FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 computationWed, 10 Dec 2014 15:13:35 +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/10/t14182245351l6189rz65lzef1.htm/, Retrieved Sun, 19 May 2024 16:29:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265342, Retrieved Sun, 19 May 2024 16:29:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact90

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 15:13:35] [cb9023b84cdbf59fe6647357de544f7b] [Current]
Feedback Forum

Post a new message

Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&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 time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.57963 -0.000105534Hours[t] + 0.0243122Blogged[t] + 0.012188LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  8.57963 -0.000105534Hours[t] +  0.0243122Blogged[t] +  0.012188LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  8.57963 -0.000105534Hours[t] +  0.0243122Blogged[t] +  0.012188LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 8.57963 -0.000105534Hours[t] + 0.0243122Blogged[t] + 0.012188LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.579630.60230314.241.97627e-339.88135e-34
Hours-0.0001055340.00714402-0.014770.9882270.494113
Blogged0.02431220.002874068.4593.14967e-151.57484e-15
LFM0.0121880.005031392.4220.01619270.00809635

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 8.57963 & 0.602303 & 14.24 & 1.97627e-33 & 9.88135e-34 \tabularnewline
Hours & -0.000105534 & 0.00714402 & -0.01477 & 0.988227 & 0.494113 \tabularnewline
Blogged & 0.0243122 & 0.00287406 & 8.459 & 3.14967e-15 & 1.57484e-15 \tabularnewline
LFM & 0.012188 & 0.00503139 & 2.422 & 0.0161927 & 0.00809635 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]8.57963[/C][C]0.602303[/C][C]14.24[/C][C]1.97627e-33[/C][C]9.88135e-34[/C][/ROW]
[ROW][C]Hours[/C][C]-0.000105534[/C][C]0.00714402[/C][C]-0.01477[/C][C]0.988227[/C][C]0.494113[/C][/ROW]
[ROW][C]Blogged[/C][C]0.0243122[/C][C]0.00287406[/C][C]8.459[/C][C]3.14967e-15[/C][C]1.57484e-15[/C][/ROW]
[ROW][C]LFM[/C][C]0.012188[/C][C]0.00503139[/C][C]2.422[/C][C]0.0161927[/C][C]0.00809635[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.579630.60230314.241.97627e-339.88135e-34
Hours-0.0001055340.00714402-0.014770.9882270.494113
Blogged0.02431220.002874068.4593.14967e-151.57484e-15
LFM0.0121880.005031392.4220.01619270.00809635






Multiple Linear Regression - Regression Statistics
Multiple R0.581762
R-squared0.338447
Adjusted R-squared0.329818
F-TEST (value)39.2222
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70832
Sum Squared Residuals1687.05

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.581762 \tabularnewline
R-squared & 0.338447 \tabularnewline
Adjusted R-squared & 0.329818 \tabularnewline
F-TEST (value) & 39.2222 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 230 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.70832 \tabularnewline
Sum Squared Residuals & 1687.05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.581762[/C][/ROW]
[ROW][C]R-squared[/C][C]0.338447[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.329818[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]39.2222[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]230[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.70832[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1687.05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&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 R0.581762
R-squared0.338447
Adjusted R-squared0.329818
F-TEST (value)39.2222
F-TEST (DF numerator)3
F-TEST (DF denominator)230
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.70832
Sum Squared Residuals1687.05






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.72050.179464
212.812.51540.284567
37.413.2655-5.86552
46.711.8105-5.11048
512.615.5761-2.97613
614.813.27891.52113
713.312.78750.51247
811.113.1757-2.07572
98.214.4481-6.24812
1011.413.4024-2.00242
116.414.9076-8.50758
121214.1372-2.13722
136.310.0845-3.78449
1411.311.6277-0.327698
1511.914.2491-2.34906
169.312.4417-3.14173
171012.0894-2.08943
1813.812.82450.975474
1910.813.8662-3.06624
2011.713.1079-1.40795
2110.915.6992-4.79917
2216.113.69432.40572
239.912.0039-2.10389
2411.512.6988-1.19878
258.312.2708-3.9708
2611.713.6584-1.95836
27912.6615-3.66153
2810.812.7679-1.96786
2910.412.2863-1.88625
3012.712.7947-0.0946917
3111.814.5675-2.76746
321312.36690.633053
3310.813.1605-2.3605
3412.310.80011.49994
3511.313.7895-2.48948
3611.612.3444-0.744438
3710.913.4416-2.54162
3812.112.992-0.89196
3913.313.6915-0.391518
4010.113.5369-3.43689
4114.312.6121.68795
429.313.436-4.13601
4312.511.95730.542666
447.611.3118-3.71179
459.212.0548-2.85482
4614.513.14631.35371
4712.313.8102-1.5102
4812.613.3771-0.777067
491314.0929-1.0929
5012.611.56661.03338
5113.215.0301-1.83009
527.711.9781-4.27809
5310.511.0551-0.555149
5410.912.209-1.30895
554.310.5846-6.28458
5610.311.5777-1.27769
5711.410.98140.418595
585.611.5208-5.92082
598.812.1155-3.31555
60910.9019-1.90193
619.611.4932-1.89322
626.410.5231-4.1231
6311.611.25240.347646
644.3510.1579-5.80787
6512.712.7322-0.0321703
6618.114.82533.27474
6717.8515.11722.73276
6816.616.28690.313079
6912.610.25692.34309
7017.121.6045-4.50448
7119.115.69263.40737
7216.118.7853-2.68528
7313.3510.80382.5462
7418.417.46160.938445
7514.711.11833.58167
7610.614.6527-4.05274
7712.613.769-1.16897
7816.215.09331.10674
7913.617.0125-3.41255
8018.915.67823.22176
8114.112.43031.66968
8214.512.05552.44452
8316.1517.9157-1.76572
8414.7513.55931.19065
8514.814.25010.549855
8612.4512.40640.0435574
8712.6514.6034-1.95343
8817.3513.86643.48357
898.612.0785-3.47854
9018.417.5940.806004
9116.117.8462-1.74622
9211.611.36230.237736
9317.7512.28725.46277
9415.2513.99371.25629
9517.6516.08911.56085
9615.613.78181.81823
9716.3515.15181.19825
9817.6515.17562.47438
9913.613.12180.478184
10011.712.4699-0.769867
10114.3513.620.73003
10214.7517.4518-2.70177
10318.2516.21152.03846
1049.915.2524-5.35238
1051614.33381.66625
10618.2515.62712.62288
10716.8517.2091-0.35908
10814.612.56482.03522
10913.8514.0101-0.16012
11018.9516.50992.4401
11115.614.56871.03131
11214.8517.2398-2.38982
11311.7512.4636-0.713625
11418.4513.33835.11165
11515.917.0503-1.15034
11617.114.49542.60465
11716.110.9365.16403
11819.914.98844.91156
11910.9510.43280.517155
12018.4515.84252.60748
12115.110.71794.38205
1221515.2845-0.284538
12311.3514.1903-2.84034
12415.9514.99290.957102
12518.113.49734.60267
12614.613.18131.41874
12715.415.9828-0.582781
12815.415.9828-0.582781
12917.613.77753.8225
13013.3514.0202-0.670247
13119.116.55182.54822
13215.3513.38981.96024
1337.612.1374-4.53744
13413.414.186-0.78595
13513.913.64530.254702
13619.117.12041.97962
13715.2514.02131.22872
13812.912.4090.491048
13916.113.99562.10443
14017.3512.37034.97971
14113.1512.52650.623528
14212.1510.02342.12656
14312.612.6971-0.0971085
14410.3511.6153-1.26529
14515.413.06162.33837
1469.611.1557-1.55573
14718.213.35314.84687
14813.612.25991.34011
14914.8514.46970.380253
15014.7516.9265-2.1765
15114.113.91170.188289
15214.911.39473.50527
15316.2512.9513.299
15419.2517.44781.80218
15513.612.0661.53404
15613.613.50120.0987755
15715.6515.12950.520521
15812.7512.2980.45199
15914.611.18793.41208
1609.8513.2665-3.41653
16112.6511.22731.42269
16211.912.2228-0.322842
16319.216.63382.5662
16416.614.32262.27745
16511.210.3020.898035
16615.2513.27081.97918
16711.915.1973-3.29735
16813.215.4947-2.29468
16916.3517.2291-0.879124
17012.413.4261-1.02613
17115.8513.07222.77779
17214.3513.61060.739378
17318.1515.10723.04277
17411.1511.6507-0.500713
17515.6515.42910.220894
17617.7516.00251.74751
1777.6512.5279-4.87791
17812.3511.98230.367692
17915.611.77843.82156
18019.316.34462.95543
18115.211.83423.36582
18217.113.52883.57121
18315.612.58433.01572
18418.415.34453.05549
18519.0515.22723.82278
18618.5513.34245.20763
18719.117.03272.0673
18813.111.9321.16797
18912.8513.3677-0.517736
1909.511.7643-2.26425
1914.511.2881-6.78806
19211.8510.66921.18084
19313.615.7331-2.13311
19411.713.4374-1.73742
19512.411.60270.797334
19613.3514.9339-1.58388
19711.413.8148-2.41479
19814.911.83273.0673
19919.914.98844.91156
20017.7512.20125.54884
20111.211.7844-0.584406
20214.615.4309-0.830858
20317.616.3331.26705
20414.0512.50181.54818
20516.115.48170.61834
20613.3513.29560.0544497
20711.8512.5171-0.667141
20811.9514.3972-2.44723
20914.7514.67760.0724019
21015.1513.41.75005
21113.213.952-0.752009
21216.8515.40431.44569
2137.8510.424-2.57402
2147.714.4728-6.77281
21512.611.85430.745671
2167.8511.7718-3.9218
21710.9510.43280.517155
21812.3512.19910.150851
2199.9512.5474-2.59736
22014.911.83273.0673
22116.6514.54372.10628
22213.413.06230.337723
22313.9513.31820.631819
22415.711.72283.97722
22516.8512.57644.27361
22610.9510.67940.270612
22715.3511.86033.48967
22812.211.26250.937454
22915.114.17840.921636
23017.7516.32911.42094
23115.213.03622.16376
23214.613.37781.22216
23316.6514.78741.86262
2348.110.8507-2.75075

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.7205 & 0.179464 \tabularnewline
2 & 12.8 & 12.5154 & 0.284567 \tabularnewline
3 & 7.4 & 13.2655 & -5.86552 \tabularnewline
4 & 6.7 & 11.8105 & -5.11048 \tabularnewline
5 & 12.6 & 15.5761 & -2.97613 \tabularnewline
6 & 14.8 & 13.2789 & 1.52113 \tabularnewline
7 & 13.3 & 12.7875 & 0.51247 \tabularnewline
8 & 11.1 & 13.1757 & -2.07572 \tabularnewline
9 & 8.2 & 14.4481 & -6.24812 \tabularnewline
10 & 11.4 & 13.4024 & -2.00242 \tabularnewline
11 & 6.4 & 14.9076 & -8.50758 \tabularnewline
12 & 12 & 14.1372 & -2.13722 \tabularnewline
13 & 6.3 & 10.0845 & -3.78449 \tabularnewline
14 & 11.3 & 11.6277 & -0.327698 \tabularnewline
15 & 11.9 & 14.2491 & -2.34906 \tabularnewline
16 & 9.3 & 12.4417 & -3.14173 \tabularnewline
17 & 10 & 12.0894 & -2.08943 \tabularnewline
18 & 13.8 & 12.8245 & 0.975474 \tabularnewline
19 & 10.8 & 13.8662 & -3.06624 \tabularnewline
20 & 11.7 & 13.1079 & -1.40795 \tabularnewline
21 & 10.9 & 15.6992 & -4.79917 \tabularnewline
22 & 16.1 & 13.6943 & 2.40572 \tabularnewline
23 & 9.9 & 12.0039 & -2.10389 \tabularnewline
24 & 11.5 & 12.6988 & -1.19878 \tabularnewline
25 & 8.3 & 12.2708 & -3.9708 \tabularnewline
26 & 11.7 & 13.6584 & -1.95836 \tabularnewline
27 & 9 & 12.6615 & -3.66153 \tabularnewline
28 & 10.8 & 12.7679 & -1.96786 \tabularnewline
29 & 10.4 & 12.2863 & -1.88625 \tabularnewline
