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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 computationMon, 15 Dec 2014 14:17:32 +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/15/t14186532485hrwzgvcd0t7mku.htm/, Retrieved Thu, 16 May 2024 06:43:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268481, Retrieved Thu, 16 May 2024 06:43:54 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact47

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [paper] [2014-12-15 14:17:32] [6ac057e9f6255a74ae39891d7e02481c] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12	12,9
8	12,2
11	12,8
13	7,4
11	6,7
10	12,6
7	14,8
10	13,3
15	11,1
12	8,2
12	11,4
10	6,4
10	10,6
14	12,0
6	6,3
12	11,3
14	11,9
11	9,3
8	9,6
12	10,0
15	6,4
13	13,8
11	10,8
12	13,8
7	11,7
11	10,9
7	16,1
12	13,4
12	9,9
13	11,5
9	8,3
11	11,7
12	9,0
15	9,7
12	10,8
6	10,3
5	10,4
13	12,7
11	9,3
6	11,8
12	5,9
10	11,4
6	13,0
12	10,8
11	12,3
6	11,3
12	11,8
12	7,9
8	12,7
10	12,3
11	11,6
7	6,7
12	10,9
13	12,1
14	13,3
12	10,1
6	5,7
14	14,3
10	8,0
12	13,3
11	9,3
10	12,5
7	7,6
12	15,9
7	9,2
12	9,1
12	11,1
10	13,0
10	14,5
12	12,2
12	12,3
12	11,4
8	8,8
10	14,6
5	12,6
10	13,0
12	12,6
11	13,2
9	9,9
12	7,7
11	10,5
10	13,4
12	10,9
10	4,3
9	10,3
11	11,8
12	11,2
7	11,4
11	8,6
12	13,2
6	12,6
9	5,6
15	9,9
10	8,8
11	7,7
12	9,0
12	7,3
12	11,4
11	13,6
9	7,9
11	10,7
12	10,3
12	8,3
14	9,6
8	14,2
10	8,5
9	13,5
10	4,9
9	6,4
10	9,6
12	11,6
11	11,1
9	4,35
11	12,7
12	18,1
12	17,85
7	16,6
12	12,6
12	17,1
12	19,1
10	16,1
15	13,35
10	18,4
15	14,7
10	10,6
15	12,6
9	16,2
15	13,6
12	18,9
13	14,1
12	14,5
12	16,15
8	14,75
9	14,8
15	12,45
12	12,65
12	17,35
15	8,6
11	18,4
12	16,1
6	11,6
14	17,75
12	15,25
12	17,65
12	16,35
11	17,65
12	13,6
12	14,35
12	14,75
12	18,25
8	9,9
12	18,25
12	16,85
11	14,6
10	13,85
11	18,95
12	15,6
13	14,85
12	11,75
12	18,45
10	15,9
10	17,1
11	16,1
8	19,9
12	10,95
9	18,45
12	15,1
11	11,35
15	15,95
8	18,1
8	14,6
11	15,4
11	15,4
11	17,6
13	13,35
7	19,1
12	15,35
8	7,6
8	13,4
4	13,9
11	19,1
10	15,25
7	12,9
12	16,1
11	17,35
9	13,15
10	12,15
8	12,6
8	10,35
11	15,4
12	9,6
10	18,2
10	13,6
12	14,85
8	14,75
11	14,1
8	14,9
10	16,25
14	19,25
9	13,6
9	13,6
10	15,65
13	12,75
12	14,6
13	9,85
8	12,65
3	19,2
8	16,6
12	11,2
11	15,25
9	11,9
12	13,2
12	16,35
12	12,4
10	15,85
13	18,15
9	11,15
12	15,65
11	17,75
14	7,65
11	12,35
9	15,6
12	19,3
8	15,2
15	17,1
12	15,6
14	18,4
12	19,05
9	18,55
9	19,1
13	13,1
13	12,85
15	9,5
11	4,5
7	11,85
10	13,6
11	11,7
14	12,4
14	13,35
13	11,4
12	14,9
8	19,9
13	11,2
9	14,6
12	17,6
13	14,05
11	16,1
11	13,35
13	11,85
12	11,95
12	14,75
10	15,15
9	13,2
10	16,85
13	7,85
13	7,7
9	12,6
11	7,85
12	10,95
8	12,35
12	9,95
12	14,9
12	16,65
9	13,4
12	13,95
12	15,7
11	16,85
12	10,95
6	15,35
7	12,2
10	15,1
12	17,75
10	15,2
12	14,6
9	16,65
3	8,1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
CS[t] = + 10.4731 + 0.0219306TOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
CS[t] =  +  10.4731 +  0.0219306TOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]CS[t] =  +  10.4731 +  0.0219306TOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&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
CS[t] = + 10.4731 + 0.0219306TOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.47310.54412319.258.17617e-534.08809e-53
TOT0.02193060.04062530.53980.5897550.294877

\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) & 10.4731 & 0.544123 & 19.25 & 8.17617e-53 & 4.08809e-53 \tabularnewline
TOT & 0.0219306 & 0.0406253 & 0.5398 & 0.589755 & 0.294877 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&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]10.4731[/C][C]0.544123[/C][C]19.25[/C][C]8.17617e-53[/C][C]4.08809e-53[/C][/ROW]
[ROW][C]TOT[/C][C]0.0219306[/C][C]0.0406253[/C][C]0.5398[/C][C]0.589755[/C][C]0.294877[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&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)10.47310.54412319.258.17617e-534.08809e-53
TOT0.02193060.04062530.53980.5897550.294877






Multiple Linear Regression - Regression Statistics
Multiple R0.0325948
R-squared0.00106242
Adjusted R-squared-0.00258333
F-TEST (value)0.291414
F-TEST (DF numerator)1
F-TEST (DF denominator)274
p-value0.589755
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29026
Sum Squared Residuals1437.21

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0325948 \tabularnewline
R-squared & 0.00106242 \tabularnewline
Adjusted R-squared & -0.00258333 \tabularnewline
F-TEST (value) & 0.291414 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 274 \tabularnewline
p-value & 0.589755 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.29026 \tabularnewline
Sum Squared Residuals & 1437.21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0325948[/C][/ROW]
[ROW][C]R-squared[/C][C]0.00106242[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]-0.00258333[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]0.291414[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]274[/C][/ROW]
[ROW][C]p-value[/C][C]0.589755[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.29026[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1437.21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&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 R0.0325948
R-squared0.00106242
Adjusted R-squared-0.00258333
F-TEST (value)0.291414
F-TEST (DF numerator)1
F-TEST (DF denominator)274
p-value0.589755
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29026
Sum Squared Residuals1437.21






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.7561.244
2810.7407-2.74065
31110.75380.24619
41310.63542.36462
51110.620.379967
61010.7494-0.749424
7710.7977-3.79767
81010.7648-0.764775
91510.71654.28347
101210.65291.34707
111210.72311.27689
121010.6135-0.613454
131010.7056-0.705562
141410.73633.26373
15610.6113-4.61126
161210.72091.27909
171410.73413.26593
181110.67710.322947
19810.6836-2.68363
201210.69241.3076
211510.61354.38655
221310.77572.22426
231110.70990.290052
241210.77571.22426
25710.7297-3.72969
261110.71210.287858
27710.8262-3.82618
281210.7671.23303
291210.69021.30979
301310.72532.2747
31910.6551-1.65512
321110.72970.270314
331210.67051.32953
341510.68584.31418
351210.70991.29005
36610.699-4.69898
37510.7012-5.70118
381310.75162.24838
391110.67710.322947
40610.7319-4.73188
411210.60251.39751
421010.7231-0.723107
43610.7582-4.7582
441210.70991.29005
451110.74280.257156
46610.7209-4.72091
471210.73191.26812
481210.64631.35365
49810.7516-2.75162
501010.7428-0.742844
511110.72750.272507
52710.62-3.62003
531210.71211.28786
541310.73852.26154
551410.76483.23522
561210.69461.3054
57610.5981-4.5981
581410.78673.21329
591010.6485-0.648543
601210.76481.23522
611110.67710.322947
621010.7472-0.747231
63710.6398-3.63977
641210.82181.17821
65710.6749-3.67486
661210.67271.32733
671210.71651.28347
681010.7582-0.758196
691010.7911-0.791092
701210.74071.25935
711210.74281.25716
721210.72311.27689
73810.6661-2.66609
741010.7933-0.793285
75510.7494-5.74942
761010.7582-0.758196
771210.74941.25058
781110.76260.237418
79910.6902-1.69021
801210.6421.35804
811110.70340.296631
821010.767-0.766968
831210.71211.28786
841010.5674-0.567399
85910.699-1.69898
861110.73190.268121
871210.71871.28128
88710.7231-3.72311
891110.66170.338299
901210.76261.23742
91610.7494-4.74942
92910.5959-1.59591
931510.69024.30979
941010.6661-0.666087
951110.6420.358036
961210.67051.32953
971210.63321.36681
981210.72311.27689
991110.77140.228646
100910.6463-1.64635
1011110.70780.292245
1021210.6991.30102
1031210.65511.34488
1041410.68363.31637
105810.7845-2.78451
1061010.6595-0.659508
107910.7692-1.76916
1081010.5806-0.580558
109910.6135-1.61345
1101010.6836-0.683632
1111210.72751.27251
1121110.71650.283472
113910.5685-1.5685
1141110.75160.248383
1151210.871.12996
1161210.86461.13544
117710.8371-3.83715
1181210.74941.25058
1191210.84811.15189
1201210.8921.10803
1211010.8262-0.826181
1221510.76594.23413
1231010.8766-0.876621
1241510.79554.20452
1251010.7056-0.705562
1261510.74944.25058
127910.8284-1.82837
1281510.77144.22865
1291210.88761.11241
1301310.78232.21768
1311210.79111.20891
1321210.82731.17272
133810.7966-2.79657
134910.7977-1.79767
1351510.74614.25387
1361210.75051.24948
1371210.85361.14641
1381510.66174.3383
1391110.87660.123379
1401210.82621.17382
141610.7275-4.72749
1421410.86243.13763
1431210.80751.19246
1441210.86021.13983
1451210.83171.16834
1461110.86020.139827
1471210.77141.22865
1481210.78781.2122
1491210.79661.20343
1501210.87331.12667
151810.6902-2.69021
1521210.87331.12667
1531210.84261.15737
1541110.79330.206715
1551010.7768-0.776837
1561110.88870.111317
1571210.81521.18478
1581310.79882.20123
1591210.73081.26922
1601210.87771.12228
1611010.8218-0.821795
1621010.8481-0.848112
1631110.82620.173819
164810.9095-2.90952
1651210.71321.28676
166910.8777-1.87772
1671210.80431.19575
1681110.7220.27799
1691510.82294.17711
170810.87-2.87004
171810.7933-2.79328
1721110.81080.189171
1731110.81080.189171
1741110.85910.140923
1751310.76592.23413
176710.892-3.89197
1771210.80971.19027
178810.6398-2.63977
179810.767-2.76697
180410.7779-6.77793
1811110.8920.108027
1821010.8075-0.80754
183710.756-3.756
1841210.82621.17382
1851110.85360.146406
186910.7615-1.76149
1871010.7396-0.739555
188810.7494-2.74942
189810.7001-2.70008
1901110.81080.189171
1911210.68361.31637
1921010.8722-0.872235
1931010.7714-0.771354
1941210.79881.20123
195810.7966-2.79657
1961110.78230.21768
197810.7999-2.79986
1981010.8295-0.82947
1991410.89533.10474
200910.7714-1.77135
201910.7714-1.77135
2021010.8163-0.816312
2031310.75272.24729
2041210.79331.20672
2051310.68912.31089
206810.7505-2.75052
207310.8942-7.89417
208810.8371-2.83715
2091210.71871.28128
2101110.80750.19246
211910.7341-1.73407
2121210.76261.23742
2131210.83171.16834
2141210.7451.25496
2151010.8207-0.820698
2161310.87112.12886
217910.7176-1.71762
2181210.81631.18369
2191110.86240.137634
2201410.64093.35913
2211110.74390.256059
222910.8152-1.81522
2231210.89641.10364
224810.8064-2.80644
2251510.84814.15189
2261210.81521.18478
2271410.87663.12338
2281210.89091.10912
229910.8799-1.87991
230910.892-1.89197
2311310.76042.23961
2321310.75492.24509
2331510.68144.31856
2341110.57180.428215
235710.733-3.73298
2361010.7714-0.771354
2371110.72970.270314
2381410.7453.25496
2391410.76593.23413
2401310.72312.27689
2411210.79991.20014
242810.9095-2.90952
2431310.71872.28128
244910.7933-1.79328
2451210.85911.14092
2461310.78122.21878
2471110.82620.173819
2481110.76590.234128
2491310.7332.26702
2501210.73521.26483
2511210.79661.20343
2521010.8053-0.805347
253910.7626-1.76258
2541010.8426-0.842629
2551310.64532.35475
2561310.6422.35804
257910.7494-1.74942
2581110.64530.354747
2591210.71321.28676
260810.7439-2.74394
2611210.69131.30869
2621210.79991.20014
2631210.83821.16176
264910.767-1.76697
2651210.7791.22097
2661210.81741.18259
2671110.84260.157371
2681210.71321.28676
269610.8097-4.80973
270710.7407-3.74065
2711010.8043-0.80425
2721210.86241.13763
2731010.8064-0.806443
2741210.79331.20672
275910.8382-1.83824
276310.6507-7.65074

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.756 & 1.244 \tabularnewline
2 & 8 & 10.7407 & -2.74065 \tabularnewline
3 & 11 & 10.7538 & 0.24619 \tabularnewline
4 & 13 & 10.6354 & 2.36462 \tabularnewline
5 & 11 & 10.62 & 0.379967 \tabularnewline
6 & 10 & 10.7494 & -0.749424 \tabularnewline
7 & 7 & 10.7977 & -3.79767 \tabularnewline
8 & 10 & 10.7648 & -0.764775 \tabularnewline
9 & 15 & 10.7165 & 4.28347 \tabularnewline
10 & 12 & 10.6529 & 1.34707 \tabularnewline
11 & 12 & 10.7231 & 1.27689 \tabularnewline
12 & 10 & 10.6135 & -0.613454 \tabularnewline
13 & 10 & 10.7056 & -0.705562 \tabularnewline
14 & 14 & 10.7363 & 3.26373 \tabularnewline
15 & 6 & 10.6113 & -4.61126 \tabularnewline
16 & 12 & 10.7209 & 1.27909 \tabularnewline
17 & 14 & 10.7341 & 3.26593 \tabularnewline
