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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 17:02:27 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418663114qm2t7wo6ltbej0e.htm/, Retrieved Thu, 16 May 2024 09:05:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268766, Retrieved Thu, 16 May 2024 09:05:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact66

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Paper MRA] [2014-11-29 15:48:00] [7d20b8d2dd16558b2d15f4ba20e18f40]
-   PD    [Multiple Regression] [regress] [2014-12-15 17:02:27] [e4db4bcf90ba40d5f3241c8a74ac70a7] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 26 50 3
12.2 57 62 3
12.8 37 54 3
7.4 67 71 3
6.7 43 54 3
12.6 52 65 7
14.8 52 73 6
13.3 43 52 6
11.1 84 84 3
8.2 67 42 3
11.4 49 66 4
6.4 70 65 3
10.6 52 78 6
12 58 73 3
6.3 68 75 3
11.3 62 72 9
11.9 43 66 3
9.3 56 70 3
9.6 56 61 4
10 74 81 5
6.4 65 71 3
13.8 63 69 5
10.8 58 71 3
13.8 57 72 3
11.7 63 68 5
10.9 53 70 3
16.1 57 68 4
13.4 51 61 7
9.9 64 67 3
11.5 53 76 3
8.3 29 70 3
11.7 54 60 6
9 58 72 3
9.7 43 69 4
10.8 51 71 6
10.3 53 62 3
10.4 54 70 3
12.7 56 64 7
9.3 61 58 5
11.8 47 76 3
5.9 39 52 3
11.4 48 59 3
13 50 68 3
10.8 35 76 3
12.3 30 65 4
11.3 68 67 3
11.8 49 59 3
7.9 61 69 3
12.7 67 76 3
12.3 47 63 3
11.6 56 75 3
6.7 50 63 6
10.9 43 60 3
12.1 67 73 3
13.3 62 63 3
10.1 57 70 3
5.7 41 75 5
14.3 54 66 9
8 45 63 3
13.3 48 63 3
9.3 61 64 3
12.5 56 70 3
7.6 41 75 9
15.9 43 61 3
9.2 53 60 5
9.1 44 62 7
11.1 66 73 3
13 58 61 3
14.5 46 66 3
12.2 37 64 3
12.3 51 59 6
11.4 51 64 3
8.8 56 60 6
14.6 66 56 3
12.6 37 78 3
13 42 67 3
12.6 38 59 4
13.2 66 66 3
9.9 34 68 3
7.7 53 71 3
10.5 49 66 3
13.4 55 73 3
10.9 49 72 3
4.3 59 71 4
10.3 40 59 8
11.8 58 64 5
11.2 60 66 3
11.4 63 78 3
8.6 56 68 5
13.2 54 73 3
12.6 52 62 6
5.6 34 65 7
9.9 69 68 5
8.8 32 65 11
7.7 48 60 4
9 67 71 3
7.3 58 65 5
11.4 57 68 7
13.6 42 64 3
7.9 64 74 3
10.7 58 69 3
10.3 66 76 3
8.3 26 68 4
9.6 61 72 3
14.2 52 67 3
8.5 51 63 5
13.5 55 59 5
4.9 50 73 3
6.4 60 66 4
9.6 56 62 3
11.6 63 69 3
11.1 61 66 3
4.35 52 51 4
12.7 16 56 3
18.1 46 67 6
17.85 56 69 3
16.6 52 57 3
12.6 55 56 12
17.1 50 55 3
19.1 59 63 3
16.1 60 67 4
13.35 52 65 3
18.4 44 47 4
14.7 67 76 3
10.6 52 64 3
12.6 55 68 3
16.2 37 64 3
13.6 54 65 3
18.9 72 71 3
14.1 51 63 4
14.5 48 60 9
16.15 60 68 5
14.75 50 72 3
14.8 63 70 3
12.45 33 61 3
12.65 67 61 3
17.35 46 62 3
8.6 54 71 3
18.4 59 71 5
16.1 61 51 7
11.6 33 56 18
17.75 47 70 3
15.25 69 73 6
17.65 52 76 4
16.35 55 68 3
17.65 41 48 5
13.6 73 52 3
14.35 52 60 3
14.75 50 59 3
18.25 51 57 6
9.9 60 79 3
16 56 60 3
18.25 56 60 4
16.85 29 59 3
14.6 66 62 3
13.85 66 59 4
18.95 73 61 3
15.6 55 71 3
14.85 64 57 4
11.75 40 66 3
18.45 46 63 4
15.9 58 69 3
17.1 43 58 3
16.1 61 59 3
19.9 51 48 6
10.95 50 66 14
18.45 52 73 4
15.1 54 67 4
15 66 61 3
11.35 61 68 6
15.95 80 75 3
18.1 51 62 8
14.6 56 69 4
15.4 56 58 6
15.4 56 60 6
17.6 53 74 4
13.35 47 55 5
19.1 25 62 3
15.35 47 63 3
7.6 46 69 7
13.4 50 58 7
13.9 39 58 4
19.1 51 68 3
15.25 58 72 3
12.9 35 62 11
16.1 58 62 5
17.35 60 65 4
13.15 62 69 5
12.15 63 66 4
12.6 53 72 4
10.35 46 62 3
15.4 67 75 5
9.6 59 58 3
18.2 64 66 3
13.6 38 55 3
14.85 50 47 11
14.75 48 72 3
14.1 48 62 7
14.9 47 64 3
16.25 66 64 3
19.25 47 19 21
13.6 63 50 3
13.6 58 68 3
15.65 44 70 3
12.75 51 79 3
14.6 43 69 3
9.85 55 71 3
12.65 38 48 9
19.2 45 73 3
16.6 50 74 3
11.2 54 66 4
15.25 57 71 3
11.9 60 74 3
13.2 55 78 3
16.35 56 75 3
12.4 49 53 6
15.85 37 60 5
18.15 59 70 3
11.15 46 69 6
15.65 51 65 3
17.75 58 78 3
7.65 64 78 9
12.35 53 59 3
15.6 48 72 5
19.3 51 70 4
15.2 47 63 13
17.1 59 63 3
15.6 62 71 4
18.4 62 74 3
19.05 51 67 4
18.55 64 66 4
19.1 52 62 5
13.1 67 80 3
12.85 50 73 3
9.5 54 67 3
4.5 58 61 4
11.85 56 73 6
13.6 63 74 5
11.7 31 32 3
12.4 65 69 4
13.35 71 69 3
11.4 50 84 3
14.9 57 64 3
19.9 47 58 10
11.2 47 59 5
14.6 57 78 3
17.6 43 57 3
14.05 41 60 10
16.1 63 68 3
13.35 63 68 3
11.85 56 73 3
11.95 51 69 3
14.75 50 67 4
15.15 22 60 13
13.2 41 65 12
16.85 59 66 3
7.85 56 74 3
7.7 66 81 6
12.6 53 72 6
7.85 42 55 3
10.95 52 49 11
12.35 54 74 3
9.95 44 53 12
14.9 62 64 9
16.65 53 65 3
13.4 50 57 3
13.95 36 51 3
15.7 76 80 3
16.85 66 67 3
10.95 62 70 4
15.35 59 74 3
12.2 47 75 3
15.1 55 70 4
17.75 58 69 3
15.2 60 65 3
14.6 44 55 4
16.65 57 71 6
8.1 45 65 8

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&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]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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 time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 16.0741 + 0.0200784AMS.I[t] -0.0605709AMS.E[t] -0.0445209AMS.A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  16.0741 +  0.0200784AMS.I[t] -0.0605709AMS.E[t] -0.0445209AMS.A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  16.0741 +  0.0200784AMS.I[t] -0.0605709AMS.E[t] -0.0445209AMS.A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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] = + 16.0741 + 0.0200784AMS.I[t] -0.0605709AMS.E[t] -0.0445209AMS.A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)16.07412.003098.0253.00059e-141.50029e-14
AMS.I0.02007840.02120570.94680.3445530.172277
AMS.E-0.06057090.0277109-2.1860.02967570.0148379
AMS.A-0.04452090.0863394-0.51560.6065150.303257

\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) & 16.0741 & 2.00309 & 8.025 & 3.00059e-14 & 1.50029e-14 \tabularnewline
AMS.I & 0.0200784 & 0.0212057 & 0.9468 & 0.344553 & 0.172277 \tabularnewline
AMS.E & -0.0605709 & 0.0277109 & -2.186 & 0.0296757 & 0.0148379 \tabularnewline
AMS.A & -0.0445209 & 0.0863394 & -0.5156 & 0.606515 & 0.303257 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&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]16.0741[/C][C]2.00309[/C][C]8.025[/C][C]3.00059e-14[/C][C]1.50029e-14[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0200784[/C][C]0.0212057[/C][C]0.9468[/C][C]0.344553[/C][C]0.172277[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0605709[/C][C]0.0277109[/C][C]-2.186[/C][C]0.0296757[/C][C]0.0148379[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0445209[/C][C]0.0863394[/C][C]-0.5156[/C][C]0.606515[/C][C]0.303257[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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)16.07412.003098.0253.00059e-141.50029e-14
AMS.I0.02007840.02120570.94680.3445530.172277
AMS.E-0.06057090.0277109-2.1860.02967570.0148379
AMS.A-0.04452090.0863394-0.51560.6065150.303257






Multiple Linear Regression - Regression Statistics
Multiple R0.132174
R-squared0.0174699
Adjusted R-squared0.00671225
F-TEST (value)1.62395
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value0.184064
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38295
Sum Squared Residuals3135.75

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.132174 \tabularnewline
R-squared & 0.0174699 \tabularnewline
Adjusted R-squared & 0.00671225 \tabularnewline
F-TEST (value) & 1.62395 \tabularnewline
F-TEST (DF numerator) & 3 \tabularnewline
F-TEST (DF denominator) & 274 \tabularnewline
p-value & 0.184064 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.38295 \tabularnewline
Sum Squared Residuals & 3135.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.132174[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0174699[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.00671225[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]1.62395[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]3[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]274[/C][/ROW]
[ROW][C]p-value[/C][C]0.184064[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.38295[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]3135.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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 R0.132174
R-squared0.0174699
Adjusted R-squared0.00671225
F-TEST (value)1.62395
F-TEST (DF numerator)3
F-TEST (DF denominator)274
p-value0.184064
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.38295
Sum Squared Residuals3135.75






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.4341-0.534073
212.213.3297-1.12965
312.813.4127-0.612652
47.412.9853-5.5853
56.713.5331-6.83312
612.612.8695-0.269465
714.812.42942.37058
813.313.5207-0.220702
911.112.5392-1.43921
108.214.7419-6.54186
1111.412.8822-1.48222
126.413.409-7.00896
1310.612.1266-1.52656
141212.6835-0.683452
156.312.7631-6.46309
1611.312.5572-1.25721
1711.912.8063-0.906272
189.312.825-3.52501
199.613.3256-3.72563
201012.4311-2.4311
216.412.9451-6.54514
2213.812.93710.862914
2310.812.8046-2.00459
2413.812.72391.07606
2511.712.9977-1.29766
2610.912.7648-1.86477
2716.112.92173.17829
2813.413.09170.30833
299.913.1673-3.26735
3011.512.4013-0.901347
318.312.2829-3.98289
3211.713.257-1.557
33912.744-3.74402
349.712.58-2.88004
3510.812.5305-1.73048
3610.313.2493-2.94934
3710.412.7849-2.38485
3812.713.0103-0.31035
399.313.5632-4.26321
4011.812.2809-0.480876
415.913.574-7.67395
4211.413.3307-1.93066
431312.82570.174321
4410.812.0399-1.23993
4512.312.5613-0.261302
4611.313.2477-1.94766
4711.813.3507-1.55074
487.912.986-5.08597
4912.712.68240.0175548
5012.313.0683-0.768298
5111.612.5222-0.922153
526.712.995-6.29497
5310.913.1697-2.2697
5412.112.8642-0.764158
5513.313.3695-0.069475
5610.112.8451-2.74509
575.712.1319-6.43193
5814.312.761.53999
59813.0281-5.02814
6013.313.08840.211623
619.313.2888-3.98883
6212.512.825-0.325008
637.611.9539-4.35385
6415.913.10912.79087
659.213.2814-4.08144
669.112.8906-3.79055
6711.112.8441-1.74408
681313.4103-0.410303
6914.512.86651.63349
7012.212.8069-0.606943
7112.313.2573-0.957333
7211.413.088-1.68804
738.813.2972-4.49715
7414.613.87380.726215
7512.611.95890.64105
761312.72560.274378
7712.613.0854-0.485355
7813.213.2681-0.068076
799.912.5044-2.60442
807.712.7042-5.0042
8110.512.9267-2.42674
8213.412.62320.776783
8310.912.5633-1.66332
844.312.7802-8.48015
8510.312.9474-2.64743
8611.813.1395-1.33955
8711.213.1476-1.94761
8811.412.481-1.08099
898.612.8571-4.25711
9013.212.60310.596862
9112.613.0957-0.495699
925.612.5081-6.90805
939.913.1181-3.21813
948.812.2898-3.48981
957.713.2256-5.52557
96912.9853-3.9853
977.313.079-5.77898
9811.412.7881-1.38814
9913.612.90730.692665
1007.912.7434-4.84335
10110.712.9257-2.22574
10210.312.6624-2.36237
1038.312.2993-3.99928
1049.612.8043-3.20426
10514.212.92641.27359
1068.513.0596-4.55957
10713.513.38220.117832
1084.912.5228-7.62282
1096.413.1031-6.70308
1109.613.3096-3.70958
11111.613.0261-1.42613
11211.113.1677-2.06768
1134.3513.851-9.50102
11412.712.8699-0.169863
11518.112.67245.42763
11617.8512.88564.96442
11716.613.53213.06788
11812.613.2522-0.652234
11917.113.61313.4869
12019.113.30925.79076
12116.113.04253.05749
12213.3513.04750.302451
12318.413.93274.46732
12414.712.68242.01755
12510.613.1081-2.50812
12612.612.9261-0.326071
12716.212.80693.39306
12813.613.08770.512294
12918.913.08575.81431
13014.113.10410.995909
13114.513.0031.49704
13216.1512.93743.21258
13314.7512.58342.1666
13414.812.96561.83444
13512.4512.9083-0.458342
13612.6513.591-0.941009
13717.3513.10884.24121
1388.612.7243-4.12428
13918.412.73565.66437
14016.113.89822.20184
14111.612.5434-0.943383
14217.7512.64435.1057
14315.2512.77082.47925
14417.6512.33675.31325
14516.3512.92613.42393
14617.6513.76733.88265
14713.614.2566-0.656618
14814.3513.35040.999597
14914.7513.37081.37918
15018.2513.37854.87153
1519.912.3602-2.46018
1521613.43072.56928
15318.2513.38624.8638
15416.8512.94923.90083
15514.613.51041.08964
15613.8513.64760.202448
15718.9513.71155.23852
15815.612.74442.85564
15914.8513.72851.12146
16011.7512.746-0.996036
16118.4513.00375.4463
16215.912.92572.97426
16317.113.29083.80916
16416.113.59172.50832
16519.913.92365.97639
16610.9512.4571-1.50709
16718.4512.51855.93154
16815.112.9222.17796
1691513.57091.42907
17011.3512.913-1.56298
17115.9513.0042.94596
17218.112.98665.11342
17314.612.84111.75894
17415.413.41831.9817
17515.413.29722.10285
17617.612.4785.12203
17713.3513.4638-0.113824
17819.112.68716.41286
17915.3513.06832.2817
1807.612.5067-4.90671
18113.413.25330.146695
18213.913.1660.733996
18319.112.84586.25424
18415.2512.7442.50598
18512.912.53180.368239
18616.113.26072.83931
18717.3513.16374.18634
18813.1512.9170.232992
18912.1513.1633-1.01332
19012.612.59910.000890249
19110.3513.1088-2.75879
19215.412.6542.74603
1939.613.6121-4.01209
19418.213.22794.97208
19513.613.37220.22784
19614.8513.74151.1085
19714.7512.54322.20676
19814.112.97091.12914
19914.913.00771.89227
20016.2513.38922.86078
20119.2514.9324.31796
20213.614.177-0.576975
20313.612.98630.613693
20415.6512.58413.06593
20512.7512.17950.570523
20614.612.62461.97544
2079.8512.7444-2.89436
20812.6513.529-0.879031
20919.212.42246.77757
21016.612.46234.13775
21111.212.9826-1.78261
21215.2512.78452.46548
21311.912.663-0.763038
21413.212.32040.879638
21516.3512.52223.82785
21612.413.5806-1.1806
21715.8512.96022.88982
21818.1512.88525.26476
21911.1512.5512-1.40123
22015.6513.02752.62253
22117.7512.38065.3694
