157
14317.7516.16481.58516
14415.2513.7671.48301
14517.6516.30381.34621
14616.3513.56882.78116
14717.6516.95890.69107
14813.612.67110.928941
14914.3517.2454-2.89544
15014.7512.77661.97339
15118.2523.4699-5.21991
1529.97.929761.97024
1531613.372.63004
15418.2518.6885-0.438537
15516.8514.6872.16296
15614.614.48310.116885
15713.8511.20222.64783
15818.9517.87421.07582
15915.618.0651-2.46507
16014.8515.4331-0.583092
16111.756.130675.61933
16218.4519.8853-1.43531
16315.912.87513.02491
16417.111.73995.36009
16516.110.91135.18874
16619.919.2560.643998
16710.958.25662.6934
16818.4513.7614.68902
16915.115.5109-0.410939
1701517.6706-2.67064
17111.3510.39290.957121
17215.9511.07574.87426
17318.116.28291.81708
17414.615.2117-0.611723
17515.416.0117-0.611723
17615.411.29084.10916
17717.618.0259-0.425903
17813.3510.8492.50095
17919.116.71642.38364
18015.3519.8658-4.51585
1817.68.10404-0.504042
18213.412.93990.460086
18313.911.94921.95082
18419.117.60981.49022
18515.2514.29350.956498
18612.910.56732.33274
18716.110.90845.1916
18817.3516.42060.929382
18913.1510.71182.4382
19012.1512.05520.094777
19112.613.6426-1.04258
19210.357.559812.79019
19315.416.5857-1.18568
1949.64.547035.05297
19518.216.61141.58862
19613.613.27810.321926
19714.8517.06-2.21
19814.7514.4580.291955
19914.110.40513.69492
20014.911.31713.58292
20116.2514.48611.76387
20219.2517.50321.74676
20313.613.20290.397103
20413.613.06050.539497
20515.6514.98550.664533
20612.759.161663.58834
20714.617.9918-3.3918
2089.858.164221.68578
20912.659.913462.73654
21019.216.782.41998
21116.615.23181.36823
21211.28.94362.2564
21315.2518.4918-3.24179
21411.914.434-2.53396
21513.214.0582-0.858186
21616.3517.2538-0.903793
21712.49.399743.00026
21815.8512.63713.21288
21918.1518.34-0.190017
22011.1510.97820.171769
22115.6514.08961.56037
22217.7522.4831-4.73306
2237.657.072610.577392
22412.358.156354.19365
22515.612.56993.03009
22619.315.78363.5164
22715.211.42093.77912
22817.114.03193.06806
22915.612.20243.39762
23018.414.4483.95197
23119.0513.65095.39908
23218.5516.34722.20282
23319.117.66741.43258
23413.113.3573-0.257281
23512.8514.782-1.932
2369.516.0946-6.59458
2374.53.061611.43839
23811.8514.0708-2.2208
23913.615.2051-1.60506
24011.710.62731.07266
24112.413.8567-1.45667
24213.3515.7203-2.3703
24311.48.051843.34816
24414.99.711265.18874
24519.920.3545-0.454547
24611.212.0159-0.815945
24714.612.99131.60866
24817.615.88661.7134
24914.0513.20340.846589
25016.115.85520.244841
25113.3513.81-0.460014
25211.8514.1809-2.33088
25311.9511.78350.166491
25414.7512.66942.08057
25515.1515.5761-0.426126
25613.211.73011.46988
25716.8519.0534-2.2034
2587.8514.7169-6.86693
2597.76.508881.19112
26012.616.1377-3.53772
2617.857.2060.643998
26210.9510.48140.468616
26312.3514.878-2.52799
2649.956.601843.34816
26514.912.77432.12571
26616.6516.13970.51031
26713.412.73770.662282
26813.959.678914.27109
26915.711.06064.63941
27016.8516.17780.672212
27110.957.183433.76657
27215.3514.17481.17521
27312.211.1031.09696
27415.113.73421.36583
27517.7515.23992.51011
27615.213.85051.34945
27714.612.61591.98405
27816.6519.2121-2.56211
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.8555420.2889170.144458
90.8315710.3368580.168429
100.8402560.3194880.159744
110.7571720.4856550.242828
120.804950.3900990.19505
130.7386180.5227640.261382
140.654480.6910390.34552
150.5909160.8181690.409084
160.6102580.7794840.389742
170.5445410.9109190.455459
180.4654370.9308740.534563
190.3939420.7878850.606058
200.3230140.6460290.676986
210.3964990.7929980.603501
220.4128590.8257170.587141
230.3513970.7027930.648603
240.2922280.5844560.707772
250.2399580.4799170.760042
260.2068110.4136210.793189
270.1731010.3462020.826899
280.2279720.4559450.772028
290.2027080.4054160.797292
300.1818130.3636250.818187
310.1560980.3121950.843902
320.1544930.3089870.845507
330.1281210.2562420.871879
340.1320230.2640460.867977
350.1097030.2194070.890297
360.08972650.1794530.910273
370.07073020.141460.92927
380.08355220.1671040.916448
390.1021480.2042950.897852
400.09085290.1817060.909147
410.1432870.2865730.856713
420.1234720.2469430.876528
430.1084070.2168140.891593
440.09087290.1817460.909127
450.09434050.1886810.905659
460.0794080.1588160.920592
470.06588110.1317620.934119
480.08338120.1667620.916619
490.08231580.1646320.917684
500.08874180.1774840.911258
510.0760560.1521120.923944
520.08061880.1612380.919381
530.07317130.1463430.926829
540.07159360.1431870.928406
550.07262710.1452540.927373
560.0626020.1252040.937398
570.1123430.2246860.887657
580.1387710.2775420.861229
590.117610.235220.88239
600.1229290.2458580.877071
610.1371670.2743350.862833
620.1310430.2620850.868957
630.1388620.2777230.861138
640.1725690.3451380.827431
650.1717660.3435330.828234
660.1489250.297850.851075
670.1503970.3007940.849603
680.1378010.2756020.862199
690.1474690.2949370.852531
700.1360070.2720130.863993
710.1240160.2480330.875984
720.1092270.2184540.890773
730.09844780.1968960.901552
740.1041950.2083890.895805
750.09673860.1934770.903261
760.08945050.1789010.910549
770.08499550.1699910.915005
780.08426570.1685310.915734
790.07123160.1424630.928768
800.09225530.1845110.907745
810.07805070.1561010.921949
820.08697480.173950.913025
830.0743440.1486880.925656
840.1615550.3231090.838445
850.1479840.2959680.852016
860.129970.259940.87003
870.1122290.2244570.887771
880.09798880.1959780.902011
890.0922870.1845740.907713
900.09595010.19190.90405
910.1009270.2018540.899073
920.1709690.3419370.829031
930.1714230.3428460.828577
940.1664660.3329330.833534
950.1825010.3650020.817499
960.1774670.3549340.822533
970.244450.48890.75555
980.232480.4649610.76752
990.2755150.5510310.724485
1000.3311160.6622310.668884
1010.3054470.6108940.694553
1020.290470.5809410.70953
1030.2934950.5869910.706505
1040.3104160.6208320.689584
1050.3413630.6827260.658637
1060.3682190.7364380.631781
1070.385810.7716190.61419
1080.6058980.7882030.394102
1090.6526940.6946130.347306
1100.6627670.6744660.337233
1110.6571640.6856720.342836
1120.6450630.7098740.354937
1130.7848260.4303480.215174
1140.7802630.4394750.219737
1150.8723830.2552340.127617
1160.9122860.1754290.0877145
1170.9026140.1947720.0973858
1180.9111040.1777920.0888958
1190.9055310.1889390.0944693
1200.924010.151980.0759899
1210.9373280.1253440.0626718
1220.946920.106160.05308
1230.9497630.1004730.0502367
1240.9689890.06202140.0310107
1250.9733070.05338680.0266934
1260.9689510.06209890.0310495
1270.9683470.0633060.031653
1280.9685930.06281430.0314071
