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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 computationTue, 09 Dec 2014 19:15:48 +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/09/t1418152566u951m16wwcnev6m.htm/, Retrieved Thu, 16 May 2024 14:47:59 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264822, Retrieved Thu, 16 May 2024 14:47:59 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-09 19:15:48] [61a57b1a717662ce9f6e819e563a5fa9] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 13 12
12.8 14 11
7.4 16 13
6.7 14 11
12.6 13 10
14.8 15 7
13.3 13 10
11.1 20 15
8.2 17 12
11.4 15 12
6.4 16 10
12 17 14
6.3 11 6
11.3 16 12
11.9 16 14
9.3 15 11
10 14 12
13.8 16 13
10.8 17 11
11.7 15 7
10.9 14 11
16.1 14 7
9.9 15 12
11.5 17 13
8.3 14 9
11.7 16 11
9 15 12
10.8 16 12
10.4 8 5
12.7 17 13
11.8 10 6
13 16 6
10.8 16 12
12.3 16 11
11.3 8 6
11.6 14 11
10.9 16 12
12.1 19 13
13.3 19 14
10.1 14 12
14.3 13 14
9.3 15 11
12.5 11 10
7.6 9 7
9.2 12 7
14.5 13 10
12.3 17 12
12.6 7 5
13 15 10
12.6 12 12
13.2 15 11
7.7 16 12
10.5 14 11
10.9 16 12
4.3 13 10
10.3 16 9
11.4 10 7
5.6 12 9
8.8 14 10
9 16 12
9.6 18 14
6.4 12 9
11.6 15 12
4.35 16 9
12.7 16 11
18.1 16 12
17.85 16 12
16.6 12 7
12.6 15 12
17.1 14 12
19.1 15 12
16.1 16 10
13.35 13 15
18.4 10 10
14.7 17 15
10.6 15 10
12.6 18 15
16.2 16 9
13.6 20 15
18.9 16 12
14.1 17 13
14.5 16 12
16.15 15 12
14.75 13 8
14.8 16 9
12.45 16 15
12.65 16 12
17.35 17 12
8.6 20 15
18.4 14 11
16.1 17 12
11.6 6 6
17.75 16 14
15.25 15 12
17.65 16 12
16.35 16 12
17.65 14 11
13.6 16 12
14.35 16 12
14.75 16 12
18.25 14 12
9.9 14 8
16 16 8
18.25 16 12
16.85 15 12
14.6 16 11
13.85 16 10
18.95 18 11
15.6 15 12
14.85 16 13
11.75 16 12
18.45 16 12
15.9 17 10
17.1 14 10
16.1 18 11
19.9 9 8
10.95 15 12
18.45 14 9
15.1 15 12
15 13 9
11.35 16 11
15.95 20 15
18.1 14 8
14.6 12 8
15.4 15 11
15.4 15 11
17.6 15 11
13.35 16 13
19.1 11 7
15.35 16 12
7.6 7 8
13.4 11 8
13.9 9 4
19.1 15 11
15.25 16 10
12.9 14 7
16.1 15 12
17.35 13 11
13.15 13 9
12.15 12 10
12.6 16 8
10.35 14 8
15.4 16 11
9.6 14 12
18.2 15 10
13.6 10 10
14.85 16 12
14.75 14 8
14.1 16 11
14.9 12 8
16.25 16 10
19.25 16 14
13.6 15 9
13.6 14 9
15.65 16 10
12.75 11 13
14.6 15 12
9.85 18 13
12.65 13 8
19.2 7 3
16.6 7 8
11.2 17 12
15.25 18 11
11.9 15 9
13.2 8 12
16.35 13 12
12.4 13 12
15.85 15 10
18.15 18 13
11.15 16 9
15.65 14 12
17.75 15 11
7.65 19 14
12.35 16 11
15.6 12 9
19.3 16 12
15.2 11 8
17.1 16 15
15.6 15 12
18.4 19 14
19.05 15 12
18.55 14 9
19.1 14 9
13.1 17 13
12.85 16 13
9.5 20 15
4.5 16 11
11.85 9 7
13.6 13 10
11.7 15 11
12.4 19 14
13.35 16 14
11.4 17 13
14.9 16 12
19.9 9 8
11.2 11 13
14.6 14 9
17.6 19 12
14.05 13 13
16.1 14 11
13.35 15 11
11.85 15 13
11.95 14 12
14.75 16 12
15.15 17 10
13.2 12 9
16.85 15 10
7.85 17 13
7.7 15 13
12.6 10 9
7.85 16 11
10.95 15 12
12.35 11 8
9.95 16 12
14.9 16 12
16.65 16 12
13.4 14 9
13.95 14 12
15.7 16 12
16.85 16 11
10.95 18 12
15.35 14 6
12.2 20 7
15.1 15 10
17.75 16 12
15.2 16 10
14.6 16 12
16.65 12 9
8.1 8 3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time7 seconds
R Server'George Udny Yule' @ yule.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 7 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&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]7 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&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 time7 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 13.0762 + 0.0218428CONFSTATTOT[t] + 0.00911564CONFSOFTTOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  13.0762 +  0.0218428CONFSTATTOT[t] +  0.00911564CONFSOFTTOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  13.0762 +  0.0218428CONFSTATTOT[t] +  0.00911564CONFSOFTTOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&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] = + 13.0762 + 0.0218428CONFSTATTOT[t] + 0.00911564CONFSOFTTOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.07621.2801710.212.20286e-201.10143e-20
CONFSTATTOT0.02184280.1121570.19480.8457620.422881
CONFSOFTTOT0.009115640.1271870.071670.9429270.471463

\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) & 13.0762 & 1.28017 & 10.21 & 2.20286e-20 & 1.10143e-20 \tabularnewline
CONFSTATTOT & 0.0218428 & 0.112157 & 0.1948 & 0.845762 & 0.422881 \tabularnewline
CONFSOFTTOT & 0.00911564 & 0.127187 & 0.07167 & 0.942927 & 0.471463 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&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]13.0762[/C][C]1.28017[/C][C]10.21[/C][C]2.20286e-20[/C][C]1.10143e-20[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]0.0218428[/C][C]0.112157[/C][C]0.1948[/C][C]0.845762[/C][C]0.422881[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]0.00911564[/C][C]0.127187[/C][C]0.07167[/C][C]0.942927[/C][C]0.471463[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&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)13.07621.2801710.212.20286e-201.10143e-20
CONFSTATTOT0.02184280.1121570.19480.8457620.422881
CONFSOFTTOT0.009115640.1271870.071670.9429270.471463






Multiple Linear Regression - Regression Statistics
Multiple R0.0220831
R-squared0.000487663
Adjusted R-squared-0.00835758
F-TEST (value)0.0551328
F-TEST (DF numerator)2
F-TEST (DF denominator)226
p-value0.946372
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.33918
Sum Squared Residuals2519.93

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0220831 \tabularnewline
R-squared & 0.000487663 \tabularnewline
Adjusted R-squared & -0.00835758 \tabularnewline
F-TEST (value) & 0.0551328 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 226 \tabularnewline
p-value & 0.946372 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.33918 \tabularnewline
Sum Squared Residuals & 2519.93 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0220831[/C][/ROW]
[ROW][C]R-squared[/C][C]0.000487663[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00835758[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.0551328[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]226[/C][/ROW]
[ROW][C]p-value[/C][C]0.946372[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.33918[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2519.93[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&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 R0.0220831
R-squared0.000487663
Adjusted R-squared-0.00835758
F-TEST (value)0.0551328
F-TEST (DF numerator)2
F-TEST (DF denominator)226
p-value0.946372
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.33918
Sum Squared Residuals2519.93






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.4696-0.569592
212.813.4823-0.682319
37.413.5442-6.14424
46.713.4823-6.78232
512.613.4514-0.851361
614.813.46771.3323
713.313.4514-0.151361
811.113.6498-2.54984
98.213.557-5.35696
1011.413.5133-2.11328
116.413.5169-7.11689
121213.5752-1.57519
136.313.3712-7.07121
1411.313.5351-2.23512
1511.913.5534-1.65335
169.313.5042-4.20416
171013.4914-3.49143
1813.813.54420.255764
1910.813.5478-2.74785
2011.713.4677-1.7677
2110.913.4823-2.58232
2216.113.44592.65414
239.913.5133-3.61328
2411.513.5661-2.06608
258.313.4641-5.16409
2611.713.526-1.826
27913.5133-4.51328
2810.813.5351-2.73512
2910.413.2966-2.89657
3012.713.5661-0.866079
3111.813.3494-1.54937
321313.4804-0.480427
3310.813.5351-2.73512
3412.313.526-1.226
3511.313.3057-2.00568
3611.613.4823-1.88232
3710.913.5351-2.63512
3812.113.6098-1.50976
3913.313.6189-0.31888
4010.113.4914-3.39143
4114.313.48780.812177
429.313.5042-4.20416
4312.513.4077-0.907675
447.613.3366-5.73664
459.213.4022-4.20217
4614.513.45141.04864
4712.313.557-1.25696
4812.613.2747-0.674726
491313.495-0.495046
5012.613.4477-0.847749
5113.213.5042-0.304162
527.713.5351-5.83512
5310.513.4823-2.98232
5410.913.5351-2.63512
554.313.4514-9.15136
5610.313.5078-3.20777
5711.413.3585-1.95849
585.613.4204-7.8204
598.813.4732-4.6732
60913.5351-4.53512
619.613.597-3.99704
626.413.4204-7.0204
6311.613.5133-1.91328
644.3513.5078-9.15777
6512.713.526-0.826005
6618.113.53514.56488
6717.8513.53514.31488
6816.613.40223.19783
6912.613.5133-0.913278
7017.113.49143.60857
7119.113.51335.58672
7216.113.51692.58311
7313.3513.4969-0.146939
7418.413.38585.01417
7514.713.58431.11569
7610.613.495-2.89505
7712.613.6062-1.00615
7816.213.50782.69223
7913.613.6498-0.0498386
8018.913.53515.36488
8114.113.56610.533921
8214.513.53510.96488
8316.1513.51332.63672
8414.7513.43311.31687
8514.813.50781.29223
8612.4513.5625-1.11247
8712.6513.5351-0.88512
8817.3513.5573.79304
898.613.6498-5.04984
9018.413.48234.91768
9116.113.5572.54304
9211.613.262-1.662
9317.7513.55344.19665
9415.2513.51331.73672
9517.6513.53514.11488
9616.3513.53512.81488
9717.6513.48234.16768
9813.613.53510.0648795
9914.3513.53510.81488
10014.7513.53511.21488
10118.2513.49144.75857
1029.913.455-3.55497
1031613.49872.50134
10418.2513.53514.71488
10516.8513.51333.33672
10614.613.5261.074
10713.8513.51690.333111
10818.9513.56975.38031
10915.613.51332.08672
11014.8513.54421.30576
11111.7513.5351-1.78512
11218.4513.53514.91488
11315.913.53872.36127
11417.113.47323.6268
11516.113.56972.53031
11619.913.34586.55424
11710.9513.5133-2.56328
11818.4513.46414.98591
11915.113.51331.58672
1201513.44221.55775
12111.3513.526-2.176
12215.9513.64982.30016
12318.113.4554.64503
12414.613.41131.18871
12515.413.50421.89584
12615.413.50421.89584
12717.613.50424.09584
12813.3513.5442-0.194236
12919.113.38035.71967
13015.3513.53511.81488
1317.613.3021-5.70207
13213.413.38940.0105561
13313.913.30930.590704
13419.113.50425.59584
13515.2513.51691.73311
13612.913.4459-0.545857
13716.113.51332.58672
13817.3513.46053.88952
13913.1513.4422-0.292245
14012.1513.4295-1.27952
14112.613.4987-0.898658
14210.3513.455-3.10497
14315.413.5261.874
1449.613.4914-3.89143
14518.213.4954.70495
14613.613.38580.214168
14714.8513.53511.31488
14814.7513.4551.29503
14914.113.5260.573995
15014.913.41131.48871
15116.2513.51692.73311
15219.2513.55345.69665
15313.613.48590.114069
15413.613.46410.135912
15515.6513.51692.13311
15612.7513.435-0.685022
15714.613.51331.08672
1589.8513.5879-3.73792
15912.6513.4331-0.78313
16019.213.25655.94351
16116.613.30213.29793
16211.213.557-2.35696
16315.2513.56971.68031
16411.913.4859-1.58593
16513.213.3604-0.160378
16616.3513.46962.88041
16712.413.4696-1.06959
16815.8513.4952.35495
16918.1513.58794.56208
17011.1513.5078-2.35777
17115.6513.49142.15857
