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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 computationWed, 10 Dec 2014 11:51:35 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/10/t1418212318wtmeklmtgo3yabh.htm/, Retrieved Sun, 19 May 2024 14:45:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264970, Retrieved Sun, 19 May 2024 14:45:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact61

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-10 11:51:35] [f8081e57f48fffedb891dd68b4ffae29] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 26
12.2 51
12.8 57
7.4 37
6.7 67
12.6 43
14.8 52
13.3 52
11.1 43
8.2 84
11.4 67
6.4 49
10.6 70
12 52
6.3 58
11.3 68
11.9 62
9.3 43
9.6 56
10 56
6.4 74
13.8 65
10.8 63
13.8 58
11.7 57
10.9 63
16.1 53
13.4 57
9.9 51
11.5 64
8.3 53
11.7 29
9 54
9.7 51
10.8 58
10.3 43
10.4 51
12.7 53
9.3 54
11.8 56
5.9 61
11.4 47
13 39
10.8 48
12.3 50
11.3 35
11.8 30
7.9 68
12.7 49
12.3 61
11.6 67
6.7 47
10.9 56
12.1 50
13.3 43
10.1 67
5.7 62
14.3 57
8 41
13.3 54
9.3 45
12.5 48
7.6 61
15.9 56
9.2 41
9.1 43
11.1 53
13 44
14.5 66
12.2 58
12.3 46
11.4 37
8.8 51
14.6 51
12.6 56
13 45
12.6 37
13.2 59
9.9 42
7.7 38
10.5 66
13.4 34
10.9 53
4.3 49
10.3 55
11.8 49
11.2 59
11.4 40
8.6 58
13.2 60
12.6 63
5.6 56
9.9 54
8.8 52
7.7 34
9 69
7.3 32
11.4 48
13.6 67
7.9 58
10.7 57
10.3 42
8.3 64
9.6 58
14.2 66
8.5 26
13.5 61
4.9 52
6.4 51
9.6 55
11.6 50
11.1 60
4.35 56
12.7 63
18.1 61
17.85 52
16.6 16
12.6 46
17.1 56
19.1 52
16.1 55
13.35 50
18.4 59
14.7 60
10.6 52
12.6 44
16.2 67
13.6 52
18.9 55
14.1 37
14.5 54
16.15 72
14.75 51
14.8 48
12.45 60
12.65 50
17.35 63
8.6 33
18.4 67
16.1 46
11.6 54
17.75 59
15.25 61
17.65 33
16.35 47
17.65 69
13.6 52
14.35 55
14.75 55
18.25 41
9.9 73
16 51
18.25 52
16.85 50
14.6 51
13.85 60
18.95 56
15.6 56
14.85 29
11.75 66
18.45 66
15.9 73
17.1 55
16.1 64
19.9 40
10.95 46
18.45 58
15.1 43
15 61
11.35 51
15.95 50
18.1 52
14.6 54
15.4 66
15.4 61
17.6 80
13.35 51
19.1 56
15.35 56
7.6 56
13.4 53
13.9 47
19.1 25
15.25 47
12.9 46
16.1 50
17.35 39
13.15 51
12.15 58
12.6 35
10.35 58
15.4 60
9.6 62
18.2 63
13.6 53
14.85 46
14.75 67
14.1 59
14.9 64
16.25 38
19.25 50
13.6 48
13.6 48
15.65 47
12.75 66
14.6 47
9.85 63
12.65 58
19.2 44
16.6 51
11.2 43
15.25 55
11.9 38
13.2 56
16.35 45
12.4 50
15.85 54
18.15 57
11.15 60
15.65 55
17.75 56
7.65 49
12.35 37
15.6 43
19.3 59
15.2 46
17.1 51
15.6 58
18.4 64
19.05 53
18.55 48
19.1 51
13.1 47
12.85 59
9.5 62
4.5 62
11.85 51
13.6 64
11.7 52
12.4 67
13.35 50
11.4 54
14.9 58
19.9 56
11.2 63
14.6 31
17.6 65
14.05 71
16.1 50
13.35 57
11.85 47
11.95 54
14.75 47
15.15 57
13.2 43
16.85 41
7.85 63
7.7 63
12.6 56
7.85 51
10.95 50
12.35 22
9.95 41
14.9 59
16.65 56
13.4 66
13.95 53
15.7 42
16.85 52
10.95 54
15.35 44
12.2 62
15.1 53
17.75 50
15.2 36
14.6 76
16.65 66
8.1 62

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 13.2042 -0.00431921AMS.I[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  13.2042 -0.00431921AMS.I[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  13.2042 -0.00431921AMS.I[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&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] = + 13.2042 -0.00431921AMS.I[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.20421.075812.276.31456e-283.15728e-28
AMS.I-0.004319210.0199098-0.21690.8284160.414208

\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) & 13.2042 & 1.0758 & 12.27 & 6.31456e-28 & 3.15728e-28 \tabularnewline
AMS.I & -0.00431921 & 0.0199098 & -0.2169 & 0.828416 & 0.414208 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&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]13.2042[/C][C]1.0758[/C][C]12.27[/C][C]6.31456e-28[/C][C]3.15728e-28[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00431921[/C][C]0.0199098[/C][C]-0.2169[/C][C]0.828416[/C][C]0.414208[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&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)13.20421.075812.276.31456e-283.15728e-28
AMS.I-0.004319210.0199098-0.21690.8284160.414208






Multiple Linear Regression - Regression Statistics
Multiple R0.0130571
R-squared0.000170488
Adjusted R-squared-0.00345208
F-TEST (value)0.0470627
F-TEST (DF numerator)1
F-TEST (DF denominator)276
p-value0.828416
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40021
Sum Squared Residuals3190.96

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0130571 \tabularnewline
R-squared & 0.000170488 \tabularnewline
Adjusted R-squared & -0.00345208 \tabularnewline
F-TEST (value) & 0.0470627 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 276 \tabularnewline
p-value & 0.828416 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.40021 \tabularnewline
Sum Squared Residuals & 3190.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0130571[/C][/ROW]
[ROW][C]R-squared[/C][C]0.000170488[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00345208[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.0470627[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]0.828416[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.40021[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3190.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&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 R0.0130571
R-squared0.000170488
Adjusted R-squared-0.00345208
F-TEST (value)0.0470627
F-TEST (DF numerator)1
F-TEST (DF denominator)276
p-value0.828416
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.40021
Sum Squared Residuals3190.96






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.0919-0.191852
212.212.9839-0.783871
312.812.958-0.157956
47.413.0443-5.64434
56.712.9148-6.21476
612.613.0184-0.418425
714.812.97961.82045
813.312.97960.320448
911.113.0184-1.91843
108.212.8413-4.64134
1111.412.9148-1.51476
126.412.9925-6.59251
1310.612.9018-2.30181
141212.9796-0.979552
156.312.9536-6.65364
1611.312.9104-1.61044
1711.912.9364-1.03636
189.313.0184-3.71843
199.612.9623-3.36228
201012.9623-2.96228
216.412.8845-6.48453
2213.812.92340.876598
2310.812.932-2.13204
2413.812.95360.846363
2511.712.958-1.25796
2610.912.932-2.03204
2716.112.97523.12477
2813.412.9580.442044
299.912.9839-3.08387
3011.512.9277-1.42772
318.312.9752-4.67523
3211.713.0789-1.37889
33912.9709-3.97091
349.712.9839-3.28387
3510.812.9536-2.15364
3610.313.0184-2.71843
3710.412.9839-2.58387
3812.712.9752-0.275233
399.312.9709-3.67091
4011.812.9623-1.16228
415.912.9407-7.04068
4211.413.0011-1.60115
431313.0357-0.035702
4410.812.9968-2.19683
4512.312.9882-0.688191
4611.313.053-1.75298
4711.813.0746-1.27457
487.912.9104-5.01044
4912.712.9925-0.29251
5012.312.9407-0.640679
5111.612.9148-1.31476
526.713.0011-6.30115
5310.912.9623-2.06228
5412.112.9882-0.888191
5513.313.01840.281575
5610.112.9148-2.81476
575.712.9364-7.23636
5814.312.9581.34204
59813.0271-5.02706
6013.312.97090.329086
619.313.0098-3.70979
6212.512.9968-0.496829
637.612.9407-5.34068
6415.912.96232.93772
659.213.0271-3.82706
669.113.0184-3.91843
6711.112.9752-1.87523
681313.0141-0.014106
6914.512.91911.58092
7012.212.9536-0.753637
7112.313.0055-0.705468
7211.413.0443-1.64434
738.812.9839-4.18387
7414.612.98391.61613
7512.612.9623-0.362275
761313.0098-0.00978676
7712.613.0443-0.44434
7813.212.94930.250682
799.913.0227-3.12274
807.713.04-5.34002
8110.512.9191-2.41908
8213.413.05730.342702
8310.912.9752-2.07523
844.312.9925-8.69251
8510.312.9666-2.66659
8611.812.9925-1.19251
8711.212.9493-1.74932
8811.413.0314-1.63138
898.612.9536-4.35364
9013.212.9450.255001
9112.612.932-0.332041
925.612.9623-7.36228
939.912.9709-3.07091
948.812.9796-4.17955
957.713.0573-5.3573
96912.9061-3.90613
977.313.0659-5.76594
9811.412.9968-1.59683
9913.612.91480.685236
1007.912.9536-5.05364
10110.712.958-2.25796
10210.313.0227-2.72274
1038.312.9277-4.62772
1049.612.9536-3.35364
10514.212.91911.28092
1068.513.0919-4.59185
10713.512.94070.559321
1084.912.9796-8.07955
1096.412.9839-6.58387
1109.612.9666-3.36659
11111.612.9882-1.38819
11211.112.945-1.845
1134.3512.9623-8.61228
11412.712.932-0.232041
11518.112.94075.15932
11617.8512.97964.87045
11716.613.1353.46496
11812.613.0055-0.405468
11917.112.96234.13772
12019.112.97966.12045
12116.112.96663.13341
12213.3512.98820.361809
12318.412.94935.45068
12414.712.9451.755
12510.612.9796-2.37955
12612.613.0141-0.414106
12716.212.91483.28524
12813.612.97960.620448
12918.912.96665.93341
13014.113.04431.05566
13114.512.97091.52909
13216.1512.89323.25683
13314.7512.98391.76613
13414.812.99681.80317
13512.4512.945-0.494999
13612.6512.9882-0.338191
13717.3512.9324.41796
1388.613.0616-4.46162
13918.412.91485.48524
14016.113.00553.09453
14111.612.9709-1.37091
14217.7512.94934.80068
14315.2512.94072.30932
14417.6513.06164.58838
14516.3513.00113.34885
14617.6512.90614.74387
14713.612.97960.620448
14814.3512.96661.38341
14914.7512.96661.78341
15018.2513.02715.22294
1519.912.8888-2.98885
1521612.98393.01613
15318.2512.97965.27045
15416.8512.98823.86181
15514.612.98391.61613
15613.8512.9450.905001
15718.9512.96235.98772
15815.612.96232.63772
15914.8513.07891.77111
16011.7512.9191-1.16908
16118.4512.91915.53092
16215.912.88883.01115
16317.112.96664.13341
16416.112.92773.17228
16519.913.03146.86862
16610.9513.0055-2.05547
16718.4512.95365.49636
16815.113.01842.08157
1691512.94072.05932
17011.3512.9839-1.63387
17115.9512.98822.96181
17218.112.97965.12045
17314.612.97091.62909
17415.412.91912.48092
17515.412.94072.45932
17617.612.85864.74139
17713.3512.98390.366129
17819.112.96236.13772
17915.3512.96232.38772
1807.612.9623-5.36228
18113.412.97520.424767
18213.913.00110.898852
18319.113.09626.00383
18415.2513.00112.24885
18512.913.0055-0.105468
18616.112.98823.11181
18717.3513.03574.3143
18813.1512.98390.166129
18912.1512.9536-0.803637
19012.613.053-0.452979
19110.3512.9536-2.60364
19215.412.9452.455
1939.612.9364-3.33636
19418.212.9325.26796
19513.612.97520.624767
19614.8513.00551.84453
19714.7512.91481.83524
19814.112.94931.15068
19914.912.92771.97228
20016.2513.043.20998
20119.2512.98826.26181
20213.612.99680.603171
20313.612.99680.603171
20415.6513.00112.64885
20512.7512.9191-0.169083
20614.613.00111.59885
2079.8512.932-3.08204
20812.6512.9536-0.303637
20919.213.01416.18589
21016.612.98393.61613
21111.213.0184-1.81843
21215.2512.96662.28341
21311.913.04-1.14002
21413.212.96230.237725
21516.3513.00983.34021
21612.412.9882-0.588191
21715.8512.97092.87909
21818.1512.9585.19204
21911.1512.945-1.795
22015.6512.96662.68341
22117.7512.96234.78772
2227.6512.9925-5.34251
22312.3513.0443-0.69434
22415.613.01842.58157
22519.312.94936.35068
22615.213.00552.19453
22717.112.98394.11613
22815.612.95362.64636
22918.412.92775.47228
23019.0512.97526.07477
23118.5512.99685.55317
23219.112.98396.11613
23313.113.00110.0988517
23412.8512.9493-0.0993178
2359.512.9364-3.43636
2364.512.9364-8.43636
23711.8512.9839-1.13387
23813.612.92770.672278
23911.712.9796-1.27955
24012.412.9148-0.514764
24113.3512.98820.361809
24211.412.9709-1.57091
24314.912.95361.94636
24419.912.96236.93772
24511.212.932-1.73204
24614.613.07031.52974
24717.612.92344.6766
24814.0512.89751.15251
24916.112.98823.11181
25013.3512.9580.392044
25111.8513.0011-1.15115
25211.9512.9709-1.02091
25314.7513.00111.74885
25415.1512.9582.19204
25513.213.01840.181575
25616.8513.02713.82294
2577.8512.932-5.08204
2587.712.932-5.23204
25912.612.9623-0.362275
2607.8512.9839-5.13387
26110.9512.9882-2.03819
26212.3513.1091-0.759129
2639.9513.0271-3.07706
26414.912.94931.95068
26516.6512.96233.68772
26613.412.91910.480917
26713.9512.97520.974767
26815.713.02272.67726
26916.8512.97963.87045
27010.9512.9709-2.02091
27115.3513.01412.33589
27212.212.9364-0.73636
27315.112.97522.12477
27417.7512.98824.76181
27515.213.04872.15134
27614.612.87591.72411
27716.6512.91913.73092
2788.112.9364-4.83636