1290.9739550.05208990.0260449
1300.9729640.05407150.0270357
1310.9749040.05019170.0250959
1320.9737140.05257220.0262861
1330.9709350.05813070.0290653
1340.9662610.06747710.0337385
1350.960010.079980.03999
1360.9536640.09267270.0463363
1370.9673080.06538340.0326917
1380.9670610.06587790.0329389
1390.9638360.07232790.0361639
1400.9573290.08534180.0426709
1410.9500720.09985670.0499283
1420.9733850.05322940.0266147
1430.972380.05523910.0276195
1440.9724080.05518360.0275918
1450.9692170.06156510.0307826
1460.9698650.06027030.0301351
1470.9650910.06981790.034909
1480.9594810.08103790.0405189
1490.9544390.09112150.0455608
1500.9531980.09360330.0468017
1510.9826170.03476640.0173832
1520.9807310.03853860.0192693
1530.9814930.03701390.018507
1540.9776140.0447730.0223865
1550.9785310.0429370.0214685
1560.9740860.0518270.0259135
1570.9730730.0538540.026927
1580.9687380.0625240.031262
1590.9668360.0663280.033164
1600.9608490.07830160.0391508
1610.9732830.05343360.0267168
1620.9688070.0623860.031193
1630.9684030.06319490.0315974
1640.9934660.01306770.00653385
1650.9948710.01025850.00512923
1660.9934660.01306880.00653441
1670.9933440.01331190.00665596
1680.9957370.008526320.00426316
1690.9944970.01100510.00550257
1700.9948280.01034450.00517226
1710.9937670.0124650.0062325
1720.995720.00856050.00428025
1730.995230.009539660.00476983
1740.9940490.01190270.00595137
1750.9926640.01467140.0073357
1760.9938850.01223040.00611522
1770.9931290.01374170.00687085
1780.9930620.01387580.00693789
1790.9921170.01576690.00788344
1800.9940170.01196690.00598346
1810.9935550.01288970.00644487
1820.991950.01610080.00805041
1830.9906450.01871040.00935519
1840.9883870.02322630.0116132
1850.9874770.02504690.0125235
1860.9853380.02932410.0146621
1870.9921240.01575190.00787593
1880.9903620.01927650.00963826
1890.9886410.02271820.0113591
1900.9855790.02884160.0144208
1910.9823340.03533270.0176664
1920.9794610.04107860.0205393
1930.9766580.04668330.0233417
1940.9852830.02943410.014717
1950.9824470.03510540.0175527
1960.9796390.04072110.0203606
1970.9798910.04021730.0201086
1980.9746910.05061730.0253086
1990.9785260.04294830.0214741
2000.978020.04396070.0219803
2010.974980.05003990.02502
2020.9733720.05325620.0266281
2030.9698910.06021890.0301095
2040.9631050.07379030.0368951
2050.9549930.09001360.0450068
2060.9651290.06974140.0348707
2070.9622540.07549180.0377459
2080.960530.07893960.0394698
2090.9561910.08761830.0438092
2100.9518090.09638250.0481913
2110.9425240.1149520.0574762
2120.9323390.1353210.0676605
2130.9468040.1063930.0531964
2140.9373370.1253270.0626634
2150.9346730.1306540.0653272
2160.9236170.1527650.0763825
2170.9205250.1589490.0794747
2180.9110310.1779390.0889693
2190.8918220.2163570.108178
2200.8696640.2606710.130336
2210.8536630.2926750.146337
2220.8738930.2522140.126107
2230.8491470.3017060.150853
2240.8578880.2842240.142112
2250.84490.3102010.1551
2260.8967480.2065040.103252
2270.9192040.1615920.0807961
2280.9261020.1477950.0738976
2290.9142970.1714060.0857028
2300.9292980.1414050.0707024
2310.953210.09358030.0467902
2320.9409540.1180920.059046
2330.9299020.1401960.0700982
2340.9195510.1608970.0804485
2350.9113430.1773150.0886573
2360.9712390.05752190.028761
2370.9699680.06006440.0300322
2380.9718970.0562060.028103
2390.9638110.07237720.0361886
2400.9518980.09620370.0481019
2410.9427780.1144440.0572222
2420.9298280.1403440.0701722
2430.9252850.1494310.0747154
2440.9155090.1689830.0844914
2450.8904960.2190080.109504
2460.8644530.2710940.135547
2470.8345860.3308270.165414
2480.8012040.3975920.198796
2490.7570670.4858660.242933
2500.704850.59030.29515
2510.660540.6789190.33946
2520.6608350.678330.339165
2530.5984470.8031050.401553
2540.5354670.9290660.464533
2550.591870.8162590.40813
2560.5275790.9448420.472421
2570.528450.94310.47155
2580.917190.1656190.0828095
2590.8810720.2378550.118928
2600.9953170.009365270.00468264
2610.9977350.004529760.00226488
2620.9979620.004075730.00203786
2630.9998270.0003463470.000173174
2640.999480.001039420.000519709
2650.9990320.001936350.000968176
2660.9980290.003942660.00197133
2670.9980520.003896670.00194833
2680.9944160.01116850.00558425
2690.9906290.01874240.0093712
2700.9635940.07281120.0364056
2710.9662060.06758770.0337939

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.855542 & 0.288917 & 0.144458 \tabularnewline
9 & 0.831571 & 0.336858 & 0.168429 \tabularnewline
10 & 0.840256 & 0.319488 & 0.159744 \tabularnewline
11 & 0.757172 & 0.485655 & 0.242828 \tabularnewline
12 & 0.80495 & 0.390099 & 0.19505 \tabularnewline
13 & 0.738618 & 0.522764 & 0.261382 \tabularnewline
14 & 0.65448 & 0.691039 & 0.34552 \tabularnewline
15 & 0.590916 & 0.818169 & 0.409084 \tabularnewline
16 & 0.610258 & 0.779484 & 0.389742 \tabularnewline
17 & 0.544541 & 0.910919 & 0.455459 \tabularnewline
18 & 0.465437 & 0.930874 & 0.534563 \tabularnewline
19 & 0.393942 & 0.787885 & 0.606058 \tabularnewline
20 & 0.323014 & 0.646029 & 0.676986 \tabularnewline
21 & 0.396499 & 0.792998 & 0.603501 \tabularnewline
22 & 0.412859 & 0.825717 & 0.587141 \tabularnewline
23 & 0.351397 & 0.702793 & 0.648603 \tabularnewline
24 & 0.292228 & 0.584456 & 0.707772 \tabularnewline
25 & 0.239958 & 0.479917 & 0.760042 \tabularnewline
26 & 0.206811 & 0.413621 & 0.793189 \tabularnewline
27 & 0.173101 & 0.346202 & 0.826899 \tabularnewline
28 & 0.227972 & 0.455945 & 0.772028 \tabularnewline
29 & 0.202708 & 0.405416 & 0.797292 \tabularnewline
30 & 0.181813 & 0.363625 & 0.818187 \tabularnewline
31 & 0.156098 & 0.312195 & 0.843902 \tabularnewline
32 & 0.154493 & 0.308987 & 0.845507 \tabularnewline
33 & 0.128121 & 0.256242 & 0.871879 \tabularnewline
34 & 0.132023 & 0.264046 & 0.867977 \tabularnewline
35 & 0.109703 & 0.219407 & 0.890297 \tabularnewline
36 & 0.0897265 & 0.179453 & 0.910273 \tabularnewline
37 & 0.0707302 & 0.14146 & 0.92927 \tabularnewline
38 & 0.0835522 & 0.167104 & 0.916448 \tabularnewline
39 & 0.102148 & 0.204295 & 0.897852 \tabularnewline
40 & 0.0908529 & 0.181706 & 0.909147 \tabularnewline
41 & 0.143287 & 0.286573 & 0.856713 \tabularnewline
42 & 0.123472 & 0.246943 & 0.876528 \tabularnewline
43 & 0.108407 & 0.216814 & 0.891593 \tabularnewline
44 & 0.0908729 & 0.181746 & 0.909127 \tabularnewline
45 & 0.0943405 & 0.188681 & 0.905659 \tabularnewline
46 & 0.079408 & 0.158816 & 0.920592 \tabularnewline
47 & 0.0658811 & 0.131762 & 0.934119 \tabularnewline
48 & 0.0833812 & 0.166762 & 0.916619 \tabularnewline
