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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 computationThu, 11 Dec 2014 15:01:23 +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/11/t1418310169k1d757i6baio16l.htm/, Retrieved Thu, 16 May 2024 10:29:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266082, Retrieved Thu, 16 May 2024 10:29:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact76

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-11 15:01:23] [9836dc3e012b89db13394c1c1d63ee5e] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149 96 18 68 86 7.5
139 70 31 39 70 6
148 88 39 32 71 6.5
158 114 46 62 108 1
128 69 31 33 64 1
224 176 67 52 119 5.5
159 114 35 62 97 8.5
105 121 52 77 129 6.5
159 110 77 76 153 4.5
167 158 37 41 78 2
165 116 32 48 80 5
159 181 36 63 99 0.5
119 77 38 30 68 5
176 141 69 78 147 5
54 35 21 19 40 2.5
91 80 26 31 57 5
163 152 54 66 120 5.5
124 97 36 35 71 3.5
137 99 42 42 84 3
121 84 23 45 68 4
153 68 34 21 55 0.5
148 101 112 25 137 6.5
221 107 35 44 79 4.5
188 88 47 69 116 7.5
149 112 47 54 101 5.5
244 171 37 74 111 4
148 137 109 80 189 7.5
92 77 24 42 66 7
150 66 20 61 81 4
153 93 22 41 63 5.5
94 105 23 46 69 2.5
156 131 32 39 71 5.5
132 102 30 34 64 3.5
161 161 92 51 143 2.5
105 120 43 42 85 4.5
97 127 55 31 86 4.5
151 77 16 39 55 4.5
131 108 49 20 69 6
166 85 71 49 120 2.5
157 168 43 53 96 5
111 48 29 31 60 0
145 152 56 39 95 5
162 75 46 54 100 6.5
163 107 19 49 68 5
59 62 23 34 57 6
187 121 59 46 105 4.5
109 124 30 55 85 5.5
90 72 61 42 103 1
105 40 7 50 57 7.5
83 58 38 13 51 6
116 97 32 37 69 5
42 88 16 25 41 1
148 126 19 30 49 5
155 104 22 28 50 6.5
125 148 48 45 93 7
116 146 23 35 58 4.5
128 80 26 28 54 0
138 97 33 41 74 8.5
49 25 9 6 15 3.5
96 99 24 45 69 7.5
164 118 34 73 107 3.5
162 58 48 17 65 6
99 63 18 40 58 1.5
202 139 43 64 107 9
186 50 33 37 70 3.5
66 60 28 25 53 3.5
183 152 71 65 136 4
214 142 26 100 126 6.5
188 94 67 28 95 7.5
104 66 34 35 69 6
177 127 80 56 136 5
126 67 29 29 58 5.5
76 90 16 43 59 3.5
99 75 59 59 118 7.5
139 128 32 50 82 6.5
162 146 43 59 102 6.5
108 69 38 27 65 6.5
159 186 29 61 90 7
74 81 36 28 64 3.5
110 85 32 51 83 1.5
96 54 35 35 70 4
116 46 21 29 50 7.5
87 106 29 48 77 4.5
97 34 12 25 37 0
127 60 37 44 81 3.5
106 95 37 64 101 5.5
80 57 47 32 79 5
74 62 51 20 71 4.5
91 36 32 28 60 2.5
133 56 21 34 55 7.5
74 54 13 31 44 7
114 64 14 26 40 0
140 76 -2 58 56 4.5
95 98 20 23 43 3
98 88 24 21 45 1.5
121 35 11 21 32 3.5
126 102 23 33 56 2.5
98 61 24 16 40 5.5
95 80 14 20 34 8
110 49 52 37 89 1
70 78 15 35 50 5
102 90 23 33 56 4.5
86 45 19 27 46 3
130 55 35 41 76 3
96 96 24 40 64 8
102 43 39 35 74 2.5
100 52 29 28 57 7
94 60 13 32 45 0
52 54 8 22 30 1
98 51 18 44 62 3.5
118 51 24 27 51 5.5
99 38 19 17 36 5.5
48 41 23 12 34 0.5
50 146 16 45 61 7.5
150 182 33 37 70 9
154 192 32 37 69 9.5
109 263 37 108 145 8.5
68 35 14 10 23 7
194 439 52 68 120 8
158 214 75 72 147 10
159 341 72 143 215 7
67 58 15 9 24 8.5
147 292 29 55 84 9
39 85 13 17 30 9.5
100 200 40 37 77 4
111 158 19 27 46 6
138 199 24 37 61 8
101 297 121 58 178 5.5
131 227 93 66 160 9.5
101 108 36 21 57 7.5
114 86 23 19 42 7
165 302 85 78 163 7.5
114 148 41 35 75 8
111 178 46 48 94 7
75 120 18 27 45 7
82 207 35 43 78 6
121 157 17 30 47 10
32 128 4 25 29 2.5
150 296 28 69 97 9
117 323 44 72 116 8
71 79 10 23 32 6
165 70 38 13 50 8.5
154 146 57 61 118 6
126 246 23 43 66 9
149 196 36 51 86 8
145 199 22 67 89 9
120 127 40 36 76 5.5
109 153 31 44 75 7
132 299 11 45 57 5.5
172 228 38 34 72 9
169 190 24 36 60 2
114 180 37 72 109 8.5
156 212 37 39 76 9
172 269 22 43 65 8.5
68 130 15 25 40 9
89 179 2 56 58 7.5
167 243 43 80 123 10
113 190 31 40 71 9
115 299 29 73 102 7.5
78 121 45 34 80 6
118 137 25 72 97 10.5
87 305 4 42 46 8.5
173 157 31 61 93 8
2 96 -4 23 19 10
162 183 66 74 140 10.5
49 52 61 16 78 6.5
122 238 32 66 98 9.5
96 40 31 9 40 8.5
100 226 39 41 80 7.5
82 190 19 57 76 5
100 214 31 48 79 8
115 145 36 51 87 10
141 119 42 53 95 7
165 222 21 29 49 7.5
165 222 21 29 49 7.5
110 159 25 55 80 9.5
118 165 32 54 86 6
158 249 26 43 69 10
146 125 28 51 79 7
49 122 32 20 52 3
90 186 41 79 120 6
121 148 29 39 69 7
155 274 33 61 94 10
104 172 17 55 72 7
147 84 13 30 43 3.5
110 168 32 55 87 8
108 102 30 22 52 10
113 106 34 37 71 5.5
115 2 59 2 61 6
61 139 13 38 51 6.5
60 95 23 27 50 6.5
109 130 10 56 67 8.5
68 72 5 25 30 4
111 141 31 39 70 9.5
77 113 19 33 52 8
73 206 32 43 75 8.5
151 268 30 57 87 5.5
89 175 25 43 69 7
78 77 48 23 72 9
110 125 35 44 79 8
220 255 67 54 121 10
65 111 15 28 43 8
141 132 22 36 58 6
117 211 18 39 57 8
122 92 33 16 50 5
63 76 46 23 69 9
44 171 24 40 64 4.5
52 83 14 24 38 8.5
131 266 12 78 90 9.5
101 186 38 57 96 8.5
42 50 12 37 49 7.5
152 117 28 27 56 7.5
107 219 41 61 102 5
77 246 12 27 40 7
154 279 31 69 100 8
103 148 33 34 67 5.5
96 137 34 44 78 8.5
175 181 21 34 55 9.5
57 98 20 39 59 7
112 226 44 51 96 8
143 234 52 34 86 8.5
49 138 7 31 38 3.5
110 85 29 13 43 6.5
131 66 11 12 23 6.5
167 236 26 51 77 10.5
56 106 24 24 48 8.5
137 135 7 19 26 8
86 122 60 30 91 10
121 218 13 81 94 10
149 199 20 42 62 9.5
168 112 52 22 74 9
140 278 28 85 114 10
88 94 25 27 52 7.5
168 113 39 25 64 4.5
94 84 9 22 31 4.5
51 86 19 19 38 0.5
48 62 13 14 27 6.5
145 222 60 45 105 4.5
66 167 19 45 64 5.5
85 82 34 28 62 5
109 207 14 51 65 6
63 184 17 41 58 4
102 83 45 31 76 8
162 183 66 74 140 10.5
86 89 48 19 68 6.5
114 225 29 51 80 8
164 237 -2 73 71 8.5
119 102 51 24 76 5.5
126 221 2 61 63 7
132 128 24 23 46 5
142 91 40 14 53 3.5
83 198 20 54 74 5
94 204 19 51 70 9
81 158 16 62 78 8.5
166 138 20 36 56 5
110 226 40 59 100 9.5
64 44 27 24 51 3
93 196 25 26 52 1.5
104 83 49 54 102 6
105 79 39 39 78 0.5
49 52 61 16 78 6.5
88 105 19 36 55 7.5
95 116 67 31 98 4.5
102 83 45 31 76 8
99 196 30 42 73 9
63 153 8 39 47 7.5
76 157 19 25 45 8.5
109 75 52 31 83 7
117 106 22 38 60 9.5
57 58 17 31 48 6.5
120 75 33 17 50 9.5
73 74 34 22 56 6
91 185 22 55 77 8
108 265 30 62 91 9.5
105 131 25 51 76 8
117 139 38 30 68 8
119 196 26 49 74 9
31 78 13 16 29 5

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'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.31603 -0.00152386LFM[t] + 0.0166319Blogs[t] -0.459417PRH[t] -0.457771CH[t] + 0.455956Hours[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.31603 -0.00152386LFM[t] +  0.0166319Blogs[t] -0.459417PRH[t] -0.457771CH[t] +  0.455956Hours[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.31603 -0.00152386LFM[t] +  0.0166319Blogs[t] -0.459417PRH[t] -0.457771CH[t] +  0.455956Hours[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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
Ex[t] = + 4.31603 -0.00152386LFM[t] + 0.0166319Blogs[t] -0.459417PRH[t] -0.457771CH[t] + 0.455956Hours[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.316030.4572169.441.76121e-188.80603e-19
LFM-0.001523860.00406953-0.37450.7083570.354179
Blogs0.01663190.00245046.7877.1348e-113.5674e-11
PRH-0.4594170.375493-1.2240.2221980.111099
CH-0.4577710.37495-1.2210.2231870.111593
Hours0.4559560.3748111.2160.224850.112425

\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) & 4.31603 & 0.457216 & 9.44 & 1.76121e-18 & 8.80603e-19 \tabularnewline
LFM & -0.00152386 & 0.00406953 & -0.3745 & 0.708357 & 0.354179 \tabularnewline
Blogs & 0.0166319 & 0.0024504 & 6.787 & 7.1348e-11 & 3.5674e-11 \tabularnewline
PRH & -0.459417 & 0.375493 & -1.224 & 0.222198 & 0.111099 \tabularnewline
CH & -0.457771 & 0.37495 & -1.221 & 0.223187 & 0.111593 \tabularnewline
Hours & 0.455956 & 0.374811 & 1.216 & 0.22485 & 0.112425 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&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]4.31603[/C][C]0.457216[/C][C]9.44[/C][C]1.76121e-18[/C][C]8.80603e-19[/C][/ROW]
[ROW][C]LFM[/C][C]-0.00152386[/C][C]0.00406953[/C][C]-0.3745[/C][C]0.708357[/C][C]0.354179[/C][/ROW]
[ROW][C]Blogs[/C][C]0.0166319[/C][C]0.0024504[/C][C]6.787[/C][C]7.1348e-11[/C][C]3.5674e-11[/C][/ROW]
[ROW][C]PRH[/C][C]-0.459417[/C][C]0.375493[/C][C]-1.224[/C][C]0.222198[/C][C]0.111099[/C][/ROW]
[ROW][C]CH[/C][C]-0.457771[/C][C]0.37495[/C][C]-1.221[/C][C]0.223187[/C][C]0.111593[/C][/ROW]
[ROW][C]Hours[/C][C]0.455956[/C][C]0.374811[/C][C]1.216[/C][C]0.22485[/C][C]0.112425[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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)4.316030.4572169.441.76121e-188.80603e-19
LFM-0.001523860.00406953-0.37450.7083570.354179
Blogs0.01663190.00245046.7877.1348e-113.5674e-11
PRH-0.4594170.375493-1.2240.2221980.111099
CH-0.4577710.37495-1.2210.2231870.111593
Hours0.4559560.3748111.2160.224850.112425






Multiple Linear Regression - Regression Statistics
Multiple R0.453836
R-squared0.205968
Adjusted R-squared0.191371
F-TEST (value)14.1111
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value2.8153e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.27834
Sum Squared Residuals1411.9

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.453836 \tabularnewline
R-squared & 0.205968 \tabularnewline
Adjusted R-squared & 0.191371 \tabularnewline
F-TEST (value) & 14.1111 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 272 \tabularnewline
p-value & 2.8153e-12 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.27834 \tabularnewline
Sum Squared Residuals & 1411.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.453836[/C][/ROW]
[ROW][C]R-squared[/C][C]0.205968[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.191371[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]14.1111[/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]2.8153e-12[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.27834[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1411.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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 R0.453836
R-squared0.205968
Adjusted R-squared0.191371
F-TEST (value)14.1111
F-TEST (DF numerator)5
F-TEST (DF denominator)272
p-value2.8153e-12
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.27834
Sum Squared Residuals1411.9






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.55.499952.00005
265.090390.909615
36.55.361061.13894
415.69958-4.69958
515.1014-4.1014
65.56.57565-1.07565
78.55.736132.76387
86.55.848790.651215
94.55.49883-0.998834
1026.48693-4.48693
1155.79604-0.796039
120.56.84519-6.34519
1355.22939-0.229389
1456.01258-1.01258
152.54.7087-2.2087
1655.36167-0.361671
175.56.28903-0.789028
183.55.55226-2.05226
1935.53224-2.53224
2045.36746-1.36746
210.55.05807-4.55807
226.55.337321.16268
234.55.55789-1.05789
247.55.205282.29472
255.55.69109-0.191089
2646.52592-2.52592
277.55.846641.65336
2875.297211.70279
2945.00525-1.00525
305.55.47910.0208954
312.55.75606-3.25606
325.56.07556-0.575562
333.55.64581-2.14581
342.56.33746-3.83746
354.55.92681-1.42681
364.56.03385-1.53385
374.55.24044-0.740438
3865.706760.293236
392.55.14213-2.64213
4056.62594-1.62594
4104.78859-4.78859
4256.35853-1.35853
436.55.059361.44064
4455.69258-0.692579
4565.1160.884
464.55.75585-1.25585
475.56.00865-0.50865
4815.08904-4.08904
497.54.706352.79365
5064.999091.00091
5155.57466-0.574662
5215.61489-4.61489
5356.06592-1.06592
546.55.68260.817403
5576.339280.660721
564.56.4244-1.9244
5705.31073-5.31073
588.55.530422.96958
593.54.61512-1.11512
607.55.651581.84842
613.55.77854-2.27854
6264.836841.16316
631.55.0781-3.5781
6496.055082.94492
653.54.68283-1.18283
663.55.07109-1.57109
6746.20153-2.20153
686.56.080210.419793
697.55.310242.18976
7065.074070.925932
7155.78005-0.780055
725.55.085370.414633
733.55.56368-2.06368
747.55.10132.3987
756.56.031610.468388
766.56.241530.258466
776.55.118541.38146
7876.956210.0437936
793.55.37504-1.87504
801.55.35882-3.85882
8144.88321-0.883215
827.54.779032.72097
834.55.75896-1.25896
8404.6468-4.6468
853.54.91251-1.41251
865.55.490340.00966152
8754.92140.078597
884.55.02164-0.521636
892.54.61455-2.11455
907.54.910372.58963
9175.000141.99986
9205.11112-5.11112
934.55.26839-0.768391
9435.69023-2.69023
951.55.50913-4.00913
963.54.63758-1.13758
972.55.68099-3.18099
985.55.069140.430861
9985.417072.58293
10014.71625-3.71625
10155.39122-0.391221
1024.55.51798-1.01798
10334.81866-1.81866
10434.83715-1.83715
10585.610752.38925
1062.54.67728-2.17728
10774.877322.12268
10805.06764-5.06764
10915.0673-4.0673
1103.54.87278-1.37278
1115.54.852380.647617
1125.54.700570.799427
1130.54.36746-3.86746
1147.56.531060.968941
11596.93312.0669
1169.57.096782.40322
1178.58.200080.29992
11874.271972.72803
119811.0184-3.01843
120107.244252.75575
12179.23653-2.23653
