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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 computationSat, 06 Dec 2014 22:25:54 +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/06/t1417904772fvinbj4101499qf.htm/, Retrieved Thu, 16 May 2024 12:58:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263679, Retrieved Thu, 16 May 2024 12:58:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact59

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Survey Scores] [Intrinsic Motivat...] [2010-10-12 11:18:40] [b98453cac15ba1066b407e146608df68]
- R PD  [Survey Scores] [] [2011-10-18 12:18:26] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [paper multiple re...] [2014-12-06 22:16:48] [e3727f74ca0896859afbe865e40a3465]
- R           [Multiple Regression] [paper multiple re...] [2014-12-06 22:25:54] [0026b73e132800f62819443873ccc691] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 0 1 0 26 50 4 21 68
7.4 0 1 0 51 68 9 26 55
12.2 0 1 1 57 62 4 22 39
12.8 0 1 0 37 54 5 22 32
7.4 0 1 1 67 71 4 18 62
6.7 0 1 1 43 54 4 23 33
12.6 0 1 1 52 65 9 12 52
14.8 0 1 0 52 73 8 20 62
13.3 0 1 1 43 52 11 22 77
11.1 0 1 1 84 84 4 21 76
8.2 0 1 1 67 42 4 19 41
11.4 0 1 1 49 66 6 22 48
6.4 0 1 1 70 65 4 15 63
10.6 0 1 1 52 78 8 20 30
12 0 1 0 58 73 4 19 78
6.3 0 1 0 68 75 4 18 19
11.3 0 0 0 62 72 11 15 31
11.9 0 1 1 43 66 4 20 66
9.3 0 1 0 56 70 4 21 35
9.6 0 0 1 56 61 6 21 42
10 0 1 0 74 81 6 15 45
6.4 0 1 1 65 71 4 16 21
13.8 0 1 1 63 69 8 23 25
10.8 0 1 0 58 71 5 21 44
13.8 0 1 1 57 72 4 18 69
11.7 0 1 1 63 68 9 25 54
10.9 0 1 1 53 70 4 9 74
16.1 0 0 1 57 68 7 30 80
13.4 0 0 0 51 61 10 20 42
9.9 0 1 1 64 67 4 23 61
11.5 0 1 0 53 76 4 16 41
8.3 0 1 0 29 70 7 16 46
11.7 0 1 0 54 60 12 19 39
6.1 0 1 1 51 77 4 25 63
9 0 1 1 58 72 7 25 34
9.7 0 1 1 43 69 5 18 51
10.8 0 1 1 51 71 8 23 42
10.3 0 1 1 53 62 5 21 31
10.4 0 1 0 54 70 4 10 39
12.7 0 0 1 56 64 9 14 20
9.3 0 1 1 61 58 7 22 49
11.8 0 1 0 47 76 4 26 53
5.9 0 1 1 39 52 4 23 31
11.4 0 1 1 48 59 4 23 39
13 0 1 1 50 68 4 24 54
10.8 0 1 1 35 76 4 24 49
12.3 0 0 1 30 65 7 18 34
11.3 0 1 0 68 67 4 23 46
11.8 0 1 1 49 59 7 15 55
7.9 0 0 1 61 69 4 19 42
12.7 0 1 0 67 76 4 16 50
12.3 0 0 1 47 63 4 25 13
11.6 0 0 1 56 75 4 23 37
6.7 0 0 1 50 63 8 17 25
10.9 0 1 1 43 60 4 19 30
12.1 0 0 1 67 73 4 21 28
13.3 0 1 1 62 63 4 18 45
10.1 0 1 1 57 70 4 27 35
5.7 0 0 0 41 75 7 21 28
14.3 0 1 1 54 66 12 13 41
8 0 0 0 45 63 4 8 6
13.3 0 0 1 48 63 4 29 45
9.3 0 1 1 61 64 4 28 73
12.5 0 1 0 56 70 5 23 17
7.6 0 1 0 41 75 15 21 40
15.9 0 1 1 43 61 5 19 64
9.2 0 1 0 53 60 10 19 37
9.1 0 0 1 44 62 9 20 25
11.1 0 1 0 66 73 8 18 65
13 0 1 1 58 61 4 19 100
14.5 0 1 1 46 66 5 17 28
12.2 0 0 0 37 64 4 19 35
12.3 0 1 0 51 59 9 25 56
11.4 0 1 0 51 64 4 19 29
8.8 0 0 0 56 60 10 22 43
14.6 0 0 1 66 56 4 23 59
7.3 0 1 1 45 66 7 26 52
12.6 0 1 0 37 78 4 14 50
13 0 1 0 42 67 7 16 59
12.6 0 0 1 38 59 5 24 27
13.2 0 1 0 66 66 4 20 61
9.9 0 0 0 34 68 4 12 28
7.7 0 1 1 53 71 4 24 51
10.5 0 0 0 49 66 4 22 35
13.4 0 0 0 55 73 4 12 29
10.9 0 0 0 49 72 4 22 48
4.3 0 0 1 59 71 6 20 25
10.3 0 0 0 40 59 10 10 44
11.8 0 0 1 58 64 7 23 64
11.2 0 0 1 60 66 4 17 32
11.4 0 0 0 63 78 4 22 20
8.6 0 0 0 56 68 7 24 28
13.2 0 0 0 54 73 4 18 34
12.6 0 0 1 52 62 8 21 31
5.6 0 0 1 34 65 11 20 26
9.9 0 0 1 69 68 6 20 58
8.8 0 0 0 32 65 14 22 23
7.7 0 0 1 48 60 5 19 21
9 0 0 0 67 71 4 20 21
7.3 0 0 1 58 65 8 26 33
11.4 0 0 1 57 68 9 23 16
13.6 0 0 1 42 64 4 24 20
7.9 0 0 1 64 74 4 21 37
10.7 0 0 1 58 69 5 21 35
10.3 0 0 0 66 76 4 19 33
8.3 0 0 1 26 68 5 8 27
9.6 0 0 1 61 72 4 17 41
14.2 0 0 1 52 67 4 20 40
8.5 0 0 0 51 63 7 11 35
13.5 0 0 0 55 59 10 8 28
4.9 0 0 0 50 73 4 15 32
6.4 0 0 0 60 66 5 18 22
9.6 0 0 0 56 62 4 18 44
11.6 0 0 0 63 69 4 19 27
11.1 0 0 1 61 66 4 19 17
4.35 1 1 1 52 51 6 23 12
12.7 1 1 1 16 56 4 22 45
18.1 1 1 1 46 67 8 21 37
17.85 1 1 1 56 69 5 25 37
16.6 1 0 0 52 57 4 30 108
12.6 1 0 1 55 56 17 17 10
17.1 1 1 1 50 55 4 27 68
19.1 1 1 0 59 63 4 23 72
16.1 1 1 1 60 67 8 23 143
13.35 1 1 0 52 65 4 18 9
18.4 1 1 0 44 47 7 18 55
14.7 1 1 1 67 76 4 23 17
10.6 1 1 1 52 64 4 19 37
12.6 1 1 1 55 68 5 15 27
16.2 1 1 1 37 64 7 20 37
13.6 1 1 1 54 65 4 16 58
18.9 1 0 1 72 71 4 24 66
14.1 1 1 1 51 63 7 25 21
14.5 1 1 1 48 60 11 25 19
16.15 1 1 0 60 68 7 19 78
14.75 1 1 1 50 72 4 19 35
14.8 1 1 1 63 70 4 16 48
12.45 1 1 1 33 61 4 19 27
12.65 1 1 1 67 61 4 19 43
17.35 1 1 1 46 62 4 23 30
8.6 1 1 1 54 71 4 21 25
18.4 1 1 0 59 71 6 22 69
16.1 1 1 1 61 51 8 19 72
11.6 1 0 1 33 56 23 20 23
17.75 1 1 1 47 70 4 20 13
15.25 1 1 1 69 73 8 3 61
17.65 1 1 1 52 76 6 23 43
15.6 1 1 0 55 59 4 14 22
16.35 1 1 0 55 68 4 23 51
17.65 1 1 0 41 48 7 20 67
13.6 1 1 1 73 52 4 15 36
11.7 1 1 0 51 59 4 13 21
14.35 1 1 0 52 60 4 16 44
14.75 1 1 0 50 59 4 7 45
18.25 1 1 1 51 57 10 24 34
9.9 1 1 0 60 79 6 17 36
16 1 1 1 56 60 5 24 72
18.25 1 1 1 56 60 5 24 39
16.85 1 1 0 29 59 4 19 43
14.6 1 0 1 66 62 4 25 25
13.85 1 0 1 66 59 5 20 56
18.95 1 1 1 73 61 5 28 80
15.6 1 1 0 55 71 5 23 40
14.85 1 0 0 64 57 5 27 73
11.75 1 0 0 40 66 4 18 34
18.45 1 0 0 46 63 6 28 72
15.9 1 0 1 58 69 4 21 42
17.1 1 1 0 43 58 4 19 61
16.1 1 1 1 61 59 4 23 23
19.9 1 0 0 51 48 9 27 74
10.95 1 0 1 50 66 18 22 16
18.45 1 0 0 52 73 6 28 66
15.1 1 0 1 54 67 5 25 9
15 1 0 0 66 61 4 21 41
11.35 1 0 0 61 68 11 22 57
15.95 1 0 1 80 75 4 28 48
18.1 1 0 0 51 62 10 20 51
14.6 1 0 1 56 69 6 29 53
15.4 1 1 1 56 58 8 25 29
15.4 1 1 1 56 60 8 25 29
17.6 1 0 1 53 74 6 20 55
13.35 1 1 1 47 55 8 20 54
19.1 1 1 0 25 62 4 16 43
15.35 1 0 1 47 63 4 20 51
7.6 1 1 0 46 69 9 20 20
13.4 1 0 0 50 58 9 23 79
13.9 1 0 0 39 58 5 18 39
19.1 1 1 1 51 68 4 25 61
15.25 1 0 0 58 72 4 18 55
12.9 1 0 1 35 62 15 19 30
16.1 1 0 0 58 62 10 25 55
17.35 1 0 0 60 65 9 25 22
13.15 1 0 0 62 69 7 25 37
12.15 1 0 0 63 66 9 24 2
12.6 1 0 1 53 72 6 19 38
10.35 1 0 1 46 62 4 26 27
15.4 1 0 1 67 75 7 10 56
9.6 1 0 1 59 58 4 17 25
18.2 1 0 0 64 66 7 13 39
13.6 1 0 0 38 55 4 17 33
14.85 1 0 1 50 47 15 30 43
14.75 1 1 0 48 72 4 25 57
14.1 1 0 0 48 62 9 4 43
14.9 1 0 0 47 64 4 16 23
16.25 1 0 0 66 64 4 21 44
19.25 1 1 1 47 19 28 23 54
13.6 1 0 1 63 50 4 22 28
13.6 1 1 0 58 68 4 17 36
15.65 1 0 0 44 70 4 20 39
12.75 1 1 1 51 79 5 20 16
14.6 1 0 0 43 69 4 22 23
9.85 1 1 1 55 71 4 16 40
12.65 1 0 1 38 48 12 23 24
11.9 1 0 1 56 66 5 16 29
19.2 1 0 0 45 73 4 0 78
16.6 1 0 1 50 74 6 18 57
11.2 1 0 1 54 66 6 25 37
15.25 1 1 1 57 71 5 23 27
11.9 1 1 0 60 74 4 12 61
13.2 1 0 0 55 78 4 18 27
16.35 1 1 0 56 75 4 24 69
12.4 1 1 1 49 53 10 11 34
15.85 1 0 1 37 60 7 18 44
14.35 1 1 0 43 50 4 14 21
18.15 1 1 1 59 70 4 23 34
11.15 1 0 1 46 69 7 24 39
15.65 1 0 0 51 65 4 29 51
17.75 1 1 0 58 78 4 18 34
7.65 1 0 0 64 78 12 15 31
12.35 1 1 1 53 59 5 29 13
15.6 1 1 1 48 72 8 16 12
19.3 1 1 0 51 70 6 19 51
15.2 1 0 0 47 63 17 22 24
17.1 1 1 0 59 63 4 16 19
15.6 1 0 1 62 71 5 23 30
18.4 1 1 1 62 74 4 23 81
19.05 1 1 0 51 67 5 19 42
18.55 1 1 0 64 66 5 4 22
19.1 1 1 0 52 62 6 20 85
13.1 1 0 1 67 80 4 24 27
12.85 1 1 1 50 73 4 20 25
9.5 1 1 1 54 67 4 4 22
4.5 1 1 1 58 61 6 24 19
11.85 1 0 0 56 73 8 22 14
13.6 1 1 1 63 74 10 16 45
11.7 1 1 1 31 32 4 3 45
12.4 1 0 1 65 69 5 15 28
13.35 1 1 0 71 69 4 24 51
11.4 1 0 0 50 84 4 17 41
14.9 1 0 1 57 64 4 20 31
19.9 1 0 0 47 58 16 27 74
17.75 1 1 1 54 60 4 23 24
11.2 1 0 1 47 59 7 26 19
14.6 1 0 1 57 78 4 23 51
17.6 1 1 0 43 57 4 17 73
14.05 1 1 1 41 60 14 20 24
16.1 1 1 0 63 68 5 22 61
13.35 1 1 1 63 68 5 19 23
11.85 1 1 1 56 73 5 24 14
11.95 1 1 0 51 69 5 19 54
14.75 1 0 1 50 67 7 23 51
