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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 17 Dec 2014 20:55:38 +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/17/t141884977342g6grfvtzi3uz7.htm/, Retrieved Thu, 16 May 2024 09:48:45 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270681, Retrieved Thu, 16 May 2024 09:48:45 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact89

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Multipleregression] [2014-12-14 15:14:52] [7c87d1c7801dd67c2a0c90c2b6a05b3c]
-   PD    [Multiple Regression] [regersvgl] [2014-12-17 20:55:38] [21b927ddce509724d48ffb8407994bd0] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26 21 12.9
37 22 12.8
67 18 7.4
43 23 6.7
52 12 12.6
52 20 14.8
43 22 13.3
84 21 11.1
67 19 8.2
49 22 11.4
70 15 6.4
58 19 12
68 18 6.3
62 15 11.3
43 20 11.9
56 21 9.3
74 15 10
63 23 13.8
58 21 10.8
63 25 11.7
53 9 10.9
57 30 16.1
64 23 9.9
53 16 11.5
29 16 8.3
54 19 11.7
58 25 9
51 23 10.8
54 10 10.4
56 14 12.7
47 26 11.8
50 24 13
35 24 10.8
30 18 12.3
68 23 11.3
56 23 11.6
43 19 10.9
67 21 12.1
62 18 13.3
57 27 10.1
54 13 14.3
61 28 9.3
56 23 12.5
41 21 7.6
53 19 9.2
46 17 14.5
51 25 12.3
37 14 12.6
42 16 13
38 24 12.6
66 20 13.2
53 24 7.7
49 22 10.5
49 22 10.9
59 20 4.3
40 10 10.3
63 22 11.4
34 20 5.6
32 22 8.8
67 20 9
61 17 9.6
60 18 6.4
63 19 11.6
52 23 4.35
16 22 12.7
46 21 18.1
56 25 17.85
52 30 16.6
55 17 12.6
50 27 17.1
59 23 19.1
60 23 16.1
52 18 13.35
44 18 18.4
67 23 14.7
52 19 10.6
55 15 12.6
37 20 16.2
54 16 13.6
72 24 18.9
51 25 14.1
48 25 14.5
60 19 16.15
50 19 14.75
63 16 14.8
33 19 12.45
67 19 12.65
46 23 17.35
54 21 8.6
59 22 18.4
61 19 16.1
33 20 11.6
47 20 17.75
69 3 15.25
52 23 17.65
55 23 16.35
41 20 17.65
73 15 13.6
52 16 14.35
50 7 14.75
51 24 18.25
60 17 9.9
56 24 16
56 24 18.25
29 19 16.85
66 25 14.6
66 20 13.85
73 28 18.95
55 23 15.6
64 27 14.85
40 18 11.75
46 28 18.45
58 21 15.9
43 19 17.1
61 23 16.1
51 27 19.9
50 22 10.95
52 28 18.45
54 25 15.1
66 21 15
61 22 11.35
80 28 15.95
51 20 18.1
56 29 14.6
56 25 15.4
56 25 15.4
53 20 17.6
47 20 13.35
25 16 19.1
47 20 15.35
46 20 7.6
50 23 13.4
39 18 13.9
51 25 19.1
58 18 15.25
35 19 12.9
58 25 16.1
60 25 17.35
62 25 13.15
63 24 12.15
53 19 12.6
46 26 10.35
67 10 15.4
59 17 9.6
64 13 18.2
38 17 13.6
50 30 14.85
48 25 14.75
48 4 14.1
47 16 14.9
66 21 16.25
47 23 19.25
63 22 13.6
58 17 13.6
44 20 15.65
51 20 12.75
43 22 14.6
55 16 9.85
38 23 12.65
45 0 19.2
50 18 16.6
54 25 11.2
57 23 15.25
60 12 11.9
55 18 13.2
56 24 16.35
49 11 12.4
37 18 15.85
59 23 18.15
46 24 11.15
51 29 15.65
58 18 17.75
64 15 7.65
53 29 12.35
48 16 15.6
51 19 19.3
47 22 15.2
59 16 17.1
62 23 15.6
62 23 18.4
51 19 19.05
64 4 18.55
52 20 19.1
67 24 13.1
50 20 12.85
54 4 9.5
58 24 4.5
56 22 11.85
63 16 13.6
31 3 11.7
65 15 12.4
71 24 13.35
50 17 11.4
57 20 14.9
47 27 19.9
47 26 11.2
57 23 14.6
43 17 17.6
41 20 14.05
63 22 16.1
63 19 13.35
56 24 11.85
51 19 11.95
50 23 14.75
22 15 15.15
41 27 13.2
59 26 16.85
56 22 7.85
66 22 7.7
53 18 12.6
42 15 7.85
52 22 10.95
54 27 12.35
44 10 9.95
62 20 14.9
53 17 16.65
50 23 13.4
36 19 13.95
76 13 15.7
66 27 16.85
62 23 10.95
59 16 15.35
47 25 12.2
55 2 15.1
58 26 17.75
60 20 15.2
44 23 14.6
57 22 16.65
45 24 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

\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
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&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]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 12.3279 -0.00157115AMS.I[t] + 0.061896NUMERACYTOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  12.3279 -0.00157115AMS.I[t] +  0.061896NUMERACYTOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  12.3279 -0.00157115AMS.I[t] +  0.061896NUMERACYTOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 12.3279 -0.00157115AMS.I[t] + 0.061896NUMERACYTOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)12.32791.371828.9871.03586e-165.17929e-17
AMS.I-0.001571150.0208876-0.075220.9401070.470053
NUMERACYTOT0.0618960.04217221.4680.1435770.0717886

\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) & 12.3279 & 1.37182 & 8.987 & 1.03586e-16 & 5.17929e-17 \tabularnewline
AMS.I & -0.00157115 & 0.0208876 & -0.07522 & 0.940107 & 0.470053 \tabularnewline
NUMERACYTOT & 0.061896 & 0.0421722 & 1.468 & 0.143577 & 0.0717886 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&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]12.3279[/C][C]1.37182[/C][C]8.987[/C][C]1.03586e-16[/C][C]5.17929e-17[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00157115[/C][C]0.0208876[/C][C]-0.07522[/C][C]0.940107[/C][C]0.470053[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.061896[/C][C]0.0421722[/C][C]1.468[/C][C]0.143577[/C][C]0.0717886[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&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)12.32791.371828.9871.03586e-165.17929e-17
AMS.I-0.001571150.0208876-0.075220.9401070.470053
NUMERACYTOT0.0618960.04217221.4680.1435770.0717886






Multiple Linear Regression - Regression Statistics
Multiple R0.0971798
R-squared0.00944392
Adjusted R-squared0.000677938
F-TEST (value)1.07734
F-TEST (DF numerator)2
F-TEST (DF denominator)226
p-value0.342243
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.32419
Sum Squared Residuals2497.35

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.0971798 \tabularnewline
R-squared & 0.00944392 \tabularnewline
Adjusted R-squared & 0.000677938 \tabularnewline
F-TEST (value) & 1.07734 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 226 \tabularnewline
p-value & 0.342243 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.32419 \tabularnewline
Sum Squared Residuals & 2497.35 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.0971798[/C][/ROW]
[ROW][C]R-squared[/C][C]0.00944392[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.000677938[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.07734[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]226[/C][/ROW]
[ROW][C]p-value[/C][C]0.342243[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.32419[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2497.35[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&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 R0.0971798
R-squared0.00944392
Adjusted R-squared0.000677938
F-TEST (value)1.07734
F-TEST (DF numerator)2
F-TEST (DF denominator)226
p-value0.342243
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.32419
Sum Squared Residuals2497.35






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.5869-0.6869
212.813.6315-0.831514
37.413.3368-5.9368
46.713.684-6.98398
512.612.989-0.388986
614.813.48421.31585
713.313.6221-0.322087
811.113.4958-2.39577
98.213.3987-5.19869
1011.413.6127-2.21266
116.413.1464-6.74639
121213.4128-1.41283
136.313.3352-7.03522
1411.313.159-1.85896
1511.913.4983-1.59829
169.313.5398-4.23977
171013.1401-3.14011
1813.813.65260.14744
1910.813.5366-2.73662
2011.713.7764-2.07635
2110.912.8017-1.90173
2216.114.09532.00474
239.913.651-3.75099
2411.513.235-1.735
258.313.2727-4.97271
2611.713.4191-1.71912
27913.7842-4.78421
2810.813.6714-2.87141
2910.412.8621-2.46205
3012.713.1065-0.406494
3111.813.8634-2.06339
321313.7349-0.734881
3310.813.7584-2.95845
3412.313.3949-1.09493
3511.313.6447-2.3447
3611.613.6636-2.06356
3710.913.4364-2.5364
3812.113.5225-1.42248
3913.313.3447-0.044651
4010.113.9096-3.80957
4114.313.04771.25226
429.313.9652-4.66518
4312.513.6636-1.16356
447.613.5633-5.96333
459.213.4207-4.22069
4614.513.30791.19211
4712.313.7952-1.49521
4812.613.1363-0.536346
491313.2523-0.252282
5012.613.7537-1.15373
5113.213.4622-0.262158
527.713.7302-6.03017
5310.513.6127-3.11266
5410.913.6127-2.71266
554.313.4732-9.17316
5610.312.884-2.58405
5711.413.5907-2.19066
585.613.5124-7.91244
598.813.6394-4.83937
60913.4606-4.46059
619.613.2843-3.68433
626.413.3478-6.94779
6311.613.405-1.80498
644.3513.6698-9.31984
6512.713.6645-0.964508
6618.113.55554.54452
6717.8513.78734.06265
6816.614.10312.49689
6912.613.2938-0.693753
7017.113.92063.17943
7119.113.65885.44116
7216.113.65732.44273
7313.3513.3604-0.0103625
7418.413.37295.02707
7514.713.64631.05372
7610.613.4223-2.82226
7712.613.17-0.569961
7816.213.50772.69228
7913.613.23340.366572
8018.913.70035.19968
8114.113.79520.304794
8214.513.79990.700081
8316.1513.40972.74031
8414.7513.42541.3246
8514.813.21931.58071
8612.4513.4521-1.00211
8712.6513.3987-0.748691
8817.3513.67933.67073
898.613.5429-4.94291
9018.413.59694.80305
9116.113.40812.69188
9211.613.514-1.91401
9317.7513.4924.25799
9415.2512.40522.84479
9517.6513.66983.98016
9616.3513.66512.68487
9717.6513.50144.14856
9813.613.14170.45832
9914.3513.23661.11343
10014.7512.68262.06735
10118.2513.73334.51669
1029.913.2859-3.3859
1031613.72552.27455
10418.2513.72554.52455
10516.8513.45843.39161
10614.613.77160.828362
10713.8513.46220.387842
10818.9513.94635.00367
10915.613.66511.93487
11014.8513.89860.951427
11111.7513.3792-1.62922
11218.4513.98874.46125
11315.913.53662.36338
11417.113.43643.6636
11516.113.65572.4443
11619.913.9195.981
11710.9513.6111-2.66109
11818.4513.97934.47068
11915.113.79051.30951
1201513.52411.47595
12111.3513.5938-2.24381
12215.9513.93532.01467
12318.113.48574.61427
12414.614.03490.565066
12515.413.78731.61265
12615.413.78731.61265
12717.613.48264.11742
12813.3513.492-0.14201
12919.113.2795.82101
13015.3513.4921.85799
1317.613.4936-5.89358
13213.413.673-0.272985
13313.913.38080.519213
13419.113.79525.30479
13515.2513.35091.89906
13612.913.449-0.548968
13716.113.78422.31579
13817.3513.78113.56893
13913.1513.7779-0.627923
14012.1513.7145-1.56446
14112.613.4207-0.820687
14210.3513.865-3.51496
14315.412.84162.55837
1449.613.2875-3.68747
14518.213.0325.16797
14613.613.32050.279537
14714.8514.10630.743743
14814.7513.79990.950081
14914.112.50011.5999
15014.913.24441.65557
15116.2513.52412.72595
15219.2513.67775.5723
15313.613.59070.00933613
15413.613.2890.31096
15515.6513.49672.15328
15612.7513.4857-0.735726
15714.613.62210.977913
1589.8513.2319-3.38186
15912.6513.6918-1.04184
16019.212.25726.94277
16116.613.36353.2365
16211.213.7905-2.59049
16315.2513.6621.58801
16411.912.9764-1.07642
16513.213.3556-0.155649
16616.3513.72552.62455
16712.412.9318-0.531804
16815.8513.38392.46607
