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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 computationMon, 15 Dec 2014 15:28:43 +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/15/t1418659393odvykcynxuw91y5.htm/, Retrieved Thu, 16 May 2024 10:27:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268684, Retrieved Thu, 16 May 2024 10:27:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Paired and Unpaired Two Samples Tests about the Mean] [] [2010-11-01 13:07:12] [b98453cac15ba1066b407e146608df68]
- RMP   [Paired and Unpaired Two Samples Tests about the Mean] [] [2014-10-21 07:47:40] [32b17a345b130fdf5cc88718ed94a974]
- RMPD    [Survey Scores] [] [2014-12-15 10:25:50] [fda96889f4ef6d31c0c28fd64d281011]
- RM D      [Chi-Squared Test, McNemar Test, and Fisher Exact Test] [] [2014-12-15 10:54:59] [fda96889f4ef6d31c0c28fd64d281011]
- RM D          [Multiple Regression] [] [2014-12-15 15:28:43] [f11ff77f11120bba23ccca75f7c5b5e0] [Current]
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Dataset

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.21356 + 0.0110085LFM[t] + 0.0276791Blogs[t] -0.359242PRH[t] -0.370158CH[t] + 0.362366Hours[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.21356 +  0.0110085LFM[t] +  0.0276791Blogs[t] -0.359242PRH[t] -0.370158CH[t] +  0.362366Hours[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.21356 +  0.0110085LFM[t] +  0.0276791Blogs[t] -0.359242PRH[t] -0.370158CH[t] +  0.362366Hours[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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] = + 8.21356 + 0.0110085LFM[t] + 0.0276791Blogs[t] -0.359242PRH[t] -0.370158CH[t] + 0.362366Hours[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.213560.54546815.061.10722e-375.53612e-38
LFM0.01100850.004855022.2670.02414730.0120736
Blogs0.02767910.002923379.4681.43585e-187.17927e-19
PRH-0.3592420.44797-0.80190.4232920.211646
CH-0.3701580.447322-0.82750.4086810.20434
Hours0.3623660.4471560.81040.4184310.209215

\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) & 8.21356 & 0.545468 & 15.06 & 1.10722e-37 & 5.53612e-38 \tabularnewline
LFM & 0.0110085 & 0.00485502 & 2.267 & 0.0241473 & 0.0120736 \tabularnewline
Blogs & 0.0276791 & 0.00292337 & 9.468 & 1.43585e-18 & 7.17927e-19 \tabularnewline
PRH & -0.359242 & 0.44797 & -0.8019 & 0.423292 & 0.211646 \tabularnewline
CH & -0.370158 & 0.447322 & -0.8275 & 0.408681 & 0.20434 \tabularnewline
Hours & 0.362366 & 0.447156 & 0.8104 & 0.418431 & 0.209215 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&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]8.21356[/C][C]0.545468[/C][C]15.06[/C][C]1.10722e-37[/C][C]5.53612e-38[/C][/ROW]
[ROW][C]LFM[/C][C]0.0110085[/C][C]0.00485502[/C][C]2.267[/C][C]0.0241473[/C][C]0.0120736[/C][/ROW]
[ROW][C]Blogs[/C][C]0.0276791[/C][C]0.00292337[/C][C]9.468[/C][C]1.43585e-18[/C][C]7.17927e-19[/C][/ROW]
[ROW][C]PRH[/C][C]-0.359242[/C][C]0.44797[/C][C]-0.8019[/C][C]0.423292[/C][C]0.211646[/C][/ROW]
[ROW][C]CH[/C][C]-0.370158[/C][C]0.447322[/C][C]-0.8275[/C][C]0.408681[/C][C]0.20434[/C][/ROW]
[ROW][C]Hours[/C][C]0.362366[/C][C]0.447156[/C][C]0.8104[/C][C]0.418431[/C][C]0.209215[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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)8.213560.54546815.061.10722e-375.53612e-38
LFM0.01100850.004855022.2670.02414730.0120736
Blogs0.02767910.002923379.4681.43585e-187.17927e-19
PRH-0.3592420.44797-0.80190.4232920.211646
CH-0.3701580.447322-0.82750.4086810.20434
Hours0.3623660.4471560.81040.4184310.209215






Multiple Linear Regression - Regression Statistics
Multiple R0.608557
R-squared0.370342
Adjusted R-squared0.358767
F-TEST (value)31.9961
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7181
Sum Squared Residuals2009.56

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.608557 \tabularnewline
R-squared & 0.370342 \tabularnewline
Adjusted R-squared & 0.358767 \tabularnewline
F-TEST (value) & 31.9961 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.7181 \tabularnewline
Sum Squared Residuals & 2009.56 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.608557[/C][/ROW]
[ROW][C]R-squared[/C][C]0.370342[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.358767[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]31.9961[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]272[/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]2.7181[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2009.56[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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 R0.608557
R-squared0.370342
Adjusted R-squared0.358767
F-TEST (value)31.9961
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.7181
Sum Squared Residuals2009.56






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.03740.862594
212.211.47420.725754
312.812.15110.648917
47.412.7689-5.36894
56.711.3722-4.67222
612.615.3551-2.75513
714.812.74562.05442
813.312.28111.0189
911.112.657-1.55699
108.214.2214-6.02141
1111.412.9667-1.5667
126.414.5954-8.19541
1310.611.5398-0.939825
141213.6616-1.66161
156.39.69435-3.39435
1611.311.26930.0306585
1711.913.8696-1.96961
189.312.1032-2.80324
199.612.2659-2.66591
201011.5919-1.59185
216.411.7226-5.32264
2213.812.79351.00648
2310.813.3746-2.57461
2413.812.32811.47188
2511.712.68-0.97996
2610.915.1718-4.27176
2716.113.3522.74796
2813.411.10542.29465
299.911.2788-1.37883
3011.512.2213-0.721283
318.311.8681-3.56809
3211.713.3529-1.65294
33912.3188-3.31875
349.714.3323-4.6323
3510.812.498-1.69802
3610.312.7269-2.42691
3710.411.7532-1.35324
3812.712.64230.0577352
399.312.2337-2.93371
4011.814.3134-2.51335
415.910.6132-4.71315
4211.413.8881-2.48809
431311.79581.20418
4410.812.6472-1.84717
4512.310.38611.9139
4611.313.4472-2.14722
4711.812.5109-0.710864
487.911.0605-3.16053
4912.710.10892.59111
5012.310.75011.54992
5111.611.9871-0.387093
526.710.9669-4.26687
5310.913.156-2.25599
5412.112.6491-0.549065
5513.313.4855-0.185454
5610.113.3308-3.23083
575.711.7-6.00003
5814.312.20122.09876
5989.42632-1.42632
6013.311.7351.56505
619.312.8225-3.5225
6212.511.61980.880173
637.610.7917-3.19174
6415.913.92031.97967
659.211.4599-2.2599
669.110.4935-1.39355
6711.114.1507-3.05068
681313.8018-0.80185
6914.512.87611.62386
7012.211.01881.18123
7112.313.4909-1.1909
7211.411.31980.0802311
738.811.2563-2.45626
7414.611.10393.49606
7512.612.997-0.397045
761313.7127-0.712703
7712.611.22071.37933
7813.214.7275-1.52752
799.911.1645-1.26449
807.711.4798-3.7798
8110.510.6017-0.101678
8213.410.60342.79657
8310.911.8219-0.921873
844.310.0652-5.76517
8510.311.0451-0.745138
8611.811.62690.173113
8711.210.56940.630556
8811.410.74780.652211
898.610.0936-1.49358
9013.211.02842.17159
9112.610.32192.27807
925.611.0811-5.48114
939.911.4002-1.50018
948.811.8552-3.05519
957.711.6395-3.93951
96910.3851-1.3851
977.312.2386-4.93862
9811.410.93110.46887
9913.611.36162.2384
1007.910.6549-2.75493
10110.710.9173-0.21727
10210.311.6423-1.34227
1038.310.2548-1.95483
1049.610.9569-1.3569
10514.211.69092.50913
1068.510.3758-1.87576
10713.510.62622.87385
1084.910.7004-5.80038
1096.410.1342-3.73424
1109.610.4174-0.817419
11111.610.78880.811202
11211.110.28210.817893
1134.359.4928-5.1428
11412.712.50450.195519
11518.114.71723.38277
11617.8515.03492.81507
11716.615.96720.632849
11812.69.534363.06564
11917.122.1329-5.03294
12019.115.54953.55048
12116.118.5132-2.41317
12213.3510.53332.81675
12318.417.57620.82385
12414.710.90383.79623
12510.614.6869-4.08689
12612.613.6578-1.05778
12716.215.02761.17245
12813.617.1098-3.50983
12918.916.07752.82253
13014.112.26361.8364
13114.511.77272.72726
13216.1518.0468-1.89683
13314.7513.0581.69196
13414.814.13210.667918
13512.4512.20650.243458
13612.6514.6201-1.97012
13717.3513.71063.63944
1388.611.9265-3.32645
13918.417.60770.79232
14016.118.0183-1.91834
14111.610.67150.928526
14217.7511.62266.12744
14315.2513.65281.59721
14417.6516.14651.50351
14516.3514.63161.71835
14617.6514.86462.78539
14713.612.89430.705716
14814.3513.40240.947607
14914.7517.9888-3.23883
15018.2516.27171.97835
1519.915.1275-5.2275
1521614.00531.99466
15318.2515.61062.63943
15416.8517.2864-0.436379
15514.612.41252.18752
15613.8513.71780.132226
15718.9516.2892.66101
15815.614.50171.09828
15914.8517.2774-2.42737
16011.7512.6594-0.909422
16118.4512.82175.62831
16215.917.2987-1.39866
16317.114.44762.65244
16416.110.70115.39894
16519.914.69185.20819
16610.9510.62060.32944
16718.4515.72992.72007
16815.110.40434.69573
1691515.3723-0.372258
17011.3513.9905-2.6405
17115.9514.96060.989428
17218.113.20814.89191
17314.612.77781.82218
17415.415.652-0.252
17515.415.652-0.252
17617.613.4754.12498
17713.3513.7588-0.408824
17819.116.59122.50883
17915.3512.97082.37922
1807.612.074-4.47396
18113.413.8652-0.465164
18213.913.79120.108822
18319.117.13171.96826
18415.2513.74381.5062
18512.911.96370.936286
18616.113.7462.354
18717.3512.14815.20195
18813.1512.20940.940573
18912.159.703642.44636
19012.612.4770.123007
19110.3511.3651-1.01506
19215.412.9692.43097
1939.610.7759-1.17586
19418.213.13125.06878
19513.611.99121.60882
19614.8514.4840.366007
19714.7516.9434-2.19343
19814.114.1426-0.0425754
19914.911.53663.36337
20016.2512.65093.59912
20119.2517.48221.76784
20213.611.83021.76982
20313.613.20760.392376
20415.6515.09420.555806
20512.7512.44390.30613
20614.610.97523.62479
2079.8513.1944-3.34436
20812.6510.94011.7099
20919.216.4482.75197
21016.614.51072.08933
21111.29.809061.39094
21215.2513.36481.88523
21311.915.106-3.20597
21413.216.0597-2.85974
21516.3517.1905-0.840543
21612.413.2821-0.882115
21715.8512.82583.02421
21818.1514.95063.19935
21911.1511.3122-0.162194
22015.6515.8044-0.154428
22117.7516.16221.58778
2227.6512.353-4.70301
22312.3512.12890.221107
22415.611.42344.17664
22519.316.26813.03191
22615.211.6523.54801
22717.113.33223.76777
22815.612.85322.7468
22918.414.98913.4109
23019.0515.09723.95281
23118.5513.15415.39591
23219.117.23711.86293
23313.111.65191.44813
23412.8513.1178-0.267775
2359.511.4301-1.9301
2364.511.0667-6.56671
23711.8510.38961.4604
23813.615.7914-2.19137
23911.713.2713-1.57125
24012.411.3071.09298
24113.3514.7894-1.43941
24211.413.7337-2.33369
24314.911.53283.36717
24419.914.69185.20819
24511.211.988-0.788012
24614.615.3895-0.789538
24717.616.00381.59616
24814.0512.68151.36847
24916.115.24870.851348
25013.3512.7430.606991
25111.8511.9491-0.0990825
25211.9514.2494-2.29944
25314.7514.55690.193136
25415.1513.04542.10457
25513.213.6427-0.442664
25616.8515.70761.14242
2577.8510.0333-2.18333
2587.714.9003-7.20033
25912.611.02581.57424
2607.8511.3741-3.52406
26110.9510.62060.32944
26212.3511.86750.482536
2639.9512.4379-2.48791
26414.911.53283.36717
26516.6514.85731.79267
26613.412.86310.536896
26713.9513.62280.327249
26815.711.41034.28967
26916.8512.20824.64182
27010.9510.2580.692006
27115.3511.58123.76885
27212.211.00021.19977
27315.113.97611.12386
27417.7515.98571.7643
27515.212.67612.52387
27614.613.23391.36609
27716.6514.28572.36427
2788.110.6297-2.52974

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.0374 & 0.862594 \tabularnewline
2 & 12.2 & 11.4742 & 0.725754 \tabularnewline
3 & 12.8 & 12.1511 & 0.648917 \tabularnewline
4 & 7.4 & 12.7689 & -5.36894 \tabularnewline
5 & 6.7 & 11.3722 & -4.67222 \tabularnewline
6 & 12.6 & 15.3551 & -2.75513 \tabularnewline
7 & 14.8 & 12.7456 & 2.05442 \tabularnewline
8 & 13.3 & 12.2811 & 1.0189 \tabularnewline
9 & 11.1 & 12.657 & -1.55699 \tabularnewline
10 & 8.2 & 14.2214 & -6.02141 \tabularnewline
11 & 11.4 & 12.9667 & -1.5667 \tabularnewline
12 & 6.4 & 14.5954 & -8.19541 \tabularnewline
13 & 10.6 & 11.5398 & -0.939825 \tabularnewline
14 & 12 & 13.6616 & -1.66161 \tabularnewline
15 & 6.3 & 9.69435 & -3.39435 \tabularnewline
16 & 11.3 & 11.2693 & 0.0306585 \tabularnewline
17 & 11.9 & 13.8696 & -1.96961 \tabularnewline
18 & 9.3 & 12.1032 & -2.80324 \tabularnewline
19 & 9.6 & 12.2659 & -2.66591 \tabularnewline
20 & 10 & 11.5919 & -1.59185 \tabularnewline
21 & 6.4 & 11.7226 & -5.32264 \tabularnewline
22 & 13.8 & 12.7935 & 1.00648 \tabularnewline
23 & 10.8 & 13.3746 & -2.57461 \tabularnewline
24 & 13.8 & 12.3281 & 1.47188 \tabularnewline
25 & 11.7 & 12.68 & -0.97996 \tabularnewline
26 & 10.9 & 15.1718 & -4.27176 \tabularnewline
27 & 16.1 & 13.352 & 2.74796 \tabularnewline
28 & 13.4 & 11.1054 & 2.29465 \tabularnewline
29 & 9.9 & 11.2788 & -1.37883 \tabularnewline
30 & 11.5 & 12.2213 & -0.721283 \tabularnewline