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.0919 & -0.191852 \tabularnewline
2 & 12.2 & 12.9839 & -0.783871 \tabularnewline
3 & 12.8 & 12.958 & -0.157956 \tabularnewline
4 & 7.4 & 13.0443 & -5.64434 \tabularnewline
5 & 6.7 & 12.9148 & -6.21476 \tabularnewline
6 & 12.6 & 13.0184 & -0.418425 \tabularnewline
7 & 14.8 & 12.9796 & 1.82045 \tabularnewline
8 & 13.3 & 12.9796 & 0.320448 \tabularnewline
9 & 11.1 & 13.0184 & -1.91843 \tabularnewline
10 & 8.2 & 12.8413 & -4.64134 \tabularnewline
11 & 11.4 & 12.9148 & -1.51476 \tabularnewline
12 & 6.4 & 12.9925 & -6.59251 \tabularnewline
13 & 10.6 & 12.9018 & -2.30181 \tabularnewline
14 & 12 & 12.9796 & -0.979552 \tabularnewline
15 & 6.3 & 12.9536 & -6.65364 \tabularnewline
16 & 11.3 & 12.9104 & -1.61044 \tabularnewline
17 & 11.9 & 12.9364 & -1.03636 \tabularnewline
18 & 9.3 & 13.0184 & -3.71843 \tabularnewline
19 & 9.6 & 12.9623 & -3.36228 \tabularnewline
20 & 10 & 12.9623 & -2.96228 \tabularnewline
21 & 6.4 & 12.8845 & -6.48453 \tabularnewline
22 & 13.8 & 12.9234 & 0.876598 \tabularnewline
23 & 10.8 & 12.932 & -2.13204 \tabularnewline
24 & 13.8 & 12.9536 & 0.846363 \tabularnewline
25 & 11.7 & 12.958 & -1.25796 \tabularnewline
26 & 10.9 & 12.932 & -2.03204 \tabularnewline
27 & 16.1 & 12.9752 & 3.12477 \tabularnewline
28 & 13.4 & 12.958 & 0.442044 \tabularnewline
29 & 9.9 & 12.9839 & -3.08387 \tabularnewline
30 & 11.5 & 12.9277 & -1.42772 \tabularnewline
31 & 8.3 & 12.9752 & -4.67523 \tabularnewline
32 & 11.7 & 13.0789 & -1.37889 \tabularnewline
33 & 9 & 12.9709 & -3.97091 \tabularnewline
34 & 9.7 & 12.9839 & -3.28387 \tabularnewline
35 & 10.8 & 12.9536 & -2.15364 \tabularnewline
36 & 10.3 & 13.0184 & -2.71843 \tabularnewline
37 & 10.4 & 12.9839 & -2.58387 \tabularnewline
38 & 12.7 & 12.9752 & -0.275233 \tabularnewline
39 & 9.3 & 12.9709 & -3.67091 \tabularnewline
40 & 11.8 & 12.9623 & -1.16228 \tabularnewline
41 & 5.9 & 12.9407 & -7.04068 \tabularnewline
42 & 11.4 & 13.0011 & -1.60115 \tabularnewline
43 & 13 & 13.0357 & -0.035702 \tabularnewline
44 & 10.8 & 12.9968 & -2.19683 \tabularnewline
45 & 12.3 & 12.9882 & -0.688191 \tabularnewline
46 & 11.3 & 13.053 & -1.75298 \tabularnewline
47 & 11.8 & 13.0746 & -1.27457 \tabularnewline
48 & 7.9 & 12.9104 & -5.01044 \tabularnewline
49 & 12.7 & 12.9925 & -0.29251 \tabularnewline
50 & 12.3 & 12.9407 & -0.640679 \tabularnewline
51 & 11.6 & 12.9148 & -1.31476 \tabularnewline
52 & 6.7 & 13.0011 & -6.30115 \tabularnewline
53 & 10.9 & 12.9623 & -2.06228 \tabularnewline
54 & 12.1 & 12.9882 & -0.888191 \tabularnewline
55 & 13.3 & 13.0184 & 0.281575 \tabularnewline
56 & 10.1 & 12.9148 & -2.81476 \tabularnewline
57 & 5.7 & 12.9364 & -7.23636 \tabularnewline
58 & 14.3 & 12.958 & 1.34204 \tabularnewline
59 & 8 & 13.0271 & -5.02706 \tabularnewline
60 & 13.3 & 12.9709 & 0.329086 \tabularnewline
61 & 9.3 & 13.0098 & -3.70979 \tabularnewline
62 & 12.5 & 12.9968 & -0.496829 \tabularnewline
63 & 7.6 & 12.9407 & -5.34068 \tabularnewline
64 & 15.9 & 12.9623 & 2.93772 \tabularnewline
65 & 9.2 & 13.0271 & -3.82706 \tabularnewline
66 & 9.1 & 13.0184 & -3.91843 \tabularnewline
67 & 11.1 & 12.9752 & -1.87523 \tabularnewline
68 & 13 & 13.0141 & -0.014106 \tabularnewline
69 & 14.5 & 12.9191 & 1.58092 \tabularnewline
70 & 12.2 & 12.9536 & -0.753637 \tabularnewline
71 & 12.3 & 13.0055 & -0.705468 \tabularnewline
72 & 11.4 & 13.0443 & -1.64434 \tabularnewline
73 & 8.8 & 12.9839 & -4.18387 \tabularnewline
74 & 14.6 & 12.9839 & 1.61613 \tabularnewline
75 & 12.6 & 12.9623 & -0.362275 \tabularnewline
76 & 13 & 13.0098 & -0.00978676 \tabularnewline
77 & 12.6 & 13.0443 & -0.44434 \tabularnewline
78 & 13.2 & 12.9493 & 0.250682 \tabularnewline
79 & 9.9 & 13.0227 & -3.12274 \tabularnewline
80 & 7.7 & 13.04 & -5.34002 \tabularnewline
81 & 10.5 & 12.9191 & -2.41908 \tabularnewline
82 & 13.4 & 13.0573 & 0.342702 \tabularnewline
83 & 10.9 & 12.9752 & -2.07523 \tabularnewline
84 & 4.3 & 12.9925 & -8.69251 \tabularnewline
85 & 10.3 & 12.9666 & -2.66659 \tabularnewline
86 & 11.8 & 12.9925 & -1.19251 \tabularnewline
87 & 11.2 & 12.9493 & -1.74932 \tabularnewline
88 & 11.4 & 13.0314 & -1.63138 \tabularnewline
89 & 8.6 & 12.9536 & -4.35364 \tabularnewline
90 & 13.2 & 12.945 & 0.255001 \tabularnewline
91 & 12.6 & 12.932 & -0.332041 \tabularnewline
92 & 5.6 & 12.9623 & -7.36228 \tabularnewline
93 & 9.9 & 12.9709 & -3.07091 \tabularnewline
94 & 8.8 & 12.9796 & -4.17955 \tabularnewline
95 & 7.7 & 13.0573 & -5.3573 \tabularnewline
96 & 9 & 12.9061 & -3.90613 \tabularnewline
97 & 7.3 & 13.0659 & -5.76594 \tabularnewline
98 & 11.4 & 12.9968 & -1.59683 \tabularnewline
99 & 13.6 & 12.9148 & 0.685236 \tabularnewline
100 & 7.9 & 12.9536 & -5.05364 \tabularnewline
101 & 10.7 & 12.958 & -2.25796 \tabularnewline
102 & 10.3 & 13.0227 & -2.72274 \tabularnewline
103 & 8.3 & 12.9277 & -4.62772 \tabularnewline
104 & 9.6 & 12.9536 & -3.35364 \tabularnewline
105 & 14.2 & 12.9191 & 1.28092 \tabularnewline
106 & 8.5 & 13.0919 & -4.59185 \tabularnewline
107 & 13.5 & 12.9407 & 0.559321 \tabularnewline
108 & 4.9 & 12.9796 & -8.07955 \tabularnewline
109 & 6.4 & 12.9839 & -6.58387 \tabularnewline
110 & 9.6 & 12.9666 & -3.36659 \tabularnewline
111 & 11.6 & 12.9882 & -1.38819 \tabularnewline
112 & 11.1 & 12.945 & -1.845 \tabularnewline
113 & 4.35 & 12.9623 & -8.61228 \tabularnewline
114 & 12.7 & 12.932 & -0.232041 \tabularnewline
115 & 18.1 & 12.9407 & 5.15932 \tabularnewline
116 & 17.85 & 12.9796 & 4.87045 \tabularnewline
117 & 16.6 & 13.135 & 3.46496 \tabularnewline
118 & 12.6 & 13.0055 & -0.405468 \tabularnewline
119 & 17.1 & 12.9623 & 4.13772 \tabularnewline
120 & 19.1 & 12.9796 & 6.12045 \tabularnewline
121 & 16.1 & 12.9666 & 3.13341 \tabularnewline
122 & 13.35 & 12.9882 & 0.361809 \tabularnewline
123 & 18.4 & 12.9493 & 5.45068 \tabularnewline
124 & 14.7 & 12.945 & 1.755 \tabularnewline
125 & 10.6 & 12.9796 & -2.37955 \tabularnewline
126 & 12.6 & 13.0141 & -0.414106 \tabularnewline
127 & 16.2 & 12.9148 & 3.28524 \tabularnewline
128 & 13.6 & 12.9796 & 0.620448 \tabularnewline
129 & 18.9 & 12.9666 & 5.93341 \tabularnewline
130 & 14.1 & 13.0443 & 1.05566 \tabularnewline
131 & 14.5 & 12.9709 & 1.52909 \tabularnewline
132 & 16.15 & 12.8932 & 3.25683 \tabularnewline
133 & 14.75 & 12.9839 & 1.76613 \tabularnewline
134 & 14.8 & 12.9968 & 1.80317 \tabularnewline
135 & 12.45 & 12.945 & -0.494999 \tabularnewline
136 & 12.65 & 12.9882 & -0.338191 \tabularnewline
137 & 17.35 & 12.932 & 4.41796 \tabularnewline
138 & 8.6 & 13.0616 & -4.46162 \tabularnewline
139 & 18.4 & 12.9148 & 5.48524 \tabularnewline
140 & 16.1 & 13.0055 & 3.09453 \tabularnewline
141 & 11.6 & 12.9709 & -1.37091 \tabularnewline
142 & 17.75 & 12.9493 & 4.80068 \tabularnewline
143 & 15.25 & 12.9407 & 2.30932 \tabularnewline
144 & 17.65 & 13.0616 & 4.58838 \tabularnewline
145 & 16.35 & 13.0011 & 3.34885 \tabularnewline
146 & 17.65 & 12.9061 & 4.74387 \tabularnewline
147 & 13.6 & 12.9796 & 0.620448 \tabularnewline
148 & 14.35 & 12.9666 & 1.38341 \tabularnewline
149 & 14.75 & 12.9666 & 1.78341 \tabularnewline
150 & 18.25 & 13.0271 & 5.22294 \tabularnewline
151 & 9.9 & 12.8888 & -2.98885 \tabularnewline
152 & 16 & 12.9839 & 3.01613 \tabularnewline
153 & 18.25 & 12.9796 & 5.27045 \tabularnewline
154 & 16.85 & 12.9882 & 3.86181 \tabularnewline
155 & 14.6 & 12.9839 & 1.61613 \tabularnewline
156 & 13.85 & 12.945 & 0.905001 \tabularnewline
157 & 18.95 & 12.9623 & 5.98772 \tabularnewline
158 & 15.6 & 12.9623 & 2.63772 \tabularnewline
159 & 14.85 & 13.0789 & 1.77111 \tabularnewline
160 & 11.75 & 12.9191 & -1.16908 \tabularnewline
161 & 18.45 & 12.9191 & 5.53092 \tabularnewline
162 & 15.9 & 12.8888 & 3.01115 \tabularnewline
163 & 17.1 & 12.9666 & 4.13341 \tabularnewline
164 & 16.1 & 12.9277 & 3.17228 \tabularnewline
165 & 19.9 & 13.0314 & 6.86862 \tabularnewline
166 & 10.95 & 13.0055 & -2.05547 \tabularnewline
167 & 18.45 & 12.9536 & 5.49636 \tabularnewline
168 & 15.1 & 13.0184 & 2.08157 \tabularnewline
169 & 15 & 12.9407 & 2.05932 \tabularnewline
170 & 11.35 & 12.9839 & -1.63387 \tabularnewline
171 & 15.95 & 12.9882 & 2.96181 \tabularnewline
172 & 18.1 & 12.9796 & 5.12045 \tabularnewline
173 & 14.6 & 12.9709 & 1.62909 \tabularnewline
174 & 15.4 & 12.9191 & 2.48092 \tabularnewline
175 & 15.4 & 12.9407 & 2.45932 \tabularnewline
176 & 17.6 & 12.8586 & 4.74139 \tabularnewline
177 & 13.35 & 12.9839 & 0.366129 \tabularnewline
178 & 19.1 & 12.9623 & 6.13772 \tabularnewline
179 & 15.35 & 12.9623 & 2.38772 \tabularnewline
180 & 7.6 & 12.9623 & -5.36228 \tabularnewline
181 & 13.4 & 12.9752 & 0.424767 \tabularnewline
182 & 13.9 & 13.0011 & 0.898852 \tabularnewline
183 & 19.1 & 13.0962 & 6.00383 \tabularnewline
184 & 15.25 & 13.0011 & 2.24885 \tabularnewline
185 & 12.9 & 13.0055 & -0.105468 \tabularnewline
186 & 16.1 & 12.9882 & 3.11181 \tabularnewline
187 & 17.35 & 13.0357 & 4.3143 \tabularnewline
188 & 13.15 & 12.9839 & 0.166129 \tabularnewline
189 & 12.15 & 12.9536 & -0.803637 \tabularnewline
190 & 12.6 & 13.053 & -0.452979 \tabularnewline
191 & 10.35 & 12.9536 & -2.60364 \tabularnewline
192 & 15.4 & 12.945 & 2.455 \tabularnewline
193 & 9.6 & 12.9364 & -3.33636 \tabularnewline
194 & 18.2 & 12.932 & 5.26796 \tabularnewline
195 & 13.6 & 12.9752 & 0.624767 \tabularnewline
196 & 14.85 & 13.0055 & 1.84453 \tabularnewline
197 & 14.75 & 12.9148 & 1.83524 \tabularnewline
198 & 14.1 & 12.9493 & 1.15068 \tabularnewline
199 & 14.9 & 12.9277 & 1.97228 \tabularnewline
200 & 16.25 & 13.04 & 3.20998 \tabularnewline
201 & 19.25 & 12.9882 & 6.26181 \tabularnewline
202 & 13.6 & 12.9968 & 0.603171 \tabularnewline
203 & 13.6 & 12.9968 & 0.603171 \tabularnewline
204 & 15.65 & 13.0011 & 2.64885 \tabularnewline
205 & 12.75 & 12.9191 & -0.169083 \tabularnewline
206 & 14.6 & 13.0011 & 1.59885 \tabularnewline
207 & 9.85 & 12.932 & -3.08204 \tabularnewline
208 & 12.65 & 12.9536 & -0.303637 \tabularnewline
209 & 19.2 & 13.0141 & 6.18589 \tabularnewline
210 & 16.6 & 12.9839 & 3.61613 \tabularnewline
211 & 11.2 & 13.0184 & -1.81843 \tabularnewline
212 & 15.25 & 12.9666 & 2.28341 \tabularnewline
213 & 11.9 & 13.04 & -1.14002 \tabularnewline
214 & 13.2 & 12.9623 & 0.237725 \tabularnewline
215 & 16.35 & 13.0098 & 3.34021 \tabularnewline
216 & 12.4 & 12.9882 & -0.588191 \tabularnewline
217 & 15.85 & 12.9709 & 2.87909 \tabularnewline
218 & 18.15 & 12.958 & 5.19204 \tabularnewline
219 & 11.15 & 12.945 & -1.795 \tabularnewline
220 & 15.65 & 12.9666 & 2.68341 \tabularnewline
221 & 17.75 & 12.9623 & 4.78772 \tabularnewline
222 & 7.65 & 12.9925 & -5.34251 \tabularnewline
223 & 12.35 & 13.0443 & -0.69434 \tabularnewline
224 & 15.6 & 13.0184 & 2.58157 \tabularnewline
225 & 19.3 & 12.9493 & 6.35068 \tabularnewline
226 & 15.2 & 13.0055 & 2.19453 \tabularnewline
227 & 17.1 & 12.9839 & 4.11613 \tabularnewline
228 & 15.6 & 12.9536 & 2.64636 \tabularnewline
229 & 18.4 & 12.9277 & 5.47228 \tabularnewline
230 & 19.05 & 12.9752 & 6.07477 \tabularnewline
231 & 18.55 & 12.9968 & 5.55317 \tabularnewline
232 & 19.1 & 12.9839 & 6.11613 \tabularnewline
233 & 13.1 & 13.0011 & 0.0988517 \tabularnewline
234 & 12.85 & 12.9493 & -0.0993178 \tabularnewline
235 & 9.5 & 12.9364 & -3.43636 \tabularnewline
236 & 4.5 & 12.9364 & -8.43636 \tabularnewline
237 & 11.85 & 12.9839 & -1.13387 \tabularnewline
238 & 13.6 & 12.9277 & 0.672278 \tabularnewline
239 & 11.7 & 12.9796 & -1.27955 \tabularnewline
240 & 12.4 & 12.9148 & -0.514764 \tabularnewline
241 & 13.35 & 12.9882 & 0.361809 \tabularnewline
242 & 11.4 & 12.9709 & -1.57091 \tabularnewline
243 & 14.9 & 12.9536 & 1.94636 \tabularnewline
244 & 19.9 & 12.9623 & 6.93772 \tabularnewline
245 & 11.2 & 12.932 & -1.73204 \tabularnewline
246 & 14.6 & 13.0703 & 1.52974 \tabularnewline
247 & 17.6 & 12.9234 & 4.6766 \tabularnewline
248 & 14.05 & 12.8975 & 1.15251 \tabularnewline
249 & 16.1 & 12.9882 & 3.11181 \tabularnewline
250 & 13.35 & 12.958 & 0.392044 \tabularnewline
251 & 11.85 & 13.0011 & -1.15115 \tabularnewline
252 & 11.95 & 12.9709 & -1.02091 \tabularnewline
253 & 14.75 & 13.0011 & 1.74885 \tabularnewline
254 & 15.15 & 12.958 & 2.19204 \tabularnewline
255 & 13.2 & 13.0184 & 0.181575 \tabularnewline
256 & 16.85 & 13.0271 & 3.82294 \tabularnewline
257 & 7.85 & 12.932 & -5.08204 \tabularnewline
258 & 7.7 & 12.932 & -5.23204 \tabularnewline
259 & 12.6 & 12.9623 & -0.362275 \tabularnewline
260 & 7.85 & 12.9839 & -5.13387 \tabularnewline
261 & 10.95 & 12.9882 & -2.03819 \tabularnewline
262 & 12.35 & 13.1091 & -0.759129 \tabularnewline
263 & 9.95 & 13.0271 & -3.07706 \tabularnewline
264 & 14.9 & 12.9493 & 1.95068 \tabularnewline
265 & 16.65 & 12.9623 & 3.68772 \tabularnewline
266 & 13.4 & 12.9191 & 0.480917 \tabularnewline
267 & 13.95 & 12.9752 & 0.974767 \tabularnewline
268 & 15.7 & 13.0227 & 2.67726 \tabularnewline
269 & 16.85 & 12.9796 & 3.87045 \tabularnewline
270 & 10.95 & 12.9709 & -2.02091 \tabularnewline
271 & 15.35 & 13.0141 & 2.33589 \tabularnewline
272 & 12.2 & 12.9364 & -0.73636 \tabularnewline
273 & 15.1 & 12.9752 & 2.12477 \tabularnewline
274 & 17.75 & 12.9882 & 4.76181 \tabularnewline
275 & 15.2 & 13.0487 & 2.15134 \tabularnewline
276 & 14.6 & 12.8759 & 1.72411 \tabularnewline
277 & 16.65 & 12.9191 & 3.73092 \tabularnewline
278 & 8.1 & 12.9364 & -4.83636 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&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]13.0919[/C][C]-0.191852[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.9839[/C][C]-0.783871[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]12.958[/C][C]-0.157956[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]13.0443[/C][C]-5.64434[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]12.9148[/C][C]-6.21476[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.0184[/C][C]-0.418425[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.9796[/C][C]1.82045[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]12.9796[/C][C]0.320448[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]13.0184[/C][C]-1.91843[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]12.8413[/C][C]-4.64134[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.9148[/C][C]-1.51476[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]12.9925[/C][C]-6.59251[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.9018[/C][C]-2.30181[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.9796[/C][C]-0.979552[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.9536[/C][C]-6.65364[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.9104[/C][C]-1.61044[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.9364[/C][C]-1.03636[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]13.0184[/C][C]-3.71843[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]12.9623[/C][C]-3.36228[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.9623[/C][C]-2.96228[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.8845[/C][C]-6.48453[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.9234[/C][C]0.876598[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.932[/C][C]-2.13204[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.9536[/C][C]0.846363[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.958[/C][C]-1.25796[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.932[/C][C]-2.03204[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.9752[/C][C]3.12477[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]12.958[/C][C]0.442044[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]12.9839[/C][C]-3.08387[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.9277[/C][C]-1.42772[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.9752[/C][C]-4.67523[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.0789[/C][C]-1.37889[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.9709[/C][C]-3.97091[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.9839[/C][C]-3.28387[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.9536[/C][C]-2.15364[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.0184[/C][C]-2.71843[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.9839[/C][C]-2.58387[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.9752[/C][C]-0.275233[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.9709[/C][C]-3.67091[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.9623[/C][C]-1.16228[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]12.9407[/C][C]-7.04068[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.0011[/C][C]-1.60115[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]13.0357[/C][C]-0.035702[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.9968[/C][C]-2.19683[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.9882[/C][C]-0.688191[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.053[/C][C]-1.75298[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.0746[/C][C]-1.27457[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.9104[/C][C]-5.01044[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.9925[/C][C]-0.29251[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]12.9407[/C][C]-0.640679[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.9148[/C][C]-1.31476[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]13.0011[/C][C]-6.30115[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.9623[/C][C]-2.06228[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.9882[/C][C]-0.888191[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.0184[/C][C]0.281575[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.9148[/C][C]-2.81476[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.9364[/C][C]-7.23636[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.958[/C][C]1.34204[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]13.0271[/C][C]-5.02706[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]12.9709[/C][C]0.329086[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.0098[/C][C]-3.70979[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.9968[/C][C]-0.496829[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.9407[/C][C]-5.34068[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]12.9623[/C][C]2.93772[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.0271[/C][C]-3.82706[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]13.0184[/C][C]-3.91843[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.9752[/C][C]-1.87523[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.0141[/C][C]-0.014106[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.9191[/C][C]1.58092[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.9536[/C][C]-0.753637[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0055[/C][C]-0.705468[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.0443[/C][C]-1.64434[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.9839[/C][C]-4.18387[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]12.9839[/C][C]1.61613[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]12.9623[/C][C]-0.362275[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]13.0098[/C][C]-0.00978676[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.0443[/C][C]-0.44434[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.9493[/C][C]0.250682[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]13.0227[/C][C]-3.12274[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]13.04[/C][C]-5.34002[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.9191[/C][C]-2.41908[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]13.0573[/C][C]0.342702[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.9752[/C][C]-2.07523[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.9925[/C][C]-8.69251[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]12.9666[/C][C]-2.66659[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]12.9925[/C][C]-1.19251[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]12.9493[/C][C]-1.74932[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]13.0314[/C][C]-1.63138[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.9536[/C][C]-4.35364[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]12.945[/C][C]0.255001[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]12.932[/C][C]-0.332041[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]12.9623[/C][C]-7.36228[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]12.9709[/C][C]-3.07091[