17217.7513.50424.24584
1737.6513.6189-5.96888
17412.3513.526-1.176
17515.613.42042.1796
17619.313.53515.76488
17715.213.38941.81056
17817.113.56253.53753
17915.613.51332.08672
18018.413.61894.78112
18119.0513.51335.53672
18218.5513.46415.08591
18319.113.46415.63591
18413.113.5661-0.466079
18512.8513.5442-0.694236
1869.513.6498-4.14984
1874.513.526-9.026
18811.8513.3366-1.48664
18913.613.45140.148639
19011.713.5042-1.80416
19112.413.6189-1.21888
19213.3513.5534-0.203352
19311.413.5661-2.16608
19414.913.53511.36488
19519.913.34586.55424
19611.213.435-2.23502
19714.613.46411.13591
19817.613.60063.99935
19914.0513.47870.571292
20016.113.48232.61768
20113.3513.5042-0.154162
20211.8513.5224-1.67239
20311.9513.4914-1.54143
20414.7513.53511.21488
20515.1513.53871.61127
20613.213.4204-0.220402
20716.8513.4953.35495
2087.8513.5661-5.71608
2097.713.5224-5.82239
21012.613.3767-0.776717
2117.8513.526-5.676
21210.9513.5133-2.56328
21312.3513.3894-1.03944
2149.9513.5351-3.58512
21514.913.53511.36488
21616.6513.53513.11488
21713.413.4641-0.064088
21813.9513.49140.458565
21915.713.53512.16488
22016.8513.5263.324
22110.9513.5788-2.62881
22215.3513.43671.91326
22312.213.5769-1.37691
22415.113.4951.60495
22517.7513.53514.21488
22615.213.51691.68311
22714.613.53511.06488
22816.6513.42043.2296
2298.113.2783-5.17834

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.4696 & -0.569592 \tabularnewline
2 & 12.8 & 13.4823 & -0.682319 \tabularnewline
3 & 7.4 & 13.5442 & -6.14424 \tabularnewline
4 & 6.7 & 13.4823 & -6.78232 \tabularnewline
5 & 12.6 & 13.4514 & -0.851361 \tabularnewline
6 & 14.8 & 13.4677 & 1.3323 \tabularnewline
7 & 13.3 & 13.4514 & -0.151361 \tabularnewline
8 & 11.1 & 13.6498 & -2.54984 \tabularnewline
9 & 8.2 & 13.557 & -5.35696 \tabularnewline
10 & 11.4 & 13.5133 & -2.11328 \tabularnewline
11 & 6.4 & 13.5169 & -7.11689 \tabularnewline
12 & 12 & 13.5752 & -1.57519 \tabularnewline
13 & 6.3 & 13.3712 & -7.07121 \tabularnewline
14 & 11.3 & 13.5351 & -2.23512 \tabularnewline
15 & 11.9 & 13.5534 & -1.65335 \tabularnewline
16 & 9.3 & 13.5042 & -4.20416 \tabularnewline
17 & 10 & 13.4914 & -3.49143 \tabularnewline
18 & 13.8 & 13.5442 & 0.255764 \tabularnewline
19 & 10.8 & 13.5478 & -2.74785 \tabularnewline
20 & 11.7 & 13.4677 & -1.7677 \tabularnewline
21 & 10.9 & 13.4823 & -2.58232 \tabularnewline
22 & 16.1 & 13.4459 & 2.65414 \tabularnewline
23 & 9.9 & 13.5133 & -3.61328 \tabularnewline
24 & 11.5 & 13.5661 & -2.06608 \tabularnewline
25 & 8.3 & 13.4641 & -5.16409 \tabularnewline
26 & 11.7 & 13.526 & -1.826 \tabularnewline
27 & 9 & 13.5133 & -4.51328 \tabularnewline
28 & 10.8 & 13.5351 & -2.73512 \tabularnewline
29 & 10.4 & 13.2966 & -2.89657 \tabularnewline
30 & 12.7 & 13.5661 & -0.866079 \tabularnewline
31 & 11.8 & 13.3494 & -1.54937 \tabularnewline
32 & 13 & 13.4804 & -0.480427 \tabularnewline
33 & 10.8 & 13.5351 & -2.73512 \tabularnewline
34 & 12.3 & 13.526 & -1.226 \tabularnewline
35 & 11.3 & 13.3057 & -2.00568 \tabularnewline
36 & 11.6 & 13.4823 & -1.88232 \tabularnewline
37 & 10.9 & 13.5351 & -2.63512 \tabularnewline
38 & 12.1 & 13.6098 & -1.50976 \tabularnewline
39 & 13.3 & 13.6189 & -0.31888 \tabularnewline
40 & 10.1 & 13.4914 & -3.39143 \tabularnewline
41 & 14.3 & 13.4878 & 0.812177 \tabularnewline
42 & 9.3 & 13.5042 & -4.20416 \tabularnewline
43 & 12.5 & 13.4077 & -0.907675 \tabularnewline
44 & 7.6 & 13.3366 & -5.73664 \tabularnewline
45 & 9.2 & 13.4022 & -4.20217 \tabularnewline
46 & 14.5 & 13.4514 & 1.04864 \tabularnewline
47 & 12.3 & 13.557 & -1.25696 \tabularnewline
48 & 12.6 & 13.2747 & -0.674726 \tabularnewline
49 & 13 & 13.495 & -0.495046 \tabularnewline
50 & 12.6 & 13.4477 & -0.847749 \tabularnewline
51 & 13.2 & 13.5042 & -0.304162 \tabularnewline
52 & 7.7 & 13.5351 & -5.83512 \tabularnewline
53 & 10.5 & 13.4823 & -2.98232 \tabularnewline
54 & 10.9 & 13.5351 & -2.63512 \tabularnewline
55 & 4.3 & 13.4514 & -9.15136 \tabularnewline
56 & 10.3 & 13.5078 & -3.20777 \tabularnewline
57 & 11.4 & 13.3585 & -1.95849 \tabularnewline
58 & 5.6 & 13.4204 & -7.8204 \tabularnewline
59 & 8.8 & 13.4732 & -4.6732 \tabularnewline
60 & 9 & 13.5351 & -4.53512 \tabularnewline
61 & 9.6 & 13.597 & -3.99704 \tabularnewline
62 & 6.4 & 13.4204 & -7.0204 \tabularnewline
63 & 11.6 & 13.5133 & -1.91328 \tabularnewline
64 & 4.35 & 13.5078 & -9.15777 \tabularnewline
65 & 12.7 & 13.526 & -0.826005 \tabularnewline
66 & 18.1 & 13.5351 & 4.56488 \tabularnewline
67 & 17.85 & 13.5351 & 4.31488 \tabularnewline
68 & 16.6 & 13.4022 & 3.19783 \tabularnewline
69 & 12.6 & 13.5133 & -0.913278 \tabularnewline
70 & 17.1 & 13.4914 & 3.60857 \tabularnewline
71 & 19.1 & 13.5133 & 5.58672 \tabularnewline
72 & 16.1 & 13.5169 & 2.58311 \tabularnewline
73 & 13.35 & 13.4969 & -0.146939 \tabularnewline
74 & 18.4 & 13.3858 & 5.01417 \tabularnewline
75 & 14.7 & 13.5843 & 1.11569 \tabularnewline
76 & 10.6 & 13.495 & -2.89505 \tabularnewline
77 & 12.6 & 13.6062 & -1.00615 \tabularnewline
78 & 16.2 & 13.5078 & 2.69223 \tabularnewline
79 & 13.6 & 13.6498 & -0.0498386 \tabularnewline
80 & 18.9 & 13.5351 & 5.36488 \tabularnewline
81 & 14.1 & 13.5661 & 0.533921 \tabularnewline
82 & 14.5 & 13.5351 & 0.96488 \tabularnewline
83 & 16.15 & 13.5133 & 2.63672 \tabularnewline
84 & 14.75 & 13.4331 & 1.31687 \tabularnewline
85 & 14.8 & 13.5078 & 1.29223 \tabularnewline
86 & 12.45 & 13.5625 & -1.11247 \tabularnewline
87 & 12.65 & 13.5351 & -0.88512 \tabularnewline
88 & 17.35 & 13.557 & 3.79304 \tabularnewline
89 & 8.6 & 13.6498 & -5.04984 \tabularnewline
90 & 18.4 & 13.4823 & 4.91768 \tabularnewline
91 & 16.1 & 13.557 & 2.54304 \tabularnewline
92 & 11.6 & 13.262 & -1.662 \tabularnewline
93 & 17.75 & 13.5534 & 4.19665 \tabularnewline
94 & 15.25 & 13.5133 & 1.73672 \tabularnewline
95 & 17.65 & 13.5351 & 4.11488 \tabularnewline
96 & 16.35 & 13.5351 & 2.81488 \tabularnewline
97 & 17.65 & 13.4823 & 4.16768 \tabularnewline
98 & 13.6 & 13.5351 & 0.0648795 \tabularnewline
99 & 14.35 & 13.5351 & 0.81488 \tabularnewline
100 & 14.75 & 13.5351 & 1.21488 \tabularnewline
101 & 18.25 & 13.4914 & 4.75857 \tabularnewline
102 & 9.9 & 13.455 & -3.55497 \tabularnewline
103 & 16 & 13.4987 & 2.50134 \tabularnewline
104 & 18.25 & 13.5351 & 4.71488 \tabularnewline
105 & 16.85 & 13.5133 & 3.33672 \tabularnewline
106 & 14.6 & 13.526 & 1.074 \tabularnewline
107 & 13.85 & 13.5169 & 0.333111 \tabularnewline
108 & 18.95 & 13.5697 & 5.38031 \tabularnewline
109 & 15.6 & 13.5133 & 2.08672 \tabularnewline
110 & 14.85 & 13.5442 & 1.30576 \tabularnewline
111 & 11.75 & 13.5351 & -1.78512 \tabularnewline
112 & 18.45 & 13.5351 & 4.91488 \tabularnewline
113 & 15.9 & 13.5387 & 2.36127 \tabularnewline
114 & 17.1 & 13.4732 & 3.6268 \tabularnewline
115 & 16.1 & 13.5697 & 2.53031 \tabularnewline
116 & 19.9 & 13.3458 & 6.55424 \tabularnewline
117 & 10.95 & 13.5133 & -2.56328 \tabularnewline
118 & 18.45 & 13.4641 & 4.98591 \tabularnewline
119 & 15.1 & 13.5133 & 1.58672 \tabularnewline
120 & 15 & 13.4422 & 1.55775 \tabularnewline
121 & 11.35 & 13.526 & -2.176 \tabularnewline
122 & 15.95 & 13.6498 & 2.30016 \tabularnewline
123 & 18.1 & 13.455 & 4.64503 \tabularnewline
124 & 14.6 & 13.4113 & 1.18871 \tabularnewline
125 & 15.4 & 13.5042 & 1.89584 \tabularnewline
126 & 15.4 & 13.5042 & 1.89584 \tabularnewline
127 & 17.6 & 13.5042 & 4.09584 \tabularnewline
128 & 13.35 & 13.5442 & -0.194236 \tabularnewline
129 & 19.1 & 13.3803 & 5.71967 \tabularnewline
130 & 15.35 & 13.5351 & 1.81488 \tabularnewline
131 & 7.6 & 13.3021 & -5.70207 \tabularnewline
132 & 13.4 & 13.3894 & 0.0105561 \tabularnewline
133 & 13.9 & 13.3093 & 0.590704 \tabularnewline
134 & 19.1 & 13.5042 & 5.59584 \tabularnewline
135 & 15.25 & 13.5169 & 1.73311 \tabularnewline
136 & 12.9 & 13.4459 & -0.545857 \tabularnewline
137 & 16.1 & 13.5133 & 2.58672 \tabularnewline
138 & 17.35 & 13.4605 & 3.88952 \tabularnewline
139 & 13.15 & 13.4422 & -0.292245 \tabularnewline
140 & 12.15 & 13.4295 & -1.27952 \tabularnewline
141 & 12.6 & 13.4987 & -0.898658 \tabularnewline
142 & 10.35 & 13.455 & -3.10497 \tabularnewline
143 & 15.4 & 13.526 & 1.874 \tabularnewline
144 & 9.6 & 13.4914 & -3.89143 \tabularnewline
145 & 18.2 & 13.495 & 4.70495 \tabularnewline
146 & 13.6 & 13.3858 & 0.214168 \tabularnewline
147 & 14.85 & 13.5351 & 1.31488 \tabularnewline
148 & 14.75 & 13.455 & 1.29503 \tabularnewline
149 & 14.1 & 13.526 & 0.573995 \tabularnewline
150 & 14.9 & 13.4113 & 1.48871 \tabularnewline
151 & 16.25 & 13.5169 & 2.73311 \tabularnewline
152 & 19.25 & 13.5534 & 5.69665 \tabularnewline
153 & 13.6 & 13.4859 & 0.114069 \tabularnewline
154 & 13.6 & 13.4641 & 0.135912 \tabularnewline
155 & 15.65 & 13.5169 & 2.13311 \tabularnewline
156 & 12.75 & 13.435 & -0.685022 \tabularnewline
157 & 14.6 & 13.5133 & 1.08672 \tabularnewline
158 & 9.85 & 13.5879 & -3.73792 \tabularnewline
159 & 12.65 & 13.4331 & -0.78313 \tabularnewline
160 & 19.2 & 13.2565 & 5.94351 \tabularnewline
161 & 16.6 & 13.3021 & 3.29793 \tabularnewline
162 & 11.2 & 13.557 & -2.35696 \tabularnewline
163 & 15.25 & 13.5697 & 1.68031 \tabularnewline
164 & 11.9 & 13.4859 & -1.58593 \tabularnewline
165 & 13.2 & 13.3604 & -0.160378 \tabularnewline
166 & 16.35 & 13.4696 & 2.88041 \tabularnewline
167 & 12.4 & 13.4696 & -1.06959 \tabularnewline
168 & 15.85 & 13.495 & 2.35495 \tabularnewline
169 & 18.15 & 13.5879 & 4.56208 \tabularnewline
170 & 11.15 & 13.5078 & -2.35777 \tabularnewline
171 & 15.65 & 13.4914 & 2.15857 \tabularnewline
172 & 17.75 & 13.5042 & 4.24584 \tabularnewline
173 & 7.65 & 13.6189 & -5.96888 \tabularnewline
174 & 12.35 & 13.526 & -1.176 \tabularnewline
175 & 15.6 & 13.4204 & 2.1796 \tabularnewline
176 & 19.3 & 13.5351 & 5.76488 \tabularnewline
177 & 15.2 & 13.3894 & 1.81056 \tabularnewline
178 & 17.1 & 13.5625 & 3.53753 \tabularnewline
179 & 15.6 & 13.5133 & 2.08672 \tabularnewline
180 & 18.4 & 13.6189 & 4.78112 \tabularnewline
181 & 19.05 & 13.5133 & 5.53672 \tabularnewline
182 & 18.55 & 13.4641 & 5.08591 \tabularnewline
183 & 19.1 & 13.4641 & 5.63591 \tabularnewline
184 & 13.1 & 13.5661 & -0.466079 \tabularnewline
185 & 12.85 & 13.5442 & -0.694236 \tabularnewline
186 & 9.5 & 13.6498 & -4.14984 \tabularnewline
187 & 4.5 & 13.526 & -9.026 \tabularnewline
188 & 11.85 & 13.3366 & -1.48664 \tabularnewline
189 & 13.6 & 13.4514 & 0.148639 \tabularnewline
190 & 11.7 & 13.5042 & -1.80416 \tabularnewline
191 & 12.4 & 13.6189 & -1.21888 \tabularnewline