30 & 12.7 & 12.7947 & -0.0946917 \tabularnewline
31 & 11.8 & 14.5675 & -2.76746 \tabularnewline
32 & 13 & 12.3669 & 0.633053 \tabularnewline
33 & 10.8 & 13.1605 & -2.3605 \tabularnewline
34 & 12.3 & 10.8001 & 1.49994 \tabularnewline
35 & 11.3 & 13.7895 & -2.48948 \tabularnewline
36 & 11.6 & 12.3444 & -0.744438 \tabularnewline
37 & 10.9 & 13.4416 & -2.54162 \tabularnewline
38 & 12.1 & 12.992 & -0.89196 \tabularnewline
39 & 13.3 & 13.6915 & -0.391518 \tabularnewline
40 & 10.1 & 13.5369 & -3.43689 \tabularnewline
41 & 14.3 & 12.612 & 1.68795 \tabularnewline
42 & 9.3 & 13.436 & -4.13601 \tabularnewline
43 & 12.5 & 11.9573 & 0.542666 \tabularnewline
44 & 7.6 & 11.3118 & -3.71179 \tabularnewline
45 & 9.2 & 12.0548 & -2.85482 \tabularnewline
46 & 14.5 & 13.1463 & 1.35371 \tabularnewline
47 & 12.3 & 13.8102 & -1.5102 \tabularnewline
48 & 12.6 & 13.3771 & -0.777067 \tabularnewline
49 & 13 & 14.0929 & -1.0929 \tabularnewline
50 & 12.6 & 11.5666 & 1.03338 \tabularnewline
51 & 13.2 & 15.0301 & -1.83009 \tabularnewline
52 & 7.7 & 11.9781 & -4.27809 \tabularnewline
53 & 10.5 & 11.0551 & -0.555149 \tabularnewline
54 & 10.9 & 12.209 & -1.30895 \tabularnewline
55 & 4.3 & 10.5846 & -6.28458 \tabularnewline
56 & 10.3 & 11.5777 & -1.27769 \tabularnewline
57 & 11.4 & 10.9814 & 0.418595 \tabularnewline
58 & 5.6 & 11.5208 & -5.92082 \tabularnewline
59 & 8.8 & 12.1155 & -3.31555 \tabularnewline
60 & 9 & 10.9019 & -1.90193 \tabularnewline
61 & 9.6 & 11.4932 & -1.89322 \tabularnewline
62 & 6.4 & 10.5231 & -4.1231 \tabularnewline
63 & 11.6 & 11.2524 & 0.347646 \tabularnewline
64 & 4.35 & 10.1579 & -5.80787 \tabularnewline
65 & 12.7 & 12.7322 & -0.0321703 \tabularnewline
66 & 18.1 & 14.8253 & 3.27474 \tabularnewline
67 & 17.85 & 15.1172 & 2.73276 \tabularnewline
68 & 16.6 & 16.2869 & 0.313079 \tabularnewline
69 & 12.6 & 10.2569 & 2.34309 \tabularnewline
70 & 17.1 & 21.6045 & -4.50448 \tabularnewline
71 & 19.1 & 15.6926 & 3.40737 \tabularnewline
72 & 16.1 & 18.7853 & -2.68528 \tabularnewline
73 & 13.35 & 10.8038 & 2.5462 \tabularnewline
74 & 18.4 & 17.4616 & 0.938445 \tabularnewline
75 & 14.7 & 11.1183 & 3.58167 \tabularnewline
76 & 10.6 & 14.6527 & -4.05274 \tabularnewline
77 & 12.6 & 13.769 & -1.16897 \tabularnewline
78 & 16.2 & 15.0933 & 1.10674 \tabularnewline
79 & 13.6 & 17.0125 & -3.41255 \tabularnewline
80 & 18.9 & 15.6782 & 3.22176 \tabularnewline
81 & 14.1 & 12.4303 & 1.66968 \tabularnewline
82 & 14.5 & 12.0555 & 2.44452 \tabularnewline
83 & 16.15 & 17.9157 & -1.76572 \tabularnewline
84 & 14.75 & 13.5593 & 1.19065 \tabularnewline
85 & 14.8 & 14.2501 & 0.549855 \tabularnewline
86 & 12.45 & 12.4064 & 0.0435574 \tabularnewline
87 & 12.65 & 14.6034 & -1.95343 \tabularnewline
88 & 17.35 & 13.8664 & 3.48357 \tabularnewline
89 & 8.6 & 12.0785 & -3.47854 \tabularnewline
90 & 18.4 & 17.594 & 0.806004 \tabularnewline
91 & 16.1 & 17.8462 & -1.74622 \tabularnewline
92 & 11.6 & 11.3623 & 0.237736 \tabularnewline
93 & 17.75 & 12.2872 & 5.46277 \tabularnewline
94 & 15.25 & 13.9937 & 1.25629 \tabularnewline
95 & 17.65 & 16.0891 & 1.56085 \tabularnewline
96 & 15.6 & 13.7818 & 1.81823 \tabularnewline
97 & 16.35 & 15.1518 & 1.19825 \tabularnewline
98 & 17.65 & 15.1756 & 2.47438 \tabularnewline
99 & 13.6 & 13.1218 & 0.478184 \tabularnewline
100 & 11.7 & 12.4699 & -0.769867 \tabularnewline
101 & 14.35 & 13.62 & 0.73003 \tabularnewline
102 & 14.75 & 17.4518 & -2.70177 \tabularnewline
103 & 18.25 & 16.2115 & 2.03846 \tabularnewline
104 & 9.9 & 15.2524 & -5.35238 \tabularnewline
105 & 16 & 14.3338 & 1.66625 \tabularnewline
106 & 18.25 & 15.6271 & 2.62288 \tabularnewline
107 & 16.85 & 17.2091 & -0.35908 \tabularnewline
108 & 14.6 & 12.5648 & 2.03522 \tabularnewline
109 & 13.85 & 14.0101 & -0.16012 \tabularnewline
110 & 18.95 & 16.5099 & 2.4401 \tabularnewline
111 & 15.6 & 14.5687 & 1.03131 \tabularnewline
112 & 14.85 & 17.2398 & -2.38982 \tabularnewline
113 & 11.75 & 12.4636 & -0.713625 \tabularnewline
114 & 18.45 & 13.3383 & 5.11165 \tabularnewline
115 & 15.9 & 17.0503 & -1.15034 \tabularnewline
116 & 17.1 & 14.4954 & 2.60465 \tabularnewline
117 & 16.1 & 10.936 & 5.16403 \tabularnewline
118 & 19.9 & 14.9884 & 4.91156 \tabularnewline
119 & 10.95 & 10.4328 & 0.517155 \tabularnewline
120 & 18.45 & 15.8425 & 2.60748 \tabularnewline
121 & 15.1 & 10.7179 & 4.38205 \tabularnewline
122 & 15 & 15.2845 & -0.284538 \tabularnewline
123 & 11.35 & 14.1903 & -2.84034 \tabularnewline
124 & 15.95 & 14.9929 & 0.957102 \tabularnewline
125 & 18.1 & 13.4973 & 4.60267 \tabularnewline
126 & 14.6 & 13.1813 & 1.41874 \tabularnewline
127 & 15.4 & 15.9828 & -0.582781 \tabularnewline
128 & 15.4 & 15.9828 & -0.582781 \tabularnewline
129 & 17.6 & 13.7775 & 3.8225 \tabularnewline
130 & 13.35 & 14.0202 & -0.670247 \tabularnewline
131 & 19.1 & 16.5518 & 2.54822 \tabularnewline
132 & 15.35 & 13.3898 & 1.96024 \tabularnewline
133 & 7.6 & 12.1374 & -4.53744 \tabularnewline
134 & 13.4 & 14.186 & -0.78595 \tabularnewline
135 & 13.9 & 13.6453 & 0.254702 \tabularnewline
136 & 19.1 & 17.1204 & 1.97962 \tabularnewline
137 & 15.25 & 14.0213 & 1.22872 \tabularnewline
138 & 12.9 & 12.409 & 0.491048 \tabularnewline
139 & 16.1 & 13.9956 & 2.10443 \tabularnewline
140 & 17.35 & 12.3703 & 4.97971 \tabularnewline
141 & 13.15 & 12.5265 & 0.623528 \tabularnewline
142 & 12.15 & 10.0234 & 2.12656 \tabularnewline
143 & 12.6 & 12.6971 & -0.0971085 \tabularnewline
144 & 10.35 & 11.6153 & -1.26529 \tabularnewline
145 & 15.4 & 13.0616 & 2.33837 \tabularnewline
146 & 9.6 & 11.1557 & -1.55573 \tabularnewline
147 & 18.2 & 13.3531 & 4.84687 \tabularnewline
148 & 13.6 & 12.2599 & 1.34011 \tabularnewline
149 & 14.85 & 14.4697 & 0.380253 \tabularnewline
150 & 14.75 & 16.9265 & -2.1765 \tabularnewline
151 & 14.1 & 13.9117 & 0.188289 \tabularnewline
152 & 14.9 & 11.3947 & 3.50527 \tabularnewline
153 & 16.25 & 12.951 & 3.299 \tabularnewline
154 & 19.25 & 17.4478 & 1.80218 \tabularnewline
155 & 13.6 & 12.066 & 1.53404 \tabularnewline
156 & 13.6 & 13.5012 & 0.0987755 \tabularnewline
157 & 15.65 & 15.1295 & 0.520521 \tabularnewline
158 & 12.75 & 12.298 & 0.45199 \tabularnewline
159 & 14.6 & 11.1879 & 3.41208 \tabularnewline
160 & 9.85 & 13.2665 & -3.41653 \tabularnewline
161 & 12.65 & 11.2273 & 1.42269 \tabularnewline
162 & 11.9 & 12.2228 & -0.322842 \tabularnewline
163 & 19.2 & 16.6338 & 2.5662 \tabularnewline
164 & 16.6 & 14.3226 & 2.27745 \tabularnewline
165 & 11.2 & 10.302 & 0.898035 \tabularnewline
166 & 15.25 & 13.2708 & 1.97918 \tabularnewline
167 & 11.9 & 15.1973 & -3.29735 \tabularnewline
168 & 13.2 & 15.4947 & -2.29468 \tabularnewline
169 & 16.35 & 17.2291 & -0.879124 \tabularnewline
170 & 12.4 & 13.4261 & -1.02613 \tabularnewline
171 & 15.85 & 13.0722 & 2.77779 \tabularnewline
172 & 14.35 & 13.6106 & 0.739378 \tabularnewline
173 & 18.15 & 15.1072 & 3.04277 \tabularnewline
174 & 11.15 & 11.6507 & -0.500713 \tabularnewline
175 & 15.65 & 15.4291 & 0.220894 \tabularnewline
176 & 17.75 & 16.0025 & 1.74751 \tabularnewline
177 & 7.65 & 12.5279 & -4.87791 \tabularnewline
178 & 12.35 & 11.9823 & 0.367692 \tabularnewline
179 & 15.6 & 11.7784 & 3.82156 \tabularnewline
180 & 19.3 & 16.3446 & 2.95543 \tabularnewline
181 & 15.2 & 11.8342 & 3.36582 \tabularnewline
182 & 17.1 & 13.5288 & 3.57121 \tabularnewline
183 & 15.6 & 12.5843 & 3.01572 \tabularnewline
184 & 18.4 & 15.3445 & 3.05549 \tabularnewline
185 & 19.05 & 15.2272 & 3.82278 \tabularnewline
186 & 18.55 & 13.3424 & 5.20763 \tabularnewline
187 & 19.1 & 17.0327 & 2.0673 \tabularnewline
188 & 13.1 & 11.932 & 1.16797 \tabularnewline
189 & 12.85 & 13.3677 & -0.517736 \tabularnewline
190 & 9.5 & 11.7643 & -2.26425 \tabularnewline
191 & 4.5 & 11.2881 & -6.78806 \tabularnewline
192 & 11.85 & 10.6692 & 1.18084 \tabularnewline
193 & 13.6 & 15.7331 & -2.13311 \tabularnewline
194 & 11.7 & 13.4374 & -1.73742 \tabularnewline
195 & 12.4 & 11.6027 & 0.797334 \tabularnewline
196 & 13.35 & 14.9339 & -1.58388 \tabularnewline
197 & 11.4 & 13.8148 & -2.41479 \tabularnewline
198 & 14.9 & 11.8327 & 3.0673 \tabularnewline
199 & 19.9 & 14.9884 & 4.91156 \tabularnewline
200 & 17.75 & 12.2012 & 5.54884 \tabularnewline
201 & 11.2 & 11.7844 & -0.584406 \tabularnewline
202 & 14.6 & 15.4309 & -0.830858 \tabularnewline
203 & 17.6 & 16.333 & 1.26705 \tabularnewline
204 & 14.05 & 12.5018 & 1.54818 \tabularnewline
205 & 16.1 & 15.4817 & 0.61834 \tabularnewline
206 & 13.35 & 13.2956 & 0.0544497 \tabularnewline
207 & 11.85 & 12.5171 & -0.667141 \tabularnewline
208 & 11.95 & 14.3972 & -2.44723 \tabularnewline
209 & 14.75 & 14.6776 & 0.0724019 \tabularnewline
210 & 15.15 & 13.4 & 1.75005 \tabularnewline
211 & 13.2 & 13.952 & -0.752009 \tabularnewline
212 & 16.85 & 15.4043 & 1.44569 \tabularnewline
213 & 7.85 & 10.424 & -2.57402 \tabularnewline
214 & 7.7 & 14.4728 & -6.77281 \tabularnewline
215 & 12.6 & 11.8543 & 0.745671 \tabularnewline
216 & 7.85 & 11.7718 & -3.9218 \tabularnewline
217 & 10.95 & 10.4328 & 0.517155 \tabularnewline
218 & 12.35 & 12.1991 & 0.150851 \tabularnewline
219 & 9.95 & 12.5474 & -2.59736 \tabularnewline
220 & 14.9 & 11.8327 & 3.0673 \tabularnewline
221 & 16.65 & 14.5437 & 2.10628 \tabularnewline
222 & 13.4 & 13.0623 & 0.337723 \tabularnewline
223 & 13.95 & 13.3182 & 0.631819 \tabularnewline
224 & 15.7 & 11.7228 & 3.97722 \tabularnewline
225 & 16.85 & 12.5764 & 4.27361 \tabularnewline
226 & 10.95 & 10.6794 & 0.270612 \tabularnewline
227 & 15.35 & 11.8603 & 3.48967 \tabularnewline
228 & 12.2 & 11.2625 & 0.937454 \tabularnewline
229 & 15.1 & 14.1784 & 0.921636 \tabularnewline
230 & 17.75 & 16.3291 & 1.42094 \tabularnewline
231 & 15.2 & 13.0362 & 2.16376 \tabularnewline
232 & 14.6 & 13.3778 & 1.22216 \tabularnewline
233 & 16.65 & 14.7874 & 1.86262 \tabularnewline
