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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 07 Dec 2014 16:00:28 +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/07/t1417968065pc836ydn37reh7m.htm/, Retrieved Thu, 16 May 2024 11:14:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263835, Retrieved Thu, 16 May 2024 11:14:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact91

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Percentiles] [Intrinsic Motivat...] [2010-10-12 12:10:58] [b98453cac15ba1066b407e146608df68]
- RMPD  [Kernel Density Estimation] [] [2011-10-18 22:42:23] [b98453cac15ba1066b407e146608df68]
- RMPD    [Percentiles] [] [2011-10-18 22:46:45] [b98453cac15ba1066b407e146608df68]
- RMPD      [Notched Boxplots] [] [2011-10-18 22:58:56] [b98453cac15ba1066b407e146608df68]
- RMPD        [Notched Boxplots] [Notched boxplot v...] [2014-11-30 20:17:00] [f12bfb29749f0c3f544bf278d0782c85]
- RMPD            [Multiple Regression] [Onderzoeksvraag 4.2] [2014-12-07 16:00:28] [5848e943dc403117a4a7bf00dc78acfc] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 26 50
12.2 57 62
12.8 37 54
7.4 67 71
6.7 43 54
12.6 52 65
14.8 52 73
13.3 43 52
11.1 84 84
8.2 67 42
11.4 49 66
6.4 70 65
10.6 52 78
12.0 58 73
6.3 68 75
11.3 62 72
11.9 43 66
9.3 56 70
9.6 56 61
10.0 74 81
6.4 65 71
13.8 63 69
10.8 58 71
13.8 57 72
11.7 63 68
10.9 53 70
16.1 57 68
13.4 51 61
9.9 64 67
11.5 53 76
8.3 29 70
11.7 54 60
9.0 58 72
9.7 43 69
10.8 51 71
10.3 53 62
10.4 54 70
12.7 56 64
9.3 61 58
11.8 47 76
5.9 39 52
11.4 48 59
13.0 50 68
10.8 35 76
12.3 30 65
11.3 68 67
11.8 49 59
7.9 61 69
12.7 67 76
12.3 47 63
11.6 56 75
6.7 50 63
10.9 43 60
12.1 67 73
13.3 62 63
10.1 57 70
5.7 41 75
14.3 54 66
8.0 45 63
13.3 48 63
9.3 61 64
12.5 56 70
7.6 41 75
15.9 43 61
9.2 53 60
9.1 44 62
11.1 66 73
13.0 58 61
14.5 46 66
12.2 37 64
12.3 51 59
11.4 51 64
8.8 56 60
14.6 66 56
12.6 37 78
NA 59 53
13.0 42 67
12.6 38 59
13.2 66 66
9.9 34 68
7.7 53 71
10.5 49 66
13.4 55 73
10.9 49 72
4.3 59 71
10.3 40 59
11.8 58 64
11.2 60 66
11.4 63 78
8.6 56 68
13.2 54 73
12.6 52 62
5.6 34 65
9.9 69 68
8.8 32 65
7.7 48 60
9.0 67 71
7.3 58 65
11.4 57 68
13.6 42 64
7.9 64 74
10.7 58 69
10.3 66 76
8.3 26 68
9.6 61 72
14.2 52 67
8.5 51 63
13.5 55 59
4.9 50 73
6.4 60 66
9.6 56 62
11.6 63 69
11.1 61 66
4.35 52 51
12.7 16 56
18.1 46 67
17.85 56 69
16.6 52 57
12.6 55 56
17.1 50 55
19.1 59 63
16.1 60 67
13.35 52 65
18.4 44 47
14.7 67 76
10.6 52 64
12.6 55 68
16.2 37 64
13.6 54 65
18.9 72 71
14.1 51 63
14.5 48 60
16.15 60 68
14.75 50 72
14.8 63 70
12.45 33 61
12.65 67 61
17.35 46 62
8.6 54 71
18.4 59 71
16.1 61 51
11.6 33 56
17.75 47 70
15.25 69 73
17.65 52 76
16.35 55 68
17.65 41 48
13.6 73 52
14.35 52 60
14.75 50 59
18.25 51 57
9.9 60 79
16 56 60
18.25 56 60
16.85 29 59
14.6 66 62
13.85 66 59
18.95 73 61
15.6 55 71
14.85 64 57
11.75 40 66
18.45 46 63
15.9 58 69
17.1 43 58
16.1 61 59
19.9 51 48
10.95 50 66
18.45 52 73
15.1 54 67
15 66 61
11.35 61 68
15.95 80 75
18.1 51 62
14.6 56 69
15.4 56 58
15.4 56 60
17.6 53 74
13.35 47 55
19.1 25 62
15.35 47 63
7.6 46 69
13.4 50 58
13.9 39 58
19.1 51 68
15.25 58 72
12.9 35 62
16.1 58 62
17.35 60 65
13.15 62 69
12.15 63 66
12.6 53 72
10.35 46 62
15.4 67 75
9.6 59 58
18.2 64 66
13.6 38 55
14.85 50 47
14.75 48 72
14.1 48 62
14.9 47 64
16.25 66 64
19.25 47 19
13.6 63 50
13.6 58 68
15.65 44 70
12.75 51 79
14.6 43 69
9.85 55 71
12.65 38 48
19.2 45 73
16.6 50 74
11.2 54 66
15.25 57 71
11.9 60 74
13.2 55 78
16.35 56 75
12.4 49 53
15.85 37 60
18.15 59 70
11.15 46 69
15.65 51 65
17.75 58 78
7.65 64 78
12.35 53 59
15.6 48 72
19.3 51 70
15.2 47 63
17.1 59 63
15.6 62 71
18.4 62 74
19.05 51 67
18.55 64 66
19.1 52 62
13.1 67 80
12.85 50 73
9.5 54 67
4.5 58 61
11.85 56 73
13.6 63 74
11.7 31 32
12.4 65 69
13.35 71 69
11.4 50 84
14.9 57 64
19.9 47 58
11.2 47 59
14.6 57 78
17.6 43 57
14.05 41 60
16.1 63 68
13.35 63 68
11.85 56 73
11.95 51 69
14.75 50 67
15.15 22 60
13.2 41 65
16.85 59 66
7.85 56 74
7.7 66 81
12.6 53 72
7.85 42 55
10.95 52 49
12.35 54 74
9.95 44 53
14.9 62 64
16.65 53 65
13.4 50 57
13.95 36 51
15.7 76 80
16.85 66 67
10.95 62 70
15.35 59 74
12.2 47 75
15.1 55 70
17.75 58 69
15.2 60 65
14.6 44 55
16.65 57 71
8.1 45 65

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'George Udny Yule' @ yule.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 & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&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]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&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'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 15.5486 + 0.0213916AMS.I[t] -0.056599AMS.E[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  15.5486 +  0.0213916AMS.I[t] -0.056599AMS.E[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  15.5486 +  0.0213916AMS.I[t] -0.056599AMS.E[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&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] = + 15.5486 + 0.0213916AMS.I[t] -0.056599AMS.E[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)15.54861.72219.0293.11815e-171.55908e-17
AMS.I0.02139160.02102411.0170.3098190.15491
AMS.E-0.0565990.0265833-2.1290.03413290.0170665

\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) & 15.5486 & 1.7221 & 9.029 & 3.11815e-17 & 1.55908e-17 \tabularnewline
AMS.I & 0.0213916 & 0.0210241 & 1.017 & 0.309819 & 0.15491 \tabularnewline
AMS.E & -0.056599 & 0.0265833 & -2.129 & 0.0341329 & 0.0170665 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&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]15.5486[/C][C]1.7221[/C][C]9.029[/C][C]3.11815e-17[/C][C]1.55908e-17[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0213916[/C][C]0.0210241[/C][C]1.017[/C][C]0.309819[/C][C]0.15491[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.056599[/C][C]0.0265833[/C][C]-2.129[/C][C]0.0341329[/C][C]0.0170665[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&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)15.54861.72219.0293.11815e-171.55908e-17
AMS.I0.02139160.02102411.0170.3098190.15491
AMS.E-0.0565990.0265833-2.1290.03413290.0170665






Multiple Linear Regression - Regression Statistics
Multiple R0.128516
R-squared0.0165164
Adjusted R-squared0.00936381
F-TEST (value)2.30915
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value0.101269
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37843
Sum Squared Residuals3138.79

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.128516 \tabularnewline
R-squared & 0.0165164 \tabularnewline
Adjusted R-squared & 0.00936381 \tabularnewline
F-TEST (value) & 2.30915 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 275 \tabularnewline
p-value & 0.101269 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.37843 \tabularnewline
Sum Squared Residuals & 3138.79 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.128516[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0165164[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00936381[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.30915[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]275[/C][/ROW]
[ROW][C]p-value[/C][C]0.101269[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.37843[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3138.79[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&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 R0.128516
R-squared0.0165164
Adjusted R-squared0.00936381
F-TEST (value)2.30915
F-TEST (DF numerator)2
F-TEST (DF denominator)275
p-value0.101269
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.37843
Sum Squared Residuals3138.79






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.2748-0.374814
212.213.2588-1.05877
312.813.2837-0.483726
47.412.9633-5.56329
56.713.4121-6.71208
612.612.982-0.382011
714.812.52922.27078
813.313.5253-0.225273
911.112.5912-1.49116
108.214.6047-6.40466
1111.412.8612-1.46124
126.413.3671-6.96706
1310.612.2462-1.64622
141212.6576-0.657568
156.312.7583-6.45829
1611.312.7997-1.49973
1711.912.7329-0.832887
189.312.7846-3.48458
199.613.294-3.69397
201012.547-2.54704
216.412.9205-6.52051
2213.812.99090.809078
2310.812.7708-1.97077
2413.812.69281.10722
2511.713.0475-1.34752
2610.912.7204-1.82041
2716.112.91923.18083
2813.413.1870.212985
299.913.1255-3.22551
3011.512.3808-0.880813
318.312.207-3.90701
3211.713.3078-1.60779
33912.7142-3.71417
349.712.5631-2.86309
3510.812.621-1.82102
3610.313.1732-2.8732
3710.412.7418-2.3418
3812.713.1242-0.424176
399.313.5707-4.27073
4011.812.2525-0.452463
415.913.4397-7.53971
4211.413.236-1.83604
431312.76940.23057
4410.811.9958-1.19576
4512.312.5114-0.211395
4611.313.2111-1.91108
4711.813.2574-1.45743
487.912.9481-5.04814
4912.712.68030.0197047
5012.312.9883-0.688251
5111.612.5016-0.901587
526.713.0524-6.35243
5310.913.0725-2.17248
5412.112.8501-0.750092
5513.313.3091-0.00912464
5610.112.806-2.70597
575.712.1807-6.48071
5814.312.96821.33181
59812.9455-4.94547
6013.313.00960.290358
619.313.2311-3.93113
6212.512.7846-0.284582
637.612.1807-4.58071
6415.913.01592.88412
659.213.2864-4.0864
669.112.9807-3.88067
6711.112.8287-1.7287
681313.3368-0.336756
6914.512.79711.70294
7012.212.7177-0.517735
7112.313.3002-1.00021
7211.413.0172-1.61722
738.813.3506-4.55057
7414.613.79090.809116
7512.611.92530.674651
76NANA0.345104
771313.4221-0.422122
7812.612.6249-0.024894
7913.215.7272-2.52716
809.914.8638-4.96381
817.710.0612-2.36124
8210.59.693390.806607
8313.415.0216-1.62164
8410.919.3922-8.49216
854.37.06491-2.76491
8610.311.667-1.36696
8711.813.6965-1.89654
8811.212.2815-1.08153
8911.415.6978-4.29778
908.67.9720.627999
9113.213.7518-0.551808
9212.619.597-6.99696
935.68.87587-3.27587
949.913.6542-3.75418
958.814.2794-5.47944
967.711.6633-3.96329
97914.8104-5.81036
987.38.81917-1.51917
9911.410.62470.775306
10013.618.4293-4.82932
1017.910.084-2.18396
10210.713.0589-2.3589
10310.314.256-3.95603
1048.311.4783-3.17834
1059.68.268811.33119
10614.218.7738-4.57382
1078.58.385780.11422
10813.521.0864-7.58644
1094.911.5965-6.69654
1106.410.0374-3.63737
1119.610.9909-1.39092
11211.613.6179-2.01794
11311.120.5244-9.4244
1144.354.3713-0.021304
11512.77.340465.35954
11618.113.09125.00882
11717.8514.68483.1652
11816.617.5556-0.955577
11912.69.005223.59478
12017.111.24495.85505
12119.116.03993.06005
12216.115.7320.367989
12313.358.779664.57034
12418.416.38032.0197
12514.717.1386-2.43861
12610.610.8764-0.276388
12712.69.117743.48226
12816.215.62480.575206
12913.67.770255.82975
13018.917.87381.02618
13114.112.77941.32056
13214.511.33333.16665
13316.1513.9432.20697
13414.7512.88431.86568
13514.815.152-0.351966
13612.4513.3293-0.879281
13712.658.323464.32654
13817.3521.4352-4.0852
1398.62.992165.60784
14018.416.26692.13308
14116.117.585-1.48496
14211.66.442065.15794
14317.7515.39292.35712
14415.259.959425.29058
14517.6514.17643.47361
14616.3512.40893.94111
14717.6518.217-0.567022
14813.612.5151.08499
14914.3512.87881.47118
15014.759.913414.83659
15118.2520.7108-2.46076
1529.97.250572.64943
1531611.10064.89943
15418.2514.22964.0204
15516.8515.70131.14871
15614.614.37110.228913
15713.858.557635.29237
15818.9516.05662.89341
15915.614.44151.1585
16014.8515.7687-0.918712
16111.756.266865.48314
16218.4515.4343.01604
16315.911.98573.91432
16417.114.51412.58587
16516.110.12285.9772
16619.921.8326-1.93263
16710.955.029225.92078
16818.4516.26162.1884
16915.113.60791.49211
1701516.6547-1.65474
17111.358.414992.93501
17215.9510.98044.96958
17318.116.34121.75882
17414.612.66381.93623
17515.413.35062.04943
17615.410.2945.10599
17717.617.691-0.0910428
17813.356.824236.52577
17919.116.73832.36175
18015.3520.3773-5.02726
1817.67.535420.0645795
18213.412.60010.799887
18313.97.590826.30918
18419.116.56422.53583
18515.2515.13820.11185
18612.910.08022.81984
18716.111.90314.19686
18817.3517.16950.18047
18913.1514.1607-1.01072
19012.1512.1572-0.00720892
19112.615.2735-2.67346
19210.357.686892.66311
19315.419.3279-3.92794
1949.64.582115.01789
19518.217.84850.351482
19613.612.7080.89199
19714.8512.60032.24975
19814.7513.71621.03376
19914.112.13171.96835
20014.911.98812.91191
20116.2512.47863.77139
20219.2519.7163-0.466304
20313.612.94060.659437
20413.610.47793.12212
20515.6515.06820.581768
20612.7510.71312.03691
20714.617.4566-2.85659
2089.8510.8447-0.994712
20912.655.829486.82052
21019.215.02984.17016
21116.618.3682-1.76819
21211.28.699372.50063
21315.2515.9938-0.743752
21411.911.01040.889602
21513.29.351593.84841
21616.3517.547-1.19702
21712.49.494132.90587
21815.8510.54885.30124
21918.1519.6273-1.47726
22011.158.460622.68938
22115.6510.27465.37543
22217.7522.6029-4.85292
2237.658.643-0.992996
22412.359.250253.09975
22515.68.977626.62238
22619.317.08832.21175
22715.211.34493.85505
22817.114.35632.74367
22915.69.886545.71346
23018.412.19746.20258
23119.0513.68215.36789
23218.5512.60185.94819
23319.118.45390.646101
23413.112.73640.363565
23512.8516.2616-3.4116
2369.518.3368-8.83676
2374.55.26478-0.764785
23811.8510.95790.892073