18 & 11 & 10.6771 & 0.322947 \tabularnewline
19 & 8 & 10.6836 & -2.68363 \tabularnewline
20 & 12 & 10.6924 & 1.3076 \tabularnewline
21 & 15 & 10.6135 & 4.38655 \tabularnewline
22 & 13 & 10.7757 & 2.22426 \tabularnewline
23 & 11 & 10.7099 & 0.290052 \tabularnewline
24 & 12 & 10.7757 & 1.22426 \tabularnewline
25 & 7 & 10.7297 & -3.72969 \tabularnewline
26 & 11 & 10.7121 & 0.287858 \tabularnewline
27 & 7 & 10.8262 & -3.82618 \tabularnewline
28 & 12 & 10.767 & 1.23303 \tabularnewline
29 & 12 & 10.6902 & 1.30979 \tabularnewline
30 & 13 & 10.7253 & 2.2747 \tabularnewline
31 & 9 & 10.6551 & -1.65512 \tabularnewline
32 & 11 & 10.7297 & 0.270314 \tabularnewline
33 & 12 & 10.6705 & 1.32953 \tabularnewline
34 & 15 & 10.6858 & 4.31418 \tabularnewline
35 & 12 & 10.7099 & 1.29005 \tabularnewline
36 & 6 & 10.699 & -4.69898 \tabularnewline
37 & 5 & 10.7012 & -5.70118 \tabularnewline
38 & 13 & 10.7516 & 2.24838 \tabularnewline
39 & 11 & 10.6771 & 0.322947 \tabularnewline
40 & 6 & 10.7319 & -4.73188 \tabularnewline
41 & 12 & 10.6025 & 1.39751 \tabularnewline
42 & 10 & 10.7231 & -0.723107 \tabularnewline
43 & 6 & 10.7582 & -4.7582 \tabularnewline
44 & 12 & 10.7099 & 1.29005 \tabularnewline
45 & 11 & 10.7428 & 0.257156 \tabularnewline
46 & 6 & 10.7209 & -4.72091 \tabularnewline
47 & 12 & 10.7319 & 1.26812 \tabularnewline
48 & 12 & 10.6463 & 1.35365 \tabularnewline
49 & 8 & 10.7516 & -2.75162 \tabularnewline
50 & 10 & 10.7428 & -0.742844 \tabularnewline
51 & 11 & 10.7275 & 0.272507 \tabularnewline
52 & 7 & 10.62 & -3.62003 \tabularnewline
53 & 12 & 10.7121 & 1.28786 \tabularnewline
54 & 13 & 10.7385 & 2.26154 \tabularnewline
55 & 14 & 10.7648 & 3.23522 \tabularnewline
56 & 12 & 10.6946 & 1.3054 \tabularnewline
57 & 6 & 10.5981 & -4.5981 \tabularnewline
58 & 14 & 10.7867 & 3.21329 \tabularnewline
59 & 10 & 10.6485 & -0.648543 \tabularnewline
60 & 12 & 10.7648 & 1.23522 \tabularnewline
61 & 11 & 10.6771 & 0.322947 \tabularnewline
62 & 10 & 10.7472 & -0.747231 \tabularnewline
63 & 7 & 10.6398 & -3.63977 \tabularnewline
64 & 12 & 10.8218 & 1.17821 \tabularnewline
65 & 7 & 10.6749 & -3.67486 \tabularnewline
66 & 12 & 10.6727 & 1.32733 \tabularnewline
67 & 12 & 10.7165 & 1.28347 \tabularnewline
68 & 10 & 10.7582 & -0.758196 \tabularnewline
69 & 10 & 10.7911 & -0.791092 \tabularnewline
70 & 12 & 10.7407 & 1.25935 \tabularnewline
71 & 12 & 10.7428 & 1.25716 \tabularnewline
72 & 12 & 10.7231 & 1.27689 \tabularnewline
73 & 8 & 10.6661 & -2.66609 \tabularnewline
74 & 10 & 10.7933 & -0.793285 \tabularnewline
75 & 5 & 10.7494 & -5.74942 \tabularnewline
76 & 10 & 10.7582 & -0.758196 \tabularnewline
77 & 12 & 10.7494 & 1.25058 \tabularnewline
78 & 11 & 10.7626 & 0.237418 \tabularnewline
79 & 9 & 10.6902 & -1.69021 \tabularnewline
80 & 12 & 10.642 & 1.35804 \tabularnewline
81 & 11 & 10.7034 & 0.296631 \tabularnewline
82 & 10 & 10.767 & -0.766968 \tabularnewline
83 & 12 & 10.7121 & 1.28786 \tabularnewline
84 & 10 & 10.5674 & -0.567399 \tabularnewline
85 & 9 & 10.699 & -1.69898 \tabularnewline
86 & 11 & 10.7319 & 0.268121 \tabularnewline
87 & 12 & 10.7187 & 1.28128 \tabularnewline
88 & 7 & 10.7231 & -3.72311 \tabularnewline
89 & 11 & 10.6617 & 0.338299 \tabularnewline
90 & 12 & 10.7626 & 1.23742 \tabularnewline
91 & 6 & 10.7494 & -4.74942 \tabularnewline
92 & 9 & 10.5959 & -1.59591 \tabularnewline
93 & 15 & 10.6902 & 4.30979 \tabularnewline
94 & 10 & 10.6661 & -0.666087 \tabularnewline
95 & 11 & 10.642 & 0.358036 \tabularnewline
96 & 12 & 10.6705 & 1.32953 \tabularnewline
97 & 12 & 10.6332 & 1.36681 \tabularnewline
98 & 12 & 10.7231 & 1.27689 \tabularnewline
99 & 11 & 10.7714 & 0.228646 \tabularnewline
100 & 9 & 10.6463 & -1.64635 \tabularnewline
101 & 11 & 10.7078 & 0.292245 \tabularnewline
102 & 12 & 10.699 & 1.30102 \tabularnewline
103 & 12 & 10.6551 & 1.34488 \tabularnewline
104 & 14 & 10.6836 & 3.31637 \tabularnewline
105 & 8 & 10.7845 & -2.78451 \tabularnewline
106 & 10 & 10.6595 & -0.659508 \tabularnewline
107 & 9 & 10.7692 & -1.76916 \tabularnewline
108 & 10 & 10.5806 & -0.580558 \tabularnewline
109 & 9 & 10.6135 & -1.61345 \tabularnewline
110 & 10 & 10.6836 & -0.683632 \tabularnewline
111 & 12 & 10.7275 & 1.27251 \tabularnewline
112 & 11 & 10.7165 & 0.283472 \tabularnewline
113 & 9 & 10.5685 & -1.5685 \tabularnewline
114 & 11 & 10.7516 & 0.248383 \tabularnewline
115 & 12 & 10.87 & 1.12996 \tabularnewline
116 & 12 & 10.8646 & 1.13544 \tabularnewline
117 & 7 & 10.8371 & -3.83715 \tabularnewline
118 & 12 & 10.7494 & 1.25058 \tabularnewline
119 & 12 & 10.8481 & 1.15189 \tabularnewline
120 & 12 & 10.892 & 1.10803 \tabularnewline
121 & 10 & 10.8262 & -0.826181 \tabularnewline
122 & 15 & 10.7659 & 4.23413 \tabularnewline
123 & 10 & 10.8766 & -0.876621 \tabularnewline
124 & 15 & 10.7955 & 4.20452 \tabularnewline
125 & 10 & 10.7056 & -0.705562 \tabularnewline
126 & 15 & 10.7494 & 4.25058 \tabularnewline
127 & 9 & 10.8284 & -1.82837 \tabularnewline
128 & 15 & 10.7714 & 4.22865 \tabularnewline
129 & 12 & 10.8876 & 1.11241 \tabularnewline
130 & 13 & 10.7823 & 2.21768 \tabularnewline
131 & 12 & 10.7911 & 1.20891 \tabularnewline
132 & 12 & 10.8273 & 1.17272 \tabularnewline
133 & 8 & 10.7966 & -2.79657 \tabularnewline
134 & 9 & 10.7977 & -1.79767 \tabularnewline
135 & 15 & 10.7461 & 4.25387 \tabularnewline
136 & 12 & 10.7505 & 1.24948 \tabularnewline
137 & 12 & 10.8536 & 1.14641 \tabularnewline
138 & 15 & 10.6617 & 4.3383 \tabularnewline
139 & 11 & 10.8766 & 0.123379 \tabularnewline
140 & 12 & 10.8262 & 1.17382 \tabularnewline
141 & 6 & 10.7275 & -4.72749 \tabularnewline
142 & 14 & 10.8624 & 3.13763 \tabularnewline
143 & 12 & 10.8075 & 1.19246 \tabularnewline
144 & 12 & 10.8602 & 1.13983 \tabularnewline
145 & 12 & 10.8317 & 1.16834 \tabularnewline
146 & 11 & 10.8602 & 0.139827 \tabularnewline
147 & 12 & 10.7714 & 1.22865 \tabularnewline
148 & 12 & 10.7878 & 1.2122 \tabularnewline
149 & 12 & 10.7966 & 1.20343 \tabularnewline
150 & 12 & 10.8733 & 1.12667 \tabularnewline
151 & 8 & 10.6902 & -2.69021 \tabularnewline
152 & 12 & 10.8733 & 1.12667 \tabularnewline
153 & 12 & 10.8426 & 1.15737 \tabularnewline
154 & 11 & 10.7933 & 0.206715 \tabularnewline
155 & 10 & 10.7768 & -0.776837 \tabularnewline
156 & 11 & 10.8887 & 0.111317 \tabularnewline
157 & 12 & 10.8152 & 1.18478 \tabularnewline
158 & 13 & 10.7988 & 2.20123 \tabularnewline
159 & 12 & 10.7308 & 1.26922 \tabularnewline
160 & 12 & 10.8777 & 1.12228 \tabularnewline
161 & 10 & 10.8218 & -0.821795 \tabularnewline
162 & 10 & 10.8481 & -0.848112 \tabularnewline
163 & 11 & 10.8262 & 0.173819 \tabularnewline
164 & 8 & 10.9095 & -2.90952 \tabularnewline
165 & 12 & 10.7132 & 1.28676 \tabularnewline
166 & 9 & 10.8777 & -1.87772 \tabularnewline
167 & 12 & 10.8043 & 1.19575 \tabularnewline
168 & 11 & 10.722 & 0.27799 \tabularnewline
169 & 15 & 10.8229 & 4.17711 \tabularnewline
170 & 8 & 10.87 & -2.87004 \tabularnewline
171 & 8 & 10.7933 & -2.79328 \tabularnewline
172 & 11 & 10.8108 & 0.189171 \tabularnewline
173 & 11 & 10.8108 & 0.189171 \tabularnewline
174 & 11 & 10.8591 & 0.140923 \tabularnewline
175 & 13 & 10.7659 & 2.23413 \tabularnewline
176 & 7 & 10.892 & -3.89197 \tabularnewline
177 & 12 & 10.8097 & 1.19027 \tabularnewline
178 & 8 & 10.6398 & -2.63977 \tabularnewline
179 & 8 & 10.767 & -2.76697 \tabularnewline
180 & 4 & 10.7779 & -6.77793 \tabularnewline
181 & 11 & 10.892 & 0.108027 \tabularnewline
182 & 10 & 10.8075 & -0.80754 \tabularnewline
183 & 7 & 10.756 & -3.756 \tabularnewline
184 & 12 & 10.8262 & 1.17382 \tabularnewline
185 & 11 & 10.8536 & 0.146406 \tabularnewline
186 & 9 & 10.7615 & -1.76149 \tabularnewline
187 & 10 & 10.7396 & -0.739555 \tabularnewline
188 & 8 & 10.7494 & -2.74942 \tabularnewline
189 & 8 & 10.7001 & -2.70008 \tabularnewline
190 & 11 & 10.8108 & 0.189171 \tabularnewline
191 & 12 & 10.6836 & 1.31637 \tabularnewline
192 & 10 & 10.8722 & -0.872235 \tabularnewline
193 & 10 & 10.7714 & -0.771354 \tabularnewline
194 & 12 & 10.7988 & 1.20123 \tabularnewline
195 & 8 & 10.7966 & -2.79657 \tabularnewline
196 & 11 & 10.7823 & 0.21768 \tabularnewline
197 & 8 & 10.7999 & -2.79986 \tabularnewline
198 & 10 & 10.8295 & -0.82947 \tabularnewline
199 & 14 & 10.8953 & 3.10474 \tabularnewline
200 & 9 & 10.7714 & -1.77135 \tabularnewline
201 & 9 & 10.7714 & -1.77135 \tabularnewline
202 & 10 & 10.8163 & -0.816312 \tabularnewline
203 & 13 & 10.7527 & 2.24729 \tabularnewline
204 & 12 & 10.7933 & 1.20672 \tabularnewline
205 & 13 & 10.6891 & 2.31089 \tabularnewline
206 & 8 & 10.7505 & -2.75052 \tabularnewline
207 & 3 & 10.8942 & -7.89417 \tabularnewline
208 & 8 & 10.8371 & -2.83715 \tabularnewline
209 & 12 & 10.7187 & 1.28128 \tabularnewline
210 & 11 & 10.8075 & 0.19246 \tabularnewline
211 & 9 & 10.7341 & -1.73407 \tabularnewline
212 & 12 & 10.7626 & 1.23742 \tabularnewline
213 & 12 & 10.8317 & 1.16834 \tabularnewline
214 & 12 & 10.745 & 1.25496 \tabularnewline
215 & 10 & 10.8207 & -0.820698 \tabularnewline
216 & 13 & 10.8711 & 2.12886 \tabularnewline
217 & 9 & 10.7176 & -1.71762 \tabularnewline
218 & 12 & 10.8163 & 1.18369 \tabularnewline
219 & 11 & 10.8624 & 0.137634 \tabularnewline
220 & 14 & 10.6409 & 3.35913 \tabularnewline
221 & 11 & 10.7439 & 0.256059 \tabularnewline
222 & 9 & 10.8152 & -1.81522 \tabularnewline
223 & 12 & 10.8964 & 1.10364 \tabularnewline
224 & 8 & 10.8064 & -2.80644 \tabularnewline
225 & 15 & 10.8481 & 4.15189 \tabularnewline
226 & 12 & 10.8152 & 1.18478 \tabularnewline
227 & 14 & 10.8766 & 3.12338 \tabularnewline
228 & 12 & 10.8909 & 1.10912 \tabularnewline
229 & 9 & 10.8799 & -1.87991 \tabularnewline
230 & 9 & 10.892 & -1.89197 \tabularnewline
231 & 13 & 10.7604 & 2.23961 \tabularnewline
232 & 13 & 10.7549 & 2.24509 \tabularnewline
233 & 15 & 10.6814 & 4.31856 \tabularnewline
234 & 11 & 10.5718 & 0.428215 \tabularnewline
235 & 7 & 10.733 & -3.73298 \tabularnewline
236 & 10 & 10.7714 & -0.771354 \tabularnewline
237 & 11 & 10.7297 & 0.270314 \tabularnewline
238 & 14 & 10.745 & 3.25496 \tabularnewline
239 & 14 & 10.7659 & 3.23413 \tabularnewline
240 & 13 & 10.7231 & 2.27689 \tabularnewline
241 & 12 & 10.7999 & 1.20014 \tabularnewline
242 & 8 & 10.9095 & -2.90952 \tabularnewline
243 & 13 & 10.7187 & 2.28128 \tabularnewline
244 & 9 & 10.7933 & -1.79328 \tabularnewline
245 & 12 & 10.8591 & 1.14092 \tabularnewline
246 & 13 & 10.7812 & 2.21878 \tabularnewline
247 & 11 & 10.8262 & 0.173819 \tabularnewline
248 & 11 & 10.7659 & 0.234128 \tabularnewline
249 & 13 & 10.733 & 2.26702 \tabularnewline
250 & 12 & 10.7352 & 1.26483 \tabularnewline
251 & 12 & 10.7966 & 1.20343 \tabularnewline
252 & 10 & 10.8053 & -0.805347 \tabularnewline
253 & 9 & 10.7626 & -1.76258 \tabularnewline
254 & 10 & 10.8426 & -0.842629 \tabularnewline
255 & 13 & 10.6453 & 2.35475 \tabularnewline
256 & 13 & 10.642 & 2.35804 \tabularnewline
257 & 9 & 10.7494 & -1.74942 \tabularnewline
258 & 11 & 10.6453 & 0.354747 \tabularnewline
259 & 12 & 10.7132 & 1.28676 \tabularnewline
260 & 8 & 10.7439 & -2.74394 \tabularnewline
261 & 12 & 10.6913 & 1.30869 \tabularnewline
262 & 12 & 10.7999 & 1.20014 \tabularnewline
263 & 12 & 10.8382 & 1.16176 \tabularnewline
264 & 9 & 10.767 & -1.76697 \tabularnewline
265 & 12 & 10.779 & 1.22097 \tabularnewline
266 & 12 & 10.8174 & 1.18259 \tabularnewline
267 & 11 & 10.8426 & 0.157371 \tabularnewline
268 & 12 & 10.7132 & 1.28676 \tabularnewline
269 & 6 & 10.8097 & -4.80973 \tabularnewline
270 & 7 & 10.7407 & -3.74065 \tabularnewline
271 & 10 & 10.8043 & -0.80425 \tabularnewline
272 & 12 & 10.8624 & 1.13763 \tabularnewline
273 & 10 & 10.8064 & -0.806443 \tabularnewline
274 & 12 & 10.7933 & 1.20672 \tabularnewline
275 & 9 & 10.8382 & -1.83824 \tabularnewline
276 & 3 & 10.6507 & -7.65074 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&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[/C][C]10.756[/C][C]1.244[/C][/ROW]