15.15 1 0 0 22 60 19 15 62
13.2 1 1 1 41 65 16 27 36
16.85 1 0 0 59 66 4 26 59
7.85 1 0 1 56 74 4 22 24
7.7 1 1 0 66 81 7 22 26
12.6 1 0 0 53 72 9 18 54
7.85 1 0 1 42 55 5 15 39
10.95 1 0 1 52 49 14 22 16
12.35 1 0 0 54 74 4 27 36
9.95 1 0 1 44 53 16 10 31
14.9 1 0 1 62 64 10 20 31
16.65 1 0 0 53 65 5 17 42
13.4 1 0 1 50 57 6 23 39
13.95 1 0 0 36 51 4 19 25
15.7 1 0 0 76 80 4 13 31
16.85 1 0 1 66 67 4 27 38
10.95 1 0 1 62 70 5 23 31
15.35 1 0 0 59 74 4 16 17
12.2 1 0 1 47 75 4 25 22
15.1 1 0 0 55 70 5 2 55
17.75 1 0 0 58 69 4 26 62
15.2 1 0 1 60 65 4 20 51
14.6 1 1 0 44 55 5 23 30
16.65 1 0 0 57 71 8 22 49
8.1 1 0 1 45 65 15 24 16

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=263679&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=263679&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&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] = + 10.0181 + 3.88626Year_Dummy[t] + 0.178684Education_Dummy[t] -0.726128gender_Dummy[t] + 0.00205983AMS.I[t] -0.0311141AMS.E[t] -0.0487718AMS.A[t] + 0.0409271NUMERACYTOT[t] + 0.0563189CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  10.0181 +  3.88626Year_Dummy[t] +  0.178684Education_Dummy[t] -0.726128gender_Dummy[t] +  0.00205983AMS.I[t] -0.0311141AMS.E[t] -0.0487718AMS.A[t] +  0.0409271NUMERACYTOT[t] +  0.0563189CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  10.0181 +  3.88626Year_Dummy[t] +  0.178684Education_Dummy[t] -0.726128gender_Dummy[t] +  0.00205983AMS.I[t] -0.0311141AMS.E[t] -0.0487718AMS.A[t] +  0.0409271NUMERACYTOT[t] +  0.0563189CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&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] = + 10.0181 + 3.88626Year_Dummy[t] + 0.178684Education_Dummy[t] -0.726128gender_Dummy[t] + 0.00205983AMS.I[t] -0.0311141AMS.E[t] -0.0487718AMS.A[t] + 0.0409271NUMERACYTOT[t] + 0.0563189CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.01811.700795.891.11466e-085.57332e-09
Year_Dummy3.886260.31553812.324.31037e-282.15518e-28
Education_Dummy0.1786840.3164040.56470.5727120.286356
gender_Dummy-0.7261280.321953-2.2550.02488970.0124448
AMS.I0.002059830.01641290.12550.9002180.450109
AMS.E-0.03111410.0212643-1.4630.1445450.0722725
AMS.A-0.04877180.0479342-1.0170.3098160.154908
NUMERACYTOT0.04092710.03069221.3330.1834740.0917369
CH0.05631890.008358586.7389.28824e-114.64412e-11

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 10.0181 & 1.70079 & 5.89 & 1.11466e-08 & 5.57332e-09 \tabularnewline
Year_Dummy & 3.88626 & 0.315538 & 12.32 & 4.31037e-28 & 2.15518e-28 \tabularnewline
Education_Dummy & 0.178684 & 0.316404 & 0.5647 & 0.572712 & 0.286356 \tabularnewline
gender_Dummy & -0.726128 & 0.321953 & -2.255 & 0.0248897 & 0.0124448 \tabularnewline
AMS.I & 0.00205983 & 0.0164129 & 0.1255 & 0.900218 & 0.450109 \tabularnewline
AMS.E & -0.0311141 & 0.0212643 & -1.463 & 0.144545 & 0.0722725 \tabularnewline
AMS.A & -0.0487718 & 0.0479342 & -1.017 & 0.309816 & 0.154908 \tabularnewline
NUMERACYTOT & 0.0409271 & 0.0306922 & 1.333 & 0.183474 & 0.0917369 \tabularnewline
CH & 0.0563189 & 0.00835858 & 6.738 & 9.28824e-11 & 4.64412e-11 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]10.0181[/C][C]1.70079[/C][C]5.89[/C][C]1.11466e-08[/C][C]5.57332e-09[/C][/ROW]
[ROW][C]Year_Dummy[/C][C]3.88626[/C][C]0.315538[/C][C]12.32[/C][C]4.31037e-28[/C][C]2.15518e-28[/C][/ROW]
[ROW][C]Education_Dummy[/C][C]0.178684[/C][C]0.316404[/C][C]0.5647[/C][C]0.572712[/C][C]0.286356[/C][/ROW]
[ROW][C]gender_Dummy[/C][C]-0.726128[/C][C]0.321953[/C][C]-2.255[/C][C]0.0248897[/C][C]0.0124448[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00205983[/C][C]0.0164129[/C][C]0.1255[/C][C]0.900218[/C][C]0.450109[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0311141[/C][C]0.0212643[/C][C]-1.463[/C][C]0.144545[/C][C]0.0722725[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0487718[/C][C]0.0479342[/C][C]-1.017[/C][C]0.309816[/C][C]0.154908[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0409271[/C][C]0.0306922[/C][C]1.333[/C][C]0.183474[/C][C]0.0917369[/C][/ROW]
[ROW][C]CH[/C][C]0.0563189[/C][C]0.00835858[/C][C]6.738[/C][C]9.28824e-11[/C][C]4.64412e-11[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.01811.700795.891.11466e-085.57332e-09
Year_Dummy3.886260.31553812.324.31037e-282.15518e-28
Education_Dummy0.1786840.3164040.56470.5727120.286356
gender_Dummy-0.7261280.321953-2.2550.02488970.0124448
AMS.I0.002059830.01641290.12550.9002180.450109
AMS.E-0.03111410.0212643-1.4630.1445450.0722725
AMS.A-0.04877180.0479342-1.0170.3098160.154908
NUMERACYTOT0.04092710.03069221.3330.1834740.0917369
CH0.05631890.008358586.7389.28824e-114.64412e-11






Multiple Linear Regression - Regression Statistics
Multiple R0.669996
R-squared0.448895
Adjusted R-squared0.432978
F-TEST (value)28.2033
F-TEST (DF numerator)8
F-TEST (DF denominator)277
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.57624
Sum Squared Residuals1838.45

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.669996 \tabularnewline
R-squared & 0.448895 \tabularnewline
Adjusted R-squared & 0.432978 \tabularnewline
F-TEST (value) & 28.2033 \tabularnewline
F-TEST (DF numerator) & 8 \tabularnewline
F-TEST (DF denominator) & 277 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.57624 \tabularnewline
Sum Squared Residuals & 1838.45 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.669996[/C][/ROW]
[ROW][C]R-squared[/C][C]0.448895[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.432978[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]28.2033[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]8[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]277[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.57624[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1838.45[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&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 R0.669996
R-squared0.448895
Adjusted R-squared0.432978
F-TEST (value)28.2033
F-TEST (DF numerator)8
F-TEST (DF denominator)277
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.57624
Sum Squared Residuals1838.45






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.1887-0.288725
27.411.9088-4.5088
312.210.56081.63924
412.811.05161.7484
57.411.433-4.03296
66.710.4839-3.78385
712.610.53612.06386
814.811.95272.84727
913.312.64180.658219
1011.111.9747-0.87474
118.211.1935-2.9935
1211.410.82920.570846
136.411.5594-5.15936
1410.69.268831.33117
151213.0204-1.02035
166.39.61498-3.31498
1711.39.728921.57108
1811.911.84620.0537758
199.310.7697-1.46972
209.610.4416-0.841619
211010.6846-0.68462
226.49.03791-2.63791
2313.89.41274.3873
2410.811.2008-0.400819
2513.811.77552.02452
2611.711.11010.589858
2710.911.7427-0.842719
2816.112.68563.41443
2913.410.92142.47857
309.911.6996-1.79955
3111.510.71010.789871
328.310.9827-2.68266
3311.710.830.870017
346.111.5561-5.45613
3599.94655-0.946553
369.710.7775-1.07747
3710.810.28320.516827
3810.310.01230.287727
3910.410.5407-0.140673
4012.78.676464.02354
419.311.1103-1.81033
4211.811.78290.0171325
435.910.4252-4.5252
4411.410.67650.723507
451311.28631.7137
4610.810.72490.0751082
4712.39.64152.6585
4811.311.5891-0.289137
4911.811.10590.694077
507.910.2187-2.31869
5112.711.24581.45416
5212.38.988863.31114
5311.69.903821.69618
546.79.14836-2.44836
5510.99.96450.935498
5612.19.399992.70001
5713.310.71422.58585
5810.110.2912-0.19121
595.79.86402-4.16402
6014.39.784254.51575
6188.62087-0.620872
6213.310.95682.34317
639.312.6672-3.36718