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.9796[/C][C]-4.17955[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]13.0573[/C][C]-5.3573[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.9061[/C][C]-3.90613[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]13.0659[/C][C]-5.76594[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.9968[/C][C]-1.59683[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.9148[/C][C]0.685236[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.9536[/C][C]-5.05364[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.958[/C][C]-2.25796[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]13.0227[/C][C]-2.72274[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]12.9277[/C][C]-4.62772[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.9536[/C][C]-3.35364[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.9191[/C][C]1.28092[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]13.0919[/C][C]-4.59185[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]12.9407[/C][C]0.559321[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.9796[/C][C]-8.07955[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]12.9839[/C][C]-6.58387[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]12.9666[/C][C]-3.36659[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]12.9882[/C][C]-1.38819[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]12.945[/C][C]-1.845[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]12.9623[/C][C]-8.61228[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.932[/C][C]-0.232041[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]12.9407[/C][C]5.15932[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.9796[/C][C]4.87045[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]13.135[/C][C]3.46496[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]13.0055[/C][C]-0.405468[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]12.9623[/C][C]4.13772[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]12.9796[/C][C]6.12045[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]12.9666[/C][C]3.13341[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]12.9882[/C][C]0.361809[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]12.9493[/C][C]5.45068[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.945[/C][C]1.755[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]12.9796[/C][C]-2.37955[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]13.0141[/C][C]-0.414106[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.9148[/C][C]3.28524[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]12.9796[/C][C]0.620448[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]12.9666[/C][C]5.93341[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.0443[/C][C]1.05566[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]12.9709[/C][C]1.52909[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.8932[/C][C]3.25683[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.9839[/C][C]1.76613[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.9968[/C][C]1.80317[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.945[/C][C]-0.494999[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]12.9882[/C][C]-0.338191[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]12.932[/C][C]4.41796[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]13.0616[/C][C]-4.46162[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]12.9148[/C][C]5.48524[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.0055[/C][C]3.09453[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.9709[/C][C]-1.37091[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]12.9493[/C][C]4.80068[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.9407[/C][C]2.30932[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]13.0616[/C][C]4.58838[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]13.0011[/C][C]3.34885[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]12.9061[/C][C]4.74387[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]12.9796[/C][C]0.620448[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]12.9666[/C][C]1.38341[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]12.9666[/C][C]1.78341[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]13.0271[/C][C]5.22294[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]12.8888[/C][C]-2.98885[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]12.9839[/C][C]3.01613[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]12.9796[/C][C]5.27045[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]12.9882[/C][C]3.86181[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.9839[/C][C]1.61613[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]12.945[/C][C]0.905001[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]12.9623[/C][C]5.98772[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]12.9623[/C][C]2.63772[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]13.0789[/C][C]1.77111[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.9191[/C][C]-1.16908[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]12.9191[/C][C]5.53092[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.8888[/C][C]3.01115[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]12.9666[/C][C]4.13341[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]12.9277[/C][C]3.17228[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]13.0314[/C][C]6.86862[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]13.0055[/C][C]-2.05547[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]12.9536[/C][C]5.49636[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.0184[/C][C]2.08157[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]12.9407[/C][C]2.05932[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]12.9839[/C][C]-1.63387[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]12.9882[/C][C]2.96181[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]12.9796[/C][C]5.12045[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.9709[/C][C]1.62909[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]12.9191[/C][C]2.48092[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]12.9407[/C][C]2.45932[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.8586[/C][C]4.74139[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]12.9839[/C][C]0.366129[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]12.9623[/C][C]6.13772[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]12.9623[/C][C]2.38772[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.9623[/C][C]-5.36228[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]12.9752[/C][C]0.424767[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.0011[/C][C]0.898852[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.0962[/C][C]6.00383[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]13.0011[/C][C]2.24885[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]13.0055[/C][C]-0.105468[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]12.9882[/C][C]3.11181[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.0357[/C][C]4.3143[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.9839[/C][C]0.166129[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]12.9536[/C][C]-0.803637[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]13.053[/C][C]-0.452979[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.9536[/C][C]-2.60364[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.945[/C][C]2.455[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.9364[/C][C]-3.33636[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]12.932[/C][C]5.26796[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]12.9752[/C][C]0.624767[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.0055[/C][C]1.84453[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]12.9148[/C][C]1.83524[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.9493[/C][C]1.15068[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]12.9277[/C][C]1.97228[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]13.04[/C][C]3.20998[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]12.9882[/C][C]6.26181[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.9968[/C][C]0.603171[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.9968[/C][C]0.603171[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]13.0011[/C][C]2.64885[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.9191[/C][C]-0.169083[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.0011[/C][C]1.59885[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.932[/C][C]-3.08204[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]12.9536[/C][C]-0.303637[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]13.0141[/C][C]6.18589[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]12.9839[/C][C]3.61613[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]13.0184[/C][C]-1.81843[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]12.9666[/C][C]2.28341[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]13.04[/C][C]-1.14002[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.9623[/C][C]0.237725[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]13.0098[/C][C]3.34021[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]12.9882[/C][C]-0.588191[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.9709[/C][C]2.87909[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]12.958[/C][C]5.19204[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.945[/C][C]-1.795[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]12.9666[/C][C]2.68341[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.9623[/C][C]4.78772[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.9925[/C][C]-5.34251[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.0443[/C][C]-0.69434[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]13.0184[/C][C]2.58157[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]12.9493[/C][C]6.35068[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.0055[/C][C]2.19453[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]12.9839[/C][C]4.11613[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.9536[/C][C]2.64636[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]12.9277[/C][C]5.47228[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]12.9752[/C][C]6.07477[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]12.9968[/C][C]5.55317[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]12.9839[/C][C]6.11613[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]13.0011[/C][C]0.0988517[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]12.9493[/C][C]-0.0993178[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]12.9364[/C][C]-3.43636[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]12.9364[/C][C]-8.43636[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.9839[/C][C]-1.13387[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]12.9277[/C][C]0.672278[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.9796[/C][C]-1.27955[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.9148[/C][C]-0.514764[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]12.9882[/C][C]0.361809[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]12.9709[/C][C]-1.57091[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]12.9536[/C][C]1.94636[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]12.9623[/C][C]6.93772[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]12.932[/C][C]-1.73204[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]13.0703[/C][C]1.52974[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]12.9234[/C][C]4.6766[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.8975[/C][C]1.15251[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]12.9882[/C][C]3.11181[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]12.958[/C][C]0.392044[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]13.0011[/C][C]-1.15115[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]12.9709[/C][C]-1.02091[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]13.0011[/C][C]1.74885[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.958[/C][C]2.19204[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]13.0184[/C][C]0.181575[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]13.0271[/C][C]3.82294[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.932[/C][C]-5.08204[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.932[/C][C]-5.23204[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.9623[/C][C]-0.362275[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]12.9839[/C][C]-5.13387[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]12.9882[/C][C]-2.03819[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]13.1091[/C][C]-0.759129[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]13.0271[/C][C]-3.07706[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]12.9493[/C][C]1.95068[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]12.9623[/C][C]3.68772[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]12.9191[/C][C]0.480917[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]12.9752[/C][C]0.974767[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]13.0227[/C][C]2.67726[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]12.9796[/C][C]3.87045[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.9709[/C][C]-2.02091[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]13.0141[/C][C]2.33589[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.9364[/C][C]-0.73636[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.9752[/C][C]2.12477[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]12.9882[/C][C]4.76181[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]13.0487[/C][C]2.15134[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]12.8759[/C][C]1.72411[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]12.9191[/C][C]3.73092[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.9364[/C][C]-4.83636[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&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
112.913.0919-0.191852
212.212.9839-0.783871
312.812.958-0.157956
47.413.0443-5.64434
56.712.9148-6.21476
612.613.0184-0.418425
714.812.97961.82045
813.312.97960.320448
911.113.0184-1.91843
108.212.8413-4.64134
1111.412.9148-1.51476
126.412.9925-6.59251
1310.612.9018-2.30181
141212.9796-0.979552
156.312.9536-6.65364
1611.312.9104-1.61044
1711.912.9364-1.03636
189.313.0184-3.71843
199.612.9623-3.36228
201012.9623-2.96228
216.412.8845-6.48453
2213.812.92340.876598
2310.812.932-2.13204
2413.812.95360.846363
2511.712.958-1.25796
2610.912.932-2.03204
2716.112.97523.12477
2813.412.9580.442044
299.912.9839-3.08387
3011.512.9277-1.42772
318.312.9752-4.67523
3211.713.0789-1.37889
33912.9709-3.97091
349.712.9839-3.28387
3510.812.9536-2.15364
3610.313.0184-2.71843
3710.412.9839-2.58387
3812.712.9752-0.275233
399.312.9709-3.67091
4011.812.9623-1.16228
415.912.9407-7.04068
4211.413.0011-1.60115
431313.0357-0.035702
4410.812.9968-2.19683
4512.312.9882-0.688191
4611.313.053-1.75298
4711.813.0746-1.27457
487.912.9104-5.01044
4912.712.9925-0.29251
5012.312.9407-0.640679
5111.612.9148-1.31476
526.713.0011-6.30115
5310.912.9623-2.06228
5412.112.9882-0.888191
5513.313.01840.281575
5610.112.9148-2.81476
575.712.9364-7.23636
5814.312.9581.34204
59813.0271-5.02706
6013.312.97090.329086
619.313.0098-3.70979
6212.512.9968-0.496829
637.612.9407-5.34068
6415.912.96232.93772
659.213.0271-3.82706
669.113.0184-3.91843
6711.112.9752-1.87523
681313.0141-0.014106
6914.512.91911.58092
7012.212.9536-0.753637
7112.313.0055-0.705468
7211.413.0443-1.64434
738.812.9839-4.18387
7414.612.98391.61613
7512.612.9623-0.362275
761313.0098-0.00978676
7712.613.0443-0.44434
7813.212.94930.250682
799.913.0227-3.12274
807.713.04-5.34002
8110.512.9191-2.41908
8213.413.05730.342702
8310.912.9752-2.07523
844.312.9925-8.69251
8510.312.9666-2.66659
8611.812.9925-1.19251
8711.212.9493-1.74932
8811.413.0314-1.63138
898.612.9536-4.35364
9013.212.9450.255001
9112.612.932-0.332041
925.612.9623-7.36228
939.912.9709-3.07091
948.812.9796-4.17955
957.713.0573-5.3573
96912.9061-3.90613
977.313.0659-5.76594
9811.412.9968-1.59683
9913.612.91480.685236
1007.912.9536-5.05364
10110.712.958-2.25796
10210.313.0227-2.72274
1038.312.9277-4.62772
1049.612.9536-3.35364
10514.212.91911.28092
1068.513.0919-4.59185
10713.512.94070.559321
1084.912.9796-8.07955
1096.412.9839-6.58387
1109.612.9666-3.36659
11111.612.9882-1.38819
11211.112.945-1.845
1134.3512.9623-8.61228
11412.712.932-0.232041
11518.112.94075.15932
11617.8512.97964.87045
11716.613.1353.46496
11812.613.0055-0.405468
11917.112.96234.13772
12019.112.97966.12045
12116.112.96663.13341
12213.3512.98820.361809
12318.412.94935.45068
12414.712.9451.755
12510.612.9796-2.37955
12612.613.0141-0.414106
12716.212.91483.28524
12813.612.97960.620448
12918.912.96665.93341
13014.113.04431.05566
13114.512.97091.52909
13216.1512.89323.25683
13314.7512.98391.76613
13414.812.99681.80317
13512.4512.945-0.494999
13612.6512.9882-0.338191
13717.3512.9324.41796
1388.613.0616-4.46162
13918.412.91485.48524
14016.113.00553.09453
14111.612.9709-1.37091
14217.7512.94934.80068
14315.2512.94072.30932
14417.6513.06164.58838
14516.3513.00113.34885
14617.6512.90614.74387
14713.612.97960.620448
14814.3512.96661.38341
14914.7512.96661.78341
15018.2513.02715.22294
1519.912.8888-2.98885
1521612.98393.01613
15318.2512.97965.27045
15416.8512.98823.86181
15514.612.98391.61613
15613.8512.9450.905001
15718.9512.96235.98772
15815.612.96232.63772
15914.8513.07891.77111
16011.7512.9191-1.16908
16118.4512.91915.53092
16215.912.88883.01115
16317.112.96664.13341
16416.112.92773.17228
16519.913.03146.86862
16610.9513.0055-2.05547
16718.4512.95365.49636
16815.113.01842.08157
1691512.94072.05932
17011.3512.9839-1.63387
17115.9512.98822.96181
17218.112.97965.12045
17314.612.97091.62909
17415.412.91912.48092
17515.412.94072.45932
17617.612.85864.74139
17713.3512.98390.366129
17819.112.96236.13772
17915.3512.96232.38772
1807.612.9623-5.36228
18113.412.97520.424767
18213.913.00110.898852
18319.113.09626.00383
18415.2513.00112.24885
18512.913.0055-0.105468
18616.112.98823.11181
18717.3513.03574.3143
18813.1512.98390.166129
18912.1512.9536-0.803637
19012.613.053-0.452979
19110.3512.9536-2.60364
19215.412.9452.455
1939.612.9364-3.33636
19418.212.9325.26796
19513.612.97520.624767
19614.8513.00551.84453
19714.7512.91481.83524
19814.112.94931.15068
19914.912.92771.97228
20016.2513.043.20998
20119.2512.98826.26181
20213.612.99680.603171
20313.612.99680.603171
20415.6513.00112.64885
20512.7512.9191-0.169083
20614.613.00111.59885
2079.8512.932-3.08204
20812.6512.9536-0.303637
20919.213.01416.18589
21016.612.98393.61613
21111.213.0184-1.81843
21215.2512.96662.28341
21311.913.04-1.14002
21413.212.96230.237725
21516.3513.00983.34021
21612.412.9882-0.588191
21715.8512.97092.87909
21818.1512.9585.19204
21911.1512.945-1.795
22015.6512.96662.68341
22117.7512.96234.78772
2227.6512.9925-5.34251
22312.3513.0443-0.69434
22415.613.01842.58157
22519.312.94936.35068
22615.213.00552.19453
22717.112.98394.11613
22815.612.95362.64636
22918.412.92775.47228
23019.0512.97526.07477
23118.5512.99685.55317
23219.112.98396.11613
23313.113.00110.0988517
23412.8512.9493-0.0993178
2359.512.9364-3.43636
2364.512.9364-8.43636
23711.8512.9839-1.13387
23813.612.92770.672278
23911.712.9796-1.27955
24012.412.9148-0.514764
24113.3512.98820.361809
24211.412.9709-1.57091
24314.912.95361.94636
24419.912.96236.93772
24511.212.932-1.73204
24614.613.07031.52974
24717.612.92344.6766
24814.0512.89751.15251
24916.112.98823.11181
25013.3512.9580.392044
25111.8513.0011-1.15115
25211.9512.9709-1.02091
25314.7513.00111.74885
25415.1512.9582.19204
25513.213.01840.181575
25616.8513.02713.82294
2577.8512.932-5.08204
2587.712.932-5.23204
25912.612.9623-0.362275
2607.8512.9839-5.13387
26110.9512.9882-2.03819
26212.3513.1091-0.759129
2639.9513.0271-3.07706
26414.912.94931.95068
26516.6512.96233.68772
26613.412.91910.480917
26713.9512.97520.974767
26815.713.02272.67726
26916.8512.97963.87045
27010.9512.9709-2.02091
27115.3513.01412.33589
27212.212.9364-0.73636
27315.112.97522.12477
27417.7512.98824.76181
27515.213.04872.15134
27614.612.87591.72411
27716.6512.91913.73092
2788.112.9364-4.83636






