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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 computationThu, 18 Dec 2014 15:03:59 +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/18/t1418915085b71i0k341z4qa5y.htm/, Retrieved Sun, 19 May 2024 17:44:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=271035, Retrieved Sun, 19 May 2024 17:44:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact60

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Multiple Regression] [2014-12-18 15:03:59] [437e345ace789396cb5e4789e8064582] [Current]
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Dataset

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

Tables (Output of Computation)





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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&T=0

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


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

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






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 16.1034 + 0.0193208AMS.I[t] -0.0556732AMS.E[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  16.1034 +  0.0193208AMS.I[t] -0.0556732AMS.E[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  16.1034 +  0.0193208AMS.I[t] -0.0556732AMS.E[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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] = + 16.1034 + 0.0193208AMS.I[t] -0.0556732AMS.E[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.10341.769289.1024.67353e-172.33677e-17
AMS.I0.01932080.02209250.87450.3827470.191374
AMS.E-0.05567320.0273839-2.0330.04321020.0216051

\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) & 16.1034 & 1.76928 & 9.102 & 4.67353e-17 & 2.33677e-17 \tabularnewline
AMS.I & 0.0193208 & 0.0220925 & 0.8745 & 0.382747 & 0.191374 \tabularnewline
AMS.E & -0.0556732 & 0.0273839 & -2.033 & 0.0432102 & 0.0216051 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&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]16.1034[/C][C]1.76928[/C][C]9.102[/C][C]4.67353e-17[/C][C]2.33677e-17[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0193208[/C][C]0.0220925[/C][C]0.8745[/C][C]0.382747[/C][C]0.191374[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0556732[/C][C]0.0273839[/C][C]-2.033[/C][C]0.0432102[/C][C]0.0216051[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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)16.10341.769289.1024.67353e-172.33677e-17
AMS.I0.01932080.02209250.87450.3827470.191374
AMS.E-0.05567320.0273839-2.0330.04321020.0216051






Multiple Linear Regression - Regression Statistics
Multiple R0.134096
R-squared0.0179817
Adjusted R-squared0.00932951
F-TEST (value)2.07829
F-TEST (DF numerator)2
F-TEST (DF denominator)227
p-value0.127519
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.31095
Sum Squared Residuals2488.46

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.134096 \tabularnewline
R-squared & 0.0179817 \tabularnewline
Adjusted R-squared & 0.00932951 \tabularnewline
F-TEST (value) & 2.07829 \tabularnewline
F-TEST (DF numerator) & 2 \tabularnewline
F-TEST (DF denominator) & 227 \tabularnewline
p-value & 0.127519 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.31095 \tabularnewline
Sum Squared Residuals & 2488.46 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.134096[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0179817[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00932951[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]2.07829[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]2[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]227[/C][/ROW]
[ROW][C]p-value[/C][C]0.127519[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.31095[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2488.46[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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 R0.134096
R-squared0.0179817
Adjusted R-squared0.00932951
F-TEST (value)2.07829
F-TEST (DF numerator)2
F-TEST (DF denominator)227
p-value0.127519
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.31095
Sum Squared Residuals2488.46