16918.1513.65884.49116
17011.1513.7412-2.59117
17115.6514.04281.60721
17217.7513.35094.39906
1737.6513.1558-5.50582
17412.3514.0396-1.68965
17515.613.24292.35714
17619.313.42385.87617
17715.213.61581.5842
17817.113.22563.87443
17915.613.65411.94587
18018.413.65414.74587
18119.0513.42385.62617
18218.5512.4756.07504
18319.113.48425.61585
18413.113.7082-0.608171
18512.8513.4873-0.637297
1869.512.4907-2.99068
1874.513.7223-9.22231
18811.8513.6017-1.75166
18913.613.21930.380712
19011.712.4649-0.764917
19112.413.1542-0.75425
19213.3513.7019-0.351887
19311.413.3016-1.90161
19414.913.47631.4237
19519.913.92535.97472
19611.213.8634-2.66339
19714.613.6620.938013
19817.613.31264.28739
19914.0513.50140.548563
20016.113.59072.50934
20113.3513.405-0.0549759
20211.8513.7255-1.87545
20311.9513.4238-1.47383
20414.7513.6731.07702
20515.1513.22181.92819
20613.213.9347-0.734709
20716.8513.84453.00547
2087.8513.6017-5.75166
2097.713.586-5.88595
21012.613.3588-0.758791
2117.8513.1904-5.34039
21210.9513.6079-2.65795
21312.3513.9143-1.56428
2149.9512.8778-2.92776
21514.913.46841.43156
21616.6513.29693.3531
21713.413.673-0.272985
21813.9513.44740.502603
21915.713.01322.68683
22016.8513.89542.95457
22110.9513.6541-2.70413
22215.3513.22562.12443
22312.213.8015-1.60149
22415.112.36532.73469
22517.7513.84613.9039
22615.213.47161.72841
22714.613.68240.917588
22816.6513.60013.04991
2298.113.7427-5.64274

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.5869 & -0.6869 \tabularnewline
2 & 12.8 & 13.6315 & -0.831514 \tabularnewline
3 & 7.4 & 13.3368 & -5.9368 \tabularnewline
4 & 6.7 & 13.684 & -6.98398 \tabularnewline
5 & 12.6 & 12.989 & -0.388986 \tabularnewline
6 & 14.8 & 13.4842 & 1.31585 \tabularnewline
7 & 13.3 & 13.6221 & -0.322087 \tabularnewline
8 & 11.1 & 13.4958 & -2.39577 \tabularnewline
9 & 8.2 & 13.3987 & -5.19869 \tabularnewline
10 & 11.4 & 13.6127 & -2.21266 \tabularnewline
11 & 6.4 & 13.1464 & -6.74639 \tabularnewline
12 & 12 & 13.4128 & -1.41283 \tabularnewline
13 & 6.3 & 13.3352 & -7.03522 \tabularnewline
14 & 11.3 & 13.159 & -1.85896 \tabularnewline
15 & 11.9 & 13.4983 & -1.59829 \tabularnewline
16 & 9.3 & 13.5398 & -4.23977 \tabularnewline
17 & 10 & 13.1401 & -3.14011 \tabularnewline
18 & 13.8 & 13.6526 & 0.14744 \tabularnewline
19 & 10.8 & 13.5366 & -2.73662 \tabularnewline
20 & 11.7 & 13.7764 & -2.07635 \tabularnewline
21 & 10.9 & 12.8017 & -1.90173 \tabularnewline
22 & 16.1 & 14.0953 & 2.00474 \tabularnewline
23 & 9.9 & 13.651 & -3.75099 \tabularnewline
24 & 11.5 & 13.235 & -1.735 \tabularnewline
25 & 8.3 & 13.2727 & -4.97271 \tabularnewline
26 & 11.7 & 13.4191 & -1.71912 \tabularnewline
27 & 9 & 13.7842 & -4.78421 \tabularnewline
28 & 10.8 & 13.6714 & -2.87141 \tabularnewline
29 & 10.4 & 12.8621 & -2.46205 \tabularnewline
30 & 12.7 & 13.1065 & -0.406494 \tabularnewline
31 & 11.8 & 13.8634 & -2.06339 \tabularnewline
32 & 13 & 13.7349 & -0.734881 \tabularnewline
33 & 10.8 & 13.7584 & -2.95845 \tabularnewline
34 & 12.3 & 13.3949 & -1.09493 \tabularnewline
35 & 11.3 & 13.6447 & -2.3447 \tabularnewline
36 & 11.6 & 13.6636 & -2.06356 \tabularnewline
37 & 10.9 & 13.4364 & -2.5364 \tabularnewline
38 & 12.1 & 13.5225 & -1.42248 \tabularnewline
39 & 13.3 & 13.3447 & -0.044651 \tabularnewline
40 & 10.1 & 13.9096 & -3.80957 \tabularnewline
41 & 14.3 & 13.0477 & 1.25226 \tabularnewline
42 & 9.3 & 13.9652 & -4.66518 \tabularnewline
43 & 12.5 & 13.6636 & -1.16356 \tabularnewline
44 & 7.6 & 13.5633 & -5.96333 \tabularnewline
45 & 9.2 & 13.4207 & -4.22069 \tabularnewline
46 & 14.5 & 13.3079 & 1.19211 \tabularnewline
47 & 12.3 & 13.7952 & -1.49521 \tabularnewline
48 & 12.6 & 13.1363 & -0.536346 \tabularnewline
49 & 13 & 13.2523 & -0.252282 \tabularnewline
50 & 12.6 & 13.7537 & -1.15373 \tabularnewline
51 & 13.2 & 13.4622 & -0.262158 \tabularnewline
52 & 7.7 & 13.7302 & -6.03017 \tabularnewline
53 & 10.5 & 13.6127 & -3.11266 \tabularnewline
54 & 10.9 & 13.6127 & -2.71266 \tabularnewline
55 & 4.3 & 13.4732 & -9.17316 \tabularnewline
56 & 10.3 & 12.884 & -2.58405 \tabularnewline
57 & 11.4 & 13.5907 & -2.19066 \tabularnewline
58 & 5.6 & 13.5124 & -7.91244 \tabularnewline
59 & 8.8 & 13.6394 & -4.83937 \tabularnewline
60 & 9 & 13.4606 & -4.46059 \tabularnewline
61 & 9.6 & 13.2843 & -3.68433 \tabularnewline
62 & 6.4 & 13.3478 & -6.94779 \tabularnewline
63 & 11.6 & 13.405 & -1.80498 \tabularnewline
64 & 4.35 & 13.6698 & -9.31984 \tabularnewline
65 & 12.7 & 13.6645 & -0.964508 \tabularnewline
66 & 18.1 & 13.5555 & 4.54452 \tabularnewline
67 & 17.85 & 13.7873 & 4.06265 \tabularnewline
68 & 16.6 & 14.1031 & 2.49689 \tabularnewline
69 & 12.6 & 13.2938 & -0.693753 \tabularnewline
70 & 17.1 & 13.9206 & 3.17943 \tabularnewline
71 & 19.1 & 13.6588 & 5.44116 \tabularnewline
72 & 16.1 & 13.6573 & 2.44273 \tabularnewline
73 & 13.35 & 13.3604 & -0.0103625 \tabularnewline
74 & 18.4 & 13.3729 & 5.02707 \tabularnewline
75 & 14.7 & 13.6463 & 1.05372 \tabularnewline
76 & 10.6 & 13.4223 & -2.82226 \tabularnewline
77 & 12.6 & 13.17 & -0.569961 \tabularnewline
78 & 16.2 & 13.5077 & 2.69228 \tabularnewline
79 & 13.6 & 13.2334 & 0.366572 \tabularnewline
80 & 18.9 & 13.7003 & 5.19968 \tabularnewline
81 & 14.1 & 13.7952 & 0.304794 \tabularnewline
82 & 14.5 & 13.7999 & 0.700081 \tabularnewline
83 & 16.15 & 13.4097 & 2.74031 \tabularnewline
84 & 14.75 & 13.4254 & 1.3246 \tabularnewline
85 & 14.8 & 13.2193 & 1.58071 \tabularnewline
86 & 12.45 & 13.4521 & -1.00211 \tabularnewline
87 & 12.65 & 13.3987 & -0.748691 \tabularnewline
88 & 17.35 & 13.6793 & 3.67073 \tabularnewline
89 & 8.6 & 13.5429 & -4.94291 \tabularnewline
90 & 18.4 & 13.5969 & 4.80305 \tabularnewline
91 & 16.1 & 13.4081 & 2.69188 \tabularnewline
92 & 11.6 & 13.514 & -1.91401 \tabularnewline
93 & 17.75 & 13.492 & 4.25799 \tabularnewline
94 & 15.25 & 12.4052 & 2.84479 \tabularnewline
95 & 17.65 & 13.6698 & 3.98016 \tabularnewline
96 & 16.35 & 13.6651 & 2.68487 \tabularnewline
97 & 17.65 & 13.5014 & 4.14856 \tabularnewline
98 & 13.6 & 13.1417 & 0.45832 \tabularnewline
99 & 14.35 & 13.2366 & 1.11343 \tabularnewline
100 & 14.75 & 12.6826 & 2.06735 \tabularnewline
101 & 18.25 & 13.7333 & 4.51669 \tabularnewline
102 & 9.9 & 13.2859 & -3.3859 \tabularnewline
103 & 16 & 13.7255 & 2.27455 \tabularnewline
104 & 18.25 & 13.7255 & 4.52455 \tabularnewline
105 & 16.85 & 13.4584 & 3.39161 \tabularnewline
106 & 14.6 & 13.7716 & 0.828362 \tabularnewline
107 & 13.85 & 13.4622 & 0.387842 \tabularnewline
108 & 18.95 & 13.9463 & 5.00367 \tabularnewline
109 & 15.6 & 13.6651 & 1.93487 \tabularnewline
110 & 14.85 & 13.8986 & 0.951427 \tabularnewline
111 & 11.75 & 13.3792 & -1.62922 \tabularnewline
112 & 18.45 & 13.9887 & 4.46125 \tabularnewline
113 & 15.9 & 13.5366 & 2.36338 \tabularnewline
114 & 17.1 & 13.4364 & 3.6636 \tabularnewline
115 & 16.1 & 13.6557 & 2.4443 \tabularnewline
116 & 19.9 & 13.919 & 5.981 \tabularnewline
117 & 10.95 & 13.6111 & -2.66109 \tabularnewline
118 & 18.45 & 13.9793 & 4.47068 \tabularnewline
119 & 15.1 & 13.7905 & 1.30951 \tabularnewline
120 & 15 & 13.5241 & 1.47595 \tabularnewline
121 & 11.35 & 13.5938 & -2.24381 \tabularnewline
122 & 15.95 & 13.9353 & 2.01467 \tabularnewline
123 & 18.1 & 13.4857 & 4.61427 \tabularnewline
124 & 14.6 & 14.0349 & 0.565066 \tabularnewline
125 & 15.4 & 13.7873 & 1.61265 \tabularnewline
126 & 15.4 & 13.7873 & 1.61265 \tabularnewline
127 & 17.6 & 13.4826 & 4.11742 \tabularnewline
128 & 13.35 & 13.492 & -0.14201 \tabularnewline
129 & 19.1 & 13.279 & 5.82101 \tabularnewline
130 & 15.35 & 13.492 & 1.85799 \tabularnewline
131 & 7.6 & 13.4936 & -5.89358 \tabularnewline
132 & 13.4 & 13.673 & -0.272985 \tabularnewline
133 & 13.9 & 13.3808 & 0.519213 \tabularnewline
134 & 19.1 & 13.7952 & 5.30479 \tabularnewline
135 & 15.25 & 13.3509 & 1.89906 \tabularnewline
136 & 12.9 & 13.449 & -0.548968 \tabularnewline
137 & 16.1 & 13.7842 & 2.31579 \tabularnewline
138 & 17.35 & 13.7811 & 3.56893 \tabularnewline
139 & 13.15 & 13.7779 & -0.627923 \tabularnewline
140 & 12.15 & 13.7145 & -1.56446 \tabularnewline
141 & 12.6 & 13.4207 & -0.820687 \tabularnewline
142 & 10.35 & 13.865 & -3.51496 \tabularnewline
143 & 15.4 & 12.8416 & 2.55837 \tabularnewline
144 & 9.6 & 13.2875 & -3.68747 \tabularnewline
145 & 18.2 & 13.032 & 5.16797 \tabularnewline
146 & 13.6 & 13.3205 & 0.279537 \tabularnewline
147 & 14.85 & 14.1063 & 0.743743 \tabularnewline
148 & 14.75 & 13.7999 & 0.950081 \tabularnewline
149 & 14.1 & 12.5001 & 1.5999 \tabularnewline
150 & 14.9 & 13.2444 & 1.65557 \tabularnewline
151 & 16.25 & 13.5241 & 2.72595 \tabularnewline
152 & 19.25 & 13.6777 & 5.5723 \tabularnewline
153 & 13.6 & 13.5907 & 0.00933613 \tabularnewline
154 & 13.6 & 13.289 & 0.31096 \tabularnewline
155 & 15.65 & 13.4967 & 2.15328 \tabularnewline
156 & 12.75 & 13.4857 & -0.735726 \tabularnewline
157 & 14.6 & 13.6221 & 0.977913 \tabularnewline
158 & 9.85 & 13.2319 & -3.38186 \tabularnewline
159 & 12.65 & 13.6918 & -1.04184 \tabularnewline
160 & 19.2 & 12.2572 & 6.94277 \tabularnewline
161 & 16.6 & 13.3635 & 3.2365 \tabularnewline
162 & 11.2 & 13.7905 & -2.59049 \tabularnewline
163 & 15.25 & 13.662 & 1.58801 \tabularnewline
164 & 11.9 & 12.9764 & -1.07642 \tabularnewline
165 & 13.2 & 13.3556 & -0.155649 \tabularnewline
166 & 16.35 & 13.7255 & 2.62455 \tabularnewline
167 & 12.4 & 12.9318 & -0.531804 \tabularnewline
168 & 15.85 & 13.3839 & 2.46607 \tabularnewline
169 & 18.15 & 13.6588 & 4.49116 \tabularnewline
170 & 11.15 & 13.7412 & -2.59117 \tabularnewline
171 & 15.65 & 14.0428 & 1.60721 \tabularnewline
172 & 17.75 & 13.3509 & 4.39906 \tabularnewline
173 & 7.65 & 13.1558 & -5.50582 \tabularnewline
174 & 12.35 & 14.0396 & -1.68965 \tabularnewline
175 & 15.6 & 13.2429 & 2.35714 \tabularnewline
176 & 19.3 & 13.4238 & 5.87617 \tabularnewline
177 & 15.2 & 13.6158 & 1.5842 \tabularnewline
178 & 17.1 & 13.2256 & 3.87443 \tabularnewline
179 & 15.6 & 13.6541 & 1.94587 \tabularnewline
180 & 18.4 & 13.6541 & 4.74587 \tabularnewline
181 & 19.05 & 13.4238 & 5.62617 \tabularnewline
182 & 18.55 & 12.475 & 6.07504 \tabularnewline
183 & 19.1 & 13.4842 & 5.61585 \tabularnewline
184 & 13.1 & 13.7082 & -0.608171 \tabularnewline
185 & 12.85 & 13.4873 & -0.637297 \tabularnewline
186 & 9.5 & 12.4907 & -2.99068 \tabularnewline
187 & 4.5 & 13.7223 & -9.22231 \tabularnewline