[ROW][C]2[/C][C]8[/C][C]10.7407[/C][C]-2.74065[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]10.7538[/C][C]0.24619[/C][/ROW]
[ROW][C]4[/C][C]13[/C][C]10.6354[/C][C]2.36462[/C][/ROW]
[ROW][C]5[/C][C]11[/C][C]10.62[/C][C]0.379967[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]10.7494[/C][C]-0.749424[/C][/ROW]
[ROW][C]7[/C][C]7[/C][C]10.7977[/C][C]-3.79767[/C][/ROW]
[ROW][C]8[/C][C]10[/C][C]10.7648[/C][C]-0.764775[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]10.7165[/C][C]4.28347[/C][/ROW]
[ROW][C]10[/C][C]12[/C][C]10.6529[/C][C]1.34707[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]10.7231[/C][C]1.27689[/C][/ROW]
[ROW][C]12[/C][C]10[/C][C]10.6135[/C][C]-0.613454[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]10.7056[/C][C]-0.705562[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]10.7363[/C][C]3.26373[/C][/ROW]
[ROW][C]15[/C][C]6[/C][C]10.6113[/C][C]-4.61126[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.7209[/C][C]1.27909[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]10.7341[/C][C]3.26593[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.6771[/C][C]0.322947[/C][/ROW]
[ROW][C]19[/C][C]8[/C][C]10.6836[/C][C]-2.68363[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]10.6924[/C][C]1.3076[/C][/ROW]
[ROW][C]21[/C][C]15[/C][C]10.6135[/C][C]4.38655[/C][/ROW]
[ROW][C]22[/C][C]13[/C][C]10.7757[/C][C]2.22426[/C][/ROW]
[ROW][C]23[/C][C]11[/C][C]10.7099[/C][C]0.290052[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]10.7757[/C][C]1.22426[/C][/ROW]
[ROW][C]25[/C][C]7[/C][C]10.7297[/C][C]-3.72969[/C][/ROW]
[ROW][C]26[/C][C]11[/C][C]10.7121[/C][C]0.287858[/C][/ROW]
[ROW][C]27[/C][C]7[/C][C]10.8262[/C][C]-3.82618[/C][/ROW]
[ROW][C]28[/C][C]12[/C][C]10.767[/C][C]1.23303[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]10.6902[/C][C]1.30979[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]10.7253[/C][C]2.2747[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]10.6551[/C][C]-1.65512[/C][/ROW]
[ROW][C]32[/C][C]11[/C][C]10.7297[/C][C]0.270314[/C][/ROW]
[ROW][C]33[/C][C]12[/C][C]10.6705[/C][C]1.32953[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]10.6858[/C][C]4.31418[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.7099[/C][C]1.29005[/C][/ROW]
[ROW][C]36[/C][C]6[/C][C]10.699[/C][C]-4.69898[/C][/ROW]
[ROW][C]37[/C][C]5[/C][C]10.7012[/C][C]-5.70118[/C][/ROW]
[ROW][C]38[/C][C]13[/C][C]10.7516[/C][C]2.24838[/C][/ROW]
[ROW][C]39[/C][C]11[/C][C]10.6771[/C][C]0.322947[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]10.7319[/C][C]-4.73188[/C][/ROW]
[ROW][C]41[/C][C]12[/C][C]10.6025[/C][C]1.39751[/C][/ROW]
[ROW][C]42[/C][C]10[/C][C]10.7231[/C][C]-0.723107[/C][/ROW]
[ROW][C]43[/C][C]6[/C][C]10.7582[/C][C]-4.7582[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]10.7099[/C][C]1.29005[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]10.7428[/C][C]0.257156[/C][/ROW]
[ROW][C]46[/C][C]6[/C][C]10.7209[/C][C]-4.72091[/C][/ROW]
[ROW][C]47[/C][C]12[/C][C]10.7319[/C][C]1.26812[/C][/ROW]
[ROW][C]48[/C][C]12[/C][C]10.6463[/C][C]1.35365[/C][/ROW]
[ROW][C]49[/C][C]8[/C][C]10.7516[/C][C]-2.75162[/C][/ROW]
[ROW][C]50[/C][C]10[/C][C]10.7428[/C][C]-0.742844[/C][/ROW]
[ROW][C]51[/C][C]11[/C][C]10.7275[/C][C]0.272507[/C][/ROW]
[ROW][C]52[/C][C]7[/C][C]10.62[/C][C]-3.62003[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]10.7121[/C][C]1.28786[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]10.7385[/C][C]2.26154[/C][/ROW]
[ROW][C]55[/C][C]14[/C][C]10.7648[/C][C]3.23522[/C][/ROW]
[ROW][C]56[/C][C]12[/C][C]10.6946[/C][C]1.3054[/C][/ROW]
[ROW][C]57[/C][C]6[/C][C]10.5981[/C][C]-4.5981[/C][/ROW]
[ROW][C]58[/C][C]14[/C][C]10.7867[/C][C]3.21329[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]10.6485[/C][C]-0.648543[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]10.7648[/C][C]1.23522[/C][/ROW]
[ROW][C]61[/C][C]11[/C][C]10.6771[/C][C]0.322947[/C][/ROW]
[ROW][C]62[/C][C]10[/C][C]10.7472[/C][C]-0.747231[/C][/ROW]
[ROW][C]63[/C][C]7[/C][C]10.6398[/C][C]-3.63977[/C][/ROW]
[ROW][C]64[/C][C]12[/C][C]10.8218[/C][C]1.17821[/C][/ROW]
[ROW][C]65[/C][C]7[/C][C]10.6749[/C][C]-3.67486[/C][/ROW]
[ROW][C]66[/C][C]12[/C][C]10.6727[/C][C]1.32733[/C][/ROW]
[ROW][C]67[/C][C]12[/C][C]10.7165[/C][C]1.28347[/C][/ROW]
[ROW][C]68[/C][C]10[/C][C]10.7582[/C][C]-0.758196[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]10.7911[/C][C]-0.791092[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]10.7407[/C][C]1.25935[/C][/ROW]
[ROW][C]71[/C][C]12[/C][C]10.7428[/C][C]1.25716[/C][/ROW]
[ROW][C]72[/C][C]12[/C][C]10.7231[/C][C]1.27689[/C][/ROW]
[ROW][C]73[/C][C]8[/C][C]10.6661[/C][C]-2.66609[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]10.7933[/C][C]-0.793285[/C][/ROW]
[ROW][C]75[/C][C]5[/C][C]10.7494[/C][C]-5.74942[/C][/ROW]
[ROW][C]76[/C][C]10[/C][C]10.7582[/C][C]-0.758196[/C][/ROW]
[ROW][C]77[/C][C]12[/C][C]10.7494[/C][C]1.25058[/C][/ROW]
[ROW][C]78[/C][C]11[/C][C]10.7626[/C][C]0.237418[/C][/ROW]
[ROW][C]79[/C][C]9[/C][C]10.6902[/C][C]-1.69021[/C][/ROW]
[ROW][C]80[/C][C]12[/C][C]10.642[/C][C]1.35804[/C][/ROW]
[ROW][C]81[/C][C]11[/C][C]10.7034[/C][C]0.296631[/C][/ROW]
[ROW][C]82[/C][C]10[/C][C]10.767[/C][C]-0.766968[/C][/ROW]
[ROW][C]83[/C][C]12[/C][C]10.7121[/C][C]1.28786[/C][/ROW]
[ROW][C]84[/C][C]10[/C][C]10.5674[/C][C]-0.567399[/C][/ROW]
[ROW][C]85[/C][C]9[/C][C]10.699[/C][C]-1.69898[/C][/ROW]
[ROW][C]86[/C][C]11[/C][C]10.7319[/C][C]0.268121[/C][/ROW]
[ROW][C]87[/C][C]12[/C][C]10.7187[/C][C]1.28128[/C][/ROW]
[ROW][C]88[/C][C]7[/C][C]10.7231[/C][C]-3.72311[/C][/ROW]
[ROW][C]89[/C][C]11[/C][C]10.6617[/C][C]0.338299[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]10.7626[/C][C]1.23742[/C][/ROW]
[ROW][C]91[/C][C]6[/C][C]10.7494[/C][C]-4.74942[/C][/ROW]
[ROW][C]92[/C][C]9[/C][C]10.5959[/C][C]-1.59591[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]10.6902[/C][C]4.30979[/C][/ROW]
[ROW][C]94[/C][C]10[/C][C]10.6661[/C][C]-0.666087[/C][/ROW]
[ROW][C]95[/C][C]11[/C][C]10.642[/C][C]0.358036[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]10.6705[/C][C]1.32953[/C][/ROW]
[ROW][C]97[/C][C]12[/C][C]10.6332[/C][C]1.36681[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]10.7231[/C][C]1.27689[/C][/ROW]
[ROW][C]99[/C][C]11[/C][C]10.7714[/C][C]0.228646[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]10.6463[/C][C]-1.64635[/C][/ROW]
[ROW][C]101[/C][C]11[/C][C]10.7078[/C][C]0.292245[/C][/ROW]
[ROW][C]102[/C][C]12[/C][C]10.699[/C][C]1.30102[/C][/ROW]
[ROW][C]103[/C][C]12[/C][C]10.6551[/C][C]1.34488[/C][/ROW]
[ROW][C]104[/C][C]14[/C][C]10.6836[/C][C]3.31637[/C][/ROW]
[ROW][C]105[/C][C]8[/C][C]10.7845[/C][C]-2.78451[/C][/ROW]
[ROW][C]106[/C][C]10[/C][C]10.6595[/C][C]-0.659508[/C][/ROW]
[ROW][C]107[/C][C]9[/C][C]10.7692[/C][C]-1.76916[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]10.5806[/C][C]-0.580558[/C][/ROW]
[ROW][C]109[/C][C]9[/C][C]10.6135[/C][C]-1.61345[/C][/ROW]
[ROW][C]110[/C][C]10[/C][C]10.6836[/C][C]-0.683632[/C][/ROW]
[ROW][C]111[/C][C]12[/C][C]10.7275[/C][C]1.27251[/C][/ROW]
[ROW][C]112[/C][C]11[/C][C]10.7165[/C][C]0.283472[/C][/ROW]
[ROW][C]113[/C][C]9[/C][C]10.5685[/C][C]-1.5685[/C][/ROW]
[ROW][C]114[/C][C]11[/C][C]10.7516[/C][C]0.248383[/C][/ROW]
[ROW][C]115[/C][C]12[/C][C]10.87[/C][C]1.12996[/C][/ROW]
[ROW][C]116[/C][C]12[/C][C]10.8646[/C][C]1.13544[/C][/ROW]
[ROW][C]117[/C][C]7[/C][C]10.8371[/C][C]-3.83715[/C][/ROW]
[ROW][C]118[/C][C]12[/C][C]10.7494[/C][C]1.25058[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]10.8481[/C][C]1.15189[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]10.892[/C][C]1.10803[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.8262[/C][C]-0.826181[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]10.7659[/C][C]4.23413[/C][/ROW]
[ROW][C]123[/C][C]10[/C][C]10.8766[/C][C]-0.876621[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]10.7955[/C][C]4.20452[/C][/ROW]
[ROW][C]125[/C][C]10[/C][C]10.7056[/C][C]-0.705562[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]10.7494[/C][C]4.25058[/C][/ROW]
[ROW][C]127[/C][C]9[/C][C]10.8284[/C][C]-1.82837[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]10.7714[/C][C]4.22865[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]10.8876[/C][C]1.11241[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]10.7823[/C][C]2.21768[/C][/ROW]
[ROW][C]131[/C][C]12[/C][C]10.7911[/C][C]1.20891[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]10.8273[/C][C]1.17272[/C][/ROW]
[ROW][C]133[/C][C]8[/C][C]10.7966[/C][C]-2.79657[/C][/ROW]
[ROW][C]134[/C][C]9[/C][C]10.7977[/C][C]-1.79767[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]10.7461[/C][C]4.25387[/C][/ROW]
[ROW][C]136[/C][C]12[/C][C]10.7505[/C][C]1.24948[/C][/ROW]
[ROW][C]137[/C][C]12[/C][C]10.8536[/C][C]1.14641[/C][/ROW]
[ROW][C]138[/C][C]15[/C][C]10.6617[/C][C]4.3383[/C][/ROW]
[ROW][C]139[/C][C]11[/C][C]10.8766[/C][C]0.123379[/C][/ROW]
[ROW][C]140[/C][C]12[/C][C]10.8262[/C][C]1.17382[/C][/ROW]
[ROW][C]141[/C][C]6[/C][C]10.7275[/C][C]-4.72749[/C][/ROW]
[ROW][C]142[/C][C]14[/C][C]10.8624[/C][C]3.13763[/C][/ROW]
[ROW][C]143[/C][C]12[/C][C]10.8075[/C][C]1.19246[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]10.8602[/C][C]1.13983[/C][/ROW]
[ROW][C]145[/C][C]12[/C][C]10.8317[/C][C]1.16834[/C][/ROW]
[ROW][C]146[/C][C]11[/C][C]10.8602[/C][C]0.139827[/C][/ROW]
[ROW][C]147[/C][C]12[/C][C]10.7714[/C][C]1.22865[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]10.7878[/C][C]1.2122[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]10.7966[/C][C]1.20343[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]10.8733[/C][C]1.12667[/C][/ROW]
[ROW][C]151[/C][C]8[/C][C]10.6902[/C][C]-2.69021[/C][/ROW]
[ROW][C]152[/C][C]12[/C][C]10.8733[/C][C]1.12667[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]10.8426[/C][C]1.15737[/C][/ROW]
[ROW][C]154[/C][C]11[/C][C]10.7933[/C][C]0.206715[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]10.7768[/C][C]-0.776837[/C][/ROW]
[ROW][C]156[/C][C]11[/C][C]10.8887[/C][C]0.111317[/C][/ROW]
[ROW][C]157[/C][C]12[/C][C]10.8152[/C][C]1.18478[/C][/ROW]
[ROW][C]158[/C][C]13[/C][C]10.7988[/C][C]2.20123[/C][/ROW]
[ROW][C]159[/C][C]12[/C][C]10.7308[/C][C]1.26922[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]10.8777[/C][C]1.12228[/C][/ROW]
[ROW][C]161[/C][C]10[/C][C]10.8218[/C][C]-0.821795[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]10.8481[/C][C]-0.848112[/C][/ROW]
[ROW][C]163[/C][C]11[/C][C]10.8262[/C][C]0.173819[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]10.9095[/C][C]-2.90952[/C][/ROW]
[ROW][C]165[/C][C]12[/C][C]10.7132[/C][C]1.28676[/C][/ROW]
[ROW][C]166[/C][C]9[/C][C]10.8777[/C][C]-1.87772[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]10.8043[/C][C]1.19575[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]10.722[/C][C]0.27799[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]10.8229[/C][C]4.17711[/C][/ROW]
[ROW][C]170[/C][C]8[/C][C]10.87[/C][C]-2.87004[/C][/ROW]
[ROW][C]171[/C][C]8[/C][C]10.7933[/C][C]-2.79328[/C][/ROW]
[ROW][C]172[/C][C]11[/C][C]10.8108[/C][C]0.189171[/C][/ROW]
[ROW][C]173[/C][C]11[/C][C]10.8108[/C][C]0.189171[/C][/ROW]
[ROW][C]174[/C][C]11[/C][C]10.8591[/C][C]0.140923[/C][/ROW]
[ROW][C]175[/C][C]13[/C][C]10.7659[/C][C]2.23413[/C][/ROW]
[ROW][C]176[/C][C]7[/C][C]10.892[/C][C]-3.89197[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]10.8097[/C][C]1.19027[/C][/ROW]
[ROW][C]178[/C][C]8[/C][C]10.6398[/C][C]-2.63977[/C][/ROW]
[ROW][C]179[/C][C]8[/C][C]10.767[/C][C]-2.76697[/C][/ROW]
[ROW][C]180[/C][C]4[/C][C]10.7779[/C][C]-6.77793[/C][/ROW]
[ROW][C]181[/C][C]11[/C][C]10.892[/C][C]0.108027[/C][/ROW]
[ROW][C]182[/C][C]10[/C][C]10.8075[/C][C]-0.80754[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]10.756[/C][C]-3.756[/C][/ROW]
[ROW][C]184[/C][C]12[/C][C]10.8262[/C][C]1.17382[/C][/ROW]
[ROW][C]185[/C][C]11[/C][C]10.8536[/C][C]0.146406[/C][/ROW]
[ROW][C]186[/C][C]9[/C][C]10.7615[/C][C]-1.76149[/C][/ROW]