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.8221-0.922066
212.813.8119-1.0119
37.413.4451-6.04508
46.713.9278-7.22783
512.613.4893-0.88931
614.813.04391.75608
713.314.0392-0.739174
811.113.0498-1.94979
98.215.0596-6.85961
1011.413.3757-1.97567
116.413.8371-7.43709
121213.1598-1.15985
136.313.2417-6.94171
1411.313.2928-1.99281
1511.913.2597-1.35975
169.313.2882-3.98823
171013.0236-3.0236
1813.813.47910.320853
1910.813.2712-2.4712
2011.713.5348-1.83482
2110.913.2303-2.33027
2216.113.41892.68111
239.913.6098-3.70981
2411.512.8962-1.39623
258.312.7666-4.46656
2611.713.8063-2.10632
27913.2155-4.21552
2810.813.136-2.33595
2910.413.2496-2.84959
3012.713.6223-0.922267
3111.812.7803-0.980301
321313.2836-0.283649
3310.812.5485-1.74845
3412.313.0643-0.764252
3511.313.6871-2.3871
3611.613.0099-1.40986
3710.913.5938-2.69379
3812.113.3337-1.23374
3913.313.7939-0.493865
4010.113.3075-3.20755
4114.313.47230.827721
429.313.7189-4.41887
4312.513.2882-0.788228
447.612.72-5.12005
459.213.787-4.587
4614.513.31771.18229
4712.313.804-1.50403
4812.612.47570.124254
49NANA-0.184755
501313.9529-0.952858
5112.613.1041-0.504129
5213.216.2745-3.07452
539.915.3746-5.47459
547.710.5757-2.87567
5510.512.6416-2.14164
5610.919.8905-8.99052
574.37.5915-3.2915
5810.311.8781-1.57809
5911.418.9415-7.54154
605.69.90289-4.30289
618.813.2451-4.44508
62912.6735-3.67349
639.616.7882-7.1882
646.48.27915-1.87915
6511.621.5187-9.91874
664.354.94482-0.594819
6712.77.862044.83796
6818.113.59394.5061
6917.8515.18472.6653
7016.618.0483-1.44833
7112.69.50743.0926
7217.111.73595.3641
7319.116.53252.56747
7416.116.2393-0.13931
7513.359.286864.06314
7618.416.86671.53328
7714.717.645-2.94498
7810.611.3803-0.780253
7912.69.655172.94483
8016.216.1280.072048
8113.68.241695.35831
8218.918.38130.518664
8314.113.29040.809607
8414.511.82692.67314
8516.1514.4611.68904
8614.7513.37351.37653
8714.815.6949-0.894907
8812.4513.8018-1.35182
8912.658.84043.8096
9017.3521.9439-4.59391
918.63.490525.10948
9218.416.74261.65738
9316.118.1233-2.02327
9411.66.964344.63566
9517.7515.87241.87762
9615.2510.47694.77309
9717.6514.68032.96975
9816.3512.92323.42677
9917.6518.6688-1.0188
10013.613.01770.582324
10114.3513.38470.965292
10214.7510.41544.33462
10318.2521.2145-2.96445
1049.97.744962.15504
1051611.5954.40504
10618.2514.7793.47103
10716.8516.17680.673178
10814.614.8438-0.243841
10913.859.017744.83226
11018.9516.56322.38677
11115.614.91650.683454
11214.8516.3018-1.45179
11311.756.784734.96527
11418.4515.93252.51746
11515.912.50513.39486
11617.114.99722.10276
11716.110.61645.48357
11819.922.345-2.445
11910.955.543925.40608
12018.4516.76661.68339
12115.114.08251.01751
1221517.1462-2.14618
12311.358.873562.47644
12415.9511.4874.46299
12518.116.84391.2561
12614.613.15631.44369
12715.413.8451.55504
12815.410.80764.59243
12917.618.1994-0.599438
13013.357.384675.96533
13119.117.25411.84595
13215.3520.9007-5.55069
1337.68.04038-0.440381
13413.413.12790.272148
13513.98.102975.79703
13619.117.06552.03448
13715.2515.6779-0.427876
13812.910.57232.32774
13916.112.39393.70612
14017.3517.6598-0.309826
14113.1514.6462-1.49617
14212.1512.6689-0.518919
14312.615.7904-3.1904
14410.358.172392.17761
14515.419.8143-4.41427
1469.65.065494.53451
14718.218.3756-0.17555
14813.613.20280.397214
14914.8513.12231.72769
15014.7514.2290.520953
15114.112.64841.45162
15214.912.46552.43452
15316.2512.95373.29633
15419.2520.1869-0.936938
15513.613.43820.161784
15613.611.00642.59362
15715.6515.59060.0594353
15812.7511.24271.50727
15914.617.9632-3.36323
1609.8511.3653-1.51526
16112.656.358686.29132
16219.215.54963.65039
16316.618.8723-2.27228
16411.29.201881.99812
16515.2516.4928-1.24282
16611.911.52350.376479
16713.29.859863.34014
16816.3518.0494-1.69943
16912.410.02792.37214
17015.8511.04624.80381
17118.1520.1507-2.00069
17211.158.969992.18001
17315.6510.78154.86852
17417.7523.0974-5.34741
1757.659.14267-1.49267
17612.359.772312.57769
17715.69.491626.10838
17819.317.60411.69595
17915.211.83593.3641
18017.114.84852.25152
18115.610.38155.21854
18218.412.70865.69136
18319.0514.16554.88451
18418.5513.10635.44367
18519.118.9440.155975
18613.113.2553-0.155283
18712.8516.7666-3.91661
1889.518.8279-9.32793
1894.55.77121-1.27121
19011.8511.45080.399219
19113.616.8208-3.22079
19211.712.8178-1.11779
19312.412.6837-0.283714
19413.3514.3429-0.992878
19511.410.14161.25841
19614.98.782426.11758
19719.922.4267-2.52675
19811.29.462161.73784
19914.610.76083.83919
20017.617.10510.494853
20114.0511.48482.56518
20216.116.2848-0.18482
20313.3514.6212-1.27121
20411.8513.1473-1.2973
20511.9510.53931.41068
20614.7512.78811.96195
20715.1515.2268-0.076781
20813.29.918883.28112
20916.8522.0655-5.21553
2107.8513.019-5.16903
2117.78.21892-0.518919
21212.618.6028-6.00283
2137.8511.2801-3.43008
21410.9511.6269-0.676893
21512.3516.4028-4.05282
2169.958.788191.16181
21714.911.75863.14137
21816.6517.1461-0.496054
21913.413.4096-0.00960159
22013.9511.36792.58209
22115.712.49853.20154
22216.8519.3042-2.45415
22310.958.72352.2265
22415.3515.986-0.635974
22512.210.36891.83109
22615.110.73254.36746
22717.7516.19391.55612
22815.214.49150.708524
22914.611.20193.39812
23016.6521.9041-5.25406
2318.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.8221 & -0.922066 \tabularnewline
2 & 12.8 & 13.8119 & -1.0119 \tabularnewline
3 & 7.4 & 13.4451 & -6.04508 \tabularnewline
4 & 6.7 & 13.9278 & -7.22783 \tabularnewline
5 & 12.6 & 13.4893 & -0.88931 \tabularnewline
6 & 14.8 & 13.0439 & 1.75608 \tabularnewline
7 & 13.3 & 14.0392 & -0.739174 \tabularnewline
8 & 11.1 & 13.0498 & -1.94979 \tabularnewline
9 & 8.2 & 15.0596 & -6.85961 \tabularnewline
10 & 11.4 & 13.3757 & -1.97567 \tabularnewline
11 & 6.4 & 13.8371 & -7.43709 \tabularnewline
12 & 12 & 13.1598 & -1.15985 \tabularnewline
13 & 6.3 & 13.2417 & -6.94171 \tabularnewline
14 & 11.3 & 13.2928 & -1.99281 \tabularnewline
15 & 11.9 & 13.2597 & -1.35975 \tabularnewline
16 & 9.3 & 13.2882 & -3.98823 \tabularnewline
17 & 10 & 13.0236 & -3.0236 \tabularnewline
18 & 13.8 & 13.4791 & 0.320853 \tabularnewline
19 & 10.8 & 13.2712 & -2.4712 \tabularnewline
20 & 11.7 & 13.5348 & -1.83482 \tabularnewline
21 & 10.9 & 13.2303 & -2.33027 \tabularnewline
22 & 16.1 & 13.4189 & 2.68111 \tabularnewline
23 & 9.9 & 13.6098 & -3.70981 \tabularnewline
24 & 11.5 & 12.8962 & -1.39623 \tabularnewline
25 & 8.3 & 12.7666 & -4.46656 \tabularnewline
26 & 11.7 & 13.8063 & -2.10632 \tabularnewline
27 & 9 & 13.2155 & -4.21552 \tabularnewline
28 & 10.8 & 13.136 & -2.33595 \tabularnewline
29 & 10.4 & 13.2496 & -2.84959 \tabularnewline
30 & 12.7 & 13.6223 & -0.922267 \tabularnewline
31 & 11.8 & 12.7803 & -0.980301 \tabularnewline
32 & 13 & 13.2836 & -0.283649 \tabularnewline
33 & 10.8 & 12.5485 & -1.74845 \tabularnewline
34 & 12.3 & 13.0643 & -0.764252 \tabularnewline
35 & 11.3 & 13.6871 & -2.3871 \tabularnewline
36 & 11.6 & 13.0099 & -1.40986 \tabularnewline
37 & 10.9 & 13.5938 & -2.69379 \tabularnewline
38 & 12.1 & 13.3337 & -1.23374 \tabularnewline
39 & 13.3 & 13.7939 & -0.493865 \tabularnewline
40 & 10.1 & 13.3075 & -3.20755 \tabularnewline
41 & 14.3 & 13.4723 & 0.827721 \tabularnewline
42 & 9.3 & 13.7189 & -4.41887 \tabularnewline
43 & 12.5 & 13.2882 & -0.788228 \tabularnewline
44 & 7.6 & 12.72 & -5.12005 \tabularnewline
45 & 9.2 & 13.787 & -4.587 \tabularnewline
46 & 14.5 & 13.3177 & 1.18229 \tabularnewline
47 & 12.3 & 13.804 & -1.50403 \tabularnewline
48 & 12.6 & 12.4757 & 0.124254 \tabularnewline
49 & NA & NA & -0.184755 \tabularnewline
50 & 13 & 13.9529 & -0.952858 \tabularnewline
51 & 12.6 & 13.1041 & -0.504129 \tabularnewline
52 & 13.2 & 16.2745 & -3.07452 \tabularnewline
53 & 9.9 & 15.3746 & -5.47459 \tabularnewline
54 & 7.7 & 10.5757 & -2.87567 \tabularnewline
55 & 10.5 & 12.6416 & -2.14164 \tabularnewline
56 & 10.9 & 19.8905 & -8.99052 \tabularnewline
57 & 4.3 & 7.5915 & -3.2915 \tabularnewline
58 & 10.3 & 11.8781 & -1.57809 \tabularnewline
59 & 11.4 & 18.9415 & -7.54154 \tabularnewline
60 & 5.6 & 9.90289 & -4.30289 \tabularnewline
61 & 8.8 & 13.2451 & -4.44508 \tabularnewline
62 & 9 & 12.6735 & -3.67349 \tabularnewline
63 & 9.6 & 16.7882 & -7.1882 \tabularnewline
64 & 6.4 & 8.27915 & -1.87915 \tabularnewline
65 & 11.6 & 21.5187 & -9.91874 \tabularnewline
66 & 4.35 & 4.94482 & -0.594819 \tabularnewline
67 & 12.7 & 7.86204 & 4.83796 \tabularnewline
68 & 18.1 & 13.5939 & 4.5061 \tabularnewline
69 & 17.85 & 15.1847 & 2.6653 \tabularnewline
70 & 16.6 & 18.0483 & -1.44833 \tabularnewline
71 & 12.6 & 9.5074 & 3.0926 \tabularnewline
72 & 17.1 & 11.7359 & 5.3641 \tabularnewline
73 & 19.1 & 16.5325 & 2.56747 \tabularnewline
74 & 16.1 & 16.2393 & -0.13931 \tabularnewline
75 & 13.35 & 9.28686 & 4.06314 \tabularnewline
76 & 18.4 & 16.8667 & 1.53328 \tabularnewline
77 & 14.7 & 17.645 & -2.94498 \tabularnewline
78 & 10.6 & 11.3803 & -0.780253 \tabularnewline
79 & 12.6 & 9.65517 & 2.94483 \tabularnewline
80 & 16.2 & 16.128 & 0.072048 \tabularnewline
81 & 13.6 & 8.24169 & 5.35831 \tabularnewline
82 & 18.9 & 18.3813 & 0.518664 \tabularnewline
83 & 14.1 & 13.2904 & 0.809607 \tabularnewline
84 & 14.5 & 11.8269 & 2.67314 \tabularnewline
85 & 16.15 & 14.461 & 1.68904 \tabularnewline
86 & 14.75 & 13.3735 & 1.37653 \tabularnewline
87 & 14.8 & 15.6949 & -0.894907 \tabularnewline
88 & 12.45 & 13.8018 & -1.35182 \tabularnewline
89 & 12.65 & 8.8404 & 3.8096 \tabularnewline
90 & 17.35 & 21.9439 & -4.59391 \tabularnewline
91 & 8.6 & 3.49052 & 5.10948 \tabularnewline
92 & 18.4 & 16.7426 & 1.65738 \tabularnewline
93 & 16.1 & 18.1233 & -2.02327 \tabularnewline
94 & 11.6 & 6.96434 & 4.63566 \tabularnewline
95 & 17.75 & 15.8724 & 1.87762 \tabularnewline
96 & 15.25 & 10.4769 & 4.77309 \tabularnewline
97 & 17.65 & 14.6803 & 2.96975 \tabularnewline
98 & 16.35 & 12.9232 & 3.42677 \tabularnewline
99 & 17.65 & 18.6688 & -1.0188 \tabularnewline
100 & 13.6 & 13.0177 & 0.582324 \tabularnewline
101 & 14.35 & 13.3847 & 0.965292 \tabularnewline
102 & 14.75 & 10.4154 & 4.33462 \tabularnewline
103 & 18.25 & 21.2145 & -2.96445 \tabularnewline
104 & 9.9 & 7.74496 & 2.15504 \tabularnewline
105 & 16 & 11.595 & 4.40504 \tabularnewline
106 & 18.25 & 14.779 & 3.47103 \tabularnewline
107 & 16.85 & 16.1768 & 0.673178 \tabularnewline
108 & 14.6 & 14.8438 & -0.243841 \tabularnewline
109 & 13.85 & 9.01774 & 4.83226 \tabularnewline
110 & 18.95 & 16.5632 & 2.38677 \tabularnewline
111 & 15.6 & 14.9165 & 0.683454 \tabularnewline
112 & 14.85 & 16.3018 & -1.45179 \tabularnewline
113 & 11.75 & 6.78473 & 4.96527 \tabularnewline