2227.6512.2339-4.58394
22312.3513.4311-1.08105
22415.612.45423.1458
22519.312.68016.61991
22615.212.62312.57691
22717.113.30923.79076
22815.612.84042.75961
22918.412.70325.69681
23019.0512.86186.18819
23118.5513.18345.3666
23219.113.14025.95978
23313.112.44020.659839
23412.8512.52280.327176
2359.512.9666-3.46656
2364.513.3658-8.86578
23711.8512.5097-0.659732
23813.612.63420.965769
23911.714.6247-2.92474
24012.413.0218-0.621764
24113.3513.18680.163245
24211.411.8565-0.456544
24314.913.20851.69149
24419.913.05956.84049
24511.213.2215-2.02154
24614.612.36052.23948
24717.613.35144.24859
24814.0512.81791.23211
24916.113.08673.0133
25013.3513.08670.263301
25111.8512.6433-0.793295
25211.9512.7852-0.835187
25314.7512.84171.90827
25415.1512.30282.84716
25513.212.4260.774002
25616.8513.12753.72247
2577.8512.5827-4.73272
2587.712.2259-4.52595
25912.612.51010.089932
2607.8513.4525-5.60247
26110.9513.6605-2.71052
26212.3512.5426-0.192567
2639.9513.2131-3.26308
26414.913.04181.85822
26516.6513.06763.58237
26613.413.492-0.0919592
26713.9513.57430.375714
26815.712.62093.07913
26916.8513.20753.64249
27010.9512.901-1.95096
27115.3512.6432.70704
27212.212.3414-0.141447
27315.112.76042.33959
27417.7512.92574.82426
27515.213.20821.99182
27614.613.44811.15189
27716.6512.6513.99905
2788.112.6844-4.5844

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.4341 & -0.534073 \tabularnewline
2 & 12.2 & 13.3297 & -1.12965 \tabularnewline
3 & 12.8 & 13.4127 & -0.612652 \tabularnewline
4 & 7.4 & 12.9853 & -5.5853 \tabularnewline
5 & 6.7 & 13.5331 & -6.83312 \tabularnewline
6 & 12.6 & 12.8695 & -0.269465 \tabularnewline
7 & 14.8 & 12.4294 & 2.37058 \tabularnewline
8 & 13.3 & 13.5207 & -0.220702 \tabularnewline
9 & 11.1 & 12.5392 & -1.43921 \tabularnewline
10 & 8.2 & 14.7419 & -6.54186 \tabularnewline
11 & 11.4 & 12.8822 & -1.48222 \tabularnewline
12 & 6.4 & 13.409 & -7.00896 \tabularnewline
13 & 10.6 & 12.1266 & -1.52656 \tabularnewline
14 & 12 & 12.6835 & -0.683452 \tabularnewline
15 & 6.3 & 12.7631 & -6.46309 \tabularnewline
16 & 11.3 & 12.5572 & -1.25721 \tabularnewline
17 & 11.9 & 12.8063 & -0.906272 \tabularnewline
18 & 9.3 & 12.825 & -3.52501 \tabularnewline
19 & 9.6 & 13.3256 & -3.72563 \tabularnewline
20 & 10 & 12.4311 & -2.4311 \tabularnewline
21 & 6.4 & 12.9451 & -6.54514 \tabularnewline
22 & 13.8 & 12.9371 & 0.862914 \tabularnewline
23 & 10.8 & 12.8046 & -2.00459 \tabularnewline
24 & 13.8 & 12.7239 & 1.07606 \tabularnewline
25 & 11.7 & 12.9977 & -1.29766 \tabularnewline
26 & 10.9 & 12.7648 & -1.86477 \tabularnewline
27 & 16.1 & 12.9217 & 3.17829 \tabularnewline
28 & 13.4 & 13.0917 & 0.30833 \tabularnewline
29 & 9.9 & 13.1673 & -3.26735 \tabularnewline
30 & 11.5 & 12.4013 & -0.901347 \tabularnewline
31 & 8.3 & 12.2829 & -3.98289 \tabularnewline
32 & 11.7 & 13.257 & -1.557 \tabularnewline
33 & 9 & 12.744 & -3.74402 \tabularnewline
34 & 9.7 & 12.58 & -2.88004 \tabularnewline
35 & 10.8 & 12.5305 & -1.73048 \tabularnewline
36 & 10.3 & 13.2493 & -2.94934 \tabularnewline
37 & 10.4 & 12.7849 & -2.38485 \tabularnewline
38 & 12.7 & 13.0103 & -0.31035 \tabularnewline
39 & 9.3 & 13.5632 & -4.26321 \tabularnewline
40 & 11.8 & 12.2809 & -0.480876 \tabularnewline
41 & 5.9 & 13.574 & -7.67395 \tabularnewline
42 & 11.4 & 13.3307 & -1.93066 \tabularnewline
43 & 13 & 12.8257 & 0.174321 \tabularnewline
44 & 10.8 & 12.0399 & -1.23993 \tabularnewline
45 & 12.3 & 12.5613 & -0.261302 \tabularnewline
46 & 11.3 & 13.2477 & -1.94766 \tabularnewline
47 & 11.8 & 13.3507 & -1.55074 \tabularnewline
48 & 7.9 & 12.986 & -5.08597 \tabularnewline
49 & 12.7 & 12.6824 & 0.0175548 \tabularnewline
50 & 12.3 & 13.0683 & -0.768298 \tabularnewline
51 & 11.6 & 12.5222 & -0.922153 \tabularnewline
52 & 6.7 & 12.995 & -6.29497 \tabularnewline
53 & 10.9 & 13.1697 & -2.2697 \tabularnewline
54 & 12.1 & 12.8642 & -0.764158 \tabularnewline
55 & 13.3 & 13.3695 & -0.069475 \tabularnewline
56 & 10.1 & 12.8451 & -2.74509 \tabularnewline
57 & 5.7 & 12.1319 & -6.43193 \tabularnewline
58 & 14.3 & 12.76 & 1.53999 \tabularnewline
59 & 8 & 13.0281 & -5.02814 \tabularnewline
60 & 13.3 & 13.0884 & 0.211623 \tabularnewline
61 & 9.3 & 13.2888 & -3.98883 \tabularnewline
62 & 12.5 & 12.825 & -0.325008 \tabularnewline
63 & 7.6 & 11.9539 & -4.35385 \tabularnewline
64 & 15.9 & 13.1091 & 2.79087 \tabularnewline
65 & 9.2 & 13.2814 & -4.08144 \tabularnewline
66 & 9.1 & 12.8906 & -3.79055 \tabularnewline
67 & 11.1 & 12.8441 & -1.74408 \tabularnewline
68 & 13 & 13.4103 & -0.410303 \tabularnewline
69 & 14.5 & 12.8665 & 1.63349 \tabularnewline
70 & 12.2 & 12.8069 & -0.606943 \tabularnewline
71 & 12.3 & 13.2573 & -0.957333 \tabularnewline
72 & 11.4 & 13.088 & -1.68804 \tabularnewline
73 & 8.8 & 13.2972 & -4.49715 \tabularnewline
74 & 14.6 & 13.8738 & 0.726215 \tabularnewline
75 & 12.6 & 11.9589 & 0.64105 \tabularnewline
76 & 13 & 12.7256 & 0.274378 \tabularnewline
77 & 12.6 & 13.0854 & -0.485355 \tabularnewline
78 & 13.2 & 13.2681 & -0.068076 \tabularnewline
79 & 9.9 & 12.5044 & -2.60442 \tabularnewline
80 & 7.7 & 12.7042 & -5.0042 \tabularnewline
81 & 10.5 & 12.9267 & -2.42674 \tabularnewline
82 & 13.4 & 12.6232 & 0.776783 \tabularnewline
83 & 10.9 & 12.5633 & -1.66332 \tabularnewline
84 & 4.3 & 12.7802 & -8.48015 \tabularnewline
85 & 10.3 & 12.9474 & -2.64743 \tabularnewline
86 & 11.8 & 13.1395 & -1.33955 \tabularnewline
87 & 11.2 & 13.1476 & -1.94761 \tabularnewline
88 & 11.4 & 12.481 & -1.08099 \tabularnewline
89 & 8.6 & 12.8571 & -4.25711 \tabularnewline
90 & 13.2 & 12.6031 & 0.596862 \tabularnewline
91 & 12.6 & 13.0957 & -0.495699 \tabularnewline
92 & 5.6 & 12.5081 & -6.90805 \tabularnewline
93 & 9.9 & 13.1181 & -3.21813 \tabularnewline
94 & 8.8 & 12.2898 & -3.48981 \tabularnewline
95 & 7.7 & 13.2256 & -5.52557 \tabularnewline
96 & 9 & 12.9853 & -3.9853 \tabularnewline
97 & 7.3 & 13.079 & -5.77898 \tabularnewline
98 & 11.4 & 12.7881 & -1.38814 \tabularnewline
99 & 13.6 & 12.9073 & 0.692665 \tabularnewline
100 & 7.9 & 12.7434 & -4.84335 \tabularnewline
101 & 10.7 & 12.9257 & -2.22574 \tabularnewline
102 & 10.3 & 12.6624 & -2.36237 \tabularnewline
103 & 8.3 & 12.2993 & -3.99928 \tabularnewline
104 & 9.6 & 12.8043 & -3.20426 \tabularnewline
105 & 14.2 & 12.9264 & 1.27359 \tabularnewline
106 & 8.5 & 13.0596 & -4.55957 \tabularnewline
107 & 13.5 & 13.3822 & 0.117832 \tabularnewline
108 & 4.9 & 12.5228 & -7.62282 \tabularnewline
109 & 6.4 & 13.1031 & -6.70308 \tabularnewline
110 & 9.6 & 13.3096 & -3.70958 \tabularnewline
111 & 11.6 & 13.0261 & -1.42613 \tabularnewline
112 & 11.1 & 13.1677 & -2.06768 \tabularnewline
113 & 4.35 & 13.851 & -9.50102 \tabularnewline
114 & 12.7 & 12.8699 & -0.169863 \tabularnewline
115 & 18.1 & 12.6724 & 5.42763 \tabularnewline
116 & 17.85 & 12.8856 & 4.96442 \tabularnewline
117 & 16.6 & 13.5321 & 3.06788 \tabularnewline
118 & 12.6 & 13.2522 & -0.652234 \tabularnewline
119 & 17.1 & 13.6131 & 3.4869 \tabularnewline
120 & 19.1 & 13.3092 & 5.79076 \tabularnewline
121 & 16.1 & 13.0425 & 3.05749 \tabularnewline
122 & 13.35 & 13.0475 & 0.302451 \tabularnewline
123 & 18.4 & 13.9327 & 4.46732 \tabularnewline
124 & 14.7 & 12.6824 & 2.01755 \tabularnewline
125 & 10.6 & 13.1081 & -2.50812 \tabularnewline
126 & 12.6 & 12.9261 & -0.326071 \tabularnewline
127 & 16.2 & 12.8069 & 3.39306 \tabularnewline
128 & 13.6 & 13.0877 & 0.512294 \tabularnewline
129 & 18.9 & 13.0857 & 5.81431 \tabularnewline
130 & 14.1 & 13.1041 & 0.995909 \tabularnewline
131 & 14.5 & 13.003 & 1.49704 \tabularnewline
132 & 16.15 & 12.9374 & 3.21258 \tabularnewline
133 & 14.75 & 12.5834 & 2.1666 \tabularnewline
134 & 14.8 & 12.9656 & 1.83444 \tabularnewline
135 & 12.45 & 12.9083 & -0.458342 \tabularnewline
136 & 12.65 & 13.591 & -0.941009 \tabularnewline
137 & 17.35 & 13.1088 & 4.24121 \tabularnewline
138 & 8.6 & 12.7243 & -4.12428 \tabularnewline
139 & 18.4 & 12.7356 & 5.66437 \tabularnewline
140 & 16.1 & 13.8982 & 2.20184 \tabularnewline
141 & 11.6 & 12.5434 & -0.943383 \tabularnewline
142 & 17.75 & 12.6443 & 5.1057 \tabularnewline
143 & 15.25 & 12.7708 & 2.47925 \tabularnewline
144 & 17.65 & 12.3367 & 5.31325 \tabularnewline
145 & 16.35 & 12.9261 & 3.42393 \tabularnewline
146 & 17.65 & 13.7673 & 3.88265 \tabularnewline
147 & 13.6 & 14.2566 & -0.656618 \tabularnewline
148 & 14.35 & 13.3504 & 0.999597 \tabularnewline
149 & 14.75 & 13.3708 & 1.37918 \tabularnewline
150 & 18.25 & 13.3785 & 4.87153 \tabularnewline
151 & 9.9 & 12.3602 & -2.46018 \tabularnewline
152 & 16 & 13.4307 & 2.56928 \tabularnewline
153 & 18.25 & 13.3862 & 4.8638 \tabularnewline
154 & 16.85 & 12.9492 & 3.90083 \tabularnewline
155 & 14.6 & 13.5104 & 1.08964 \tabularnewline
156 & 13.85 & 13.6476 & 0.202448 \tabularnewline
157 & 18.95 & 13.7115 & 5.23852 \tabularnewline
158 & 15.6 & 12.7444 & 2.85564 \tabularnewline
159 & 14.85 & 13.7285 & 1.12146 \tabularnewline
160 & 11.75 & 12.746 & -0.996036 \tabularnewline
161 & 18.45 & 13.0037 & 5.4463 \tabularnewline
162 & 15.9 & 12.9257 & 2.97426 \tabularnewline
163 & 17.1 & 13.2908 & 3.80916 \tabularnewline
164 & 16.1 & 13.5917 & 2.50832 \tabularnewline
165 & 19.9 & 13.9236 & 5.97639 \tabularnewline
166 & 10.95 & 12.4571 & -1.50709 \tabularnewline
167 & 18.45 & 12.5185 & 5.93154 \tabularnewline
168 & 15.1 & 12.922 & 2.17796 \tabularnewline
169 & 15 & 13.5709 & 1.42907 \tabularnewline
170 & 11.35 & 12.913 & -1.56298 \tabularnewline
171 & 15.95 & 13.004 & 2.94596 \tabularnewline
172 & 18.1 & 12.9866 & 5.11342 \tabularnewline
173 & 14.6 & 12.8411 & 1.75894 \tabularnewline
174 & 15.4 & 13.4183 & 1.9817 \tabularnewline
175 & 15.4 & 13.2972 & 2.10285 \tabularnewline
176 & 17.6 & 12.478 & 5.12203 \tabularnewline
177 & 13.35 & 13.4638 & -0.113824 \tabularnewline
178 & 19.1 & 12.6871 & 6.41286 \tabularnewline
179 & 15.35 & 13.0683 & 2.2817 \tabularnewline
180 & 7.6 & 12.5067 & -4.90671 \tabularnewline
181 & 13.4 & 13.2533 & 0.146695 \tabularnewline
182 & 13.9 & 13.166 & 0.733996 \tabularnewline
183 & 19.1 & 12.8458 & 6.25424 \tabularnewline
184 & 15.25 & 12.744 & 2.50598 \tabularnewline
185 & 12.9 & 12.5318 & 0.368239 \tabularnewline
186 & 16.1 & 13.2607 & 2.83931 \tabularnewline
187 & 17.35 & 13.1637 & 4.18634 \tabularnewline
188 & 13.15 & 12.917 & 0.232992 \tabularnewline
189 & 12.15 & 13.1633 & -1.01332 \tabularnewline
190 & 12.6 & 12.5991 & 0.000890249 \tabularnewline
191 & 10.35 & 13.1088 & -2.75879 \tabularnewline
192 & 15.4 & 12.654 & 2.74603 \tabularnewline
193 & 9.6 & 13.6121 & -4.01209 \tabularnewline
194 & 18.2 & 13.2279 & 4.97208 \tabularnewline
195 & 13.6 & 13.3722 & 0.22784 \tabularnewline
196 & 14.85 & 13.7415 & 1.1085 \tabularnewline
197 & 14.75 & 12.5432 & 2.20676 \tabularnewline
198 & 14.1 & 12.9709 & 1.12914 \tabularnewline
199 & 14.9 & 13.0077 & 1.89227 \tabularnewline
200 & 16.25 & 13.3892 & 2.86078 \tabularnewline
201 & 19.25 & 14.932 & 4.31796 \tabularnewline
202 & 13.6 & 14.177 & -0.576975 \tabularnewline
203 & 13.6 & 12.9863 & 0.613693 \tabularnewline
204 & 15.65 & 12.5841 & 3.06593 \tabularnewline
205 & 12.75 & 12.1795 & 0.570523 \tabularnewline
206 & 14.6 & 12.6246 & 1.97544 \tabularnewline
207 & 9.85 & 12.7444 & -2.89436 \tabularnewline
208 & 12.65 & 13.529 & -0.879031 \tabularnewline
209 & 19.2 & 12.4224 & 6.77757 \tabularnewline
210 & 16.6 & 12.4623 & 4.13775 \tabularnewline
211 & 11.2 & 12.9826 & -1.78261 \tabularnewline
212 & 15.25 & 12.7845 & 2.46548 \tabularnewline
213 & 11.9 & 12.663 & -0.763038 \tabularnewline
214 & 13.2 & 12.3204 & 0.879638 \tabularnewline
215 & 16.35 & 12.5222 & 3.82785 \tabularnewline
216 & 12.4 & 13.5806 & -1.1806 \tabularnewline
217 & 15.85 & 12.9602 & 2.88982 \tabularnewline
218 & 18.15 & 12.8852 & 5.26476 \tabularnewline
219 & 11.15 & 12.5512 & -1.40123 \tabularnewline
220 & 15.65 & 13.0275 & 2.62253 \tabularnewline
221 & 17.75 & 12.3806 & 5.3694 \tabularnewline
222 & 7.65 & 12.2339 & -4.58394 \tabularnewline
223 & 12.35 & 13.4311 & -1.08105 \tabularnewline
224 & 15.6 & 12.4542 & 3.1458 \tabularnewline
225 & 19.3 & 12.6801 & 6.61991 \tabularnewline
226 & 15.2 & 12.6231 & 2.57691 \tabularnewline
227 & 17.1 & 13.3092 & 3.79076 \tabularnewline
228 & 15.6 & 12.8404 & 2.75961 \tabularnewline
229 & 18.4 & 12.7032 & 5.69681 \tabularnewline
230 & 19.05 & 12.8618 & 6.18819 \tabularnewline
231 & 18.55 & 13.1834 & 5.3666 \tabularnewline
232 & 19.1 & 13.1402 & 5.95978 \tabularnewline
233 & 13.1 & 12.4402 & 0.659839 \tabularnewline
234 & 12.85 & 12.5228 & 0.327176 \tabularnewline
235 & 9.5 & 12.9666 & -3.46656 \tabularnewline
236 & 4.5 & 13.3658 & -8.86578 \tabularnewline
237 & 11.85 & 12.5097 & -0.659732 \tabularnewline
238 & 13.6 & 12.6342 & 0.965769 \tabularnewline
239 & 11.7 & 14.6247 & -2.92474 \tabularnewline
240 & 12.4 & 13.0218 & -0.621764 \tabularnewline
241 & 13.35 & 13.1868 & 0.163245 \tabularnewline
242 & 11.4 & 11.8565 & -0.456544 \tabularnewline
243 & 14.9 & 13.2085 & 1.69149 \tabularnewline
244 & 19.9 & 13.0595 & 6.84049 \tabularnewline
245 & 11.2 & 13.2215 & -2.02154 \tabularnewline
246 & 14.6 & 12.3605 & 2.23948 \tabularnewline
247 & 17.6 & 13.3514 & 4.24859 \tabularnewline
