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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 16:05:51 +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/t14183141133t1h4hu76ze5l4e.htm/, Retrieved Thu, 16 May 2024 06:33:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=266153, Retrieved Thu, 16 May 2024 06:33:13 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-11 16:05:51] [8fb8f54f5311a3bdb9fc3d530bb27adb] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
149 7.5 68
139 6 39
148 6.5 32
158 1 62
128 1 33
224 5.5 52
159 8.5 62
105 6.5 77
159 4.5 76
167 2 41
165 5 48
159 0.5 63
119 5 30
176 5 78
54 2.5 19
91 5 31
163 5.5 66
124 3.5 35
137 3 42
121 4 45
153 0.5 21
148 6.5 25
221 4.5 44
188 7.5 69
149 5.5 54
244 4 74
148 7.5 80
92 7 42
150 4 61
153 5.5 41
94 2.5 46
156 5.5 39
132 3.5 34
161 2.5 51
105 4.5 42
97 4.5 31
151 4.5 39
131 6 20
166 2.5 49
157 5 53
111 0 31
145 5 39
162 6.5 54
163 5 49
59 6 34
187 4.5 46
109 5.5 55
90 1 42
105 7.5 50
83 6 13
116 5 37
42 1 25
148 5 30
155 6.5 28
125 7 45
116 4.5 35
128 0 28
138 8.5 41
49 3.5 6
96 7.5 45
164 3.5 73
162 6 17
99 1.5 40
202 9 64
186 3.5 37
66 3.5 25
183 4 65
214 6.5 100
188 7.5 28
104 6 35
177 5 56
126 5.5 29
76 3.5 43
99 7.5 59
139 6.5 50
78 NA 3
162 6.5 59
108 6.5 27
159 7 61
74 3.5 28
110 1.5 51
96 4 35
116 7.5 29
87 4.5 48
97 0 25
127 3.5 44
106 5.5 64
80 5 32
74 4.5 20
91 2.5 28
133 7.5 34
74 7 31
114 0 26
140 4.5 58
95 3 23
98 1.5 21
121 3.5 21
126 2.5 33
98 5.5 16
95 8 20
110 1 37
70 5 35
102 4.5 33
86 3 27
130 3 41
96 8 40
102 2.5 35
100 7 28
94 0 32
52 1 22
98 3.5 44
118 5.5 27
99 5.5 17
48 0.5 12
50 7.5 45
150 9 37
154 9.5 37
109 8.5 108
68 7 10
194 8 68
158 10 72
159 7 143
67 8.5 9
147 9 55
39 9.5 17
100 4 37
111 6 27
138 8 37
101 5.5 58
131 9.5 66
101 7.5 21
114 7 19
165 7.5 78
114 8 35
111 7 48
75 7 27
82 6 43
121 10 30
32 2.5 25
150 9 69
117 8 72
71 6 23
165 8.5 13
154 6 61
126 9 43
149 8 51
145 9 67
120 5.5 36
109 7 44
132 5.5 45
172 9 34
169 2 36
114 8.5 72
156 9 39
172 8.5 43
68 9 25
89 7.5 56
167 10 80
113 9 40
115 7.5 73
78 6 34
118 10.5 72
87 8.5 42
173 8 61
2 10 23
162 10.5 74
49 6.5 16
122 9.5 66
96 8.5 9
100 7.5 41
82 5 57
100 8 48
115 10 51
141 7 53
165 7.5 29
165 7.5 29
110 9.5 55
118 6 54
158 10 43
146 7 51
49 3 20
90 6 79
121 7 39
155 10 61
104 7 55
147 3.5 30
110 8 55
108 10 22
113 5.5 37
115 6 2
61 6.5 38
60 6.5 27
109 8.5 56
68 4 25
111 9.5 39
77 8 33
73 8.5 43
151 5.5 57
89 7 43
78 9 23
110 8 44
220 10 54
65 8 28
141 6 36
117 8 39
122 5 16
63 9 23
44 4.5 40
52 8.5 24
131 9.5 78
101 8.5 57
42 7.5 37
152 7.5 27
107 5 61
77 7 27
154 8 69
103 5.5 34
96 8.5 44
175 9.5 34
57 7 39
112 8 51
143 8.5 34
49 3.5 31
110 6.5 13
131 6.5 12
167 10.5 51
56 8.5 24
137 8 19
86 10 30
121 10 81
149 9.5 42
168 9 22
140 10 85
88 7.5 27
168 4.5 25
94 4.5 22
51 0.5 19
48 6.5 14
145 4.5 45
66 5.5 45
85 5 28
109 6 51
63 4 41
102 8 31
162 10.5 74
86 6.5 19
114 8 51
164 8.5 73
119 5.5 24
126 7 61
132 5 23
142 3.5 14
83 5 54
94 9 51
81 8.5 62
166 5 36
110 9.5 59
64 3 24
93 1.5 26
104 6 54
105 0.5 39
49 6.5 16
88 7.5 36
95 4.5 31
102 8 31
99 9 42
63 7.5 39
76 8.5 25
109 7 31
117 9.5 38
57 6.5 31
120 9.5 17
73 6 22
91 8 55
108 9.5 62
105 8 51
117 8 30
119 9 49
31 5 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 4.837 -0.000260363LFM[t] + 0.0332298CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  4.837 -0.000260363LFM[t] +  0.0332298CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  4.837 -0.000260363LFM[t] +  0.0332298CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&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] = + 4.837 -0.000260363LFM[t] + 0.0332298CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.8370.4790510.11.35161e-206.75803e-21
LFM-0.0002603630.00415221-0.06270.9500470.475024
CH0.03322980.008674593.8310.0001583467.91728e-05

\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) & 4.837 & 0.47905 & 10.1 & 1.35161e-20 & 6.75803e-21 \tabularnewline
LFM & -0.000260363 & 0.00415221 & -0.0627 & 0.950047 & 0.475024 \tabularnewline
CH & 0.0332298 & 0.00867459 & 3.831 & 0.000158346 & 7.91728e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&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]4.837[/C][C]0.47905[/C][C]10.1[/C][C]1.35161e-20[/C][C]6.75803e-21[/C][/ROW]
[ROW][C]LFM[/C][C]-0.000260363[/C][C]0.00415221[/C][C]-0.0627[/C][C]0.950047[/C][C]0.475024[/C][/ROW]
[ROW][C]CH[/C][C]0.0332298[/C][C]0.00867459[/C][C]3.831[/C][C]0.000158346[/C][C]7.91728e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&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)4.8370.4790510.11.35161e-206.75803e-21
LFM-0.0002603630.00415221-0.06270.9500470.475024
CH0.03322980.008674593.8310.0001583467.91728e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.248275
R-squared0.0616406
Adjusted R-squared0.0548162
F-TEST (value)9.03234
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value0.000158769
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.46321
Sum Squared Residuals1668.54

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.248275 \tabularnewline
R-squared & 0.0616406 \tabularnewline
Adjusted R-squared & 0.0548162 \tabularnewline
F-TEST (value) & 9.03234 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 0.000158769 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.46321 \tabularnewline
Sum Squared Residuals & 1668.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.248275[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0616406[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0548162[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]9.03234[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]0.000158769[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.46321[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1668.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&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 R0.248275
R-squared0.0616406
Adjusted R-squared0.0548162
F-TEST (value)9.03234
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value0.000158769
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.46321
Sum Squared Residuals1668.54






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.57.057830.442174
266.09677-0.0967665
36.55.861810.638185
416.8561-5.8561
515.90025-4.90025
65.56.50662-1.00662
78.56.855841.64416
86.57.36835-0.86835
94.57.32106-2.82106
1026.15594-4.15594
1156.38906-1.38906
120.56.88907-6.38907
1355.80291-0.802906
1457.38309-2.38309
152.55.4543-2.9543
1655.84343-0.843426
175.56.98772-1.48772
183.55.96775-2.46775
1936.19698-3.19698
2046.30083-2.30083
210.55.49499-4.99499
226.55.629210.870793
234.56.24157-1.74157
247.57.08090.419099
255.56.59261-1.09261
2647.23247-3.23247
277.57.456840.0431568
2876.208690.791307
2946.82496-2.82496
305.56.15958-0.659581
312.56.34109-3.84109
325.56.09234-0.59234
333.55.93244-2.43244
342.56.4898-3.9898
354.56.20531-1.70531
364.55.84186-1.34186
374.56.09364-1.59364
3865.467480.532516
392.56.42203-3.92203
4056.5573-1.5573
4105.83822-5.83822
4256.0952-1.0952
436.56.58922-0.0892245
4456.42282-1.42282
4565.951450.0485532
464.56.31688-1.81688
475.56.63625-1.13625
4816.20921-5.20921
497.56.471151.02885
5065.247370.752627
5156.0363-1.0363
5215.65681-4.65681
5355.79536-0.795355
546.55.727070.772927
5576.299790.70021
564.55.96984-1.46984
5705.7341-5.7341
588.56.163492.33651
593.55.02362-1.52362
607.56.307341.19266
613.57.22007-3.72007
6265.359720.640276
631.56.14041-4.64041
6496.911112.08889
653.56.01807-2.51807
663.55.65056-2.15056
6746.94928-2.94928
686.58.10425-1.60425
697.55.718481.78152
7065.972960.0270398
7156.65178-1.65178
725.55.76785-0.267854
733.56.24609-2.74609
747.56.771780.728224
756.56.462290.0377062
76NANA-0.255373
776.55.706080.793919
786.56.322610.177386
7979.24816-2.24816
803.58.50307-5.00307
811.53.47504-1.97504
8242.270461.72954
837.59.40937-1.90937
844.510.1425-5.64249
8502.76604-2.76604
863.54.9361-1.4361
875.56.37952-0.87952
8855.98232-0.982325
894.57.74374-3.24374
902.50.932181.56782
917.56.347851.15215
92712.6713-5.67129
9302.22787-2.22787
944.57.07655-2.57655
9537.00931-4.00931
961.53.50332-2.00332
973.56.90077-3.40077
982.52.343160.156843
995.52.976862.52314
100813.0379-5.03786
10111.98181-0.981813
10256.40702-1.40702
1034.57.21181-2.71181
10436.16557-3.16557
10531.141191.85881
106811.4735-3.47348
1072.51.241391.25861
108712.8759-5.87587
10904.55451-4.55451
11013.77359-2.77359
1113.53.70348-0.203477
1125.55.376130.123874
1135.510.2233-4.72326
1140.5-0.6806831.18068
1157.54.527442.97256
11695.52643.4736
1179.59.397430.102569
1188.56.651591.84841
11976.046110.953891
12085.18842.8116
1211012.5475-2.54745
12273.618623.38138
1238.56.126362.37364
12494.891754.10825
1259.511.5405-2.04046
12643.70530.2947
12764.030571.96943
12889.23803-1.23803
1295.52.996052.50395
1309.57.508521.99148
1317.55.938681.56132
13276.885960.114042
1337.55.470362.02964
13487.403120.596876
13575.714671.28533
13677.24453-0.244526
13761.802394.19761
1381013.1594-3.15941
1392.50.5907951.9092
14098.199080.800924
14187.58280.417205
14262.726023.27398
1438.59.32392-0.823916
14463.233072.76693
14597.492921.50708
14686.025641.97436
14799.50202-0.502024
1485.54.770730.729274
14977.79797-0.797968
1505.52.422033.07797
151912.9893-3.98927
15220.6998581.30014
1538.55.592342.90766
15496.721092.27891
1558.55.150043.34996
15698.174690.82531
1577.54.95192.5481
158107.136772.86323
15998.732830.267173
1607.57.44650.0535001
16162.698823.30118
16210.58.209992.29001
1638.57.318971.18103
16483.600764.39924
165106.753823.24618
16610.59.355911.14409
1676.53.99842.5016
1689.56.111073.38893
1698.57.173381.32662
1707.59.20974-1.70974
17153.405991.59401
17284.501773.49823
173109.561460.438538
17475.25771.7423
1757.55.75771.7423
1767.54.635992.86401
1779.510.1007-0.60068
17862.224743.77526
179109.49370.506299
18079.48883-2.48883
18134.43871-1.43871
18265.101450.898547
18373.823663.17634
184109.637560.362445
18579.29562-2.29562
1863.52.135991.36401
18783.539934.46007
1881010.5371-0.537076
1895.54.373511.12649
19065.583850.416155
1916.55.718580.781422
1926.54.669481.83052
1938.510.15-1.65004
19440.6040573.39594
1959.57.413532.08647
19685.746872.25313
1978.59.69178-1.19178
1985.54.74270.757296
19973.580973.41903
20097.270471.72953
20184.574123.42588
202107.750512.24949
20387.996560.0034435
20464.102491.89751
20588.33691-0.336908
20651.584883.41512
207910.6547-1.65473
2084.51.620972.87903
2098.56.394812.10519
2109.57.70481.7952
2118.57.055561.44444
2127.55.694621.80538
2137.59.33615-1.83615
21453.714151.28585
21576.089750.910246
21688.43999-0.439991
2175.53.274112.22589
2188.54.921243.57876
2199.58.618120.881884
22075.502551.49745
22185.429582.57042
2228.510.8544-2.35436
2233.52.240341.25966
2246.55.201651.29835
2256.52.488234.01177
22610.57.619932.88007
2278.55.932692.56731
22883.81154.1885
229107.49712.5029
230106.693853.30615
2319.56.024313.47569
23296.625072.37493
233108.211291.78871
2347.58.624-1.124
2354.55.54358-1.04358
2364.59.45508-4.95508
2370.5-0.7102841.21028
2386.58.29458-1.79458
2394.55.31515-0.815152
2405.56.2453-0.745299
24155.50333-0.503334
24268.18301-2.18301
24341.840562.15944
24484.753823.24618
24510.59.445971.05403
2466.55.002031.49797
24786.720071.27993
2488.58.60353-0.103527
2495.55.331210.168794
25077.56691-0.566913
25156.76524-1.76524
2523.55.10979-1.60979
25352.507242.49276
25497.376151.62385
2558.59.49005-0.990047
25652.268912.73109
2579.512.1178-2.61785
25837.17676-4.17676
2591.52.10433-0.604326
260611.6056-5.60562
2610.5-0.6440851.14409
2626.55.010361.48964
2637.58.84238-1.34238
2644.52.340562.15944
26585.206872.79313
26697.616551.38345
2677.54.647952.85205
2688.57.338741.16126
26973.569263.43074
2709.58.852280.647722
2716.52.370664.12934
2729.59.049040.450955
27364.640941.35906
27485.369122.63088
2759.58.004381.49562
27685.803432.19657
27785.434272.56573
27899.3606-0.360601
2795NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 7.05783 & 0.442174 \tabularnewline
2 & 6 & 6.09677 & -0.0967665 \tabularnewline
3 & 6.5 & 5.86181 & 0.638185 \tabularnewline
4 & 1 & 6.8561 & -5.8561 \tabularnewline
5 & 1 & 5.90025 & -4.90025 \tabularnewline
6 & 5.5 & 6.50662 & -1.00662 \tabularnewline
7 & 8.5 & 6.85584 & 1.64416 \tabularnewline
8 & 6.5 & 7.36835 & -0.86835 \tabularnewline
9 & 4.5 & 7.32106 & -2.82106 \tabularnewline
10 & 2 & 6.15594 & -4.15594 \tabularnewline
11 & 5 & 6.38906 & -1.38906 \tabularnewline
12 & 0.5 & 6.88907 & -6.38907 \tabularnewline
13 & 5 & 5.80291 & -0.802906 \tabularnewline
14 & 5 & 7.38309 & -2.38309 \tabularnewline
15 & 2.5 & 5.4543 & -2.9543 \tabularnewline
16 & 5 & 5.84343 & -0.843426 \tabularnewline