49 & 0.0823158 & 0.164632 & 0.917684 \tabularnewline
50 & 0.0887418 & 0.177484 & 0.911258 \tabularnewline
51 & 0.076056 & 0.152112 & 0.923944 \tabularnewline
52 & 0.0806188 & 0.161238 & 0.919381 \tabularnewline
53 & 0.0731713 & 0.146343 & 0.926829 \tabularnewline
54 & 0.0715936 & 0.143187 & 0.928406 \tabularnewline
55 & 0.0726271 & 0.145254 & 0.927373 \tabularnewline
56 & 0.062602 & 0.125204 & 0.937398 \tabularnewline
57 & 0.112343 & 0.224686 & 0.887657 \tabularnewline
58 & 0.138771 & 0.277542 & 0.861229 \tabularnewline
59 & 0.11761 & 0.23522 & 0.88239 \tabularnewline
60 & 0.122929 & 0.245858 & 0.877071 \tabularnewline
61 & 0.137167 & 0.274335 & 0.862833 \tabularnewline
62 & 0.131043 & 0.262085 & 0.868957 \tabularnewline
63 & 0.138862 & 0.277723 & 0.861138 \tabularnewline
64 & 0.172569 & 0.345138 & 0.827431 \tabularnewline
65 & 0.171766 & 0.343533 & 0.828234 \tabularnewline
66 & 0.148925 & 0.29785 & 0.851075 \tabularnewline
67 & 0.150397 & 0.300794 & 0.849603 \tabularnewline
68 & 0.137801 & 0.275602 & 0.862199 \tabularnewline
69 & 0.147469 & 0.294937 & 0.852531 \tabularnewline
70 & 0.136007 & 0.272013 & 0.863993 \tabularnewline
71 & 0.124016 & 0.248033 & 0.875984 \tabularnewline
72 & 0.109227 & 0.218454 & 0.890773 \tabularnewline
73 & 0.0984478 & 0.196896 & 0.901552 \tabularnewline
74 & 0.104195 & 0.208389 & 0.895805 \tabularnewline
75 & 0.0967386 & 0.193477 & 0.903261 \tabularnewline
76 & 0.0894505 & 0.178901 & 0.910549 \tabularnewline
77 & 0.0849955 & 0.169991 & 0.915005 \tabularnewline
78 & 0.0842657 & 0.168531 & 0.915734 \tabularnewline
79 & 0.0712316 & 0.142463 & 0.928768 \tabularnewline
80 & 0.0922553 & 0.184511 & 0.907745 \tabularnewline
81 & 0.0780507 & 0.156101 & 0.921949 \tabularnewline
82 & 0.0869748 & 0.17395 & 0.913025 \tabularnewline
83 & 0.074344 & 0.148688 & 0.925656 \tabularnewline
84 & 0.161555 & 0.323109 & 0.838445 \tabularnewline
85 & 0.147984 & 0.295968 & 0.852016 \tabularnewline
86 & 0.12997 & 0.25994 & 0.87003 \tabularnewline
87 & 0.112229 & 0.224457 & 0.887771 \tabularnewline
88 & 0.0979888 & 0.195978 & 0.902011 \tabularnewline
89 & 0.092287 & 0.184574 & 0.907713 \tabularnewline
90 & 0.0959501 & 0.1919 & 0.90405 \tabularnewline
91 & 0.100927 & 0.201854 & 0.899073 \tabularnewline
92 & 0.170969 & 0.341937 & 0.829031 \tabularnewline
93 & 0.171423 & 0.342846 & 0.828577 \tabularnewline
94 & 0.166466 & 0.332933 & 0.833534 \tabularnewline
95 & 0.182501 & 0.365002 & 0.817499 \tabularnewline
96 & 0.177467 & 0.354934 & 0.822533 \tabularnewline
97 & 0.24445 & 0.4889 & 0.75555 \tabularnewline
98 & 0.23248 & 0.464961 & 0.76752 \tabularnewline
99 & 0.275515 & 0.551031 & 0.724485 \tabularnewline
100 & 0.331116 & 0.662231 & 0.668884 \tabularnewline
101 & 0.305447 & 0.610894 & 0.694553 \tabularnewline
102 & 0.29047 & 0.580941 & 0.70953 \tabularnewline
103 & 0.293495 & 0.586991 & 0.706505 \tabularnewline
104 & 0.310416 & 0.620832 & 0.689584 \tabularnewline
105 & 0.341363 & 0.682726 & 0.658637 \tabularnewline
106 & 0.368219 & 0.736438 & 0.631781 \tabularnewline
107 & 0.38581 & 0.771619 & 0.61419 \tabularnewline
108 & 0.605898 & 0.788203 & 0.394102 \tabularnewline
109 & 0.652694 & 0.694613 & 0.347306 \tabularnewline
110 & 0.662767 & 0.674466 & 0.337233 \tabularnewline
111 & 0.657164 & 0.685672 & 0.342836 \tabularnewline
112 & 0.645063 & 0.709874 & 0.354937 \tabularnewline
113 & 0.784826 & 0.430348 & 0.215174 \tabularnewline
114 & 0.780263 & 0.439475 & 0.219737 \tabularnewline
115 & 0.872383 & 0.255234 & 0.127617 \tabularnewline
116 & 0.912286 & 0.175429 & 0.0877145 \tabularnewline
117 & 0.902614 & 0.194772 & 0.0973858 \tabularnewline
118 & 0.911104 & 0.177792 & 0.0888958 \tabularnewline
119 & 0.905531 & 0.188939 & 0.0944693 \tabularnewline
120 & 0.92401 & 0.15198 & 0.0759899 \tabularnewline
121 & 0.937328 & 0.125344 & 0.0626718 \tabularnewline
122 & 0.94692 & 0.10616 & 0.05308 \tabularnewline
123 & 0.949763 & 0.100473 & 0.0502367 \tabularnewline
124 & 0.968989 & 0.0620214 & 0.0310107 \tabularnewline
125 & 0.973307 & 0.0533868 & 0.0266934 \tabularnewline
126 & 0.968951 & 0.0620989 & 0.0310495 \tabularnewline
127 & 0.968347 & 0.063306 & 0.031653 \tabularnewline
128 & 0.968593 & 0.0628143 & 0.0314071 \tabularnewline
129 & 0.973955 & 0.0520899 & 0.0260449 \tabularnewline
130 & 0.972964 & 0.0540715 & 0.0270357 \tabularnewline
131 & 0.974904 & 0.0501917 & 0.0250959 \tabularnewline
132 & 0.973714 & 0.0525722 & 0.0262861 \tabularnewline
133 & 0.970935 & 0.0581307 & 0.0290653 \tabularnewline
134 & 0.966261 & 0.0674771 & 0.0337385 \tabularnewline
135 & 0.96001 & 0.07998 & 0.03999 \tabularnewline
136 & 0.953664 & 0.0926727 & 0.0463363 \tabularnewline
137 & 0.967308 & 0.0653834 & 0.0326917 \tabularnewline
138 & 0.967061 & 0.0658779 & 0.0329389 \tabularnewline
139 & 0.963836 & 0.0723279 & 0.0361639 \tabularnewline
140 & 0.957329 & 0.0853418 & 0.0426709 \tabularnewline
141 & 0.950072 & 0.0998567 & 0.0499283 \tabularnewline
142 & 0.973385 & 0.0532294 & 0.0266147 \tabularnewline
143 & 0.97238 & 0.0552391 & 0.0276195 \tabularnewline
144 & 0.972408 & 0.0551836 & 0.0275918 \tabularnewline
145 & 0.969217 & 0.0615651 & 0.0307826 \tabularnewline
146 & 0.969865 & 0.0602703 & 0.0301351 \tabularnewline
147 & 0.965091 & 0.0698179 & 0.034909 \tabularnewline
148 & 0.959481 & 0.0810379 & 0.0405189 \tabularnewline
149 & 0.954439 & 0.0911215 & 0.0455608 \tabularnewline
150 & 0.953198 & 0.0936033 & 0.0468017 \tabularnewline
151 & 0.982617 & 0.0347664 & 0.0173832 \tabularnewline
152 & 0.980731 & 0.0385386 & 0.0192693 \tabularnewline
153 & 0.981493 & 0.0370139 & 0.018507 \tabularnewline
154 & 0.977614 & 0.044773 & 0.0223865 \tabularnewline
155 & 0.978531 & 0.042937 & 0.0214685 \tabularnewline
156 & 0.974086 & 0.051827 & 0.0259135 \tabularnewline
157 & 0.973073 & 0.053854 & 0.026927 \tabularnewline
158 & 0.968738 & 0.062524 & 0.031262 \tabularnewline
159 & 0.966836 & 0.066328 & 0.033164 \tabularnewline
160 & 0.960849 & 0.0783016 & 0.0391508 \tabularnewline
161 & 0.973283 & 0.0534336 & 0.0267168 \tabularnewline
162 & 0.968807 & 0.062386 & 0.031193 \tabularnewline
163 & 0.968403 & 0.0631949 & 0.0315974 \tabularnewline
164 & 0.993466 & 0.0130677 & 0.00653385 \tabularnewline
165 & 0.994871 & 0.0102585 & 0.00512923 \tabularnewline
166 & 0.993466 & 0.0130688 & 0.00653441 \tabularnewline
167 & 0.993344 & 0.0133119 & 0.00665596 \tabularnewline
168 & 0.995737 & 0.00852632 & 0.00426316 \tabularnewline
169 & 0.994497 & 0.0110051 & 0.00550257 \tabularnewline