[ROW][C]187[/C][C]10[/C][C]10.7396[/C][C]-0.739555[/C][/ROW]
[ROW][C]188[/C][C]8[/C][C]10.7494[/C][C]-2.74942[/C][/ROW]
[ROW][C]189[/C][C]8[/C][C]10.7001[/C][C]-2.70008[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.8108[/C][C]0.189171[/C][/ROW]
[ROW][C]191[/C][C]12[/C][C]10.6836[/C][C]1.31637[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]10.8722[/C][C]-0.872235[/C][/ROW]
[ROW][C]193[/C][C]10[/C][C]10.7714[/C][C]-0.771354[/C][/ROW]
[ROW][C]194[/C][C]12[/C][C]10.7988[/C][C]1.20123[/C][/ROW]
[ROW][C]195[/C][C]8[/C][C]10.7966[/C][C]-2.79657[/C][/ROW]
[ROW][C]196[/C][C]11[/C][C]10.7823[/C][C]0.21768[/C][/ROW]
[ROW][C]197[/C][C]8[/C][C]10.7999[/C][C]-2.79986[/C][/ROW]
[ROW][C]198[/C][C]10[/C][C]10.8295[/C][C]-0.82947[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]10.8953[/C][C]3.10474[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]10.7714[/C][C]-1.77135[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]10.7714[/C][C]-1.77135[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]10.8163[/C][C]-0.816312[/C][/ROW]
[ROW][C]203[/C][C]13[/C][C]10.7527[/C][C]2.24729[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]10.7933[/C][C]1.20672[/C][/ROW]
[ROW][C]205[/C][C]13[/C][C]10.6891[/C][C]2.31089[/C][/ROW]
[ROW][C]206[/C][C]8[/C][C]10.7505[/C][C]-2.75052[/C][/ROW]
[ROW][C]207[/C][C]3[/C][C]10.8942[/C][C]-7.89417[/C][/ROW]
[ROW][C]208[/C][C]8[/C][C]10.8371[/C][C]-2.83715[/C][/ROW]
[ROW][C]209[/C][C]12[/C][C]10.7187[/C][C]1.28128[/C][/ROW]
[ROW][C]210[/C][C]11[/C][C]10.8075[/C][C]0.19246[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]10.7341[/C][C]-1.73407[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]10.7626[/C][C]1.23742[/C][/ROW]
[ROW][C]213[/C][C]12[/C][C]10.8317[/C][C]1.16834[/C][/ROW]
[ROW][C]214[/C][C]12[/C][C]10.745[/C][C]1.25496[/C][/ROW]
[ROW][C]215[/C][C]10[/C][C]10.8207[/C][C]-0.820698[/C][/ROW]
[ROW][C]216[/C][C]13[/C][C]10.8711[/C][C]2.12886[/C][/ROW]
[ROW][C]217[/C][C]9[/C][C]10.7176[/C][C]-1.71762[/C][/ROW]
[ROW][C]218[/C][C]12[/C][C]10.8163[/C][C]1.18369[/C][/ROW]
[ROW][C]219[/C][C]11[/C][C]10.8624[/C][C]0.137634[/C][/ROW]
[ROW][C]220[/C][C]14[/C][C]10.6409[/C][C]3.35913[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]10.7439[/C][C]0.256059[/C][/ROW]
[ROW][C]222[/C][C]9[/C][C]10.8152[/C][C]-1.81522[/C][/ROW]
[ROW][C]223[/C][C]12[/C][C]10.8964[/C][C]1.10364[/C][/ROW]
[ROW][C]224[/C][C]8[/C][C]10.8064[/C][C]-2.80644[/C][/ROW]
[ROW][C]225[/C][C]15[/C][C]10.8481[/C][C]4.15189[/C][/ROW]
[ROW][C]226[/C][C]12[/C][C]10.8152[/C][C]1.18478[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]10.8766[/C][C]3.12338[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]10.8909[/C][C]1.10912[/C][/ROW]
[ROW][C]229[/C][C]9[/C][C]10.8799[/C][C]-1.87991[/C][/ROW]
[ROW][C]230[/C][C]9[/C][C]10.892[/C][C]-1.89197[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]10.7604[/C][C]2.23961[/C][/ROW]
[ROW][C]232[/C][C]13[/C][C]10.7549[/C][C]2.24509[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]10.6814[/C][C]4.31856[/C][/ROW]
[ROW][C]234[/C][C]11[/C][C]10.5718[/C][C]0.428215[/C][/ROW]
[ROW][C]235[/C][C]7[/C][C]10.733[/C][C]-3.73298[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]10.7714[/C][C]-0.771354[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]10.7297[/C][C]0.270314[/C][/ROW]
[ROW][C]238[/C][C]14[/C][C]10.745[/C][C]3.25496[/C][/ROW]
[ROW][C]239[/C][C]14[/C][C]10.7659[/C][C]3.23413[/C][/ROW]
[ROW][C]240[/C][C]13[/C][C]10.7231[/C][C]2.27689[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]10.7999[/C][C]1.20014[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.9095[/C][C]-2.90952[/C][/ROW]
[ROW][C]243[/C][C]13[/C][C]10.7187[/C][C]2.28128[/C][/ROW]
[ROW][C]244[/C][C]9[/C][C]10.7933[/C][C]-1.79328[/C][/ROW]
[ROW][C]245[/C][C]12[/C][C]10.8591[/C][C]1.14092[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]10.7812[/C][C]2.21878[/C][/ROW]
[ROW][C]247[/C][C]11[/C][C]10.8262[/C][C]0.173819[/C][/ROW]
[ROW][C]248[/C][C]11[/C][C]10.7659[/C][C]0.234128[/C][/ROW]
[ROW][C]249[/C][C]13[/C][C]10.733[/C][C]2.26702[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]10.7352[/C][C]1.26483[/C][/ROW]
[ROW][C]251[/C][C]12[/C][C]10.7966[/C][C]1.20343[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]10.8053[/C][C]-0.805347[/C][/ROW]
[ROW][C]253[/C][C]9[/C][C]10.7626[/C][C]-1.76258[/C][/ROW]
[ROW][C]254[/C][C]10[/C][C]10.8426[/C][C]-0.842629[/C][/ROW]
[ROW][C]255[/C][C]13[/C][C]10.6453[/C][C]2.35475[/C][/ROW]
[ROW][C]256[/C][C]13[/C][C]10.642[/C][C]2.35804[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.7494[/C][C]-1.74942[/C][/ROW]
[ROW][C]258[/C][C]11[/C][C]10.6453[/C][C]0.354747[/C][/ROW]
[ROW][C]259[/C][C]12[/C][C]10.7132[/C][C]1.28676[/C][/ROW]
[ROW][C]260[/C][C]8[/C][C]10.7439[/C][C]-2.74394[/C][/ROW]
[ROW][C]261[/C][C]12[/C][C]10.6913[/C][C]1.30869[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]10.7999[/C][C]1.20014[/C][/ROW]
[ROW][C]263[/C][C]12[/C][C]10.8382[/C][C]1.16176[/C][/ROW]
[ROW][C]264[/C][C]9[/C][C]10.767[/C][C]-1.76697[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]10.779[/C][C]1.22097[/C][/ROW]
[ROW][C]266[/C][C]12[/C][C]10.8174[/C][C]1.18259[/C][/ROW]
[ROW][C]267[/C][C]11[/C][C]10.8426[/C][C]0.157371[/C][/ROW]
[ROW][C]268[/C][C]12[/C][C]10.7132[/C][C]1.28676[/C][/ROW]
[ROW][C]269[/C][C]6[/C][C]10.8097[/C][C]-4.80973[/C][/ROW]
[ROW][C]270[/C][C]7[/C][C]10.7407[/C][C]-3.74065[/C][/ROW]
[ROW][C]271[/C][C]10[/C][C]10.8043[/C][C]-0.80425[/C][/ROW]
[ROW][C]272[/C][C]12[/C][C]10.8624[/C][C]1.13763[/C][/ROW]
[ROW][C]273[/C][C]10[/C][C]10.8064[/C][C]-0.806443[/C][/ROW]
[ROW][C]274[/C][C]12[/C][C]10.7933[/C][C]1.20672[/C][/ROW]
[ROW][C]275[/C][C]9[/C][C]10.8382[/C][C]-1.83824[/C][/ROW]
[ROW][C]276[/C][C]3[/C][C]10.6507[/C][C]-7.65074[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&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
11210.7561.244
2810.7407-2.74065
31110.75380.24619
41310.63542.36462
51110.620.379967
61010.7494-0.749424
7710.7977-3.79767
81010.7648-0.764775
91510.71654.28347
101210.65291.34707
111210.72311.27689
121010.6135-0.613454
131010.7056-0.705562
141410.73633.26373
15610.6113-4.61126
161210.72091.27909
171410.73413.26593
181110.67710.322947
19810.6836-2.68363
201210.69241.3076
211510.61354.38655
221310.77572.22426
231110.70990.290052
241210.77571.22426
25710.7297-3.72969
261110.71210.287858
27710.8262-3.82618
281210.7671.23303
291210.69021.30979
301310.72532.2747
31910.6551-1.65512
321110.72970.270314
331210.67051.32953
341510.68584.31418
351210.70991.29005
36610.699-4.69898
37510.7012-5.70118
381310.75162.24838
391110.67710.322947
40610.7319-4.73188
411210.60251.39751
421010.7231-0.723107
43610.7582-4.7582
441210.70991.29005
451110.74280.257156
46610.7209-4.72091
471210.73191.26812
481210.64631.35365
49810.7516-2.75162
501010.7428-0.742844
511110.72750.272507
52710.62-3.62003
531210.71211.28786
541310.73852.26154
551410.76483.23522
561210.69461.3054
57610.5981-4.5981
581410.78673.21329
591010.6485-0.648543
601210.76481.23522
611110.67710.322947
621010.7472-0.747231
63710.6398-3.63977
641210.82181.17821
65710.6749-3.67486
661210.67271.32733
671210.71651.28347
681010.7582-0.758196
691010.7911-0.791092
701210.74071.25935
711210.74281.25716
721210.72311.27689
73810.6661-2.66609
741010.7933-0.793285
75510.7494-5.74942
761010.7582-0.758196
771210.74941.25058
781110.76260.237418
79910.6902-1.69021
801210.6421.35804
811110.70340.296631
821010.767-0.766968
831210.71211.28786
841010.5674-0.567399
85910.699-1.69898
861110.73190.268121
871210.71871.28128
88710.7231-3.72311
891110.66170.338299
901210.76261.23742
91610.7494-4.74942
92910.5959-1.59591
931510.69024.30979
941010.6661-0.666087
951110.6420.358036
961210.67051.32953
971210.63321.36681
981210.72311.27689
991110.77140.228646
100910.6463-1.64635
1011110.70780.292245
1021210.6991.30102
1031210.65511.34488
1041410.68363.31637
105810.7845-2.78451
1061010.6595-0.659508
107910.7692-1.76916
1081010.5806-0.580558
109910.6135-1.61345
1101010.6836-0.683632
1111210.72751.27251
1121110.71650.283472
113910.5685-1.5685
1141110.75160.248383
1151210.871.12996
1161210.86461.13544
117710.8371-3.83715
1181210.74941.25058
1191210.84811.15189
1201210.8921.10803
1211010.8262-0.826181
1221510.76594.23413
1231010.8766-0.876621
1241510.79554.20452
1251010.7056-0.705562
1261510.74944.25058
127910.8284-1.82837
1281510.77144.22865
1291210.88761.11241
1301310.78232.21768
1311210.79111.20891
1321210.82731.17272
133810.7966-2.79657
134910.7977-1.79767
1351510.74614.25387
1361210.75051.24948
1371210.85361.14641
1381510.66174.3383
1391110.87660.123379
1401210.82621.17382
141610.7275-4.72749
1421410.86243.13763
1431210.80751.19246
1441210.86021.13983
1451210.83171.16834
1461110.86020.139827
1471210.77141.22865
1481210.78781.2122
1491210.79661.20343
1501210.87331.12667
151810.6902-2.69021
1521210.87331.12667
1531210.84261.15737
1541110.79330.206715
1551010.7768-0.776837
1561110.88870.111317
1571210.81521.18478
1581310.79882.20123
1591210.73081.26922
1601210.87771.12228
1611010.8218-0.821795
1621010.8481-0.848112
1631110.82620.173819
164810.9095-2.90952
1651210.71321.28676
166910.8777-1.87772
1671210.80431.19575
1681110.7220.27799
1691510.82294.17711
170810.87-2.87004
171810.7933-2.79328
1721110.81080.189171
1731110.81080.189171
1741110.85910.140923
1751310.76592.23413
176710.892-3.89197
1771210.80971.19027
178810.6398-2.63977
179810.767-2.76697
180410.7779-6.77793
1811110.8920.108027
1821010.8075-0.80754
183710.756-3.756
1841210.82621.17382
1851110.85360.146406
186910.7615-1.76149
1871010.7396-0.739555
188810.7494-2.74942
189810.7001-2.70008
1901110.81080.189171
1911210.68361.31637
1921010.8722-0.872235
1931010.7714-0.771354
1941210.79881.20123
195810.7966-2.79657
1961110.78230.21768
197810.7999-2.79986
1981010.8295-0.82947
1991410.89533.10474
200910.7714-1.77135
201910.7714-1.77135
2021010.8163-0.816312
2031310.75272.24729
2041210.79331.20672
2051310.68912.31089
206810.7505-2.75052
207310.8942-7.89417
208810.8371-2.83715
2091210.71871.28128
2101110.80750.19246
211910.7341-1.73407
2121210.76261.23742
2131210.83171.16834
2141210.7451.25496
2151010.8207-0.820698
2161310.87112.12886
217910.7176-1.71762
2181210.81631.18369
2191110.86240.137634
2201410.64093.35913
2211110.74390.256059
222910.8152-1.81522
2231210.89641.10364
224810.8064-2.80644
2251510.84814.15189
2261210.81521.18478
2271410.87663.12338
2281210.89091.10912
229910.8799-1.87991
230910.892-1.89197
2311310.76042.23961
2321310.75492.24509
2331510.68144.31856
2341110.57180.428215
235710.733-3.73298
2361010.7714-0.771354
2371110.72970.270314
2381410.7453.25496
2391410.76593.23413
2401310.72312.27689
2411210.79991.20014
242810.9095-2.90952
2431310.71872.28128
244910.7933-1.79328
2451210.85911.14092
2461310.78122.21878
2471110.82620.173819
2481110.76590.234128
2491310.7332.26702
2501210.73521.26483
2511210.79661.20343
2521010.8053-0.805347
253910.7626-1.76258
2541010.8426-0.842629
2551310.64532.35475
2561310.6422.35804
257910.7494-1.74942
2581110.64530.354747
2591210.71321.28676
260810.7439-2.74394
2611210.69131.30869
2621210.79991.20014
2631210.83821.16176
264910.767-1.76697
2651210.7791.22097
2661210.81741.18259
2671110.84260.157371
2681210.71321.28676
269610.8097-4.80973
270710.7407-3.74065
2711010.8043-0.80425
2721210.86241.13763
2731010.8064-0.806443
2741210.79331.20672
275910.8382-1.83824
276310.6507-7.65074






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.4773990.9547980.522601
60.3151410.6302810.684859
70.3385790.6771570.661421
80.2287920.4575840.771208
90.5495450.9009090.450455
100.4419220.8838440.558078
110.366840.7336790.63316
120.3973720.7947440.602628
130.3246880.6493760.675312
140.4315580.8631150.568442
150.7567270.4865460.243273
160.7088890.5822220.291111
170.7475720.5048560.252428
180.685650.6287010.31435
190.7117290.5765410.288271