192 & 13.35 & 13.5534 & -0.203352 \tabularnewline
193 & 11.4 & 13.5661 & -2.16608 \tabularnewline
194 & 14.9 & 13.5351 & 1.36488 \tabularnewline
195 & 19.9 & 13.3458 & 6.55424 \tabularnewline
196 & 11.2 & 13.435 & -2.23502 \tabularnewline
197 & 14.6 & 13.4641 & 1.13591 \tabularnewline
198 & 17.6 & 13.6006 & 3.99935 \tabularnewline
199 & 14.05 & 13.4787 & 0.571292 \tabularnewline
200 & 16.1 & 13.4823 & 2.61768 \tabularnewline
201 & 13.35 & 13.5042 & -0.154162 \tabularnewline
202 & 11.85 & 13.5224 & -1.67239 \tabularnewline
203 & 11.95 & 13.4914 & -1.54143 \tabularnewline
204 & 14.75 & 13.5351 & 1.21488 \tabularnewline
205 & 15.15 & 13.5387 & 1.61127 \tabularnewline
206 & 13.2 & 13.4204 & -0.220402 \tabularnewline
207 & 16.85 & 13.495 & 3.35495 \tabularnewline
208 & 7.85 & 13.5661 & -5.71608 \tabularnewline
209 & 7.7 & 13.5224 & -5.82239 \tabularnewline
210 & 12.6 & 13.3767 & -0.776717 \tabularnewline
211 & 7.85 & 13.526 & -5.676 \tabularnewline
212 & 10.95 & 13.5133 & -2.56328 \tabularnewline
213 & 12.35 & 13.3894 & -1.03944 \tabularnewline
214 & 9.95 & 13.5351 & -3.58512 \tabularnewline
215 & 14.9 & 13.5351 & 1.36488 \tabularnewline
216 & 16.65 & 13.5351 & 3.11488 \tabularnewline
217 & 13.4 & 13.4641 & -0.064088 \tabularnewline
218 & 13.95 & 13.4914 & 0.458565 \tabularnewline
219 & 15.7 & 13.5351 & 2.16488 \tabularnewline
220 & 16.85 & 13.526 & 3.324 \tabularnewline
221 & 10.95 & 13.5788 & -2.62881 \tabularnewline
222 & 15.35 & 13.4367 & 1.91326 \tabularnewline
223 & 12.2 & 13.5769 & -1.37691 \tabularnewline
224 & 15.1 & 13.495 & 1.60495 \tabularnewline
225 & 17.75 & 13.5351 & 4.21488 \tabularnewline
226 & 15.2 & 13.5169 & 1.68311 \tabularnewline
227 & 14.6 & 13.5351 & 1.06488 \tabularnewline
228 & 16.65 & 13.4204 & 3.2296 \tabularnewline
229 & 8.1 & 13.2783 & -5.17834 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&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]13.4696[/C][C]-0.569592[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]13.4823[/C][C]-0.682319[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.5442[/C][C]-6.14424[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]13.4823[/C][C]-6.78232[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]13.4514[/C][C]-0.851361[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.4677[/C][C]1.3323[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]13.4514[/C][C]-0.151361[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.6498[/C][C]-2.54984[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]13.557[/C][C]-5.35696[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.5133[/C][C]-2.11328[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]13.5169[/C][C]-7.11689[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.5752[/C][C]-1.57519[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]13.3712[/C][C]-7.07121[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]13.5351[/C][C]-2.23512[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]13.5534[/C][C]-1.65335[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]13.5042[/C][C]-4.20416[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]13.4914[/C][C]-3.49143[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.5442[/C][C]0.255764[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.5478[/C][C]-2.74785[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.4677[/C][C]-1.7677[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]13.4823[/C][C]-2.58232[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.4459[/C][C]2.65414[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]13.5133[/C][C]-3.61328[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]13.5661[/C][C]-2.06608[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]13.4641[/C][C]-5.16409[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.526[/C][C]-1.826[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]13.5133[/C][C]-4.51328[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]13.5351[/C][C]-2.73512[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]13.2966[/C][C]-2.89657[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]13.5661[/C][C]-0.866079[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]13.3494[/C][C]-1.54937[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.4804[/C][C]-0.480427[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]13.5351[/C][C]-2.73512[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]13.526[/C][C]-1.226[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.3057[/C][C]-2.00568[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]13.4823[/C][C]-1.88232[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.5351[/C][C]-2.63512[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]13.6098[/C][C]-1.50976[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.6189[/C][C]-0.31888[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.4914[/C][C]-3.39143[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]13.4878[/C][C]0.812177[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.5042[/C][C]-4.20416[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]13.4077[/C][C]-0.907675[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]13.3366[/C][C]-5.73664[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]13.4022[/C][C]-4.20217[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.4514[/C][C]1.04864[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.557[/C][C]-1.25696[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.2747[/C][C]-0.674726[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]13.495[/C][C]-0.495046[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]13.4477[/C][C]-0.847749[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]13.5042[/C][C]-0.304162[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]13.5351[/C][C]-5.83512[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]13.4823[/C][C]-2.98232[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]13.5351[/C][C]-2.63512[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]13.4514[/C][C]-9.15136[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]13.5078[/C][C]-3.20777[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]13.3585[/C][C]-1.95849[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]13.4204[/C][C]-7.8204[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]13.4732[/C][C]-4.6732[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]13.5351[/C][C]-4.53512[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]13.597[/C][C]-3.99704[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]13.4204[/C][C]-7.0204[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]13.5133[/C][C]-1.91328[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]13.5078[/C][C]-9.15777[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]13.526[/C][C]-0.826005[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]13.5351[/C][C]4.56488[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]13.5351[/C][C]4.31488[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]13.4022[/C][C]3.19783[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]13.5133[/C][C]-0.913278[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]13.4914[/C][C]3.60857[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]13.5133[/C][C]5.58672[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]13.5169[/C][C]2.58311[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]13.4969[/C][C]-0.146939[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]13.3858[/C][C]5.01417[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]13.5843[/C][C]1.11569[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]13.495[/C][C]-2.89505[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.6062[/C][C]-1.00615[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]13.5078[/C][C]2.69223[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]13.6498[/C][C]-0.0498386[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]13.5351[/C][C]5.36488[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]13.5661[/C][C]0.533921[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]13.5351[/C][C]0.96488[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]13.5133[/C][C]2.63672[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.4331[/C][C]1.31687[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]13.5078[/C][C]1.29223[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]13.5625[/C][C]-1.11247[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]13.5351[/C][C]-0.88512[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.557[/C][C]3.79304[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]13.6498[/C][C]-5.04984[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]13.4823[/C][C]4.91768[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]13.557[/C][C]2.54304[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]13.262[/C][C]-1.662[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]13.5534[/C][C]4.19665[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]13.5133[/C][C]1.73672[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]13.5351[/C][C]4.11488[/C][/ROW]
[ROW][C]96[/C][C]16.35[/C][C]13.5351[/C][C]2.81488[/C][/ROW]
[ROW][C]97[/C][C]17.65[/C][C]13.4823[/C][C]4.16768[/C][/ROW]
[ROW][C]98[/C][C]13.6[/C][C]13.5351[/C][C]0.0648795[/C][/ROW]
[ROW][C]99[/C][C]14.35[/C][C]13.5351[/C][C]0.81488[/C][/ROW]
[ROW][C]100[/C][C]14.75[/C][C]13.5351[/C][C]1.21488[/C][/ROW]
[ROW][C]101[/C][C]18.25[/C][C]13.4914[/C][C]4.75857[/C][/ROW]
[ROW][C]102[/C][C]9.9[/C][C]13.455[/C][C]-3.55497[/C][/ROW]
[ROW][C]103[/C][C]16[/C][C]13.4987[/C][C]2.50134[/C][/ROW]
[ROW][C]104[/C][C]18.25[/C][C]13.5351[/C][C]4.71488[/C][/ROW]
[ROW][C]105[/C][C]16.85[/C][C]13.5133[/C][C]3.33672[/C][/ROW]
[ROW][C]106[/C][C]14.6[/C][C]13.526[/C][C]1.074[/C][/ROW]
[ROW][C]107[/C][C]13.85[/C][C]13.5169[/C][C]0.333111[/C][/ROW]
[ROW][C]108[/C][C]18.95[/C][C]13.5697[/C][C]5.38031[/C][/ROW]
[ROW][C]109[/C][C]15.6[/C][C]13.5133[/C][C]2.08672[/C][/ROW]
[ROW][C]110[/C][C]14.85[/C][C]13.5442[/C][C]1.30576[/C][/ROW]
[ROW][C]111[/C][C]11.75[/C][C]13.5351[/C][C]-1.78512[/C][/ROW]
[ROW][C]112[/C][C]18.45[/C][C]13.5351[/C][C]4.91488[/C][/ROW]
[ROW][C]113[/C][C]15.9[/C][C]13.5387[/C][C]2.36127[/C][/ROW]
[ROW][C]114[/C][C]17.1[/C][C]13.4732[/C][C]3.6268[/C][/ROW]
[ROW][C]115[/C][C]16.1[/C][C]13.5697[/C][C]2.53031[/C][/ROW]