17 & 5.5 & 6.98772 & -1.48772 \tabularnewline
18 & 3.5 & 5.96775 & -2.46775 \tabularnewline
19 & 3 & 6.19698 & -3.19698 \tabularnewline
20 & 4 & 6.30083 & -2.30083 \tabularnewline
21 & 0.5 & 5.49499 & -4.99499 \tabularnewline
22 & 6.5 & 5.62921 & 0.870793 \tabularnewline
23 & 4.5 & 6.24157 & -1.74157 \tabularnewline
24 & 7.5 & 7.0809 & 0.419099 \tabularnewline
25 & 5.5 & 6.59261 & -1.09261 \tabularnewline
26 & 4 & 7.23247 & -3.23247 \tabularnewline
27 & 7.5 & 7.45684 & 0.0431568 \tabularnewline
28 & 7 & 6.20869 & 0.791307 \tabularnewline
29 & 4 & 6.82496 & -2.82496 \tabularnewline
30 & 5.5 & 6.15958 & -0.659581 \tabularnewline
31 & 2.5 & 6.34109 & -3.84109 \tabularnewline
32 & 5.5 & 6.09234 & -0.59234 \tabularnewline
33 & 3.5 & 5.93244 & -2.43244 \tabularnewline
34 & 2.5 & 6.4898 & -3.9898 \tabularnewline
35 & 4.5 & 6.20531 & -1.70531 \tabularnewline
36 & 4.5 & 5.84186 & -1.34186 \tabularnewline
37 & 4.5 & 6.09364 & -1.59364 \tabularnewline
38 & 6 & 5.46748 & 0.532516 \tabularnewline
39 & 2.5 & 6.42203 & -3.92203 \tabularnewline
40 & 5 & 6.5573 & -1.5573 \tabularnewline
41 & 0 & 5.83822 & -5.83822 \tabularnewline
42 & 5 & 6.0952 & -1.0952 \tabularnewline
43 & 6.5 & 6.58922 & -0.0892245 \tabularnewline
44 & 5 & 6.42282 & -1.42282 \tabularnewline
45 & 6 & 5.95145 & 0.0485532 \tabularnewline
46 & 4.5 & 6.31688 & -1.81688 \tabularnewline
47 & 5.5 & 6.63625 & -1.13625 \tabularnewline
48 & 1 & 6.20921 & -5.20921 \tabularnewline
49 & 7.5 & 6.47115 & 1.02885 \tabularnewline
50 & 6 & 5.24737 & 0.752627 \tabularnewline
51 & 5 & 6.0363 & -1.0363 \tabularnewline
52 & 1 & 5.65681 & -4.65681 \tabularnewline
53 & 5 & 5.79536 & -0.795355 \tabularnewline
54 & 6.5 & 5.72707 & 0.772927 \tabularnewline
55 & 7 & 6.29979 & 0.70021 \tabularnewline
56 & 4.5 & 5.96984 & -1.46984 \tabularnewline
57 & 0 & 5.7341 & -5.7341 \tabularnewline
58 & 8.5 & 6.16349 & 2.33651 \tabularnewline
59 & 3.5 & 5.02362 & -1.52362 \tabularnewline
60 & 7.5 & 6.30734 & 1.19266 \tabularnewline
61 & 3.5 & 7.22007 & -3.72007 \tabularnewline
62 & 6 & 5.35972 & 0.640276 \tabularnewline
63 & 1.5 & 6.14041 & -4.64041 \tabularnewline
64 & 9 & 6.91111 & 2.08889 \tabularnewline
65 & 3.5 & 6.01807 & -2.51807 \tabularnewline
66 & 3.5 & 5.65056 & -2.15056 \tabularnewline
67 & 4 & 6.94928 & -2.94928 \tabularnewline
68 & 6.5 & 8.10425 & -1.60425 \tabularnewline
69 & 7.5 & 5.71848 & 1.78152 \tabularnewline
70 & 6 & 5.97296 & 0.0270398 \tabularnewline
71 & 5 & 6.65178 & -1.65178 \tabularnewline
72 & 5.5 & 5.76785 & -0.267854 \tabularnewline
73 & 3.5 & 6.24609 & -2.74609 \tabularnewline
74 & 7.5 & 6.77178 & 0.728224 \tabularnewline
75 & 6.5 & 6.46229 & 0.0377062 \tabularnewline
76 & NA & NA & -0.255373 \tabularnewline
77 & 6.5 & 5.70608 & 0.793919 \tabularnewline
78 & 6.5 & 6.32261 & 0.177386 \tabularnewline
79 & 7 & 9.24816 & -2.24816 \tabularnewline
80 & 3.5 & 8.50307 & -5.00307 \tabularnewline
81 & 1.5 & 3.47504 & -1.97504 \tabularnewline
82 & 4 & 2.27046 & 1.72954 \tabularnewline
83 & 7.5 & 9.40937 & -1.90937 \tabularnewline
84 & 4.5 & 10.1425 & -5.64249 \tabularnewline
85 & 0 & 2.76604 & -2.76604 \tabularnewline
86 & 3.5 & 4.9361 & -1.4361 \tabularnewline
87 & 5.5 & 6.37952 & -0.87952 \tabularnewline
88 & 5 & 5.98232 & -0.982325 \tabularnewline
89 & 4.5 & 7.74374 & -3.24374 \tabularnewline
90 & 2.5 & 0.93218 & 1.56782 \tabularnewline
91 & 7.5 & 6.34785 & 1.15215 \tabularnewline
92 & 7 & 12.6713 & -5.67129 \tabularnewline
93 & 0 & 2.22787 & -2.22787 \tabularnewline
94 & 4.5 & 7.07655 & -2.57655 \tabularnewline
95 & 3 & 7.00931 & -4.00931 \tabularnewline
96 & 1.5 & 3.50332 & -2.00332 \tabularnewline
97 & 3.5 & 6.90077 & -3.40077 \tabularnewline
98 & 2.5 & 2.34316 & 0.156843 \tabularnewline
99 & 5.5 & 2.97686 & 2.52314 \tabularnewline
100 & 8 & 13.0379 & -5.03786 \tabularnewline
101 & 1 & 1.98181 & -0.981813 \tabularnewline
102 & 5 & 6.40702 & -1.40702 \tabularnewline
103 & 4.5 & 7.21181 & -2.71181 \tabularnewline
104 & 3 & 6.16557 & -3.16557 \tabularnewline
105 & 3 & 1.14119 & 1.85881 \tabularnewline
106 & 8 & 11.4735 & -3.47348 \tabularnewline
107 & 2.5 & 1.24139 & 1.25861 \tabularnewline
108 & 7 & 12.8759 & -5.87587 \tabularnewline
109 & 0 & 4.55451 & -4.55451 \tabularnewline
110 & 1 & 3.77359 & -2.77359 \tabularnewline
111 & 3.5 & 3.70348 & -0.203477 \tabularnewline
112 & 5.5 & 5.37613 & 0.123874 \tabularnewline
113 & 5.5 & 10.2233 & -4.72326 \tabularnewline
114 & 0.5 & -0.680683 & 1.18068 \tabularnewline
115 & 7.5 & 4.52744 & 2.97256 \tabularnewline
116 & 9 & 5.5264 & 3.4736 \tabularnewline
117 & 9.5 & 9.39743 & 0.102569 \tabularnewline
118 & 8.5 & 6.65159 & 1.84841 \tabularnewline
119 & 7 & 6.04611 & 0.953891 \tabularnewline
120 & 8 & 5.1884 & 2.8116 \tabularnewline
121 & 10 & 12.5475 & -2.54745 \tabularnewline
122 & 7 & 3.61862 & 3.38138 \tabularnewline
123 & 8.5 & 6.12636 & 2.37364 \tabularnewline
124 & 9 & 4.89175 & 4.10825 \tabularnewline
125 & 9.5 & 11.5405 & -2.04046 \tabularnewline
126 & 4 & 3.7053 & 0.2947 \tabularnewline
127 & 6 & 4.03057 & 1.96943 \tabularnewline
128 & 8 & 9.23803 & -1.23803 \tabularnewline
129 & 5.5 & 2.99605 & 2.50395 \tabularnewline
130 & 9.5 & 7.50852 & 1.99148 \tabularnewline
131 & 7.5 & 5.93868 & 1.56132 \tabularnewline
132 & 7 & 6.88596 & 0.114042 \tabularnewline
133 & 7.5 & 5.47036 & 2.02964 \tabularnewline
134 & 8 & 7.40312 & 0.596876 \tabularnewline
135 & 7 & 5.71467 & 1.28533 \tabularnewline
136 & 7 & 7.24453 & -0.244526 \tabularnewline
137 & 6 & 1.80239 & 4.19761 \tabularnewline
138 & 10 & 13.1594 & -3.15941 \tabularnewline
139 & 2.5 & 0.590795 & 1.9092 \tabularnewline
140 & 9 & 8.19908 & 0.800924 \tabularnewline
141 & 8 & 7.5828 & 0.417205 \tabularnewline
142 & 6 & 2.72602 & 3.27398 \tabularnewline
143 & 8.5 & 9.32392 & -0.823916 \tabularnewline
144 & 6 & 3.23307 & 2.76693 \tabularnewline
145 & 9 & 7.49292 & 1.50708 \tabularnewline
146 & 8 & 6.02564 & 1.97436 \tabularnewline
147 & 9 & 9.50202 & -0.502024 \tabularnewline
148 & 5.5 & 4.77073 & 0.729274 \tabularnewline
149 & 7 & 7.79797 & -0.797968 \tabularnewline
150 & 5.5 & 2.42203 & 3.07797 \tabularnewline
151 & 9 & 12.9893 & -3.98927 \tabularnewline
152 & 2 & 0.699858 & 1.30014 \tabularnewline
153 & 8.5 & 5.59234 & 2.90766 \tabularnewline
154 & 9 & 6.72109 & 2.27891 \tabularnewline
155 & 8.5 & 5.15004 & 3.34996 \tabularnewline
156 & 9 & 8.17469 & 0.82531 \tabularnewline
157 & 7.5 & 4.9519 & 2.5481 \tabularnewline
158 & 10 & 7.13677 & 2.86323 \tabularnewline
159 & 9 & 8.73283 & 0.267173 \tabularnewline
160 & 7.5 & 7.4465 & 0.0535001 \tabularnewline
161 & 6 & 2.69882 & 3.30118 \tabularnewline
162 & 10.5 & 8.20999 & 2.29001 \tabularnewline
163 & 8.5 & 7.31897 & 1.18103 \tabularnewline
164 & 8 & 3.60076 & 4.39924 \tabularnewline
165 & 10 & 6.75382 & 3.24618 \tabularnewline
166 & 10.5 & 9.35591 & 1.14409 \tabularnewline
167 & 6.5 & 3.9984 & 2.5016 \tabularnewline
168 & 9.5 & 6.11107 & 3.38893 \tabularnewline
169 & 8.5 & 7.17338 & 1.32662 \tabularnewline
170 & 7.5 & 9.20974 & -1.70974 \tabularnewline
171 & 5 & 3.40599 & 1.59401 \tabularnewline
172 & 8 & 4.50177 & 3.49823 \tabularnewline
173 & 10 & 9.56146 & 0.438538 \tabularnewline
174 & 7 & 5.2577 & 1.7423 \tabularnewline
175 & 7.5 & 5.7577 & 1.7423 \tabularnewline
176 & 7.5 & 4.63599 & 2.86401 \tabularnewline
177 & 9.5 & 10.1007 & -0.60068 \tabularnewline
178 & 6 & 2.22474 & 3.77526 \tabularnewline
179 & 10 & 9.4937 & 0.506299 \tabularnewline
180 & 7 & 9.48883 & -2.48883 \tabularnewline
181 & 3 & 4.43871 & -1.43871 \tabularnewline
182 & 6 & 5.10145 & 0.898547 \tabularnewline
183 & 7 & 3.82366 & 3.17634 \tabularnewline
184 & 10 & 9.63756 & 0.362445 \tabularnewline
185 & 7 & 9.29562 & -2.29562 \tabularnewline
186 & 3.5 & 2.13599 & 1.36401 \tabularnewline
187 & 8 & 3.53993 & 4.46007 \tabularnewline
188 & 10 & 10.5371 & -0.537076 \tabularnewline
189 & 5.5 & 4.37351 & 1.12649 \tabularnewline
190 & 6 & 5.58385 & 0.416155 \tabularnewline
191 & 6.5 & 5.71858 & 0.781422 \tabularnewline
192 & 6.5 & 4.66948 & 1.83052 \tabularnewline
193 & 8.5 & 10.15 & -1.65004 \tabularnewline
194 & 4 & 0.604057 & 3.39594 \tabularnewline
195 & 9.5 & 7.41353 & 2.08647 \tabularnewline
196 & 8 & 5.74687 & 2.25313 \tabularnewline
197 & 8.5 & 9.69178 & -1.19178 \tabularnewline
198 & 5.5 & 4.7427 & 0.757296 \tabularnewline
199 & 7 & 3.58097 & 3.41903 \tabularnewline
200 & 9 & 7.27047 & 1.72953 \tabularnewline
201 & 8 & 4.57412 & 3.42588 \tabularnewline
202 & 10 & 7.75051 & 2.24949 \tabularnewline
203 & 8 & 7.99656 & 0.0034435 \tabularnewline
204 & 6 & 4.10249 & 1.89751 \tabularnewline
205 & 8 & 8.33691 & -0.336908 \tabularnewline
206 & 5 & 1.58488 & 3.41512 \tabularnewline
207 & 9 & 10.6547 & -1.65473 \tabularnewline
208 & 4.5 & 1.62097 & 2.87903 \tabularnewline
209 & 8.5 & 6.39481 & 2.10519 \tabularnewline
210 & 9.5 & 7.7048 & 1.7952 \tabularnewline
211 & 8.5 & 7.05556 & 1.44444 \tabularnewline
212 & 7.5 & 5.69462 & 1.80538 \tabularnewline
213 & 7.5 & 9.33615 & -1.83615 \tabularnewline
214 & 5 & 3.71415 & 1.28585 \tabularnewline
215 & 7 & 6.08975 & 0.910246 \tabularnewline
216 & 8 & 8.43999 & -0.439991 \tabularnewline
217 & 5.5 & 3.27411 & 2.22589 \tabularnewline
218 & 8.5 & 4.92124 & 3.57876 \tabularnewline
219 & 9.5 & 8.61812 & 0.881884 \tabularnewline
220 & 7 & 5.50255 & 1.49745 \tabularnewline
221 & 8 & 5.42958 & 2.57042 \tabularnewline
222 & 8.5 & 10.8544 & -2.35436 \tabularnewline
223 & 3.5 & 2.24034 & 1.25966 \tabularnewline
224 & 6.5 & 5.20165 & 1.29835 \tabularnewline
225 & 6.5 & 2.48823 & 4.01177 \tabularnewline
226 & 10.5 & 7.61993 & 2.88007 \tabularnewline
227 & 8.5 & 5.93269 & 2.56731 \tabularnewline
228 & 8 & 3.8115 & 4.1885 \tabularnewline
229 & 10 & 7.4971 & 2.5029 \tabularnewline
230 & 10 & 6.69385 & 3.30615 \tabularnewline
231 & 9.5 & 6.02431 & 3.47569 \tabularnewline
232 & 9 & 6.62507 & 2.37493 \tabularnewline
233 & 10 & 8.21129 & 1.78871 \tabularnewline
234 & 7.5 & 8.624 & -1.124 \tabularnewline
235 & 4.5 & 5.54358 & -1.04358 \tabularnewline
236 & 4.5 & 9.45508 & -4.95508 \tabularnewline
237 & 0.5 & -0.710284 & 1.21028 \tabularnewline
238 & 6.5 & 8.29458 & -1.79458 \tabularnewline
239 & 4.5 & 5.31515 & -0.815152 \tabularnewline
240 & 5.5 & 6.2453 & -0.745299 \tabularnewline
241 & 5 & 5.50333 & -0.503334 \tabularnewline
242 & 6 & 8.18301 & -2.18301 \tabularnewline
243 & 4 & 1.84056 & 2.15944 \tabularnewline
244 & 8 & 4.75382 & 3.24618 \tabularnewline
245 & 10.5 & 9.44597 & 1.05403 \tabularnewline
246 & 6.5 & 5.00203 & 1.49797 \tabularnewline
247 & 8 & 6.72007 & 1.27993 \tabularnewline
248 & 8.5 & 8.60353 & -0.103527 \tabularnewline
249 & 5.5 & 5.33121 & 0.168794 \tabularnewline
250 & 7 & 7.56691 & -0.566913 \tabularnewline
251 & 5 & 6.76524 & -1.76524 \tabularnewline
252 & 3.5 & 5.10979 & -1.60979 \tabularnewline
253 & 5 & 2.50724 & 2.49276 \tabularnewline
254 & 9 & 7.37615 & 1.62385 \tabularnewline
255 & 8.5 & 9.49005 & -0.990047 \tabularnewline
256 & 5 & 2.26891 & 2.73109 \tabularnewline
257 & 9.5 & 12.1178 & -2.61785 \tabularnewline
258 & 3 & 7.17676 & -4.17676 \tabularnewline
259 & 1.5 & 2.10433 & -0.604326 \tabularnewline
260 & 6 & 11.6056 & -5.60562 \tabularnewline
261 & 0.5 & -0.644085 & 1.14409 \tabularnewline
262 & 6.5 & 5.01036 & 1.48964 \tabularnewline
263 & 7.5 & 8.84238 & -1.34238 \tabularnewline
264 & 4.5 & 2.34056 & 2.15944 \tabularnewline
265 & 8 & 5.20687 & 2.79313 \tabularnewline
266 & 9 & 7.61655 & 1.38345 \tabularnewline
267 & 7.5 & 4.64795 & 2.85205 \tabularnewline
268 & 8.5 & 7.33874 & 1.16126 \tabularnewline
269 & 7 & 3.56926 & 3.43074 \tabularnewline
270 & 9.5 & 8.85228 & 0.647722 \tabularnewline
271 & 6.5 & 2.37066 & 4.12934 \tabularnewline
272 & 9.5 & 9.04904 & 0.450955 \tabularnewline
273 & 6 & 4.64094 & 1.35906 \tabularnewline
274 & 8 & 5.36912 & 2.63088 \tabularnewline
275 & 9.5 & 8.00438 & 1.49562 \tabularnewline
276 & 8 & 5.80343 & 2.19657 \tabularnewline
277 & 8 & 5.43427 & 2.56573 \tabularnewline