248 & 14.05 & 12.8179 & 1.23211 \tabularnewline
249 & 16.1 & 13.0867 & 3.0133 \tabularnewline
250 & 13.35 & 13.0867 & 0.263301 \tabularnewline
251 & 11.85 & 12.6433 & -0.793295 \tabularnewline
252 & 11.95 & 12.7852 & -0.835187 \tabularnewline
253 & 14.75 & 12.8417 & 1.90827 \tabularnewline
254 & 15.15 & 12.3028 & 2.84716 \tabularnewline
255 & 13.2 & 12.426 & 0.774002 \tabularnewline
256 & 16.85 & 13.1275 & 3.72247 \tabularnewline
257 & 7.85 & 12.5827 & -4.73272 \tabularnewline
258 & 7.7 & 12.2259 & -4.52595 \tabularnewline
259 & 12.6 & 12.5101 & 0.089932 \tabularnewline
260 & 7.85 & 13.4525 & -5.60247 \tabularnewline
261 & 10.95 & 13.6605 & -2.71052 \tabularnewline
262 & 12.35 & 12.5426 & -0.192567 \tabularnewline
263 & 9.95 & 13.2131 & -3.26308 \tabularnewline
264 & 14.9 & 13.0418 & 1.85822 \tabularnewline
265 & 16.65 & 13.0676 & 3.58237 \tabularnewline
266 & 13.4 & 13.492 & -0.0919592 \tabularnewline
267 & 13.95 & 13.5743 & 0.375714 \tabularnewline
268 & 15.7 & 12.6209 & 3.07913 \tabularnewline
269 & 16.85 & 13.2075 & 3.64249 \tabularnewline
270 & 10.95 & 12.901 & -1.95096 \tabularnewline
271 & 15.35 & 12.643 & 2.70704 \tabularnewline
272 & 12.2 & 12.3414 & -0.141447 \tabularnewline
273 & 15.1 & 12.7604 & 2.33959 \tabularnewline
274 & 17.75 & 12.9257 & 4.82426 \tabularnewline
275 & 15.2 & 13.2082 & 1.99182 \tabularnewline
276 & 14.6 & 13.4481 & 1.15189 \tabularnewline
277 & 16.65 & 12.651 & 3.99905 \tabularnewline
278 & 8.1 & 12.6844 & -4.5844 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&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]13.4341[/C][C]-0.534073[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]13.3297[/C][C]-1.12965[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.4127[/C][C]-0.612652[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]12.9853[/C][C]-5.5853[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]13.5331[/C][C]-6.83312[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]12.8695[/C][C]-0.269465[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.4294[/C][C]2.37058[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.5207[/C][C]-0.220702[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.5392[/C][C]-1.43921[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]14.7419[/C][C]-6.54186[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]12.8822[/C][C]-1.48222[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]13.409[/C][C]-7.00896[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.1266[/C][C]-1.52656[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.6835[/C][C]-0.683452[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]12.7631[/C][C]-6.46309[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]12.5572[/C][C]-1.25721[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.8063[/C][C]-0.906272[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]12.825[/C][C]-3.52501[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.3256[/C][C]-3.72563[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.4311[/C][C]-2.4311[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]12.9451[/C][C]-6.54514[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.9371[/C][C]0.862914[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]12.8046[/C][C]-2.00459[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.7239[/C][C]1.07606[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]12.9977[/C][C]-1.29766[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]12.7648[/C][C]-1.86477[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.9217[/C][C]3.17829[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.0917[/C][C]0.30833[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]13.1673[/C][C]-3.26735[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]12.4013[/C][C]-0.901347[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.2829[/C][C]-3.98289[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.257[/C][C]-1.557[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.744[/C][C]-3.74402[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]12.58[/C][C]-2.88004[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.5305[/C][C]-1.73048[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]13.2493[/C][C]-2.94934[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.7849[/C][C]-2.38485[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]13.0103[/C][C]-0.31035[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.5632[/C][C]-4.26321[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.2809[/C][C]-0.480876[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]13.574[/C][C]-7.67395[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.3307[/C][C]-1.93066[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]12.8257[/C][C]0.174321[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]12.0399[/C][C]-1.23993[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.5613[/C][C]-0.261302[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.2477[/C][C]-1.94766[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]13.3507[/C][C]-1.55074[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]12.986[/C][C]-5.08597[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]12.6824[/C][C]0.0175548[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]13.0683[/C][C]-0.768298[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]12.5222[/C][C]-0.922153[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]12.995[/C][C]-6.29497[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]13.1697[/C][C]-2.2697[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.8642[/C][C]-0.764158[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.3695[/C][C]-0.069475[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.8451[/C][C]-2.74509[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]12.1319[/C][C]-6.43193[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.76[/C][C]1.53999[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]13.0281[/C][C]-5.02814[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.0884[/C][C]0.211623[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]13.2888[/C][C]-3.98883[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.825[/C][C]-0.325008[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]11.9539[/C][C]-4.35385[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.1091[/C][C]2.79087[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.2814[/C][C]-4.08144[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]12.8906[/C][C]-3.79055[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.8441[/C][C]-1.74408[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.4103[/C][C]-0.410303[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.8665[/C][C]1.63349[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]12.8069[/C][C]-0.606943[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.2573[/C][C]-0.957333[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]13.088[/C][C]-1.68804[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]13.2972[/C][C]-4.49715[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.8738[/C][C]0.726215[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.9589[/C][C]0.64105[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]12.7256[/C][C]0.274378[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]13.0854[/C][C]-0.485355[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]13.2681[/C][C]-0.068076[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]12.5044[/C][C]-2.60442[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]12.7042[/C][C]-5.0042[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]12.9267[/C][C]-2.42674[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]12.6232[/C][C]0.776783[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]12.5633[/C][C]-1.66332[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]12.7802[/C][C]-8.48015[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]12.9474[/C][C]-2.64743[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]13.1395[/C][C]-1.33955[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]13.1476[/C][C]-1.94761[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]12.481[/C][C]-1.08099[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]12.8571[/C][C]-4.25711[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]12.6031[/C][C]0.596862[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]13.0957[/C][C]-0.495699[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]12.5081[/C][C]-6.90805[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]13.1181[/C][C]-3.21813[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]12.2898[/C][C]-3.48981[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]13.2256[/C][C]-5.52557[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]12.9853[/C][C]-3.9853[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]13.079[/C][C]-5.77898[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]12.7881[/C][C]-1.38814[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]12.9073[/C][C]0.692665[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]12.7434[/C][C]-4.84335[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]12.9257[/C][C]-2.22574[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]12.6624[/C][C]-2.36237[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]12.2993[/C][C]-3.99928[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]12.8043[/C][C]-3.20426[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]12.9264[/C][C]1.27359[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]13.0596[/C][C]-4.55957[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]13.3822[/C][C]0.117832[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]12.5228[/C][C]-7.62282[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]13.1031[/C][C]-6.70308[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]13.3096[/C][C]-3.70958[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]13.0261[/C][C]-1.42613[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]13.1677[/C][C]-2.06768[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]13.851[/C][C]-9.50102[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.8699[/C][C]-0.169863[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]12.6724[/C][C]5.42763[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]12.8856[/C][C]4.96442[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]13.5321[/C][C]3.06788[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]13.2522[/C][C]-0.652234[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]13.6131[/C][C]3.4869[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]13.3092[/C][C]5.79076[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]13.0425[/C][C]3.05749[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]13.0475[/C][C]0.302451[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]13.9327[/C][C]4.46732[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]12.6824[/C][C]2.01755[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]13.1081[/C][C]-2.50812[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.9261[/C][C]-0.326071[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]12.8069[/C][C]3.39306[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]13.0877[/C][C]0.512294[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]13.0857[/C][C]5.81431[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]13.1041[/C][C]0.995909[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.003[/C][C]1.49704[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]12.9374[/C][C]3.21258[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]12.5834[/C][C]2.1666[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]12.9656[/C][C]1.83444[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.9083[/C][C]-0.458342[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]13.591[/C][C]-0.941009[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.1088[/C][C]4.24121[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]12.7243[/C][C]-4.12428[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]12.7356[/C][C]5.66437[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]13.8982[/C][C]2.20184[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]12.5434[/C][C]-0.943383[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]12.6443[/C][C]5.1057[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]12.7708[/C][C]2.47925[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]12.3367[/C][C]5.31325[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]12.9261[/C][C]3.42393[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]13.7673[/C][C]3.88265[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]14.2566[/C][C]-0.656618[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]13.3504[/C][C]0.999597[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]13.3708[/C][C]1.37918[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]13.3785[/C][C]4.87153[