234 & 8.1 & 10.8507 & -2.75075 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.7205[/C][C]0.179464[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]12.5154[/C][C]0.284567[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.2655[/C][C]-5.86552[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]11.8105[/C][C]-5.11048[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]15.5761[/C][C]-2.97613[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.2789[/C][C]1.52113[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]12.7875[/C][C]0.51247[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.1757[/C][C]-2.07572[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]14.4481[/C][C]-6.24812[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.4024[/C][C]-2.00242[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]14.9076[/C][C]-8.50758[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]14.1372[/C][C]-2.13722[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]10.0845[/C][C]-3.78449[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]11.6277[/C][C]-0.327698[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]14.2491[/C][C]-2.34906[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]12.4417[/C][C]-3.14173[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]12.0894[/C][C]-2.08943[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]12.8245[/C][C]0.975474[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.8662[/C][C]-3.06624[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.1079[/C][C]-1.40795[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]15.6992[/C][C]-4.79917[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.6943[/C][C]2.40572[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]12.0039[/C][C]-2.10389[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]12.6988[/C][C]-1.19878[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]12.2708[/C][C]-3.9708[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.6584[/C][C]-1.95836[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]12.6615[/C][C]-3.66153[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]12.7679[/C][C]-1.96786[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]12.2863[/C][C]-1.88625[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]12.7947[/C][C]-0.0946917[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]14.5675[/C][C]-2.76746[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.3669[/C][C]0.633053[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]13.1605[/C][C]-2.3605[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]10.8001[/C][C]1.49994[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.7895[/C][C]-2.48948[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]12.3444[/C][C]-0.744438[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.4416[/C][C]-2.54162[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]12.992[/C][C]-0.89196[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.6915[/C][C]-0.391518[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.5369[/C][C]-3.43689[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]12.612[/C][C]1.68795[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.436[/C][C]-4.13601[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]11.9573[/C][C]0.542666[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]11.3118[/C][C]-3.71179[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]12.0548[/C][C]-2.85482[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.1463[/C][C]1.35371[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.8102[/C][C]-1.5102[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.3771[/C][C]-0.777067[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]14.0929[/C][C]-1.0929[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]11.5666[/C][C]1.03338[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]15.0301[/C][C]-1.83009[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]11.9781[/C][C]-4.27809[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]11.0551[/C][C]-0.555149[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]12.209[/C][C]-1.30895[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]10.5846[/C][C]-6.28458[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]11.5777[/C][C]-1.27769[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]10.9814[/C][C]0.418595[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]11.5208[/C][C]-5.92082[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]12.1155[/C][C]-3.31555[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]10.9019[/C][C]-1.90193[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]11.4932[/C][C]-1.89322[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]10.5231[/C][C]-4.1231[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]11.2524[/C][C]0.347646[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]10.1579[/C][C]-5.80787[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]12.7322[/C][C]-0.0321703[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]14.8253[/C][C]3.27474[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]15.1172[/C][C]2.73276[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]16.2869[/C][C]0.313079[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]10.2569[/C][C]2.34309[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]21.6045[/C][C]-4.50448[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]15.6926[/C][C]3.40737[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]18.7853[/C][C]-2.68528[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]10.8038[/C][C]2.5462[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]17.4616[/C][C]0.938445[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]11.1183[/C][C]3.58167[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]14.6527[/C][C]-4.05274[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.769[/C][C]-1.16897[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]15.0933[/C][C]1.10674[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]17.0125[/C][C]-3.41255[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]15.6782[/C][C]3.22176[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]12.4303[/C][C]1.66968[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]12.0555[/C][C]2.44452[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]17.9157[/C][C]-1.76572[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.5593[/C][C]1.19065[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]14.2501[/C][C]0.549855[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]12.4064[/C][C]0.0435574[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]14.6034[/C][C]-1.95343[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.8664[/C][C]3.48357[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.0785[/C][C]-3.47854[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]17.594[/C][C]0.806004[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]17.8462[/C][C]-1.74622[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]11.3623[/C][C]0.237736[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]12.2872[/C][C]5.46277[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]13.9937[/C][C]1.25629[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]16.0891[/C][C]1.56085[/C][/ROW]
[ROW][C]96[/C][C]15.6[/C][C]13.7818[/C][C]1.81823[/C][/ROW]
[ROW][C]97[/C][C]16.35[/C][C]15.1518[/C][C]1.19825[/C][/ROW]
[ROW][C]98[/C][C]17.65[/C][C]15.1756[/C][C]2.47438[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]13.1218[/C][C]0.478184[/C][/ROW]
[ROW][C]100[/C][C]11.7[/C][C]12.4699[/C][C]-0.769867[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.62[/C][C]0.73003[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]17.4518[/C][C]-2.70177[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]16.2115[/C][C]2.03846[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]15.2524[/C][C]-5.35238[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]14.3338[/C][C]1.66625[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]15.6271[/C][C]2.62288[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]17.2091[/C][C]-0.35908[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]12.5648[/C][C]2.03522[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]14.0101[/C][C]-0.16012[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.5099[/C][C]2.4401[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.5687[/C][C]1.03131[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]17.2398[/C][C]-2.38982[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]12.4636[/C][C]-0.713625[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]13.3383[/C][C]5.11165[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]17.0503[/C][C]-1.15034[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.4954[/C][C]2.60465[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]10.936[/C][C]5.16403[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]14.9884[/C][C]4.91156[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]10.4328[/C][C]0.517155[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]15.8425[/C][C]2.60748[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]10.7179[/C][C]4.38205[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]15.2845[/C][C]-0.284538[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]14.1903[/C][C]-2.84034[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]14.9929[/C][C]0.957102[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]13.4973[/C][C]4.60267[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.1813[/C][C]1.41874[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]15.9828[/C][C]-0.582781[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]15.9828[/C][C]-0.582781[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]13.7775[/C][C]3.8225[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]14.0202[/C][C]-0.670247[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]16.5518[/C][C]2.54822[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]13.3898[/C][C]1.96024[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]12.1374[/C][C]-4.53744[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]14.186[/C][C]-0.78595[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]13.6453[/C][C]0.254702[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.1204[/C][C]1.97962[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]14.0213[/C][C]1.22872[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]12.409[/C][C]0.491048[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]13.9956[/C][C]2.10443[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]12.3703[/C][C]4.97971[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]12.5265[/C][C]0.623528[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]10.0234[/C][C]2.12656[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]12.6971[/C][C]-0.0971085[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]11.6153[/C][C]-1.26529[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]13.0616[/C][C]2.33837[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]11.1557[/C][C]-1.55573[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]13.3531[/C][C]4.84687[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.2599[/C][C]1.34011[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]14.4697[/C][C]0.380253[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]16.9265[/C][C]-2.1765[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]13.9117[/C][C]0.188289[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]11.3947[/C][C]3.50527[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]12.951[/C][C]3.299[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]17.4478[/C][C]1.80218[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]12.066[/C][C]1.53404[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]13.5012[/C][C]0.0987755[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.1295[/C][C]0.520521[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]12.298[/C][C]0.45199[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]11.1879[/C][C]3.41208[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]13.2665[/C][C]-3.41653[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]11.2273[/C][C]1.42269[/C][/ROW]