6412.59.789062.71094
657.610.3284-2.72835
6615.911.79954.10054
679.210.8128-1.61283
689.19.24112-0.141123
6911.112.0687-0.968669
701313.9066-0.906607
7114.59.540734.95927
7212.210.65671.54328
7312.312.20420.0957831
7411.410.52630.873667
758.811.101-2.30102
7614.611.75462.84539
777.311.1611-3.86113
7812.611.041.56004
791311.83491.16508
8012.69.793542.80646
8113.212.33810.861866
829.99.845370.0546328
837.711.0302-3.33018
8410.510.742-0.241996
8513.49.789373.61063
8610.911.2875-0.387457
874.39.13831-4.83831
8810.310.6644-0.36437
8911.811.62450.175506
9011.29.664931.53507
9111.49.552681.84732
928.610.2355-1.63549
9313.210.31452.88553
9412.69.685212.91479
955.69.08596-3.48596
969.911.1108-1.21077
978.89.57455-0.774548
987.79.24048-1.54048
9999.75318-0.753184
1007.39.9215-2.6215
10111.48.697132.70287
10213.69.300754.29925
1037.99.86956-1.96956
10410.79.851370.848635
10510.310.23050.0695469
1068.38.83396-0.533962
1079.69.98718-0.387179
10814.210.19074.00933
1098.510.2429-1.74294
11013.59.712313.78769
1114.910.0708-5.17081
1126.49.82003-3.42003
1139.611.224-1.62403
11411.610.10421.49584
11511.18.904062.19594
1164.3513.2018-8.85175
11712.714.8872-2.18717
11818.113.92014.17986
11917.8514.18853.66146
12016.619.3532-2.75316
12112.611.9790.621012
12217.116.48830.611713
12319.117.04562.05439
12416.120.0006-3.90064
12513.3513.21620.133764
12618.416.20422.19584
12714.712.83391.86606
12810.614.1391-3.53908
12912.613.2451-0.645132
13016.214.00282.19721
13113.615.172-1.572
13218.915.62173.27833
13314.113.36630.733723
13414.513.14571.35429
13516.1516.92-0.769987
13614.7513.77340.976592
13714.814.47180.328222
13812.4513.6301-1.18009
13912.6514.6012-1.95123
14017.3513.95843.39158
1418.613.3314-4.73143
14218.416.48931.91073
14316.116.3382-0.238173
14411.612.496-0.895968
14517.7512.63145.11863
14615.2514.39580.854199
14717.6514.16983.48021
14815.613.97751.62246
14916.3515.69910.650898
15017.6516.92460.725449
15113.614.3357-0.735676
15211.713.8721-2.17205
15314.3515.2611-0.911113
15414.7514.9761-0.226083
15518.2514.09794.15214
1569.914.1793-4.27926
1571616.3988-0.398798
15818.2514.54033.70973
15916.8515.31131.53869
16014.613.62120.978804
16113.8515.207-1.35702
16218.9517.0171.93304
16315.614.93750.66252
16414.8517.2352-2.38516
16511.7514.3897-2.63969
16618.4516.94721.50276
16715.914.18061.71937
16817.116.3850.714995
16916.113.68842.41157
17019.917.34962.55036
17110.9512.1513-1.20133
17218.4516.31052.13946
17315.112.4912.60897
1741515.1158-0.115832
17511.3515.4884-4.13836
17615.9514.66371.28633
17718.115.28352.81655
17814.615.0259-0.425892
17915.413.93391.46607
18015.413.87171.5283
18117.614.60842.99156
18213.3515.2121-1.86207
18319.115.0874.01305
18415.3514.81060.5394
1857.613.5369-5.93692
18613.417.1543-3.75433
18713.914.8694-0.969367
18819.115.60983.49022
18915.2515.4228-0.172781
19012.913.0569-0.156883
19116.115.72780.37222
19217.3513.82883.52119
19313.1514.6508-1.5008
19412.1512.6366-0.486567
19512.613.6723-1.07232
19610.3513.7336-3.38356
19715.414.20441.19556
1989.613.4038-3.80382
19918.214.36983.83023
20013.614.6306-1.03058
20114.8514.73680.113165
20214.7515.98-1.22999
20314.114.2207-0.120659
20414.913.7651.13502
20516.2515.19141.05855
20619.2515.47953.77048
20713.614.0346-0.434561
20813.614.6149-1.01494
20915.6514.63691.01308
21012.7512.47980.270235
21114.613.84670.75327
2129.8513.9736-4.12363
21312.6513.4708-0.82077
21411.913.2843-1.3843
21519.215.92353.27646
21616.614.6331.96696
21711.214.0503-2.8503
21815.2513.48331.76667
21911.915.6357-3.73571
22013.213.653-0.452988
22116.3516.538-0.18803
22212.413.6861-1.28615
22315.8514.26091.58906
22414.3514.17650.173473
22518.1513.96164.18844
22611.1513.9634-2.81342
22715.6515.8511-0.201083
22817.7514.23213.51792
2297.6513.3838-5.73385
23012.3513.3056-0.955554
23115.612.15613.44391
23219.315.36743.93262
23315.213.46391.73606
23417.113.77423.32578
23515.613.48392.1161
23618.416.49031.90973
23719.0515.00264.04737
23818.5513.32025.22977
23919.117.57411.52588
24013.113.1349-0.0349124
24112.8513.22-0.370032
2429.512.5912-3.09117
2434.513.3381-8.83813
24411.8513.0471-1.19709
24513.613.8857-0.285734
24611.714.8872-3.18719
24712.413.1123-0.712251
24813.3515.7419-2.39187
24911.414.2035-2.80354
25014.913.67371.22629
25119.916.68893.21114
25217.7513.69924.05078
25311.213.2321-2.0321
25414.614.48730.112732
25517.617.01010.589908
25614.0513.06190.988061
25716.116.1891-0.0890703
25813.3513.20.149957
25911.8512.7278-0.87782
26011.9515.6162-3.66622
26114.7514.66880.0812108
26215.1515.2619-0.11187
26313.213.7711-0.571141
26416.8516.16420.685782
2657.8513.0481-5.19813
2667.713.7221-6.02206
26712.615.1123-2.5123
2687.8514.12-6.26998
26910.9512.8795-1.92947
27012.3514.6506-2.3006
2719.9512.9947-3.04465
27214.913.39141.50862
27316.6514.80841.84156
27413.414.3529-0.952875
27513.9514.3822-0.432221
27615.713.65472.04534
27716.8514.27962.57038
27810.9513.5713-2.62133
27915.3513.14062.20936
28012.213.0086-0.808619
28115.114.77520.324775
28217.7516.23781.51223
28315.214.77510.42485
28414.614.8495-0.249458
28516.6515.08251.56746
2868.112.4003-4.30031

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.1887 & -0.288725 \tabularnewline
2 & 7.4 & 11.9088 & -4.5088 \tabularnewline
3 & 12.2 & 10.5608 & 1.63924 \tabularnewline
4 & 12.8 & 11.0516 & 1.7484 \tabularnewline
5 & 7.4 & 11.433 & -4.03296 \tabularnewline
6 & 6.7 & 10.4839 & -3.78385 \tabularnewline
7 & 12.6 & 10.5361 & 2.06386 \tabularnewline
8 & 14.8 & 11.9527 & 2.84727 \tabularnewline
9 & 13.3 & 12.6418 & 0.658219 \tabularnewline
10 & 11.1 & 11.9747 & -0.87474 \tabularnewline
11 & 8.2 & 11.1935 & -2.9935 \tabularnewline
12 & 11.4 & 10.8292 & 0.570846 \tabularnewline
13 & 6.4 & 11.5594 & -5.15936 \tabularnewline
14 & 10.6 & 9.26883 & 1.33117 \tabularnewline
15 & 12 & 13.0204 & -1.02035 \tabularnewline
16 & 6.3 & 9.61498 & -3.31498 \tabularnewline
17 & 11.3 & 9.72892 & 1.57108 \tabularnewline
18 & 11.9 & 11.8462 & 0.0537758 \tabularnewline
19 & 9.3 & 10.7697 & -1.46972 \tabularnewline
20 & 9.6 & 10.4416 & -0.841619 \tabularnewline
21 & 10 & 10.6846 & -0.68462 \tabularnewline
22 & 6.4 & 9.03791 & -2.63791 \tabularnewline
23 & 13.8 & 9.4127 & 4.3873 \tabularnewline
24 & 10.8 & 11.2008 & -0.400819 \tabularnewline
25 & 13.8 & 11.7755 & 2.02452 \tabularnewline
26 & 11.7 & 11.1101 & 0.589858 \tabularnewline
27 & 10.9 & 11.7427 & -0.842719 \tabularnewline
28 & 16.1 & 12.6856 & 3.41443 \tabularnewline
29 & 13.4 & 10.9214 & 2.47857 \tabularnewline
30 & 9.9 & 11.6996 & -1.79955 \tabularnewline
31 & 11.5 & 10.7101 & 0.789871 \tabularnewline
32 & 8.3 & 10.9827 & -2.68266 \tabularnewline
33 & 11.7 & 10.83 & 0.870017 \tabularnewline
34 & 6.1 & 11.5561 & -5.45613 \tabularnewline
35 & 9 & 9.94655 & -0.946553 \tabularnewline
36 & 9.7 & 10.7775 & -1.07747 \tabularnewline
37 & 10.8 & 10.2832 & 0.516827 \tabularnewline
38 & 10.3 & 10.0123 & 0.287727 \tabularnewline
39 & 10.4 & 10.5407 & -0.140673 \tabularnewline
40 & 12.7 & 8.67646 & 4.02354 \tabularnewline
41 & 9.3 & 11.1103 & -1.81033 \tabularnewline
42 & 11.8 & 11.7829 & 0.0171325 \tabularnewline
43 & 5.9 & 10.4252 & -4.5252 \tabularnewline
44 & 11.4 & 10.6765 & 0.723507 \tabularnewline
45 & 13 & 11.2863 & 1.7137 \tabularnewline
46 & 10.8 & 10.7249 & 0.0751082 \tabularnewline
47 & 12.3 & 9.6415 & 2.6585 \tabularnewline
48 & 11.3 & 11.5891 & -0.289137 \tabularnewline
49 & 11.8 & 11.1059 & 0.694077 \tabularnewline
50 & 7.9 & 10.2187 & -2.31869 \tabularnewline
51 & 12.7 & 11.2458 & 1.45416 \tabularnewline