278 & 9 & 9.3606 & -0.360601 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&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]7.05783[/C][C]0.442174[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]6.09677[/C][C]-0.0967665[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.86181[/C][C]0.638185[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]6.8561[/C][C]-5.8561[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]5.90025[/C][C]-4.90025[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]6.50662[/C][C]-1.00662[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]6.85584[/C][C]1.64416[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]7.36835[/C][C]-0.86835[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]7.32106[/C][C]-2.82106[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]6.15594[/C][C]-4.15594[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]6.38906[/C][C]-1.38906[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]6.88907[/C][C]-6.38907[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]5.80291[/C][C]-0.802906[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]7.38309[/C][C]-2.38309[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]5.4543[/C][C]-2.9543[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]5.84343[/C][C]-0.843426[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]6.98772[/C][C]-1.48772[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]5.96775[/C][C]-2.46775[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]6.19698[/C][C]-3.19698[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]6.30083[/C][C]-2.30083[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]5.49499[/C][C]-4.99499[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]5.62921[/C][C]0.870793[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]6.24157[/C][C]-1.74157[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]7.0809[/C][C]0.419099[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]6.59261[/C][C]-1.09261[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]7.23247[/C][C]-3.23247[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]7.45684[/C][C]0.0431568[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]6.20869[/C][C]0.791307[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]6.82496[/C][C]-2.82496[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]6.15958[/C][C]-0.659581[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]6.34109[/C][C]-3.84109[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]6.09234[/C][C]-0.59234[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]5.93244[/C][C]-2.43244[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]6.4898[/C][C]-3.9898[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]6.20531[/C][C]-1.70531[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]5.84186[/C][C]-1.34186[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]6.09364[/C][C]-1.59364[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]5.46748[/C][C]0.532516[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]6.42203[/C][C]-3.92203[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]6.5573[/C][C]-1.5573[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]5.83822[/C][C]-5.83822[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.0952[/C][C]-1.0952[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]6.58922[/C][C]-0.0892245[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.42282[/C][C]-1.42282[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]5.95145[/C][C]0.0485532[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]6.31688[/C][C]-1.81688[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]6.63625[/C][C]-1.13625[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]6.20921[/C][C]-5.20921[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]6.47115[/C][C]1.02885[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]5.24737[/C][C]0.752627[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]6.0363[/C][C]-1.0363[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]5.65681[/C][C]-4.65681[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.79536[/C][C]-0.795355[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.72707[/C][C]0.772927[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]6.29979[/C][C]0.70021[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]5.96984[/C][C]-1.46984[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.7341[/C][C]-5.7341[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]6.16349[/C][C]2.33651[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]5.02362[/C][C]-1.52362[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]6.30734[/C][C]1.19266[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]7.22007[/C][C]-3.72007[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]5.35972[/C][C]0.640276[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]6.14041[/C][C]-4.64041[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]6.91111[/C][C]2.08889[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]6.01807[/C][C]-2.51807[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]5.65056[/C][C]-2.15056[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]6.94928[/C][C]-2.94928[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]8.10425[/C][C]-1.60425[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]5.71848[/C][C]1.78152[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]5.97296[/C][C]0.0270398[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]6.65178[/C][C]-1.65178[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]5.76785[/C][C]-0.267854[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]6.24609[/C][C]-2.74609[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]6.77178[/C][C]0.728224[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]6.46229[/C][C]0.0377062[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-0.255373[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]5.70608[/C][C]0.793919[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]6.32261[/C][C]0.177386[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]9.24816[/C][C]-2.24816[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]8.50307[/C][C]-5.00307[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]3.47504[/C][C]-1.97504[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]2.27046[/C][C]1.72954[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]9.40937[/C][C]-1.90937[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]10.1425[/C][C]-5.64249[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]2.76604[/C][C]-2.76604[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]4.9361[/C][C]-1.4361[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]6.37952[/C][C]-0.87952[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]5.98232[/C][C]-0.982325[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]7.74374[/C][C]-3.24374[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]0.93218[/C][C]1.56782[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]6.34785[/C][C]1.15215[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]12.6713[/C][C]-5.67129[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]2.22787[/C][C]-2.22787[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]7.07655[/C][C]-2.57655[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]7.00931[/C][C]-4.00931[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]3.50332[/C][C]-2.00332[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]6.90077[/C][C]-3.40077[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]2.34316[/C][C]0.156843[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]2.97686[/C][C]2.52314[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]13.0379[/C][C]-5.03786[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]1.98181[/C][C]-0.981813[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]6.40702[/C][C]-1.40702[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]7.21181[/C][C]-2.71181[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]6.16557[/C][C]-3.16557[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]1.14119[/C][C]1.85881[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]11.4735[/C][C]-3.47348[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]1.24139[/C][C]1.25861[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]12.8759[/C][C]-5.87587[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]4.55451[/C][C]-4.55451[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]3.77359[/C][C]-2.77359[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]3.70348[/C][C]-0.203477[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]5.37613[/C][C]0.123874[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]10.2233[/C][C]-4.72326[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]-0.680683[/C][C]1.18068[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]4.52744[/C][C]2.97256[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]5.5264[/C][C]3.4736[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]9.39743[/C][C]0.102569[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]6.65159[/C][C]1.84841[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]6.04611[/C][C]0.953891[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]5.1884[/C][C]2.8116[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]12.5475[/C][C]-2.54745[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]3.61862[/C][C]3.38138[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]6.12636[/C][C]2.37364[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]4.89175[/C][C]4.10825[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]11.5405[/C][C]-2.04046[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]3.7053[/C][C]0.2947[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]4.03057[/C][C]1.96943[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]9.23803[/C][C]-1.23803[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]2.99605[/C][C]2.50395[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]7.50852[/C][C]1.99148[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]5.93868[/C][C]1.56132[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]6.88596[/C][C]0.114042[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.47036[/C][C]2.02964[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.40312[/C][C]0.596876[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]5.71467[/C][C]1.28533[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]7.24453[/C][C]-0.244526[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]1.80239[/C][C]4.19761[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]13.1594[/C][C]-3.15941[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]0.590795[/C][C]1.9092[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]8.19908[/C][C]0.800924[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]7.5828[/C][C]0.417205[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]2.72602[/C][C]3.27398[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]9.32392[/C][C]-0.823916[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]3.23307[/C][C]2.76693[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]7.49292[/C][C]1.50708[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]6.02564[/C][C]1.97436[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]9.50202[/C][C]-0.502024[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]4.77073[/C][C]0.729274[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]7.79797[/C][C]-0.797968[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]2.42203[/C][C]3.07797[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]12.9893[/C][C]-3.98927[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]0.699858[/C][C]1.30014[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]5.59234[/C][C]2.90766[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]6.72109[/C][C]2.27891[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]5.15004[/C][C]3.34996[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]8.17469[/C][C]0.82531[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]4.9519[/C][C]2.5481[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]7.13677[/C][C]2.86323[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]8.73283[/C][C]0.267173[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]7.4465[/C][C]0.0535001[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]2.69882[/C][C]3.30118[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.20999[/C][C]2.29001[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]7.31897[/C][C]1.18103[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]3.60076[/C][C]4.39924[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]6.75382[/C][C]3.24618[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]9.35591[/C][C]1.14409[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]3.9984[/C][C]2.5016[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]6.11107[/C][C]3.38893[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]7.17338[/C][C]1.32662[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]9.20974[/C][C]-1.70974[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]3.40599[/C][C]1.59401[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]4.50177[/C][C]3.49823[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]9.56146[/C][C]0.438538[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