188 & 11.85 & 13.6017 & -1.75166 \tabularnewline
189 & 13.6 & 13.2193 & 0.380712 \tabularnewline
190 & 11.7 & 12.4649 & -0.764917 \tabularnewline
191 & 12.4 & 13.1542 & -0.75425 \tabularnewline
192 & 13.35 & 13.7019 & -0.351887 \tabularnewline
193 & 11.4 & 13.3016 & -1.90161 \tabularnewline
194 & 14.9 & 13.4763 & 1.4237 \tabularnewline
195 & 19.9 & 13.9253 & 5.97472 \tabularnewline
196 & 11.2 & 13.8634 & -2.66339 \tabularnewline
197 & 14.6 & 13.662 & 0.938013 \tabularnewline
198 & 17.6 & 13.3126 & 4.28739 \tabularnewline
199 & 14.05 & 13.5014 & 0.548563 \tabularnewline
200 & 16.1 & 13.5907 & 2.50934 \tabularnewline
201 & 13.35 & 13.405 & -0.0549759 \tabularnewline
202 & 11.85 & 13.7255 & -1.87545 \tabularnewline
203 & 11.95 & 13.4238 & -1.47383 \tabularnewline
204 & 14.75 & 13.673 & 1.07702 \tabularnewline
205 & 15.15 & 13.2218 & 1.92819 \tabularnewline
206 & 13.2 & 13.9347 & -0.734709 \tabularnewline
207 & 16.85 & 13.8445 & 3.00547 \tabularnewline
208 & 7.85 & 13.6017 & -5.75166 \tabularnewline
209 & 7.7 & 13.586 & -5.88595 \tabularnewline
210 & 12.6 & 13.3588 & -0.758791 \tabularnewline
211 & 7.85 & 13.1904 & -5.34039 \tabularnewline
212 & 10.95 & 13.6079 & -2.65795 \tabularnewline
213 & 12.35 & 13.9143 & -1.56428 \tabularnewline
214 & 9.95 & 12.8778 & -2.92776 \tabularnewline
215 & 14.9 & 13.4684 & 1.43156 \tabularnewline
216 & 16.65 & 13.2969 & 3.3531 \tabularnewline
217 & 13.4 & 13.673 & -0.272985 \tabularnewline
218 & 13.95 & 13.4474 & 0.502603 \tabularnewline
219 & 15.7 & 13.0132 & 2.68683 \tabularnewline
220 & 16.85 & 13.8954 & 2.95457 \tabularnewline
221 & 10.95 & 13.6541 & -2.70413 \tabularnewline
222 & 15.35 & 13.2256 & 2.12443 \tabularnewline
223 & 12.2 & 13.8015 & -1.60149 \tabularnewline
224 & 15.1 & 12.3653 & 2.73469 \tabularnewline
225 & 17.75 & 13.8461 & 3.9039 \tabularnewline
226 & 15.2 & 13.4716 & 1.72841 \tabularnewline
227 & 14.6 & 13.6824 & 0.917588 \tabularnewline
228 & 16.65 & 13.6001 & 3.04991 \tabularnewline
229 & 8.1 & 13.7427 & -5.64274 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.5869[/C][C]-0.6869[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]13.6315[/C][C]-0.831514[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.3368[/C][C]-5.9368[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]13.684[/C][C]-6.98398[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]12.989[/C][C]-0.388986[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.4842[/C][C]1.31585[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]13.6221[/C][C]-0.322087[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.4958[/C][C]-2.39577[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]13.3987[/C][C]-5.19869[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.6127[/C][C]-2.21266[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]13.1464[/C][C]-6.74639[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.4128[/C][C]-1.41283[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]13.3352[/C][C]-7.03522[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]13.159[/C][C]-1.85896[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]13.4983[/C][C]-1.59829[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]13.5398[/C][C]-4.23977[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]13.1401[/C][C]-3.14011[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.6526[/C][C]0.14744[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.5366[/C][C]-2.73662[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.7764[/C][C]-2.07635[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]12.8017[/C][C]-1.90173[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]14.0953[/C][C]2.00474[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]13.651[/C][C]-3.75099[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]13.235[/C][C]-1.735[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]13.2727[/C][C]-4.97271[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.4191[/C][C]-1.71912[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]13.7842[/C][C]-4.78421[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]13.6714[/C][C]-2.87141[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]12.8621[/C][C]-2.46205[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]13.1065[/C][C]-0.406494[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]13.8634[/C][C]-2.06339[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.7349[/C][C]-0.734881[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]13.7584[/C][C]-2.95845[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]13.3949[/C][C]-1.09493[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.6447[/C][C]-2.3447[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]13.6636[/C][C]-2.06356[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.4364[/C][C]-2.5364[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]13.5225[/C][C]-1.42248[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.3447[/C][C]-0.044651[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.9096[/C][C]-3.80957[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]13.0477[/C][C]1.25226[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.9652[/C][C]-4.66518[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]13.6636[/C][C]-1.16356[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]13.5633[/C][C]-5.96333[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]13.4207[/C][C]-4.22069[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.3079[/C][C]1.19211[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.7952[/C][C]-1.49521[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]13.1363[/C][C]-0.536346[/C][/ROW]
[ROW][C]49[/C][C]13[/C][C]13.2523[/C][C]-0.252282[/C][/ROW]
[ROW][C]50[/C][C]12.6[/C][C]13.7537[/C][C]-1.15373[/C][/ROW]
[ROW][C]51[/C][C]13.2[/C][C]13.4622[/C][C]-0.262158[/C][/ROW]
[ROW][C]52[/C][C]7.7[/C][C]13.7302[/C][C]-6.03017[/C][/ROW]
[ROW][C]53[/C][C]10.5[/C][C]13.6127[/C][C]-3.11266[/C][/ROW]
[ROW][C]54[/C][C]10.9[/C][C]13.6127[/C][C]-2.71266[/C][/ROW]
[ROW][C]55[/C][C]4.3[/C][C]13.4732[/C][C]-9.17316[/C][/ROW]
[ROW][C]56[/C][C]10.3[/C][C]12.884[/C][C]-2.58405[/C][/ROW]
[ROW][C]57[/C][C]11.4[/C][C]13.5907[/C][C]-2.19066[/C][/ROW]
[ROW][C]58[/C][C]5.6[/C][C]13.5124[/C][C]-7.91244[/C][/ROW]
[ROW][C]59[/C][C]8.8[/C][C]13.6394[/C][C]-4.83937[/C][/ROW]
[ROW][C]60[/C][C]9[/C][C]13.4606[/C][C]-4.46059[/C][/ROW]
[ROW][C]61[/C][C]9.6[/C][C]13.2843[/C][C]-3.68433[/C][/ROW]
[ROW][C]62[/C][C]6.4[/C][C]13.3478[/C][C]-6.94779[/C][/ROW]
[ROW][C]63[/C][C]11.6[/C][C]13.405[/C][C]-1.80498[/C][/ROW]
[ROW][C]64[/C][C]4.35[/C][C]13.6698[/C][C]-9.31984[/C][/ROW]
[ROW][C]65[/C][C]12.7[/C][C]13.6645[/C][C]-0.964508[/C][/ROW]
[ROW][C]66[/C][C]18.1[/C][C]13.5555[/C][C]4.54452[/C][/ROW]
[ROW][C]67[/C][C]17.85[/C][C]13.7873[/C][C]4.06265[/C][/ROW]
[ROW][C]68[/C][C]16.6[/C][C]14.1031[/C][C]2.49689[/C][/ROW]
[ROW][C]69[/C][C]12.6[/C][C]13.2938[/C][C]-0.693753[/C][/ROW]
[ROW][C]70[/C][C]17.1[/C][C]13.9206[/C][C]3.17943[/C][/ROW]
[ROW][C]71[/C][C]19.1[/C][C]13.6588[/C][C]5.44116[/C][/ROW]
[ROW][C]72[/C][C]16.1[/C][C]13.6573[/C][C]2.44273[/C][/ROW]
[ROW][C]73[/C][C]13.35[/C][C]13.3604[/C][C]-0.0103625[/C][/ROW]
[ROW][C]74[/C][C]18.4[/C][C]13.3729[/C][C]5.02707[/C][/ROW]
[ROW][C]75[/C][C]14.7[/C][C]13.6463[/C][C]1.05372[/C][/ROW]
[ROW][C]76[/C][C]10.6[/C][C]13.4223[/C][C]-2.82226[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.17[/C][C]-0.569961[/C][/ROW]
[ROW][C]78[/C][C]16.2[/C][C]13.5077[/C][C]2.69228[/C][/ROW]
[ROW][C]79[/C][C]13.6[/C][C]13.2334[/C][C]0.366572[/C][/ROW]
[ROW][C]80[/C][C]18.9[/C][C]13.7003[/C][C]5.19968[/C][/ROW]
[ROW][C]81[/C][C]14.1[/C][C]13.7952[/C][C]0.304794[/C][/ROW]
[ROW][C]82[/C][C]14.5[/C][C]13.7999[/C][C]0.700081[/C][/ROW]
[ROW][C]83[/C][C]16.15[/C][C]13.4097[/C][C]2.74031[/C][/ROW]
[ROW][C]84[/C][C]14.75[/C][C]13.4254[/C][C]1.3246[/C][/ROW]
[ROW][C]85[/C][C]14.8[/C][C]13.2193[/C][C]1.58071[/C][/ROW]
[ROW][C]86[/C][C]12.45[/C][C]13.4521[/C][C]-1.00211[/C][/ROW]
[ROW][C]87[/C][C]12.65[/C][C]13.3987[/C][C]-0.748691[/C][/ROW]
[ROW][C]88[/C][C]17.35[/C][C]13.6793[/C][C]3.67073[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]13.5429[/C][C]-4.94291[/C][/ROW]
[ROW][C]90[/C][C]18.4[/C][C]13.5969[/C][C]4.80305[/C][/ROW]
[ROW][C]91[/C][C]16.1[/C][C]13.4081[/C][C]2.69188[/C][/ROW]
[ROW][C]92[/C][C]11.6[/C][C]13.514[/C][C]-1.91401[/C][/ROW]
[ROW][C]93[/C][C]17.75[/C][C]13.492[/C][C]4.25799[/C][/ROW]
[ROW][C]94[/C][C]15.25[/C][C]12.4052[/C][C]2.84479[/C][/ROW]
[ROW][C]95[/C][C]17.65[/C][C]13.6698[/C][C]3.98016[/C][/ROW]
[ROW][C]96[/C][C]16.35[/C][C]13.6651[/C][C]2.68487[/C][/ROW]
[ROW][C]97[/C][C]17.65[/C][C]13.5014[/C][C]4.14856[/C][/ROW]
[ROW][C]98[/C][C]13.6[/C][C]13.1417[/C][C]0.45832[/C][/ROW]
[ROW][C]99[/C][C]14.35[/C][C]13.2366[/C][C]1.11343[/C][/ROW]
[ROW][C]100[/C][C]14.75[/C][C]12.6826[/C][C]2.06735[/C][/ROW]
[ROW][C]101[/C][C]18.25[/C][C]13.7333[/C][C]4.51669[/C][/ROW]
[ROW][C]102[/C][C]9.9[/C][C]13.2859[/C][C]-3.3859[/C][/ROW]
[ROW][C]103[/C][C]16[/C][C]13.7255[/C][C]2.27455[/C][/ROW]
[ROW][C]104[/C][C]18.25[/C][C]13.7255[/C][C]4.52455[/C][/ROW]
[ROW][C]105[/C][C]16.85[/C][C]13.4584[/C][C]3.39161[/C][/ROW]
[ROW][C]106[/C][C]14.6[/C][C]13.7716[/C][C]0.828362[/C][/ROW]
[ROW][C]107[/C][C]13.85[/C][C]13.4622[/C][C]0.387842[/C][/ROW]
[ROW][C]108[/C][C]18.95[/C][C]13.9463[/C][C]5.00367[/C][/ROW]
[ROW][C]109[/C][C]15.6[/C][C]13.6651[/C][C]1.93487[/C][/ROW]
[ROW][C]110[/C][C]14.85[/C][C]13.8986[/C][C]0.951427[/C][/ROW]
[ROW][C]111[/C][C]11.75[/C][C]13.3792[/C][C]-1.62922[/C][/ROW]
[ROW][C]112[/C][C]18.45[/C][C]13.9887[/C][C]4.46125[/C][/ROW]
[ROW][C]113[/C][C]15.9[/C][C]13.5366[/C][C]2.36338[/C][/ROW]
[ROW][C]114[/C][C]17.1[/C][C]13.4364[/C][C]3.6636[/C][/ROW]
[ROW][C]115[/C][C]16.1[/C][C]13.6557[/C][C]2.4443[/C][/ROW]
[ROW][C]116[/C][C]19.9[/C][C]13.919[/C][C]5.981[/C][/ROW]
[ROW][C]117[/C][C]10.95[/C][C]13.6111[/C][C]-2.66109[/C][/ROW]
[ROW][C]118[/C][C]18.45[/C][C]13.9793[/C][C]4.47068[/C][/ROW]
[ROW][C]119[/C][C]15.1[/C][C]13.7905[/C][C]1.30951[/C][/ROW]
[ROW][C]120[/C][C]15[/C][C]13.5241[/C][C]1.47595[/C][/ROW]
[ROW][C]121[/C][C]11.35[/C][C]13.5938[/C][C]-2.24381[/C][/ROW]
[ROW][C]122[/C][C]15.95[/C][C]13.9353[/C][C]2.01467[/C][/ROW]
[ROW][C]123[/C][C]18.1[/C][C]13.4857[/C][C]4.61427[/C][/ROW]