23913.616.3006-2.70055
24011.712.3337-0.633705
24112.412.21210.187945
24213.3513.8138-0.463846
24311.49.645571.75443
24414.98.271256.62875
24519.921.9146-2.01465
24611.28.953182.24682
24714.610.24234.35772
24817.616.57971.0203
24914.0510.99753.05248
25016.115.79750.302479
25113.3514.1148-0.764785
25211.8512.6342-0.784223
25311.9510.0261.92397
25414.7512.22332.52674
25515.1514.69670.453297
25613.29.425153.77485
25716.8521.5582-4.70819
2587.8512.5259-4.67591
2597.77.70721-0.00720892
26012.618.0841-5.48408
2617.8510.7876-2.9376
26210.9511.1154-0.165402
26312.3515.8901-3.54007
2649.958.302531.64747
26514.911.25343.6466
26616.6516.6420.00798043
26713.412.88210.517869
26813.9510.89643.05358
26915.712.01833.68171
27016.8518.8129-1.96293
27110.958.222362.72764
27215.3515.4591-0.109062
27312.29.863192.33681
27415.110.2344.86604
27517.7515.70312.04686
27615.213.97691.22313
27714.610.69943.90063
27816.6521.3823-4.73227
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.2748 & -0.374814 \tabularnewline
2 & 12.2 & 13.2588 & -1.05877 \tabularnewline
3 & 12.8 & 13.2837 & -0.483726 \tabularnewline
4 & 7.4 & 12.9633 & -5.56329 \tabularnewline
5 & 6.7 & 13.4121 & -6.71208 \tabularnewline
6 & 12.6 & 12.982 & -0.382011 \tabularnewline
7 & 14.8 & 12.5292 & 2.27078 \tabularnewline
8 & 13.3 & 13.5253 & -0.225273 \tabularnewline
9 & 11.1 & 12.5912 & -1.49116 \tabularnewline
10 & 8.2 & 14.6047 & -6.40466 \tabularnewline
11 & 11.4 & 12.8612 & -1.46124 \tabularnewline
12 & 6.4 & 13.3671 & -6.96706 \tabularnewline
13 & 10.6 & 12.2462 & -1.64622 \tabularnewline
14 & 12 & 12.6576 & -0.657568 \tabularnewline
15 & 6.3 & 12.7583 & -6.45829 \tabularnewline
16 & 11.3 & 12.7997 & -1.49973 \tabularnewline
17 & 11.9 & 12.7329 & -0.832887 \tabularnewline
18 & 9.3 & 12.7846 & -3.48458 \tabularnewline
19 & 9.6 & 13.294 & -3.69397 \tabularnewline
20 & 10 & 12.547 & -2.54704 \tabularnewline
21 & 6.4 & 12.9205 & -6.52051 \tabularnewline
22 & 13.8 & 12.9909 & 0.809078 \tabularnewline
23 & 10.8 & 12.7708 & -1.97077 \tabularnewline
24 & 13.8 & 12.6928 & 1.10722 \tabularnewline
25 & 11.7 & 13.0475 & -1.34752 \tabularnewline
26 & 10.9 & 12.7204 & -1.82041 \tabularnewline
27 & 16.1 & 12.9192 & 3.18083 \tabularnewline
28 & 13.4 & 13.187 & 0.212985 \tabularnewline
29 & 9.9 & 13.1255 & -3.22551 \tabularnewline
30 & 11.5 & 12.3808 & -0.880813 \tabularnewline
31 & 8.3 & 12.207 & -3.90701 \tabularnewline
32 & 11.7 & 13.3078 & -1.60779 \tabularnewline
33 & 9 & 12.7142 & -3.71417 \tabularnewline
34 & 9.7 & 12.5631 & -2.86309 \tabularnewline
35 & 10.8 & 12.621 & -1.82102 \tabularnewline
36 & 10.3 & 13.1732 & -2.8732 \tabularnewline
37 & 10.4 & 12.7418 & -2.3418 \tabularnewline
38 & 12.7 & 13.1242 & -0.424176 \tabularnewline
39 & 9.3 & 13.5707 & -4.27073 \tabularnewline
40 & 11.8 & 12.2525 & -0.452463 \tabularnewline
41 & 5.9 & 13.4397 & -7.53971 \tabularnewline
42 & 11.4 & 13.236 & -1.83604 \tabularnewline
43 & 13 & 12.7694 & 0.23057 \tabularnewline
44 & 10.8 & 11.9958 & -1.19576 \tabularnewline
45 & 12.3 & 12.5114 & -0.211395 \tabularnewline
46 & 11.3 & 13.2111 & -1.91108 \tabularnewline
47 & 11.8 & 13.2574 & -1.45743 \tabularnewline
48 & 7.9 & 12.9481 & -5.04814 \tabularnewline
49 & 12.7 & 12.6803 & 0.0197047 \tabularnewline
50 & 12.3 & 12.9883 & -0.688251 \tabularnewline
51 & 11.6 & 12.5016 & -0.901587 \tabularnewline
52 & 6.7 & 13.0524 & -6.35243 \tabularnewline
53 & 10.9 & 13.0725 & -2.17248 \tabularnewline
54 & 12.1 & 12.8501 & -0.750092 \tabularnewline
55 & 13.3 & 13.3091 & -0.00912464 \tabularnewline
56 & 10.1 & 12.806 & -2.70597 \tabularnewline
57 & 5.7 & 12.1807 & -6.48071 \tabularnewline
58 & 14.3 & 12.9682 & 1.33181 \tabularnewline
59 & 8 & 12.9455 & -4.94547 \tabularnewline
60 & 13.3 & 13.0096 & 0.290358 \tabularnewline
61 & 9.3 & 13.2311 & -3.93113 \tabularnewline
62 & 12.5 & 12.7846 & -0.284582 \tabularnewline
63 & 7.6 & 12.1807 & -4.58071 \tabularnewline
64 & 15.9 & 13.0159 & 2.88412 \tabularnewline
65 & 9.2 & 13.2864 & -4.0864 \tabularnewline
66 & 9.1 & 12.9807 & -3.88067 \tabularnewline
67 & 11.1 & 12.8287 & -1.7287 \tabularnewline
68 & 13 & 13.3368 & -0.336756 \tabularnewline
69 & 14.5 & 12.7971 & 1.70294 \tabularnewline
70 & 12.2 & 12.7177 & -0.517735 \tabularnewline
71 & 12.3 & 13.3002 & -1.00021 \tabularnewline
72 & 11.4 & 13.0172 & -1.61722 \tabularnewline
73 & 8.8 & 13.3506 & -4.55057 \tabularnewline
74 & 14.6 & 13.7909 & 0.809116 \tabularnewline
75 & 12.6 & 11.9253 & 0.674651 \tabularnewline
76 & NA & NA & 0.345104 \tabularnewline
77 & 13 & 13.4221 & -0.422122 \tabularnewline
78 & 12.6 & 12.6249 & -0.024894 \tabularnewline
79 & 13.2 & 15.7272 & -2.52716 \tabularnewline
80 & 9.9 & 14.8638 & -4.96381 \tabularnewline
81 & 7.7 & 10.0612 & -2.36124 \tabularnewline
82 & 10.5 & 9.69339 & 0.806607 \tabularnewline
83 & 13.4 & 15.0216 & -1.62164 \tabularnewline
84 & 10.9 & 19.3922 & -8.49216 \tabularnewline
85 & 4.3 & 7.06491 & -2.76491 \tabularnewline
86 & 10.3 & 11.667 & -1.36696 \tabularnewline
87 & 11.8 & 13.6965 & -1.89654 \tabularnewline
88 & 11.2 & 12.2815 & -1.08153 \tabularnewline
89 & 11.4 & 15.6978 & -4.29778 \tabularnewline
90 & 8.6 & 7.972 & 0.627999 \tabularnewline
91 & 13.2 & 13.7518 & -0.551808 \tabularnewline
92 & 12.6 & 19.597 & -6.99696 \tabularnewline
93 & 5.6 & 8.87587 & -3.27587 \tabularnewline
94 & 9.9 & 13.6542 & -3.75418 \tabularnewline
95 & 8.8 & 14.2794 & -5.47944 \tabularnewline
96 & 7.7 & 11.6633 & -3.96329 \tabularnewline
97 & 9 & 14.8104 & -5.81036 \tabularnewline
98 & 7.3 & 8.81917 & -1.51917 \tabularnewline
99 & 11.4 & 10.6247 & 0.775306 \tabularnewline
100 & 13.6 & 18.4293 & -4.82932 \tabularnewline
101 & 7.9 & 10.084 & -2.18396 \tabularnewline
102 & 10.7 & 13.0589 & -2.3589 \tabularnewline
103 & 10.3 & 14.256 & -3.95603 \tabularnewline
104 & 8.3 & 11.4783 & -3.17834 \tabularnewline
105 & 9.6 & 8.26881 & 1.33119 \tabularnewline
106 & 14.2 & 18.7738 & -4.57382 \tabularnewline
107 & 8.5 & 8.38578 & 0.11422 \tabularnewline
108 & 13.5 & 21.0864 & -7.58644 \tabularnewline
109 & 4.9 & 11.5965 & -6.69654 \tabularnewline
110 & 6.4 & 10.0374 & -3.63737 \tabularnewline
111 & 9.6 & 10.9909 & -1.39092 \tabularnewline
112 & 11.6 & 13.6179 & -2.01794 \tabularnewline
113 & 11.1 & 20.5244 & -9.4244 \tabularnewline
114 & 4.35 & 4.3713 & -0.021304 \tabularnewline
115 & 12.7 & 7.34046 & 5.35954 \tabularnewline
116 & 18.1 & 13.0912 & 5.00882 \tabularnewline
117 & 17.85 & 14.6848 & 3.1652 \tabularnewline
118 & 16.6 & 17.5556 & -0.955577 \tabularnewline
119 & 12.6 & 9.00522 & 3.59478 \tabularnewline
120 & 17.1 & 11.2449 & 5.85505 \tabularnewline
121 & 19.1 & 16.0399 & 3.06005 \tabularnewline
122 & 16.1 & 15.732 & 0.367989 \tabularnewline
123 & 13.35 & 8.77966 & 4.57034 \tabularnewline
124 & 18.4 & 16.3803 & 2.0197 \tabularnewline
125 & 14.7 & 17.1386 & -2.43861 \tabularnewline
126 & 10.6 & 10.8764 & -0.276388 \tabularnewline
127 & 12.6 & 9.11774 & 3.48226 \tabularnewline
128 & 16.2 & 15.6248 & 0.575206 \tabularnewline
129 & 13.6 & 7.77025 & 5.82975 \tabularnewline
130 & 18.9 & 17.8738 & 1.02618 \tabularnewline
131 & 14.1 & 12.7794 & 1.32056 \tabularnewline
132 & 14.5 & 11.3333 & 3.16665 \tabularnewline
133 & 16.15 & 13.943 & 2.20697 \tabularnewline
134 & 14.75 & 12.8843 & 1.86568 \tabularnewline
135 & 14.8 & 15.152 & -0.351966 \tabularnewline
136 & 12.45 & 13.3293 & -0.879281 \tabularnewline
137 & 12.65 & 8.32346 & 4.32654 \tabularnewline
138 & 17.35 & 21.4352 & -4.0852 \tabularnewline
139 & 8.6 & 2.99216 & 5.60784 \tabularnewline
140 & 18.4 & 16.2669 & 2.13308 \tabularnewline
141 & 16.1 & 17.585 & -1.48496 \tabularnewline
142 & 11.6 & 6.44206 & 5.15794 \tabularnewline
143 & 17.75 & 15.3929 & 2.35712 \tabularnewline
144 & 15.25 & 9.95942 & 5.29058 \tabularnewline
145 & 17.65 & 14.1764 & 3.47361 \tabularnewline
146 & 16.35 & 12.4089 & 3.94111 \tabularnewline
147 & 17.65 & 18.217 & -0.567022 \tabularnewline
148 & 13.6 & 12.515 & 1.08499 \tabularnewline
149 & 14.35 & 12.8788 & 1.47118 \tabularnewline
150 & 14.75 & 9.91341 & 4.83659 \tabularnewline
151 & 18.25 & 20.7108 & -2.46076 \tabularnewline
152 & 9.9 & 7.25057 & 2.64943 \tabularnewline
153 & 16 & 11.1006 & 4.89943 \tabularnewline
154 & 18.25 & 14.2296 & 4.0204 \tabularnewline
155 & 16.85 & 15.7013 & 1.14871 \tabularnewline
156 & 14.6 & 14.3711 & 0.228913 \tabularnewline
157 & 13.85 & 8.55763 & 5.29237 \tabularnewline
158 & 18.95 & 16.0566 & 2.89341 \tabularnewline
159 & 15.6 & 14.4415 & 1.1585 \tabularnewline
160 & 14.85 & 15.7687 & -0.918712 \tabularnewline
161 & 11.75 & 6.26686 & 5.48314 \tabularnewline
162 & 18.45 & 15.434 & 3.01604 \tabularnewline
163 & 15.9 & 11.9857 & 3.91432 \tabularnewline
164 & 17.1 & 14.5141 & 2.58587 \tabularnewline
165 & 16.1 & 10.1228 & 5.9772 \tabularnewline
166 & 19.9 & 21.8326 & -1.93263 \tabularnewline
167 & 10.95 & 5.02922 & 5.92078 \tabularnewline
168 & 18.45 & 16.2616 & 2.1884 \tabularnewline
169 & 15.1 & 13.6079 & 1.49211 \tabularnewline
170 & 15 & 16.6547 & -1.65474 \tabularnewline
171 & 11.35 & 8.41499 & 2.93501 \tabularnewline
172 & 15.95 & 10.9804 & 4.96958 \tabularnewline
173 & 18.1 & 16.3412 & 1.75882 \tabularnewline
174 & 14.6 & 12.6638 & 1.93623 \tabularnewline
175 & 15.4 & 13.3506 & 2.04943 \tabularnewline
176 & 15.4 & 10.294 & 5.10599 \tabularnewline
177 & 17.6 & 17.691 & -0.0910428 \tabularnewline
178 & 13.35 & 6.82423 & 6.52577 \tabularnewline
179 & 19.1 & 16.7383 & 2.36175 \tabularnewline
180 & 15.35 & 20.3773 & -5.02726 \tabularnewline
181 & 7.6 & 7.53542 & 0.0645795 \tabularnewline
182 & 13.4 & 12.6001 & 0.799887 \tabularnewline
183 & 13.9 & 7.59082 & 6.30918 \tabularnewline
184 & 19.1 & 16.5642 & 2.53583 \tabularnewline
185 & 15.25 & 15.1382 & 0.11185 \tabularnewline
186 & 12.9 & 10.0802 & 2.81984 \tabularnewline
187 & 16.1 & 11.9031 & 4.19686 \tabularnewline
188 & 17.35 & 17.1695 & 0.18047 \tabularnewline
189 & 13.15 & 14.1607 & -1.01072 \tabularnewline
190 & 12.15 & 12.1572 & -0.00720892 \tabularnewline
191 & 12.6 & 15.2735 & -2.67346 \tabularnewline
192 & 10.35 & 7.68689 & 2.66311 \tabularnewline
193 & 15.4 & 19.3279 & -3.92794 \tabularnewline
194 & 9.6 & 4.58211 & 5.01789 \tabularnewline
195 & 18.2 & 17.8485 & 0.351482 \tabularnewline
196 & 13.6 & 12.708 & 0.89199 \tabularnewline
197 & 14.85 & 12.6003 & 2.24975 \tabularnewline
198 & 14.75 & 13.7162 & 1.03376 \tabularnewline
199 & 14.1 & 12.1317 & 1.96835 \tabularnewline
200 & 14.9 & 11.9881 & 2.91191 \tabularnewline
201 & 16.25 & 12.4786 & 3.77139 \tabularnewline
202 & 19.25 & 19.7163 & -0.466304 \tabularnewline
203 & 13.6 & 12.9406 & 0.659437 \tabularnewline
204 & 13.6 & 10.4779 & 3.12212 \tabularnewline
205 & 15.65 & 15.0682 & 0.581768 \tabularnewline
206 & 12.75 & 10.7131 & 2.03691 \tabularnewline
207 & 14.6 & 17.4566 & -2.85659 \tabularnewline
208 & 9.85 & 10.8447 & -0.994712 \tabularnewline
209 & 12.65 & 5.82948 & 6.82052 \tabularnewline
210 & 19.2 & 15.0298 & 4.17016 \tabularnewline
211 & 16.6 & 18.3682 & -1.76819 \tabularnewline
212 & 11.2 & 8.69937 & 2.50063 \tabularnewline
213 & 15.25 & 15.9938 & -0.743752 \tabularnewline
214 & 11.9 & 11.0104 & 0.889602 \tabularnewline
215 & 13.2 & 9.35159 & 3.84841 \tabularnewline
216 & 16.35 & 17.547 & -1.19702 \tabularnewline
217 & 12.4 & 9.49413 & 2.90587 \tabularnewline
218 & 15.85 & 10.5488 & 5.30124 \tabularnewline
219 & 18.15 & 19.6273 & -1.47726 \tabularnewline
220 & 11.15 & 8.46062 & 2.68938 \tabularnewline
221 & 15.65 & 10.2746 & 5.37543 \tabularnewline
222 & 17.75 & 22.6029 & -4.85292 \tabularnewline
223 & 7.65 & 8.643 & -0.992996 \tabularnewline
224 & 12.35 & 9.25025 & 3.09975 \tabularnewline
225 & 15.6 & 8.97762 & 6.62238 \tabularnewline
226 & 19.3 & 17.0883 & 2.21175 \tabularnewline
227 & 15.2 & 11.3449 & 3.85505 \tabularnewline
228 & 17.1 & 14.3563 & 2.74367 \tabularnewline
229 & 15.6 & 9.88654 & 5.71346 \tabularnewline
230 & 18.4 & 12.1974 & 6.20258 \tabularnewline
231 & 19.05 & 13.6821 & 5.36789 \tabularnewline
232 & 18.55 & 12.6018 & 5.94819 \tabularnewline
233 & 19.1 & 18.4539 & 0.646101 \tabularnewline
234 & 13.1 & 12.7364 & 0.363565 \tabularnewline
235 & 12.85 & 16.2616 & -3.4116 \tabularnewline
236 & 9.5 & 18.3368 & -8.83676 \tabularnewline
237 & 4.5 & 5.26478 & -0.764785 \tabularnewline
238 & 11.85 & 10.9579 & 0.892073 \tabularnewline
239 & 13.6 & 16.3006 & -2.70055 \tabularnewline
240 & 11.7 & 12.3337 & -0.633705 \tabularnewline
241 & 12.4 & 12.2121 & 0.187945 \tabularnewline
242 & 13.35 & 13.8138 & -0.463846 \tabularnewline
243 & 11.4 & 9.64557 & 1.75443 \tabularnewline
244 & 14.9 & 8.27125 & 6.62875 \tabularnewline
245 & 19.9 & 21.9146 & -2.01465 \tabularnewline
246 & 11.2 & 8.95318 & 2.24682 \tabularnewline
247 & 14.6 & 10.2423 & 4.35772 \tabularnewline
248 & 17.6 & 16.5797 & 1.0203 \tabularnewline
249 & 14.05 & 10.9975 & 3.05248 \tabularnewline
250 & 16.1 & 15.7975 & 0.302479 \tabularnewline
251 & 13.35 & 14.1148 & -0.764785 \tabularnewline
252 & 11.85 & 12.6342 & -0.784223 \tabularnewline
253 & 11.95 & 10.026 & 1.92397 \tabularnewline