52 & 12.3 & 8.98886 & 3.31114 \tabularnewline
53 & 11.6 & 9.90382 & 1.69618 \tabularnewline
54 & 6.7 & 9.14836 & -2.44836 \tabularnewline
55 & 10.9 & 9.9645 & 0.935498 \tabularnewline
56 & 12.1 & 9.39999 & 2.70001 \tabularnewline
57 & 13.3 & 10.7142 & 2.58585 \tabularnewline
58 & 10.1 & 10.2912 & -0.19121 \tabularnewline
59 & 5.7 & 9.86402 & -4.16402 \tabularnewline
60 & 14.3 & 9.78425 & 4.51575 \tabularnewline
61 & 8 & 8.62087 & -0.620872 \tabularnewline
62 & 13.3 & 10.9568 & 2.34317 \tabularnewline
63 & 9.3 & 12.6672 & -3.36718 \tabularnewline
64 & 12.5 & 9.78906 & 2.71094 \tabularnewline
65 & 7.6 & 10.3284 & -2.72835 \tabularnewline
66 & 15.9 & 11.7995 & 4.10054 \tabularnewline
67 & 9.2 & 10.8128 & -1.61283 \tabularnewline
68 & 9.1 & 9.24112 & -0.141123 \tabularnewline
69 & 11.1 & 12.0687 & -0.968669 \tabularnewline
70 & 13 & 13.9066 & -0.906607 \tabularnewline
71 & 14.5 & 9.54073 & 4.95927 \tabularnewline
72 & 12.2 & 10.6567 & 1.54328 \tabularnewline
73 & 12.3 & 12.2042 & 0.0957831 \tabularnewline
74 & 11.4 & 10.5263 & 0.873667 \tabularnewline
75 & 8.8 & 11.101 & -2.30102 \tabularnewline
76 & 14.6 & 11.7546 & 2.84539 \tabularnewline
77 & 7.3 & 11.1611 & -3.86113 \tabularnewline
78 & 12.6 & 11.04 & 1.56004 \tabularnewline
79 & 13 & 11.8349 & 1.16508 \tabularnewline
80 & 12.6 & 9.79354 & 2.80646 \tabularnewline
81 & 13.2 & 12.3381 & 0.861866 \tabularnewline
82 & 9.9 & 9.84537 & 0.0546328 \tabularnewline
83 & 7.7 & 11.0302 & -3.33018 \tabularnewline
84 & 10.5 & 10.742 & -0.241996 \tabularnewline
85 & 13.4 & 9.78937 & 3.61063 \tabularnewline
86 & 10.9 & 11.2875 & -0.387457 \tabularnewline
87 & 4.3 & 9.13831 & -4.83831 \tabularnewline
88 & 10.3 & 10.6644 & -0.36437 \tabularnewline
89 & 11.8 & 11.6245 & 0.175506 \tabularnewline
90 & 11.2 & 9.66493 & 1.53507 \tabularnewline
91 & 11.4 & 9.55268 & 1.84732 \tabularnewline
92 & 8.6 & 10.2355 & -1.63549 \tabularnewline
93 & 13.2 & 10.3145 & 2.88553 \tabularnewline
94 & 12.6 & 9.68521 & 2.91479 \tabularnewline
95 & 5.6 & 9.08596 & -3.48596 \tabularnewline
96 & 9.9 & 11.1108 & -1.21077 \tabularnewline
97 & 8.8 & 9.57455 & -0.774548 \tabularnewline
98 & 7.7 & 9.24048 & -1.54048 \tabularnewline
99 & 9 & 9.75318 & -0.753184 \tabularnewline
100 & 7.3 & 9.9215 & -2.6215 \tabularnewline
101 & 11.4 & 8.69713 & 2.70287 \tabularnewline
102 & 13.6 & 9.30075 & 4.29925 \tabularnewline
103 & 7.9 & 9.86956 & -1.96956 \tabularnewline
104 & 10.7 & 9.85137 & 0.848635 \tabularnewline
105 & 10.3 & 10.2305 & 0.0695469 \tabularnewline
106 & 8.3 & 8.83396 & -0.533962 \tabularnewline
107 & 9.6 & 9.98718 & -0.387179 \tabularnewline
108 & 14.2 & 10.1907 & 4.00933 \tabularnewline
109 & 8.5 & 10.2429 & -1.74294 \tabularnewline
110 & 13.5 & 9.71231 & 3.78769 \tabularnewline
111 & 4.9 & 10.0708 & -5.17081 \tabularnewline
112 & 6.4 & 9.82003 & -3.42003 \tabularnewline
113 & 9.6 & 11.224 & -1.62403 \tabularnewline
114 & 11.6 & 10.1042 & 1.49584 \tabularnewline
115 & 11.1 & 8.90406 & 2.19594 \tabularnewline
116 & 4.35 & 13.2018 & -8.85175 \tabularnewline
117 & 12.7 & 14.8872 & -2.18717 \tabularnewline
118 & 18.1 & 13.9201 & 4.17986 \tabularnewline
119 & 17.85 & 14.1885 & 3.66146 \tabularnewline
120 & 16.6 & 19.3532 & -2.75316 \tabularnewline
121 & 12.6 & 11.979 & 0.621012 \tabularnewline
122 & 17.1 & 16.4883 & 0.611713 \tabularnewline
123 & 19.1 & 17.0456 & 2.05439 \tabularnewline
124 & 16.1 & 20.0006 & -3.90064 \tabularnewline
125 & 13.35 & 13.2162 & 0.133764 \tabularnewline
126 & 18.4 & 16.2042 & 2.19584 \tabularnewline
127 & 14.7 & 12.8339 & 1.86606 \tabularnewline
128 & 10.6 & 14.1391 & -3.53908 \tabularnewline
129 & 12.6 & 13.2451 & -0.645132 \tabularnewline
130 & 16.2 & 14.0028 & 2.19721 \tabularnewline
131 & 13.6 & 15.172 & -1.572 \tabularnewline
132 & 18.9 & 15.6217 & 3.27833 \tabularnewline
133 & 14.1 & 13.3663 & 0.733723 \tabularnewline
134 & 14.5 & 13.1457 & 1.35429 \tabularnewline
135 & 16.15 & 16.92 & -0.769987 \tabularnewline
136 & 14.75 & 13.7734 & 0.976592 \tabularnewline
137 & 14.8 & 14.4718 & 0.328222 \tabularnewline
138 & 12.45 & 13.6301 & -1.18009 \tabularnewline
139 & 12.65 & 14.6012 & -1.95123 \tabularnewline
140 & 17.35 & 13.9584 & 3.39158 \tabularnewline
141 & 8.6 & 13.3314 & -4.73143 \tabularnewline
142 & 18.4 & 16.4893 & 1.91073 \tabularnewline
143 & 16.1 & 16.3382 & -0.238173 \tabularnewline
144 & 11.6 & 12.496 & -0.895968 \tabularnewline
145 & 17.75 & 12.6314 & 5.11863 \tabularnewline
146 & 15.25 & 14.3958 & 0.854199 \tabularnewline
147 & 17.65 & 14.1698 & 3.48021 \tabularnewline
148 & 15.6 & 13.9775 & 1.62246 \tabularnewline
149 & 16.35 & 15.6991 & 0.650898 \tabularnewline
150 & 17.65 & 16.9246 & 0.725449 \tabularnewline
151 & 13.6 & 14.3357 & -0.735676 \tabularnewline
152 & 11.7 & 13.8721 & -2.17205 \tabularnewline
153 & 14.35 & 15.2611 & -0.911113 \tabularnewline
154 & 14.75 & 14.9761 & -0.226083 \tabularnewline
155 & 18.25 & 14.0979 & 4.15214 \tabularnewline
156 & 9.9 & 14.1793 & -4.27926 \tabularnewline
157 & 16 & 16.3988 & -0.398798 \tabularnewline
158 & 18.25 & 14.5403 & 3.70973 \tabularnewline
159 & 16.85 & 15.3113 & 1.53869 \tabularnewline
160 & 14.6 & 13.6212 & 0.978804 \tabularnewline
161 & 13.85 & 15.207 & -1.35702 \tabularnewline
162 & 18.95 & 17.017 & 1.93304 \tabularnewline
163 & 15.6 & 14.9375 & 0.66252 \tabularnewline
164 & 14.85 & 17.2352 & -2.38516 \tabularnewline
165 & 11.75 & 14.3897 & -2.63969 \tabularnewline
166 & 18.45 & 16.9472 & 1.50276 \tabularnewline
167 & 15.9 & 14.1806 & 1.71937 \tabularnewline
168 & 17.1 & 16.385 & 0.714995 \tabularnewline
169 & 16.1 & 13.6884 & 2.41157 \tabularnewline
170 & 19.9 & 17.3496 & 2.55036 \tabularnewline
171 & 10.95 & 12.1513 & -1.20133 \tabularnewline
172 & 18.45 & 16.3105 & 2.13946 \tabularnewline
173 & 15.1 & 12.491 & 2.60897 \tabularnewline
174 & 15 & 15.1158 & -0.115832 \tabularnewline
175 & 11.35 & 15.4884 & -4.13836 \tabularnewline
176 & 15.95 & 14.6637 & 1.28633 \tabularnewline
177 & 18.1 & 15.2835 & 2.81655 \tabularnewline
178 & 14.6 & 15.0259 & -0.425892 \tabularnewline
179 & 15.4 & 13.9339 & 1.46607 \tabularnewline
180 & 15.4 & 13.8717 & 1.5283 \tabularnewline
181 & 17.6 & 14.6084 & 2.99156 \tabularnewline
182 & 13.35 & 15.2121 & -1.86207 \tabularnewline
183 & 19.1 & 15.087 & 4.01305 \tabularnewline
184 & 15.35 & 14.8106 & 0.5394 \tabularnewline
185 & 7.6 & 13.5369 & -5.93692 \tabularnewline
186 & 13.4 & 17.1543 & -3.75433 \tabularnewline
187 & 13.9 & 14.8694 & -0.969367 \tabularnewline
188 & 19.1 & 15.6098 & 3.49022 \tabularnewline
189 & 15.25 & 15.4228 & -0.172781 \tabularnewline
190 & 12.9 & 13.0569 & -0.156883 \tabularnewline
191 & 16.1 & 15.7278 & 0.37222 \tabularnewline
192 & 17.35 & 13.8288 & 3.52119 \tabularnewline
193 & 13.15 & 14.6508 & -1.5008 \tabularnewline
194 & 12.15 & 12.6366 & -0.486567 \tabularnewline
195 & 12.6 & 13.6723 & -1.07232 \tabularnewline
196 & 10.35 & 13.7336 & -3.38356 \tabularnewline
197 & 15.4 & 14.2044 & 1.19556 \tabularnewline
198 & 9.6 & 13.4038 & -3.80382 \tabularnewline
199 & 18.2 & 14.3698 & 3.83023 \tabularnewline
200 & 13.6 & 14.6306 & -1.03058 \tabularnewline
201 & 14.85 & 14.7368 & 0.113165 \tabularnewline
202 & 14.75 & 15.98 & -1.22999 \tabularnewline
203 & 14.1 & 14.2207 & -0.120659 \tabularnewline
204 & 14.9 & 13.765 & 1.13502 \tabularnewline
205 & 16.25 & 15.1914 & 1.05855 \tabularnewline
206 & 19.25 & 15.4795 & 3.77048 \tabularnewline
207 & 13.6 & 14.0346 & -0.434561 \tabularnewline
208 & 13.6 & 14.6149 & -1.01494 \tabularnewline
209 & 15.65 & 14.6369 & 1.01308 \tabularnewline