200.6651020.6697960.334898
210.7671870.4656250.232813
220.7525390.4949230.247461
230.6994030.6011930.300597
240.6505430.6989140.349457
250.7530990.4938010.246901
260.7031550.5936910.296845
270.761380.4772410.23862
280.7307270.5385450.269273
290.6901010.6197980.309899
300.6795960.6408070.320404
310.6733730.6532540.326627
320.6225230.7549540.377477
330.5782790.8434430.421721
340.6691110.6617790.330889
350.628350.7433010.37165
360.7863530.4272940.213647
370.9223980.1552030.0776016
380.9202450.1595090.0797546
390.9006490.1987020.0993508
400.9474610.1050790.0525395
410.935570.128860.0644298
420.9208450.1583110.0791554
430.9546520.09069570.0453479
440.9463240.1073520.053676
450.9332380.1335240.066762
460.9636380.07272430.0363621
470.9576290.08474260.0423713
480.9487210.1025590.0512794
490.9487130.1025730.0512867
500.936610.126780.06339
510.9225330.1549340.0774672
520.9475930.1048140.0524069
530.9396490.1207030.0603513
540.9404880.1190230.0595116
550.9530860.0938280.046914
560.9452140.1095730.0547864
570.9714740.05705140.0285257
580.976480.04703910.0235196
590.9705910.05881710.0294086
600.9650890.06982210.0349111
610.9567240.08655110.0432755
620.9477150.104570.0522849
630.9590460.08190710.0409536
640.9512760.09744870.0487243
650.9622450.07551050.0377552
660.9569420.08611650.0430582
670.9502550.09948960.0497448
680.9407470.1185070.0592534
690.9302530.1394940.069747
700.9202760.1594480.079724
710.9091630.1816730.0908366
720.8973920.2052160.102608
730.9001180.1997640.0998819
740.8853270.2293450.114673
750.9530160.09396740.0469837
760.9440320.1119360.0559679
770.9360360.1279270.0639636
780.9234860.1530280.076514
790.9159580.1680840.0840421
800.9074090.1851820.0925911
810.8914110.2171790.108589
820.875120.2497610.12488
830.8618630.2762740.138137
840.8414370.3171250.158563
850.8298910.3402180.170109
860.8059540.3880920.194046
870.7883590.4232830.211641
880.8262620.3474760.173738
890.8029660.3940670.197034
900.7842870.4314250.215713
910.8581110.2837770.141889
920.8463390.3073210.153661
930.894070.211860.10593
940.8781530.2436930.121847
950.8600060.2799890.139994
960.846730.306540.15327
970.8331270.3337460.166873
980.8172540.3654920.182746
990.7929160.4141670.207084
1000.7799710.4400590.220029
1010.7533310.4933380.246669
1020.7339710.5320580.266029
1030.7147580.5704850.285242
1040.7455980.5088040.254402
1050.7578630.4842740.242137
1060.7320740.5358520.267926
1070.7194370.5611250.280563
1080.6918230.6163550.308177
1090.6773670.6452660.322633
1100.6487210.7025570.351279
1110.625780.748440.37422
1120.5927920.8144150.407208
1130.5775880.8448240.422412
1140.5435590.9128810.456441
1150.5170460.9659090.482954
1160.4900920.9801850.509908
1170.5532240.8935520.446776
1180.5285680.9428630.471432
1190.5026740.9946520.497326
1200.4761350.952270.523865
1210.4465380.8930760.553462
1220.5261110.9477780.473889
1230.4973550.9947090.502645
1240.5742490.8515020.425751
1250.5443410.9113190.455659
1260.6210780.7578440.378922
1270.6111760.7776470.388824
1280.6829340.6341320.317066
1290.6582070.6835860.341793
1300.6533960.6932070.346604
1310.6286730.7426530.371327
1320.602940.7941210.39706
1330.6228270.7543460.377173
1340.6123340.7753310.387666
1350.6853980.6292050.314602
1360.6624360.6751270.337564
1370.6375530.7248940.362447
1380.7151270.5697470.284873
1390.6858540.6282930.314146
1400.6621030.6757940.337897
1410.7597320.4805350.240268
1420.7805480.4389050.219452
1430.760850.47830.23915
1440.7400980.5198050.259902
1450.7185930.5628140.281407
1460.6898510.6202980.310149
1470.6670010.6659970.332999
1480.6434240.7131530.356576
1490.6192730.7614530.380727
1500.5947980.8104040.405202
1510.6104820.7790350.389518
1520.5864610.8270790.413539
1530.5619160.8761680.438084
1540.5282070.9435850.471793
1550.4986180.9972350.501382
1560.466730.933460.53327
1570.4418650.883730.558135
1580.4389070.8778140.561093
1590.414190.828380.58581
1600.391580.7831590.60842
1610.3639590.7279180.636041
1620.3375070.6750140.662493
1630.3074550.614910.692545
1640.326190.652380.67381
1650.3039790.6079590.696021
1660.2937380.5874750.706262
1670.2727840.5455680.727216
1680.2447060.4894120.755294
1690.3157860.6315730.684214
1700.3314340.6628680.668566
1710.3458230.6916450.654177
1720.3145790.6291580.685421
1730.2845880.5691760.715412
1740.2565050.5130090.743495
1750.2555050.511010.744495
1760.3054930.6109850.694507
1770.2842640.5685270.715736
1780.2971590.5943170.702841
1790.3104030.6208070.689597
1800.5772780.8454440.422722
1810.5431360.9137280.456864
1820.5109070.9781860.489093
1830.5740020.8519970.425998
1840.5492280.9015440.450772
1850.5139170.9721660.486083
1860.4998850.9997710.500115
1870.468140.936280.53186
1880.4877110.9754230.512289
1890.5126740.9746520.487326
1900.4760350.9520690.523965
1910.4465260.8930510.553474
1920.4132860.8265720.586714
1930.3819790.7639580.618021
1940.3563290.7126570.643671
1950.3728650.7457290.627135
1960.3378470.6756950.662153
1970.354480.708960.64552
1980.3235020.6470040.676498
1990.3653150.730630.634685
2000.3528760.7057520.647124
2010.3409230.6818470.659077
2020.3099930.6199860.690007
2030.3030940.6061880.696906
2040.2783830.5567660.721617
2050.2689690.5379380.731031
2060.2880380.5760760.711962
2070.6750420.6499160.324958
2080.6975680.6048650.302432
2090.6686140.6627730.331386
2100.6309370.7381260.369063
2110.6225070.7549860.377493
2120.5908650.818270.409135
2130.5594830.8810350.440517
2140.5265330.9469340.473467
2150.4916450.983290.508355
2160.4862810.9725610.513719
2170.4776740.9553490.522326
2180.4452410.8904820.554759
2190.4037960.8075930.596204
2200.4276080.8552170.572392
2210.3858770.7717540.614123
2220.3722920.7445830.627708
2230.3417570.6835150.658243
2240.3653540.7307080.634646
2250.4605140.9210290.539486
2260.4274060.8548120.572594
2270.4790190.9580390.520981
2280.4552810.9105630.544719
2290.4282070.8564130.571793
2300.4024080.8048150.597592
2310.3946330.7892650.605367
2320.3875340.7750690.612466
2330.4847110.9694210.515289
2340.4370220.8740440.562978
2350.5236180.9527650.476382
2360.4804860.9609720.519514
2370.4310370.8620750.568963
2380.47370.9474010.5263
2390.5253220.9493560.474678
2400.524330.951340.47567
2410.4916610.9833230.508339
2420.5068870.9862260.493113
2430.5135740.9728520.486426
2440.4875290.9750580.512471
2450.447670.8953390.55233
2460.4524450.9048890.547555
2470.3983510.7967010.601649
2480.3461410.6922820.653859
2490.3571150.714230.642885
2500.3296890.6593790.670311
2510.3013160.6026320.698684
2520.2512270.5024540.748773
2530.2180.4359990.782
2540.1758830.3517670.824117
2550.203330.4066610.79667
2560.2836480.5672960.716352
2570.2363070.4726130.763693
2580.246120.492240.75388
2590.2904680.5809360.709532
2600.2482160.4964320.751784
2610.3975660.7951330.602434
2620.3681760.7363520.631824
2630.3024940.6049870.697506
2640.2320160.4640320.767984
2650.2447680.4895360.755232
2660.2126540.4253070.787346
2670.1472770.2945550.852723
2680.525010.949980.47499
2690.7912250.417550.208775
2700.6681170.6637660.331883
2710.5004980.9990040.499502

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0.477399 & 0.954798 & 0.522601 \tabularnewline
6 & 0.315141 & 0.630281 & 0.684859 \tabularnewline
7 & 0.338579 & 0.677157 & 0.661421 \tabularnewline
8 & 0.228792 & 0.457584 & 0.771208 \tabularnewline
9 & 0.549545 & 0.900909 & 0.450455 \tabularnewline
10 & 0.441922 & 0.883844 & 0.558078 \tabularnewline
11 & 0.36684 & 0.733679 & 0.63316 \tabularnewline
12 & 0.397372 & 0.794744 & 0.602628 \tabularnewline
13 & 0.324688 & 0.649376 & 0.675312 \tabularnewline
14 & 0.431558 & 0.863115 & 0.568442 \tabularnewline
15 & 0.756727 & 0.486546 & 0.243273 \tabularnewline
16 & 0.708889 & 0.582222 & 0.291111 \tabularnewline
17 & 0.747572 & 0.504856 & 0.252428 \tabularnewline
18 & 0.68565 & 0.628701 & 0.31435 \tabularnewline
19 & 0.711729 & 0.576541 & 0.288271 \tabularnewline
20 & 0.665102 & 0.669796 & 0.334898 \tabularnewline
21 & 0.767187 & 0.465625 & 0.232813 \tabularnewline
22 & 0.752539 & 0.494923 & 0.247461 \tabularnewline
23 & 0.699403 & 0.601193 & 0.300597 \tabularnewline
24 & 0.650543 & 0.698914 & 0.349457 \tabularnewline
25 & 0.753099 & 0.493801 & 0.246901 \tabularnewline
26 & 0.703155 & 0.593691 & 0.296845 \tabularnewline
27 & 0.76138 & 0.477241 & 0.23862 \tabularnewline
28 & 0.730727 & 0.538545 & 0.269273 \tabularnewline
29 & 0.690101 & 0.619798 & 0.309899 \tabularnewline
30 & 0.679596 & 0.640807 & 0.320404 \tabularnewline
31 & 0.673373 & 0.653254 & 0.326627 \tabularnewline
32 & 0.622523 & 0.754954 & 0.377477 \tabularnewline
33 & 0.578279 & 0.843443 & 0.421721 \tabularnewline
34 & 0.669111 & 0.661779 & 0.330889 \tabularnewline
35 & 0.62835 & 0.743301 & 0.37165 \tabularnewline
36 & 0.786353 & 0.427294 & 0.213647 \tabularnewline
37 & 0.922398 & 0.155203 & 0.0776016 \tabularnewline
38 & 0.920245 & 0.159509 & 0.0797546 \tabularnewline
39 & 0.900649 & 0.198702 & 0.0993508 \tabularnewline
40 & 0.947461 & 0.105079 & 0.0525395 \tabularnewline
41 & 0.93557 & 0.12886 & 0.0644298 \tabularnewline
42 & 0.920845 & 0.158311 & 0.0791554 \tabularnewline
43 & 0.954652 & 0.0906957 & 0.0453479 \tabularnewline
44 & 0.946324 & 0.107352 & 0.053676 \tabularnewline
45 & 0.933238 & 0.133524 & 0.066762 \tabularnewline
46 & 0.963638 & 0.0727243 & 0.0363621 \tabularnewline
47 & 0.957629 & 0.0847426 & 0.0423713 \tabularnewline
48 & 0.948721 & 0.102559 & 0.0512794 \tabularnewline
49 & 0.948713 & 0.102573 & 0.0512867 \tabularnewline
50 & 0.93661 & 0.12678 & 0.06339 \tabularnewline
51 & 0.922533 & 0.154934 & 0.0774672 \tabularnewline
52 & 0.947593 & 0.104814 & 0.0524069 \tabularnewline
53 & 0.939649 & 0.120703 & 0.0603513 \tabularnewline
54 & 0.940488 & 0.119023 & 0.0595116 \tabularnewline
55 & 0.953086 & 0.093828 & 0.046914 \tabularnewline
56 & 0.945214 & 0.109573 & 0.0547864 \tabularnewline
57 & 0.971474 & 0.0570514 & 0.0285257 \tabularnewline
58 & 0.97648 & 0.0470391 & 0.0235196 \tabularnewline
59 & 0.970591 & 0.0588171 & 0.0294086 \tabularnewline
60 & 0.965089 & 0.0698221 & 0.0349111 \tabularnewline
61 & 0.956724 & 0.0865511 & 0.0432755 \tabularnewline
62 & 0.947715 & 0.10457 & 0.0522849 \tabularnewline
63 & 0.959046 & 0.0819071 & 0.0409536 \tabularnewline
64 & 0.951276 & 0.0974487 & 0.0487243 \tabularnewline
65 & 0.962245 & 0.0755105 & 0.0377552 \tabularnewline
66 & 0.956942 & 0.0861165 & 0.0430582 \tabularnewline
67 & 0.950255 & 0.0994896 & 0.0497448 \tabularnewline
68 & 0.940747 & 0.118507 & 0.0592534 \tabularnewline
69 & 0.930253 & 0.139494 & 0.069747 \tabularnewline
70 & 0.920276 & 0.159448 & 0.079724 \tabularnewline
71 & 0.909163 & 0.181673 & 0.0908366 \tabularnewline
72 & 0.897392 & 0.205216 & 0.102608 \tabularnewline
73 & 0.900118 & 0.199764 & 0.0998819 \tabularnewline
74 & 0.885327 & 0.229345 & 0.114673 \tabularnewline
75 & 0.953016 & 0.0939674 & 0.0469837 \tabularnewline
76 & 0.944032 & 0.111936 & 0.0559679 \tabularnewline
77 & 0.936036 & 0.127927 & 0.0639636 \tabularnewline
78 & 0.923486 & 0.153028 & 0.076514 \tabularnewline
79 & 0.915958 & 0.168084 & 0.0840421 \tabularnewline
80 & 0.907409 & 0.185182 & 0.0925911 \tabularnewline
81 & 0.891411 & 0.217179 & 0.108589 \tabularnewline
82 & 0.87512 & 0.249761 & 0.12488 \tabularnewline
83 & 0.861863 & 0.276274 & 0.138137 \tabularnewline
84 & 0.841437 & 0.317125 & 0.158563 \tabularnewline
85 & 0.829891 & 0.340218 & 0.170109 \tabularnewline
86 & 0.805954 & 0.388092 & 0.194046 \tabularnewline
87 & 0.788359 & 0.423283 & 0.211641 \tabularnewline
88 & 0.826262 & 0.347476 & 0.173738 \tabularnewline
89 & 0.802966 & 0.394067 & 0.197034 \tabularnewline
90 & 0.784287 & 0.431425 & 0.215713 \tabularnewline
91 & 0.858111 & 0.283777 & 0.141889 \tabularnewline
92 & 0.846339 & 0.307321 & 0.153661 \tabularnewline
93 & 0.89407 & 0.21186 & 0.10593 \tabularnewline
94 & 0.878153 & 0.243693 & 0.121847 \tabularnewline
95 & 0.860006 & 0.279989 & 0.139994 \tabularnewline