31 & 8.3 & 11.8681 & -3.56809 \tabularnewline
32 & 11.7 & 13.3529 & -1.65294 \tabularnewline
33 & 9 & 12.3188 & -3.31875 \tabularnewline
34 & 9.7 & 14.3323 & -4.6323 \tabularnewline
35 & 10.8 & 12.498 & -1.69802 \tabularnewline
36 & 10.3 & 12.7269 & -2.42691 \tabularnewline
37 & 10.4 & 11.7532 & -1.35324 \tabularnewline
38 & 12.7 & 12.6423 & 0.0577352 \tabularnewline
39 & 9.3 & 12.2337 & -2.93371 \tabularnewline
40 & 11.8 & 14.3134 & -2.51335 \tabularnewline
41 & 5.9 & 10.6132 & -4.71315 \tabularnewline
42 & 11.4 & 13.8881 & -2.48809 \tabularnewline
43 & 13 & 11.7958 & 1.20418 \tabularnewline
44 & 10.8 & 12.6472 & -1.84717 \tabularnewline
45 & 12.3 & 10.3861 & 1.9139 \tabularnewline
46 & 11.3 & 13.4472 & -2.14722 \tabularnewline
47 & 11.8 & 12.5109 & -0.710864 \tabularnewline
48 & 7.9 & 11.0605 & -3.16053 \tabularnewline
49 & 12.7 & 10.1089 & 2.59111 \tabularnewline
50 & 12.3 & 10.7501 & 1.54992 \tabularnewline
51 & 11.6 & 11.9871 & -0.387093 \tabularnewline
52 & 6.7 & 10.9669 & -4.26687 \tabularnewline
53 & 10.9 & 13.156 & -2.25599 \tabularnewline
54 & 12.1 & 12.6491 & -0.549065 \tabularnewline
55 & 13.3 & 13.4855 & -0.185454 \tabularnewline
56 & 10.1 & 13.3308 & -3.23083 \tabularnewline
57 & 5.7 & 11.7 & -6.00003 \tabularnewline
58 & 14.3 & 12.2012 & 2.09876 \tabularnewline
59 & 8 & 9.42632 & -1.42632 \tabularnewline
60 & 13.3 & 11.735 & 1.56505 \tabularnewline
61 & 9.3 & 12.8225 & -3.5225 \tabularnewline
62 & 12.5 & 11.6198 & 0.880173 \tabularnewline
63 & 7.6 & 10.7917 & -3.19174 \tabularnewline
64 & 15.9 & 13.9203 & 1.97967 \tabularnewline
65 & 9.2 & 11.4599 & -2.2599 \tabularnewline
66 & 9.1 & 10.4935 & -1.39355 \tabularnewline
67 & 11.1 & 14.1507 & -3.05068 \tabularnewline
68 & 13 & 13.8018 & -0.80185 \tabularnewline
69 & 14.5 & 12.8761 & 1.62386 \tabularnewline
70 & 12.2 & 11.0188 & 1.18123 \tabularnewline
71 & 12.3 & 13.4909 & -1.1909 \tabularnewline
72 & 11.4 & 11.3198 & 0.0802311 \tabularnewline
73 & 8.8 & 11.2563 & -2.45626 \tabularnewline
74 & 14.6 & 11.1039 & 3.49606 \tabularnewline
75 & 12.6 & 12.997 & -0.397045 \tabularnewline
76 & 13 & 13.7127 & -0.712703 \tabularnewline
77 & 12.6 & 11.2207 & 1.37933 \tabularnewline
78 & 13.2 & 14.7275 & -1.52752 \tabularnewline
79 & 9.9 & 11.1645 & -1.26449 \tabularnewline
80 & 7.7 & 11.4798 & -3.7798 \tabularnewline
81 & 10.5 & 10.6017 & -0.101678 \tabularnewline
82 & 13.4 & 10.6034 & 2.79657 \tabularnewline
83 & 10.9 & 11.8219 & -0.921873 \tabularnewline
84 & 4.3 & 10.0652 & -5.76517 \tabularnewline
85 & 10.3 & 11.0451 & -0.745138 \tabularnewline
86 & 11.8 & 11.6269 & 0.173113 \tabularnewline
87 & 11.2 & 10.5694 & 0.630556 \tabularnewline
88 & 11.4 & 10.7478 & 0.652211 \tabularnewline
89 & 8.6 & 10.0936 & -1.49358 \tabularnewline
90 & 13.2 & 11.0284 & 2.17159 \tabularnewline
91 & 12.6 & 10.3219 & 2.27807 \tabularnewline
92 & 5.6 & 11.0811 & -5.48114 \tabularnewline
93 & 9.9 & 11.4002 & -1.50018 \tabularnewline
94 & 8.8 & 11.8552 & -3.05519 \tabularnewline
95 & 7.7 & 11.6395 & -3.93951 \tabularnewline
96 & 9 & 10.3851 & -1.3851 \tabularnewline
97 & 7.3 & 12.2386 & -4.93862 \tabularnewline
98 & 11.4 & 10.9311 & 0.46887 \tabularnewline
99 & 13.6 & 11.3616 & 2.2384 \tabularnewline
100 & 7.9 & 10.6549 & -2.75493 \tabularnewline
101 & 10.7 & 10.9173 & -0.21727 \tabularnewline
102 & 10.3 & 11.6423 & -1.34227 \tabularnewline
103 & 8.3 & 10.2548 & -1.95483 \tabularnewline
104 & 9.6 & 10.9569 & -1.3569 \tabularnewline
105 & 14.2 & 11.6909 & 2.50913 \tabularnewline
106 & 8.5 & 10.3758 & -1.87576 \tabularnewline
107 & 13.5 & 10.6262 & 2.87385 \tabularnewline
108 & 4.9 & 10.7004 & -5.80038 \tabularnewline
109 & 6.4 & 10.1342 & -3.73424 \tabularnewline
110 & 9.6 & 10.4174 & -0.817419 \tabularnewline
111 & 11.6 & 10.7888 & 0.811202 \tabularnewline
112 & 11.1 & 10.2821 & 0.817893 \tabularnewline
113 & 4.35 & 9.4928 & -5.1428 \tabularnewline
114 & 12.7 & 12.5045 & 0.195519 \tabularnewline
115 & 18.1 & 14.7172 & 3.38277 \tabularnewline
116 & 17.85 & 15.0349 & 2.81507 \tabularnewline
117 & 16.6 & 15.9672 & 0.632849 \tabularnewline
118 & 12.6 & 9.53436 & 3.06564 \tabularnewline
119 & 17.1 & 22.1329 & -5.03294 \tabularnewline
120 & 19.1 & 15.5495 & 3.55048 \tabularnewline
121 & 16.1 & 18.5132 & -2.41317 \tabularnewline
122 & 13.35 & 10.5333 & 2.81675 \tabularnewline
123 & 18.4 & 17.5762 & 0.82385 \tabularnewline
124 & 14.7 & 10.9038 & 3.79623 \tabularnewline
125 & 10.6 & 14.6869 & -4.08689 \tabularnewline
126 & 12.6 & 13.6578 & -1.05778 \tabularnewline
127 & 16.2 & 15.0276 & 1.17245 \tabularnewline
128 & 13.6 & 17.1098 & -3.50983 \tabularnewline
129 & 18.9 & 16.0775 & 2.82253 \tabularnewline
130 & 14.1 & 12.2636 & 1.8364 \tabularnewline
131 & 14.5 & 11.7727 & 2.72726 \tabularnewline
132 & 16.15 & 18.0468 & -1.89683 \tabularnewline
133 & 14.75 & 13.058 & 1.69196 \tabularnewline
134 & 14.8 & 14.1321 & 0.667918 \tabularnewline
135 & 12.45 & 12.2065 & 0.243458 \tabularnewline
136 & 12.65 & 14.6201 & -1.97012 \tabularnewline
137 & 17.35 & 13.7106 & 3.63944 \tabularnewline
138 & 8.6 & 11.9265 & -3.32645 \tabularnewline
139 & 18.4 & 17.6077 & 0.79232 \tabularnewline
140 & 16.1 & 18.0183 & -1.91834 \tabularnewline
141 & 11.6 & 10.6715 & 0.928526 \tabularnewline
142 & 17.75 & 11.6226 & 6.12744 \tabularnewline
143 & 15.25 & 13.6528 & 1.59721 \tabularnewline
144 & 17.65 & 16.1465 & 1.50351 \tabularnewline
145 & 16.35 & 14.6316 & 1.71835 \tabularnewline
146 & 17.65 & 14.8646 & 2.78539 \tabularnewline
147 & 13.6 & 12.8943 & 0.705716 \tabularnewline
148 & 14.35 & 13.4024 & 0.947607 \tabularnewline
149 & 14.75 & 17.9888 & -3.23883 \tabularnewline
150 & 18.25 & 16.2717 & 1.97835 \tabularnewline
151 & 9.9 & 15.1275 & -5.2275 \tabularnewline
152 & 16 & 14.0053 & 1.99466 \tabularnewline
153 & 18.25 & 15.6106 & 2.63943 \tabularnewline
154 & 16.85 & 17.2864 & -0.436379 \tabularnewline
155 & 14.6 & 12.4125 & 2.18752 \tabularnewline
156 & 13.85 & 13.7178 & 0.132226 \tabularnewline
157 & 18.95 & 16.289 & 2.66101 \tabularnewline
158 & 15.6 & 14.5017 & 1.09828 \tabularnewline
159 & 14.85 & 17.2774 & -2.42737 \tabularnewline
160 & 11.75 & 12.6594 & -0.909422 \tabularnewline
161 & 18.45 & 12.8217 & 5.62831 \tabularnewline
162 & 15.9 & 17.2987 & -1.39866 \tabularnewline
163 & 17.1 & 14.4476 & 2.65244 \tabularnewline
164 & 16.1 & 10.7011 & 5.39894 \tabularnewline
165 & 19.9 & 14.6918 & 5.20819 \tabularnewline
166 & 10.95 & 10.6206 & 0.32944 \tabularnewline
167 & 18.45 & 15.7299 & 2.72007 \tabularnewline
168 & 15.1 & 10.4043 & 4.69573 \tabularnewline
169 & 15 & 15.3723 & -0.372258 \tabularnewline
170 & 11.35 & 13.9905 & -2.6405 \tabularnewline
171 & 15.95 & 14.9606 & 0.989428 \tabularnewline
172 & 18.1 & 13.2081 & 4.89191 \tabularnewline
173 & 14.6 & 12.7778 & 1.82218 \tabularnewline
174 & 15.4 & 15.652 & -0.252 \tabularnewline
175 & 15.4 & 15.652 & -0.252 \tabularnewline
176 & 17.6 & 13.475 & 4.12498 \tabularnewline
177 & 13.35 & 13.7588 & -0.408824 \tabularnewline
178 & 19.1 & 16.5912 & 2.50883 \tabularnewline
179 & 15.35 & 12.9708 & 2.37922 \tabularnewline
180 & 7.6 & 12.074 & -4.47396 \tabularnewline
181 & 13.4 & 13.8652 & -0.465164 \tabularnewline
182 & 13.9 & 13.7912 & 0.108822 \tabularnewline
183 & 19.1 & 17.1317 & 1.96826 \tabularnewline
184 & 15.25 & 13.7438 & 1.5062 \tabularnewline
185 & 12.9 & 11.9637 & 0.936286 \tabularnewline
186 & 16.1 & 13.746 & 2.354 \tabularnewline
187 & 17.35 & 12.1481 & 5.20195 \tabularnewline
188 & 13.15 & 12.2094 & 0.940573 \tabularnewline
189 & 12.15 & 9.70364 & 2.44636 \tabularnewline
190 & 12.6 & 12.477 & 0.123007 \tabularnewline
191 & 10.35 & 11.3651 & -1.01506 \tabularnewline
192 & 15.4 & 12.969 & 2.43097 \tabularnewline
193 & 9.6 & 10.7759 & -1.17586 \tabularnewline
194 & 18.2 & 13.1312 & 5.06878 \tabularnewline
195 & 13.6 & 11.9912 & 1.60882 \tabularnewline
196 & 14.85 & 14.484 & 0.366007 \tabularnewline
197 & 14.75 & 16.9434 & -2.19343 \tabularnewline
198 & 14.1 & 14.1426 & -0.0425754 \tabularnewline
199 & 14.9 & 11.5366 & 3.36337 \tabularnewline
200 & 16.25 & 12.6509 & 3.59912 \tabularnewline
201 & 19.25 & 17.4822 & 1.76784 \tabularnewline
202 & 13.6 & 11.8302 & 1.76982 \tabularnewline
203 & 13.6 & 13.2076 & 0.392376 \tabularnewline
204 & 15.65 & 15.0942 & 0.555806 \tabularnewline
205 & 12.75 & 12.4439 & 0.30613 \tabularnewline
206 & 14.6 & 10.9752 & 3.62479 \tabularnewline
207 & 9.85 & 13.1944 & -3.34436 \tabularnewline
208 & 12.65 & 10.9401 & 1.7099 \tabularnewline
209 & 19.2 & 16.448 & 2.75197 \tabularnewline
210 & 16.6 & 14.5107 & 2.08933 \tabularnewline
211 & 11.2 & 9.80906 & 1.39094 \tabularnewline
212 & 15.25 & 13.3648 & 1.88523 \tabularnewline
213 & 11.9 & 15.106 & -3.20597 \tabularnewline
214 & 13.2 & 16.0597 & -2.85974 \tabularnewline
215 & 16.35 & 17.1905 & -0.840543 \tabularnewline
216 & 12.4 & 13.2821 & -0.882115 \tabularnewline
217 & 15.85 & 12.8258 & 3.02421 \tabularnewline
218 & 18.15 & 14.9506 & 3.19935 \tabularnewline
219 & 11.15 & 11.3122 & -0.162194 \tabularnewline
220 & 15.65 & 15.8044 & -0.154428 \tabularnewline
221 & 17.75 & 16.1622 & 1.58778 \tabularnewline
222 & 7.65 & 12.353 & -4.70301 \tabularnewline
223 & 12.35 & 12.1289 & 0.221107 \tabularnewline
224 & 15.6 & 11.4234 & 4.17664 \tabularnewline
225 & 19.3 & 16.2681 & 3.03191 \tabularnewline
226 & 15.2 & 11.652 & 3.54801 \tabularnewline
227 & 17.1 & 13.3322 & 3.76777 \tabularnewline
228 & 15.6 & 12.8532 & 2.7468 \tabularnewline
229 & 18.4 & 14.9891 & 3.4109 \tabularnewline
230 & 19.05 & 15.0972 & 3.95281 \tabularnewline
231 & 18.55 & 13.1541 & 5.39591 \tabularnewline
232 & 19.1 & 17.2371 & 1.86293 \tabularnewline
233 & 13.1 & 11.6519 & 1.44813 \tabularnewline
234 & 12.85 & 13.1178 & -0.267775 \tabularnewline
235 & 9.5 & 11.4301 & -1.9301 \tabularnewline
236 & 4.5 & 11.0667 & -6.56671 \tabularnewline
237 & 11.85 & 10.3896 & 1.4604 \tabularnewline
238 & 13.6 & 15.7914 & -2.19137 \tabularnewline
239 & 11.7 & 13.2713 & -1.57125 \tabularnewline
240 & 12.4 & 11.307 & 1.09298 \tabularnewline
241 & 13.35 & 14.7894 & -1.43941 \tabularnewline
242 & 11.4 & 13.7337 & -2.33369 \tabularnewline
243 & 14.9 & 11.5328 & 3.36717 \tabularnewline
244 & 19.9 & 14.6918 & 5.20819 \tabularnewline
245 & 11.2 & 11.988 & -0.788012 \tabularnewline
246 & 14.6 & 15.3895 & -0.789538 \tabularnewline
247 & 17.6 & 16.0038 & 1.59616 \tabularnewline
248 & 14.05 & 12.6815 & 1.36847 \tabularnewline
249 & 16.1 & 15.2487 & 0.851348 \tabularnewline
250 & 13.35 & 12.743 & 0.606991 \tabularnewline
251 & 11.85 & 11.9491 & -0.0990825 \tabularnewline
252 & 11.95 & 14.2494 & -2.29944 \tabularnewline
253 & 14.75 & 14.5569 & 0.193136 \tabularnewline
254 & 15.15 & 13.0454 & 2.10457 \tabularnewline
255 & 13.2 & 13.6427 & -0.442664 \tabularnewline
256 & 16.85 & 15.7076 & 1.14242 \tabularnewline
257 & 7.85 & 10.0333 & -2.18333 \tabularnewline
258 & 7.7 & 14.9003 & -7.20033 \tabularnewline
259 & 12.6 & 11.0258 & 1.57424 \tabularnewline
260 & 7.85 & 11.3741 & -3.52406 \tabularnewline
261 & 10.95 & 10.6206 & 0.32944 \tabularnewline
262 & 12.35 & 11.8675 & 0.482536 \tabularnewline
263 & 9.95 & 12.4379 & -2.48791 \tabularnewline
264 & 14.9 & 11.5328 & 3.36717 \tabularnewline
265 & 16.65 & 14.8573 & 1.79267 \tabularnewline
266 & 13.4 & 12.8631 & 0.536896 \tabularnewline
267 & 13.95 & 13.6228 & 0.327249 \tabularnewline
268 & 15.7 & 11.4103 & 4.28967 \tabularnewline
269 & 16.85 & 12.2082 & 4.64182 \tabularnewline
270 & 10.95 & 10.258 & 0.692006 \tabularnewline
271 & 15.35 & 11.5812 & 3.76885 \tabularnewline
272 & 12.2 & 11.0002 & 1.19977 \tabularnewline
273 & 15.1 & 13.9761 & 1.12386 \tabularnewline
274 & 17.75 & 15.9857 & 1.7643 \tabularnewline
275 & 15.2 & 12.6761 & 2.52387 \tabularnewline
276 & 14.6 & 13.2339 & 1.36609 \tabularnewline
277 & 16.65 & 14.2857 & 2.36427 \tabularnewline