1228.55.110333.38967
12398.748360.251642
1249.55.594473.90553
12547.28444-3.28444
12666.65997-0.659965
12787.265280.734723
1285.58.1218-2.6218
1299.57.906161.59384
1307.55.795661.70434
13175.458571.54143
1327.58.65169-1.15169
13385.942462.05754
13476.861050.138952
13576.086270.913726
13667.43471-1.43471
137106.629573.37043
1382.56.33694-3.83694
13998.788370.211629
14089.2269-1.2269
14164.989451.01055
1428.54.617763.88224
14366.20164-0.201641
14498.057830.942166
14586.675731.32427
14697.207091.79291
1475.56.04165-0.541649
14876.507470.492527
1495.59.42404-3.92404
15097.652781.34722
15127.07016-5.07016
1528.56.877341.62266
15397.405441.59456
1548.58.373730.126269
15596.277272.72273
1567.57.048980.451025
157107.80912.1909
15897.124011.87599
1597.58.88088-1.38088
16066.44814-0.448139
16110.56.197614.30239
1628.59.16612-0.66612
16386.901581.09842
164105.881754.11825
16510.56.750093.74991
1666.55.322021.17798
1679.57.857991.64201
1688.54.711393.78861
1697.57.71307-0.213069
17057.18194-2.18194
17187.528470.471527
172106.335273.66473
17375.838821.16118
1747.57.175610.324391
1757.57.175610.324391
1769.56.606552.89345
17766.67173-0.671734
178108.048581.95142
17975.983081.01692
18036.1234-3.1234
18166.98716-0.987157
18276.877980.122022
183108.412061.58794
18476.859590.140407
1853.55.38967-1.88967
18686.732011.26799
187105.704154.29585
1885.55.722-0.221998
18963.966222.03378
1906.56.420960.0790414
1916.55.676030.82397
1928.56.63181.8682
19345.34723-1.34723
1949.56.313923.18608
19585.952452.04755
1968.57.442171.05783
1975.58.33601-2.83601
19877.38239-0.382388
19995.725913.27409
20086.026411.97359
201107.892032.10797
20285.960392.03961
20366.15511-0.155107
20487.5140.486003
20555.97296-0.97296
20695.283113.71689
2074.56.93738-2.43738
2088.55.525232.97477
2099.58.357411.14259
2108.57.476651.02335
2117.54.974952.52505
2127.56.340391.15961
21357.54277-2.54277
21478.65556-1.65556
21588.48915-0.489151
2165.56.44468-0.94468
2178.56.250792.24921
2189.56.925352.57465
21975.719111.28089
22088.11529-0.115288
2218.57.748310.751694
2223.56.45608-2.95608
2236.55.894110.605888
2246.55.154261.34574
22510.57.804142.69586
2268.55.867062.63294
22786.293861.70614
228106.407923.59208
229107.565422.43458
2309.57.253292.24671
23195.70293.2971
232108.931161.06884
2337.55.609811.89019
2344.55.75908-1.25908
2354.55.4988-0.998796
2360.55.56842-5.06842
2376.55.203661.29634
2384.57.49803-2.99803
2395.56.84556-1.34556
24055.38183-0.381833
24167.45173-1.45173
24247.14706-3.14706
24385.329042.67096
24410.56.750093.74991
2456.55.920560.579436
24687.691570.308432
2478.57.882330.617669
2485.56.06703-0.567035
24977.68206-0.682058
25055.663-0.663005
2513.54.99334-1.49334
25257.31545-2.31545
25397.407391.59261
2548.56.652551.84745
25556.22372-1.22372
2569.58.117661.38234
25734.81331-1.81331
2581.57.75641-6.25641
25964.814461.18554
2600.55.26419-4.76419
2616.55.322021.17798
2627.55.797191.70281
2634.55.81242-1.31242
26485.329042.67096
26597.700931.29907
2667.56.666250.833752
2678.57.156251.34375
26875.161091.83891
2699.55.755623.74438
2706.55.078731.42127
2719.55.23554.2645
27265.277950.722049
27387.078310.921688
2749.57.886611.61339
27586.155731.84427
27686.263611.73639
27796.759682.24032
27855.49205-0.492051

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.49995 & 2.00005 \tabularnewline
2 & 6 & 5.09039 & 0.909615 \tabularnewline
3 & 6.5 & 5.36106 & 1.13894 \tabularnewline
4 & 1 & 5.69958 & -4.69958 \tabularnewline
5 & 1 & 5.1014 & -4.1014 \tabularnewline
6 & 5.5 & 6.57565 & -1.07565 \tabularnewline
7 & 8.5 & 5.73613 & 2.76387 \tabularnewline
8 & 6.5 & 5.84879 & 0.651215 \tabularnewline
9 & 4.5 & 5.49883 & -0.998834 \tabularnewline
10 & 2 & 6.48693 & -4.48693 \tabularnewline
11 & 5 & 5.79604 & -0.796039 \tabularnewline
12 & 0.5 & 6.84519 & -6.34519 \tabularnewline
13 & 5 & 5.22939 & -0.229389 \tabularnewline
14 & 5 & 6.01258 & -1.01258 \tabularnewline
15 & 2.5 & 4.7087 & -2.2087 \tabularnewline
16 & 5 & 5.36167 & -0.361671 \tabularnewline
17 & 5.5 & 6.28903 & -0.789028 \tabularnewline
18 & 3.5 & 5.55226 & -2.05226 \tabularnewline
19 & 3 & 5.53224 & -2.53224 \tabularnewline
20 & 4 & 5.36746 & -1.36746 \tabularnewline
21 & 0.5 & 5.05807 & -4.55807 \tabularnewline
22 & 6.5 & 5.33732 & 1.16268 \tabularnewline
23 & 4.5 & 5.55789 & -1.05789 \tabularnewline
24 & 7.5 & 5.20528 & 2.29472 \tabularnewline
25 & 5.5 & 5.69109 & -0.191089 \tabularnewline
26 & 4 & 6.52592 & -2.52592 \tabularnewline
27 & 7.5 & 5.84664 & 1.65336 \tabularnewline
28 & 7 & 5.29721 & 1.70279 \tabularnewline
29 & 4 & 5.00525 & -1.00525 \tabularnewline
30 & 5.5 & 5.4791 & 0.0208954 \tabularnewline
31 & 2.5 & 5.75606 & -3.25606 \tabularnewline
32 & 5.5 & 6.07556 & -0.575562 \tabularnewline
33 & 3.5 & 5.64581 & -2.14581 \tabularnewline
34 & 2.5 & 6.33746 & -3.83746 \tabularnewline
35 & 4.5 & 5.92681 & -1.42681 \tabularnewline
36 & 4.5 & 6.03385 & -1.53385 \tabularnewline
37 & 4.5 & 5.24044 & -0.740438 \tabularnewline
38 & 6 & 5.70676 & 0.293236 \tabularnewline
39 & 2.5 & 5.14213 & -2.64213 \tabularnewline
40 & 5 & 6.62594 & -1.62594 \tabularnewline
41 & 0 & 4.78859 & -4.78859 \tabularnewline
42 & 5 & 6.35853 & -1.35853 \tabularnewline
43 & 6.5 & 5.05936 & 1.44064 \tabularnewline
44 & 5 & 5.69258 & -0.692579 \tabularnewline
45 & 6 & 5.116 & 0.884 \tabularnewline
46 & 4.5 & 5.75585 & -1.25585 \tabularnewline
47 & 5.5 & 6.00865 & -0.50865 \tabularnewline
48 & 1 & 5.08904 & -4.08904 \tabularnewline
49 & 7.5 & 4.70635 & 2.79365 \tabularnewline
50 & 6 & 4.99909 & 1.00091 \tabularnewline
51 & 5 & 5.57466 & -0.574662 \tabularnewline
52 & 1 & 5.61489 & -4.61489 \tabularnewline
53 & 5 & 6.06592 & -1.06592 \tabularnewline
54 & 6.5 & 5.6826 & 0.817403 \tabularnewline
55 & 7 & 6.33928 & 0.660721 \tabularnewline
56 & 4.5 & 6.4244 & -1.9244 \tabularnewline
57 & 0 & 5.31073 & -5.31073 \tabularnewline
58 & 8.5 & 5.53042 & 2.96958 \tabularnewline
59 & 3.5 & 4.61512 & -1.11512 \tabularnewline
60 & 7.5 & 5.65158 & 1.84842 \tabularnewline
61 & 3.5 & 5.77854 & -2.27854 \tabularnewline
62 & 6 & 4.83684 & 1.16316 \tabularnewline
63 & 1.5 & 5.0781 & -3.5781 \tabularnewline
64 & 9 & 6.05508 & 2.94492 \tabularnewline
65 & 3.5 & 4.68283 & -1.18283 \tabularnewline
66 & 3.5 & 5.07109 & -1.57109 \tabularnewline
67 & 4 & 6.20153 & -2.20153 \tabularnewline
68 & 6.5 & 6.08021 & 0.419793 \tabularnewline
69 & 7.5 & 5.31024 & 2.18976 \tabularnewline
70 & 6 & 5.07407 & 0.925932 \tabularnewline
71 & 5 & 5.78005 & -0.780055 \tabularnewline
72 & 5.5 & 5.08537 & 0.414633 \tabularnewline
73 & 3.5 & 5.56368 & -2.06368 \tabularnewline
74 & 7.5 & 5.1013 & 2.3987 \tabularnewline
75 & 6.5 & 6.03161 & 0.468388 \tabularnewline
76 & 6.5 & 6.24153 & 0.258466 \tabularnewline
77 & 6.5 & 5.11854 & 1.38146 \tabularnewline
78 & 7 & 6.95621 & 0.0437936 \tabularnewline
79 & 3.5 & 5.37504 & -1.87504 \tabularnewline
80 & 1.5 & 5.35882 & -3.85882 \tabularnewline
81 & 4 & 4.88321 & -0.883215 \tabularnewline
82 & 7.5 & 4.77903 & 2.72097 \tabularnewline
83 & 4.5 & 5.75896 & -1.25896 \tabularnewline
84 & 0 & 4.6468 & -4.6468 \tabularnewline
85 & 3.5 & 4.91251 & -1.41251 \tabularnewline
86 & 5.5 & 5.49034 & 0.00966152 \tabularnewline
87 & 5 & 4.9214 & 0.078597 \tabularnewline
88 & 4.5 & 5.02164 & -0.521636 \tabularnewline
89 & 2.5 & 4.61455 & -2.11455 \tabularnewline
90 & 7.5 & 4.91037 & 2.58963 \tabularnewline
91 & 7 & 5.00014 & 1.99986 \tabularnewline
92 & 0 & 5.11112 & -5.11112 \tabularnewline
93 & 4.5 & 5.26839 & -0.768391 \tabularnewline
94 & 3 & 5.69023 & -2.69023 \tabularnewline
95 & 1.5 & 5.50913 & -4.00913 \tabularnewline
96 & 3.5 & 4.63758 & -1.13758 \tabularnewline
97 & 2.5 & 5.68099 & -3.18099 \tabularnewline
98 & 5.5 & 5.06914 & 0.430861 \tabularnewline
99 & 8 & 5.41707 & 2.58293 \tabularnewline
100 & 1 & 4.71625 & -3.71625 \tabularnewline
101 & 5 & 5.39122 & -0.391221 \tabularnewline
102 & 4.5 & 5.51798 & -1.01798 \tabularnewline
103 & 3 & 4.81866 & -1.81866 \tabularnewline
104 & 3 & 4.83715 & -1.83715 \tabularnewline
105 & 8 & 5.61075 & 2.38925 \tabularnewline
106 & 2.5 & 4.67728 & -2.17728 \tabularnewline
107 & 7 & 4.87732 & 2.12268 \tabularnewline
108 & 0 & 5.06764 & -5.06764 \tabularnewline
109 & 1 & 5.0673 & -4.0673 \tabularnewline
110 & 3.5 & 4.87278 & -1.37278 \tabularnewline
111 & 5.5 & 4.85238 & 0.647617 \tabularnewline
112 & 5.5 & 4.70057 & 0.799427 \tabularnewline
113 & 0.5 & 4.36746 & -3.86746 \tabularnewline
114 & 7.5 & 6.53106 & 0.968941 \tabularnewline
115 & 9 & 6.9331 & 2.0669 \tabularnewline
116 & 9.5 & 7.09678 & 2.40322 \tabularnewline
117 & 8.5 & 8.20008 & 0.29992 \tabularnewline
118 & 7 & 4.27197 & 2.72803 \tabularnewline
119 & 8 & 11.0184 & -3.01843 \tabularnewline
120 & 10 & 7.24425 & 2.75575 \tabularnewline
121 & 7 & 9.23653 & -2.23653 \tabularnewline
122 & 8.5 & 5.11033 & 3.38967 \tabularnewline
123 & 9 & 8.74836 & 0.251642 \tabularnewline
124 & 9.5 & 5.59447 & 3.90553 \tabularnewline
125 & 4 & 7.28444 & -3.28444 \tabularnewline
126 & 6 & 6.65997 & -0.659965 \tabularnewline
127 & 8 & 7.26528 & 0.734723 \tabularnewline
128 & 5.5 & 8.1218 & -2.6218 \tabularnewline
129 & 9.5 & 7.90616 & 1.59384 \tabularnewline
130 & 7.5 & 5.79566 & 1.70434 \tabularnewline
131 & 7 & 5.45857 & 1.54143 \tabularnewline
132 & 7.5 & 8.65169 & -1.15169 \tabularnewline
133 & 8 & 5.94246 & 2.05754 \tabularnewline
134 & 7 & 6.86105 & 0.138952 \tabularnewline
135 & 7 & 6.08627 & 0.913726 \tabularnewline
136 & 6 & 7.43471 & -1.43471 \tabularnewline
137 & 10 & 6.62957 & 3.37043 \tabularnewline
138 & 2.5 & 6.33694 & -3.83694 \tabularnewline
139 & 9 & 8.78837 & 0.211629 \tabularnewline
140 & 8 & 9.2269 & -1.2269 \tabularnewline
141 & 6 & 4.98945 & 1.01055 \tabularnewline
142 & 8.5 & 4.61776 & 3.88224 \tabularnewline
143 & 6 & 6.20164 & -0.201641 \tabularnewline
144 & 9 & 8.05783 & 0.942166 \tabularnewline
145 & 8 & 6.67573 & 1.32427 \tabularnewline
146 & 9 & 7.20709 & 1.79291 \tabularnewline
147 & 5.5 & 6.04165 & -0.541649 \tabularnewline
148 & 7 & 6.50747 & 0.492527 \tabularnewline
149 & 5.5 & 9.42404 & -3.92404 \tabularnewline
150 & 9 & 7.65278 & 1.34722 \tabularnewline
151 & 2 & 7.07016 & -5.07016 \tabularnewline
152 & 8.5 & 6.87734 & 1.62266 \tabularnewline
153 & 9 & 7.40544 & 1.59456 \tabularnewline
154 & 8.5 & 8.37373 & 0.126269 \tabularnewline
155 & 9 & 6.27727 & 2.72273 \tabularnewline
156 & 7.5 & 7.04898 & 0.451025 \tabularnewline
157 & 10 & 7.8091 & 2.1909 \tabularnewline
158 & 9 & 7.12401 & 1.87599 \tabularnewline
159 & 7.5 & 8.88088 & -1.38088 \tabularnewline
160 & 6 & 6.44814 & -0.448139 \tabularnewline
161 & 10.5 & 6.19761 & 4.30239 \tabularnewline
162 & 8.5 & 9.16612 & -0.66612 \tabularnewline
163 & 8 & 6.90158 & 1.09842 \tabularnewline
164 & 10 & 5.88175 & 4.11825 \tabularnewline
165 & 10.5 & 6.75009 & 3.74991 \tabularnewline
166 & 6.5 & 5.32202 & 1.17798 \tabularnewline
167 & 9.5 & 7.85799 & 1.64201 \tabularnewline
168 & 8.5 & 4.71139 & 3.78861 \tabularnewline
169 & 7.5 & 7.71307 & -0.213069 \tabularnewline
170 & 5 & 7.18194 & -2.18194 \tabularnewline
171 & 8 & 7.52847 & 0.471527 \tabularnewline
172 & 10 & 6.33527 & 3.66473 \tabularnewline
173 & 7 & 5.83882 & 1.16118 \tabularnewline
174 & 7.5 & 7.17561 & 0.324391 \tabularnewline
175 & 7.5 & 7.17561 & 0.324391 \tabularnewline
176 & 9.5 & 6.60655 & 2.89345 \tabularnewline
177 & 6 & 6.67173 & -0.671734 \tabularnewline
178 & 10 & 8.04858 & 1.95142 \tabularnewline
179 & 7 & 5.98308 & 1.01692 \tabularnewline
180 & 3 & 6.1234 & -3.1234 \tabularnewline
181 & 6 & 6.98716 & -0.987157 \tabularnewline
182 & 7 & 6.87798 & 0.122022 \tabularnewline
183 & 10 & 8.41206 & 1.58794 \tabularnewline
184 & 7 & 6.85959 & 0.140407 \tabularnewline
185 & 3.5 & 5.38967 & -1.88967 \tabularnewline
186 & 8 & 6.73201 & 1.26799 \tabularnewline
187 & 10 & 5.70415 & 4.29585 \tabularnewline
188 & 5.5 & 5.722 & -0.221998 \tabularnewline
189 & 6 & 3.96622 & 2.03378 \tabularnewline
190 & 6.5 & 6.42096 & 0.0790414 \tabularnewline
191 & 6.5 & 5.67603 & 0.82397 \tabularnewline
192 & 8.5 & 6.6318 & 1.8682 \tabularnewline
193 & 4 & 5.34723 & -1.34723 \tabularnewline
194 & 9.5 & 6.31392 & 3.18608 \tabularnewline
195 & 8 & 5.95245 & 2.04755 \tabularnewline
196 & 8.5 & 7.44217 & 1.05783 \tabularnewline
197 & 5.5 & 8.33601 & -2.83601 \tabularnewline
198 & 7 & 7.38239 & -0.382388 \tabularnewline
199 & 9 & 5.72591 & 3.27409 \tabularnewline
200 & 8 & 6.02641 & 1.97359 \tabularnewline
201 & 10 & 7.89203 & 2.10797 \tabularnewline
202 & 8 & 5.96039 & 2.03961 \tabularnewline
203 & 6 & 6.15511 & -0.155107 \tabularnewline
204 & 8 & 7.514 & 0.486003 \tabularnewline