114 & 18.45 & 15.9325 & 2.51746 \tabularnewline
115 & 15.9 & 12.5051 & 3.39486 \tabularnewline
116 & 17.1 & 14.9972 & 2.10276 \tabularnewline
117 & 16.1 & 10.6164 & 5.48357 \tabularnewline
118 & 19.9 & 22.345 & -2.445 \tabularnewline
119 & 10.95 & 5.54392 & 5.40608 \tabularnewline
120 & 18.45 & 16.7666 & 1.68339 \tabularnewline
121 & 15.1 & 14.0825 & 1.01751 \tabularnewline
122 & 15 & 17.1462 & -2.14618 \tabularnewline
123 & 11.35 & 8.87356 & 2.47644 \tabularnewline
124 & 15.95 & 11.487 & 4.46299 \tabularnewline
125 & 18.1 & 16.8439 & 1.2561 \tabularnewline
126 & 14.6 & 13.1563 & 1.44369 \tabularnewline
127 & 15.4 & 13.845 & 1.55504 \tabularnewline
128 & 15.4 & 10.8076 & 4.59243 \tabularnewline
129 & 17.6 & 18.1994 & -0.599438 \tabularnewline
130 & 13.35 & 7.38467 & 5.96533 \tabularnewline
131 & 19.1 & 17.2541 & 1.84595 \tabularnewline
132 & 15.35 & 20.9007 & -5.55069 \tabularnewline
133 & 7.6 & 8.04038 & -0.440381 \tabularnewline
134 & 13.4 & 13.1279 & 0.272148 \tabularnewline
135 & 13.9 & 8.10297 & 5.79703 \tabularnewline
136 & 19.1 & 17.0655 & 2.03448 \tabularnewline
137 & 15.25 & 15.6779 & -0.427876 \tabularnewline
138 & 12.9 & 10.5723 & 2.32774 \tabularnewline
139 & 16.1 & 12.3939 & 3.70612 \tabularnewline
140 & 17.35 & 17.6598 & -0.309826 \tabularnewline
141 & 13.15 & 14.6462 & -1.49617 \tabularnewline
142 & 12.15 & 12.6689 & -0.518919 \tabularnewline
143 & 12.6 & 15.7904 & -3.1904 \tabularnewline
144 & 10.35 & 8.17239 & 2.17761 \tabularnewline
145 & 15.4 & 19.8143 & -4.41427 \tabularnewline
146 & 9.6 & 5.06549 & 4.53451 \tabularnewline
147 & 18.2 & 18.3756 & -0.17555 \tabularnewline
148 & 13.6 & 13.2028 & 0.397214 \tabularnewline
149 & 14.85 & 13.1223 & 1.72769 \tabularnewline
150 & 14.75 & 14.229 & 0.520953 \tabularnewline
151 & 14.1 & 12.6484 & 1.45162 \tabularnewline
152 & 14.9 & 12.4655 & 2.43452 \tabularnewline
153 & 16.25 & 12.9537 & 3.29633 \tabularnewline
154 & 19.25 & 20.1869 & -0.936938 \tabularnewline
155 & 13.6 & 13.4382 & 0.161784 \tabularnewline
156 & 13.6 & 11.0064 & 2.59362 \tabularnewline
157 & 15.65 & 15.5906 & 0.0594353 \tabularnewline
158 & 12.75 & 11.2427 & 1.50727 \tabularnewline
159 & 14.6 & 17.9632 & -3.36323 \tabularnewline
160 & 9.85 & 11.3653 & -1.51526 \tabularnewline
161 & 12.65 & 6.35868 & 6.29132 \tabularnewline
162 & 19.2 & 15.5496 & 3.65039 \tabularnewline
163 & 16.6 & 18.8723 & -2.27228 \tabularnewline
164 & 11.2 & 9.20188 & 1.99812 \tabularnewline
165 & 15.25 & 16.4928 & -1.24282 \tabularnewline
166 & 11.9 & 11.5235 & 0.376479 \tabularnewline
167 & 13.2 & 9.85986 & 3.34014 \tabularnewline
168 & 16.35 & 18.0494 & -1.69943 \tabularnewline
169 & 12.4 & 10.0279 & 2.37214 \tabularnewline
170 & 15.85 & 11.0462 & 4.80381 \tabularnewline
171 & 18.15 & 20.1507 & -2.00069 \tabularnewline
172 & 11.15 & 8.96999 & 2.18001 \tabularnewline
173 & 15.65 & 10.7815 & 4.86852 \tabularnewline
174 & 17.75 & 23.0974 & -5.34741 \tabularnewline
175 & 7.65 & 9.14267 & -1.49267 \tabularnewline
176 & 12.35 & 9.77231 & 2.57769 \tabularnewline
177 & 15.6 & 9.49162 & 6.10838 \tabularnewline
178 & 19.3 & 17.6041 & 1.69595 \tabularnewline
179 & 15.2 & 11.8359 & 3.3641 \tabularnewline
180 & 17.1 & 14.8485 & 2.25152 \tabularnewline
181 & 15.6 & 10.3815 & 5.21854 \tabularnewline
182 & 18.4 & 12.7086 & 5.69136 \tabularnewline
183 & 19.05 & 14.1655 & 4.88451 \tabularnewline
184 & 18.55 & 13.1063 & 5.44367 \tabularnewline
185 & 19.1 & 18.944 & 0.155975 \tabularnewline
186 & 13.1 & 13.2553 & -0.155283 \tabularnewline
187 & 12.85 & 16.7666 & -3.91661 \tabularnewline
188 & 9.5 & 18.8279 & -9.32793 \tabularnewline
189 & 4.5 & 5.77121 & -1.27121 \tabularnewline
190 & 11.85 & 11.4508 & 0.399219 \tabularnewline
191 & 13.6 & 16.8208 & -3.22079 \tabularnewline
192 & 11.7 & 12.8178 & -1.11779 \tabularnewline
193 & 12.4 & 12.6837 & -0.283714 \tabularnewline
194 & 13.35 & 14.3429 & -0.992878 \tabularnewline
195 & 11.4 & 10.1416 & 1.25841 \tabularnewline
196 & 14.9 & 8.78242 & 6.11758 \tabularnewline
197 & 19.9 & 22.4267 & -2.52675 \tabularnewline
198 & 11.2 & 9.46216 & 1.73784 \tabularnewline
199 & 14.6 & 10.7608 & 3.83919 \tabularnewline
200 & 17.6 & 17.1051 & 0.494853 \tabularnewline
201 & 14.05 & 11.4848 & 2.56518 \tabularnewline
202 & 16.1 & 16.2848 & -0.18482 \tabularnewline
203 & 13.35 & 14.6212 & -1.27121 \tabularnewline
204 & 11.85 & 13.1473 & -1.2973 \tabularnewline
205 & 11.95 & 10.5393 & 1.41068 \tabularnewline
206 & 14.75 & 12.7881 & 1.96195 \tabularnewline
207 & 15.15 & 15.2268 & -0.076781 \tabularnewline
208 & 13.2 & 9.91888 & 3.28112 \tabularnewline
209 & 16.85 & 22.0655 & -5.21553 \tabularnewline
210 & 7.85 & 13.019 & -5.16903 \tabularnewline
211 & 7.7 & 8.21892 & -0.518919 \tabularnewline
212 & 12.6 & 18.6028 & -6.00283 \tabularnewline
213 & 7.85 & 11.2801 & -3.43008 \tabularnewline
214 & 10.95 & 11.6269 & -0.676893 \tabularnewline
215 & 12.35 & 16.4028 & -4.05282 \tabularnewline
216 & 9.95 & 8.78819 & 1.16181 \tabularnewline
217 & 14.9 & 11.7586 & 3.14137 \tabularnewline
218 & 16.65 & 17.1461 & -0.496054 \tabularnewline
219 & 13.4 & 13.4096 & -0.00960159 \tabularnewline
220 & 13.95 & 11.3679 & 2.58209 \tabularnewline
221 & 15.7 & 12.4985 & 3.20154 \tabularnewline
222 & 16.85 & 19.3042 & -2.45415 \tabularnewline
223 & 10.95 & 8.7235 & 2.2265 \tabularnewline
224 & 15.35 & 15.986 & -0.635974 \tabularnewline
225 & 12.2 & 10.3689 & 1.83109 \tabularnewline
226 & 15.1 & 10.7325 & 4.36746 \tabularnewline
227 & 17.75 & 16.1939 & 1.55612 \tabularnewline
228 & 15.2 & 14.4915 & 0.708524 \tabularnewline
229 & 14.6 & 11.2019 & 3.39812 \tabularnewline
230 & 16.65 & 21.9041 & -5.25406 \tabularnewline
231 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&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]13.8221[/C][C]-0.922066[/C][/ROW]
[ROW][C]2[/C][C]12.8[/C][C]13.8119[/C][C]-1.0119[/C][/ROW]
[ROW][C]3[/C][C]7.4[/C][C]13.4451[/C][C]-6.04508[/C][/ROW]
[ROW][C]4[/C][C]6.7[/C][C]13.9278[/C][C]-7.22783[/C][/ROW]
[ROW][C]5[/C][C]12.6[/C][C]13.4893[/C][C]-0.88931[/C][/ROW]
[ROW][C]6[/C][C]14.8[/C][C]13.0439[/C][C]1.75608[/C][/ROW]
[ROW][C]7[/C][C]13.3[/C][C]14.0392[/C][C]-0.739174[/C][/ROW]
[ROW][C]8[/C][C]11.1[/C][C]13.0498[/C][C]-1.94979[/C][/ROW]
[ROW][C]9[/C][C]8.2[/C][C]15.0596[/C][C]-6.85961[/C][/ROW]
[ROW][C]10[/C][C]11.4[/C][C]13.3757[/C][C]-1.97567[/C][/ROW]
[ROW][C]11[/C][C]6.4[/C][C]13.8371[/C][C]-7.43709[/C][/ROW]
[ROW][C]12[/C][C]12[/C][C]13.1598[/C][C]-1.15985[/C][/ROW]
[ROW][C]13[/C][C]6.3[/C][C]13.2417[/C][C]-6.94171[/C][/ROW]
[ROW][C]14[/C][C]11.3[/C][C]13.2928[/C][C]-1.99281[/C][/ROW]
[ROW][C]15[/C][C]11.9[/C][C]13.2597[/C][C]-1.35975[/C][/ROW]
[ROW][C]16[/C][C]9.3[/C][C]13.2882[/C][C]-3.98823[/C][/ROW]
[ROW][C]17[/C][C]10[/C][C]13.0236[/C][C]-3.0236[/C][/ROW]
[ROW][C]18[/C][C]13.8[/C][C]13.4791[/C][C]0.320853[/C][/ROW]
[ROW][C]19[/C][C]10.8[/C][C]13.2712[/C][C]-2.4712[/C][/ROW]
[ROW][C]20[/C][C]11.7[/C][C]13.5348[/C][C]-1.83482[/C][/ROW]
[ROW][C]21[/C][C]10.9[/C][C]13.2303[/C][C]-2.33027[/C][/ROW]
[ROW][C]22[/C][C]16.1[/C][C]13.4189[/C][C]2.68111[/C][/ROW]
[ROW][C]23[/C][C]9.9[/C][C]13.6098[/C][C]-3.70981[/C][/ROW]
[ROW][C]24[/C][C]11.5[/C][C]12.8962[/C][C]-1.39623[/C][/ROW]
[ROW][C]25[/C][C]8.3[/C][C]12.7666[/C][C]-4.46656[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]13.8063[/C][C]-2.10632[/C][/ROW]
[ROW][C]27[/C][C]9[/C][C]13.2155[/C][C]-4.21552[/C][/ROW]
[ROW][C]28[/C][C]10.8[/C][C]13.136[/C][C]-2.33595[/C][/ROW]
[ROW][C]29[/C][C]10.4[/C][C]13.2496[/C][C]-2.84959[/C][/ROW]
[ROW][C]30[/C][C]12.7[/C][C]13.6223[/C][C]-0.922267[/C][/ROW]
[ROW][C]31[/C][C]11.8[/C][C]12.7803[/C][C]-0.980301[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.2836[/C][C]-0.283649[/C][/ROW]
[ROW][C]33[/C][C]10.8[/C][C]12.5485[/C][C]-1.74845[/C][/ROW]
[ROW][C]34[/C][C]12.3[/C][C]13.0643[/C][C]-0.764252[/C][/ROW]
[ROW][C]35[/C][C]11.3[/C][C]13.6871[/C][C]-2.3871[/C][/ROW]
[ROW][C]36[/C][C]11.6[/C][C]13.0099[/C][C]-1.40986[/C][/ROW]
[ROW][C]37[/C][C]10.9[/C][C]13.5938[/C][C]-2.69379[/C][/ROW]
[ROW][C]38[/C][C]12.1[/C][C]13.3337[/C][C]-1.23374[/C][/ROW]
[ROW][C]39[/C][C]13.3[/C][C]13.7939[/C][C]-0.493865[/C][/ROW]
[ROW][C]40[/C][C]10.1[/C][C]13.3075[/C][C]-3.20755[/C][/ROW]
[ROW][C]41[/C][C]14.3[/C][C]13.4723[/C][C]0.827721[/C][/ROW]
[ROW][C]42[/C][C]9.3[/C][C]13.7189[/C][C]-4.41887[/C][/ROW]
[ROW][C]43[/C][C]12.5[/C][C]13.2882[/C][C]-0.788228[/C][/ROW]
[ROW][C]44[/C][C]7.6[/C][C]12.72[/C][C]-5.12005[/C][/ROW]
[ROW][C]45[/C][C]9.2[/C][C]13.787[/C][C]-4.587[/C][/ROW]
[ROW][C]46[/C][C]14.5[/C][C]13.3177[/C][C]1.18229[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]13.804[/C][C]-1.50403[/C][/ROW]
[ROW][C]48[/C][C]12.6[/C][C]12.4757[/C][C]0.124254[/C][/ROW]
[ROW][C]49[/C][C]NA[/C][C]NA[/C][C]-0.184755[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]13.9529[/C][C]-0.952858[/C][/ROW]
[ROW][C]51[/C][C]12.6[/C][C]13.1041[/C][C]-0.504129[/C][/ROW]
[ROW][C]52[/C][C]13.2[/C][C]16.2745[/C][C]-3.07452[/C][/ROW]
[ROW][C]53[/C][C]9.9[/C][C]15.3746[/C][C]-5.47459[/C][/ROW]
[ROW][C]54[/C][C]7.7[/C][C]10.5757[/C][C]-2.87567[/C][/ROW]
[ROW][C]55[/C][C]10.5[/C][C]12.6416[/C][C]-2.14164[/C][/ROW]
[ROW][C]56[/C][C]10.9[/C][C]19.8905[/C][C]-8.99052[/C][/ROW]
[ROW][C]57[/C][C]4.3[/C][C]7.5915[/C][C]-3.2915[/C][/ROW]
[ROW][C]58[/C][C]10.3[/C][C]11.8781[/C][C]-1.57809[/C][/ROW]
[ROW][C]59[/C][C]11.4[/C][C]18.9415[/C][C]-7.54154[/C][/ROW]
[ROW][C]60[/C][C]5.6[/C][C]9.90289[/C][C]-4.30289[/C][/ROW]
[ROW][C]61[/C][C]8.8[/C][C]13.2451[/C][C]-4.44508[/C][/ROW]
[ROW][C]62[/C][C]9[/C][C]12.6735[/C][C]-3.67349[/C][/ROW]
[ROW][C]63[/C][C]9.6[/C][C]16.7882[/C][C]-7.1882[/C][/ROW]
[ROW][C]64[/C][C]6.4[/C][C]8.27915[/C][C]-1.87915[/C][/ROW]
[ROW][C]65[/C][C]11.6[/C][C]21.5187[/C][C]-9.91874[/C][/ROW]
[ROW][C]66[/C][C]4.35[/C][C]4.94482[/C][C]-0.594819[/C][/ROW]
[ROW][C]67[/C][C]12.7[/C][C]7.86204[/C][C]4.83796[/C][/ROW]
[ROW][C]68[/C][C]18.1[/C][C]13.5939[/C][C]4.5061[/C][/ROW]
[ROW][C]69[/C][C]17.85[/C][C]15.1847[/C][C]2.6653[/C][/ROW]
[ROW][C]70[/C][C]16.6[/C][C]18.0483[/C][C]-1.44833[/C][/ROW]
[ROW][C]71[/C][C]12.6[/C][C]9.5074[/C][C]3.0926[/C][/ROW]
[ROW][C]72[/C][C]17.1[/C][C]11.7359[/C][C]5.3641[/C][/ROW]
[ROW][C]73[/C][C]19.1[/C][C]16.5325[/C][C]2.56747[/C][/ROW]
[ROW][C]74[/C][C]16.1[/C][C]16.2393[/C][C]-0.13931[/C][/ROW]
[ROW][C]75[/C][C]13.35[/C][C]9.28686[/C][C]4.06314[/C][/ROW]
[ROW][C]76[/C][C]18.4[/C][C]16.8667[/C][C]1.53328[/C][/ROW]
[ROW][C]77[/C][C]14.7[/C][C]17.645[/C][C]-2.94498[/C][/ROW]
[ROW][C]78[/C][C]10.6[/C][C]11.3803[/C][C]-0.780253[/C][/ROW]