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.5981980.8036040.401802
60.4730990.9461980.526901
70.5291960.9416080.470804
80.444520.8890390.55548
90.3331630.6663250.666837
100.2530680.5061360.746932
110.1839160.3678320.816084
120.2993420.5986830.700658
130.2255570.4511140.774443
140.1689350.337870.831065
150.2280530.4561070.771947
160.1805840.3611680.819416
170.1430840.2861670.856916
180.1183350.2366710.881665
190.08825270.1765050.911747
200.06288530.1257710.937115
210.07059890.1411980.929401
220.08744240.1748850.912558
230.06410240.1282050.935898
240.06819760.1363950.931802
250.05087090.1017420.949129
260.03641570.07283140.963584
270.06900940.1380190.930991
280.06172170.1234430.938278
290.04877230.09754470.951228
300.03632170.07264350.963678
310.03632810.07265610.963672
320.02608570.05217150.973914
330.0222950.044590.977705
340.01730490.03460990.982695
350.01222150.02444290.987779
360.008928670.01785730.991071
370.0062840.0125680.993716
380.004910370.009820750.99509
390.003882910.007765820.996117
400.002721420.005442840.997279
410.006112080.01222420.993888
420.004241640.008483280.995758
430.003194430.006388850.996806
440.002195770.004391550.997804
450.001583440.003166880.998417
460.001060780.002121550.998939
470.0006922260.001384450.999308
480.0006736110.001347220.999326
490.0005032550.001006510.999497
500.0003891830.0007783670.999611
510.0002802770.0005605540.99972
520.0006398690.001279740.99936
530.0004330130.0008660250.999567
540.0003021580.0006043150.999698
550.0002394290.0004788580.999761
560.0001644630.0003289270.999836
570.0004789560.0009579120.999521
580.0006018490.00120370.999398
590.0007995280.001599060.9992
600.0007151050.001430210.999285
610.000622970.001245940.999377
620.000464140.000928280.999536
630.0005644640.001128930.999436
640.001218920.002437850.998781
650.001131890.002263780.998868
660.00105390.00210780.998946
670.0007634210.001526840.999237
680.00060330.00120660.999397
690.0008138510.00162770.999186
700.0006216870.001243370.999378
710.0004560910.0009121830.999544
720.0003215280.0006430570.999678
730.0003144250.0006288510.999686
740.0003658370.0007316740.999634
750.0002850840.0005701680.999715
760.0002203190.0004406370.99978
770.0001569170.0003138350.999843
780.0001344280.0002688560.999866
790.0001107590.0002215190.999889
800.0001765960.0003531930.999823
810.0001306640.0002613280.999869
820.000101930.0002038610.999898
837.33458e-050.0001466920.999927
840.0006058510.00121170.999394
850.000478450.0009568990.999522
860.0003556960.0007113920.999644
870.0002657910.0005315820.999734
880.0001946470.0003892930.999805
890.0002054530.0004109050.999795
900.0001800990.0003601980.99982
910.0001453830.0002907660.999855
920.0005012370.001002470.999499
930.0004269540.0008539090.999573
940.0004501020.0009002040.99955
950.0007102210.001420440.99929
960.0006933430.001386690.999307
970.00124390.002487810.998756
980.000988320.001976640.999012
990.0009515940.001903190.999048
1000.001276540.002553070.998723
1010.001054130.002108260.998946
1020.0009138670.001827730.999086
1030.001107780.002215560.998892
1040.001049370.002098750.998951
1050.001137340.002274690.998863
1060.001456110.002912220.998544
1070.001353230.002706460.998647
1080.006021740.01204350.993978
1090.01297350.0259470.987027
1100.01305940.02611880.986941
1110.01141970.02283940.98858
1120.01006040.02012080.98994
1130.04382710.08765410.956173
1140.04010780.08021560.959892
1150.08509010.170180.91491
1160.1447990.2895990.855201
1170.1771060.3542110.822894
1180.1638730.3277460.836127
1190.2171460.4342920.782854
1200.3553810.7107610.644619
1210.3857710.7715420.614229
1220.3668340.7336690.633166
1230.4806160.9612320.519384
1240.4757010.9514010.524299
1250.4682680.9365370.531732
1260.4454770.8909540.554523
1270.4739450.9478910.526055
1280.4536450.907290.546355
1290.5752910.8494180.424709
1300.5574710.8850580.442529
1310.544050.91190.45595
1320.5634090.8731820.436591
1330.5518720.8962570.448128
1340.5403870.9192260.459613
1350.5149360.9701270.485064
1360.4902220.9804440.509778
1370.5382880.9234240.461712
1380.5924610.8150780.407539
1390.6724330.6551330.327567
1400.6797660.6404680.320234
1410.6630140.6739720.336986
1420.7106420.5787160.289358
1430.7014780.5970450.298522
1440.7380690.5238620.261931
1450.7446040.5107920.255396
1460.7809840.4380310.219016
1470.7603760.4792490.239624
1480.7415490.5169010.258451
1490.7249480.5501050.275052
1500.7692810.4614380.230719
1510.771280.457440.22872
1520.768820.462360.23118
1530.8088660.3822690.191134
1540.8175420.3649170.182458
1550.8011680.3976650.198832
1560.7801620.4396760.219838
1570.8335090.3329820.166491
1580.8251260.3497480.174874
1590.8099580.3800840.190042
1600.7931790.4136430.206821
1610.8337950.3324110.166205
1620.8294010.3411980.170599
1630.8387640.3224730.161236
1640.8353680.3292640.164632
1650.8909120.2181770.109088
1660.88740.22520.1126
1670.9112790.1774410.0887206
1680.901230.1975390.0987697
1690.890320.2193590.10968
1700.8826820.2346360.117318
1710.8761740.2476510.123826
1720.8946430.2107140.105357
1730.8807580.2384840.119242
1740.8709740.2580510.129026
1750.8600750.2798490.139925
1760.8814670.2370650.118533
1770.8641110.2717780.135889
1780.9012960.1974080.0987039
1790.8914140.2171730.108586
1800.9254710.1490570.0745286
1810.9126010.1747980.0873991
1820.8986030.2027930.101397
1830.9190780.1618440.080922
1840.9088230.1823540.0911769
1850.8950690.2098610.104931
1860.8885350.2229310.111465
1870.8920190.2159620.107981
1880.8750170.2499650.124983
1890.8589030.2821940.141097
1900.8432760.3134480.156724
1910.8423870.3152250.157613
1920.8279590.3440810.172041
1930.8375660.3248680.162434
1940.8632870.2734270.136713
1950.8423210.3153590.157679
1960.822090.355820.17791
1970.8018340.3963330.198166
1980.7757850.4484290.224215
1990.7533210.4933580.246679
2000.7385120.5229750.261488
2010.7938680.4122640.206132
2020.7661410.4677190.233859
2030.7363730.5272540.263627
2040.7154840.5690320.284516
2050.6824340.6351330.317566
2060.6500920.6998160.349908
2070.6557850.6884290.344215
2080.6221080.7557850.377892
2090.6834030.6331950.316597
2100.6764940.6470110.323506
2110.6627380.6745250.337262
2120.6349510.7300980.365049
2130.6120720.7758560.387928
2140.5735690.8528620.426431
2150.5570670.8858660.442933
2160.5231950.9536090.476805
2170.50030.99940.4997
2180.5368240.9263530.463176
2190.5150370.9699260.484963
2200.4890670.9781330.510933
2210.5129930.9740130.487007
2220.6088560.7822890.391144
2230.580660.8386790.41934
2240.5484780.9030440.451522
2250.6351760.7296480.364824
2260.6003040.7993930.399696
2270.6030460.7939080.396954
2280.5783280.8433440.421672
2290.6441480.7117050.355852
2300.7203540.5592930.279646
2310.7691850.461630.230815
2320.8382110.3235770.161789
2330.8072110.3855790.192789
2340.7722090.4555830.227791
2350.775030.4499390.22497
2360.9361180.1277640.0638819
2370.9235970.1528050.0764026
2380.9035460.1929090.0964545
2390.8875990.2248020.112401
2400.8624650.275070.137535
2410.8314790.3370420.168521
2420.8119820.3760350.188018
2430.7810660.4378690.218934
2440.8840170.2319670.115983
2450.8666080.2667840.133392
2460.8356220.3287570.164378
2470.8678910.2642170.132109
2480.8400820.3198370.159918
2490.8304260.3391470.169574
2500.7896860.4206280.210314
2510.7542190.4915620.245781
2520.7106950.5786110.289305
2530.6631350.6737310.336865
2540.6269670.7460660.373033
2550.5645660.8708690.435434
2560.5636670.8726670.436333
2570.6510390.6979210.348961
2580.7738310.4523370.226169
2590.7204590.5590820.279541
2600.8525230.2949550.147477
2610.8501170.2997660.149883
2620.8200550.359890.179945
2630.900650.1987010.0993504
2640.8580280.2839440.141972
2650.8369350.326130.163065
2660.7694110.4611790.230589
2670.68780.6243990.3122
2680.5926480.8147030.407352
2690.5460850.907830.453915
2700.5440430.9119130.455957
2710.4166640.8333270.583336
2720.3215770.6431540.678423
2730.1973970.3947940.802603