254 & 14.75 & 12.2233 & 2.52674 \tabularnewline
255 & 15.15 & 14.6967 & 0.453297 \tabularnewline
256 & 13.2 & 9.42515 & 3.77485 \tabularnewline
257 & 16.85 & 21.5582 & -4.70819 \tabularnewline
258 & 7.85 & 12.5259 & -4.67591 \tabularnewline
259 & 7.7 & 7.70721 & -0.00720892 \tabularnewline
260 & 12.6 & 18.0841 & -5.48408 \tabularnewline
261 & 7.85 & 10.7876 & -2.9376 \tabularnewline
262 & 10.95 & 11.1154 & -0.165402 \tabularnewline
263 & 12.35 & 15.8901 & -3.54007 \tabularnewline
264 & 9.95 & 8.30253 & 1.64747 \tabularnewline
265 & 14.9 & 11.2534 & 3.6466 \tabularnewline
266 & 16.65 & 16.642 & 0.00798043 \tabularnewline
267 & 13.4 & 12.8821 & 0.517869 \tabularnewline
268 & 13.95 & 10.8964 & 3.05358 \tabularnewline
269 & 15.7 & 12.0183 & 3.68171 \tabularnewline
270 & 16.85 & 18.8129 & -1.96293 \tabularnewline
271 & 10.95 & 8.22236 & 2.72764 \tabularnewline
272 & 15.35 & 15.4591 & -0.109062 \tabularnewline
273 & 12.2 & 9.86319 & 2.33681 \tabularnewline
274 & 15.1 & 10.234 & 4.86604 \tabularnewline
275 & 17.75 & 15.7031 & 2.04686 \tabularnewline
276 & 15.2 & 13.9769 & 1.22313 \tabularnewline
277 & 14.6 & 10.6994 & 3.90063 \tabularnewline
278 & 16.65 & 21.3823 & -4.73227 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&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]13.2748[/C][C]-0.374814[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.2588[/C][C]-1.05877[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.2837[/C][C]-0.483726[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.9633[/C][C]-5.56329[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.4121[/C][C]-6.71208[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.982[/C][C]-0.382011[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.5292[/C][C]2.27078[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.5253[/C][C]-0.225273[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.5912[/C][C]-1.49116[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.6047[/C][C]-6.40466[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.8612[/C][C]-1.46124[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.3671[/C][C]-6.96706[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.2462[/C][C]-1.64622[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.6576[/C][C]-0.657568[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.7583[/C][C]-6.45829[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.7997[/C][C]-1.49973[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.7329[/C][C]-0.832887[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.7846[/C][C]-3.48458[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.294[/C][C]-3.69397[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.547[/C][C]-2.54704[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9205[/C][C]-6.52051[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.9909[/C][C]0.809078[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.7708[/C][C]-1.97077[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.6928[/C][C]1.10722[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]13.0475[/C][C]-1.34752[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.7204[/C][C]-1.82041[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.9192[/C][C]3.18083[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.187[/C][C]0.212985[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.1255[/C][C]-3.22551[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.3808[/C][C]-0.880813[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.207[/C][C]-3.90701[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.3078[/C][C]-1.60779[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.7142[/C][C]-3.71417[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.5631[/C][C]-2.86309[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.621[/C][C]-1.82102[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.1732[/C][C]-2.8732[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.7418[/C][C]-2.3418[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]13.1242[/C][C]-0.424176[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.5707[/C][C]-4.27073[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.2525[/C][C]-0.452463[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.4397[/C][C]-7.53971[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.236[/C][C]-1.83604[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]12.7694[/C][C]0.23057[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.9958[/C][C]-1.19576[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.5114[/C][C]-0.211395[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.2111[/C][C]-1.91108[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.2574[/C][C]-1.45743[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.9481[/C][C]-5.04814[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.6803[/C][C]0.0197047[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.9883[/C][C]-0.688251[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.5016[/C][C]-0.901587[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]13.0524[/C][C]-6.35243[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.0725[/C][C]-2.17248[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.8501[/C][C]-0.750092[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.3091[/C][C]-0.00912464[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.806[/C][C]-2.70597[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.1807[/C][C]-6.48071[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.9682[/C][C]1.33181[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]12.9455[/C][C]-4.94547[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.0096[/C][C]0.290358[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2311[/C][C]-3.93113[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.7846[/C][C]-0.284582[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.1807[/C][C]-4.58071[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.0159[/C][C]2.88412[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.2864[/C][C]-4.0864[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.9807[/C][C]-3.88067[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.8287[/C][C]-1.7287[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.3368[/C][C]-0.336756[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.7971[/C][C]1.70294[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.7177[/C][C]-0.517735[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.3002[/C][C]-1.00021[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.0172[/C][C]-1.61722[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.3506[/C][C]-4.55057[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.7909[/C][C]0.809116[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.9253[/C][C]0.674651[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.345104[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]13.4221[/C][C]-0.422122[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.6249[/C][C]-0.024894[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]15.7272[/C][C]-2.52716[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.8638[/C][C]-4.96381[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]10.0612[/C][C]-2.36124[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.69339[/C][C]0.806607[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.0216[/C][C]-1.62164[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]19.3922[/C][C]-8.49216[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.06491[/C][C]-2.76491[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]11.667[/C][C]-1.36696[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]13.6965[/C][C]-1.89654[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]12.2815[/C][C]-1.08153[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.6978[/C][C]-4.29778[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.972[/C][C]0.627999[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]13.7518[/C][C]-0.551808[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]19.597[/C][C]-6.99696[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]8.87587[/C][C]-3.27587[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.6542[/C][C]-3.75418[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]14.2794[/C][C]-5.47944[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]11.6633[/C][C]-3.96329[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.8104[/C][C]-5.81036[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]8.81917[/C][C]-1.51917[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]10.6247[/C][C]0.775306[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.4293[/C][C]-4.82932[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]10.084[/C][C]-2.18396[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.0589[/C][C]-2.3589[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]14.256[/C][C]-3.95603[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]11.4783[/C][C]-3.17834[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]8.26881[/C][C]1.33119[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]18.7738[/C][C]-4.57382[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]8.38578[/C][C]0.11422[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]21.0864[/C][C]-7.58644[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]11.5965[/C][C]-6.69654[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]10.0374[/C][C]-3.63737[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.9909[/C][C]-1.39092[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]13.6179[/C][C]-2.01794[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]20.5244[/C][C]-9.4244[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.3713[/C][C]-0.021304[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]7.34046[/C][C]5.35954[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]13.0912[/C][C]5.00882[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]14.6848[/C][C]3.1652[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]17.5556[/C][C]-0.955577[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]9.00522[/C][C]3.59478[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]11.2449[/C][C]5.85505[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]16.0399[/C][C]3.06005[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.732[/C][C]0.367989[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]8.77966[/C][C]4.57034[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]16.3803[/C][C]2.0197[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.1386[/C][C]-2.43861[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]10.8764[/C][C]-0.276388[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.11774[/C][C]3.48226[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.6248[/C][C]0.575206[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]7.77025[/C][C]5.82975[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.8738[/C][C]1.02618[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.7794[/C][C]1.32056[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]11.3333[/C][C]3.16665[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]13.943[/C][C]2.20697[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]12.8843[/C][C]1.86568[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.152[/C][C]-0.351966[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.3293[/C][C]-0.879281[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]8.32346[/C][C]4.32654[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]21.4352[/C][C]-4.0852[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]2.99216[/C][C]5.60784[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.2669[/C][C]2.13308[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.585[/C][C]-1.48496[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.44206[/C][C]5.15794[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.3929[/C][C]2.35712[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]9.95942[/C][C]5.29058[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]14.1764[/C][C]3.47361[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.4089[/C][C]3.94111[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.217[/C][C]-0.567022[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]12.515[/C][C]1.08499[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]12.8788[/C][C]1.47118[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]9.91341[/C][C]4.83659[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]20.7108[/C][C]-2.46076[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.25057[/C][C]2.64943[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.1006[/C][C]4.89943[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]14.2296[/C][C]4.0204[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.7013[/C][C]1.14871[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.3711[/C][C]0.228913[