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]12.3602[/C][C]-2.46018[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.4307[/C][C]2.56928[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]13.3862[/C][C]4.8638[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]12.9492[/C][C]3.90083[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]13.5104[/C][C]1.08964[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]13.6476[/C][C]0.202448[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]13.7115[/C][C]5.23852[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]12.7444[/C][C]2.85564[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]13.7285[/C][C]1.12146[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]12.746[/C][C]-0.996036[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]13.0037[/C][C]5.4463[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]12.9257[/C][C]2.97426[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]13.2908[/C][C]3.80916[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]13.5917[/C][C]2.50832[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]13.9236[/C][C]5.97639[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]12.4571[/C][C]-1.50709[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]12.5185[/C][C]5.93154[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]12.922[/C][C]2.17796[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]13.5709[/C][C]1.42907[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]12.913[/C][C]-1.56298[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]13.004[/C][C]2.94596[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]12.9866[/C][C]5.11342[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]12.8411[/C][C]1.75894[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]13.4183[/C][C]1.9817[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.2972[/C][C]2.10285[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]12.478[/C][C]5.12203[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]13.4638[/C][C]-0.113824[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]12.6871[/C][C]6.41286[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]13.0683[/C][C]2.2817[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]12.5067[/C][C]-4.90671[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]13.2533[/C][C]0.146695[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]13.166[/C][C]0.733996[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]12.8458[/C][C]6.25424[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]12.744[/C][C]2.50598[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]12.5318[/C][C]0.368239[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]13.2607[/C][C]2.83931[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]13.1637[/C][C]4.18634[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]12.917[/C][C]0.232992[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]13.1633[/C][C]-1.01332[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.5991[/C][C]0.000890249[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]13.1088[/C][C]-2.75879[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]12.654[/C][C]2.74603[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]13.6121[/C][C]-4.01209[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]13.2279[/C][C]4.97208[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]13.3722[/C][C]0.22784[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]13.7415[/C][C]1.1085[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]12.5432[/C][C]2.20676[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]12.9709[/C][C]1.12914[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]13.0077[/C][C]1.89227[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]13.3892[/C][C]2.86078[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]14.932[/C][C]4.31796[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]14.177[/C][C]-0.576975[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]12.9863[/C][C]0.613693[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]12.5841[/C][C]3.06593[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]12.1795[/C][C]0.570523[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]12.6246[/C][C]1.97544[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]12.7444[/C][C]-2.89436[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]13.529[/C][C]-0.879031[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]12.4224[/C][C]6.77757[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]12.4623[/C][C]4.13775[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]12.9826[/C][C]-1.78261[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]12.7845[/C][C]2.46548[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]12.663[/C][C]-0.763038[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]12.3204[/C][C]0.879638[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]12.5222[/C][C]3.82785[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.5806[/C][C]-1.1806[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]12.9602[/C][C]2.88982[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]12.8852[/C][C]5.26476[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.5512[/C][C]-1.40123[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]13.0275[/C][C]2.62253[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]12.3806[/C][C]5.3694[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.2339[/C][C]-4.58394[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.4311[/C][C]-1.08105[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]12.4542[/C][C]3.1458[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]12.6801[/C][C]6.61991[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]12.6231[/C][C]2.57691[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]13.3092[/C][C]3.79076[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]12.8404[/C][C]2.75961[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]12.7032[/C][C]5.69681[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]12.8618[/C][C]6.18819[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]13.1834[/C][C]5.3666[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]13.1402[/C][C]5.95978[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]12.4402[/C][C]0.659839[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]12.5228[/C][C]0.327176[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]12.9666[/C][C]-3.46656[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]13.3658[/C][C]-8.86578[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.5097[/C][C]-0.659732[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]12.6342[/C][C]0.965769[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]14.6247[/C][C]-2.92474[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]13.0218[/C][C]-0.621764[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]13.1868[/C][C]0.163245[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]11.8565[/C][C]-0.456544[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]13.2085[/C][C]1.69149[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]13.0595[/C][C]6.84049[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.2215[/C][C]-2.02154[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]12.3605[/C][C]2.23948[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]13.3514[/C][C]4.24859[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]12.8179[/C][C]1.23211[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]13.0867[/C][C]3.0133[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]13.0867[/C][C]0.263301[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]12.6433[/C][C]-0.793295[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]12.7852[/C][C]-0.835187[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]12.8417[/C][C]1.90827[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]12.3028[/C][C]2.84716[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]12.426[/C][C]0.774002[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]13.1275[/C][C]3.72247[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.5827[/C][C]-4.73272[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.2259[/C][C]-4.52595[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]12.5101[/C][C]0.089932[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]13.4525[/C][C]-5.60247[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]13.6605[/C][C]-2.71052[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]12.5426[/C][C]-0.192567[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]13.2131[/C][C]-3.26308[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]13.0418[/C][C]1.85822[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]13.0676[/C][C]3.58237[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.492[/C][C]-0.0919592[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.5743[/C][C]0.375714[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]12.6209[/C][C]3.07913[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]13.2075[/C][C]3.64249[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.901[/C][C]-1.95096[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]12.643[/C][C]2.70704[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.3414[/C][C]-0.141447[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]12.7604[/C][C]2.33959[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]12.9257[/C][C]4.82426[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]13.2082[/C][C]1.99182[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]13.4481[/C][C]1.15189[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]12.651[/C][C]3.99905[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]12.6844[/C][C]-4.5844[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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
112.913.4341-0.534073
212.213.3297-1.12965
312.813.4127-0.612652
47.412.9853-5.5853
56.713.5331-6.83312
612.612.8695-0.269465
714.812.42942.37058
813.313.5207-0.220702
911.112.5392-1.43921
108.214.7419-6.54186
1111.412.8822-1.48222
126.413.409-7.00896
1310.612.1266-1.52656
141212.6835-0.683452
156.312.7631-6.46309
1611.312.5572-1.25721
1711.912.8063-0.906272
189.312.825-3.52501
199.613.3256-3.72563
201012.4311-2.4311
216.412.9451-6.54514
2213.812.93710.862914
2310.812.8046-2.00459
2413.812.72391.07606
2511.712.9977-1.29766
2610.912.7648-1.86477
2716.112.92173.17829
2813.413.09170.30833
299.913.1673-3.26735
3011.512.4013-0.901347
318.312.2829-3.98289
3211.713.257-1.557
33912.744-3.74402
349.712.58-2.88004
3510.812.5305-1.73048
3610.313.2493-2.94934
3710.412.7849-2.38485
3812.713.0103-0.31035
399.313.5632-4.26321
4011.812.2809-0.480876
415.913.574-7.67395
4211.413.3307-1.93066
431312.82570.174321
4410.812.0399-1.23993
4512.312.5613-0.261302
4611.313.2477-1.94766
4711.813.3507-1.55074
487.912.986-5.08597
4912.712.68240.0175548
5012.313.0683-0.768298
5111.612.5222-0.922153
526.712.995-6.29497
5310.913.1697-2.2697
5412.112.8642-0.764158
5513.313.3695-0.069475
5610.112.8451-2.74509
575.712.1319-6.43193
5814.312.761.53999
59813.0281-5.02814
6013.313.08840.211623
619.313.2888-3.98883
6212.512.825-0.325008
637.611.9539-4.35385
6415.913.10912.79087
659.213.2814-4.08144
669.112.8906-3.79055
6711.112.8441-1.74408
681313.4103-0.410303
6914.512.86651.63349
7012.212.8069-0.606943
7112.313.2573-0.957333
7211.413.088-1.68804
738.813.2972-4.49715
7414.613.87380.726215
7512.611.95890.64105
761312.72560.274378
7712.613.0854-0.485355
7813.213.2681-0.068076
799.912.5044-2.60442
807.712.7042-5.0042
8110.512.9267-2.42674
8213.412.62320.776783
8310.912.5633-1.66332
844.312.7802-8.48015
8510.312.9474-2.64743
8611.813.1395-1.33955
8711.213.1476-1.94761
8811.412.481-1.08099
898.612.8571-4.25711
9013.212.60310.596862
9112.613.0957-0.495699
925.612.5081-6.90805
939.913.1181-3.21813
948.812.2898-3.48981
957.713.2256-5.52557
96912.9853-3.9853
977.313.079-5.77898
9811.412.7881-1.38814
9913.612.90730.692665
1007.912.7434-4.84335
10110.712.9257-2.22574
10210.312.6624-2.36237
1038.312.2993-3.99928
1049.612.8043-3.20426
10514.212.92641.27359
1068.513.0596-4.55957
10713.513.38220.117832
1084.912.5228-7.62282
1096.413.1031-6.70308
1109.613.3096-3.70958
11111.613.0261-1.42613
11211.113.1677-2.06768
1134.3513.851-9.50102
11412.712.8699-0.169863
11518.112.67245.42763
11617.8512.88564.96442
11716.613.53213.06788
11812.613.2522-0.652234
11917.113.61313.4869
12019.113.30925.79076
12116.113.04253.05749
12213.3513.04750.302451
12318.413.93274.46732
12414.712.68242.01755
12510.613.1081-2.50812
12612.612.9261-0.326071
12716.212.80693.39306
12813.613.08770.512294
12918.913.08575.81431
13014.113.10410.995909
13114.513.0031.49704
13216.1512.93743.21258
13314.7512.58342.1666
13414.812.96561.83444
13512.4512.9083-0.458342
13612.6513.591-0.941009
13717.3513.10884.24121
1388.612.7243-4.12428
13918.412.73565.66437
14016.113.89822.20184
14111.612.5434-0.943383
14217.7512.64435.1057
14315.2512.77082.47925
14417.6512.33675.31325
14516.3512.92613.42393