278 & 8.1 & 10.6297 & -2.52974 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&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]12.0374[/C][C]0.862594[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.4742[/C][C]0.725754[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.1511[/C][C]0.648917[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.7689[/C][C]-5.36894[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.3722[/C][C]-4.67222[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]15.3551[/C][C]-2.75513[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.7456[/C][C]2.05442[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.2811[/C][C]1.0189[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.657[/C][C]-1.55699[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.2214[/C][C]-6.02141[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.9667[/C][C]-1.5667[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.5954[/C][C]-8.19541[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]11.5398[/C][C]-0.939825[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.6616[/C][C]-1.66161[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.69435[/C][C]-3.39435[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.2693[/C][C]0.0306585[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]13.8696[/C][C]-1.96961[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.1032[/C][C]-2.80324[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.2659[/C][C]-2.66591[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]11.5919[/C][C]-1.59185[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.7226[/C][C]-5.32264[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.7935[/C][C]1.00648[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.3746[/C][C]-2.57461[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.3281[/C][C]1.47188[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.68[/C][C]-0.97996[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]15.1718[/C][C]-4.27176[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.352[/C][C]2.74796[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]11.1054[/C][C]2.29465[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.2788[/C][C]-1.37883[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.2213[/C][C]-0.721283[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]11.8681[/C][C]-3.56809[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3529[/C][C]-1.65294[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.3188[/C][C]-3.31875[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]14.3323[/C][C]-4.6323[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.498[/C][C]-1.69802[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.7269[/C][C]-2.42691[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.7532[/C][C]-1.35324[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6423[/C][C]0.0577352[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.2337[/C][C]-2.93371[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.3134[/C][C]-2.51335[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.6132[/C][C]-4.71315[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.8881[/C][C]-2.48809[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.7958[/C][C]1.20418[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.6472[/C][C]-1.84717[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]10.3861[/C][C]1.9139[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.4472[/C][C]-2.14722[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.5109[/C][C]-0.710864[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]11.0605[/C][C]-3.16053[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.1089[/C][C]2.59111[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]10.7501[/C][C]1.54992[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]11.9871[/C][C]-0.387093[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]10.9669[/C][C]-4.26687[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.156[/C][C]-2.25599[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.6491[/C][C]-0.549065[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.4855[/C][C]-0.185454[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]13.3308[/C][C]-3.23083[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.7[/C][C]-6.00003[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.2012[/C][C]2.09876[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.42632[/C][C]-1.42632[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]11.735[/C][C]1.56505[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.8225[/C][C]-3.5225[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.6198[/C][C]0.880173[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.7917[/C][C]-3.19174[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.9203[/C][C]1.97967[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]11.4599[/C][C]-2.2599[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]10.4935[/C][C]-1.39355[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]14.1507[/C][C]-3.05068[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.8018[/C][C]-0.80185[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.8761[/C][C]1.62386[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]11.0188[/C][C]1.18123[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.4909[/C][C]-1.1909[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.3198[/C][C]0.0802311[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]11.2563[/C][C]-2.45626[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.1039[/C][C]3.49606[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.997[/C][C]-0.397045[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.7127[/C][C]-0.712703[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]11.2207[/C][C]1.37933[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]14.7275[/C][C]-1.52752[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]11.1645[/C][C]-1.26449[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]11.4798[/C][C]-3.7798[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.6017[/C][C]-0.101678[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.6034[/C][C]2.79657[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]11.8219[/C][C]-0.921873[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]10.0652[/C][C]-5.76517[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.0451[/C][C]-0.745138[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.6269[/C][C]0.173113[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]10.5694[/C][C]0.630556[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]10.7478[/C][C]0.652211[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.0936[/C][C]-1.49358[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.0284[/C][C]2.17159[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]10.3219[/C][C]2.27807[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]11.0811[/C][C]-5.48114[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.4002[/C][C]-1.50018[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]11.8552[/C][C]-3.05519[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]11.6395[/C][C]-3.93951[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.3851[/C][C]-1.3851[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]12.2386[/C][C]-4.93862[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]10.9311[/C][C]0.46887[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]11.3616[/C][C]2.2384[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.6549[/C][C]-2.75493[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]10.9173[/C][C]-0.21727[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]11.6423[/C][C]-1.34227[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]10.2548[/C][C]-1.95483[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.9569[/C][C]-1.3569[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]11.6909[/C][C]2.50913[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.3758[/C][C]-1.87576[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]10.6262[/C][C]2.87385[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]10.7004[/C][C]-5.80038[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]10.1342[/C][C]-3.73424[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.4174[/C][C]-0.817419[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.7888[/C][C]0.811202[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]10.2821[/C][C]0.817893[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]9.4928[/C][C]-5.1428[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.5045[/C][C]0.195519[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]14.7172[/C][C]3.38277[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]15.0349[/C][C]2.81507[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]15.9672[/C][C]0.632849[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]9.53436[/C][C]3.06564[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]22.1329[/C][C]-5.03294[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]15.5495[/C][C]3.55048[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.5132[/C][C]-2.41317[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]10.5333[/C][C]2.81675[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]17.5762[/C][C]0.82385[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]10.9038[/C][C]3.79623[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]14.6869[/C][C]-4.08689[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.6578[/C][C]-1.05778[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]15.0276[/C][C]1.17245[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]17.1098[/C][C]-3.50983[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]16.0775[/C][C]2.82253[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.2636[/C][C]1.8364[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]11.7727[/C][C]2.72726[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]18.0468[/C][C]-1.89683[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.058[/C][C]1.69196[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]14.1321[/C][C]0.667918[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.2065[/C][C]0.243458[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]14.6201[/C][C]-1.97012[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.7106[/C][C]3.63944[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]11.9265[/C][C]-3.32645[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]17.6077[/C][C]0.79232[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]18.0183[/C][C]-1.91834[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]10.6715[/C][C]0.928526[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]11.6226[/C][C]6.12744[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]13.6528[/C][C]1.59721[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]16.1465[/C][C]1.50351[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]14.6316[/C][C]1.71835[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]14.8646[/C][C]2.78539[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.8943[/C][C]0.705716[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.4024[/C][C]0.947607[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]17.9888[/C][C]-3.23883[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.2717[/C][C]1.97835[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]15.1275[/C][C]-5.2275[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]14.0053[/C][C]1.99466[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]15.6106[/C][C]2.63943[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]17.2864[/C][C]-0.436379[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.4125[/C][C]2.18752[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.7178[/C][C]0.132226[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]16.289[/C][C]2.66101[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.5017[/C][C]1.09828[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]17.2774[/C][C]-2.42737[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.6594[/C][C]-0.909422[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]12.8217[/C][C]5.62831[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]17.2987[/C][C]-1.39866[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]14.4476[/C][C]2.65244[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]10.7011[/C][C]5.39894[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]14.6918[/C][C]5.20819[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]10.6206[/C][C]0.32944[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]15.7299[/C][C]2.72007[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]10.4043[/C][C]4.69573[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.3723[/C][C]-0.372258[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]13.9905[/C][C]-2.6405[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]14.9606[/C][C]0.989428[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]13.2081[/C][C]4.89191[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