[ROW][C]79[/C][C]12.6[/C][C]9.65517[/C][C]2.94483[/C][/ROW]
[ROW][C]80[/C][C]16.2[/C][C]16.128[/C][C]0.072048[/C][/ROW]
[ROW][C]81[/C][C]13.6[/C][C]8.24169[/C][C]5.35831[/C][/ROW]
[ROW][C]82[/C][C]18.9[/C][C]18.3813[/C][C]0.518664[/C][/ROW]
[ROW][C]83[/C][C]14.1[/C][C]13.2904[/C][C]0.809607[/C][/ROW]
[ROW][C]84[/C][C]14.5[/C][C]11.8269[/C][C]2.67314[/C][/ROW]
[ROW][C]85[/C][C]16.15[/C][C]14.461[/C][C]1.68904[/C][/ROW]
[ROW][C]86[/C][C]14.75[/C][C]13.3735[/C][C]1.37653[/C][/ROW]
[ROW][C]87[/C][C]14.8[/C][C]15.6949[/C][C]-0.894907[/C][/ROW]
[ROW][C]88[/C][C]12.45[/C][C]13.8018[/C][C]-1.35182[/C][/ROW]
[ROW][C]89[/C][C]12.65[/C][C]8.8404[/C][C]3.8096[/C][/ROW]
[ROW][C]90[/C][C]17.35[/C][C]21.9439[/C][C]-4.59391[/C][/ROW]
[ROW][C]91[/C][C]8.6[/C][C]3.49052[/C][C]5.10948[/C][/ROW]
[ROW][C]92[/C][C]18.4[/C][C]16.7426[/C][C]1.65738[/C][/ROW]
[ROW][C]93[/C][C]16.1[/C][C]18.1233[/C][C]-2.02327[/C][/ROW]
[ROW][C]94[/C][C]11.6[/C][C]6.96434[/C][C]4.63566[/C][/ROW]
[ROW][C]95[/C][C]17.75[/C][C]15.8724[/C][C]1.87762[/C][/ROW]
[ROW][C]96[/C][C]15.25[/C][C]10.4769[/C][C]4.77309[/C][/ROW]
[ROW][C]97[/C][C]17.65[/C][C]14.6803[/C][C]2.96975[/C][/ROW]
[ROW][C]98[/C][C]16.35[/C][C]12.9232[/C][C]3.42677[/C][/ROW]
[ROW][C]99[/C][C]17.65[/C][C]18.6688[/C][C]-1.0188[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]13.0177[/C][C]0.582324[/C][/ROW]
[ROW][C]101[/C][C]14.35[/C][C]13.3847[/C][C]0.965292[/C][/ROW]
[ROW][C]102[/C][C]14.75[/C][C]10.4154[/C][C]4.33462[/C][/ROW]
[ROW][C]103[/C][C]18.25[/C][C]21.2145[/C][C]-2.96445[/C][/ROW]
[ROW][C]104[/C][C]9.9[/C][C]7.74496[/C][C]2.15504[/C][/ROW]
[ROW][C]105[/C][C]16[/C][C]11.595[/C][C]4.40504[/C][/ROW]
[ROW][C]106[/C][C]18.25[/C][C]14.779[/C][C]3.47103[/C][/ROW]
[ROW][C]107[/C][C]16.85[/C][C]16.1768[/C][C]0.673178[/C][/ROW]
[ROW][C]108[/C][C]14.6[/C][C]14.8438[/C][C]-0.243841[/C][/ROW]
[ROW][C]109[/C][C]13.85[/C][C]9.01774[/C][C]4.83226[/C][/ROW]
[ROW][C]110[/C][C]18.95[/C][C]16.5632[/C][C]2.38677[/C][/ROW]
[ROW][C]111[/C][C]15.6[/C][C]14.9165[/C][C]0.683454[/C][/ROW]
[ROW][C]112[/C][C]14.85[/C][C]16.3018[/C][C]-1.45179[/C][/ROW]
[ROW][C]113[/C][C]11.75[/C][C]6.78473[/C][C]4.96527[/C][/ROW]
[ROW][C]114[/C][C]18.45[/C][C]15.9325[/C][C]2.51746[/C][/ROW]
[ROW][C]115[/C][C]15.9[/C][C]12.5051[/C][C]3.39486[/C][/ROW]
[ROW][C]116[/C][C]17.1[/C][C]14.9972[/C][C]2.10276[/C][/ROW]
[ROW][C]117[/C][C]16.1[/C][C]10.6164[/C][C]5.48357[/C][/ROW]
[ROW][C]118[/C][C]19.9[/C][C]22.345[/C][C]-2.445[/C][/ROW]
[ROW][C]119[/C][C]10.95[/C][C]5.54392[/C][C]5.40608[/C][/ROW]
[ROW][C]120[/C][C]18.45[/C][C]16.7666[/C][C]1.68339[/C][/ROW]
[ROW][C]121[/C][C]15.1[/C][C]14.0825[/C][C]1.01751[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]17.1462[/C][C]-2.14618[/C][/ROW]
[ROW][C]123[/C][C]11.35[/C][C]8.87356[/C][C]2.47644[/C][/ROW]
[ROW][C]124[/C][C]15.95[/C][C]11.487[/C][C]4.46299[/C][/ROW]
[ROW][C]125[/C][C]18.1[/C][C]16.8439[/C][C]1.2561[/C][/ROW]
[ROW][C]126[/C][C]14.6[/C][C]13.1563[/C][C]1.44369[/C][/ROW]
[ROW][C]127[/C][C]15.4[/C][C]13.845[/C][C]1.55504[/C][/ROW]
[ROW][C]128[/C][C]15.4[/C][C]10.8076[/C][C]4.59243[/C][/ROW]
[ROW][C]129[/C][C]17.6[/C][C]18.1994[/C][C]-0.599438[/C][/ROW]
[ROW][C]130[/C][C]13.35[/C][C]7.38467[/C][C]5.96533[/C][/ROW]
[ROW][C]131[/C][C]19.1[/C][C]17.2541[/C][C]1.84595[/C][/ROW]
[ROW][C]132[/C][C]15.35[/C][C]20.9007[/C][C]-5.55069[/C][/ROW]
[ROW][C]133[/C][C]7.6[/C][C]8.04038[/C][C]-0.440381[/C][/ROW]
[ROW][C]134[/C][C]13.4[/C][C]13.1279[/C][C]0.272148[/C][/ROW]
[ROW][C]135[/C][C]13.9[/C][C]8.10297[/C][C]5.79703[/C][/ROW]
[ROW][C]136[/C][C]19.1[/C][C]17.0655[/C][C]2.03448[/C][/ROW]
[ROW][C]137[/C][C]15.25[/C][C]15.6779[/C][C]-0.427876[/C][/ROW]
[ROW][C]138[/C][C]12.9[/C][C]10.5723[/C][C]2.32774[/C][/ROW]
[ROW][C]139[/C][C]16.1[/C][C]12.3939[/C][C]3.70612[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]17.6598[/C][C]-0.309826[/C][/ROW]
[ROW][C]141[/C][C]13.15[/C][C]14.6462[/C][C]-1.49617[/C][/ROW]
[ROW][C]142[/C][C]12.15[/C][C]12.6689[/C][C]-0.518919[/C][/ROW]
[ROW][C]143[/C][C]12.6[/C][C]15.7904[/C][C]-3.1904[/C][/ROW]
[ROW][C]144[/C][C]10.35[/C][C]8.17239[/C][C]2.17761[/C][/ROW]
[ROW][C]145[/C][C]15.4[/C][C]19.8143[/C][C]-4.41427[/C][/ROW]
[ROW][C]146[/C][C]9.6[/C][C]5.06549[/C][C]4.53451[/C][/ROW]
[ROW][C]147[/C][C]18.2[/C][C]18.3756[/C][C]-0.17555[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.2028[/C][C]0.397214[/C][/ROW]
[ROW][C]149[/C][C]14.85[/C][C]13.1223[/C][C]1.72769[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]14.229[/C][C]0.520953[/C][/ROW]
[ROW][C]151[/C][C]14.1[/C][C]12.6484[/C][C]1.45162[/C][/ROW]
[ROW][C]152[/C][C]14.9[/C][C]12.4655[/C][C]2.43452[/C][/ROW]
[ROW][C]153[/C][C]16.25[/C][C]12.9537[/C][C]3.29633[/C][/ROW]
[ROW][C]154[/C][C]19.25[/C][C]20.1869[/C][C]-0.936938[/C][/ROW]
[ROW][C]155[/C][C]13.6[/C][C]13.4382[/C][C]0.161784[/C][/ROW]
[ROW][C]156[/C][C]13.6[/C][C]11.0064[/C][C]2.59362[/C][/ROW]
[ROW][C]157[/C][C]15.65[/C][C]15.5906[/C][C]0.0594353[/C][/ROW]
[ROW][C]158[/C][C]12.75[/C][C]11.2427[/C][C]1.50727[/C][/ROW]
[ROW][C]159[/C][C]14.6[/C][C]17.9632[/C][C]-3.36323[/C][/ROW]
[ROW][C]160[/C][C]9.85[/C][C]11.3653[/C][C]-1.51526[/C][/ROW]
[ROW][C]161[/C][C]12.65[/C][C]6.35868[/C][C]6.29132[/C][/ROW]
[ROW][C]162[/C][C]19.2[/C][C]15.5496[/C][C]3.65039[/C][/ROW]
[ROW][C]163[/C][C]16.6[/C][C]18.8723[/C][C]-2.27228[/C][/ROW]
[ROW][C]164[/C][C]11.2[/C][C]9.20188[/C][C]1.99812[/C][/ROW]
[ROW][C]165[/C][C]15.25[/C][C]16.4928[/C][C]-1.24282[/C][/ROW]
[ROW][C]166[/C][C]11.9[/C][C]11.5235[/C][C]0.376479[/C][/ROW]
[ROW][C]167[/C][C]13.2[/C][C]9.85986[/C][C]3.34014[/C][/ROW]
[ROW][C]168[/C][C]16.35[/C][C]18.0494[/C][C]-1.69943[/C][/ROW]
[ROW][C]169[/C][C]12.4[/C][C]10.0279[/C][C]2.37214[/C][/ROW]
[ROW][C]170[/C][C]15.85[/C][C]11.0462[/C][C]4.80381[/C][/ROW]
[ROW][C]171[/C][C]18.15[/C][C]20.1507[/C][C]-2.00069[/C][/ROW]
[ROW][C]172[/C][C]11.15[/C][C]8.96999[/C][C]2.18001[/C][/ROW]
[ROW][C]173[/C][C]15.65[/C][C]10.7815[/C][C]4.86852[/C][/ROW]
[ROW][C]174[/C][C]17.75[/C][C]23.0974[/C][C]-5.34741[/C][/ROW]
[ROW][C]175[/C][C]7.65[/C][C]9.14267[/C][C]-1.49267[/C][/ROW]
[ROW][C]176[/C][C]12.35[/C][C]9.77231[/C][C]2.57769[/C][/ROW]
[ROW][C]177[/C][C]15.6[/C][C]9.49162[/C][C]6.10838[/C][/ROW]
[ROW][C]178[/C][C]19.3[/C][C]17.6041[/C][C]1.69595[/C][/ROW]
[ROW][C]179[/C][C]15.2[/C][C]11.8359[/C][C]3.3641[/C][/ROW]
[ROW][C]180[/C][C]17.1[/C][C]14.8485[/C][C]2.25152[/C][/ROW]
[ROW][C]181[/C][C]15.6[/C][C]10.3815[/C][C]5.21854[/C][/ROW]
[ROW][C]182[/C][C]18.4[/C][C]12.7086[/C][C]5.69136[/C][/ROW]
[ROW][C]183[/C][C]19.05[/C][C]14.1655[/C][C]4.88451[/C][/ROW]
[ROW][C]184[/C][C]18.55[/C][C]13.1063[/C][C]5.44367[/C][/ROW]
[ROW][C]185[/C][C]19.1[/C][C]18.944[/C][C]0.155975[/C][/ROW]
[ROW][C]186[/C][C]13.1[/C][C]13.2553[/C][C]-0.155283[/C][/ROW]
[ROW][C]187[/C][C]12.85[/C][C]16.7666[/C][C]-3.91661[/C][/ROW]
[ROW][C]188[/C][C]9.5[/C][C]18.8279[/C][C]-9.32793[/C][/ROW]
[ROW][C]189[/C][C]4.5[/C][C]5.77121[/C][C]-1.27121[/C][/ROW]
[ROW][C]190[/C][C]11.85[/C][C]11.4508[/C][C]0.399219[/C][/ROW]
[ROW][C]191[/C][C]13.6[/C][C]16.8208[/C][C]-3.22079[/C][/ROW]
[ROW][C]192[/C][C]11.7[/C][C]12.8178[/C][C]-1.11779[/C][/ROW]
[ROW][C]193[/C][C]12.4[/C][C]12.6837[/C][C]-0.283714[/C][/ROW]
[ROW][C]194[/C][C]13.35[/C][C]14.3429[/C][C]-0.992878[/C][/ROW]
[ROW][C]195[/C][C]11.4[/C][C]10.1416[/C][C]1.25841[/C][/ROW]
[ROW][C]196[/C][C]14.9[/C][C]8.78242[/C][C]6.11758[/C][/ROW]
[ROW][C]197[/C][C]19.9[/C][C]22.4267[/C][C]-2.52675[/C][/ROW]
[ROW][C]198[/C][C]11.2[/C][C]9.46216[/C][C]1.73784[/C][/ROW]
[ROW][C]199[/C][C]14.6[/C][C]10.7608[/C][C]3.83919[/C][/ROW]
[ROW][C]200[/C][C]17.6[/C][C]17.1051[/C][C]0.494853[/C][/ROW]
[ROW][C]201[/C][C]14.05[/C][C]11.4848[/C][C]2.56518[/C][/ROW]
[ROW][C]202[/C][C]16.1[/C][C]16.2848[/C][C]-0.18482[/C][/ROW]
[ROW][C]203[/C][C]13.35[/C][C]14.6212[/C][C]-1.27121[/C][/ROW]
[ROW][C]204[/C][C]11.85[/C][C]13.1473[/C][C]-1.2973[/C][/ROW]
[ROW][C]205[/C][C]11.95[/C][C]10.5393[/C][C]1.41068[/C][/ROW]
[ROW][C]206[/C][C]14.75[/C][C]12.7881[/C][C]1.96195[/C][/ROW]
[ROW][C]207[/C][C]15.15[/C][C]15.2268[/C][C]-0.076781[/C][/ROW]
[ROW][C]208[/C][C]13.2[/C][C]9.91888[/C][C]3.28112[/C][/ROW]
[ROW][C]209[/C][C]16.85[/C][C]22.0655[/C][C]-5.21553[/C][/ROW]
[ROW][C]210[/C][C]7.85[/C][C]13.019[/C][C]-5.16903[/C][/ROW]
[ROW][C]211[/C][C]7.7[/C][C]8.21892[/C][C]-0.518919[/C][/ROW]
[ROW][C]212[/C][C]12.6[/C][C]18.6028[/C][C]-6.00283[/C][/ROW]
[ROW][C]213[/C][C]7.85[/C][C]11.2801[/C][C]-3.43008[/C][/ROW]
[ROW][C]214[/C][C]10.95[/C][C]11.6269[/C][C]-0.676893[/C][/ROW]
[ROW][C]215[/C][C]12.35[/C][C]16.4028[/C][C]-4.05282[/C][/ROW]
[ROW][C]216[/C][C]9.95[/C][C]8.78819[/C][C]1.16181[/C][/ROW]
[ROW][C]217[/C][C]14.9[/C][C]11.7586[/C][C]3.14137[/C][/ROW]
[ROW][C]218[/C][C]16.65[/C][C]17.1461[/C][C]-0.496054[/C][/ROW]
[ROW][C]219[/C][C]13.4[/C][C]13.4096[/C][C]-0.00960159[/C][/ROW]
[ROW][C]220[/C][C]13.95[/C][C]11.3679[/C][C]2.58209[/C][/ROW]
[ROW][C]221[/C][C]15.7[/C][C]12.4985[/C][C]3.20154[/C][/ROW]
[ROW][C]222[/C][C]16.85[/C][C]19.3042[/C][C]-2.45415[/C][/ROW]
[ROW][C]223[/C][C]10.95[/C][C]8.7235[/C][C]2.2265[/C][/ROW]
[ROW][C]224[/C][C]15.35[/C][C]15.986[/C][C]-0.635974[/C][/ROW]
[ROW][C]225[/C][C]12.2[/C][C]10.3689[/C][C]1.83109[/C][/ROW]
[ROW][C]226[/C][C]15.1[/C][C]10.7325[/C][C]4.36746[/C][/ROW]
[ROW][C]227[/C][C]17.75[/C][C]16.1939[/C][C]1.55612[/C][/ROW]
[ROW][C]228[/C][C]15.2[/C][C]14.4915[/C][C]0.708524[/C][/ROW]
[ROW][C]229[/C][C]14.6[/C][C]11.2019[/C][C]3.39812[/C][/ROW]
[ROW][C]230[/C][C]16.65[/C][C]21.9041[/C][C]-5.25406[/C][/ROW]
[ROW][C]231[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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
112.913.8221-0.922066
212.813.8119-1.0119
37.413.4451-6.04508
46.713.9278-7.22783
512.613.4893-0.88931
614.813.04391.75608
713.314.0392-0.739174
811.113.0498-1.94979
98.215.0596-6.85961
1011.413.3757-1.97567
116.413.8371-7.43709
121213.1598-1.15985
136.313.2417-6.94171
1411.313.2928-1.99281
1511.913.2597-1.35975
169.313.2882-3.98823
171013.0236-3.0236
1813.813.47910.320853
1910.813.2712-2.4712
2011.713.5348-1.83482
2110.913.2303-2.33027
2216.113.41892.68111
239.913.6098-3.70981
2411.512.8962-1.39623
258.312.7666-4.46656
2611.713.8063-2.10632
27913.2155-4.21552
2810.813.136-2.33595
2910.413.2496-2.84959
3012.713.6223-0.922267
3111.812.7803-0.980301
321313.2836-0.283649
3310.812.5485-1.74845
3412.313.0643-0.764252
3511.313.6871-2.3871
3611.613.0099-1.40986
3710.913.5938-2.69379
3812.113.3337-1.23374
3913.313.7939-0.493865
4010.113.3075-3.20755
4114.313.47230.827721