]5.2577[/C][C]1.7423[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]5.7577[/C][C]1.7423[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]4.63599[/C][C]2.86401[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]10.1007[/C][C]-0.60068[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]2.22474[/C][C]3.77526[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]9.4937[/C][C]0.506299[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]9.48883[/C][C]-2.48883[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]4.43871[/C][C]-1.43871[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]5.10145[/C][C]0.898547[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]3.82366[/C][C]3.17634[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]9.63756[/C][C]0.362445[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]9.29562[/C][C]-2.29562[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]2.13599[/C][C]1.36401[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]3.53993[/C][C]4.46007[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]10.5371[/C][C]-0.537076[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]4.37351[/C][C]1.12649[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]5.58385[/C][C]0.416155[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]5.71858[/C][C]0.781422[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]4.66948[/C][C]1.83052[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]10.15[/C][C]-1.65004[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]0.604057[/C][C]3.39594[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]7.41353[/C][C]2.08647[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]5.74687[/C][C]2.25313[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]9.69178[/C][C]-1.19178[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]4.7427[/C][C]0.757296[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]3.58097[/C][C]3.41903[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]7.27047[/C][C]1.72953[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]4.57412[/C][C]3.42588[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]7.75051[/C][C]2.24949[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]7.99656[/C][C]0.0034435[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]4.10249[/C][C]1.89751[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]8.33691[/C][C]-0.336908[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]1.58488[/C][C]3.41512[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]10.6547[/C][C]-1.65473[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]1.62097[/C][C]2.87903[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]6.39481[/C][C]2.10519[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.7048[/C][C]1.7952[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]7.05556[/C][C]1.44444[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]5.69462[/C][C]1.80538[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]9.33615[/C][C]-1.83615[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]3.71415[/C][C]1.28585[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]6.08975[/C][C]0.910246[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]8.43999[/C][C]-0.439991[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]3.27411[/C][C]2.22589[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]4.92124[/C][C]3.57876[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]8.61812[/C][C]0.881884[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]5.50255[/C][C]1.49745[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]5.42958[/C][C]2.57042[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]10.8544[/C][C]-2.35436[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]2.24034[/C][C]1.25966[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]5.20165[/C][C]1.29835[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]2.48823[/C][C]4.01177[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]7.61993[/C][C]2.88007[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]5.93269[/C][C]2.56731[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]3.8115[/C][C]4.1885[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]7.4971[/C][C]2.5029[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]6.69385[/C][C]3.30615[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]6.02431[/C][C]3.47569[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]6.62507[/C][C]2.37493[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]8.21129[/C][C]1.78871[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]8.624[/C][C]-1.124[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.54358[/C][C]-1.04358[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]9.45508[/C][C]-4.95508[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]-0.710284[/C][C]1.21028[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]8.29458[/C][C]-1.79458[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]5.31515[/C][C]-0.815152[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.2453[/C][C]-0.745299[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]5.50333[/C][C]-0.503334[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]8.18301[/C][C]-2.18301[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]1.84056[/C][C]2.15944[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]4.75382[/C][C]3.24618[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]9.44597[/C][C]1.05403[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]5.00203[/C][C]1.49797[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]6.72007[/C][C]1.27993[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]8.60353[/C][C]-0.103527[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]5.33121[/C][C]0.168794[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]7.56691[/C][C]-0.566913[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]6.76524[/C][C]-1.76524[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]5.10979[/C][C]-1.60979[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]2.50724[/C][C]2.49276[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]7.37615[/C][C]1.62385[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]9.49005[/C][C]-0.990047[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]2.26891[/C][C]2.73109[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]12.1178[/C][C]-2.61785[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]7.17676[/C][C]-4.17676[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]2.10433[/C][C]-0.604326[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]11.6056[/C][C]-5.60562[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]-0.644085[/C][C]1.14409[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]5.01036[/C][C]1.48964[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]8.84238[/C][C]-1.34238[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]2.34056[/C][C]2.15944[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]5.20687[/C][C]2.79313[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]7.61655[/C][C]1.38345[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]4.64795[/C][C]2.85205[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]7.33874[/C][C]1.16126[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]3.56926[/C][C]3.43074[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]8.85228[/C][C]0.647722[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]2.37066[/C][C]4.12934[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]9.04904[/C][C]0.450955[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]4.64094[/C][C]1.35906[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]5.36912[/C][C]2.63088[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]8.00438[/C][C]1.49562[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]5.80343[/C][C]2.19657[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]5.43427[/C][C]2.56573[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]9.3606[/C][C]-0.360601[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&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
17.57.057830.442174
266.09677-0.0967665
36.55.861810.638185
416.8561-5.8561
515.90025-4.90025
65.56.50662-1.00662
78.56.855841.64416
86.57.36835-0.86835
94.57.32106-2.82106
1026.15594-4.15594
1156.38906-1.38906
120.56.88907-6.38907
1355.80291-0.802906
1457.38309-2.38309
152.55.4543-2.9543
1655.84343-0.843426
175.56.98772-1.48772
183.55.96775-2.46775
1936.19698-3.19698
2046.30083-2.30083
210.55.49499-4.99499
226.55.629210.870793
234.56.24157-1.74157
247.57.08090.419099
255.56.59261-1.09261
2647.23247-3.23247
277.57.456840.0431568
2876.208690.791307
2946.82496-2.82496
305.56.15958-0.659581
312.56.34109-3.84109
325.56.09234-0.59234
333.55.93244-2.43244
342.56.4898-3.9898
354.56.20531-1.70531
364.55.84186-1.34186
374.56.09364-1.59364
3865.467480.532516
392.56.42203-3.92203
4056.5573-1.5573
4105.83822-5.83822
4256.0952-1.0952
436.56.58922-0.0892245
4456.42282-1.42282
4565.951450.0485532
464.56.31688-1.81688
475.56.63625-1.13625
4816.20921-5.20921
497.56.471151.02885
5065.247370.752627
5156.0363-1.0363
5215.65681-4.65681
5355.79536-0.795355
546.55.727070.772927
5576.299790.70021
564.55.96984-1.46984
5705.7341-5.7341
588.56.163492.33651
593.55.02362-1.52362
607.56.307341.19266
613.57.22007-3.72007
6265.359720.640276
631.56.14041-4.64041
6496.911112.08889
653.56.01807-2.51807
663.55.65056-2.15056
6746.94928-2.94928
686.58.10425-1.60425
697.55.718481.78152
7065.972960.0270398
7156.65178-1.65178
725.55.76785-0.267854
733.56.24609-2.74609
747.56.771780.728224
756.56.462290.0377062
76NANA-0.255373
776.55.706080.793919
786.56.322610.177386
7979.24816-2.24816
803.58.50307-5.00307
811.53.47504-1.97504
8242.270461.72954
837.59.40937-1.90937
844.510.1425-5.64249
8502.76604-2.76604
863.54.9361-1.4361
875.56.37952-0.87952
8855.98232-0.982325
894.57.74374-3.24374
902.50.932181.56782
917.56.347851.15215
92712.6713-5.67129
9302.22787-2.22787
944.57.07655-2.57655
9537.00931-4.00931
961.53.50332-2.00332
973.56.90077-3.40077
982.52.343160.156843
995.52.976862.52314
100813.0379-5.03786
10111.98181-0.981813
10256.40702-1.40702
1034.57.21181-2.71181
10436.16557-3.16557
10531.141191.85881
106811.4735-3.47348
1072.51.241391.25861
108712.8759-5.87587
10904.55451-4.55451
11013.77359-2.77359
1113.53.70348-0.203477
1125.55.376130.123874
1135.510.2233-4.72326
1140.5-0.6806831.18068
1157.54.527442.97256
11695.52643.4736
1179.59.397430.102569
1188.56.651591.84841
11976.046110.953891
12085.18842.8116
1211012.5475-2.54745
12273.618623.38138
1238.56.126362.37364
12494.891754.10825
1259.511.5405-2.04046
12643.70530.2947
12764.030571.96943
12889.23803-1.23803
1295.52.996052.50395
1309.57.508521.99148
1317.55.938681.56132
13276.885960.114042
1337.55.470362.02964
13487.403120.596876
13575.714671.28533
13677.24453-0.244526
13761.802394.19761
1381013.1594-3.15941
1392.50.5907951.9092
14098.199080.800924
14187.58280.417205
14262.726023.27398
1438.59.32392-0.823916
14463.233072.76693
14597.492921.50708
14686.025641.97436
14799.50202-0.502024
1485.54.770730.729274
14977.79797-0.797968
1505.52.422033.07797
151912.9893-3.98927
15220.6998581.30014
1538.55.592342.90766
15496.721092.27891
1558.55.150043.34996
15698.174690.82531
1577.54.95192.5481
158107.136772.86323
15998.732830.267173
1607.57.44650.0535001
16162.698823.30118
16210.58.209992.29001
1638.57.318971.18103
16483.600764.39924
165106.753823.24618
16610.59.355911.14409
1676.53.99842.5016
1689.56.111073.38893
1698.57.173381.32662
1707.59.20974-1.70974
17153.405991.59401
17284.501773.49823
173109.561460.438538
17475.25771.7423
1757.55.75771.7423
1767.54.635992.86401
1779.510.1007-0.60068
17862.224743.77526
179109.49370.506299
18079.48883-2.48883
18134.43871-1.43871
18265.101450.898547
18373.823663.17634
184109.637560.362445
18579.29562-2.29562
1863.52.135991.36401
18783.539934.46007
1881010.5371-0.537076
1895.54.373511.12649
19065.583850.416155
1916.55.718580.781422
1926.54.669481.83052
1938.510.15-1.65004
19440.6040573.39594
1959.57.413532.08647
19685.746872.25313
1978.59.69178-1.19178
1985.54.74270.757296
19973.580973.41903
20097.270471.72953
20184.574123.42588
202107.750512.24949
20387.996560.0034435
20464.102491.89751
20588.33691-0.336908
20651.584883.41512
207910.6547-1.65473
2084.51.620972.87903
2098.56.394812.10519
2109.57.70481.7952
2118.57.055561.44444
2127.55.694621.80538
2137.59.33615-1.83615
21453.714151.28585
21576.089750.910246
21688.43999-0.439991
2175.53.274112.22589
2188.54.921243.57876
2199.58.618120.881884
22075.502551.49745
22185.429582.57042
2228.510.8544-2.35436
2233.52.240341.25966
2246.55.201651.29835