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]8.55763[/C][C]5.29237[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]16.0566[/C][C]2.89341[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]14.4415[/C][C]1.1585[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.7687[/C][C]-0.918712[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]6.26686[/C][C]5.48314[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.434[/C][C]3.01604[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]11.9857[/C][C]3.91432[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]14.5141[/C][C]2.58587[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]10.1228[/C][C]5.9772[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.8326[/C][C]-1.93263[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]5.02922[/C][C]5.92078[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.2616[/C][C]2.1884[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.6079[/C][C]1.49211[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]16.6547[/C][C]-1.65474[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.41499[/C][C]2.93501[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]10.9804[/C][C]4.96958[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]16.3412[/C][C]1.75882[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]12.6638[/C][C]1.93623[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.3506[/C][C]2.04943[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]10.294[/C][C]5.10599[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.691[/C][C]-0.0910428[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]6.82423[/C][C]6.52577[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]16.7383[/C][C]2.36175[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]20.3773[/C][C]-5.02726[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]7.53542[/C][C]0.0645795[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]12.6001[/C][C]0.799887[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]7.59082[/C][C]6.30918[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]16.5642[/C][C]2.53583[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.1382[/C][C]0.11185[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.0802[/C][C]2.81984[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]11.9031[/C][C]4.19686[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]17.1695[/C][C]0.18047[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.1607[/C][C]-1.01072[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.1572[/C][C]-0.00720892[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.2735[/C][C]-2.67346[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]7.68689[/C][C]2.66311[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]19.3279[/C][C]-3.92794[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]4.58211[/C][C]5.01789[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]17.8485[/C][C]0.351482[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.708[/C][C]0.89199[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]12.6003[/C][C]2.24975[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]13.7162[/C][C]1.03376[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.1317[/C][C]1.96835[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]11.9881[/C][C]2.91191[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]12.4786[/C][C]3.77139[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]19.7163[/C][C]-0.466304[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.9406[/C][C]0.659437[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]10.4779[/C][C]3.12212[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]15.0682[/C][C]0.581768[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]10.7131[/C][C]2.03691[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]17.4566[/C][C]-2.85659[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]10.8447[/C][C]-0.994712[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]5.82948[/C][C]6.82052[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]15.0298[/C][C]4.17016[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]18.3682[/C][C]-1.76819[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]8.69937[/C][C]2.50063[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]15.9938[/C][C]-0.743752[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]11.0104[/C][C]0.889602[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]9.35159[/C][C]3.84841[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.547[/C][C]-1.19702[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.49413[/C][C]2.90587[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]10.5488[/C][C]5.30124[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.6273[/C][C]-1.47726[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]8.46062[/C][C]2.68938[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.2746[/C][C]5.37543[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.6029[/C][C]-4.85292[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.643[/C][C]-0.992996[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.25025[/C][C]3.09975[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]8.97762[/C][C]6.62238[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.0883[/C][C]2.21175[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]11.3449[/C][C]3.85505[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.3563[/C][C]2.74367[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]9.88654[/C][C]5.71346[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.1974[/C][C]6.20258[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]13.6821[/C][C]5.36789[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]12.6018[/C][C]5.94819[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.4539[/C][C]0.646101[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]12.7364[/C][C]0.363565[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]16.2616[/C][C]-3.4116[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]18.3368[/C][C]-8.83676[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]5.26478[/C][C]-0.764785[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]10.9579[/C][C]0.892073[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]16.3006[/C][C]-2.70055[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.3337[/C][C]-0.633705[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.2121[/C][C]0.187945[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]13.8138[/C][C]-0.463846[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.64557[/C][C]1.75443[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]8.27125[/C][C]6.62875[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]21.9146[/C][C]-2.01465[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]8.95318[/C][C]2.24682[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]10.2423[/C][C]4.35772[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.5797[/C][C]1.0203[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]10.9975[/C][C]3.05248[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.7975[/C][C]0.302479[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]14.1148[/C][C]-0.764785[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.6342[/C][C]-0.784223[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.026[/C][C]1.92397[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.2233[/C][C]2.52674[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]14.6967[/C][C]0.453297[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]9.42515[/C][C]3.77485[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.5582[/C][C]-4.70819[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.5259[/C][C]-4.67591[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]7.70721[/C][C]-0.00720892[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]18.0841[/C][C]-5.48408[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]10.7876[/C][C]-2.9376[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]11.1154[/C][C]-0.165402[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.8901[/C][C]-3.54007[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.30253[/C][C]1.64747[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.2534[/C][C]3.6466[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.642[/C][C]0.00798043[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]12.8821[/C][C]0.517869[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.8964[/C][C]3.05358[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]12.0183[/C][C]3.68171[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.8129[/C][C]-1.96293[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]8.22236[/C][C]2.72764[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.4591[/C][C]-0.109062[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.86319[/C][C]2.33681[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]10.234[/C][C]4.86604[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.7031[/C][C]2.04686[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]13.9769[/C][C]1.22313[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]10.6994[/C][C]3.90063[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]21.3823[/C][C]-4.73227[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&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
112.913.2748-0.374814
212.213.2588-1.05877
312.813.2837-0.483726
47.412.9633-5.56329
56.713.4121-6.71208
612.612.982-0.382011
714.812.52922.27078
813.313.5253-0.225273
911.112.5912-1.49116
108.214.6047-6.40466
1111.412.8612-1.46124
126.413.3671-6.96706
1310.612.2462-1.64622
141212.6576-0.657568
156.312.7583-6.45829
1611.312.7997-1.49973
1711.912.7329-0.832887
189.312.7846-3.48458
199.613.294-3.69397
201012.547-2.54704
216.412.9205-6.52051
2213.812.99090.809078
2310.812.7708-1.97077
2413.812.69281.10722
2511.713.0475-1.34752
2610.912.7204-1.82041
2716.112.91923.18083
2813.413.1870.212985
299.913.1255-3.22551
3011.512.3808-0.880813
318.312.207-3.90701
3211.713.3078-1.60779
33912.7142-3.71417
349.712.5631-2.86309
3510.812.621-1.82102
3610.313.1732-2.8732
3710.412.7418-2.3418
3812.713.1242-0.424176
399.313.5707-4.27073
4011.812.2525-0.452463
415.913.4397-7.53971
4211.413.236-1.83604
431312.76940.23057
4410.811.9958-1.19576
4512.312.5114-0.211395
4611.313.2111-1.91108
4711.813.2574-1.45743
487.912.9481-5.04814
4912.712.68030.0197047
5012.312.9883-0.688251
5111.612.5016-0.901587
526.713.0524-6.35243
5310.913.0725-2.17248
5412.112.8501-0.750092
5513.313.3091-0.00912464
5610.112.806-2.70597
575.712.1807-6.48071
5814.312.96821.33181
59812.9455-4.94547
6013.313.00960.290358
619.313.2311-3.93113
6212.512.7846-0.284582
637.612.1807-4.58071
6415.913.01592.88412
659.213.2864-4.0864
669.112.9807-3.88067
6711.112.8287-1.7287
681313.3368-0.336756
6914.512.79711.70294
7012.212.7177-0.517735
7112.313.3002-1.00021
7211.413.0172-1.61722
738.813.3506-4.55057
7414.613.79090.809116
7512.611.92530.674651
76NANA0.345104
771313.4221-0.422122
7812.612.6249-0.024894
7913.215.7272-2.52716
809.914.8638-4.96381
817.710.0612-2.36124
8210.59.693390.806607
8313.415.0216-1.62164
8410.919.3922-8.49216
854.37.06491-2.76491
8610.311.667-1.36696
8711.813.6965-1.89654
8811.212.2815-1.08153
8911.415.6978-4.29778
908.67.9720.627999
9113.213.7518-0.551808
9212.619.597-6.99696
935.68.87587-3.27587
949.913.6542-3.75418
958.814.2794-5.47944
967.711.6633-3.96329
97914.8104-5.81036
987.38.81917-1.51917
9911.410.62470.775306
10013.618.4293-4.82932
1017.910.084-2.18396
10210.713.0589-2.3589
10310.314.256-3.95603
1048.311.4783-3.17834
1059.68.268811.33119
10614.218.7738-4.57382
1078.58.385780.11422
10813.521.0864-7.58644
1094.911.5965-6.69654
1106.410.0374-3.63737
1119.610.9909-1.39092
11211.613.6179-2.01794
11311.120.5244-9.4244
1144.354.3713-0.021304
11512.77.340465.35954
11618.113.09125.00882
11717.8514.68483.1652
11816.617.5556-0.955577
11912.69.005223.59478
12017.111.24495.85505
12119.116.03993.06005
12216.115.7320.367989
12313.358.779664.57034
12418.416.38032.0197
12514.717.1386-2.43861
12610.610.8764-0.276388
12712.69.117743.48226
12816.215.62480.575206
12913.67.770255.82975
13018.917.87381.02618
13114.112.77941.32056
13214.511.33333.16665
13316.1513.9432.20697
13414.7512.88431.86568
13514.815.152-0.351966
13612.4513.3293-0.879281
13712.658.323464.32654
13817.3521.4352-4.0852
1398.62.992165.60784
14018.416.26692.13308
14116.117.585-1.48496
14211.66.442065.15794
14317.7515.39292.35712
14415.259.959425.29058
14517.6514.17643.47361
14616.3512.40893.94111
14717.6518.217-0.567022
14813.612.5151.08499
14914.3512.87881.47118
15014.759.913414.83659
15118.2520.7108-2.46076
1529.97.250572.64943
1531611.10064.89943
15418.2514.22964.0204
15516.8515.70131.14871
15614.614.37110.228913
15713.858.557635.29237
15818.9516.05662.89341
15915.614.44151.1585
16014.8515.7687-0.918712
16111.756.266865.48314
16218.4515.4343.01604
16315.911.98573.91432
16417.114.51412.58587
16516.110.12285.9772
16619.921.8326-1.93263