429.313.7189-4.41887
4312.513.2882-0.788228
447.612.72-5.12005
459.213.787-4.587
4614.513.31771.18229
4712.313.804-1.50403
4812.612.47570.124254
49NANA-0.184755
501313.9529-0.952858
5112.613.1041-0.504129
5213.216.2745-3.07452
539.915.3746-5.47459
547.710.5757-2.87567
5510.512.6416-2.14164
5610.919.8905-8.99052
574.37.5915-3.2915
5810.311.8781-1.57809
5911.418.9415-7.54154
605.69.90289-4.30289
618.813.2451-4.44508
62912.6735-3.67349
639.616.7882-7.1882
646.48.27915-1.87915
6511.621.5187-9.91874
664.354.94482-0.594819
6712.77.862044.83796
6818.113.59394.5061
6917.8515.18472.6653
7016.618.0483-1.44833
7112.69.50743.0926
7217.111.73595.3641
7319.116.53252.56747
7416.116.2393-0.13931
7513.359.286864.06314
7618.416.86671.53328
7714.717.645-2.94498
7810.611.3803-0.780253
7912.69.655172.94483
8016.216.1280.072048
8113.68.241695.35831
8218.918.38130.518664
8314.113.29040.809607
8414.511.82692.67314
8516.1514.4611.68904
8614.7513.37351.37653
8714.815.6949-0.894907
8812.4513.8018-1.35182
8912.658.84043.8096
9017.3521.9439-4.59391
918.63.490525.10948
9218.416.74261.65738
9316.118.1233-2.02327
9411.66.964344.63566
9517.7515.87241.87762
9615.2510.47694.77309
9717.6514.68032.96975
9816.3512.92323.42677
9917.6518.6688-1.0188
10013.613.01770.582324
10114.3513.38470.965292
10214.7510.41544.33462
10318.2521.2145-2.96445
1049.97.744962.15504
1051611.5954.40504
10618.2514.7793.47103
10716.8516.17680.673178
10814.614.8438-0.243841
10913.859.017744.83226
11018.9516.56322.38677
11115.614.91650.683454
11214.8516.3018-1.45179
11311.756.784734.96527
11418.4515.93252.51746
11515.912.50513.39486
11617.114.99722.10276
11716.110.61645.48357
11819.922.345-2.445
11910.955.543925.40608
12018.4516.76661.68339
12115.114.08251.01751
1221517.1462-2.14618
12311.358.873562.47644
12415.9511.4874.46299
12518.116.84391.2561
12614.613.15631.44369
12715.413.8451.55504
12815.410.80764.59243
12917.618.1994-0.599438
13013.357.384675.96533
13119.117.25411.84595
13215.3520.9007-5.55069
1337.68.04038-0.440381
13413.413.12790.272148
13513.98.102975.79703
13619.117.06552.03448
13715.2515.6779-0.427876
13812.910.57232.32774
13916.112.39393.70612
14017.3517.6598-0.309826
14113.1514.6462-1.49617
14212.1512.6689-0.518919
14312.615.7904-3.1904
14410.358.172392.17761
14515.419.8143-4.41427
1469.65.065494.53451
14718.218.3756-0.17555
14813.613.20280.397214
14914.8513.12231.72769
15014.7514.2290.520953
15114.112.64841.45162
15214.912.46552.43452
15316.2512.95373.29633
15419.2520.1869-0.936938
15513.613.43820.161784
15613.611.00642.59362
15715.6515.59060.0594353
15812.7511.24271.50727
15914.617.9632-3.36323
1609.8511.3653-1.51526
16112.656.358686.29132
16219.215.54963.65039
16316.618.8723-2.27228
16411.29.201881.99812
16515.2516.4928-1.24282
16611.911.52350.376479
16713.29.859863.34014
16816.3518.0494-1.69943
16912.410.02792.37214
17015.8511.04624.80381
17118.1520.1507-2.00069
17211.158.969992.18001
17315.6510.78154.86852
17417.7523.0974-5.34741
1757.659.14267-1.49267
17612.359.772312.57769
17715.69.491626.10838
17819.317.60411.69595
17915.211.83593.3641
18017.114.84852.25152
18115.610.38155.21854
18218.412.70865.69136
18319.0514.16554.88451
18418.5513.10635.44367
18519.118.9440.155975
18613.113.2553-0.155283
18712.8516.7666-3.91661
1889.518.8279-9.32793
1894.55.77121-1.27121
19011.8511.45080.399219
19113.616.8208-3.22079
19211.712.8178-1.11779
19312.412.6837-0.283714
19413.3514.3429-0.992878
19511.410.14161.25841
19614.98.782426.11758
19719.922.4267-2.52675
19811.29.462161.73784
19914.610.76083.83919
20017.617.10510.494853
20114.0511.48482.56518
20216.116.2848-0.18482
20313.3514.6212-1.27121
20411.8513.1473-1.2973
20511.9510.53931.41068
20614.7512.78811.96195
20715.1515.2268-0.076781
20813.29.918883.28112
20916.8522.0655-5.21553
2107.8513.019-5.16903
2117.78.21892-0.518919
21212.618.6028-6.00283
2137.8511.2801-3.43008
21410.9511.6269-0.676893
21512.3516.4028-4.05282
2169.958.788191.16181
21714.911.75863.14137
21816.6517.1461-0.496054
21913.413.4096-0.00960159
22013.9511.36792.58209
22115.712.49853.20154
22216.8519.3042-2.45415
22310.958.72352.2265
22415.3515.986-0.635974
22512.210.36891.83109
22615.110.73254.36746
22717.7516.19391.55612
22815.214.49150.708524
22914.611.20193.39812
23016.6521.9041-5.25406
2318.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
60.1822550.3645110.817745
70.4408640.8817270.559136
80.3465070.6930150.653493
90.3511850.7023710.648815
100.2491490.4982980.750851
110.2544040.5088080.745596
120.1759350.351870.824065
130.2452760.4905520.754724
140.1812640.3625280.818736
150.1279880.2559750.872012
160.1026460.2052920.897354
170.07027060.1405410.929729
180.09586560.1917310.904134
190.0664190.1328380.933581
200.05119110.1023820.948809
210.0350390.07007790.964961
220.08415780.1683160.915842
230.06195330.1239070.938047
240.04476060.08952110.955239
250.1025860.2051710.897414
260.07970790.1594160.920292
270.07026610.1405320.929734
280.05218350.1043670.947817
290.0388680.0777360.961132
300.0326270.0652540.967373
310.02282380.04564760.977176
320.01799490.03598980.982005
330.0139910.0279820.986009
340.009435770.01887150.990564
350.006896170.01379230.993104
360.004647260.009294520.995353
370.00316470.00632940.996835
380.002374270.004748550.997626
390.002333080.004666160.997667
400.001682380.003364770.998318
410.001949570.003899150.99805
420.001628730.003257460.998371
430.001173240.002346480.998827
440.002305770.004611550.997694
450.002096450.004192890.997904
460.002338680.004677370.997661
470.001696180.003392360.998304
480.001141840.002283670.998858
490.0008209550.001641910.999179
500.0005539550.001107910.999446
510.0005088230.001017650.999491
520.0004425890.0008851770.999557
530.0007261310.001452260.999274
540.0005318260.001063650.999468
550.0003664450.0007328910.999634
560.003890560.007781130.996109
570.003197030.006394070.996803
580.002395690.004791380.997604
590.01015990.02031970.98984
600.01097040.02194080.98903
610.01085540.02171070.989145
620.00979470.01958940.990205
630.02092910.04185810.979071
640.01753230.03506470.982468
650.07783750.1556750.922162
660.06640410.1328080.933596
670.1559880.3119760.844012
680.2785750.5571490.721425
690.357550.7150990.64245
700.3367610.6735220.663239
710.4211390.8422790.578861
720.6126170.7747650.387383
730.648080.703840.35192
740.6227640.7544730.377236
750.7032390.5935210.296761
760.7051170.5897660.294883
770.6924810.6150380.307519
780.6649820.6700360.335018
790.68380.63240.3162
800.6590540.6818920.340946
810.7780520.4438960.221948
820.7582530.4834940.241747
830.7394520.5210950.260548
840.7518550.496290.248145
850.7416320.5167370.258368
860.7292580.5414840.270742
870.700850.59830.29915
880.6741890.6516220.325811
890.7105370.5789270.289463
900.740790.518420.25921
910.8090140.3819710.190986
920.7996890.4006220.200311
930.7833650.4332690.216635
940.8257570.3484860.174243
950.8176620.3646760.182338
960.8545160.2909680.145484
970.8575760.2848480.142424
980.8680730.2638530.131927
990.8503170.2993660.149683
1000.8309880.3380240.169012
1010.8117380.3765240.188262
1020.8380190.3239610.161981
1030.8365650.3268710.163435
1040.8269190.3461620.173081
1050.8514040.2971930.148596
1060.8560240.2879510.143976
1070.8367950.326410.163205
1080.8144290.3711420.185571
1090.8464350.307130.153565
1100.8387490.3225020.161251
1110.8163280.3673440.183672
1120.7976780.4046430.202322
1130.8327320.3345360.167268
1140.8248040.3503920.175196
1150.8265570.3468860.173443
1160.8118790.3762420.188121
1170.8526590.2946820.147341
1180.8453440.3093110.154656
1190.8827710.2344580.117229
1200.8688170.2623660.131183
1210.8496110.3007780.150389
1220.8392390.3215220.160761
1230.8301340.3397320.169866
1240.8486270.3027460.151373
1250.8291710.3416580.170829
1260.8081720.3836560.191828
1270.7865260.4269480.213474
1280.8112970.3774050.188703
1290.7858010.4283970.214199
1300.8438270.3123450.156173
1310.8269060.3461880.173094
1320.8738260.2523470.126174
1330.853560.292880.14644
1340.8303180.3393640.169682
1350.8748810.2502380.125119
1360.8613660.2772690.138634
1370.8394090.3211820.160591
1380.8255580.3488830.174442
1390.8296430.3407150.170357
1400.8052240.3895520.194776
1410.7859710.4280570.214029
1420.7592150.4815690.240785
1430.7618150.476370.238185
1440.7422950.5154110.257705
1450.774720.4505610.22528
1460.7947320.4105360.205268
1470.7656470.4687070.234353
1480.7341830.5316340.265817
1490.7080360.5839280.291964
1500.6732770.6534450.326723
1510.6417450.716510.358255
1520.6206920.7586160.379308
1530.6478080.7043840.352192
1540.6115460.7769080.388454
1550.5726930.8546140.427307
1560.5509680.8980640.449032
1570.5158040.9683910.484196
1580.4802350.960470.519765
1590.494280.9885590.50572
1600.4596570.9193150.540343
1610.5447580.9104840.455242
1620.5431160.9137670.456884
1630.5258830.9482340.474117
1640.4946180.9892370.505382
1650.465430.9308590.53457
1660.4257040.8514070.574296
1670.4149680.8299350.585032
1680.3833790.7667580.616621
1690.363290.726580.63671
1700.3945730.7891460.605427
1710.3721330.7442650.627867
1720.3456770.6913550.654323
1730.3746220.7492440.625378
1740.4707670.9415340.529233
1750.4363440.8726880.563656
1760.4125070.8250140.587493
1770.5065330.9869350.493467
1780.4730530.9461060.526947
1790.4674020.9348030.532598
1800.4359110.8718210.564089
1810.4868580.9737150.513142
1820.5789740.8420510.421026
1830.6300030.7399940.369997
1840.7198950.560210.280105
1850.6772940.6454120.322706
1860.6317210.7365580.368279
1870.6466450.7067090.353355
1880.905290.1894210.0947103
1890.8868050.2263890.113195
1900.8595470.2809060.140453
1910.8500670.2998650.149933
1920.8257420.3485150.174258
1930.7939640.4120720.206036
1940.7553360.4893270.244664
1950.7136380.5727240.286362
1960.8319860.3360280.168014
1970.8141680.3716640.185832
1980.7824850.4350310.217515
1990.8176450.3647110.182355
2000.7821880.4356240.217812
2010.7589690.4820630.241031
2020.7093710.5812580.290629
2030.66380.67240.3362
2040.6119610.7760780.388039
2050.56480.8704010.4352
2060.6353870.7292260.364613
2070.5977520.8044960.402248
2080.5856530.8286940.414347
2090.6782060.6435880.321794
2100.8978520.2042960.102148
2110.8625630.2748740.137437
2120.9033560.1932880.0966439
2130.9101270.1797450.0898727
2140.8769670.2460650.123033
2150.9026140.1947710.0973857
2160.8612890.2774220.138711
2170.8433460.3133070.156654
2180.787060.425880.21294
2190.7119130.5761750.288087
2200.6360820.7278360.363918
2210.5203880.9592240.479612
2220.7825870.4348260.217413
2230.6573640.6852720.342636
2240.5305860.9388270.469414
2250.3405670.6811340.659433