96 & 0.84673 & 0.30654 & 0.15327 \tabularnewline
97 & 0.833127 & 0.333746 & 0.166873 \tabularnewline
98 & 0.817254 & 0.365492 & 0.182746 \tabularnewline
99 & 0.792916 & 0.414167 & 0.207084 \tabularnewline
100 & 0.779971 & 0.440059 & 0.220029 \tabularnewline
101 & 0.753331 & 0.493338 & 0.246669 \tabularnewline
102 & 0.733971 & 0.532058 & 0.266029 \tabularnewline
103 & 0.714758 & 0.570485 & 0.285242 \tabularnewline
104 & 0.745598 & 0.508804 & 0.254402 \tabularnewline
105 & 0.757863 & 0.484274 & 0.242137 \tabularnewline
106 & 0.732074 & 0.535852 & 0.267926 \tabularnewline
107 & 0.719437 & 0.561125 & 0.280563 \tabularnewline
108 & 0.691823 & 0.616355 & 0.308177 \tabularnewline
109 & 0.677367 & 0.645266 & 0.322633 \tabularnewline
110 & 0.648721 & 0.702557 & 0.351279 \tabularnewline
111 & 0.62578 & 0.74844 & 0.37422 \tabularnewline
112 & 0.592792 & 0.814415 & 0.407208 \tabularnewline
113 & 0.577588 & 0.844824 & 0.422412 \tabularnewline
114 & 0.543559 & 0.912881 & 0.456441 \tabularnewline
115 & 0.517046 & 0.965909 & 0.482954 \tabularnewline
116 & 0.490092 & 0.980185 & 0.509908 \tabularnewline
117 & 0.553224 & 0.893552 & 0.446776 \tabularnewline
118 & 0.528568 & 0.942863 & 0.471432 \tabularnewline
119 & 0.502674 & 0.994652 & 0.497326 \tabularnewline
120 & 0.476135 & 0.95227 & 0.523865 \tabularnewline
121 & 0.446538 & 0.893076 & 0.553462 \tabularnewline
122 & 0.526111 & 0.947778 & 0.473889 \tabularnewline
123 & 0.497355 & 0.994709 & 0.502645 \tabularnewline
124 & 0.574249 & 0.851502 & 0.425751 \tabularnewline
125 & 0.544341 & 0.911319 & 0.455659 \tabularnewline
126 & 0.621078 & 0.757844 & 0.378922 \tabularnewline
127 & 0.611176 & 0.777647 & 0.388824 \tabularnewline
128 & 0.682934 & 0.634132 & 0.317066 \tabularnewline
129 & 0.658207 & 0.683586 & 0.341793 \tabularnewline
130 & 0.653396 & 0.693207 & 0.346604 \tabularnewline
131 & 0.628673 & 0.742653 & 0.371327 \tabularnewline
132 & 0.60294 & 0.794121 & 0.39706 \tabularnewline
133 & 0.622827 & 0.754346 & 0.377173 \tabularnewline
134 & 0.612334 & 0.775331 & 0.387666 \tabularnewline
135 & 0.685398 & 0.629205 & 0.314602 \tabularnewline
136 & 0.662436 & 0.675127 & 0.337564 \tabularnewline
137 & 0.637553 & 0.724894 & 0.362447 \tabularnewline
138 & 0.715127 & 0.569747 & 0.284873 \tabularnewline
139 & 0.685854 & 0.628293 & 0.314146 \tabularnewline
140 & 0.662103 & 0.675794 & 0.337897 \tabularnewline
141 & 0.759732 & 0.480535 & 0.240268 \tabularnewline
142 & 0.780548 & 0.438905 & 0.219452 \tabularnewline
143 & 0.76085 & 0.4783 & 0.23915 \tabularnewline
144 & 0.740098 & 0.519805 & 0.259902 \tabularnewline
145 & 0.718593 & 0.562814 & 0.281407 \tabularnewline
146 & 0.689851 & 0.620298 & 0.310149 \tabularnewline
147 & 0.667001 & 0.665997 & 0.332999 \tabularnewline
148 & 0.643424 & 0.713153 & 0.356576 \tabularnewline
149 & 0.619273 & 0.761453 & 0.380727 \tabularnewline
150 & 0.594798 & 0.810404 & 0.405202 \tabularnewline
151 & 0.610482 & 0.779035 & 0.389518 \tabularnewline
152 & 0.586461 & 0.827079 & 0.413539 \tabularnewline
153 & 0.561916 & 0.876168 & 0.438084 \tabularnewline
154 & 0.528207 & 0.943585 & 0.471793 \tabularnewline
155 & 0.498618 & 0.997235 & 0.501382 \tabularnewline
156 & 0.46673 & 0.93346 & 0.53327 \tabularnewline
157 & 0.441865 & 0.88373 & 0.558135 \tabularnewline
158 & 0.438907 & 0.877814 & 0.561093 \tabularnewline
159 & 0.41419 & 0.82838 & 0.58581 \tabularnewline
160 & 0.39158 & 0.783159 & 0.60842 \tabularnewline
161 & 0.363959 & 0.727918 & 0.636041 \tabularnewline
162 & 0.337507 & 0.675014 & 0.662493 \tabularnewline
163 & 0.307455 & 0.61491 & 0.692545 \tabularnewline
164 & 0.32619 & 0.65238 & 0.67381 \tabularnewline
165 & 0.303979 & 0.607959 & 0.696021 \tabularnewline
166 & 0.293738 & 0.587475 & 0.706262 \tabularnewline
167 & 0.272784 & 0.545568 & 0.727216 \tabularnewline
168 & 0.244706 & 0.489412 & 0.755294 \tabularnewline
169 & 0.315786 & 0.631573 & 0.684214 \tabularnewline
170 & 0.331434 & 0.662868 & 0.668566 \tabularnewline
171 & 0.345823 & 0.691645 & 0.654177 \tabularnewline
172 & 0.314579 & 0.629158 & 0.685421 \tabularnewline
173 & 0.284588 & 0.569176 & 0.715412 \tabularnewline
174 & 0.256505 & 0.513009 & 0.743495 \tabularnewline
175 & 0.255505 & 0.51101 & 0.744495 \tabularnewline
176 & 0.305493 & 0.610985 & 0.694507 \tabularnewline
177 & 0.284264 & 0.568527 & 0.715736 \tabularnewline
178 & 0.297159 & 0.594317 & 0.702841 \tabularnewline
179 & 0.310403 & 0.620807 & 0.689597 \tabularnewline
180 & 0.577278 & 0.845444 & 0.422722 \tabularnewline
181 & 0.543136 & 0.913728 & 0.456864 \tabularnewline
182 & 0.510907 & 0.978186 & 0.489093 \tabularnewline
183 & 0.574002 & 0.851997 & 0.425998 \tabularnewline
184 & 0.549228 & 0.901544 & 0.450772 \tabularnewline
185 & 0.513917 & 0.972166 & 0.486083 \tabularnewline
186 & 0.499885 & 0.999771 & 0.500115 \tabularnewline
187 & 0.46814 & 0.93628 & 0.53186 \tabularnewline
188 & 0.487711 & 0.975423 & 0.512289 \tabularnewline
189 & 0.512674 & 0.974652 & 0.487326 \tabularnewline
190 & 0.476035 & 0.952069 & 0.523965 \tabularnewline
191 & 0.446526 & 0.893051 & 0.553474 \tabularnewline
192 & 0.413286 & 0.826572 & 0.586714 \tabularnewline
193 & 0.381979 & 0.763958 & 0.618021 \tabularnewline
194 & 0.356329 & 0.712657 & 0.643671 \tabularnewline
195 & 0.372865 & 0.745729 & 0.627135 \tabularnewline
196 & 0.337847 & 0.675695 & 0.662153 \tabularnewline
197 & 0.35448 & 0.70896 & 0.64552 \tabularnewline
198 & 0.323502 & 0.647004 & 0.676498 \tabularnewline
199 & 0.365315 & 0.73063 & 0.634685 \tabularnewline
200 & 0.352876 & 0.705752 & 0.647124 \tabularnewline
201 & 0.340923 & 0.681847 & 0.659077 \tabularnewline
202 & 0.309993 & 0.619986 & 0.690007 \tabularnewline
203 & 0.303094 & 0.606188 & 0.696906 \tabularnewline
204 & 0.278383 & 0.556766 & 0.721617 \tabularnewline
205 & 0.268969 & 0.537938 & 0.731031 \tabularnewline
206 & 0.288038 & 0.576076 & 0.711962 \tabularnewline
207 & 0.675042 & 0.649916 & 0.324958 \tabularnewline
208 & 0.697568 & 0.604865 & 0.302432 \tabularnewline
209 & 0.668614 & 0.662773 & 0.331386 \tabularnewline
210 & 0.630937 & 0.738126 & 0.369063 \tabularnewline
211 & 0.622507 & 0.754986 & 0.377493 \tabularnewline
212 & 0.590865 & 0.81827 & 0.409135 \tabularnewline
213 & 0.559483 & 0.881035 & 0.440517 \tabularnewline
214 & 0.526533 & 0.946934 & 0.473467 \tabularnewline
215 & 0.491645 & 0.98329 & 0.508355 \tabularnewline
216 & 0.486281 & 0.972561 & 0.513719 \tabularnewline
217 & 0.477674 & 0.955349 & 0.522326 \tabularnewline
218 & 0.445241 & 0.890482 & 0.554759 \tabularnewline
219 & 0.403796 & 0.807593 & 0.596204 \tabularnewline
220 & 0.427608 & 0.855217 & 0.572392 \tabularnewline
221 & 0.385877 & 0.771754 & 0.614123 \tabularnewline
222 & 0.372292 & 0.744583 & 0.627708 \tabularnewline
223 & 0.341757 & 0.683515 & 0.658243 \tabularnewline
224 & 0.365354 & 0.730708 & 0.634646 \tabularnewline
225 & 0.460514 & 0.921029 & 0.539486 \tabularnewline
226 & 0.427406 & 0.854812 & 0.572594 \tabularnewline
227 & 0.479019 & 0.958039 & 0.520981 \tabularnewline
228 & 0.455281 & 0.910563 & 0.544719 \tabularnewline
229 & 0.428207 & 0.856413 & 0.571793 \tabularnewline
230 & 0.402408 & 0.804815 & 0.597592 \tabularnewline
231 & 0.394633 & 0.789265 & 0.605367 \tabularnewline
232 & 0.387534 & 0.775069 & 0.612466 \tabularnewline
233 & 0.484711 & 0.969421 & 0.515289 \tabularnewline
234 & 0.437022 & 0.874044 & 0.562978 \tabularnewline
235 & 0.523618 & 0.952765 & 0.476382 \tabularnewline
236 & 0.480486 & 0.960972 & 0.519514 \tabularnewline
237 & 0.431037 & 0.862075 & 0.568963 \tabularnewline
238 & 0.4737 & 0.947401 & 0.5263 \tabularnewline
239 & 0.525322 & 0.949356 & 0.474678 \tabularnewline
240 & 0.52433 & 0.95134 & 0.47567 \tabularnewline
241 & 0.491661 & 0.983323 & 0.508339 \tabularnewline
242 & 0.506887 & 0.986226 & 0.493113 \tabularnewline
243 & 0.513574 & 0.972852 & 0.486426 \tabularnewline
244 & 0.487529 & 0.975058 & 0.512471 \tabularnewline
245 & 0.44767 & 0.895339 & 0.55233 \tabularnewline
246 & 0.452445 & 0.904889 & 0.547555 \tabularnewline
247 & 0.398351 & 0.796701 & 0.601649 \tabularnewline
248 & 0.346141 & 0.692282 & 0.653859 \tabularnewline
249 & 0.357115 & 0.71423 & 0.642885 \tabularnewline
250 & 0.329689 & 0.659379 & 0.670311 \tabularnewline
251 & 0.301316 & 0.602632 & 0.698684 \tabularnewline
252 & 0.251227 & 0.502454 & 0.748773 \tabularnewline
253 & 0.218 & 0.435999 & 0.782 \tabularnewline
254 & 0.175883 & 0.351767 & 0.824117 \tabularnewline
255 & 0.20333 & 0.406661 & 0.79667 \tabularnewline
256 & 0.283648 & 0.567296 & 0.716352 \tabularnewline
257 & 0.236307 & 0.472613 & 0.763693 \tabularnewline
258 & 0.24612 & 0.49224 & 0.75388 \tabularnewline
259 & 0.290468 & 0.580936 & 0.709532 \tabularnewline
260 & 0.248216 & 0.496432 & 0.751784 \tabularnewline
261 & 0.397566 & 0.795133 & 0.602434 \tabularnewline
262 & 0.368176 & 0.736352 & 0.631824 \tabularnewline
263 & 0.302494 & 0.604987 & 0.697506 \tabularnewline
264 & 0.232016 & 0.464032 & 0.767984 \tabularnewline
265 & 0.244768 & 0.489536 & 0.755232 \tabularnewline
266 & 0.212654 & 0.425307 & 0.787346 \tabularnewline
267 & 0.147277 & 0.294555 & 0.852723 \tabularnewline
268 & 0.52501 & 0.94998 & 0.47499 \tabularnewline
269 & 0.791225 & 0.41755 & 0.208775 \tabularnewline
270 & 0.668117 & 0.663766 & 0.331883 \tabularnewline
271 & 0.500498 & 0.999004 & 0.499502 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]5[/C][C]0.477399[/C][C]0.954798[/C][C]0.522601[/C][/ROW]
[ROW][C]6[/C][C]0.315141[/C][C]0.630281[/C][C]0.684859[/C][/ROW]
[ROW][C]7[/C][C]0.338579[/C][C]0.677157[/C][C]0.661421[/C][/ROW]
[ROW][C]8[/C][C]0.228792[/C][C]0.457584[/C][C]0.771208[/C][/ROW]
[ROW][C]9[/C][C]0.549545[/C][C]0.900909[/C][C]0.450455[/C][/ROW]
[ROW][C]10[/C][C]0.441922[/C][C]0.883844[/C][C]0.558078[/C][/ROW]
[ROW][C]11[/C][C]0.36684[/C][C]0.733679[/C][C]0.63316[/C][/ROW]
[ROW][C]12[/C][C]0.397372[/C][C]0.794744[/C][C]0.602628[/C][/ROW]
[ROW][C]13[/C][C]0.324688[/C][C]0.649376[/C][C]0.675312[/C][/ROW]
[ROW][C]14[/C][C]0.431558[/C][C]0.863115[/C][C]0.568442[/C][/ROW]
[ROW][C]15[/C][C]0.756727[/C][C]0.486546[/C][C]0.243273[/C][/ROW]
[ROW][C]16[/C][C]0.708889[/C][C]0.582222[/C][C]0.291111[/C][/ROW]
[ROW][C]17[/C][C]0.747572[/C][C]0.504856[/C][C]0.252428[/C][/ROW]
[ROW][C]18[/C][C]0.68565[/C][C]0.628701[/C][C]0.31435[/C][/ROW]
[ROW][C]19[/C][C]0.711729[/C][C]0.576541[/C][C]0.288271[/C][/ROW]
[ROW][C]20[/C][C]0.665102[/C][C]0.669796[/C][C]0.334898[/C][/ROW]
[ROW][C]21[/C][C]0.767187[/C][C]0.465625[/C][C]0.232813[/C][/ROW]
[ROW][C]22[/C][C]0.752539[/C][C]0.494923[/C][C]0.247461[/C][/ROW]
[ROW][C]23[/C][C]0.699403[/C][C]0.601193[/C][C]0.300597[/C][/ROW]
[ROW][C]24[/C][C]0.650543[/C][C]0.698914[/C][C]0.349457[/C][/ROW]
[ROW][C]25[/C][C]0.753099[/C][C]0.493801[/C][C]0.246901[/C][/ROW]
[ROW][C]26[/C][C]0.703155[/C][C]0.593691[/C][C]0.296845[/C][/ROW]
[ROW][C]27[/C][C]0.76138[/C][C]0.477241[/C][C]0.23862[/C][/ROW]
[ROW][C]28[/C][C]0.730727[/C][C]0.538545[/C][C]0.269273[/C][/ROW]
[ROW][C]29[/C][C]0.690101[/C][C]0.619798[/C][C]0.309899[/C][/ROW]
[ROW][C]30[/C][C]0.679596[/C][C]0.640807[/C][C]0.320404[/C][/ROW]
[ROW][C]31[/C][C]0.673373[/C][C]0.653254[/C][C]0.326627[/C][/ROW]
[ROW][C]32[/C][C]0.622523[/C][C]0.754954[/C][C]0.377477[/C][/ROW]
[ROW][C]33[/C][C]0.578279[/C][C]0.843443[/C][C]0.421721[/C][/ROW]
[ROW][C]34[/C][C]0.669111[/C][C]0.661779[/C][C]0.330889[/C][/ROW]
[ROW][C]35[/C][C]0.62835[/C][C]0.743301[/C][C]0.37165[/C][/ROW]
[ROW][C]36[/C][C]0.786353[/C][C]0.427294[/C][C]0.213647[/C][/ROW]
[ROW][C]37[/C][C]0.922398[/C][C]0.155203[/C][C]0.0776016[/C][/ROW]
[ROW][C]38[/C][C]0.920245[/C][C]0.159509[/C][C]0.0797546[/C][/ROW]
[ROW][C]39[/C][C]0.900649[/C][C]0.198702[/C][C]0.0993508[/C][/ROW]
[ROW][C]40[/C][C]0.947461[/C][C]0.105079[/C][C]0.0525395[/C][/ROW]
[ROW][C]41[/C][C]0.93557[/C][C]0.12886[/C][C]0.0644298[/C][/ROW]
[ROW][C]42[/C][C]0.920845[/C][C]0.158311[/C][C]0.0791554[/C][/ROW]