210 & 12.75 & 12.4798 & 0.270235 \tabularnewline
211 & 14.6 & 13.8467 & 0.75327 \tabularnewline
212 & 9.85 & 13.9736 & -4.12363 \tabularnewline
213 & 12.65 & 13.4708 & -0.82077 \tabularnewline
214 & 11.9 & 13.2843 & -1.3843 \tabularnewline
215 & 19.2 & 15.9235 & 3.27646 \tabularnewline
216 & 16.6 & 14.633 & 1.96696 \tabularnewline
217 & 11.2 & 14.0503 & -2.8503 \tabularnewline
218 & 15.25 & 13.4833 & 1.76667 \tabularnewline
219 & 11.9 & 15.6357 & -3.73571 \tabularnewline
220 & 13.2 & 13.653 & -0.452988 \tabularnewline
221 & 16.35 & 16.538 & -0.18803 \tabularnewline
222 & 12.4 & 13.6861 & -1.28615 \tabularnewline
223 & 15.85 & 14.2609 & 1.58906 \tabularnewline
224 & 14.35 & 14.1765 & 0.173473 \tabularnewline
225 & 18.15 & 13.9616 & 4.18844 \tabularnewline
226 & 11.15 & 13.9634 & -2.81342 \tabularnewline
227 & 15.65 & 15.8511 & -0.201083 \tabularnewline
228 & 17.75 & 14.2321 & 3.51792 \tabularnewline
229 & 7.65 & 13.3838 & -5.73385 \tabularnewline
230 & 12.35 & 13.3056 & -0.955554 \tabularnewline
231 & 15.6 & 12.1561 & 3.44391 \tabularnewline
232 & 19.3 & 15.3674 & 3.93262 \tabularnewline
233 & 15.2 & 13.4639 & 1.73606 \tabularnewline
234 & 17.1 & 13.7742 & 3.32578 \tabularnewline
235 & 15.6 & 13.4839 & 2.1161 \tabularnewline
236 & 18.4 & 16.4903 & 1.90973 \tabularnewline
237 & 19.05 & 15.0026 & 4.04737 \tabularnewline
238 & 18.55 & 13.3202 & 5.22977 \tabularnewline
239 & 19.1 & 17.5741 & 1.52588 \tabularnewline
240 & 13.1 & 13.1349 & -0.0349124 \tabularnewline
241 & 12.85 & 13.22 & -0.370032 \tabularnewline
242 & 9.5 & 12.5912 & -3.09117 \tabularnewline
243 & 4.5 & 13.3381 & -8.83813 \tabularnewline
244 & 11.85 & 13.0471 & -1.19709 \tabularnewline
245 & 13.6 & 13.8857 & -0.285734 \tabularnewline
246 & 11.7 & 14.8872 & -3.18719 \tabularnewline
247 & 12.4 & 13.1123 & -0.712251 \tabularnewline
248 & 13.35 & 15.7419 & -2.39187 \tabularnewline
249 & 11.4 & 14.2035 & -2.80354 \tabularnewline
250 & 14.9 & 13.6737 & 1.22629 \tabularnewline
251 & 19.9 & 16.6889 & 3.21114 \tabularnewline
252 & 17.75 & 13.6992 & 4.05078 \tabularnewline
253 & 11.2 & 13.2321 & -2.0321 \tabularnewline
254 & 14.6 & 14.4873 & 0.112732 \tabularnewline
255 & 17.6 & 17.0101 & 0.589908 \tabularnewline
256 & 14.05 & 13.0619 & 0.988061 \tabularnewline
257 & 16.1 & 16.1891 & -0.0890703 \tabularnewline
258 & 13.35 & 13.2 & 0.149957 \tabularnewline
259 & 11.85 & 12.7278 & -0.87782 \tabularnewline
260 & 11.95 & 15.6162 & -3.66622 \tabularnewline
261 & 14.75 & 14.6688 & 0.0812108 \tabularnewline
262 & 15.15 & 15.2619 & -0.11187 \tabularnewline
263 & 13.2 & 13.7711 & -0.571141 \tabularnewline
264 & 16.85 & 16.1642 & 0.685782 \tabularnewline
265 & 7.85 & 13.0481 & -5.19813 \tabularnewline
266 & 7.7 & 13.7221 & -6.02206 \tabularnewline
267 & 12.6 & 15.1123 & -2.5123 \tabularnewline
268 & 7.85 & 14.12 & -6.26998 \tabularnewline
269 & 10.95 & 12.8795 & -1.92947 \tabularnewline
270 & 12.35 & 14.6506 & -2.3006 \tabularnewline
271 & 9.95 & 12.9947 & -3.04465 \tabularnewline
272 & 14.9 & 13.3914 & 1.50862 \tabularnewline
273 & 16.65 & 14.8084 & 1.84156 \tabularnewline
274 & 13.4 & 14.3529 & -0.952875 \tabularnewline
275 & 13.95 & 14.3822 & -0.432221 \tabularnewline
276 & 15.7 & 13.6547 & 2.04534 \tabularnewline
277 & 16.85 & 14.2796 & 2.57038 \tabularnewline
278 & 10.95 & 13.5713 & -2.62133 \tabularnewline
279 & 15.35 & 13.1406 & 2.20936 \tabularnewline
280 & 12.2 & 13.0086 & -0.808619 \tabularnewline
281 & 15.1 & 14.7752 & 0.324775 \tabularnewline
282 & 17.75 & 16.2378 & 1.51223 \tabularnewline
283 & 15.2 & 14.7751 & 0.42485 \tabularnewline
284 & 14.6 & 14.8495 & -0.249458 \tabularnewline
285 & 16.65 & 15.0825 & 1.56746 \tabularnewline
286 & 8.1 & 12.4003 & -4.30031 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&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]13.1887[/C][C]-0.288725[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]11.9088[/C][C]-4.5088[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]10.5608[/C][C]1.63924[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]11.0516[/C][C]1.7484[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]11.433[/C][C]-4.03296[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]10.4839[/C][C]-3.78385[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]10.5361[/C][C]2.06386[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]11.9527[/C][C]2.84727[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]12.6418[/C][C]0.658219[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]11.9747[/C][C]-0.87474[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]11.1935[/C][C]-2.9935[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]10.8292[/C][C]0.570846[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]11.5594[/C][C]-5.15936[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]9.26883[/C][C]1.33117[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]13.0204[/C][C]-1.02035[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]9.61498[/C][C]-3.31498[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]9.72892[/C][C]1.57108[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]11.8462[/C][C]0.0537758[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]10.7697[/C][C]-1.46972[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]10.4416[/C][C]-0.841619[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]10.6846[/C][C]-0.68462[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]9.03791[/C][C]-2.63791[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]9.4127[/C][C]4.3873[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]11.2008[/C][C]-0.400819[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]11.7755[/C][C]2.02452[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]11.1101[/C][C]0.589858[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]11.7427[/C][C]-0.842719[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]12.6856[/C][C]3.41443[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]10.9214[/C][C]2.47857[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]11.6996[/C][C]-1.79955[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]10.7101[/C][C]0.789871[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]10.9827[/C][C]-2.68266[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]10.83[/C][C]0.870017[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]11.5561[/C][C]-5.45613[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]9.94655[/C][C]-0.946553[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]10.7775[/C][C]-1.07747[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]10.2832[/C][C]0.516827[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]10.0123[/C][C]0.287727[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]10.5407[/C][C]-0.140673[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]8.67646[/C][C]4.02354[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]11.1103[/C][C]-1.81033[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]11.7829[/C][C]0.0171325[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]10.4252[/C][C]-4.5252[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]10.6765[/C][C]0.723507[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]11.2863[/C][C]1.7137[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]10.7249[/C][C]0.0751082[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]9.6415[/C][C]2.6585[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]11.5891[/C][C]-0.289137[