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0.598198 & 0.803604 & 0.401802 \tabularnewline
6 & 0.473099 & 0.946198 & 0.526901 \tabularnewline
7 & 0.529196 & 0.941608 & 0.470804 \tabularnewline
8 & 0.44452 & 0.889039 & 0.55548 \tabularnewline
9 & 0.333163 & 0.666325 & 0.666837 \tabularnewline
10 & 0.253068 & 0.506136 & 0.746932 \tabularnewline
11 & 0.183916 & 0.367832 & 0.816084 \tabularnewline
12 & 0.299342 & 0.598683 & 0.700658 \tabularnewline
13 & 0.225557 & 0.451114 & 0.774443 \tabularnewline
14 & 0.168935 & 0.33787 & 0.831065 \tabularnewline
15 & 0.228053 & 0.456107 & 0.771947 \tabularnewline
16 & 0.180584 & 0.361168 & 0.819416 \tabularnewline
17 & 0.143084 & 0.286167 & 0.856916 \tabularnewline
18 & 0.118335 & 0.236671 & 0.881665 \tabularnewline
19 & 0.0882527 & 0.176505 & 0.911747 \tabularnewline
20 & 0.0628853 & 0.125771 & 0.937115 \tabularnewline
21 & 0.0705989 & 0.141198 & 0.929401 \tabularnewline
22 & 0.0874424 & 0.174885 & 0.912558 \tabularnewline
23 & 0.0641024 & 0.128205 & 0.935898 \tabularnewline
24 & 0.0681976 & 0.136395 & 0.931802 \tabularnewline
25 & 0.0508709 & 0.101742 & 0.949129 \tabularnewline
26 & 0.0364157 & 0.0728314 & 0.963584 \tabularnewline
27 & 0.0690094 & 0.138019 & 0.930991 \tabularnewline
28 & 0.0617217 & 0.123443 & 0.938278 \tabularnewline
29 & 0.0487723 & 0.0975447 & 0.951228 \tabularnewline
30 & 0.0363217 & 0.0726435 & 0.963678 \tabularnewline
31 & 0.0363281 & 0.0726561 & 0.963672 \tabularnewline
32 & 0.0260857 & 0.0521715 & 0.973914 \tabularnewline
33 & 0.022295 & 0.04459 & 0.977705 \tabularnewline
34 & 0.0173049 & 0.0346099 & 0.982695 \tabularnewline
35 & 0.0122215 & 0.0244429 & 0.987779 \tabularnewline
36 & 0.00892867 & 0.0178573 & 0.991071 \tabularnewline
37 & 0.006284 & 0.012568 & 0.993716 \tabularnewline
38 & 0.00491037 & 0.00982075 & 0.99509 \tabularnewline
39 & 0.00388291 & 0.00776582 & 0.996117 \tabularnewline
40 & 0.00272142 & 0.00544284 & 0.997279 \tabularnewline
41 & 0.00611208 & 0.0122242 & 0.993888 \tabularnewline
42 & 0.00424164 & 0.00848328 & 0.995758 \tabularnewline
43 & 0.00319443 & 0.00638885 & 0.996806 \tabularnewline
44 & 0.00219577 & 0.00439155 & 0.997804 \tabularnewline
45 & 0.00158344 & 0.00316688 & 0.998417 \tabularnewline
46 & 0.00106078 & 0.00212155 & 0.998939 \tabularnewline
47 & 0.000692226 & 0.00138445 & 0.999308 \tabularnewline
48 & 0.000673611 & 0.00134722 & 0.999326 \tabularnewline
49 & 0.000503255 & 0.00100651 & 0.999497 \tabularnewline
50 & 0.000389183 & 0.000778367 & 0.999611 \tabularnewline
51 & 0.000280277 & 0.000560554 & 0.99972 \tabularnewline
52 & 0.000639869 & 0.00127974 & 0.99936 \tabularnewline
53 & 0.000433013 & 0.000866025 & 0.999567 \tabularnewline
54 & 0.000302158 & 0.000604315 & 0.999698 \tabularnewline
55 & 0.000239429 & 0.000478858 & 0.999761 \tabularnewline
56 & 0.000164463 & 0.000328927 & 0.999836 \tabularnewline
57 & 0.000478956 & 0.000957912 & 0.999521 \tabularnewline
58 & 0.000601849 & 0.0012037 & 0.999398 \tabularnewline
59 & 0.000799528 & 0.00159906 & 0.9992 \tabularnewline
60 & 0.000715105 & 0.00143021 & 0.999285 \tabularnewline
61 & 0.00062297 & 0.00124594 & 0.999377 \tabularnewline
62 & 0.00046414 & 0.00092828 & 0.999536 \tabularnewline
63 & 0.000564464 & 0.00112893 & 0.999436 \tabularnewline
64 & 0.00121892 & 0.00243785 & 0.998781 \tabularnewline
65 & 0.00113189 & 0.00226378 & 0.998868 \tabularnewline
66 & 0.0010539 & 0.0021078 & 0.998946 \tabularnewline
67 & 0.000763421 & 0.00152684 & 0.999237 \tabularnewline
68 & 0.0006033 & 0.0012066 & 0.999397 \tabularnewline
69 & 0.000813851 & 0.0016277 & 0.999186 \tabularnewline
70 & 0.000621687 & 0.00124337 & 0.999378 \tabularnewline
71 & 0.000456091 & 0.000912183 & 0.999544 \tabularnewline
72 & 0.000321528 & 0.000643057 & 0.999678 \tabularnewline
73 & 0.000314425 & 0.000628851 & 0.999686 \tabularnewline
74 & 0.000365837 & 0.000731674 & 0.999634 \tabularnewline
75 & 0.000285084 & 0.000570168 & 0.999715 \tabularnewline
76 & 0.000220319 & 0.000440637 & 0.99978 \tabularnewline
77 & 0.000156917 & 0.000313835 & 0.999843 \tabularnewline
78 & 0.000134428 & 0.000268856 & 0.999866 \tabularnewline
79 & 0.000110759 & 0.000221519 & 0.999889 \tabularnewline
80 & 0.000176596 & 0.000353193 & 0.999823 \tabularnewline
81 & 0.000130664 & 0.000261328 & 0.999869 \tabularnewline
82 & 0.00010193 & 0.000203861 & 0.999898 \tabularnewline
83 & 7.33458e-05 & 0.000146692 & 0.999927 \tabularnewline
84 & 0.000605851 & 0.0012117 & 0.999394 \tabularnewline
85 & 0.00047845 & 0.000956899 & 0.999522 \tabularnewline
86 & 0.000355696 & 0.000711392 & 0.999644 \tabularnewline
87 & 0.000265791 & 0.000531582 & 0.999734 \tabularnewline
88 & 0.000194647 & 0.000389293 & 0.999805 \tabularnewline
89 & 0.000205453 & 0.000410905 & 0.999795 \tabularnewline
90 & 0.000180099 & 0.000360198 & 0.99982 \tabularnewline
91 & 0.000145383 & 0.000290766 & 0.999855 \tabularnewline
92 & 0.000501237 & 0.00100247 & 0.999499 \tabularnewline
93 & 0.000426954 & 0.000853909 & 0.999573 \tabularnewline
94 & 0.000450102 & 0.000900204 & 0.99955 \tabularnewline
95 & 0.000710221 & 0.00142044 & 0.99929 \tabularnewline
96 & 0.000693343 & 0.00138669 & 0.999307 \tabularnewline
97 & 0.0012439 & 0.00248781 & 0.998756 \tabularnewline
98 & 0.00098832 & 0.00197664 & 0.999012 \tabularnewline
99 & 0.000951594 & 0.00190319 & 0.999048 \tabularnewline
100 & 0.00127654 & 0.00255307 & 0.998723 \tabularnewline
101 & 0.00105413 & 0.00210826 & 0.998946 \tabularnewline
102 & 0.000913867 & 0.00182773 & 0.999086 \tabularnewline
103 & 0.00110778 & 0.00221556 & 0.998892 \tabularnewline
104 & 0.00104937 & 0.00209875 & 0.998951 \tabularnewline
105 & 0.00113734 & 0.00227469 & 0.998863 \tabularnewline
106 & 0.00145611 & 0.00291222 & 0.998544 \tabularnewline
107 & 0.00135323 & 0.00270646 & 0.998647 \tabularnewline
108 & 0.00602174 & 0.0120435 & 0.993978 \tabularnewline
109 & 0.0129735 & 0.025947 & 0.987027 \tabularnewline
110 & 0.0130594 & 0.0261188 & 0.986941 \tabularnewline
111 & 0.0114197 & 0.0228394 & 0.98858 \tabularnewline
112 & 0.0100604 & 0.0201208 & 0.98994 \tabularnewline
113 & 0.0438271 & 0.0876541 & 0.956173 \tabularnewline
114 & 0.0401078 & 0.0802156 & 0.959892 \tabularnewline
115 & 0.0850901 & 0.17018 & 0.91491 \tabularnewline
116 & 0.144799 & 0.289599 & 0.855201 \tabularnewline
117 & 0.177106 & 0.354211 & 0.822894 \tabularnewline
118 & 0.163873 & 0.327746 & 0.836127 \tabularnewline
119 & 0.217146 & 0.434292 & 0.782854 \tabularnewline
120 & 0.355381 & 0.710761 & 0.644619 \tabularnewline
121 & 0.385771 & 0.771542 & 0.614229 \tabularnewline
122 & 0.366834 & 0.733669 & 0.633166 \tabularnewline
123 & 0.480616 & 0.961232 & 0.519384 \tabularnewline
124 & 0.475701 & 0.951401 & 0.524299 \tabularnewline
125 & 0.468268 & 0.936537 & 0.531732 \tabularnewline
126 & 0.445477 & 0.890954 & 0.554523 \tabularnewline
127 & 0.473945 & 0.947891 & 0.526055 \tabularnewline
128 & 0.453645 & 0.90729 & 0.546355 \tabularnewline
129 & 0.575291 & 0.849418 & 0.424709 \tabularnewline
130 & 0.557471 & 0.885058 & 0.442529 \tabularnewline
131 & 0.54405 & 0.9119 & 0.45595 \tabularnewline
132 & 0.563409 & 0.873182 & 0.436591 \tabularnewline
133 & 0.551872 & 0.896257 & 0.448128 \tabularnewline
134 & 0.540387 & 0.919226 & 0.459613 \tabularnewline
135 & 0.514936 & 0.970127 & 0.485064 \tabularnewline
136 & 0.490222 & 0.980444 & 0.509778 \tabularnewline
137 & 0.538288 & 0.923424 & 0.461712 \tabularnewline
138 & 0.592461 & 0.815078 & 0.407539 \tabularnewline
139 & 0.672433 & 0.655133 & 0.327567 \tabularnewline
140 & 0.679766 & 0.640468 & 0.320234 \tabularnewline
141 & 0.663014 & 0.673972 & 0.336986 \tabularnewline
142 & 0.710642 & 0.578716 & 0.289358 \tabularnewline
143 & 0.701478 & 0.597045 & 0.298522 \tabularnewline
144 & 0.738069 & 0.523862 & 0.261931 \tabularnewline
145 & 0.744604 & 0.510792 & 0.255396 \tabularnewline
146 & 0.780984 & 0.438031 & 0.219016 \tabularnewline
147 & 0.760376 & 0.479249 & 0.239624 \tabularnewline
148 & 0.741549 & 0.516901 & 0.258451 \tabularnewline
149 & 0.724948 & 0.550105 & 0.275052 \tabularnewline
150 & 0.769281 & 0.461438 & 0.230719 \tabularnewline
151 & 0.77128 & 0.45744 & 0.22872 \tabularnewline
152 & 0.76882 & 0.46236 & 0.23118 \tabularnewline
153 & 0.808866 & 0.382269 & 0.191134 \tabularnewline
154 & 0.817542 & 0.364917 & 0.182458 \tabularnewline
155 & 0.801168 & 0.397665 & 0.198832 \tabularnewline
156 & 0.780162 & 0.439676 & 0.219838 \tabularnewline
157 & 0.833509 & 0.332982 & 0.166491 \tabularnewline
158 & 0.825126 & 0.349748 & 0.174874 \tabularnewline
159 & 0.809958 & 0.380084 & 0.190042 \tabularnewline
160 & 0.793179 & 0.413643 & 0.206821 \tabularnewline
161 & 0.833795 & 0.332411 & 0.166205 \tabularnewline
162 & 0.829401 & 0.341198 & 0.170599 \tabularnewline
163 & 0.838764 & 0.322473 & 0.161236 \tabularnewline
164 & 0.835368 & 0.329264 & 0.164632 \tabularnewline
165 & 0.890912 & 0.218177 & 0.109088 \tabularnewline
166 & 0.8874 & 0.2252 & 0.1126 \tabularnewline
167 & 0.911279 & 0.177441 & 0.0887206 \tabularnewline
168 & 0.90123 & 0.197539 & 0.0987697 \tabularnewline
169 & 0.89032 & 0.219359 & 0.10968 \tabularnewline
170 & 0.882682 & 0.234636 & 0.117318 \tabularnewline
171 & 0.876174 & 0.247651 & 0.123826 \tabularnewline
172 & 0.894643 & 0.210714 & 0.105357 \tabularnewline
173 & 0.880758 & 0.238484 & 0.119242 \tabularnewline
174 & 0.870974 & 0.258051 & 0.129026 \tabularnewline
175 & 0.860075 & 0.279849 & 0.139925 \tabularnewline
176 & 0.881467 & 0.237065 & 0.118533 \tabularnewline
177 & 0.864111 & 0.271778 & 0.135889 \tabularnewline
178 & 0.901296 & 0.197408 & 0.0987039 \tabularnewline
179 & 0.891414 & 0.217173 & 0.108586 \tabularnewline
180 & 0.925471 & 0.149057 & 0.0745286 \tabularnewline
181 & 0.912601 & 0.174798 & 0.0873991 \tabularnewline
182 & 0.898603 & 0.202793 & 0.101397 \tabularnewline
183 & 0.919078 & 0.161844 & 0.080922 \tabularnewline
184 & 0.908823 & 0.182354 & 0.0911769 \tabularnewline
185 & 0.895069 & 0.209861 & 0.104931 \tabularnewline
186 & 0.888535 & 0.222931 & 0.111465 \tabularnewline
187 & 0.892019 & 0.215962 & 0.107981 \tabularnewline
188 & 0.875017 & 0.249965 & 0.124983 \tabularnewline
189 & 0.858903 & 0.282194 & 0.141097 \tabularnewline
190 & 0.843276 & 0.313448 & 0.156724 \tabularnewline
191 & 0.842387 & 0.315225 & 0.157613 \tabularnewline
192 & 0.827959 & 0.344081 & 0.172041 \tabularnewline
193 & 0.837566 & 0.324868 & 0.162434 \tabularnewline
194 & 0.863287 & 0.273427 & 0.136713 \tabularnewline
195 & 0.842321 & 0.315359 & 0.157679 \tabularnewline
196 & 0.82209 & 0.35582 & 0.17791 \tabularnewline