[ROW][C]43[/C][C]0.954652[/C][C]0.0906957[/C][C]0.0453479[/C][/ROW]
[ROW][C]44[/C][C]0.946324[/C][C]0.107352[/C][C]0.053676[/C][/ROW]
[ROW][C]45[/C][C]0.933238[/C][C]0.133524[/C][C]0.066762[/C][/ROW]
[ROW][C]46[/C][C]0.963638[/C][C]0.0727243[/C][C]0.0363621[/C][/ROW]
[ROW][C]47[/C][C]0.957629[/C][C]0.0847426[/C][C]0.0423713[/C][/ROW]
[ROW][C]48[/C][C]0.948721[/C][C]0.102559[/C][C]0.0512794[/C][/ROW]
[ROW][C]49[/C][C]0.948713[/C][C]0.102573[/C][C]0.0512867[/C][/ROW]
[ROW][C]50[/C][C]0.93661[/C][C]0.12678[/C][C]0.06339[/C][/ROW]
[ROW][C]51[/C][C]0.922533[/C][C]0.154934[/C][C]0.0774672[/C][/ROW]
[ROW][C]52[/C][C]0.947593[/C][C]0.104814[/C][C]0.0524069[/C][/ROW]
[ROW][C]53[/C][C]0.939649[/C][C]0.120703[/C][C]0.0603513[/C][/ROW]
[ROW][C]54[/C][C]0.940488[/C][C]0.119023[/C][C]0.0595116[/C][/ROW]
[ROW][C]55[/C][C]0.953086[/C][C]0.093828[/C][C]0.046914[/C][/ROW]
[ROW][C]56[/C][C]0.945214[/C][C]0.109573[/C][C]0.0547864[/C][/ROW]
[ROW][C]57[/C][C]0.971474[/C][C]0.0570514[/C][C]0.0285257[/C][/ROW]
[ROW][C]58[/C][C]0.97648[/C][C]0.0470391[/C][C]0.0235196[/C][/ROW]
[ROW][C]59[/C][C]0.970591[/C][C]0.0588171[/C][C]0.0294086[/C][/ROW]
[ROW][C]60[/C][C]0.965089[/C][C]0.0698221[/C][C]0.0349111[/C][/ROW]
[ROW][C]61[/C][C]0.956724[/C][C]0.0865511[/C][C]0.0432755[/C][/ROW]
[ROW][C]62[/C][C]0.947715[/C][C]0.10457[/C][C]0.0522849[/C][/ROW]
[ROW][C]63[/C][C]0.959046[/C][C]0.0819071[/C][C]0.0409536[/C][/ROW]
[ROW][C]64[/C][C]0.951276[/C][C]0.0974487[/C][C]0.0487243[/C][/ROW]
[ROW][C]65[/C][C]0.962245[/C][C]0.0755105[/C][C]0.0377552[/C][/ROW]
[ROW][C]66[/C][C]0.956942[/C][C]0.0861165[/C][C]0.0430582[/C][/ROW]
[ROW][C]67[/C][C]0.950255[/C][C]0.0994896[/C][C]0.0497448[/C][/ROW]
[ROW][C]68[/C][C]0.940747[/C][C]0.118507[/C][C]0.0592534[/C][/ROW]
[ROW][C]69[/C][C]0.930253[/C][C]0.139494[/C][C]0.069747[/C][/ROW]
[ROW][C]70[/C][C]0.920276[/C][C]0.159448[/C][C]0.079724[/C][/ROW]
[ROW][C]71[/C][C]0.909163[/C][C]0.181673[/C][C]0.0908366[/C][/ROW]
[ROW][C]72[/C][C]0.897392[/C][C]0.205216[/C][C]0.102608[/C][/ROW]
[ROW][C]73[/C][C]0.900118[/C][C]0.199764[/C][C]0.0998819[/C][/ROW]
[ROW][C]74[/C][C]0.885327[/C][C]0.229345[/C][C]0.114673[/C][/ROW]
[ROW][C]75[/C][C]0.953016[/C][C]0.0939674[/C][C]0.0469837[/C][/ROW]
[ROW][C]76[/C][C]0.944032[/C][C]0.111936[/C][C]0.0559679[/C][/ROW]
[ROW][C]77[/C][C]0.936036[/C][C]0.127927[/C][C]0.0639636[/C][/ROW]
[ROW][C]78[/C][C]0.923486[/C][C]0.153028[/C][C]0.076514[/C][/ROW]
[ROW][C]79[/C][C]0.915958[/C][C]0.168084[/C][C]0.0840421[/C][/ROW]
[ROW][C]80[/C][C]0.907409[/C][C]0.185182[/C][C]0.0925911[/C][/ROW]
[ROW][C]81[/C][C]0.891411[/C][C]0.217179[/C][C]0.108589[/C][/ROW]
[ROW][C]82[/C][C]0.87512[/C][C]0.249761[/C][C]0.12488[/C][/ROW]
[ROW][C]83[/C][C]0.861863[/C][C]0.276274[/C][C]0.138137[/C][/ROW]
[ROW][C]84[/C][C]0.841437[/C][C]0.317125[/C][C]0.158563[/C][/ROW]
[ROW][C]85[/C][C]0.829891[/C][C]0.340218[/C][C]0.170109[/C][/ROW]
[ROW][C]86[/C][C]0.805954[/C][C]0.388092[/C][C]0.194046[/C][/ROW]
[ROW][C]87[/C][C]0.788359[/C][C]0.423283[/C][C]0.211641[/C][/ROW]
[ROW][C]88[/C][C]0.826262[/C][C]0.347476[/C][C]0.173738[/C][/ROW]
[ROW][C]89[/C][C]0.802966[/C][C]0.394067[/C][C]0.197034[/C][/ROW]
[ROW][C]90[/C][C]0.784287[/C][C]0.431425[/C][C]0.215713[/C][/ROW]
[ROW][C]91[/C][C]0.858111[/C][C]0.283777[/C][C]0.141889[/C][/ROW]
[ROW][C]92[/C][C]0.846339[/C][C]0.307321[/C][C]0.153661[/C][/ROW]
[ROW][C]93[/C][C]0.89407[/C][C]0.21186[/C][C]0.10593[/C][/ROW]
[ROW][C]94[/C][C]0.878153[/C][C]0.243693[/C][C]0.121847[/C][/ROW]
[ROW][C]95[/C][C]0.860006[/C][C]0.279989[/C][C]0.139994[/C][/ROW]
[ROW][C]96[/C][C]0.84673[/C][C]0.30654[/C][C]0.15327[/C][/ROW]
[ROW][C]97[/C][C]0.833127[/C][C]0.333746[/C][C]0.166873[/C][/ROW]
[ROW][C]98[/C][C]0.817254[/C][C]0.365492[/C][C]0.182746[/C][/ROW]
[ROW][C]99[/C][C]0.792916[/C][C]0.414167[/C][C]0.207084[/C][/ROW]
[ROW][C]100[/C][C]0.779971[/C][C]0.440059[/C][C]0.220029[/C][/ROW]
[ROW][C]101[/C][C]0.753331[/C][C]0.493338[/C][C]0.246669[/C][/ROW]
[ROW][C]102[/C][C]0.733971[/C][C]0.532058[/C][C]0.266029[/C][/ROW]
[ROW][C]103[/C][C]0.714758[/C][C]0.570485[/C][C]0.285242[/C][/ROW]
[ROW][C]104[/C][C]0.745598[/C][C]0.508804[/C][C]0.254402[/C][/ROW]
[ROW][C]105[/C][C]0.757863[/C][C]0.484274[/C][C]0.242137[/C][/ROW]
[ROW][C]106[/C][C]0.732074[/C][C]0.535852[/C][C]0.267926[/C][/ROW]
[ROW][C]107[/C][C]0.719437[/C][C]0.561125[/C][C]0.280563[/C][/ROW]
[ROW][C]108[/C][C]0.691823[/C][C]0.616355[/C][C]0.308177[/C][/ROW]
[ROW][C]109[/C][C]0.677367[/C][C]0.645266[/C][C]0.322633[/C][/ROW]
[ROW][C]110[/C][C]0.648721[/C][C]0.702557[/C][C]0.351279[/C][/ROW]
[ROW][C]111[/C][C]0.62578[/C][C]0.74844[/C][C]0.37422[/C][/ROW]
[ROW][C]112[/C][C]0.592792[/C][C]0.814415[/C][C]0.407208[/C][/ROW]
[ROW][C]113[/C][C]0.577588[/C][C]0.844824[/C][C]0.422412[/C][/ROW]
[ROW][C]114[/C][C]0.543559[/C][C]0.912881[/C][C]0.456441[/C][/ROW]
[ROW][C]115[/C][C]0.517046[/C][C]0.965909[/C][C]0.482954[/C][/ROW]
[ROW][C]116[/C][C]0.490092[/C][C]0.980185[/C][C]0.509908[/C][/ROW]
[ROW][C]117[/C][C]0.553224[/C][C]0.893552[/C][C]0.446776[/C][/ROW]
[ROW][C]118[/C][C]0.528568[/C][C]0.942863[/C][C]0.471432[/C][/ROW]
[ROW][C]119[/C][C]0.502674[/C][C]0.994652[/C][C]0.497326[/C][/ROW]
[ROW][C]120[/C][C]0.476135[/C][C]0.95227[/C][C]0.523865[/C][/ROW]
[ROW][C]121[/C][C]0.446538[/C][C]0.893076[/C][C]0.553462[/C][/ROW]
[ROW][C]122[/C][C]0.526111[/C][C]0.947778[/C][C]0.473889[/C][/ROW]
[ROW][C]123[/C][C]0.497355[/C][C]0.994709[/C][C]0.502645[/C][/ROW]
[ROW][C]124[/C][C]0.574249[/C][C]0.851502[/C][C]0.425751[/C][/ROW]
[ROW][C]125[/C][C]0.544341[/C][C]0.911319[/C][C]0.455659[/C][/ROW]
[ROW][C]126[/C][C]0.621078[/C][C]0.757844[/C][C]0.378922[/C][/ROW]
[ROW][C]127[/C][C]0.611176[/C][C]0.777647[/C][C]0.388824[/C][/ROW]
[ROW][C]128[/C][C]0.682934[/C][C]0.634132[/C][C]0.317066[/C][/ROW]
[ROW][C]129[/C][C]0.658207[/C][C]0.683586[/C][C]0.341793[/C][/ROW]
[ROW][C]130[/C][C]0.653396[/C][C]0.693207[/C][C]0.346604[/C][/ROW]
[ROW][C]131[/C][C]0.628673[/C][C]0.742653[/C][C]0.371327[/C][/ROW]
[ROW][C]132[/C][C]0.60294[/C][C]0.794121[/C][C]0.39706[/C][/ROW]
[ROW][C]133[/C][C]0.622827[/C][C]0.754346[/C][C]0.377173[/C][/ROW]
[ROW][C]134[/C][C]0.612334[/C][C]0.775331[/C][C]0.387666[/C][/ROW]
[ROW][C]135[/C][C]0.685398[/C][C]0.629205[/C][C]0.314602[/C][/ROW]
[ROW][C]136[/C][C]0.662436[/C][C]0.675127[/C][C]0.337564[/C][/ROW]
[ROW][C]137[/C][C]0.637553[/C][C]0.724894[/C][C]0.362447[/C][/ROW]
[ROW][C]138[/C][C]0.715127[/C][C]0.569747[/C][C]0.284873[/C][/ROW]
[ROW][C]139[/C][C]0.685854[/C][C]0.628293[/C][C]0.314146[/C][/ROW]
[ROW][C]140[/C][C]0.662103[/C][C]0.675794[/C][C]0.337897[/C][/ROW]
[ROW][C]141[/C][C]0.759732[/C][C]0.480535[/C][C]0.240268[/C][/ROW]
[ROW][C]142[/C][C]0.780548[/C][C]0.438905[/C][C]0.219452[/C][/ROW]
[ROW][C]143[/C][C]0.76085[/C][C]0.4783[/C][C]0.23915[/C][/ROW]
[ROW][C]144[/C][C]0.740098[/C][C]0.519805[/C][C]0.259902[/C][/ROW]
[ROW][C]145[/C][C]0.718593[/C][C]0.562814[/C][C]0.281407[/C][/ROW]
[ROW][C]146[/C][C]0.689851[/C][C]0.620298[/C][C]0.310149[/C][/ROW]
[ROW][C]147[/C][C]0.667001[/C][C]0.665997[/C][C]0.332999[/C][/ROW]
[ROW][C]148[/C][C]0.643424[/C][C]0.713153[/C][C]0.356576[/C][/ROW]
[ROW][C]149[/C][C]0.619273[/C][C]0.761453[/C][C]0.380727[/C][/ROW]
[ROW][C]150[/C][C]0.594798[/C][C]0.810404[/C][C]0.405202[/C][/ROW]
[ROW][C]151[/C][C]0.610482[/C][C]0.779035[/C][C]0.389518[/C][/ROW]
[ROW][C]152[/C][C]0.586461[/C][C]0.827079[/C][C]0.413539[/C][/ROW]
[ROW][C]153[/C][C]0.561916[/C][C]0.876168[/C][C]0.438084[/C][/ROW]
[ROW][C]154[/C][C]0.528207[/C][C]0.943585[/C][C]0.471793[/C][/ROW]
[ROW][C]155[/C][C]0.498618[/C][C]0.997235[/C][C]0.501382[/C][/ROW]
[ROW][C]156[/C][C]0.46673[/C][C]0.93346[/C][C]0.53327[/C][/ROW]
[ROW][C]157[/C][C]0.441865[/C][C]0.88373[/C][C]0.558135[/C][/ROW]
[ROW][C]158[/C][C]0.438907[/C][C]0.877814[/C][C]0.561093[/C][/ROW]
[ROW][C]159[/C][C]0.41419[/C][C]0.82838[/C][C]0.58581[/C][/ROW]
[ROW][C]160[/C][C]0.39158[/C][C]0.783159[/C][C]0.60842[/C][/ROW]
[ROW][C]161[/C][C]0.363959[/C][C]0.727918[/C][C]0.636041[/C][/ROW]
[ROW][C]162[/C][C]0.337507[/C][C]0.675014[/C][C]0.662493[/C][/ROW]
[ROW][C]163[/C][C]0.307455[/C][C]0.61491[/C][C]0.692545[/C][/ROW]
[ROW][C]164[/C][C]0.32619[/C][C]0.65238[/C][C]0.67381[/C][/ROW]
[ROW][C]165[/C][C]0.303979[/C][C]0.607959[/C][C]0.696021[/C][/ROW]
[ROW][C]166[/C][C]0.293738[/C][C]0.587475[/C][C]0.706262[/C][/ROW]
[ROW][C]167[/C][C]0.272784[/C][C]0.545568[/C][C]0.727216[/C][/ROW]
[ROW][C]168[/C][C]0.244706[/C][C]0.489412[/C][C]0.755294[/C][/ROW]
[ROW][C]169[/C][C]0.315786[/C][C]0.631573[/C][C]0.684214[/C][/ROW]
[ROW][C]170[/C][C]0.331434[/C][C]0.662868[/C][C]0.668566[/C][/ROW]
[ROW][C]171[/C][C]0.345823[/C][C]0.691645[/C][C]0.654177[/C][/ROW]
[ROW][C]172[/C][C]0.314579[/C][C]0.629158[/C][C]0.685421[/C][/ROW]
[ROW][C]173[/C][C]0.284588[/C][C]0.569176[/C][C]0.715412[/C][/ROW]
[ROW][C]174[/C][C]0.256505[/C][C]0.513009[/C][C]0.743495[/C][/ROW]
[ROW][C]175[/C][C]0.255505[/C][C]0.51101[/C][C]0.744495[/C][/ROW]
[ROW][C]176[/C][C]0.305493[/C][C]0.610985[/C][C]0.694507[/C][/ROW]
[ROW][C]177[/C][C]0.284264[/C][C]0.568527[/C][C]0.715736[/C][/ROW]
[ROW][C]178[/C][C]0.297159[/C][C]0.594317[/C][C]0.702841[/C][/ROW]
[ROW][C]179[/C][C]0.310403[/C][C]0.620807[/C][C]0.689597[/C][/ROW]
[ROW][C]180[/C][C]0.577278[/C][C]0.845444[/C][C]0.422722[/C][/ROW]
[ROW][C]181[/C][C]0.543136[/C][C]0.913728[/C][C]0.456864[/C][/ROW]
[ROW][C]182[/C][C]0.510907[/C][C]0.978186[/C][C]0.489093[/C][/ROW]
[ROW][C]183[/C][C]0.574002[/C][C]0.851997[/C][C]0.425998[/C][/ROW]
[ROW][C]184[/C][C]0.549228[/C][C]0.901544[/C][C]0.450772[/C][/ROW]
[ROW][C]185[/C][C]0.513917[/C][C]0.972166[/C][C]0.486083[/C][/ROW]
[ROW][C]186[/C][C]0.499885[/C][C]0.999771[/C][C]0.500115[/C][/ROW]
[ROW][C]187[/C][C]0.46814[/C][C]0.93628[/C][C]0.53186[/C][/ROW]
[ROW][C]188[/C][C]0.487711[/C][C]0.975423[/C][C]0.512289[/C][/ROW]
[ROW][C]189[/C][C]0.512674[/C][C]0.974652[/C][C]0.487326[/C][/ROW]
[ROW][C]190[/C][C]0.476035[/C][C]0.952069[/C][C]0.523965[/C][/ROW]
[ROW][C]191[/C][C]0.446526[/C][C]0.893051[/C][C]0.553474[/C][/ROW]
[ROW][C]192[/C][C]0.413286[/C][C]0.826572[/C][C]0.586714[/C][/ROW]
[ROW][C]193[/C][C]0.381979[/C][C]0.763958[/C][C]0.618021[/C][/ROW]
[ROW][C]194[/C][C]0.356329[/C][C]0.712657[/C][C]0.643671[/C][/ROW]
[ROW][C]195[/C][C]0.372865[/C][C]0.745729[/C][C]0.627135[/C][/ROW]
[ROW][C]196[/C][C]0.337847[/C][C]0.675695[/C][C]0.662153[/C][/ROW]
[ROW][C]197[/C][C]0.35448[/C][C]0.70896[/C][C]0.64552[/C][/ROW]
[ROW][C]198[/C][C]0.323502[/C][C]0.647004[/C][C]0.676498[/C][/ROW]
[ROW][C]199[/C][C]0.365315[/C][C]0.73063[/C][C]0.634685[/C][/ROW]
[ROW][C]200[/C][C]0.352876[/C][C]0.705752[/C][C]0.647124[/C][/ROW]
[ROW][C]201[/C][C]0.340923[/C][C]0.681847[/C][C]0.659077[/C][/ROW]
[ROW][C]202[/C][C]0.309993[/C][C]0.619986[/C][C]0.690007[/C][/ROW]
[ROW][C]203[/C][C]0.303094[/C][C]0.606188[/C][C]0.696906[/C][/ROW]
[ROW][C]204[/C][C]0.278383[/C][C]0.556766[/C][C]0.721617[/C][/ROW]
[ROW][C]205[/C][C]0.268969[/C][C]0.537938[/C][C]0.731031[/C][/ROW]
[ROW][C]206[/C][C]0.288038[/C][C]0.576076[/C][C]0.711962[/C][/ROW]
[ROW][C]207[/C][C]0.675042[/C][C]0.649916[/C][C]0.324958[/C][/ROW]
[ROW][C]208[/C][C]0.697568[/C][C]0.604865[/C][C]0.302432[/C][/ROW]
[ROW][C]209[/C][C]0.668614[/C][C]0.662773[/C][C]0.331386[/C][/ROW]
[ROW][C]210[/C][C]0.630937[/C][C]0.738126[/C][C]0.369063[/C][/ROW]
[ROW][C]211[/C][C]0.622507[/C][C]0.754986[/C][C]0.377493[/C][/ROW]
[ROW][C]212[/C][C]0.590865[/C][C]0.81827[/C][C]0.409135[/C][/ROW]
[ROW][C]213[/C][C]0.559483[/C][C]0.881035[/C][C]0.440517[/C][/ROW]
[ROW][C]214[/C][C]0.526533[/C][C]0.946934[/C][C]0.473467[/C][/ROW]
[ROW][C]215[/C][C]0.491645[/C][C]0.98329[/C][C]0.508355[/C][/ROW]
[ROW][C]216[/C][C]0.486281[/C][C]0.972561[/C][C]0.513719[/C][/ROW]
[ROW][C]217[/C][C]0.477674[/C][C]0.955349[/C][C]0.522326[/C][/ROW]
[ROW][C]218[/C][C]0.445241[/C][C]0.890482[/C][C]0.554759[/C][/ROW]
[ROW][C]219[/C][C]0.403796[/C][C]0.807593[/C][C]0.596204[/C][/ROW]