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
6 & 0.182255 & 0.364511 & 0.817745 \tabularnewline
7 & 0.440864 & 0.881727 & 0.559136 \tabularnewline
8 & 0.346507 & 0.693015 & 0.653493 \tabularnewline
9 & 0.351185 & 0.702371 & 0.648815 \tabularnewline
10 & 0.249149 & 0.498298 & 0.750851 \tabularnewline
11 & 0.254404 & 0.508808 & 0.745596 \tabularnewline
12 & 0.175935 & 0.35187 & 0.824065 \tabularnewline
13 & 0.245276 & 0.490552 & 0.754724 \tabularnewline
14 & 0.181264 & 0.362528 & 0.818736 \tabularnewline
15 & 0.127988 & 0.255975 & 0.872012 \tabularnewline
16 & 0.102646 & 0.205292 & 0.897354 \tabularnewline
17 & 0.0702706 & 0.140541 & 0.929729 \tabularnewline
18 & 0.0958656 & 0.191731 & 0.904134 \tabularnewline
19 & 0.066419 & 0.132838 & 0.933581 \tabularnewline
20 & 0.0511911 & 0.102382 & 0.948809 \tabularnewline
21 & 0.035039 & 0.0700779 & 0.964961 \tabularnewline
22 & 0.0841578 & 0.168316 & 0.915842 \tabularnewline
23 & 0.0619533 & 0.123907 & 0.938047 \tabularnewline
24 & 0.0447606 & 0.0895211 & 0.955239 \tabularnewline
25 & 0.102586 & 0.205171 & 0.897414 \tabularnewline
26 & 0.0797079 & 0.159416 & 0.920292 \tabularnewline
27 & 0.0702661 & 0.140532 & 0.929734 \tabularnewline
28 & 0.0521835 & 0.104367 & 0.947817 \tabularnewline
29 & 0.038868 & 0.077736 & 0.961132 \tabularnewline
30 & 0.032627 & 0.065254 & 0.967373 \tabularnewline
31 & 0.0228238 & 0.0456476 & 0.977176 \tabularnewline
32 & 0.0179949 & 0.0359898 & 0.982005 \tabularnewline
33 & 0.013991 & 0.027982 & 0.986009 \tabularnewline
34 & 0.00943577 & 0.0188715 & 0.990564 \tabularnewline
35 & 0.00689617 & 0.0137923 & 0.993104 \tabularnewline
36 & 0.00464726 & 0.00929452 & 0.995353 \tabularnewline
37 & 0.0031647 & 0.0063294 & 0.996835 \tabularnewline
38 & 0.00237427 & 0.00474855 & 0.997626 \tabularnewline
39 & 0.00233308 & 0.00466616 & 0.997667 \tabularnewline
40 & 0.00168238 & 0.00336477 & 0.998318 \tabularnewline
41 & 0.00194957 & 0.00389915 & 0.99805 \tabularnewline
42 & 0.00162873 & 0.00325746 & 0.998371 \tabularnewline
43 & 0.00117324 & 0.00234648 & 0.998827 \tabularnewline
44 & 0.00230577 & 0.00461155 & 0.997694 \tabularnewline
45 & 0.00209645 & 0.00419289 & 0.997904 \tabularnewline
46 & 0.00233868 & 0.00467737 & 0.997661 \tabularnewline
47 & 0.00169618 & 0.00339236 & 0.998304 \tabularnewline
48 & 0.00114184 & 0.00228367 & 0.998858 \tabularnewline
49 & 0.000820955 & 0.00164191 & 0.999179 \tabularnewline
50 & 0.000553955 & 0.00110791 & 0.999446 \tabularnewline
51 & 0.000508823 & 0.00101765 & 0.999491 \tabularnewline
52 & 0.000442589 & 0.000885177 & 0.999557 \tabularnewline
53 & 0.000726131 & 0.00145226 & 0.999274 \tabularnewline
54 & 0.000531826 & 0.00106365 & 0.999468 \tabularnewline
55 & 0.000366445 & 0.000732891 & 0.999634 \tabularnewline
56 & 0.00389056 & 0.00778113 & 0.996109 \tabularnewline
57 & 0.00319703 & 0.00639407 & 0.996803 \tabularnewline
58 & 0.00239569 & 0.00479138 & 0.997604 \tabularnewline
59 & 0.0101599 & 0.0203197 & 0.98984 \tabularnewline
60 & 0.0109704 & 0.0219408 & 0.98903 \tabularnewline
61 & 0.0108554 & 0.0217107 & 0.989145 \tabularnewline
62 & 0.0097947 & 0.0195894 & 0.990205 \tabularnewline
63 & 0.0209291 & 0.0418581 & 0.979071 \tabularnewline
64 & 0.0175323 & 0.0350647 & 0.982468 \tabularnewline
65 & 0.0778375 & 0.155675 & 0.922162 \tabularnewline
66 & 0.0664041 & 0.132808 & 0.933596 \tabularnewline
67 & 0.155988 & 0.311976 & 0.844012 \tabularnewline
68 & 0.278575 & 0.557149 & 0.721425 \tabularnewline
69 & 0.35755 & 0.715099 & 0.64245 \tabularnewline
70 & 0.336761 & 0.673522 & 0.663239 \tabularnewline
71 & 0.421139 & 0.842279 & 0.578861 \tabularnewline
72 & 0.612617 & 0.774765 & 0.387383 \tabularnewline
73 & 0.64808 & 0.70384 & 0.35192 \tabularnewline
74 & 0.622764 & 0.754473 & 0.377236 \tabularnewline
75 & 0.703239 & 0.593521 & 0.296761 \tabularnewline
76 & 0.705117 & 0.589766 & 0.294883 \tabularnewline
77 & 0.692481 & 0.615038 & 0.307519 \tabularnewline
78 & 0.664982 & 0.670036 & 0.335018 \tabularnewline
79 & 0.6838 & 0.6324 & 0.3162 \tabularnewline
80 & 0.659054 & 0.681892 & 0.340946 \tabularnewline
81 & 0.778052 & 0.443896 & 0.221948 \tabularnewline
82 & 0.758253 & 0.483494 & 0.241747 \tabularnewline
83 & 0.739452 & 0.521095 & 0.260548 \tabularnewline
84 & 0.751855 & 0.49629 & 0.248145 \tabularnewline
85 & 0.741632 & 0.516737 & 0.258368 \tabularnewline
86 & 0.729258 & 0.541484 & 0.270742 \tabularnewline
87 & 0.70085 & 0.5983 & 0.29915 \tabularnewline
88 & 0.674189 & 0.651622 & 0.325811 \tabularnewline
89 & 0.710537 & 0.578927 & 0.289463 \tabularnewline
90 & 0.74079 & 0.51842 & 0.25921 \tabularnewline
91 & 0.809014 & 0.381971 & 0.190986 \tabularnewline
92 & 0.799689 & 0.400622 & 0.200311 \tabularnewline
93 & 0.783365 & 0.433269 & 0.216635 \tabularnewline
94 & 0.825757 & 0.348486 & 0.174243 \tabularnewline
95 & 0.817662 & 0.364676 & 0.182338 \tabularnewline
96 & 0.854516 & 0.290968 & 0.145484 \tabularnewline
97 & 0.857576 & 0.284848 & 0.142424 \tabularnewline
98 & 0.868073 & 0.263853 & 0.131927 \tabularnewline
99 & 0.850317 & 0.299366 & 0.149683 \tabularnewline
100 & 0.830988 & 0.338024 & 0.169012 \tabularnewline
101 & 0.811738 & 0.376524 & 0.188262 \tabularnewline
102 & 0.838019 & 0.323961 & 0.161981 \tabularnewline
103 & 0.836565 & 0.326871 & 0.163435 \tabularnewline
104 & 0.826919 & 0.346162 & 0.173081 \tabularnewline
105 & 0.851404 & 0.297193 & 0.148596 \tabularnewline
106 & 0.856024 & 0.287951 & 0.143976 \tabularnewline
107 & 0.836795 & 0.32641 & 0.163205 \tabularnewline
108 & 0.814429 & 0.371142 & 0.185571 \tabularnewline
109 & 0.846435 & 0.30713 & 0.153565 \tabularnewline
110 & 0.838749 & 0.322502 & 0.161251 \tabularnewline
111 & 0.816328 & 0.367344 & 0.183672 \tabularnewline
112 & 0.797678 & 0.404643 & 0.202322 \tabularnewline
113 & 0.832732 & 0.334536 & 0.167268 \tabularnewline
114 & 0.824804 & 0.350392 & 0.175196 \tabularnewline
115 & 0.826557 & 0.346886 & 0.173443 \tabularnewline
116 & 0.811879 & 0.376242 & 0.188121 \tabularnewline
117 & 0.852659 & 0.294682 & 0.147341 \tabularnewline
118 & 0.845344 & 0.309311 & 0.154656 \tabularnewline
119 & 0.882771 & 0.234458 & 0.117229 \tabularnewline
120 & 0.868817 & 0.262366 & 0.131183 \tabularnewline
121 & 0.849611 & 0.300778 & 0.150389 \tabularnewline
122 & 0.839239 & 0.321522 & 0.160761 \tabularnewline
123 & 0.830134 & 0.339732 & 0.169866 \tabularnewline
124 & 0.848627 & 0.302746 & 0.151373 \tabularnewline
125 & 0.829171 & 0.341658 & 0.170829 \tabularnewline
126 & 0.808172 & 0.383656 & 0.191828 \tabularnewline
127 & 0.786526 & 0.426948 & 0.213474 \tabularnewline
128 & 0.811297 & 0.377405 & 0.188703 \tabularnewline
129 & 0.785801 & 0.428397 & 0.214199 \tabularnewline
130 & 0.843827 & 0.312345 & 0.156173 \tabularnewline
131 & 0.826906 & 0.346188 & 0.173094 \tabularnewline
132 & 0.873826 & 0.252347 & 0.126174 \tabularnewline
133 & 0.85356 & 0.29288 & 0.14644 \tabularnewline
134 & 0.830318 & 0.339364 & 0.169682 \tabularnewline
135 & 0.874881 & 0.250238 & 0.125119 \tabularnewline
136 & 0.861366 & 0.277269 & 0.138634 \tabularnewline
137 & 0.839409 & 0.321182 & 0.160591 \tabularnewline
138 & 0.825558 & 0.348883 & 0.174442 \tabularnewline
139 & 0.829643 & 0.340715 & 0.170357 \tabularnewline
140 & 0.805224 & 0.389552 & 0.194776 \tabularnewline
141 & 0.785971 & 0.428057 & 0.214029 \tabularnewline
142 & 0.759215 & 0.481569 & 0.240785 \tabularnewline
143 & 0.761815 & 0.47637 & 0.238185 \tabularnewline
144 & 0.742295 & 0.515411 & 0.257705 \tabularnewline
145 & 0.77472 & 0.450561 & 0.22528 \tabularnewline
146 & 0.794732 & 0.410536 & 0.205268 \tabularnewline
147 & 0.765647 & 0.468707 & 0.234353 \tabularnewline
148 & 0.734183 & 0.531634 & 0.265817 \tabularnewline
149 & 0.708036 & 0.583928 & 0.291964 \tabularnewline
150 & 0.673277 & 0.653445 & 0.326723 \tabularnewline
151 & 0.641745 & 0.71651 & 0.358255 \tabularnewline
152 & 0.620692 & 0.758616 & 0.379308 \tabularnewline
153 & 0.647808 & 0.704384 & 0.352192 \tabularnewline
154 & 0.611546 & 0.776908 & 0.388454 \tabularnewline
155 & 0.572693 & 0.854614 & 0.427307 \tabularnewline
156 & 0.550968 & 0.898064 & 0.449032 \tabularnewline
157 & 0.515804 & 0.968391 & 0.484196 \tabularnewline
158 & 0.480235 & 0.96047 & 0.519765 \tabularnewline
159 & 0.49428 & 0.988559 & 0.50572 \tabularnewline
160 & 0.459657 & 0.919315 & 0.540343 \tabularnewline
161 & 0.544758 & 0.910484 & 0.455242 \tabularnewline
162 & 0.543116 & 0.913767 & 0.456884 \tabularnewline
163 & 0.525883 & 0.948234 & 0.474117 \tabularnewline
164 & 0.494618 & 0.989237 & 0.505382 \tabularnewline
165 & 0.46543 & 0.930859 & 0.53457 \tabularnewline
166 & 0.425704 & 0.851407 & 0.574296 \tabularnewline
167 & 0.414968 & 0.829935 & 0.585032 \tabularnewline
168 & 0.383379 & 0.766758 & 0.616621 \tabularnewline
169 & 0.36329 & 0.72658 & 0.63671 \tabularnewline
170 & 0.394573 & 0.789146 & 0.605427 \tabularnewline
171 & 0.372133 & 0.744265 & 0.627867 \tabularnewline
172 & 0.345677 & 0.691355 & 0.654323 \tabularnewline
173 & 0.374622 & 0.749244 & 0.625378 \tabularnewline
174 & 0.470767 & 0.941534 & 0.529233 \tabularnewline
175 & 0.436344 & 0.872688 & 0.563656 \tabularnewline
176 & 0.412507 & 0.825014 & 0.587493 \tabularnewline
177 & 0.506533 & 0.986935 & 0.493467 \tabularnewline
178 & 0.473053 & 0.946106 & 0.526947 \tabularnewline
179 & 0.467402 & 0.934803 & 0.532598 \tabularnewline
180 & 0.435911 & 0.871821 & 0.564089 \tabularnewline
181 & 0.486858 & 0.973715 & 0.513142 \tabularnewline
182 & 0.578974 & 0.842051 & 0.421026 \tabularnewline
183 & 0.630003 & 0.739994 & 0.369997 \tabularnewline
184 & 0.719895 & 0.56021 & 0.280105 \tabularnewline
185 & 0.677294 & 0.645412 & 0.322706 \tabularnewline
186 & 0.631721 & 0.736558 & 0.368279 \tabularnewline
187 & 0.646645 & 0.706709 & 0.353355 \tabularnewline
188 & 0.90529 & 0.189421 & 0.0947103 \tabularnewline
189 & 0.886805 & 0.226389 & 0.113195 \tabularnewline
190 & 0.859547 & 0.280906 & 0.140453 \tabularnewline
191 & 0.850067 & 0.299865 & 0.149933 \tabularnewline
192 & 0.825742 & 0.348515 & 0.174258 \tabularnewline
193 & 0.793964 & 0.412072 & 0.206036 \tabularnewline
194 & 0.755336 & 0.489327 & 0.244664 \tabularnewline
195 & 0.713638 & 0.572724 & 0.286362 \tabularnewline
196 & 0.831986 & 0.336028 & 0.168014 \tabularnewline
197 & 0.814168 & 0.371664 & 0.185832 \tabularnewline
198 & 0.782485 & 0.435031 & 0.217515 \tabularnewline
199 & 0.817645 & 0.364711 & 0.182355 \tabularnewline
200 & 0.782188 & 0.435624 & 0.217812 \tabularnewline
201 & 0.758969 & 0.482063 & 0.241031 \tabularnewline
202 & 0.709371 & 0.581258 & 0.290629 \tabularnewline
203 & 0.6638 & 0.6724 & 0.3362 \tabularnewline
204 & 0.611961 & 0.776078 & 0.388039 \tabularnewline
205 & 0.5648 & 0.870401 & 0.4352 \tabularnewline
206 & 0.635387 & 0.729226 & 0.364613 \tabularnewline
207 & 0.597752 & 0.804496 & 0.402248 \tabularnewline
208 & 0.585653 & 0.828694 & 0.414347 \tabularnewline
209 & 0.678206 & 0.643588 & 0.321794 \tabularnewline
210 & 0.897852 & 0.204296 & 0.102148 \tabularnewline
211 & 0.862563 & 0.274874 & 0.137437 \tabularnewline
212 & 0.903356 & 0.193288 & 0.0966439 \tabularnewline
213 & 0.910127 & 0.179745 & 0.0898727 \tabularnewline
214 & 0.876967 & 0.246065 & 0.123033 \tabularnewline
215 & 0.902614 & 0.194771 & 0.0973857 \tabularnewline
216 & 0.861289 & 0.277422 & 0.138711 \tabularnewline
217 & 0.843346 & 0.313307 & 0.156654 \tabularnewline