197 & 0.801834 & 0.396333 & 0.198166 \tabularnewline
198 & 0.775785 & 0.448429 & 0.224215 \tabularnewline
199 & 0.753321 & 0.493358 & 0.246679 \tabularnewline
200 & 0.738512 & 0.522975 & 0.261488 \tabularnewline
201 & 0.793868 & 0.412264 & 0.206132 \tabularnewline
202 & 0.766141 & 0.467719 & 0.233859 \tabularnewline
203 & 0.736373 & 0.527254 & 0.263627 \tabularnewline
204 & 0.715484 & 0.569032 & 0.284516 \tabularnewline
205 & 0.682434 & 0.635133 & 0.317566 \tabularnewline
206 & 0.650092 & 0.699816 & 0.349908 \tabularnewline
207 & 0.655785 & 0.688429 & 0.344215 \tabularnewline
208 & 0.622108 & 0.755785 & 0.377892 \tabularnewline
209 & 0.683403 & 0.633195 & 0.316597 \tabularnewline
210 & 0.676494 & 0.647011 & 0.323506 \tabularnewline
211 & 0.662738 & 0.674525 & 0.337262 \tabularnewline
212 & 0.634951 & 0.730098 & 0.365049 \tabularnewline
213 & 0.612072 & 0.775856 & 0.387928 \tabularnewline
214 & 0.573569 & 0.852862 & 0.426431 \tabularnewline
215 & 0.557067 & 0.885866 & 0.442933 \tabularnewline
216 & 0.523195 & 0.953609 & 0.476805 \tabularnewline
217 & 0.5003 & 0.9994 & 0.4997 \tabularnewline
218 & 0.536824 & 0.926353 & 0.463176 \tabularnewline
219 & 0.515037 & 0.969926 & 0.484963 \tabularnewline
220 & 0.489067 & 0.978133 & 0.510933 \tabularnewline
221 & 0.512993 & 0.974013 & 0.487007 \tabularnewline
222 & 0.608856 & 0.782289 & 0.391144 \tabularnewline
223 & 0.58066 & 0.838679 & 0.41934 \tabularnewline
224 & 0.548478 & 0.903044 & 0.451522 \tabularnewline
225 & 0.635176 & 0.729648 & 0.364824 \tabularnewline
226 & 0.600304 & 0.799393 & 0.399696 \tabularnewline
227 & 0.603046 & 0.793908 & 0.396954 \tabularnewline
228 & 0.578328 & 0.843344 & 0.421672 \tabularnewline
229 & 0.644148 & 0.711705 & 0.355852 \tabularnewline
230 & 0.720354 & 0.559293 & 0.279646 \tabularnewline
231 & 0.769185 & 0.46163 & 0.230815 \tabularnewline
232 & 0.838211 & 0.323577 & 0.161789 \tabularnewline
233 & 0.807211 & 0.385579 & 0.192789 \tabularnewline
234 & 0.772209 & 0.455583 & 0.227791 \tabularnewline
235 & 0.77503 & 0.449939 & 0.22497 \tabularnewline
236 & 0.936118 & 0.127764 & 0.0638819 \tabularnewline
237 & 0.923597 & 0.152805 & 0.0764026 \tabularnewline
238 & 0.903546 & 0.192909 & 0.0964545 \tabularnewline
239 & 0.887599 & 0.224802 & 0.112401 \tabularnewline
240 & 0.862465 & 0.27507 & 0.137535 \tabularnewline
241 & 0.831479 & 0.337042 & 0.168521 \tabularnewline
242 & 0.811982 & 0.376035 & 0.188018 \tabularnewline
243 & 0.781066 & 0.437869 & 0.218934 \tabularnewline
244 & 0.884017 & 0.231967 & 0.115983 \tabularnewline
245 & 0.866608 & 0.266784 & 0.133392 \tabularnewline
246 & 0.835622 & 0.328757 & 0.164378 \tabularnewline
247 & 0.867891 & 0.264217 & 0.132109 \tabularnewline
248 & 0.840082 & 0.319837 & 0.159918 \tabularnewline
249 & 0.830426 & 0.339147 & 0.169574 \tabularnewline
250 & 0.789686 & 0.420628 & 0.210314 \tabularnewline
251 & 0.754219 & 0.491562 & 0.245781 \tabularnewline
252 & 0.710695 & 0.578611 & 0.289305 \tabularnewline
253 & 0.663135 & 0.673731 & 0.336865 \tabularnewline
254 & 0.626967 & 0.746066 & 0.373033 \tabularnewline
255 & 0.564566 & 0.870869 & 0.435434 \tabularnewline
256 & 0.563667 & 0.872667 & 0.436333 \tabularnewline
257 & 0.651039 & 0.697921 & 0.348961 \tabularnewline
258 & 0.773831 & 0.452337 & 0.226169 \tabularnewline
259 & 0.720459 & 0.559082 & 0.279541 \tabularnewline
260 & 0.852523 & 0.294955 & 0.147477 \tabularnewline
261 & 0.850117 & 0.299766 & 0.149883 \tabularnewline
262 & 0.820055 & 0.35989 & 0.179945 \tabularnewline
263 & 0.90065 & 0.198701 & 0.0993504 \tabularnewline
264 & 0.858028 & 0.283944 & 0.141972 \tabularnewline
265 & 0.836935 & 0.32613 & 0.163065 \tabularnewline
266 & 0.769411 & 0.461179 & 0.230589 \tabularnewline
267 & 0.6878 & 0.624399 & 0.3122 \tabularnewline
268 & 0.592648 & 0.814703 & 0.407352 \tabularnewline
269 & 0.546085 & 0.90783 & 0.453915 \tabularnewline
270 & 0.544043 & 0.911913 & 0.455957 \tabularnewline
271 & 0.416664 & 0.833327 & 0.583336 \tabularnewline
272 & 0.321577 & 0.643154 & 0.678423 \tabularnewline
273 & 0.197397 & 0.394794 & 0.802603 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&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]5[/C][C]0.598198[/C][C]0.803604[/C][C]0.401802[/C][/ROW]
[ROW][C]6[/C][C]0.473099[/C][C]0.946198[/C][C]0.526901[/C][/ROW]
[ROW][C]7[/C][C]0.529196[/C][C]0.941608[/C][C]0.470804[/C][/ROW]
[ROW][C]8[/C][C]0.44452[/C][C]0.889039[/C][C]0.55548[/C][/ROW]
[ROW][C]9[/C][C]0.333163[/C][C]0.666325[/C][C]0.666837[/C][/ROW]
[ROW][C]10[/C][C]0.253068[/C][C]0.506136[/C][C]0.746932[/C][/ROW]
[ROW][C]11[/C][C]0.183916[/C][C]0.367832[/C][C]0.816084[/C][/ROW]
[ROW][C]12[/C][C]0.299342[/C][C]0.598683[/C][C]0.700658[/C][/ROW]
[ROW][C]13[/C][C]0.225557[/C][C]0.451114[/C][C]0.774443[/C][/ROW]
[ROW][C]14[/C][C]0.168935[/C][C]0.33787[/C][C]0.831065[/C][/ROW]
[ROW][C]15[/C][C]0.228053[/C][C]0.456107[/C][C]0.771947[/C][/ROW]
[ROW][C]16[/C][C]0.180584[/C][C]0.361168[/C][C]0.819416[/C][/ROW]
[ROW][C]17[/C][C]0.143084[/C][C]0.286167[/C][C]0.856916[/C][/ROW]
[ROW][C]18[/C][C]0.118335[/C][C]0.236671[/C][C]0.881665[/C][/ROW]
[ROW][C]19[/C][C]0.0882527[/C][C]0.176505[/C][C]0.911747[/C][/ROW]
[ROW][C]20[/C][C]0.0628853[/C][C]0.125771[/C][C]0.937115[/C][/ROW]
[ROW][C]21[/C][C]0.0705989[/C][C]0.141198[/C][C]0.929401[/C][/ROW]
[ROW][C]22[/C][C]0.0874424[/C][C]0.174885[/C][C]0.912558[/C][/ROW]
[ROW][C]23[/C][C]0.0641024[/C][C]0.128205[/C][C]0.935898[/C][/ROW]
[ROW][C]24[/C][C]0.0681976[/C][C]0.136395[/C][C]0.931802[/C][/ROW]
[ROW][C]25[/C][C]0.0508709[/C][C]0.101742[/C][C]0.949129[/C][/ROW]
[ROW][C]26[/C][C]0.0364157[/C][C]0.0728314[/C][C]0.963584[/C][/ROW]
[ROW][C]27[/C][C]0.0690094[/C][C]0.138019[/C][C]0.930991[/C][/ROW]
[ROW][C]28[/C][C]0.0617217[/C][C]0.123443[/C][C]0.938278[/C][/ROW]
[ROW][C]29[/C][C]0.0487723[/C][C]0.0975447[/C][C]0.951228[/C][/ROW]
[ROW][C]30[/C][C]0.0363217[/C][C]0.0726435[/C][C]0.963678[/C][/ROW]
[ROW][C]31[/C][C]0.0363281[/C][C]0.0726561[/C][C]0.963672[/C][/ROW]
[ROW][C]32[/C][C]0.0260857[/C][C]0.0521715[/C][C]0.973914[/C][/ROW]
[ROW][C]33[/C][C]0.022295[/C][C]0.04459[/C][C]0.977705[/C][/ROW]
[ROW][C]34[/C][C]0.0173049[/C][C]0.0346099[/C][C]0.982695[/C][/ROW]
[ROW][C]35[/C][C]0.0122215[/C][C]0.0244429[/C][C]0.987779[/C][/ROW]
[ROW][C]36[/C][C]0.00892867[/C][C]0.0178573[/C][C]0.991071[/C][/ROW]
[ROW][C]37[/C][C]0.006284[/C][C]0.012568[/C][C]0.993716[/C][/ROW]
[ROW][C]38[/C][C]0.00491037[/C][C]0.00982075[/C][C]0.99509[/C][/ROW]
[ROW][C]39[/C][C]0.00388291[/C][C]0.00776582[/C][C]0.996117[/C][/ROW]
[ROW][C]40[/C][C]0.00272142[/C][C]0.00544284[/C][C]0.997279[/C][/ROW]
[ROW][C]41[/C][C]0.00611208[/C][C]0.0122242[/C][C]0.993888[/C][/ROW]
[ROW][C]42[/C][C]0.00424164[/C][C]0.00848328[/C][C]0.995758[/C][/ROW]
[ROW][C]43[/C][C]0.00319443[/C][C]0.00638885[/C][C]0.996806[/C][/ROW]
[ROW][C]44[/C][C]0.00219577[/C][C]0.00439155[/C][C]0.997804[/C][/ROW]
[ROW][C]45[/C][C]0.00158344[/C][C]0.00316688[/C][C]0.998417[/C][/ROW]
[ROW][C]46[/C][C]0.00106078[/C][C]0.00212155[/C][C]0.998939[/C][/ROW]
[ROW][C]47[/C][C]0.000692226[/C][C]0.00138445[/C][C]0.999308[/C][/ROW]
[ROW][C]48[/C][C]0.000673611[/C][C]0.00134722[/C][C]0.999326[/C][/ROW]
[ROW][C]49[/C][C]0.000503255[/C][C]0.00100651[/C][C]0.999497[/C][/ROW]
[ROW][C]50[/C][C]0.000389183[/C][C]0.000778367[/C][C]0.999611[/C][/ROW]
[ROW][C]51[/C][C]0.000280277[/C][C]0.000560554[/C][C]0.99972[/C][/ROW]
[ROW][C]52[/C][C]0.000639869[/C][C]0.00127974[/C][C]0.99936[/C][/ROW]
[ROW][C]53[/C][C]0.000433013[/C][C]0.000866025[/C][C]0.999567[/C][/ROW]
[ROW][C]54[/C][C]0.000302158[/C][C]0.000604315[/C][C]0.999698[/C][/ROW]
[ROW][C]55[/C][C]0.000239429[/C][C]0.000478858[/C][C]0.999761[/C][/ROW]
[ROW][C]56[/C][C]0.000164463[/C][C]0.000328927[/C][C]0.999836[/C][/ROW]
[ROW][C]57[/C][C]0.000478956[/C][C]0.000957912[/C][C]0.999521[/C][/ROW]
[ROW][C]58[/C][C]0.000601849[/C][C]0.0012037[/C][C]0.999398[/C][/ROW]
[ROW][C]59[/C][C]0.000799528[/C][C]0.00159906[/C][C]0.9992[/C][/ROW]
[ROW][C]60[/C][C]0.000715105[/C][C]0.00143021[/C][C]0.999285[/C][/ROW]
[ROW][C]61[/C][C]0.00062297[/C][C]0.00124594[/C][C]0.999377[/C][/ROW]
[ROW][C]62[/C][C]0.00046414[/C][C]0.00092828[/C][C]0.999536[/C][/ROW]
[ROW][C]63[/C][C]0.000564464[/C][C]0.00112893[/C][C]0.999436[/C][/ROW]
[ROW][C]64[/C][C]0.00121892[/C][C]0.00243785[/C][C]0.998781[/C][/ROW]
[ROW][C]65[/C][C]0.00113189[/C][C]0.00226378[/C][C]0.998868[/C][/ROW]
[ROW][C]66[/C][C]0.0010539[/C][C]0.0021078[/C][C]0.998946[/C][/ROW]
[ROW][C]67[/C][C]0.000763421[/C][C]0.00152684[/C][C]0.999237[/C][/ROW]
[ROW][C]68[/C][C]0.0006033[/C][C]0.0012066[/C][C]0.999397[/C][/ROW]
[ROW][C]69[/C][C]0.000813851[/C][C]0.0016277[/C][C]0.999186[/C][/ROW]
[ROW][C]70[/C][C]0.000621687[/C][C]0.00124337[/C][C]0.999378[/C][/ROW]
[ROW][C]71[/C][C]0.000456091[/C][C]0.000912183[/C][C]0.999544[/C][/ROW]
[ROW][C]72[/C][C]0.000321528[/C][C]0.000643057[/C][C]0.999678[/C][/ROW]
[ROW][C]73[/C][C]0.000314425[/C][C]0.000628851[/C][C]0.999686[/C][/ROW]
[ROW][C]74[/C][C]0.000365837[/C][C]0.000731674[/C][C]0.999634[/C][/ROW]
[ROW][C]75[/C][C]0.000285084[/C][C]0.000570168[/C][C]0.999715[/C][/ROW]
[ROW][C]76[/C][C]0.000220319[/C][C]0.000440637[/C][C]0.99978[/C][/ROW]
[ROW][C]77[/C][C]0.000156917[/C][C]0.000313835[/C][C]0.999843[/C][/ROW]
[ROW][C]78[/C][C]0.000134428[/C][C]0.000268856[/C][C]0.999866[/C][/ROW]
[ROW][C]79[/C][C]0.000110759[/C][C]0.000221519[/C][C]0.999889[/C][/ROW]
[ROW][C]80[/C][C]0.000176596[/C][C]0.000353193[/C][C]0.999823[/C][/ROW]
[ROW][C]81[/C][C]0.000130664[/C][C]0.000261328[/C][C]0.999869[/C][/ROW]
[ROW][C]82[/C][C]0.00010193[/C][C]0.000203861[/C][C]0.999898[/C][/ROW]
[ROW][C]83[/C][C]7.33458e-05[/C][C]0.000146692[/C][C]0.999927[/C][/ROW]
[ROW][C]84[/C][C]0.000605851[/C][C]0.0012117[/C][C]0.999394[/C][/ROW]
[ROW][C]85[/C][C]0.00047845[/C][C]0.000956899[/C][C]0.999522[/C][/ROW]
[ROW][C]86[/C][C]0.000355696[/C][C]0.000711392[/C][C]0.999644[/C][/ROW]
[ROW][C]87[/C][C]0.000265791[/C][C]0.000531582[/C][C]0.999734[/C][/ROW]
[ROW][C]88[/C][C]0.000194647[/C][C]0.000389293[/C][C]0.999805[/C][/ROW]
[ROW][C]89[/C][C]0.000205453[/C][C]0.000410905[/C][C]0.999795[/C][/ROW]
[ROW][C]90[/C][C]0.000180099[/C][C]0.000360198[/C][C]0.99982[/C][/ROW]
[ROW][C]91[/C][C]0.000145383[/C][C]0.000290766[/C][C]0.999855[/C][/ROW]
[ROW][C]92[/C][C]0.000501237[/C][C]0.00100247[/C][C]0.999499[/C][/ROW]
[ROW][C]93[/C][C]0.000426954[/C][C]0.000853909[/C][C]0.999573[/C][/ROW]
[ROW][C]94[/C][C]0.000450102[/C][C]0.000900204[/C][C]0.99955[/C][/ROW]
[ROW][C]95[/C][C]0.000710221[/C][C]0.00142044[/C][C]0.99929[/C][/ROW]