2256.52.488234.01177
22610.57.619932.88007
2278.55.932692.56731
22883.81154.1885
229107.49712.5029
230106.693853.30615
2319.56.024313.47569
23296.625072.37493
233108.211291.78871
2347.58.624-1.124
2354.55.54358-1.04358
2364.59.45508-4.95508
2370.5-0.7102841.21028
2386.58.29458-1.79458
2394.55.31515-0.815152
2405.56.2453-0.745299
24155.50333-0.503334
24268.18301-2.18301
24341.840562.15944
24484.753823.24618
24510.59.445971.05403
2466.55.002031.49797
24786.720071.27993
2488.58.60353-0.103527
2495.55.331210.168794
25077.56691-0.566913
25156.76524-1.76524
2523.55.10979-1.60979
25352.507242.49276
25497.376151.62385
2558.59.49005-0.990047
25652.268912.73109
2579.512.1178-2.61785
25837.17676-4.17676
2591.52.10433-0.604326
260611.6056-5.60562
2610.5-0.6440851.14409
2626.55.010361.48964
2637.58.84238-1.34238
2644.52.340562.15944
26585.206872.79313
26697.616551.38345
2677.54.647952.85205
2688.57.338741.16126
26973.569263.43074
2709.58.852280.647722
2716.52.370664.12934
2729.59.049040.450955
27364.640941.35906
27485.369122.63088
2759.58.004381.49562
27685.803432.19657
27785.434272.56573
27899.3606-0.360601
2795NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.9091650.181670.0908352
70.9151570.1696860.0848432
80.8547960.2904070.145204
90.810730.3785390.18927
100.8025540.3948930.197446
110.7253140.5493720.274686
120.8629850.2740290.137015
130.8150690.3698620.184931
140.7547950.4904110.245205
150.7038620.5922770.296138
160.6445020.7109970.355498
170.5736410.8527180.426359
180.5048760.9902470.495124
190.4550360.9100720.544964
200.3875970.7751930.612403
210.4196250.839250.580375
220.4689150.9378290.531085
230.4073690.8147390.592631
240.4001650.800330.599835
250.3463960.6927910.653604
260.3215720.6431450.678428
270.2939250.587850.706075
280.2959320.5918650.704068
290.2642110.5284230.735789
300.2310510.4621010.768949
310.2366990.4733980.763301
320.2079170.4158340.792083
330.1757890.3515770.824211
340.1816960.3633920.818304
350.1492610.2985220.850739
360.1217660.2435320.878234
370.09873870.1974770.901261
380.10080.20160.8992
390.1053320.2106650.894668
400.08563440.1712690.914366
410.1571820.3143630.842818
420.1339530.2679070.866047
430.1238490.2476980.876151
440.103420.206840.89658
450.09409140.1881830.905909
460.07863730.1572750.921363
470.06368520.127370.936315
480.099910.199820.90009
490.109630.219260.89037
500.1121560.2243120.887844
510.09394580.1878920.906054
520.1209330.2418660.879067
530.104470.2089390.89553
540.1063680.2127370.893632
550.1074760.2149520.892524
560.09034150.1806830.909658
570.1613470.3226940.838653
580.2168990.4337980.783101
590.1888330.3776660.811167
600.1998480.3996960.800152
610.212680.425360.78732
620.2053690.4107390.794631
630.2491940.4983880.750806
640.2911440.5822880.708856
650.2828490.5656980.717151
660.256570.513140.74343
670.2565720.5131450.743428
680.238690.4773790.76131
690.2541590.5083180.745841
700.2375190.4750380.762481
710.2193080.4386160.780692
720.1984410.3968830.801559
730.1845920.3691830.815408
740.1888740.3777490.811126
750.1748360.3496720.825164
760.1593530.3187050.840647
770.1548810.3097610.845119
780.1440370.2880750.855963
790.1300760.2601530.869924
800.1830160.3660330.816984
810.1662680.3325360.833732
820.1813590.3627170.818641
830.1637510.3275020.836249
840.2647460.5294920.735254
850.2638360.5276720.736164
860.2427150.4854310.757285
870.2200560.4401110.779944
880.1975230.3950460.802477
890.2039210.4078410.796079
900.2144340.4288680.785566
910.2217160.4434320.778284
920.3562740.7125480.643726
930.3492280.6984560.650772
940.3441680.6883350.655832
950.3927750.7855490.607225
960.3824150.7648290.617585
970.4163780.8327570.583622
980.3984990.7969990.601501
990.455730.911460.54427
1000.576170.847660.42383
1010.5499920.9000170.450008
1020.5295030.9409940.470497
1030.5334960.9330080.466504
1040.5673930.8652130.432607
1050.5978790.8042430.402121
1060.6363330.7273340.363667
1070.6398410.7203190.360159
1080.8020460.3959090.197954
1090.8558550.288290.144145
1100.8653610.2692790.134639
1110.8550740.2898530.144926
1120.8444090.3111820.155591
1130.901220.197560.0987801
1140.9082110.1835780.0917891
1150.9291810.1416370.0708185
1160.9510540.09789230.0489461
1170.9474840.1050320.0525158
1180.9520550.09588910.0479446
1190.9487670.1024660.0512328
1200.9589680.08206350.0410318
1210.9628740.0742520.037126
1220.9771170.04576690.0228835
1230.9796360.04072880.0203644
1240.9914790.01704190.00852094
1250.9917620.01647570.00823786
1260.9903560.01928790.00964394
1270.9904380.01912470.00956236
1280.9895940.02081170.0104058
1290.9910470.01790650.00895323
1300.9912130.01757470.00878737
1310.990530.01893910.00946957
1320.9894480.02110350.0105517
1330.9895570.02088670.0104433
1340.9879120.02417650.0120883
1350.9867840.02643140.0132157
1360.9843730.03125470.0156274
1370.9911920.01761510.00880753
1380.9927690.01446220.00723108
1390.9925240.0149520.007476
1400.9913990.01720150.00860074
1410.9896690.02066140.0103307
1420.9912510.01749790.00874897
1430.9907380.01852320.00926161
1440.9916860.01662770.00831383
1450.9906350.01873080.0093654
1460.9901310.01973810.00986907
1470.9886170.02276560.0113828
1480.9865830.02683460.0134173
1490.9853390.02932290.0146615
1500.9864020.02719640.0135982
1510.9949290.01014260.0050713
1520.9942130.0115740.00578698
1530.9945090.01098190.00549095
1540.9940180.01196480.00598238
1550.9957640.008472550.00423628
1560.9948950.01020930.00510463
1570.9947390.01052260.00526132
1580.9951750.009650060.00482503
1590.9941950.01161050.00580527
1600.9928130.01437390.00718696
1610.9939390.01212240.00606122
1620.9938040.01239260.00619629
1630.9925790.01484120.00742058
1640.9972190.005561870.00278094
1650.9973680.005263040.00263152
1660.9968410.00631710.00315855
1670.9966540.006692970.00334648
1680.9974340.005131710.00256585
1690.9968350.006330130.00316507
1700.9968080.0063850.0031925
1710.9961680.007664220.00383211
1720.9968550.00628990.00314495
1730.9961090.0077820.003891
1740.9953110.00937710.00468855
1750.9943450.01130960.0056548
1760.994450.01109990.00554997
1770.9936340.01273290.00636643
1780.9946030.01079320.00539661
1790.9933480.0133040.00665198
1800.9937680.01246370.00623187
1810.9937930.01241360.00620679
1820.9921840.0156320.00781598
1830.9921460.0157090.00785449
1840.9901940.01961250.00980626
1850.9927960.01440720.00720361
1860.9910720.01785520.00892762
1870.9948460.01030740.00515369
1880.993940.01212060.0060603
1890.9923560.01528740.00764368
1900.9901950.01960970.00980485
1910.9876730.02465310.0123266
1920.9853230.02935440.0146772
1930.9844530.03109320.0155466
1940.9861350.02773060.0138653
1950.9846590.03068110.0153405
1960.9834510.0330990.0165495
1970.9846460.03070860.0153543
1980.9806640.03867250.0193362
1990.9845950.0308110.0154055
2000.9814160.0371670.0185835
2010.9800330.03993440.0199672
2020.9792040.04159140.0207957
2030.9753370.04932680.0246634
2040.9708730.05825440.0291272
2050.9654030.0691940.034597
2060.9734190.05316240.0265812
2070.9704230.05915490.0295775
2080.9748550.05029020.0251451
2090.9697790.0604410.0302205
2100.9639290.07214180.0360709
2110.9594610.08107770.0405388
2120.951220.09755980.0487799
2130.9566020.08679520.0433976
2140.9485850.102830.0514152
2150.9401170.1197660.0598829
2160.9297540.1404920.0702459
2170.922080.155840.0779202
2180.9207180.1585630.0792816
2190.90550.1890.0944999
2200.8878660.2242680.112134
2210.8764220.2471560.123578
2220.8756260.2487480.124374
2230.8552780.2894450.144722
2240.8317290.3365420.168271
2250.8405230.3189540.159477
2260.8561310.2877390.143869
2270.850650.2987010.14935
2280.8974410.2051170.102559
2290.8808420.2383160.119158
2300.8825950.234810.117405
2310.9008670.1982660.0991331
2320.8821080.2357840.117892
2330.8717370.2565250.128263
2340.8540980.2918040.145902
2350.8291340.3417310.170866
2360.9125430.1749130.0874566
2370.8987050.202590.101295
2380.9061240.1877530.0938764
2390.890560.2188810.10944
2400.8688840.2622320.131116
2410.8511460.2977070.148854
2420.8660310.2679380.133969
2430.851960.296080.14804
2440.8373130.3253740.162687
2450.8063770.3872470.193623
2460.7680460.4639080.231954
2470.7236770.5526470.276323
2480.6732440.6535120.326756
2490.6319240.7361510.368076
2500.5802270.8395460.419773
2510.5646860.8706280.435314
2520.579240.841520.42076
2530.5368870.9262250.463113
2540.4754320.9508630.524568
2550.4907520.9815030.509248
2560.4471460.8942930.552854
2570.4713360.9426710.528664
2580.7378940.5242120.262106
2590.7125750.574850.287425
2600.9993170.001366360.000683178
2610.9986880.002624470.00131223
2620.9971580.00568330.00284165
2630.999910.0001806369.03181e-05
2640.9997350.0005301920.000265096
2650.9994320.001135940.000567968
2660.9987150.002569330.00128467
2670.9991960.00160770.000803848
2680.9994560.001087920.000543962
2690.9985550.002889780.00144489
2700.9950290.009941080.00497054
2710.9985920.002816060.00140803
2720.9926770.01464590.00732297
2730.962290.07541950.0377098

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.909165 & 0.18167 & 0.0908352 \tabularnewline
7 & 0.915157 & 0.169686 & 0.0848432 \tabularnewline
8 & 0.854796 & 0.290407 & 0.145204 \tabularnewline
9 & 0.81073 & 0.378539 & 0.18927 \tabularnewline
10 & 0.802554 & 0.394893 & 0.197446 \tabularnewline
11 & 0.725314 & 0.549372 & 0.274686 \tabularnewline
12 & 0.862985 & 0.274029 & 0.137015 \tabularnewline
13 & 0.815069 & 0.369862 & 0.184931 \tabularnewline
14 & 0.754795 & 0.490411 & 0.245205 \tabularnewline
15 & 0.703862 & 0.592277 & 0.296138 \tabularnewline
16 & 0.644502 & 0.710997 & 0.355498 \tabularnewline
17 & 0.573641 & 0.852718 & 0.426359 \tabularnewline
18 & 0.504876 & 0.990247 & 0.495124 \tabularnewline
19 & 0.455036 & 0.910072 & 0.544964 \tabularnewline
20 & 0.387597 & 0.775193 & 0.612403 \tabularnewline
21 & 0.419625 & 0.83925 & 0.580375 \tabularnewline
22 & 0.468915 & 0.937829 & 0.531085 \tabularnewline
23 & 0.407369 & 0.814739 & 0.592631 \tabularnewline
24 & 0.400165 & 0.80033 & 0.599835 \tabularnewline
25 & 0.346396 & 0.692791 & 0.653604 \tabularnewline
26 & 0.321572 & 0.643145 & 0.678428 \tabularnewline
27 & 0.293925 & 0.58785 & 0.706075 \tabularnewline
28 & 0.295932 & 0.591865 & 0.704068 \tabularnewline
29 & 0.264211 & 0.528423 & 0.735789 \tabularnewline
30 & 0.231051 & 0.462101 & 0.768949 \tabularnewline
31 & 0.236699 & 0.473398 & 0.763301 \tabularnewline
32 & 0.207917 & 0.415834 & 0.792083 \tabularnewline
33 & 0.175789 & 0.351577 & 0.824211 \tabularnewline
34 & 0.181696 & 0.363392 & 0.818304 \tabularnewline
35 & 0.149261 & 0.298522 & 0.850739 \tabularnewline
36 & 0.121766 & 0.243532 & 0.878234 \tabularnewline
37 & 0.0987387 & 0.197477 & 0.901261 \tabularnewline
38 & 0.1008 & 0.2016 & 0.8992 \tabularnewline
39 & 0.105332 & 0.210665 & 0.894668 \tabularnewline
40 & 0.0856344 & 0.171269 & 0.914366 \tabularnewline
41 & 0.157182 & 0.314363 & 0.842818 \tabularnewline
42 & 0.133953 & 0.267907 & 0.866047 \tabularnewline
43 & 0.123849 & 0.247698 & 0.876151 \tabularnewline
44 & 0.10342 & 0.20684 & 0.89658 \tabularnewline
45 & 0.0940914 & 0.188183 & 0.905909 \tabularnewline
46 & 0.0786373 & 0.157275 & 0.921363 \tabularnewline
47 & 0.0636852 & 0.12737 & 0.936315 \tabularnewline
48 & 0.09991 & 0.19982 & 0.90009 \tabularnewline
49 & 0.10963 & 0.21926 & 0.89037 \tabularnewline
50 & 0.112156 & 0.224312 & 0.887844 \tabularnewline
51 & 0.0939458 & 0.187892 & 0.906054 \tabularnewline
52 & 0.120933 & 0.241866 & 0.879067 \tabularnewline
53 & 0.10447 & 0.208939 & 0.89553 \tabularnewline
54 & 0.106368 & 0.212737 & 0.893632 \tabularnewline
55 & 0.107476 & 0.214952 & 0.892524 \tabularnewline
56 & 0.0903415 & 0.180683 & 0.909658 \tabularnewline
57 & 0.161347 & 0.322694 & 0.838653 \tabularnewline
58 & 0.216899 & 0.433798 & 0.783101 \tabularnewline
59 & 0.188833 & 0.377666 & 0.811167 \tabularnewline
60 & 0.199848 & 0.399696 & 0.800152 \tabularnewline
61 & 0.21268 & 0.42536 & 0.78732 \tabularnewline
62 & 0.205369 & 0.410739 & 0.794631 \tabularnewline
63 & 0.249194 & 0.498388 & 0.750806 \tabularnewline
64 & 0.291144 & 0.582288 & 0.708856 \tabularnewline
65 & 0.282849 & 0.565698 & 0.717151 \tabularnewline
66 & 0.25657 & 0.51314 & 0.74343 \tabularnewline
67 & 0.256572 & 0.513145 & 0.743428 \tabularnewline
68 & 0.23869 & 0.477379 & 0.76131 \tabularnewline
69 & 0.254159 & 0.508318 & 0.745841 \tabularnewline
70 & 0.237519 & 0.475038 & 0.762481 \tabularnewline
71 & 0.219308 & 0.438616 & 0.780692 \tabularnewline
72 & 0.198441 & 0.396883 & 0.801559 \tabularnewline
73 & 0.184592 & 0.369183 & 0.815408 \tabularnewline
74 & 0.188874 & 0.377749 & 0.811126 \tabularnewline
75 & 0.174836 & 0.349672 & 0.825164 \tabularnewline
76 & 0.159353 & 0.318705 & 0.840647 \tabularnewline
77 & 0.154881 & 0.309761 & 0.845119 \tabularnewline