[ROW][C]124[/C][C]14.6[/C][C]14.0349[/C][C]0.565066[/C][/ROW]
[ROW][C]125[/C][C]15.4[/C][C]13.7873[/C][C]1.61265[/C][/ROW]
[ROW][C]126[/C][C]15.4[/C][C]13.7873[/C][C]1.61265[/C][/ROW]
[ROW][C]127[/C][C]17.6[/C][C]13.4826[/C][C]4.11742[/C][/ROW]
[ROW][C]128[/C][C]13.35[/C][C]13.492[/C][C]-0.14201[/C][/ROW]
[ROW][C]129[/C][C]19.1[/C][C]13.279[/C][C]5.82101[/C][/ROW]
[ROW][C]130[/C][C]15.35[/C][C]13.492[/C][C]1.85799[/C][/ROW]
[ROW][C]131[/C][C]7.6[/C][C]13.4936[/C][C]-5.89358[/C][/ROW]
[ROW][C]132[/C][C]13.4[/C][C]13.673[/C][C]-0.272985[/C][/ROW]
[ROW][C]133[/C][C]13.9[/C][C]13.3808[/C][C]0.519213[/C][/ROW]
[ROW][C]134[/C][C]19.1[/C][C]13.7952[/C][C]5.30479[/C][/ROW]
[ROW][C]135[/C][C]15.25[/C][C]13.3509[/C][C]1.89906[/C][/ROW]
[ROW][C]136[/C][C]12.9[/C][C]13.449[/C][C]-0.548968[/C][/ROW]
[ROW][C]137[/C][C]16.1[/C][C]13.7842[/C][C]2.31579[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]13.7811[/C][C]3.56893[/C][/ROW]
[ROW][C]139[/C][C]13.15[/C][C]13.7779[/C][C]-0.627923[/C][/ROW]
[ROW][C]140[/C][C]12.15[/C][C]13.7145[/C][C]-1.56446[/C][/ROW]
[ROW][C]141[/C][C]12.6[/C][C]13.4207[/C][C]-0.820687[/C][/ROW]
[ROW][C]142[/C][C]10.35[/C][C]13.865[/C][C]-3.51496[/C][/ROW]
[ROW][C]143[/C][C]15.4[/C][C]12.8416[/C][C]2.55837[/C][/ROW]
[ROW][C]144[/C][C]9.6[/C][C]13.2875[/C][C]-3.68747[/C][/ROW]
[ROW][C]145[/C][C]18.2[/C][C]13.032[/C][C]5.16797[/C][/ROW]
[ROW][C]146[/C][C]13.6[/C][C]13.3205[/C][C]0.279537[/C][/ROW]
[ROW][C]147[/C][C]14.85[/C][C]14.1063[/C][C]0.743743[/C][/ROW]
[ROW][C]148[/C][C]14.75[/C][C]13.7999[/C][C]0.950081[/C][/ROW]
[ROW][C]149[/C][C]14.1[/C][C]12.5001[/C][C]1.5999[/C][/ROW]
[ROW][C]150[/C][C]14.9[/C][C]13.2444[/C][C]1.65557[/C][/ROW]
[ROW][C]151[/C][C]16.25[/C][C]13.5241[/C][C]2.72595[/C][/ROW]
[ROW][C]152[/C][C]19.25[/C][C]13.6777[/C][C]5.5723[/C][/ROW]
[ROW][C]153[/C][C]13.6[/C][C]13.5907[/C][C]0.00933613[/C][/ROW]
[ROW][C]154[/C][C]13.6[/C][C]13.289[/C][C]0.31096[/C][/ROW]
[ROW][C]155[/C][C]15.65[/C][C]13.4967[/C][C]2.15328[/C][/ROW]
[ROW][C]156[/C][C]12.75[/C][C]13.4857[/C][C]-0.735726[/C][/ROW]
[ROW][C]157[/C][C]14.6[/C][C]13.6221[/C][C]0.977913[/C][/ROW]
[ROW][C]158[/C][C]9.85[/C][C]13.2319[/C][C]-3.38186[/C][/ROW]
[ROW][C]159[/C][C]12.65[/C][C]13.6918[/C][C]-1.04184[/C][/ROW]
[ROW][C]160[/C][C]19.2[/C][C]12.2572[/C][C]6.94277[/C][/ROW]
[ROW][C]161[/C][C]16.6[/C][C]13.3635[/C][C]3.2365[/C][/ROW]
[ROW][C]162[/C][C]11.2[/C][C]13.7905[/C][C]-2.59049[/C][/ROW]
[ROW][C]163[/C][C]15.25[/C][C]13.662[/C][C]1.58801[/C][/ROW]
[ROW][C]164[/C][C]11.9[/C][C]12.9764[/C][C]-1.07642[/C][/ROW]
[ROW][C]165[/C][C]13.2[/C][C]13.3556[/C][C]-0.155649[/C][/ROW]
[ROW][C]166[/C][C]16.35[/C][C]13.7255[/C][C]2.62455[/C][/ROW]
[ROW][C]167[/C][C]12.4[/C][C]12.9318[/C][C]-0.531804[/C][/ROW]
[ROW][C]168[/C][C]15.85[/C][C]13.3839[/C][C]2.46607[/C][/ROW]
[ROW][C]169[/C][C]18.15[/C][C]13.6588[/C][C]4.49116[/C][/ROW]
[ROW][C]170[/C][C]11.15[/C][C]13.7412[/C][C]-2.59117[/C][/ROW]
[ROW][C]171[/C][C]15.65[/C][C]14.0428[/C][C]1.60721[/C][/ROW]
[ROW][C]172[/C][C]17.75[/C][C]13.3509[/C][C]4.39906[/C][/ROW]
[ROW][C]173[/C][C]7.65[/C][C]13.1558[/C][C]-5.50582[/C][/ROW]
[ROW][C]174[/C][C]12.35[/C][C]14.0396[/C][C]-1.68965[/C][/ROW]
[ROW][C]175[/C][C]15.6[/C][C]13.2429[/C][C]2.35714[/C][/ROW]
[ROW][C]176[/C][C]19.3[/C][C]13.4238[/C][C]5.87617[/C][/ROW]
[ROW][C]177[/C][C]15.2[/C][C]13.6158[/C][C]1.5842[/C][/ROW]
[ROW][C]178[/C][C]17.1[/C][C]13.2256[/C][C]3.87443[/C][/ROW]
[ROW][C]179[/C][C]15.6[/C][C]13.6541[/C][C]1.94587[/C][/ROW]
[ROW][C]180[/C][C]18.4[/C][C]13.6541[/C][C]4.74587[/C][/ROW]
[ROW][C]181[/C][C]19.05[/C][C]13.4238[/C][C]5.62617[/C][/ROW]
[ROW][C]182[/C][C]18.55[/C][C]12.475[/C][C]6.07504[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]13.4842[/C][C]5.61585[/C][/ROW]
[ROW][C]184[/C][C]13.1[/C][C]13.7082[/C][C]-0.608171[/C][/ROW]
[ROW][C]185[/C][C]12.85[/C][C]13.4873[/C][C]-0.637297[/C][/ROW]
[ROW][C]186[/C][C]9.5[/C][C]12.4907[/C][C]-2.99068[/C][/ROW]
[ROW][C]187[/C][C]4.5[/C][C]13.7223[/C][C]-9.22231[/C][/ROW]
[ROW][C]188[/C][C]11.85[/C][C]13.6017[/C][C]-1.75166[/C][/ROW]
[ROW][C]189[/C][C]13.6[/C][C]13.2193[/C][C]0.380712[/C][/ROW]
[ROW][C]190[/C][C]11.7[/C][C]12.4649[/C][C]-0.764917[/C][/ROW]
[ROW][C]191[/C][C]12.4[/C][C]13.1542[/C][C]-0.75425[/C][/ROW]
[ROW][C]192[/C][C]13.35[/C][C]13.7019[/C][C]-0.351887[/C][/ROW]
[ROW][C]193[/C][C]11.4[/C][C]13.3016[/C][C]-1.90161[/C][/ROW]
[ROW][C]194[/C][C]14.9[/C][C]13.4763[/C][C]1.4237[/C][/ROW]
[ROW][C]195[/C][C]19.9[/C][C]13.9253[/C][C]5.97472[/C][/ROW]
[ROW][C]196[/C][C]11.2[/C][C]13.8634[/C][C]-2.66339[/C][/ROW]
[ROW][C]197[/C][C]14.6[/C][C]13.662[/C][C]0.938013[/C][/ROW]
[ROW][C]198[/C][C]17.6[/C][C]13.3126[/C][C]4.28739[/C][/ROW]
[ROW][C]199[/C][C]14.05[/C][C]13.5014[/C][C]0.548563[/C][/ROW]
[ROW][C]200[/C][C]16.1[/C][C]13.5907[/C][C]2.50934[/C][/ROW]
[ROW][C]201[/C][C]13.35[/C][C]13.405[/C][C]-0.0549759[/C][/ROW]
[ROW][C]202[/C][C]11.85[/C][C]13.7255[/C][C]-1.87545[/C][/ROW]
[ROW][C]203[/C][C]11.95[/C][C]13.4238[/C][C]-1.47383[/C][/ROW]
[ROW][C]204[/C][C]14.75[/C][C]13.673[/C][C]1.07702[/C][/ROW]
[ROW][C]205[/C][C]15.15[/C][C]13.2218[/C][C]1.92819[/C][/ROW]
[ROW][C]206[/C][C]13.2[/C][C]13.9347[/C][C]-0.734709[/C][/ROW]
[ROW][C]207[/C][C]16.85[/C][C]13.8445[/C][C]3.00547[/C][/ROW]
[ROW][C]208[/C][C]7.85[/C][C]13.6017[/C][C]-5.75166[/C][/ROW]
[ROW][C]209[/C][C]7.7[/C][C]13.586[/C][C]-5.88595[/C][/ROW]
[ROW][C]210[/C][C]12.6[/C][C]13.3588[/C][C]-0.758791[/C][/ROW]
[ROW][C]211[/C][C]7.85[/C][C]13.1904[/C][C]-5.34039[/C][/ROW]
[ROW][C]212[/C][C]10.95[/C][C]13.6079[/C][C]-2.65795[/C][/ROW]
[ROW][C]213[/C][C]12.35[/C][C]13.9143[/C][C]-1.56428[/C][/ROW]
[ROW][C]214[/C][C]9.95[/C][C]12.8778[/C][C]-2.92776[/C][/ROW]
[ROW][C]215[/C][C]14.9[/C][C]13.4684[/C][C]1.43156[/C][/ROW]
[ROW][C]216[/C][C]16.65[/C][C]13.2969[/C][C]3.3531[/C][/ROW]
[ROW][C]217[/C][C]13.4[/C][C]13.673[/C][C]-0.272985[/C][/ROW]
[ROW][C]218[/C][C]13.95[/C][C]13.4474[/C][C]0.502603[/C][/ROW]
[ROW][C]219[/C][C]15.7[/C][C]13.0132[/C][C]2.68683[/C][/ROW]
[ROW][C]220[/C][C]16.85[/C][C]13.8954[/C][C]2.95457[/C][/ROW]
[ROW][C]221[/C][C]10.95[/C][C]13.6541[/C][C]-2.70413[/C][/ROW]
[ROW][C]222[/C][C]15.35[/C][C]13.2256[/C][C]2.12443[/C][/ROW]
[ROW][C]223[/C][C]12.2[/C][C]13.8015[/C][C]-1.60149[/C][/ROW]
[ROW][C]224[/C][C]15.1[/C][C]12.3653[/C][C]2.73469[/C][/ROW]
[ROW][C]225[/C][C]17.75[/C][C]13.8461[/C][C]3.9039[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.4716[/C][C]1.72841[/C][/ROW]
[ROW][C]227[/C][C]14.6[/C][C]13.6824[/C][C]0.917588[/C][/ROW]
[ROW][C]228[/C][C]16.65[/C][C]13.6001[/C][C]3.04991[/C][/ROW]
[ROW][C]229[/C][C]8.1[/C][C]13.7427[/C][C]-5.64274[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.5869-0.6869
212.813.6315-0.831514
37.413.3368-5.9368
46.713.684-6.98398
512.612.989-0.388986
614.813.48421.31585
713.313.6221-0.322087
811.113.4958-2.39577
98.213.3987-5.19869
1011.413.6127-2.21266
116.413.1464-6.74639
121213.4128-1.41283
136.313.3352-7.03522
1411.313.159-1.85896
1511.913.4983-1.59829
169.313.5398-4.23977
171013.1401-3.14011
1813.813.65260.14744
1910.813.5366-2.73662
2011.713.7764-2.07635
2110.912.8017-1.90173
2216.114.09532.00474
239.913.651-3.75099
2411.513.235-1.735
258.313.2727-4.97271
2611.713.4191-1.71912
27913.7842-4.78421
2810.813.6714-2.87141
2910.412.8621-2.46205
3012.713.1065-0.406494
3111.813.8634-2.06339
321313.7349-0.734881
3310.813.7584-2.95845
3412.313.3949-1.09493
3511.313.6447-2.3447
3611.613.6636-2.06356
3710.913.4364-2.5364
3812.113.5225-1.42248
3913.313.3447-0.044651
4010.113.9096-3.80957
4114.313.04771.25226
429.313.9652-4.66518
4312.513.6636-1.16356
447.613.5633-5.96333
459.213.4207-4.22069
4614.513.30791.19211
4712.313.7952-1.49521
4812.613.1363-0.536346
491313.2523-0.252282
5012.613.7537-1.15373
5113.213.4622-0.262158
527.713.7302-6.03017
5310.513.6127-3.11266
5410.913.6127-2.71266
554.313.4732-9.17316
5610.312.884-2.58405
5711.413.5907-2.19066
585.613.5124-7.91244
598.813.6394-4.83937
60913.4606-4.46059
619.613.2843-3.68433
626.413.3478-6.94779
6311.613.405-1.80498
644.3513.6698-9.31984
6512.713.6645-0.964508
6618.113.55554.54452
6717.8513.78734.06265
6816.614.10312.49689
6912.613.2938-0.693753
7017.113.92063.17943
7119.113.65885.44116
7216.113.65732.44273
7313.3513.3604-0.0103625
7418.413.37295.02707
7514.713.64631.05372
7610.613.4223-2.82226
7712.613.17-0.569961
7816.213.50772.69228
7913.613.23340.366572
8018.913.70035.19968
8114.113.79520.304794
8214.513.79990.700081
8316.1513.40972.74031
8414.7513.42541.3246
8514.813.21931.58071
8612.4513.4521-1.00211
8712.6513.3987-0.748691
8817.3513.67933.67073
898.613.5429-4.94291
9018.413.59694.80305
9116.113.40812.69188
9211.613.514-1.91401
9317.7513.4924.25799
9415.2512.40522.84479
9517.6513.66983.98016
9616.3513.66512.68487
9717.6513.50144.14856
9813.613.14170.45832
9914.3513.23661.11343
10014.7512.68262.06735
10118.2513.73334.51669
1029.913.2859-3.3859
1031613.72552.27455
10418.2513.72554.52455
10516.8513.45843.39161
10614.613.77160.828362
10713.8513.46220.387842
10818.9513.94635.00367
10915.613.66511.93487
11014.8513.89860.951427
11111.7513.3792-1.62922
11218.4513.98874.46125
11315.913.53662.36338
11417.113.43643.6636
11516.113.65572.4443
11619.913.9195.981
11710.9513.6111-2.66109
11818.4513.97934.47068
11915.113.79051.30951
1201513.52411.47595
12111.3513.5938-2.24381
12215.9513.93532.01467
12318.113.48574.61427
12414.614.03490.565066
12515.413.78731.61265
12615.413.78731.61265
12717.613.48264.11742
12813.3513.492-0.14201
12919.113.2795.82101
13015.3513.4921.85799
1317.613.4936-5.89358
13213.413.673-0.272985
13313.913.38080.519213
13419.113.79525.30479
13515.2513.35091.89906
13612.913.449-0.548968
13716.113.78422.31579
13817.3513.78113.56893
13913.1513.7779-0.627923
14012.1513.7145-1.56446
14112.613.4207-0.820687
14210.3513.865-3.51496
14315.412.84162.55837
1449.613.2875-3.68747
14518.213.0325.16797
14613.613.32050.279537
14714.8514.10630.743743
14814.7513.79990.950081
14914.112.50011.5999
15014.913.24441.65557
15116.2513.52412.72595
15219.2513.67775.5723
15313.613.59070.00933613
15413.613.2890.31096
15515.6513.49672.15328
15612.7513.4857-0.735726
15714.613.62210.977913
1589.8513.2319-3.38186
15912.6513.6918-1.04184
16019.212.25726.94277
16116.613.36353.2365
16211.213.7905-2.59049
16315.2513.6621.58801