14617.6513.76733.88265
14713.614.2566-0.656618
14814.3513.35040.999597
14914.7513.37081.37918
15018.2513.37854.87153
1519.912.3602-2.46018
1521613.43072.56928
15318.2513.38624.8638
15416.8512.94923.90083
15514.613.51041.08964
15613.8513.64760.202448
15718.9513.71155.23852
15815.612.74442.85564
15914.8513.72851.12146
16011.7512.746-0.996036
16118.4513.00375.4463
16215.912.92572.97426
16317.113.29083.80916
16416.113.59172.50832
16519.913.92365.97639
16610.9512.4571-1.50709
16718.4512.51855.93154
16815.112.9222.17796
1691513.57091.42907
17011.3512.913-1.56298
17115.9513.0042.94596
17218.112.98665.11342
17314.612.84111.75894
17415.413.41831.9817
17515.413.29722.10285
17617.612.4785.12203
17713.3513.4638-0.113824
17819.112.68716.41286
17915.3513.06832.2817
1807.612.5067-4.90671
18113.413.25330.146695
18213.913.1660.733996
18319.112.84586.25424
18415.2512.7442.50598
18512.912.53180.368239
18616.113.26072.83931
18717.3513.16374.18634
18813.1512.9170.232992
18912.1513.1633-1.01332
19012.612.59910.000890249
19110.3513.1088-2.75879
19215.412.6542.74603
1939.613.6121-4.01209
19418.213.22794.97208
19513.613.37220.22784
19614.8513.74151.1085
19714.7512.54322.20676
19814.112.97091.12914
19914.913.00771.89227
20016.2513.38922.86078
20119.2514.9324.31796
20213.614.177-0.576975
20313.612.98630.613693
20415.6512.58413.06593
20512.7512.17950.570523
20614.612.62461.97544
2079.8512.7444-2.89436
20812.6513.529-0.879031
20919.212.42246.77757
21016.612.46234.13775
21111.212.9826-1.78261
21215.2512.78452.46548
21311.912.663-0.763038
21413.212.32040.879638
21516.3512.52223.82785
21612.413.5806-1.1806
21715.8512.96022.88982
21818.1512.88525.26476
21911.1512.5512-1.40123
22015.6513.02752.62253
22117.7512.38065.3694
2227.6512.2339-4.58394
22312.3513.4311-1.08105
22415.612.45423.1458
22519.312.68016.61991
22615.212.62312.57691
22717.113.30923.79076
22815.612.84042.75961
22918.412.70325.69681
23019.0512.86186.18819
23118.5513.18345.3666
23219.113.14025.95978
23313.112.44020.659839
23412.8512.52280.327176
2359.512.9666-3.46656
2364.513.3658-8.86578
23711.8512.5097-0.659732
23813.612.63420.965769
23911.714.6247-2.92474
24012.413.0218-0.621764
24113.3513.18680.163245
24211.411.8565-0.456544
24314.913.20851.69149
24419.913.05956.84049
24511.213.2215-2.02154
24614.612.36052.23948
24717.613.35144.24859
24814.0512.81791.23211
24916.113.08673.0133
25013.3513.08670.263301
25111.8512.6433-0.793295
25211.9512.7852-0.835187
25314.7512.84171.90827
25415.1512.30282.84716
25513.212.4260.774002
25616.8513.12753.72247
2577.8512.5827-4.73272
2587.712.2259-4.52595
25912.612.51010.089932
2607.8513.4525-5.60247
26110.9513.6605-2.71052
26212.3512.5426-0.192567
2639.9513.2131-3.26308
26414.913.04181.85822
26516.6513.06763.58237
26613.413.492-0.0919592
26713.9513.57430.375714
26815.712.62093.07913
26916.8513.20753.64249
27010.9512.901-1.95096
27115.3512.6432.70704
27212.212.3414-0.141447
27315.112.76042.33959
27417.7512.92574.82426
27515.213.20821.99182
27614.613.44811.15189
27716.6512.6513.99905
2788.112.6844-4.5844






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
70.487740.975480.51226
80.358830.7176610.64117
90.2849170.5698330.715083
100.2138740.4277480.786126
110.1343530.2687050.865647
120.1313690.2627370.868631
130.1351920.2703840.864808
140.09810410.1962080.901896
150.1147510.2295010.885249
160.08696510.173930.913035
170.05612780.1122560.943872
180.0379150.075830.962085
190.02421030.04842050.97579
200.01455760.02911510.985442
210.01663180.03326360.983368
220.02261980.04523970.97738
230.01483060.02966130.985169
240.01959140.03918280.980409
250.01353920.02707840.986461
260.00848670.01697340.991513
270.02628230.05256460.973718
280.01797310.03594630.982027
290.01225950.02451890.987741
300.007911040.01582210.992089
310.01629630.03259260.983704
320.01100880.02201760.988991
330.008218560.01643710.991781
340.006755190.01351040.993245
350.005021840.01004370.994978
360.003350560.006701110.996649
370.002179720.004359440.99782
380.001368540.002737070.998631
390.001061020.002122040.998939
400.000682570.001365140.999317
410.001996250.003992510.998004
420.001450150.002900290.99855
430.001338590.002677170.998661
440.0009010070.001802010.999099
450.000568730.001137460.999431
460.0004495890.0008991780.99955
470.0003335170.0006670350.999666
480.0003177860.0006355720.999682
490.0003128060.0006256130.999687
500.0002379540.0004759070.999762
510.0001571390.0003142790.999843
520.0005852460.001170490.999415
530.0003953450.000790690.999605
540.0003193740.0006387480.999681
550.0003795460.0007590910.99962
560.0002624580.0005249150.999738
570.001427120.002854240.998573
580.001115970.002231930.998884
590.001196790.002393570.998803
600.0011640.002327990.998836
610.0009390830.001878170.999061
620.0007714620.001542920.999229
630.001691190.003382380.998309
640.003319950.00663990.99668
650.003018930.006037860.996981
660.002889210.005778410.997111
670.002168010.004336010.997832
680.001922120.003844250.998078
690.002213810.004427620.997786
700.001665980.003331960.998334
710.001256390.002512770.998744
720.0009286620.001857320.999071
730.0009353360.001870670.999065
740.001170650.00234130.998829
750.0008986320.001797260.999101
760.0007184760.001436950.999282
770.0005390170.001078030.999461
780.0004735460.0009470920.999526
790.000380940.000761880.999619
800.000502140.001004280.999498
810.0003828850.000765770.999617
820.0003380350.000676070.999662
830.0002451780.0004903560.999755
840.001517650.00303530.998482
850.001229320.002458650.998771
860.0009422170.001884430.999058
870.000727090.001454180.999273
880.0005448190.001089640.999455
890.0005764140.001152830.999424
900.0004945060.0009890130.999505
910.0003863980.0007727960.999614
920.001219240.002438490.998781
930.001047670.002095350.998952
940.0009662320.001932460.999034
950.001416020.002832040.998584
960.001441510.002883030.998558
970.002248270.004496540.997752
980.001800540.003601080.998199
990.001624090.003248190.998376
1000.002129420.004258830.997871
1010.00177950.003559010.99822
1020.001515760.003031520.998484
1030.00180730.00361460.998193
1040.001715780.003431560.998284
1050.001752880.003505750.998247
1060.002099650.004199310.9979
1070.00194590.00389180.998054
1080.007827120.01565420.992173
1090.01666460.03332910.983335
1100.01748430.03496860.982516
1110.01547930.03095870.984521
1120.01402830.02805670.985972
1130.0688390.1376780.931161
1140.06215930.1243190.937841
1150.1261020.2522040.873898
1160.202350.40470.79765
1170.2436490.4872980.756351
1180.2279140.4558290.772086
1190.2776590.5553170.722341
1200.4189690.8379380.581031
1210.4501280.9002560.549872
1220.4301260.8602520.569874
1230.5056660.9886680.494334
1240.5068850.9862290.493115
1250.5036330.9927340.496367
1260.4809590.9619170.519041
1270.5018510.9962980.498149
1280.4805960.9611920.519404
1290.6024170.7951660.397583
1300.583730.8325410.41627
1310.5739680.8520630.426032
1320.593510.812980.40649
1330.5853010.8293980.414699
1340.5740490.8519020.425951
1350.5507430.8985150.449257
1360.5288910.9422180.471109
1370.5666610.8666790.433339
1380.6082710.7834570.391729
1390.6956590.6086820.304341
1400.6915780.6168440.308422
1410.6635710.6728570.336429
1420.7160190.5679610.283981
1430.711870.576260.28813
1440.7633730.4732550.236627
1450.7696550.460690.230345
1460.7861180.4277640.213882
1470.7680790.4638420.231921
1480.7478850.504230.252115
1490.7283150.543370.271685
1500.7661620.4676760.233838
1510.7666790.4666420.233321
1520.7575430.4849140.242457
1530.7891350.4217310.210865
1540.795660.408680.20434
1550.7756630.4486750.224337
1560.7529860.4940290.247014
1570.7903360.4193270.209664
1580.7835250.432950.216475
1590.7608020.4783960.239198
1600.7440540.5118920.255946
1610.7853970.4292050.214603
1620.7784780.4430450.221522
1630.7810020.4379970.218998
1640.7665780.4668450.233422
1650.8185040.3629910.181496
1660.8035890.3928230.196411
1670.8486510.3026980.151349
1680.8350620.3298750.164938
1690.8153340.3693310.184666
1700.8032480.3935030.196752
1710.7951830.4096340.204817
1720.8243730.3512540.175627
1730.806050.38790.19395
1740.7873940.4252130.212606
1750.7687180.4625650.231282
1760.7967090.4065820.203291
1770.7718260.4563470.228174
1780.8306570.3386850.169343
1790.8149990.3700020.185001
1800.8570770.2858450.142923
1810.8364180.3271640.163582
1820.81340.3731990.1866
1830.8608170.2783660.139183
1840.8481160.3037680.151884
1850.8267590.3464810.173241
1860.8153790.3692430.184621
1870.8220230.3559540.177977
1880.7988250.4023490.201175
1890.7798160.4403680.220184
1900.754540.4909210.24546
1910.7556470.4887060.244353
1920.7393110.5213780.260689
1930.7694320.4611360.230568
1940.790140.419720.20986
1950.7622520.4754960.237748
1960.7332410.5335190.266759
1970.7093030.5813940.290697
1980.677490.6450190.32251
1990.6482170.7035670.351783
2000.6292850.7414310.370715
2010.6938260.6123480.306174
2020.6594160.6811680.340584
2030.6244210.7511570.375579
2040.603130.7937410.39687
2050.5729320.8541360.427068
2060.5393190.9213620.460681
2070.5570710.8858590.442929
2080.519140.9617190.48086
2090.5925520.8148960.407448
2100.5890640.8218720.410936
2110.5725820.8548370.427418
2120.542710.9145790.45729
2130.5160630.9678740.483937
2140.4790460.9580920.520954
2150.4672860.9345720.532714
2160.4330150.8660310.566985
2170.4120970.8241940.587903
2180.4416870.8833740.558313
2190.4169660.8339320.583034
2200.3890510.7781020.610949
2210.4166950.833390.583305
2220.4944030.9888050.505597
2230.4596840.9193680.540316
2240.4381050.876210.561895
2250.5318820.9362370.468118
2260.503880.992240.49612
2270.498410.9968210.50159
2280.4684730.9369460.531527
2290.5186940.9626130.481306
2300.6092250.781550.390775
2310.6589990.6820020.341001
2320.745340.509320.25466
2330.7051770.5896470.294823
2340.661490.6770210.33851
2350.6722380.6555240.327762
2360.9090760.1818490.0909243
2370.8904650.2190690.109535
2380.8641330.2717340.135867
2390.8577540.2844930.142246
2400.8334150.3331710.166585
2410.8022920.3954170.197708
2420.7646370.4707260.235363
2430.7232040.5535920.276796
2440.8578280.2843440.142172
2450.8434710.3130590.156529
2460.8133320.3733370.186668
2470.8294380.3411230.170562
2480.8001680.3996630.199832
2490.7759030.4481930.224097
2500.7281040.5437930.271896
2510.685550.6288990.31445
2520.6385030.7229940.361497
2530.5875260.8249480.412474
2540.7220940.5558120.277906
2550.7963380.4073240.203662
2560.7644570.4710850.235543
2570.8588240.2823520.141176
2580.9483180.1033640.0516818
2590.922430.155140.0775699
2600.9801650.03967060.0198353
2610.970520.058960.02948
2620.9575970.08480610.0424031
2630.9315040.1369920.0684962
2640.918270.1634590.0817296
2650.8912890.2174220.108711
2660.8552050.2895890.144795
2670.778370.443260.22163
2680.6871850.625630.312815
2690.5621770.8756460.437823
2700.7887090.4225810.211291
2710.6540060.6919880.345994

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
7 & 0.48774 & 0.97548 & 0.51226 \tabularnewline
8 & 0.35883 & 0.717661 & 0.64117 \tabularnewline
9 & 0.284917 & 0.569833 & 0.715083 \tabularnewline
10 & 0.213874 & 0.427748 & 0.786126 \tabularnewline
11 & 0.134353 & 0.268705 & 0.865647 \tabularnewline
12 & 0.131369 & 0.262737 & 0.868631 \tabularnewline
13 & 0.135192 & 0.270384 & 0.864808 \tabularnewline
14 & 0.0981041 & 0.196208 & 0.901896 \tabularnewline
15 & 0.114751 & 0.229501 & 0.885249 \tabularnewline
16 & 0.0869651 & 0.17393 & 0.913035 \tabularnewline
17 & 0.0561278 & 0.112256 & 0.943872 \tabularnewline
18 & 0.037915 & 0.07583 & 0.962085 \tabularnewline
19 & 0.0242103 & 0.0484205 & 0.97579 \tabularnewline
20 & 0.0145576 & 0.0291151 & 0.985442 \tabularnewline
21 & 0.0166318 & 0.0332636 & 0.983368 \tabularnewline
22 & 0.0226198 & 0.0452397 & 0.97738 \tabularnewline
23 & 0.0148306 & 0.0296613 & 0.985169 \tabularnewline
24 & 0.0195914 & 0.0391828 & 0.980409 \tabularnewline
25 & 0.0135392 & 0.0270784 & 0.986461 \tabularnewline
26 & 0.0084867 & 0.0169734 & 0.991513 \tabularnewline
27 & 0.0262823 & 0.0525646 & 0.973718 \tabularnewline
28 & 0.0179731 & 0.0359463 & 0.982027 \tabularnewline
29 & 0.0122595 & 0.0245189 & 0.987741 \tabularnewline
30 & 0.00791104 & 0.0158221 & 0.992089 \tabularnewline
31 & 0.0162963 & 0.0325926 & 0.983704 \tabularnewline
32 & 0.0110088 & 0.0220176 & 0.988991 \tabularnewline
33 & 0.00821856 & 0.0164371 & 0.991781 \tabularnewline
34 & 0.00675519 & 0.0135104 & 0.993245 \tabularnewline
35 & 0.00502184 & 0.0100437 & 0.994978 \tabularnewline
36 & 0.00335056 & 0.00670111 & 0.996649 \tabularnewline
37 & 0.00217972 & 0.00435944 & 0.99782 \tabularnewline
38 & 0.00136854 & 0.00273707 & 0.998631 \tabularnewline
39 & 0.00106102 & 0.00212204 & 0.998939 \tabularnewline
40 & 0.00068257 & 0.00136514 & 0.999317 \tabularnewline
41 & 0.00199625 & 0.00399251 & 0.998004 \tabularnewline
42 & 0.00145015 & 0.00290029 & 0.99855 \tabularnewline
43 & 0.00133859 & 0.00267717 & 0.998661 \tabularnewline
44 & 0.000901007 & 0.00180201 & 0.999099 \tabularnewline
45 & 0.00056873 & 0.00113746 & 0.999431 \tabularnewline
46 & 0.000449589 & 0.000899178 & 0.99955 \tabularnewline
47 & 0.000333517 & 0.000667035 & 0.999666 \tabularnewline