170 & 0.994828 & 0.0103445 & 0.00517226 \tabularnewline
171 & 0.993767 & 0.012465 & 0.0062325 \tabularnewline
172 & 0.99572 & 0.0085605 & 0.00428025 \tabularnewline
173 & 0.99523 & 0.00953966 & 0.00476983 \tabularnewline
174 & 0.994049 & 0.0119027 & 0.00595137 \tabularnewline
175 & 0.992664 & 0.0146714 & 0.0073357 \tabularnewline
176 & 0.993885 & 0.0122304 & 0.00611522 \tabularnewline
177 & 0.993129 & 0.0137417 & 0.00687085 \tabularnewline
178 & 0.993062 & 0.0138758 & 0.00693789 \tabularnewline
179 & 0.992117 & 0.0157669 & 0.00788344 \tabularnewline
180 & 0.994017 & 0.0119669 & 0.00598346 \tabularnewline
181 & 0.993555 & 0.0128897 & 0.00644487 \tabularnewline
182 & 0.99195 & 0.0161008 & 0.00805041 \tabularnewline
183 & 0.990645 & 0.0187104 & 0.00935519 \tabularnewline
184 & 0.988387 & 0.0232263 & 0.0116132 \tabularnewline
185 & 0.987477 & 0.0250469 & 0.0125235 \tabularnewline
186 & 0.985338 & 0.0293241 & 0.0146621 \tabularnewline
187 & 0.992124 & 0.0157519 & 0.00787593 \tabularnewline
188 & 0.990362 & 0.0192765 & 0.00963826 \tabularnewline
189 & 0.988641 & 0.0227182 & 0.0113591 \tabularnewline
190 & 0.985579 & 0.0288416 & 0.0144208 \tabularnewline
191 & 0.982334 & 0.0353327 & 0.0176664 \tabularnewline
192 & 0.979461 & 0.0410786 & 0.0205393 \tabularnewline
193 & 0.976658 & 0.0466833 & 0.0233417 \tabularnewline
194 & 0.985283 & 0.0294341 & 0.014717 \tabularnewline
195 & 0.982447 & 0.0351054 & 0.0175527 \tabularnewline
196 & 0.979639 & 0.0407211 & 0.0203606 \tabularnewline
197 & 0.979891 & 0.0402173 & 0.0201086 \tabularnewline
198 & 0.974691 & 0.0506173 & 0.0253086 \tabularnewline
199 & 0.978526 & 0.0429483 & 0.0214741 \tabularnewline
200 & 0.97802 & 0.0439607 & 0.0219803 \tabularnewline
201 & 0.97498 & 0.0500399 & 0.02502 \tabularnewline
202 & 0.973372 & 0.0532562 & 0.0266281 \tabularnewline
203 & 0.969891 & 0.0602189 & 0.0301095 \tabularnewline
204 & 0.963105 & 0.0737903 & 0.0368951 \tabularnewline
205 & 0.954993 & 0.0900136 & 0.0450068 \tabularnewline
206 & 0.965129 & 0.0697414 & 0.0348707 \tabularnewline
207 & 0.962254 & 0.0754918 & 0.0377459 \tabularnewline
208 & 0.96053 & 0.0789396 & 0.0394698 \tabularnewline
209 & 0.956191 & 0.0876183 & 0.0438092 \tabularnewline
210 & 0.951809 & 0.0963825 & 0.0481913 \tabularnewline
211 & 0.942524 & 0.114952 & 0.0574762 \tabularnewline
212 & 0.932339 & 0.135321 & 0.0676605 \tabularnewline
213 & 0.946804 & 0.106393 & 0.0531964 \tabularnewline
214 & 0.937337 & 0.125327 & 0.0626634 \tabularnewline
215 & 0.934673 & 0.130654 & 0.0653272 \tabularnewline
216 & 0.923617 & 0.152765 & 0.0763825 \tabularnewline
217 & 0.920525 & 0.158949 & 0.0794747 \tabularnewline
218 & 0.911031 & 0.177939 & 0.0889693 \tabularnewline
219 & 0.891822 & 0.216357 & 0.108178 \tabularnewline
220 & 0.869664 & 0.260671 & 0.130336 \tabularnewline
221 & 0.853663 & 0.292675 & 0.146337 \tabularnewline
222 & 0.873893 & 0.252214 & 0.126107 \tabularnewline
223 & 0.849147 & 0.301706 & 0.150853 \tabularnewline
224 & 0.857888 & 0.284224 & 0.142112 \tabularnewline
225 & 0.8449 & 0.310201 & 0.1551 \tabularnewline
226 & 0.896748 & 0.206504 & 0.103252 \tabularnewline
227 & 0.919204 & 0.161592 & 0.0807961 \tabularnewline
228 & 0.926102 & 0.147795 & 0.0738976 \tabularnewline
229 & 0.914297 & 0.171406 & 0.0857028 \tabularnewline
230 & 0.929298 & 0.141405 & 0.0707024 \tabularnewline
231 & 0.95321 & 0.0935803 & 0.0467902 \tabularnewline
232 & 0.940954 & 0.118092 & 0.059046 \tabularnewline
233 & 0.929902 & 0.140196 & 0.0700982 \tabularnewline
234 & 0.919551 & 0.160897 & 0.0804485 \tabularnewline
235 & 0.911343 & 0.177315 & 0.0886573 \tabularnewline
236 & 0.971239 & 0.0575219 & 0.028761 \tabularnewline
237 & 0.969968 & 0.0600644 & 0.0300322 \tabularnewline
238 & 0.971897 & 0.056206 & 0.028103 \tabularnewline
239 & 0.963811 & 0.0723772 & 0.0361886 \tabularnewline
240 & 0.951898 & 0.0962037 & 0.0481019 \tabularnewline
241 & 0.942778 & 0.114444 & 0.0572222 \tabularnewline
242 & 0.929828 & 0.140344 & 0.0701722 \tabularnewline
243 & 0.925285 & 0.149431 & 0.0747154 \tabularnewline
244 & 0.915509 & 0.168983 & 0.0844914 \tabularnewline
245 & 0.890496 & 0.219008 & 0.109504 \tabularnewline
246 & 0.864453 & 0.271094 & 0.135547 \tabularnewline
247 & 0.834586 & 0.330827 & 0.165414 \tabularnewline
248 & 0.801204 & 0.397592 & 0.198796 \tabularnewline
249 & 0.757067 & 0.485866 & 0.242933 \tabularnewline
250 & 0.70485 & 0.5903 & 0.29515 \tabularnewline
251 & 0.66054 & 0.678919 & 0.33946 \tabularnewline
252 & 0.660835 & 0.67833 & 0.339165 \tabularnewline
253 & 0.598447 & 0.803105 & 0.401553 \tabularnewline
254 & 0.535467 & 0.929066 & 0.464533 \tabularnewline
255 & 0.59187 & 0.816259 & 0.40813 \tabularnewline
256 & 0.527579 & 0.944842 & 0.472421 \tabularnewline
257 & 0.52845 & 0.9431 & 0.47155 \tabularnewline
258 & 0.91719 & 0.165619 & 0.0828095 \tabularnewline
259 & 0.881072 & 0.237855 & 0.118928 \tabularnewline
260 & 0.995317 & 0.00936527 & 0.00468264 \tabularnewline
261 & 0.997735 & 0.00452976 & 0.00226488 \tabularnewline
262 & 0.997962 & 0.00407573 & 0.00203786 \tabularnewline
263 & 0.999827 & 0.000346347 & 0.000173174 \tabularnewline
264 & 0.99948 & 0.00103942 & 0.000519709 \tabularnewline
265 & 0.999032 & 0.00193635 & 0.000968176 \tabularnewline
266 & 0.998029 & 0.00394266 & 0.00197133 \tabularnewline
267 & 0.998052 & 0.00389667 & 0.00194833 \tabularnewline
268 & 0.994416 & 0.0111685 & 0.00558425 \tabularnewline
269 & 0.990629 & 0.0187424 & 0.0093712 \tabularnewline
270 & 0.963594 & 0.0728112 & 0.0364056 \tabularnewline
271 & 0.966206 & 0.0675877 & 0.0337939 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&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]8[/C][C]0.855542[/C][C]0.288917[/C][C]0.144458[/C][/ROW]
[ROW][C]9[/C][C]0.831571[/C][C]0.336858[/C][C]0.168429[/C][/ROW]
[ROW][C]10[/C][C]0.840256[/C][C]0.319488[/C][C]0.159744[/C][/ROW]
[ROW][C]11[/C][C]0.757172[/C][C]0.485655[/C][C]0.242828[/C][/ROW]
[ROW][C]12[/C][C]0.80495[/C][C]0.390099[/C][C]0.19505[/C][/ROW]
[ROW][C]13[/C][C]0.738618[/C][C]0.522764[/C][C]0.261382[/C][/ROW]
[ROW][C]14[/C][C]0.65448[/C][C]0.691039[/C][C]0.34552[/C][/ROW]
[ROW][C]15[/C][C]0.590916[/C][C]0.818169[/C][C]0.409084[/C][/ROW]
[ROW][C]16[/C][C]0.610258[/C][C]0.779484[/C][C]0.389742[/C][/ROW]
[ROW][C]17[/C][C]0.544541[/C][C]0.910919[/C][C]0.455459[/C][/ROW]
[ROW][C]18[/C][C]0.465437[/C][C]0.930874[/C][C]0.534563[/C][/ROW]
[ROW][C]19[/C][C]0.393942[/C][C]0.787885[/C][C]0.606058[/C][/ROW]