78 & 0.144037 & 0.288075 & 0.855963 \tabularnewline
79 & 0.130076 & 0.260153 & 0.869924 \tabularnewline
80 & 0.183016 & 0.366033 & 0.816984 \tabularnewline
81 & 0.166268 & 0.332536 & 0.833732 \tabularnewline
82 & 0.181359 & 0.362717 & 0.818641 \tabularnewline
83 & 0.163751 & 0.327502 & 0.836249 \tabularnewline
84 & 0.264746 & 0.529492 & 0.735254 \tabularnewline
85 & 0.263836 & 0.527672 & 0.736164 \tabularnewline
86 & 0.242715 & 0.485431 & 0.757285 \tabularnewline
87 & 0.220056 & 0.440111 & 0.779944 \tabularnewline
88 & 0.197523 & 0.395046 & 0.802477 \tabularnewline
89 & 0.203921 & 0.407841 & 0.796079 \tabularnewline
90 & 0.214434 & 0.428868 & 0.785566 \tabularnewline
91 & 0.221716 & 0.443432 & 0.778284 \tabularnewline
92 & 0.356274 & 0.712548 & 0.643726 \tabularnewline
93 & 0.349228 & 0.698456 & 0.650772 \tabularnewline
94 & 0.344168 & 0.688335 & 0.655832 \tabularnewline
95 & 0.392775 & 0.785549 & 0.607225 \tabularnewline
96 & 0.382415 & 0.764829 & 0.617585 \tabularnewline
97 & 0.416378 & 0.832757 & 0.583622 \tabularnewline
98 & 0.398499 & 0.796999 & 0.601501 \tabularnewline
99 & 0.45573 & 0.91146 & 0.54427 \tabularnewline
100 & 0.57617 & 0.84766 & 0.42383 \tabularnewline
101 & 0.549992 & 0.900017 & 0.450008 \tabularnewline
102 & 0.529503 & 0.940994 & 0.470497 \tabularnewline
103 & 0.533496 & 0.933008 & 0.466504 \tabularnewline
104 & 0.567393 & 0.865213 & 0.432607 \tabularnewline
105 & 0.597879 & 0.804243 & 0.402121 \tabularnewline
106 & 0.636333 & 0.727334 & 0.363667 \tabularnewline
107 & 0.639841 & 0.720319 & 0.360159 \tabularnewline
108 & 0.802046 & 0.395909 & 0.197954 \tabularnewline
109 & 0.855855 & 0.28829 & 0.144145 \tabularnewline
110 & 0.865361 & 0.269279 & 0.134639 \tabularnewline
111 & 0.855074 & 0.289853 & 0.144926 \tabularnewline
112 & 0.844409 & 0.311182 & 0.155591 \tabularnewline
113 & 0.90122 & 0.19756 & 0.0987801 \tabularnewline
114 & 0.908211 & 0.183578 & 0.0917891 \tabularnewline
115 & 0.929181 & 0.141637 & 0.0708185 \tabularnewline
116 & 0.951054 & 0.0978923 & 0.0489461 \tabularnewline
117 & 0.947484 & 0.105032 & 0.0525158 \tabularnewline
118 & 0.952055 & 0.0958891 & 0.0479446 \tabularnewline
119 & 0.948767 & 0.102466 & 0.0512328 \tabularnewline
120 & 0.958968 & 0.0820635 & 0.0410318 \tabularnewline
121 & 0.962874 & 0.074252 & 0.037126 \tabularnewline
122 & 0.977117 & 0.0457669 & 0.0228835 \tabularnewline
123 & 0.979636 & 0.0407288 & 0.0203644 \tabularnewline
124 & 0.991479 & 0.0170419 & 0.00852094 \tabularnewline
125 & 0.991762 & 0.0164757 & 0.00823786 \tabularnewline
126 & 0.990356 & 0.0192879 & 0.00964394 \tabularnewline
127 & 0.990438 & 0.0191247 & 0.00956236 \tabularnewline
128 & 0.989594 & 0.0208117 & 0.0104058 \tabularnewline
129 & 0.991047 & 0.0179065 & 0.00895323 \tabularnewline
130 & 0.991213 & 0.0175747 & 0.00878737 \tabularnewline
131 & 0.99053 & 0.0189391 & 0.00946957 \tabularnewline
132 & 0.989448 & 0.0211035 & 0.0105517 \tabularnewline
133 & 0.989557 & 0.0208867 & 0.0104433 \tabularnewline
134 & 0.987912 & 0.0241765 & 0.0120883 \tabularnewline
135 & 0.986784 & 0.0264314 & 0.0132157 \tabularnewline
136 & 0.984373 & 0.0312547 & 0.0156274 \tabularnewline
137 & 0.991192 & 0.0176151 & 0.00880753 \tabularnewline
138 & 0.992769 & 0.0144622 & 0.00723108 \tabularnewline
139 & 0.992524 & 0.014952 & 0.007476 \tabularnewline
140 & 0.991399 & 0.0172015 & 0.00860074 \tabularnewline
141 & 0.989669 & 0.0206614 & 0.0103307 \tabularnewline
142 & 0.991251 & 0.0174979 & 0.00874897 \tabularnewline
143 & 0.990738 & 0.0185232 & 0.00926161 \tabularnewline
144 & 0.991686 & 0.0166277 & 0.00831383 \tabularnewline
145 & 0.990635 & 0.0187308 & 0.0093654 \tabularnewline
146 & 0.990131 & 0.0197381 & 0.00986907 \tabularnewline
147 & 0.988617 & 0.0227656 & 0.0113828 \tabularnewline
148 & 0.986583 & 0.0268346 & 0.0134173 \tabularnewline
149 & 0.985339 & 0.0293229 & 0.0146615 \tabularnewline
150 & 0.986402 & 0.0271964 & 0.0135982 \tabularnewline
151 & 0.994929 & 0.0101426 & 0.0050713 \tabularnewline
152 & 0.994213 & 0.011574 & 0.00578698 \tabularnewline
153 & 0.994509 & 0.0109819 & 0.00549095 \tabularnewline
154 & 0.994018 & 0.0119648 & 0.00598238 \tabularnewline
155 & 0.995764 & 0.00847255 & 0.00423628 \tabularnewline
156 & 0.994895 & 0.0102093 & 0.00510463 \tabularnewline
157 & 0.994739 & 0.0105226 & 0.00526132 \tabularnewline
158 & 0.995175 & 0.00965006 & 0.00482503 \tabularnewline
159 & 0.994195 & 0.0116105 & 0.00580527 \tabularnewline
160 & 0.992813 & 0.0143739 & 0.00718696 \tabularnewline
161 & 0.993939 & 0.0121224 & 0.00606122 \tabularnewline
162 & 0.993804 & 0.0123926 & 0.00619629 \tabularnewline
163 & 0.992579 & 0.0148412 & 0.00742058 \tabularnewline
164 & 0.997219 & 0.00556187 & 0.00278094 \tabularnewline
165 & 0.997368 & 0.00526304 & 0.00263152 \tabularnewline
166 & 0.996841 & 0.0063171 & 0.00315855 \tabularnewline
167 & 0.996654 & 0.00669297 & 0.00334648 \tabularnewline
168 & 0.997434 & 0.00513171 & 0.00256585 \tabularnewline
169 & 0.996835 & 0.00633013 & 0.00316507 \tabularnewline
170 & 0.996808 & 0.006385 & 0.0031925 \tabularnewline
171 & 0.996168 & 0.00766422 & 0.00383211 \tabularnewline
172 & 0.996855 & 0.0062899 & 0.00314495 \tabularnewline
173 & 0.996109 & 0.007782 & 0.003891 \tabularnewline
174 & 0.995311 & 0.0093771 & 0.00468855 \tabularnewline
175 & 0.994345 & 0.0113096 & 0.0056548 \tabularnewline
176 & 0.99445 & 0.0110999 & 0.00554997 \tabularnewline
177 & 0.993634 & 0.0127329 & 0.00636643 \tabularnewline
178 & 0.994603 & 0.0107932 & 0.00539661 \tabularnewline
179 & 0.993348 & 0.013304 & 0.00665198 \tabularnewline
180 & 0.993768 & 0.0124637 & 0.00623187 \tabularnewline
181 & 0.993793 & 0.0124136 & 0.00620679 \tabularnewline
182 & 0.992184 & 0.015632 & 0.00781598 \tabularnewline
183 & 0.992146 & 0.015709 & 0.00785449 \tabularnewline
184 & 0.990194 & 0.0196125 & 0.00980626 \tabularnewline
185 & 0.992796 & 0.0144072 & 0.00720361 \tabularnewline
186 & 0.991072 & 0.0178552 & 0.00892762 \tabularnewline
187 & 0.994846 & 0.0103074 & 0.00515369 \tabularnewline
188 & 0.99394 & 0.0121206 & 0.0060603 \tabularnewline
189 & 0.992356 & 0.0152874 & 0.00764368 \tabularnewline
190 & 0.990195 & 0.0196097 & 0.00980485 \tabularnewline
191 & 0.987673 & 0.0246531 & 0.0123266 \tabularnewline
192 & 0.985323 & 0.0293544 & 0.0146772 \tabularnewline
193 & 0.984453 & 0.0310932 & 0.0155466 \tabularnewline
194 & 0.986135 & 0.0277306 & 0.0138653 \tabularnewline
195 & 0.984659 & 0.0306811 & 0.0153405 \tabularnewline
196 & 0.983451 & 0.033099 & 0.0165495 \tabularnewline
197 & 0.984646 & 0.0307086 & 0.0153543 \tabularnewline
198 & 0.980664 & 0.0386725 & 0.0193362 \tabularnewline
199 & 0.984595 & 0.030811 & 0.0154055 \tabularnewline
200 & 0.981416 & 0.037167 & 0.0185835 \tabularnewline
201 & 0.980033 & 0.0399344 & 0.0199672 \tabularnewline
202 & 0.979204 & 0.0415914 & 0.0207957 \tabularnewline
203 & 0.975337 & 0.0493268 & 0.0246634 \tabularnewline
204 & 0.970873 & 0.0582544 & 0.0291272 \tabularnewline
205 & 0.965403 & 0.069194 & 0.034597 \tabularnewline
206 & 0.973419 & 0.0531624 & 0.0265812 \tabularnewline
207 & 0.970423 & 0.0591549 & 0.0295775 \tabularnewline
208 & 0.974855 & 0.0502902 & 0.0251451 \tabularnewline
209 & 0.969779 & 0.060441 & 0.0302205 \tabularnewline
210 & 0.963929 & 0.0721418 & 0.0360709 \tabularnewline
211 & 0.959461 & 0.0810777 & 0.0405388 \tabularnewline
212 & 0.95122 & 0.0975598 & 0.0487799 \tabularnewline
213 & 0.956602 & 0.0867952 & 0.0433976 \tabularnewline
214 & 0.948585 & 0.10283 & 0.0514152 \tabularnewline
215 & 0.940117 & 0.119766 & 0.0598829 \tabularnewline
216 & 0.929754 & 0.140492 & 0.0702459 \tabularnewline
217 & 0.92208 & 0.15584 & 0.0779202 \tabularnewline
218 & 0.920718 & 0.158563 & 0.0792816 \tabularnewline
219 & 0.9055 & 0.189 & 0.0944999 \tabularnewline
220 & 0.887866 & 0.224268 & 0.112134 \tabularnewline
221 & 0.876422 & 0.247156 & 0.123578 \tabularnewline
222 & 0.875626 & 0.248748 & 0.124374 \tabularnewline
223 & 0.855278 & 0.289445 & 0.144722 \tabularnewline
224 & 0.831729 & 0.336542 & 0.168271 \tabularnewline
225 & 0.840523 & 0.318954 & 0.159477 \tabularnewline
226 & 0.856131 & 0.287739 & 0.143869 \tabularnewline
227 & 0.85065 & 0.298701 & 0.14935 \tabularnewline
228 & 0.897441 & 0.205117 & 0.102559 \tabularnewline
229 & 0.880842 & 0.238316 & 0.119158 \tabularnewline
230 & 0.882595 & 0.23481 & 0.117405 \tabularnewline
231 & 0.900867 & 0.198266 & 0.0991331 \tabularnewline
232 & 0.882108 & 0.235784 & 0.117892 \tabularnewline
233 & 0.871737 & 0.256525 & 0.128263 \tabularnewline
234 & 0.854098 & 0.291804 & 0.145902 \tabularnewline
235 & 0.829134 & 0.341731 & 0.170866 \tabularnewline
236 & 0.912543 & 0.174913 & 0.0874566 \tabularnewline
237 & 0.898705 & 0.20259 & 0.101295 \tabularnewline
238 & 0.906124 & 0.187753 & 0.0938764 \tabularnewline
239 & 0.89056 & 0.218881 & 0.10944 \tabularnewline
240 & 0.868884 & 0.262232 & 0.131116 \tabularnewline
241 & 0.851146 & 0.297707 & 0.148854 \tabularnewline
242 & 0.866031 & 0.267938 & 0.133969 \tabularnewline
243 & 0.85196 & 0.29608 & 0.14804 \tabularnewline
244 & 0.837313 & 0.325374 & 0.162687 \tabularnewline
245 & 0.806377 & 0.387247 & 0.193623 \tabularnewline
246 & 0.768046 & 0.463908 & 0.231954 \tabularnewline
247 & 0.723677 & 0.552647 & 0.276323 \tabularnewline
248 & 0.673244 & 0.653512 & 0.326756 \tabularnewline
249 & 0.631924 & 0.736151 & 0.368076 \tabularnewline
250 & 0.580227 & 0.839546 & 0.419773 \tabularnewline
251 & 0.564686 & 0.870628 & 0.435314 \tabularnewline
252 & 0.57924 & 0.84152 & 0.42076 \tabularnewline
253 & 0.536887 & 0.926225 & 0.463113 \tabularnewline
254 & 0.475432 & 0.950863 & 0.524568 \tabularnewline
255 & 0.490752 & 0.981503 & 0.509248 \tabularnewline
256 & 0.447146 & 0.894293 & 0.552854 \tabularnewline
257 & 0.471336 & 0.942671 & 0.528664 \tabularnewline
258 & 0.737894 & 0.524212 & 0.262106 \tabularnewline
259 & 0.712575 & 0.57485 & 0.287425 \tabularnewline
260 & 0.999317 & 0.00136636 & 0.000683178 \tabularnewline
261 & 0.998688 & 0.00262447 & 0.00131223 \tabularnewline
262 & 0.997158 & 0.0056833 & 0.00284165 \tabularnewline
263 & 0.99991 & 0.000180636 & 9.03181e-05 \tabularnewline
264 & 0.999735 & 0.000530192 & 0.000265096 \tabularnewline
265 & 0.999432 & 0.00113594 & 0.000567968 \tabularnewline
266 & 0.998715 & 0.00256933 & 0.00128467 \tabularnewline
267 & 0.999196 & 0.0016077 & 0.000803848 \tabularnewline
268 & 0.999456 & 0.00108792 & 0.000543962 \tabularnewline
269 & 0.998555 & 0.00288978 & 0.00144489 \tabularnewline
270 & 0.995029 & 0.00994108 & 0.00497054 \tabularnewline
271 & 0.998592 & 0.00281606 & 0.00140803 \tabularnewline
272 & 0.992677 & 0.0146459 & 0.00732297 \tabularnewline
273 & 0.96229 & 0.0754195 & 0.0377098 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&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]6[/C][C]0.909165[/C][C]0.18167[/C][C]0.0908352[/C][/ROW]
[ROW][C]7[/C][C]0.915157[/C][C]0.169686[/C][C]0.0848432[/C][/ROW]
[ROW][C]8[/C][C]0.854796[/C][C]0.290407[/C][C]0.145204[/C][/ROW]
[ROW][C]9[/C][C]0.81073[/C][C]0.378539[/C][C]0.18927[/C][/ROW]
[ROW][C]10[/C][C]0.802554[/C][C]0.394893[/C][C]0.197446[/C][/ROW]
[ROW][C]11[/C][C]0.725314[/C][C]0.549372[/C][C]0.274686[/C][/ROW]
[ROW][C]12[/C][C]0.862985[/C][C]0.274029[/C][C]0.137015[/C][/ROW]
[ROW][C]13[/C][C]0.815069[/C][C]0.369862[/C][C]0.184931[/C][/ROW]
[ROW][C]14[/C][C]0.754795[/C][C]0.490411[/C][C]0.245205[/C][/ROW]
[ROW][C]15[/C][C]0.703862[/C][C]0.592277[/C][C]0.296138[/C][/ROW]
[ROW][C]16[/C][C]0.644502[/C][C]0.710997[/C][C]0.355498[/C][/ROW]
[ROW][C]17[/C][C]0.573641[/C][C]0.852718[/C][C]0.426359[/C][/ROW]
[ROW][C]18[/C][C]0.504876[/C][C]0.990247[/C][C]0.495124[/C][/ROW]
[ROW][C]19[/C][C]0.455036[/C][C]0.910072[/C][C]0.544964[/C][/ROW]
[ROW][C]20[/C][C]0.387597[/C][C]0.775193[/C][C]0.612403[/C][/ROW]
[ROW][C]21[/C][C]0.419625[/C][C]0.83925[/C][C]0.580375[/C][/ROW]
[ROW][C]22[/C][C]0.468915[/C][C]0.937829[/C][C]0.531085[/C][/ROW]
[ROW][C]23[/C][C]0.407369[/C][C]0.814739[/C][C]0.592631[/C][/ROW]
[ROW][C]24[/C][C]0.400165[/C][C]0.80033[/C][C]0.599835[/C][/ROW]
[ROW][C]25[/C][C]0.346396[/C][C]0.692791[/C][C]0.653604[/C][/ROW]
[ROW][C]26[/C][C]0.321572[/C][C]0.643145[/C][C]0.678428[/C][/ROW]
[ROW][C]27[/C][C]0.293925[/C][C]0.58785[/C][C]0.706075[/C][/ROW]
[ROW][C]28[/C][C]0.295932[/C][C]0.591865[/C][C]0.704068[/C][/ROW]
[ROW][C]29[/C][C]0.264211[/C][C]0.528423[/C][C]0.735789[/C][/ROW]
[ROW][C]30[/C][C]0.231051[/C][C]0.462101[/C][C]0.768949[/C][/ROW]
[ROW][C]31[/C][C]0.236699[/C][C]0.473398[/C][C]0.763301[/C][/ROW]
[ROW][C]32[/C][C]0.207917[/C][C]0.415834[/C][C]0.792083[/C][/ROW]
[ROW][C]33[/C][C]0.175789[/C][C]0.351577[/C][C]0.824211[/C][/ROW]