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]11.1059[/C][C]0.694077[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]10.2187[/C][C]-2.31869[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]11.2458[/C][C]1.45416[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]8.98886[/C][C]3.31114[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]9.90382[/C][C]1.69618[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]9.14836[/C][C]-2.44836[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]9.9645[/C][C]0.935498[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]9.39999[/C][C]2.70001[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]10.7142[/C][C]2.58585[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]10.2912[/C][C]-0.19121[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]9.86402[/C][C]-4.16402[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]9.78425[/C][C]4.51575[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]8.62087[/C][C]-0.620872[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]10.9568[/C][C]2.34317[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]12.6672[/C][C]-3.36718[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]9.78906[/C][C]2.71094[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]10.3284[/C][C]-2.72835[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]11.7995[/C][C]4.10054[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]10.8128[/C][C]-1.61283[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]9.24112[/C][C]-0.141123[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]12.0687[/C][C]-0.968669[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]13.9066[/C][C]-0.906607[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]9.54073[/C][C]4.95927[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]10.6567[/C][C]1.54328[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]12.2042[/C][C]0.0957831[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]10.5263[/C][C]0.873667[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]11.101[/C][C]-2.30102[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]11.7546[/C][C]2.84539[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]11.1611[/C][C]-3.86113[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.04[/C][C]1.56004[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]11.8349[/C][C]1.16508[/C][/ROW]
[ROW][C]80[/C][C]12.6[/C][C]9.79354[/C][C]2.80646[/C][/ROW]
[ROW][C]81[/C][C]13.2[/C][C]12.3381[/C][C]0.861866[/C][/ROW]
[ROW][C]82[/C][C]9.9[/C][C]9.84537[/C][C]0.0546328[/C][/ROW]
[ROW][C]83[/C][C]7.7[/C][C]11.0302[/C][C]-3.33018[/C][/ROW]
[ROW][C]84[/C][C]10.5[/C][C]10.742[/C][C]-0.241996[/C][/ROW]
[ROW][C]85[/C][C]13.4[/C][C]9.78937[/C][C]3.61063[/C][/ROW]
[ROW][C]86[/C][C]10.9[/C][C]11.2875[/C][C]-0.387457[/C][/ROW]
[ROW][C]87[/C][C]4.3[/C][C]9.13831[/C][C]-4.83831[/C][/ROW]
[ROW][C]88[/C][C]10.3[/C][C]10.6644[/C][C]-0.36437[/C][/ROW]
[ROW][C]89[/C][C]11.8[/C][C]11.6245[/C][C]0.175506[/C][/ROW]
[ROW][C]90[/C][C]11.2[/C][C]9.66493[/C][C]1.53507[/C][/ROW]
[ROW][C]91[/C][C]11.4[/C][C]9.55268[/C][C]1.84732[/C][/ROW]
[ROW][C]92[/C][C]8.6[/C][C]10.2355[/C][C]-1.63549[/C][/ROW]
[ROW][C]93[/C][C]13.2[/C][C]10.3145[/C][C]2.88553[/C][/ROW]
[ROW][C]94[/C][C]12.6[/C][C]9.68521[/C][C]2.91479[/C][/ROW]
[ROW][C]95[/C][C]5.6[/C][C]9.08596[/C][C]-3.48596[/C][/ROW]
[ROW][C]96[/C][C]9.9[/C][C]11.1108[/C][C]-1.21077[/C][/ROW]
[ROW][C]97[/C][C]8.8[/C][C]9.57455[/C][C]-0.774548[/C][/ROW]
[ROW][C]98[/C][C]7.7[/C][C]9.24048[/C][C]-1.54048[/C][/ROW]
[ROW][C]99[/C][C]9[/C][C]9.75318[/C][C]-0.753184[/C][/ROW]
[ROW][C]100[/C][C]7.3[/C][C]9.9215[/C][C]-2.6215[/C][/ROW]
[ROW][C]101[/C][C]11.4[/C][C]8.69713[/C][C]2.70287[/C][/ROW]
[ROW][C]102[/C][C]13.6[/C][C]9.30075[/C][C]4.29925[/C][/ROW]
[ROW][C]103[/C][C]7.9[/C][C]9.86956[/C][C]-1.96956[/C][/ROW]
[ROW][C]104[/C][C]10.7[/C][C]9.85137[/C][C]0.848635[/C][/ROW]
[ROW][C]105[/C][C]10.3[/C][C]10.2305[/C][C]0.0695469[/C][/ROW]
[ROW][C]106[/C][C]8.3[/C][C]8.83396[/C][C]-0.533962[/C][/ROW]
[ROW][C]107[/C][C]9.6[/C][C]9.98718[/C][C]-0.387179[/C][/ROW]
[ROW][C]108[/C][C]14.2[/C][C]10.1907[/C][C]4.00933[/C][/ROW]
[ROW][C]109[/C][C]8.5[/C][C]10.2429[/C][C]-1.74294[/C][/ROW]
[ROW][C]110[/C][C]13.5[/C][C]9.71231[/C][C]3.78769[/C][/ROW]
[ROW][C]111[/C][C]4.9[/C][C]10.0708[/C][C]-5.17081[/C][/ROW]
[ROW][C]112[/C][C]6.4[/C][C]9.82003[/C][C]-3.42003[/C][/ROW]
[ROW][C]113[/C][C]9.6[/C][C]11.224[/C][C]-1.62403[/C][/ROW]
[ROW][C]114[/C][C]11.6[/C][C]10.1042[/C][C]1.49584[/C][/ROW]
[ROW][C]115[/C][C]11.1[/C][C]8.90406[/C][C]2.19594[/C][/ROW]
[ROW][C]116[/C][C]4.35[/C][C]13.2018[/C][C]-8.85175[/C][/ROW]
[ROW][C]117[/C][C]12.7[/C][C]14.8872[/C][C]-2.18717[/C][/ROW]
[ROW][C]118[/C][C]18.1[/C][C]13.9201[/C][C]4.17986[/C][/ROW]
[ROW][C]119[/C][C]17.85[/C][C]14.1885[/C][C]3.66146[/C][/ROW]
[ROW][C]120[/C][C]16.6[/C][C]19.3532[/C][C]-2.75316[/C][/ROW]
[ROW][C]121[/C][C]12.6[/C][C]11.979[/C][C]0.621012[/C][/ROW]
[ROW][C]122[/C][C]17.1[/C][C]16.4883[/C][C]0.611713[/C][/ROW]
[ROW][C]123[/C][C]19.1[/C][C]17.0456[/C][C]2.05439[/C][/ROW]
[ROW][C]124[/C][C]16.1[/C][C]20.0006[/C][C]-3.90064[/C][/ROW]
[ROW][C]125[/C][C]13.35[/C][C]13.2162[/C][C]0.133764[/C][/ROW]
[ROW][C]126[/C][C]18.4[/C][C]16.2042[/C][C]2.19584[/C][/ROW]
[ROW][C]127[/C][C]14.7[/C][C]12.8339[/C][C]1.86606[/C][/ROW]
[ROW][C]128[/C][C]10.6[/C][C]14.1391[/C][C]-3.53908[/C][/ROW]
[ROW][C]129[/C][C]12.6[/C][C]13.2451[/C][C]-0.645132[/C][/ROW]
[ROW][C]130[/C][C]16.2[/C][C]14.0028[/C][C]2.19721[/C][/ROW]
[ROW][C]131[/C][C]13.6[/C][C]15.172[/C][C]-1.572[/C][/ROW]
[ROW][C]132[/C][C]18.9[/C][C]15.6217[/C][C]3.27833[/C][/ROW]
[ROW][C]133[/C][C]14.1[/C][C]13.3663[/C][C]0.733723[/C][/ROW]
[ROW][C]134[/C][C]14.5[/C][C]13.1457[/C][C]1.35429[/C][/ROW]
[ROW][C]135[/C][C]16.15[/C][C]16.92[/C][C]-0.769987[/C][/ROW]
[ROW][C]136[/C][C]14.75[/C][C]13.7734[/C][C]0.976592[/C][/ROW]
[ROW][C]137[/C][C]14.8[/C][C]14.4718[/C][C]0.328222[/C][/ROW]
[ROW][C]138[/C][C]12.45[/C][C]13.6301[/C][C]-1.18009[/C][/ROW]
[ROW][C]139[/C][C]12.65[/C][C]14.6012[/C][C]-1.95123[/C][/ROW]
[ROW][C]140[/C][C]17.35[/C][C]13.9584[/C][C]3.39158[/C][/ROW]
[ROW][C]141[/C][C]8.6[/C][C]13.3314[/C][C]-4.73143[/C][/ROW]
[ROW][C]142[/C][C]18.4[/C][C]16.4893[/C][C]1.91073[/C][/ROW]
[ROW][C]143[/C][C]16.1[/C][C]16.3382[/C][C]-0.238173[/C][/ROW]
[ROW][C]144[/C][C]11.6[/C][C]12.496[/C][C]-0.895968[/C][/ROW]
[ROW][C]145[/C][C]17.75[/C][C]12.6314[/C][C]5.11863[/C][/ROW]
[ROW][C]146[/C][C]15.25[/C][C]14.3958[/C][C]0.854199[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]14.1698[/C][C]3.48021[/C][/ROW]
[ROW][C]148[/C][C]15.6[/C][C]13.9775[/C][C]1.62246[/C][/ROW]
[ROW][C]149[/C][C]16.35[/C][C]15.6991[/C][C]0.650898[/C][/ROW]
[ROW][C]150[/C][C]17.65[/C][C]16.9246[/C][C]0.725449[/C][/ROW]
[ROW][C]151[/C][C]13.6[/C][C]14.3357[/C][C]-0.735676[/C][/ROW]
[ROW][C]152[/C][C]11.7[/C][C]13.8721[/C][C]-2.17205[/C][/ROW]
[ROW][C]153[/C][C]14.35[/C][C]15.2611[/C][C]-0.911113[/C][/ROW]
[ROW][C]154[/C][C]14.75[/C][C]14.9761[/C][C]-0.226083[/C][/ROW]
[ROW][C]155[/C][C]18.25[/C][C]14.0979[/C][C]4.15214[/C][/ROW]
[ROW][C]156[/C][C]9.9[/C][C]14.1793[/C][C]-4.27926[/C][/ROW]
[ROW][C]157[/C][C]16[/C][C]16.3988[/C][C]-0.398798[/C][/ROW]
[ROW][C]158[/C][C]18.25[/C][C]14.5403[/C][C]3.70973[/C][/ROW]
[ROW][C]159[/C][C]16.85[/C][C]15.3113[/C][C]1.53869[/C][/ROW]
[ROW][C]160[/C][C]14.6[/C][C]13.6212[/C][C]0.978804[/C][/ROW]
[ROW][C]161[/C][C]13.85[/C][C]15.207[/C][C]-1.35702[/C][/ROW]