16710.955.029225.92078
16818.4516.26162.1884
16915.113.60791.49211
1701516.6547-1.65474
17111.358.414992.93501
17215.9510.98044.96958
17318.116.34121.75882
17414.612.66381.93623
17515.413.35062.04943
17615.410.2945.10599
17717.617.691-0.0910428
17813.356.824236.52577
17919.116.73832.36175
18015.3520.3773-5.02726
1817.67.535420.0645795
18213.412.60010.799887
18313.97.590826.30918
18419.116.56422.53583
18515.2515.13820.11185
18612.910.08022.81984
18716.111.90314.19686
18817.3517.16950.18047
18913.1514.1607-1.01072
19012.1512.1572-0.00720892
19112.615.2735-2.67346
19210.357.686892.66311
19315.419.3279-3.92794
1949.64.582115.01789
19518.217.84850.351482
19613.612.7080.89199
19714.8512.60032.24975
19814.7513.71621.03376
19914.112.13171.96835
20014.911.98812.91191
20116.2512.47863.77139
20219.2519.7163-0.466304
20313.612.94060.659437
20413.610.47793.12212
20515.6515.06820.581768
20612.7510.71312.03691
20714.617.4566-2.85659
2089.8510.8447-0.994712
20912.655.829486.82052
21019.215.02984.17016
21116.618.3682-1.76819
21211.28.699372.50063
21315.2515.9938-0.743752
21411.911.01040.889602
21513.29.351593.84841
21616.3517.547-1.19702
21712.49.494132.90587
21815.8510.54885.30124
21918.1519.6273-1.47726
22011.158.460622.68938
22115.6510.27465.37543
22217.7522.6029-4.85292
2237.658.643-0.992996
22412.359.250253.09975
22515.68.977626.62238
22619.317.08832.21175
22715.211.34493.85505
22817.114.35632.74367
22915.69.886545.71346
23018.412.19746.20258
23119.0513.68215.36789
23218.5512.60185.94819
23319.118.45390.646101
23413.112.73640.363565
23512.8516.2616-3.4116
2369.518.3368-8.83676
2374.55.26478-0.764785
23811.8510.95790.892073
23913.616.3006-2.70055
24011.712.3337-0.633705
24112.412.21210.187945
24213.3513.8138-0.463846
24311.49.645571.75443
24414.98.271256.62875
24519.921.9146-2.01465
24611.28.953182.24682
24714.610.24234.35772
24817.616.57971.0203
24914.0510.99753.05248
25016.115.79750.302479
25113.3514.1148-0.764785
25211.8512.6342-0.784223
25311.9510.0261.92397
25414.7512.22332.52674
25515.1514.69670.453297
25613.29.425153.77485
25716.8521.5582-4.70819
2587.8512.5259-4.67591
2597.77.70721-0.00720892
26012.618.0841-5.48408
2617.8510.7876-2.9376
26210.9511.1154-0.165402
26312.3515.8901-3.54007
2649.958.302531.64747
26514.911.25343.6466
26616.6516.6420.00798043
26713.412.88210.517869
26813.9510.89643.05358
26915.712.01833.68171
27016.8518.8129-1.96293
27110.958.222362.72764
27215.3515.4591-0.109062
27312.29.863192.33681
27415.110.2344.86604
27517.7515.70312.04686
27615.213.97691.22313
27714.610.69943.90063
27816.6521.3823-4.73227
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.5137650.9724690.486235
70.3453510.6907010.654649
80.3854050.770810.614595
90.2762530.5525070.723747
100.2374130.4748260.762587
110.1614610.3229220.838539
120.1730940.3461880.826906
130.1447320.2894630.855268
140.0973170.1946340.902683
150.13480.2695990.8652
160.09545410.1909080.904546
170.06359380.1271880.936406
180.04835890.09671770.951641
190.03201150.0640230.967988
200.02041980.04083950.97958
210.02776840.05553670.972232
220.04209330.08418670.957907
230.0281790.0563580.971821
240.02774230.05548460.972258
250.02131460.04262910.978685
260.01421510.02843020.985785
270.03640130.07280260.963599
280.03130950.0626190.96869
290.0222490.0444980.977751
300.01544610.03089230.984554
310.0378750.07574990.962125
320.02814450.05628890.971856
330.02388330.04776660.976117
340.02023030.04046060.97977
350.01432930.02865860.985671
360.01025380.02050750.989746
370.007202230.01440450.992798
380.005860510.0117210.994139
390.004421590.008843170.995578
400.002924860.005849710.997075
410.008657890.01731580.991342
420.006206890.01241380.993793
430.004994880.009989760.995005
440.003738350.007476710.996262
450.002530830.005061670.997469
460.001849320.003698640.998151
470.001308020.002616030.998692
480.001414680.002829360.998585
490.001175910.002351830.998824
500.000843230.001686460.999157
510.0005591750.001118350.999441
520.001100410.002200830.9989
530.0007531050.001506210.999247
540.0005681590.001136320.999432
550.0005821780.001164360.999418
560.0004165520.0008331040.999583
570.001656610.003313220.998343
580.00191960.003839210.99808
590.002177970.004355950.997822
600.001933650.003867290.998066
610.001617190.003234380.998383
620.001261780.002523570.998738
630.001665410.003330830.998335
640.00301980.00603960.99698
650.002674550.005349090.997325
660.002409010.004818010.997591
670.001791720.003583440.998208
680.001549730.003099470.99845
690.001734820.003469630.998265
700.001281980.002563950.998718
710.0009848980.00196980.999015
720.0007167390.001433480.999283
730.0007048070.001409610.999295
740.0008715360.001743070.999128
750.0006598670.001319730.99934
760.0005206760.001041350.999479
770.0003870260.0007740530.999613
780.0003365020.0006730050.999663
790.000267750.00053550.999732
800.0003566320.0007132640.999643
810.0002679680.0005359350.999732
820.0002336930.0004673870.999766
830.0001674470.0003348930.999833
840.001090090.002180170.99891
850.0008824340.001764870.999118
860.0006752060.001350410.999325
870.0005135280.001027060.999486
880.0003822220.0007644440.999618
890.0004071880.0008143750.999593
900.0003475560.0006951130.999652
910.000272230.000544460.999728
920.0009157390.001831480.999084
930.0007962240.001592450.999204
940.0008119090.001623820.999188
950.00117440.002348810.998826
960.001184610.002369220.998815
970.001909890.003819770.99809
980.001527810.003055630.998472
990.001402730.002805470.998597
1000.00182220.00364440.998178
1010.001510790.003021570.998489
1020.001285050.00257010.998715
1030.001503340.003006680.998497
1040.0014140.0028280.998586
1050.001472280.002944560.998528
1060.001788520.003577040.998211
1070.001636230.003272450.998364
1080.006471020.0129420.993529
1090.01395750.02791510.986042
1100.01431030.02862060.98569
1110.01258640.02517280.987414
1120.01126370.02252730.988736
1130.05453580.1090720.945464
1140.04849620.09699230.951504
1150.09936510.198730.900635
1160.1672650.3345290.832735
1170.2074090.4148170.792591
1180.1948290.3896570.805171
1190.2441820.4883650.755818
1200.3845080.7690150.615492
1210.4152050.8304110.584795
1220.3954910.7909810.604509
1230.4762670.9525340.523733
1240.4785820.9571650.521418
1250.4713790.9427570.528621
1260.4482860.8965730.551714
1270.4743760.9487520.525624
1280.453610.907220.54639
1290.5780770.8438470.421923
1300.5591340.8817320.440866
1310.5424840.9150310.457516
1320.559840.8803190.44016
1330.5530180.8939640.446982
1340.542760.9144790.45724
1350.5163180.9673650.483682
1360.4928020.9856050.507198
1370.5371380.9257240.462862
1380.5744820.8510360.425518
1390.6588590.6822810.341141
1400.6516870.6966260.348313
1410.6345450.7309110.365455
1420.6923920.6152150.307608
1430.685310.6293790.31469
1440.7382390.5235230.261761
1450.7466250.5067490.253375
1460.7665150.4669710.233485
1470.7457650.5084710.254235
1480.7246850.5506310.275315
1490.7049440.5901130.295056
1500.7429740.5140520.257026
1510.7437430.5125140.256257
1520.736110.5277810.26389
1530.7713840.4572320.228616
1540.783250.43350.21675
1550.7628350.4743310.237165
1560.7390930.5218150.260907
1570.780670.438660.21933
1580.7749090.4501830.225091
1590.751840.4963190.24816
1600.7325630.5348750.267437
1610.7775660.4448670.222434
1620.7719360.4561290.228064
1630.7790.4420.221
1640.7665010.4669990.233499
1650.818920.3621610.18108
1660.8112160.3775680.188784
1670.8549420.2901150.145058
1680.8419260.3161480.158074
1690.8232880.3534240.176712
1700.8128040.3743930.187196
1710.8050390.3899210.194961
1720.8286170.3427650.171383
1730.8106860.3786270.189314
1740.7918680.4162650.208132
1750.772870.454260.22713
1760.8003120.3993750.199688
1770.775440.449120.22456
1780.8388010.3223970.161199
1790.8247130.3505730.175287
1800.8680770.2638470.131923
1810.8484730.3030550.151527
1820.8267440.3465120.173256
1830.8732840.2534320.126716
1840.8618160.2763680.138184
1850.8412280.3175440.158772
1860.830230.3395410.16977
1870.836730.3265390.16327
1880.8147060.3705890.185294
1890.7967290.4065410.203271
1900.7726790.4546420.227321
1910.7730190.4539610.226981
1920.7564630.4870730.243537
1930.7835150.432970.216485
1940.8049740.3900510.195026
1950.7781620.4436750.221838
1960.7493490.5013020.250651
1970.7268980.5462040.273102
1980.6955960.6088080.304404
1990.6680220.6639560.331978
2000.650610.698780.34939
2010.6819610.6360780.318039
2020.6469080.7061850.353092
2030.611380.777240.38862
2040.5934030.8131940.406597
2050.5615870.8768260.438413
2060.5294230.9411530.470577
2070.5413570.9172850.458643
2080.5054480.9891040.494552
2090.5900780.8198440.409922
2100.5910770.8178450.408923
2110.5732680.8534640.426732
2120.5451050.909790.454895
2130.516980.9660410.48302
2140.4792340.9584680.520766
2150.4706090.9412190.529391
2160.4373250.8746490.562675
2170.4195660.8391320.580434
2180.4533250.906650.546675
2190.4293990.8587980.570601
2200.4043280.8086550.595672
2210.4356430.8712850.564357
2220.5276610.9446780.472339
2230.492710.9854190.50729
2240.4708710.9417430.529129
2250.5656010.8687980.434399
2260.5346030.9307930.465397
2270.5308890.9382210.469111
2280.5011650.997670.498835
2290.5526920.8946150.447308
2300.6429810.7140370.357019
2310.6918530.6162940.308147
2320.7745190.4509630.225481
2330.7370220.5259550.262978
2340.6958320.6083360.304168
2350.7058840.5882320.294116
2360.924170.151660.0758298
2370.9083790.1832410.0916205
2380.8853140.2293720.114686
2390.8754430.2491150.124557
2400.8539170.2921650.146083
2410.8258170.3483670.174183
2420.7907070.4185850.209293
2430.7531630.4936740.246837
2440.8601770.2796460.139823
2450.8433160.3133680.156684
2460.8154720.3690570.184528
2470.8475580.3048830.152442
2480.8161860.3676280.183814
2490.7956850.408630.204315
2500.7504020.4991950.249598
2510.7074860.5850280.292514
2520.6577970.6844060.342203
2530.6129960.7740070.387004
2540.6813260.6373490.318674
2550.6454070.7091850.354593
2560.6338640.7322710.366136
2570.717030.565940.28297
2580.9138480.1723050.0861523
2590.8823850.235230.117615
2600.9161940.1676130.0838064
2610.9213180.1573640.0786819
2620.8909770.2180450.109023
2630.9130890.1738220.086911
2640.8748830.2502350.125117
2650.8578870.2842260.142113
2660.8044860.3910280.195514
2670.7322510.5354980.267749
2680.6582470.6835060.341753
2690.543810.9123810.45619
2700.795820.4083610.20418
2710.6735620.6528760.326438
2720.5469050.906190.453095
2730.3547950.709590.645205

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.513765 & 0.972469 & 0.486235 \tabularnewline
7 & 0.345351 & 0.690701 & 0.654649 \tabularnewline
8 & 0.385405 & 0.77081 & 0.614595 \tabularnewline
9 & 0.276253 & 0.552507 & 0.723747 \tabularnewline
10 & 0.237413 & 0.474826 & 0.762587 \tabularnewline
11 & 0.161461 & 0.322922 & 0.838539 \tabularnewline
12 & 0.173094 & 0.346188 & 0.826906 \tabularnewline
13 & 0.144732 & 0.289463 & 0.855268 \tabularnewline
14 & 0.097317 & 0.194634 & 0.902683 \tabularnewline
15 & 0.1348 & 0.269599 & 0.8652 \tabularnewline
16 & 0.0954541 & 0.190908 & 0.904546 \tabularnewline
17 & 0.0635938 & 0.127188 & 0.936406 \tabularnewline
18 & 0.0483589 & 0.0967177 & 0.951641 \tabularnewline
19 & 0.0320115 & 0.064023 & 0.967988 \tabularnewline
20 & 0.0204198 & 0.0408395 & 0.97958 \tabularnewline
21 & 0.0277684 & 0.0555367 & 0.972232 \tabularnewline
22 & 0.0420933 & 0.0841867 & 0.957907 \tabularnewline
23 & 0.028179 & 0.056358 & 0.971821 \tabularnewline
24 & 0.0277423 & 0.0554846 & 0.972258 \tabularnewline
25 & 0.0213146 & 0.0426291 & 0.978685 \tabularnewline
26 & 0.0142151 & 0.0284302 & 0.985785 \tabularnewline
27 & 0.0364013 & 0.0728026 & 0.963599 \tabularnewline
28 & 0.0313095 & 0.062619 & 0.96869 \tabularnewline
29 & 0.022249 & 0.044498 & 0.977751 \tabularnewline
30 & 0.0154461 & 0.0308923 & 0.984554 \tabularnewline
31 & 0.037875 & 0.0757499 & 0.962125 \tabularnewline
32 & 0.0281445 & 0.0562889 & 0.971856 \tabularnewline
33 & 0.0238833 & 0.0477666 & 0.976117 \tabularnewline
34 & 0.0202303 & 0.0404606 & 0.97977 \tabularnewline
35 & 0.0143293 & 0.0286586 & 0.985671 \tabularnewline
36 & 0.0102538 & 0.0205075 & 0.989746 \tabularnewline
37 & 0.00720223 & 0.0144045 & 0.992798 \tabularnewline
38 & 0.00586051 & 0.011721 & 0.994139 \tabularnewline
39 & 0.00442159 & 0.00884317 & 0.995578 \tabularnewline
40 & 0.00292486 & 0.00584971 & 0.997075 \tabularnewline
41 & 0.00865789 & 0.0173158 & 0.991342 \tabularnewline
42 & 0.00620689 & 0.0124138 & 0.993793 \tabularnewline
43 & 0.00499488 & 0.00998976 & 0.995005 \tabularnewline
44 & 0.00373835 & 0.00747671 & 0.996262 \tabularnewline
45 & 0.00253083 & 0.00506167 & 0.997469 \tabularnewline
46 & 0.00184932 & 0.00369864 & 0.998151 \tabularnewline
47 & 0.00130802 & 0.00261603 & 0.998692 \tabularnewline
48 & 0.00141468 & 0.00282936 & 0.998585 \tabularnewline
49 & 0.00117591 & 0.00235183 & 0.998824 \tabularnewline
50 & 0.00084323 & 0.00168646 & 0.999157 \tabularnewline
51 & 0.000559175 & 0.00111835 & 0.999441 \tabularnewline
52 & 0.00110041 & 0.00220083 & 0.9989 \tabularnewline
53 & 0.000753105 & 0.00150621 & 0.999247 \tabularnewline