[ROW][C]116[/C][C]19.9[/C][C]13.3458[/C][C]6.55424[/C][/ROW]
[ROW][C]117[/C][C]10.95[/C][C]13.5133[/C][C]-2.56328[/C][/ROW]
[ROW][C]118[/C][C]18.45[/C][C]13.4641[/C][C]4.98591[/C][/ROW]
[ROW][C]119[/C][C]15.1[/C][C]13.5133[/C][C]1.58672[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]13.4422[/C][C]1.55775[/C][/ROW]
[ROW][C]121[/C][C]11.35[/C][C]13.526[/C][C]-2.176[/C][/ROW]
[ROW][C]122[/C][C]15.95[/C][C]13.6498[/C][C]2.30016[/C][/ROW]
[ROW][C]123[/C][C]18.1[/C][C]13.455[/C][C]4.64503[/C][/ROW]
[ROW][C]124[/C][C]14.6[/C][C]13.4113[/C][C]1.18871[/C][/ROW]
[ROW][C]125[/C][C]15.4[/C][C]13.5042[/C][C]1.89584[/C][/ROW]
[ROW][C]126[/C][C]15.4[/C][C]13.5042[/C][C]1.89584[/C][/ROW]
[ROW][C]127[/C][C]17.6[/C][C]13.5042[/C][C]4.09584[/C][/ROW]
[ROW][C]128[/C][C]13.35[/C][C]13.5442[/C][C]-0.194236[/C][/ROW]
[ROW][C]129[/C][C]19.1[/C][C]13.3803[/C][C]5.71967[/C][/ROW]
[ROW][C]130[/C][C]15.35[/C][C]13.5351[/C][C]1.81488[/C][/ROW]
[ROW][C]131[/C][C]7.6[/C][C]13.3021[/C][C]-5.70207[/C][/ROW]
[ROW][C]132[/C][C]13.4[/C][C]13.3894[/C][C]0.0105561[/C][/ROW]
[ROW][C]133[/C][C]13.9[/C][C]13.3093[/C][C]0.590704[/C][/ROW]
[ROW][C]134[/C][C]19.1[/C][C]13.5042[/C][C]5.59584[/C][/ROW]
[ROW][C]135[/C][C]15.25[/C][C]13.5169[/C][C]1.73311[/C][/ROW]
[ROW][C]136[/C][C]12.9[/C][C]13.4459[/C][C]-0.545857[/C][/ROW]
[ROW][C]137[/C][C]16.1[/C][C]13.5133[/C][C]2.58672[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]13.4605[/C][C]3.88952[/C][/ROW]
[ROW][C]139[/C][C]13.15[/C][C]13.4422[/C][C]-0.292245[/C][/ROW]
[ROW][C]140[/C][C]12.15[/C][C]13.4295[/C][C]-1.27952[/C][/ROW]
[ROW][C]141[/C][C]12.6[/C][C]13.4987[/C][C]-0.898658[/C][/ROW]
[ROW][C]142[/C][C]10.35[/C][C]13.455[/C][C]-3.10497[/C][/ROW]
[ROW][C]143[/C][C]15.4[/C][C]13.526[/C][C]1.874[/C][/ROW]
[ROW][C]144[/C][C]9.6[/C][C]13.4914[/C][C]-3.89143[/C][/ROW]
[ROW][C]145[/C][C]18.2[/C][C]13.495[/C][C]4.70495[/C][/ROW]
[ROW][C]146[/C][C]13.6[/C][C]13.3858[/C][C]0.214168[/C][/ROW]
[ROW][C]147[/C][C]14.85[/C][C]13.5351[/C][C]1.31488[/C][/ROW]
[ROW][C]148[/C][C]14.75[/C][C]13.455[/C][C]1.29503[/C][/ROW]
[ROW][C]149[/C][C]14.1[/C][C]13.526[/C][C]0.573995[/C][/ROW]
[ROW][C]150[/C][C]14.9[/C][C]13.4113[/C][C]1.48871[/C][/ROW]
[ROW][C]151[/C][C]16.25[/C][C]13.5169[/C][C]2.73311[/C][/ROW]
[ROW][C]152[/C][C]19.25[/C][C]13.5534[/C][C]5.69665[/C][/ROW]
[ROW][C]153[/C][C]13.6[/C][C]13.4859[/C][C]0.114069[/C][/ROW]
[ROW][C]154[/C][C]13.6[/C][C]13.4641[/C][C]0.135912[/C][/ROW]
[ROW][C]155[/C][C]15.65[/C][C]13.5169[/C][C]2.13311[/C][/ROW]
[ROW][C]156[/C][C]12.75[/C][C]13.435[/C][C]-0.685022[/C][/ROW]
[ROW][C]157[/C][C]14.6[/C][C]13.5133[/C][C]1.08672[/C][/ROW]
[ROW][C]158[/C][C]9.85[/C][C]13.5879[/C][C]-3.73792[/C][/ROW]
[ROW][C]159[/C][C]12.65[/C][C]13.4331[/C][C]-0.78313[/C][/ROW]
[ROW][C]160[/C][C]19.2[/C][C]13.2565[/C][C]5.94351[/C][/ROW]
[ROW][C]161[/C][C]16.6[/C][C]13.3021[/C][C]3.29793[/C][/ROW]
[ROW][C]162[/C][C]11.2[/C][C]13.557[/C][C]-2.35696[/C][/ROW]
[ROW][C]163[/C][C]15.25[/C][C]13.5697[/C][C]1.68031[/C][/ROW]
[ROW][C]164[/C][C]11.9[/C][C]13.4859[/C][C]-1.58593[/C][/ROW]
[ROW][C]165[/C][C]13.2[/C][C]13.3604[/C][C]-0.160378[/C][/ROW]
[ROW][C]166[/C][C]16.35[/C][C]13.4696[/C][C]2.88041[/C][/ROW]
[ROW][C]167[/C][C]12.4[/C][C]13.4696[/C][C]-1.06959[/C][/ROW]
[ROW][C]168[/C][C]15.85[/C][C]13.495[/C][C]2.35495[/C][/ROW]
[ROW][C]169[/C][C]18.15[/C][C]13.5879[/C][C]4.56208[/C][/ROW]
[ROW][C]170[/C][C]11.15[/C][C]13.5078[/C][C]-2.35777[/C][/ROW]
[ROW][C]171[/C][C]15.65[/C][C]13.4914[/C][C]2.15857[/C][/ROW]
[ROW][C]172[/C][C]17.75[/C][C]13.5042[/C][C]4.24584[/C][/ROW]
[ROW][C]173[/C][C]7.65[/C][C]13.6189[/C][C]-5.96888[/C][/ROW]
[ROW][C]174[/C][C]12.35[/C][C]13.526[/C][C]-1.176[/C][/ROW]
[ROW][C]175[/C][C]15.6[/C][C]13.4204[/C][C]2.1796[/C][/ROW]
[ROW][C]176[/C][C]19.3[/C][C]13.5351[/C][C]5.76488[/C][/ROW]
[ROW][C]177[/C][C]15.2[/C][C]13.3894[/C][C]1.81056[/C][/ROW]
[ROW][C]178[/C][C]17.1[/C][C]13.5625[/C][C]3.53753[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]13.5133[/C][C]2.08672[/C][/ROW]
[ROW][C]180[/C][C]18.4[/C][C]13.6189[/C][C]4.78112[/C][/ROW]
[ROW][C]181[/C][C]19.05[/C][C]13.5133[/C][C]5.53672[/C][/ROW]
[ROW][C]182[/C][C]18.55[/C][C]13.4641[/C][C]5.08591[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.4641[/C][C]5.63591[/C][/ROW]
[ROW][C]184[/C][C]13.1[/C][C]13.5661[/C][C]-0.466079[/C][/ROW]
[ROW][C]185[/C][C]12.85[/C][C]13.5442[/C][C]-0.694236[/C][/ROW]
[ROW][C]186[/C][C]9.5[/C][C]13.6498[/C][C]-4.14984[/C][/ROW]
[ROW][C]187[/C][C]4.5[/C][C]13.526[/C][C]-9.026[/C][/ROW]
[ROW][C]188[/C][C]11.85[/C][C]13.3366[/C][C]-1.48664[/C][/ROW]
[ROW][C]189[/C][C]13.6[/C][C]13.4514[/C][C]0.148639[/C][/ROW]
[ROW][C]190[/C][C]11.7[/C][C]13.5042[/C][C]-1.80416[/C][/ROW]
[ROW][C]191[/C][C]12.4[/C][C]13.6189[/C][C]-1.21888[/C][/ROW]
[ROW][C]192[/C][C]13.35[/C][C]13.5534[/C][C]-0.203352[/C][/ROW]
[ROW][C]193[/C][C]11.4[/C][C]13.5661[/C][C]-2.16608[/C][/ROW]
[ROW][C]194[/C][C]14.9[/C][C]13.5351[/C][C]1.36488[/C][/ROW]
[ROW][C]195[/C][C]19.9[/C][C]13.3458[/C][C]6.55424[/C][/ROW]
[ROW][C]196[/C][C]11.2[/C][C]13.435[/C][C]-2.23502[/C][/ROW]
[ROW][C]197[/C][C]14.6[/C][C]13.4641[/C][C]1.13591[/C][/ROW]
[ROW][C]198[/C][C]17.6[/C][C]13.6006[/C][C]3.99935[/C][/ROW]
[ROW][C]199[/C][C]14.05[/C][C]13.4787[/C][C]0.571292[/C][/ROW]
[ROW][C]200[/C][C]16.1[/C][C]13.4823[/C][C]2.61768[/C][/ROW]
[ROW][C]201[/C][C]13.35[/C][C]13.5042[/C][C]-0.154162[/C][/ROW]
[ROW][C]202[/C][C]11.85[/C][C]13.5224[/C][C]-1.67239[/C][/ROW]
[ROW][C]203[/C][C]11.95[/C][C]13.4914[/C][C]-1.54143[/C][/ROW]
[ROW][C]204[/C][C]14.75[/C][C]13.5351[/C][C]1.21488[/C][/ROW]
[ROW][C]205[/C][C]15.15[/C][C]13.5387[/C][C]1.61127[/C][/ROW]
[ROW][C]206[/C][C]13.2[/C][C]13.4204[/C][C]-0.220402[/C][/ROW]
[ROW][C]207[/C][C]16.85[/C][C]13.495[/C][C]3.35495[/C][/ROW]
[ROW][C]208[/C][C]7.85[/C][C]13.5661[/C][C]-5.71608[/C][/ROW]
[ROW][C]209[/C][C]7.7[/C][C]13.5224[/C][C]-5.82239[/C][/ROW]
[ROW][C]210[/C][C]12.6[/C][C]13.3767[/C][C]-0.776717[/C][/ROW]
[ROW][C]211[/C][C]7.85[/C][C]13.526[/C][C]-5.676[/C][/ROW]
[ROW][C]212[/C][C]10.95[/C][C]13.5133[/C][C]-2.56328[/C][/ROW]
[ROW][C]213[/C][C]12.35[/C][C]13.3894[/C][C]-1.03944[/C][/ROW]
[ROW][C]214[/C][C]9.95[/C][C]13.5351[/C][C]-3.58512[/C][/ROW]
[ROW][C]215[/C][C]14.9[/C][C]13.5351[/C][C]1.36488[/C][/ROW]
[ROW][C]216[/C][C]16.65[/C][C]13.5351[/C][C]3.11488[/C][/ROW]
[ROW][C]217[/C][C]13.4[/C][C]13.4641[/C][C]-0.064088[/C][/ROW]
[ROW][C]218[/C][C]13.95[/C][C]13.4914[/C][C]0.458565[/C][/ROW]
[ROW][C]219[/C][C]15.7[/C][C]13.5351[/C][C]2.16488[/C][/ROW]
[ROW][C]220[/C][C]16.85[/C][C]13.526[/C][C]3.324[/C][/ROW]
[ROW][C]221[/C][C]10.95[/C][C]13.5788[/C][C]-2.62881[/C][/ROW]
[ROW][C]222[/C][C]15.35[/C][C]13.4367[/C][C]1.91326[/C][/ROW]
[ROW][C]223[/C][C]12.2[/C][C]13.5769[/C][C]-1.37691[/C][/ROW]
[ROW][C]224[/C][C]15.1[/C][C]13.495[/C][C]1.60495[/C][/ROW]
[ROW][C]225[/C][C]17.75[/C][C]13.5351[/C][C]4.21488[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.5169[/C][C]1.68311[/C][/ROW]
[ROW][C]227[/C][C]14.6[/C][C]13.5351[/C][C]1.06488[/C][/ROW]
[ROW][C]228[/C][C]16.65[/C][C]13.4204[/C][C]3.2296[/C][/ROW]
[ROW][C]229[/C][C]8.1[/C][C]13.2783[/C][C]-5.17834[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&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
112.913.4696-0.569592
212.813.4823-0.682319
37.413.5442-6.14424
46.713.4823-6.78232
512.613.4514-0.851361
614.813.46771.3323
713.313.4514-0.151361
811.113.6498-2.54984
98.213.557-5.35696
1011.413.5133-2.11328
116.413.5169-7.11689
121213.5752-1.57519
136.313.3712-7.07121
1411.313.5351-2.23512
1511.913.5534-1.65335
169.313.5042-4.20416
171013.4914-3.49143
1813.813.54420.255764
1910.813.5478-2.74785
2011.713.4677-1.7677
2110.913.4823-2.58232
2216.113.44592.65414
239.913.5133-3.61328
2411.513.5661-2.06608
258.313.4641-5.16409
2611.713.526-1.826
27913.5133-4.51328
2810.813.5351-2.73512
2910.413.2966-2.89657
3012.713.5661-0.866079
3111.813.3494-1.54937
321313.4804-0.480427
3310.813.5351-2.73512
3412.313.526-1.226
3511.313.3057-2.00568
3611.613.4823-1.88232
3710.913.5351-2.63512
3812.113.6098-1.50976
3913.313.6189-0.31888
4010.113.4914-3.39143
4114.313.48780.812177
429.313.5042-4.20416
4312.513.4077-0.907675
447.613.3366-5.73664
459.213.4022-4.20217
4614.513.45141.04864
4712.313.557-1.25696
4812.613.2747-0.674726
491313.495-0.495046
5012.613.4477-0.847749
5113.213.5042-0.304162
527.713.5351-5.83512
5310.513.4823-2.98232
5410.913.5351-2.63512
554.313.4514-9.15136
5610.313.5078-3.20777
5711.413.3585-1.95849
585.613.4204-7.8204
598.813.4732-4.6732
60913.5351-4.53512
619.613.597-3.99704
626.413.4204-7.0204
6311.613.5133-1.91328
644.3513.5078-9.15777
6512.713.526-0.826005
6618.113.53514.56488
6717.8513.53514.31488
6816.613.40223.19783
6912.613.5133-0.913278
7017.113.49143.60857
7119.113.51335.58672
7216.113.51692.58311
7313.3513.4969-0.146939
7418.413.38585.01417
7514.713.58431.11569
7610.613.495-2.89505
7712.613.6062-1.00615
7816.213.50782.69223
7913.613.6498-0.0498386
8018.913.53515.36488
8114.113.56610.533921
8214.513.53510.96488
8316.1513.51332.63672
8414.7513.43311.31687
8514.813.50781.29223
8612.4513.5625-1.11247
8712.6513.5351-0.88512
8817.3513.5573.79304
898.613.6498-5.04984
9018.413.48234.91768
9116.113.5572.54304
9211.613.262-1.662
9317.7513.55344.19665
9415.2513.51331.73672
9517.6513.53514.11488
9616.3513.53512.81488
9717.6513.48234.16768
9813.613.53510.0648795
9914.3513.53510.81488
10014.7513.53511.21488
10118.2513.49144.75857
1029.913.455-3.55497
1031613.49872.50134
10418.2513.53514.71488
10516.8513.51333.33672
10614.613.5261.074
10713.8513.51690.333111
10818.9513.56975.38031
10915.613.51332.08672
11014.8513.54421.30576
11111.7513.5351-1.78512
11218.4513.53514.91488
11315.913.53872.36127
11417.113.47323.6268
11516.113.56972.53031
11619.913.34586.55424
11710.9513.5133-2.56328
11818.4513.46414.98591
11915.113.51331.58672
1201513.44221.55775
12111.3513.526-2.176
12215.9513.64982.30016
12318.113.4554.64503
12414.613.41131.18871
12515.413.50421.89584
12615.413.50421.89584
12717.613.50424.09584
12813.3513.5442-0.194236
12919.113.38035.71967
13015.3513.53511.81488
1317.613.3021-5.70207
13213.413.38940.0105561
13313.913.30930.590704
13419.113.50425.59584
13515.2513.51691.73311
13612.913.4459-0.545857
13716.113.51332.58672
13817.3513.46053.88952
13913.1513.4422-0.292245
14012.1513.4295-1.27952
14112.613.4987-0.898658
14210.3513.455-3.10497
14315.413.5261.874
1449.613.4914-3.89143
14518.213.4954.70495