[ROW][C]162[/C][C]18.95[/C][C]17.017[/C][C]1.93304[/C][/ROW]
[ROW][C]163[/C][C]15.6[/C][C]14.9375[/C][C]0.66252[/C][/ROW]
[ROW][C]164[/C][C]14.85[/C][C]17.2352[/C][C]-2.38516[/C][/ROW]
[ROW][C]165[/C][C]11.75[/C][C]14.3897[/C][C]-2.63969[/C][/ROW]
[ROW][C]166[/C][C]18.45[/C][C]16.9472[/C][C]1.50276[/C][/ROW]
[ROW][C]167[/C][C]15.9[/C][C]14.1806[/C][C]1.71937[/C][/ROW]
[ROW][C]168[/C][C]17.1[/C][C]16.385[/C][C]0.714995[/C][/ROW]
[ROW][C]169[/C][C]16.1[/C][C]13.6884[/C][C]2.41157[/C][/ROW]
[ROW][C]170[/C][C]19.9[/C][C]17.3496[/C][C]2.55036[/C][/ROW]
[ROW][C]171[/C][C]10.95[/C][C]12.1513[/C][C]-1.20133[/C][/ROW]
[ROW][C]172[/C][C]18.45[/C][C]16.3105[/C][C]2.13946[/C][/ROW]
[ROW][C]173[/C][C]15.1[/C][C]12.491[/C][C]2.60897[/C][/ROW]
[ROW][C]174[/C][C]15[/C][C]15.1158[/C][C]-0.115832[/C][/ROW]
[ROW][C]175[/C][C]11.35[/C][C]15.4884[/C][C]-4.13836[/C][/ROW]
[ROW][C]176[/C][C]15.95[/C][C]14.6637[/C][C]1.28633[/C][/ROW]
[ROW][C]177[/C][C]18.1[/C][C]15.2835[/C][C]2.81655[/C][/ROW]
[ROW][C]178[/C][C]14.6[/C][C]15.0259[/C][C]-0.425892[/C][/ROW]
[ROW][C]179[/C][C]15.4[/C][C]13.9339[/C][C]1.46607[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]13.8717[/C][C]1.5283[/C][/ROW]
[ROW][C]181[/C][C]17.6[/C][C]14.6084[/C][C]2.99156[/C][/ROW]
[ROW][C]182[/C][C]13.35[/C][C]15.2121[/C][C]-1.86207[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]15.087[/C][C]4.01305[/C][/ROW]
[ROW][C]184[/C][C]15.35[/C][C]14.8106[/C][C]0.5394[/C][/ROW]
[ROW][C]185[/C][C]7.6[/C][C]13.5369[/C][C]-5.93692[/C][/ROW]
[ROW][C]186[/C][C]13.4[/C][C]17.1543[/C][C]-3.75433[/C][/ROW]
[ROW][C]187[/C][C]13.9[/C][C]14.8694[/C][C]-0.969367[/C][/ROW]
[ROW][C]188[/C][C]19.1[/C][C]15.6098[/C][C]3.49022[/C][/ROW]
[ROW][C]189[/C][C]15.25[/C][C]15.4228[/C][C]-0.172781[/C][/ROW]
[ROW][C]190[/C][C]12.9[/C][C]13.0569[/C][C]-0.156883[/C][/ROW]
[ROW][C]191[/C][C]16.1[/C][C]15.7278[/C][C]0.37222[/C][/ROW]
[ROW][C]192[/C][C]17.35[/C][C]13.8288[/C][C]3.52119[/C][/ROW]
[ROW][C]193[/C][C]13.15[/C][C]14.6508[/C][C]-1.5008[/C][/ROW]
[ROW][C]194[/C][C]12.15[/C][C]12.6366[/C][C]-0.486567[/C][/ROW]
[ROW][C]195[/C][C]12.6[/C][C]13.6723[/C][C]-1.07232[/C][/ROW]
[ROW][C]196[/C][C]10.35[/C][C]13.7336[/C][C]-3.38356[/C][/ROW]
[ROW][C]197[/C][C]15.4[/C][C]14.2044[/C][C]1.19556[/C][/ROW]
[ROW][C]198[/C][C]9.6[/C][C]13.4038[/C][C]-3.80382[/C][/ROW]
[ROW][C]199[/C][C]18.2[/C][C]14.3698[/C][C]3.83023[/C][/ROW]
[ROW][C]200[/C][C]13.6[/C][C]14.6306[/C][C]-1.03058[/C][/ROW]
[ROW][C]201[/C][C]14.85[/C][C]14.7368[/C][C]0.113165[/C][/ROW]
[ROW][C]202[/C][C]14.75[/C][C]15.98[/C][C]-1.22999[/C][/ROW]
[ROW][C]203[/C][C]14.1[/C][C]14.2207[/C][C]-0.120659[/C][/ROW]
[ROW][C]204[/C][C]14.9[/C][C]13.765[/C][C]1.13502[/C][/ROW]
[ROW][C]205[/C][C]16.25[/C][C]15.1914[/C][C]1.05855[/C][/ROW]
[ROW][C]206[/C][C]19.25[/C][C]15.4795[/C][C]3.77048[/C][/ROW]
[ROW][C]207[/C][C]13.6[/C][C]14.0346[/C][C]-0.434561[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]14.6149[/C][C]-1.01494[/C][/ROW]
[ROW][C]209[/C][C]15.65[/C][C]14.6369[/C][C]1.01308[/C][/ROW]
[ROW][C]210[/C][C]12.75[/C][C]12.4798[/C][C]0.270235[/C][/ROW]
[ROW][C]211[/C][C]14.6[/C][C]13.8467[/C][C]0.75327[/C][/ROW]
[ROW][C]212[/C][C]9.85[/C][C]13.9736[/C][C]-4.12363[/C][/ROW]
[ROW][C]213[/C][C]12.65[/C][C]13.4708[/C][C]-0.82077[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]13.2843[/C][C]-1.3843[/C][/ROW]
[ROW][C]215[/C][C]19.2[/C][C]15.9235[/C][C]3.27646[/C][/ROW]
[ROW][C]216[/C][C]16.6[/C][C]14.633[/C][C]1.96696[/C][/ROW]
[ROW][C]217[/C][C]11.2[/C][C]14.0503[/C][C]-2.8503[/C][/ROW]
[ROW][C]218[/C][C]15.25[/C][C]13.4833[/C][C]1.76667[/C][/ROW]
[ROW][C]219[/C][C]11.9[/C][C]15.6357[/C][C]-3.73571[/C][/ROW]
[ROW][C]220[/C][C]13.2[/C][C]13.653[/C][C]-0.452988[/C][/ROW]
[ROW][C]221[/C][C]16.35[/C][C]16.538[/C][C]-0.18803[/C][/ROW]
[ROW][C]222[/C][C]12.4[/C][C]13.6861[/C][C]-1.28615[/C][/ROW]
[ROW][C]223[/C][C]15.85[/C][C]14.2609[/C][C]1.58906[/C][/ROW]
[ROW][C]224[/C][C]14.35[/C][C]14.1765[/C][C]0.173473[/C][/ROW]
[ROW][C]225[/C][C]18.15[/C][C]13.9616[/C][C]4.18844[/C][/ROW]
[ROW][C]226[/C][C]11.15[/C][C]13.9634[/C][C]-2.81342[/C][/ROW]
[ROW][C]227[/C][C]15.65[/C][C]15.8511[/C][C]-0.201083[/C][/ROW]
[ROW][C]228[/C][C]17.75[/C][C]14.2321[/C][C]3.51792[/C][/ROW]
[ROW][C]229[/C][C]7.65[/C][C]13.3838[/C][C]-5.73385[/C][/ROW]
[ROW][C]230[/C][C]12.35[/C][C]13.3056[/C][C]-0.955554[/C][/ROW]
[ROW][C]231[/C][C]15.6[/C][C]12.1561[/C][C]3.44391[/C][/ROW]
[ROW][C]232[/C][C]19.3[/C][C]15.3674[/C][C]3.93262[/C][/ROW]
[ROW][C]233[/C][C]15.2[/C][C]13.4639[/C][C]1.73606[/C][/ROW]
[ROW][C]234[/C][C]17.1[/C][C]13.7742[/C][C]3.32578[/C][/ROW]
[ROW][C]235[/C][C]15.6[/C][C]13.4839[/C][C]2.1161[/C][/ROW]
[ROW][C]236[/C][C]18.4[/C][C]16.4903[/C][C]1.90973[/C][/ROW]
[ROW][C]237[/C][C]19.05[/C][C]15.0026[/C][C]4.04737[/C][/ROW]
[ROW][C]238[/C][C]18.55[/C][C]13.3202[/C][C]5.22977[/C][/ROW]
[ROW][C]239[/C][C]19.1[/C][C]17.5741[/C][C]1.52588[/C][/ROW]
[ROW][C]240[/C][C]13.1[/C][C]13.1349[/C][C]-0.0349124[/C][/ROW]
[ROW][C]241[/C][C]12.85[/C][C]13.22[/C][C]-0.370032[/C][/ROW]
[ROW][C]242[/C][C]9.5[/C][C]12.5912[/C][C]-3.09117[/C][/ROW]
[ROW][C]243[/C][C]4.5[/C][C]13.3381[/C][C]-8.83813[/C][/ROW]
[ROW][C]244[/C][C]11.85[/C][C]13.0471[/C][C]-1.19709[/C][/ROW]
[ROW][C]245[/C][C]13.6[/C][C]13.8857[/C][C]-0.285734[/C][/ROW]
[ROW][C]246[/C][C]11.7[/C][C]14.8872[/C][C]-3.18719[/C][/ROW]
[ROW][C]247[/C][C]12.4[/C][C]13.1123[/C][C]-0.712251[/C][/ROW]
[ROW][C]248[/C][C]13.35[/C][C]15.7419[/C][C]-2.39187[/C][/ROW]
[ROW][C]249[/C][C]11.4[/C][C]14.2035[/C][C]-2.80354[/C][/ROW]
[ROW][C]250[/C][C]14.9[/C][C]13.6737[/C][C]1.22629[/C][/ROW]
[ROW][C]251[/C][C]19.9[/C][C]16.6889[/C][C]3.21114[/C][/ROW]
[ROW][C]252[/C][C]17.75[/C][C]13.6992[/C][C]4.05078[/C][/ROW]
[ROW][C]253[/C][C]11.2[/C][C]13.2321[/C][C]-2.0321[/C][/ROW]
[ROW][C]254[/C][C]14.6[/C][C]14.4873[/C][C]0.112732[/C][/ROW]
[ROW][C]255[/C][C]17.6[/C][C]17.0101[/C][C]0.589908[/C][/ROW]
[ROW][C]256[/C][C]14.05[/C][C]13.0619[/C][C]0.988061[/C][/ROW]
[ROW][C]257[/C][C]16.1[/C][C]16.1891[/C][C]-0.0890703[/C][/ROW]
[ROW][C]258[/C][C]13.35[/C][C]13.2[/C][C]0.149957[/C][/ROW]
[ROW][C]259[/C][C]11.85[/C][C]12.7278[/C][C]-0.87782[/C][/ROW]
[ROW][C]260[/C][C]11.95[/C][C]15.6162[/C][C]-3.66622[/C][/ROW]
[ROW][C]261[/C][C]14.75[/C][C]14.6688[/C][C]0.0812108[/C][/ROW]
[ROW][C]262[/C][C]15.15[/C][C]15.2619[/C][C]-0.11187[/C][/ROW]
[ROW][C]263[/C][C]13.2[/C][C]13.7711[/C][C]-0.571141[/C][/ROW]
[ROW][C]264[/C][C]16.85[/C][C]16.1642[/C][C]0.685782[/C][/ROW]
[ROW][C]265[/C][C]7.85[/C][C]13.0481[/C][C]-5.19813[/C][/ROW]
[ROW][C]266[/C][C]7.7[/C][C]13.7221[/C][C]-6.02206[/C][/ROW]
[ROW][C]267[/C][C]12.6[/C][C]15.1123[/C][C]-2.5123[/C][/ROW]
[ROW][C]268[/C][C]7.85[/C][C]14.12[/C][C]-6.26998[/C][/ROW]
[ROW][C]269[/C][C]10.95[/C][C]12.8795[/C][C]-1.92947[/C][/ROW]
[ROW][C]270[/C][C]12.35[/C][C]14.6506[/C][C]-2.3006[/C][/ROW]
[ROW][C]271[/C][C]9.95[/C][C]12.9947[/C][C]-3.04465[/C][/ROW]
[ROW][C]272[/C][C]14.9[/C][C]13.3914[/C][C]1.50862[/C][/ROW]
[ROW][C]273[/C][C]16.65[/C][C]14.8084[/C][C]1.84156[/C][/ROW]
[ROW][C]274[/C][C]13.4[/C][C]14.3529[/C][C]-0.952875[/C][/ROW]
[ROW][C]275[/C][C]13.95[/C][C]14.3822[/C][C]-0.432221[/C][/ROW]
[ROW][C]276[/C][C]15.7[/C][C]13.6547[/C][C]2.04534[/C][/ROW]
[ROW][C]277[/C][C]16.85[/C][C]14.2796[/C][C]2.57038[/C][/ROW]
[ROW][C]278[/C][C]10.95[/C][C]13.5713[/C][C]-2.62133[/C][/ROW]
[ROW][C]279[/C][C]15.35[/C][C]13.1406[/C][C]2.20936[/C][/ROW]
[ROW][C]280[/C][C]12.2[/C][C]13.0086[/C][C]-0.808619[/C][/ROW]