16411.912.9764-1.07642
16513.213.3556-0.155649
16616.3513.72552.62455
16712.412.9318-0.531804
16815.8513.38392.46607
16918.1513.65884.49116
17011.1513.7412-2.59117
17115.6514.04281.60721
17217.7513.35094.39906
1737.6513.1558-5.50582
17412.3514.0396-1.68965
17515.613.24292.35714
17619.313.42385.87617
17715.213.61581.5842
17817.113.22563.87443
17915.613.65411.94587
18018.413.65414.74587
18119.0513.42385.62617
18218.5512.4756.07504
18319.113.48425.61585
18413.113.7082-0.608171
18512.8513.4873-0.637297
1869.512.4907-2.99068
1874.513.7223-9.22231
18811.8513.6017-1.75166
18913.613.21930.380712
19011.712.4649-0.764917
19112.413.1542-0.75425
19213.3513.7019-0.351887
19311.413.3016-1.90161
19414.913.47631.4237
19519.913.92535.97472
19611.213.8634-2.66339
19714.613.6620.938013
19817.613.31264.28739
19914.0513.50140.548563
20016.113.59072.50934
20113.3513.405-0.0549759
20211.8513.7255-1.87545
20311.9513.4238-1.47383
20414.7513.6731.07702
20515.1513.22181.92819
20613.213.9347-0.734709
20716.8513.84453.00547
2087.8513.6017-5.75166
2097.713.586-5.88595
21012.613.3588-0.758791
2117.8513.1904-5.34039
21210.9513.6079-2.65795
21312.3513.9143-1.56428
2149.9512.8778-2.92776
21514.913.46841.43156
21616.6513.29693.3531
21713.413.673-0.272985
21813.9513.44740.502603
21915.713.01322.68683
22016.8513.89542.95457
22110.9513.6541-2.70413
22215.3513.22562.12443
22312.213.8015-1.60149
22415.112.36532.73469
22517.7513.84613.9039
22615.213.47161.72841
22714.613.68240.917588
22816.6513.60013.04991
2298.113.7427-5.64274






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.680470.6390590.31953
70.597150.8057010.40285
80.5511010.8977990.448899
90.4870660.9741310.512934
100.3713250.7426490.628675
110.4077240.8154470.592276
120.3330840.6661680.666916
130.3503390.7006780.649661
140.2835240.5670470.716476
150.211780.423560.78822
160.1642420.3284840.835758
170.123650.24730.87635
180.1532140.3064270.846786
190.1120660.2241330.887934
200.08315440.1663090.916846
210.05927710.1185540.940723
220.07990780.1598160.920092
230.06197130.1239430.938029
240.04497470.08994950.955025
250.05557750.1111550.944423
260.04047150.0809430.959528
270.04188310.08376620.958117
280.0307120.06142390.969288
290.02263710.04527430.977363
300.02123820.04247650.978762
310.01465040.02930090.98535
320.01066460.02132910.989335
330.008254190.01650840.991746
340.005496260.01099250.994504
350.003723880.007447760.996276
360.002440110.004880220.99756
370.001607040.003214080.998393
380.00116190.002323810.998838
390.00116650.0023330.998834
400.0009533050.001906610.999047
410.00143320.002866390.998567
420.00136050.0027210.998639
430.0009643930.001928790.999036
440.001931830.003863650.998068
450.001720750.00344150.998279
460.002029790.004059580.99797
470.001421170.002842350.998579
480.0009937350.001987470.999006
490.0007310850.001462170.999269
500.0004851780.0009703560.999515
510.0004391890.0008783780.999561
520.0007967580.001593520.999203
530.0005944490.00118890.999406
540.0004207070.0008414140.999579
550.004490780.008981550.995509
560.003515250.007030510.996485
570.002675190.005350390.997325
580.01208020.02416040.98792
590.01372860.02745720.986271
600.01353540.02707080.986465
610.0121160.02423210.987884
620.02439650.04879290.975604
630.02048690.04097380.979513
640.09121220.1824240.908788
650.07778980.155580.92221
660.173310.3466190.82669
670.2907620.5815240.709238
680.3349190.6698370.665081
690.3130.6259990.687
700.3713350.742670.628665
710.5550750.8898510.444925
720.5839020.8321960.416098
730.5616090.8767820.438391
740.6881790.6236420.311821
750.6793260.6413490.320674
760.6639770.6720460.336023
770.639520.720960.36048
780.6559020.6881960.344098
790.6365290.7269420.363471
800.7475780.5048430.252422
810.7220590.5558830.277941
820.6975430.6049140.302457
830.7160180.5679650.283982
840.7030430.5939150.296957
850.6981640.6036720.301836
860.6689920.6620160.331008
870.6405520.7188970.359448
880.6722770.6554450.327723
890.7127860.5744280.287214
900.7756860.4486280.224314
910.7823780.4352450.217622
920.7642590.4714820.235741
930.8020280.3959440.197972
940.8168940.3662120.183106
950.8397550.320490.160245
960.8388870.3222250.161113
970.8610270.2779460.138973
980.8436420.3127170.156358
990.827090.345820.17291
1000.8177990.3644030.182201
1010.8471320.3057350.152868
1020.8505440.2989130.149456
1030.8425710.3148570.157429
1040.8672380.2655240.132762
1050.8716530.2566950.128347
1060.8540060.2919870.145994
1070.8340770.3318470.165923
1080.8648270.2703450.135173
1090.8520190.2959620.147981
1100.8312910.3374170.168709
1110.8145620.3708770.185438
1120.8349330.3301350.165067
1130.8243790.3512420.175621
1140.8324380.3351240.167562
1150.8214840.3570330.178516
1160.8715350.256930.128465
1170.8664850.267030.133515
1180.881380.237240.11862
1190.8641760.2716480.135824
1200.8469370.3061260.153063
1210.8372870.3254260.162713
1220.8196080.3607850.180392
1230.8430550.313890.156945
1240.8193440.3613110.180656
1250.7985130.4029730.201487
1260.7762880.4474250.223712
1270.7917710.4164570.208229
1280.7641550.471690.235845
1290.8268820.3462370.173118
1300.8094810.3810370.190519
1310.8660170.2679650.133983
1320.8444940.3110120.155506
1330.8213570.3572870.178643
1340.8576420.2847160.142358
1350.8422320.3155360.157768
1360.8186440.3627120.181356
1370.8037640.3924720.196236
1380.8064550.3870890.193545
1390.7801640.4396720.219836
1400.7591870.4816260.240813
1410.7315320.5369370.268468
1420.7390920.5218170.260908
1430.7273830.5452350.272617
1440.7454570.5090860.254543
1450.7832410.4335180.216759
1460.7538660.4922670.246134
1470.7229650.554070.277035
1480.6906960.6186080.309304
1490.6658970.6682050.334103
1500.6362540.7274920.363746
1510.6197570.7604860.380243
1520.6850810.6298380.314919
1530.6484950.7030090.351505
1540.6111290.7777410.388871
1550.5865110.8269780.413489
1560.5497060.9005870.450294
1570.5119730.9760530.488027
1580.5253170.9493660.474683
1590.4881150.976230.511885
1600.5971540.8056910.402846
1610.5900280.8199450.409972
1620.5771360.8457280.422864
1630.5424390.9151230.457561
1640.5109150.9781710.489085
1650.4698840.9397670.530116
1660.4497440.8994890.550256
1670.412070.8241410.58793
1680.3920360.7840710.607964
1690.4177360.8354720.582264
1700.4002570.8005140.599743
1710.3691270.7382540.630873
1720.3888570.7777140.611143
1730.490970.981940.50903
1740.4560450.912090.543955
1750.4287070.8574140.571293
1760.5138310.9723390.486169
1770.4795830.9591650.520417
1780.4822280.9644560.517772
1790.4485290.8970570.551471
1800.4904120.9808230.509588
1810.5780890.8438220.421911
1820.6604880.6790240.339512
1830.7500650.4998690.249935
1840.7102820.5794350.289718
1850.6670550.6658910.332945
1860.6636460.6727090.336354
1870.9064120.1871760.0935879
1880.8907520.2184960.109248
1890.8640350.2719290.135965
1900.8343010.3313970.165699
1910.8045090.3909810.195491
1920.7676870.4646260.232313
1930.741930.516140.25807
1940.7016250.596750.298375
1950.8322790.3354410.167721
1960.8102890.3794220.189711
1970.7724470.4551060.227553
1980.8157310.3685380.184269
1990.7802910.4394190.219709
2000.7589710.4820580.241029
2010.70890.58220.2911
2020.6668630.6662740.333137
2030.616870.7662590.38313
2040.5681680.8636640.431832
2050.6057660.7884680.394234
2060.5515090.8969830.448491
2070.5497070.9005860.450293
2080.6726320.6547350.327368
2090.9041860.1916270.0958135
2100.8693190.2613610.130681
2110.9075360.1849290.0924643
2120.9026270.1947470.0973734
2130.8758690.2482610.124131
2140.8872330.2255350.112767
2150.8358030.3283940.164197
2160.8131620.3736760.186838
2170.7368490.5263020.263151
2180.6821880.6356240.317812
2190.6266350.746730.373365
2200.5172870.9654250.482713
2210.7407910.5184180.259209
2220.6190240.7619520.380976
2230.4506310.9012610.549369

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.68047 & 0.639059 & 0.31953 \tabularnewline
7 & 0.59715 & 0.805701 & 0.40285 \tabularnewline
8 & 0.551101 & 0.897799 & 0.448899 \tabularnewline
9 & 0.487066 & 0.974131 & 0.512934 \tabularnewline
10 & 0.371325 & 0.742649 & 0.628675 \tabularnewline
11 & 0.407724 & 0.815447 & 0.592276 \tabularnewline
12 & 0.333084 & 0.666168 & 0.666916 \tabularnewline
13 & 0.350339 & 0.700678 & 0.649661 \tabularnewline
14 & 0.283524 & 0.567047 & 0.716476 \tabularnewline
15 & 0.21178 & 0.42356 & 0.78822 \tabularnewline
16 & 0.164242 & 0.328484 & 0.835758 \tabularnewline
17 & 0.12365 & 0.2473 & 0.87635 \tabularnewline
18 & 0.153214 & 0.306427 & 0.846786 \tabularnewline
19 & 0.112066 & 0.224133 & 0.887934 \tabularnewline
20 & 0.0831544 & 0.166309 & 0.916846 \tabularnewline
21 & 0.0592771 & 0.118554 & 0.940723 \tabularnewline
22 & 0.0799078 & 0.159816 & 0.920092 \tabularnewline
23 & 0.0619713 & 0.123943 & 0.938029 \tabularnewline
24 & 0.0449747 & 0.0899495 & 0.955025 \tabularnewline
25 & 0.0555775 & 0.111155 & 0.944423 \tabularnewline
26 & 0.0404715 & 0.080943 & 0.959528 \tabularnewline
27 & 0.0418831 & 0.0837662 & 0.958117 \tabularnewline
28 & 0.030712 & 0.0614239 & 0.969288 \tabularnewline
29 & 0.0226371 & 0.0452743 & 0.977363 \tabularnewline
30 & 0.0212382 & 0.0424765 & 0.978762 \tabularnewline
31 & 0.0146504 & 0.0293009 & 0.98535 \tabularnewline
32 & 0.0106646 & 0.0213291 & 0.989335 \tabularnewline
33 & 0.00825419 & 0.0165084 & 0.991746 \tabularnewline
34 & 0.00549626 & 0.0109925 & 0.994504 \tabularnewline
35 & 0.00372388 & 0.00744776 & 0.996276 \tabularnewline
36 & 0.00244011 & 0.00488022 & 0.99756 \tabularnewline
37 & 0.00160704 & 0.00321408 & 0.998393 \tabularnewline
38 & 0.0011619 & 0.00232381 & 0.998838 \tabularnewline
39 & 0.0011665 & 0.002333 & 0.998834 \tabularnewline
40 & 0.000953305 & 0.00190661 & 0.999047 \tabularnewline
41 & 0.0014332 & 0.00286639 & 0.998567 \tabularnewline
42 & 0.0013605 & 0.002721 & 0.998639 \tabularnewline
43 & 0.000964393 & 0.00192879 & 0.999036 \tabularnewline
44 & 0.00193183 & 0.00386365 & 0.998068 \tabularnewline
45 & 0.00172075 & 0.0034415 & 0.998279 \tabularnewline
46 & 0.00202979 & 0.00405958 & 0.99797 \tabularnewline
47 & 0.00142117 & 0.00284235 & 0.998579 \tabularnewline
48 & 0.000993735 & 0.00198747 & 0.999006 \tabularnewline
49 & 0.000731085 & 0.00146217 & 0.999269 \tabularnewline
50 & 0.000485178 & 0.000970356 & 0.999515 \tabularnewline
51 & 0.000439189 & 0.000878378 & 0.999561 \tabularnewline
52 & 0.000796758 & 0.00159352 & 0.999203 \tabularnewline