[ROW][C]20[/C][C]0.323014[/C][C]0.646029[/C][C]0.676986[/C][/ROW]
[ROW][C]21[/C][C]0.396499[/C][C]0.792998[/C][C]0.603501[/C][/ROW]
[ROW][C]22[/C][C]0.412859[/C][C]0.825717[/C][C]0.587141[/C][/ROW]
[ROW][C]23[/C][C]0.351397[/C][C]0.702793[/C][C]0.648603[/C][/ROW]
[ROW][C]24[/C][C]0.292228[/C][C]0.584456[/C][C]0.707772[/C][/ROW]
[ROW][C]25[/C][C]0.239958[/C][C]0.479917[/C][C]0.760042[/C][/ROW]
[ROW][C]26[/C][C]0.206811[/C][C]0.413621[/C][C]0.793189[/C][/ROW]
[ROW][C]27[/C][C]0.173101[/C][C]0.346202[/C][C]0.826899[/C][/ROW]
[ROW][C]28[/C][C]0.227972[/C][C]0.455945[/C][C]0.772028[/C][/ROW]
[ROW][C]29[/C][C]0.202708[/C][C]0.405416[/C][C]0.797292[/C][/ROW]
[ROW][C]30[/C][C]0.181813[/C][C]0.363625[/C][C]0.818187[/C][/ROW]
[ROW][C]31[/C][C]0.156098[/C][C]0.312195[/C][C]0.843902[/C][/ROW]
[ROW][C]32[/C][C]0.154493[/C][C]0.308987[/C][C]0.845507[/C][/ROW]
[ROW][C]33[/C][C]0.128121[/C][C]0.256242[/C][C]0.871879[/C][/ROW]
[ROW][C]34[/C][C]0.132023[/C][C]0.264046[/C][C]0.867977[/C][/ROW]
[ROW][C]35[/C][C]0.109703[/C][C]0.219407[/C][C]0.890297[/C][/ROW]
[ROW][C]36[/C][C]0.0897265[/C][C]0.179453[/C][C]0.910273[/C][/ROW]
[ROW][C]37[/C][C]0.0707302[/C][C]0.14146[/C][C]0.92927[/C][/ROW]
[ROW][C]38[/C][C]0.0835522[/C][C]0.167104[/C][C]0.916448[/C][/ROW]
[ROW][C]39[/C][C]0.102148[/C][C]0.204295[/C][C]0.897852[/C][/ROW]
[ROW][C]40[/C][C]0.0908529[/C][C]0.181706[/C][C]0.909147[/C][/ROW]
[ROW][C]41[/C][C]0.143287[/C][C]0.286573[/C][C]0.856713[/C][/ROW]
[ROW][C]42[/C][C]0.123472[/C][C]0.246943[/C][C]0.876528[/C][/ROW]
[ROW][C]43[/C][C]0.108407[/C][C]0.216814[/C][C]0.891593[/C][/ROW]
[ROW][C]44[/C][C]0.0908729[/C][C]0.181746[/C][C]0.909127[/C][/ROW]
[ROW][C]45[/C][C]0.0943405[/C][C]0.188681[/C][C]0.905659[/C][/ROW]
[ROW][C]46[/C][C]0.079408[/C][C]0.158816[/C][C]0.920592[/C][/ROW]
[ROW][C]47[/C][C]0.0658811[/C][C]0.131762[/C][C]0.934119[/C][/ROW]
[ROW][C]48[/C][C]0.0833812[/C][C]0.166762[/C][C]0.916619[/C][/ROW]
[ROW][C]49[/C][C]0.0823158[/C][C]0.164632[/C][C]0.917684[/C][/ROW]
[ROW][C]50[/C][C]0.0887418[/C][C]0.177484[/C][C]0.911258[/C][/ROW]
[ROW][C]51[/C][C]0.076056[/C][C]0.152112[/C][C]0.923944[/C][/ROW]
[ROW][C]52[/C][C]0.0806188[/C][C]0.161238[/C][C]0.919381[/C][/ROW]
[ROW][C]53[/C][C]0.0731713[/C][C]0.146343[/C][C]0.926829[/C][/ROW]
[ROW][C]54[/C][C]0.0715936[/C][C]0.143187[/C][C]0.928406[/C][/ROW]
[ROW][C]55[/C][C]0.0726271[/C][C]0.145254[/C][C]0.927373[/C][/ROW]
[ROW][C]56[/C][C]0.062602[/C][C]0.125204[/C][C]0.937398[/C][/ROW]
[ROW][C]57[/C][C]0.112343[/C][C]0.224686[/C][C]0.887657[/C][/ROW]
[ROW][C]58[/C][C]0.138771[/C][C]0.277542[/C][C]0.861229[/C][/ROW]
[ROW][C]59[/C][C]0.11761[/C][C]0.23522[/C][C]0.88239[/C][/ROW]
[ROW][C]60[/C][C]0.122929[/C][C]0.245858[/C][C]0.877071[/C][/ROW]
[ROW][C]61[/C][C]0.137167[/C][C]0.274335[/C][C]0.862833[/C][/ROW]
[ROW][C]62[/C][C]0.131043[/C][C]0.262085[/C][C]0.868957[/C][/ROW]
[ROW][C]63[/C][C]0.138862[/C][C]0.277723[/C][C]0.861138[/C][/ROW]
[ROW][C]64[/C][C]0.172569[/C][C]0.345138[/C][C]0.827431[/C][/ROW]
[ROW][C]65[/C][C]0.171766[/C][C]0.343533[/C][C]0.828234[/C][/ROW]
[ROW][C]66[/C][C]0.148925[/C][C]0.29785[/C][C]0.851075[/C][/ROW]
[ROW][C]67[/C][C]0.150397[/C][C]0.300794[/C][C]0.849603[/C][/ROW]
[ROW][C]68[/C][C]0.137801[/C][C]0.275602[/C][C]0.862199[/C][/ROW]
[ROW][C]69[/C][C]0.147469[/C][C]0.294937[/C][C]0.852531[/C][/ROW]
[ROW][C]70[/C][C]0.136007[/C][C]0.272013[/C][C]0.863993[/C][/ROW]
[ROW][C]71[/C][C]0.124016[/C][C]0.248033[/C][C]0.875984[/C][/ROW]
[ROW][C]72[/C][C]0.109227[/C][C]0.218454[/C][C]0.890773[/C][/ROW]
[ROW][C]73[/C][C]0.0984478[/C][C]0.196896[/C][C]0.901552[/C][/ROW]
[ROW][C]74[/C][C]0.104195[/C][C]0.208389[/C][C]0.895805[/C][/ROW]
[ROW][C]75[/C][C]0.0967386[/C][C]0.193477[/C][C]0.903261[/C][/ROW]
[ROW][C]76[/C][C]0.0894505[/C][C]0.178901[/C][C]0.910549[/C][/ROW]
[ROW][C]77[/C][C]0.0849955[/C][C]0.169991[/C][C]0.915005[/C][/ROW]
[ROW][C]78[/C][C]0.0842657[/C][C]0.168531[/C][C]0.915734[/C][/ROW]
[ROW][C]79[/C][C]0.0712316[/C][C]0.142463[/C][C]0.928768[/C][/ROW]
[ROW][C]80[/C][C]0.0922553[/C][C]0.184511[/C][C]0.907745[/C][/ROW]
[ROW][C]81[/C][C]0.0780507[/C][C]0.156101[/C][C]0.921949[/C][/ROW]
[ROW][C]82[/C][C]0.0869748[/C][C]0.17395[/C][C]0.913025[/C][/ROW]
[ROW][C]83[/C][C]0.074344[/C][C]0.148688[/C][C]0.925656[/C][/ROW]
[ROW][C]84[/C][C]0.161555[/C][C]0.323109[/C][C]0.838445[/C][/ROW]
[ROW][C]85[/C][C]0.147984[/C][C]0.295968[/C][C]0.852016[/C][/ROW]
[ROW][C]86[/C][C]0.12997[/C][C]0.25994[/C][C]0.87003[/C][/ROW]
[ROW][C]87[/C][C]0.112229[/C][C]0.224457[/C][C]0.887771[/C][/ROW]
[ROW][C]88[/C][C]0.0979888[/C][C]0.195978[/C][C]0.902011[/C][/ROW]
[ROW][C]89[/C][C]0.092287[/C][C]0.184574[/C][C]0.907713[/C][/ROW]
[ROW][C]90[/C][C]0.0959501[/C][C]0.1919[/C][C]0.90405[/C][/ROW]
[ROW][C]91[/C][C]0.100927[/C][C]0.201854[/C][C]0.899073[/C][/ROW]
[ROW][C]92[/C][C]0.170969[/C][C]0.341937[/C][C]0.829031[/C][/ROW]
[ROW][C]93[/C][C]0.171423[/C][C]0.342846[/C][C]0.828577[/C][/ROW]
[ROW][C]94[/C][C]0.166466[/C][C]0.332933[/C][C]0.833534[/C][/ROW]
[ROW][C]95[/C][C]0.182501[/C][C]0.365002[/C][C]0.817499[/C][/ROW]
[ROW][C]96[/C][C]0.177467[/C][C]0.354934[/C][C]0.822533[/C][/ROW]
[ROW][C]97[/C][C]0.24445[/C][C]0.4889[/C][C]0.75555[/C][/ROW]
[ROW][C]98[/C][C]0.23248[/C][C]0.464961[/C][C]0.76752[/C][/ROW]
[ROW][C]99[/C][C]0.275515[/C][C]0.551031[/C][C]0.724485[/C][/ROW]
[ROW][C]100[/C][C]0.331116[/C][C]0.662231[/C][C]0.668884[/C][/ROW]
[ROW][C]101[/C][C]0.305447[/C][C]0.610894[/C][C]0.694553[/C][/ROW]
[ROW][C]102[/C][C]0.29047[/C][C]0.580941[/C][C]0.70953[/C][/ROW]
[ROW][C]103[/C][C]0.293495[/C][C]0.586991[/C][C]0.706505[/C][/ROW]
[ROW][C]104[/C][C]0.310416[/C][C]0.620832[/C][C]0.689584[/C][/ROW]
[ROW][C]105[/C][C]0.341363[/C][C]0.682726[/C][C]0.658637[/C][/ROW]
[ROW][C]106[/C][C]0.368219[/C][C]0.736438[/C][C]0.631781[/C][/ROW]
[ROW][C]107[/C][C]0.38581[/C][C]0.771619[/C][C]0.61419[/C][/ROW]
[ROW][C]108[/C][C]0.605898[/C][C]0.788203[/C][C]0.394102[/C][/ROW]
[ROW][C]109[/C][C]0.652694[/C][C]0.694613[/C][C]0.347306[/C][/ROW]
[ROW][C]110[/C][C]0.662767[/C][C]0.674466[/C][C]0.337233[/C][/ROW]
[ROW][C]111[/C][C]0.657164[/C][C]0.685672[/C][C]0.342836[/C][/ROW]
[ROW][C]112[/C][C]0.645063[/C][C]0.709874[/C][C]0.354937[/C][/ROW]
[ROW][C]113[/C][C]0.784826[/C][C]0.430348[/C][C]0.215174[/C][/ROW]
[ROW][C]114[/C][C]0.780263[/C][C]0.439475[/C][C]0.219737[/C][/ROW]
[ROW][C]115[/C][C]0.872383[/C][C]0.255234[/C][C]0.127617[/C][/ROW]
[ROW][C]116[/C][C]0.912286[/C][C]0.175429[/C][C]0.0877145[/C][/ROW]