[ROW][C]162[/C][C]11.9[/C][C]12.2228[/C][C]-0.322842[/C][/ROW]
[ROW][C]163[/C][C]19.2[/C][C]16.6338[/C][C]2.5662[/C][/ROW]
[ROW][C]164[/C][C]16.6[/C][C]14.3226[/C][C]2.27745[/C][/ROW]
[ROW][C]165[/C][C]11.2[/C][C]10.302[/C][C]0.898035[/C][/ROW]
[ROW][C]166[/C][C]15.25[/C][C]13.2708[/C][C]1.97918[/C][/ROW]
[ROW][C]167[/C][C]11.9[/C][C]15.1973[/C][C]-3.29735[/C][/ROW]
[ROW][C]168[/C][C]13.2[/C][C]15.4947[/C][C]-2.29468[/C][/ROW]
[ROW][C]169[/C][C]16.35[/C][C]17.2291[/C][C]-0.879124[/C][/ROW]
[ROW][C]170[/C][C]12.4[/C][C]13.4261[/C][C]-1.02613[/C][/ROW]
[ROW][C]171[/C][C]15.85[/C][C]13.0722[/C][C]2.77779[/C][/ROW]
[ROW][C]172[/C][C]14.35[/C][C]13.6106[/C][C]0.739378[/C][/ROW]
[ROW][C]173[/C][C]18.15[/C][C]15.1072[/C][C]3.04277[/C][/ROW]
[ROW][C]174[/C][C]11.15[/C][C]11.6507[/C][C]-0.500713[/C][/ROW]
[ROW][C]175[/C][C]15.65[/C][C]15.4291[/C][C]0.220894[/C][/ROW]
[ROW][C]176[/C][C]17.75[/C][C]16.0025[/C][C]1.74751[/C][/ROW]
[ROW][C]177[/C][C]7.65[/C][C]12.5279[/C][C]-4.87791[/C][/ROW]
[ROW][C]178[/C][C]12.35[/C][C]11.9823[/C][C]0.367692[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]11.7784[/C][C]3.82156[/C][/ROW]
[ROW][C]180[/C][C]19.3[/C][C]16.3446[/C][C]2.95543[/C][/ROW]
[ROW][C]181[/C][C]15.2[/C][C]11.8342[/C][C]3.36582[/C][/ROW]
[ROW][C]182[/C][C]17.1[/C][C]13.5288[/C][C]3.57121[/C][/ROW]
[ROW][C]183[/C][C]15.6[/C][C]12.5843[/C][C]3.01572[/C][/ROW]
[ROW][C]184[/C][C]18.4[/C][C]15.3445[/C][C]3.05549[/C][/ROW]
[ROW][C]185[/C][C]19.05[/C][C]15.2272[/C][C]3.82278[/C][/ROW]
[ROW][C]186[/C][C]18.55[/C][C]13.3424[/C][C]5.20763[/C][/ROW]
[ROW][C]187[/C][C]19.1[/C][C]17.0327[/C][C]2.0673[/C][/ROW]
[ROW][C]188[/C][C]13.1[/C][C]11.932[/C][C]1.16797[/C][/ROW]
[ROW][C]189[/C][C]12.85[/C][C]13.3677[/C][C]-0.517736[/C][/ROW]
[ROW][C]190[/C][C]9.5[/C][C]11.7643[/C][C]-2.26425[/C][/ROW]
[ROW][C]191[/C][C]4.5[/C][C]11.2881[/C][C]-6.78806[/C][/ROW]
[ROW][C]192[/C][C]11.85[/C][C]10.6692[/C][C]1.18084[/C][/ROW]
[ROW][C]193[/C][C]13.6[/C][C]15.7331[/C][C]-2.13311[/C][/ROW]
[ROW][C]194[/C][C]11.7[/C][C]13.4374[/C][C]-1.73742[/C][/ROW]
[ROW][C]195[/C][C]12.4[/C][C]11.6027[/C][C]0.797334[/C][/ROW]
[ROW][C]196[/C][C]13.35[/C][C]14.9339[/C][C]-1.58388[/C][/ROW]
[ROW][C]197[/C][C]11.4[/C][C]13.8148[/C][C]-2.41479[/C][/ROW]
[ROW][C]198[/C][C]14.9[/C][C]11.8327[/C][C]3.0673[/C][/ROW]
[ROW][C]199[/C][C]19.9[/C][C]14.9884[/C][C]4.91156[/C][/ROW]
[ROW][C]200[/C][C]17.75[/C][C]12.2012[/C][C]5.54884[/C][/ROW]
[ROW][C]201[/C][C]11.2[/C][C]11.7844[/C][C]-0.584406[/C][/ROW]
[ROW][C]202[/C][C]14.6[/C][C]15.4309[/C][C]-0.830858[/C][/ROW]
[ROW][C]203[/C][C]17.6[/C][C]16.333[/C][C]1.26705[/C][/ROW]
[ROW][C]204[/C][C]14.05[/C][C]12.5018[/C][C]1.54818[/C][/ROW]
[ROW][C]205[/C][C]16.1[/C][C]15.4817[/C][C]0.61834[/C][/ROW]
[ROW][C]206[/C][C]13.35[/C][C]13.2956[/C][C]0.0544497[/C][/ROW]
[ROW][C]207[/C][C]11.85[/C][C]12.5171[/C][C]-0.667141[/C][/ROW]
[ROW][C]208[/C][C]11.95[/C][C]14.3972[/C][C]-2.44723[/C][/ROW]
[ROW][C]209[/C][C]14.75[/C][C]14.6776[/C][C]0.0724019[/C][/ROW]
[ROW][C]210[/C][C]15.15[/C][C]13.4[/C][C]1.75005[/C][/ROW]
[ROW][C]211[/C][C]13.2[/C][C]13.952[/C][C]-0.752009[/C][/ROW]
[ROW][C]212[/C][C]16.85[/C][C]15.4043[/C][C]1.44569[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]10.424[/C][C]-2.57402[/C][/ROW]
[ROW][C]214[/C][C]7.7[/C][C]14.4728[/C][C]-6.77281[/C][/ROW]
[ROW][C]215[/C][C]12.6[/C][C]11.8543[/C][C]0.745671[/C][/ROW]
[ROW][C]216[/C][C]7.85[/C][C]11.7718[/C][C]-3.9218[/C][/ROW]
[ROW][C]217[/C][C]10.95[/C][C]10.4328[/C][C]0.517155[/C][/ROW]
[ROW][C]218[/C][C]12.35[/C][C]12.1991[/C][C]0.150851[/C][/ROW]
[ROW][C]219[/C][C]9.95[/C][C]12.5474[/C][C]-2.59736[/C][/ROW]
[ROW][C]220[/C][C]14.9[/C][C]11.8327[/C][C]3.0673[/C][/ROW]
[ROW][C]221[/C][C]16.65[/C][C]14.5437[/C][C]2.10628[/C][/ROW]
[ROW][C]222[/C][C]13.4[/C][C]13.0623[/C][C]0.337723[/C][/ROW]
[ROW][C]223[/C][C]13.95[/C][C]13.3182[/C][C]0.631819[/C][/ROW]
[ROW][C]224[/C][C]15.7[/C][C]11.7228[/C][C]3.97722[/C][/ROW]
[ROW][C]225[/C][C]16.85[/C][C]12.5764[/C][C]4.27361[/C][/ROW]
[ROW][C]226[/C][C]10.95[/C][C]10.6794[/C][C]0.270612[/C][/ROW]
[ROW][C]227[/C][C]15.35[/C][C]11.8603[/C][C]3.48967[/C][/ROW]
[ROW][C]228[/C][C]12.2[/C][C]11.2625[/C][C]0.937454[/C][/ROW]
[ROW][C]229[/C][C]15.1[/C][C]14.1784[/C][C]0.921636[/C][/ROW]
[ROW][C]230[/C][C]17.75[/C][C]16.3291[/C][C]1.42094[/C][/ROW]
[ROW][C]231[/C][C]15.2[/C][C]13.0362[/C][C]2.16376[/C][/ROW]
[ROW][C]232[/C][C]14.6[/C][C]13.3778[/C][C]1.22216[/C][/ROW]
[ROW][C]233[/C][C]16.65[/C][C]14.7874[/C][C]1.86262[/C][/ROW]
[ROW][C]234[/C][C]8.1[/C][C]10.8507[/C][C]-2.75075[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.72050.179464
212.812.51540.284567
37.413.2655-5.86552
46.711.8105-5.11048
512.615.5761-2.97613
614.813.27891.52113
713.312.78750.51247
811.113.1757-2.07572
98.214.4481-6.24812
1011.413.4024-2.00242
116.414.9076-8.50758
121214.1372-2.13722
136.310.0845-3.78449
1411.311.6277-0.327698
1511.914.2491-2.34906
169.312.4417-3.14173
171012.0894-2.08943
1813.812.82450.975474
1910.813.8662-3.06624
2011.713.1079-1.40795
2110.915.6992-4.79917
2216.113.69432.40572
239.912.0039-2.10389
2411.512.6988-1.19878
258.312.2708-3.9708
2611.713.6584-1.95836
27912.6615-3.66153
2810.812.7679-1.96786
2910.412.2863-1.88625
3012.712.7947-0.0946917
3111.814.5675-2.76746
321312.36690.633053
3310.813.1605-2.3605
3412.310.80011.49994
3511.313.7895-2.48948
3611.612.3444-0.744438
3710.913.4416-2.54162
3812.112.992-0.89196
3913.313.6915-0.391518
4010.113.5369-3.43689
4114.312.6121.68795
429.313.436-4.13601
4312.511.95730.542666
447.611.3118-3.71179
459.212.0548-2.85482
4614.513.14631.35371
4712.313.8102-1.5102
4812.613.3771-0.777067
491314.0929-1.0929
5012.611.56661.03338
5113.215.0301-1.83009
527.711.9781-4.27809
5310.511.0551-0.555149
5410.912.209-1.30895
554.310.5846-6.28458
5610.311.5777-1.27769
5711.410.98140.418595
585.611.5208-5.92082
598.812.1155-3.31555
60910.9019-1.90193
619.611.4932-1.89322
626.410.5231-4.1231
6311.611.25240.347646
644.3510.1579-5.80787
6512.712.7322-0.0321703
6618.114.82533.27474
6717.8515.11722.73276
6816.616.28690.313079
6912.610.25692.34309
7017.121.6045-4.50448
7119.115.69263.40737
7216.118.7853-2.68528
7313.3510.80382.5462
7418.417.46160.938445
7514.711.11833.58167
7610.614.6527-4.05274
7712.613.769-1.16897
7816.215.09331.10674
7913.617.0125-3.41255
8018.915.67823.22176
8114.112.43031.66968
8214.512.05552.44452
8316.1517.9157-1.76572
8414.7513.55931.19065
8514.814.25010.549855
8612.4512.40640.0435574
8712.6514.6034-1.95343
8817.3513.86643.48357
898.612.0785-3.47854
9018.417.5940.806004
9116.117.8462-1.74622
9211.611.36230.237736
9317.7512.28725.46277
9415.2513.99371.25629
9517.6516.08911.56085
9615.613.78181.81823
9716.3515.15181.19825
9817.6515.17562.47438
9913.613.12180.478184
10011.712.4699-0.769867
10114.3513.620.73003
10214.7517.4518-2.70177
10318.2516.21152.03846
1049.915.2524-5.35238
1051614.33381.66625
10618.2515.62712.62288
10716.8517.2091-0.35908
10814.612.56482.03522
10913.8514.0101-0.16012
11018.9516.50992.4401
11115.614.56871.03131
11214.8517.2398-2.38982
11311.7512.4636-0.713625
11418.4513.33835.11165
11515.917.0503-1.15034
11617.114.49542.60465
11716.110.9365.16403
11819.914.98844.91156
11910.9510.43280.517155
12018.4515.84252.60748
12115.110.71794.38205
1221515.2845-0.284538
12311.3514.1903-2.84034
12415.9514.99290.957102
12518.113.49734.60267
12614.613.18131.41874
12715.415.9828-0.582781
12815.415.9828-0.582781
12917.613.77753.8225
13013.3514.0202-0.670247
13119.116.55182.54822
13215.3513.38981.96024
1337.612.1374-4.53744
13413.414.186-0.78595
13513.913.64530.254702
13619.117.12041.97962
13715.2514.02131.22872
13812.912.4090.491048
13916.113.99562.10443
14017.3512.37034.97971
14113.1512.52650.623528
14212.1510.02342.12656
14312.612.6971-0.0971085
14410.3511.6153-1.26529
14515.413.06162.33837
1469.611.1557-1.55573
14718.213.35314.84687
14813.612.25991.34011
14914.8514.46970.380253
15014.7516.9265-2.1765
15114.113.91170.188289
15214.911.39473.50527
15316.2512.9513.299
15419.2517.44781.80218
15513.612.0661.53404
15613.613.50120.0987755
15715.6515.12950.520521
15812.7512.2980.45199
15914.611.18793.41208
1609.8513.2665-3.41653
16112.6511.22731.42269
16211.912.2228-0.322842
16319.216.63382.5662
16416.614.32262.27745
16511.210.3020.898035
16615.2513.27081.97918
16711.915.1973-3.29735
16813.215.4947-2.29468
16916.3517.2291-0.879124
17012.413.4261-1.02613
17115.8513.07222.77779
17214.3513.61060.739378
17318.1515.10723.04277
17411.1511.6507-0.500713
17515.6515.42910.220894
17617.7516.00251.74751
1777.6512.5279-4.87791
17812.3511.98230.367692
17915.611.77843.82156
18019.316.34462.95543
18115.211.83423.36582
18217.113.52883.57121
18315.612.58433.01572
18418.415.34453.05549
18519.0515.22723.82278
18618.5513.34245.20763
18719.117.03272.0673
18813.111.9321.16797
18912.8513.3677-0.517736
1909.511.7643-2.26425
1914.511.2881-6.78806
19211.8510.66921.18084
19313.615.7331-2.13311
19411.713.4374-1.73742
19512.411.60270.797334
19613.3514.9339-1.58388
19711.413.8148-2.41479
19814.911.83273.0673
19919.914.98844.91156
20017.7512.20125.54884
20111.211.7844-0.584406
20214.615.4309-0.830858