48 & 0.000317786 & 0.000635572 & 0.999682 \tabularnewline
49 & 0.000312806 & 0.000625613 & 0.999687 \tabularnewline
50 & 0.000237954 & 0.000475907 & 0.999762 \tabularnewline
51 & 0.000157139 & 0.000314279 & 0.999843 \tabularnewline
52 & 0.000585246 & 0.00117049 & 0.999415 \tabularnewline
53 & 0.000395345 & 0.00079069 & 0.999605 \tabularnewline
54 & 0.000319374 & 0.000638748 & 0.999681 \tabularnewline
55 & 0.000379546 & 0.000759091 & 0.99962 \tabularnewline
56 & 0.000262458 & 0.000524915 & 0.999738 \tabularnewline
57 & 0.00142712 & 0.00285424 & 0.998573 \tabularnewline
58 & 0.00111597 & 0.00223193 & 0.998884 \tabularnewline
59 & 0.00119679 & 0.00239357 & 0.998803 \tabularnewline
60 & 0.001164 & 0.00232799 & 0.998836 \tabularnewline
61 & 0.000939083 & 0.00187817 & 0.999061 \tabularnewline
62 & 0.000771462 & 0.00154292 & 0.999229 \tabularnewline
63 & 0.00169119 & 0.00338238 & 0.998309 \tabularnewline
64 & 0.00331995 & 0.0066399 & 0.99668 \tabularnewline
65 & 0.00301893 & 0.00603786 & 0.996981 \tabularnewline
66 & 0.00288921 & 0.00577841 & 0.997111 \tabularnewline
67 & 0.00216801 & 0.00433601 & 0.997832 \tabularnewline
68 & 0.00192212 & 0.00384425 & 0.998078 \tabularnewline
69 & 0.00221381 & 0.00442762 & 0.997786 \tabularnewline
70 & 0.00166598 & 0.00333196 & 0.998334 \tabularnewline
71 & 0.00125639 & 0.00251277 & 0.998744 \tabularnewline
72 & 0.000928662 & 0.00185732 & 0.999071 \tabularnewline
73 & 0.000935336 & 0.00187067 & 0.999065 \tabularnewline
74 & 0.00117065 & 0.0023413 & 0.998829 \tabularnewline
75 & 0.000898632 & 0.00179726 & 0.999101 \tabularnewline
76 & 0.000718476 & 0.00143695 & 0.999282 \tabularnewline
77 & 0.000539017 & 0.00107803 & 0.999461 \tabularnewline
78 & 0.000473546 & 0.000947092 & 0.999526 \tabularnewline
79 & 0.00038094 & 0.00076188 & 0.999619 \tabularnewline
80 & 0.00050214 & 0.00100428 & 0.999498 \tabularnewline
81 & 0.000382885 & 0.00076577 & 0.999617 \tabularnewline
82 & 0.000338035 & 0.00067607 & 0.999662 \tabularnewline
83 & 0.000245178 & 0.000490356 & 0.999755 \tabularnewline
84 & 0.00151765 & 0.0030353 & 0.998482 \tabularnewline
85 & 0.00122932 & 0.00245865 & 0.998771 \tabularnewline
86 & 0.000942217 & 0.00188443 & 0.999058 \tabularnewline
87 & 0.00072709 & 0.00145418 & 0.999273 \tabularnewline
88 & 0.000544819 & 0.00108964 & 0.999455 \tabularnewline
89 & 0.000576414 & 0.00115283 & 0.999424 \tabularnewline
90 & 0.000494506 & 0.000989013 & 0.999505 \tabularnewline
91 & 0.000386398 & 0.000772796 & 0.999614 \tabularnewline
92 & 0.00121924 & 0.00243849 & 0.998781 \tabularnewline
93 & 0.00104767 & 0.00209535 & 0.998952 \tabularnewline
94 & 0.000966232 & 0.00193246 & 0.999034 \tabularnewline
95 & 0.00141602 & 0.00283204 & 0.998584 \tabularnewline
96 & 0.00144151 & 0.00288303 & 0.998558 \tabularnewline
97 & 0.00224827 & 0.00449654 & 0.997752 \tabularnewline
98 & 0.00180054 & 0.00360108 & 0.998199 \tabularnewline
99 & 0.00162409 & 0.00324819 & 0.998376 \tabularnewline
100 & 0.00212942 & 0.00425883 & 0.997871 \tabularnewline
101 & 0.0017795 & 0.00355901 & 0.99822 \tabularnewline
102 & 0.00151576 & 0.00303152 & 0.998484 \tabularnewline
103 & 0.0018073 & 0.0036146 & 0.998193 \tabularnewline
104 & 0.00171578 & 0.00343156 & 0.998284 \tabularnewline
105 & 0.00175288 & 0.00350575 & 0.998247 \tabularnewline
106 & 0.00209965 & 0.00419931 & 0.9979 \tabularnewline
107 & 0.0019459 & 0.0038918 & 0.998054 \tabularnewline
108 & 0.00782712 & 0.0156542 & 0.992173 \tabularnewline
109 & 0.0166646 & 0.0333291 & 0.983335 \tabularnewline
110 & 0.0174843 & 0.0349686 & 0.982516 \tabularnewline
111 & 0.0154793 & 0.0309587 & 0.984521 \tabularnewline
112 & 0.0140283 & 0.0280567 & 0.985972 \tabularnewline
113 & 0.068839 & 0.137678 & 0.931161 \tabularnewline
114 & 0.0621593 & 0.124319 & 0.937841 \tabularnewline
115 & 0.126102 & 0.252204 & 0.873898 \tabularnewline
116 & 0.20235 & 0.4047 & 0.79765 \tabularnewline
117 & 0.243649 & 0.487298 & 0.756351 \tabularnewline
118 & 0.227914 & 0.455829 & 0.772086 \tabularnewline
119 & 0.277659 & 0.555317 & 0.722341 \tabularnewline
120 & 0.418969 & 0.837938 & 0.581031 \tabularnewline
121 & 0.450128 & 0.900256 & 0.549872 \tabularnewline
122 & 0.430126 & 0.860252 & 0.569874 \tabularnewline
123 & 0.505666 & 0.988668 & 0.494334 \tabularnewline
124 & 0.506885 & 0.986229 & 0.493115 \tabularnewline
125 & 0.503633 & 0.992734 & 0.496367 \tabularnewline
126 & 0.480959 & 0.961917 & 0.519041 \tabularnewline
127 & 0.501851 & 0.996298 & 0.498149 \tabularnewline
128 & 0.480596 & 0.961192 & 0.519404 \tabularnewline
129 & 0.602417 & 0.795166 & 0.397583 \tabularnewline
130 & 0.58373 & 0.832541 & 0.41627 \tabularnewline
131 & 0.573968 & 0.852063 & 0.426032 \tabularnewline
132 & 0.59351 & 0.81298 & 0.40649 \tabularnewline
133 & 0.585301 & 0.829398 & 0.414699 \tabularnewline
134 & 0.574049 & 0.851902 & 0.425951 \tabularnewline
135 & 0.550743 & 0.898515 & 0.449257 \tabularnewline
136 & 0.528891 & 0.942218 & 0.471109 \tabularnewline
137 & 0.566661 & 0.866679 & 0.433339 \tabularnewline
138 & 0.608271 & 0.783457 & 0.391729 \tabularnewline
139 & 0.695659 & 0.608682 & 0.304341 \tabularnewline
140 & 0.691578 & 0.616844 & 0.308422 \tabularnewline
141 & 0.663571 & 0.672857 & 0.336429 \tabularnewline
142 & 0.716019 & 0.567961 & 0.283981 \tabularnewline
143 & 0.71187 & 0.57626 & 0.28813 \tabularnewline
144 & 0.763373 & 0.473255 & 0.236627 \tabularnewline
145 & 0.769655 & 0.46069 & 0.230345 \tabularnewline
146 & 0.786118 & 0.427764 & 0.213882 \tabularnewline
147 & 0.768079 & 0.463842 & 0.231921 \tabularnewline
148 & 0.747885 & 0.50423 & 0.252115 \tabularnewline
149 & 0.728315 & 0.54337 & 0.271685 \tabularnewline
150 & 0.766162 & 0.467676 & 0.233838 \tabularnewline
151 & 0.766679 & 0.466642 & 0.233321 \tabularnewline
152 & 0.757543 & 0.484914 & 0.242457 \tabularnewline
153 & 0.789135 & 0.421731 & 0.210865 \tabularnewline
154 & 0.79566 & 0.40868 & 0.20434 \tabularnewline
155 & 0.775663 & 0.448675 & 0.224337 \tabularnewline
156 & 0.752986 & 0.494029 & 0.247014 \tabularnewline
157 & 0.790336 & 0.419327 & 0.209664 \tabularnewline
158 & 0.783525 & 0.43295 & 0.216475 \tabularnewline
159 & 0.760802 & 0.478396 & 0.239198 \tabularnewline
160 & 0.744054 & 0.511892 & 0.255946 \tabularnewline
161 & 0.785397 & 0.429205 & 0.214603 \tabularnewline
162 & 0.778478 & 0.443045 & 0.221522 \tabularnewline
163 & 0.781002 & 0.437997 & 0.218998 \tabularnewline
164 & 0.766578 & 0.466845 & 0.233422 \tabularnewline
165 & 0.818504 & 0.362991 & 0.181496 \tabularnewline
166 & 0.803589 & 0.392823 & 0.196411 \tabularnewline
167 & 0.848651 & 0.302698 & 0.151349 \tabularnewline
168 & 0.835062 & 0.329875 & 0.164938 \tabularnewline
169 & 0.815334 & 0.369331 & 0.184666 \tabularnewline
170 & 0.803248 & 0.393503 & 0.196752 \tabularnewline
171 & 0.795183 & 0.409634 & 0.204817 \tabularnewline
172 & 0.824373 & 0.351254 & 0.175627 \tabularnewline
173 & 0.80605 & 0.3879 & 0.19395 \tabularnewline
174 & 0.787394 & 0.425213 & 0.212606 \tabularnewline
175 & 0.768718 & 0.462565 & 0.231282 \tabularnewline
176 & 0.796709 & 0.406582 & 0.203291 \tabularnewline
177 & 0.771826 & 0.456347 & 0.228174 \tabularnewline
178 & 0.830657 & 0.338685 & 0.169343 \tabularnewline
179 & 0.814999 & 0.370002 & 0.185001 \tabularnewline
180 & 0.857077 & 0.285845 & 0.142923 \tabularnewline
181 & 0.836418 & 0.327164 & 0.163582 \tabularnewline
182 & 0.8134 & 0.373199 & 0.1866 \tabularnewline
183 & 0.860817 & 0.278366 & 0.139183 \tabularnewline
184 & 0.848116 & 0.303768 & 0.151884 \tabularnewline
185 & 0.826759 & 0.346481 & 0.173241 \tabularnewline
186 & 0.815379 & 0.369243 & 0.184621 \tabularnewline
187 & 0.822023 & 0.355954 & 0.177977 \tabularnewline
188 & 0.798825 & 0.402349 & 0.201175 \tabularnewline
189 & 0.779816 & 0.440368 & 0.220184 \tabularnewline
190 & 0.75454 & 0.490921 & 0.24546 \tabularnewline
191 & 0.755647 & 0.488706 & 0.244353 \tabularnewline
192 & 0.739311 & 0.521378 & 0.260689 \tabularnewline
193 & 0.769432 & 0.461136 & 0.230568 \tabularnewline
194 & 0.79014 & 0.41972 & 0.20986 \tabularnewline
195 & 0.762252 & 0.475496 & 0.237748 \tabularnewline
196 & 0.733241 & 0.533519 & 0.266759 \tabularnewline
197 & 0.709303 & 0.581394 & 0.290697 \tabularnewline
198 & 0.67749 & 0.645019 & 0.32251 \tabularnewline
199 & 0.648217 & 0.703567 & 0.351783 \tabularnewline
200 & 0.629285 & 0.741431 & 0.370715 \tabularnewline
201 & 0.693826 & 0.612348 & 0.306174 \tabularnewline
202 & 0.659416 & 0.681168 & 0.340584 \tabularnewline
203 & 0.624421 & 0.751157 & 0.375579 \tabularnewline
204 & 0.60313 & 0.793741 & 0.39687 \tabularnewline
205 & 0.572932 & 0.854136 & 0.427068 \tabularnewline
206 & 0.539319 & 0.921362 & 0.460681 \tabularnewline
207 & 0.557071 & 0.885859 & 0.442929 \tabularnewline
208 & 0.51914 & 0.961719 & 0.48086 \tabularnewline
209 & 0.592552 & 0.814896 & 0.407448 \tabularnewline
210 & 0.589064 & 0.821872 & 0.410936 \tabularnewline
211 & 0.572582 & 0.854837 & 0.427418 \tabularnewline
212 & 0.54271 & 0.914579 & 0.45729 \tabularnewline
213 & 0.516063 & 0.967874 & 0.483937 \tabularnewline
214 & 0.479046 & 0.958092 & 0.520954 \tabularnewline
215 & 0.467286 & 0.934572 & 0.532714 \tabularnewline
216 & 0.433015 & 0.866031 & 0.566985 \tabularnewline
217 & 0.412097 & 0.824194 & 0.587903 \tabularnewline
218 & 0.441687 & 0.883374 & 0.558313 \tabularnewline
219 & 0.416966 & 0.833932 & 0.583034 \tabularnewline
220 & 0.389051 & 0.778102 & 0.610949 \tabularnewline
221 & 0.416695 & 0.83339 & 0.583305 \tabularnewline
222 & 0.494403 & 0.988805 & 0.505597 \tabularnewline
223 & 0.459684 & 0.919368 & 0.540316 \tabularnewline
224 & 0.438105 & 0.87621 & 0.561895 \tabularnewline
225 & 0.531882 & 0.936237 & 0.468118 \tabularnewline
226 & 0.50388 & 0.99224 & 0.49612 \tabularnewline
227 & 0.49841 & 0.996821 & 0.50159 \tabularnewline
228 & 0.468473 & 0.936946 & 0.531527 \tabularnewline
229 & 0.518694 & 0.962613 & 0.481306 \tabularnewline
230 & 0.609225 & 0.78155 & 0.390775 \tabularnewline
231 & 0.658999 & 0.682002 & 0.341001 \tabularnewline
232 & 0.74534 & 0.50932 & 0.25466 \tabularnewline
233 & 0.705177 & 0.589647 & 0.294823 \tabularnewline
234 & 0.66149 & 0.677021 & 0.33851 \tabularnewline
235 & 0.672238 & 0.655524 & 0.327762 \tabularnewline
236 & 0.909076 & 0.181849 & 0.0909243 \tabularnewline
237 & 0.890465 & 0.219069 & 0.109535 \tabularnewline
238 & 0.864133 & 0.271734 & 0.135867 \tabularnewline
239 & 0.857754 & 0.284493 & 0.142246 \tabularnewline
240 & 0.833415 & 0.333171 & 0.166585 \tabularnewline
241 & 0.802292 & 0.395417 & 0.197708 \tabularnewline
242 & 0.764637 & 0.470726 & 0.235363 \tabularnewline
243 & 0.723204 & 0.553592 & 0.276796 \tabularnewline
244 & 0.857828 & 0.284344 & 0.142172 \tabularnewline
245 & 0.843471 & 0.313059 & 0.156529 \tabularnewline
246 & 0.813332 & 0.373337 & 0.186668 \tabularnewline
247 & 0.829438 & 0.341123 & 0.170562 \tabularnewline
248 & 0.800168 & 0.399663 & 0.199832 \tabularnewline
249 & 0.775903 & 0.448193 & 0.224097 \tabularnewline
250 & 0.728104 & 0.543793 & 0.271896 \tabularnewline
251 & 0.68555 & 0.628899 & 0.31445 \tabularnewline
252 & 0.638503 & 0.722994 & 0.361497 \tabularnewline
253 & 0.587526 & 0.824948 & 0.412474 \tabularnewline
254 & 0.722094 & 0.555812 & 0.277906 \tabularnewline
255 & 0.796338 & 0.407324 & 0.203662 \tabularnewline
256 & 0.764457 & 0.471085 & 0.235543 \tabularnewline
257 & 0.858824 & 0.282352 & 0.141176 \tabularnewline
258 & 0.948318 & 0.103364 & 0.0516818 \tabularnewline
259 & 0.92243 & 0.15514 & 0.0775699 \tabularnewline
260 & 0.980165 & 0.0396706 & 0.0198353 \tabularnewline
261 & 0.97052 & 0.05896 & 0.02948 \tabularnewline
262 & 0.957597 & 0.0848061 & 0.0424031 \tabularnewline
263 & 0.931504 & 0.136992 & 0.0684962 \tabularnewline
264 & 0.91827 & 0.163459 & 0.0817296 \tabularnewline
265 & 0.891289 & 0.217422 & 0.108711 \tabularnewline
266 & 0.855205 & 0.289589 & 0.144795 \tabularnewline
267 & 0.77837 & 0.44326 & 0.22163 \tabularnewline
268 & 0.687185 & 0.62563 & 0.312815 \tabularnewline
269 & 0.562177 & 0.875646 & 0.437823 \tabularnewline
270 & 0.788709 & 0.422581 & 0.211291 \tabularnewline
271 & 0.654006 & 0.691988 & 0.345994 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&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]7[/C][C]0.48774[/C][C]0.97548[/C][C]0.51226[/C][/ROW]
[ROW][C]8[/C][C]0.35883[/C][C]0.717661[/C][C]0.64117[/C][/ROW]
[ROW][C]9[/C][C]0.284917[/C][C]0.569833[/C][C]0.715083[/C][/ROW]
[ROW][C]10[/C][C]0.213874[/C][C]0.427748[/C][C]0.786126[/C][/ROW]
[ROW][C]11[/C][C]0.134353[/C][C]0.268705[/C][C]0.865647[/C][/ROW]
[ROW][C]12[/C][C]0.131369[/C][C]0.262737[/C][C]0.868631[/C][/ROW]
[ROW][C]13[/C][C]0.135192[/C][C]0.270384[/C][C]0.864808[/C][/ROW]
[ROW][C]14[/C][C]0.0981041[/C][C]0.196208[/C][C]0.901896[/C][/ROW]
[ROW][C]15[/C][C]0.114751[/C][C]0.229501[/C][C]0.885249[/C][/ROW]
[ROW][C]16[/C][C]0.0869651[/C][C]0.17393[/C][C]0.913035[/C][/ROW]
[ROW][C]17[/C][C]0.0561278[/C][C]0.112256[/C][C]0.943872[/C][/ROW]
[ROW][C]18[/C][C]0.037915[/C][C]0.07583[/C][C]0.962085[/C][/ROW]
[ROW][C]19[/C][C]0.0242103[/C][C]0.0484205[/C][C]0.97579[/C][/ROW]