205 & 5 & 5.97296 & -0.97296 \tabularnewline
206 & 9 & 5.28311 & 3.71689 \tabularnewline
207 & 4.5 & 6.93738 & -2.43738 \tabularnewline
208 & 8.5 & 5.52523 & 2.97477 \tabularnewline
209 & 9.5 & 8.35741 & 1.14259 \tabularnewline
210 & 8.5 & 7.47665 & 1.02335 \tabularnewline
211 & 7.5 & 4.97495 & 2.52505 \tabularnewline
212 & 7.5 & 6.34039 & 1.15961 \tabularnewline
213 & 5 & 7.54277 & -2.54277 \tabularnewline
214 & 7 & 8.65556 & -1.65556 \tabularnewline
215 & 8 & 8.48915 & -0.489151 \tabularnewline
216 & 5.5 & 6.44468 & -0.94468 \tabularnewline
217 & 8.5 & 6.25079 & 2.24921 \tabularnewline
218 & 9.5 & 6.92535 & 2.57465 \tabularnewline
219 & 7 & 5.71911 & 1.28089 \tabularnewline
220 & 8 & 8.11529 & -0.115288 \tabularnewline
221 & 8.5 & 7.74831 & 0.751694 \tabularnewline
222 & 3.5 & 6.45608 & -2.95608 \tabularnewline
223 & 6.5 & 5.89411 & 0.605888 \tabularnewline
224 & 6.5 & 5.15426 & 1.34574 \tabularnewline
225 & 10.5 & 7.80414 & 2.69586 \tabularnewline
226 & 8.5 & 5.86706 & 2.63294 \tabularnewline
227 & 8 & 6.29386 & 1.70614 \tabularnewline
228 & 10 & 6.40792 & 3.59208 \tabularnewline
229 & 10 & 7.56542 & 2.43458 \tabularnewline
230 & 9.5 & 7.25329 & 2.24671 \tabularnewline
231 & 9 & 5.7029 & 3.2971 \tabularnewline
232 & 10 & 8.93116 & 1.06884 \tabularnewline
233 & 7.5 & 5.60981 & 1.89019 \tabularnewline
234 & 4.5 & 5.75908 & -1.25908 \tabularnewline
235 & 4.5 & 5.4988 & -0.998796 \tabularnewline
236 & 0.5 & 5.56842 & -5.06842 \tabularnewline
237 & 6.5 & 5.20366 & 1.29634 \tabularnewline
238 & 4.5 & 7.49803 & -2.99803 \tabularnewline
239 & 5.5 & 6.84556 & -1.34556 \tabularnewline
240 & 5 & 5.38183 & -0.381833 \tabularnewline
241 & 6 & 7.45173 & -1.45173 \tabularnewline
242 & 4 & 7.14706 & -3.14706 \tabularnewline
243 & 8 & 5.32904 & 2.67096 \tabularnewline
244 & 10.5 & 6.75009 & 3.74991 \tabularnewline
245 & 6.5 & 5.92056 & 0.579436 \tabularnewline
246 & 8 & 7.69157 & 0.308432 \tabularnewline
247 & 8.5 & 7.88233 & 0.617669 \tabularnewline
248 & 5.5 & 6.06703 & -0.567035 \tabularnewline
249 & 7 & 7.68206 & -0.682058 \tabularnewline
250 & 5 & 5.663 & -0.663005 \tabularnewline
251 & 3.5 & 4.99334 & -1.49334 \tabularnewline
252 & 5 & 7.31545 & -2.31545 \tabularnewline
253 & 9 & 7.40739 & 1.59261 \tabularnewline
254 & 8.5 & 6.65255 & 1.84745 \tabularnewline
255 & 5 & 6.22372 & -1.22372 \tabularnewline
256 & 9.5 & 8.11766 & 1.38234 \tabularnewline
257 & 3 & 4.81331 & -1.81331 \tabularnewline
258 & 1.5 & 7.75641 & -6.25641 \tabularnewline
259 & 6 & 4.81446 & 1.18554 \tabularnewline
260 & 0.5 & 5.26419 & -4.76419 \tabularnewline
261 & 6.5 & 5.32202 & 1.17798 \tabularnewline
262 & 7.5 & 5.79719 & 1.70281 \tabularnewline
263 & 4.5 & 5.81242 & -1.31242 \tabularnewline
264 & 8 & 5.32904 & 2.67096 \tabularnewline
265 & 9 & 7.70093 & 1.29907 \tabularnewline
266 & 7.5 & 6.66625 & 0.833752 \tabularnewline
267 & 8.5 & 7.15625 & 1.34375 \tabularnewline
268 & 7 & 5.16109 & 1.83891 \tabularnewline
269 & 9.5 & 5.75562 & 3.74438 \tabularnewline
270 & 6.5 & 5.07873 & 1.42127 \tabularnewline
271 & 9.5 & 5.2355 & 4.2645 \tabularnewline
272 & 6 & 5.27795 & 0.722049 \tabularnewline
273 & 8 & 7.07831 & 0.921688 \tabularnewline
274 & 9.5 & 7.88661 & 1.61339 \tabularnewline
275 & 8 & 6.15573 & 1.84427 \tabularnewline
276 & 8 & 6.26361 & 1.73639 \tabularnewline
277 & 9 & 6.75968 & 2.24032 \tabularnewline
278 & 5 & 5.49205 & -0.492051 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.49995[/C][C]2.00005[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]5.09039[/C][C]0.909615[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.36106[/C][C]1.13894[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]5.69958[/C][C]-4.69958[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.1014[/C][C]-4.1014[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]6.57565[/C][C]-1.07565[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]5.73613[/C][C]2.76387[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]5.84879[/C][C]0.651215[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]5.49883[/C][C]-0.998834[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.48693[/C][C]-4.48693[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]5.79604[/C][C]-0.796039[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]6.84519[/C][C]-6.34519[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.22939[/C][C]-0.229389[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]6.01258[/C][C]-1.01258[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]4.7087[/C][C]-2.2087[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.36167[/C][C]-0.361671[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.28903[/C][C]-0.789028[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.55226[/C][C]-2.05226[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.53224[/C][C]-2.53224[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]5.36746[/C][C]-1.36746[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]5.05807[/C][C]-4.55807[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.33732[/C][C]1.16268[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]5.55789[/C][C]-1.05789[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]5.20528[/C][C]2.29472[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]5.69109[/C][C]-0.191089[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]6.52592[/C][C]-2.52592[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]5.84664[/C][C]1.65336[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]5.29721[/C][C]1.70279[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]5.00525[/C][C]-1.00525[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]5.4791[/C][C]0.0208954[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]5.75606[/C][C]-3.25606[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]6.07556[/C][C]-0.575562[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.64581[/C][C]-2.14581[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.33746[/C][C]-3.83746[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]5.92681[/C][C]-1.42681[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]6.03385[/C][C]-1.53385[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.24044[/C][C]-0.740438[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.70676[/C][C]0.293236[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.14213[/C][C]-2.64213[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.62594[/C][C]-1.62594[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.78859[/C][C]-4.78859[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.35853[/C][C]-1.35853[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]5.05936[/C][C]1.44064[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]5.69258[/C][C]-0.692579[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.116[/C][C]0.884[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.75585[/C][C]-1.25585[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]6.00865[/C][C]-0.50865[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]5.08904[/C][C]-4.08904[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]4.70635[/C][C]2.79365[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]4.99909[/C][C]1.00091[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]5.57466[/C][C]-0.574662[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.61489[/C][C]-4.61489[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]6.06592[/C][C]-1.06592[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.6826[/C][C]0.817403[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]6.33928[/C][C]0.660721[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]6.4244[/C][C]-1.9244[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.31073[/C][C]-5.31073[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]5.53042[/C][C]2.96958[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]4.61512[/C][C]-1.11512[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]5.65158[/C][C]1.84842[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.77854[/C][C]-2.27854[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]4.83684[/C][C]1.16316[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]5.0781[/C][C]-3.5781[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.05508[/C][C]2.94492[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]4.68283[/C][C]-1.18283[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.07109[/C][C]-1.57109[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.20153[/C][C]-2.20153[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]6.08021[/C][C]0.419793[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]5.31024[/C][C]2.18976[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.07407[/C][C]0.925932[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]5.78005[/C][C]-0.780055[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.08537[/C][C]0.414633[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]5.56368[/C][C]-2.06368[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]5.1013[/C][C]2.3987[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]6.03161[/C][C]0.468388[/C][/ROW]
[ROW][C]76[/C][C]6.5[/C][C]6.24153[/C][C]0.258466[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.11854[/C][C]1.38146[/C][/ROW]
[ROW][C]78[/C][C]7[/C][C]6.95621[/C][C]0.0437936[/C][/ROW]
[ROW][C]79[/C][C]3.5[/C][C]5.37504[/C][C]-1.87504[/C][/ROW]
[ROW][C]80[/C][C]1.5[/C][C]5.35882[/C][C]-3.85882[/C][/ROW]
[ROW][C]81[/C][C]4[/C][C]4.88321[/C][C]-0.883215[/C][/ROW]
[ROW][C]82[/C][C]7.5[/C][C]4.77903[/C][C]2.72097[/C][/ROW]
[ROW][C]83[/C][C]4.5[/C][C]5.75896[/C][C]-1.25896[/C][/ROW]
[ROW][C]84[/C][C]0[/C][C]4.6468[/C][C]-4.6468[/C][/ROW]
[ROW][C]85[/C][C]3.5[/C][C]4.91251[/C][C]-1.41251[/C][/ROW]
[ROW][C]86[/C][C]5.5[/C][C]5.49034[/C][C]0.00966152[/C][/ROW]
[ROW][C]87[/C][C]5[/C][C]4.9214[/C][C]0.078597[/C][/ROW]
[ROW][C]88[/C][C]4.5[/C][C]5.02164[/C][C]-0.521636[/C][/ROW]
[ROW][C]89[/C][C]2.5[/C][C]4.61455[/C][C]-2.11455[/C][/ROW]
[ROW][C]90[/C][C]7.5[/C][C]4.91037[/C][C]2.58963[/C][/ROW]
[ROW][C]91[/C][C]7[/C][C]5.00014[/C][C]1.99986[/C][/ROW]
[ROW][C]92[/C][C]0[/C][C]5.11112[/C][C]-5.11112[/C][/ROW]
[ROW][C]93[/C][C]4.5[/C][C]5.26839[/C][C]-0.768391[/C][/ROW]
[ROW][C]94[/C][C]3[/C][C]5.69023[/C][C]-2.69023[/C][/ROW]
[ROW][C]95[/C][C]1.5[/C][C]5.50913[/C][C]-4.00913[/C][/ROW]
[ROW][C]96[/C][C]3.5[/C][C]4.63758[/C][C]-1.13758[/C][/ROW]
[ROW][C]97[/C][C]2.5[/C][C]5.68099[/C][C]-3.18099[/C][/ROW]
[ROW][C]98[/C][C]5.5[/C][C]5.06914[/C][C]0.430861[/C][/ROW]
[ROW][C]99[/C][C]8[/C][C]5.41707[/C][C]2.58293[/C][/ROW]
[ROW][C]100[/C][C]1[/C][C]4.71625[/C][C]-3.71625[/C][/ROW]
[ROW][C]101[/C][C]5[/C][C]5.39122[/C][C]-0.391221[/C][/ROW]
[ROW][C]102[/C][C]4.5[/C][C]5.51798[/C][C]-1.01798[/C][/ROW]
[ROW][C]103[/C][C]3[/C][C]4.81866[/C][C]-1.81866[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.83715[/C][C]-1.83715[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]5.61075[/C][C]2.38925[/C][/ROW]
[ROW][C]106[/C][C]2.5[/C][C]4.67728[/C][C]-2.17728[/C][/ROW]
[ROW][C]107[/C][C]7[/C][C]4.87732[/C][C]2.12268[/C][/ROW]
[ROW][C]108[/C][C]0[/C][C]5.06764[/C][C]-5.06764[/C][/ROW]
[ROW][C]109[/C][C]1[/C][C]5.0673[/C][C]-4.0673[/C][/ROW]
[ROW][C]110[/C][C]3.5[/C][C]4.87278[/C][C]-1.37278[/C][/ROW]
[ROW][C]111[/C][C]5.5[/C][C]4.85238[/C][C]0.647617[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.70057[/C][C]0.799427[/C][/ROW]
[ROW][C]113[/C][C]0.5[/C][C]4.36746[/C][C]-3.86746[/C][/ROW]
[ROW][C]114[/C][C]7.5[/C][C]6.53106[/C][C]0.968941[/C][/ROW]
[ROW][C]115[/C][C]9[/C][C]6.9331[/C][C]2.0669[/C][/ROW]
[ROW][C]116[/C][C]9.5[/C][C]7.09678[/C][C]2.40322[/C][/ROW]
[ROW][C]117[/C][C]8.5[/C][C]8.20008[/C][C]0.29992[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]4.27197[/C][C]2.72803[/C][/ROW]
[ROW][C]119[/C][C]8[/C][C]11.0184[/C][C]-3.01843[/C][/ROW]
[ROW][C]120[/C][C]10[/C][C]7.24425[/C][C]2.75575[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]9.23653[/C][C]-2.23653[/C][/ROW]
[ROW][C]122[/C][C]8.5[/C][C]5.11033[/C][C]3.38967[/C][/ROW]
[ROW][C]123[/C][C]9[/C][C]8.74836[/C][C]0.251642[/C][/ROW]
[ROW][C]124[/C][C]9.5[/C][C]5.59447[/C][C]3.90553[/C][/ROW]
[ROW][C]125[/C][C]4[/C][C]7.28444[/C][C]-3.28444[/C][/ROW]
[ROW][C]126[/C][C]6[/C][C]6.65997[/C][C]-0.659965[/C][/ROW]
[ROW][C]127[/C][C]8[/C][C]7.26528[/C][C]0.734723[/C][/ROW]
[ROW][C]128[/C][C]5.5[/C][C]8.1218[/C][C]-2.6218[/C][/ROW]
[ROW][C]129[/C][C]9.5[/C][C]7.90616[/C][C]1.59384[/C][/ROW]
[ROW][C]130[/C][C]7.5[/C][C]5.79566[/C][C]1.70434[/C][/ROW]