[ROW][C]117[/C][C]0.902614[/C][C]0.194772[/C][C]0.0973858[/C][/ROW]
[ROW][C]118[/C][C]0.911104[/C][C]0.177792[/C][C]0.0888958[/C][/ROW]
[ROW][C]119[/C][C]0.905531[/C][C]0.188939[/C][C]0.0944693[/C][/ROW]
[ROW][C]120[/C][C]0.92401[/C][C]0.15198[/C][C]0.0759899[/C][/ROW]
[ROW][C]121[/C][C]0.937328[/C][C]0.125344[/C][C]0.0626718[/C][/ROW]
[ROW][C]122[/C][C]0.94692[/C][C]0.10616[/C][C]0.05308[/C][/ROW]
[ROW][C]123[/C][C]0.949763[/C][C]0.100473[/C][C]0.0502367[/C][/ROW]
[ROW][C]124[/C][C]0.968989[/C][C]0.0620214[/C][C]0.0310107[/C][/ROW]
[ROW][C]125[/C][C]0.973307[/C][C]0.0533868[/C][C]0.0266934[/C][/ROW]
[ROW][C]126[/C][C]0.968951[/C][C]0.0620989[/C][C]0.0310495[/C][/ROW]
[ROW][C]127[/C][C]0.968347[/C][C]0.063306[/C][C]0.031653[/C][/ROW]
[ROW][C]128[/C][C]0.968593[/C][C]0.0628143[/C][C]0.0314071[/C][/ROW]
[ROW][C]129[/C][C]0.973955[/C][C]0.0520899[/C][C]0.0260449[/C][/ROW]
[ROW][C]130[/C][C]0.972964[/C][C]0.0540715[/C][C]0.0270357[/C][/ROW]
[ROW][C]131[/C][C]0.974904[/C][C]0.0501917[/C][C]0.0250959[/C][/ROW]
[ROW][C]132[/C][C]0.973714[/C][C]0.0525722[/C][C]0.0262861[/C][/ROW]
[ROW][C]133[/C][C]0.970935[/C][C]0.0581307[/C][C]0.0290653[/C][/ROW]
[ROW][C]134[/C][C]0.966261[/C][C]0.0674771[/C][C]0.0337385[/C][/ROW]
[ROW][C]135[/C][C]0.96001[/C][C]0.07998[/C][C]0.03999[/C][/ROW]
[ROW][C]136[/C][C]0.953664[/C][C]0.0926727[/C][C]0.0463363[/C][/ROW]
[ROW][C]137[/C][C]0.967308[/C][C]0.0653834[/C][C]0.0326917[/C][/ROW]
[ROW][C]138[/C][C]0.967061[/C][C]0.0658779[/C][C]0.0329389[/C][/ROW]
[ROW][C]139[/C][C]0.963836[/C][C]0.0723279[/C][C]0.0361639[/C][/ROW]
[ROW][C]140[/C][C]0.957329[/C][C]0.0853418[/C][C]0.0426709[/C][/ROW]
[ROW][C]141[/C][C]0.950072[/C][C]0.0998567[/C][C]0.0499283[/C][/ROW]
[ROW][C]142[/C][C]0.973385[/C][C]0.0532294[/C][C]0.0266147[/C][/ROW]
[ROW][C]143[/C][C]0.97238[/C][C]0.0552391[/C][C]0.0276195[/C][/ROW]
[ROW][C]144[/C][C]0.972408[/C][C]0.0551836[/C][C]0.0275918[/C][/ROW]
[ROW][C]145[/C][C]0.969217[/C][C]0.0615651[/C][C]0.0307826[/C][/ROW]
[ROW][C]146[/C][C]0.969865[/C][C]0.0602703[/C][C]0.0301351[/C][/ROW]
[ROW][C]147[/C][C]0.965091[/C][C]0.0698179[/C][C]0.034909[/C][/ROW]
[ROW][C]148[/C][C]0.959481[/C][C]0.0810379[/C][C]0.0405189[/C][/ROW]
[ROW][C]149[/C][C]0.954439[/C][C]0.0911215[/C][C]0.0455608[/C][/ROW]
[ROW][C]150[/C][C]0.953198[/C][C]0.0936033[/C][C]0.0468017[/C][/ROW]
[ROW][C]151[/C][C]0.982617[/C][C]0.0347664[/C][C]0.0173832[/C][/ROW]
[ROW][C]152[/C][C]0.980731[/C][C]0.0385386[/C][C]0.0192693[/C][/ROW]
[ROW][C]153[/C][C]0.981493[/C][C]0.0370139[/C][C]0.018507[/C][/ROW]
[ROW][C]154[/C][C]0.977614[/C][C]0.044773[/C][C]0.0223865[/C][/ROW]
[ROW][C]155[/C][C]0.978531[/C][C]0.042937[/C][C]0.0214685[/C][/ROW]
[ROW][C]156[/C][C]0.974086[/C][C]0.051827[/C][C]0.0259135[/C][/ROW]
[ROW][C]157[/C][C]0.973073[/C][C]0.053854[/C][C]0.026927[/C][/ROW]
[ROW][C]158[/C][C]0.968738[/C][C]0.062524[/C][C]0.031262[/C][/ROW]
[ROW][C]159[/C][C]0.966836[/C][C]0.066328[/C][C]0.033164[/C][/ROW]
[ROW][C]160[/C][C]0.960849[/C][C]0.0783016[/C][C]0.0391508[/C][/ROW]
[ROW][C]161[/C][C]0.973283[/C][C]0.0534336[/C][C]0.0267168[/C][/ROW]
[ROW][C]162[/C][C]0.968807[/C][C]0.062386[/C][C]0.031193[/C][/ROW]
[ROW][C]163[/C][C]0.968403[/C][C]0.0631949[/C][C]0.0315974[/C][/ROW]
[ROW][C]164[/C][C]0.993466[/C][C]0.0130677[/C][C]0.00653385[/C][/ROW]
[ROW][C]165[/C][C]0.994871[/C][C]0.0102585[/C][C]0.00512923[/C][/ROW]
[ROW][C]166[/C][C]0.993466[/C][C]0.0130688[/C][C]0.00653441[/C][/ROW]
[ROW][C]167[/C][C]0.993344[/C][C]0.0133119[/C][C]0.00665596[/C][/ROW]
[ROW][C]168[/C][C]0.995737[/C][C]0.00852632[/C][C]0.00426316[/C][/ROW]
[ROW][C]169[/C][C]0.994497[/C][C]0.0110051[/C][C]0.00550257[/C][/ROW]
[ROW][C]170[/C][C]0.994828[/C][C]0.0103445[/C][C]0.00517226[/C][/ROW]
[ROW][C]171[/C][C]0.993767[/C][C]0.012465[/C][C]0.0062325[/C][/ROW]
[ROW][C]172[/C][C]0.99572[/C][C]0.0085605[/C][C]0.00428025[/C][/ROW]
[ROW][C]173[/C][C]0.99523[/C][C]0.00953966[/C][C]0.00476983[/C][/ROW]
[ROW][C]174[/C][C]0.994049[/C][C]0.0119027[/C][C]0.00595137[/C][/ROW]
[ROW][C]175[/C][C]0.992664[/C][C]0.0146714[/C][C]0.0073357[/C][/ROW]
[ROW][C]176[/C][C]0.993885[/C][C]0.0122304[/C][C]0.00611522[/C][/ROW]
[ROW][C]177[/C][C]0.993129[/C][C]0.0137417[/C][C]0.00687085[/C][/ROW]
[ROW][C]178[/C][C]0.993062[/C][C]0.0138758[/C][C]0.00693789[/C][/ROW]
[ROW][C]179[/C][C]0.992117[/C][C]0.0157669[/C][C]0.00788344[/C][/ROW]
[ROW][C]180[/C][C]0.994017[/C][C]0.0119669[/C][C]0.00598346[/C][/ROW]
[ROW][C]181[/C][C]0.993555[/C][C]0.0128897[/C][C]0.00644487[/C][/ROW]
[ROW][C]182[/C][C]0.99195[/C][C]0.0161008[/C][C]0.00805041[/C][/ROW]
[ROW][C]183[/C][C]0.990645[/C][C]0.0187104[/C][C]0.00935519[/C][/ROW]
[ROW][C]184[/C][C]0.988387[/C][C]0.0232263[/C][C]0.0116132[/C][/ROW]
[ROW][C]185[/C][C]0.987477[/C][C]0.0250469[/C][C]0.0125235[/C][/ROW]
[ROW][C]186[/C][C]0.985338[/C][C]0.0293241[/C][C]0.0146621[/C][/ROW]
[ROW][C]187[/C][C]0.992124[/C][C]0.0157519[/C][C]0.00787593[/C][/ROW]
[ROW][C]188[/C][C]0.990362[/C][C]0.0192765[/C][C]0.00963826[/C][/ROW]
[ROW][C]189[/C][C]0.988641[/C][C]0.0227182[/C][C]0.0113591[/C][/ROW]
[ROW][C]190[/C][C]0.985579[/C][C]0.0288416[/C][C]0.0144208[/C][/ROW]
[ROW][C]191[/C][C]0.982334[/C][C]0.0353327[/C][C]0.0176664[/C][/ROW]
[ROW][C]192[/C][C]0.979461[/C][C]0.0410786[/C][C]0.0205393[/C][/ROW]
[ROW][C]193[/C][C]0.976658[/C][C]0.0466833[/C][C]0.0233417[/C][/ROW]
[ROW][C]194[/C][C]0.985283[/C][C]0.0294341[/C][C]0.014717[/C][/ROW]
[ROW][C]195[/C][C]0.982447[/C][C]0.0351054[/C][C]0.0175527[/C][/ROW]
[ROW][C]196[/C][C]0.979639[/C][C]0.0407211[/C][C]0.0203606[/C][/ROW]
[ROW][C]197[/C][C]0.979891[/C][C]0.0402173[/C][C]0.0201086[/C][/ROW]
[ROW][C]198[/C][C]0.974691[/C][C]0.0506173[/C][C]0.0253086[/C][/ROW]
[ROW][C]199[/C][C]0.978526[/C][C]0.0429483[/C][C]0.0214741[/C][/ROW]
[ROW][C]200[/C][C]0.97802[/C][C]0.0439607[/C][C]0.0219803[/C][/ROW]
[ROW][C]201[/C][C]0.97498[/C][C]0.0500399[/C][C]0.02502[/C][/ROW]
[ROW][C]202[/C][C]0.973372[/C][C]0.0532562[/C][C]0.0266281[/C][/ROW]
[ROW][C]203[/C][C]0.969891[/C][C]0.0602189[/C][C]0.0301095[/C][/ROW]
[ROW][C]204[/C][C]0.963105[/C][C]0.0737903[/C][C]0.0368951[/C][/ROW]
[ROW][C]205[/C][C]0.954993[/C][C]0.0900136[/C][C]0.0450068[/C][/ROW]
[ROW][C]206[/C][C]0.965129[/C][C]0.0697414[/C][C]0.0348707[/C][/ROW]
[ROW][C]207[/C][C]0.962254[/C][C]0.0754918[/C][C]0.0377459[/C][/ROW]
[ROW][C]208[/C][C]0.96053[/C][C]0.0789396[/C][C]0.0394698[/C][/ROW]
[ROW][C]209[/C][C]0.956191[/C][C]0.0876183[/C][C]0.0438092[/C][/ROW]
[ROW][C]210[/C][C]0.951809[/C][C]0.0963825[/C][C]0.0481913[/C][/ROW]