[ROW][C]20[/C][C]0.0145576[/C][C]0.0291151[/C][C]0.985442[/C][/ROW]
[ROW][C]21[/C][C]0.0166318[/C][C]0.0332636[/C][C]0.983368[/C][/ROW]
[ROW][C]22[/C][C]0.0226198[/C][C]0.0452397[/C][C]0.97738[/C][/ROW]
[ROW][C]23[/C][C]0.0148306[/C][C]0.0296613[/C][C]0.985169[/C][/ROW]
[ROW][C]24[/C][C]0.0195914[/C][C]0.0391828[/C][C]0.980409[/C][/ROW]
[ROW][C]25[/C][C]0.0135392[/C][C]0.0270784[/C][C]0.986461[/C][/ROW]
[ROW][C]26[/C][C]0.0084867[/C][C]0.0169734[/C][C]0.991513[/C][/ROW]
[ROW][C]27[/C][C]0.0262823[/C][C]0.0525646[/C][C]0.973718[/C][/ROW]
[ROW][C]28[/C][C]0.0179731[/C][C]0.0359463[/C][C]0.982027[/C][/ROW]
[ROW][C]29[/C][C]0.0122595[/C][C]0.0245189[/C][C]0.987741[/C][/ROW]
[ROW][C]30[/C][C]0.00791104[/C][C]0.0158221[/C][C]0.992089[/C][/ROW]
[ROW][C]31[/C][C]0.0162963[/C][C]0.0325926[/C][C]0.983704[/C][/ROW]
[ROW][C]32[/C][C]0.0110088[/C][C]0.0220176[/C][C]0.988991[/C][/ROW]
[ROW][C]33[/C][C]0.00821856[/C][C]0.0164371[/C][C]0.991781[/C][/ROW]
[ROW][C]34[/C][C]0.00675519[/C][C]0.0135104[/C][C]0.993245[/C][/ROW]
[ROW][C]35[/C][C]0.00502184[/C][C]0.0100437[/C][C]0.994978[/C][/ROW]
[ROW][C]36[/C][C]0.00335056[/C][C]0.00670111[/C][C]0.996649[/C][/ROW]
[ROW][C]37[/C][C]0.00217972[/C][C]0.00435944[/C][C]0.99782[/C][/ROW]
[ROW][C]38[/C][C]0.00136854[/C][C]0.00273707[/C][C]0.998631[/C][/ROW]
[ROW][C]39[/C][C]0.00106102[/C][C]0.00212204[/C][C]0.998939[/C][/ROW]
[ROW][C]40[/C][C]0.00068257[/C][C]0.00136514[/C][C]0.999317[/C][/ROW]
[ROW][C]41[/C][C]0.00199625[/C][C]0.00399251[/C][C]0.998004[/C][/ROW]
[ROW][C]42[/C][C]0.00145015[/C][C]0.00290029[/C][C]0.99855[/C][/ROW]
[ROW][C]43[/C][C]0.00133859[/C][C]0.00267717[/C][C]0.998661[/C][/ROW]
[ROW][C]44[/C][C]0.000901007[/C][C]0.00180201[/C][C]0.999099[/C][/ROW]
[ROW][C]45[/C][C]0.00056873[/C][C]0.00113746[/C][C]0.999431[/C][/ROW]
[ROW][C]46[/C][C]0.000449589[/C][C]0.000899178[/C][C]0.99955[/C][/ROW]
[ROW][C]47[/C][C]0.000333517[/C][C]0.000667035[/C][C]0.999666[/C][/ROW]
[ROW][C]48[/C][C]0.000317786[/C][C]0.000635572[/C][C]0.999682[/C][/ROW]
[ROW][C]49[/C][C]0.000312806[/C][C]0.000625613[/C][C]0.999687[/C][/ROW]
[ROW][C]50[/C][C]0.000237954[/C][C]0.000475907[/C][C]0.999762[/C][/ROW]
[ROW][C]51[/C][C]0.000157139[/C][C]0.000314279[/C][C]0.999843[/C][/ROW]
[ROW][C]52[/C][C]0.000585246[/C][C]0.00117049[/C][C]0.999415[/C][/ROW]
[ROW][C]53[/C][C]0.000395345[/C][C]0.00079069[/C][C]0.999605[/C][/ROW]
[ROW][C]54[/C][C]0.000319374[/C][C]0.000638748[/C][C]0.999681[/C][/ROW]
[ROW][C]55[/C][C]0.000379546[/C][C]0.000759091[/C][C]0.99962[/C][/ROW]
[ROW][C]56[/C][C]0.000262458[/C][C]0.000524915[/C][C]0.999738[/C][/ROW]
[ROW][C]57[/C][C]0.00142712[/C][C]0.00285424[/C][C]0.998573[/C][/ROW]
[ROW][C]58[/C][C]0.00111597[/C][C]0.00223193[/C][C]0.998884[/C][/ROW]
[ROW][C]59[/C][C]0.00119679[/C][C]0.00239357[/C][C]0.998803[/C][/ROW]
[ROW][C]60[/C][C]0.001164[/C][C]0.00232799[/C][C]0.998836[/C][/ROW]
[ROW][C]61[/C][C]0.000939083[/C][C]0.00187817[/C][C]0.999061[/C][/ROW]
[ROW][C]62[/C][C]0.000771462[/C][C]0.00154292[/C][C]0.999229[/C][/ROW]
[ROW][C]63[/C][C]0.00169119[/C][C]0.00338238[/C][C]0.998309[/C][/ROW]
[ROW][C]64[/C][C]0.00331995[/C][C]0.0066399[/C][C]0.99668[/C][/ROW]
[ROW][C]65[/C][C]0.00301893[/C][C]0.00603786[/C][C]0.996981[/C][/ROW]
[ROW][C]66[/C][C]0.00288921[/C][C]0.00577841[/C][C]0.997111[/C][/ROW]
[ROW][C]67[/C][C]0.00216801[/C][C]0.00433601[/C][C]0.997832[/C][/ROW]
[ROW][C]68[/C][C]0.00192212[/C][C]0.00384425[/C][C]0.998078[/C][/ROW]
[ROW][C]69[/C][C]0.00221381[/C][C]0.00442762[/C][C]0.997786[/C][/ROW]
[ROW][C]70[/C][C]0.00166598[/C][C]0.00333196[/C][C]0.998334[/C][/ROW]
[ROW][C]71[/C][C]0.00125639[/C][C]0.00251277[/C][C]0.998744[/C][/ROW]
[ROW][C]72[/C][C]0.000928662[/C][C]0.00185732[/C][C]0.999071[/C][/ROW]
[ROW][C]73[/C][C]0.000935336[/C][C]0.00187067[/C][C]0.999065[/C][/ROW]
[ROW][C]74[/C][C]0.00117065[/C][C]0.0023413[/C][C]0.998829[/C][/ROW]
[ROW][C]75[/C][C]0.000898632[/C][C]0.00179726[/C][C]0.999101[/C][/ROW]
[ROW][C]76[/C][C]0.000718476[/C][C]0.00143695[/C][C]0.999282[/C][/ROW]
[ROW][C]77[/C][C]0.000539017[/C][C]0.00107803[/C][C]0.999461[/C][/ROW]
[ROW][C]78[/C][C]0.000473546[/C][C]0.000947092[/C][C]0.999526[/C][/ROW]
[ROW][C]79[/C][C]0.00038094[/C][C]0.00076188[/C][C]0.999619[/C][/ROW]
[ROW][C]80[/C][C]0.00050214[/C][C]0.00100428[/C][C]0.999498[/C][/ROW]
[ROW][C]81[/C][C]0.000382885[/C][C]0.00076577[/C][C]0.999617[/C][/ROW]
[ROW][C]82[/C][C]0.000338035[/C][C]0.00067607[/C][C]0.999662[/C][/ROW]
[ROW][C]83[/C][C]0.000245178[/C][C]0.000490356[/C][C]0.999755[/C][/ROW]
[ROW][C]84[/C][C]0.00151765[/C][C]0.0030353[/C][C]0.998482[/C][/ROW]
[ROW][C]85[/C][C]0.00122932[/C][C]0.00245865[/C][C]0.998771[/C][/ROW]
[ROW][C]86[/C][C]0.000942217[/C][C]0.00188443[/C][C]0.999058[/C][/ROW]
[ROW][C]87[/C][C]0.00072709[/C][C]0.00145418[/C][C]0.999273[/C][/ROW]
[ROW][C]88[/C][C]0.000544819[/C][C]0.00108964[/C][C]0.999455[/C][/ROW]
[ROW][C]89[/C][C]0.000576414[/C][C]0.00115283[/C][C]0.999424[/C][/ROW]
[ROW][C]90[/C][C]0.000494506[/C][C]0.000989013[/C][C]0.999505[/C][/ROW]
[ROW][C]91[/C][C]0.000386398[/C][C]0.000772796[/C][C]0.999614[/C][/ROW]
[ROW][C]92[/C][C]0.00121924[/C][C]0.00243849[/C][C]0.998781[/C][/ROW]
[ROW][C]93[/C][C]0.00104767[/C][C]0.00209535[/C][C]0.998952[/C][/ROW]
[ROW][C]94[/C][C]0.000966232[/C][C]0.00193246[/C][C]0.999034[/C][/ROW]
[ROW][C]95[/C][C]0.00141602[/C][C]0.00283204[/C][C]0.998584[/C][/ROW]
[ROW][C]96[/C][C]0.00144151[/C][C]0.00288303[/C][C]0.998558[/C][/ROW]
[ROW][C]97[/C][C]0.00224827[/C][C]0.00449654[/C][C]0.997752[/C][/ROW]
[ROW][C]98[/C][C]0.00180054[/C][C]0.00360108[/C][C]0.998199[/C][/ROW]
[ROW][C]99[/C][C]0.00162409[/C][C]0.00324819[/C][C]0.998376[/C][/ROW]
[ROW][C]100[/C][C]0.00212942[/C][C]0.00425883[/C][C]0.997871[/C][/ROW]
[ROW][C]101[/C][C]0.0017795[/C][C]0.00355901[/C][C]0.99822[/C][/ROW]
[ROW][C]102[/C][C]0.00151576[/C][C]0.00303152[/C][C]0.998484[/C][/ROW]
[ROW][C]103[/C][C]0.0018073[/C][C]0.0036146[/C][C]0.998193[/C][/ROW]
[ROW][C]104[/C][C]0.00171578[/C][C]0.00343156[/C][C]0.998284[/C][/ROW]
[ROW][C]105[/C][C]0.00175288[/C][C]0.00350575[/C][C]0.998247[/C][/ROW]
[ROW][C]106[/C][C]0.00209965[/C][C]0.00419931[/C][C]0.9979[/C][/ROW]
[ROW][C]107[/C][C]0.0019459[/C][C]0.0038918[/C][C]0.998054[/C][/ROW]
[ROW][C]108[/C][C]0.00782712[/C][C]0.0156542[/C][C]0.992173[/C][/ROW]
[ROW][C]109[/C][C]0.0166646[/C][C]0.0333291[/C][C]0.983335[/C][/ROW]
[ROW][C]110[/C][C]0.0174843[/C][C]0.0349686[/C][C]0.982516[/C][/ROW]
[ROW][C]111[/C][C]0.0154793[/C][C]0.0309587[/C][C]0.984521[/C][/ROW]
[ROW][C]112[/C][C]0.0140283[/C][C]0.0280567[/C][C]0.985972[/C][/ROW]
[ROW][C]113[/C][C]0.068839[/C][C]0.137678[/C][C]0.931161[/C][/ROW]
[ROW][C]114[/C][C]0.0621593[/C][C]0.124319[/C][C]0.937841[/C][/ROW]
[ROW][C]115[/C][C]0.126102[/C][C]0.252204[/C][C]0.873898[/C][/ROW]
[ROW][C]116[/C][C]0.20235[/C][C]0.4047[/C][C]0.79765[/C][/ROW]
[ROW][C]117[/C][C]0.243649[/C][C]0.487298[/C][C]0.756351[/C][/ROW]
[ROW][C]118[/C][C]0.227914[/C][C]0.455829[/C][C]0.772086[/C][/ROW]
[ROW][C]119[/C][C]0.277659[/C][C]0.555317[/C][C]0.722341[/C][/ROW]
[ROW][C]120[/C][C]0.418969[/C][C]0.837938[/C][C]0.581031[/C][/ROW]
[ROW][C]121[/C][C]0.450128[/C][C]0.900256[/C][C]0.549872[/C][/ROW]
[ROW][C]122[/C][C]0.430126[/C][C]0.860252[/C][C]0.569874[/C][/ROW]
[ROW][C]123[/C][C]0.505666[/C][C]0.988668[/C][C]0.494334[/C][/ROW]
[ROW][C]124[/C][C]0.506885[/C][C]0.986229[/C][C]0.493115[/C][/ROW]
[ROW][C]125[/C][C]0.503633[/C][C]0.992734[/C][C]0.496367[/C][/ROW]
[ROW][C]126[/C][C]0.480959[/C][C]0.961917[/C][C]0.519041[/C][/ROW]
[ROW][C]127[/C][C]0.501851[/C][C]0.996298[/C][C]0.498149[/C][/ROW]
[ROW][C]128[/C][C]0.480596[/C][C]0.961192[/C][C]0.519404[/C][/ROW]
[ROW][C]129[/C][C]0.602417[/C][C]0.795166[/C][C]0.397583[/C][/ROW]
[ROW][C]130[/C][C]0.58373[/C][C]0.832541[/C][C]0.41627[/C][/ROW]
[ROW][C]131[/C][C]0.573968[/C][C]0.852063[/C][C]0.426032[/C][/ROW]
[ROW][C]132[/C][C]0.59351[/C][C]0.81298[/C][C]0.40649[/C][/ROW]
[ROW][C]133[/C][C]0.585301[/C][C]0.829398[/C][C]0.414699[/C][/ROW]
[ROW][C]134[/C][C]0.574049[/C][C]0.851902[/C][C]0.425951[/C][/ROW]
[ROW][C]135[/C][C]0.550743[/C][C]0.898515[/C][C]0.449257[/C][/ROW]
[ROW][C]136[/C][C]0.528891[/C][C]0.942218[/C][C]0.471109[/C][/ROW]
[ROW][C]137[/C][C]0.566661[/C][C]0.866679[/C][C]0.433339[/C][/ROW]
[ROW][C]138[/C][C]0.608271[/C][C]0.783457[/C][C]0.391729[/C][/ROW]
[ROW][C]139[/C][C]0.695659[/C][C]0.608682[/C][C]0.304341[/C][/ROW]
[ROW][C]140[/C][C]0.691578[/C][C]0.616844[/C][C]0.308422[/C][/ROW]
[ROW][C]141[/C][C]0.663571[/C][C]0.672857[/C][C]0.336429[/C][/ROW]
[ROW][C]142[/C][C]0.716019[/C][C]0.567961[/C][C]0.283981[/C][/ROW]
[ROW][C]143[/C][C]0.71187[/C][C]0.57626[/C][C]0.28813[/C][/ROW]
[ROW][C]144[/C][C]0.763373[/C][C]0.473255[/C][C]0.236627[/C][/ROW]
[ROW][C]145[/C][C]0.769655[/C][C]0.46069[/C][C]0.230345[/C][/ROW]
[ROW][C]146[/C][C]0.786118[/C][C]0.427764[/C][C]0.213882[/C][/ROW]
[ROW][C]147[/C][C]0.768079[/C][C]0.463842[/C][C]0.231921[/C][/ROW]
[ROW][C]148[/C][C]0.747885[/C][C]0.50423[/C][C]0.252115[/C][/ROW]
[ROW][C]149[/C][C]0.728315[/C][C]0.54337[/C][C]0.271685[/C][/ROW]
[ROW][C]150[/C][C]0.766162[/C][C]0.467676[/C][C]0.233838[/C][/ROW]
[ROW][C]151[/C][C]0.766679[/C][C]0.466642[/C][C]0.233321[/C][/ROW]
[ROW][C]152[/C][C]0.757543[/C][C]0.484914[/C][C]0.242457[/C][/ROW]
[ROW][C]153[/C][C]0.789135[/C][C]0.421731[/C][C]0.210865[/C][/ROW]
[ROW][C]154[/C][C]0.79566[/C][C]0.40868[/C][C]0.20434[/C][/ROW]
[ROW][C]155[/C][C]0.775663[/C][C]0.448675[/C][C]0.224337[/C][/ROW]
[ROW][C]156[/C][C]0.752986[/C][C]0.494029[/C][C]0.247014[/C][/ROW]
[ROW][C]157[/C][C]0.790336[/C][C]0.419327[/C][C]0.209664[/C][/ROW]
[ROW][C]158[/C][C]0.783525[/C][C]0.43295[/C][C]0.216475[/C][/ROW]
[ROW][C]159[/C][C]0.760802[/C][C]0.478396[/C][C]0.239198[/C][/ROW]
[ROW][C]160[/C][C]0.744054[/C][C]0.511892[/C][C]0.255946[/C][/ROW]
[ROW][C]161[/C][C]0.785397[/C][C]0.429205[/C][C]0.214603[/C][/ROW]
[ROW][C]162[/C][C]0.778478[/C][C]0.443045[/C][C]0.221522[/C][/ROW]
[ROW][C]163[/C][C]0.781002[/C][C]0.437997[/C][C]0.218998[/C][/ROW]
[ROW][C]164[/C][C]0.766578[/C][C]0.466845[/C][C]0.233422[/C][/ROW]
[ROW][C]165[/C][C]0.818504[/C][C]0.362991[/C][C]0.181496[/C][/ROW]
[ROW][C]166[/C][C]0.803589[/C][C]0.392823[/C][C]0.196411[/C][/ROW]
[ROW][C]167[/C][C]0.848651[/C][C]0.302698[/C][C]0.151349[/C][/ROW]
[ROW][C]168[/C][C]0.835062[/C][C]0.329875[/C][C]0.164938[/C][/ROW]
[ROW][C]169[/C][C]0.815334[/C][C]0.369331[/C][C]0.184666[/C][/ROW]
[ROW][C]170[/C][C]0.803248[/C][C]0.393503[/C][C]0.196752[/C][/ROW]
[ROW][C]171[/C][C]0.795183[/C][C]0.409634[/C][C]0.204817[/C][/ROW]
[ROW][C]172[/C][C]0.824373[/C][C]0.351254[/C][C]0.175627[/C][/ROW]
[ROW][C]173[/C][C]0.80605[/C][C]0.3879[/C][C]0.19395[/C][/ROW]
[ROW][C]174[/C][C]0.787394[/C][C]0.425213[/C][C]0.212606[/C][/ROW]
[ROW][C]175[/C][C]0.768718[/C][C]0.462565[/C][C]0.231282[/C][/ROW]
[ROW][C]176[/C][C]0.796709[/C][C]0.406582[/C][C]0.203291[/C][/ROW]
[ROW][C]177[/C][C]0.771826[/C][C]0.456347[/C][C]0.228174[/C][/ROW]
[ROW][C]178[/C][C]0.830657[/C][C]0.338685[/C][C]0.169343[/C][/ROW]
[ROW][C]179[/C][C]0.814999[/C][C]0.370002[/C][C]0.185001[/C][/ROW]
[ROW][C]180[/C][C]0.857077[/C][C]0.285845[/C][C]0.142923[/C][/ROW]
[ROW][C]181[/C][C]0.836418[/C][C]0.327164[/C][C]0.163582[/C][/ROW]
[ROW][C]182[/C][C]0.8134[/C][C]0.373199[/C][C]0.1866[/C][/ROW]
[ROW][C]183[/C][C]0.860817[/C][C]0.278366[/C][C]0.139183[/C][/ROW]
[ROW][C]184[/C][C]0.848116[/C][C]0.303768[/C][C]0.151884[/C][/ROW]
[ROW][C]185[/C][C]0.826759[/C][C]0.346481[/C][C]0.173241[/C][/ROW]
[ROW][C]186[/C][C]0.815379[/C][C]0.369243[/C][C]0.184621[/C][/ROW]
[ROW][C]187[/C][C]0.822023[/C][C]0.355954[/C][C]0.177977[/C][/ROW]
[ROW][C]188[/C][C]0.798825[/C][C]0.402349[/C][C]0.201175[/C][/ROW]
[ROW][C]189[/C][C]0.779816[/C][C]0.440368[/C][C]0.220184[/C][/ROW]
[ROW][C]190[/C][C]0.75454[/C][C]0.490921[/C][C]0.24546[/C][/ROW]
[ROW][C]191[/C][C]0.755647[/C][C]0.488706[/C][C]0.244353[/C][/ROW]
[ROW][C]192[/C][C]0.739311[/C][C]0.521378[/C][C]0.260689[/C][/ROW]
[ROW][C]193[/C][C]0.769432[/C][C]0.461136[/C][C]0.230568[/C][/ROW]
[ROW][C]194[/C][C]0.79014[/C][C]0.41972[/C][C]0.20986[/C][/ROW]
[ROW][C]195[/C][C]0.762252[/C][C]0.475496[/C][C]0.237748[/C][/ROW]
[ROW][C]196[/C][C]0.733241[/C][C]0.533519[/C][C]0.266759[/C][/ROW]
[ROW][C]197[/C][C]0.709303[/C][C]0.581394[/C][C]0.290697[/C][/ROW]
[ROW][C]198[/C][C]0.67749[/C][C]0.645019[/C][C]0.32251[/C][/ROW]
[ROW][C]199[/C][C]0.648217[/C][C]0.703567[/C][C]0.351783[/C][/ROW]
[ROW][C]200[/C][C]0.629285[/C][C]0.741431[/C][C]0.370715[/C][/ROW]
[ROW][C]201[/C][C]0.693826[/C][C]0.612348[/C][C]0.306174[/C][/ROW]
[ROW][C]202[/C][C]0.659416[/C][C]0.681168[/C][C]0.340584[/C][/ROW]
[ROW][C]203[/C][C]0.624421[/C][C]0.751157[/C][C]0.375579[/C][/ROW]
[ROW][C]204[/C][C]0.60313[/C][C]0.793741[/C][C]0.39687[/C][/ROW]
[ROW][C]205[/C][C]0.572932[/C][C]0.854136[/C][C]0.427068[/C][/ROW]
[ROW][C]206[/C][C]0.539319[/C][C]0.921362[/C][C]0.460681[/C][/ROW]
[ROW][C]207[/C][C]0.557071[/C][C]0.885859[/C][C]0.442929[/C][/ROW]
[ROW][C]208[/C][C]0.51914[/C][C]0.961719[/C][C]0.48086[/C][/ROW]