54 & 0.000568159 & 0.00113632 & 0.999432 \tabularnewline
55 & 0.000582178 & 0.00116436 & 0.999418 \tabularnewline
56 & 0.000416552 & 0.000833104 & 0.999583 \tabularnewline
57 & 0.00165661 & 0.00331322 & 0.998343 \tabularnewline
58 & 0.0019196 & 0.00383921 & 0.99808 \tabularnewline
59 & 0.00217797 & 0.00435595 & 0.997822 \tabularnewline
60 & 0.00193365 & 0.00386729 & 0.998066 \tabularnewline
61 & 0.00161719 & 0.00323438 & 0.998383 \tabularnewline
62 & 0.00126178 & 0.00252357 & 0.998738 \tabularnewline
63 & 0.00166541 & 0.00333083 & 0.998335 \tabularnewline
64 & 0.0030198 & 0.0060396 & 0.99698 \tabularnewline
65 & 0.00267455 & 0.00534909 & 0.997325 \tabularnewline
66 & 0.00240901 & 0.00481801 & 0.997591 \tabularnewline
67 & 0.00179172 & 0.00358344 & 0.998208 \tabularnewline
68 & 0.00154973 & 0.00309947 & 0.99845 \tabularnewline
69 & 0.00173482 & 0.00346963 & 0.998265 \tabularnewline
70 & 0.00128198 & 0.00256395 & 0.998718 \tabularnewline
71 & 0.000984898 & 0.0019698 & 0.999015 \tabularnewline
72 & 0.000716739 & 0.00143348 & 0.999283 \tabularnewline
73 & 0.000704807 & 0.00140961 & 0.999295 \tabularnewline
74 & 0.000871536 & 0.00174307 & 0.999128 \tabularnewline
75 & 0.000659867 & 0.00131973 & 0.99934 \tabularnewline
76 & 0.000520676 & 0.00104135 & 0.999479 \tabularnewline
77 & 0.000387026 & 0.000774053 & 0.999613 \tabularnewline
78 & 0.000336502 & 0.000673005 & 0.999663 \tabularnewline
79 & 0.00026775 & 0.0005355 & 0.999732 \tabularnewline
80 & 0.000356632 & 0.000713264 & 0.999643 \tabularnewline
81 & 0.000267968 & 0.000535935 & 0.999732 \tabularnewline
82 & 0.000233693 & 0.000467387 & 0.999766 \tabularnewline
83 & 0.000167447 & 0.000334893 & 0.999833 \tabularnewline
84 & 0.00109009 & 0.00218017 & 0.99891 \tabularnewline
85 & 0.000882434 & 0.00176487 & 0.999118 \tabularnewline
86 & 0.000675206 & 0.00135041 & 0.999325 \tabularnewline
87 & 0.000513528 & 0.00102706 & 0.999486 \tabularnewline
88 & 0.000382222 & 0.000764444 & 0.999618 \tabularnewline
89 & 0.000407188 & 0.000814375 & 0.999593 \tabularnewline
90 & 0.000347556 & 0.000695113 & 0.999652 \tabularnewline
91 & 0.00027223 & 0.00054446 & 0.999728 \tabularnewline
92 & 0.000915739 & 0.00183148 & 0.999084 \tabularnewline
93 & 0.000796224 & 0.00159245 & 0.999204 \tabularnewline
94 & 0.000811909 & 0.00162382 & 0.999188 \tabularnewline
95 & 0.0011744 & 0.00234881 & 0.998826 \tabularnewline
96 & 0.00118461 & 0.00236922 & 0.998815 \tabularnewline
97 & 0.00190989 & 0.00381977 & 0.99809 \tabularnewline
98 & 0.00152781 & 0.00305563 & 0.998472 \tabularnewline
99 & 0.00140273 & 0.00280547 & 0.998597 \tabularnewline
100 & 0.0018222 & 0.0036444 & 0.998178 \tabularnewline
101 & 0.00151079 & 0.00302157 & 0.998489 \tabularnewline
102 & 0.00128505 & 0.0025701 & 0.998715 \tabularnewline
103 & 0.00150334 & 0.00300668 & 0.998497 \tabularnewline
104 & 0.001414 & 0.002828 & 0.998586 \tabularnewline
105 & 0.00147228 & 0.00294456 & 0.998528 \tabularnewline
106 & 0.00178852 & 0.00357704 & 0.998211 \tabularnewline
107 & 0.00163623 & 0.00327245 & 0.998364 \tabularnewline
108 & 0.00647102 & 0.012942 & 0.993529 \tabularnewline
109 & 0.0139575 & 0.0279151 & 0.986042 \tabularnewline
110 & 0.0143103 & 0.0286206 & 0.98569 \tabularnewline
111 & 0.0125864 & 0.0251728 & 0.987414 \tabularnewline
112 & 0.0112637 & 0.0225273 & 0.988736 \tabularnewline
113 & 0.0545358 & 0.109072 & 0.945464 \tabularnewline
114 & 0.0484962 & 0.0969923 & 0.951504 \tabularnewline
115 & 0.0993651 & 0.19873 & 0.900635 \tabularnewline
116 & 0.167265 & 0.334529 & 0.832735 \tabularnewline
117 & 0.207409 & 0.414817 & 0.792591 \tabularnewline
118 & 0.194829 & 0.389657 & 0.805171 \tabularnewline
119 & 0.244182 & 0.488365 & 0.755818 \tabularnewline
120 & 0.384508 & 0.769015 & 0.615492 \tabularnewline
121 & 0.415205 & 0.830411 & 0.584795 \tabularnewline
122 & 0.395491 & 0.790981 & 0.604509 \tabularnewline
123 & 0.476267 & 0.952534 & 0.523733 \tabularnewline
124 & 0.478582 & 0.957165 & 0.521418 \tabularnewline
125 & 0.471379 & 0.942757 & 0.528621 \tabularnewline
126 & 0.448286 & 0.896573 & 0.551714 \tabularnewline
127 & 0.474376 & 0.948752 & 0.525624 \tabularnewline
128 & 0.45361 & 0.90722 & 0.54639 \tabularnewline
129 & 0.578077 & 0.843847 & 0.421923 \tabularnewline
130 & 0.559134 & 0.881732 & 0.440866 \tabularnewline
131 & 0.542484 & 0.915031 & 0.457516 \tabularnewline
132 & 0.55984 & 0.880319 & 0.44016 \tabularnewline
133 & 0.553018 & 0.893964 & 0.446982 \tabularnewline
134 & 0.54276 & 0.914479 & 0.45724 \tabularnewline
135 & 0.516318 & 0.967365 & 0.483682 \tabularnewline
136 & 0.492802 & 0.985605 & 0.507198 \tabularnewline
137 & 0.537138 & 0.925724 & 0.462862 \tabularnewline
138 & 0.574482 & 0.851036 & 0.425518 \tabularnewline
139 & 0.658859 & 0.682281 & 0.341141 \tabularnewline
140 & 0.651687 & 0.696626 & 0.348313 \tabularnewline
141 & 0.634545 & 0.730911 & 0.365455 \tabularnewline
142 & 0.692392 & 0.615215 & 0.307608 \tabularnewline
143 & 0.68531 & 0.629379 & 0.31469 \tabularnewline
144 & 0.738239 & 0.523523 & 0.261761 \tabularnewline
145 & 0.746625 & 0.506749 & 0.253375 \tabularnewline
146 & 0.766515 & 0.466971 & 0.233485 \tabularnewline
147 & 0.745765 & 0.508471 & 0.254235 \tabularnewline
148 & 0.724685 & 0.550631 & 0.275315 \tabularnewline
149 & 0.704944 & 0.590113 & 0.295056 \tabularnewline
150 & 0.742974 & 0.514052 & 0.257026 \tabularnewline
151 & 0.743743 & 0.512514 & 0.256257 \tabularnewline
152 & 0.73611 & 0.527781 & 0.26389 \tabularnewline
153 & 0.771384 & 0.457232 & 0.228616 \tabularnewline
154 & 0.78325 & 0.4335 & 0.21675 \tabularnewline
155 & 0.762835 & 0.474331 & 0.237165 \tabularnewline
156 & 0.739093 & 0.521815 & 0.260907 \tabularnewline
157 & 0.78067 & 0.43866 & 0.21933 \tabularnewline
158 & 0.774909 & 0.450183 & 0.225091 \tabularnewline
159 & 0.75184 & 0.496319 & 0.24816 \tabularnewline
160 & 0.732563 & 0.534875 & 0.267437 \tabularnewline
161 & 0.777566 & 0.444867 & 0.222434 \tabularnewline
162 & 0.771936 & 0.456129 & 0.228064 \tabularnewline
163 & 0.779 & 0.442 & 0.221 \tabularnewline
164 & 0.766501 & 0.466999 & 0.233499 \tabularnewline
165 & 0.81892 & 0.362161 & 0.18108 \tabularnewline
166 & 0.811216 & 0.377568 & 0.188784 \tabularnewline
167 & 0.854942 & 0.290115 & 0.145058 \tabularnewline
168 & 0.841926 & 0.316148 & 0.158074 \tabularnewline
169 & 0.823288 & 0.353424 & 0.176712 \tabularnewline
170 & 0.812804 & 0.374393 & 0.187196 \tabularnewline
171 & 0.805039 & 0.389921 & 0.194961 \tabularnewline
172 & 0.828617 & 0.342765 & 0.171383 \tabularnewline
173 & 0.810686 & 0.378627 & 0.189314 \tabularnewline
174 & 0.791868 & 0.416265 & 0.208132 \tabularnewline
175 & 0.77287 & 0.45426 & 0.22713 \tabularnewline
176 & 0.800312 & 0.399375 & 0.199688 \tabularnewline
177 & 0.77544 & 0.44912 & 0.22456 \tabularnewline
178 & 0.838801 & 0.322397 & 0.161199 \tabularnewline
179 & 0.824713 & 0.350573 & 0.175287 \tabularnewline
180 & 0.868077 & 0.263847 & 0.131923 \tabularnewline
181 & 0.848473 & 0.303055 & 0.151527 \tabularnewline
182 & 0.826744 & 0.346512 & 0.173256 \tabularnewline
183 & 0.873284 & 0.253432 & 0.126716 \tabularnewline
184 & 0.861816 & 0.276368 & 0.138184 \tabularnewline
185 & 0.841228 & 0.317544 & 0.158772 \tabularnewline
186 & 0.83023 & 0.339541 & 0.16977 \tabularnewline
187 & 0.83673 & 0.326539 & 0.16327 \tabularnewline
188 & 0.814706 & 0.370589 & 0.185294 \tabularnewline
189 & 0.796729 & 0.406541 & 0.203271 \tabularnewline
190 & 0.772679 & 0.454642 & 0.227321 \tabularnewline
191 & 0.773019 & 0.453961 & 0.226981 \tabularnewline
192 & 0.756463 & 0.487073 & 0.243537 \tabularnewline
193 & 0.783515 & 0.43297 & 0.216485 \tabularnewline
194 & 0.804974 & 0.390051 & 0.195026 \tabularnewline
195 & 0.778162 & 0.443675 & 0.221838 \tabularnewline
196 & 0.749349 & 0.501302 & 0.250651 \tabularnewline
197 & 0.726898 & 0.546204 & 0.273102 \tabularnewline
198 & 0.695596 & 0.608808 & 0.304404 \tabularnewline
199 & 0.668022 & 0.663956 & 0.331978 \tabularnewline
200 & 0.65061 & 0.69878 & 0.34939 \tabularnewline
201 & 0.681961 & 0.636078 & 0.318039 \tabularnewline
202 & 0.646908 & 0.706185 & 0.353092 \tabularnewline
203 & 0.61138 & 0.77724 & 0.38862 \tabularnewline
204 & 0.593403 & 0.813194 & 0.406597 \tabularnewline
205 & 0.561587 & 0.876826 & 0.438413 \tabularnewline
206 & 0.529423 & 0.941153 & 0.470577 \tabularnewline
207 & 0.541357 & 0.917285 & 0.458643 \tabularnewline
208 & 0.505448 & 0.989104 & 0.494552 \tabularnewline
209 & 0.590078 & 0.819844 & 0.409922 \tabularnewline
210 & 0.591077 & 0.817845 & 0.408923 \tabularnewline
211 & 0.573268 & 0.853464 & 0.426732 \tabularnewline
212 & 0.545105 & 0.90979 & 0.454895 \tabularnewline
213 & 0.51698 & 0.966041 & 0.48302 \tabularnewline
214 & 0.479234 & 0.958468 & 0.520766 \tabularnewline
215 & 0.470609 & 0.941219 & 0.529391 \tabularnewline
216 & 0.437325 & 0.874649 & 0.562675 \tabularnewline
217 & 0.419566 & 0.839132 & 0.580434 \tabularnewline
218 & 0.453325 & 0.90665 & 0.546675 \tabularnewline
219 & 0.429399 & 0.858798 & 0.570601 \tabularnewline
220 & 0.404328 & 0.808655 & 0.595672 \tabularnewline
221 & 0.435643 & 0.871285 & 0.564357 \tabularnewline
222 & 0.527661 & 0.944678 & 0.472339 \tabularnewline
223 & 0.49271 & 0.985419 & 0.50729 \tabularnewline
224 & 0.470871 & 0.941743 & 0.529129 \tabularnewline
225 & 0.565601 & 0.868798 & 0.434399 \tabularnewline
226 & 0.534603 & 0.930793 & 0.465397 \tabularnewline
227 & 0.530889 & 0.938221 & 0.469111 \tabularnewline
228 & 0.501165 & 0.99767 & 0.498835 \tabularnewline
229 & 0.552692 & 0.894615 & 0.447308 \tabularnewline
230 & 0.642981 & 0.714037 & 0.357019 \tabularnewline
231 & 0.691853 & 0.616294 & 0.308147 \tabularnewline
232 & 0.774519 & 0.450963 & 0.225481 \tabularnewline
233 & 0.737022 & 0.525955 & 0.262978 \tabularnewline
234 & 0.695832 & 0.608336 & 0.304168 \tabularnewline
235 & 0.705884 & 0.588232 & 0.294116 \tabularnewline
236 & 0.92417 & 0.15166 & 0.0758298 \tabularnewline
237 & 0.908379 & 0.183241 & 0.0916205 \tabularnewline
238 & 0.885314 & 0.229372 & 0.114686 \tabularnewline
239 & 0.875443 & 0.249115 & 0.124557 \tabularnewline
240 & 0.853917 & 0.292165 & 0.146083 \tabularnewline
241 & 0.825817 & 0.348367 & 0.174183 \tabularnewline
242 & 0.790707 & 0.418585 & 0.209293 \tabularnewline
243 & 0.753163 & 0.493674 & 0.246837 \tabularnewline
244 & 0.860177 & 0.279646 & 0.139823 \tabularnewline
245 & 0.843316 & 0.313368 & 0.156684 \tabularnewline
246 & 0.815472 & 0.369057 & 0.184528 \tabularnewline
247 & 0.847558 & 0.304883 & 0.152442 \tabularnewline
248 & 0.816186 & 0.367628 & 0.183814 \tabularnewline
249 & 0.795685 & 0.40863 & 0.204315 \tabularnewline
250 & 0.750402 & 0.499195 & 0.249598 \tabularnewline
251 & 0.707486 & 0.585028 & 0.292514 \tabularnewline
252 & 0.657797 & 0.684406 & 0.342203 \tabularnewline
253 & 0.612996 & 0.774007 & 0.387004 \tabularnewline
254 & 0.681326 & 0.637349 & 0.318674 \tabularnewline
255 & 0.645407 & 0.709185 & 0.354593 \tabularnewline
256 & 0.633864 & 0.732271 & 0.366136 \tabularnewline
257 & 0.71703 & 0.56594 & 0.28297 \tabularnewline
258 & 0.913848 & 0.172305 & 0.0861523 \tabularnewline
259 & 0.882385 & 0.23523 & 0.117615 \tabularnewline
260 & 0.916194 & 0.167613 & 0.0838064 \tabularnewline
261 & 0.921318 & 0.157364 & 0.0786819 \tabularnewline
262 & 0.890977 & 0.218045 & 0.109023 \tabularnewline
263 & 0.913089 & 0.173822 & 0.086911 \tabularnewline
264 & 0.874883 & 0.250235 & 0.125117 \tabularnewline
265 & 0.857887 & 0.284226 & 0.142113 \tabularnewline
266 & 0.804486 & 0.391028 & 0.195514 \tabularnewline
267 & 0.732251 & 0.535498 & 0.267749 \tabularnewline
268 & 0.658247 & 0.683506 & 0.341753 \tabularnewline
269 & 0.54381 & 0.912381 & 0.45619 \tabularnewline
270 & 0.79582 & 0.408361 & 0.20418 \tabularnewline
271 & 0.673562 & 0.652876 & 0.326438 \tabularnewline
272 & 0.546905 & 0.90619 & 0.453095 \tabularnewline
273 & 0.354795 & 0.70959 & 0.645205 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]6[/C][C]0.513765[/C][C]0.972469[/C][C]0.486235[/C][/ROW]
[ROW][C]7[/C][C]0.345351[/C][C]0.690701[/C][C]0.654649[/C][/ROW]
[ROW][C]8[/C][C]0.385405[/C][C]0.77081[/C][C]0.614595[/C][/ROW]
[ROW][C]9[/C][C]0.276253[/C][C]0.552507[/C][C]0.723747[/C][/ROW]
[ROW][C]10[/C][C]0.237413[/C][C]0.474826[/C][C]0.762587[/C][/ROW]
[ROW][C]11[/C][C]0.161461[/C][C]0.322922[/C][C]0.838539[/C][/ROW]
[ROW][C]12[/C][C]0.173094[/C][C]0.346188[/C][C]0.826906[/C][/ROW]
[ROW][C]13[/C][C]0.144732[/C][C]0.289463[/C][C]0.855268[/C][/ROW]
[ROW][C]14[/C][C]0.097317[/C][C]0.194634[/C][C]0.902683[/C][/ROW]
[ROW][C]15[/C][C]0.1348[/C][C]0.269599[/C][C]0.8652[/C][/ROW]
[ROW][C]16[/C][C]0.0954541[/C][C]0.190908[/C][C]0.904546[/C][/ROW]
[ROW][C]17[/C][C]0.0635938[/C][C]0.127188[/C][C]0.936406[/C][/ROW]
[ROW][C]18[/C][C]0.0483589[/C][C]0.0967177[/C][C]0.951641[/C][/ROW]
[ROW][C]19[/C][C]0.0320115[/C][C]0.064023[/C][C]0.967988[/C][/ROW]
[ROW][C]20[/C][C]0.0204198[/C][C]0.0408395[/C][C]0.97958[/C][/ROW]
[ROW][C]21[/C][C]0.0277684[/C][C]0.0555367[/C][C]0.972232[/C][/ROW]