[ROW][C]131[/C][C]7[/C][C]5.45857[/C][C]1.54143[/C][/ROW]
[ROW][C]132[/C][C]7.5[/C][C]8.65169[/C][C]-1.15169[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]5.94246[/C][C]2.05754[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]6.86105[/C][C]0.138952[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.08627[/C][C]0.913726[/C][/ROW]
[ROW][C]136[/C][C]6[/C][C]7.43471[/C][C]-1.43471[/C][/ROW]
[ROW][C]137[/C][C]10[/C][C]6.62957[/C][C]3.37043[/C][/ROW]
[ROW][C]138[/C][C]2.5[/C][C]6.33694[/C][C]-3.83694[/C][/ROW]
[ROW][C]139[/C][C]9[/C][C]8.78837[/C][C]0.211629[/C][/ROW]
[ROW][C]140[/C][C]8[/C][C]9.2269[/C][C]-1.2269[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]4.98945[/C][C]1.01055[/C][/ROW]
[ROW][C]142[/C][C]8.5[/C][C]4.61776[/C][C]3.88224[/C][/ROW]
[ROW][C]143[/C][C]6[/C][C]6.20164[/C][C]-0.201641[/C][/ROW]
[ROW][C]144[/C][C]9[/C][C]8.05783[/C][C]0.942166[/C][/ROW]
[ROW][C]145[/C][C]8[/C][C]6.67573[/C][C]1.32427[/C][/ROW]
[ROW][C]146[/C][C]9[/C][C]7.20709[/C][C]1.79291[/C][/ROW]
[ROW][C]147[/C][C]5.5[/C][C]6.04165[/C][C]-0.541649[/C][/ROW]
[ROW][C]148[/C][C]7[/C][C]6.50747[/C][C]0.492527[/C][/ROW]
[ROW][C]149[/C][C]5.5[/C][C]9.42404[/C][C]-3.92404[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]7.65278[/C][C]1.34722[/C][/ROW]
[ROW][C]151[/C][C]2[/C][C]7.07016[/C][C]-5.07016[/C][/ROW]
[ROW][C]152[/C][C]8.5[/C][C]6.87734[/C][C]1.62266[/C][/ROW]
[ROW][C]153[/C][C]9[/C][C]7.40544[/C][C]1.59456[/C][/ROW]
[ROW][C]154[/C][C]8.5[/C][C]8.37373[/C][C]0.126269[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.27727[/C][C]2.72273[/C][/ROW]
[ROW][C]156[/C][C]7.5[/C][C]7.04898[/C][C]0.451025[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]7.8091[/C][C]2.1909[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]7.12401[/C][C]1.87599[/C][/ROW]
[ROW][C]159[/C][C]7.5[/C][C]8.88088[/C][C]-1.38088[/C][/ROW]
[ROW][C]160[/C][C]6[/C][C]6.44814[/C][C]-0.448139[/C][/ROW]
[ROW][C]161[/C][C]10.5[/C][C]6.19761[/C][C]4.30239[/C][/ROW]
[ROW][C]162[/C][C]8.5[/C][C]9.16612[/C][C]-0.66612[/C][/ROW]
[ROW][C]163[/C][C]8[/C][C]6.90158[/C][C]1.09842[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]5.88175[/C][C]4.11825[/C][/ROW]
[ROW][C]165[/C][C]10.5[/C][C]6.75009[/C][C]3.74991[/C][/ROW]
[ROW][C]166[/C][C]6.5[/C][C]5.32202[/C][C]1.17798[/C][/ROW]
[ROW][C]167[/C][C]9.5[/C][C]7.85799[/C][C]1.64201[/C][/ROW]
[ROW][C]168[/C][C]8.5[/C][C]4.71139[/C][C]3.78861[/C][/ROW]
[ROW][C]169[/C][C]7.5[/C][C]7.71307[/C][C]-0.213069[/C][/ROW]
[ROW][C]170[/C][C]5[/C][C]7.18194[/C][C]-2.18194[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]7.52847[/C][C]0.471527[/C][/ROW]
[ROW][C]172[/C][C]10[/C][C]6.33527[/C][C]3.66473[/C][/ROW]
[ROW][C]173[/C][C]7[/C][C]5.83882[/C][C]1.16118[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]7.17561[/C][C]0.324391[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]7.17561[/C][C]0.324391[/C][/ROW]
[ROW][C]176[/C][C]9.5[/C][C]6.60655[/C][C]2.89345[/C][/ROW]
[ROW][C]177[/C][C]6[/C][C]6.67173[/C][C]-0.671734[/C][/ROW]
[ROW][C]178[/C][C]10[/C][C]8.04858[/C][C]1.95142[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]5.98308[/C][C]1.01692[/C][/ROW]
[ROW][C]180[/C][C]3[/C][C]6.1234[/C][C]-3.1234[/C][/ROW]
[ROW][C]181[/C][C]6[/C][C]6.98716[/C][C]-0.987157[/C][/ROW]
[ROW][C]182[/C][C]7[/C][C]6.87798[/C][C]0.122022[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]8.41206[/C][C]1.58794[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]6.85959[/C][C]0.140407[/C][/ROW]
[ROW][C]185[/C][C]3.5[/C][C]5.38967[/C][C]-1.88967[/C][/ROW]
[ROW][C]186[/C][C]8[/C][C]6.73201[/C][C]1.26799[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]5.70415[/C][C]4.29585[/C][/ROW]
[ROW][C]188[/C][C]5.5[/C][C]5.722[/C][C]-0.221998[/C][/ROW]
[ROW][C]189[/C][C]6[/C][C]3.96622[/C][C]2.03378[/C][/ROW]
[ROW][C]190[/C][C]6.5[/C][C]6.42096[/C][C]0.0790414[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]5.67603[/C][C]0.82397[/C][/ROW]
[ROW][C]192[/C][C]8.5[/C][C]6.6318[/C][C]1.8682[/C][/ROW]
[ROW][C]193[/C][C]4[/C][C]5.34723[/C][C]-1.34723[/C][/ROW]
[ROW][C]194[/C][C]9.5[/C][C]6.31392[/C][C]3.18608[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]5.95245[/C][C]2.04755[/C][/ROW]
[ROW][C]196[/C][C]8.5[/C][C]7.44217[/C][C]1.05783[/C][/ROW]
[ROW][C]197[/C][C]5.5[/C][C]8.33601[/C][C]-2.83601[/C][/ROW]
[ROW][C]198[/C][C]7[/C][C]7.38239[/C][C]-0.382388[/C][/ROW]
[ROW][C]199[/C][C]9[/C][C]5.72591[/C][C]3.27409[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.02641[/C][C]1.97359[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]7.89203[/C][C]2.10797[/C][/ROW]
[ROW][C]202[/C][C]8[/C][C]5.96039[/C][C]2.03961[/C][/ROW]
[ROW][C]203[/C][C]6[/C][C]6.15511[/C][C]-0.155107[/C][/ROW]
[ROW][C]204[/C][C]8[/C][C]7.514[/C][C]0.486003[/C][/ROW]
[ROW][C]205[/C][C]5[/C][C]5.97296[/C][C]-0.97296[/C][/ROW]
[ROW][C]206[/C][C]9[/C][C]5.28311[/C][C]3.71689[/C][/ROW]
[ROW][C]207[/C][C]4.5[/C][C]6.93738[/C][C]-2.43738[/C][/ROW]
[ROW][C]208[/C][C]8.5[/C][C]5.52523[/C][C]2.97477[/C][/ROW]
[ROW][C]209[/C][C]9.5[/C][C]8.35741[/C][C]1.14259[/C][/ROW]
[ROW][C]210[/C][C]8.5[/C][C]7.47665[/C][C]1.02335[/C][/ROW]
[ROW][C]211[/C][C]7.5[/C][C]4.97495[/C][C]2.52505[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]6.34039[/C][C]1.15961[/C][/ROW]
[ROW][C]213[/C][C]5[/C][C]7.54277[/C][C]-2.54277[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]8.65556[/C][C]-1.65556[/C][/ROW]
[ROW][C]215[/C][C]8[/C][C]8.48915[/C][C]-0.489151[/C][/ROW]
[ROW][C]216[/C][C]5.5[/C][C]6.44468[/C][C]-0.94468[/C][/ROW]
[ROW][C]217[/C][C]8.5[/C][C]6.25079[/C][C]2.24921[/C][/ROW]
[ROW][C]218[/C][C]9.5[/C][C]6.92535[/C][C]2.57465[/C][/ROW]
[ROW][C]219[/C][C]7[/C][C]5.71911[/C][C]1.28089[/C][/ROW]
[ROW][C]220[/C][C]8[/C][C]8.11529[/C][C]-0.115288[/C][/ROW]
[ROW][C]221[/C][C]8.5[/C][C]7.74831[/C][C]0.751694[/C][/ROW]
[ROW][C]222[/C][C]3.5[/C][C]6.45608[/C][C]-2.95608[/C][/ROW]
[ROW][C]223[/C][C]6.5[/C][C]5.89411[/C][C]0.605888[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.15426[/C][C]1.34574[/C][/ROW]
[ROW][C]225[/C][C]10.5[/C][C]7.80414[/C][C]2.69586[/C][/ROW]
[ROW][C]226[/C][C]8.5[/C][C]5.86706[/C][C]2.63294[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]6.29386[/C][C]1.70614[/C][/ROW]
[ROW][C]228[/C][C]10[/C][C]6.40792[/C][C]3.59208[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.56542[/C][C]2.43458[/C][/ROW]
[ROW][C]230[/C][C]9.5[/C][C]7.25329[/C][C]2.24671[/C][/ROW]
[ROW][C]231[/C][C]9[/C][C]5.7029[/C][C]3.2971[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]8.93116[/C][C]1.06884[/C][/ROW]
[ROW][C]233[/C][C]7.5[/C][C]5.60981[/C][C]1.89019[/C][/ROW]
[ROW][C]234[/C][C]4.5[/C][C]5.75908[/C][C]-1.25908[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.4988[/C][C]-0.998796[/C][/ROW]
[ROW][C]236[/C][C]0.5[/C][C]5.56842[/C][C]-5.06842[/C][/ROW]
[ROW][C]237[/C][C]6.5[/C][C]5.20366[/C][C]1.29634[/C][/ROW]
[ROW][C]238[/C][C]4.5[/C][C]7.49803[/C][C]-2.99803[/C][/ROW]
[ROW][C]239[/C][C]5.5[/C][C]6.84556[/C][C]-1.34556[/C][/ROW]
[ROW][C]240[/C][C]5[/C][C]5.38183[/C][C]-0.381833[/C][/ROW]
[ROW][C]241[/C][C]6[/C][C]7.45173[/C][C]-1.45173[/C][/ROW]
[ROW][C]242[/C][C]4[/C][C]7.14706[/C][C]-3.14706[/C][/ROW]
[ROW][C]243[/C][C]8[/C][C]5.32904[/C][C]2.67096[/C][/ROW]
[ROW][C]244[/C][C]10.5[/C][C]6.75009[/C][C]3.74991[/C][/ROW]
[ROW][C]245[/C][C]6.5[/C][C]5.92056[/C][C]0.579436[/C][/ROW]
[ROW][C]246[/C][C]8[/C][C]7.69157[/C][C]0.308432[/C][/ROW]
[ROW][C]247[/C][C]8.5[/C][C]7.88233[/C][C]0.617669[/C][/ROW]
[ROW][C]248[/C][C]5.5[/C][C]6.06703[/C][C]-0.567035[/C][/ROW]
[ROW][C]249[/C][C]7[/C][C]7.68206[/C][C]-0.682058[/C][/ROW]
[ROW][C]250[/C][C]5[/C][C]5.663[/C][C]-0.663005[/C][/ROW]
[ROW][C]251[/C][C]3.5[/C][C]4.99334[/C][C]-1.49334[/C][/ROW]
[ROW][C]252[/C][C]5[/C][C]7.31545[/C][C]-2.31545[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]7.40739[/C][C]1.59261[/C][/ROW]
[ROW][C]254[/C][C]8.5[/C][C]6.65255[/C][C]1.84745[/C][/ROW]
[ROW][C]255[/C][C]5[/C][C]6.22372[/C][C]-1.22372[/C][/ROW]
[ROW][C]256[/C][C]9.5[/C][C]8.11766[/C][C]1.38234[/C][/ROW]
[ROW][C]257[/C][C]3[/C][C]4.81331[/C][C]-1.81331[/C][/ROW]
[ROW][C]258[/C][C]1.5[/C][C]7.75641[/C][C]-6.25641[/C][/ROW]
[ROW][C]259[/C][C]6[/C][C]4.81446[/C][C]1.18554[/C][/ROW]
[ROW][C]260[/C][C]0.5[/C][C]5.26419[/C][C]-4.76419[/C][/ROW]
[ROW][C]261[/C][C]6.5[/C][C]5.32202[/C][C]1.17798[/C][/ROW]
[ROW][C]262[/C][C]7.5[/C][C]5.79719[/C][C]1.70281[/C][/ROW]
[ROW][C]263[/C][C]4.5[/C][C]5.81242[/C][C]-1.31242[/C][/ROW]
[ROW][C]264[/C][C]8[/C][C]5.32904[/C][C]2.67096[/C][/ROW]
[ROW][C]265[/C][C]9[/C][C]7.70093[/C][C]1.29907[/C][/ROW]
[ROW][C]266[/C][C]7.5[/C][C]6.66625[/C][C]0.833752[/C][/ROW]
[ROW][C]267[/C][C]8.5[/C][C]7.15625[/C][C]1.34375[/C][/ROW]
[ROW][C]268[/C][C]7[/C][C]5.16109[/C][C]1.83891[/C][/ROW]
[ROW][C]269[/C][C]9.5[/C][C]5.75562[/C][C]3.74438[/C][/ROW]
[ROW][C]270[/C][C]6.5[/C][C]5.07873[/C][C]1.42127[/C][/ROW]
[ROW][C]271[/C][C]9.5[/C][C]5.2355[/C][C]4.2645[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]5.27795[/C][C]0.722049[/C][/ROW]
[ROW][C]273[/C][C]8[/C][C]7.07831[/C][C]0.921688[/C][/ROW]
[ROW][C]274[/C][C]9.5[/C][C]7.88661[/C][C]1.61339[/C][/ROW]
[ROW][C]275[/C][C]8[/C][C]6.15573[/C][C]1.84427[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]6.26361[/C][C]1.73639[/C][/ROW]
[ROW][C]277[/C][C]9[/C][C]6.75968[/C][C]2.24032[/C][/ROW]
[ROW][C]278[/C][C]5[/C][C]5.49205[/C][C]-0.492051[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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
17.55.499952.00005
265.090390.909615
36.55.361061.13894
415.69958-4.69958
515.1014-4.1014
65.56.57565-1.07565
78.55.736132.76387
86.55.848790.651215
94.55.49883-0.998834
1026.48693-4.48693
1155.79604-0.796039
120.56.84519-6.34519
1355.22939-0.229389
1456.01258-1.01258
152.54.7087-2.2087
1655.36167-0.361671
175.56.28903-0.789028
183.55.55226-2.05226
1935.53224-2.53224
2045.36746-1.36746
210.55.05807-4.55807
226.55.337321.16268
234.55.55789-1.05789
247.55.205282.29472
255.55.69109-0.191089
2646.52592-2.52592
277.55.846641.65336
2875.297211.70279
2945.00525-1.00525
305.55.47910.0208954
312.55.75606-3.25606
325.56.07556-0.575562
333.55.64581-2.14581
342.56.33746-3.83746
354.55.92681-1.42681
364.56.03385-1.53385
374.55.24044-0.740438
3865.706760.293236
392.55.14213-2.64213
4056.62594-1.62594
4104.78859-4.78859
4256.35853-1.35853
436.55.059361.44064
4455.69258-0.692579
4565.1160.884
464.55.75585-1.25585
475.56.00865-0.50865
4815.08904-4.08904
497.54.706352.79365
5064.999091.00091
5155.57466-0.574662
5215.61489-4.61489
5356.06592-1.06592
546.55.68260.817403
5576.339280.660721
564.56.4244-1.9244
5705.31073-5.31073
588.55.530422.96958
593.54.61512-1.11512
607.55.651581.84842
613.55.77854-2.27854
6264.836841.16316
631.55.0781-3.5781
6496.055082.94492
653.54.68283-1.18283
663.55.07109-1.57109
6746.20153-2.20153
686.56.080210.419793
697.55.310242.18976
7065.074070.925932
7155.78005-0.780055
725.55.085370.414633
733.55.56368-2.06368
747.55.10132.3987
756.56.031610.468388
766.56.241530.258466
776.55.118541.38146
7876.956210.0437936
793.55.37504-1.87504
801.55.35882-3.85882
8144.88321-0.883215
827.54.779032.72097
834.55.75896-1.25896
8404.6468-4.6468
853.54.91251-1.41251
865.55.490340.00966152
8754.92140.078597
884.55.02164-0.521636
892.54.61455-2.11455
907.54.910372.58963
9175.000141.99986
9205.11112-5.11112
934.55.26839-0.768391
9435.69023-2.69023
951.55.50913-4.00913
963.54.63758-1.13758
972.55.68099-3.18099
985.55.069140.430861
9985.417072.58293
10014.71625-3.71625
10155.39122-0.391221
1024.55.51798-1.01798
10334.81866-1.81866
10434.83715-1.83715
10585.610752.38925
1062.54.67728-2.17728
10774.877322.12268
10805.06764-5.06764
10915.0673-4.0673
1103.54.87278-1.37278
1115.54.852380.647617
1125.54.700570.799427
1130.54.36746-3.86746
1147.56.531060.968941
11596.93312.0669
1169.57.096782.40322
1178.58.200080.29992
11874.271972.72803
119811.0184-3.01843
120107.244252.75575
12179.23653-2.23653
1228.55.110333.38967
12398.748360.251642
1249.55.594473.90553
12547.28444-3.28444
12666.65997-0.659965
12787.265280.734723
1285.58.1218-2.6218
1299.57.906161.59384
1307.55.795661.70434
13175.458571.54143
1327.58.65169-1.15169
13385.942462.05754
13476.861050.138952
13576.086270.913726
13667.43471-1.43471
137106.629573.37043
1382.56.33694-3.83694
13998.788370.211629
14089.2269-1.2269
14164.989451.01055
1428.54.617763.88224
14366.20164-0.201641
14498.057830.942166
14586.675731.32427
14697.207091.79291
1475.56.04165-0.541649
14876.507470.492527
1495.59.42404-3.92404
15097.652781.34722
15127.07016-5.07016