[ROW][C]220[/C][C]0.427608[/C][C]0.855217[/C][C]0.572392[/C][/ROW]
[ROW][C]221[/C][C]0.385877[/C][C]0.771754[/C][C]0.614123[/C][/ROW]
[ROW][C]222[/C][C]0.372292[/C][C]0.744583[/C][C]0.627708[/C][/ROW]
[ROW][C]223[/C][C]0.341757[/C][C]0.683515[/C][C]0.658243[/C][/ROW]
[ROW][C]224[/C][C]0.365354[/C][C]0.730708[/C][C]0.634646[/C][/ROW]
[ROW][C]225[/C][C]0.460514[/C][C]0.921029[/C][C]0.539486[/C][/ROW]
[ROW][C]226[/C][C]0.427406[/C][C]0.854812[/C][C]0.572594[/C][/ROW]
[ROW][C]227[/C][C]0.479019[/C][C]0.958039[/C][C]0.520981[/C][/ROW]
[ROW][C]228[/C][C]0.455281[/C][C]0.910563[/C][C]0.544719[/C][/ROW]
[ROW][C]229[/C][C]0.428207[/C][C]0.856413[/C][C]0.571793[/C][/ROW]
[ROW][C]230[/C][C]0.402408[/C][C]0.804815[/C][C]0.597592[/C][/ROW]
[ROW][C]231[/C][C]0.394633[/C][C]0.789265[/C][C]0.605367[/C][/ROW]
[ROW][C]232[/C][C]0.387534[/C][C]0.775069[/C][C]0.612466[/C][/ROW]
[ROW][C]233[/C][C]0.484711[/C][C]0.969421[/C][C]0.515289[/C][/ROW]
[ROW][C]234[/C][C]0.437022[/C][C]0.874044[/C][C]0.562978[/C][/ROW]
[ROW][C]235[/C][C]0.523618[/C][C]0.952765[/C][C]0.476382[/C][/ROW]
[ROW][C]236[/C][C]0.480486[/C][C]0.960972[/C][C]0.519514[/C][/ROW]
[ROW][C]237[/C][C]0.431037[/C][C]0.862075[/C][C]0.568963[/C][/ROW]
[ROW][C]238[/C][C]0.4737[/C][C]0.947401[/C][C]0.5263[/C][/ROW]
[ROW][C]239[/C][C]0.525322[/C][C]0.949356[/C][C]0.474678[/C][/ROW]
[ROW][C]240[/C][C]0.52433[/C][C]0.95134[/C][C]0.47567[/C][/ROW]
[ROW][C]241[/C][C]0.491661[/C][C]0.983323[/C][C]0.508339[/C][/ROW]
[ROW][C]242[/C][C]0.506887[/C][C]0.986226[/C][C]0.493113[/C][/ROW]
[ROW][C]243[/C][C]0.513574[/C][C]0.972852[/C][C]0.486426[/C][/ROW]
[ROW][C]244[/C][C]0.487529[/C][C]0.975058[/C][C]0.512471[/C][/ROW]
[ROW][C]245[/C][C]0.44767[/C][C]0.895339[/C][C]0.55233[/C][/ROW]
[ROW][C]246[/C][C]0.452445[/C][C]0.904889[/C][C]0.547555[/C][/ROW]
[ROW][C]247[/C][C]0.398351[/C][C]0.796701[/C][C]0.601649[/C][/ROW]
[ROW][C]248[/C][C]0.346141[/C][C]0.692282[/C][C]0.653859[/C][/ROW]
[ROW][C]249[/C][C]0.357115[/C][C]0.71423[/C][C]0.642885[/C][/ROW]
[ROW][C]250[/C][C]0.329689[/C][C]0.659379[/C][C]0.670311[/C][/ROW]
[ROW][C]251[/C][C]0.301316[/C][C]0.602632[/C][C]0.698684[/C][/ROW]
[ROW][C]252[/C][C]0.251227[/C][C]0.502454[/C][C]0.748773[/C][/ROW]
[ROW][C]253[/C][C]0.218[/C][C]0.435999[/C][C]0.782[/C][/ROW]
[ROW][C]254[/C][C]0.175883[/C][C]0.351767[/C][C]0.824117[/C][/ROW]
[ROW][C]255[/C][C]0.20333[/C][C]0.406661[/C][C]0.79667[/C][/ROW]
[ROW][C]256[/C][C]0.283648[/C][C]0.567296[/C][C]0.716352[/C][/ROW]
[ROW][C]257[/C][C]0.236307[/C][C]0.472613[/C][C]0.763693[/C][/ROW]
[ROW][C]258[/C][C]0.24612[/C][C]0.49224[/C][C]0.75388[/C][/ROW]
[ROW][C]259[/C][C]0.290468[/C][C]0.580936[/C][C]0.709532[/C][/ROW]
[ROW][C]260[/C][C]0.248216[/C][C]0.496432[/C][C]0.751784[/C][/ROW]
[ROW][C]261[/C][C]0.397566[/C][C]0.795133[/C][C]0.602434[/C][/ROW]
[ROW][C]262[/C][C]0.368176[/C][C]0.736352[/C][C]0.631824[/C][/ROW]
[ROW][C]263[/C][C]0.302494[/C][C]0.604987[/C][C]0.697506[/C][/ROW]
[ROW][C]264[/C][C]0.232016[/C][C]0.464032[/C][C]0.767984[/C][/ROW]
[ROW][C]265[/C][C]0.244768[/C][C]0.489536[/C][C]0.755232[/C][/ROW]
[ROW][C]266[/C][C]0.212654[/C][C]0.425307[/C][C]0.787346[/C][/ROW]
[ROW][C]267[/C][C]0.147277[/C][C]0.294555[/C][C]0.852723[/C][/ROW]
[ROW][C]268[/C][C]0.52501[/C][C]0.94998[/C][C]0.47499[/C][/ROW]
[ROW][C]269[/C][C]0.791225[/C][C]0.41755[/C][C]0.208775[/C][/ROW]
[ROW][C]270[/C][C]0.668117[/C][C]0.663766[/C][C]0.331883[/C][/ROW]
[ROW][C]271[/C][C]0.500498[/C][C]0.999004[/C][C]0.499502[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.4773990.9547980.522601
60.3151410.6302810.684859
70.3385790.6771570.661421
80.2287920.4575840.771208
90.5495450.9009090.450455
100.4419220.8838440.558078
110.366840.7336790.63316
120.3973720.7947440.602628
130.3246880.6493760.675312
140.4315580.8631150.568442
150.7567270.4865460.243273
160.7088890.5822220.291111
170.7475720.5048560.252428
180.685650.6287010.31435
190.7117290.5765410.288271
200.6651020.6697960.334898
210.7671870.4656250.232813
220.7525390.4949230.247461
230.6994030.6011930.300597
240.6505430.6989140.349457
250.7530990.4938010.246901
260.7031550.5936910.296845
270.761380.4772410.23862
280.7307270.5385450.269273
290.6901010.6197980.309899
300.6795960.6408070.320404
310.6733730.6532540.326627
320.6225230.7549540.377477
330.5782790.8434430.421721
340.6691110.6617790.330889
350.628350.7433010.37165
360.7863530.4272940.213647
370.9223980.1552030.0776016
380.9202450.1595090.0797546
390.9006490.1987020.0993508
400.9474610.1050790.0525395
410.935570.128860.0644298
420.9208450.1583110.0791554
430.9546520.09069570.0453479
440.9463240.1073520.053676
450.9332380.1335240.066762
460.9636380.07272430.0363621
470.9576290.08474260.0423713
480.9487210.1025590.0512794
490.9487130.1025730.0512867
500.936610.126780.06339
510.9225330.1549340.0774672
520.9475930.1048140.0524069
530.9396490.1207030.0603513
540.9404880.1190230.0595116
550.9530860.0938280.046914
560.9452140.1095730.0547864
570.9714740.05705140.0285257
580.976480.04703910.0235196
590.9705910.05881710.0294086
600.9650890.06982210.0349111
610.9567240.08655110.0432755
620.9477150.104570.0522849
630.9590460.08190710.0409536
640.9512760.09744870.0487243
650.9622450.07551050.0377552
660.9569420.08611650.0430582
670.9502550.09948960.0497448
680.9407470.1185070.0592534
690.9302530.1394940.069747
700.9202760.1594480.079724
710.9091630.1816730.0908366
720.8973920.2052160.102608
730.9001180.1997640.0998819
740.8853270.2293450.114673
750.9530160.09396740.0469837
760.9440320.1119360.0559679
770.9360360.1279270.0639636
780.9234860.1530280.076514
790.9159580.1680840.0840421
800.9074090.1851820.0925911
810.8914110.2171790.108589
820.875120.2497610.12488
830.8618630.2762740.138137
840.8414370.3171250.158563
850.8298910.3402180.170109
860.8059540.3880920.194046
870.7883590.4232830.211641
880.8262620.3474760.173738
890.8029660.3940670.197034
900.7842870.4314250.215713
910.8581110.2837770.141889
920.8463390.3073210.153661
930.894070.211860.10593
940.8781530.2436930.121847
950.8600060.2799890.139994
960.846730.306540.15327
970.8331270.3337460.166873
980.8172540.3654920.182746
990.7929160.4141670.207084
1000.7799710.4400590.220029
1010.7533310.4933380.246669
1020.7339710.5320580.266029
1030.7147580.5704850.285242
1040.7455980.5088040.254402
1050.7578630.4842740.242137
1060.7320740.5358520.267926
1070.7194370.5611250.280563
1080.6918230.6163550.308177
1090.6773670.6452660.322633
1100.6487210.7025570.351279
1110.625780.748440.37422
1120.5927920.8144150.407208
1130.5775880.8448240.422412
1140.5435590.9128810.456441
1150.5170460.9659090.482954
1160.4900920.9801850.509908
1170.5532240.8935520.446776
1180.5285680.9428630.471432
1190.5026740.9946520.497326
1200.4761350.952270.523865
1210.4465380.8930760.553462
1220.5261110.9477780.473889
1230.4973550.9947090.502645
1240.5742490.8515020.425751
1250.5443410.9113190.455659
1260.6210780.7578440.378922
1270.6111760.7776470.388824
1280.6829340.6341320.317066
1290.6582070.6835860.341793
1300.6533960.6932070.346604
1310.6286730.7426530.371327
1320.602940.7941210.39706
1330.6228270.7543460.377173
1340.6123340.7753310.387666
1350.6853980.6292050.314602
1360.6624360.6751270.337564
1370.6375530.7248940.362447
1380.7151270.5697470.284873
1390.6858540.6282930.314146
1400.6621030.6757940.337897
1410.7597320.4805350.240268
1420.7805480.4389050.219452
1430.760850.47830.23915
1440.7400980.5198050.259902
1450.7185930.5628140.281407
1460.6898510.6202980.310149
1470.6670010.6659970.332999
1480.6434240.7131530.356576
1490.6192730.7614530.380727
1500.5947980.8104040.405202
1510.6104820.7790350.389518
1520.5864610.8270790.413539
1530.5619160.8761680.438084
1540.5282070.9435850.471793
1550.4986180.9972350.501382
1560.466730.933460.53327
1570.4418650.883730.558135
1580.4389070.8778140.561093
1590.414190.828380.58581
1600.391580.7831590.60842
1610.3639590.7279180.636041
1620.3375070.6750140.662493
1630.3074550.614910.692545
1640.326190.652380.67381
1650.3039790.6079590.696021
1660.2937380.5874750.706262
1670.2727840.5455680.727216
1680.2447060.4894120.755294
1690.3157860.6315730.684214
1700.3314340.6628680.668566
1710.3458230.6916450.654177
1720.3145790.6291580.685421
1730.2845880.5691760.715412
1740.2565050.5130090.743495
1750.2555050.511010.744495
1760.3054930.6109850.694507
1770.2842640.5685270.715736
1780.2971590.5943170.702841
1790.3104030.6208070.689597
1800.5772780.8454440.422722
1810.5431360.9137280.456864
1820.5109070.9781860.489093
1830.5740020.8519970.425998
1840.5492280.9015440.450772
1850.5139170.9721660.486083
1860.4998850.9997710.500115
1870.468140.936280.53186
1880.4877110.9754230.512289
1890.5126740.9746520.487326
1900.4760350.9520690.523965
1910.4465260.8930510.553474
1920.4132860.8265720.586714
1930.3819790.7639580.618021
1940.3563290.7126570.643671
1950.3728650.7457290.627135
1960.3378470.6756950.662153
1970.354480.708960.64552
1980.3235020.6470040.676498
1990.3653150.730630.634685
2000.3528760.7057520.647124
2010.3409230.6818470.659077
2020.3099930.6199860.690007
2030.3030940.6061880.696906
2040.2783830.5567660.721617
2050.2689690.5379380.731031
2060.2880380.5760760.711962
2070.6750420.6499160.324958
2080.6975680.6048650.302432
2090.6686140.6627730.331386
2100.6309370.7381260.369063
2110.6225070.7549860.377493
2120.5908650.818270.409135
2130.5594830.8810350.440517
2140.5265330.9469340.473467
2150.4916450.983290.508355
2160.4862810.9725610.513719
2170.4776740.9553490.522326
2180.4452410.8904820.554759
2190.4037960.8075930.596204
2200.4276080.8552170.572392
2210.3858770.7717540.614123
2220.3722920.7445830.627708
2230.3417570.6835150.658243
2240.3653540.7307080.634646
2250.4605140.9210290.539486
2260.4274060.8548120.572594
2270.4790190.9580390.520981
2280.4552810.9105630.544719
2290.4282070.8564130.571793
2300.4024080.8048150.597592
2310.3946330.7892650.605367
2320.3875340.7750690.612466
2330.4847110.9694210.515289
2340.4370220.8740440.562978
2350.5236180.9527650.476382
2360.4804860.9609720.519514
2370.4310370.8620750.568963
2380.47370.9474010.5263
2390.5253220.9493560.474678
2400.524330.951340.47567
2410.4916610.9833230.508339
2420.5068870.9862260.493113
2430.5135740.9728520.486426
2440.4875290.9750580.512471
2450.447670.8953390.55233
2460.4524450.9048890.547555
2470.3983510.7967010.601649
2480.3461410.6922820.653859
2490.3571150.714230.642885
2500.3296890.6593790.670311
2510.3013160.6026320.698684
2520.2512270.5024540.748773
2530.2180.4359990.782
2540.1758830.3517670.824117
2550.203330.4066610.79667
2560.2836480.5672960.716352
2570.2363070.4726130.763693
2580.246120.492240.75388
2590.2904680.5809360.709532
2600.2482160.4964320.751784
2610.3975660.7951330.602434
2620.3681760.7363520.631824
2630.3024940.6049870.697506
2640.2320160.4640320.767984
2650.2447680.4895360.755232
2660.2126540.4253070.787346
2670.1472770.2945550.852723
2680.525010.949980.47499
2690.7912250.417550.208775
2700.6681170.6637660.331883
2710.5004980.9990040.499502






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00374532OK
10% type I error level150.0561798OK

\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 & 0 & 0 & OK \tabularnewline
5% type I error level & 1 & 0.00374532 & OK \tabularnewline
10% type I error level & 15 & 0.0561798 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268481&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]1[/C][C]0.00374532[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]15[/C][C]0.0561798[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268481&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268481&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 level00OK
5% type I error level10.00374532OK
10% type I error level150.0561798OK


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):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- '1'
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')
}