20317.616.3331.26705
20414.0512.50181.54818
20516.115.48170.61834
20613.3513.29560.0544497
20711.8512.5171-0.667141
20811.9514.3972-2.44723
20914.7514.67760.0724019
21015.1513.41.75005
21113.213.952-0.752009
21216.8515.40431.44569
2137.8510.424-2.57402
2147.714.4728-6.77281
21512.611.85430.745671
2167.8511.7718-3.9218
21710.9510.43280.517155
21812.3512.19910.150851
2199.9512.5474-2.59736
22014.911.83273.0673
22116.6514.54372.10628
22213.413.06230.337723
22313.9513.31820.631819
22415.711.72283.97722
22516.8512.57644.27361
22610.9510.67940.270612
22715.3511.86033.48967
22812.211.26250.937454
22915.114.17840.921636
23017.7516.32911.42094
23115.213.03622.16376
23214.613.37781.22216
23316.6514.78741.86262
2348.110.8507-2.75075






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.8748370.2503260.125163
80.8387250.322550.161275
90.8787570.2424860.121243
100.8150460.3699080.184954
110.8515280.2969440.148472
120.7880220.4239550.211978
130.7430330.5139330.256967
140.7498620.5002750.250138
150.6904540.6190920.309546
160.6195250.760950.380475
170.5423290.9153430.457671
180.4755920.9511850.524408
190.4212580.8425150.578742
200.3555330.7110650.644467
210.3173990.6347980.682601
220.2770010.5540010.722999
230.2399970.4799940.760003
240.21790.43580.7821
250.1820150.364030.817985
260.1824680.3649360.817532
270.1520130.3040260.847987
280.1267560.2535120.873244
290.1011580.2023150.898842
300.1186930.2373860.881307
310.1065760.2131530.893424
320.08555840.1711170.914442
330.0693320.1386640.930668
340.07691710.1538340.923083
350.06364250.1272850.936357
360.05354530.1070910.946455
370.04918160.09836320.950818
380.04949620.09899230.950504
390.05202570.1040510.947974
400.04290.08580.9571
410.05915920.1183180.940841
420.07215810.1443160.927842
430.06227750.1245550.937723
440.07676780.1535360.923232
450.08363680.1672740.916363
460.09273590.1854720.907264
470.08205270.1641050.917947
480.07600920.1520180.923991
490.0698790.1397580.930121
500.06496790.1299360.935032
510.06611520.132230.933885
520.09825920.1965180.901741
530.08122930.1624590.918771
540.06695920.1339180.933041
550.18440.3688010.8156
560.1696960.3393930.830304
570.149370.2987410.85063
580.2571460.5142920.742854
590.2487540.4975080.751246
600.2414650.4829290.758535
610.2458640.4917270.754136
620.26710.5342010.7329
630.2664250.5328510.733575
640.4060860.8121720.593914
650.4240740.8481480.575926
660.6541410.6917180.345859
670.762180.475640.23782
680.7308920.5382160.269108
690.7886940.4226120.211306
700.7915090.4169820.208491
710.8306680.3386650.169332
720.8468770.3062470.153123
730.8815810.2368390.118419
740.8887820.2224370.111218
750.9302570.1394860.0697429
760.9416170.1167660.0583828
770.9322380.1355240.0677618
780.9333590.1332810.0666407
790.944530.110940.0554701
800.9535410.09291750.0464587
810.9534880.09302430.0465122
820.9601890.07962190.0398109
830.9598750.08025010.0401251
840.9564910.08701720.0435086
850.9495110.1009780.050489
860.9397340.1205330.0602663
870.9313190.1373630.0686813
880.9544290.09114240.0455712
890.955780.08844010.04422
900.9509310.09813850.0490693
910.9428240.1143530.0571764
920.9327910.1344170.0672086
930.9719250.056150.028075
940.9706840.05863220.0293161
950.9700710.05985730.0299286
960.969140.06171930.0308597
970.9654520.06909660.0345483
980.9663840.06723250.0336162
990.9609460.07810740.0390537
1000.9565280.08694460.0434723
1010.9491690.1016620.050831
1020.9444290.1111420.0555711
1030.9430490.1139010.0569507
1040.9778020.04439570.0221978
1050.9750820.04983550.0249177
1060.9761940.04761210.023806
1070.9712450.05751070.0287553
1080.9716770.0566470.0283235
1090.9650480.06990390.0349519
1100.9639370.0721260.036063
1110.9578020.08439630.0421982
1120.9554830.08903360.0445168
1130.9480250.1039490.0519746
1140.9687950.06240980.0312049
1150.9627930.07441330.0372066
1160.9625780.0748430.0374215
1170.9917160.01656710.00828357
1180.9941590.01168110.00584055
1190.9924410.01511740.00755871
1200.9924080.01518430.00759216
1210.9950380.009923280.00496164
1220.9934910.01301710.00650855
1230.9936750.012650.00632499
1240.9921960.01560720.00780358
1250.9949170.01016540.00508269
1260.9940930.01181380.00590692
1270.992790.01442080.0072104
1280.9913280.01734360.00867182
1290.993180.01363930.00681967
1300.9919860.01602720.00801358
1310.9917250.01654960.00827481
1320.9904030.01919430.00959715
1330.993740.012520.00626001
1340.9925820.01483540.0074177
1350.9906650.01866910.00933453
1360.9891340.02173260.0108663
1370.9866430.02671430.0133572
1380.9846640.03067270.0153363
1390.9823740.03525120.0176256
1400.9899170.02016680.0100834
1410.9874770.02504630.0125231
1420.9856410.02871770.0143589
1430.9818990.03620220.0181011
1440.9780570.04388630.0219432
1450.9754750.04904990.0245249
1460.9713970.05720510.0286025
1470.9819130.03617440.0180872
1480.978520.04295920.0214796
1490.974120.05176080.0258804
1500.9747230.05055350.0252768
1510.968260.063480.03174
1520.970740.05851960.0292598
1530.9708140.05837180.0291859
1540.9693130.06137320.0306866
1550.9670350.06592940.0329647
1560.9618610.07627740.0381387
1570.9530980.09380360.0469018
1580.9441550.111690.0558449
1590.9518480.09630420.0481521
1600.9506750.09864990.049325
1610.9481480.1037040.0518518
1620.9365430.1269140.0634572
1630.9345630.1308740.0654372
1640.928970.142060.0710302
1650.9193930.1612150.0806073
1660.9068270.1863470.0931733
1670.9246680.1506640.075332
1680.9118220.1763560.0881778
1690.9065390.1869210.0934605
1700.8936360.2127280.106364
1710.8905220.2189560.109478
1720.8783230.2433540.121677
1730.8659150.268170.134085
1740.8409730.3180550.159027
1750.8128830.3742350.187117
1760.785720.428560.21428
1770.8142420.3715150.185758
1780.7843790.4312410.215621
1790.7913830.4172330.208617
1800.7723630.4552750.227637
1810.8290720.3418560.170928
1820.8462230.3075540.153777
1830.8419770.3160450.158023
1840.8372880.3254250.162712
1850.8505420.2989160.149458
1860.8667160.2665670.133284
1870.8448770.3102460.155123
1880.821070.3578590.17893
1890.8218320.3563370.178168
1900.8100960.3798070.189904
1910.9239660.1520670.0760336
1920.9175620.1648750.0824377
1930.9388620.1222770.0611385
1940.9232170.1535650.0767825
1950.9023640.1952720.0976362
1960.8864170.2271670.113583
1970.8655020.2689960.134498
1980.8535020.2929960.146498
1990.8442510.3114970.155749
2000.9129050.1741890.0870945
2010.8906710.2186570.109329
2020.8681170.2637670.131883
2030.8338490.3323030.166151
2040.7951590.4096820.204841
2050.7492680.5014630.250732
2060.6978410.6043180.302159
2070.6710550.657890.328945
2080.6581940.6836110.341806
2090.5957340.8085320.404266
2100.5527880.8944230.447212
2110.6054750.789050.394525
2120.5440210.9119570.455979
2130.5334380.9331230.466562
2140.9430250.1139510.0569755
2150.915480.1690390.0845196
2160.996620.00675950.00337975
2170.9969860.006027580.00301379
2180.9955970.008805490.00440275
2190.9999390.0001213116.06557e-05
2200.9998050.0003895120.000194756
2210.9995540.0008921810.00044609
2220.999290.001419750.000709873
2230.9989240.002152260.00107613
2240.996280.007440490.00372025
2250.9973510.005297840.00264892
2260.9900760.01984870.00992434
2270.9940380.01192310.00596156

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.874837 & 0.250326 & 0.125163 \tabularnewline
8 & 0.838725 & 0.32255 & 0.161275 \tabularnewline
9 & 0.878757 & 0.242486 & 0.121243 \tabularnewline
10 & 0.815046 & 0.369908 & 0.184954 \tabularnewline
11 & 0.851528 & 0.296944 & 0.148472 \tabularnewline
12 & 0.788022 & 0.423955 & 0.211978 \tabularnewline
13 & 0.743033 & 0.513933 & 0.256967 \tabularnewline
14 & 0.749862 & 0.500275 & 0.250138 \tabularnewline
15 & 0.690454 & 0.619092 & 0.309546 \tabularnewline
16 & 0.619525 & 0.76095 & 0.380475 \tabularnewline
17 & 0.542329 & 0.915343 & 0.457671 \tabularnewline
18 & 0.475592 & 0.951185 & 0.524408 \tabularnewline
19 & 0.421258 & 0.842515 & 0.578742 \tabularnewline
20 & 0.355533 & 0.711065 & 0.644467 \tabularnewline
21 & 0.317399 & 0.634798 & 0.682601 \tabularnewline
22 & 0.277001 & 0.554001 & 0.722999 \tabularnewline
23 & 0.239997 & 0.479994 & 0.760003 \tabularnewline
24 & 0.2179 & 0.4358 & 0.7821 \tabularnewline
25 & 0.182015 & 0.36403 & 0.817985 \tabularnewline
26 & 0.182468 & 0.364936 & 0.817532 \tabularnewline
27 & 0.152013 & 0.304026 & 0.847987 \tabularnewline
28 & 0.126756 & 0.253512 & 0.873244 \tabularnewline
29 & 0.101158 & 0.202315 & 0.898842 \tabularnewline
30 & 0.118693 & 0.237386 & 0.881307 \tabularnewline
31 & 0.106576 & 0.213153 & 0.893424 \tabularnewline
32 & 0.0855584 & 0.171117 & 0.914442 \tabularnewline
33 & 0.069332 & 0.138664 & 0.930668 \tabularnewline
34 & 0.0769171 & 0.153834 & 0.923083 \tabularnewline
35 & 0.0636425 & 0.127285 & 0.936357 \tabularnewline
36 & 0.0535453 & 0.107091 & 0.946455 \tabularnewline
37 & 0.0491816 & 0.0983632 & 0.950818 \tabularnewline
38 & 0.0494962 & 0.0989923 & 0.950504 \tabularnewline
39 & 0.0520257 & 0.104051 & 0.947974 \tabularnewline
40 & 0.0429 & 0.0858 & 0.9571 \tabularnewline
41 & 0.0591592 & 0.118318 & 0.940841 \tabularnewline
42 & 0.0721581 & 0.144316 & 0.927842 \tabularnewline
43 & 0.0622775 & 0.124555 & 0.937723 \tabularnewline
44 & 0.0767678 & 0.153536 & 0.923232 \tabularnewline
45 & 0.0836368 & 0.167274 & 0.916363 \tabularnewline
46 & 0.0927359 & 0.185472 & 0.907264 \tabularnewline
47 & 0.0820527 & 0.164105 & 0.917947 \tabularnewline
48 & 0.0760092 & 0.152018 & 0.923991 \tabularnewline
49 & 0.069879 & 0.139758 & 0.930121 \tabularnewline
50 & 0.0649679 & 0.129936 & 0.935032 \tabularnewline
51 & 0.0661152 & 0.13223 & 0.933885 \tabularnewline
52 & 0.0982592 & 0.196518 & 0.901741 \tabularnewline
53 & 0.0812293 & 0.162459 & 0.918771 \tabularnewline
54 & 0.0669592 & 0.133918 & 0.933041 \tabularnewline
55 & 0.1844 & 0.368801 & 0.8156 \tabularnewline
56 & 0.169696 & 0.339393 & 0.830304 \tabularnewline
57 & 0.14937 & 0.298741 & 0.85063 \tabularnewline
58 & 0.257146 & 0.514292 & 0.742854 \tabularnewline
59 & 0.248754 & 0.497508 & 0.751246 \tabularnewline
60 & 0.241465 & 0.482929 & 0.758535 \tabularnewline
61 & 0.245864 & 0.491727 & 0.754136 \tabularnewline
62 & 0.2671 & 0.534201 & 0.7329 \tabularnewline
63 & 0.266425 & 0.532851 & 0.733575 \tabularnewline
64 & 0.406086 & 0.812172 & 0.593914 \tabularnewline
65 & 0.424074 & 0.848148 & 0.575926 \tabularnewline
66 & 0.654141 & 0.691718 & 0.345859 \tabularnewline
67 & 0.76218 & 0.47564 & 0.23782 \tabularnewline
68 & 0.730892 & 0.538216 & 0.269108 \tabularnewline