[ROW][C]209[/C][C]0.592552[/C][C]0.814896[/C][C]0.407448[/C][/ROW]
[ROW][C]210[/C][C]0.589064[/C][C]0.821872[/C][C]0.410936[/C][/ROW]
[ROW][C]211[/C][C]0.572582[/C][C]0.854837[/C][C]0.427418[/C][/ROW]
[ROW][C]212[/C][C]0.54271[/C][C]0.914579[/C][C]0.45729[/C][/ROW]
[ROW][C]213[/C][C]0.516063[/C][C]0.967874[/C][C]0.483937[/C][/ROW]
[ROW][C]214[/C][C]0.479046[/C][C]0.958092[/C][C]0.520954[/C][/ROW]
[ROW][C]215[/C][C]0.467286[/C][C]0.934572[/C][C]0.532714[/C][/ROW]
[ROW][C]216[/C][C]0.433015[/C][C]0.866031[/C][C]0.566985[/C][/ROW]
[ROW][C]217[/C][C]0.412097[/C][C]0.824194[/C][C]0.587903[/C][/ROW]
[ROW][C]218[/C][C]0.441687[/C][C]0.883374[/C][C]0.558313[/C][/ROW]
[ROW][C]219[/C][C]0.416966[/C][C]0.833932[/C][C]0.583034[/C][/ROW]
[ROW][C]220[/C][C]0.389051[/C][C]0.778102[/C][C]0.610949[/C][/ROW]
[ROW][C]221[/C][C]0.416695[/C][C]0.83339[/C][C]0.583305[/C][/ROW]
[ROW][C]222[/C][C]0.494403[/C][C]0.988805[/C][C]0.505597[/C][/ROW]
[ROW][C]223[/C][C]0.459684[/C][C]0.919368[/C][C]0.540316[/C][/ROW]
[ROW][C]224[/C][C]0.438105[/C][C]0.87621[/C][C]0.561895[/C][/ROW]
[ROW][C]225[/C][C]0.531882[/C][C]0.936237[/C][C]0.468118[/C][/ROW]
[ROW][C]226[/C][C]0.50388[/C][C]0.99224[/C][C]0.49612[/C][/ROW]
[ROW][C]227[/C][C]0.49841[/C][C]0.996821[/C][C]0.50159[/C][/ROW]
[ROW][C]228[/C][C]0.468473[/C][C]0.936946[/C][C]0.531527[/C][/ROW]
[ROW][C]229[/C][C]0.518694[/C][C]0.962613[/C][C]0.481306[/C][/ROW]
[ROW][C]230[/C][C]0.609225[/C][C]0.78155[/C][C]0.390775[/C][/ROW]
[ROW][C]231[/C][C]0.658999[/C][C]0.682002[/C][C]0.341001[/C][/ROW]
[ROW][C]232[/C][C]0.74534[/C][C]0.50932[/C][C]0.25466[/C][/ROW]
[ROW][C]233[/C][C]0.705177[/C][C]0.589647[/C][C]0.294823[/C][/ROW]
[ROW][C]234[/C][C]0.66149[/C][C]0.677021[/C][C]0.33851[/C][/ROW]
[ROW][C]235[/C][C]0.672238[/C][C]0.655524[/C][C]0.327762[/C][/ROW]
[ROW][C]236[/C][C]0.909076[/C][C]0.181849[/C][C]0.0909243[/C][/ROW]
[ROW][C]237[/C][C]0.890465[/C][C]0.219069[/C][C]0.109535[/C][/ROW]
[ROW][C]238[/C][C]0.864133[/C][C]0.271734[/C][C]0.135867[/C][/ROW]
[ROW][C]239[/C][C]0.857754[/C][C]0.284493[/C][C]0.142246[/C][/ROW]
[ROW][C]240[/C][C]0.833415[/C][C]0.333171[/C][C]0.166585[/C][/ROW]
[ROW][C]241[/C][C]0.802292[/C][C]0.395417[/C][C]0.197708[/C][/ROW]
[ROW][C]242[/C][C]0.764637[/C][C]0.470726[/C][C]0.235363[/C][/ROW]
[ROW][C]243[/C][C]0.723204[/C][C]0.553592[/C][C]0.276796[/C][/ROW]
[ROW][C]244[/C][C]0.857828[/C][C]0.284344[/C][C]0.142172[/C][/ROW]
[ROW][C]245[/C][C]0.843471[/C][C]0.313059[/C][C]0.156529[/C][/ROW]
[ROW][C]246[/C][C]0.813332[/C][C]0.373337[/C][C]0.186668[/C][/ROW]
[ROW][C]247[/C][C]0.829438[/C][C]0.341123[/C][C]0.170562[/C][/ROW]
[ROW][C]248[/C][C]0.800168[/C][C]0.399663[/C][C]0.199832[/C][/ROW]
[ROW][C]249[/C][C]0.775903[/C][C]0.448193[/C][C]0.224097[/C][/ROW]
[ROW][C]250[/C][C]0.728104[/C][C]0.543793[/C][C]0.271896[/C][/ROW]
[ROW][C]251[/C][C]0.68555[/C][C]0.628899[/C][C]0.31445[/C][/ROW]
[ROW][C]252[/C][C]0.638503[/C][C]0.722994[/C][C]0.361497[/C][/ROW]
[ROW][C]253[/C][C]0.587526[/C][C]0.824948[/C][C]0.412474[/C][/ROW]
[ROW][C]254[/C][C]0.722094[/C][C]0.555812[/C][C]0.277906[/C][/ROW]
[ROW][C]255[/C][C]0.796338[/C][C]0.407324[/C][C]0.203662[/C][/ROW]
[ROW][C]256[/C][C]0.764457[/C][C]0.471085[/C][C]0.235543[/C][/ROW]
[ROW][C]257[/C][C]0.858824[/C][C]0.282352[/C][C]0.141176[/C][/ROW]
[ROW][C]258[/C][C]0.948318[/C][C]0.103364[/C][C]0.0516818[/C][/ROW]
[ROW][C]259[/C][C]0.92243[/C][C]0.15514[/C][C]0.0775699[/C][/ROW]
[ROW][C]260[/C][C]0.980165[/C][C]0.0396706[/C][C]0.0198353[/C][/ROW]
[ROW][C]261[/C][C]0.97052[/C][C]0.05896[/C][C]0.02948[/C][/ROW]
[ROW][C]262[/C][C]0.957597[/C][C]0.0848061[/C][C]0.0424031[/C][/ROW]
[ROW][C]263[/C][C]0.931504[/C][C]0.136992[/C][C]0.0684962[/C][/ROW]
[ROW][C]264[/C][C]0.91827[/C][C]0.163459[/C][C]0.0817296[/C][/ROW]
[ROW][C]265[/C][C]0.891289[/C][C]0.217422[/C][C]0.108711[/C][/ROW]
[ROW][C]266[/C][C]0.855205[/C][C]0.289589[/C][C]0.144795[/C][/ROW]
[ROW][C]267[/C][C]0.77837[/C][C]0.44326[/C][C]0.22163[/C][/ROW]
[ROW][C]268[/C][C]0.687185[/C][C]0.62563[/C][C]0.312815[/C][/ROW]
[ROW][C]269[/C][C]0.562177[/C][C]0.875646[/C][C]0.437823[/C][/ROW]
[ROW][C]270[/C][C]0.788709[/C][C]0.422581[/C][C]0.211291[/C][/ROW]
[ROW][C]271[/C][C]0.654006[/C][C]0.691988[/C][C]0.345994[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&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
70.487740.975480.51226
80.358830.7176610.64117
90.2849170.5698330.715083
100.2138740.4277480.786126
110.1343530.2687050.865647
120.1313690.2627370.868631
130.1351920.2703840.864808
140.09810410.1962080.901896
150.1147510.2295010.885249
160.08696510.173930.913035
170.05612780.1122560.943872
180.0379150.075830.962085
190.02421030.04842050.97579
200.01455760.02911510.985442
210.01663180.03326360.983368
220.02261980.04523970.97738
230.01483060.02966130.985169
240.01959140.03918280.980409
250.01353920.02707840.986461
260.00848670.01697340.991513
270.02628230.05256460.973718
280.01797310.03594630.982027
290.01225950.02451890.987741
300.007911040.01582210.992089
310.01629630.03259260.983704
320.01100880.02201760.988991
330.008218560.01643710.991781
340.006755190.01351040.993245
350.005021840.01004370.994978
360.003350560.006701110.996649
370.002179720.004359440.99782
380.001368540.002737070.998631
390.001061020.002122040.998939
400.000682570.001365140.999317
410.001996250.003992510.998004
420.001450150.002900290.99855
430.001338590.002677170.998661
440.0009010070.001802010.999099
450.000568730.001137460.999431
460.0004495890.0008991780.99955
470.0003335170.0006670350.999666
480.0003177860.0006355720.999682
490.0003128060.0006256130.999687
500.0002379540.0004759070.999762
510.0001571390.0003142790.999843
520.0005852460.001170490.999415
530.0003953450.000790690.999605
540.0003193740.0006387480.999681
550.0003795460.0007590910.99962
560.0002624580.0005249150.999738
570.001427120.002854240.998573
580.001115970.002231930.998884
590.001196790.002393570.998803
600.0011640.002327990.998836
610.0009390830.001878170.999061
620.0007714620.001542920.999229
630.001691190.003382380.998309
640.003319950.00663990.99668
650.003018930.006037860.996981
660.002889210.005778410.997111
670.002168010.004336010.997832
680.001922120.003844250.998078
690.002213810.004427620.997786
700.001665980.003331960.998334
710.001256390.002512770.998744
720.0009286620.001857320.999071
730.0009353360.001870670.999065
740.001170650.00234130.998829
750.0008986320.001797260.999101
760.0007184760.001436950.999282
770.0005390170.001078030.999461
780.0004735460.0009470920.999526
790.000380940.000761880.999619
800.000502140.001004280.999498
810.0003828850.000765770.999617
820.0003380350.000676070.999662
830.0002451780.0004903560.999755
840.001517650.00303530.998482
850.001229320.002458650.998771
860.0009422170.001884430.999058
870.000727090.001454180.999273
880.0005448190.001089640.999455
890.0005764140.001152830.999424
900.0004945060.0009890130.999505
910.0003863980.0007727960.999614
920.001219240.002438490.998781
930.001047670.002095350.998952
940.0009662320.001932460.999034
950.001416020.002832040.998584
960.001441510.002883030.998558
970.002248270.004496540.997752
980.001800540.003601080.998199
990.001624090.003248190.998376
1000.002129420.004258830.997871
1010.00177950.003559010.99822
1020.001515760.003031520.998484
1030.00180730.00361460.998193
1040.001715780.003431560.998284
1050.001752880.003505750.998247
1060.002099650.004199310.9979
1070.00194590.00389180.998054
1080.007827120.01565420.992173
1090.01666460.03332910.983335
1100.01748430.03496860.982516
1110.01547930.03095870.984521
1120.01402830.02805670.985972
1130.0688390.1376780.931161
1140.06215930.1243190.937841
1150.1261020.2522040.873898
1160.202350.40470.79765
1170.2436490.4872980.756351
1180.2279140.4558290.772086
1190.2776590.5553170.722341
1200.4189690.8379380.581031
1210.4501280.9002560.549872
1220.4301260.8602520.569874
1230.5056660.9886680.494334
1240.5068850.9862290.493115
1250.5036330.9927340.496367
1260.4809590.9619170.519041
1270.5018510.9962980.498149
1280.4805960.9611920.519404
1290.6024170.7951660.397583
1300.583730.8325410.41627
1310.5739680.8520630.426032
1320.593510.812980.40649
1330.5853010.8293980.414699
1340.5740490.8519020.425951
1350.5507430.8985150.449257
1360.5288910.9422180.471109
1370.5666610.8666790.433339
1380.6082710.7834570.391729
1390.6956590.6086820.304341
1400.6915780.6168440.308422
1410.6635710.6728570.336429
1420.7160190.5679610.283981
1430.711870.576260.28813
1440.7633730.4732550.236627
1450.7696550.460690.230345
1460.7861180.4277640.213882
1470.7680790.4638420.231921
1480.7478850.504230.252115
1490.7283150.543370.271685
1500.7661620.4676760.233838
1510.7666790.4666420.233321
1520.7575430.4849140.242457
1530.7891350.4217310.210865
1540.795660.408680.20434
1550.7756630.4486750.224337
1560.7529860.4940290.247014
1570.7903360.4193270.209664
1580.7835250.432950.216475
1590.7608020.4783960.239198
1600.7440540.5118920.255946
1610.7853970.4292050.214603
1620.7784780.4430450.221522
1630.7810020.4379970.218998
1640.7665780.4668450.233422
1650.8185040.3629910.181496
1660.8035890.3928230.196411
1670.8486510.3026980.151349
1680.8350620.3298750.164938
1690.8153340.3693310.184666
1700.8032480.3935030.196752
1710.7951830.4096340.204817
1720.8243730.3512540.175627
1730.806050.38790.19395
1740.7873940.4252130.212606
1750.7687180.4625650.231282
1760.7967090.4065820.203291
1770.7718260.4563470.228174
1780.8306570.3386850.169343
1790.8149990.3700020.185001
1800.8570770.2858450.142923
1810.8364180.3271640.163582
1820.81340.3731990.1866
1830.8608170.2783660.139183
1840.8481160.3037680.151884
1850.8267590.3464810.173241
1860.8153790.3692430.184621
1870.8220230.3559540.177977
1880.7988250.4023490.201175
1890.7798160.4403680.220184
1900.754540.4909210.24546
1910.7556470.4887060.244353
1920.7393110.5213780.260689
1930.7694320.4611360.230568
1940.790140.419720.20986
1950.7622520.4754960.237748
1960.7332410.5335190.266759
1970.7093030.5813940.290697
1980.677490.6450190.32251
1990.6482170.7035670.351783
2000.6292850.7414310.370715
2010.6938260.6123480.306174
2020.6594160.6811680.340584
2030.6244210.7511570.375579
2040.603130.7937410.39687
2050.5729320.8541360.427068
2060.5393190.9213620.460681
2070.5570710.8858590.442929
2080.519140.9617190.48086
2090.5925520.8148960.407448
2100.5890640.8218720.410936
2110.5725820.8548370.427418
2120.542710.9145790.45729
2130.5160630.9678740.483937
2140.4790460.9580920.520954
2150.4672860.9345720.532714
2160.4330150.8660310.566985
2170.4120970.8241940.587903
2180.4416870.8833740.558313
2190.4169660.8339320.583034
2200.3890510.7781020.610949
2210.4166950.833390.583305
2220.4944030.9888050.505597
2230.4596840.9193680.540316
2240.4381050.876210.561895
2250.5318820.9362370.468118
2260.503880.992240.49612
2270.498410.9968210.50159
2280.4684730.9369460.531527
2290.5186940.9626130.481306
2300.6092250.781550.390775
2310.6589990.6820020.341001
2320.745340.509320.25466
2330.7051770.5896470.294823
2340.661490.6770210.33851
2350.6722380.6555240.327762
2360.9090760.1818490.0909243
2370.8904650.2190690.109535
2380.8641330.2717340.135867
2390.8577540.2844930.142246
2400.8334150.3331710.166585
2410.8022920.3954170.197708
2420.7646370.4707260.235363
2430.7232040.5535920.276796
2440.8578280.2843440.142172
2450.8434710.3130590.156529
2460.8133320.3733370.186668
2470.8294380.3411230.170562
2480.8001680.3996630.199832
2490.7759030.4481930.224097
2500.7281040.5437930.271896
2510.685550.6288990.31445
2520.6385030.7229940.361497
2530.5875260.8249480.412474
2540.7220940.5558120.277906
2550.7963380.4073240.203662
2560.7644570.4710850.235543
2570.8588240.2823520.141176
2580.9483180.1033640.0516818
2590.922430.155140.0775699
2600.9801650.03967060.0198353
2610.970520.058960.02948
2620.9575970.08480610.0424031
2630.9315040.1369920.0684962
2640.918270.1634590.0817296
2650.8912890.2174220.108711
2660.8552050.2895890.144795
2670.778370.443260.22163
2680.6871850.625630.312815
2690.5621770.8756460.437823
2700.7887090.4225810.211291
2710.6540060.6919880.345994






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level720.271698NOK
5% type I error level940.354717NOK
10% type I error level980.369811NOK

\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 & 72 & 0.271698 & NOK \tabularnewline
5% type I error level & 94 & 0.354717 & NOK \tabularnewline
10% type I error level & 98 & 0.369811 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268766&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]72[/C][C]0.271698[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]94[/C][C]0.354717[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]98[/C][C]0.369811[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268766&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268766&T=6

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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 level720.271698NOK
5% type I error level940.354717NOK
10% type I error level980.369811NOK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
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')
}