[ROW][C]22[/C][C]0.0420933[/C][C]0.0841867[/C][C]0.957907[/C][/ROW]
[ROW][C]23[/C][C]0.028179[/C][C]0.056358[/C][C]0.971821[/C][/ROW]
[ROW][C]24[/C][C]0.0277423[/C][C]0.0554846[/C][C]0.972258[/C][/ROW]
[ROW][C]25[/C][C]0.0213146[/C][C]0.0426291[/C][C]0.978685[/C][/ROW]
[ROW][C]26[/C][C]0.0142151[/C][C]0.0284302[/C][C]0.985785[/C][/ROW]
[ROW][C]27[/C][C]0.0364013[/C][C]0.0728026[/C][C]0.963599[/C][/ROW]
[ROW][C]28[/C][C]0.0313095[/C][C]0.062619[/C][C]0.96869[/C][/ROW]
[ROW][C]29[/C][C]0.022249[/C][C]0.044498[/C][C]0.977751[/C][/ROW]
[ROW][C]30[/C][C]0.0154461[/C][C]0.0308923[/C][C]0.984554[/C][/ROW]
[ROW][C]31[/C][C]0.037875[/C][C]0.0757499[/C][C]0.962125[/C][/ROW]
[ROW][C]32[/C][C]0.0281445[/C][C]0.0562889[/C][C]0.971856[/C][/ROW]
[ROW][C]33[/C][C]0.0238833[/C][C]0.0477666[/C][C]0.976117[/C][/ROW]
[ROW][C]34[/C][C]0.0202303[/C][C]0.0404606[/C][C]0.97977[/C][/ROW]
[ROW][C]35[/C][C]0.0143293[/C][C]0.0286586[/C][C]0.985671[/C][/ROW]
[ROW][C]36[/C][C]0.0102538[/C][C]0.0205075[/C][C]0.989746[/C][/ROW]
[ROW][C]37[/C][C]0.00720223[/C][C]0.0144045[/C][C]0.992798[/C][/ROW]
[ROW][C]38[/C][C]0.00586051[/C][C]0.011721[/C][C]0.994139[/C][/ROW]
[ROW][C]39[/C][C]0.00442159[/C][C]0.00884317[/C][C]0.995578[/C][/ROW]
[ROW][C]40[/C][C]0.00292486[/C][C]0.00584971[/C][C]0.997075[/C][/ROW]
[ROW][C]41[/C][C]0.00865789[/C][C]0.0173158[/C][C]0.991342[/C][/ROW]
[ROW][C]42[/C][C]0.00620689[/C][C]0.0124138[/C][C]0.993793[/C][/ROW]
[ROW][C]43[/C][C]0.00499488[/C][C]0.00998976[/C][C]0.995005[/C][/ROW]
[ROW][C]44[/C][C]0.00373835[/C][C]0.00747671[/C][C]0.996262[/C][/ROW]
[ROW][C]45[/C][C]0.00253083[/C][C]0.00506167[/C][C]0.997469[/C][/ROW]
[ROW][C]46[/C][C]0.00184932[/C][C]0.00369864[/C][C]0.998151[/C][/ROW]
[ROW][C]47[/C][C]0.00130802[/C][C]0.00261603[/C][C]0.998692[/C][/ROW]
[ROW][C]48[/C][C]0.00141468[/C][C]0.00282936[/C][C]0.998585[/C][/ROW]
[ROW][C]49[/C][C]0.00117591[/C][C]0.00235183[/C][C]0.998824[/C][/ROW]
[ROW][C]50[/C][C]0.00084323[/C][C]0.00168646[/C][C]0.999157[/C][/ROW]
[ROW][C]51[/C][C]0.000559175[/C][C]0.00111835[/C][C]0.999441[/C][/ROW]
[ROW][C]52[/C][C]0.00110041[/C][C]0.00220083[/C][C]0.9989[/C][/ROW]
[ROW][C]53[/C][C]0.000753105[/C][C]0.00150621[/C][C]0.999247[/C][/ROW]
[ROW][C]54[/C][C]0.000568159[/C][C]0.00113632[/C][C]0.999432[/C][/ROW]
[ROW][C]55[/C][C]0.000582178[/C][C]0.00116436[/C][C]0.999418[/C][/ROW]
[ROW][C]56[/C][C]0.000416552[/C][C]0.000833104[/C][C]0.999583[/C][/ROW]
[ROW][C]57[/C][C]0.00165661[/C][C]0.00331322[/C][C]0.998343[/C][/ROW]
[ROW][C]58[/C][C]0.0019196[/C][C]0.00383921[/C][C]0.99808[/C][/ROW]
[ROW][C]59[/C][C]0.00217797[/C][C]0.00435595[/C][C]0.997822[/C][/ROW]
[ROW][C]60[/C][C]0.00193365[/C][C]0.00386729[/C][C]0.998066[/C][/ROW]
[ROW][C]61[/C][C]0.00161719[/C][C]0.00323438[/C][C]0.998383[/C][/ROW]
[ROW][C]62[/C][C]0.00126178[/C][C]0.00252357[/C][C]0.998738[/C][/ROW]
[ROW][C]63[/C][C]0.00166541[/C][C]0.00333083[/C][C]0.998335[/C][/ROW]
[ROW][C]64[/C][C]0.0030198[/C][C]0.0060396[/C][C]0.99698[/C][/ROW]
[ROW][C]65[/C][C]0.00267455[/C][C]0.00534909[/C][C]0.997325[/C][/ROW]
[ROW][C]66[/C][C]0.00240901[/C][C]0.00481801[/C][C]0.997591[/C][/ROW]
[ROW][C]67[/C][C]0.00179172[/C][C]0.00358344[/C][C]0.998208[/C][/ROW]
[ROW][C]68[/C][C]0.00154973[/C][C]0.00309947[/C][C]0.99845[/C][/ROW]
[ROW][C]69[/C][C]0.00173482[/C][C]0.00346963[/C][C]0.998265[/C][/ROW]
[ROW][C]70[/C][C]0.00128198[/C][C]0.00256395[/C][C]0.998718[/C][/ROW]
[ROW][C]71[/C][C]0.000984898[/C][C]0.0019698[/C][C]0.999015[/C][/ROW]
[ROW][C]72[/C][C]0.000716739[/C][C]0.00143348[/C][C]0.999283[/C][/ROW]
[ROW][C]73[/C][C]0.000704807[/C][C]0.00140961[/C][C]0.999295[/C][/ROW]
[ROW][C]74[/C][C]0.000871536[/C][C]0.00174307[/C][C]0.999128[/C][/ROW]
[ROW][C]75[/C][C]0.000659867[/C][C]0.00131973[/C][C]0.99934[/C][/ROW]
[ROW][C]76[/C][C]0.000520676[/C][C]0.00104135[/C][C]0.999479[/C][/ROW]
[ROW][C]77[/C][C]0.000387026[/C][C]0.000774053[/C][C]0.999613[/C][/ROW]
[ROW][C]78[/C][C]0.000336502[/C][C]0.000673005[/C][C]0.999663[/C][/ROW]
[ROW][C]79[/C][C]0.00026775[/C][C]0.0005355[/C][C]0.999732[/C][/ROW]
[ROW][C]80[/C][C]0.000356632[/C][C]0.000713264[/C][C]0.999643[/C][/ROW]
[ROW][C]81[/C][C]0.000267968[/C][C]0.000535935[/C][C]0.999732[/C][/ROW]
[ROW][C]82[/C][C]0.000233693[/C][C]0.000467387[/C][C]0.999766[/C][/ROW]
[ROW][C]83[/C][C]0.000167447[/C][C]0.000334893[/C][C]0.999833[/C][/ROW]
[ROW][C]84[/C][C]0.00109009[/C][C]0.00218017[/C][C]0.99891[/C][/ROW]
[ROW][C]85[/C][C]0.000882434[/C][C]0.00176487[/C][C]0.999118[/C][/ROW]
[ROW][C]86[/C][C]0.000675206[/C][C]0.00135041[/C][C]0.999325[/C][/ROW]
[ROW][C]87[/C][C]0.000513528[/C][C]0.00102706[/C][C]0.999486[/C][/ROW]
[ROW][C]88[/C][C]0.000382222[/C][C]0.000764444[/C][C]0.999618[/C][/ROW]
[ROW][C]89[/C][C]0.000407188[/C][C]0.000814375[/C][C]0.999593[/C][/ROW]
[ROW][C]90[/C][C]0.000347556[/C][C]0.000695113[/C][C]0.999652[/C][/ROW]
[ROW][C]91[/C][C]0.00027223[/C][C]0.00054446[/C][C]0.999728[/C][/ROW]
[ROW][C]92[/C][C]0.000915739[/C][C]0.00183148[/C][C]0.999084[/C][/ROW]
[ROW][C]93[/C][C]0.000796224[/C][C]0.00159245[/C][C]0.999204[/C][/ROW]
[ROW][C]94[/C][C]0.000811909[/C][C]0.00162382[/C][C]0.999188[/C][/ROW]
[ROW][C]95[/C][C]0.0011744[/C][C]0.00234881[/C][C]0.998826[/C][/ROW]
[ROW][C]96[/C][C]0.00118461[/C][C]0.00236922[/C][C]0.998815[/C][/ROW]
[ROW][C]97[/C][C]0.00190989[/C][C]0.00381977[/C][C]0.99809[/C][/ROW]
[ROW][C]98[/C][C]0.00152781[/C][C]0.00305563[/C][C]0.998472[/C][/ROW]
[ROW][C]99[/C][C]0.00140273[/C][C]0.00280547[/C][C]0.998597[/C][/ROW]
[ROW][C]100[/C][C]0.0018222[/C][C]0.0036444[/C][C]0.998178[/C][/ROW]
[ROW][C]101[/C][C]0.00151079[/C][C]0.00302157[/C][C]0.998489[/C][/ROW]
[ROW][C]102[/C][C]0.00128505[/C][C]0.0025701[/C][C]0.998715[/C][/ROW]
[ROW][C]103[/C][C]0.00150334[/C][C]0.00300668[/C][C]0.998497[/C][/ROW]
[ROW][C]104[/C][C]0.001414[/C][C]0.002828[/C][C]0.998586[/C][/ROW]
[ROW][C]105[/C][C]0.00147228[/C][C]0.00294456[/C][C]0.998528[/C][/ROW]
[ROW][C]106[/C][C]0.00178852[/C][C]0.00357704[/C][C]0.998211[/C][/ROW]
[ROW][C]107[/C][C]0.00163623[/C][C]0.00327245[/C][C]0.998364[/C][/ROW]
[ROW][C]108[/C][C]0.00647102[/C][C]0.012942[/C][C]0.993529[/C][/ROW]
[ROW][C]109[/C][C]0.0139575[/C][C]0.0279151[/C][C]0.986042[/C][/ROW]
[ROW][C]110[/C][C]0.0143103[/C][C]0.0286206[/C][C]0.98569[/C][/ROW]
[ROW][C]111[/C][C]0.0125864[/C][C]0.0251728[/C][C]0.987414[/C][/ROW]
[ROW][C]112[/C][C]0.0112637[/C][C]0.0225273[/C][C]0.988736[/C][/ROW]
[ROW][C]113[/C][C]0.0545358[/C][C]0.109072[/C][C]0.945464[/C][/ROW]
[ROW][C]114[/C][C]0.0484962[/C][C]0.0969923[/C][C]0.951504[/C][/ROW]
[ROW][C]115[/C][C]0.0993651[/C][C]0.19873[/C][C]0.900635[/C][/ROW]
[ROW][C]116[/C][C]0.167265[/C][C]0.334529[/C][C]0.832735[/C][/ROW]
[ROW][C]117[/C][C]0.207409[/C][C]0.414817[/C][C]0.792591[/C][/ROW]
[ROW][C]118[/C][C]0.194829[/C][C]0.389657[/C][C]0.805171[/C][/ROW]
[ROW][C]119[/C][C]0.244182[/C][C]0.488365[/C][C]0.755818[/C][/ROW]
[ROW][C]120[/C][C]0.384508[/C][C]0.769015[/C][C]0.615492[/C][/ROW]
[ROW][C]121[/C][C]0.415205[/C][C]0.830411[/C][C]0.584795[/C][/ROW]
[ROW][C]122[/C][C]0.395491[/C][C]0.790981[/C][C]0.604509[/C][/ROW]
[ROW][C]123[/C][C]0.476267[/C][C]0.952534[/C][C]0.523733[/C][/ROW]
[ROW][C]124[/C][C]0.478582[/C][C]0.957165[/C][C]0.521418[/C][/ROW]
[ROW][C]125[/C][C]0.471379[/C][C]0.942757[/C][C]0.528621[/C][/ROW]
[ROW][C]126[/C][C]0.448286[/C][C]0.896573[/C][C]0.551714[/C][/ROW]
[ROW][C]127[/C][C]0.474376[/C][C]0.948752[/C][C]0.525624[/C][/ROW]
[ROW][C]128[/C][C]0.45361[/C][C]0.90722[/C][C]0.54639[/C][/ROW]
[ROW][C]129[/C][C]0.578077[/C][C]0.843847[/C][C]0.421923[/C][/ROW]
[ROW][C]130[/C][C]0.559134[/C][C]0.881732[/C][C]0.440866[/C][/ROW]
[ROW][C]131[/C][C]0.542484[/C][C]0.915031[/C][C]0.457516[/C][/ROW]
[ROW][C]132[/C][C]0.55984[/C][C]0.880319[/C][C]0.44016[/C][/ROW]
[ROW][C]133[/C][C]0.553018[/C][C]0.893964[/C][C]0.446982[/C][/ROW]
[ROW][C]134[/C][C]0.54276[/C][C]0.914479[/C][C]0.45724[/C][/ROW]
[ROW][C]135[/C][C]0.516318[/C][C]0.967365[/C][C]0.483682[/C][/ROW]
[ROW][C]136[/C][C]0.492802[/C][C]0.985605[/C][C]0.507198[/C][/ROW]
[ROW][C]137[/C][C]0.537138[/C][C]0.925724[/C][C]0.462862[/C][/ROW]
[ROW][C]138[/C][C]0.574482[/C][C]0.851036[/C][C]0.425518[/C][/ROW]
[ROW][C]139[/C][C]0.658859[/C][C]0.682281[/C][C]0.341141[/C][/ROW]
[ROW][C]140[/C][C]0.651687[/C][C]0.696626[/C][C]0.348313[/C][/ROW]
[ROW][C]141[/C][C]0.634545[/C][C]0.730911[/C][C]0.365455[/C][/ROW]
[ROW][C]142[/C][C]0.692392[/C][C]0.615215[/C][C]0.307608[/C][/ROW]
[ROW][C]143[/C][C]0.68531[/C][C]0.629379[/C][C]0.31469[/C][/ROW]
[ROW][C]144[/C][C]0.738239[/C][C]0.523523[/C][C]0.261761[/C][/ROW]
[ROW][C]145[/C][C]0.746625[/C][C]0.506749[/C][C]0.253375[/C][/ROW]
[ROW][C]146[/C][C]0.766515[/C][C]0.466971[/C][C]0.233485[/C][/ROW]
[ROW][C]147[/C][C]0.745765[/C][C]0.508471[/C][C]0.254235[/C][/ROW]
[ROW][C]148[/C][C]0.724685[/C][C]0.550631[/C][C]0.275315[/C][/ROW]
[ROW][C]149[/C][C]0.704944[/C][C]0.590113[/C][C]0.295056[/C][/ROW]
[ROW][C]150[/C][C]0.742974[/C][C]0.514052[/C][C]0.257026[/C][/ROW]
[ROW][C]151[/C][C]0.743743[/C][C]0.512514[/C][C]0.256257[/C][/ROW]
[ROW][C]152[/C][C]0.73611[/C][C]0.527781[/C][C]0.26389[/C][/ROW]
[ROW][C]153[/C][C]0.771384[/C][C]0.457232[/C][C]0.228616[/C][/ROW]
[ROW][C]154[/C][C]0.78325[/C][C]0.4335[/C][C]0.21675[/C][/ROW]
[ROW][C]155[/C][C]0.762835[/C][C]0.474331[/C][C]0.237165[/C][/ROW]
[ROW][C]156[/C][C]0.739093[/C][C]0.521815[/C][C]0.260907[/C][/ROW]
[ROW][C]157[/C][C]0.78067[/C][C]0.43866[/C][C]0.21933[/C][/ROW]
[ROW][C]158[/C][C]0.774909[/C][C]0.450183[/C][C]0.225091[/C][/ROW]
[ROW][C]159[/C][C]0.75184[/C][C]0.496319[/C][C]0.24816[/C][/ROW]
[ROW][C]160[/C][C]0.732563[/C][C]0.534875[/C][C]0.267437[/C][/ROW]
[ROW][C]161[/C][C]0.777566[/C][C]0.444867[/C][C]0.222434[/C][/ROW]
[ROW][C]162[/C][C]0.771936[/C][C]0.456129[/C][C]0.228064[/C][/ROW]
[ROW][C]163[/C][C]0.779[/C][C]0.442[/C][C]0.221[/C][/ROW]
[ROW][C]164[/C][C]0.766501[/C][C]0.466999[/C][C]0.233499[/C][/ROW]
[ROW][C]165[/C][C]0.81892[/C][C]0.362161[/C][C]0.18108[/C][/ROW]
[ROW][C]166[/C][C]0.811216[/C][C]0.377568[/C][C]0.188784[/C][/ROW]
[ROW][C]167[/C][C]0.854942[/C][C]0.290115[/C][C]0.145058[/C][/ROW]
[ROW][C]168[/C][C]0.841926[/C][C]0.316148[/C][C]0.158074[/C][/ROW]
[ROW][C]169[/C][C]0.823288[/C][C]0.353424[/C][C]0.176712[/C][/ROW]
[ROW][C]170[/C][C]0.812804[/C][C]0.374393[/C][C]0.187196[/C][/ROW]
[ROW][C]171[/C][C]0.805039[/C][C]0.389921[/C][C]0.194961[/C][/ROW]
[ROW][C]172[/C][C]0.828617[/C][C]0.342765[/C][C]0.171383[/C][/ROW]
[ROW][C]173[/C][C]0.810686[/C][C]0.378627[/C][C]0.189314[/C][/ROW]
[ROW][C]174[/C][C]0.791868[/C][C]0.416265[/C][C]0.208132[/C][/ROW]
[ROW][C]175[/C][C]0.77287[/C][C]0.45426[/C][C]0.22713[/C][/ROW]
[ROW][C]176[/C][C]0.800312[/C][C]0.399375[/C][C]0.199688[/C][/ROW]
[ROW][C]177[/C][C]0.77544[/C][C]0.44912[/C][C]0.22456[/C][/ROW]
[ROW][C]178[/C][C]0.838801[/C][C]0.322397[/C][C]0.161199[/C][/ROW]
[ROW][C]179[/C][C]0.824713[/C][C]0.350573[/C][C]0.175287[/C][/ROW]
[ROW][C]180[/C][C]0.868077[/C][C]0.263847[/C][C]0.131923[/C][/ROW]
[ROW][C]181[/C][C]0.848473[/C][C]0.303055[/C][C]0.151527[/C][/ROW]
[ROW][C]182[/C][C]0.826744[/C][C]0.346512[/C][C]0.173256[/C][/ROW]
[ROW][C]183[/C][C]0.873284[/C][C]0.253432[/C][C]0.126716[/C][/ROW]
[ROW][C]184[/C][C]0.861816[/C][C]0.276368[/C][C]0.138184[/C][/ROW]
[ROW][C]185[/C][C]0.841228[/C][C]0.317544[/C][C]0.158772[/C][/ROW]
[ROW][C]186[/C][C]0.83023[/C][C]0.339541[/C][C]0.16977[/C][/ROW]
[ROW][C]187[/C][C]0.83673[/C][C]0.326539[/C][C]0.16327[/C][/ROW]
[ROW][C]188[/C][C]0.814706[/C][C]0.370589[/C][C]0.185294[/C][/ROW]
[ROW][C]189[/C][C]0.796729[/C][C]0.406541[/C][C]0.203271[/C][/ROW]
[ROW][C]190[/C][C]0.772679[/C][C]0.454642[/C][C]0.227321[/C][/ROW]
[ROW][C]191[/C][C]0.773019[/C][C]0.453961[/C][C]0.226981[/C][/ROW]
[ROW][C]192[/C][C]0.756463[/C][C]0.487073[/C][C]0.243537[/C][/ROW]
[ROW][C]193[/C][C]0.783515[/C][C]0.43297[/C][C]0.216485[/C][/ROW]
[ROW][C]194[/C][C]0.804974[/C][C]0.390051[/C][C]0.195026[/C][/ROW]
[ROW][C]195[/C][C]0.778162[/C][C]0.443675[/C][C]0.221838[/C][/ROW]
[ROW][C]196[/C][C]0.749349[/C][C]0.501302[/C][C]0.250651[/C][/ROW]
[ROW][C]197[/C][C]0.726898[/C][C]0.546204[/C][C]0.273102[/C][/ROW]
[ROW][C]198[/C][C]0.695596[/C][C]0.608808[/C][C]0.304404[/C][/ROW]
[ROW][C]199[/C][C]0.668022[/C][C]0.663956[/C][C]0.331978[/C][/ROW]
[ROW][C]200[/C][C]0.65061[/C][C]0.69878[/C][C]0.34939[/C][/ROW]
[ROW][C]201[/C][C]0.681961[/C][C]0.636078[/C][C]0.318039[/C][/ROW]
[ROW][C]202[/C][C]0.646908[/C][C]0.706185[/C][C]0.353092[/C][/ROW]
[ROW][C]203[/C][C]0.61138[/C][C]0.77724[/C][C]0.38862[/C][/ROW]
[ROW][C]204[/C][C]0.593403[/C][C]0.813194[/C][C]0.406597[/C][/ROW]
[ROW][C]205[/C][C]0.561587[/C][C]0.876826[/C][C]0.438413[/C][/ROW]
[ROW][C]206[/C][C]0.529423[/C][C]0.941153[/C][C]0.470577[/C][/ROW]
[ROW][C]207[/C][C]0.541357[/C][C]0.917285[/C][C]0.458643[/C][/ROW]
[ROW][C]208[/C][C]0.505448[/C][C]0.989104[/C][C]0.494552[/C][/ROW]
[ROW][C]209[/C][C]0.590078[/C][C]0.819844[/C][C]0.409922[/C][/ROW]
[ROW][C]210[/C][C]0.591077[/C][C]0.817845[/C][C]0.408923[/C][/ROW]