69 & 0.788694 & 0.422612 & 0.211306 \tabularnewline
70 & 0.791509 & 0.416982 & 0.208491 \tabularnewline
71 & 0.830668 & 0.338665 & 0.169332 \tabularnewline
72 & 0.846877 & 0.306247 & 0.153123 \tabularnewline
73 & 0.881581 & 0.236839 & 0.118419 \tabularnewline
74 & 0.888782 & 0.222437 & 0.111218 \tabularnewline
75 & 0.930257 & 0.139486 & 0.0697429 \tabularnewline
76 & 0.941617 & 0.116766 & 0.0583828 \tabularnewline
77 & 0.932238 & 0.135524 & 0.0677618 \tabularnewline
78 & 0.933359 & 0.133281 & 0.0666407 \tabularnewline
79 & 0.94453 & 0.11094 & 0.0554701 \tabularnewline
80 & 0.953541 & 0.0929175 & 0.0464587 \tabularnewline
81 & 0.953488 & 0.0930243 & 0.0465122 \tabularnewline
82 & 0.960189 & 0.0796219 & 0.0398109 \tabularnewline
83 & 0.959875 & 0.0802501 & 0.0401251 \tabularnewline
84 & 0.956491 & 0.0870172 & 0.0435086 \tabularnewline
85 & 0.949511 & 0.100978 & 0.050489 \tabularnewline
86 & 0.939734 & 0.120533 & 0.0602663 \tabularnewline
87 & 0.931319 & 0.137363 & 0.0686813 \tabularnewline
88 & 0.954429 & 0.0911424 & 0.0455712 \tabularnewline
89 & 0.95578 & 0.0884401 & 0.04422 \tabularnewline
90 & 0.950931 & 0.0981385 & 0.0490693 \tabularnewline
91 & 0.942824 & 0.114353 & 0.0571764 \tabularnewline
92 & 0.932791 & 0.134417 & 0.0672086 \tabularnewline
93 & 0.971925 & 0.05615 & 0.028075 \tabularnewline
94 & 0.970684 & 0.0586322 & 0.0293161 \tabularnewline
95 & 0.970071 & 0.0598573 & 0.0299286 \tabularnewline
96 & 0.96914 & 0.0617193 & 0.0308597 \tabularnewline
97 & 0.965452 & 0.0690966 & 0.0345483 \tabularnewline
98 & 0.966384 & 0.0672325 & 0.0336162 \tabularnewline
99 & 0.960946 & 0.0781074 & 0.0390537 \tabularnewline
100 & 0.956528 & 0.0869446 & 0.0434723 \tabularnewline
101 & 0.949169 & 0.101662 & 0.050831 \tabularnewline
102 & 0.944429 & 0.111142 & 0.0555711 \tabularnewline
103 & 0.943049 & 0.113901 & 0.0569507 \tabularnewline
104 & 0.977802 & 0.0443957 & 0.0221978 \tabularnewline
105 & 0.975082 & 0.0498355 & 0.0249177 \tabularnewline
106 & 0.976194 & 0.0476121 & 0.023806 \tabularnewline
107 & 0.971245 & 0.0575107 & 0.0287553 \tabularnewline
108 & 0.971677 & 0.056647 & 0.0283235 \tabularnewline
109 & 0.965048 & 0.0699039 & 0.0349519 \tabularnewline
110 & 0.963937 & 0.072126 & 0.036063 \tabularnewline
111 & 0.957802 & 0.0843963 & 0.0421982 \tabularnewline
112 & 0.955483 & 0.0890336 & 0.0445168 \tabularnewline
113 & 0.948025 & 0.103949 & 0.0519746 \tabularnewline
114 & 0.968795 & 0.0624098 & 0.0312049 \tabularnewline
115 & 0.962793 & 0.0744133 & 0.0372066 \tabularnewline
116 & 0.962578 & 0.074843 & 0.0374215 \tabularnewline
117 & 0.991716 & 0.0165671 & 0.00828357 \tabularnewline
118 & 0.994159 & 0.0116811 & 0.00584055 \tabularnewline
119 & 0.992441 & 0.0151174 & 0.00755871 \tabularnewline
120 & 0.992408 & 0.0151843 & 0.00759216 \tabularnewline
121 & 0.995038 & 0.00992328 & 0.00496164 \tabularnewline
122 & 0.993491 & 0.0130171 & 0.00650855 \tabularnewline
123 & 0.993675 & 0.01265 & 0.00632499 \tabularnewline
124 & 0.992196 & 0.0156072 & 0.00780358 \tabularnewline
125 & 0.994917 & 0.0101654 & 0.00508269 \tabularnewline
126 & 0.994093 & 0.0118138 & 0.00590692 \tabularnewline
127 & 0.99279 & 0.0144208 & 0.0072104 \tabularnewline
128 & 0.991328 & 0.0173436 & 0.00867182 \tabularnewline
129 & 0.99318 & 0.0136393 & 0.00681967 \tabularnewline
130 & 0.991986 & 0.0160272 & 0.00801358 \tabularnewline
131 & 0.991725 & 0.0165496 & 0.00827481 \tabularnewline
132 & 0.990403 & 0.0191943 & 0.00959715 \tabularnewline
133 & 0.99374 & 0.01252 & 0.00626001 \tabularnewline
134 & 0.992582 & 0.0148354 & 0.0074177 \tabularnewline
135 & 0.990665 & 0.0186691 & 0.00933453 \tabularnewline
136 & 0.989134 & 0.0217326 & 0.0108663 \tabularnewline
137 & 0.986643 & 0.0267143 & 0.0133572 \tabularnewline
138 & 0.984664 & 0.0306727 & 0.0153363 \tabularnewline
139 & 0.982374 & 0.0352512 & 0.0176256 \tabularnewline
140 & 0.989917 & 0.0201668 & 0.0100834 \tabularnewline
141 & 0.987477 & 0.0250463 & 0.0125231 \tabularnewline
142 & 0.985641 & 0.0287177 & 0.0143589 \tabularnewline
143 & 0.981899 & 0.0362022 & 0.0181011 \tabularnewline
144 & 0.978057 & 0.0438863 & 0.0219432 \tabularnewline
145 & 0.975475 & 0.0490499 & 0.0245249 \tabularnewline
146 & 0.971397 & 0.0572051 & 0.0286025 \tabularnewline
147 & 0.981913 & 0.0361744 & 0.0180872 \tabularnewline
148 & 0.97852 & 0.0429592 & 0.0214796 \tabularnewline
149 & 0.97412 & 0.0517608 & 0.0258804 \tabularnewline
150 & 0.974723 & 0.0505535 & 0.0252768 \tabularnewline
151 & 0.96826 & 0.06348 & 0.03174 \tabularnewline
152 & 0.97074 & 0.0585196 & 0.0292598 \tabularnewline
153 & 0.970814 & 0.0583718 & 0.0291859 \tabularnewline
154 & 0.969313 & 0.0613732 & 0.0306866 \tabularnewline
155 & 0.967035 & 0.0659294 & 0.0329647 \tabularnewline
156 & 0.961861 & 0.0762774 & 0.0381387 \tabularnewline
157 & 0.953098 & 0.0938036 & 0.0469018 \tabularnewline
158 & 0.944155 & 0.11169 & 0.0558449 \tabularnewline
159 & 0.951848 & 0.0963042 & 0.0481521 \tabularnewline
160 & 0.950675 & 0.0986499 & 0.049325 \tabularnewline
161 & 0.948148 & 0.103704 & 0.0518518 \tabularnewline
162 & 0.936543 & 0.126914 & 0.0634572 \tabularnewline
163 & 0.934563 & 0.130874 & 0.0654372 \tabularnewline
164 & 0.92897 & 0.14206 & 0.0710302 \tabularnewline
165 & 0.919393 & 0.161215 & 0.0806073 \tabularnewline
166 & 0.906827 & 0.186347 & 0.0931733 \tabularnewline
167 & 0.924668 & 0.150664 & 0.075332 \tabularnewline
168 & 0.911822 & 0.176356 & 0.0881778 \tabularnewline
169 & 0.906539 & 0.186921 & 0.0934605 \tabularnewline
170 & 0.893636 & 0.212728 & 0.106364 \tabularnewline
171 & 0.890522 & 0.218956 & 0.109478 \tabularnewline
172 & 0.878323 & 0.243354 & 0.121677 \tabularnewline
173 & 0.865915 & 0.26817 & 0.134085 \tabularnewline
174 & 0.840973 & 0.318055 & 0.159027 \tabularnewline
175 & 0.812883 & 0.374235 & 0.187117 \tabularnewline
176 & 0.78572 & 0.42856 & 0.21428 \tabularnewline
177 & 0.814242 & 0.371515 & 0.185758 \tabularnewline
178 & 0.784379 & 0.431241 & 0.215621 \tabularnewline
179 & 0.791383 & 0.417233 & 0.208617 \tabularnewline
180 & 0.772363 & 0.455275 & 0.227637 \tabularnewline
181 & 0.829072 & 0.341856 & 0.170928 \tabularnewline
182 & 0.846223 & 0.307554 & 0.153777 \tabularnewline
183 & 0.841977 & 0.316045 & 0.158023 \tabularnewline
184 & 0.837288 & 0.325425 & 0.162712 \tabularnewline
185 & 0.850542 & 0.298916 & 0.149458 \tabularnewline
186 & 0.866716 & 0.266567 & 0.133284 \tabularnewline
187 & 0.844877 & 0.310246 & 0.155123 \tabularnewline
188 & 0.82107 & 0.357859 & 0.17893 \tabularnewline
189 & 0.821832 & 0.356337 & 0.178168 \tabularnewline
190 & 0.810096 & 0.379807 & 0.189904 \tabularnewline
191 & 0.923966 & 0.152067 & 0.0760336 \tabularnewline
192 & 0.917562 & 0.164875 & 0.0824377 \tabularnewline
193 & 0.938862 & 0.122277 & 0.0611385 \tabularnewline
194 & 0.923217 & 0.153565 & 0.0767825 \tabularnewline
195 & 0.902364 & 0.195272 & 0.0976362 \tabularnewline
196 & 0.886417 & 0.227167 & 0.113583 \tabularnewline
197 & 0.865502 & 0.268996 & 0.134498 \tabularnewline
198 & 0.853502 & 0.292996 & 0.146498 \tabularnewline
199 & 0.844251 & 0.311497 & 0.155749 \tabularnewline
200 & 0.912905 & 0.174189 & 0.0870945 \tabularnewline
201 & 0.890671 & 0.218657 & 0.109329 \tabularnewline
202 & 0.868117 & 0.263767 & 0.131883 \tabularnewline
203 & 0.833849 & 0.332303 & 0.166151 \tabularnewline
204 & 0.795159 & 0.409682 & 0.204841 \tabularnewline
205 & 0.749268 & 0.501463 & 0.250732 \tabularnewline
206 & 0.697841 & 0.604318 & 0.302159 \tabularnewline
207 & 0.671055 & 0.65789 & 0.328945 \tabularnewline
208 & 0.658194 & 0.683611 & 0.341806 \tabularnewline
209 & 0.595734 & 0.808532 & 0.404266 \tabularnewline
210 & 0.552788 & 0.894423 & 0.447212 \tabularnewline
211 & 0.605475 & 0.78905 & 0.394525 \tabularnewline
212 & 0.544021 & 0.911957 & 0.455979 \tabularnewline
213 & 0.533438 & 0.933123 & 0.466562 \tabularnewline
214 & 0.943025 & 0.113951 & 0.0569755 \tabularnewline
215 & 0.91548 & 0.169039 & 0.0845196 \tabularnewline
216 & 0.99662 & 0.0067595 & 0.00337975 \tabularnewline
217 & 0.996986 & 0.00602758 & 0.00301379 \tabularnewline
218 & 0.995597 & 0.00880549 & 0.00440275 \tabularnewline
219 & 0.999939 & 0.000121311 & 6.06557e-05 \tabularnewline
220 & 0.999805 & 0.000389512 & 0.000194756 \tabularnewline
221 & 0.999554 & 0.000892181 & 0.00044609 \tabularnewline
222 & 0.99929 & 0.00141975 & 0.000709873 \tabularnewline
223 & 0.998924 & 0.00215226 & 0.00107613 \tabularnewline
224 & 0.99628 & 0.00744049 & 0.00372025 \tabularnewline
225 & 0.997351 & 0.00529784 & 0.00264892 \tabularnewline
226 & 0.990076 & 0.0198487 & 0.00992434 \tabularnewline
227 & 0.994038 & 0.0119231 & 0.00596156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&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]7[/C][C]0.874837[/C][C]0.250326[/C][C]0.125163[/C][/ROW]
[ROW][C]8[/C][C]0.838725[/C][C]0.32255[/C][C]0.161275[/C][/ROW]
[ROW][C]9[/C][C]0.878757[/C][C]0.242486[/C][C]0.121243[/C][/ROW]
[ROW][C]10[/C][C]0.815046[/C][C]0.369908[/C][C]0.184954[/C][/ROW]
[ROW][C]11[/C][C]0.851528[/C][C]0.296944[/C][C]0.148472[/C][/ROW]
[ROW][C]12[/C][C]0.788022[/C][C]0.423955[/C][C]0.211978[/C][/ROW]
[ROW][C]13[/C][C]0.743033[/C][C]0.513933[/C][C]0.256967[/C][/ROW]
[ROW][C]14[/C][C]0.749862[/C][C]0.500275[/C][C]0.250138[/C][/ROW]
[ROW][C]15[/C][C]0.690454[/C][C]0.619092[/C][C]0.309546[/C][/ROW]
[ROW][C]16[/C][C]0.619525[/C][C]0.76095[/C][C]0.380475[/C][/ROW]
[ROW][C]17[/C][C]0.542329[/C][C]0.915343[/C][C]0.457671[/C][/ROW]
[ROW][C]18[/C][C]0.475592[/C][C]0.951185[/C][C]0.524408[/C][/ROW]
[ROW][C]19[/C][C]0.421258[/C][C]0.842515[/C][C]0.578742[/C][/ROW]
[ROW][C]20[/C][C]0.355533[/C][C]0.711065[/C][C]0.644467[/C][/ROW]
[ROW][C]21[/C][C]0.317399[/C][C]0.634798[/C][C]0.682601[/C][/ROW]
[ROW][C]22[/C][C]0.277001[/C][C]0.554001[/C][C]0.722999[/C][/ROW]
[ROW][C]23[/C][C]0.239997[/C][C]0.479994[/C][C]0.760003[/C][/ROW]
[ROW][C]24[/C][C]0.2179[/C][C]0.4358[/C][C]0.7821[/C][/ROW]
[ROW][C]25[/C][C]0.182015[/C][C]0.36403[/C][C]0.817985[/C][/ROW]
[ROW][C]26[/C][C]0.182468[/C][C]0.364936[/C][C]0.817532[/C][/ROW]
[ROW][C]27[/C][C]0.152013[/C][C]0.304026[/C][C]0.847987[/C][/ROW]
[ROW][C]28[/C][C]0.126756[/C][C]0.253512[/C][C]0.873244[/C][/ROW]
[ROW][C]29[/C][C]0.101158[/C][C]0.202315[/C][C]0.898842[/C][/ROW]
[ROW][C]30[/C][C]0.118693[/C][C]0.237386[/C][C]0.881307[/C][/ROW]
[ROW][C]31[/C][C]0.106576[/C][C]0.213153[/C][C]0.893424[/C][/ROW]