14613.613.38580.214168
14714.8513.53511.31488
14814.7513.4551.29503
14914.113.5260.573995
15014.913.41131.48871
15116.2513.51692.73311
15219.2513.55345.69665
15313.613.48590.114069
15413.613.46410.135912
15515.6513.51692.13311
15612.7513.435-0.685022
15714.613.51331.08672
1589.8513.5879-3.73792
15912.6513.4331-0.78313
16019.213.25655.94351
16116.613.30213.29793
16211.213.557-2.35696
16315.2513.56971.68031
16411.913.4859-1.58593
16513.213.3604-0.160378
16616.3513.46962.88041
16712.413.4696-1.06959
16815.8513.4952.35495
16918.1513.58794.56208
17011.1513.5078-2.35777
17115.6513.49142.15857
17217.7513.50424.24584
1737.6513.6189-5.96888
17412.3513.526-1.176
17515.613.42042.1796
17619.313.53515.76488
17715.213.38941.81056
17817.113.56253.53753
17915.613.51332.08672
18018.413.61894.78112
18119.0513.51335.53672
18218.5513.46415.08591
18319.113.46415.63591
18413.113.5661-0.466079
18512.8513.5442-0.694236
1869.513.6498-4.14984
1874.513.526-9.026
18811.8513.3366-1.48664
18913.613.45140.148639
19011.713.5042-1.80416
19112.413.6189-1.21888
19213.3513.5534-0.203352
19311.413.5661-2.16608
19414.913.53511.36488
19519.913.34586.55424
19611.213.435-2.23502
19714.613.46411.13591
19817.613.60063.99935
19914.0513.47870.571292
20016.113.48232.61768
20113.3513.5042-0.154162
20211.8513.5224-1.67239
20311.9513.4914-1.54143
20414.7513.53511.21488
20515.1513.53871.61127
20613.213.4204-0.220402
20716.8513.4953.35495
2087.8513.5661-5.71608
2097.713.5224-5.82239
21012.613.3767-0.776717
2117.8513.526-5.676
21210.9513.5133-2.56328
21312.3513.3894-1.03944
2149.9513.5351-3.58512
21514.913.53511.36488
21616.6513.53513.11488
21713.413.4641-0.064088
21813.9513.49140.458565
21915.713.53512.16488
22016.8513.5263.324
22110.9513.5788-2.62881
22215.3513.43671.91326
22312.213.5769-1.37691
22415.113.4951.60495
22517.7513.53514.21488
22615.213.51691.68311
22714.613.53511.06488
22816.6513.42043.2296
2298.113.2783-5.17834






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.5010550.997890.498945
70.3321630.6643260.667837
80.4296390.8592770.570361
90.3937680.7875360.606232
100.288710.577420.71129
110.4505750.9011490.549425
120.4077960.8155920.592204
130.5602760.8794480.439724
140.4760210.9520420.523979
150.3963510.7927020.603649
160.3338550.667710.666145
170.2707520.5415030.729248
180.2633080.5266160.736692
190.2069730.4139460.793027
200.1720320.3440640.827968
210.1299770.2599540.870023
220.2165560.4331130.783444
230.1767770.3535550.823223
240.1383280.2766570.861672
250.1382960.2765910.861704
260.1073860.2147720.892614
270.09324410.1864880.906756
280.07071910.1414380.929281
290.05289720.1057940.947103
300.04307830.08615660.956922
310.03241830.06483650.967582
320.02397960.04795930.97602
330.01718940.03437880.982811
340.01259850.02519690.987402
350.008922440.01784490.991078
360.006264390.01252880.993736
370.004288190.008576380.995712
380.002915140.005830280.997085
390.002347810.004695630.997652
400.001639740.003279470.99836
410.002471720.004943440.997528
420.002158150.00431630.997842
430.001634120.003268230.998366
440.002211510.004423020.997788
450.001899430.003798850.998101
460.002437690.004875380.997562
470.001720190.003440390.99828
480.001419190.002838390.998581
490.00110150.0022030.998898
500.0008258910.001651780.999174
510.0006551360.001310270.999345
520.001092520.002185040.998907
530.0008041150.001608230.999196
540.0005685940.001137190.999431
550.005774680.01154940.994225
560.004669920.009339840.99533
570.003546210.007092430.996454
580.01164240.02328480.988358
590.01222120.02444250.987779
600.01251890.02503780.987481
610.01163330.02326650.988367
620.02396010.04792020.97604
630.01973980.03947970.98026
640.08517250.1703450.914827
650.0767450.153490.923255
660.1721770.3443550.827823
670.2854980.5709950.714502
680.3700050.740010.629995
690.3424460.6848930.657554
700.4271730.8543450.572827
710.6077240.7845520.392276
720.6408410.7183170.359159
730.6095990.7808020.390401
740.7180690.5638630.281931
750.6992730.6014540.300727
760.6853610.6292790.314639
770.6530730.6938530.346927
780.6878840.6242320.312116
790.6581910.6836190.341809
800.763860.4722790.23614
810.7411110.5177770.258889
820.7225370.5549260.277463
830.7299960.5400080.270004
840.7226240.5547530.277376
850.7120880.5758230.287912
860.6820730.6358540.317927
870.6517990.6964020.348201
880.6880970.6238060.311903
890.7338580.5322830.266142
900.7968750.406250.203125
910.7971370.4057250.202863
920.7801550.439690.219845
930.8087720.3824550.191228
940.7959020.4081960.204098
950.8230040.3539920.176996
960.8236860.3526290.176314
970.8480060.3039880.151994
980.8265590.3468810.173441
990.8056950.388610.194305
1000.7858510.4282980.214149
1010.8219630.3560750.178037
1020.8276960.3446090.172304
1030.8285110.3429780.171489
1040.8584210.2831590.141579
1050.8620430.2759140.137957
1060.8448290.3103430.155171
1070.8242920.3514160.175708
1080.8667760.2664480.133224
1090.8555650.2888690.144435
1100.8370940.3258130.162906
1110.8213520.3572960.178648
1120.8524210.2951580.147579
1130.8430780.3138440.156922
1140.8504640.2990710.149536
1150.8411930.3176140.158807
1160.9042410.1915180.0957591
1170.8990020.2019960.100998
1180.9195280.1609440.0804718
1190.9079980.1840030.0920017
1200.8958660.2082680.104134
1210.8874970.2250060.112503
1220.877110.245780.12289
1230.8947080.2105850.105292
1240.8795920.2408150.120408
1250.8658790.2682430.134121
1260.8510560.2978870.148944
1270.8613040.2773920.138696
1280.8392610.3214780.160739
1290.8792320.2415360.120768
1300.8644840.2710310.135516
1310.9096330.1807340.090367
1320.894460.2110790.10554
1330.8786260.2427490.121374
1340.9095790.1808410.0904206
1350.8967960.2064080.103204
1360.8803640.2392730.119636
1370.8716890.2566220.128311
1380.8769910.2460180.123009
1390.8574350.285130.142565
1400.8409850.318030.159015
1410.8199810.3600390.180019
1420.825520.3489590.17448
1430.8062420.3875160.193758
1440.8216850.3566290.178315
1450.8422010.3155980.157799
1460.8191560.3616880.180844
1470.7953620.4092750.204638
1480.7686650.462670.231335
1490.7375040.5249910.262496
1500.7082420.5835170.291758
1510.69330.6134010.3067
1520.7614370.4771270.238563
1530.7293940.5412130.270606
1540.6956170.6087650.304383
1550.671260.657480.32874
1560.6377950.7244090.362205
1570.6018420.7963160.398158
1580.610050.7799010.38995
1590.578080.8438410.42192
1600.6268690.7462620.373131
1610.6131190.7737620.386881
1620.5950750.809850.404925
1630.5626550.8746910.437345
1640.534450.93110.46555
1650.4949960.9899910.505004
1660.4774180.9548360.522582
1670.4422970.8845940.557703
1680.4162020.8324050.583798
1690.4523980.9047970.547602
1700.4347770.8695550.565223
1710.4061140.8122280.593886
1720.4249910.8499810.575009
1730.5149310.9701380.485069
1740.478260.956520.52174
1750.4463550.892710.553645
1760.5268080.9463830.473192
1770.4895270.9790540.510473
1780.4996790.9993590.500321
1790.4713090.9426190.528691
1800.5332910.9334180.466709
1810.6243320.7513350.375668
1820.6766140.6467710.323386
1830.7541910.4916180.245809
1840.7140890.5718220.285911
1850.6709260.6581480.329074
1860.6771850.6456310.322815
1870.9051980.1896050.0948024
1880.8882160.2235690.111784
1890.8610350.2779290.138965
1900.8401860.3196270.159814
1910.8095080.3809830.190492
1920.7705160.4589690.229484
1930.7467390.5065230.253261
1940.7079980.5840040.292002
1950.8578360.2843270.142164
1960.829930.340140.17007
1970.7964820.4070360.203518
1980.8060890.3878210.193911
1990.766740.466520.23326
2000.7593390.4813210.240661
2010.7087630.5824730.291237
2020.6622080.6755840.337792
2030.6105590.7788830.389441
2040.5576230.8847540.442377
2050.5077130.9845740.492287
2060.4421280.8842570.557872
2070.4539910.9079830.546009
2080.5863460.8273080.413654
2090.7663540.4672910.233646
2100.7053930.5892140.294607
2110.873130.253740.12687
2120.8988220.2023560.101178
2130.8594240.2811530.140576
2140.9496260.1007480.050374
2150.9212950.157410.078705
2160.8848670.2302670.115133
2170.8281160.3437680.171884
2180.7847460.4305080.215254
2190.6919310.6161370.308069
2200.6105060.7789880.389494
2210.8307210.3385580.169279
2220.8966460.2067070.103354
2230.8142250.371550.185775

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.501055 & 0.99789 & 0.498945 \tabularnewline
7 & 0.332163 & 0.664326 & 0.667837 \tabularnewline
8 & 0.429639 & 0.859277 & 0.570361 \tabularnewline
9 & 0.393768 & 0.787536 & 0.606232 \tabularnewline
10 & 0.28871 & 0.57742 & 0.71129 \tabularnewline
11 & 0.450575 & 0.901149 & 0.549425 \tabularnewline
12 & 0.407796 & 0.815592 & 0.592204 \tabularnewline
13 & 0.560276 & 0.879448 & 0.439724 \tabularnewline
14 & 0.476021 & 0.952042 & 0.523979 \tabularnewline
15 & 0.396351 & 0.792702 & 0.603649 \tabularnewline
16 & 0.333855 & 0.66771 & 0.666145 \tabularnewline
17 & 0.270752 & 0.541503 & 0.729248 \tabularnewline
18 & 0.263308 & 0.526616 & 0.736692 \tabularnewline
19 & 0.206973 & 0.413946 & 0.793027 \tabularnewline
20 & 0.172032 & 0.344064 & 0.827968 \tabularnewline
21 & 0.129977 & 0.259954 & 0.870023 \tabularnewline
22 & 0.216556 & 0.433113 & 0.783444 \tabularnewline
23 & 0.176777 & 0.353555 & 0.823223 \tabularnewline
24 & 0.138328 & 0.276657 & 0.861672 \tabularnewline
25 & 0.138296 & 0.276591 & 0.861704 \tabularnewline
26 & 0.107386 & 0.214772 & 0.892614 \tabularnewline
27 & 0.0932441 & 0.186488 & 0.906756 \tabularnewline
28 & 0.0707191 & 0.141438 & 0.929281 \tabularnewline
29 & 0.0528972 & 0.105794 & 0.947103 \tabularnewline
30 & 0.0430783 & 0.0861566 & 0.956922 \tabularnewline
31 & 0.0324183 & 0.0648365 & 0.967582 \tabularnewline
32 & 0.0239796 & 0.0479593 & 0.97602 \tabularnewline
33 & 0.0171894 & 0.0343788 & 0.982811 \tabularnewline
34 & 0.0125985 & 0.0251969 & 0.987402 \tabularnewline
35 & 0.00892244 & 0.0178449 & 0.991078 \tabularnewline
36 & 0.00626439 & 0.0125288 & 0.993736 \tabularnewline
37 & 0.00428819 & 0.00857638 & 0.995712 \tabularnewline
38 & 0.00291514 & 0.00583028 & 0.997085 \tabularnewline
39 & 0.00234781 & 0.00469563 & 0.997652 \tabularnewline
40 & 0.00163974 & 0.00327947 & 0.99836 \tabularnewline
41 & 0.00247172 & 0.00494344 & 0.997528 \tabularnewline
42 & 0.00215815 & 0.0043163 & 0.997842 \tabularnewline
43 & 0.00163412 & 0.00326823 & 0.998366 \tabularnewline
44 & 0.00221151 & 0.00442302 & 0.997788 \tabularnewline
45 & 0.00189943 & 0.00379885 & 0.998101 \tabularnewline
46 & 0.00243769 & 0.00487538 & 0.997562 \tabularnewline
47 & 0.00172019 & 0.00344039 & 0.99828 \tabularnewline