[ROW][C]211[/C][C]0.573268[/C][C]0.853464[/C][C]0.426732[/C][/ROW]
[ROW][C]212[/C][C]0.545105[/C][C]0.90979[/C][C]0.454895[/C][/ROW]
[ROW][C]213[/C][C]0.51698[/C][C]0.966041[/C][C]0.48302[/C][/ROW]
[ROW][C]214[/C][C]0.479234[/C][C]0.958468[/C][C]0.520766[/C][/ROW]
[ROW][C]215[/C][C]0.470609[/C][C]0.941219[/C][C]0.529391[/C][/ROW]
[ROW][C]216[/C][C]0.437325[/C][C]0.874649[/C][C]0.562675[/C][/ROW]
[ROW][C]217[/C][C]0.419566[/C][C]0.839132[/C][C]0.580434[/C][/ROW]
[ROW][C]218[/C][C]0.453325[/C][C]0.90665[/C][C]0.546675[/C][/ROW]
[ROW][C]219[/C][C]0.429399[/C][C]0.858798[/C][C]0.570601[/C][/ROW]
[ROW][C]220[/C][C]0.404328[/C][C]0.808655[/C][C]0.595672[/C][/ROW]
[ROW][C]221[/C][C]0.435643[/C][C]0.871285[/C][C]0.564357[/C][/ROW]
[ROW][C]222[/C][C]0.527661[/C][C]0.944678[/C][C]0.472339[/C][/ROW]
[ROW][C]223[/C][C]0.49271[/C][C]0.985419[/C][C]0.50729[/C][/ROW]
[ROW][C]224[/C][C]0.470871[/C][C]0.941743[/C][C]0.529129[/C][/ROW]
[ROW][C]225[/C][C]0.565601[/C][C]0.868798[/C][C]0.434399[/C][/ROW]
[ROW][C]226[/C][C]0.534603[/C][C]0.930793[/C][C]0.465397[/C][/ROW]
[ROW][C]227[/C][C]0.530889[/C][C]0.938221[/C][C]0.469111[/C][/ROW]
[ROW][C]228[/C][C]0.501165[/C][C]0.99767[/C][C]0.498835[/C][/ROW]
[ROW][C]229[/C][C]0.552692[/C][C]0.894615[/C][C]0.447308[/C][/ROW]
[ROW][C]230[/C][C]0.642981[/C][C]0.714037[/C][C]0.357019[/C][/ROW]
[ROW][C]231[/C][C]0.691853[/C][C]0.616294[/C][C]0.308147[/C][/ROW]
[ROW][C]232[/C][C]0.774519[/C][C]0.450963[/C][C]0.225481[/C][/ROW]
[ROW][C]233[/C][C]0.737022[/C][C]0.525955[/C][C]0.262978[/C][/ROW]
[ROW][C]234[/C][C]0.695832[/C][C]0.608336[/C][C]0.304168[/C][/ROW]
[ROW][C]235[/C][C]0.705884[/C][C]0.588232[/C][C]0.294116[/C][/ROW]
[ROW][C]236[/C][C]0.92417[/C][C]0.15166[/C][C]0.0758298[/C][/ROW]
[ROW][C]237[/C][C]0.908379[/C][C]0.183241[/C][C]0.0916205[/C][/ROW]
[ROW][C]238[/C][C]0.885314[/C][C]0.229372[/C][C]0.114686[/C][/ROW]
[ROW][C]239[/C][C]0.875443[/C][C]0.249115[/C][C]0.124557[/C][/ROW]
[ROW][C]240[/C][C]0.853917[/C][C]0.292165[/C][C]0.146083[/C][/ROW]
[ROW][C]241[/C][C]0.825817[/C][C]0.348367[/C][C]0.174183[/C][/ROW]
[ROW][C]242[/C][C]0.790707[/C][C]0.418585[/C][C]0.209293[/C][/ROW]
[ROW][C]243[/C][C]0.753163[/C][C]0.493674[/C][C]0.246837[/C][/ROW]
[ROW][C]244[/C][C]0.860177[/C][C]0.279646[/C][C]0.139823[/C][/ROW]
[ROW][C]245[/C][C]0.843316[/C][C]0.313368[/C][C]0.156684[/C][/ROW]
[ROW][C]246[/C][C]0.815472[/C][C]0.369057[/C][C]0.184528[/C][/ROW]
[ROW][C]247[/C][C]0.847558[/C][C]0.304883[/C][C]0.152442[/C][/ROW]
[ROW][C]248[/C][C]0.816186[/C][C]0.367628[/C][C]0.183814[/C][/ROW]
[ROW][C]249[/C][C]0.795685[/C][C]0.40863[/C][C]0.204315[/C][/ROW]
[ROW][C]250[/C][C]0.750402[/C][C]0.499195[/C][C]0.249598[/C][/ROW]
[ROW][C]251[/C][C]0.707486[/C][C]0.585028[/C][C]0.292514[/C][/ROW]
[ROW][C]252[/C][C]0.657797[/C][C]0.684406[/C][C]0.342203[/C][/ROW]
[ROW][C]253[/C][C]0.612996[/C][C]0.774007[/C][C]0.387004[/C][/ROW]
[ROW][C]254[/C][C]0.681326[/C][C]0.637349[/C][C]0.318674[/C][/ROW]
[ROW][C]255[/C][C]0.645407[/C][C]0.709185[/C][C]0.354593[/C][/ROW]
[ROW][C]256[/C][C]0.633864[/C][C]0.732271[/C][C]0.366136[/C][/ROW]
[ROW][C]257[/C][C]0.71703[/C][C]0.56594[/C][C]0.28297[/C][/ROW]
[ROW][C]258[/C][C]0.913848[/C][C]0.172305[/C][C]0.0861523[/C][/ROW]
[ROW][C]259[/C][C]0.882385[/C][C]0.23523[/C][C]0.117615[/C][/ROW]
[ROW][C]260[/C][C]0.916194[/C][C]0.167613[/C][C]0.0838064[/C][/ROW]
[ROW][C]261[/C][C]0.921318[/C][C]0.157364[/C][C]0.0786819[/C][/ROW]
[ROW][C]262[/C][C]0.890977[/C][C]0.218045[/C][C]0.109023[/C][/ROW]
[ROW][C]263[/C][C]0.913089[/C][C]0.173822[/C][C]0.086911[/C][/ROW]
[ROW][C]264[/C][C]0.874883[/C][C]0.250235[/C][C]0.125117[/C][/ROW]
[ROW][C]265[/C][C]0.857887[/C][C]0.284226[/C][C]0.142113[/C][/ROW]
[ROW][C]266[/C][C]0.804486[/C][C]0.391028[/C][C]0.195514[/C][/ROW]
[ROW][C]267[/C][C]0.732251[/C][C]0.535498[/C][C]0.267749[/C][/ROW]
[ROW][C]268[/C][C]0.658247[/C][C]0.683506[/C][C]0.341753[/C][/ROW]
[ROW][C]269[/C][C]0.54381[/C][C]0.912381[/C][C]0.45619[/C][/ROW]
[ROW][C]270[/C][C]0.79582[/C][C]0.408361[/C][C]0.20418[/C][/ROW]
[ROW][C]271[/C][C]0.673562[/C][C]0.652876[/C][C]0.326438[/C][/ROW]
[ROW][C]272[/C][C]0.546905[/C][C]0.90619[/C][C]0.453095[/C][/ROW]
[ROW][C]273[/C][C]0.354795[/C][C]0.70959[/C][C]0.645205[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.5137650.9724690.486235
70.3453510.6907010.654649
80.3854050.770810.614595
90.2762530.5525070.723747
100.2374130.4748260.762587
110.1614610.3229220.838539
120.1730940.3461880.826906
130.1447320.2894630.855268
140.0973170.1946340.902683
150.13480.2695990.8652
160.09545410.1909080.904546
170.06359380.1271880.936406
180.04835890.09671770.951641
190.03201150.0640230.967988
200.02041980.04083950.97958
210.02776840.05553670.972232
220.04209330.08418670.957907
230.0281790.0563580.971821
240.02774230.05548460.972258
250.02131460.04262910.978685
260.01421510.02843020.985785
270.03640130.07280260.963599
280.03130950.0626190.96869
290.0222490.0444980.977751
300.01544610.03089230.984554
310.0378750.07574990.962125
320.02814450.05628890.971856
330.02388330.04776660.976117
340.02023030.04046060.97977
350.01432930.02865860.985671
360.01025380.02050750.989746
370.007202230.01440450.992798
380.005860510.0117210.994139
390.004421590.008843170.995578
400.002924860.005849710.997075
410.008657890.01731580.991342
420.006206890.01241380.993793
430.004994880.009989760.995005
440.003738350.007476710.996262
450.002530830.005061670.997469
460.001849320.003698640.998151
470.001308020.002616030.998692
480.001414680.002829360.998585
490.001175910.002351830.998824
500.000843230.001686460.999157
510.0005591750.001118350.999441
520.001100410.002200830.9989
530.0007531050.001506210.999247
540.0005681590.001136320.999432
550.0005821780.001164360.999418
560.0004165520.0008331040.999583
570.001656610.003313220.998343
580.00191960.003839210.99808
590.002177970.004355950.997822
600.001933650.003867290.998066
610.001617190.003234380.998383
620.001261780.002523570.998738
630.001665410.003330830.998335
640.00301980.00603960.99698
650.002674550.005349090.997325
660.002409010.004818010.997591
670.001791720.003583440.998208
680.001549730.003099470.99845
690.001734820.003469630.998265
700.001281980.002563950.998718
710.0009848980.00196980.999015
720.0007167390.001433480.999283
730.0007048070.001409610.999295
740.0008715360.001743070.999128
750.0006598670.001319730.99934
760.0005206760.001041350.999479
770.0003870260.0007740530.999613
780.0003365020.0006730050.999663
790.000267750.00053550.999732
800.0003566320.0007132640.999643
810.0002679680.0005359350.999732
820.0002336930.0004673870.999766
830.0001674470.0003348930.999833
840.001090090.002180170.99891
850.0008824340.001764870.999118
860.0006752060.001350410.999325
870.0005135280.001027060.999486
880.0003822220.0007644440.999618
890.0004071880.0008143750.999593
900.0003475560.0006951130.999652
910.000272230.000544460.999728
920.0009157390.001831480.999084
930.0007962240.001592450.999204
940.0008119090.001623820.999188
950.00117440.002348810.998826
960.001184610.002369220.998815
970.001909890.003819770.99809
980.001527810.003055630.998472
990.001402730.002805470.998597
1000.00182220.00364440.998178
1010.001510790.003021570.998489
1020.001285050.00257010.998715
1030.001503340.003006680.998497
1040.0014140.0028280.998586
1050.001472280.002944560.998528
1060.001788520.003577040.998211
1070.001636230.003272450.998364
1080.006471020.0129420.993529
1090.01395750.02791510.986042
1100.01431030.02862060.98569
1110.01258640.02517280.987414
1120.01126370.02252730.988736
1130.05453580.1090720.945464
1140.04849620.09699230.951504
1150.09936510.198730.900635
1160.1672650.3345290.832735
1170.2074090.4148170.792591
1180.1948290.3896570.805171
1190.2441820.4883650.755818
1200.3845080.7690150.615492
1210.4152050.8304110.584795
1220.3954910.7909810.604509
1230.4762670.9525340.523733
1240.4785820.9571650.521418
1250.4713790.9427570.528621
1260.4482860.8965730.551714
1270.4743760.9487520.525624
1280.453610.907220.54639
1290.5780770.8438470.421923
1300.5591340.8817320.440866
1310.5424840.9150310.457516
1320.559840.8803190.44016
1330.5530180.8939640.446982
1340.542760.9144790.45724
1350.5163180.9673650.483682
1360.4928020.9856050.507198
1370.5371380.9257240.462862
1380.5744820.8510360.425518
1390.6588590.6822810.341141
1400.6516870.6966260.348313
1410.6345450.7309110.365455
1420.6923920.6152150.307608
1430.685310.6293790.31469
1440.7382390.5235230.261761
1450.7466250.5067490.253375
1460.7665150.4669710.233485
1470.7457650.5084710.254235
1480.7246850.5506310.275315
1490.7049440.5901130.295056
1500.7429740.5140520.257026
1510.7437430.5125140.256257
1520.736110.5277810.26389
1530.7713840.4572320.228616
1540.783250.43350.21675
1550.7628350.4743310.237165
1560.7390930.5218150.260907
1570.780670.438660.21933
1580.7749090.4501830.225091
1590.751840.4963190.24816
1600.7325630.5348750.267437
1610.7775660.4448670.222434
1620.7719360.4561290.228064
1630.7790.4420.221
1640.7665010.4669990.233499
1650.818920.3621610.18108
1660.8112160.3775680.188784
1670.8549420.2901150.145058
1680.8419260.3161480.158074
1690.8232880.3534240.176712
1700.8128040.3743930.187196
1710.8050390.3899210.194961
1720.8286170.3427650.171383
1730.8106860.3786270.189314
1740.7918680.4162650.208132
1750.772870.454260.22713
1760.8003120.3993750.199688
1770.775440.449120.22456
1780.8388010.3223970.161199
1790.8247130.3505730.175287
1800.8680770.2638470.131923
1810.8484730.3030550.151527
1820.8267440.3465120.173256
1830.8732840.2534320.126716
1840.8618160.2763680.138184
1850.8412280.3175440.158772
1860.830230.3395410.16977
1870.836730.3265390.16327
1880.8147060.3705890.185294
1890.7967290.4065410.203271
1900.7726790.4546420.227321
1910.7730190.4539610.226981
1920.7564630.4870730.243537
1930.7835150.432970.216485
1940.8049740.3900510.195026
1950.7781620.4436750.221838
1960.7493490.5013020.250651
1970.7268980.5462040.273102
1980.6955960.6088080.304404
1990.6680220.6639560.331978
2000.650610.698780.34939
2010.6819610.6360780.318039
2020.6469080.7061850.353092
2030.611380.777240.38862
2040.5934030.8131940.406597
2050.5615870.8768260.438413
2060.5294230.9411530.470577
2070.5413570.9172850.458643
2080.5054480.9891040.494552
2090.5900780.8198440.409922
2100.5910770.8178450.408923
2110.5732680.8534640.426732
2120.5451050.909790.454895
2130.516980.9660410.48302
2140.4792340.9584680.520766
2150.4706090.9412190.529391
2160.4373250.8746490.562675
2170.4195660.8391320.580434
2180.4533250.906650.546675
2190.4293990.8587980.570601
2200.4043280.8086550.595672
2210.4356430.8712850.564357
2220.5276610.9446780.472339
2230.492710.9854190.50729
2240.4708710.9417430.529129
2250.5656010.8687980.434399
2260.5346030.9307930.465397
2270.5308890.9382210.469111
2280.5011650.997670.498835
2290.5526920.8946150.447308
2300.6429810.7140370.357019
2310.6918530.6162940.308147
2320.7745190.4509630.225481
2330.7370220.5259550.262978
2340.6958320.6083360.304168
2350.7058840.5882320.294116
2360.924170.151660.0758298
2370.9083790.1832410.0916205
2380.8853140.2293720.114686
2390.8754430.2491150.124557
2400.8539170.2921650.146083
2410.8258170.3483670.174183
2420.7907070.4185850.209293
2430.7531630.4936740.246837
2440.8601770.2796460.139823
2450.8433160.3133680.156684
2460.8154720.3690570.184528
2470.8475580.3048830.152442
2480.8161860.3676280.183814
2490.7956850.408630.204315
2500.7504020.4991950.249598
2510.7074860.5850280.292514
2520.6577970.6844060.342203
2530.6129960.7740070.387004
2540.6813260.6373490.318674
2550.6454070.7091850.354593
2560.6338640.7322710.366136
2570.717030.565940.28297
2580.9138480.1723050.0861523
2590.8823850.235230.117615
2600.9161940.1676130.0838064
2610.9213180.1573640.0786819
2620.8909770.2180450.109023
2630.9130890.1738220.086911
2640.8748830.2502350.125117
2650.8578870.2842260.142113
2660.8044860.3910280.195514
2670.7322510.5354980.267749
2680.6582470.6835060.341753
2690.543810.9123810.45619
2700.795820.4083610.20418
2710.6735620.6528760.326438
2720.5469050.906190.453095
2730.3547950.709590.645205






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level670.25NOK
5% type I error level850.317164NOK
10% type I error level960.358209NOK

\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 & 67 & 0.25 & NOK \tabularnewline
5% type I error level & 85 & 0.317164 & NOK \tabularnewline
10% type I error level & 96 & 0.358209 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263835&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]67[/C][C]0.25[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]85[/C][C]0.317164[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]96[/C][C]0.358209[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263835&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263835&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level670.25NOK
5% type I error level850.317164NOK
10% type I error level960.358209NOK


Figures (Output of Computation)

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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')
}