[ROW][C]211[/C][C]0.942524[/C][C]0.114952[/C][C]0.0574762[/C][/ROW]
[ROW][C]212[/C][C]0.932339[/C][C]0.135321[/C][C]0.0676605[/C][/ROW]
[ROW][C]213[/C][C]0.946804[/C][C]0.106393[/C][C]0.0531964[/C][/ROW]
[ROW][C]214[/C][C]0.937337[/C][C]0.125327[/C][C]0.0626634[/C][/ROW]
[ROW][C]215[/C][C]0.934673[/C][C]0.130654[/C][C]0.0653272[/C][/ROW]
[ROW][C]216[/C][C]0.923617[/C][C]0.152765[/C][C]0.0763825[/C][/ROW]
[ROW][C]217[/C][C]0.920525[/C][C]0.158949[/C][C]0.0794747[/C][/ROW]
[ROW][C]218[/C][C]0.911031[/C][C]0.177939[/C][C]0.0889693[/C][/ROW]
[ROW][C]219[/C][C]0.891822[/C][C]0.216357[/C][C]0.108178[/C][/ROW]
[ROW][C]220[/C][C]0.869664[/C][C]0.260671[/C][C]0.130336[/C][/ROW]
[ROW][C]221[/C][C]0.853663[/C][C]0.292675[/C][C]0.146337[/C][/ROW]
[ROW][C]222[/C][C]0.873893[/C][C]0.252214[/C][C]0.126107[/C][/ROW]
[ROW][C]223[/C][C]0.849147[/C][C]0.301706[/C][C]0.150853[/C][/ROW]
[ROW][C]224[/C][C]0.857888[/C][C]0.284224[/C][C]0.142112[/C][/ROW]
[ROW][C]225[/C][C]0.8449[/C][C]0.310201[/C][C]0.1551[/C][/ROW]
[ROW][C]226[/C][C]0.896748[/C][C]0.206504[/C][C]0.103252[/C][/ROW]
[ROW][C]227[/C][C]0.919204[/C][C]0.161592[/C][C]0.0807961[/C][/ROW]
[ROW][C]228[/C][C]0.926102[/C][C]0.147795[/C][C]0.0738976[/C][/ROW]
[ROW][C]229[/C][C]0.914297[/C][C]0.171406[/C][C]0.0857028[/C][/ROW]
[ROW][C]230[/C][C]0.929298[/C][C]0.141405[/C][C]0.0707024[/C][/ROW]
[ROW][C]231[/C][C]0.95321[/C][C]0.0935803[/C][C]0.0467902[/C][/ROW]
[ROW][C]232[/C][C]0.940954[/C][C]0.118092[/C][C]0.059046[/C][/ROW]
[ROW][C]233[/C][C]0.929902[/C][C]0.140196[/C][C]0.0700982[/C][/ROW]
[ROW][C]234[/C][C]0.919551[/C][C]0.160897[/C][C]0.0804485[/C][/ROW]
[ROW][C]235[/C][C]0.911343[/C][C]0.177315[/C][C]0.0886573[/C][/ROW]
[ROW][C]236[/C][C]0.971239[/C][C]0.0575219[/C][C]0.028761[/C][/ROW]
[ROW][C]237[/C][C]0.969968[/C][C]0.0600644[/C][C]0.0300322[/C][/ROW]
[ROW][C]238[/C][C]0.971897[/C][C]0.056206[/C][C]0.028103[/C][/ROW]
[ROW][C]239[/C][C]0.963811[/C][C]0.0723772[/C][C]0.0361886[/C][/ROW]
[ROW][C]240[/C][C]0.951898[/C][C]0.0962037[/C][C]0.0481019[/C][/ROW]
[ROW][C]241[/C][C]0.942778[/C][C]0.114444[/C][C]0.0572222[/C][/ROW]
[ROW][C]242[/C][C]0.929828[/C][C]0.140344[/C][C]0.0701722[/C][/ROW]
[ROW][C]243[/C][C]0.925285[/C][C]0.149431[/C][C]0.0747154[/C][/ROW]
[ROW][C]244[/C][C]0.915509[/C][C]0.168983[/C][C]0.0844914[/C][/ROW]
[ROW][C]245[/C][C]0.890496[/C][C]0.219008[/C][C]0.109504[/C][/ROW]
[ROW][C]246[/C][C]0.864453[/C][C]0.271094[/C][C]0.135547[/C][/ROW]
[ROW][C]247[/C][C]0.834586[/C][C]0.330827[/C][C]0.165414[/C][/ROW]
[ROW][C]248[/C][C]0.801204[/C][C]0.397592[/C][C]0.198796[/C][/ROW]
[ROW][C]249[/C][C]0.757067[/C][C]0.485866[/C][C]0.242933[/C][/ROW]
[ROW][C]250[/C][C]0.70485[/C][C]0.5903[/C][C]0.29515[/C][/ROW]
[ROW][C]251[/C][C]0.66054[/C][C]0.678919[/C][C]0.33946[/C][/ROW]
[ROW][C]252[/C][C]0.660835[/C][C]0.67833[/C][C]0.339165[/C][/ROW]
[ROW][C]253[/C][C]0.598447[/C][C]0.803105[/C][C]0.401553[/C][/ROW]
[ROW][C]254[/C][C]0.535467[/C][C]0.929066[/C][C]0.464533[/C][/ROW]
[ROW][C]255[/C][C]0.59187[/C][C]0.816259[/C][C]0.40813[/C][/ROW]
[ROW][C]256[/C][C]0.527579[/C][C]0.944842[/C][C]0.472421[/C][/ROW]
[ROW][C]257[/C][C]0.52845[/C][C]0.9431[/C][C]0.47155[/C][/ROW]
[ROW][C]258[/C][C]0.91719[/C][C]0.165619[/C][C]0.0828095[/C][/ROW]
[ROW][C]259[/C][C]0.881072[/C][C]0.237855[/C][C]0.118928[/C][/ROW]
[ROW][C]260[/C][C]0.995317[/C][C]0.00936527[/C][C]0.00468264[/C][/ROW]
[ROW][C]261[/C][C]0.997735[/C][C]0.00452976[/C][C]0.00226488[/C][/ROW]
[ROW][C]262[/C][C]0.997962[/C][C]0.00407573[/C][C]0.00203786[/C][/ROW]
[ROW][C]263[/C][C]0.999827[/C][C]0.000346347[/C][C]0.000173174[/C][/ROW]
[ROW][C]264[/C][C]0.99948[/C][C]0.00103942[/C][C]0.000519709[/C][/ROW]
[ROW][C]265[/C][C]0.999032[/C][C]0.00193635[/C][C]0.000968176[/C][/ROW]
[ROW][C]266[/C][C]0.998029[/C][C]0.00394266[/C][C]0.00197133[/C][/ROW]
[ROW][C]267[/C][C]0.998052[/C][C]0.00389667[/C][C]0.00194833[/C][/ROW]
[ROW][C]268[/C][C]0.994416[/C][C]0.0111685[/C][C]0.00558425[/C][/ROW]
[ROW][C]269[/C][C]0.990629[/C][C]0.0187424[/C][C]0.0093712[/C][/ROW]
[ROW][C]270[/C][C]0.963594[/C][C]0.0728112[/C][C]0.0364056[/C][/ROW]
[ROW][C]271[/C][C]0.966206[/C][C]0.0675877[/C][C]0.0337939[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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
80.8555420.2889170.144458
90.8315710.3368580.168429
100.8402560.3194880.159744
110.7571720.4856550.242828
120.804950.3900990.19505
130.7386180.5227640.261382
140.654480.6910390.34552
150.5909160.8181690.409084
160.6102580.7794840.389742
170.5445410.9109190.455459
180.4654370.9308740.534563
190.3939420.7878850.606058
200.3230140.6460290.676986
210.3964990.7929980.603501
220.4128590.8257170.587141
230.3513970.7027930.648603
240.2922280.5844560.707772
250.2399580.4799170.760042
260.2068110.4136210.793189
270.1731010.3462020.826899
280.2279720.4559450.772028
290.2027080.4054160.797292
300.1818130.3636250.818187
310.1560980.3121950.843902
320.1544930.3089870.845507
330.1281210.2562420.871879
340.1320230.2640460.867977
350.1097030.2194070.890297
360.08972650.1794530.910273
370.07073020.141460.92927
380.08355220.1671040.916448
390.1021480.2042950.897852
400.09085290.1817060.909147
410.1432870.2865730.856713
420.1234720.2469430.876528
430.1084070.2168140.891593
440.09087290.1817460.909127
450.09434050.1886810.905659
460.0794080.1588160.920592
470.06588110.1317620.934119
480.08338120.1667620.916619
490.08231580.1646320.917684
500.08874180.1774840.911258
510.0760560.1521120.923944
520.08061880.1612380.919381
530.07317130.1463430.926829
540.07159360.1431870.928406
550.07262710.1452540.927373
560.0626020.1252040.937398
570.1123430.2246860.887657
580.1387710.2775420.861229
590.117610.235220.88239
600.1229290.2458580.877071
610.1371670.2743350.862833
620.1310430.2620850.868957
630.1388620.2777230.861138
640.1725690.3451380.827431
650.1717660.3435330.828234
660.1489250.297850.851075
670.1503970.3007940.849603
680.1378010.2756020.862199
690.1474690.2949370.852531
700.1360070.2720130.863993
710.1240160.2480330.875984
720.1092270.2184540.890773
730.09844780.1968960.901552
740.1041950.2083890.895805
750.09673860.1934770.903261
760.08945050.1789010.910549
770.08499550.1699910.915005
780.08426570.1685310.915734
790.07123160.1424630.928768
800.09225530.1845110.907745
810.07805070.1561010.921949
820.08697480.173950.913025
830.0743440.1486880.925656
840.1615550.3231090.838445
850.1479840.2959680.852016
860.129970.259940.87003
870.1122290.2244570.887771