48 & 0.00141919 & 0.00283839 & 0.998581 \tabularnewline
49 & 0.0011015 & 0.002203 & 0.998898 \tabularnewline
50 & 0.000825891 & 0.00165178 & 0.999174 \tabularnewline
51 & 0.000655136 & 0.00131027 & 0.999345 \tabularnewline
52 & 0.00109252 & 0.00218504 & 0.998907 \tabularnewline
53 & 0.000804115 & 0.00160823 & 0.999196 \tabularnewline
54 & 0.000568594 & 0.00113719 & 0.999431 \tabularnewline
55 & 0.00577468 & 0.0115494 & 0.994225 \tabularnewline
56 & 0.00466992 & 0.00933984 & 0.99533 \tabularnewline
57 & 0.00354621 & 0.00709243 & 0.996454 \tabularnewline
58 & 0.0116424 & 0.0232848 & 0.988358 \tabularnewline
59 & 0.0122212 & 0.0244425 & 0.987779 \tabularnewline
60 & 0.0125189 & 0.0250378 & 0.987481 \tabularnewline
61 & 0.0116333 & 0.0232665 & 0.988367 \tabularnewline
62 & 0.0239601 & 0.0479202 & 0.97604 \tabularnewline
63 & 0.0197398 & 0.0394797 & 0.98026 \tabularnewline
64 & 0.0851725 & 0.170345 & 0.914827 \tabularnewline
65 & 0.076745 & 0.15349 & 0.923255 \tabularnewline
66 & 0.172177 & 0.344355 & 0.827823 \tabularnewline
67 & 0.285498 & 0.570995 & 0.714502 \tabularnewline
68 & 0.370005 & 0.74001 & 0.629995 \tabularnewline
69 & 0.342446 & 0.684893 & 0.657554 \tabularnewline
70 & 0.427173 & 0.854345 & 0.572827 \tabularnewline
71 & 0.607724 & 0.784552 & 0.392276 \tabularnewline
72 & 0.640841 & 0.718317 & 0.359159 \tabularnewline
73 & 0.609599 & 0.780802 & 0.390401 \tabularnewline
74 & 0.718069 & 0.563863 & 0.281931 \tabularnewline
75 & 0.699273 & 0.601454 & 0.300727 \tabularnewline
76 & 0.685361 & 0.629279 & 0.314639 \tabularnewline
77 & 0.653073 & 0.693853 & 0.346927 \tabularnewline
78 & 0.687884 & 0.624232 & 0.312116 \tabularnewline
79 & 0.658191 & 0.683619 & 0.341809 \tabularnewline
80 & 0.76386 & 0.472279 & 0.23614 \tabularnewline
81 & 0.741111 & 0.517777 & 0.258889 \tabularnewline
82 & 0.722537 & 0.554926 & 0.277463 \tabularnewline
83 & 0.729996 & 0.540008 & 0.270004 \tabularnewline
84 & 0.722624 & 0.554753 & 0.277376 \tabularnewline
85 & 0.712088 & 0.575823 & 0.287912 \tabularnewline
86 & 0.682073 & 0.635854 & 0.317927 \tabularnewline
87 & 0.651799 & 0.696402 & 0.348201 \tabularnewline
88 & 0.688097 & 0.623806 & 0.311903 \tabularnewline
89 & 0.733858 & 0.532283 & 0.266142 \tabularnewline
90 & 0.796875 & 0.40625 & 0.203125 \tabularnewline
91 & 0.797137 & 0.405725 & 0.202863 \tabularnewline
92 & 0.780155 & 0.43969 & 0.219845 \tabularnewline
93 & 0.808772 & 0.382455 & 0.191228 \tabularnewline
94 & 0.795902 & 0.408196 & 0.204098 \tabularnewline
95 & 0.823004 & 0.353992 & 0.176996 \tabularnewline
96 & 0.823686 & 0.352629 & 0.176314 \tabularnewline
97 & 0.848006 & 0.303988 & 0.151994 \tabularnewline
98 & 0.826559 & 0.346881 & 0.173441 \tabularnewline
99 & 0.805695 & 0.38861 & 0.194305 \tabularnewline
100 & 0.785851 & 0.428298 & 0.214149 \tabularnewline
101 & 0.821963 & 0.356075 & 0.178037 \tabularnewline
102 & 0.827696 & 0.344609 & 0.172304 \tabularnewline
103 & 0.828511 & 0.342978 & 0.171489 \tabularnewline
104 & 0.858421 & 0.283159 & 0.141579 \tabularnewline
105 & 0.862043 & 0.275914 & 0.137957 \tabularnewline
106 & 0.844829 & 0.310343 & 0.155171 \tabularnewline
107 & 0.824292 & 0.351416 & 0.175708 \tabularnewline
108 & 0.866776 & 0.266448 & 0.133224 \tabularnewline
109 & 0.855565 & 0.288869 & 0.144435 \tabularnewline
110 & 0.837094 & 0.325813 & 0.162906 \tabularnewline
111 & 0.821352 & 0.357296 & 0.178648 \tabularnewline
112 & 0.852421 & 0.295158 & 0.147579 \tabularnewline
113 & 0.843078 & 0.313844 & 0.156922 \tabularnewline
114 & 0.850464 & 0.299071 & 0.149536 \tabularnewline
115 & 0.841193 & 0.317614 & 0.158807 \tabularnewline
116 & 0.904241 & 0.191518 & 0.0957591 \tabularnewline
117 & 0.899002 & 0.201996 & 0.100998 \tabularnewline
118 & 0.919528 & 0.160944 & 0.0804718 \tabularnewline
119 & 0.907998 & 0.184003 & 0.0920017 \tabularnewline
120 & 0.895866 & 0.208268 & 0.104134 \tabularnewline
121 & 0.887497 & 0.225006 & 0.112503 \tabularnewline
122 & 0.87711 & 0.24578 & 0.12289 \tabularnewline
123 & 0.894708 & 0.210585 & 0.105292 \tabularnewline
124 & 0.879592 & 0.240815 & 0.120408 \tabularnewline
125 & 0.865879 & 0.268243 & 0.134121 \tabularnewline
126 & 0.851056 & 0.297887 & 0.148944 \tabularnewline
127 & 0.861304 & 0.277392 & 0.138696 \tabularnewline
128 & 0.839261 & 0.321478 & 0.160739 \tabularnewline
129 & 0.879232 & 0.241536 & 0.120768 \tabularnewline
130 & 0.864484 & 0.271031 & 0.135516 \tabularnewline
131 & 0.909633 & 0.180734 & 0.090367 \tabularnewline
132 & 0.89446 & 0.211079 & 0.10554 \tabularnewline
133 & 0.878626 & 0.242749 & 0.121374 \tabularnewline
134 & 0.909579 & 0.180841 & 0.0904206 \tabularnewline
135 & 0.896796 & 0.206408 & 0.103204 \tabularnewline
136 & 0.880364 & 0.239273 & 0.119636 \tabularnewline
137 & 0.871689 & 0.256622 & 0.128311 \tabularnewline
138 & 0.876991 & 0.246018 & 0.123009 \tabularnewline
139 & 0.857435 & 0.28513 & 0.142565 \tabularnewline
140 & 0.840985 & 0.31803 & 0.159015 \tabularnewline
141 & 0.819981 & 0.360039 & 0.180019 \tabularnewline
142 & 0.82552 & 0.348959 & 0.17448 \tabularnewline
143 & 0.806242 & 0.387516 & 0.193758 \tabularnewline
144 & 0.821685 & 0.356629 & 0.178315 \tabularnewline
145 & 0.842201 & 0.315598 & 0.157799 \tabularnewline
146 & 0.819156 & 0.361688 & 0.180844 \tabularnewline
147 & 0.795362 & 0.409275 & 0.204638 \tabularnewline
148 & 0.768665 & 0.46267 & 0.231335 \tabularnewline
149 & 0.737504 & 0.524991 & 0.262496 \tabularnewline
150 & 0.708242 & 0.583517 & 0.291758 \tabularnewline
151 & 0.6933 & 0.613401 & 0.3067 \tabularnewline
152 & 0.761437 & 0.477127 & 0.238563 \tabularnewline
153 & 0.729394 & 0.541213 & 0.270606 \tabularnewline
154 & 0.695617 & 0.608765 & 0.304383 \tabularnewline
155 & 0.67126 & 0.65748 & 0.32874 \tabularnewline
156 & 0.637795 & 0.724409 & 0.362205 \tabularnewline
157 & 0.601842 & 0.796316 & 0.398158 \tabularnewline
158 & 0.61005 & 0.779901 & 0.38995 \tabularnewline
159 & 0.57808 & 0.843841 & 0.42192 \tabularnewline
160 & 0.626869 & 0.746262 & 0.373131 \tabularnewline
161 & 0.613119 & 0.773762 & 0.386881 \tabularnewline
162 & 0.595075 & 0.80985 & 0.404925 \tabularnewline
163 & 0.562655 & 0.874691 & 0.437345 \tabularnewline
164 & 0.53445 & 0.9311 & 0.46555 \tabularnewline
165 & 0.494996 & 0.989991 & 0.505004 \tabularnewline
166 & 0.477418 & 0.954836 & 0.522582 \tabularnewline
167 & 0.442297 & 0.884594 & 0.557703 \tabularnewline
168 & 0.416202 & 0.832405 & 0.583798 \tabularnewline
169 & 0.452398 & 0.904797 & 0.547602 \tabularnewline
170 & 0.434777 & 0.869555 & 0.565223 \tabularnewline
171 & 0.406114 & 0.812228 & 0.593886 \tabularnewline
172 & 0.424991 & 0.849981 & 0.575009 \tabularnewline
173 & 0.514931 & 0.970138 & 0.485069 \tabularnewline
174 & 0.47826 & 0.95652 & 0.52174 \tabularnewline
175 & 0.446355 & 0.89271 & 0.553645 \tabularnewline
176 & 0.526808 & 0.946383 & 0.473192 \tabularnewline
177 & 0.489527 & 0.979054 & 0.510473 \tabularnewline
178 & 0.499679 & 0.999359 & 0.500321 \tabularnewline
179 & 0.471309 & 0.942619 & 0.528691 \tabularnewline
180 & 0.533291 & 0.933418 & 0.466709 \tabularnewline
181 & 0.624332 & 0.751335 & 0.375668 \tabularnewline
182 & 0.676614 & 0.646771 & 0.323386 \tabularnewline
183 & 0.754191 & 0.491618 & 0.245809 \tabularnewline
184 & 0.714089 & 0.571822 & 0.285911 \tabularnewline
185 & 0.670926 & 0.658148 & 0.329074 \tabularnewline
186 & 0.677185 & 0.645631 & 0.322815 \tabularnewline
187 & 0.905198 & 0.189605 & 0.0948024 \tabularnewline
188 & 0.888216 & 0.223569 & 0.111784 \tabularnewline
189 & 0.861035 & 0.277929 & 0.138965 \tabularnewline
190 & 0.840186 & 0.319627 & 0.159814 \tabularnewline
191 & 0.809508 & 0.380983 & 0.190492 \tabularnewline
192 & 0.770516 & 0.458969 & 0.229484 \tabularnewline
193 & 0.746739 & 0.506523 & 0.253261 \tabularnewline
194 & 0.707998 & 0.584004 & 0.292002 \tabularnewline
195 & 0.857836 & 0.284327 & 0.142164 \tabularnewline
196 & 0.82993 & 0.34014 & 0.17007 \tabularnewline
197 & 0.796482 & 0.407036 & 0.203518 \tabularnewline
198 & 0.806089 & 0.387821 & 0.193911 \tabularnewline
199 & 0.76674 & 0.46652 & 0.23326 \tabularnewline
200 & 0.759339 & 0.481321 & 0.240661 \tabularnewline
201 & 0.708763 & 0.582473 & 0.291237 \tabularnewline
202 & 0.662208 & 0.675584 & 0.337792 \tabularnewline
203 & 0.610559 & 0.778883 & 0.389441 \tabularnewline
204 & 0.557623 & 0.884754 & 0.442377 \tabularnewline
205 & 0.507713 & 0.984574 & 0.492287 \tabularnewline
206 & 0.442128 & 0.884257 & 0.557872 \tabularnewline
207 & 0.453991 & 0.907983 & 0.546009 \tabularnewline
208 & 0.586346 & 0.827308 & 0.413654 \tabularnewline
209 & 0.766354 & 0.467291 & 0.233646 \tabularnewline
210 & 0.705393 & 0.589214 & 0.294607 \tabularnewline
211 & 0.87313 & 0.25374 & 0.12687 \tabularnewline
212 & 0.898822 & 0.202356 & 0.101178 \tabularnewline
213 & 0.859424 & 0.281153 & 0.140576 \tabularnewline
214 & 0.949626 & 0.100748 & 0.050374 \tabularnewline
215 & 0.921295 & 0.15741 & 0.078705 \tabularnewline
216 & 0.884867 & 0.230267 & 0.115133 \tabularnewline
217 & 0.828116 & 0.343768 & 0.171884 \tabularnewline
218 & 0.784746 & 0.430508 & 0.215254 \tabularnewline
219 & 0.691931 & 0.616137 & 0.308069 \tabularnewline
220 & 0.610506 & 0.778988 & 0.389494 \tabularnewline
221 & 0.830721 & 0.338558 & 0.169279 \tabularnewline
222 & 0.896646 & 0.206707 & 0.103354 \tabularnewline
223 & 0.814225 & 0.37155 & 0.185775 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]6[/C][C]0.501055[/C][C]0.99789[/C][C]0.498945[/C][/ROW]
[ROW][C]7[/C][C]0.332163[/C][C]0.664326[/C][C]0.667837[/C][/ROW]
[ROW][C]8[/C][C]0.429639[/C][C]0.859277[/C][C]0.570361[/C][/ROW]
[ROW][C]9[/C][C]0.393768[/C][C]0.787536[/C][C]0.606232[/C][/ROW]
[ROW][C]10[/C][C]0.28871[/C][C]0.57742[/C][C]0.71129[/C][/ROW]
[ROW][C]11[/C][C]0.450575[/C][C]0.901149[/C][C]0.549425[/C][/ROW]
[ROW][C]12[/C][C]0.407796[/C][C]0.815592[/C][C]0.592204[/C][/ROW]
[ROW][C]13[/C][C]0.560276[/C][C]0.879448[/C][C]0.439724[/C][/ROW]
[ROW][C]14[/C][C]0.476021[/C][C]0.952042[/C][C]0.523979[/C][/ROW]
[ROW][C]15[/C][C]0.396351[/C][C]0.792702[/C][C]0.603649[/C][/ROW]
[ROW][C]16[/C][C]0.333855[/C][C]0.66771[/C][C]0.666145[/C][/ROW]
[ROW][C]17[/C][C]0.270752[/C][C]0.541503[/C][C]0.729248[/C][/ROW]
[ROW][C]18[/C][C]0.263308[/C][C]0.526616[/C][C]0.736692[/C][/ROW]
[ROW][C]19[/C][C]0.206973[/C][C]0.413946[/C][C]0.793027[/C][/ROW]
[ROW][C]20[/C][C]0.172032[/C][C]0.344064[/C][C]0.827968[/C][/ROW]
[ROW][C]21[/C][C]0.129977[/C][C]0.259954[/C][C]0.870023[/C][/ROW]