[ROW][C]34[/C][C]0.181696[/C][C]0.363392[/C][C]0.818304[/C][/ROW]
[ROW][C]35[/C][C]0.149261[/C][C]0.298522[/C][C]0.850739[/C][/ROW]
[ROW][C]36[/C][C]0.121766[/C][C]0.243532[/C][C]0.878234[/C][/ROW]
[ROW][C]37[/C][C]0.0987387[/C][C]0.197477[/C][C]0.901261[/C][/ROW]
[ROW][C]38[/C][C]0.1008[/C][C]0.2016[/C][C]0.8992[/C][/ROW]
[ROW][C]39[/C][C]0.105332[/C][C]0.210665[/C][C]0.894668[/C][/ROW]
[ROW][C]40[/C][C]0.0856344[/C][C]0.171269[/C][C]0.914366[/C][/ROW]
[ROW][C]41[/C][C]0.157182[/C][C]0.314363[/C][C]0.842818[/C][/ROW]
[ROW][C]42[/C][C]0.133953[/C][C]0.267907[/C][C]0.866047[/C][/ROW]
[ROW][C]43[/C][C]0.123849[/C][C]0.247698[/C][C]0.876151[/C][/ROW]
[ROW][C]44[/C][C]0.10342[/C][C]0.20684[/C][C]0.89658[/C][/ROW]
[ROW][C]45[/C][C]0.0940914[/C][C]0.188183[/C][C]0.905909[/C][/ROW]
[ROW][C]46[/C][C]0.0786373[/C][C]0.157275[/C][C]0.921363[/C][/ROW]
[ROW][C]47[/C][C]0.0636852[/C][C]0.12737[/C][C]0.936315[/C][/ROW]
[ROW][C]48[/C][C]0.09991[/C][C]0.19982[/C][C]0.90009[/C][/ROW]
[ROW][C]49[/C][C]0.10963[/C][C]0.21926[/C][C]0.89037[/C][/ROW]
[ROW][C]50[/C][C]0.112156[/C][C]0.224312[/C][C]0.887844[/C][/ROW]
[ROW][C]51[/C][C]0.0939458[/C][C]0.187892[/C][C]0.906054[/C][/ROW]
[ROW][C]52[/C][C]0.120933[/C][C]0.241866[/C][C]0.879067[/C][/ROW]
[ROW][C]53[/C][C]0.10447[/C][C]0.208939[/C][C]0.89553[/C][/ROW]
[ROW][C]54[/C][C]0.106368[/C][C]0.212737[/C][C]0.893632[/C][/ROW]
[ROW][C]55[/C][C]0.107476[/C][C]0.214952[/C][C]0.892524[/C][/ROW]
[ROW][C]56[/C][C]0.0903415[/C][C]0.180683[/C][C]0.909658[/C][/ROW]
[ROW][C]57[/C][C]0.161347[/C][C]0.322694[/C][C]0.838653[/C][/ROW]
[ROW][C]58[/C][C]0.216899[/C][C]0.433798[/C][C]0.783101[/C][/ROW]
[ROW][C]59[/C][C]0.188833[/C][C]0.377666[/C][C]0.811167[/C][/ROW]
[ROW][C]60[/C][C]0.199848[/C][C]0.399696[/C][C]0.800152[/C][/ROW]
[ROW][C]61[/C][C]0.21268[/C][C]0.42536[/C][C]0.78732[/C][/ROW]
[ROW][C]62[/C][C]0.205369[/C][C]0.410739[/C][C]0.794631[/C][/ROW]
[ROW][C]63[/C][C]0.249194[/C][C]0.498388[/C][C]0.750806[/C][/ROW]
[ROW][C]64[/C][C]0.291144[/C][C]0.582288[/C][C]0.708856[/C][/ROW]
[ROW][C]65[/C][C]0.282849[/C][C]0.565698[/C][C]0.717151[/C][/ROW]
[ROW][C]66[/C][C]0.25657[/C][C]0.51314[/C][C]0.74343[/C][/ROW]
[ROW][C]67[/C][C]0.256572[/C][C]0.513145[/C][C]0.743428[/C][/ROW]
[ROW][C]68[/C][C]0.23869[/C][C]0.477379[/C][C]0.76131[/C][/ROW]
[ROW][C]69[/C][C]0.254159[/C][C]0.508318[/C][C]0.745841[/C][/ROW]
[ROW][C]70[/C][C]0.237519[/C][C]0.475038[/C][C]0.762481[/C][/ROW]
[ROW][C]71[/C][C]0.219308[/C][C]0.438616[/C][C]0.780692[/C][/ROW]
[ROW][C]72[/C][C]0.198441[/C][C]0.396883[/C][C]0.801559[/C][/ROW]
[ROW][C]73[/C][C]0.184592[/C][C]0.369183[/C][C]0.815408[/C][/ROW]
[ROW][C]74[/C][C]0.188874[/C][C]0.377749[/C][C]0.811126[/C][/ROW]
[ROW][C]75[/C][C]0.174836[/C][C]0.349672[/C][C]0.825164[/C][/ROW]
[ROW][C]76[/C][C]0.159353[/C][C]0.318705[/C][C]0.840647[/C][/ROW]
[ROW][C]77[/C][C]0.154881[/C][C]0.309761[/C][C]0.845119[/C][/ROW]
[ROW][C]78[/C][C]0.144037[/C][C]0.288075[/C][C]0.855963[/C][/ROW]
[ROW][C]79[/C][C]0.130076[/C][C]0.260153[/C][C]0.869924[/C][/ROW]
[ROW][C]80[/C][C]0.183016[/C][C]0.366033[/C][C]0.816984[/C][/ROW]
[ROW][C]81[/C][C]0.166268[/C][C]0.332536[/C][C]0.833732[/C][/ROW]
[ROW][C]82[/C][C]0.181359[/C][C]0.362717[/C][C]0.818641[/C][/ROW]
[ROW][C]83[/C][C]0.163751[/C][C]0.327502[/C][C]0.836249[/C][/ROW]
[ROW][C]84[/C][C]0.264746[/C][C]0.529492[/C][C]0.735254[/C][/ROW]
[ROW][C]85[/C][C]0.263836[/C][C]0.527672[/C][C]0.736164[/C][/ROW]
[ROW][C]86[/C][C]0.242715[/C][C]0.485431[/C][C]0.757285[/C][/ROW]
[ROW][C]87[/C][C]0.220056[/C][C]0.440111[/C][C]0.779944[/C][/ROW]
[ROW][C]88[/C][C]0.197523[/C][C]0.395046[/C][C]0.802477[/C][/ROW]
[ROW][C]89[/C][C]0.203921[/C][C]0.407841[/C][C]0.796079[/C][/ROW]
[ROW][C]90[/C][C]0.214434[/C][C]0.428868[/C][C]0.785566[/C][/ROW]
[ROW][C]91[/C][C]0.221716[/C][C]0.443432[/C][C]0.778284[/C][/ROW]
[ROW][C]92[/C][C]0.356274[/C][C]0.712548[/C][C]0.643726[/C][/ROW]
[ROW][C]93[/C][C]0.349228[/C][C]0.698456[/C][C]0.650772[/C][/ROW]
[ROW][C]94[/C][C]0.344168[/C][C]0.688335[/C][C]0.655832[/C][/ROW]
[ROW][C]95[/C][C]0.392775[/C][C]0.785549[/C][C]0.607225[/C][/ROW]
[ROW][C]96[/C][C]0.382415[/C][C]0.764829[/C][C]0.617585[/C][/ROW]
[ROW][C]97[/C][C]0.416378[/C][C]0.832757[/C][C]0.583622[/C][/ROW]
[ROW][C]98[/C][C]0.398499[/C][C]0.796999[/C][C]0.601501[/C][/ROW]
[ROW][C]99[/C][C]0.45573[/C][C]0.91146[/C][C]0.54427[/C][/ROW]
[ROW][C]100[/C][C]0.57617[/C][C]0.84766[/C][C]0.42383[/C][/ROW]
[ROW][C]101[/C][C]0.549992[/C][C]0.900017[/C][C]0.450008[/C][/ROW]
[ROW][C]102[/C][C]0.529503[/C][C]0.940994[/C][C]0.470497[/C][/ROW]
[ROW][C]103[/C][C]0.533496[/C][C]0.933008[/C][C]0.466504[/C][/ROW]
[ROW][C]104[/C][C]0.567393[/C][C]0.865213[/C][C]0.432607[/C][/ROW]
[ROW][C]105[/C][C]0.597879[/C][C]0.804243[/C][C]0.402121[/C][/ROW]
[ROW][C]106[/C][C]0.636333[/C][C]0.727334[/C][C]0.363667[/C][/ROW]
[ROW][C]107[/C][C]0.639841[/C][C]0.720319[/C][C]0.360159[/C][/ROW]
[ROW][C]108[/C][C]0.802046[/C][C]0.395909[/C][C]0.197954[/C][/ROW]
[ROW][C]109[/C][C]0.855855[/C][C]0.28829[/C][C]0.144145[/C][/ROW]
[ROW][C]110[/C][C]0.865361[/C][C]0.269279[/C][C]0.134639[/C][/ROW]
[ROW][C]111[/C][C]0.855074[/C][C]0.289853[/C][C]0.144926[/C][/ROW]
[ROW][C]112[/C][C]0.844409[/C][C]0.311182[/C][C]0.155591[/C][/ROW]
[ROW][C]113[/C][C]0.90122[/C][C]0.19756[/C][C]0.0987801[/C][/ROW]
[ROW][C]114[/C][C]0.908211[/C][C]0.183578[/C][C]0.0917891[/C][/ROW]
[ROW][C]115[/C][C]0.929181[/C][C]0.141637[/C][C]0.0708185[/C][/ROW]
[ROW][C]116[/C][C]0.951054[/C][C]0.0978923[/C][C]0.0489461[/C][/ROW]
[ROW][C]117[/C][C]0.947484[/C][C]0.105032[/C][C]0.0525158[/C][/ROW]
[ROW][C]118[/C][C]0.952055[/C][C]0.0958891[/C][C]0.0479446[/C][/ROW]
[ROW][C]119[/C][C]0.948767[/C][C]0.102466[/C][C]0.0512328[/C][/ROW]
[ROW][C]120[/C][C]0.958968[/C][C]0.0820635[/C][C]0.0410318[/C][/ROW]
[ROW][C]121[/C][C]0.962874[/C][C]0.074252[/C][C]0.037126[/C][/ROW]
[ROW][C]122[/C][C]0.977117[/C][C]0.0457669[/C][C]0.0228835[/C][/ROW]
[ROW][C]123[/C][C]0.979636[/C][C]0.0407288[/C][C]0.0203644[/C][/ROW]
[ROW][C]124[/C][C]0.991479[/C][C]0.0170419[/C][C]0.00852094[/C][/ROW]
[ROW][C]125[/C][C]0.991762[/C][C]0.0164757[/C][C]0.00823786[/C][/ROW]
[ROW][C]126[/C][C]0.990356[/C][C]0.0192879[/C][C]0.00964394[/C][/ROW]
[ROW][C]127[/C][C]0.990438[/C][C]0.0191247[/C][C]0.00956236[/C][/ROW]
[ROW][C]128[/C][C]0.989594[/C][C]0.0208117[/C][C]0.0104058[/C][/ROW]
[ROW][C]129[/C][C]0.991047[/C][C]0.0179065[/C][C]0.00895323[/C][/ROW]
[ROW][C]130[/C][C]0.991213[/C][C]0.0175747[/C][C]0.00878737[/C][/ROW]
[ROW][C]131[/C][C]0.99053[/C][C]0.0189391[/C][C]0.00946957[/C][/ROW]
[ROW][C]132[/C][C]0.989448[/C][C]0.0211035[/C][C]0.0105517[/C][/ROW]
[ROW][C]133[/C][C]0.989557[/C][C]0.0208867[/C][C]0.0104433[/C][/ROW]
[ROW][C]134[/C][C]0.987912[/C][C]0.0241765[/C][C]0.0120883[/C][/ROW]
[ROW][C]135[/C][C]0.986784[/C][C]0.0264314[/C][C]0.0132157[/C][/ROW]
[ROW][C]136[/C][C]0.984373[/C][C]0.0312547[/C][C]0.0156274[/C][/ROW]
[ROW][C]137[/C][C]0.991192[/C][C]0.0176151[/C][C]0.00880753[/C][/ROW]
[ROW][C]138[/C][C]0.992769[/C][C]0.0144622[/C][C]0.00723108[/C][/ROW]
[ROW][C]139[/C][C]0.992524[/C][C]0.014952[/C][C]0.007476[/C][/ROW]
[ROW][C]140[/C][C]0.991399[/C][C]0.0172015[/C][C]0.00860074[/C][/ROW]
[ROW][C]141[/C][C]0.989669[/C][C]0.0206614[/C][C]0.0103307[/C][/ROW]
[ROW][C]142[/C][C]0.991251[/C][C]0.0174979[/C][C]0.00874897[/C][/ROW]
[ROW][C]143[/C][C]0.990738[/C][C]0.0185232[/C][C]0.00926161[/C][/ROW]
[ROW][C]144[/C][C]0.991686[/C][C]0.0166277[/C][C]0.00831383[/C][/ROW]
[ROW][C]145[/C][C]0.990635[/C][C]0.0187308[/C][C]0.0093654[/C][/ROW]
[ROW][C]146[/C][C]0.990131[/C][C]0.0197381[/C][C]0.00986907[/C][/ROW]
[ROW][C]147[/C][C]0.988617[/C][C]0.0227656[/C][C]0.0113828[/C][/ROW]
[ROW][C]148[/C][C]0.986583[/C][C]0.0268346[/C][C]0.0134173[/C][/ROW]
[ROW][C]149[/C][C]0.985339[/C][C]0.0293229[/C][C]0.0146615[/C][/ROW]
[ROW][C]150[/C][C]0.986402[/C][C]0.0271964[/C][C]0.0135982[/C][/ROW]
[ROW][C]151[/C][C]0.994929[/C][C]0.0101426[/C][C]0.0050713[/C][/ROW]
[ROW][C]152[/C][C]0.994213[/C][C]0.011574[/C][C]0.00578698[/C][/ROW]
[ROW][C]153[/C][C]0.994509[/C][C]0.0109819[/C][C]0.00549095[/C][/ROW]
[ROW][C]154[/C][C]0.994018[/C][C]0.0119648[/C][C]0.00598238[/C][/ROW]
[ROW][C]155[/C][C]0.995764[/C][C]0.00847255[/C][C]0.00423628[/C][/ROW]
[ROW][C]156[/C][C]0.994895[/C][C]0.0102093[/C][C]0.00510463[/C][/ROW]
[ROW][C]157[/C][C]0.994739[/C][C]0.0105226[/C][C]0.00526132[/C][/ROW]
[ROW][C]158[/C][C]0.995175[/C][C]0.00965006[/C][C]0.00482503[/C][/ROW]
[ROW][C]159[/C][C]0.994195[/C][C]0.0116105[/C][C]0.00580527[/C][/ROW]
[ROW][C]160[/C][C]0.992813[/C][C]0.0143739[/C][C]0.00718696[/C][/ROW]
[ROW][C]161[/C][C]0.993939[/C][C]0.0121224[/C][C]0.00606122[/C][/ROW]
[ROW][C]162[/C][C]0.993804[/C][C]0.0123926[/C][C]0.00619629[/C][/ROW]
[ROW][C]163[/C][C]0.992579[/C][C]0.0148412[/C][C]0.00742058[/C][/ROW]
[ROW][C]164[/C][C]0.997219[/C][C]0.00556187[/C][C]0.00278094[/C][/ROW]
[ROW][C]165[/C][C]0.997368[/C][C]0.00526304[/C][C]0.00263152[/C][/ROW]
[ROW][C]166[/C][C]0.996841[/C][C]0.0063171[/C][C]0.00315855[/C][/ROW]
[ROW][C]167[/C][C]0.996654[/C][C]0.00669297[/C][C]0.00334648[/C][/ROW]
[ROW][C]168[/C][C]0.997434[/C][C]0.00513171[/C][C]0.00256585[/C][/ROW]
[ROW][C]169[/C][C]0.996835[/C][C]0.00633013[/C][C]0.00316507[/C][/ROW]
[ROW][C]170[/C][C]0.996808[/C][C]0.006385[/C][C]0.0031925[/C][/ROW]
[ROW][C]171[/C][C]0.996168[/C][C]0.00766422[/C][C]0.00383211[/C][/ROW]
[ROW][C]172[/C][C]0.996855[/C][C]0.0062899[/C][C]0.00314495[/C][/ROW]
[ROW][C]173[/C][C]0.996109[/C][C]0.007782[/C][C]0.003891[/C][/ROW]
[ROW][C]174[/C][C]0.995311[/C][C]0.0093771[/C][C]0.00468855[/C][/ROW]
[ROW][C]175[/C][C]0.994345[/C][C]0.0113096[/C][C]0.0056548[/C][/ROW]
[ROW][C]176[/C][C]0.99445[/C][C]0.0110999[/C][C]0.00554997[/C][/ROW]
[ROW][C]177[/C][C]0.993634[/C][C]0.0127329[/C][C]0.00636643[/C][/ROW]
[ROW][C]178[/C][C]0.994603[/C][C]0.0107932[/C][C]0.00539661[/C][/ROW]
[ROW][C]179[/C][C]0.993348[/C][C]0.013304[/C][C]0.00665198[/C][/ROW]
[ROW][C]180[/C][C]0.993768[/C][C]0.0124637[/C][C]0.00623187[/C][/ROW]
[ROW][C]181[/C][C]0.993793[/C][C]0.0124136[/C][C]0.00620679[/C][/ROW]
[ROW][C]182[/C][C]0.992184[/C][C]0.015632[/C][C]0.00781598[/C][/ROW]
[ROW][C]183[/C][C]0.992146[/C][C]0.015709[/C][C]0.00785449[/C][/ROW]
[ROW][C]184[/C][C]0.990194[/C][C]0.0196125[/C][C]0.00980626[/C][/ROW]
[ROW][C]185[/C][C]0.992796[/C][C]0.0144072[/C][C]0.00720361[/C][/ROW]
[ROW][C]186[/C][C]0.991072[/C][C]0.0178552[/C][C]0.00892762[/C][/ROW]
[ROW][C]187[/C][C]0.994846[/C][C]0.0103074[/C][C]0.00515369[/C][/ROW]
[ROW][C]188[/C][C]0.99394[/C][C]0.0121206[/C][C]0.0060603[/C][/ROW]
[ROW][C]189[/C][C]0.992356[/C][C]0.0152874[/C][C]0.00764368[/C][/ROW]
[ROW][C]190[/C][C]0.990195[/C][C]0.0196097[/C][C]0.00980485[/C][/ROW]
[ROW][C]191[/C][C]0.987673[/C][C]0.0246531[/C][C]0.0123266[/C][/ROW]
[ROW][C]192[/C][C]0.985323[/C][C]0.0293544[/C][C]0.0146772[/C][/ROW]
[ROW][C]193[/C][C]0.984453[/C][C]0.0310932[/C][C]0.0155466[/C][/ROW]
[ROW][C]194[/C][C]0.986135[/C][C]0.0277306[/C][C]0.0138653[/C][/ROW]
[ROW][C]195[/C][C]0.984659[/C][C]0.0306811[/C][C]0.0153405[/C][/ROW]
[ROW][C]196[/C][C]0.983451[/C][C]0.033099[/C][C]0.0165495[/C][/ROW]
[ROW][C]197[/C][C]0.984646[/C][C]0.0307086[/C][C]0.0153543[/C][/ROW]
[ROW][C]198[/C][C]0.980664[/C][C]0.0386725[/C][C]0.0193362[/C][/ROW]
[ROW][C]199[/C][C]0.984595[/C][C]0.030811[/C][C]0.0154055[/C][/ROW]
[ROW][C]200[/C][C]0.981416[/C][C]0.037167[/C][C]0.0185835[/C][/ROW]
[ROW][C]201[/C][C]0.980033[/C][C]0.0399344[/C][C]0.0199672[/C][/ROW]
[ROW][C]202[/C][C]0.979204[/C][C]0.0415914[/C][C]0.0207957[/C][/ROW]
[ROW][C]203[/C][C]0.975337[/C][C]0.0493268[/C][C]0.0246634[/C][/ROW]
[ROW][C]204[/C][C]0.970873[/C][C]0.0582544[/C][C]0.0291272[/C][/ROW]
[ROW][C]205[/C][C]0.965403[/C][C]0.069194[/C][C]0.034597[/C][/ROW]
[ROW][C]206[/C][C]0.973419[/C][C]0.0531624[/C][C]0.0265812[/C][/ROW]
[ROW][C]207[/C][C]0.970423[/C][C]0.0591549[/C][C]0.0295775[/C][/ROW]
[ROW][C]208[/C][C]0.974855[/C][C]0.0502902[/C][C]0.0251451[/C][/ROW]
[ROW][C]209[/C][C]0.969779[/C][C]0.060441[/C][C]0.0302205[/C][/ROW]
[ROW][C]210[/C][C]0.963929[/C][C]0.0721418[/C][C]0.0360709[/C][/ROW]
[ROW][C]211[/C][C]0.959461[/C][C]0.0810777[/C][C]0.0405388[/C][/ROW]
[ROW][C]212[/C][C]0.95122[/C][C]0.0975598[/C][C]0.0487799[/C][/ROW]
[ROW][C]213[/C][C]0.956602[/C][C]0.0867952[/C][C]0.0433976[/C][/ROW]
[ROW][C]214[/C][C]0.948585[/C][C]0.10283[/C][C]0.0514152[/C][/ROW]
[ROW][C]215[/C][C]0.940117[/C][C]0.119766[/C][C]0.0598829[/C][/ROW]
[ROW][C]216[/C][C]0.929754[/C][C]0.140492[/C][C]0.0702459[/C][/ROW]
[ROW][C]217[/C][C]0.92208[/C][C]0.15584[/C][C]0.0779202[/C][/ROW]
[ROW][C]218[/C][C]0.920718[/C][C]0.158563[/C][C]0.0792816[/C][/ROW]
[ROW][C]219[/C][C]0.9055[/C][C]0.189[/C][C]0.0944999[/C][/ROW]