1528.56.877341.62266
15397.405441.59456
1548.58.373730.126269
15596.277272.72273
1567.57.048980.451025
157107.80912.1909
15897.124011.87599
1597.58.88088-1.38088
16066.44814-0.448139
16110.56.197614.30239
1628.59.16612-0.66612
16386.901581.09842
164105.881754.11825
16510.56.750093.74991
1666.55.322021.17798
1679.57.857991.64201
1688.54.711393.78861
1697.57.71307-0.213069
17057.18194-2.18194
17187.528470.471527
172106.335273.66473
17375.838821.16118
1747.57.175610.324391
1757.57.175610.324391
1769.56.606552.89345
17766.67173-0.671734
178108.048581.95142
17975.983081.01692
18036.1234-3.1234
18166.98716-0.987157
18276.877980.122022
183108.412061.58794
18476.859590.140407
1853.55.38967-1.88967
18686.732011.26799
187105.704154.29585
1885.55.722-0.221998
18963.966222.03378
1906.56.420960.0790414
1916.55.676030.82397
1928.56.63181.8682
19345.34723-1.34723
1949.56.313923.18608
19585.952452.04755
1968.57.442171.05783
1975.58.33601-2.83601
19877.38239-0.382388
19995.725913.27409
20086.026411.97359
201107.892032.10797
20285.960392.03961
20366.15511-0.155107
20487.5140.486003
20555.97296-0.97296
20695.283113.71689
2074.56.93738-2.43738
2088.55.525232.97477
2099.58.357411.14259
2108.57.476651.02335
2117.54.974952.52505
2127.56.340391.15961
21357.54277-2.54277
21478.65556-1.65556
21588.48915-0.489151
2165.56.44468-0.94468
2178.56.250792.24921
2189.56.925352.57465
21975.719111.28089
22088.11529-0.115288
2218.57.748310.751694
2223.56.45608-2.95608
2236.55.894110.605888
2246.55.154261.34574
22510.57.804142.69586
2268.55.867062.63294
22786.293861.70614
228106.407923.59208
229107.565422.43458
2309.57.253292.24671
23195.70293.2971
232108.931161.06884
2337.55.609811.89019
2344.55.75908-1.25908
2354.55.4988-0.998796
2360.55.56842-5.06842
2376.55.203661.29634
2384.57.49803-2.99803
2395.56.84556-1.34556
24055.38183-0.381833
24167.45173-1.45173
24247.14706-3.14706
24385.329042.67096
24410.56.750093.74991
2456.55.920560.579436
24687.691570.308432
2478.57.882330.617669
2485.56.06703-0.567035
24977.68206-0.682058
25055.663-0.663005
2513.54.99334-1.49334
25257.31545-2.31545
25397.407391.59261
2548.56.652551.84745
25556.22372-1.22372
2569.58.117661.38234
25734.81331-1.81331
2581.57.75641-6.25641
25964.814461.18554
2600.55.26419-4.76419
2616.55.322021.17798
2627.55.797191.70281
2634.55.81242-1.31242
26485.329042.67096
26597.700931.29907
2667.56.666250.833752
2678.57.156251.34375
26875.161091.83891
2699.55.755623.74438
2706.55.078731.42127
2719.55.23554.2645
27265.277950.722049
27387.078310.921688
2749.57.886611.61339
27586.155731.84427
27686.263611.73639
27796.759682.24032
27855.49205-0.492051






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.9633140.07337170.0366859
100.9605590.07888190.039441
110.9262160.1475680.0737839
120.9403880.1192230.0596117
130.9176560.1646880.0823442
140.8740990.2518020.125901
150.8211350.357730.178865
160.7975830.4048350.202417
170.7546310.4907380.245369
180.6867430.6265130.313257
190.6348010.7303970.365199
200.5681620.8636770.431838
210.6687260.6625470.331274
220.6971860.6056290.302814
230.6339480.7321040.366052
240.5791030.8417940.420897
250.518240.9635190.48176
260.4675020.9350050.532498
270.4051180.8102360.594882
280.441310.8826190.55869
290.4177290.8354580.582271
300.3850520.7701050.614948
310.3538850.707770.646115
320.3538960.7077920.646104
330.305810.611620.69419
340.3108860.6217730.689114
350.2712670.5425350.728733
360.2420450.484090.757955
370.201570.4031390.79843
380.214440.4288790.78556
390.2611840.5223690.738816
400.2335460.4670920.766454
410.3787020.7574050.621298
420.3435920.6871830.656408
430.3170410.6340830.682959
440.279560.559120.72044
450.2645460.5290910.735454
460.2298110.4596220.770189
470.1991470.3982940.800853
480.2865230.5730470.713477
490.3041370.6082750.695863
500.3070560.6141120.692944
510.2716420.5432850.728358
520.3096290.6192570.690371
530.2871980.5743950.712802
540.2949470.5898940.705053
550.3110960.6221930.688904
560.2805260.5610510.719474
570.4107540.8215080.589246
580.4987950.9975910.501205
590.4577790.9155580.542221
600.4800940.9601870.519906
610.4818190.9636370.518181
620.4654010.9308020.534599
630.5145940.9708130.485406
640.573920.8521610.42608
650.5531820.8936360.446818
660.5190970.9618060.480903
670.5093550.9812890.490645
680.4698580.9397160.530142
690.4858640.9717280.514136
700.4625270.9250540.537473
710.4306270.8612550.569373
720.3993530.7987060.600647
730.373930.7478590.62607
740.3752110.7504220.624789
750.3580470.7160950.641953
760.3345850.6691710.665415
770.326270.652540.67373
780.3165510.6331020.683449
790.2929390.5858790.707061
800.3575730.7151450.642427
810.3277180.6554370.672282
820.3527890.7055770.647211
830.3232440.6464870.676756
840.4422690.8845380.557731
850.427680.855360.57232
860.3942540.7885070.605746
870.3620580.7241160.637942
880.3308430.6616870.669157
890.3303230.6606460.669677
900.3491010.6982030.650899
910.3624680.7249360.637532
920.5024670.9950660.497533
930.4782250.956450.521775
940.4712230.9424450.528777
950.5193640.9612730.480636
960.5001870.9996270.499813
970.5269050.946190.473095
980.5079320.9841360.492068
990.5727270.8545460.427273
1000.6718830.6562340.328117
1010.6455540.7088910.354446
1020.6228460.7543090.377154
1030.6191970.7616050.380803
1040.6376420.7247160.362358
1050.66730.6654010.3327
1060.6916340.6167320.308366
1070.6963510.6072980.303649
1080.8345390.3309220.165461
1090.8801590.2396830.119841
1100.8858120.2283760.114188
1110.8767230.2465550.123277
1120.8675070.2649850.132493
1130.8956880.2086240.104312
1140.8990770.2018460.100923
1150.9140630.1718740.0859369
1160.928660.1426810.0713403
1170.9174810.1650380.0825189
1180.9376720.1246560.0623282
1190.9292240.1415520.0707761
1200.9371360.1257270.0628637
1210.943840.112320.0561599
1220.9623790.07524250.0376213
1230.9578770.08424540.0421227
1240.9781470.04370590.0218529
1250.9804990.03900140.0195007
1260.9765110.04697760.0234888
1270.9732880.05342490.0267125
1280.9715220.05695630.0284782
1290.9684430.06311370.0315569
1300.9670270.06594620.0329731
1310.9640720.07185520.0359276
1320.9598270.08034630.0401731
1330.9618640.07627270.0381363
1340.9551540.08969110.0448456
1350.9493530.1012940.0506472
1360.9417570.1164850.0582426
1370.9575920.0848170.0424085
1380.9670790.06584210.032921
1390.9609150.07816950.0390847
1400.9537230.09255330.0462766
1410.9474130.1051730.0525867
1420.9557440.08851110.0442556
1430.9534240.09315280.0465764
1440.9490230.1019550.0509775
1450.9404370.1191270.0595633
1460.9356050.1287910.0643953
1470.9282370.1435260.0717628
1480.9173410.1653180.0826591
1490.9218250.1563490.0781745
1500.9152780.1694430.0847217
1510.9661330.06773420.0338671
1520.9624510.07509780.0375489
1530.959440.08111920.0405596
1540.9515750.09685010.0484251
1550.960130.07973910.0398695
1560.9527640.09447230.0472361
1570.949390.1012190.0506096
1580.9480710.1038580.0519289
1590.9408890.1182220.0591111
1600.9333790.1332410.0666207
1610.9488870.1022260.0511132
1620.9404660.1190670.0595337
1630.9349440.1301110.0650557
1640.9697790.06044260.0302213
1650.9725480.05490390.0274519
1660.9692770.0614460.030723
1670.965730.06853980.0342699
1680.9744770.05104650.0255232
1690.9686390.06272290.0313615
1700.9692760.06144720.0307236
1710.9630480.07390370.0369518
1720.9695490.06090220.0304511
1730.9645450.07090980.0354549
1740.9571210.08575770.0428789
1750.9485840.1028330.0514164
1760.9503160.09936710.0496835
1770.944840.1103210.0551603
1780.9447030.1105930.0552965
1790.9360330.1279330.0639666
1800.9422270.1155470.0577734
1810.9431010.1137970.0568987
1820.9332390.1335220.066761
1830.9270650.145870.0729352
1840.9140820.1718360.0859181
1850.9282940.1434120.0717059
1860.9164670.1670670.0835334
1870.9459690.1080630.0540314
1880.9395550.120890.0604452
1890.9319460.1361080.0680542
1900.9185280.1629440.0814718
1910.904870.190260.0951299
1920.8931550.2136910.106845
1930.8873920.2252160.112608
1940.8968480.2063040.103152
1950.8907520.2184950.109248
1960.8834850.233030.116515
1970.8939870.2120250.106013
1980.8760930.2478130.123907
1990.887490.2250210.11251
2000.8736940.2526110.126306
2010.8609440.2781120.139056
2020.8585220.2829550.141478
2030.8416530.3166930.158347
2040.8204420.3591170.179558
2050.80910.38180.1909
2060.8503610.2992770.149639
2070.8408660.3182690.159134
2080.8628450.2743090.137155
2090.8409010.3181980.159099
2100.8158430.3683140.184157
2110.8083350.383330.191665
2120.7814320.4371370.218568
2130.8025430.3949140.197457
2140.7758520.4482960.224148
2150.7517420.4965160.248258
2160.7255350.5489290.274465
2170.7097730.5804540.290227
2180.7007950.598410.299205
2190.6698360.6603280.330164
2200.6303770.7392460.369623
2210.5982140.8035730.401786
2220.5998820.8002370.400118
2230.5567390.8865210.443261
2240.5188130.9623750.481187
2250.5224490.9551020.477551
2260.5594090.8811820.440591
2270.5541350.8917290.445865
2280.6072120.7855750.392788
2290.5731190.8537620.426881
2300.5759240.8481530.424076
2310.6153730.7692540.384627
2320.5700530.8598940.429947
2330.5534840.8930320.446516
2340.5244830.9510340.475517
2350.48270.96540.5173
2360.6444870.7110260.355513
2370.6177180.7645630.382282
2380.6516530.6966950.348347
2390.6180450.7639090.381955
2400.5740080.8519850.425992
2410.5435010.9129980.456499
2420.5793050.8413910.420695
2430.5624830.8750340.437517
2440.547110.905780.45289
2450.494490.9889810.50551
2460.4367850.8735710.563215
2470.3816080.7632150.618392
2480.3291350.6582710.670865
2490.2978460.5956920.702154
2500.25210.50420.7479
2510.2398170.4796340.760183
2520.2692710.5385410.730729
2530.2245750.449150.775425
2540.1819680.3639360.818032
2550.2153490.4306970.784651
2560.1870370.3740750.812963
2570.2033720.4067430.796628
2580.7710510.4578990.228949
2590.7373590.5252820.262641
2600.9995520.000896610.000448305
2610.9999853.0315e-051.51575e-05
2620.9999598.10929e-054.05465e-05
2630.999959.92501e-054.9625e-05
2640.9999370.0001257486.2874e-05
2650.9997210.0005575350.000278768
2660.9988030.002394420.00119721
2670.9967280.006543180.00327159
2680.9869820.02603510.0130176
2690.9543040.09139120.0456956

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.963314 & 0.0733717 & 0.0366859 \tabularnewline
10 & 0.960559 & 0.0788819 & 0.039441 \tabularnewline
11 & 0.926216 & 0.147568 & 0.0737839 \tabularnewline
12 & 0.940388 & 0.119223 & 0.0596117 \tabularnewline
13 & 0.917656 & 0.164688 & 0.0823442 \tabularnewline
14 & 0.874099 & 0.251802 & 0.125901 \tabularnewline
15 & 0.821135 & 0.35773 & 0.178865 \tabularnewline
16 & 0.797583 & 0.404835 & 0.202417 \tabularnewline
17 & 0.754631 & 0.490738 & 0.245369 \tabularnewline
18 & 0.686743 & 0.626513 & 0.313257 \tabularnewline
19 & 0.634801 & 0.730397 & 0.365199 \tabularnewline
20 & 0.568162 & 0.863677 & 0.431838 \tabularnewline
21 & 0.668726 & 0.662547 & 0.331274 \tabularnewline
22 & 0.697186 & 0.605629 & 0.302814 \tabularnewline
23 & 0.633948 & 0.732104 & 0.366052 \tabularnewline
24 & 0.579103 & 0.841794 & 0.420897 \tabularnewline
25 & 0.51824 & 0.963519 & 0.48176 \tabularnewline
26 & 0.467502 & 0.935005 & 0.532498 \tabularnewline
27 & 0.405118 & 0.810236 & 0.594882 \tabularnewline
28 & 0.44131 & 0.882619 & 0.55869 \tabularnewline
29 & 0.417729 & 0.835458 & 0.582271 \tabularnewline
30 & 0.385052 & 0.770105 & 0.614948 \tabularnewline
31 & 0.353885 & 0.70777 & 0.646115 \tabularnewline
32 & 0.353896 & 0.707792 & 0.646104 \tabularnewline
33 & 0.30581 & 0.61162 & 0.69419 \tabularnewline
34 & 0.310886 & 0.621773 & 0.689114 \tabularnewline
35 & 0.271267 & 0.542535 & 0.728733 \tabularnewline
36 & 0.242045 & 0.48409 & 0.757955 \tabularnewline
37 & 0.20157 & 0.403139 & 0.79843 \tabularnewline
38 & 0.21444 & 0.428879 & 0.78556 \tabularnewline
39 & 0.261184 & 0.522369 & 0.738816 \tabularnewline
40 & 0.233546 & 0.467092 & 0.766454 \tabularnewline
41 & 0.378702 & 0.757405 & 0.621298 \tabularnewline
42 & 0.343592 & 0.687183 & 0.656408 \tabularnewline
43 & 0.317041 & 0.634083 & 0.682959 \tabularnewline
44 & 0.27956 & 0.55912 & 0.72044 \tabularnewline
45 & 0.264546 & 0.529091 & 0.735454 \tabularnewline
46 & 0.229811 & 0.459622 & 0.770189 \tabularnewline
47 & 0.199147 & 0.398294 & 0.800853 \tabularnewline
48 & 0.286523 & 0.573047 & 0.713477 \tabularnewline
49 & 0.304137 & 0.608275 & 0.695863 \tabularnewline
50 & 0.307056 & 0.614112 & 0.692944 \tabularnewline
51 & 0.271642 & 0.543285 & 0.728358 \tabularnewline
52 & 0.309629 & 0.619257 & 0.690371 \tabularnewline
53 & 0.287198 & 0.574395 & 0.712802 \tabularnewline
54 & 0.294947 & 0.589894 & 0.705053 \tabularnewline
55 & 0.311096 & 0.622193 & 0.688904 \tabularnewline