[ROW][C]22[/C][C]0.216556[/C][C]0.433113[/C][C]0.783444[/C][/ROW]
[ROW][C]23[/C][C]0.176777[/C][C]0.353555[/C][C]0.823223[/C][/ROW]
[ROW][C]24[/C][C]0.138328[/C][C]0.276657[/C][C]0.861672[/C][/ROW]
[ROW][C]25[/C][C]0.138296[/C][C]0.276591[/C][C]0.861704[/C][/ROW]
[ROW][C]26[/C][C]0.107386[/C][C]0.214772[/C][C]0.892614[/C][/ROW]
[ROW][C]27[/C][C]0.0932441[/C][C]0.186488[/C][C]0.906756[/C][/ROW]
[ROW][C]28[/C][C]0.0707191[/C][C]0.141438[/C][C]0.929281[/C][/ROW]
[ROW][C]29[/C][C]0.0528972[/C][C]0.105794[/C][C]0.947103[/C][/ROW]
[ROW][C]30[/C][C]0.0430783[/C][C]0.0861566[/C][C]0.956922[/C][/ROW]
[ROW][C]31[/C][C]0.0324183[/C][C]0.0648365[/C][C]0.967582[/C][/ROW]
[ROW][C]32[/C][C]0.0239796[/C][C]0.0479593[/C][C]0.97602[/C][/ROW]
[ROW][C]33[/C][C]0.0171894[/C][C]0.0343788[/C][C]0.982811[/C][/ROW]
[ROW][C]34[/C][C]0.0125985[/C][C]0.0251969[/C][C]0.987402[/C][/ROW]
[ROW][C]35[/C][C]0.00892244[/C][C]0.0178449[/C][C]0.991078[/C][/ROW]
[ROW][C]36[/C][C]0.00626439[/C][C]0.0125288[/C][C]0.993736[/C][/ROW]
[ROW][C]37[/C][C]0.00428819[/C][C]0.00857638[/C][C]0.995712[/C][/ROW]
[ROW][C]38[/C][C]0.00291514[/C][C]0.00583028[/C][C]0.997085[/C][/ROW]
[ROW][C]39[/C][C]0.00234781[/C][C]0.00469563[/C][C]0.997652[/C][/ROW]
[ROW][C]40[/C][C]0.00163974[/C][C]0.00327947[/C][C]0.99836[/C][/ROW]
[ROW][C]41[/C][C]0.00247172[/C][C]0.00494344[/C][C]0.997528[/C][/ROW]
[ROW][C]42[/C][C]0.00215815[/C][C]0.0043163[/C][C]0.997842[/C][/ROW]
[ROW][C]43[/C][C]0.00163412[/C][C]0.00326823[/C][C]0.998366[/C][/ROW]
[ROW][C]44[/C][C]0.00221151[/C][C]0.00442302[/C][C]0.997788[/C][/ROW]
[ROW][C]45[/C][C]0.00189943[/C][C]0.00379885[/C][C]0.998101[/C][/ROW]
[ROW][C]46[/C][C]0.00243769[/C][C]0.00487538[/C][C]0.997562[/C][/ROW]
[ROW][C]47[/C][C]0.00172019[/C][C]0.00344039[/C][C]0.99828[/C][/ROW]
[ROW][C]48[/C][C]0.00141919[/C][C]0.00283839[/C][C]0.998581[/C][/ROW]
[ROW][C]49[/C][C]0.0011015[/C][C]0.002203[/C][C]0.998898[/C][/ROW]
[ROW][C]50[/C][C]0.000825891[/C][C]0.00165178[/C][C]0.999174[/C][/ROW]
[ROW][C]51[/C][C]0.000655136[/C][C]0.00131027[/C][C]0.999345[/C][/ROW]
[ROW][C]52[/C][C]0.00109252[/C][C]0.00218504[/C][C]0.998907[/C][/ROW]
[ROW][C]53[/C][C]0.000804115[/C][C]0.00160823[/C][C]0.999196[/C][/ROW]
[ROW][C]54[/C][C]0.000568594[/C][C]0.00113719[/C][C]0.999431[/C][/ROW]
[ROW][C]55[/C][C]0.00577468[/C][C]0.0115494[/C][C]0.994225[/C][/ROW]
[ROW][C]56[/C][C]0.00466992[/C][C]0.00933984[/C][C]0.99533[/C][/ROW]
[ROW][C]57[/C][C]0.00354621[/C][C]0.00709243[/C][C]0.996454[/C][/ROW]
[ROW][C]58[/C][C]0.0116424[/C][C]0.0232848[/C][C]0.988358[/C][/ROW]
[ROW][C]59[/C][C]0.0122212[/C][C]0.0244425[/C][C]0.987779[/C][/ROW]
[ROW][C]60[/C][C]0.0125189[/C][C]0.0250378[/C][C]0.987481[/C][/ROW]
[ROW][C]61[/C][C]0.0116333[/C][C]0.0232665[/C][C]0.988367[/C][/ROW]
[ROW][C]62[/C][C]0.0239601[/C][C]0.0479202[/C][C]0.97604[/C][/ROW]
[ROW][C]63[/C][C]0.0197398[/C][C]0.0394797[/C][C]0.98026[/C][/ROW]
[ROW][C]64[/C][C]0.0851725[/C][C]0.170345[/C][C]0.914827[/C][/ROW]
[ROW][C]65[/C][C]0.076745[/C][C]0.15349[/C][C]0.923255[/C][/ROW]
[ROW][C]66[/C][C]0.172177[/C][C]0.344355[/C][C]0.827823[/C][/ROW]
[ROW][C]67[/C][C]0.285498[/C][C]0.570995[/C][C]0.714502[/C][/ROW]
[ROW][C]68[/C][C]0.370005[/C][C]0.74001[/C][C]0.629995[/C][/ROW]
[ROW][C]69[/C][C]0.342446[/C][C]0.684893[/C][C]0.657554[/C][/ROW]
[ROW][C]70[/C][C]0.427173[/C][C]0.854345[/C][C]0.572827[/C][/ROW]
[ROW][C]71[/C][C]0.607724[/C][C]0.784552[/C][C]0.392276[/C][/ROW]
[ROW][C]72[/C][C]0.640841[/C][C]0.718317[/C][C]0.359159[/C][/ROW]
[ROW][C]73[/C][C]0.609599[/C][C]0.780802[/C][C]0.390401[/C][/ROW]
[ROW][C]74[/C][C]0.718069[/C][C]0.563863[/C][C]0.281931[/C][/ROW]
[ROW][C]75[/C][C]0.699273[/C][C]0.601454[/C][C]0.300727[/C][/ROW]
[ROW][C]76[/C][C]0.685361[/C][C]0.629279[/C][C]0.314639[/C][/ROW]
[ROW][C]77[/C][C]0.653073[/C][C]0.693853[/C][C]0.346927[/C][/ROW]
[ROW][C]78[/C][C]0.687884[/C][C]0.624232[/C][C]0.312116[/C][/ROW]
[ROW][C]79[/C][C]0.658191[/C][C]0.683619[/C][C]0.341809[/C][/ROW]
[ROW][C]80[/C][C]0.76386[/C][C]0.472279[/C][C]0.23614[/C][/ROW]
[ROW][C]81[/C][C]0.741111[/C][C]0.517777[/C][C]0.258889[/C][/ROW]
[ROW][C]82[/C][C]0.722537[/C][C]0.554926[/C][C]0.277463[/C][/ROW]
[ROW][C]83[/C][C]0.729996[/C][C]0.540008[/C][C]0.270004[/C][/ROW]
[ROW][C]84[/C][C]0.722624[/C][C]0.554753[/C][C]0.277376[/C][/ROW]
[ROW][C]85[/C][C]0.712088[/C][C]0.575823[/C][C]0.287912[/C][/ROW]
[ROW][C]86[/C][C]0.682073[/C][C]0.635854[/C][C]0.317927[/C][/ROW]
[ROW][C]87[/C][C]0.651799[/C][C]0.696402[/C][C]0.348201[/C][/ROW]
[ROW][C]88[/C][C]0.688097[/C][C]0.623806[/C][C]0.311903[/C][/ROW]
[ROW][C]89[/C][C]0.733858[/C][C]0.532283[/C][C]0.266142[/C][/ROW]
[ROW][C]90[/C][C]0.796875[/C][C]0.40625[/C][C]0.203125[/C][/ROW]
[ROW][C]91[/C][C]0.797137[/C][C]0.405725[/C][C]0.202863[/C][/ROW]
[ROW][C]92[/C][C]0.780155[/C][C]0.43969[/C][C]0.219845[/C][/ROW]
[ROW][C]93[/C][C]0.808772[/C][C]0.382455[/C][C]0.191228[/C][/ROW]
[ROW][C]94[/C][C]0.795902[/C][C]0.408196[/C][C]0.204098[/C][/ROW]
[ROW][C]95[/C][C]0.823004[/C][C]0.353992[/C][C]0.176996[/C][/ROW]
[ROW][C]96[/C][C]0.823686[/C][C]0.352629[/C][C]0.176314[/C][/ROW]
[ROW][C]97[/C][C]0.848006[/C][C]0.303988[/C][C]0.151994[/C][/ROW]
[ROW][C]98[/C][C]0.826559[/C][C]0.346881[/C][C]0.173441[/C][/ROW]
[ROW][C]99[/C][C]0.805695[/C][C]0.38861[/C][C]0.194305[/C][/ROW]
[ROW][C]100[/C][C]0.785851[/C][C]0.428298[/C][C]0.214149[/C][/ROW]
[ROW][C]101[/C][C]0.821963[/C][C]0.356075[/C][C]0.178037[/C][/ROW]
[ROW][C]102[/C][C]0.827696[/C][C]0.344609[/C][C]0.172304[/C][/ROW]
[ROW][C]103[/C][C]0.828511[/C][C]0.342978[/C][C]0.171489[/C][/ROW]
[ROW][C]104[/C][C]0.858421[/C][C]0.283159[/C][C]0.141579[/C][/ROW]
[ROW][C]105[/C][C]0.862043[/C][C]0.275914[/C][C]0.137957[/C][/ROW]
[ROW][C]106[/C][C]0.844829[/C][C]0.310343[/C][C]0.155171[/C][/ROW]
[ROW][C]107[/C][C]0.824292[/C][C]0.351416[/C][C]0.175708[/C][/ROW]
[ROW][C]108[/C][C]0.866776[/C][C]0.266448[/C][C]0.133224[/C][/ROW]
[ROW][C]109[/C][C]0.855565[/C][C]0.288869[/C][C]0.144435[/C][/ROW]
[ROW][C]110[/C][C]0.837094[/C][C]0.325813[/C][C]0.162906[/C][/ROW]
[ROW][C]111[/C][C]0.821352[/C][C]0.357296[/C][C]0.178648[/C][/ROW]
[ROW][C]112[/C][C]0.852421[/C][C]0.295158[/C][C]0.147579[/C][/ROW]
[ROW][C]113[/C][C]0.843078[/C][C]0.313844[/C][C]0.156922[/C][/ROW]
[ROW][C]114[/C][C]0.850464[/C][C]0.299071[/C][C]0.149536[/C][/ROW]
[ROW][C]115[/C][C]0.841193[/C][C]0.317614[/C][C]0.158807[/C][/ROW]
[ROW][C]116[/C][C]0.904241[/C][C]0.191518[/C][C]0.0957591[/C][/ROW]
[ROW][C]117[/C][C]0.899002[/C][C]0.201996[/C][C]0.100998[/C][/ROW]
[ROW][C]118[/C][C]0.919528[/C][C]0.160944[/C][C]0.0804718[/C][/ROW]
[ROW][C]119[/C][C]0.907998[/C][C]0.184003[/C][C]0.0920017[/C][/ROW]
[ROW][C]120[/C][C]0.895866[/C][C]0.208268[/C][C]0.104134[/C][/ROW]
[ROW][C]121[/C][C]0.887497[/C][C]0.225006[/C][C]0.112503[/C][/ROW]
[ROW][C]122[/C][C]0.87711[/C][C]0.24578[/C][C]0.12289[/C][/ROW]
[ROW][C]123[/C][C]0.894708[/C][C]0.210585[/C][C]0.105292[/C][/ROW]
[ROW][C]124[/C][C]0.879592[/C][C]0.240815[/C][C]0.120408[/C][/ROW]
[ROW][C]125[/C][C]0.865879[/C][C]0.268243[/C][C]0.134121[/C][/ROW]
[ROW][C]126[/C][C]0.851056[/C][C]0.297887[/C][C]0.148944[/C][/ROW]
[ROW][C]127[/C][C]0.861304[/C][C]0.277392[/C][C]0.138696[/C][/ROW]
[ROW][C]128[/C][C]0.839261[/C][C]0.321478[/C][C]0.160739[/C][/ROW]
[ROW][C]129[/C][C]0.879232[/C][C]0.241536[/C][C]0.120768[/C][/ROW]
[ROW][C]130[/C][C]0.864484[/C][C]0.271031[/C][C]0.135516[/C][/ROW]
[ROW][C]131[/C][C]0.909633[/C][C]0.180734[/C][C]0.090367[/C][/ROW]
[ROW][C]132[/C][C]0.89446[/C][C]0.211079[/C][C]0.10554[/C][/ROW]
[ROW][C]133[/C][C]0.878626[/C][C]0.242749[/C][C]0.121374[/C][/ROW]
[ROW][C]134[/C][C]0.909579[/C][C]0.180841[/C][C]0.0904206[/C][/ROW]
[ROW][C]135[/C][C]0.896796[/C][C]0.206408[/C][C]0.103204[/C][/ROW]
[ROW][C]136[/C][C]0.880364[/C][C]0.239273[/C][C]0.119636[/C][/ROW]
[ROW][C]137[/C][C]0.871689[/C][C]0.256622[/C][C]0.128311[/C][/ROW]
[ROW][C]138[/C][C]0.876991[/C][C]0.246018[/C][C]0.123009[/C][/ROW]
[ROW][C]139[/C][C]0.857435[/C][C]0.28513[/C][C]0.142565[/C][/ROW]
[ROW][C]140[/C][C]0.840985[/C][C]0.31803[/C][C]0.159015[/C][/ROW]
[ROW][C]141[/C][C]0.819981[/C][C]0.360039[/C][C]0.180019[/C][/ROW]
[ROW][C]142[/C][C]0.82552[/C][C]0.348959[/C][C]0.17448[/C][/ROW]
[ROW][C]143[/C][C]0.806242[/C][C]0.387516[/C][C]0.193758[/C][/ROW]
[ROW][C]144[/C][C]0.821685[/C][C]0.356629[/C][C]0.178315[/C][/ROW]
[ROW][C]145[/C][C]0.842201[/C][C]0.315598[/C][C]0.157799[/C][/ROW]
[ROW][C]146[/C][C]0.819156[/C][C]0.361688[/C][C]0.180844[/C][/ROW]
[ROW][C]147[/C][C]0.795362[/C][C]0.409275[/C][C]0.204638[/C][/ROW]
[ROW][C]148[/C][C]0.768665[/C][C]0.46267[/C][C]0.231335[/C][/ROW]
[ROW][C]149[/C][C]0.737504[/C][C]0.524991[/C][C]0.262496[/C][/ROW]
[ROW][C]150[/C][C]0.708242[/C][C]0.583517[/C][C]0.291758[/C][/ROW]
[ROW][C]151[/C][C]0.6933[/C][C]0.613401[/C][C]0.3067[/C][/ROW]
[ROW][C]152[/C][C]0.761437[/C][C]0.477127[/C][C]0.238563[/C][/ROW]
[ROW][C]153[/C][C]0.729394[/C][C]0.541213[/C][C]0.270606[/C][/ROW]
[ROW][C]154[/C][C]0.695617[/C][C]0.608765[/C][C]0.304383[/C][/ROW]
[ROW][C]155[/C][C]0.67126[/C][C]0.65748[/C][C]0.32874[/C][/ROW]
[ROW][C]156[/C][C]0.637795[/C][C]0.724409[/C][C]0.362205[/C][/ROW]
[ROW][C]157[/C][C]0.601842[/C][C]0.796316[/C][C]0.398158[/C][/ROW]
[ROW][C]158[/C][C]0.61005[/C][C]0.779901[/C][C]0.38995[/C][/ROW]
[ROW][C]159[/C][C]0.57808[/C][C]0.843841[/C][C]0.42192[/C][/ROW]
[ROW][C]160[/C][C]0.626869[/C][C]0.746262[/C][C]0.373131[/C][/ROW]
[ROW][C]161[/C][C]0.613119[/C][C]0.773762[/C][C]0.386881[/C][/ROW]
[ROW][C]162[/C][C]0.595075[/C][C]0.80985[/C][C]0.404925[/C][/ROW]
[ROW][C]163[/C][C]0.562655[/C][C]0.874691[/C][C]0.437345[/C][/ROW]
[ROW][C]164[/C][C]0.53445[/C][C]0.9311[/C][C]0.46555[/C][/ROW]
[ROW][C]165[/C][C]0.494996[/C][C]0.989991[/C][C]0.505004[/C][/ROW]
[ROW][C]166[/C][C]0.477418[/C][C]0.954836[/C][C]0.522582[/C][/ROW]
[ROW][C]167[/C][C]0.442297[/C][C]0.884594[/C][C]0.557703[/C][/ROW]
[ROW][C]168[/C][C]0.416202[/C][C]0.832405[/C][C]0.583798[/C][/ROW]
[ROW][C]169[/C][C]0.452398[/C][C]0.904797[/C][C]0.547602[/C][/ROW]
[ROW][C]170[/C][C]0.434777[/C][C]0.869555[/C][C]0.565223[/C][/ROW]
[ROW][C]171[/C][C]0.406114[/C][C]0.812228[/C][C]0.593886[/C][/ROW]
[ROW][C]172[/C][C]0.424991[/C][C]0.849981[/C][C]0.575009[/C][/ROW]
[ROW][C]173[/C][C]0.514931[/C][C]0.970138[/C][C]0.485069[/C][/ROW]
[ROW][C]174[/C][C]0.47826[/C][C]0.95652[/C][C]0.52174[/C][/ROW]
[ROW][C]175[/C][C]0.446355[/C][C]0.89271[/C][C]0.553645[/C][/ROW]