53 & 0.000594449 & 0.0011889 & 0.999406 \tabularnewline
54 & 0.000420707 & 0.000841414 & 0.999579 \tabularnewline
55 & 0.00449078 & 0.00898155 & 0.995509 \tabularnewline
56 & 0.00351525 & 0.00703051 & 0.996485 \tabularnewline
57 & 0.00267519 & 0.00535039 & 0.997325 \tabularnewline
58 & 0.0120802 & 0.0241604 & 0.98792 \tabularnewline
59 & 0.0137286 & 0.0274572 & 0.986271 \tabularnewline
60 & 0.0135354 & 0.0270708 & 0.986465 \tabularnewline
61 & 0.012116 & 0.0242321 & 0.987884 \tabularnewline
62 & 0.0243965 & 0.0487929 & 0.975604 \tabularnewline
63 & 0.0204869 & 0.0409738 & 0.979513 \tabularnewline
64 & 0.0912122 & 0.182424 & 0.908788 \tabularnewline
65 & 0.0777898 & 0.15558 & 0.92221 \tabularnewline
66 & 0.17331 & 0.346619 & 0.82669 \tabularnewline
67 & 0.290762 & 0.581524 & 0.709238 \tabularnewline
68 & 0.334919 & 0.669837 & 0.665081 \tabularnewline
69 & 0.313 & 0.625999 & 0.687 \tabularnewline
70 & 0.371335 & 0.74267 & 0.628665 \tabularnewline
71 & 0.555075 & 0.889851 & 0.444925 \tabularnewline
72 & 0.583902 & 0.832196 & 0.416098 \tabularnewline
73 & 0.561609 & 0.876782 & 0.438391 \tabularnewline
74 & 0.688179 & 0.623642 & 0.311821 \tabularnewline
75 & 0.679326 & 0.641349 & 0.320674 \tabularnewline
76 & 0.663977 & 0.672046 & 0.336023 \tabularnewline
77 & 0.63952 & 0.72096 & 0.36048 \tabularnewline
78 & 0.655902 & 0.688196 & 0.344098 \tabularnewline
79 & 0.636529 & 0.726942 & 0.363471 \tabularnewline
80 & 0.747578 & 0.504843 & 0.252422 \tabularnewline
81 & 0.722059 & 0.555883 & 0.277941 \tabularnewline
82 & 0.697543 & 0.604914 & 0.302457 \tabularnewline
83 & 0.716018 & 0.567965 & 0.283982 \tabularnewline
84 & 0.703043 & 0.593915 & 0.296957 \tabularnewline
85 & 0.698164 & 0.603672 & 0.301836 \tabularnewline
86 & 0.668992 & 0.662016 & 0.331008 \tabularnewline
87 & 0.640552 & 0.718897 & 0.359448 \tabularnewline
88 & 0.672277 & 0.655445 & 0.327723 \tabularnewline
89 & 0.712786 & 0.574428 & 0.287214 \tabularnewline
90 & 0.775686 & 0.448628 & 0.224314 \tabularnewline
91 & 0.782378 & 0.435245 & 0.217622 \tabularnewline
92 & 0.764259 & 0.471482 & 0.235741 \tabularnewline
93 & 0.802028 & 0.395944 & 0.197972 \tabularnewline
94 & 0.816894 & 0.366212 & 0.183106 \tabularnewline
95 & 0.839755 & 0.32049 & 0.160245 \tabularnewline
96 & 0.838887 & 0.322225 & 0.161113 \tabularnewline
97 & 0.861027 & 0.277946 & 0.138973 \tabularnewline
98 & 0.843642 & 0.312717 & 0.156358 \tabularnewline
99 & 0.82709 & 0.34582 & 0.17291 \tabularnewline
100 & 0.817799 & 0.364403 & 0.182201 \tabularnewline
101 & 0.847132 & 0.305735 & 0.152868 \tabularnewline
102 & 0.850544 & 0.298913 & 0.149456 \tabularnewline
103 & 0.842571 & 0.314857 & 0.157429 \tabularnewline
104 & 0.867238 & 0.265524 & 0.132762 \tabularnewline
105 & 0.871653 & 0.256695 & 0.128347 \tabularnewline
106 & 0.854006 & 0.291987 & 0.145994 \tabularnewline
107 & 0.834077 & 0.331847 & 0.165923 \tabularnewline
108 & 0.864827 & 0.270345 & 0.135173 \tabularnewline
109 & 0.852019 & 0.295962 & 0.147981 \tabularnewline
110 & 0.831291 & 0.337417 & 0.168709 \tabularnewline
111 & 0.814562 & 0.370877 & 0.185438 \tabularnewline
112 & 0.834933 & 0.330135 & 0.165067 \tabularnewline
113 & 0.824379 & 0.351242 & 0.175621 \tabularnewline
114 & 0.832438 & 0.335124 & 0.167562 \tabularnewline
115 & 0.821484 & 0.357033 & 0.178516 \tabularnewline
116 & 0.871535 & 0.25693 & 0.128465 \tabularnewline
117 & 0.866485 & 0.26703 & 0.133515 \tabularnewline
118 & 0.88138 & 0.23724 & 0.11862 \tabularnewline
119 & 0.864176 & 0.271648 & 0.135824 \tabularnewline
120 & 0.846937 & 0.306126 & 0.153063 \tabularnewline
121 & 0.837287 & 0.325426 & 0.162713 \tabularnewline
122 & 0.819608 & 0.360785 & 0.180392 \tabularnewline
123 & 0.843055 & 0.31389 & 0.156945 \tabularnewline
124 & 0.819344 & 0.361311 & 0.180656 \tabularnewline
125 & 0.798513 & 0.402973 & 0.201487 \tabularnewline
126 & 0.776288 & 0.447425 & 0.223712 \tabularnewline
127 & 0.791771 & 0.416457 & 0.208229 \tabularnewline
128 & 0.764155 & 0.47169 & 0.235845 \tabularnewline
129 & 0.826882 & 0.346237 & 0.173118 \tabularnewline
130 & 0.809481 & 0.381037 & 0.190519 \tabularnewline
131 & 0.866017 & 0.267965 & 0.133983 \tabularnewline
132 & 0.844494 & 0.311012 & 0.155506 \tabularnewline
133 & 0.821357 & 0.357287 & 0.178643 \tabularnewline
134 & 0.857642 & 0.284716 & 0.142358 \tabularnewline
135 & 0.842232 & 0.315536 & 0.157768 \tabularnewline
136 & 0.818644 & 0.362712 & 0.181356 \tabularnewline
137 & 0.803764 & 0.392472 & 0.196236 \tabularnewline
138 & 0.806455 & 0.387089 & 0.193545 \tabularnewline
139 & 0.780164 & 0.439672 & 0.219836 \tabularnewline
140 & 0.759187 & 0.481626 & 0.240813 \tabularnewline
141 & 0.731532 & 0.536937 & 0.268468 \tabularnewline
142 & 0.739092 & 0.521817 & 0.260908 \tabularnewline
143 & 0.727383 & 0.545235 & 0.272617 \tabularnewline
144 & 0.745457 & 0.509086 & 0.254543 \tabularnewline
145 & 0.783241 & 0.433518 & 0.216759 \tabularnewline
146 & 0.753866 & 0.492267 & 0.246134 \tabularnewline
147 & 0.722965 & 0.55407 & 0.277035 \tabularnewline
148 & 0.690696 & 0.618608 & 0.309304 \tabularnewline
149 & 0.665897 & 0.668205 & 0.334103 \tabularnewline
150 & 0.636254 & 0.727492 & 0.363746 \tabularnewline
151 & 0.619757 & 0.760486 & 0.380243 \tabularnewline
152 & 0.685081 & 0.629838 & 0.314919 \tabularnewline
153 & 0.648495 & 0.703009 & 0.351505 \tabularnewline
154 & 0.611129 & 0.777741 & 0.388871 \tabularnewline
155 & 0.586511 & 0.826978 & 0.413489 \tabularnewline
156 & 0.549706 & 0.900587 & 0.450294 \tabularnewline
157 & 0.511973 & 0.976053 & 0.488027 \tabularnewline
158 & 0.525317 & 0.949366 & 0.474683 \tabularnewline
159 & 0.488115 & 0.97623 & 0.511885 \tabularnewline
160 & 0.597154 & 0.805691 & 0.402846 \tabularnewline
161 & 0.590028 & 0.819945 & 0.409972 \tabularnewline
162 & 0.577136 & 0.845728 & 0.422864 \tabularnewline
163 & 0.542439 & 0.915123 & 0.457561 \tabularnewline
164 & 0.510915 & 0.978171 & 0.489085 \tabularnewline
165 & 0.469884 & 0.939767 & 0.530116 \tabularnewline
166 & 0.449744 & 0.899489 & 0.550256 \tabularnewline
167 & 0.41207 & 0.824141 & 0.58793 \tabularnewline
168 & 0.392036 & 0.784071 & 0.607964 \tabularnewline
169 & 0.417736 & 0.835472 & 0.582264 \tabularnewline
170 & 0.400257 & 0.800514 & 0.599743 \tabularnewline
171 & 0.369127 & 0.738254 & 0.630873 \tabularnewline
172 & 0.388857 & 0.777714 & 0.611143 \tabularnewline
173 & 0.49097 & 0.98194 & 0.50903 \tabularnewline
174 & 0.456045 & 0.91209 & 0.543955 \tabularnewline
175 & 0.428707 & 0.857414 & 0.571293 \tabularnewline
176 & 0.513831 & 0.972339 & 0.486169 \tabularnewline
177 & 0.479583 & 0.959165 & 0.520417 \tabularnewline
178 & 0.482228 & 0.964456 & 0.517772 \tabularnewline
179 & 0.448529 & 0.897057 & 0.551471 \tabularnewline
180 & 0.490412 & 0.980823 & 0.509588 \tabularnewline
181 & 0.578089 & 0.843822 & 0.421911 \tabularnewline
182 & 0.660488 & 0.679024 & 0.339512 \tabularnewline
183 & 0.750065 & 0.499869 & 0.249935 \tabularnewline
184 & 0.710282 & 0.579435 & 0.289718 \tabularnewline
185 & 0.667055 & 0.665891 & 0.332945 \tabularnewline
186 & 0.663646 & 0.672709 & 0.336354 \tabularnewline
187 & 0.906412 & 0.187176 & 0.0935879 \tabularnewline
188 & 0.890752 & 0.218496 & 0.109248 \tabularnewline
189 & 0.864035 & 0.271929 & 0.135965 \tabularnewline
190 & 0.834301 & 0.331397 & 0.165699 \tabularnewline
191 & 0.804509 & 0.390981 & 0.195491 \tabularnewline
192 & 0.767687 & 0.464626 & 0.232313 \tabularnewline
193 & 0.74193 & 0.51614 & 0.25807 \tabularnewline
194 & 0.701625 & 0.59675 & 0.298375 \tabularnewline
195 & 0.832279 & 0.335441 & 0.167721 \tabularnewline
196 & 0.810289 & 0.379422 & 0.189711 \tabularnewline
197 & 0.772447 & 0.455106 & 0.227553 \tabularnewline
198 & 0.815731 & 0.368538 & 0.184269 \tabularnewline
199 & 0.780291 & 0.439419 & 0.219709 \tabularnewline
200 & 0.758971 & 0.482058 & 0.241029 \tabularnewline
201 & 0.7089 & 0.5822 & 0.2911 \tabularnewline
202 & 0.666863 & 0.666274 & 0.333137 \tabularnewline
203 & 0.61687 & 0.766259 & 0.38313 \tabularnewline
204 & 0.568168 & 0.863664 & 0.431832 \tabularnewline
205 & 0.605766 & 0.788468 & 0.394234 \tabularnewline
206 & 0.551509 & 0.896983 & 0.448491 \tabularnewline
207 & 0.549707 & 0.900586 & 0.450293 \tabularnewline
208 & 0.672632 & 0.654735 & 0.327368 \tabularnewline
209 & 0.904186 & 0.191627 & 0.0958135 \tabularnewline
210 & 0.869319 & 0.261361 & 0.130681 \tabularnewline
211 & 0.907536 & 0.184929 & 0.0924643 \tabularnewline
212 & 0.902627 & 0.194747 & 0.0973734 \tabularnewline
213 & 0.875869 & 0.248261 & 0.124131 \tabularnewline
214 & 0.887233 & 0.225535 & 0.112767 \tabularnewline
215 & 0.835803 & 0.328394 & 0.164197 \tabularnewline
216 & 0.813162 & 0.373676 & 0.186838 \tabularnewline
217 & 0.736849 & 0.526302 & 0.263151 \tabularnewline
218 & 0.682188 & 0.635624 & 0.317812 \tabularnewline
219 & 0.626635 & 0.74673 & 0.373365 \tabularnewline
220 & 0.517287 & 0.965425 & 0.482713 \tabularnewline
221 & 0.740791 & 0.518418 & 0.259209 \tabularnewline
222 & 0.619024 & 0.761952 & 0.380976 \tabularnewline
223 & 0.450631 & 0.901261 & 0.549369 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]6[/C][C]0.68047[/C][C]0.639059[/C][C]0.31953[/C][/ROW]
[ROW][C]7[/C][C]0.59715[/C][C]0.805701[/C][C]0.40285[/C][/ROW]
[ROW][C]8[/C][C]0.551101[/C][C]0.897799[/C][C]0.448899[/C][/ROW]
[ROW][C]9[/C][C]0.487066[/C][C]0.974131[/C][C]0.512934[/C][/ROW]
[ROW][C]10[/C][C]0.371325[/C][C]0.742649[/C][C]0.628675[/C][/ROW]
[ROW][C]11[/C][C]0.407724[/C][C]0.815447[/C][C]0.592276[/C][/ROW]
[ROW][C]12[/C][C]0.333084[/C][C]0.666168[/C][C]0.666916[/C][/ROW]
[ROW][C]13[/C][C]0.350339[/C][C]0.700678[/C][C]0.649661[/C][/ROW]
[ROW][C]14[/C][C]0.283524[/C][C]0.567047[/C][C]0.716476[/C][/ROW]
[ROW][C]15[/C][C]0.21178[/C][C]0.42356[/C][C]0.78822[/C][/ROW]
[ROW][C]16[/C][C]0.164242[/C][C]0.328484[/C][C]0.835758[/C][/ROW]
[ROW][C]17[/C][C]0.12365[/C][C]0.2473[/C][C]0.87635[/C][/ROW]
[ROW][C]18[/C][C]0.153214[/C][C]0.306427[/C][C]0.846786[/C][/ROW]
[ROW][C]19[/C][C]0.112066[/C][C]0.224133[/C][C]0.887934[/C][/ROW]
[ROW][C]20[/C][C]0.0831544[/C][C]0.166309[/C][C]0.916846[/C][/ROW]
[ROW][C]21[/C][C]0.0592771[/C][C]0.118554[/C][C]0.940723[/C][/ROW]
[ROW][C]22[/C][C]0.0799078[/C][C]0.159816[/C][C]0.920092[/C][/ROW]
[ROW][C]23[/C][C]0.0619713[/C][C]0.123943[/C][C]0.938029[/C][/ROW]