.7778[/C][C]1.82218[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]15.652[/C][C]-0.252[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.652[/C][C]-0.252[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]13.475[/C][C]4.12498[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.7588[/C][C]-0.408824[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.5912[/C][C]2.50883[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.9708[/C][C]2.37922[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.074[/C][C]-4.47396[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.8652[/C][C]-0.465164[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.7912[/C][C]0.108822[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]17.1317[/C][C]1.96826[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.7438[/C][C]1.5062[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]11.9637[/C][C]0.936286[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.746[/C][C]2.354[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]12.1481[/C][C]5.20195[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.2094[/C][C]0.940573[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]9.70364[/C][C]2.44636[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.477[/C][C]0.123007[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]11.3651[/C][C]-1.01506[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.969[/C][C]2.43097[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]10.7759[/C][C]-1.17586[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.1312[/C][C]5.06878[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]11.9912[/C][C]1.60882[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]14.484[/C][C]0.366007[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]16.9434[/C][C]-2.19343[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]14.1426[/C][C]-0.0425754[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]11.5366[/C][C]3.36337[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]12.6509[/C][C]3.59912[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]17.4822[/C][C]1.76784[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]11.8302[/C][C]1.76982[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.2076[/C][C]0.392376[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.0942[/C][C]0.555806[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.4439[/C][C]0.30613[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]10.9752[/C][C]3.62479[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]13.1944[/C][C]-3.34436[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]10.9401[/C][C]1.7099[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]16.448[/C][C]2.75197[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]14.5107[/C][C]2.08933[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]9.80906[/C][C]1.39094[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]13.3648[/C][C]1.88523[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]15.106[/C][C]-3.20597[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]16.0597[/C][C]-2.85974[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]17.1905[/C][C]-0.840543[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.2821[/C][C]-0.882115[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.8258[/C][C]3.02421[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]14.9506[/C][C]3.19935[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]11.3122[/C][C]-0.162194[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]15.8044[/C][C]-0.154428[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]16.1622[/C][C]1.58778[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.353[/C][C]-4.70301[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]12.1289[/C][C]0.221107[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]11.4234[/C][C]4.17664[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.2681[/C][C]3.03191[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]11.652[/C][C]3.54801[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.3322[/C][C]3.76777[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.8532[/C][C]2.7468[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]14.9891[/C][C]3.4109[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]15.0972[/C][C]3.95281[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.1541[/C][C]5.39591[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]17.2371[/C][C]1.86293[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]11.6519[/C][C]1.44813[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]13.1178[/C][C]-0.267775[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.4301[/C][C]-1.9301[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.0667[/C][C]-6.56671[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]10.3896[/C][C]1.4604[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]15.7914[/C][C]-2.19137[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]13.2713[/C][C]-1.57125[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]11.307[/C][C]1.09298[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.7894[/C][C]-1.43941[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.7337[/C][C]-2.33369[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]11.5328[/C][C]3.36717[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]14.6918[/C][C]5.20819[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]11.988[/C][C]-0.788012[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.3895[/C][C]-0.789538[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]16.0038[/C][C]1.59616[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.6815[/C][C]1.36847[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.2487[/C][C]0.851348[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.743[/C][C]0.606991[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]11.9491[/C][C]-0.0990825[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]14.2494[/C][C]-2.29944[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.5569[/C][C]0.193136[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]13.0454[/C][C]2.10457[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]13.6427[/C][C]-0.442664[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]15.7076[/C][C]1.14242[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]10.0333[/C][C]-2.18333[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]14.9003[/C][C]-7.20033[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]11.0258[/C][C]1.57424[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]11.3741[/C][C]-3.52406[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]10.6206[/C][C]0.32944[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]11.8675[/C][C]0.482536[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]12.4379[/C][C]-2.48791[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]11.5328[/C][C]3.36717[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]14.8573[/C][C]1.79267[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]12.8631[/C][C]0.536896[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.6228[/C][C]0.327249[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]11.4103[/C][C]4.28967[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.2082[/C][C]4.64182[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.258[/C][C]0.692006[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]11.5812[/C][C]3.76885[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]11.0002[/C][C]1.19977[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]13.9761[/C][C]1.12386[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]15.9857[/C][C]1.7643[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]12.6761[/C][C]2.52387[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.2339[/C][C]1.36609[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]14.2857[/C][C]2.36427[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]10.6297[/C][C]-2.52974[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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
112.912.03740.862594
212.211.47420.725754
312.812.15110.648917
47.412.7689-5.36894
56.711.3722-4.67222
612.615.3551-2.75513
714.812.74562.05442
813.312.28111.0189
911.112.657-1.55699
108.214.2214-6.02141
1111.412.9667-1.5667
126.414.5954-8.19541
1310.611.5398-0.939825
141213.6616-1.66161
156.39.69435-3.39435
1611.311.26930.0306585
1711.913.8696-1.96961
189.312.1032-2.80324
199.612.2659-2.66591
201011.5919-1.59185
216.411.7226-5.32264
2213.812.79351.00648
2310.813.3746-2.57461
2413.812.32811.47188
2511.712.68-0.97996
2610.915.1718-4.27176
2716.113.3522.74796
2813.411.10542.29465
299.911.2788-1.37883
3011.512.2213-0.721283
318.311.8681-3.56809
3211.713.3529-1.65294
33912.3188-3.31875
349.714.3323-4.6323
3510.812.498-1.69802
3610.312.7269-2.42691
3710.411.7532-1.35324
3812.712.64230.0577352
399.312.2337-2.93371
4011.814.3134-2.51335
415.910.6132-4.71315
4211.413.8881-2.48809
431311.79581.20418
4410.812.6472-1.84717
4512.310.38611.9139
4611.313.4472-2.14722
4711.812.5109-0.710864
487.911.0605-3.16053
4912.710.10892.59111
5012.310.75011.54992
5111.611.9871-0.387093
526.710.9669-4.26687
5310.913.156-2.25599
5412.112.6491-0.549065
5513.313.4855-0.185454
5610.113.3308-3.23083
575.711.7-6.00003
5814.312.20122.09876
5989.42632-1.42632
6013.311.7351.56505
619.312.8225-3.5225
6212.511.61980.880173
637.610.7917-3.19174
6415.913.92031.97967
659.211.4599-2.2599
669.110.4935-1.39355
6711.114.1507-3.05068
681313.8018-0.80185
6914.512.87611.62386
7012.211.01881.18123
7112.313.4909-1.1909
7211.411.31980.0802311
738.811.2563-2.45626
7414.611.10393.49606
7512.612.997-0.397045
761313.7127-0.712703
7712.611.22071.37933
7813.214.7275-1.52752
799.911.1645-1.26449
807.711.4798-3.7798
8110.510.6017-0.101678
8213.410.60342.79657
8310.911.8219-0.921873
844.310.0652-5.76517
8510.311.0451-0.745138
8611.811.62690.173113
8711.210.56940.630556
8811.410.74780.652211
898.610.0936-1.49358
9013.211.02842.17159
9112.610.32192.27807
925.611.0811-5.48114
939.911.4002-1.50018
948.811.8552-3.05519
957.711.6395-3.93951
96910.3851-1.3851
977.312.2386-4.93862
9811.410.93110.46887
9913.611.36162.2384
1007.910.6549-2.75493
10110.710.9173-0.21727
10210.311.6423-1.34227
1038.310.2548-1.95483
1049.610.9569-1.3569
10514.211.69092.50913
1068.510.3758-1.87576
10713.510.62622.87385
1084.910.7004-5.80038
1096.410.1342-3.73424
1109.610.4174-0.817419
11111.610.78880.811202
11211.110.28210.817893
1134.359.4928-5.1428
11412.712.50450.195519
11518.114.71723.38277
11617.8515.03492.81507
11716.615.96720.632849
11812.69.534363.06564
11917.122.1329-5.03294
12019.115.54953.55048
12116.118.5132-2.41317
12213.3510.53332.81675
12318.417.57620.82385
12414.710.90383.79623
12510.614.6869-4.08689
12612.613.6578-1.05778
12716.215.02761.17245
12813.617.1098-3.50983
12918.916.07752.82253
13014.112.26361.8364
13114.511.77272.72726
13216.1518.0468-1.89683
13314.7513.0581.69196
13414.814.13210.667918
13512.4512.20650.243458
13612.6514.6201-1.97012
13717.3513.71063.63944
1388.611.9265-3.32645
13918.417.60770.79232
14016.118.0183-1.91834
14111.610.67150.928526
14217.7511.62266.12744
14315.2513.65281.59721
14417.6516.14651.50351
14516.3514.63161.71835
14617.6514.86462.78539
14713.612.89430.705716
14814.3513.40240.947607
14914.7517.9888-3.23883
15018.2516.27171.97835
1519.915.1275-5.2275
1521614.00531.99466
15318.2515.61062.63943
15416.8517.2864-0.436379
15514.612.41252.18752
15613.8513.71780.132226
15718.9516.2892.66101
15815.614.50171.09828
15914.8517.2774-2.42737
16011.7512.6594-0.909422
16118.4512.82175.62831
16215.917.2987-1.39866
16317.114.44762.65244
16416.110.70115.39894
16519.914.69185.20819
16610.9510.62060.32944
16718.4515.72992.72007
16815.110.40434.69573
1691515.3723-0.372258
17011.3513.9905-2.6405
17115.9514.96060.989428
17218.113.20814.89191
17314.612.77781.82218
17415.415.652-0.252
17515.415.652-0.252
17617.613.4754.12498
17713.3513.7588-0.408824
17819.116.59122.50883
17915.3512.97082.37922
1807.612.074-4.47396
18113.413.8652-0.465164
18213.913.79120.108822
18319.117.13171.96826
18415.2513.74381.5062
18512.911.96370.936286
18616.113.7462.354
18717.3512.14815.20195
18813.1512.20940.940573
18912.159.703642.44636
19012.612.4770.123007
19110.3511.3651-1.01506
19215.412.9692.43097
1939.610.7759-1.17586
19418.213.13125.06878
19513.611.99121.60882
19614.8514.4840.366007
19714.7516.9434-2.19343
19814.114.1426-0.0425754