[ROW][C]176[/C][C]0.526808[/C][C]0.946383[/C][C]0.473192[/C][/ROW]
[ROW][C]177[/C][C]0.489527[/C][C]0.979054[/C][C]0.510473[/C][/ROW]
[ROW][C]178[/C][C]0.499679[/C][C]0.999359[/C][C]0.500321[/C][/ROW]
[ROW][C]179[/C][C]0.471309[/C][C]0.942619[/C][C]0.528691[/C][/ROW]
[ROW][C]180[/C][C]0.533291[/C][C]0.933418[/C][C]0.466709[/C][/ROW]
[ROW][C]181[/C][C]0.624332[/C][C]0.751335[/C][C]0.375668[/C][/ROW]
[ROW][C]182[/C][C]0.676614[/C][C]0.646771[/C][C]0.323386[/C][/ROW]
[ROW][C]183[/C][C]0.754191[/C][C]0.491618[/C][C]0.245809[/C][/ROW]
[ROW][C]184[/C][C]0.714089[/C][C]0.571822[/C][C]0.285911[/C][/ROW]
[ROW][C]185[/C][C]0.670926[/C][C]0.658148[/C][C]0.329074[/C][/ROW]
[ROW][C]186[/C][C]0.677185[/C][C]0.645631[/C][C]0.322815[/C][/ROW]
[ROW][C]187[/C][C]0.905198[/C][C]0.189605[/C][C]0.0948024[/C][/ROW]
[ROW][C]188[/C][C]0.888216[/C][C]0.223569[/C][C]0.111784[/C][/ROW]
[ROW][C]189[/C][C]0.861035[/C][C]0.277929[/C][C]0.138965[/C][/ROW]
[ROW][C]190[/C][C]0.840186[/C][C]0.319627[/C][C]0.159814[/C][/ROW]
[ROW][C]191[/C][C]0.809508[/C][C]0.380983[/C][C]0.190492[/C][/ROW]
[ROW][C]192[/C][C]0.770516[/C][C]0.458969[/C][C]0.229484[/C][/ROW]
[ROW][C]193[/C][C]0.746739[/C][C]0.506523[/C][C]0.253261[/C][/ROW]
[ROW][C]194[/C][C]0.707998[/C][C]0.584004[/C][C]0.292002[/C][/ROW]
[ROW][C]195[/C][C]0.857836[/C][C]0.284327[/C][C]0.142164[/C][/ROW]
[ROW][C]196[/C][C]0.82993[/C][C]0.34014[/C][C]0.17007[/C][/ROW]
[ROW][C]197[/C][C]0.796482[/C][C]0.407036[/C][C]0.203518[/C][/ROW]
[ROW][C]198[/C][C]0.806089[/C][C]0.387821[/C][C]0.193911[/C][/ROW]
[ROW][C]199[/C][C]0.76674[/C][C]0.46652[/C][C]0.23326[/C][/ROW]
[ROW][C]200[/C][C]0.759339[/C][C]0.481321[/C][C]0.240661[/C][/ROW]
[ROW][C]201[/C][C]0.708763[/C][C]0.582473[/C][C]0.291237[/C][/ROW]
[ROW][C]202[/C][C]0.662208[/C][C]0.675584[/C][C]0.337792[/C][/ROW]
[ROW][C]203[/C][C]0.610559[/C][C]0.778883[/C][C]0.389441[/C][/ROW]
[ROW][C]204[/C][C]0.557623[/C][C]0.884754[/C][C]0.442377[/C][/ROW]
[ROW][C]205[/C][C]0.507713[/C][C]0.984574[/C][C]0.492287[/C][/ROW]
[ROW][C]206[/C][C]0.442128[/C][C]0.884257[/C][C]0.557872[/C][/ROW]
[ROW][C]207[/C][C]0.453991[/C][C]0.907983[/C][C]0.546009[/C][/ROW]
[ROW][C]208[/C][C]0.586346[/C][C]0.827308[/C][C]0.413654[/C][/ROW]
[ROW][C]209[/C][C]0.766354[/C][C]0.467291[/C][C]0.233646[/C][/ROW]
[ROW][C]210[/C][C]0.705393[/C][C]0.589214[/C][C]0.294607[/C][/ROW]
[ROW][C]211[/C][C]0.87313[/C][C]0.25374[/C][C]0.12687[/C][/ROW]
[ROW][C]212[/C][C]0.898822[/C][C]0.202356[/C][C]0.101178[/C][/ROW]
[ROW][C]213[/C][C]0.859424[/C][C]0.281153[/C][C]0.140576[/C][/ROW]
[ROW][C]214[/C][C]0.949626[/C][C]0.100748[/C][C]0.050374[/C][/ROW]
[ROW][C]215[/C][C]0.921295[/C][C]0.15741[/C][C]0.078705[/C][/ROW]
[ROW][C]216[/C][C]0.884867[/C][C]0.230267[/C][C]0.115133[/C][/ROW]
[ROW][C]217[/C][C]0.828116[/C][C]0.343768[/C][C]0.171884[/C][/ROW]
[ROW][C]218[/C][C]0.784746[/C][C]0.430508[/C][C]0.215254[/C][/ROW]
[ROW][C]219[/C][C]0.691931[/C][C]0.616137[/C][C]0.308069[/C][/ROW]
[ROW][C]220[/C][C]0.610506[/C][C]0.778988[/C][C]0.389494[/C][/ROW]
[ROW][C]221[/C][C]0.830721[/C][C]0.338558[/C][C]0.169279[/C][/ROW]
[ROW][C]222[/C][C]0.896646[/C][C]0.206707[/C][C]0.103354[/C][/ROW]
[ROW][C]223[/C][C]0.814225[/C][C]0.37155[/C][C]0.185775[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.5010550.997890.498945
70.3321630.6643260.667837
80.4296390.8592770.570361
90.3937680.7875360.606232
100.288710.577420.71129
110.4505750.9011490.549425
120.4077960.8155920.592204
130.5602760.8794480.439724
140.4760210.9520420.523979
150.3963510.7927020.603649
160.3338550.667710.666145
170.2707520.5415030.729248
180.2633080.5266160.736692
190.2069730.4139460.793027
200.1720320.3440640.827968
210.1299770.2599540.870023
220.2165560.4331130.783444
230.1767770.3535550.823223
240.1383280.2766570.861672
250.1382960.2765910.861704
260.1073860.2147720.892614
270.09324410.1864880.906756
280.07071910.1414380.929281
290.05289720.1057940.947103
300.04307830.08615660.956922
310.03241830.06483650.967582
320.02397960.04795930.97602
330.01718940.03437880.982811
340.01259850.02519690.987402
350.008922440.01784490.991078
360.006264390.01252880.993736
370.004288190.008576380.995712
380.002915140.005830280.997085
390.002347810.004695630.997652
400.001639740.003279470.99836
410.002471720.004943440.997528
420.002158150.00431630.997842
430.001634120.003268230.998366
440.002211510.004423020.997788
450.001899430.003798850.998101
460.002437690.004875380.997562
470.001720190.003440390.99828
480.001419190.002838390.998581
490.00110150.0022030.998898
500.0008258910.001651780.999174
510.0006551360.001310270.999345
520.001092520.002185040.998907
530.0008041150.001608230.999196
540.0005685940.001137190.999431
550.005774680.01154940.994225
560.004669920.009339840.99533
570.003546210.007092430.996454
580.01164240.02328480.988358
590.01222120.02444250.987779
600.01251890.02503780.987481
610.01163330.02326650.988367
620.02396010.04792020.97604
630.01973980.03947970.98026
640.08517250.1703450.914827
650.0767450.153490.923255
660.1721770.3443550.827823
670.2854980.5709950.714502
680.3700050.740010.629995
690.3424460.6848930.657554
700.4271730.8543450.572827
710.6077240.7845520.392276
720.6408410.7183170.359159
730.6095990.7808020.390401
740.7180690.5638630.281931
750.6992730.6014540.300727
760.6853610.6292790.314639
770.6530730.6938530.346927
780.6878840.6242320.312116
790.6581910.6836190.341809
800.763860.4722790.23614
810.7411110.5177770.258889
820.7225370.5549260.277463
830.7299960.5400080.270004
840.7226240.5547530.277376
850.7120880.5758230.287912
860.6820730.6358540.317927
870.6517990.6964020.348201
880.6880970.6238060.311903
890.7338580.5322830.266142
900.7968750.406250.203125
910.7971370.4057250.202863
920.7801550.439690.219845
930.8087720.3824550.191228
940.7959020.4081960.204098
950.8230040.3539920.176996
960.8236860.3526290.176314
970.8480060.3039880.151994
980.8265590.3468810.173441
990.8056950.388610.194305
1000.7858510.4282980.214149
1010.8219630.3560750.178037
1020.8276960.3446090.172304
1030.8285110.3429780.171489
1040.8584210.2831590.141579
1050.8620430.2759140.137957
1060.8448290.3103430.155171
1070.8242920.3514160.175708
1080.8667760.2664480.133224
1090.8555650.2888690.144435
1100.8370940.3258130.162906
1110.8213520.3572960.178648
1120.8524210.2951580.147579
1130.8430780.3138440.156922
1140.8504640.2990710.149536
1150.8411930.3176140.158807
1160.9042410.1915180.0957591
1170.8990020.2019960.100998
1180.9195280.1609440.0804718
1190.9079980.1840030.0920017
1200.8958660.2082680.104134
1210.8874970.2250060.112503
1220.877110.245780.12289
1230.8947080.2105850.105292
1240.8795920.2408150.120408
1250.8658790.2682430.134121
1260.8510560.2978870.148944
1270.8613040.2773920.138696
1280.8392610.3214780.160739
1290.8792320.2415360.120768
1300.8644840.2710310.135516
1310.9096330.1807340.090367
1320.894460.2110790.10554
1330.8786260.2427490.121374
1340.9095790.1808410.0904206
1350.8967960.2064080.103204
1360.8803640.2392730.119636
1370.8716890.2566220.128311
1380.8769910.2460180.123009
1390.8574350.285130.142565
1400.8409850.318030.159015
1410.8199810.3600390.180019
1420.825520.3489590.17448
1430.8062420.3875160.193758
1440.8216850.3566290.178315
1450.8422010.3155980.157799
1460.8191560.3616880.180844
1470.7953620.4092750.204638
1480.7686650.462670.231335
1490.7375040.5249910.262496
1500.7082420.5835170.291758
1510.69330.6134010.3067
1520.7614370.4771270.238563
1530.7293940.5412130.270606
1540.6956170.6087650.304383
1550.671260.657480.32874
1560.6377950.7244090.362205
1570.6018420.7963160.398158
1580.610050.7799010.38995
1590.578080.8438410.42192
1600.6268690.7462620.373131
1610.6131190.7737620.386881
1620.5950750.809850.404925
1630.5626550.8746910.437345
1640.534450.93110.46555
1650.4949960.9899910.505004
1660.4774180.9548360.522582
1670.4422970.8845940.557703
1680.4162020.8324050.583798
1690.4523980.9047970.547602
1700.4347770.8695550.565223
1710.4061140.8122280.593886
1720.4249910.8499810.575009
1730.5149310.9701380.485069
1740.478260.956520.52174
1750.4463550.892710.553645
1760.5268080.9463830.473192
1770.4895270.9790540.510473
1780.4996790.9993590.500321
1790.4713090.9426190.528691
1800.5332910.9334180.466709
1810.6243320.7513350.375668
1820.6766140.6467710.323386
1830.7541910.4916180.245809
1840.7140890.5718220.285911
1850.6709260.6581480.329074
1860.6771850.6456310.322815
1870.9051980.1896050.0948024
1880.8882160.2235690.111784
1890.8610350.2779290.138965
1900.8401860.3196270.159814
1910.8095080.3809830.190492
1920.7705160.4589690.229484
1930.7467390.5065230.253261
1940.7079980.5840040.292002
1950.8578360.2843270.142164
1960.829930.340140.17007
1970.7964820.4070360.203518
1980.8060890.3878210.193911
1990.766740.466520.23326
2000.7593390.4813210.240661
2010.7087630.5824730.291237
2020.6622080.6755840.337792
2030.6105590.7788830.389441
2040.5576230.8847540.442377
2050.5077130.9845740.492287
2060.4421280.8842570.557872
2070.4539910.9079830.546009
2080.5863460.8273080.413654
2090.7663540.4672910.233646
2100.7053930.5892140.294607
2110.873130.253740.12687
2120.8988220.2023560.101178
2130.8594240.2811530.140576
2140.9496260.1007480.050374
2150.9212950.157410.078705
2160.8848670.2302670.115133
2170.8281160.3437680.171884
2180.7847460.4305080.215254
2190.6919310.6161370.308069
2200.6105060.7789880.389494
2210.8307210.3385580.169279
2220.8966460.2067070.103354
2230.8142250.371550.185775






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level200.0917431NOK
5% type I error level320.146789NOK
10% type I error level340.155963NOK

\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 & 20 & 0.0917431 & NOK \tabularnewline
5% type I error level & 32 & 0.146789 & NOK \tabularnewline
10% type I error level & 34 & 0.155963 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264822&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]20[/C][C]0.0917431[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]32[/C][C]0.146789[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]34[/C][C]0.155963[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264822&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264822&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level200.0917431NOK
5% type I error level320.146789NOK
10% type I error level340.155963NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; 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')
}