[ROW][C]32[/C][C]0.0855584[/C][C]0.171117[/C][C]0.914442[/C][/ROW]
[ROW][C]33[/C][C]0.069332[/C][C]0.138664[/C][C]0.930668[/C][/ROW]
[ROW][C]34[/C][C]0.0769171[/C][C]0.153834[/C][C]0.923083[/C][/ROW]
[ROW][C]35[/C][C]0.0636425[/C][C]0.127285[/C][C]0.936357[/C][/ROW]
[ROW][C]36[/C][C]0.0535453[/C][C]0.107091[/C][C]0.946455[/C][/ROW]
[ROW][C]37[/C][C]0.0491816[/C][C]0.0983632[/C][C]0.950818[/C][/ROW]
[ROW][C]38[/C][C]0.0494962[/C][C]0.0989923[/C][C]0.950504[/C][/ROW]
[ROW][C]39[/C][C]0.0520257[/C][C]0.104051[/C][C]0.947974[/C][/ROW]
[ROW][C]40[/C][C]0.0429[/C][C]0.0858[/C][C]0.9571[/C][/ROW]
[ROW][C]41[/C][C]0.0591592[/C][C]0.118318[/C][C]0.940841[/C][/ROW]
[ROW][C]42[/C][C]0.0721581[/C][C]0.144316[/C][C]0.927842[/C][/ROW]
[ROW][C]43[/C][C]0.0622775[/C][C]0.124555[/C][C]0.937723[/C][/ROW]
[ROW][C]44[/C][C]0.0767678[/C][C]0.153536[/C][C]0.923232[/C][/ROW]
[ROW][C]45[/C][C]0.0836368[/C][C]0.167274[/C][C]0.916363[/C][/ROW]
[ROW][C]46[/C][C]0.0927359[/C][C]0.185472[/C][C]0.907264[/C][/ROW]
[ROW][C]47[/C][C]0.0820527[/C][C]0.164105[/C][C]0.917947[/C][/ROW]
[ROW][C]48[/C][C]0.0760092[/C][C]0.152018[/C][C]0.923991[/C][/ROW]
[ROW][C]49[/C][C]0.069879[/C][C]0.139758[/C][C]0.930121[/C][/ROW]
[ROW][C]50[/C][C]0.0649679[/C][C]0.129936[/C][C]0.935032[/C][/ROW]
[ROW][C]51[/C][C]0.0661152[/C][C]0.13223[/C][C]0.933885[/C][/ROW]
[ROW][C]52[/C][C]0.0982592[/C][C]0.196518[/C][C]0.901741[/C][/ROW]
[ROW][C]53[/C][C]0.0812293[/C][C]0.162459[/C][C]0.918771[/C][/ROW]
[ROW][C]54[/C][C]0.0669592[/C][C]0.133918[/C][C]0.933041[/C][/ROW]
[ROW][C]55[/C][C]0.1844[/C][C]0.368801[/C][C]0.8156[/C][/ROW]
[ROW][C]56[/C][C]0.169696[/C][C]0.339393[/C][C]0.830304[/C][/ROW]
[ROW][C]57[/C][C]0.14937[/C][C]0.298741[/C][C]0.85063[/C][/ROW]
[ROW][C]58[/C][C]0.257146[/C][C]0.514292[/C][C]0.742854[/C][/ROW]
[ROW][C]59[/C][C]0.248754[/C][C]0.497508[/C][C]0.751246[/C][/ROW]
[ROW][C]60[/C][C]0.241465[/C][C]0.482929[/C][C]0.758535[/C][/ROW]
[ROW][C]61[/C][C]0.245864[/C][C]0.491727[/C][C]0.754136[/C][/ROW]
[ROW][C]62[/C][C]0.2671[/C][C]0.534201[/C][C]0.7329[/C][/ROW]
[ROW][C]63[/C][C]0.266425[/C][C]0.532851[/C][C]0.733575[/C][/ROW]
[ROW][C]64[/C][C]0.406086[/C][C]0.812172[/C][C]0.593914[/C][/ROW]
[ROW][C]65[/C][C]0.424074[/C][C]0.848148[/C][C]0.575926[/C][/ROW]
[ROW][C]66[/C][C]0.654141[/C][C]0.691718[/C][C]0.345859[/C][/ROW]
[ROW][C]67[/C][C]0.76218[/C][C]0.47564[/C][C]0.23782[/C][/ROW]
[ROW][C]68[/C][C]0.730892[/C][C]0.538216[/C][C]0.269108[/C][/ROW]
[ROW][C]69[/C][C]0.788694[/C][C]0.422612[/C][C]0.211306[/C][/ROW]
[ROW][C]70[/C][C]0.791509[/C][C]0.416982[/C][C]0.208491[/C][/ROW]
[ROW][C]71[/C][C]0.830668[/C][C]0.338665[/C][C]0.169332[/C][/ROW]
[ROW][C]72[/C][C]0.846877[/C][C]0.306247[/C][C]0.153123[/C][/ROW]
[ROW][C]73[/C][C]0.881581[/C][C]0.236839[/C][C]0.118419[/C][/ROW]
[ROW][C]74[/C][C]0.888782[/C][C]0.222437[/C][C]0.111218[/C][/ROW]
[ROW][C]75[/C][C]0.930257[/C][C]0.139486[/C][C]0.0697429[/C][/ROW]
[ROW][C]76[/C][C]0.941617[/C][C]0.116766[/C][C]0.0583828[/C][/ROW]
[ROW][C]77[/C][C]0.932238[/C][C]0.135524[/C][C]0.0677618[/C][/ROW]
[ROW][C]78[/C][C]0.933359[/C][C]0.133281[/C][C]0.0666407[/C][/ROW]
[ROW][C]79[/C][C]0.94453[/C][C]0.11094[/C][C]0.0554701[/C][/ROW]
[ROW][C]80[/C][C]0.953541[/C][C]0.0929175[/C][C]0.0464587[/C][/ROW]
[ROW][C]81[/C][C]0.953488[/C][C]0.0930243[/C][C]0.0465122[/C][/ROW]
[ROW][C]82[/C][C]0.960189[/C][C]0.0796219[/C][C]0.0398109[/C][/ROW]
[ROW][C]83[/C][C]0.959875[/C][C]0.0802501[/C][C]0.0401251[/C][/ROW]
[ROW][C]84[/C][C]0.956491[/C][C]0.0870172[/C][C]0.0435086[/C][/ROW]
[ROW][C]85[/C][C]0.949511[/C][C]0.100978[/C][C]0.050489[/C][/ROW]
[ROW][C]86[/C][C]0.939734[/C][C]0.120533[/C][C]0.0602663[/C][/ROW]
[ROW][C]87[/C][C]0.931319[/C][C]0.137363[/C][C]0.0686813[/C][/ROW]
[ROW][C]88[/C][C]0.954429[/C][C]0.0911424[/C][C]0.0455712[/C][/ROW]
[ROW][C]89[/C][C]0.95578[/C][C]0.0884401[/C][C]0.04422[/C][/ROW]
[ROW][C]90[/C][C]0.950931[/C][C]0.0981385[/C][C]0.0490693[/C][/ROW]
[ROW][C]91[/C][C]0.942824[/C][C]0.114353[/C][C]0.0571764[/C][/ROW]
[ROW][C]92[/C][C]0.932791[/C][C]0.134417[/C][C]0.0672086[/C][/ROW]
[ROW][C]93[/C][C]0.971925[/C][C]0.05615[/C][C]0.028075[/C][/ROW]
[ROW][C]94[/C][C]0.970684[/C][C]0.0586322[/C][C]0.0293161[/C][/ROW]
[ROW][C]95[/C][C]0.970071[/C][C]0.0598573[/C][C]0.0299286[/C][/ROW]
[ROW][C]96[/C][C]0.96914[/C][C]0.0617193[/C][C]0.0308597[/C][/ROW]
[ROW][C]97[/C][C]0.965452[/C][C]0.0690966[/C][C]0.0345483[/C][/ROW]
[ROW][C]98[/C][C]0.966384[/C][C]0.0672325[/C][C]0.0336162[/C][/ROW]
[ROW][C]99[/C][C]0.960946[/C][C]0.0781074[/C][C]0.0390537[/C][/ROW]
[ROW][C]100[/C][C]0.956528[/C][C]0.0869446[/C][C]0.0434723[/C][/ROW]
[ROW][C]101[/C][C]0.949169[/C][C]0.101662[/C][C]0.050831[/C][/ROW]
[ROW][C]102[/C][C]0.944429[/C][C]0.111142[/C][C]0.0555711[/C][/ROW]
[ROW][C]103[/C][C]0.943049[/C][C]0.113901[/C][C]0.0569507[/C][/ROW]
[ROW][C]104[/C][C]0.977802[/C][C]0.0443957[/C][C]0.0221978[/C][/ROW]
[ROW][C]105[/C][C]0.975082[/C][C]0.0498355[/C][C]0.0249177[/C][/ROW]
[ROW][C]106[/C][C]0.976194[/C][C]0.0476121[/C][C]0.023806[/C][/ROW]
[ROW][C]107[/C][C]0.971245[/C][C]0.0575107[/C][C]0.0287553[/C][/ROW]
[ROW][C]108[/C][C]0.971677[/C][C]0.056647[/C][C]0.0283235[/C][/ROW]
[ROW][C]109[/C][C]0.965048[/C][C]0.0699039[/C][C]0.0349519[/C][/ROW]
[ROW][C]110[/C][C]0.963937[/C][C]0.072126[/C][C]0.036063[/C][/ROW]
[ROW][C]111[/C][C]0.957802[/C][C]0.0843963[/C][C]0.0421982[/C][/ROW]
[ROW][C]112[/C][C]0.955483[/C][C]0.0890336[/C][C]0.0445168[/C][/ROW]
[ROW][C]113[/C][C]0.948025[/C][C]0.103949[/C][C]0.0519746[/C][/ROW]
[ROW][C]114[/C][C]0.968795[/C][C]0.0624098[/C][C]0.0312049[/C][/ROW]
[ROW][C]115[/C][C]0.962793[/C][C]0.0744133[/C][C]0.0372066[/C][/ROW]
[ROW][C]116[/C][C]0.962578[/C][C]0.074843[/C][C]0.0374215[/C][/ROW]
[ROW][C]117[/C][C]0.991716[/C][C]0.0165671[/C][C]0.00828357[/C][/ROW]
[ROW][C]118[/C][C]0.994159[/C][C]0.0116811[/C][C]0.00584055[/C][/ROW]
[ROW][C]119[/C][C]0.992441[/C][C]0.0151174[/C][C]0.00755871[/C][/ROW]
[ROW][C]120[/C][C]0.992408[/C][C]0.0151843[/C][C]0.00759216[/C][/ROW]
[ROW][C]121[/C][C]0.995038[/C][C]0.00992328[/C][C]0.00496164[/C][/ROW]
[ROW][C]122[/C][C]0.993491[/C][C]0.0130171[/C][C]0.00650855[/C][/ROW]
[ROW][C]123[/C][C]0.993675[/C][C]0.01265[/C][C]0.00632499[/C][/ROW]
[ROW][C]124[/C][C]0.992196[/C][C]0.0156072[/C][C]0.00780358[/C][/ROW]
[ROW][C]125[/C][C]0.994917[/C][C]0.0101654[/C][C]0.00508269[/C][/ROW]
[ROW][C]126[/C][C]0.994093[/C][C]0.0118138[/C][C]0.00590692[/C][/ROW]
[ROW][C]127[/C][C]0.99279[/C][C]0.0144208[/C][C]0.0072104[/C][/ROW]
[ROW][C]128[/C][C]0.991328[/C][C]0.0173436[/C][C]0.00867182[/C][/ROW]
[ROW][C]129[/C][C]0.99318[/C][C]0.0136393[/C][C]0.00681967[/C][/ROW]
[ROW][C]130[/C][C]0.991986[/C][C]0.0160272[/C][C]0.00801358[/C][/ROW]
[ROW][C]131[/C][C]0.991725[/C][C]0.0165496[/C][C]0.00827481[/C][/ROW]
[ROW][C]132[/C][C]0.990403[/C][C]0.0191943[/C][C]0.00959715[/C][/ROW]
[ROW][C]133[/C][C]0.99374[/C][C]0.01252[/C][C]0.00626001[/C][/ROW]
[ROW][C]134[/C][C]0.992582[/C][C]0.0148354[/C][C]0.0074177[/C][/ROW]
[ROW][C]135[/C][C]0.990665[/C][C]0.0186691[/C][C]0.00933453[/C][/ROW]
[ROW][C]136[/C][C]0.989134[/C][C]0.0217326[/C][C]0.0108663[/C][/ROW]
[ROW][C]137[/C][C]0.986643[/C][C]0.0267143[/C][C]0.0133572[/C][/ROW]
[ROW][C]138[/C][C]0.984664[/C][C]0.0306727[/C][C]0.0153363[/C][/ROW]
[ROW][C]139[/C][C]0.982374[/C][C]0.0352512[/C][C]0.0176256[/C][/ROW]
[ROW][C]140[/C][C]0.989917[/C][C]0.0201668[/C][C]0.0100834[/C][/ROW]
[ROW][C]141[/C][C]0.987477[/C][C]0.0250463[/C][C]0.0125231[/C][/ROW]
[ROW][C]142[/C][C]0.985641[/C][C]0.0287177[/C][C]0.0143589[/C][/ROW]
[ROW][C]143[/C][C]0.981899[/C][C]0.0362022[/C][C]0.0181011[/C][/ROW]
[ROW][C]144[/C][C]0.978057[/C][C]0.0438863[/C][C]0.0219432[/C][/ROW]
[ROW][C]145[/C][C]0.975475[/C][C]0.0490499[/C][C]0.0245249[/C][/ROW]
[ROW][C]146[/C][C]0.971397[/C][C]0.0572051[/C][C]0.0286025[/C][/ROW]
[ROW][C]147[/C][C]0.981913[/C][C]0.0361744[/C][C]0.0180872[/C][/ROW]
[ROW][C]148[/C][C]0.97852[/C][C]0.0429592[/C][C]0.0214796[/C][/ROW]
[ROW][C]149[/C][C]0.97412[/C][C]0.0517608[/C][C]0.0258804[/C][/ROW]
[ROW][C]150[/C][C]0.974723[/C][C]0.0505535[/C][C]0.0252768[/C][/ROW]
[ROW][C]151[/C][C]0.96826[/C][C]0.06348[/C][C]0.03174[/C][/ROW]
[ROW][C]152[/C][C]0.97074[/C][C]0.0585196[/C][C]0.0292598[/C][/ROW]
[ROW][C]153[/C][C]0.970814[/C][C]0.0583718[/C][C]0.0291859[/C][/ROW]
[ROW][C]154[/C][C]0.969313[/C][C]0.0613732[/C][C]0.0306866[/C][/ROW]
[ROW][C]155[/C][C]0.967035[/C][C]0.0659294[/C][C]0.0329647[/C][/ROW]
[ROW][C]156[/C][C]0.961861[/C][C]0.0762774[/C][C]0.0381387[/C][/ROW]
[ROW][C]157[/C][C]0.953098[/C][C]0.0938036[/C][C]0.0469018[/C][/ROW]
[ROW][C]158[/C][C]0.944155[/C][C]0.11169[/C][C]0.0558449[/C][/ROW]
[ROW][C]159[/C][C]0.951848[/C][C]0.0963042[/C][C]0.0481521[/C][/ROW]
[ROW][C]160[/C][C]0.950675[/C][C]0.0986499[/C][C]0.049325[/C][/ROW]
[ROW][C]161[/C][C]0.948148[/C][C]0.103704[/C][C]0.0518518[/C][/ROW]
[ROW][C]162[/C][C]0.936543[/C][C]0.126914[/C][C]0.0634572[/C][/ROW]
[ROW][C]163[/C][C]0.934563[/C][C]0.130874[/C][C]0.0654372[/C][/ROW]
[ROW][C]164[/C][C]0.92897[/C][C]0.14206[/C][C]0.0710302[/C][/ROW]
[ROW][C]165[/C][C]0.919393[/C][C]0.161215[/C][C]0.0806073[/C][/ROW]
[ROW][C]166[/C][C]0.906827[/C][C]0.186347[/C][C]0.0931733[/C][/ROW]
[ROW][C]167[/C][C]0.924668[/C][C]0.150664[/C][C]0.075332[/C][/ROW]
[ROW][C]168[/C][C]0.911822[/C][C]0.176356[/C][C]0.0881778[/C][/ROW]
[ROW][C]169[/C][C]0.906539[/C][C]0.186921[/C][C]0.0934605[/C][/ROW]
[ROW][C]170[/C][C]0.893636[/C][C]0.212728[/C][C]0.106364[/C][/ROW]
[ROW][C]171[/C][C]0.890522[/C][C]0.218956[/C][C]0.109478[/C][/ROW]
[ROW][C]172[/C][C]0.878323[/C][C]0.243354[/C][C]0.121677[/C][/ROW]
[ROW][C]173[/C][C]0.865915[/C][C]0.26817[/C][C]0.134085[/C][/ROW]
[ROW][C]174[/C][C]0.840973[/C][C]0.318055[/C][C]0.159027[/C][/ROW]
[ROW][C]175[/C][C]0.812883[/C][C]0.374235[/C][C]0.187117[/C][/ROW]
[ROW][C]176[/C][C]0.78572[/C][C]0.42856[/C][C]0.21428[/C][/ROW]
[ROW][C]177[/C][C]0.814242[/C][C]0.371515[/C][C]0.185758[/C][/ROW]
[ROW][C]178[/C][C]0.784379[/C][C]0.431241[/C][C]0.215621[/C][/ROW]
[ROW][C]179[/C][C]0.791383[/C][C]0.417233[/C][C]0.208617[/C][/ROW]
[ROW][C]180[/C][C]0.772363[/C][C]0.455275[/C][C]0.227637[/C][/ROW]
[ROW][C]181[/C][C]0.829072[/C][C]0.341856[/C][C]0.170928[/C][/ROW]
[ROW][C]182[/C][C]0.846223[/C][C]0.307554[/C][C]0.153777[/C][/ROW]
[ROW][C]183[/C][C]0.841977[/C][C]0.316045[/C][C]0.158023[/C][/ROW]
[ROW][C]184[/C][C]0.837288[/C][C]0.325425[/C][C]0.162712[/C][/ROW]