218 & 0.78706 & 0.42588 & 0.21294 \tabularnewline
219 & 0.711913 & 0.576175 & 0.288087 \tabularnewline
220 & 0.636082 & 0.727836 & 0.363918 \tabularnewline
221 & 0.520388 & 0.959224 & 0.479612 \tabularnewline
222 & 0.782587 & 0.434826 & 0.217413 \tabularnewline
223 & 0.657364 & 0.685272 & 0.342636 \tabularnewline
224 & 0.530586 & 0.938827 & 0.469414 \tabularnewline
225 & 0.340567 & 0.681134 & 0.659433 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&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]0.182255[/C][C]0.364511[/C][C]0.817745[/C][/ROW]
[ROW][C]7[/C][C]0.440864[/C][C]0.881727[/C][C]0.559136[/C][/ROW]
[ROW][C]8[/C][C]0.346507[/C][C]0.693015[/C][C]0.653493[/C][/ROW]
[ROW][C]9[/C][C]0.351185[/C][C]0.702371[/C][C]0.648815[/C][/ROW]
[ROW][C]10[/C][C]0.249149[/C][C]0.498298[/C][C]0.750851[/C][/ROW]
[ROW][C]11[/C][C]0.254404[/C][C]0.508808[/C][C]0.745596[/C][/ROW]
[ROW][C]12[/C][C]0.175935[/C][C]0.35187[/C][C]0.824065[/C][/ROW]
[ROW][C]13[/C][C]0.245276[/C][C]0.490552[/C][C]0.754724[/C][/ROW]
[ROW][C]14[/C][C]0.181264[/C][C]0.362528[/C][C]0.818736[/C][/ROW]
[ROW][C]15[/C][C]0.127988[/C][C]0.255975[/C][C]0.872012[/C][/ROW]
[ROW][C]16[/C][C]0.102646[/C][C]0.205292[/C][C]0.897354[/C][/ROW]
[ROW][C]17[/C][C]0.0702706[/C][C]0.140541[/C][C]0.929729[/C][/ROW]
[ROW][C]18[/C][C]0.0958656[/C][C]0.191731[/C][C]0.904134[/C][/ROW]
[ROW][C]19[/C][C]0.066419[/C][C]0.132838[/C][C]0.933581[/C][/ROW]
[ROW][C]20[/C][C]0.0511911[/C][C]0.102382[/C][C]0.948809[/C][/ROW]
[ROW][C]21[/C][C]0.035039[/C][C]0.0700779[/C][C]0.964961[/C][/ROW]
[ROW][C]22[/C][C]0.0841578[/C][C]0.168316[/C][C]0.915842[/C][/ROW]
[ROW][C]23[/C][C]0.0619533[/C][C]0.123907[/C][C]0.938047[/C][/ROW]
[ROW][C]24[/C][C]0.0447606[/C][C]0.0895211[/C][C]0.955239[/C][/ROW]
[ROW][C]25[/C][C]0.102586[/C][C]0.205171[/C][C]0.897414[/C][/ROW]
[ROW][C]26[/C][C]0.0797079[/C][C]0.159416[/C][C]0.920292[/C][/ROW]
[ROW][C]27[/C][C]0.0702661[/C][C]0.140532[/C][C]0.929734[/C][/ROW]
[ROW][C]28[/C][C]0.0521835[/C][C]0.104367[/C][C]0.947817[/C][/ROW]
[ROW][C]29[/C][C]0.038868[/C][C]0.077736[/C][C]0.961132[/C][/ROW]
[ROW][C]30[/C][C]0.032627[/C][C]0.065254[/C][C]0.967373[/C][/ROW]
[ROW][C]31[/C][C]0.0228238[/C][C]0.0456476[/C][C]0.977176[/C][/ROW]
[ROW][C]32[/C][C]0.0179949[/C][C]0.0359898[/C][C]0.982005[/C][/ROW]
[ROW][C]33[/C][C]0.013991[/C][C]0.027982[/C][C]0.986009[/C][/ROW]
[ROW][C]34[/C][C]0.00943577[/C][C]0.0188715[/C][C]0.990564[/C][/ROW]
[ROW][C]35[/C][C]0.00689617[/C][C]0.0137923[/C][C]0.993104[/C][/ROW]
[ROW][C]36[/C][C]0.00464726[/C][C]0.00929452[/C][C]0.995353[/C][/ROW]
[ROW][C]37[/C][C]0.0031647[/C][C]0.0063294[/C][C]0.996835[/C][/ROW]
[ROW][C]38[/C][C]0.00237427[/C][C]0.00474855[/C][C]0.997626[/C][/ROW]
[ROW][C]39[/C][C]0.00233308[/C][C]0.00466616[/C][C]0.997667[/C][/ROW]
[ROW][C]40[/C][C]0.00168238[/C][C]0.00336477[/C][C]0.998318[/C][/ROW]
[ROW][C]41[/C][C]0.00194957[/C][C]0.00389915[/C][C]0.99805[/C][/ROW]
[ROW][C]42[/C][C]0.00162873[/C][C]0.00325746[/C][C]0.998371[/C][/ROW]
[ROW][C]43[/C][C]0.00117324[/C][C]0.00234648[/C][C]0.998827[/C][/ROW]
[ROW][C]44[/C][C]0.00230577[/C][C]0.00461155[/C][C]0.997694[/C][/ROW]
[ROW][C]45[/C][C]0.00209645[/C][C]0.00419289[/C][C]0.997904[/C][/ROW]
[ROW][C]46[/C][C]0.00233868[/C][C]0.00467737[/C][C]0.997661[/C][/ROW]
[ROW][C]47[/C][C]0.00169618[/C][C]0.00339236[/C][C]0.998304[/C][/ROW]
[ROW][C]48[/C][C]0.00114184[/C][C]0.00228367[/C][C]0.998858[/C][/ROW]
[ROW][C]49[/C][C]0.000820955[/C][C]0.00164191[/C][C]0.999179[/C][/ROW]
[ROW][C]50[/C][C]0.000553955[/C][C]0.00110791[/C][C]0.999446[/C][/ROW]
[ROW][C]51[/C][C]0.000508823[/C][C]0.00101765[/C][C]0.999491[/C][/ROW]
[ROW][C]52[/C][C]0.000442589[/C][C]0.000885177[/C][C]0.999557[/C][/ROW]
[ROW][C]53[/C][C]0.000726131[/C][C]0.00145226[/C][C]0.999274[/C][/ROW]
[ROW][C]54[/C][C]0.000531826[/C][C]0.00106365[/C][C]0.999468[/C][/ROW]
[ROW][C]55[/C][C]0.000366445[/C][C]0.000732891[/C][C]0.999634[/C][/ROW]
[ROW][C]56[/C][C]0.00389056[/C][C]0.00778113[/C][C]0.996109[/C][/ROW]
[ROW][C]57[/C][C]0.00319703[/C][C]0.00639407[/C][C]0.996803[/C][/ROW]
[ROW][C]58[/C][C]0.00239569[/C][C]0.00479138[/C][C]0.997604[/C][/ROW]
[ROW][C]59[/C][C]0.0101599[/C][C]0.0203197[/C][C]0.98984[/C][/ROW]
[ROW][C]60[/C][C]0.0109704[/C][C]0.0219408[/C][C]0.98903[/C][/ROW]
[ROW][C]61[/C][C]0.0108554[/C][C]0.0217107[/C][C]0.989145[/C][/ROW]
[ROW][C]62[/C][C]0.0097947[/C][C]0.0195894[/C][C]0.990205[/C][/ROW]
[ROW][C]63[/C][C]0.0209291[/C][C]0.0418581[/C][C]0.979071[/C][/ROW]
[ROW][C]64[/C][C]0.0175323[/C][C]0.0350647[/C][C]0.982468[/C][/ROW]
[ROW][C]65[/C][C]0.0778375[/C][C]0.155675[/C][C]0.922162[/C][/ROW]
[ROW][C]66[/C][C]0.0664041[/C][C]0.132808[/C][C]0.933596[/C][/ROW]
[ROW][C]67[/C][C]0.155988[/C][C]0.311976[/C][C]0.844012[/C][/ROW]
[ROW][C]68[/C][C]0.278575[/C][C]0.557149[/C][C]0.721425[/C][/ROW]
[ROW][C]69[/C][C]0.35755[/C][C]0.715099[/C][C]0.64245[/C][/ROW]
[ROW][C]70[/C][C]0.336761[/C][C]0.673522[/C][C]0.663239[/C][/ROW]
[ROW][C]71[/C][C]0.421139[/C][C]0.842279[/C][C]0.578861[/C][/ROW]
[ROW][C]72[/C][C]0.612617[/C][C]0.774765[/C][C]0.387383[/C][/ROW]
[ROW][C]73[/C][C]0.64808[/C][C]0.70384[/C][C]0.35192[/C][/ROW]
[ROW][C]74[/C][C]0.622764[/C][C]0.754473[/C][C]0.377236[/C][/ROW]
[ROW][C]75[/C][C]0.703239[/C][C]0.593521[/C][C]0.296761[/C][/ROW]
[ROW][C]76[/C][C]0.705117[/C][C]0.589766[/C][C]0.294883[/C][/ROW]
[ROW][C]77[/C][C]0.692481[/C][C]0.615038[/C][C]0.307519[/C][/ROW]
[ROW][C]78[/C][C]0.664982[/C][C]0.670036[/C][C]0.335018[/C][/ROW]
[ROW][C]79[/C][C]0.6838[/C][C]0.6324[/C][C]0.3162[/C][/ROW]
[ROW][C]80[/C][C]0.659054[/C][C]0.681892[/C][C]0.340946[/C][/ROW]
[ROW][C]81[/C][C]0.778052[/C][C]0.443896[/C][C]0.221948[/C][/ROW]
[ROW][C]82[/C][C]0.758253[/C][C]0.483494[/C][C]0.241747[/C][/ROW]
[ROW][C]83[/C][C]0.739452[/C][C]0.521095[/C][C]0.260548[/C][/ROW]
[ROW][C]84[/C][C]0.751855[/C][C]0.49629[/C][C]0.248145[/C][/ROW]
[ROW][C]85[/C][C]0.741632[/C][C]0.516737[/C][C]0.258368[/C][/ROW]
[ROW][C]86[/C][C]0.729258[/C][C]0.541484[/C][C]0.270742[/C][/ROW]
[ROW][C]87[/C][C]0.70085[/C][C]0.5983[/C][C]0.29915[/C][/ROW]
[ROW][C]88[/C][C]0.674189[/C][C]0.651622[/C][C]0.325811[/C][/ROW]
[ROW][C]89[/C][C]0.710537[/C][C]0.578927[/C][C]0.289463[/C][/ROW]
[ROW][C]90[/C][C]0.74079[/C][C]0.51842[/C][C]0.25921[/C][/ROW]
[ROW][C]91[/C][C]0.809014[/C][C]0.381971[/C][C]0.190986[/C][/ROW]
[ROW][C]92[/C][C]0.799689[/C][C]0.400622[/C][C]0.200311[/C][/ROW]
[ROW][C]93[/C][C]0.783365[/C][C]0.433269[/C][C]0.216635[/C][/ROW]
[ROW][C]94[/C][C]0.825757[/C][C]0.348486[/C][C]0.174243[/C][/ROW]
[ROW][C]95[/C][C]0.817662[/C][C]0.364676[/C][C]0.182338[/C][/ROW]
[ROW][C]96[/C][C]0.854516[/C][C]0.290968[/C][C]0.145484[/C][/ROW]
[ROW][C]97[/C][C]0.857576[/C][C]0.284848[/C][C]0.142424[/C][/ROW]
[ROW][C]98[/C][C]0.868073[/C][C]0.263853[/C][C]0.131927[/C][/ROW]
[ROW][C]99[/C][C]0.850317[/C][C]0.299366[/C][C]0.149683[/C][/ROW]
[ROW][C]100[/C][C]0.830988[/C][C]0.338024[/C][C]0.169012[/C][/ROW]
[ROW][C]101[/C][C]0.811738[/C][C]0.376524[/C][C]0.188262[/C][/ROW]
[ROW][C]102[/C][C]0.838019[/C][C]0.323961[/C][C]0.161981[/C][/ROW]
[ROW][C]103[/C][C]0.836565[/C][C]0.326871[/C][C]0.163435[/C][/ROW]
[ROW][C]104[/C][C]0.826919[/C][C]0.346162[/C][C]0.173081[/C][/ROW]
[ROW][C]105[/C][C]0.851404[/C][C]0.297193[/C][C]0.148596[/C][/ROW]
[ROW][C]106[/C][C]0.856024[/C][C]0.287951[/C][C]0.143976[/C][/ROW]
[ROW][C]107[/C][C]0.836795[/C][C]0.32641[/C][C]0.163205[/C][/ROW]
[ROW][C]108[/C][C]0.814429[/C][C]0.371142[/C][C]0.185571[/C][/ROW]
[ROW][C]109[/C][C]0.846435[/C][C]0.30713[/C][C]0.153565[/C][/ROW]
[ROW][C]110[/C][C]0.838749[/C][C]0.322502[/C][C]0.161251[/C][/ROW]
[ROW][C]111[/C][C]0.816328[/C][C]0.367344[/C][C]0.183672[/C][/ROW]
[ROW][C]112[/C][C]0.797678[/C][C]0.404643[/C][C]0.202322[/C][/ROW]
[ROW][C]113[/C][C]0.832732[/C][C]0.334536[/C][C]0.167268[/C][/ROW]
[ROW][C]114[/C][C]0.824804[/C][C]0.350392[/C][C]0.175196[/C][/ROW]
[ROW][C]115[/C][C]0.826557[/C][C]0.346886[/C][C]0.173443[/C][/ROW]
[ROW][C]116[/C][C]0.811879[/C][C]0.376242[/C][C]0.188121[/C][/ROW]
[ROW][C]117[/C][C]0.852659[/C][C]0.294682[/C][C]0.147341[/C][/ROW]
[ROW][C]118[/C][C]0.845344[/C][C]0.309311[/C][C]0.154656[/C][/ROW]
[ROW][C]119[/C][C]0.882771[/C][C]0.234458[/C][C]0.117229[/C][/ROW]
[ROW][C]120[/C][C]0.868817[/C][C]0.262366[/C][C]0.131183[/C][/ROW]
[ROW][C]121[/C][C]0.849611[/C][C]0.300778[/C][C]0.150389[/C][/ROW]
[ROW][C]122[/C][C]0.839239[/C][C]0.321522[/C][C]0.160761[/C][/ROW]
[ROW][C]123[/C][C]0.830134[/C][C]0.339732[/C][C]0.169866[/C][/ROW]
[ROW][C]124[/C][C]0.848627[/C][C]0.302746[/C][C]0.151373[/C][/ROW]
[ROW][C]125[/C][C]0.829171[/C][C]0.341658[/C][C]0.170829[/C][/ROW]
[ROW][C]126[/C][C]0.808172[/C][C]0.383656[/C][C]0.191828[/C][/ROW]
[ROW][C]127[/C][C]0.786526[/C][C]0.426948[/C][C]0.213474[/C][/ROW]
[ROW][C]128[/C][C]0.811297[/C][C]0.377405[/C][C]0.188703[/C][/ROW]
[ROW][C]129[/C][C]0.785801[/C][C]0.428397[/C][C]0.214199[/C][/ROW]
[ROW][C]130[/C][C]0.843827[/C][C]0.312345[/C][C]0.156173[/C][/ROW]
[ROW][C]131[/C][C]0.826906[/C][C]0.346188[/C][C]0.173094[/C][/ROW]
[ROW][C]132[/C][C]0.873826[/C][C]0.252347[/C][C]0.126174[/C][/ROW]
[ROW][C]133[/C][C]0.85356[/C][C]0.29288[/C][C]0.14644[/C][/ROW]
[ROW][C]134[/C][C]0.830318[/C][C]0.339364[/C][C]0.169682[/C][/ROW]
[ROW][C]135[/C][C]0.874881[/C][C]0.250238[/C][C]0.125119[/C][/ROW]
[ROW][C]136[/C][C]0.861366[/C][C]0.277269[/C][C]0.138634[/C][/ROW]
[ROW][C]137[/C][C]0.839409[/C][C]0.321182[/C][C]0.160591[/C][/ROW]
[ROW][C]138[/C][C]0.825558[/C][C]0.348883[/C][C]0.174442[/C][/ROW]
[ROW][C]139[/C][C]0.829643[/C][C]0.340715[/C][C]0.170357[/C][/ROW]
[ROW][C]140[/C][C]0.805224[/C][C]0.389552[/C][C]0.194776[/C][/ROW]
[ROW][C]141[/C][C]0.785971[/C][C]0.428057[/C][C]0.214029[/C][/ROW]
[ROW][C]142[/C][C]0.759215[/C][C]0.481569[/C][C]0.240785[/C][/ROW]
[ROW][C]143[/C][C]0.761815[/C][C]0.47637[/C][C]0.238185[/C][/ROW]
[ROW][C]144[/C][C]0.742295[/C][C]0.515411[/C][C]0.257705[/C][/ROW]
[ROW][C]145[/C][C]0.77472[/C][C]0.450561[/C][C]0.22528[/C][/ROW]
[ROW][C]146[/C][C]0.794732[/C][C]0.410536[/C][C]0.205268[/C][/ROW]
[ROW][C]147[/C][C]0.765647[/C][C]0.468707[/C][C]0.234353[/C][/ROW]
[ROW][C]148[/C][C]0.734183[/C][C]0.531634[/C][C]0.265817[/C][/ROW]
[ROW][C]149[/C][C]0.708036[/C][C]0.583928[/C][C]0.291964[/C][/ROW]
[ROW][C]150[/C][C]0.673277[/C][C]0.653445[/C][C]0.326723[/C][/ROW]
[ROW][C]151[/C][C]0.641745[/C][C]0.71651[/C][C]0.358255[/C][/ROW]
[ROW][C]152[/C][C]0.620692[/C][C]0.758616[/C][C]0.379308[/C][/ROW]
[ROW][C]153[/C][C]0.647808[/C][C]0.704384[/C][C]0.352192[/C][/ROW]
[ROW][C]154[/C][C]0.611546[/C][C]0.776908[/C][C]0.388454[/C][/ROW]
[ROW][C]155[/C][C]0.572693[/C][C]0.854614[/C][C]0.427307[/C][/ROW]
[ROW][C]156[/C][C]0.550968[/C][C]0.898064[/C][C]0.449032[/C][/ROW]
[ROW][C]157[/C][C]0.515804[/C][C]0.968391[/C][C]0.484196[/C][/ROW]
[ROW][C]158[/C][C]0.480235[/C][C]0.96047[/C][C]0.519765[/C][/ROW]
[ROW][C]159[/C][C]0.49428[/C][C]0.988559[/C][C]0.50572[/C][/ROW]
[ROW][C]160[/C][C]0.459657[/C][C]0.919315[/C][C]0.540343[/C][/ROW]
[ROW][C]161[/C][C]0.544758[/C][C]0.910484[/C][C]0.455242[/C][/ROW]
[ROW][C]162[/C][C]0.543116[/C][C]0.913767[/C][C]0.456884[/C][/ROW]
[ROW][C]163[/C][C]0.525883[/C][C]0.948234[/C][C]0.474117[/C][/ROW]
[ROW][C]164[/C][C]0.494618[/C][C]0.989237[/C][C]0.505382[/C][/ROW]
[ROW][C]165[/C][C]0.46543[/C][C]0.930859[/C][C]0.53457[/C][/ROW]