[ROW][C]96[/C][C]0.000693343[/C][C]0.00138669[/C][C]0.999307[/C][/ROW]
[ROW][C]97[/C][C]0.0012439[/C][C]0.00248781[/C][C]0.998756[/C][/ROW]
[ROW][C]98[/C][C]0.00098832[/C][C]0.00197664[/C][C]0.999012[/C][/ROW]
[ROW][C]99[/C][C]0.000951594[/C][C]0.00190319[/C][C]0.999048[/C][/ROW]
[ROW][C]100[/C][C]0.00127654[/C][C]0.00255307[/C][C]0.998723[/C][/ROW]
[ROW][C]101[/C][C]0.00105413[/C][C]0.00210826[/C][C]0.998946[/C][/ROW]
[ROW][C]102[/C][C]0.000913867[/C][C]0.00182773[/C][C]0.999086[/C][/ROW]
[ROW][C]103[/C][C]0.00110778[/C][C]0.00221556[/C][C]0.998892[/C][/ROW]
[ROW][C]104[/C][C]0.00104937[/C][C]0.00209875[/C][C]0.998951[/C][/ROW]
[ROW][C]105[/C][C]0.00113734[/C][C]0.00227469[/C][C]0.998863[/C][/ROW]
[ROW][C]106[/C][C]0.00145611[/C][C]0.00291222[/C][C]0.998544[/C][/ROW]
[ROW][C]107[/C][C]0.00135323[/C][C]0.00270646[/C][C]0.998647[/C][/ROW]
[ROW][C]108[/C][C]0.00602174[/C][C]0.0120435[/C][C]0.993978[/C][/ROW]
[ROW][C]109[/C][C]0.0129735[/C][C]0.025947[/C][C]0.987027[/C][/ROW]
[ROW][C]110[/C][C]0.0130594[/C][C]0.0261188[/C][C]0.986941[/C][/ROW]
[ROW][C]111[/C][C]0.0114197[/C][C]0.0228394[/C][C]0.98858[/C][/ROW]
[ROW][C]112[/C][C]0.0100604[/C][C]0.0201208[/C][C]0.98994[/C][/ROW]
[ROW][C]113[/C][C]0.0438271[/C][C]0.0876541[/C][C]0.956173[/C][/ROW]
[ROW][C]114[/C][C]0.0401078[/C][C]0.0802156[/C][C]0.959892[/C][/ROW]
[ROW][C]115[/C][C]0.0850901[/C][C]0.17018[/C][C]0.91491[/C][/ROW]
[ROW][C]116[/C][C]0.144799[/C][C]0.289599[/C][C]0.855201[/C][/ROW]
[ROW][C]117[/C][C]0.177106[/C][C]0.354211[/C][C]0.822894[/C][/ROW]
[ROW][C]118[/C][C]0.163873[/C][C]0.327746[/C][C]0.836127[/C][/ROW]
[ROW][C]119[/C][C]0.217146[/C][C]0.434292[/C][C]0.782854[/C][/ROW]
[ROW][C]120[/C][C]0.355381[/C][C]0.710761[/C][C]0.644619[/C][/ROW]
[ROW][C]121[/C][C]0.385771[/C][C]0.771542[/C][C]0.614229[/C][/ROW]
[ROW][C]122[/C][C]0.366834[/C][C]0.733669[/C][C]0.633166[/C][/ROW]
[ROW][C]123[/C][C]0.480616[/C][C]0.961232[/C][C]0.519384[/C][/ROW]
[ROW][C]124[/C][C]0.475701[/C][C]0.951401[/C][C]0.524299[/C][/ROW]
[ROW][C]125[/C][C]0.468268[/C][C]0.936537[/C][C]0.531732[/C][/ROW]
[ROW][C]126[/C][C]0.445477[/C][C]0.890954[/C][C]0.554523[/C][/ROW]
[ROW][C]127[/C][C]0.473945[/C][C]0.947891[/C][C]0.526055[/C][/ROW]
[ROW][C]128[/C][C]0.453645[/C][C]0.90729[/C][C]0.546355[/C][/ROW]
[ROW][C]129[/C][C]0.575291[/C][C]0.849418[/C][C]0.424709[/C][/ROW]
[ROW][C]130[/C][C]0.557471[/C][C]0.885058[/C][C]0.442529[/C][/ROW]
[ROW][C]131[/C][C]0.54405[/C][C]0.9119[/C][C]0.45595[/C][/ROW]
[ROW][C]132[/C][C]0.563409[/C][C]0.873182[/C][C]0.436591[/C][/ROW]
[ROW][C]133[/C][C]0.551872[/C][C]0.896257[/C][C]0.448128[/C][/ROW]
[ROW][C]134[/C][C]0.540387[/C][C]0.919226[/C][C]0.459613[/C][/ROW]
[ROW][C]135[/C][C]0.514936[/C][C]0.970127[/C][C]0.485064[/C][/ROW]
[ROW][C]136[/C][C]0.490222[/C][C]0.980444[/C][C]0.509778[/C][/ROW]
[ROW][C]137[/C][C]0.538288[/C][C]0.923424[/C][C]0.461712[/C][/ROW]
[ROW][C]138[/C][C]0.592461[/C][C]0.815078[/C][C]0.407539[/C][/ROW]
[ROW][C]139[/C][C]0.672433[/C][C]0.655133[/C][C]0.327567[/C][/ROW]
[ROW][C]140[/C][C]0.679766[/C][C]0.640468[/C][C]0.320234[/C][/ROW]
[ROW][C]141[/C][C]0.663014[/C][C]0.673972[/C][C]0.336986[/C][/ROW]
[ROW][C]142[/C][C]0.710642[/C][C]0.578716[/C][C]0.289358[/C][/ROW]
[ROW][C]143[/C][C]0.701478[/C][C]0.597045[/C][C]0.298522[/C][/ROW]
[ROW][C]144[/C][C]0.738069[/C][C]0.523862[/C][C]0.261931[/C][/ROW]
[ROW][C]145[/C][C]0.744604[/C][C]0.510792[/C][C]0.255396[/C][/ROW]
[ROW][C]146[/C][C]0.780984[/C][C]0.438031[/C][C]0.219016[/C][/ROW]
[ROW][C]147[/C][C]0.760376[/C][C]0.479249[/C][C]0.239624[/C][/ROW]
[ROW][C]148[/C][C]0.741549[/C][C]0.516901[/C][C]0.258451[/C][/ROW]
[ROW][C]149[/C][C]0.724948[/C][C]0.550105[/C][C]0.275052[/C][/ROW]
[ROW][C]150[/C][C]0.769281[/C][C]0.461438[/C][C]0.230719[/C][/ROW]
[ROW][C]151[/C][C]0.77128[/C][C]0.45744[/C][C]0.22872[/C][/ROW]
[ROW][C]152[/C][C]0.76882[/C][C]0.46236[/C][C]0.23118[/C][/ROW]
[ROW][C]153[/C][C]0.808866[/C][C]0.382269[/C][C]0.191134[/C][/ROW]
[ROW][C]154[/C][C]0.817542[/C][C]0.364917[/C][C]0.182458[/C][/ROW]
[ROW][C]155[/C][C]0.801168[/C][C]0.397665[/C][C]0.198832[/C][/ROW]
[ROW][C]156[/C][C]0.780162[/C][C]0.439676[/C][C]0.219838[/C][/ROW]
[ROW][C]157[/C][C]0.833509[/C][C]0.332982[/C][C]0.166491[/C][/ROW]
[ROW][C]158[/C][C]0.825126[/C][C]0.349748[/C][C]0.174874[/C][/ROW]
[ROW][C]159[/C][C]0.809958[/C][C]0.380084[/C][C]0.190042[/C][/ROW]
[ROW][C]160[/C][C]0.793179[/C][C]0.413643[/C][C]0.206821[/C][/ROW]
[ROW][C]161[/C][C]0.833795[/C][C]0.332411[/C][C]0.166205[/C][/ROW]
[ROW][C]162[/C][C]0.829401[/C][C]0.341198[/C][C]0.170599[/C][/ROW]
[ROW][C]163[/C][C]0.838764[/C][C]0.322473[/C][C]0.161236[/C][/ROW]
[ROW][C]164[/C][C]0.835368[/C][C]0.329264[/C][C]0.164632[/C][/ROW]
[ROW][C]165[/C][C]0.890912[/C][C]0.218177[/C][C]0.109088[/C][/ROW]
[ROW][C]166[/C][C]0.8874[/C][C]0.2252[/C][C]0.1126[/C][/ROW]
[ROW][C]167[/C][C]0.911279[/C][C]0.177441[/C][C]0.0887206[/C][/ROW]
[ROW][C]168[/C][C]0.90123[/C][C]0.197539[/C][C]0.0987697[/C][/ROW]
[ROW][C]169[/C][C]0.89032[/C][C]0.219359[/C][C]0.10968[/C][/ROW]
[ROW][C]170[/C][C]0.882682[/C][C]0.234636[/C][C]0.117318[/C][/ROW]
[ROW][C]171[/C][C]0.876174[/C][C]0.247651[/C][C]0.123826[/C][/ROW]
[ROW][C]172[/C][C]0.894643[/C][C]0.210714[/C][C]0.105357[/C][/ROW]
[ROW][C]173[/C][C]0.880758[/C][C]0.238484[/C][C]0.119242[/C][/ROW]
[ROW][C]174[/C][C]0.870974[/C][C]0.258051[/C][C]0.129026[/C][/ROW]
[ROW][C]175[/C][C]0.860075[/C][C]0.279849[/C][C]0.139925[/C][/ROW]
[ROW][C]176[/C][C]0.881467[/C][C]0.237065[/C][C]0.118533[/C][/ROW]
[ROW][C]177[/C][C]0.864111[/C][C]0.271778[/C][C]0.135889[/C][/ROW]
[ROW][C]178[/C][C]0.901296[/C][C]0.197408[/C][C]0.0987039[/C][/ROW]
[ROW][C]179[/C][C]0.891414[/C][C]0.217173[/C][C]0.108586[/C][/ROW]
[ROW][C]180[/C][C]0.925471[/C][C]0.149057[/C][C]0.0745286[/C][/ROW]
[ROW][C]181[/C][C]0.912601[/C][C]0.174798[/C][C]0.0873991[/C][/ROW]
[ROW][C]182[/C][C]0.898603[/C][C]0.202793[/C][C]0.101397[/C][/ROW]
[ROW][C]183[/C][C]0.919078[/C][C]0.161844[/C][C]0.080922[/C][/ROW]
[ROW][C]184[/C][C]0.908823[/C][C]0.182354[/C][C]0.0911769[/C][/ROW]
[ROW][C]185[/C][C]0.895069[/C][C]0.209861[/C][C]0.104931[/C][/ROW]
[ROW][C]186[/C][C]0.888535[/C][C]0.222931[/C][C]0.111465[/C][/ROW]
[ROW][C]187[/C][C]0.892019[/C][C]0.215962[/C][C]0.107981[/C][/ROW]
[ROW][C]188[/C][C]0.875017[/C][C]0.249965[/C][C]0.124983[/C][/ROW]
[ROW][C]189[/C][C]0.858903[/C][C]0.282194[/C][C]0.141097[/C][/ROW]
[ROW][C]190[/C][C]0.843276[/C][C]0.313448[/C][C]0.156724[/C][/ROW]
[ROW][C]191[/C][C]0.842387[/C][C]0.315225[/C][C]0.157613[/C][/ROW]
[ROW][C]192[/C][C]0.827959[/C][C]0.344081[/C][C]0.172041[/C][/ROW]
[ROW][C]193[/C][C]0.837566[/C][C]0.324868[/C][C]0.162434[/C][/ROW]
[ROW][C]194[/C][C]0.863287[/C][C]0.273427[/C][C]0.136713[/C][/ROW]
[ROW][C]195[/C][C]0.842321[/C][C]0.315359[/C][C]0.157679[/C][/ROW]
[ROW][C]196[/C][C]0.82209[/C][C]0.35582[/C][C]0.17791[/C][/ROW]
[ROW][C]197[/C][C]0.801834[/C][C]0.396333[/C][C]0.198166[/C][/ROW]
[ROW][C]198[/C][C]0.775785[/C][C]0.448429[/C][C]0.224215[/C][/ROW]
[ROW][C]199[/C][C]0.753321[/C][C]0.493358[/C][C]0.246679[/C][/ROW]
[ROW][C]200[/C][C]0.738512[/C][C]0.522975[/C][C]0.261488[/C][/ROW]
[ROW][C]201[/C][C]0.793868[/C][C]0.412264[/C][C]0.206132[/C][/ROW]
[ROW][C]202[/C][C]0.766141[/C][C]0.467719[/C][C]0.233859[/C][/ROW]
[ROW][C]203[/C][C]0.736373[/C][C]0.527254[/C][C]0.263627[/C][/ROW]
[ROW][C]204[/C][C]0.715484[/C][C]0.569032[/C][C]0.284516[/C][/ROW]
[ROW][C]205[/C][C]0.682434[/C][C]0.635133[/C][C]0.317566[/C][/ROW]
[ROW][C]206[/C][C]0.650092[/C][C]0.699816[/C][C]0.349908[/C][/ROW]
[ROW][C]207[/C][C]0.655785[/C][C]0.688429[/C][C]0.344215[/C][/ROW]
[ROW][C]208[/C][C]0.622108[/C][C]0.755785[/C][C]0.377892[/C][/ROW]
[ROW][C]209[/C][C]0.683403[/C][C]0.633195[/C][C]0.316597[/C][/ROW]
[ROW][C]210[/C][C]0.676494[/C][C]0.647011[/C][C]0.323506[/C][/ROW]
[ROW][C]211[/C][C]0.662738[/C][C]0.674525[/C][C]0.337262[/C][/ROW]
[ROW][C]212[/C][C]0.634951[/C][C]0.730098[/C][C]0.365049[/C][/ROW]
[ROW][C]213[/C][C]0.612072[/C][C]0.775856[/C][C]0.387928[/C][/ROW]
[ROW][C]214[/C][C]0.573569[/C][C]0.852862[/C][C]0.426431[/C][/ROW]
[ROW][C]215[/C][C]0.557067[/C][C]0.885866[/C][C]0.442933[/C][/ROW]
[ROW][C]216[/C][C]0.523195[/C][C]0.953609[/C][C]0.476805[/C][/ROW]
[ROW][C]217[/C][C]0.5003[/C][C]0.9994[/C][C]0.4997[/C][/ROW]
[ROW][C]218[/C][C]0.536824[/C][C]0.926353[/C][C]0.463176[/C][/ROW]
[ROW][C]219[/C][C]0.515037[/C][C]0.969926[/C][C]0.484963[/C][/ROW]
[ROW][C]220[/C][C]0.489067[/C][C]0.978133[/C][C]0.510933[/C][/ROW]
[ROW][C]221[/C][C]0.512993[/C][C]0.974013[/C][C]0.487007[/C][/ROW]
[ROW][C]222[/C][C]0.608856[/C][C]0.782289[/C][C]0.391144[/C][/ROW]
[ROW][C]223[/C][C]0.58066[/C][C]0.838679[/C][C]0.41934[/C][/ROW]
[ROW][C]224[/C][C]0.548478[/C][C]0.903044[/C][C]0.451522[/C][/ROW]
[ROW][C]225[/C][C]0.635176[/C][C]0.729648[/C][C]0.364824[/C][/ROW]
[ROW][C]226[/C][C]0.600304[/C][C]0.799393[/C][C]0.399696[/C][/ROW]
[ROW][C]227[/C][C]0.603046[/C][C]0.793908[/C][C]0.396954[/C][/ROW]
[ROW][C]228[/C][C]0.578328[/C][C]0.843344[/C][C]0.421672[/C][/ROW]
[ROW][C]229[/C][C]0.644148[/C][C]0.711705[/C][C]0.355852[/C][/ROW]
[ROW][C]230[/C][C]0.720354[/C][C]0.559293[/C][C]0.279646[/C][/ROW]
[ROW][C]231[/C][C]0.769185[/C][C]0.46163[/C][C]0.230815[/C][/ROW]
[ROW][C]232[/C][C]0.838211[/C][C]0.323577[/C][C]0.161789[/C][/ROW]
[ROW][C]233[/C][C]0.807211[/C][C]0.385579[/C][C]0.192789[/C][/ROW]
[ROW][C]234[/C][C]0.772209[/C][C]0.455583[/C][C]0.227791[/C][/ROW]
[ROW][C]235[/C][C]0.77503[/C][C]0.449939[/C][C]0.22497[/C][/ROW]
[ROW][C]236[/C][C]0.936118[/C][C]0.127764[/C][C]0.0638819[/C][/ROW]
[ROW][C]237[/C][C]0.923597[/C][C]0.152805[/C][C]0.0764026[/C][/ROW]
[ROW][C]238[/C][C]0.903546[/C][C]0.192909[/C][C]0.0964545[/C][/ROW]
[ROW][C]239[/C][C]0.887599[/C][C]0.224802[/C][C]0.112401[/C][/ROW]
[ROW][C]240[/C][C]0.862465[/C][C]0.27507[/C][C]0.137535[/C][/ROW]
[ROW][C]241[/C][C]0.831479[/C][C]0.337042[/C][C]0.168521[/C][/ROW]
[ROW][C]242[/C][C]0.811982[/C][C]0.376035[/C][C]0.188018[/C][/ROW]
[ROW][C]243[/C][C]0.781066[/C][C]0.437869[/C][C]0.218934[/C][/ROW]
[ROW][C]244[/C][C]0.884017[/C][C]0.231967[/C][C]0.115983[/C][/ROW]
[ROW][C]245[/C][C]0.866608[/C][C]0.266784[/C][C]0.133392[/C][/ROW]
[ROW][C]246[/C][C]0.835622[/C][C]0.328757[/C][C]0.164378[/C][/ROW]
[ROW][C]247[/C][C]0.867891[/C][C]0.264217[/C][C]0.132109[/C][/ROW]
[ROW][C]248[/C][C]0.840082[/C][C]0.319837[/C][C]0.159918[/C][/ROW]
[ROW][C]249[/C][C]0.830426[/C][C]0.339147[/C][C]0.169574[/C][/ROW]
[ROW][C]250[/C][C]0.789686[/C][C]0.420628[/C][C]0.210314[/C][/ROW]
[ROW][C]251[/C][C]0.754219[/C][C]0.491562[/C][C]0.245781[/C][/ROW]