56 & 0.280526 & 0.561051 & 0.719474 \tabularnewline
57 & 0.410754 & 0.821508 & 0.589246 \tabularnewline
58 & 0.498795 & 0.997591 & 0.501205 \tabularnewline
59 & 0.457779 & 0.915558 & 0.542221 \tabularnewline
60 & 0.480094 & 0.960187 & 0.519906 \tabularnewline
61 & 0.481819 & 0.963637 & 0.518181 \tabularnewline
62 & 0.465401 & 0.930802 & 0.534599 \tabularnewline
63 & 0.514594 & 0.970813 & 0.485406 \tabularnewline
64 & 0.57392 & 0.852161 & 0.42608 \tabularnewline
65 & 0.553182 & 0.893636 & 0.446818 \tabularnewline
66 & 0.519097 & 0.961806 & 0.480903 \tabularnewline
67 & 0.509355 & 0.981289 & 0.490645 \tabularnewline
68 & 0.469858 & 0.939716 & 0.530142 \tabularnewline
69 & 0.485864 & 0.971728 & 0.514136 \tabularnewline
70 & 0.462527 & 0.925054 & 0.537473 \tabularnewline
71 & 0.430627 & 0.861255 & 0.569373 \tabularnewline
72 & 0.399353 & 0.798706 & 0.600647 \tabularnewline
73 & 0.37393 & 0.747859 & 0.62607 \tabularnewline
74 & 0.375211 & 0.750422 & 0.624789 \tabularnewline
75 & 0.358047 & 0.716095 & 0.641953 \tabularnewline
76 & 0.334585 & 0.669171 & 0.665415 \tabularnewline
77 & 0.32627 & 0.65254 & 0.67373 \tabularnewline
78 & 0.316551 & 0.633102 & 0.683449 \tabularnewline
79 & 0.292939 & 0.585879 & 0.707061 \tabularnewline
80 & 0.357573 & 0.715145 & 0.642427 \tabularnewline
81 & 0.327718 & 0.655437 & 0.672282 \tabularnewline
82 & 0.352789 & 0.705577 & 0.647211 \tabularnewline
83 & 0.323244 & 0.646487 & 0.676756 \tabularnewline
84 & 0.442269 & 0.884538 & 0.557731 \tabularnewline
85 & 0.42768 & 0.85536 & 0.57232 \tabularnewline
86 & 0.394254 & 0.788507 & 0.605746 \tabularnewline
87 & 0.362058 & 0.724116 & 0.637942 \tabularnewline
88 & 0.330843 & 0.661687 & 0.669157 \tabularnewline
89 & 0.330323 & 0.660646 & 0.669677 \tabularnewline
90 & 0.349101 & 0.698203 & 0.650899 \tabularnewline
91 & 0.362468 & 0.724936 & 0.637532 \tabularnewline
92 & 0.502467 & 0.995066 & 0.497533 \tabularnewline
93 & 0.478225 & 0.95645 & 0.521775 \tabularnewline
94 & 0.471223 & 0.942445 & 0.528777 \tabularnewline
95 & 0.519364 & 0.961273 & 0.480636 \tabularnewline
96 & 0.500187 & 0.999627 & 0.499813 \tabularnewline
97 & 0.526905 & 0.94619 & 0.473095 \tabularnewline
98 & 0.507932 & 0.984136 & 0.492068 \tabularnewline
99 & 0.572727 & 0.854546 & 0.427273 \tabularnewline
100 & 0.671883 & 0.656234 & 0.328117 \tabularnewline
101 & 0.645554 & 0.708891 & 0.354446 \tabularnewline
102 & 0.622846 & 0.754309 & 0.377154 \tabularnewline
103 & 0.619197 & 0.761605 & 0.380803 \tabularnewline
104 & 0.637642 & 0.724716 & 0.362358 \tabularnewline
105 & 0.6673 & 0.665401 & 0.3327 \tabularnewline
106 & 0.691634 & 0.616732 & 0.308366 \tabularnewline
107 & 0.696351 & 0.607298 & 0.303649 \tabularnewline
108 & 0.834539 & 0.330922 & 0.165461 \tabularnewline
109 & 0.880159 & 0.239683 & 0.119841 \tabularnewline
110 & 0.885812 & 0.228376 & 0.114188 \tabularnewline
111 & 0.876723 & 0.246555 & 0.123277 \tabularnewline
112 & 0.867507 & 0.264985 & 0.132493 \tabularnewline
113 & 0.895688 & 0.208624 & 0.104312 \tabularnewline
114 & 0.899077 & 0.201846 & 0.100923 \tabularnewline
115 & 0.914063 & 0.171874 & 0.0859369 \tabularnewline
116 & 0.92866 & 0.142681 & 0.0713403 \tabularnewline
117 & 0.917481 & 0.165038 & 0.0825189 \tabularnewline
118 & 0.937672 & 0.124656 & 0.0623282 \tabularnewline
119 & 0.929224 & 0.141552 & 0.0707761 \tabularnewline
120 & 0.937136 & 0.125727 & 0.0628637 \tabularnewline
121 & 0.94384 & 0.11232 & 0.0561599 \tabularnewline
122 & 0.962379 & 0.0752425 & 0.0376213 \tabularnewline
123 & 0.957877 & 0.0842454 & 0.0421227 \tabularnewline
124 & 0.978147 & 0.0437059 & 0.0218529 \tabularnewline
125 & 0.980499 & 0.0390014 & 0.0195007 \tabularnewline
126 & 0.976511 & 0.0469776 & 0.0234888 \tabularnewline
127 & 0.973288 & 0.0534249 & 0.0267125 \tabularnewline
128 & 0.971522 & 0.0569563 & 0.0284782 \tabularnewline
129 & 0.968443 & 0.0631137 & 0.0315569 \tabularnewline
130 & 0.967027 & 0.0659462 & 0.0329731 \tabularnewline
131 & 0.964072 & 0.0718552 & 0.0359276 \tabularnewline
132 & 0.959827 & 0.0803463 & 0.0401731 \tabularnewline
133 & 0.961864 & 0.0762727 & 0.0381363 \tabularnewline
134 & 0.955154 & 0.0896911 & 0.0448456 \tabularnewline
135 & 0.949353 & 0.101294 & 0.0506472 \tabularnewline
136 & 0.941757 & 0.116485 & 0.0582426 \tabularnewline
137 & 0.957592 & 0.084817 & 0.0424085 \tabularnewline
138 & 0.967079 & 0.0658421 & 0.032921 \tabularnewline
139 & 0.960915 & 0.0781695 & 0.0390847 \tabularnewline
140 & 0.953723 & 0.0925533 & 0.0462766 \tabularnewline
141 & 0.947413 & 0.105173 & 0.0525867 \tabularnewline
142 & 0.955744 & 0.0885111 & 0.0442556 \tabularnewline
143 & 0.953424 & 0.0931528 & 0.0465764 \tabularnewline
144 & 0.949023 & 0.101955 & 0.0509775 \tabularnewline
145 & 0.940437 & 0.119127 & 0.0595633 \tabularnewline
146 & 0.935605 & 0.128791 & 0.0643953 \tabularnewline
147 & 0.928237 & 0.143526 & 0.0717628 \tabularnewline
148 & 0.917341 & 0.165318 & 0.0826591 \tabularnewline
149 & 0.921825 & 0.156349 & 0.0781745 \tabularnewline
150 & 0.915278 & 0.169443 & 0.0847217 \tabularnewline
151 & 0.966133 & 0.0677342 & 0.0338671 \tabularnewline
152 & 0.962451 & 0.0750978 & 0.0375489 \tabularnewline
153 & 0.95944 & 0.0811192 & 0.0405596 \tabularnewline
154 & 0.951575 & 0.0968501 & 0.0484251 \tabularnewline
155 & 0.96013 & 0.0797391 & 0.0398695 \tabularnewline
156 & 0.952764 & 0.0944723 & 0.0472361 \tabularnewline
157 & 0.94939 & 0.101219 & 0.0506096 \tabularnewline
158 & 0.948071 & 0.103858 & 0.0519289 \tabularnewline
159 & 0.940889 & 0.118222 & 0.0591111 \tabularnewline
160 & 0.933379 & 0.133241 & 0.0666207 \tabularnewline
161 & 0.948887 & 0.102226 & 0.0511132 \tabularnewline
162 & 0.940466 & 0.119067 & 0.0595337 \tabularnewline
163 & 0.934944 & 0.130111 & 0.0650557 \tabularnewline
164 & 0.969779 & 0.0604426 & 0.0302213 \tabularnewline
165 & 0.972548 & 0.0549039 & 0.0274519 \tabularnewline
166 & 0.969277 & 0.061446 & 0.030723 \tabularnewline
167 & 0.96573 & 0.0685398 & 0.0342699 \tabularnewline
168 & 0.974477 & 0.0510465 & 0.0255232 \tabularnewline
169 & 0.968639 & 0.0627229 & 0.0313615 \tabularnewline
170 & 0.969276 & 0.0614472 & 0.0307236 \tabularnewline
171 & 0.963048 & 0.0739037 & 0.0369518 \tabularnewline
172 & 0.969549 & 0.0609022 & 0.0304511 \tabularnewline
173 & 0.964545 & 0.0709098 & 0.0354549 \tabularnewline
174 & 0.957121 & 0.0857577 & 0.0428789 \tabularnewline
175 & 0.948584 & 0.102833 & 0.0514164 \tabularnewline
176 & 0.950316 & 0.0993671 & 0.0496835 \tabularnewline
177 & 0.94484 & 0.110321 & 0.0551603 \tabularnewline
178 & 0.944703 & 0.110593 & 0.0552965 \tabularnewline
179 & 0.936033 & 0.127933 & 0.0639666 \tabularnewline
180 & 0.942227 & 0.115547 & 0.0577734 \tabularnewline
181 & 0.943101 & 0.113797 & 0.0568987 \tabularnewline
182 & 0.933239 & 0.133522 & 0.066761 \tabularnewline
183 & 0.927065 & 0.14587 & 0.0729352 \tabularnewline
184 & 0.914082 & 0.171836 & 0.0859181 \tabularnewline
185 & 0.928294 & 0.143412 & 0.0717059 \tabularnewline
186 & 0.916467 & 0.167067 & 0.0835334 \tabularnewline
187 & 0.945969 & 0.108063 & 0.0540314 \tabularnewline
188 & 0.939555 & 0.12089 & 0.0604452 \tabularnewline
189 & 0.931946 & 0.136108 & 0.0680542 \tabularnewline
190 & 0.918528 & 0.162944 & 0.0814718 \tabularnewline
191 & 0.90487 & 0.19026 & 0.0951299 \tabularnewline
192 & 0.893155 & 0.213691 & 0.106845 \tabularnewline
193 & 0.887392 & 0.225216 & 0.112608 \tabularnewline
194 & 0.896848 & 0.206304 & 0.103152 \tabularnewline
195 & 0.890752 & 0.218495 & 0.109248 \tabularnewline
196 & 0.883485 & 0.23303 & 0.116515 \tabularnewline
197 & 0.893987 & 0.212025 & 0.106013 \tabularnewline
198 & 0.876093 & 0.247813 & 0.123907 \tabularnewline
199 & 0.88749 & 0.225021 & 0.11251 \tabularnewline
200 & 0.873694 & 0.252611 & 0.126306 \tabularnewline
201 & 0.860944 & 0.278112 & 0.139056 \tabularnewline
202 & 0.858522 & 0.282955 & 0.141478 \tabularnewline
203 & 0.841653 & 0.316693 & 0.158347 \tabularnewline
204 & 0.820442 & 0.359117 & 0.179558 \tabularnewline
205 & 0.8091 & 0.3818 & 0.1909 \tabularnewline
206 & 0.850361 & 0.299277 & 0.149639 \tabularnewline
207 & 0.840866 & 0.318269 & 0.159134 \tabularnewline
208 & 0.862845 & 0.274309 & 0.137155 \tabularnewline
209 & 0.840901 & 0.318198 & 0.159099 \tabularnewline
210 & 0.815843 & 0.368314 & 0.184157 \tabularnewline
211 & 0.808335 & 0.38333 & 0.191665 \tabularnewline
212 & 0.781432 & 0.437137 & 0.218568 \tabularnewline
213 & 0.802543 & 0.394914 & 0.197457 \tabularnewline
214 & 0.775852 & 0.448296 & 0.224148 \tabularnewline
215 & 0.751742 & 0.496516 & 0.248258 \tabularnewline
216 & 0.725535 & 0.548929 & 0.274465 \tabularnewline
217 & 0.709773 & 0.580454 & 0.290227 \tabularnewline
218 & 0.700795 & 0.59841 & 0.299205 \tabularnewline
219 & 0.669836 & 0.660328 & 0.330164 \tabularnewline
220 & 0.630377 & 0.739246 & 0.369623 \tabularnewline
221 & 0.598214 & 0.803573 & 0.401786 \tabularnewline
222 & 0.599882 & 0.800237 & 0.400118 \tabularnewline
223 & 0.556739 & 0.886521 & 0.443261 \tabularnewline
224 & 0.518813 & 0.962375 & 0.481187 \tabularnewline
225 & 0.522449 & 0.955102 & 0.477551 \tabularnewline
226 & 0.559409 & 0.881182 & 0.440591 \tabularnewline
227 & 0.554135 & 0.891729 & 0.445865 \tabularnewline
228 & 0.607212 & 0.785575 & 0.392788 \tabularnewline
229 & 0.573119 & 0.853762 & 0.426881 \tabularnewline
230 & 0.575924 & 0.848153 & 0.424076 \tabularnewline
231 & 0.615373 & 0.769254 & 0.384627 \tabularnewline
232 & 0.570053 & 0.859894 & 0.429947 \tabularnewline
233 & 0.553484 & 0.893032 & 0.446516 \tabularnewline
234 & 0.524483 & 0.951034 & 0.475517 \tabularnewline
235 & 0.4827 & 0.9654 & 0.5173 \tabularnewline
236 & 0.644487 & 0.711026 & 0.355513 \tabularnewline
237 & 0.617718 & 0.764563 & 0.382282 \tabularnewline
238 & 0.651653 & 0.696695 & 0.348347 \tabularnewline
239 & 0.618045 & 0.763909 & 0.381955 \tabularnewline
240 & 0.574008 & 0.851985 & 0.425992 \tabularnewline
241 & 0.543501 & 0.912998 & 0.456499 \tabularnewline
242 & 0.579305 & 0.841391 & 0.420695 \tabularnewline
243 & 0.562483 & 0.875034 & 0.437517 \tabularnewline
244 & 0.54711 & 0.90578 & 0.45289 \tabularnewline
245 & 0.49449 & 0.988981 & 0.50551 \tabularnewline
246 & 0.436785 & 0.873571 & 0.563215 \tabularnewline
247 & 0.381608 & 0.763215 & 0.618392 \tabularnewline
248 & 0.329135 & 0.658271 & 0.670865 \tabularnewline
249 & 0.297846 & 0.595692 & 0.702154 \tabularnewline
250 & 0.2521 & 0.5042 & 0.7479 \tabularnewline
251 & 0.239817 & 0.479634 & 0.760183 \tabularnewline
252 & 0.269271 & 0.538541 & 0.730729 \tabularnewline
253 & 0.224575 & 0.44915 & 0.775425 \tabularnewline
254 & 0.181968 & 0.363936 & 0.818032 \tabularnewline
255 & 0.215349 & 0.430697 & 0.784651 \tabularnewline
256 & 0.187037 & 0.374075 & 0.812963 \tabularnewline
257 & 0.203372 & 0.406743 & 0.796628 \tabularnewline
258 & 0.771051 & 0.457899 & 0.228949 \tabularnewline
259 & 0.737359 & 0.525282 & 0.262641 \tabularnewline
260 & 0.999552 & 0.00089661 & 0.000448305 \tabularnewline
261 & 0.999985 & 3.0315e-05 & 1.51575e-05 \tabularnewline
262 & 0.999959 & 8.10929e-05 & 4.05465e-05 \tabularnewline
263 & 0.99995 & 9.92501e-05 & 4.9625e-05 \tabularnewline
264 & 0.999937 & 0.000125748 & 6.2874e-05 \tabularnewline
265 & 0.999721 & 0.000557535 & 0.000278768 \tabularnewline
266 & 0.998803 & 0.00239442 & 0.00119721 \tabularnewline
267 & 0.996728 & 0.00654318 & 0.00327159 \tabularnewline
268 & 0.986982 & 0.0260351 & 0.0130176 \tabularnewline
269 & 0.954304 & 0.0913912 & 0.0456956 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&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]0.963314[/C][C]0.0733717[/C][C]0.0366859[/C][/ROW]
[ROW][C]10[/C][C]0.960559[/C][C]0.0788819[/C][C]0.039441[/C][/ROW]
[ROW][C]11[/C][C]0.926216[/C][C]0.147568[/C][C]0.0737839[/C][/ROW]
[ROW][C]12[/C][C]0.940388[/C][C]0.119223[/C][C]0.0596117[/C][/ROW]
[ROW][C]13[/C][C]0.917656[/C][C]0.164688[/C][C]0.0823442[/C][/ROW]
[ROW][C]14[/C][C]0.874099[/C][C]0.251802[/C][C]0.125901[/C][/ROW]
[ROW][C]15[/C][C]0.821135[/C][C]0.35773[/C][C]0.178865[/C][/ROW]
[ROW][C]16[/C][C]0.797583[/C][C]0.404835[/C][C]0.202417[/C][/ROW]
[ROW][C]17[/C][C]0.754631[/C][C]0.490738[/C][C]0.245369[/C][/ROW]
[ROW][C]18[/C][C]0.686743[/C][C]0.626513[/C][C]0.313257[/C][/ROW]
[ROW][C]19[/C][C]0.634801[/C][C]0.730397[/C][C]0.365199[/C][/ROW]
[ROW][C]20[/C][C]0.568162[/C][C]0.863677[/C][C]0.431838[/C][/ROW]
[ROW][C]21[/C][C]0.668726[/C][C]0.662547[/C][C]0.331274[/C][/ROW]
[ROW][C]22[/C][C]0.697186[/C][C]0.605629[/C][C]0.302814[/C][/ROW]
[ROW][C]23[/C][C]0.633948[/C][C]0.732104[/C][C]0.366052[/C][/ROW]