880.09798880.1959780.902011
890.0922870.1845740.907713
900.09595010.19190.90405
910.1009270.2018540.899073
920.1709690.3419370.829031
930.1714230.3428460.828577
940.1664660.3329330.833534
950.1825010.3650020.817499
960.1774670.3549340.822533
970.244450.48890.75555
980.232480.4649610.76752
990.2755150.5510310.724485
1000.3311160.6622310.668884
1010.3054470.6108940.694553
1020.290470.5809410.70953
1030.2934950.5869910.706505
1040.3104160.6208320.689584
1050.3413630.6827260.658637
1060.3682190.7364380.631781
1070.385810.7716190.61419
1080.6058980.7882030.394102
1090.6526940.6946130.347306
1100.6627670.6744660.337233
1110.6571640.6856720.342836
1120.6450630.7098740.354937
1130.7848260.4303480.215174
1140.7802630.4394750.219737
1150.8723830.2552340.127617
1160.9122860.1754290.0877145
1170.9026140.1947720.0973858
1180.9111040.1777920.0888958
1190.9055310.1889390.0944693
1200.924010.151980.0759899
1210.9373280.1253440.0626718
1220.946920.106160.05308
1230.9497630.1004730.0502367
1240.9689890.06202140.0310107
1250.9733070.05338680.0266934
1260.9689510.06209890.0310495
1270.9683470.0633060.031653
1280.9685930.06281430.0314071
1290.9739550.05208990.0260449
1300.9729640.05407150.0270357
1310.9749040.05019170.0250959
1320.9737140.05257220.0262861
1330.9709350.05813070.0290653
1340.9662610.06747710.0337385
1350.960010.079980.03999
1360.9536640.09267270.0463363
1370.9673080.06538340.0326917
1380.9670610.06587790.0329389
1390.9638360.07232790.0361639
1400.9573290.08534180.0426709
1410.9500720.09985670.0499283
1420.9733850.05322940.0266147
1430.972380.05523910.0276195
1440.9724080.05518360.0275918
1450.9692170.06156510.0307826
1460.9698650.06027030.0301351
1470.9650910.06981790.034909
1480.9594810.08103790.0405189
1490.9544390.09112150.0455608
1500.9531980.09360330.0468017
1510.9826170.03476640.0173832
1520.9807310.03853860.0192693
1530.9814930.03701390.018507
1540.9776140.0447730.0223865
1550.9785310.0429370.0214685
1560.9740860.0518270.0259135
1570.9730730.0538540.026927
1580.9687380.0625240.031262
1590.9668360.0663280.033164
1600.9608490.07830160.0391508
1610.9732830.05343360.0267168
1620.9688070.0623860.031193
1630.9684030.06319490.0315974
1640.9934660.01306770.00653385
1650.9948710.01025850.00512923
1660.9934660.01306880.00653441
1670.9933440.01331190.00665596
1680.9957370.008526320.00426316
1690.9944970.01100510.00550257
1700.9948280.01034450.00517226
1710.9937670.0124650.0062325
1720.995720.00856050.00428025
1730.995230.009539660.00476983
1740.9940490.01190270.00595137
1750.9926640.01467140.0073357
1760.9938850.01223040.00611522
1770.9931290.01374170.00687085
1780.9930620.01387580.00693789
1790.9921170.01576690.00788344
1800.9940170.01196690.00598346
1810.9935550.01288970.00644487
1820.991950.01610080.00805041
1830.9906450.01871040.00935519
1840.9883870.02322630.0116132
1850.9874770.02504690.0125235
1860.9853380.02932410.0146621
1870.9921240.01575190.00787593
1880.9903620.01927650.00963826
1890.9886410.02271820.0113591
1900.9855790.02884160.0144208
1910.9823340.03533270.0176664
1920.9794610.04107860.0205393
1930.9766580.04668330.0233417
1940.9852830.02943410.014717
1950.9824470.03510540.0175527
1960.9796390.04072110.0203606
1970.9798910.04021730.0201086
1980.9746910.05061730.0253086
1990.9785260.04294830.0214741
2000.978020.04396070.0219803
2010.974980.05003990.02502
2020.9733720.05325620.0266281
2030.9698910.06021890.0301095
2040.9631050.07379030.0368951
2050.9549930.09001360.0450068
2060.9651290.06974140.0348707
2070.9622540.07549180.0377459
2080.960530.07893960.0394698
2090.9561910.08761830.0438092
2100.9518090.09638250.0481913
2110.9425240.1149520.0574762
2120.9323390.1353210.0676605
2130.9468040.1063930.0531964
2140.9373370.1253270.0626634
2150.9346730.1306540.0653272
2160.9236170.1527650.0763825
2170.9205250.1589490.0794747
2180.9110310.1779390.0889693
2190.8918220.2163570.108178
2200.8696640.2606710.130336
2210.8536630.2926750.146337
2220.8738930.2522140.126107
2230.8491470.3017060.150853
2240.8578880.2842240.142112
2250.84490.3102010.1551
2260.8967480.2065040.103252
2270.9192040.1615920.0807961
2280.9261020.1477950.0738976
2290.9142970.1714060.0857028
2300.9292980.1414050.0707024
2310.953210.09358030.0467902
2320.9409540.1180920.059046
2330.9299020.1401960.0700982
2340.9195510.1608970.0804485
2350.9113430.1773150.0886573
2360.9712390.05752190.028761
2370.9699680.06006440.0300322
2380.9718970.0562060.028103
2390.9638110.07237720.0361886
2400.9518980.09620370.0481019
2410.9427780.1144440.0572222
2420.9298280.1403440.0701722
2430.9252850.1494310.0747154
2440.9155090.1689830.0844914
2450.8904960.2190080.109504
2460.8644530.2710940.135547
2470.8345860.3308270.165414
2480.8012040.3975920.198796
2490.7570670.4858660.242933
2500.704850.59030.29515
2510.660540.6789190.33946
2520.6608350.678330.339165
2530.5984470.8031050.401553
2540.5354670.9290660.464533
2550.591870.8162590.40813
2560.5275790.9448420.472421
2570.528450.94310.47155
2580.917190.1656190.0828095
2590.8810720.2378550.118928
2600.9953170.009365270.00468264
2610.9977350.004529760.00226488
2620.9979620.004075730.00203786
2630.9998270.0003463470.000173174
2640.999480.001039420.000519709
2650.9990320.001936350.000968176
2660.9980290.003942660.00197133
2670.9980520.003896670.00194833
2680.9944160.01116850.00558425
2690.9906290.01874240.0093712
2700.9635940.07281120.0364056
2710.9662060.06758770.0337939






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level110.0416667NOK
5% type I error level510.193182NOK
10% type I error level1050.397727NOK

\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 & 11 & 0.0416667 & NOK \tabularnewline
5% type I error level & 51 & 0.193182 & NOK \tabularnewline
10% type I error level & 105 & 0.397727 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264581&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]11[/C][C]0.0416667[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]51[/C][C]0.193182[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]105[/C][C]0.397727[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264581&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264581&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 level110.0416667NOK
5% type I error level510.193182NOK
10% type I error level1050.397727NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = 2 ; par3 = Pearson Chi-Squared ;
Parameters (R input):
par1 = 5 ; 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')
}