19914.911.53663.36337
20016.2512.65093.59912
20119.2517.48221.76784
20213.611.83021.76982
20313.613.20760.392376
20415.6515.09420.555806
20512.7512.44390.30613
20614.610.97523.62479
2079.8513.1944-3.34436
20812.6510.94011.7099
20919.216.4482.75197
21016.614.51072.08933
21111.29.809061.39094
21215.2513.36481.88523
21311.915.106-3.20597
21413.216.0597-2.85974
21516.3517.1905-0.840543
21612.413.2821-0.882115
21715.8512.82583.02421
21818.1514.95063.19935
21911.1511.3122-0.162194
22015.6515.8044-0.154428
22117.7516.16221.58778
2227.6512.353-4.70301
22312.3512.12890.221107
22415.611.42344.17664
22519.316.26813.03191
22615.211.6523.54801
22717.113.33223.76777
22815.612.85322.7468
22918.414.98913.4109
23019.0515.09723.95281
23118.5513.15415.39591
23219.117.23711.86293
23313.111.65191.44813
23412.8513.1178-0.267775
2359.511.4301-1.9301
2364.511.0667-6.56671
23711.8510.38961.4604
23813.615.7914-2.19137
23911.713.2713-1.57125
24012.411.3071.09298
24113.3514.7894-1.43941
24211.413.7337-2.33369
24314.911.53283.36717
24419.914.69185.20819
24511.211.988-0.788012
24614.615.3895-0.789538
24717.616.00381.59616
24814.0512.68151.36847
24916.115.24870.851348
25013.3512.7430.606991
25111.8511.9491-0.0990825
25211.9514.2494-2.29944
25314.7514.55690.193136
25415.1513.04542.10457
25513.213.6427-0.442664
25616.8515.70761.14242
2577.8510.0333-2.18333
2587.714.9003-7.20033
25912.611.02581.57424
2607.8511.3741-3.52406
26110.9510.62060.32944
26212.3511.86750.482536
2639.9512.4379-2.48791
26414.911.53283.36717
26516.6514.85731.79267
26613.412.86310.536896
26713.9513.62280.327249
26815.711.41034.28967
26916.8512.20824.64182
27010.9510.2580.692006
27115.3511.58123.76885
27212.211.00021.19977
27315.113.97611.12386
27417.7515.98571.7643
27515.212.67612.52387
27614.613.23391.36609
27716.6514.28572.36427
2788.110.6297-2.52974






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9072230.1855540.0927769
100.9051520.1896950.0948477
110.8388140.3223720.161186
120.8692030.2615930.130797
130.8126360.3747290.187364
140.7371120.5257750.262888
150.6757320.6485350.324268
160.6889160.6221680.311084
170.624280.751440.37572
180.5444350.9111310.455565
190.4694350.9388710.530565
200.3927520.7855050.607248
210.46630.9326010.5337
220.4804090.9608180.519591
230.4152770.8305550.584723
240.3508670.7017340.649133
250.2925570.5851130.707443
260.2547050.509410.745295
270.2156420.4312850.784358
280.2754570.5509140.724543
290.2464510.4929020.753549
300.2221230.4442450.777877
310.1921770.3843540.807823
320.1895050.379010.810495
330.1587190.3174380.841281
340.1623020.3246050.837698
350.1360040.2720080.863996
360.1121710.2243430.887829
370.08940580.1788120.910594
380.1040590.2081180.895941
390.1251180.2502360.874882
400.1116620.2233240.888338
410.1706660.3413330.829334
420.1479190.2958390.852081
430.130470.260940.86953
440.1102080.2204170.889792
450.1138640.2277280.886136
460.09648370.1929670.903516
470.08056880.1611380.919431
480.1003030.2006060.899697
490.09877730.1975550.901223
500.1058180.2116370.894182
510.09113630.1822730.908864
520.09596980.191940.90403
530.08733190.1746640.912668
540.08534560.1706910.914654
550.08628370.1725670.913716
560.07467680.1493540.925323
570.1303420.2606840.869658
580.1590540.3181070.840946
590.135580.2711590.86442
600.141170.282340.85883
610.1566080.3132160.843392
620.1496810.2993620.850319
630.1579610.3159220.842039
640.1940130.3880250.805987
650.1932920.3865840.806708
660.1683720.3367440.831628
670.1697060.3394120.830294
680.1562710.3125410.843729
690.1664960.3329920.833504
700.1538780.3077550.846122
710.1406110.2812230.859389
720.1243290.2486580.875671
730.1123120.2246240.887688
740.1185590.2371170.881441
750.1102470.2204950.889753
760.1021330.2042650.897867
770.09708970.1941790.90291
780.09620530.1924110.903795
790.08163660.1632730.918363
800.1046160.2092310.895384
810.08889040.1777810.91111
820.09851280.1970260.901487
830.0845010.1690020.915499
840.1787370.3574740.821263
850.1641480.3282960.835852
860.1446540.2893080.855346
870.1253930.2507870.874607
880.1098750.2197490.890125
890.103520.207040.89648
900.1073510.2147020.892649
910.1126210.2252420.887379
920.1876630.3753270.812337
930.1887030.3774070.811297
940.1832590.3665180.816741
950.2000390.4000770.799961
960.1950.390.805
970.2657020.5314030.734298
980.2529990.5059980.747001
990.2974820.5949640.702518
1000.354210.7084210.64579
1010.3275930.6551870.672407
1020.3119860.6239720.688014
1030.3149550.6299110.685045
1040.3325670.6651350.667433
1050.3640480.7280950.635952
1060.3911090.7822180.608891
1070.4087230.8174460.591277
1080.6288490.7423020.371151
1090.674130.651740.32587
1100.6840540.6318930.315946
1110.6786280.6427440.321372
1120.6667360.6665270.333264
1130.7282230.5435540.271777
1140.7213690.5572620.278631
1150.8325060.3349880.167494
1160.8829670.2340660.117033
1170.8717580.2564850.128242
1180.914750.17050.08525
1190.9091990.1816010.0908007
1200.9272040.1455920.0727961
1210.939640.1207190.0603597
1220.948690.102620.0513099
1230.951390.09721910.0486096
1240.9699720.06005610.030028
1250.9740840.05183180.0259159
1260.969770.06045910.0302296
1270.9691110.06177750.0308888
1280.9659950.06801040.0340052
1290.9646910.07061780.0353089
1300.9630580.07388480.0369424
1310.965340.06932030.0346602
1320.9635930.07281470.0364074
1330.9666430.06671320.0333566
1340.9612410.07751730.0387586
1350.9540770.0918470.0459235
1360.947060.1058810.0529404
1370.9620150.07597090.0379855
1380.9620790.07584250.0379213
1390.9584310.08313750.0415687
1400.9511160.09776880.0488844
1410.9459810.1080380.0540188
1420.973390.05321970.0266098
1430.9723090.05538280.0276914
1440.9723750.05525030.0276251
1450.9685140.06297170.0314858
1460.9691280.06174370.0308718
1470.9642330.07153350.0357668
1480.9585140.08297130.0414856
1490.9531220.09375540.0468777
1500.951920.09616050.0480802
1510.982090.03581970.0179098
1520.980110.0397810.0198905
1530.9809350.03812950.0190647
1540.9769450.04610980.0230549
1550.9780250.043950.021975
1560.9734710.05305870.0265294
1570.9723310.05533770.0276688
1580.9679480.06410350.0320518
1590.9658590.06828190.034141
1600.9602450.07950940.0397547
1610.9727280.05454490.0272725
1620.9682260.06354890.0317745
1630.9692030.06159480.0307974
1640.9939310.01213760.00606879
1650.9952470.009506570.00475329
1660.9939050.01218960.0060948
1670.9938210.01235780.00617892
1680.9960940.00781250.00390625
1690.9949660.01006840.00503422
1700.9952170.00956650.00478325
1710.9942690.01146230.00573116
1720.9961090.007781820.00389091
1730.9956520.008695740.00434787
1740.99440.01119920.00559962
1750.9928590.01428170.00714085
1760.9940510.01189710.00594856
1770.9932830.01343470.00671734
1780.993290.013420.00671002
1790.9923790.01524110.00762054
1800.9940230.01195410.00597706
1810.9935350.01293070.00646534
1820.9921380.01572490.00786243
1830.9909050.01819060.00909528
1840.9886870.0226260.011313
1850.987920.02416010.0120801
1860.9858520.02829690.0141484
1870.9925690.01486160.00743079
1880.9908630.01827360.00913678
1890.9891870.02162610.0108131
1900.9862740.02745180.0137259
1910.9830440.03391260.0169563
1920.9799810.04003770.0200189
1930.9772610.04547750.0227387
1940.9858870.02822630.0141131
1950.9831960.03360740.0168037
1960.981010.03797980.0189899
1970.980850.03830080.0191504
1980.9756720.04865640.0243282
1990.977430.04513920.0225696
2000.9769050.04619080.0230954
2010.9734050.0531890.0265945
2020.97190.05620030.0281002
2030.9683030.06339350.0316968
2040.9614010.0771990.0385995
2050.9537520.09249660.0462483
2060.9654230.06915360.0345768
2070.9618250.07634980.0381749
2080.9604580.07908440.0395422
2090.9560250.08795040.0439752
2100.9488290.1023420.0511711
2110.9388130.1223730.0611867
2120.9279780.1440440.0720219
2130.9415240.1169510.0584757
2140.9321710.1356580.0678292
2150.9286970.1426070.0713035
2160.9162840.1674310.0837156
2170.9133680.1732630.0866317
2180.9028690.1942620.0971311
2190.8822510.2354970.117749
2200.8589120.2821760.141088
2210.8445070.3109860.155493
2220.8634050.273190.136595
2230.8381240.3237530.161876
2240.8442980.3114040.155702
2250.8303920.3392160.169608
2260.8894390.2211230.110561
2270.9112030.1775940.0887972
2280.9133680.1732630.0866315
2290.899730.200540.10027
2300.9162350.167530.0837649
2310.9431930.1136150.0568073
2320.9282110.1435770.0717886
2330.9153390.1693210.0846607
2340.9040660.1918680.0959339
2350.8952010.2095980.104799
2360.9628380.0743240.037162
2370.961690.07661970.0383099
2380.9631090.07378290.0368914
2390.9526610.09467750.0473387
2400.9378570.1242850.0621426
2410.9264780.1470450.0735223
2420.9098450.180310.090155
2430.9041850.191630.0958149
2440.8916480.2167050.108352
2450.8625420.2749150.137458
2460.8313460.3373090.168654
2470.7987020.4025960.201298
2480.7565480.4869040.243452
2490.7074760.5850480.292524
2500.6502420.6995160.349758
2510.5990430.8019140.400957
2520.5976720.8046560.402328
2530.5315310.9369390.468469
2540.466620.9332390.53338
2550.5222890.9554220.477711
2560.4539390.9078780.546061
2570.4532230.9064450.546777
2580.8927250.214550.107275
2590.8512250.297550.148775
2600.9954340.009131150.00456557
2610.9965910.006818230.00340912
2620.9970250.005949530.00297476
2630.9997990.00040110.00020055
2640.9993490.001301640.000650819
2650.9978660.004267660.00213383
2660.9956320.008735480.00436774
2670.9941620.0116770.00583848
2680.9818050.03638930.0181947
2690.9703860.05922790.0296139

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.907223 & 0.185554 & 0.0927769 \tabularnewline
10 & 0.905152 & 0.189695 & 0.0948477 \tabularnewline
11 & 0.838814 & 0.322372 & 0.161186 \tabularnewline
12 & 0.869203 & 0.261593 & 0.130797 \tabularnewline
13 & 0.812636 & 0.374729 & 0.187364 \tabularnewline
14 & 0.737112 & 0.525775 & 0.262888 \tabularnewline
15 & 0.675732 & 0.648535 & 0.324268 \tabularnewline
16 & 0.688916 & 0.622168 & 0.311084 \tabularnewline
17 & 0.62428 & 0.75144 & 0.37572 \tabularnewline
18 & 0.544435 & 0.911131 & 0.455565 \tabularnewline
19 & 0.469435 & 0.938871 & 0.530565 \tabularnewline
20 & 0.392752 & 0.785505 & 0.607248 \tabularnewline
21 & 0.4663 & 0.932601 & 0.5337 \tabularnewline
22 & 0.480409 & 0.960818 & 0.519591 \tabularnewline
23 & 0.415277 & 0.830555 & 0.584723 \tabularnewline
24 & 0.350867 & 0.701734 & 0.649133 \tabularnewline
25 & 0.292557 & 0.585113 & 0.707443 \tabularnewline
26 & 0.254705 & 0.50941 & 0.745295 \tabularnewline
27 & 0.215642 & 0.431285 & 0.784358 \tabularnewline
28 & 0.275457 & 0.550914 & 0.724543 \tabularnewline
29 & 0.246451 & 0.492902 & 0.753549 \tabularnewline
30 & 0.222123 & 0.444245 & 0.777877 \tabularnewline
31 & 0.192177 & 0.384354 & 0.807823 \tabularnewline
32 & 0.189505 & 0.37901 & 0.810495 \tabularnewline
33 & 0.158719 & 0.317438 & 0.841281 \tabularnewline
34 & 0.162302 & 0.324605 & 0.837698 \tabularnewline
35 & 0.136004 & 0.272008 & 0.863996 \tabularnewline
36 & 0.112171 & 0.224343 & 0.887829 \tabularnewline
37 & 0.0894058 & 0.178812 & 0.910594 \tabularnewline
38 & 0.104059 & 0.208118 & 0.895941 \tabularnewline
39 & 0.125118 & 0.250236 & 0.874882 \tabularnewline
40 & 0.111662 & 0.223324 & 0.888338 \tabularnewline
41 & 0.170666 & 0.341333 & 0.829334 \tabularnewline
42 & 0.147919 & 0.295839 & 0.852081 \tabularnewline
43 & 0.13047 & 0.26094 & 0.86953 \tabularnewline
44 & 0.110208 & 0.220417 & 0.889792 \tabularnewline
45 & 0.113864 & 0.227728 & 0.886136 \tabularnewline
46 & 0.0964837 & 0.192967 & 0.903516 \tabularnewline
47 & 0.0805688 & 0.161138 & 0.919431 \tabularnewline
48 & 0.100303 & 0.200606 & 0.899697 \tabularnewline
49 & 0.0987773 & 0.197555 & 0.901223 \tabularnewline
50 & 0.105818 & 0.211637 & 0.894182 \tabularnewline
51 & 0.0911363 & 0.182273 & 0.908864 \tabularnewline
52 & 0.0959698 & 0.19194 & 0.90403 \tabularnewline
53 & 0.0873319 & 0.174664 & 0.912668 \tabularnewline
54 & 0.0853456 & 0.170691 & 0.914654 \tabularnewline
55 & 0.0862837 & 0.172567 & 0.913716 \tabularnewline
56 & 0.0746768 & 0.149354 & 0.925323 \tabularnewline
57 & 0.130342 & 0.260684 & 0.869658 \tabularnewline
58 & 0.159054 & 0.318107 & 0.840946 \tabularnewline
59 & 0.13558 & 0.271159 & 0.86442 \tabularnewline
60 & 0.14117 & 0.28234 & 0.85883 \tabularnewline
61 & 0.156608 & 0.313216 & 0.843392 \tabularnewline
62 & 0.149681 & 0.299362 & 0.850319 \tabularnewline
63 & 0.157961 & 0.315922 & 0.842039 \tabularnewline
64 & 0.194013 & 0.388025 & 0.805987 \tabularnewline
65 & 0.193292 & 0.386584 & 0.806708 \tabularnewline
66 & 0.168372 & 0.336744 & 0.831628 \tabularnewline