[ROW][C]252[/C][C]0.710695[/C][C]0.578611[/C][C]0.289305[/C][/ROW]
[ROW][C]253[/C][C]0.663135[/C][C]0.673731[/C][C]0.336865[/C][/ROW]
[ROW][C]254[/C][C]0.626967[/C][C]0.746066[/C][C]0.373033[/C][/ROW]
[ROW][C]255[/C][C]0.564566[/C][C]0.870869[/C][C]0.435434[/C][/ROW]
[ROW][C]256[/C][C]0.563667[/C][C]0.872667[/C][C]0.436333[/C][/ROW]
[ROW][C]257[/C][C]0.651039[/C][C]0.697921[/C][C]0.348961[/C][/ROW]
[ROW][C]258[/C][C]0.773831[/C][C]0.452337[/C][C]0.226169[/C][/ROW]
[ROW][C]259[/C][C]0.720459[/C][C]0.559082[/C][C]0.279541[/C][/ROW]
[ROW][C]260[/C][C]0.852523[/C][C]0.294955[/C][C]0.147477[/C][/ROW]
[ROW][C]261[/C][C]0.850117[/C][C]0.299766[/C][C]0.149883[/C][/ROW]
[ROW][C]262[/C][C]0.820055[/C][C]0.35989[/C][C]0.179945[/C][/ROW]
[ROW][C]263[/C][C]0.90065[/C][C]0.198701[/C][C]0.0993504[/C][/ROW]
[ROW][C]264[/C][C]0.858028[/C][C]0.283944[/C][C]0.141972[/C][/ROW]
[ROW][C]265[/C][C]0.836935[/C][C]0.32613[/C][C]0.163065[/C][/ROW]
[ROW][C]266[/C][C]0.769411[/C][C]0.461179[/C][C]0.230589[/C][/ROW]
[ROW][C]267[/C][C]0.6878[/C][C]0.624399[/C][C]0.3122[/C][/ROW]
[ROW][C]268[/C][C]0.592648[/C][C]0.814703[/C][C]0.407352[/C][/ROW]
[ROW][C]269[/C][C]0.546085[/C][C]0.90783[/C][C]0.453915[/C][/ROW]
[ROW][C]270[/C][C]0.544043[/C][C]0.911913[/C][C]0.455957[/C][/ROW]
[ROW][C]271[/C][C]0.416664[/C][C]0.833327[/C][C]0.583336[/C][/ROW]
[ROW][C]272[/C][C]0.321577[/C][C]0.643154[/C][C]0.678423[/C][/ROW]
[ROW][C]273[/C][C]0.197397[/C][C]0.394794[/C][C]0.802603[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&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
50.5981980.8036040.401802
60.4730990.9461980.526901
70.5291960.9416080.470804
80.444520.8890390.55548
90.3331630.6663250.666837
100.2530680.5061360.746932
110.1839160.3678320.816084
120.2993420.5986830.700658
130.2255570.4511140.774443
140.1689350.337870.831065
150.2280530.4561070.771947
160.1805840.3611680.819416
170.1430840.2861670.856916
180.1183350.2366710.881665
190.08825270.1765050.911747
200.06288530.1257710.937115
210.07059890.1411980.929401
220.08744240.1748850.912558
230.06410240.1282050.935898
240.06819760.1363950.931802
250.05087090.1017420.949129
260.03641570.07283140.963584
270.06900940.1380190.930991
280.06172170.1234430.938278
290.04877230.09754470.951228
300.03632170.07264350.963678
310.03632810.07265610.963672
320.02608570.05217150.973914
330.0222950.044590.977705
340.01730490.03460990.982695
350.01222150.02444290.987779
360.008928670.01785730.991071
370.0062840.0125680.993716
380.004910370.009820750.99509
390.003882910.007765820.996117
400.002721420.005442840.997279
410.006112080.01222420.993888
420.004241640.008483280.995758
430.003194430.006388850.996806
440.002195770.004391550.997804
450.001583440.003166880.998417
460.001060780.002121550.998939
470.0006922260.001384450.999308
480.0006736110.001347220.999326
490.0005032550.001006510.999497
500.0003891830.0007783670.999611
510.0002802770.0005605540.99972
520.0006398690.001279740.99936
530.0004330130.0008660250.999567
540.0003021580.0006043150.999698
550.0002394290.0004788580.999761
560.0001644630.0003289270.999836
570.0004789560.0009579120.999521
580.0006018490.00120370.999398
590.0007995280.001599060.9992
600.0007151050.001430210.999285
610.000622970.001245940.999377
620.000464140.000928280.999536
630.0005644640.001128930.999436
640.001218920.002437850.998781
650.001131890.002263780.998868
660.00105390.00210780.998946
670.0007634210.001526840.999237
680.00060330.00120660.999397
690.0008138510.00162770.999186
700.0006216870.001243370.999378
710.0004560910.0009121830.999544
720.0003215280.0006430570.999678
730.0003144250.0006288510.999686
740.0003658370.0007316740.999634
750.0002850840.0005701680.999715
760.0002203190.0004406370.99978
770.0001569170.0003138350.999843
780.0001344280.0002688560.999866
790.0001107590.0002215190.999889
800.0001765960.0003531930.999823
810.0001306640.0002613280.999869
820.000101930.0002038610.999898
837.33458e-050.0001466920.999927
840.0006058510.00121170.999394
850.000478450.0009568990.999522
860.0003556960.0007113920.999644
870.0002657910.0005315820.999734
880.0001946470.0003892930.999805
890.0002054530.0004109050.999795
900.0001800990.0003601980.99982
910.0001453830.0002907660.999855
920.0005012370.001002470.999499
930.0004269540.0008539090.999573
940.0004501020.0009002040.99955
950.0007102210.001420440.99929
960.0006933430.001386690.999307
970.00124390.002487810.998756
980.000988320.001976640.999012
990.0009515940.001903190.999048
1000.001276540.002553070.998723
1010.001054130.002108260.998946
1020.0009138670.001827730.999086
1030.001107780.002215560.998892
1040.001049370.002098750.998951
1050.001137340.002274690.998863
1060.001456110.002912220.998544
1070.001353230.002706460.998647
1080.006021740.01204350.993978
1090.01297350.0259470.987027
1100.01305940.02611880.986941
1110.01141970.02283940.98858
1120.01006040.02012080.98994
1130.04382710.08765410.956173
1140.04010780.08021560.959892
1150.08509010.170180.91491
1160.1447990.2895990.855201
1170.1771060.3542110.822894
1180.1638730.3277460.836127
1190.2171460.4342920.782854
1200.3553810.7107610.644619
1210.3857710.7715420.614229
1220.3668340.7336690.633166
1230.4806160.9612320.519384
1240.4757010.9514010.524299
1250.4682680.9365370.531732
1260.4454770.8909540.554523
1270.4739450.9478910.526055
1280.4536450.907290.546355
1290.5752910.8494180.424709
1300.5574710.8850580.442529
1310.544050.91190.45595
1320.5634090.8731820.436591
1330.5518720.8962570.448128
1340.5403870.9192260.459613
1350.5149360.9701270.485064
1360.4902220.9804440.509778
1370.5382880.9234240.461712
1380.5924610.8150780.407539
1390.6724330.6551330.327567
1400.6797660.6404680.320234
1410.6630140.6739720.336986
1420.7106420.5787160.289358
1430.7014780.5970450.298522
1440.7380690.5238620.261931
1450.7446040.5107920.255396
1460.7809840.4380310.219016
1470.7603760.4792490.239624
1480.7415490.5169010.258451
1490.7249480.5501050.275052
1500.7692810.4614380.230719
1510.771280.457440.22872
1520.768820.462360.23118
1530.8088660.3822690.191134
1540.8175420.3649170.182458
1550.8011680.3976650.198832
1560.7801620.4396760.219838
1570.8335090.3329820.166491
1580.8251260.3497480.174874
1590.8099580.3800840.190042
1600.7931790.4136430.206821
1610.8337950.3324110.166205
1620.8294010.3411980.170599
1630.8387640.3224730.161236
1640.8353680.3292640.164632
1650.8909120.2181770.109088
1660.88740.22520.1126
1670.9112790.1774410.0887206
1680.901230.1975390.0987697
1690.890320.2193590.10968
1700.8826820.2346360.117318
1710.8761740.2476510.123826
1720.8946430.2107140.105357
1730.8807580.2384840.119242
1740.8709740.2580510.129026
1750.8600750.2798490.139925
1760.8814670.2370650.118533
1770.8641110.2717780.135889
1780.9012960.1974080.0987039
1790.8914140.2171730.108586
1800.9254710.1490570.0745286
1810.9126010.1747980.0873991
1820.8986030.2027930.101397
1830.9190780.1618440.080922
1840.9088230.1823540.0911769
1850.8950690.2098610.104931
1860.8885350.2229310.111465
1870.8920190.2159620.107981
1880.8750170.2499650.124983
1890.8589030.2821940.141097
1900.8432760.3134480.156724
1910.8423870.3152250.157613
1920.8279590.3440810.172041
1930.8375660.3248680.162434
1940.8632870.2734270.136713
1950.8423210.3153590.157679
1960.822090.355820.17791
1970.8018340.3963330.198166
1980.7757850.4484290.224215
1990.7533210.4933580.246679
2000.7385120.5229750.261488
2010.7938680.4122640.206132
2020.7661410.4677190.233859
2030.7363730.5272540.263627
2040.7154840.5690320.284516
2050.6824340.6351330.317566
2060.6500920.6998160.349908
2070.6557850.6884290.344215
2080.6221080.7557850.377892
2090.6834030.6331950.316597
2100.6764940.6470110.323506
2110.6627380.6745250.337262
2120.6349510.7300980.365049
2130.6120720.7758560.387928
2140.5735690.8528620.426431
2150.5570670.8858660.442933
2160.5231950.9536090.476805
2170.50030.99940.4997
2180.5368240.9263530.463176
2190.5150370.9699260.484963
2200.4890670.9781330.510933
2210.5129930.9740130.487007
2220.6088560.7822890.391144
2230.580660.8386790.41934
2240.5484780.9030440.451522
2250.6351760.7296480.364824
2260.6003040.7993930.399696
2270.6030460.7939080.396954
2280.5783280.8433440.421672
2290.6441480.7117050.355852
2300.7203540.5592930.279646
2310.7691850.461630.230815
2320.8382110.3235770.161789
2330.8072110.3855790.192789
2340.7722090.4555830.227791
2350.775030.4499390.22497
2360.9361180.1277640.0638819
2370.9235970.1528050.0764026
2380.9035460.1929090.0964545
2390.8875990.2248020.112401
2400.8624650.275070.137535
2410.8314790.3370420.168521
2420.8119820.3760350.188018
2430.7810660.4378690.218934
2440.8840170.2319670.115983
2450.8666080.2667840.133392
2460.8356220.3287570.164378
2470.8678910.2642170.132109
2480.8400820.3198370.159918
2490.8304260.3391470.169574
2500.7896860.4206280.210314
2510.7542190.4915620.245781
2520.7106950.5786110.289305
2530.6631350.6737310.336865
2540.6269670.7460660.373033
2550.5645660.8708690.435434
2560.5636670.8726670.436333
2570.6510390.6979210.348961
2580.7738310.4523370.226169
2590.7204590.5590820.279541
2600.8525230.2949550.147477
2610.8501170.2997660.149883
2620.8200550.359890.179945
2630.900650.1987010.0993504
2640.8580280.2839440.141972
2650.8369350.326130.163065
2660.7694110.4611790.230589
2670.68780.6243990.3122
2680.5926480.8147030.407352
2690.5460850.907830.453915
2700.5440430.9119130.455957
2710.4166640.8333270.583336
2720.3215770.6431540.678423
2730.1973970.3947940.802603






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level690.256506NOK
5% type I error level800.297398NOK
10% type I error level870.32342NOK

\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 & 69 & 0.256506 & NOK \tabularnewline
5% type I error level & 80 & 0.297398 & NOK \tabularnewline
10% type I error level & 87 & 0.32342 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264970&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]69[/C][C]0.256506[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]80[/C][C]0.297398[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]87[/C][C]0.32342[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264970&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264970&T=6

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Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level690.256506NOK
5% type I error level800.297398NOK
10% type I error level870.32342NOK


Figures (Output of Computation)

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Input Parameters & R Code

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