[ROW][C]24[/C][C]0.579103[/C][C]0.841794[/C][C]0.420897[/C][/ROW]
[ROW][C]25[/C][C]0.51824[/C][C]0.963519[/C][C]0.48176[/C][/ROW]
[ROW][C]26[/C][C]0.467502[/C][C]0.935005[/C][C]0.532498[/C][/ROW]
[ROW][C]27[/C][C]0.405118[/C][C]0.810236[/C][C]0.594882[/C][/ROW]
[ROW][C]28[/C][C]0.44131[/C][C]0.882619[/C][C]0.55869[/C][/ROW]
[ROW][C]29[/C][C]0.417729[/C][C]0.835458[/C][C]0.582271[/C][/ROW]
[ROW][C]30[/C][C]0.385052[/C][C]0.770105[/C][C]0.614948[/C][/ROW]
[ROW][C]31[/C][C]0.353885[/C][C]0.70777[/C][C]0.646115[/C][/ROW]
[ROW][C]32[/C][C]0.353896[/C][C]0.707792[/C][C]0.646104[/C][/ROW]
[ROW][C]33[/C][C]0.30581[/C][C]0.61162[/C][C]0.69419[/C][/ROW]
[ROW][C]34[/C][C]0.310886[/C][C]0.621773[/C][C]0.689114[/C][/ROW]
[ROW][C]35[/C][C]0.271267[/C][C]0.542535[/C][C]0.728733[/C][/ROW]
[ROW][C]36[/C][C]0.242045[/C][C]0.48409[/C][C]0.757955[/C][/ROW]
[ROW][C]37[/C][C]0.20157[/C][C]0.403139[/C][C]0.79843[/C][/ROW]
[ROW][C]38[/C][C]0.21444[/C][C]0.428879[/C][C]0.78556[/C][/ROW]
[ROW][C]39[/C][C]0.261184[/C][C]0.522369[/C][C]0.738816[/C][/ROW]
[ROW][C]40[/C][C]0.233546[/C][C]0.467092[/C][C]0.766454[/C][/ROW]
[ROW][C]41[/C][C]0.378702[/C][C]0.757405[/C][C]0.621298[/C][/ROW]
[ROW][C]42[/C][C]0.343592[/C][C]0.687183[/C][C]0.656408[/C][/ROW]
[ROW][C]43[/C][C]0.317041[/C][C]0.634083[/C][C]0.682959[/C][/ROW]
[ROW][C]44[/C][C]0.27956[/C][C]0.55912[/C][C]0.72044[/C][/ROW]
[ROW][C]45[/C][C]0.264546[/C][C]0.529091[/C][C]0.735454[/C][/ROW]
[ROW][C]46[/C][C]0.229811[/C][C]0.459622[/C][C]0.770189[/C][/ROW]
[ROW][C]47[/C][C]0.199147[/C][C]0.398294[/C][C]0.800853[/C][/ROW]
[ROW][C]48[/C][C]0.286523[/C][C]0.573047[/C][C]0.713477[/C][/ROW]
[ROW][C]49[/C][C]0.304137[/C][C]0.608275[/C][C]0.695863[/C][/ROW]
[ROW][C]50[/C][C]0.307056[/C][C]0.614112[/C][C]0.692944[/C][/ROW]
[ROW][C]51[/C][C]0.271642[/C][C]0.543285[/C][C]0.728358[/C][/ROW]
[ROW][C]52[/C][C]0.309629[/C][C]0.619257[/C][C]0.690371[/C][/ROW]
[ROW][C]53[/C][C]0.287198[/C][C]0.574395[/C][C]0.712802[/C][/ROW]
[ROW][C]54[/C][C]0.294947[/C][C]0.589894[/C][C]0.705053[/C][/ROW]
[ROW][C]55[/C][C]0.311096[/C][C]0.622193[/C][C]0.688904[/C][/ROW]
[ROW][C]56[/C][C]0.280526[/C][C]0.561051[/C][C]0.719474[/C][/ROW]
[ROW][C]57[/C][C]0.410754[/C][C]0.821508[/C][C]0.589246[/C][/ROW]
[ROW][C]58[/C][C]0.498795[/C][C]0.997591[/C][C]0.501205[/C][/ROW]
[ROW][C]59[/C][C]0.457779[/C][C]0.915558[/C][C]0.542221[/C][/ROW]
[ROW][C]60[/C][C]0.480094[/C][C]0.960187[/C][C]0.519906[/C][/ROW]
[ROW][C]61[/C][C]0.481819[/C][C]0.963637[/C][C]0.518181[/C][/ROW]
[ROW][C]62[/C][C]0.465401[/C][C]0.930802[/C][C]0.534599[/C][/ROW]
[ROW][C]63[/C][C]0.514594[/C][C]0.970813[/C][C]0.485406[/C][/ROW]
[ROW][C]64[/C][C]0.57392[/C][C]0.852161[/C][C]0.42608[/C][/ROW]
[ROW][C]65[/C][C]0.553182[/C][C]0.893636[/C][C]0.446818[/C][/ROW]
[ROW][C]66[/C][C]0.519097[/C][C]0.961806[/C][C]0.480903[/C][/ROW]
[ROW][C]67[/C][C]0.509355[/C][C]0.981289[/C][C]0.490645[/C][/ROW]
[ROW][C]68[/C][C]0.469858[/C][C]0.939716[/C][C]0.530142[/C][/ROW]
[ROW][C]69[/C][C]0.485864[/C][C]0.971728[/C][C]0.514136[/C][/ROW]
[ROW][C]70[/C][C]0.462527[/C][C]0.925054[/C][C]0.537473[/C][/ROW]
[ROW][C]71[/C][C]0.430627[/C][C]0.861255[/C][C]0.569373[/C][/ROW]
[ROW][C]72[/C][C]0.399353[/C][C]0.798706[/C][C]0.600647[/C][/ROW]
[ROW][C]73[/C][C]0.37393[/C][C]0.747859[/C][C]0.62607[/C][/ROW]
[ROW][C]74[/C][C]0.375211[/C][C]0.750422[/C][C]0.624789[/C][/ROW]
[ROW][C]75[/C][C]0.358047[/C][C]0.716095[/C][C]0.641953[/C][/ROW]
[ROW][C]76[/C][C]0.334585[/C][C]0.669171[/C][C]0.665415[/C][/ROW]
[ROW][C]77[/C][C]0.32627[/C][C]0.65254[/C][C]0.67373[/C][/ROW]
[ROW][C]78[/C][C]0.316551[/C][C]0.633102[/C][C]0.683449[/C][/ROW]
[ROW][C]79[/C][C]0.292939[/C][C]0.585879[/C][C]0.707061[/C][/ROW]
[ROW][C]80[/C][C]0.357573[/C][C]0.715145[/C][C]0.642427[/C][/ROW]
[ROW][C]81[/C][C]0.327718[/C][C]0.655437[/C][C]0.672282[/C][/ROW]
[ROW][C]82[/C][C]0.352789[/C][C]0.705577[/C][C]0.647211[/C][/ROW]
[ROW][C]83[/C][C]0.323244[/C][C]0.646487[/C][C]0.676756[/C][/ROW]
[ROW][C]84[/C][C]0.442269[/C][C]0.884538[/C][C]0.557731[/C][/ROW]
[ROW][C]85[/C][C]0.42768[/C][C]0.85536[/C][C]0.57232[/C][/ROW]
[ROW][C]86[/C][C]0.394254[/C][C]0.788507[/C][C]0.605746[/C][/ROW]
[ROW][C]87[/C][C]0.362058[/C][C]0.724116[/C][C]0.637942[/C][/ROW]
[ROW][C]88[/C][C]0.330843[/C][C]0.661687[/C][C]0.669157[/C][/ROW]
[ROW][C]89[/C][C]0.330323[/C][C]0.660646[/C][C]0.669677[/C][/ROW]
[ROW][C]90[/C][C]0.349101[/C][C]0.698203[/C][C]0.650899[/C][/ROW]
[ROW][C]91[/C][C]0.362468[/C][C]0.724936[/C][C]0.637532[/C][/ROW]
[ROW][C]92[/C][C]0.502467[/C][C]0.995066[/C][C]0.497533[/C][/ROW]
[ROW][C]93[/C][C]0.478225[/C][C]0.95645[/C][C]0.521775[/C][/ROW]
[ROW][C]94[/C][C]0.471223[/C][C]0.942445[/C][C]0.528777[/C][/ROW]
[ROW][C]95[/C][C]0.519364[/C][C]0.961273[/C][C]0.480636[/C][/ROW]
[ROW][C]96[/C][C]0.500187[/C][C]0.999627[/C][C]0.499813[/C][/ROW]
[ROW][C]97[/C][C]0.526905[/C][C]0.94619[/C][C]0.473095[/C][/ROW]
[ROW][C]98[/C][C]0.507932[/C][C]0.984136[/C][C]0.492068[/C][/ROW]
[ROW][C]99[/C][C]0.572727[/C][C]0.854546[/C][C]0.427273[/C][/ROW]
[ROW][C]100[/C][C]0.671883[/C][C]0.656234[/C][C]0.328117[/C][/ROW]
[ROW][C]101[/C][C]0.645554[/C][C]0.708891[/C][C]0.354446[/C][/ROW]
[ROW][C]102[/C][C]0.622846[/C][C]0.754309[/C][C]0.377154[/C][/ROW]
[ROW][C]103[/C][C]0.619197[/C][C]0.761605[/C][C]0.380803[/C][/ROW]
[ROW][C]104[/C][C]0.637642[/C][C]0.724716[/C][C]0.362358[/C][/ROW]
[ROW][C]105[/C][C]0.6673[/C][C]0.665401[/C][C]0.3327[/C][/ROW]
[ROW][C]106[/C][C]0.691634[/C][C]0.616732[/C][C]0.308366[/C][/ROW]
[ROW][C]107[/C][C]0.696351[/C][C]0.607298[/C][C]0.303649[/C][/ROW]
[ROW][C]108[/C][C]0.834539[/C][C]0.330922[/C][C]0.165461[/C][/ROW]
[ROW][C]109[/C][C]0.880159[/C][C]0.239683[/C][C]0.119841[/C][/ROW]
[ROW][C]110[/C][C]0.885812[/C][C]0.228376[/C][C]0.114188[/C][/ROW]
[ROW][C]111[/C][C]0.876723[/C][C]0.246555[/C][C]0.123277[/C][/ROW]
[ROW][C]112[/C][C]0.867507[/C][C]0.264985[/C][C]0.132493[/C][/ROW]
[ROW][C]113[/C][C]0.895688[/C][C]0.208624[/C][C]0.104312[/C][/ROW]
[ROW][C]114[/C][C]0.899077[/C][C]0.201846[/C][C]0.100923[/C][/ROW]
[ROW][C]115[/C][C]0.914063[/C][C]0.171874[/C][C]0.0859369[/C][/ROW]
[ROW][C]116[/C][C]0.92866[/C][C]0.142681[/C][C]0.0713403[/C][/ROW]
[ROW][C]117[/C][C]0.917481[/C][C]0.165038[/C][C]0.0825189[/C][/ROW]
[ROW][C]118[/C][C]0.937672[/C][C]0.124656[/C][C]0.0623282[/C][/ROW]
[ROW][C]119[/C][C]0.929224[/C][C]0.141552[/C][C]0.0707761[/C][/ROW]
[ROW][C]120[/C][C]0.937136[/C][C]0.125727[/C][C]0.0628637[/C][/ROW]
[ROW][C]121[/C][C]0.94384[/C][C]0.11232[/C][C]0.0561599[/C][/ROW]
[ROW][C]122[/C][C]0.962379[/C][C]0.0752425[/C][C]0.0376213[/C][/ROW]
[ROW][C]123[/C][C]0.957877[/C][C]0.0842454[/C][C]0.0421227[/C][/ROW]
[ROW][C]124[/C][C]0.978147[/C][C]0.0437059[/C][C]0.0218529[/C][/ROW]
[ROW][C]125[/C][C]0.980499[/C][C]0.0390014[/C][C]0.0195007[/C][/ROW]
[ROW][C]126[/C][C]0.976511[/C][C]0.0469776[/C][C]0.0234888[/C][/ROW]
[ROW][C]127[/C][C]0.973288[/C][C]0.0534249[/C][C]0.0267125[/C][/ROW]
[ROW][C]128[/C][C]0.971522[/C][C]0.0569563[/C][C]0.0284782[/C][/ROW]
[ROW][C]129[/C][C]0.968443[/C][C]0.0631137[/C][C]0.0315569[/C][/ROW]
[ROW][C]130[/C][C]0.967027[/C][C]0.0659462[/C][C]0.0329731[/C][/ROW]
[ROW][C]131[/C][C]0.964072[/C][C]0.0718552[/C][C]0.0359276[/C][/ROW]
[ROW][C]132[/C][C]0.959827[/C][C]0.0803463[/C][C]0.0401731[/C][/ROW]
[ROW][C]133[/C][C]0.961864[/C][C]0.0762727[/C][C]0.0381363[/C][/ROW]
[ROW][C]134[/C][C]0.955154[/C][C]0.0896911[/C][C]0.0448456[/C][/ROW]
[ROW][C]135[/C][C]0.949353[/C][C]0.101294[/C][C]0.0506472[/C][/ROW]
[ROW][C]136[/C][C]0.941757[/C][C]0.116485[/C][C]0.0582426[/C][/ROW]
[ROW][C]137[/C][C]0.957592[/C][C]0.084817[/C][C]0.0424085[/C][/ROW]
[ROW][C]138[/C][C]0.967079[/C][C]0.0658421[/C][C]0.032921[/C][/ROW]
[ROW][C]139[/C][C]0.960915[/C][C]0.0781695[/C][C]0.0390847[/C][/ROW]
[ROW][C]140[/C][C]0.953723[/C][C]0.0925533[/C][C]0.0462766[/C][/ROW]
[ROW][C]141[/C][C]0.947413[/C][C]0.105173[/C][C]0.0525867[/C][/ROW]
[ROW][C]142[/C][C]0.955744[/C][C]0.0885111[/C][C]0.0442556[/C][/ROW]
[ROW][C]143[/C][C]0.953424[/C][C]0.0931528[/C][C]0.0465764[/C][/ROW]
[ROW][C]144[/C][C]0.949023[/C][C]0.101955[/C][C]0.0509775[/C][/ROW]
[ROW][C]145[/C][C]0.940437[/C][C]0.119127[/C][C]0.0595633[/C][/ROW]
[ROW][C]146[/C][C]0.935605[/C][C]0.128791[/C][C]0.0643953[/C][/ROW]
[ROW][C]147[/C][C]0.928237[/C][C]0.143526[/C][C]0.0717628[/C][/ROW]
[ROW][C]148[/C][C]0.917341[/C][C]0.165318[/C][C]0.0826591[/C][/ROW]
[ROW][C]149[/C][C]0.921825[/C][C]0.156349[/C][C]0.0781745[/C][/ROW]
[ROW][C]150[/C][C]0.915278[/C][C]0.169443[/C][C]0.0847217[/C][/ROW]
[ROW][C]151[/C][C]0.966133[/C][C]0.0677342[/C][C]0.0338671[/C][/ROW]
[ROW][C]152[/C][C]0.962451[/C][C]0.0750978[/C][C]0.0375489[/C][/ROW]
[ROW][C]153[/C][C]0.95944[/C][C]0.0811192[/C][C]0.0405596[/C][/ROW]
[ROW][C]154[/C][C]0.951575[/C][C]0.0968501[/C][C]0.0484251[/C][/ROW]
[ROW][C]155[/C][C]0.96013[/C][C]0.0797391[/C][C]0.0398695[/C][/ROW]
[ROW][C]156[/C][C]0.952764[/C][C]0.0944723[/C][C]0.0472361[/C][/ROW]
[ROW][C]157[/C][C]0.94939[/C][C]0.101219[/C][C]0.0506096[/C][/ROW]
[ROW][C]158[/C][C]0.948071[/C][C]0.103858[/C][C]0.0519289[/C][/ROW]
[ROW][C]159[/C][C]0.940889[/C][C]0.118222[/C][C]0.0591111[/C][/ROW]
[ROW][C]160[/C][C]0.933379[/C][C]0.133241[/C][C]0.0666207[/C][/ROW]
[ROW][C]161[/C][C]0.948887[/C][C]0.102226[/C][C]0.0511132[/C][/ROW]
[ROW][C]162[/C][C]0.940466[/C][C]0.119067[/C][C]0.0595337[/C][/ROW]
[ROW][C]163[/C][C]0.934944[/C][C]0.130111[/C][C]0.0650557[/C][/ROW]
[ROW][C]164[/C][C]0.969779[/C][C]0.0604426[/C][C]0.0302213[/C][/ROW]
[ROW][C]165[/C][C]0.972548[/C][C]0.0549039[/C][C]0.0274519[/C][/ROW]
[ROW][C]166[/C][C]0.969277[/C][C]0.061446[/C][C]0.030723[/C][/ROW]
[ROW][C]167[/C][C]0.96573[/C][C]0.0685398[/C][C]0.0342699[/C][/ROW]
[ROW][C]168[/C][C]0.974477[/C][C]0.0510465[/C][C]0.0255232[/C][/ROW]
[ROW][C]169[/C][C]0.968639[/C][C]0.0627229[/C][C]0.0313615[/C][/ROW]
[ROW][C]170[/C][C]0.969276[/C][C]0.0614472[/C][C]0.0307236[/C][/ROW]
[ROW][C]171[/C][C]0.963048[/C][C]0.0739037[/C][C]0.0369518[/C][/ROW]
[ROW][C]172[/C][C]0.969549[/C][C]0.0609022[/C][C]0.0304511[/C][/ROW]
[ROW][C]173[/C][C]0.964545[/C][C]0.0709098[/C][C]0.0354549[/C][/ROW]
[ROW][C]174[/C][C]0.957121[/C][C]0.0857577[/C][C]0.0428789[/C][/ROW]
[ROW][C]175[/C][C]0.948584[/C][C]0.102833[/C][C]0.0514164[/C][/ROW]
[ROW][C]176[/C][C]0.950316[/C][C]0.0993671[/C][C]0.0496835[/C][/ROW]
[ROW][C]177[/C][C]0.94484[/C][C]0.110321[/C][C]0.0551603[/C][/ROW]
[ROW][C]178[/C][C]0.944703[/C][C]0.110593[/C][C]0.0552965[/C][/ROW]
[ROW][C]179[/C][C]0.936033[/C][C]0.127933[/C][C]0.0639666[/C][/ROW]
[ROW][C]180[/C][C]0.942227[/C][C]0.115547[/C][C]0.0577734[/C][/ROW]
[ROW][C]181[/C][C]0.943101[/C][C]0.113797[/C][C]0.0568987[/C][/ROW]
[ROW][C]182[/C][C]0.933239[/C][C]0.133522[/C][C]0.066761[/C][/ROW]
[ROW][C]183[/C][C]0.927065[/C][C]0.14587[/C][C]0.0729352[/C][/ROW]
[ROW][C]184[/C][C]0.914082[/C][C]0.171836[/C][C]0.0859181[/C][/ROW]
[ROW][C]185[/C][C]0.928294[/C][C]0.143412[/C][C]0.0717059[/C][/ROW]
[ROW][C]186[/C][C]0.916467[/C][C]0.167067[/C][C]0.0835334[/C][/ROW]
[ROW][C]187[/C][C]0.945969[/C][C]0.108063[/C][C]0.0540314[/C][/ROW]
[ROW][C]188[/C][C]0.939555[/C][C]0.12089[/C][C]0.0604452[/C][/ROW]
[ROW][C]189[/C][C]0.931946[/C][C]0.136108[/C][C]0.0680542[/C][/ROW]
[ROW][C]190[/C][C]0.918528[/C][C]0.162944[/C][C]0.0814718[/C][/ROW]
[ROW][C]191[/C][C]0.90487[/C][C]0.19026[/C][C]0.0951299[/C][/ROW]
[ROW][C]192[/C][C]0.893155[/C][C]0.213691[/C][C]0.106845[/C][/ROW]
[ROW][C]193[/C][C]0.887392[/C][C]0.225216[/C][C]0.112608[/C][/ROW]
[ROW][C]194[/C][C]0.896848[/C][C]0.206304[/C][C]0.103152[/C][/ROW]
[ROW][C]195[/C][C]0.890752[/C][C]0.218495[/C][C]0.109248[/C][/ROW]
[ROW][C]196[/C][C]0.883485[/C][C]0.23303[/C][C]0.116515[/C][/ROW]
[ROW][C]197[/C][C]0.893987[/C][C]0.212025[/C][C]0.106013[/C][/ROW]
[ROW][C]198[/C][C]0.876093[/C][C]0.247813[/C][C]0.123907[/C][/ROW]
[ROW][C]199[/C][C]0.88749[/C][C]0.225021[/C][C]0.11251[/C][/ROW]
[ROW][C]200[/C][C]0.873694[/C][C]0.252611[/C][C]0.126306[/C][/ROW]
[ROW][C]201[/C][C]0.860944[/C][C]0.278112[/C][C]0.139056[/C][/ROW]
[ROW][C]202[/C][C]0.858522[/C][C]0.282955[/C][C]0.141478[/C][/ROW]
[ROW][C]203[/C][C]0.841653[/C][C]0.316693[/C][C]0.158347[/C][/ROW]
[ROW][C]204[/C][C]0.820442[/C][C]0.359117[/C][C]0.179558[/C][/ROW]
[ROW][C]205[/C][C]0.8091[/C][C]0.3818[/C][C]0.1909[/C][/ROW]
[ROW][C]206[/C][C]0.850361[/C][C]0.299277[/C][C]0.149639[/C][/ROW]
[ROW][C]207[/C][C]0.840866[/C][C]0.318269[/C][C]0.159134[/C][/ROW]
[ROW][C]208[/C][C]0.862845[/C][C]0.274309[/C][C]0.137155[/C][/ROW]
[ROW][C]209[/C][C]0.840901[/C][C]0.318198[/C][C]0.159099[/C][/ROW]