67 & 0.169706 & 0.339412 & 0.830294 \tabularnewline
68 & 0.156271 & 0.312541 & 0.843729 \tabularnewline
69 & 0.166496 & 0.332992 & 0.833504 \tabularnewline
70 & 0.153878 & 0.307755 & 0.846122 \tabularnewline
71 & 0.140611 & 0.281223 & 0.859389 \tabularnewline
72 & 0.124329 & 0.248658 & 0.875671 \tabularnewline
73 & 0.112312 & 0.224624 & 0.887688 \tabularnewline
74 & 0.118559 & 0.237117 & 0.881441 \tabularnewline
75 & 0.110247 & 0.220495 & 0.889753 \tabularnewline
76 & 0.102133 & 0.204265 & 0.897867 \tabularnewline
77 & 0.0970897 & 0.194179 & 0.90291 \tabularnewline
78 & 0.0962053 & 0.192411 & 0.903795 \tabularnewline
79 & 0.0816366 & 0.163273 & 0.918363 \tabularnewline
80 & 0.104616 & 0.209231 & 0.895384 \tabularnewline
81 & 0.0888904 & 0.177781 & 0.91111 \tabularnewline
82 & 0.0985128 & 0.197026 & 0.901487 \tabularnewline
83 & 0.084501 & 0.169002 & 0.915499 \tabularnewline
84 & 0.178737 & 0.357474 & 0.821263 \tabularnewline
85 & 0.164148 & 0.328296 & 0.835852 \tabularnewline
86 & 0.144654 & 0.289308 & 0.855346 \tabularnewline
87 & 0.125393 & 0.250787 & 0.874607 \tabularnewline
88 & 0.109875 & 0.219749 & 0.890125 \tabularnewline
89 & 0.10352 & 0.20704 & 0.89648 \tabularnewline
90 & 0.107351 & 0.214702 & 0.892649 \tabularnewline
91 & 0.112621 & 0.225242 & 0.887379 \tabularnewline
92 & 0.187663 & 0.375327 & 0.812337 \tabularnewline
93 & 0.188703 & 0.377407 & 0.811297 \tabularnewline
94 & 0.183259 & 0.366518 & 0.816741 \tabularnewline
95 & 0.200039 & 0.400077 & 0.799961 \tabularnewline
96 & 0.195 & 0.39 & 0.805 \tabularnewline
97 & 0.265702 & 0.531403 & 0.734298 \tabularnewline
98 & 0.252999 & 0.505998 & 0.747001 \tabularnewline
99 & 0.297482 & 0.594964 & 0.702518 \tabularnewline
100 & 0.35421 & 0.708421 & 0.64579 \tabularnewline
101 & 0.327593 & 0.655187 & 0.672407 \tabularnewline
102 & 0.311986 & 0.623972 & 0.688014 \tabularnewline
103 & 0.314955 & 0.629911 & 0.685045 \tabularnewline
104 & 0.332567 & 0.665135 & 0.667433 \tabularnewline
105 & 0.364048 & 0.728095 & 0.635952 \tabularnewline
106 & 0.391109 & 0.782218 & 0.608891 \tabularnewline
107 & 0.408723 & 0.817446 & 0.591277 \tabularnewline
108 & 0.628849 & 0.742302 & 0.371151 \tabularnewline
109 & 0.67413 & 0.65174 & 0.32587 \tabularnewline
110 & 0.684054 & 0.631893 & 0.315946 \tabularnewline
111 & 0.678628 & 0.642744 & 0.321372 \tabularnewline
112 & 0.666736 & 0.666527 & 0.333264 \tabularnewline
113 & 0.728223 & 0.543554 & 0.271777 \tabularnewline
114 & 0.721369 & 0.557262 & 0.278631 \tabularnewline
115 & 0.832506 & 0.334988 & 0.167494 \tabularnewline
116 & 0.882967 & 0.234066 & 0.117033 \tabularnewline
117 & 0.871758 & 0.256485 & 0.128242 \tabularnewline
118 & 0.91475 & 0.1705 & 0.08525 \tabularnewline
119 & 0.909199 & 0.181601 & 0.0908007 \tabularnewline
120 & 0.927204 & 0.145592 & 0.0727961 \tabularnewline
121 & 0.93964 & 0.120719 & 0.0603597 \tabularnewline
122 & 0.94869 & 0.10262 & 0.0513099 \tabularnewline
123 & 0.95139 & 0.0972191 & 0.0486096 \tabularnewline
124 & 0.969972 & 0.0600561 & 0.030028 \tabularnewline
125 & 0.974084 & 0.0518318 & 0.0259159 \tabularnewline
126 & 0.96977 & 0.0604591 & 0.0302296 \tabularnewline
127 & 0.969111 & 0.0617775 & 0.0308888 \tabularnewline
128 & 0.965995 & 0.0680104 & 0.0340052 \tabularnewline
129 & 0.964691 & 0.0706178 & 0.0353089 \tabularnewline
130 & 0.963058 & 0.0738848 & 0.0369424 \tabularnewline
131 & 0.96534 & 0.0693203 & 0.0346602 \tabularnewline
132 & 0.963593 & 0.0728147 & 0.0364074 \tabularnewline
133 & 0.966643 & 0.0667132 & 0.0333566 \tabularnewline
134 & 0.961241 & 0.0775173 & 0.0387586 \tabularnewline
135 & 0.954077 & 0.091847 & 0.0459235 \tabularnewline
136 & 0.94706 & 0.105881 & 0.0529404 \tabularnewline
137 & 0.962015 & 0.0759709 & 0.0379855 \tabularnewline
138 & 0.962079 & 0.0758425 & 0.0379213 \tabularnewline
139 & 0.958431 & 0.0831375 & 0.0415687 \tabularnewline
140 & 0.951116 & 0.0977688 & 0.0488844 \tabularnewline
141 & 0.945981 & 0.108038 & 0.0540188 \tabularnewline
142 & 0.97339 & 0.0532197 & 0.0266098 \tabularnewline
143 & 0.972309 & 0.0553828 & 0.0276914 \tabularnewline
144 & 0.972375 & 0.0552503 & 0.0276251 \tabularnewline
145 & 0.968514 & 0.0629717 & 0.0314858 \tabularnewline
146 & 0.969128 & 0.0617437 & 0.0308718 \tabularnewline
147 & 0.964233 & 0.0715335 & 0.0357668 \tabularnewline
148 & 0.958514 & 0.0829713 & 0.0414856 \tabularnewline
149 & 0.953122 & 0.0937554 & 0.0468777 \tabularnewline
150 & 0.95192 & 0.0961605 & 0.0480802 \tabularnewline
151 & 0.98209 & 0.0358197 & 0.0179098 \tabularnewline
152 & 0.98011 & 0.039781 & 0.0198905 \tabularnewline
153 & 0.980935 & 0.0381295 & 0.0190647 \tabularnewline
154 & 0.976945 & 0.0461098 & 0.0230549 \tabularnewline
155 & 0.978025 & 0.04395 & 0.021975 \tabularnewline
156 & 0.973471 & 0.0530587 & 0.0265294 \tabularnewline
157 & 0.972331 & 0.0553377 & 0.0276688 \tabularnewline
158 & 0.967948 & 0.0641035 & 0.0320518 \tabularnewline
159 & 0.965859 & 0.0682819 & 0.034141 \tabularnewline
160 & 0.960245 & 0.0795094 & 0.0397547 \tabularnewline
161 & 0.972728 & 0.0545449 & 0.0272725 \tabularnewline
162 & 0.968226 & 0.0635489 & 0.0317745 \tabularnewline
163 & 0.969203 & 0.0615948 & 0.0307974 \tabularnewline
164 & 0.993931 & 0.0121376 & 0.00606879 \tabularnewline
165 & 0.995247 & 0.00950657 & 0.00475329 \tabularnewline
166 & 0.993905 & 0.0121896 & 0.0060948 \tabularnewline
167 & 0.993821 & 0.0123578 & 0.00617892 \tabularnewline
168 & 0.996094 & 0.0078125 & 0.00390625 \tabularnewline
169 & 0.994966 & 0.0100684 & 0.00503422 \tabularnewline
170 & 0.995217 & 0.0095665 & 0.00478325 \tabularnewline
171 & 0.994269 & 0.0114623 & 0.00573116 \tabularnewline
172 & 0.996109 & 0.00778182 & 0.00389091 \tabularnewline
173 & 0.995652 & 0.00869574 & 0.00434787 \tabularnewline
174 & 0.9944 & 0.0111992 & 0.00559962 \tabularnewline
175 & 0.992859 & 0.0142817 & 0.00714085 \tabularnewline
176 & 0.994051 & 0.0118971 & 0.00594856 \tabularnewline
177 & 0.993283 & 0.0134347 & 0.00671734 \tabularnewline
178 & 0.99329 & 0.01342 & 0.00671002 \tabularnewline
179 & 0.992379 & 0.0152411 & 0.00762054 \tabularnewline
180 & 0.994023 & 0.0119541 & 0.00597706 \tabularnewline
181 & 0.993535 & 0.0129307 & 0.00646534 \tabularnewline
182 & 0.992138 & 0.0157249 & 0.00786243 \tabularnewline
183 & 0.990905 & 0.0181906 & 0.00909528 \tabularnewline
184 & 0.988687 & 0.022626 & 0.011313 \tabularnewline
185 & 0.98792 & 0.0241601 & 0.0120801 \tabularnewline
186 & 0.985852 & 0.0282969 & 0.0141484 \tabularnewline
187 & 0.992569 & 0.0148616 & 0.00743079 \tabularnewline
188 & 0.990863 & 0.0182736 & 0.00913678 \tabularnewline
189 & 0.989187 & 0.0216261 & 0.0108131 \tabularnewline
190 & 0.986274 & 0.0274518 & 0.0137259 \tabularnewline
191 & 0.983044 & 0.0339126 & 0.0169563 \tabularnewline
192 & 0.979981 & 0.0400377 & 0.0200189 \tabularnewline
193 & 0.977261 & 0.0454775 & 0.0227387 \tabularnewline
194 & 0.985887 & 0.0282263 & 0.0141131 \tabularnewline
195 & 0.983196 & 0.0336074 & 0.0168037 \tabularnewline
196 & 0.98101 & 0.0379798 & 0.0189899 \tabularnewline
197 & 0.98085 & 0.0383008 & 0.0191504 \tabularnewline
198 & 0.975672 & 0.0486564 & 0.0243282 \tabularnewline
199 & 0.97743 & 0.0451392 & 0.0225696 \tabularnewline
200 & 0.976905 & 0.0461908 & 0.0230954 \tabularnewline
201 & 0.973405 & 0.053189 & 0.0265945 \tabularnewline
202 & 0.9719 & 0.0562003 & 0.0281002 \tabularnewline
203 & 0.968303 & 0.0633935 & 0.0316968 \tabularnewline
204 & 0.961401 & 0.077199 & 0.0385995 \tabularnewline
205 & 0.953752 & 0.0924966 & 0.0462483 \tabularnewline
206 & 0.965423 & 0.0691536 & 0.0345768 \tabularnewline
207 & 0.961825 & 0.0763498 & 0.0381749 \tabularnewline
208 & 0.960458 & 0.0790844 & 0.0395422 \tabularnewline
209 & 0.956025 & 0.0879504 & 0.0439752 \tabularnewline
210 & 0.948829 & 0.102342 & 0.0511711 \tabularnewline
211 & 0.938813 & 0.122373 & 0.0611867 \tabularnewline
212 & 0.927978 & 0.144044 & 0.0720219 \tabularnewline
213 & 0.941524 & 0.116951 & 0.0584757 \tabularnewline
214 & 0.932171 & 0.135658 & 0.0678292 \tabularnewline
215 & 0.928697 & 0.142607 & 0.0713035 \tabularnewline
216 & 0.916284 & 0.167431 & 0.0837156 \tabularnewline
217 & 0.913368 & 0.173263 & 0.0866317 \tabularnewline
218 & 0.902869 & 0.194262 & 0.0971311 \tabularnewline
219 & 0.882251 & 0.235497 & 0.117749 \tabularnewline
220 & 0.858912 & 0.282176 & 0.141088 \tabularnewline
221 & 0.844507 & 0.310986 & 0.155493 \tabularnewline
222 & 0.863405 & 0.27319 & 0.136595 \tabularnewline
223 & 0.838124 & 0.323753 & 0.161876 \tabularnewline
224 & 0.844298 & 0.311404 & 0.155702 \tabularnewline
225 & 0.830392 & 0.339216 & 0.169608 \tabularnewline
226 & 0.889439 & 0.221123 & 0.110561 \tabularnewline
227 & 0.911203 & 0.177594 & 0.0887972 \tabularnewline
228 & 0.913368 & 0.173263 & 0.0866315 \tabularnewline
229 & 0.89973 & 0.20054 & 0.10027 \tabularnewline
230 & 0.916235 & 0.16753 & 0.0837649 \tabularnewline
231 & 0.943193 & 0.113615 & 0.0568073 \tabularnewline
232 & 0.928211 & 0.143577 & 0.0717886 \tabularnewline
233 & 0.915339 & 0.169321 & 0.0846607 \tabularnewline
234 & 0.904066 & 0.191868 & 0.0959339 \tabularnewline
235 & 0.895201 & 0.209598 & 0.104799 \tabularnewline
236 & 0.962838 & 0.074324 & 0.037162 \tabularnewline
237 & 0.96169 & 0.0766197 & 0.0383099 \tabularnewline
238 & 0.963109 & 0.0737829 & 0.0368914 \tabularnewline
239 & 0.952661 & 0.0946775 & 0.0473387 \tabularnewline
240 & 0.937857 & 0.124285 & 0.0621426 \tabularnewline
241 & 0.926478 & 0.147045 & 0.0735223 \tabularnewline
242 & 0.909845 & 0.18031 & 0.090155 \tabularnewline
243 & 0.904185 & 0.19163 & 0.0958149 \tabularnewline
244 & 0.891648 & 0.216705 & 0.108352 \tabularnewline
245 & 0.862542 & 0.274915 & 0.137458 \tabularnewline
246 & 0.831346 & 0.337309 & 0.168654 \tabularnewline
247 & 0.798702 & 0.402596 & 0.201298 \tabularnewline
248 & 0.756548 & 0.486904 & 0.243452 \tabularnewline
249 & 0.707476 & 0.585048 & 0.292524 \tabularnewline
250 & 0.650242 & 0.699516 & 0.349758 \tabularnewline
251 & 0.599043 & 0.801914 & 0.400957 \tabularnewline
252 & 0.597672 & 0.804656 & 0.402328 \tabularnewline
253 & 0.531531 & 0.936939 & 0.468469 \tabularnewline
254 & 0.46662 & 0.933239 & 0.53338 \tabularnewline
255 & 0.522289 & 0.955422 & 0.477711 \tabularnewline
256 & 0.453939 & 0.907878 & 0.546061 \tabularnewline
257 & 0.453223 & 0.906445 & 0.546777 \tabularnewline
258 & 0.892725 & 0.21455 & 0.107275 \tabularnewline
259 & 0.851225 & 0.29755 & 0.148775 \tabularnewline
260 & 0.995434 & 0.00913115 & 0.00456557 \tabularnewline
261 & 0.996591 & 0.00681823 & 0.00340912 \tabularnewline
262 & 0.997025 & 0.00594953 & 0.00297476 \tabularnewline
263 & 0.999799 & 0.0004011 & 0.00020055 \tabularnewline
264 & 0.999349 & 0.00130164 & 0.000650819 \tabularnewline
265 & 0.997866 & 0.00426766 & 0.00213383 \tabularnewline
266 & 0.995632 & 0.00873548 & 0.00436774 \tabularnewline
267 & 0.994162 & 0.011677 & 0.00583848 \tabularnewline
268 & 0.981805 & 0.0363893 & 0.0181947 \tabularnewline
269 & 0.970386 & 0.0592279 & 0.0296139 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&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]9[/C][C]0.907223[/C][C]0.185554[/C][C]0.0927769[/C][/ROW]
[ROW][C]10[/C][C]0.905152[/C][C]0.189695[/C][C]0.0948477[/C][/ROW]
[ROW][C]11[/C][C]0.838814[/C][C]0.322372[/C][C]0.161186[/C][/ROW]
[ROW][C]12[/C][C]0.869203[/C][C]0.261593[/C][C]0.130797[/C][/ROW]
[ROW][C]13[/C][C]0.812636[/C][C]0.374729[/C][C]0.187364[/C][/ROW]
[ROW][C]14[/C][C]0.737112[/C][C]0.525775[/C][C]0.262888[/C][/ROW]
[ROW][C]15[/C][C]0.675732[/C][C]0.648535[/C][C]0.324268[/C][/ROW]
[ROW][C]16[/C][C]0.688916[/C][C]0.622168[/C][C]0.311084[/C][/ROW]
[ROW][C]17[/C][C]0.62428[/C][C]0.75144[/C][C]0.37572[/C][/ROW]
[ROW][C]18[/C][C]0.544435[/C][C]0.911131[/C][C]0.455565[/C][/ROW]
[ROW][C]19[/C][C]0.469435[/C][C]0.938871[/C][C]0.530565[/C][/ROW]
[ROW][C]20[/C][C]0.392752[/C][C]0.785505[/C][C]0.607248[/C][/ROW]
[ROW][C]21[/C][C]0.4663[/C][C]0.932601[/C][C]0.5337[/C][/ROW]
[ROW][C]22[/C][C]0.480409[/C][C]0.960818[/C][C]0.519591[/C][/ROW]
[ROW][C]23[/C][C]0.415277[/C][C]0.830555[/C][C]0.584723[/C][/ROW]
[ROW][C]24[/C][C]0.350867[/C][C]0.701734[/C][C]0.649133[/C][/ROW]
[ROW][C]25[/C][C]0.292557[/C][C]0.585113[/C][C]0.707443[/C][/ROW]
[ROW][C]26[/C][C]0.254705[/C][C]0.50941[/C][C]0.745295[/C][/ROW]
[ROW][C]27[/C][C]0.215642[/C][C]0.431285[/C][C]0.784358[/C][/ROW]
[ROW][C]28[/C][C]0.275457[/C][C]0.550914[/C][C]0.724543[/C][/ROW]
[ROW][C]29[/C][C]0.246451[/C][C]0.492902[/C][C]0.753549[/C][/ROW]