[ROW][C]24[/C][C]0.0449747[/C][C]0.0899495[/C][C]0.955025[/C][/ROW]
[ROW][C]25[/C][C]0.0555775[/C][C]0.111155[/C][C]0.944423[/C][/ROW]
[ROW][C]26[/C][C]0.0404715[/C][C]0.080943[/C][C]0.959528[/C][/ROW]
[ROW][C]27[/C][C]0.0418831[/C][C]0.0837662[/C][C]0.958117[/C][/ROW]
[ROW][C]28[/C][C]0.030712[/C][C]0.0614239[/C][C]0.969288[/C][/ROW]
[ROW][C]29[/C][C]0.0226371[/C][C]0.0452743[/C][C]0.977363[/C][/ROW]
[ROW][C]30[/C][C]0.0212382[/C][C]0.0424765[/C][C]0.978762[/C][/ROW]
[ROW][C]31[/C][C]0.0146504[/C][C]0.0293009[/C][C]0.98535[/C][/ROW]
[ROW][C]32[/C][C]0.0106646[/C][C]0.0213291[/C][C]0.989335[/C][/ROW]
[ROW][C]33[/C][C]0.00825419[/C][C]0.0165084[/C][C]0.991746[/C][/ROW]
[ROW][C]34[/C][C]0.00549626[/C][C]0.0109925[/C][C]0.994504[/C][/ROW]
[ROW][C]35[/C][C]0.00372388[/C][C]0.00744776[/C][C]0.996276[/C][/ROW]
[ROW][C]36[/C][C]0.00244011[/C][C]0.00488022[/C][C]0.99756[/C][/ROW]
[ROW][C]37[/C][C]0.00160704[/C][C]0.00321408[/C][C]0.998393[/C][/ROW]
[ROW][C]38[/C][C]0.0011619[/C][C]0.00232381[/C][C]0.998838[/C][/ROW]
[ROW][C]39[/C][C]0.0011665[/C][C]0.002333[/C][C]0.998834[/C][/ROW]
[ROW][C]40[/C][C]0.000953305[/C][C]0.00190661[/C][C]0.999047[/C][/ROW]
[ROW][C]41[/C][C]0.0014332[/C][C]0.00286639[/C][C]0.998567[/C][/ROW]
[ROW][C]42[/C][C]0.0013605[/C][C]0.002721[/C][C]0.998639[/C][/ROW]
[ROW][C]43[/C][C]0.000964393[/C][C]0.00192879[/C][C]0.999036[/C][/ROW]
[ROW][C]44[/C][C]0.00193183[/C][C]0.00386365[/C][C]0.998068[/C][/ROW]
[ROW][C]45[/C][C]0.00172075[/C][C]0.0034415[/C][C]0.998279[/C][/ROW]
[ROW][C]46[/C][C]0.00202979[/C][C]0.00405958[/C][C]0.99797[/C][/ROW]
[ROW][C]47[/C][C]0.00142117[/C][C]0.00284235[/C][C]0.998579[/C][/ROW]
[ROW][C]48[/C][C]0.000993735[/C][C]0.00198747[/C][C]0.999006[/C][/ROW]
[ROW][C]49[/C][C]0.000731085[/C][C]0.00146217[/C][C]0.999269[/C][/ROW]
[ROW][C]50[/C][C]0.000485178[/C][C]0.000970356[/C][C]0.999515[/C][/ROW]
[ROW][C]51[/C][C]0.000439189[/C][C]0.000878378[/C][C]0.999561[/C][/ROW]
[ROW][C]52[/C][C]0.000796758[/C][C]0.00159352[/C][C]0.999203[/C][/ROW]
[ROW][C]53[/C][C]0.000594449[/C][C]0.0011889[/C][C]0.999406[/C][/ROW]
[ROW][C]54[/C][C]0.000420707[/C][C]0.000841414[/C][C]0.999579[/C][/ROW]
[ROW][C]55[/C][C]0.00449078[/C][C]0.00898155[/C][C]0.995509[/C][/ROW]
[ROW][C]56[/C][C]0.00351525[/C][C]0.00703051[/C][C]0.996485[/C][/ROW]
[ROW][C]57[/C][C]0.00267519[/C][C]0.00535039[/C][C]0.997325[/C][/ROW]
[ROW][C]58[/C][C]0.0120802[/C][C]0.0241604[/C][C]0.98792[/C][/ROW]
[ROW][C]59[/C][C]0.0137286[/C][C]0.0274572[/C][C]0.986271[/C][/ROW]
[ROW][C]60[/C][C]0.0135354[/C][C]0.0270708[/C][C]0.986465[/C][/ROW]
[ROW][C]61[/C][C]0.012116[/C][C]0.0242321[/C][C]0.987884[/C][/ROW]
[ROW][C]62[/C][C]0.0243965[/C][C]0.0487929[/C][C]0.975604[/C][/ROW]
[ROW][C]63[/C][C]0.0204869[/C][C]0.0409738[/C][C]0.979513[/C][/ROW]
[ROW][C]64[/C][C]0.0912122[/C][C]0.182424[/C][C]0.908788[/C][/ROW]
[ROW][C]65[/C][C]0.0777898[/C][C]0.15558[/C][C]0.92221[/C][/ROW]
[ROW][C]66[/C][C]0.17331[/C][C]0.346619[/C][C]0.82669[/C][/ROW]
[ROW][C]67[/C][C]0.290762[/C][C]0.581524[/C][C]0.709238[/C][/ROW]
[ROW][C]68[/C][C]0.334919[/C][C]0.669837[/C][C]0.665081[/C][/ROW]
[ROW][C]69[/C][C]0.313[/C][C]0.625999[/C][C]0.687[/C][/ROW]
[ROW][C]70[/C][C]0.371335[/C][C]0.74267[/C][C]0.628665[/C][/ROW]
[ROW][C]71[/C][C]0.555075[/C][C]0.889851[/C][C]0.444925[/C][/ROW]
[ROW][C]72[/C][C]0.583902[/C][C]0.832196[/C][C]0.416098[/C][/ROW]
[ROW][C]73[/C][C]0.561609[/C][C]0.876782[/C][C]0.438391[/C][/ROW]
[ROW][C]74[/C][C]0.688179[/C][C]0.623642[/C][C]0.311821[/C][/ROW]
[ROW][C]75[/C][C]0.679326[/C][C]0.641349[/C][C]0.320674[/C][/ROW]
[ROW][C]76[/C][C]0.663977[/C][C]0.672046[/C][C]0.336023[/C][/ROW]
[ROW][C]77[/C][C]0.63952[/C][C]0.72096[/C][C]0.36048[/C][/ROW]
[ROW][C]78[/C][C]0.655902[/C][C]0.688196[/C][C]0.344098[/C][/ROW]
[ROW][C]79[/C][C]0.636529[/C][C]0.726942[/C][C]0.363471[/C][/ROW]
[ROW][C]80[/C][C]0.747578[/C][C]0.504843[/C][C]0.252422[/C][/ROW]
[ROW][C]81[/C][C]0.722059[/C][C]0.555883[/C][C]0.277941[/C][/ROW]
[ROW][C]82[/C][C]0.697543[/C][C]0.604914[/C][C]0.302457[/C][/ROW]
[ROW][C]83[/C][C]0.716018[/C][C]0.567965[/C][C]0.283982[/C][/ROW]
[ROW][C]84[/C][C]0.703043[/C][C]0.593915[/C][C]0.296957[/C][/ROW]
[ROW][C]85[/C][C]0.698164[/C][C]0.603672[/C][C]0.301836[/C][/ROW]
[ROW][C]86[/C][C]0.668992[/C][C]0.662016[/C][C]0.331008[/C][/ROW]
[ROW][C]87[/C][C]0.640552[/C][C]0.718897[/C][C]0.359448[/C][/ROW]
[ROW][C]88[/C][C]0.672277[/C][C]0.655445[/C][C]0.327723[/C][/ROW]
[ROW][C]89[/C][C]0.712786[/C][C]0.574428[/C][C]0.287214[/C][/ROW]
[ROW][C]90[/C][C]0.775686[/C][C]0.448628[/C][C]0.224314[/C][/ROW]
[ROW][C]91[/C][C]0.782378[/C][C]0.435245[/C][C]0.217622[/C][/ROW]
[ROW][C]92[/C][C]0.764259[/C][C]0.471482[/C][C]0.235741[/C][/ROW]
[ROW][C]93[/C][C]0.802028[/C][C]0.395944[/C][C]0.197972[/C][/ROW]
[ROW][C]94[/C][C]0.816894[/C][C]0.366212[/C][C]0.183106[/C][/ROW]
[ROW][C]95[/C][C]0.839755[/C][C]0.32049[/C][C]0.160245[/C][/ROW]
[ROW][C]96[/C][C]0.838887[/C][C]0.322225[/C][C]0.161113[/C][/ROW]
[ROW][C]97[/C][C]0.861027[/C][C]0.277946[/C][C]0.138973[/C][/ROW]
[ROW][C]98[/C][C]0.843642[/C][C]0.312717[/C][C]0.156358[/C][/ROW]
[ROW][C]99[/C][C]0.82709[/C][C]0.34582[/C][C]0.17291[/C][/ROW]
[ROW][C]100[/C][C]0.817799[/C][C]0.364403[/C][C]0.182201[/C][/ROW]
[ROW][C]101[/C][C]0.847132[/C][C]0.305735[/C][C]0.152868[/C][/ROW]
[ROW][C]102[/C][C]0.850544[/C][C]0.298913[/C][C]0.149456[/C][/ROW]
[ROW][C]103[/C][C]0.842571[/C][C]0.314857[/C][C]0.157429[/C][/ROW]
[ROW][C]104[/C][C]0.867238[/C][C]0.265524[/C][C]0.132762[/C][/ROW]
[ROW][C]105[/C][C]0.871653[/C][C]0.256695[/C][C]0.128347[/C][/ROW]
[ROW][C]106[/C][C]0.854006[/C][C]0.291987[/C][C]0.145994[/C][/ROW]
[ROW][C]107[/C][C]0.834077[/C][C]0.331847[/C][C]0.165923[/C][/ROW]
[ROW][C]108[/C][C]0.864827[/C][C]0.270345[/C][C]0.135173[/C][/ROW]
[ROW][C]109[/C][C]0.852019[/C][C]0.295962[/C][C]0.147981[/C][/ROW]
[ROW][C]110[/C][C]0.831291[/C][C]0.337417[/C][C]0.168709[/C][/ROW]
[ROW][C]111[/C][C]0.814562[/C][C]0.370877[/C][C]0.185438[/C][/ROW]
[ROW][C]112[/C][C]0.834933[/C][C]0.330135[/C][C]0.165067[/C][/ROW]
[ROW][C]113[/C][C]0.824379[/C][C]0.351242[/C][C]0.175621[/C][/ROW]
[ROW][C]114[/C][C]0.832438[/C][C]0.335124[/C][C]0.167562[/C][/ROW]
[ROW][C]115[/C][C]0.821484[/C][C]0.357033[/C][C]0.178516[/C][/ROW]
[ROW][C]116[/C][C]0.871535[/C][C]0.25693[/C][C]0.128465[/C][/ROW]
[ROW][C]117[/C][C]0.866485[/C][C]0.26703[/C][C]0.133515[/C][/ROW]
[ROW][C]118[/C][C]0.88138[/C][C]0.23724[/C][C]0.11862[/C][/ROW]
[ROW][C]119[/C][C]0.864176[/C][C]0.271648[/C][C]0.135824[/C][/ROW]
[ROW][C]120[/C][C]0.846937[/C][C]0.306126[/C][C]0.153063[/C][/ROW]
[ROW][C]121[/C][C]0.837287[/C][C]0.325426[/C][C]0.162713[/C][/ROW]
[ROW][C]122[/C][C]0.819608[/C][C]0.360785[/C][C]0.180392[/C][/ROW]
[ROW][C]123[/C][C]0.843055[/C][C]0.31389[/C][C]0.156945[/C][/ROW]
[ROW][C]124[/C][C]0.819344[/C][C]0.361311[/C][C]0.180656[/C][/ROW]
[ROW][C]125[/C][C]0.798513[/C][C]0.402973[/C][C]0.201487[/C][/ROW]
[ROW][C]126[/C][C]0.776288[/C][C]0.447425[/C][C]0.223712[/C][/ROW]
[ROW][C]127[/C][C]0.791771[/C][C]0.416457[/C][C]0.208229[/C][/ROW]
[ROW][C]128[/C][C]0.764155[/C][C]0.47169[/C][C]0.235845[/C][/ROW]
[ROW][C]129[/C][C]0.826882[/C][C]0.346237[/C][C]0.173118[/C][/ROW]
[ROW][C]130[/C][C]0.809481[/C][C]0.381037[/C][C]0.190519[/C][/ROW]
[ROW][C]131[/C][C]0.866017[/C][C]0.267965[/C][C]0.133983[/C][/ROW]
[ROW][C]132[/C][C]0.844494[/C][C]0.311012[/C][C]0.155506[/C][/ROW]
[ROW][C]133[/C][C]0.821357[/C][C]0.357287[/C][C]0.178643[/C][/ROW]
[ROW][C]134[/C][C]0.857642[/C][C]0.284716[/C][C]0.142358[/C][/ROW]
[ROW][C]135[/C][C]0.842232[/C][C]0.315536[/C][C]0.157768[/C][/ROW]
[ROW][C]136[/C][C]0.818644[/C][C]0.362712[/C][C]0.181356[/C][/ROW]
[ROW][C]137[/C][C]0.803764[/C][C]0.392472[/C][C]0.196236[/C][/ROW]
[ROW][C]138[/C][C]0.806455[/C][C]0.387089[/C][C]0.193545[/C][/ROW]
[ROW][C]139[/C][C]0.780164[/C][C]0.439672[/C][C]0.219836[/C][/ROW]
[ROW][C]140[/C][C]0.759187[/C][C]0.481626[/C][C]0.240813[/C][/ROW]
[ROW][C]141[/C][C]0.731532[/C][C]0.536937[/C][C]0.268468[/C][/ROW]
[ROW][C]142[/C][C]0.739092[/C][C]0.521817[/C][C]0.260908[/C][/ROW]
[ROW][C]143[/C][C]0.727383[/C][C]0.545235[/C][C]0.272617[/C][/ROW]
[ROW][C]144[/C][C]0.745457[/C][C]0.509086[/C][C]0.254543[/C][/ROW]
[ROW][C]145[/C][C]0.783241[/C][C]0.433518[/C][C]0.216759[/C][/ROW]
[ROW][C]146[/C][C]0.753866[/C][C]0.492267[/C][C]0.246134[/C][/ROW]
[ROW][C]147[/C][C]0.722965[/C][C]0.55407[/C][C]0.277035[/C][/ROW]
[ROW][C]148[/C][C]0.690696[/C][C]0.618608[/C][C]0.309304[/C][/ROW]
[ROW][C]149[/C][C]0.665897[/C][C]0.668205[/C][C]0.334103[/C][/ROW]
[ROW][C]150[/C][C]0.636254[/C][C]0.727492[/C][C]0.363746[/C][/ROW]
[ROW][C]151[/C][C]0.619757[/C][C]0.760486[/C][C]0.380243[/C][/ROW]
[ROW][C]152[/C][C]0.685081[/C][C]0.629838[/C][C]0.314919[/C][/ROW]
[ROW][C]153[/C][C]0.648495[/C][C]0.703009[/C][C]0.351505[/C][/ROW]
[ROW][C]154[/C][C]0.611129[/C][C]0.777741[/C][C]0.388871[/C][/ROW]
[ROW][C]155[/C][C]0.586511[/C][C]0.826978[/C][C]0.413489[/C][/ROW]
[ROW][C]156[/C][C]0.549706[/C][C]0.900587[/C][C]0.450294[/C][/ROW]
[ROW][C]157[/C][C]0.511973[/C][C]0.976053[/C][C]0.488027[/C][/ROW]
[ROW][C]158[/C][C]0.525317[/C][C]0.949366[/C][C]0.474683[/C][/ROW]
[ROW][C]159[/C][C]0.488115[/C][C]0.97623[/C][C]0.511885[/C][/ROW]
[ROW][C]160[/C][C]0.597154[/C][C]0.805691[/C][C]0.402846[/C][/ROW]
[ROW][C]161[/C][C]0.590028[/C][C]0.819945[/C][C]0.409972[/C][/ROW]
[ROW][C]162[/C][C]0.577136[/C][C]0.845728[/C][C]0.422864[/C][/ROW]
[ROW][C]163[/C][C]0.542439[/C][C]0.915123[/C][C]0.457561[/C][/ROW]
[ROW][C]164[/C][C]0.510915[/C][C]0.978171[/C][C]0.489085[/C][/ROW]
[ROW][C]165[/C][C]0.469884[/C][C]0.939767[/C][C]0.530116[/C][/ROW]
[ROW][C]166[/C][C]0.449744[/C][C]0.899489[/C][C]0.550256[/C][/ROW]
[ROW][C]167[/C][C]0.41207[/C][C]0.824141[/C][C]0.58793[/C][/ROW]
[ROW][C]168[/C][C]0.392036[/C][C]0.784071[/C][C]0.607964[/C][/ROW]
[ROW][C]169[/C][C]0.417736[/C][C]0.835472[/C][C]0.582264[/C][/ROW]
[ROW][C]170[/C][C]0.400257[/C][C]0.800514[/C][C]0.599743[/C][/ROW]
[ROW][C]171[/C][C]0.369127[/C][C]0.738254[/C][C]0.630873[/C][/ROW]
[ROW][C]172[/C][C]0.388857[/C][C]0.777714[/C][C]0.611143[/C][/ROW]
[ROW][C]173[/C][C]0.49097[/C][C]0.98194[/C][C]0.50903[/C][/ROW]
[ROW][C]174[/C][C]0.456045[/C][C]0.91209[/C][C]0.543955[/C][/ROW]
[ROW][C]175[/C][C]0.428707[/C][C]0.857414[/C][C]0.571293[/C][/ROW]
[ROW][C]176[/C][C]0.513831[/C][C]0.972339[/C][C]0.486169[/C][/ROW]