[ROW][C]220[/C][C]0.887866[/C][C]0.224268[/C][C]0.112134[/C][/ROW]
[ROW][C]221[/C][C]0.876422[/C][C]0.247156[/C][C]0.123578[/C][/ROW]
[ROW][C]222[/C][C]0.875626[/C][C]0.248748[/C][C]0.124374[/C][/ROW]
[ROW][C]223[/C][C]0.855278[/C][C]0.289445[/C][C]0.144722[/C][/ROW]
[ROW][C]224[/C][C]0.831729[/C][C]0.336542[/C][C]0.168271[/C][/ROW]
[ROW][C]225[/C][C]0.840523[/C][C]0.318954[/C][C]0.159477[/C][/ROW]
[ROW][C]226[/C][C]0.856131[/C][C]0.287739[/C][C]0.143869[/C][/ROW]
[ROW][C]227[/C][C]0.85065[/C][C]0.298701[/C][C]0.14935[/C][/ROW]
[ROW][C]228[/C][C]0.897441[/C][C]0.205117[/C][C]0.102559[/C][/ROW]
[ROW][C]229[/C][C]0.880842[/C][C]0.238316[/C][C]0.119158[/C][/ROW]
[ROW][C]230[/C][C]0.882595[/C][C]0.23481[/C][C]0.117405[/C][/ROW]
[ROW][C]231[/C][C]0.900867[/C][C]0.198266[/C][C]0.0991331[/C][/ROW]
[ROW][C]232[/C][C]0.882108[/C][C]0.235784[/C][C]0.117892[/C][/ROW]
[ROW][C]233[/C][C]0.871737[/C][C]0.256525[/C][C]0.128263[/C][/ROW]
[ROW][C]234[/C][C]0.854098[/C][C]0.291804[/C][C]0.145902[/C][/ROW]
[ROW][C]235[/C][C]0.829134[/C][C]0.341731[/C][C]0.170866[/C][/ROW]
[ROW][C]236[/C][C]0.912543[/C][C]0.174913[/C][C]0.0874566[/C][/ROW]
[ROW][C]237[/C][C]0.898705[/C][C]0.20259[/C][C]0.101295[/C][/ROW]
[ROW][C]238[/C][C]0.906124[/C][C]0.187753[/C][C]0.0938764[/C][/ROW]
[ROW][C]239[/C][C]0.89056[/C][C]0.218881[/C][C]0.10944[/C][/ROW]
[ROW][C]240[/C][C]0.868884[/C][C]0.262232[/C][C]0.131116[/C][/ROW]
[ROW][C]241[/C][C]0.851146[/C][C]0.297707[/C][C]0.148854[/C][/ROW]
[ROW][C]242[/C][C]0.866031[/C][C]0.267938[/C][C]0.133969[/C][/ROW]
[ROW][C]243[/C][C]0.85196[/C][C]0.29608[/C][C]0.14804[/C][/ROW]
[ROW][C]244[/C][C]0.837313[/C][C]0.325374[/C][C]0.162687[/C][/ROW]
[ROW][C]245[/C][C]0.806377[/C][C]0.387247[/C][C]0.193623[/C][/ROW]
[ROW][C]246[/C][C]0.768046[/C][C]0.463908[/C][C]0.231954[/C][/ROW]
[ROW][C]247[/C][C]0.723677[/C][C]0.552647[/C][C]0.276323[/C][/ROW]
[ROW][C]248[/C][C]0.673244[/C][C]0.653512[/C][C]0.326756[/C][/ROW]
[ROW][C]249[/C][C]0.631924[/C][C]0.736151[/C][C]0.368076[/C][/ROW]
[ROW][C]250[/C][C]0.580227[/C][C]0.839546[/C][C]0.419773[/C][/ROW]
[ROW][C]251[/C][C]0.564686[/C][C]0.870628[/C][C]0.435314[/C][/ROW]
[ROW][C]252[/C][C]0.57924[/C][C]0.84152[/C][C]0.42076[/C][/ROW]
[ROW][C]253[/C][C]0.536887[/C][C]0.926225[/C][C]0.463113[/C][/ROW]
[ROW][C]254[/C][C]0.475432[/C][C]0.950863[/C][C]0.524568[/C][/ROW]
[ROW][C]255[/C][C]0.490752[/C][C]0.981503[/C][C]0.509248[/C][/ROW]
[ROW][C]256[/C][C]0.447146[/C][C]0.894293[/C][C]0.552854[/C][/ROW]
[ROW][C]257[/C][C]0.471336[/C][C]0.942671[/C][C]0.528664[/C][/ROW]
[ROW][C]258[/C][C]0.737894[/C][C]0.524212[/C][C]0.262106[/C][/ROW]
[ROW][C]259[/C][C]0.712575[/C][C]0.57485[/C][C]0.287425[/C][/ROW]
[ROW][C]260[/C][C]0.999317[/C][C]0.00136636[/C][C]0.000683178[/C][/ROW]
[ROW][C]261[/C][C]0.998688[/C][C]0.00262447[/C][C]0.00131223[/C][/ROW]
[ROW][C]262[/C][C]0.997158[/C][C]0.0056833[/C][C]0.00284165[/C][/ROW]
[ROW][C]263[/C][C]0.99991[/C][C]0.000180636[/C][C]9.03181e-05[/C][/ROW]
[ROW][C]264[/C][C]0.999735[/C][C]0.000530192[/C][C]0.000265096[/C][/ROW]
[ROW][C]265[/C][C]0.999432[/C][C]0.00113594[/C][C]0.000567968[/C][/ROW]
[ROW][C]266[/C][C]0.998715[/C][C]0.00256933[/C][C]0.00128467[/C][/ROW]
[ROW][C]267[/C][C]0.999196[/C][C]0.0016077[/C][C]0.000803848[/C][/ROW]
[ROW][C]268[/C][C]0.999456[/C][C]0.00108792[/C][C]0.000543962[/C][/ROW]
[ROW][C]269[/C][C]0.998555[/C][C]0.00288978[/C][C]0.00144489[/C][/ROW]
[ROW][C]270[/C][C]0.995029[/C][C]0.00994108[/C][C]0.00497054[/C][/ROW]
[ROW][C]271[/C][C]0.998592[/C][C]0.00281606[/C][C]0.00140803[/C][/ROW]
[ROW][C]272[/C][C]0.992677[/C][C]0.0146459[/C][C]0.00732297[/C][/ROW]
[ROW][C]273[/C][C]0.96229[/C][C]0.0754195[/C][C]0.0377098[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&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
60.9091650.181670.0908352
70.9151570.1696860.0848432
80.8547960.2904070.145204
90.810730.3785390.18927
100.8025540.3948930.197446
110.7253140.5493720.274686
120.8629850.2740290.137015
130.8150690.3698620.184931
140.7547950.4904110.245205
150.7038620.5922770.296138
160.6445020.7109970.355498
170.5736410.8527180.426359
180.5048760.9902470.495124
190.4550360.9100720.544964
200.3875970.7751930.612403
210.4196250.839250.580375
220.4689150.9378290.531085
230.4073690.8147390.592631
240.4001650.800330.599835
250.3463960.6927910.653604
260.3215720.6431450.678428
270.2939250.587850.706075
280.2959320.5918650.704068
290.2642110.5284230.735789
300.2310510.4621010.768949
310.2366990.4733980.763301
320.2079170.4158340.792083
330.1757890.3515770.824211
340.1816960.3633920.818304
350.1492610.2985220.850739
360.1217660.2435320.878234
370.09873870.1974770.901261
380.10080.20160.8992
390.1053320.2106650.894668
400.08563440.1712690.914366
410.1571820.3143630.842818
420.1339530.2679070.866047
430.1238490.2476980.876151
440.103420.206840.89658
450.09409140.1881830.905909
460.07863730.1572750.921363
470.06368520.127370.936315
480.099910.199820.90009
490.109630.219260.89037
500.1121560.2243120.887844
510.09394580.1878920.906054
520.1209330.2418660.879067
530.104470.2089390.89553
540.1063680.2127370.893632
550.1074760.2149520.892524
560.09034150.1806830.909658
570.1613470.3226940.838653
580.2168990.4337980.783101
590.1888330.3776660.811167
600.1998480.3996960.800152
610.212680.425360.78732
620.2053690.4107390.794631
630.2491940.4983880.750806
640.2911440.5822880.708856
650.2828490.5656980.717151
660.256570.513140.74343
670.2565720.5131450.743428
680.238690.4773790.76131
690.2541590.5083180.745841
700.2375190.4750380.762481
710.2193080.4386160.780692
720.1984410.3968830.801559
730.1845920.3691830.815408
740.1888740.3777490.811126
750.1748360.3496720.825164
760.1593530.3187050.840647
770.1548810.3097610.845119
780.1440370.2880750.855963
790.1300760.2601530.869924
800.1830160.3660330.816984
810.1662680.3325360.833732
820.1813590.3627170.818641
830.1637510.3275020.836249
840.2647460.5294920.735254
850.2638360.5276720.736164
860.2427150.4854310.757285
870.2200560.4401110.779944
880.1975230.3950460.802477
890.2039210.4078410.796079
900.2144340.4288680.785566
910.2217160.4434320.778284
920.3562740.7125480.643726
930.3492280.6984560.650772
940.3441680.6883350.655832
950.3927750.7855490.607225
960.3824150.7648290.617585
970.4163780.8327570.583622
980.3984990.7969990.601501
990.455730.911460.54427
1000.576170.847660.42383
1010.5499920.9000170.450008
1020.5295030.9409940.470497
1030.5334960.9330080.466504
1040.5673930.8652130.432607
1050.5978790.8042430.402121
1060.6363330.7273340.363667
1070.6398410.7203190.360159
1080.8020460.3959090.197954
1090.8558550.288290.144145
1100.8653610.2692790.134639
1110.8550740.2898530.144926
1120.8444090.3111820.155591
1130.901220.197560.0987801
1140.9082110.1835780.0917891
1150.9291810.1416370.0708185
1160.9510540.09789230.0489461
1170.9474840.1050320.0525158
1180.9520550.09588910.0479446
1190.9487670.1024660.0512328
1200.9589680.08206350.0410318
1210.9628740.0742520.037126
1220.9771170.04576690.0228835
1230.9796360.04072880.0203644
1240.9914790.01704190.00852094
1250.9917620.01647570.00823786
1260.9903560.01928790.00964394
1270.9904380.01912470.00956236
1280.9895940.02081170.0104058
1290.9910470.01790650.00895323
1300.9912130.01757470.00878737
1310.990530.01893910.00946957
1320.9894480.02110350.0105517
1330.9895570.02088670.0104433
1340.9879120.02417650.0120883
1350.9867840.02643140.0132157
1360.9843730.03125470.0156274
1370.9911920.01761510.00880753
1380.9927690.01446220.00723108
1390.9925240.0149520.007476
1400.9913990.01720150.00860074
1410.9896690.02066140.0103307
1420.9912510.01749790.00874897
1430.9907380.01852320.00926161
1440.9916860.01662770.00831383
1450.9906350.01873080.0093654
1460.9901310.01973810.00986907
1470.9886170.02276560.0113828
1480.9865830.02683460.0134173
1490.9853390.02932290.0146615
1500.9864020.02719640.0135982
1510.9949290.01014260.0050713
1520.9942130.0115740.00578698
1530.9945090.01098190.00549095
1540.9940180.01196480.00598238
1550.9957640.008472550.00423628
1560.9948950.01020930.00510463
1570.9947390.01052260.00526132
1580.9951750.009650060.00482503
1590.9941950.01161050.00580527
1600.9928130.01437390.00718696
1610.9939390.01212240.00606122
1620.9938040.01239260.00619629
1630.9925790.01484120.00742058
1640.9972190.005561870.00278094
1650.9973680.005263040.00263152
1660.9968410.00631710.00315855
1670.9966540.006692970.00334648
1680.9974340.005131710.00256585
1690.9968350.006330130.00316507
1700.9968080.0063850.0031925
1710.9961680.007664220.00383211
1720.9968550.00628990.00314495
1730.9961090.0077820.003891
1740.9953110.00937710.00468855
1750.9943450.01130960.0056548
1760.994450.01109990.00554997
1770.9936340.01273290.00636643
1780.9946030.01079320.00539661
1790.9933480.0133040.00665198
1800.9937680.01246370.00623187
1810.9937930.01241360.00620679
1820.9921840.0156320.00781598
1830.9921460.0157090.00785449
1840.9901940.01961250.00980626
1850.9927960.01440720.00720361
1860.9910720.01785520.00892762
1870.9948460.01030740.00515369
1880.993940.01212060.0060603
1890.9923560.01528740.00764368
1900.9901950.01960970.00980485
1910.9876730.02465310.0123266
1920.9853230.02935440.0146772
1930.9844530.03109320.0155466
1940.9861350.02773060.0138653
1950.9846590.03068110.0153405
1960.9834510.0330990.0165495
1970.9846460.03070860.0153543
1980.9806640.03867250.0193362
1990.9845950.0308110.0154055
2000.9814160.0371670.0185835
2010.9800330.03993440.0199672
2020.9792040.04159140.0207957
2030.9753370.04932680.0246634
2040.9708730.05825440.0291272
2050.9654030.0691940.034597
2060.9734190.05316240.0265812
2070.9704230.05915490.0295775
2080.9748550.05029020.0251451
2090.9697790.0604410.0302205
2100.9639290.07214180.0360709
2110.9594610.08107770.0405388
2120.951220.09755980.0487799
2130.9566020.08679520.0433976
2140.9485850.102830.0514152
2150.9401170.1197660.0598829
2160.9297540.1404920.0702459
2170.922080.155840.0779202
2180.9207180.1585630.0792816
2190.90550.1890.0944999
2200.8878660.2242680.112134
2210.8764220.2471560.123578
2220.8756260.2487480.124374
2230.8552780.2894450.144722
2240.8317290.3365420.168271
2250.8405230.3189540.159477
2260.8561310.2877390.143869
2270.850650.2987010.14935
2280.8974410.2051170.102559
2290.8808420.2383160.119158
2300.8825950.234810.117405
2310.9008670.1982660.0991331
2320.8821080.2357840.117892
2330.8717370.2565250.128263
2340.8540980.2918040.145902
2350.8291340.3417310.170866
2360.9125430.1749130.0874566
2370.8987050.202590.101295
2380.9061240.1877530.0938764
2390.890560.2188810.10944
2400.8688840.2622320.131116
2410.8511460.2977070.148854
2420.8660310.2679380.133969
2430.851960.296080.14804
2440.8373130.3253740.162687
2450.8063770.3872470.193623
2460.7680460.4639080.231954
2470.7236770.5526470.276323
2480.6732440.6535120.326756
2490.6319240.7361510.368076
2500.5802270.8395460.419773
2510.5646860.8706280.435314
2520.579240.841520.42076
2530.5368870.9262250.463113
2540.4754320.9508630.524568
2550.4907520.9815030.509248
2560.4471460.8942930.552854
2570.4713360.9426710.528664
2580.7378940.5242120.262106
2590.7125750.574850.287425
2600.9993170.001366360.000683178
2610.9986880.002624470.00131223
2620.9971580.00568330.00284165
2630.999910.0001806369.03181e-05
2640.9997350.0005301920.000265096
2650.9994320.001135940.000567968
2660.9987150.002569330.00128467
2670.9991960.00160770.000803848
2680.9994560.001087920.000543962
2690.9985550.002889780.00144489
2700.9950290.009941080.00497054
2710.9985920.002816060.00140803
2720.9926770.01464590.00732297
2730.962290.07541950.0377098






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level250.0932836NOK
5% type I error level950.354478NOK
10% type I error level1100.410448NOK

\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 & 25 & 0.0932836 & NOK \tabularnewline
5% type I error level & 95 & 0.354478 & NOK \tabularnewline
10% type I error level & 110 & 0.410448 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=266153&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]25[/C][C]0.0932836[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]95[/C][C]0.354478[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]110[/C][C]0.410448[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=266153&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=266153&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level250.0932836NOK
5% type I error level950.354478NOK
10% type I error level1100.410448NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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QR Code


Input Parameters & R Code

Parameters (Session):
par1 = 2 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 2 ; 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')
}