[ROW][C]210[/C][C]0.815843[/C][C]0.368314[/C][C]0.184157[/C][/ROW]
[ROW][C]211[/C][C]0.808335[/C][C]0.38333[/C][C]0.191665[/C][/ROW]
[ROW][C]212[/C][C]0.781432[/C][C]0.437137[/C][C]0.218568[/C][/ROW]
[ROW][C]213[/C][C]0.802543[/C][C]0.394914[/C][C]0.197457[/C][/ROW]
[ROW][C]214[/C][C]0.775852[/C][C]0.448296[/C][C]0.224148[/C][/ROW]
[ROW][C]215[/C][C]0.751742[/C][C]0.496516[/C][C]0.248258[/C][/ROW]
[ROW][C]216[/C][C]0.725535[/C][C]0.548929[/C][C]0.274465[/C][/ROW]
[ROW][C]217[/C][C]0.709773[/C][C]0.580454[/C][C]0.290227[/C][/ROW]
[ROW][C]218[/C][C]0.700795[/C][C]0.59841[/C][C]0.299205[/C][/ROW]
[ROW][C]219[/C][C]0.669836[/C][C]0.660328[/C][C]0.330164[/C][/ROW]
[ROW][C]220[/C][C]0.630377[/C][C]0.739246[/C][C]0.369623[/C][/ROW]
[ROW][C]221[/C][C]0.598214[/C][C]0.803573[/C][C]0.401786[/C][/ROW]
[ROW][C]222[/C][C]0.599882[/C][C]0.800237[/C][C]0.400118[/C][/ROW]
[ROW][C]223[/C][C]0.556739[/C][C]0.886521[/C][C]0.443261[/C][/ROW]
[ROW][C]224[/C][C]0.518813[/C][C]0.962375[/C][C]0.481187[/C][/ROW]
[ROW][C]225[/C][C]0.522449[/C][C]0.955102[/C][C]0.477551[/C][/ROW]
[ROW][C]226[/C][C]0.559409[/C][C]0.881182[/C][C]0.440591[/C][/ROW]
[ROW][C]227[/C][C]0.554135[/C][C]0.891729[/C][C]0.445865[/C][/ROW]
[ROW][C]228[/C][C]0.607212[/C][C]0.785575[/C][C]0.392788[/C][/ROW]
[ROW][C]229[/C][C]0.573119[/C][C]0.853762[/C][C]0.426881[/C][/ROW]
[ROW][C]230[/C][C]0.575924[/C][C]0.848153[/C][C]0.424076[/C][/ROW]
[ROW][C]231[/C][C]0.615373[/C][C]0.769254[/C][C]0.384627[/C][/ROW]
[ROW][C]232[/C][C]0.570053[/C][C]0.859894[/C][C]0.429947[/C][/ROW]
[ROW][C]233[/C][C]0.553484[/C][C]0.893032[/C][C]0.446516[/C][/ROW]
[ROW][C]234[/C][C]0.524483[/C][C]0.951034[/C][C]0.475517[/C][/ROW]
[ROW][C]235[/C][C]0.4827[/C][C]0.9654[/C][C]0.5173[/C][/ROW]
[ROW][C]236[/C][C]0.644487[/C][C]0.711026[/C][C]0.355513[/C][/ROW]
[ROW][C]237[/C][C]0.617718[/C][C]0.764563[/C][C]0.382282[/C][/ROW]
[ROW][C]238[/C][C]0.651653[/C][C]0.696695[/C][C]0.348347[/C][/ROW]
[ROW][C]239[/C][C]0.618045[/C][C]0.763909[/C][C]0.381955[/C][/ROW]
[ROW][C]240[/C][C]0.574008[/C][C]0.851985[/C][C]0.425992[/C][/ROW]
[ROW][C]241[/C][C]0.543501[/C][C]0.912998[/C][C]0.456499[/C][/ROW]
[ROW][C]242[/C][C]0.579305[/C][C]0.841391[/C][C]0.420695[/C][/ROW]
[ROW][C]243[/C][C]0.562483[/C][C]0.875034[/C][C]0.437517[/C][/ROW]
[ROW][C]244[/C][C]0.54711[/C][C]0.90578[/C][C]0.45289[/C][/ROW]
[ROW][C]245[/C][C]0.49449[/C][C]0.988981[/C][C]0.50551[/C][/ROW]
[ROW][C]246[/C][C]0.436785[/C][C]0.873571[/C][C]0.563215[/C][/ROW]
[ROW][C]247[/C][C]0.381608[/C][C]0.763215[/C][C]0.618392[/C][/ROW]
[ROW][C]248[/C][C]0.329135[/C][C]0.658271[/C][C]0.670865[/C][/ROW]
[ROW][C]249[/C][C]0.297846[/C][C]0.595692[/C][C]0.702154[/C][/ROW]
[ROW][C]250[/C][C]0.2521[/C][C]0.5042[/C][C]0.7479[/C][/ROW]
[ROW][C]251[/C][C]0.239817[/C][C]0.479634[/C][C]0.760183[/C][/ROW]
[ROW][C]252[/C][C]0.269271[/C][C]0.538541[/C][C]0.730729[/C][/ROW]
[ROW][C]253[/C][C]0.224575[/C][C]0.44915[/C][C]0.775425[/C][/ROW]
[ROW][C]254[/C][C]0.181968[/C][C]0.363936[/C][C]0.818032[/C][/ROW]
[ROW][C]255[/C][C]0.215349[/C][C]0.430697[/C][C]0.784651[/C][/ROW]
[ROW][C]256[/C][C]0.187037[/C][C]0.374075[/C][C]0.812963[/C][/ROW]
[ROW][C]257[/C][C]0.203372[/C][C]0.406743[/C][C]0.796628[/C][/ROW]
[ROW][C]258[/C][C]0.771051[/C][C]0.457899[/C][C]0.228949[/C][/ROW]
[ROW][C]259[/C][C]0.737359[/C][C]0.525282[/C][C]0.262641[/C][/ROW]
[ROW][C]260[/C][C]0.999552[/C][C]0.00089661[/C][C]0.000448305[/C][/ROW]
[ROW][C]261[/C][C]0.999985[/C][C]3.0315e-05[/C][C]1.51575e-05[/C][/ROW]
[ROW][C]262[/C][C]0.999959[/C][C]8.10929e-05[/C][C]4.05465e-05[/C][/ROW]
[ROW][C]263[/C][C]0.99995[/C][C]9.92501e-05[/C][C]4.9625e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999937[/C][C]0.000125748[/C][C]6.2874e-05[/C][/ROW]
[ROW][C]265[/C][C]0.999721[/C][C]0.000557535[/C][C]0.000278768[/C][/ROW]
[ROW][C]266[/C][C]0.998803[/C][C]0.00239442[/C][C]0.00119721[/C][/ROW]
[ROW][C]267[/C][C]0.996728[/C][C]0.00654318[/C][C]0.00327159[/C][/ROW]
[ROW][C]268[/C][C]0.986982[/C][C]0.0260351[/C][C]0.0130176[/C][/ROW]
[ROW][C]269[/C][C]0.954304[/C][C]0.0913912[/C][C]0.0456956[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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
90.9633140.07337170.0366859
100.9605590.07888190.039441
110.9262160.1475680.0737839
120.9403880.1192230.0596117
130.9176560.1646880.0823442
140.8740990.2518020.125901
150.8211350.357730.178865
160.7975830.4048350.202417
170.7546310.4907380.245369
180.6867430.6265130.313257
190.6348010.7303970.365199
200.5681620.8636770.431838
210.6687260.6625470.331274
220.6971860.6056290.302814
230.6339480.7321040.366052
240.5791030.8417940.420897
250.518240.9635190.48176
260.4675020.9350050.532498
270.4051180.8102360.594882
280.441310.8826190.55869
290.4177290.8354580.582271
300.3850520.7701050.614948
310.3538850.707770.646115
320.3538960.7077920.646104
330.305810.611620.69419
340.3108860.6217730.689114
350.2712670.5425350.728733
360.2420450.484090.757955
370.201570.4031390.79843
380.214440.4288790.78556
390.2611840.5223690.738816
400.2335460.4670920.766454
410.3787020.7574050.621298
420.3435920.6871830.656408
430.3170410.6340830.682959
440.279560.559120.72044
450.2645460.5290910.735454
460.2298110.4596220.770189
470.1991470.3982940.800853
480.2865230.5730470.713477
490.3041370.6082750.695863
500.3070560.6141120.692944
510.2716420.5432850.728358
520.3096290.6192570.690371
530.2871980.5743950.712802
540.2949470.5898940.705053
550.3110960.6221930.688904
560.2805260.5610510.719474
570.4107540.8215080.589246
580.4987950.9975910.501205
590.4577790.9155580.542221
600.4800940.9601870.519906
610.4818190.9636370.518181
620.4654010.9308020.534599
630.5145940.9708130.485406
640.573920.8521610.42608
650.5531820.8936360.446818
660.5190970.9618060.480903
670.5093550.9812890.490645
680.4698580.9397160.530142
690.4858640.9717280.514136
700.4625270.9250540.537473
710.4306270.8612550.569373
720.3993530.7987060.600647
730.373930.7478590.62607
740.3752110.7504220.624789
750.3580470.7160950.641953
760.3345850.6691710.665415
770.326270.652540.67373
780.3165510.6331020.683449
790.2929390.5858790.707061
800.3575730.7151450.642427
810.3277180.6554370.672282
820.3527890.7055770.647211
830.3232440.6464870.676756
840.4422690.8845380.557731
850.427680.855360.57232
860.3942540.7885070.605746
870.3620580.7241160.637942
880.3308430.6616870.669157
890.3303230.6606460.669677
900.3491010.6982030.650899
910.3624680.7249360.637532
920.5024670.9950660.497533
930.4782250.956450.521775
940.4712230.9424450.528777
950.5193640.9612730.480636
960.5001870.9996270.499813
970.5269050.946190.473095
980.5079320.9841360.492068
990.5727270.8545460.427273
1000.6718830.6562340.328117
1010.6455540.7088910.354446
1020.6228460.7543090.377154
1030.6191970.7616050.380803
1040.6376420.7247160.362358
1050.66730.6654010.3327
1060.6916340.6167320.308366
1070.6963510.6072980.303649
1080.8345390.3309220.165461
1090.8801590.2396830.119841
1100.8858120.2283760.114188
1110.8767230.2465550.123277
1120.8675070.2649850.132493
1130.8956880.2086240.104312
1140.8990770.2018460.100923
1150.9140630.1718740.0859369
1160.928660.1426810.0713403
1170.9174810.1650380.0825189
1180.9376720.1246560.0623282
1190.9292240.1415520.0707761
1200.9371360.1257270.0628637
1210.943840.112320.0561599
1220.9623790.07524250.0376213
1230.9578770.08424540.0421227
1240.9781470.04370590.0218529
1250.9804990.03900140.0195007
1260.9765110.04697760.0234888
1270.9732880.05342490.0267125
1280.9715220.05695630.0284782
1290.9684430.06311370.0315569
1300.9670270.06594620.0329731
1310.9640720.07185520.0359276
1320.9598270.08034630.0401731
1330.9618640.07627270.0381363
1340.9551540.08969110.0448456
1350.9493530.1012940.0506472
1360.9417570.1164850.0582426
1370.9575920.0848170.0424085
1380.9670790.06584210.032921
1390.9609150.07816950.0390847
1400.9537230.09255330.0462766
1410.9474130.1051730.0525867
1420.9557440.08851110.0442556
1430.9534240.09315280.0465764
1440.9490230.1019550.0509775
1450.9404370.1191270.0595633
1460.9356050.1287910.0643953
1470.9282370.1435260.0717628
1480.9173410.1653180.0826591
1490.9218250.1563490.0781745
1500.9152780.1694430.0847217
1510.9661330.06773420.0338671
1520.9624510.07509780.0375489
1530.959440.08111920.0405596
1540.9515750.09685010.0484251
1550.960130.07973910.0398695
1560.9527640.09447230.0472361
1570.949390.1012190.0506096
1580.9480710.1038580.0519289
1590.9408890.1182220.0591111
1600.9333790.1332410.0666207
1610.9488870.1022260.0511132
1620.9404660.1190670.0595337
1630.9349440.1301110.0650557
1640.9697790.06044260.0302213
1650.9725480.05490390.0274519
1660.9692770.0614460.030723
1670.965730.06853980.0342699
1680.9744770.05104650.0255232
1690.9686390.06272290.0313615
1700.9692760.06144720.0307236
1710.9630480.07390370.0369518
1720.9695490.06090220.0304511
1730.9645450.07090980.0354549
1740.9571210.08575770.0428789
1750.9485840.1028330.0514164
1760.9503160.09936710.0496835
1770.944840.1103210.0551603
1780.9447030.1105930.0552965
1790.9360330.1279330.0639666
1800.9422270.1155470.0577734
1810.9431010.1137970.0568987
1820.9332390.1335220.066761
1830.9270650.145870.0729352
1840.9140820.1718360.0859181
1850.9282940.1434120.0717059
1860.9164670.1670670.0835334
1870.9459690.1080630.0540314
1880.9395550.120890.0604452
1890.9319460.1361080.0680542
1900.9185280.1629440.0814718
1910.904870.190260.0951299
1920.8931550.2136910.106845
1930.8873920.2252160.112608
1940.8968480.2063040.103152
1950.8907520.2184950.109248
1960.8834850.233030.116515
1970.8939870.2120250.106013
1980.8760930.2478130.123907
1990.887490.2250210.11251
2000.8736940.2526110.126306
2010.8609440.2781120.139056
2020.8585220.2829550.141478
2030.8416530.3166930.158347
2040.8204420.3591170.179558
2050.80910.38180.1909
2060.8503610.2992770.149639
2070.8408660.3182690.159134
2080.8628450.2743090.137155
2090.8409010.3181980.159099
2100.8158430.3683140.184157
2110.8083350.383330.191665
2120.7814320.4371370.218568
2130.8025430.3949140.197457
2140.7758520.4482960.224148
2150.7517420.4965160.248258
2160.7255350.5489290.274465
2170.7097730.5804540.290227
2180.7007950.598410.299205
2190.6698360.6603280.330164
2200.6303770.7392460.369623
2210.5982140.8035730.401786
2220.5998820.8002370.400118
2230.5567390.8865210.443261
2240.5188130.9623750.481187
2250.5224490.9551020.477551
2260.5594090.8811820.440591
2270.5541350.8917290.445865
2280.6072120.7855750.392788
2290.5731190.8537620.426881
2300.5759240.8481530.424076
2310.6153730.7692540.384627
2320.5700530.8598940.429947
2330.5534840.8930320.446516
2340.5244830.9510340.475517
2350.48270.96540.5173
2360.6444870.7110260.355513
2370.6177180.7645630.382282
2380.6516530.6966950.348347
2390.6180450.7639090.381955
2400.5740080.8519850.425992
2410.5435010.9129980.456499
2420.5793050.8413910.420695
2430.5624830.8750340.437517
2440.547110.905780.45289
2450.494490.9889810.50551
2460.4367850.8735710.563215
2470.3816080.7632150.618392
2480.3291350.6582710.670865
2490.2978460.5956920.702154
2500.25210.50420.7479
2510.2398170.4796340.760183
2520.2692710.5385410.730729
2530.2245750.449150.775425
2540.1819680.3639360.818032
2550.2153490.4306970.784651
2560.1870370.3740750.812963
2570.2033720.4067430.796628
2580.7710510.4578990.228949
2590.7373590.5252820.262641
2600.9995520.000896610.000448305
2610.9999853.0315e-051.51575e-05
2620.9999598.10929e-054.05465e-05
2630.999959.92501e-054.9625e-05
2640.9999370.0001257486.2874e-05
2650.9997210.0005575350.000278768
2660.9988030.002394420.00119721
2670.9967280.006543180.00327159
2680.9869820.02603510.0130176
2690.9543040.09139120.0456956






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level80.0306513NOK
5% type I error level120.045977OK
10% type I error level490.187739NOK

\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 & 8 & 0.0306513 & NOK \tabularnewline
5% type I error level & 12 & 0.045977 & OK \tabularnewline
10% type I error level & 49 & 0.187739 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266082&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]8[/C][C]0.0306513[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]12[/C][C]0.045977[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]49[/C][C]0.187739[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266082&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266082&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 level80.0306513NOK
5% type I error level120.045977OK
10% type I error level490.187739NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 6 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')
}