[ROW][C]177[/C][C]0.479583[/C][C]0.959165[/C][C]0.520417[/C][/ROW]
[ROW][C]178[/C][C]0.482228[/C][C]0.964456[/C][C]0.517772[/C][/ROW]
[ROW][C]179[/C][C]0.448529[/C][C]0.897057[/C][C]0.551471[/C][/ROW]
[ROW][C]180[/C][C]0.490412[/C][C]0.980823[/C][C]0.509588[/C][/ROW]
[ROW][C]181[/C][C]0.578089[/C][C]0.843822[/C][C]0.421911[/C][/ROW]
[ROW][C]182[/C][C]0.660488[/C][C]0.679024[/C][C]0.339512[/C][/ROW]
[ROW][C]183[/C][C]0.750065[/C][C]0.499869[/C][C]0.249935[/C][/ROW]
[ROW][C]184[/C][C]0.710282[/C][C]0.579435[/C][C]0.289718[/C][/ROW]
[ROW][C]185[/C][C]0.667055[/C][C]0.665891[/C][C]0.332945[/C][/ROW]
[ROW][C]186[/C][C]0.663646[/C][C]0.672709[/C][C]0.336354[/C][/ROW]
[ROW][C]187[/C][C]0.906412[/C][C]0.187176[/C][C]0.0935879[/C][/ROW]
[ROW][C]188[/C][C]0.890752[/C][C]0.218496[/C][C]0.109248[/C][/ROW]
[ROW][C]189[/C][C]0.864035[/C][C]0.271929[/C][C]0.135965[/C][/ROW]
[ROW][C]190[/C][C]0.834301[/C][C]0.331397[/C][C]0.165699[/C][/ROW]
[ROW][C]191[/C][C]0.804509[/C][C]0.390981[/C][C]0.195491[/C][/ROW]
[ROW][C]192[/C][C]0.767687[/C][C]0.464626[/C][C]0.232313[/C][/ROW]
[ROW][C]193[/C][C]0.74193[/C][C]0.51614[/C][C]0.25807[/C][/ROW]
[ROW][C]194[/C][C]0.701625[/C][C]0.59675[/C][C]0.298375[/C][/ROW]
[ROW][C]195[/C][C]0.832279[/C][C]0.335441[/C][C]0.167721[/C][/ROW]
[ROW][C]196[/C][C]0.810289[/C][C]0.379422[/C][C]0.189711[/C][/ROW]
[ROW][C]197[/C][C]0.772447[/C][C]0.455106[/C][C]0.227553[/C][/ROW]
[ROW][C]198[/C][C]0.815731[/C][C]0.368538[/C][C]0.184269[/C][/ROW]
[ROW][C]199[/C][C]0.780291[/C][C]0.439419[/C][C]0.219709[/C][/ROW]
[ROW][C]200[/C][C]0.758971[/C][C]0.482058[/C][C]0.241029[/C][/ROW]
[ROW][C]201[/C][C]0.7089[/C][C]0.5822[/C][C]0.2911[/C][/ROW]
[ROW][C]202[/C][C]0.666863[/C][C]0.666274[/C][C]0.333137[/C][/ROW]
[ROW][C]203[/C][C]0.61687[/C][C]0.766259[/C][C]0.38313[/C][/ROW]
[ROW][C]204[/C][C]0.568168[/C][C]0.863664[/C][C]0.431832[/C][/ROW]
[ROW][C]205[/C][C]0.605766[/C][C]0.788468[/C][C]0.394234[/C][/ROW]
[ROW][C]206[/C][C]0.551509[/C][C]0.896983[/C][C]0.448491[/C][/ROW]
[ROW][C]207[/C][C]0.549707[/C][C]0.900586[/C][C]0.450293[/C][/ROW]
[ROW][C]208[/C][C]0.672632[/C][C]0.654735[/C][C]0.327368[/C][/ROW]
[ROW][C]209[/C][C]0.904186[/C][C]0.191627[/C][C]0.0958135[/C][/ROW]
[ROW][C]210[/C][C]0.869319[/C][C]0.261361[/C][C]0.130681[/C][/ROW]
[ROW][C]211[/C][C]0.907536[/C][C]0.184929[/C][C]0.0924643[/C][/ROW]
[ROW][C]212[/C][C]0.902627[/C][C]0.194747[/C][C]0.0973734[/C][/ROW]
[ROW][C]213[/C][C]0.875869[/C][C]0.248261[/C][C]0.124131[/C][/ROW]
[ROW][C]214[/C][C]0.887233[/C][C]0.225535[/C][C]0.112767[/C][/ROW]
[ROW][C]215[/C][C]0.835803[/C][C]0.328394[/C][C]0.164197[/C][/ROW]
[ROW][C]216[/C][C]0.813162[/C][C]0.373676[/C][C]0.186838[/C][/ROW]
[ROW][C]217[/C][C]0.736849[/C][C]0.526302[/C][C]0.263151[/C][/ROW]
[ROW][C]218[/C][C]0.682188[/C][C]0.635624[/C][C]0.317812[/C][/ROW]
[ROW][C]219[/C][C]0.626635[/C][C]0.74673[/C][C]0.373365[/C][/ROW]
[ROW][C]220[/C][C]0.517287[/C][C]0.965425[/C][C]0.482713[/C][/ROW]
[ROW][C]221[/C][C]0.740791[/C][C]0.518418[/C][C]0.259209[/C][/ROW]
[ROW][C]222[/C][C]0.619024[/C][C]0.761952[/C][C]0.380976[/C][/ROW]
[ROW][C]223[/C][C]0.450631[/C][C]0.901261[/C][C]0.549369[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.680470.6390590.31953
70.597150.8057010.40285
80.5511010.8977990.448899
90.4870660.9741310.512934
100.3713250.7426490.628675
110.4077240.8154470.592276
120.3330840.6661680.666916
130.3503390.7006780.649661
140.2835240.5670470.716476
150.211780.423560.78822
160.1642420.3284840.835758
170.123650.24730.87635
180.1532140.3064270.846786
190.1120660.2241330.887934
200.08315440.1663090.916846
210.05927710.1185540.940723
220.07990780.1598160.920092
230.06197130.1239430.938029
240.04497470.08994950.955025
250.05557750.1111550.944423
260.04047150.0809430.959528
270.04188310.08376620.958117
280.0307120.06142390.969288
290.02263710.04527430.977363
300.02123820.04247650.978762
310.01465040.02930090.98535
320.01066460.02132910.989335
330.008254190.01650840.991746
340.005496260.01099250.994504
350.003723880.007447760.996276
360.002440110.004880220.99756
370.001607040.003214080.998393
380.00116190.002323810.998838
390.00116650.0023330.998834
400.0009533050.001906610.999047
410.00143320.002866390.998567
420.00136050.0027210.998639
430.0009643930.001928790.999036
440.001931830.003863650.998068
450.001720750.00344150.998279
460.002029790.004059580.99797
470.001421170.002842350.998579
480.0009937350.001987470.999006
490.0007310850.001462170.999269
500.0004851780.0009703560.999515
510.0004391890.0008783780.999561
520.0007967580.001593520.999203
530.0005944490.00118890.999406
540.0004207070.0008414140.999579
550.004490780.008981550.995509
560.003515250.007030510.996485
570.002675190.005350390.997325
580.01208020.02416040.98792
590.01372860.02745720.986271
600.01353540.02707080.986465
610.0121160.02423210.987884
620.02439650.04879290.975604
630.02048690.04097380.979513
640.09121220.1824240.908788
650.07778980.155580.92221
660.173310.3466190.82669
670.2907620.5815240.709238
680.3349190.6698370.665081
690.3130.6259990.687
700.3713350.742670.628665
710.5550750.8898510.444925
720.5839020.8321960.416098
730.5616090.8767820.438391
740.6881790.6236420.311821
750.6793260.6413490.320674
760.6639770.6720460.336023
770.639520.720960.36048
780.6559020.6881960.344098
790.6365290.7269420.363471
800.7475780.5048430.252422
810.7220590.5558830.277941
820.6975430.6049140.302457
830.7160180.5679650.283982
840.7030430.5939150.296957
850.6981640.6036720.301836
860.6689920.6620160.331008
870.6405520.7188970.359448
880.6722770.6554450.327723
890.7127860.5744280.287214
900.7756860.4486280.224314
910.7823780.4352450.217622
920.7642590.4714820.235741
930.8020280.3959440.197972
940.8168940.3662120.183106
950.8397550.320490.160245
960.8388870.3222250.161113
970.8610270.2779460.138973
980.8436420.3127170.156358
990.827090.345820.17291
1000.8177990.3644030.182201
1010.8471320.3057350.152868
1020.8505440.2989130.149456
1030.8425710.3148570.157429
1040.8672380.2655240.132762
1050.8716530.2566950.128347
1060.8540060.2919870.145994
1070.8340770.3318470.165923
1080.8648270.2703450.135173
1090.8520190.2959620.147981
1100.8312910.3374170.168709
1110.8145620.3708770.185438
1120.8349330.3301350.165067
1130.8243790.3512420.175621
1140.8324380.3351240.167562
1150.8214840.3570330.178516
1160.8715350.256930.128465
1170.8664850.267030.133515
1180.881380.237240.11862
1190.8641760.2716480.135824
1200.8469370.3061260.153063
1210.8372870.3254260.162713
1220.8196080.3607850.180392
1230.8430550.313890.156945
1240.8193440.3613110.180656
1250.7985130.4029730.201487
1260.7762880.4474250.223712
1270.7917710.4164570.208229
1280.7641550.471690.235845
1290.8268820.3462370.173118
1300.8094810.3810370.190519
1310.8660170.2679650.133983
1320.8444940.3110120.155506
1330.8213570.3572870.178643
1340.8576420.2847160.142358
1350.8422320.3155360.157768
1360.8186440.3627120.181356
1370.8037640.3924720.196236
1380.8064550.3870890.193545
1390.7801640.4396720.219836
1400.7591870.4816260.240813
1410.7315320.5369370.268468
1420.7390920.5218170.260908
1430.7273830.5452350.272617
1440.7454570.5090860.254543
1450.7832410.4335180.216759
1460.7538660.4922670.246134
1470.7229650.554070.277035
1480.6906960.6186080.309304
1490.6658970.6682050.334103
1500.6362540.7274920.363746
1510.6197570.7604860.380243
1520.6850810.6298380.314919
1530.6484950.7030090.351505
1540.6111290.7777410.388871
1550.5865110.8269780.413489
1560.5497060.9005870.450294
1570.5119730.9760530.488027
1580.5253170.9493660.474683
1590.4881150.976230.511885
1600.5971540.8056910.402846
1610.5900280.8199450.409972
1620.5771360.8457280.422864
1630.5424390.9151230.457561
1640.5109150.9781710.489085
1650.4698840.9397670.530116
1660.4497440.8994890.550256
1670.412070.8241410.58793
1680.3920360.7840710.607964
1690.4177360.8354720.582264
1700.4002570.8005140.599743
1710.3691270.7382540.630873
1720.3888570.7777140.611143
1730.490970.981940.50903
1740.4560450.912090.543955
1750.4287070.8574140.571293
1760.5138310.9723390.486169
1770.4795830.9591650.520417
1780.4822280.9644560.517772
1790.4485290.8970570.551471
1800.4904120.9808230.509588
1810.5780890.8438220.421911
1820.6604880.6790240.339512
1830.7500650.4998690.249935
1840.7102820.5794350.289718
1850.6670550.6658910.332945
1860.6636460.6727090.336354
1870.9064120.1871760.0935879
1880.8907520.2184960.109248
1890.8640350.2719290.135965
1900.8343010.3313970.165699
1910.8045090.3909810.195491
1920.7676870.4646260.232313
1930.741930.516140.25807
1940.7016250.596750.298375
1950.8322790.3354410.167721
1960.8102890.3794220.189711
1970.7724470.4551060.227553
1980.8157310.3685380.184269
1990.7802910.4394190.219709
2000.7589710.4820580.241029
2010.70890.58220.2911
2020.6668630.6662740.333137
2030.616870.7662590.38313
2040.5681680.8636640.431832
2050.6057660.7884680.394234
2060.5515090.8969830.448491
2070.5497070.9005860.450293
2080.6726320.6547350.327368
2090.9041860.1916270.0958135
2100.8693190.2613610.130681
2110.9075360.1849290.0924643
2120.9026270.1947470.0973734
2130.8758690.2482610.124131
2140.8872330.2255350.112767
2150.8358030.3283940.164197
2160.8131620.3736760.186838
2170.7368490.5263020.263151
2180.6821880.6356240.317812
2190.6266350.746730.373365
2200.5172870.9654250.482713
2210.7407910.5184180.259209
2220.6190240.7619520.380976
2230.4506310.9012610.549369






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level230.105505NOK
5% type I error level350.16055NOK
10% type I error level390.178899NOK

\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 & 23 & 0.105505 & NOK \tabularnewline
5% type I error level & 35 & 0.16055 & NOK \tabularnewline
10% type I error level & 39 & 0.178899 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270681&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]23[/C][C]0.105505[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]35[/C][C]0.16055[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]39[/C][C]0.178899[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270681&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270681&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 level230.105505NOK
5% type I error level350.16055NOK
10% type I error level390.178899NOK


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