[ROW][C]30[/C][C]0.222123[/C][C]0.444245[/C][C]0.777877[/C][/ROW]
[ROW][C]31[/C][C]0.192177[/C][C]0.384354[/C][C]0.807823[/C][/ROW]
[ROW][C]32[/C][C]0.189505[/C][C]0.37901[/C][C]0.810495[/C][/ROW]
[ROW][C]33[/C][C]0.158719[/C][C]0.317438[/C][C]0.841281[/C][/ROW]
[ROW][C]34[/C][C]0.162302[/C][C]0.324605[/C][C]0.837698[/C][/ROW]
[ROW][C]35[/C][C]0.136004[/C][C]0.272008[/C][C]0.863996[/C][/ROW]
[ROW][C]36[/C][C]0.112171[/C][C]0.224343[/C][C]0.887829[/C][/ROW]
[ROW][C]37[/C][C]0.0894058[/C][C]0.178812[/C][C]0.910594[/C][/ROW]
[ROW][C]38[/C][C]0.104059[/C][C]0.208118[/C][C]0.895941[/C][/ROW]
[ROW][C]39[/C][C]0.125118[/C][C]0.250236[/C][C]0.874882[/C][/ROW]
[ROW][C]40[/C][C]0.111662[/C][C]0.223324[/C][C]0.888338[/C][/ROW]
[ROW][C]41[/C][C]0.170666[/C][C]0.341333[/C][C]0.829334[/C][/ROW]
[ROW][C]42[/C][C]0.147919[/C][C]0.295839[/C][C]0.852081[/C][/ROW]
[ROW][C]43[/C][C]0.13047[/C][C]0.26094[/C][C]0.86953[/C][/ROW]
[ROW][C]44[/C][C]0.110208[/C][C]0.220417[/C][C]0.889792[/C][/ROW]
[ROW][C]45[/C][C]0.113864[/C][C]0.227728[/C][C]0.886136[/C][/ROW]
[ROW][C]46[/C][C]0.0964837[/C][C]0.192967[/C][C]0.903516[/C][/ROW]
[ROW][C]47[/C][C]0.0805688[/C][C]0.161138[/C][C]0.919431[/C][/ROW]
[ROW][C]48[/C][C]0.100303[/C][C]0.200606[/C][C]0.899697[/C][/ROW]
[ROW][C]49[/C][C]0.0987773[/C][C]0.197555[/C][C]0.901223[/C][/ROW]
[ROW][C]50[/C][C]0.105818[/C][C]0.211637[/C][C]0.894182[/C][/ROW]
[ROW][C]51[/C][C]0.0911363[/C][C]0.182273[/C][C]0.908864[/C][/ROW]
[ROW][C]52[/C][C]0.0959698[/C][C]0.19194[/C][C]0.90403[/C][/ROW]
[ROW][C]53[/C][C]0.0873319[/C][C]0.174664[/C][C]0.912668[/C][/ROW]
[ROW][C]54[/C][C]0.0853456[/C][C]0.170691[/C][C]0.914654[/C][/ROW]
[ROW][C]55[/C][C]0.0862837[/C][C]0.172567[/C][C]0.913716[/C][/ROW]
[ROW][C]56[/C][C]0.0746768[/C][C]0.149354[/C][C]0.925323[/C][/ROW]
[ROW][C]57[/C][C]0.130342[/C][C]0.260684[/C][C]0.869658[/C][/ROW]
[ROW][C]58[/C][C]0.159054[/C][C]0.318107[/C][C]0.840946[/C][/ROW]
[ROW][C]59[/C][C]0.13558[/C][C]0.271159[/C][C]0.86442[/C][/ROW]
[ROW][C]60[/C][C]0.14117[/C][C]0.28234[/C][C]0.85883[/C][/ROW]
[ROW][C]61[/C][C]0.156608[/C][C]0.313216[/C][C]0.843392[/C][/ROW]
[ROW][C]62[/C][C]0.149681[/C][C]0.299362[/C][C]0.850319[/C][/ROW]
[ROW][C]63[/C][C]0.157961[/C][C]0.315922[/C][C]0.842039[/C][/ROW]
[ROW][C]64[/C][C]0.194013[/C][C]0.388025[/C][C]0.805987[/C][/ROW]
[ROW][C]65[/C][C]0.193292[/C][C]0.386584[/C][C]0.806708[/C][/ROW]
[ROW][C]66[/C][C]0.168372[/C][C]0.336744[/C][C]0.831628[/C][/ROW]
[ROW][C]67[/C][C]0.169706[/C][C]0.339412[/C][C]0.830294[/C][/ROW]
[ROW][C]68[/C][C]0.156271[/C][C]0.312541[/C][C]0.843729[/C][/ROW]
[ROW][C]69[/C][C]0.166496[/C][C]0.332992[/C][C]0.833504[/C][/ROW]
[ROW][C]70[/C][C]0.153878[/C][C]0.307755[/C][C]0.846122[/C][/ROW]
[ROW][C]71[/C][C]0.140611[/C][C]0.281223[/C][C]0.859389[/C][/ROW]
[ROW][C]72[/C][C]0.124329[/C][C]0.248658[/C][C]0.875671[/C][/ROW]
[ROW][C]73[/C][C]0.112312[/C][C]0.224624[/C][C]0.887688[/C][/ROW]
[ROW][C]74[/C][C]0.118559[/C][C]0.237117[/C][C]0.881441[/C][/ROW]
[ROW][C]75[/C][C]0.110247[/C][C]0.220495[/C][C]0.889753[/C][/ROW]
[ROW][C]76[/C][C]0.102133[/C][C]0.204265[/C][C]0.897867[/C][/ROW]
[ROW][C]77[/C][C]0.0970897[/C][C]0.194179[/C][C]0.90291[/C][/ROW]
[ROW][C]78[/C][C]0.0962053[/C][C]0.192411[/C][C]0.903795[/C][/ROW]
[ROW][C]79[/C][C]0.0816366[/C][C]0.163273[/C][C]0.918363[/C][/ROW]
[ROW][C]80[/C][C]0.104616[/C][C]0.209231[/C][C]0.895384[/C][/ROW]
[ROW][C]81[/C][C]0.0888904[/C][C]0.177781[/C][C]0.91111[/C][/ROW]
[ROW][C]82[/C][C]0.0985128[/C][C]0.197026[/C][C]0.901487[/C][/ROW]
[ROW][C]83[/C][C]0.084501[/C][C]0.169002[/C][C]0.915499[/C][/ROW]
[ROW][C]84[/C][C]0.178737[/C][C]0.357474[/C][C]0.821263[/C][/ROW]
[ROW][C]85[/C][C]0.164148[/C][C]0.328296[/C][C]0.835852[/C][/ROW]
[ROW][C]86[/C][C]0.144654[/C][C]0.289308[/C][C]0.855346[/C][/ROW]
[ROW][C]87[/C][C]0.125393[/C][C]0.250787[/C][C]0.874607[/C][/ROW]
[ROW][C]88[/C][C]0.109875[/C][C]0.219749[/C][C]0.890125[/C][/ROW]
[ROW][C]89[/C][C]0.10352[/C][C]0.20704[/C][C]0.89648[/C][/ROW]
[ROW][C]90[/C][C]0.107351[/C][C]0.214702[/C][C]0.892649[/C][/ROW]
[ROW][C]91[/C][C]0.112621[/C][C]0.225242[/C][C]0.887379[/C][/ROW]
[ROW][C]92[/C][C]0.187663[/C][C]0.375327[/C][C]0.812337[/C][/ROW]
[ROW][C]93[/C][C]0.188703[/C][C]0.377407[/C][C]0.811297[/C][/ROW]
[ROW][C]94[/C][C]0.183259[/C][C]0.366518[/C][C]0.816741[/C][/ROW]
[ROW][C]95[/C][C]0.200039[/C][C]0.400077[/C][C]0.799961[/C][/ROW]
[ROW][C]96[/C][C]0.195[/C][C]0.39[/C][C]0.805[/C][/ROW]
[ROW][C]97[/C][C]0.265702[/C][C]0.531403[/C][C]0.734298[/C][/ROW]
[ROW][C]98[/C][C]0.252999[/C][C]0.505998[/C][C]0.747001[/C][/ROW]
[ROW][C]99[/C][C]0.297482[/C][C]0.594964[/C][C]0.702518[/C][/ROW]
[ROW][C]100[/C][C]0.35421[/C][C]0.708421[/C][C]0.64579[/C][/ROW]
[ROW][C]101[/C][C]0.327593[/C][C]0.655187[/C][C]0.672407[/C][/ROW]
[ROW][C]102[/C][C]0.311986[/C][C]0.623972[/C][C]0.688014[/C][/ROW]
[ROW][C]103[/C][C]0.314955[/C][C]0.629911[/C][C]0.685045[/C][/ROW]
[ROW][C]104[/C][C]0.332567[/C][C]0.665135[/C][C]0.667433[/C][/ROW]
[ROW][C]105[/C][C]0.364048[/C][C]0.728095[/C][C]0.635952[/C][/ROW]
[ROW][C]106[/C][C]0.391109[/C][C]0.782218[/C][C]0.608891[/C][/ROW]
[ROW][C]107[/C][C]0.408723[/C][C]0.817446[/C][C]0.591277[/C][/ROW]
[ROW][C]108[/C][C]0.628849[/C][C]0.742302[/C][C]0.371151[/C][/ROW]
[ROW][C]109[/C][C]0.67413[/C][C]0.65174[/C][C]0.32587[/C][/ROW]
[ROW][C]110[/C][C]0.684054[/C][C]0.631893[/C][C]0.315946[/C][/ROW]
[ROW][C]111[/C][C]0.678628[/C][C]0.642744[/C][C]0.321372[/C][/ROW]
[ROW][C]112[/C][C]0.666736[/C][C]0.666527[/C][C]0.333264[/C][/ROW]
[ROW][C]113[/C][C]0.728223[/C][C]0.543554[/C][C]0.271777[/C][/ROW]
[ROW][C]114[/C][C]0.721369[/C][C]0.557262[/C][C]0.278631[/C][/ROW]
[ROW][C]115[/C][C]0.832506[/C][C]0.334988[/C][C]0.167494[/C][/ROW]
[ROW][C]116[/C][C]0.882967[/C][C]0.234066[/C][C]0.117033[/C][/ROW]
[ROW][C]117[/C][C]0.871758[/C][C]0.256485[/C][C]0.128242[/C][/ROW]
[ROW][C]118[/C][C]0.91475[/C][C]0.1705[/C][C]0.08525[/C][/ROW]
[ROW][C]119[/C][C]0.909199[/C][C]0.181601[/C][C]0.0908007[/C][/ROW]
[ROW][C]120[/C][C]0.927204[/C][C]0.145592[/C][C]0.0727961[/C][/ROW]
[ROW][C]121[/C][C]0.93964[/C][C]0.120719[/C][C]0.0603597[/C][/ROW]
[ROW][C]122[/C][C]0.94869[/C][C]0.10262[/C][C]0.0513099[/C][/ROW]
[ROW][C]123[/C][C]0.95139[/C][C]0.0972191[/C][C]0.0486096[/C][/ROW]
[ROW][C]124[/C][C]0.969972[/C][C]0.0600561[/C][C]0.030028[/C][/ROW]
[ROW][C]125[/C][C]0.974084[/C][C]0.0518318[/C][C]0.0259159[/C][/ROW]
[ROW][C]126[/C][C]0.96977[/C][C]0.0604591[/C][C]0.0302296[/C][/ROW]
[ROW][C]127[/C][C]0.969111[/C][C]0.0617775[/C][C]0.0308888[/C][/ROW]
[ROW][C]128[/C][C]0.965995[/C][C]0.0680104[/C][C]0.0340052[/C][/ROW]
[ROW][C]129[/C][C]0.964691[/C][C]0.0706178[/C][C]0.0353089[/C][/ROW]
[ROW][C]130[/C][C]0.963058[/C][C]0.0738848[/C][C]0.0369424[/C][/ROW]
[ROW][C]131[/C][C]0.96534[/C][C]0.0693203[/C][C]0.0346602[/C][/ROW]
[ROW][C]132[/C][C]0.963593[/C][C]0.0728147[/C][C]0.0364074[/C][/ROW]
[ROW][C]133[/C][C]0.966643[/C][C]0.0667132[/C][C]0.0333566[/C][/ROW]
[ROW][C]134[/C][C]0.961241[/C][C]0.0775173[/C][C]0.0387586[/C][/ROW]
[ROW][C]135[/C][C]0.954077[/C][C]0.091847[/C][C]0.0459235[/C][/ROW]
[ROW][C]136[/C][C]0.94706[/C][C]0.105881[/C][C]0.0529404[/C][/ROW]
[ROW][C]137[/C][C]0.962015[/C][C]0.0759709[/C][C]0.0379855[/C][/ROW]
[ROW][C]138[/C][C]0.962079[/C][C]0.0758425[/C][C]0.0379213[/C][/ROW]
[ROW][C]139[/C][C]0.958431[/C][C]0.0831375[/C][C]0.0415687[/C][/ROW]
[ROW][C]140[/C][C]0.951116[/C][C]0.0977688[/C][C]0.0488844[/C][/ROW]
[ROW][C]141[/C][C]0.945981[/C][C]0.108038[/C][C]0.0540188[/C][/ROW]
[ROW][C]142[/C][C]0.97339[/C][C]0.0532197[/C][C]0.0266098[/C][/ROW]
[ROW][C]143[/C][C]0.972309[/C][C]0.0553828[/C][C]0.0276914[/C][/ROW]
[ROW][C]144[/C][C]0.972375[/C][C]0.0552503[/C][C]0.0276251[/C][/ROW]
[ROW][C]145[/C][C]0.968514[/C][C]0.0629717[/C][C]0.0314858[/C][/ROW]
[ROW][C]146[/C][C]0.969128[/C][C]0.0617437[/C][C]0.0308718[/C][/ROW]
[ROW][C]147[/C][C]0.964233[/C][C]0.0715335[/C][C]0.0357668[/C][/ROW]
[ROW][C]148[/C][C]0.958514[/C][C]0.0829713[/C][C]0.0414856[/C][/ROW]
[ROW][C]149[/C][C]0.953122[/C][C]0.0937554[/C][C]0.0468777[/C][/ROW]
[ROW][C]150[/C][C]0.95192[/C][C]0.0961605[/C][C]0.0480802[/C][/ROW]
[ROW][C]151[/C][C]0.98209[/C][C]0.0358197[/C][C]0.0179098[/C][/ROW]
[ROW][C]152[/C][C]0.98011[/C][C]0.039781[/C][C]0.0198905[/C][/ROW]
[ROW][C]153[/C][C]0.980935[/C][C]0.0381295[/C][C]0.0190647[/C][/ROW]
[ROW][C]154[/C][C]0.976945[/C][C]0.0461098[/C][C]0.0230549[/C][/ROW]
[ROW][C]155[/C][C]0.978025[/C][C]0.04395[/C][C]0.021975[/C][/ROW]
[ROW][C]156[/C][C]0.973471[/C][C]0.0530587[/C][C]0.0265294[/C][/ROW]
[ROW][C]157[/C][C]0.972331[/C][C]0.0553377[/C][C]0.0276688[/C][/ROW]
[ROW][C]158[/C][C]0.967948[/C][C]0.0641035[/C][C]0.0320518[/C][/ROW]
[ROW][C]159[/C][C]0.965859[/C][C]0.0682819[/C][C]0.034141[/C][/ROW]
[ROW][C]160[/C][C]0.960245[/C][C]0.0795094[/C][C]0.0397547[/C][/ROW]
[ROW][C]161[/C][C]0.972728[/C][C]0.0545449[/C][C]0.0272725[/C][/ROW]
[ROW][C]162[/C][C]0.968226[/C][C]0.0635489[/C][C]0.0317745[/C][/ROW]
[ROW][C]163[/C][C]0.969203[/C][C]0.0615948[/C][C]0.0307974[/C][/ROW]
[ROW][C]164[/C][C]0.993931[/C][C]0.0121376[/C][C]0.00606879[/C][/ROW]
[ROW][C]165[/C][C]0.995247[/C][C]0.00950657[/C][C]0.00475329[/C][/ROW]
[ROW][C]166[/C][C]0.993905[/C][C]0.0121896[/C][C]0.0060948[/C][/ROW]
[ROW][C]167[/C][C]0.993821[/C][C]0.0123578[/C][C]0.00617892[/C][/ROW]
[ROW][C]168[/C][C]0.996094[/C][C]0.0078125[/C][C]0.00390625[/C][/ROW]
[ROW][C]169[/C][C]0.994966[/C][C]0.0100684[/C][C]0.00503422[/C][/ROW]
[ROW][C]170[/C][C]0.995217[/C][C]0.0095665[/C][C]0.00478325[/C][/ROW]
[ROW][C]171[/C][C]0.994269[/C][C]0.0114623[/C][C]0.00573116[/C][/ROW]
[ROW][C]172[/C][C]0.996109[/C][C]0.00778182[/C][C]0.00389091[/C][/ROW]
[ROW][C]173[/C][C]0.995652[/C][C]0.00869574[/C][C]0.00434787[/C][/ROW]
[ROW][C]174[/C][C]0.9944[/C][C]0.0111992[/C][C]0.00559962[/C][/ROW]
[ROW][C]175[/C][C]0.992859[/C][C]0.0142817[/C][C]0.00714085[/C][/ROW]
[ROW][C]176[/C][C]0.994051[/C][C]0.0118971[/C][C]0.00594856[/C][/ROW]
[ROW][C]177[/C][C]0.993283[/C][C]0.0134347[/C][C]0.00671734[/C][/ROW]
[ROW][C]178[/C][C]0.99329[/C][C]0.01342[/C][C]0.00671002[/C][/ROW]
[ROW][C]179[/C][C]0.992379[/C][C]0.0152411[/C][C]0.00762054[/C][/ROW]
[ROW][C]180[/C][C]0.994023[/C][C]0.0119541[/C][C]0.00597706[/C][/ROW]
[ROW][C]181[/C][C]0.993535[/C][C]0.0129307[/C][C]0.00646534[/C][/ROW]
[ROW][C]182[/C][C]0.992138[/C][C]0.0157249[/C][C]0.00786243[/C][/ROW]
[ROW][C]183[/C][C]0.990905[/C][C]0.0181906[/C][C]0.00909528[/C][/ROW]
[ROW][C]184[/C][C]0.988687[/C][C]0.022626[/C][C]0.011313[/C][/ROW]
[ROW][C]185[/C][C]0.98792[/C][C]0.0241601[/C][C]0.0120801[/C][/ROW]
[ROW][C]186[/C][C]0.985852[/C][C]0.0282969[/C][C]0.0141484[/C][/ROW]
[ROW][C]187[/C][C]0.992569[/C][C]0.0148616[/C][C]0.00743079[/C][/ROW]
[ROW][C]188[/C][C]0.990863[/C][C]0.0182736[/C][C]0.00913678[/C][/ROW]
[ROW][C]189[/C][C]0.989187[/C][C]0.0216261[/C][C]0.0108131[/C][/ROW]
[ROW][C]190[/C][C]0.986274[/C][C]0.0274518[/C][C]0.0137259[/C][/ROW]
[ROW][C]191[/C][C]0.983044[/C][C]0.0339126[/C][C]0.0169563[/C][/ROW]
[ROW][C]192[/C][C]0.979981[/C][C]0.0400377[/C][C]0.0200189[/C][/ROW]
[ROW][C]193[/C][C]0.977261[/C][C]0.0454775[/C][C]0.0227387[/C][/ROW]
[ROW][C]194[/C][C]0.985887[/C][C]0.0282263[/C][C]0.0141131[/C][/ROW]
[ROW][C]195[/C][C]0.983196[/C][C]0.0336074[/C][C]0.0168037[/C][/ROW]
[ROW][C]196[/C][C]0.98101[/C][C]0.0379798[/C][C]0.0189899[/C][/ROW]
[ROW][C]197[/C][C]0.98085[/C][C]0.0383008[/C][C]0.0191504[/C][/ROW]
[ROW][C]198[/C][C]0.975672[/C][C]0.0486564[/C][C]0.0243282[/C][/ROW]
[ROW][C]199[/C][C]0.97743[/C][C]0.0451392[/C][C]0.0225696[/C][/ROW]
[ROW][C]200[/C][C]0.976905[/C][C]0.0461908[/C][C]0.0230954[/C][/ROW]
[ROW][C]201[/C][C]0.973405[/C][C]0.053189[/C][C]0.0265945[/C][/ROW]
[ROW][C]202[/C][C]0.9719[/C][C]0.0562003[/C][C]0.0281002[/C][/ROW]
[ROW][C]203[/C][C]0.968303[/C][C]0.0633935[/C][C]0.0316968[/C][/ROW]
[ROW][C]204[/C][C]0.961401[/C][C]0.077199[/C][C]0.0385995[/C][/ROW]
[ROW][C]205[/C][C]0.953752[/C][C]0.0924966[/C][C]0.0462483[/C][/ROW]
[ROW][C]206[/C][C]0.965423[/C][C]0.0691536[/C][C]0.0345768[/C][/ROW]
[ROW][C]207[/C][C]0.961825[/C][C]0.0763498[/C][C]0.0381749[/C][/ROW]
[ROW][C]208[/C][C]0.960458[/C][C]0.0790844[/C][C]0.0395422[/C][/ROW]
[ROW][C]209[/C][C]0.956025[/C][C]0.0879504[/C][C]0.0439752[/C][/ROW]
[ROW][C]210[/C][C]0.948829[/C][C]0.102342[/C][C]0.0511711[/C][/ROW]
[ROW][C]211[/C][C]0.938813[/C][C]0.122373[/C][C]0.0611867[/C][/ROW]
[ROW][C]212[/C][C]0.927978[/C][C]0.144044[/C][C]0.0720219[/C][/ROW]