[ROW][C]166[/C][C]0.425704[/C][C]0.851407[/C][C]0.574296[/C][/ROW]
[ROW][C]167[/C][C]0.414968[/C][C]0.829935[/C][C]0.585032[/C][/ROW]
[ROW][C]168[/C][C]0.383379[/C][C]0.766758[/C][C]0.616621[/C][/ROW]
[ROW][C]169[/C][C]0.36329[/C][C]0.72658[/C][C]0.63671[/C][/ROW]
[ROW][C]170[/C][C]0.394573[/C][C]0.789146[/C][C]0.605427[/C][/ROW]
[ROW][C]171[/C][C]0.372133[/C][C]0.744265[/C][C]0.627867[/C][/ROW]
[ROW][C]172[/C][C]0.345677[/C][C]0.691355[/C][C]0.654323[/C][/ROW]
[ROW][C]173[/C][C]0.374622[/C][C]0.749244[/C][C]0.625378[/C][/ROW]
[ROW][C]174[/C][C]0.470767[/C][C]0.941534[/C][C]0.529233[/C][/ROW]
[ROW][C]175[/C][C]0.436344[/C][C]0.872688[/C][C]0.563656[/C][/ROW]
[ROW][C]176[/C][C]0.412507[/C][C]0.825014[/C][C]0.587493[/C][/ROW]
[ROW][C]177[/C][C]0.506533[/C][C]0.986935[/C][C]0.493467[/C][/ROW]
[ROW][C]178[/C][C]0.473053[/C][C]0.946106[/C][C]0.526947[/C][/ROW]
[ROW][C]179[/C][C]0.467402[/C][C]0.934803[/C][C]0.532598[/C][/ROW]
[ROW][C]180[/C][C]0.435911[/C][C]0.871821[/C][C]0.564089[/C][/ROW]
[ROW][C]181[/C][C]0.486858[/C][C]0.973715[/C][C]0.513142[/C][/ROW]
[ROW][C]182[/C][C]0.578974[/C][C]0.842051[/C][C]0.421026[/C][/ROW]
[ROW][C]183[/C][C]0.630003[/C][C]0.739994[/C][C]0.369997[/C][/ROW]
[ROW][C]184[/C][C]0.719895[/C][C]0.56021[/C][C]0.280105[/C][/ROW]
[ROW][C]185[/C][C]0.677294[/C][C]0.645412[/C][C]0.322706[/C][/ROW]
[ROW][C]186[/C][C]0.631721[/C][C]0.736558[/C][C]0.368279[/C][/ROW]
[ROW][C]187[/C][C]0.646645[/C][C]0.706709[/C][C]0.353355[/C][/ROW]
[ROW][C]188[/C][C]0.90529[/C][C]0.189421[/C][C]0.0947103[/C][/ROW]
[ROW][C]189[/C][C]0.886805[/C][C]0.226389[/C][C]0.113195[/C][/ROW]
[ROW][C]190[/C][C]0.859547[/C][C]0.280906[/C][C]0.140453[/C][/ROW]
[ROW][C]191[/C][C]0.850067[/C][C]0.299865[/C][C]0.149933[/C][/ROW]
[ROW][C]192[/C][C]0.825742[/C][C]0.348515[/C][C]0.174258[/C][/ROW]
[ROW][C]193[/C][C]0.793964[/C][C]0.412072[/C][C]0.206036[/C][/ROW]
[ROW][C]194[/C][C]0.755336[/C][C]0.489327[/C][C]0.244664[/C][/ROW]
[ROW][C]195[/C][C]0.713638[/C][C]0.572724[/C][C]0.286362[/C][/ROW]
[ROW][C]196[/C][C]0.831986[/C][C]0.336028[/C][C]0.168014[/C][/ROW]
[ROW][C]197[/C][C]0.814168[/C][C]0.371664[/C][C]0.185832[/C][/ROW]
[ROW][C]198[/C][C]0.782485[/C][C]0.435031[/C][C]0.217515[/C][/ROW]
[ROW][C]199[/C][C]0.817645[/C][C]0.364711[/C][C]0.182355[/C][/ROW]
[ROW][C]200[/C][C]0.782188[/C][C]0.435624[/C][C]0.217812[/C][/ROW]
[ROW][C]201[/C][C]0.758969[/C][C]0.482063[/C][C]0.241031[/C][/ROW]
[ROW][C]202[/C][C]0.709371[/C][C]0.581258[/C][C]0.290629[/C][/ROW]
[ROW][C]203[/C][C]0.6638[/C][C]0.6724[/C][C]0.3362[/C][/ROW]
[ROW][C]204[/C][C]0.611961[/C][C]0.776078[/C][C]0.388039[/C][/ROW]
[ROW][C]205[/C][C]0.5648[/C][C]0.870401[/C][C]0.4352[/C][/ROW]
[ROW][C]206[/C][C]0.635387[/C][C]0.729226[/C][C]0.364613[/C][/ROW]
[ROW][C]207[/C][C]0.597752[/C][C]0.804496[/C][C]0.402248[/C][/ROW]
[ROW][C]208[/C][C]0.585653[/C][C]0.828694[/C][C]0.414347[/C][/ROW]
[ROW][C]209[/C][C]0.678206[/C][C]0.643588[/C][C]0.321794[/C][/ROW]
[ROW][C]210[/C][C]0.897852[/C][C]0.204296[/C][C]0.102148[/C][/ROW]
[ROW][C]211[/C][C]0.862563[/C][C]0.274874[/C][C]0.137437[/C][/ROW]
[ROW][C]212[/C][C]0.903356[/C][C]0.193288[/C][C]0.0966439[/C][/ROW]
[ROW][C]213[/C][C]0.910127[/C][C]0.179745[/C][C]0.0898727[/C][/ROW]
[ROW][C]214[/C][C]0.876967[/C][C]0.246065[/C][C]0.123033[/C][/ROW]
[ROW][C]215[/C][C]0.902614[/C][C]0.194771[/C][C]0.0973857[/C][/ROW]
[ROW][C]216[/C][C]0.861289[/C][C]0.277422[/C][C]0.138711[/C][/ROW]
[ROW][C]217[/C][C]0.843346[/C][C]0.313307[/C][C]0.156654[/C][/ROW]
[ROW][C]218[/C][C]0.78706[/C][C]0.42588[/C][C]0.21294[/C][/ROW]
[ROW][C]219[/C][C]0.711913[/C][C]0.576175[/C][C]0.288087[/C][/ROW]
[ROW][C]220[/C][C]0.636082[/C][C]0.727836[/C][C]0.363918[/C][/ROW]
[ROW][C]221[/C][C]0.520388[/C][C]0.959224[/C][C]0.479612[/C][/ROW]
[ROW][C]222[/C][C]0.782587[/C][C]0.434826[/C][C]0.217413[/C][/ROW]
[ROW][C]223[/C][C]0.657364[/C][C]0.685272[/C][C]0.342636[/C][/ROW]
[ROW][C]224[/C][C]0.530586[/C][C]0.938827[/C][C]0.469414[/C][/ROW]
[ROW][C]225[/C][C]0.340567[/C][C]0.681134[/C][C]0.659433[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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
60.1822550.3645110.817745
70.4408640.8817270.559136
80.3465070.6930150.653493
90.3511850.7023710.648815
100.2491490.4982980.750851
110.2544040.5088080.745596
120.1759350.351870.824065
130.2452760.4905520.754724
140.1812640.3625280.818736
150.1279880.2559750.872012
160.1026460.2052920.897354
170.07027060.1405410.929729
180.09586560.1917310.904134
190.0664190.1328380.933581
200.05119110.1023820.948809
210.0350390.07007790.964961
220.08415780.1683160.915842
230.06195330.1239070.938047
240.04476060.08952110.955239
250.1025860.2051710.897414
260.07970790.1594160.920292
270.07026610.1405320.929734
280.05218350.1043670.947817
290.0388680.0777360.961132
300.0326270.0652540.967373
310.02282380.04564760.977176
320.01799490.03598980.982005
330.0139910.0279820.986009
340.009435770.01887150.990564
350.006896170.01379230.993104
360.004647260.009294520.995353
370.00316470.00632940.996835
380.002374270.004748550.997626
390.002333080.004666160.997667
400.001682380.003364770.998318
410.001949570.003899150.99805
420.001628730.003257460.998371
430.001173240.002346480.998827
440.002305770.004611550.997694
450.002096450.004192890.997904
460.002338680.004677370.997661
470.001696180.003392360.998304
480.001141840.002283670.998858
490.0008209550.001641910.999179
500.0005539550.001107910.999446
510.0005088230.001017650.999491
520.0004425890.0008851770.999557
530.0007261310.001452260.999274
540.0005318260.001063650.999468
550.0003664450.0007328910.999634
560.003890560.007781130.996109
570.003197030.006394070.996803
580.002395690.004791380.997604
590.01015990.02031970.98984
600.01097040.02194080.98903
610.01085540.02171070.989145
620.00979470.01958940.990205
630.02092910.04185810.979071
640.01753230.03506470.982468
650.07783750.1556750.922162
660.06640410.1328080.933596
670.1559880.3119760.844012
680.2785750.5571490.721425
690.357550.7150990.64245
700.3367610.6735220.663239
710.4211390.8422790.578861
720.6126170.7747650.387383
730.648080.703840.35192
740.6227640.7544730.377236
750.7032390.5935210.296761
760.7051170.5897660.294883
770.6924810.6150380.307519
780.6649820.6700360.335018
790.68380.63240.3162
800.6590540.6818920.340946
810.7780520.4438960.221948
820.7582530.4834940.241747
830.7394520.5210950.260548
840.7518550.496290.248145
850.7416320.5167370.258368
860.7292580.5414840.270742
870.700850.59830.29915
880.6741890.6516220.325811
890.7105370.5789270.289463
900.740790.518420.25921
910.8090140.3819710.190986
920.7996890.4006220.200311
930.7833650.4332690.216635
940.8257570.3484860.174243
950.8176620.3646760.182338
960.8545160.2909680.145484
970.8575760.2848480.142424
980.8680730.2638530.131927
990.8503170.2993660.149683
1000.8309880.3380240.169012
1010.8117380.3765240.188262
1020.8380190.3239610.161981
1030.8365650.3268710.163435
1040.8269190.3461620.173081
1050.8514040.2971930.148596
1060.8560240.2879510.143976
1070.8367950.326410.163205
1080.8144290.3711420.185571
1090.8464350.307130.153565
1100.8387490.3225020.161251
1110.8163280.3673440.183672
1120.7976780.4046430.202322
1130.8327320.3345360.167268
1140.8248040.3503920.175196
1150.8265570.3468860.173443
1160.8118790.3762420.188121
1170.8526590.2946820.147341
1180.8453440.3093110.154656
1190.8827710.2344580.117229
1200.8688170.2623660.131183
1210.8496110.3007780.150389
1220.8392390.3215220.160761
1230.8301340.3397320.169866
1240.8486270.3027460.151373
1250.8291710.3416580.170829
1260.8081720.3836560.191828
1270.7865260.4269480.213474
1280.8112970.3774050.188703
1290.7858010.4283970.214199
1300.8438270.3123450.156173
1310.8269060.3461880.173094
1320.8738260.2523470.126174
1330.853560.292880.14644
1340.8303180.3393640.169682
1350.8748810.2502380.125119
1360.8613660.2772690.138634
1370.8394090.3211820.160591
1380.8255580.3488830.174442
1390.8296430.3407150.170357
1400.8052240.3895520.194776
1410.7859710.4280570.214029
1420.7592150.4815690.240785
1430.7618150.476370.238185
1440.7422950.5154110.257705
1450.774720.4505610.22528
1460.7947320.4105360.205268
1470.7656470.4687070.234353
1480.7341830.5316340.265817
1490.7080360.5839280.291964
1500.6732770.6534450.326723
1510.6417450.716510.358255
1520.6206920.7586160.379308
1530.6478080.7043840.352192
1540.6115460.7769080.388454
1550.5726930.8546140.427307
1560.5509680.8980640.449032
1570.5158040.9683910.484196
1580.4802350.960470.519765
1590.494280.9885590.50572
1600.4596570.9193150.540343
1610.5447580.9104840.455242
1620.5431160.9137670.456884
1630.5258830.9482340.474117
1640.4946180.9892370.505382
1650.465430.9308590.53457
1660.4257040.8514070.574296
1670.4149680.8299350.585032
1680.3833790.7667580.616621
1690.363290.726580.63671
1700.3945730.7891460.605427
1710.3721330.7442650.627867
1720.3456770.6913550.654323
1730.3746220.7492440.625378
1740.4707670.9415340.529233
1750.4363440.8726880.563656
1760.4125070.8250140.587493
1770.5065330.9869350.493467
1780.4730530.9461060.526947
1790.4674020.9348030.532598
1800.4359110.8718210.564089
1810.4868580.9737150.513142
1820.5789740.8420510.421026
1830.6300030.7399940.369997
1840.7198950.560210.280105
1850.6772940.6454120.322706
1860.6317210.7365580.368279
1870.6466450.7067090.353355
1880.905290.1894210.0947103
1890.8868050.2263890.113195
1900.8595470.2809060.140453
1910.8500670.2998650.149933
1920.8257420.3485150.174258
1930.7939640.4120720.206036
1940.7553360.4893270.244664
1950.7136380.5727240.286362
1960.8319860.3360280.168014
1970.8141680.3716640.185832
1980.7824850.4350310.217515
1990.8176450.3647110.182355
2000.7821880.4356240.217812
2010.7589690.4820630.241031
2020.7093710.5812580.290629
2030.66380.67240.3362
2040.6119610.7760780.388039
2050.56480.8704010.4352
2060.6353870.7292260.364613
2070.5977520.8044960.402248
2080.5856530.8286940.414347
2090.6782060.6435880.321794
2100.8978520.2042960.102148
2110.8625630.2748740.137437
2120.9033560.1932880.0966439
2130.9101270.1797450.0898727
2140.8769670.2460650.123033
2150.9026140.1947710.0973857
2160.8612890.2774220.138711
2170.8433460.3133070.156654
2180.787060.425880.21294
2190.7119130.5761750.288087
2200.6360820.7278360.363918
2210.5203880.9592240.479612
2220.7825870.4348260.217413
2230.6573640.6852720.342636
2240.5305860.9388270.469414
2250.3405670.6811340.659433






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level230.104545NOK
5% type I error level340.154545NOK
10% type I error level380.172727NOK

\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 & 0.104545 & NOK \tabularnewline
5% type I error level & 34 & 0.154545 & NOK \tabularnewline
10% type I error level & 38 & 0.172727 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=271035&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]0.104545[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]34[/C][C]0.154545[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]38[/C][C]0.172727[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=271035&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=271035&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 level230.104545NOK
5% type I error level340.154545NOK
10% type I error level380.172727NOK


Figures (Output of Computation)

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

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