[ROW][C]185[/C][C]0.850542[/C][C]0.298916[/C][C]0.149458[/C][/ROW]
[ROW][C]186[/C][C]0.866716[/C][C]0.266567[/C][C]0.133284[/C][/ROW]
[ROW][C]187[/C][C]0.844877[/C][C]0.310246[/C][C]0.155123[/C][/ROW]
[ROW][C]188[/C][C]0.82107[/C][C]0.357859[/C][C]0.17893[/C][/ROW]
[ROW][C]189[/C][C]0.821832[/C][C]0.356337[/C][C]0.178168[/C][/ROW]
[ROW][C]190[/C][C]0.810096[/C][C]0.379807[/C][C]0.189904[/C][/ROW]
[ROW][C]191[/C][C]0.923966[/C][C]0.152067[/C][C]0.0760336[/C][/ROW]
[ROW][C]192[/C][C]0.917562[/C][C]0.164875[/C][C]0.0824377[/C][/ROW]
[ROW][C]193[/C][C]0.938862[/C][C]0.122277[/C][C]0.0611385[/C][/ROW]
[ROW][C]194[/C][C]0.923217[/C][C]0.153565[/C][C]0.0767825[/C][/ROW]
[ROW][C]195[/C][C]0.902364[/C][C]0.195272[/C][C]0.0976362[/C][/ROW]
[ROW][C]196[/C][C]0.886417[/C][C]0.227167[/C][C]0.113583[/C][/ROW]
[ROW][C]197[/C][C]0.865502[/C][C]0.268996[/C][C]0.134498[/C][/ROW]
[ROW][C]198[/C][C]0.853502[/C][C]0.292996[/C][C]0.146498[/C][/ROW]
[ROW][C]199[/C][C]0.844251[/C][C]0.311497[/C][C]0.155749[/C][/ROW]
[ROW][C]200[/C][C]0.912905[/C][C]0.174189[/C][C]0.0870945[/C][/ROW]
[ROW][C]201[/C][C]0.890671[/C][C]0.218657[/C][C]0.109329[/C][/ROW]
[ROW][C]202[/C][C]0.868117[/C][C]0.263767[/C][C]0.131883[/C][/ROW]
[ROW][C]203[/C][C]0.833849[/C][C]0.332303[/C][C]0.166151[/C][/ROW]
[ROW][C]204[/C][C]0.795159[/C][C]0.409682[/C][C]0.204841[/C][/ROW]
[ROW][C]205[/C][C]0.749268[/C][C]0.501463[/C][C]0.250732[/C][/ROW]
[ROW][C]206[/C][C]0.697841[/C][C]0.604318[/C][C]0.302159[/C][/ROW]
[ROW][C]207[/C][C]0.671055[/C][C]0.65789[/C][C]0.328945[/C][/ROW]
[ROW][C]208[/C][C]0.658194[/C][C]0.683611[/C][C]0.341806[/C][/ROW]
[ROW][C]209[/C][C]0.595734[/C][C]0.808532[/C][C]0.404266[/C][/ROW]
[ROW][C]210[/C][C]0.552788[/C][C]0.894423[/C][C]0.447212[/C][/ROW]
[ROW][C]211[/C][C]0.605475[/C][C]0.78905[/C][C]0.394525[/C][/ROW]
[ROW][C]212[/C][C]0.544021[/C][C]0.911957[/C][C]0.455979[/C][/ROW]
[ROW][C]213[/C][C]0.533438[/C][C]0.933123[/C][C]0.466562[/C][/ROW]
[ROW][C]214[/C][C]0.943025[/C][C]0.113951[/C][C]0.0569755[/C][/ROW]
[ROW][C]215[/C][C]0.91548[/C][C]0.169039[/C][C]0.0845196[/C][/ROW]
[ROW][C]216[/C][C]0.99662[/C][C]0.0067595[/C][C]0.00337975[/C][/ROW]
[ROW][C]217[/C][C]0.996986[/C][C]0.00602758[/C][C]0.00301379[/C][/ROW]
[ROW][C]218[/C][C]0.995597[/C][C]0.00880549[/C][C]0.00440275[/C][/ROW]
[ROW][C]219[/C][C]0.999939[/C][C]0.000121311[/C][C]6.06557e-05[/C][/ROW]
[ROW][C]220[/C][C]0.999805[/C][C]0.000389512[/C][C]0.000194756[/C][/ROW]
[ROW][C]221[/C][C]0.999554[/C][C]0.000892181[/C][C]0.00044609[/C][/ROW]
[ROW][C]222[/C][C]0.99929[/C][C]0.00141975[/C][C]0.000709873[/C][/ROW]
[ROW][C]223[/C][C]0.998924[/C][C]0.00215226[/C][C]0.00107613[/C][/ROW]
[ROW][C]224[/C][C]0.99628[/C][C]0.00744049[/C][C]0.00372025[/C][/ROW]
[ROW][C]225[/C][C]0.997351[/C][C]0.00529784[/C][C]0.00264892[/C][/ROW]
[ROW][C]226[/C][C]0.990076[/C][C]0.0198487[/C][C]0.00992434[/C][/ROW]
[ROW][C]227[/C][C]0.994038[/C][C]0.0119231[/C][C]0.00596156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&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
70.8748370.2503260.125163
80.8387250.322550.161275
90.8787570.2424860.121243
100.8150460.3699080.184954
110.8515280.2969440.148472
120.7880220.4239550.211978
130.7430330.5139330.256967
140.7498620.5002750.250138
150.6904540.6190920.309546
160.6195250.760950.380475
170.5423290.9153430.457671
180.4755920.9511850.524408
190.4212580.8425150.578742
200.3555330.7110650.644467
210.3173990.6347980.682601
220.2770010.5540010.722999
230.2399970.4799940.760003
240.21790.43580.7821
250.1820150.364030.817985
260.1824680.3649360.817532
270.1520130.3040260.847987
280.1267560.2535120.873244
290.1011580.2023150.898842
300.1186930.2373860.881307
310.1065760.2131530.893424
320.08555840.1711170.914442
330.0693320.1386640.930668
340.07691710.1538340.923083
350.06364250.1272850.936357
360.05354530.1070910.946455
370.04918160.09836320.950818
380.04949620.09899230.950504
390.05202570.1040510.947974
400.04290.08580.9571
410.05915920.1183180.940841
420.07215810.1443160.927842
430.06227750.1245550.937723
440.07676780.1535360.923232
450.08363680.1672740.916363
460.09273590.1854720.907264
470.08205270.1641050.917947
480.07600920.1520180.923991
490.0698790.1397580.930121
500.06496790.1299360.935032
510.06611520.132230.933885
520.09825920.1965180.901741
530.08122930.1624590.918771
540.06695920.1339180.933041
550.18440.3688010.8156
560.1696960.3393930.830304
570.149370.2987410.85063
580.2571460.5142920.742854
590.2487540.4975080.751246
600.2414650.4829290.758535
610.2458640.4917270.754136
620.26710.5342010.7329
630.2664250.5328510.733575
640.4060860.8121720.593914
650.4240740.8481480.575926
660.6541410.6917180.345859
670.762180.475640.23782
680.7308920.5382160.269108
690.7886940.4226120.211306
700.7915090.4169820.208491
710.8306680.3386650.169332
720.8468770.3062470.153123
730.8815810.2368390.118419
740.8887820.2224370.111218
750.9302570.1394860.0697429
760.9416170.1167660.0583828
770.9322380.1355240.0677618
780.9333590.1332810.0666407
790.944530.110940.0554701
800.9535410.09291750.0464587
810.9534880.09302430.0465122
820.9601890.07962190.0398109
830.9598750.08025010.0401251
840.9564910.08701720.0435086
850.9495110.1009780.050489
860.9397340.1205330.0602663
870.9313190.1373630.0686813
880.9544290.09114240.0455712
890.955780.08844010.04422
900.9509310.09813850.0490693
910.9428240.1143530.0571764
920.9327910.1344170.0672086
930.9719250.056150.028075
940.9706840.05863220.0293161
950.9700710.05985730.0299286
960.969140.06171930.0308597
970.9654520.06909660.0345483
980.9663840.06723250.0336162
990.9609460.07810740.0390537
1000.9565280.08694460.0434723
1010.9491690.1016620.050831
1020.9444290.1111420.0555711
1030.9430490.1139010.0569507
1040.9778020.04439570.0221978
1050.9750820.04983550.0249177
1060.9761940.04761210.023806
1070.9712450.05751070.0287553
1080.9716770.0566470.0283235
1090.9650480.06990390.0349519
1100.9639370.0721260.036063
1110.9578020.08439630.0421982
1120.9554830.08903360.0445168
1130.9480250.1039490.0519746
1140.9687950.06240980.0312049
1150.9627930.07441330.0372066
1160.9625780.0748430.0374215
1170.9917160.01656710.00828357
1180.9941590.01168110.00584055
1190.9924410.01511740.00755871
1200.9924080.01518430.00759216
1210.9950380.009923280.00496164
1220.9934910.01301710.00650855
1230.9936750.012650.00632499
1240.9921960.01560720.00780358
1250.9949170.01016540.00508269
1260.9940930.01181380.00590692
1270.992790.01442080.0072104
1280.9913280.01734360.00867182
1290.993180.01363930.00681967
1300.9919860.01602720.00801358
1310.9917250.01654960.00827481
1320.9904030.01919430.00959715
1330.993740.012520.00626001
1340.9925820.01483540.0074177
1350.9906650.01866910.00933453
1360.9891340.02173260.0108663
1370.9866430.02671430.0133572
1380.9846640.03067270.0153363
1390.9823740.03525120.0176256
1400.9899170.02016680.0100834
1410.9874770.02504630.0125231
1420.9856410.02871770.0143589
1430.9818990.03620220.0181011
1440.9780570.04388630.0219432
1450.9754750.04904990.0245249
1460.9713970.05720510.0286025
1470.9819130.03617440.0180872
1480.978520.04295920.0214796
1490.974120.05176080.0258804
1500.9747230.05055350.0252768
1510.968260.063480.03174
1520.970740.05851960.0292598
1530.9708140.05837180.0291859
1540.9693130.06137320.0306866
1550.9670350.06592940.0329647
1560.9618610.07627740.0381387
1570.9530980.09380360.0469018
1580.9441550.111690.0558449
1590.9518480.09630420.0481521
1600.9506750.09864990.049325
1610.9481480.1037040.0518518
1620.9365430.1269140.0634572
1630.9345630.1308740.0654372
1640.928970.142060.0710302
1650.9193930.1612150.0806073
1660.9068270.1863470.0931733
1670.9246680.1506640.075332
1680.9118220.1763560.0881778
1690.9065390.1869210.0934605
1700.8936360.2127280.106364
1710.8905220.2189560.109478
1720.8783230.2433540.121677
1730.8659150.268170.134085
1740.8409730.3180550.159027
1750.8128830.3742350.187117
1760.785720.428560.21428
1770.8142420.3715150.185758
1780.7843790.4312410.215621
1790.7913830.4172330.208617
1800.7723630.4552750.227637
1810.8290720.3418560.170928
1820.8462230.3075540.153777
1830.8419770.3160450.158023
1840.8372880.3254250.162712
1850.8505420.2989160.149458
1860.8667160.2665670.133284
1870.8448770.3102460.155123
1880.821070.3578590.17893
1890.8218320.3563370.178168
1900.8100960.3798070.189904
1910.9239660.1520670.0760336
1920.9175620.1648750.0824377
1930.9388620.1222770.0611385
1940.9232170.1535650.0767825
1950.9023640.1952720.0976362
1960.8864170.2271670.113583
1970.8655020.2689960.134498
1980.8535020.2929960.146498
1990.8442510.3114970.155749
2000.9129050.1741890.0870945
2010.8906710.2186570.109329
2020.8681170.2637670.131883
2030.8338490.3323030.166151
2040.7951590.4096820.204841
2050.7492680.5014630.250732
2060.6978410.6043180.302159
2070.6710550.657890.328945
2080.6581940.6836110.341806
2090.5957340.8085320.404266
2100.5527880.8944230.447212
2110.6054750.789050.394525
2120.5440210.9119570.455979
2130.5334380.9331230.466562
2140.9430250.1139510.0569755
2150.915480.1690390.0845196
2160.996620.00675950.00337975
2170.9969860.006027580.00301379
2180.9955970.008805490.00440275
2190.9999390.0001213116.06557e-05
2200.9998050.0003895120.000194756
2210.9995540.0008921810.00044609
2220.999290.001419750.000709873
2230.9989240.002152260.00107613
2240.996280.007440490.00372025
2250.9973510.005297840.00264892
2260.9900760.01984870.00992434
2270.9940380.01192310.00596156






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level110.0497738NOK
5% type I error level460.208145NOK
10% type I error level860.38914NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 11 & 0.0497738 & NOK \tabularnewline
5% type I error level & 46 & 0.208145 & NOK \tabularnewline
10% type I error level & 86 & 0.38914 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265342&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]11[/C][C]0.0497738[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]46[/C][C]0.208145[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]86[/C][C]0.38914[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265342&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265342&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 level110.0497738NOK
5% type I error level460.208145NOK
10% type I error level860.38914NOK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

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