[ROW][C]213[/C][C]0.941524[/C][C]0.116951[/C][C]0.0584757[/C][/ROW]
[ROW][C]214[/C][C]0.932171[/C][C]0.135658[/C][C]0.0678292[/C][/ROW]
[ROW][C]215[/C][C]0.928697[/C][C]0.142607[/C][C]0.0713035[/C][/ROW]
[ROW][C]216[/C][C]0.916284[/C][C]0.167431[/C][C]0.0837156[/C][/ROW]
[ROW][C]217[/C][C]0.913368[/C][C]0.173263[/C][C]0.0866317[/C][/ROW]
[ROW][C]218[/C][C]0.902869[/C][C]0.194262[/C][C]0.0971311[/C][/ROW]
[ROW][C]219[/C][C]0.882251[/C][C]0.235497[/C][C]0.117749[/C][/ROW]
[ROW][C]220[/C][C]0.858912[/C][C]0.282176[/C][C]0.141088[/C][/ROW]
[ROW][C]221[/C][C]0.844507[/C][C]0.310986[/C][C]0.155493[/C][/ROW]
[ROW][C]222[/C][C]0.863405[/C][C]0.27319[/C][C]0.136595[/C][/ROW]
[ROW][C]223[/C][C]0.838124[/C][C]0.323753[/C][C]0.161876[/C][/ROW]
[ROW][C]224[/C][C]0.844298[/C][C]0.311404[/C][C]0.155702[/C][/ROW]
[ROW][C]225[/C][C]0.830392[/C][C]0.339216[/C][C]0.169608[/C][/ROW]
[ROW][C]226[/C][C]0.889439[/C][C]0.221123[/C][C]0.110561[/C][/ROW]
[ROW][C]227[/C][C]0.911203[/C][C]0.177594[/C][C]0.0887972[/C][/ROW]
[ROW][C]228[/C][C]0.913368[/C][C]0.173263[/C][C]0.0866315[/C][/ROW]
[ROW][C]229[/C][C]0.89973[/C][C]0.20054[/C][C]0.10027[/C][/ROW]
[ROW][C]230[/C][C]0.916235[/C][C]0.16753[/C][C]0.0837649[/C][/ROW]
[ROW][C]231[/C][C]0.943193[/C][C]0.113615[/C][C]0.0568073[/C][/ROW]
[ROW][C]232[/C][C]0.928211[/C][C]0.143577[/C][C]0.0717886[/C][/ROW]
[ROW][C]233[/C][C]0.915339[/C][C]0.169321[/C][C]0.0846607[/C][/ROW]
[ROW][C]234[/C][C]0.904066[/C][C]0.191868[/C][C]0.0959339[/C][/ROW]
[ROW][C]235[/C][C]0.895201[/C][C]0.209598[/C][C]0.104799[/C][/ROW]
[ROW][C]236[/C][C]0.962838[/C][C]0.074324[/C][C]0.037162[/C][/ROW]
[ROW][C]237[/C][C]0.96169[/C][C]0.0766197[/C][C]0.0383099[/C][/ROW]
[ROW][C]238[/C][C]0.963109[/C][C]0.0737829[/C][C]0.0368914[/C][/ROW]
[ROW][C]239[/C][C]0.952661[/C][C]0.0946775[/C][C]0.0473387[/C][/ROW]
[ROW][C]240[/C][C]0.937857[/C][C]0.124285[/C][C]0.0621426[/C][/ROW]
[ROW][C]241[/C][C]0.926478[/C][C]0.147045[/C][C]0.0735223[/C][/ROW]
[ROW][C]242[/C][C]0.909845[/C][C]0.18031[/C][C]0.090155[/C][/ROW]
[ROW][C]243[/C][C]0.904185[/C][C]0.19163[/C][C]0.0958149[/C][/ROW]
[ROW][C]244[/C][C]0.891648[/C][C]0.216705[/C][C]0.108352[/C][/ROW]
[ROW][C]245[/C][C]0.862542[/C][C]0.274915[/C][C]0.137458[/C][/ROW]
[ROW][C]246[/C][C]0.831346[/C][C]0.337309[/C][C]0.168654[/C][/ROW]
[ROW][C]247[/C][C]0.798702[/C][C]0.402596[/C][C]0.201298[/C][/ROW]
[ROW][C]248[/C][C]0.756548[/C][C]0.486904[/C][C]0.243452[/C][/ROW]
[ROW][C]249[/C][C]0.707476[/C][C]0.585048[/C][C]0.292524[/C][/ROW]
[ROW][C]250[/C][C]0.650242[/C][C]0.699516[/C][C]0.349758[/C][/ROW]
[ROW][C]251[/C][C]0.599043[/C][C]0.801914[/C][C]0.400957[/C][/ROW]
[ROW][C]252[/C][C]0.597672[/C][C]0.804656[/C][C]0.402328[/C][/ROW]
[ROW][C]253[/C][C]0.531531[/C][C]0.936939[/C][C]0.468469[/C][/ROW]
[ROW][C]254[/C][C]0.46662[/C][C]0.933239[/C][C]0.53338[/C][/ROW]
[ROW][C]255[/C][C]0.522289[/C][C]0.955422[/C][C]0.477711[/C][/ROW]
[ROW][C]256[/C][C]0.453939[/C][C]0.907878[/C][C]0.546061[/C][/ROW]
[ROW][C]257[/C][C]0.453223[/C][C]0.906445[/C][C]0.546777[/C][/ROW]
[ROW][C]258[/C][C]0.892725[/C][C]0.21455[/C][C]0.107275[/C][/ROW]
[ROW][C]259[/C][C]0.851225[/C][C]0.29755[/C][C]0.148775[/C][/ROW]
[ROW][C]260[/C][C]0.995434[/C][C]0.00913115[/C][C]0.00456557[/C][/ROW]
[ROW][C]261[/C][C]0.996591[/C][C]0.00681823[/C][C]0.00340912[/C][/ROW]
[ROW][C]262[/C][C]0.997025[/C][C]0.00594953[/C][C]0.00297476[/C][/ROW]
[ROW][C]263[/C][C]0.999799[/C][C]0.0004011[/C][C]0.00020055[/C][/ROW]
[ROW][C]264[/C][C]0.999349[/C][C]0.00130164[/C][C]0.000650819[/C][/ROW]
[ROW][C]265[/C][C]0.997866[/C][C]0.00426766[/C][C]0.00213383[/C][/ROW]
[ROW][C]266[/C][C]0.995632[/C][C]0.00873548[/C][C]0.00436774[/C][/ROW]
[ROW][C]267[/C][C]0.994162[/C][C]0.011677[/C][C]0.00583848[/C][/ROW]
[ROW][C]268[/C][C]0.981805[/C][C]0.0363893[/C][C]0.0181947[/C][/ROW]
[ROW][C]269[/C][C]0.970386[/C][C]0.0592279[/C][C]0.0296139[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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
90.9072230.1855540.0927769
100.9051520.1896950.0948477
110.8388140.3223720.161186
120.8692030.2615930.130797
130.8126360.3747290.187364
140.7371120.5257750.262888
150.6757320.6485350.324268
160.6889160.6221680.311084
170.624280.751440.37572
180.5444350.9111310.455565
190.4694350.9388710.530565
200.3927520.7855050.607248
210.46630.9326010.5337
220.4804090.9608180.519591
230.4152770.8305550.584723
240.3508670.7017340.649133
250.2925570.5851130.707443
260.2547050.509410.745295
270.2156420.4312850.784358
280.2754570.5509140.724543
290.2464510.4929020.753549
300.2221230.4442450.777877
310.1921770.3843540.807823
320.1895050.379010.810495
330.1587190.3174380.841281
340.1623020.3246050.837698
350.1360040.2720080.863996
360.1121710.2243430.887829
370.08940580.1788120.910594
380.1040590.2081180.895941
390.1251180.2502360.874882
400.1116620.2233240.888338
410.1706660.3413330.829334
420.1479190.2958390.852081
430.130470.260940.86953
440.1102080.2204170.889792
450.1138640.2277280.886136
460.09648370.1929670.903516
470.08056880.1611380.919431
480.1003030.2006060.899697
490.09877730.1975550.901223
500.1058180.2116370.894182
510.09113630.1822730.908864
520.09596980.191940.90403
530.08733190.1746640.912668
540.08534560.1706910.914654
550.08628370.1725670.913716
560.07467680.1493540.925323
570.1303420.2606840.869658
580.1590540.3181070.840946
590.135580.2711590.86442
600.141170.282340.85883
610.1566080.3132160.843392
620.1496810.2993620.850319
630.1579610.3159220.842039
640.1940130.3880250.805987
650.1932920.3865840.806708
660.1683720.3367440.831628
670.1697060.3394120.830294
680.1562710.3125410.843729
690.1664960.3329920.833504
700.1538780.3077550.846122
710.1406110.2812230.859389
720.1243290.2486580.875671
730.1123120.2246240.887688
740.1185590.2371170.881441
750.1102470.2204950.889753
760.1021330.2042650.897867
770.09708970.1941790.90291
780.09620530.1924110.903795
790.08163660.1632730.918363
800.1046160.2092310.895384
810.08889040.1777810.91111
820.09851280.1970260.901487
830.0845010.1690020.915499
840.1787370.3574740.821263
850.1641480.3282960.835852
860.1446540.2893080.855346
870.1253930.2507870.874607
880.1098750.2197490.890125
890.103520.207040.89648
900.1073510.2147020.892649
910.1126210.2252420.887379
920.1876630.3753270.812337
930.1887030.3774070.811297
940.1832590.3665180.816741
950.2000390.4000770.799961
960.1950.390.805
970.2657020.5314030.734298
980.2529990.5059980.747001
990.2974820.5949640.702518
1000.354210.7084210.64579
1010.3275930.6551870.672407
1020.3119860.6239720.688014
1030.3149550.6299110.685045
1040.3325670.6651350.667433
1050.3640480.7280950.635952
1060.3911090.7822180.608891
1070.4087230.8174460.591277
1080.6288490.7423020.371151
1090.674130.651740.32587
1100.6840540.6318930.315946
1110.6786280.6427440.321372
1120.6667360.6665270.333264
1130.7282230.5435540.271777
1140.7213690.5572620.278631
1150.8325060.3349880.167494
1160.8829670.2340660.117033
1170.8717580.2564850.128242
1180.914750.17050.08525
1190.9091990.1816010.0908007
1200.9272040.1455920.0727961
1210.939640.1207190.0603597
1220.948690.102620.0513099
1230.951390.09721910.0486096
1240.9699720.06005610.030028
1250.9740840.05183180.0259159
1260.969770.06045910.0302296
1270.9691110.06177750.0308888
1280.9659950.06801040.0340052
1290.9646910.07061780.0353089
1300.9630580.07388480.0369424
1310.965340.06932030.0346602
1320.9635930.07281470.0364074
1330.9666430.06671320.0333566
1340.9612410.07751730.0387586
1350.9540770.0918470.0459235
1360.947060.1058810.0529404
1370.9620150.07597090.0379855
1380.9620790.07584250.0379213
1390.9584310.08313750.0415687
1400.9511160.09776880.0488844
1410.9459810.1080380.0540188
1420.973390.05321970.0266098
1430.9723090.05538280.0276914
1440.9723750.05525030.0276251
1450.9685140.06297170.0314858
1460.9691280.06174370.0308718
1470.9642330.07153350.0357668
1480.9585140.08297130.0414856
1490.9531220.09375540.0468777
1500.951920.09616050.0480802
1510.982090.03581970.0179098
1520.980110.0397810.0198905
1530.9809350.03812950.0190647
1540.9769450.04610980.0230549
1550.9780250.043950.021975
1560.9734710.05305870.0265294
1570.9723310.05533770.0276688
1580.9679480.06410350.0320518
1590.9658590.06828190.034141
1600.9602450.07950940.0397547
1610.9727280.05454490.0272725
1620.9682260.06354890.0317745
1630.9692030.06159480.0307974
1640.9939310.01213760.00606879
1650.9952470.009506570.00475329
1660.9939050.01218960.0060948
1670.9938210.01235780.00617892
1680.9960940.00781250.00390625
1690.9949660.01006840.00503422
1700.9952170.00956650.00478325
1710.9942690.01146230.00573116
1720.9961090.007781820.00389091
1730.9956520.008695740.00434787
1740.99440.01119920.00559962
1750.9928590.01428170.00714085
1760.9940510.01189710.00594856
1770.9932830.01343470.00671734
1780.993290.013420.00671002
1790.9923790.01524110.00762054
1800.9940230.01195410.00597706
1810.9935350.01293070.00646534
1820.9921380.01572490.00786243
1830.9909050.01819060.00909528
1840.9886870.0226260.011313
1850.987920.02416010.0120801
1860.9858520.02829690.0141484
1870.9925690.01486160.00743079
1880.9908630.01827360.00913678
1890.9891870.02162610.0108131
1900.9862740.02745180.0137259
1910.9830440.03391260.0169563
1920.9799810.04003770.0200189
1930.9772610.04547750.0227387
1940.9858870.02822630.0141131
1950.9831960.03360740.0168037
1960.981010.03797980.0189899
1970.980850.03830080.0191504
1980.9756720.04865640.0243282
1990.977430.04513920.0225696
2000.9769050.04619080.0230954
2010.9734050.0531890.0265945
2020.97190.05620030.0281002
2030.9683030.06339350.0316968
2040.9614010.0771990.0385995
2050.9537520.09249660.0462483
2060.9654230.06915360.0345768
2070.9618250.07634980.0381749
2080.9604580.07908440.0395422
2090.9560250.08795040.0439752
2100.9488290.1023420.0511711
2110.9388130.1223730.0611867
2120.9279780.1440440.0720219
2130.9415240.1169510.0584757
2140.9321710.1356580.0678292
2150.9286970.1426070.0713035
2160.9162840.1674310.0837156
2170.9133680.1732630.0866317
2180.9028690.1942620.0971311
2190.8822510.2354970.117749
2200.8589120.2821760.141088
2210.8445070.3109860.155493
2220.8634050.273190.136595
2230.8381240.3237530.161876
2240.8442980.3114040.155702
2250.8303920.3392160.169608
2260.8894390.2211230.110561
2270.9112030.1775940.0887972
2280.9133680.1732630.0866315
2290.899730.200540.10027
2300.9162350.167530.0837649
2310.9431930.1136150.0568073
2320.9282110.1435770.0717886
2330.9153390.1693210.0846607
2340.9040660.1918680.0959339
2350.8952010.2095980.104799
2360.9628380.0743240.037162
2370.961690.07661970.0383099
2380.9631090.07378290.0368914
2390.9526610.09467750.0473387
2400.9378570.1242850.0621426
2410.9264780.1470450.0735223
2420.9098450.180310.090155
2430.9041850.191630.0958149
2440.8916480.2167050.108352
2450.8625420.2749150.137458
2460.8313460.3373090.168654
2470.7987020.4025960.201298
2480.7565480.4869040.243452
2490.7074760.5850480.292524
2500.6502420.6995160.349758
2510.5990430.8019140.400957
2520.5976720.8046560.402328
2530.5315310.9369390.468469
2540.466620.9332390.53338
2550.5222890.9554220.477711
2560.4539390.9078780.546061
2570.4532230.9064450.546777
2580.8927250.214550.107275
2590.8512250.297550.148775
2600.9954340.009131150.00456557
2610.9965910.006818230.00340912
2620.9970250.005949530.00297476
2630.9997990.00040110.00020055
2640.9993490.001301640.000650819
2650.9978660.004267660.00213383
2660.9956320.008735480.00436774
2670.9941620.0116770.00583848
2680.9818050.03638930.0181947
2690.9703860.05922790.0296139






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level120.045977NOK
5% type I error level510.195402NOK
10% type I error level990.37931NOK

\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 & 12 & 0.045977 & NOK \tabularnewline
5% type I error level & 51 & 0.195402 & NOK \tabularnewline
10% type I error level & 99 & 0.37931 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268684&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]12[/C][C]0.045977[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]51[/C][C]0.195402[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]99[/C][C]0.37931[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268684&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268684&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 level120.045977NOK
5% type I error level510.195402NOK
10% type I error level990.37931NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 2 3 4 5 6 7 ;
Parameters (R input):
par1 = 6 ; 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')
}