[ROW][C]281[/C][C]15.1[/C][C]14.7752[/C][C]0.324775[/C][/ROW]
[ROW][C]282[/C][C]17.75[/C][C]16.2378[/C][C]1.51223[/C][/ROW]
[ROW][C]283[/C][C]15.2[/C][C]14.7751[/C][C]0.42485[/C][/ROW]
[ROW][C]284[/C][C]14.6[/C][C]14.8495[/C][C]-0.249458[/C][/ROW]
[ROW][C]285[/C][C]16.65[/C][C]15.0825[/C][C]1.56746[/C][/ROW]
[ROW][C]286[/C][C]8.1[/C][C]12.4003[/C][C]-4.30031[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&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
112.913.1887-0.288725
27.411.9088-4.5088
312.210.56081.63924
412.811.05161.7484
57.411.433-4.03296
66.710.4839-3.78385
712.610.53612.06386
814.811.95272.84727
913.312.64180.658219
1011.111.9747-0.87474
118.211.1935-2.9935
1211.410.82920.570846
136.411.5594-5.15936
1410.69.268831.33117
151213.0204-1.02035
166.39.61498-3.31498
1711.39.728921.57108
1811.911.84620.0537758
199.310.7697-1.46972
209.610.4416-0.841619
211010.6846-0.68462
226.49.03791-2.63791
2313.89.41274.3873
2410.811.2008-0.400819
2513.811.77552.02452
2611.711.11010.589858
2710.911.7427-0.842719
2816.112.68563.41443
2913.410.92142.47857
309.911.6996-1.79955
3111.510.71010.789871
328.310.9827-2.68266
3311.710.830.870017
346.111.5561-5.45613
3599.94655-0.946553
369.710.7775-1.07747
3710.810.28320.516827
3810.310.01230.287727
3910.410.5407-0.140673
4012.78.676464.02354
419.311.1103-1.81033
4211.811.78290.0171325
435.910.4252-4.5252
4411.410.67650.723507
451311.28631.7137
4610.810.72490.0751082
4712.39.64152.6585
4811.311.5891-0.289137
4911.811.10590.694077
507.910.2187-2.31869
5112.711.24581.45416
5212.38.988863.31114
5311.69.903821.69618
546.79.14836-2.44836
5510.99.96450.935498
5612.19.399992.70001
5713.310.71422.58585
5810.110.2912-0.19121
595.79.86402-4.16402
6014.39.784254.51575
6188.62087-0.620872
6213.310.95682.34317
639.312.6672-3.36718
6412.59.789062.71094
657.610.3284-2.72835
6615.911.79954.10054
679.210.8128-1.61283
689.19.24112-0.141123
6911.112.0687-0.968669
701313.9066-0.906607
7114.59.540734.95927
7212.210.65671.54328
7312.312.20420.0957831
7411.410.52630.873667
758.811.101-2.30102
7614.611.75462.84539
777.311.1611-3.86113
7812.611.041.56004
791311.83491.16508
8012.69.793542.80646
8113.212.33810.861866
829.99.845370.0546328
837.711.0302-3.33018
8410.510.742-0.241996
8513.49.789373.61063
8610.911.2875-0.387457
874.39.13831-4.83831
8810.310.6644-0.36437
8911.811.62450.175506
9011.29.664931.53507
9111.49.552681.84732
928.610.2355-1.63549
9313.210.31452.88553
9412.69.685212.91479
955.69.08596-3.48596
969.911.1108-1.21077
978.89.57455-0.774548
987.79.24048-1.54048
9999.75318-0.753184
1007.39.9215-2.6215
10111.48.697132.70287
10213.69.300754.29925
1037.99.86956-1.96956
10410.79.851370.848635
10510.310.23050.0695469
1068.38.83396-0.533962
1079.69.98718-0.387179
10814.210.19074.00933
1098.510.2429-1.74294
11013.59.712313.78769
1114.910.0708-5.17081
1126.49.82003-3.42003
1139.611.224-1.62403
11411.610.10421.49584
11511.18.904062.19594
1164.3513.2018-8.85175
11712.714.8872-2.18717
11818.113.92014.17986
11917.8514.18853.66146
12016.619.3532-2.75316
12112.611.9790.621012
12217.116.48830.611713
12319.117.04562.05439
12416.120.0006-3.90064
12513.3513.21620.133764
12618.416.20422.19584
12714.712.83391.86606
12810.614.1391-3.53908
12912.613.2451-0.645132
13016.214.00282.19721
13113.615.172-1.572
13218.915.62173.27833
13314.113.36630.733723
13414.513.14571.35429
13516.1516.92-0.769987
13614.7513.77340.976592
13714.814.47180.328222
13812.4513.6301-1.18009
13912.6514.6012-1.95123
14017.3513.95843.39158
1418.613.3314-4.73143
14218.416.48931.91073
14316.116.3382-0.238173
14411.612.496-0.895968
14517.7512.63145.11863
14615.2514.39580.854199
14717.6514.16983.48021
14815.613.97751.62246
14916.3515.69910.650898
15017.6516.92460.725449
15113.614.3357-0.735676
15211.713.8721-2.17205
15314.3515.2611-0.911113
15414.7514.9761-0.226083
15518.2514.09794.15214
1569.914.1793-4.27926
1571616.3988-0.398798
15818.2514.54033.70973
15916.8515.31131.53869
16014.613.62120.978804
16113.8515.207-1.35702
16218.9517.0171.93304
16315.614.93750.66252
16414.8517.2352-2.38516
16511.7514.3897-2.63969
16618.4516.94721.50276
16715.914.18061.71937
16817.116.3850.714995
16916.113.68842.41157
17019.917.34962.55036
17110.9512.1513-1.20133
17218.4516.31052.13946
17315.112.4912.60897
1741515.1158-0.115832
17511.3515.4884-4.13836
17615.9514.66371.28633
17718.115.28352.81655
17814.615.0259-0.425892
17915.413.93391.46607
18015.413.87171.5283
18117.614.60842.99156
18213.3515.2121-1.86207
18319.115.0874.01305
18415.3514.81060.5394
1857.613.5369-5.93692
18613.417.1543-3.75433
18713.914.8694-0.969367
18819.115.60983.49022
18915.2515.4228-0.172781
19012.913.0569-0.156883
19116.115.72780.37222
19217.3513.82883.52119
19313.1514.6508-1.5008
19412.1512.6366-0.486567
19512.613.6723-1.07232
19610.3513.7336-3.38356
19715.414.20441.19556
1989.613.4038-3.80382
19918.214.36983.83023
20013.614.6306-1.03058
20114.8514.73680.113165
20214.7515.98-1.22999
20314.114.2207-0.120659
20414.913.7651.13502
20516.2515.19141.05855
20619.2515.47953.77048
20713.614.0346-0.434561
20813.614.6149-1.01494
20915.6514.63691.01308
21012.7512.47980.270235
21114.613.84670.75327
2129.8513.9736-4.12363
21312.6513.4708-0.82077
21411.913.2843-1.3843
21519.215.92353.27646
21616.614.6331.96696
21711.214.0503-2.8503
21815.2513.48331.76667
21911.915.6357-3.73571
22013.213.653-0.452988
22116.3516.538-0.18803
22212.413.6861-1.28615
22315.8514.26091.58906
22414.3514.17650.173473
22518.1513.96164.18844
22611.1513.9634-2.81342
22715.6515.8511-0.201083
22817.7514.23213.51792
2297.6513.3838-5.73385
23012.3513.3056-0.955554
23115.612.15613.44391
23219.315.36743.93262
23315.213.46391.73606
23417.113.77423.32578
23515.613.48392.1161
23618.416.49031.90973
23719.0515.00264.04737
23818.5513.32025.22977
23919.117.57411.52588
24013.113.1349-0.0349124
24112.8513.22-0.370032
2429.512.5912-3.09117
2434.513.3381-8.83813
24411.8513.0471-1.19709
24513.613.8857-0.285734
24611.714.8872-3.18719
24712.413.1123-0.712251
24813.3515.7419-2.39187
24911.414.2035-2.80354
25014.913.67371.22629
25119.916.68893.21114
25217.7513.69924.05078
25311.213.2321-2.0321
25414.614.48730.112732
25517.617.01010.589908
25614.0513.06190.988061
25716.116.1891-0.0890703
25813.3513.20.149957
25911.8512.7278-0.87782
26011.9515.6162-3.66622
26114.7514.66880.0812108
26215.1515.2619-0.11187
26313.213.7711-0.571141
26416.8516.16420.685782
2657.8513.0481-5.19813
2667.713.7221-6.02206
26712.615.1123-2.5123
2687.8514.12-6.26998
26910.9512.8795-1.92947
27012.3514.6506-2.3006
2719.9512.9947-3.04465
27214.913.39141.50862
27316.6514.80841.84156
27413.414.3529-0.952875
27513.9514.3822-0.432221
27615.713.65472.04534
27716.8514.27962.57038
27810.9513.5713-2.62133
27915.3513.14062.20936
28012.213.0086-0.808619
28115.114.77520.324775
28217.7516.23781.51223
28315.214.77510.42485
28414.614.8495-0.249458
28516.6515.08251.56746
2868.112.4003-4.30031






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
120.9474090.1051820.052591
130.9592650.08146910.0407345
140.9251460.1497070.0748536
150.8756530.2486950.124347
160.841430.3171410.15857
170.7722180.4555630.227782
180.692520.6149610.30748
190.6066080.7867850.393392
200.5202340.9595310.479766
210.4359240.8718480.564076
220.3814490.7628980.618551
230.5662130.8675730.433787
240.4945950.9891890.505405
250.5058860.9882290.494114
260.4334310.8668610.566569
270.3675640.7351280.632436
280.3583460.7166920.641654
290.3071830.6143660.692817
300.254280.5085590.74572
310.2172880.4345760.782712
320.3110040.6220080.688996
330.2582450.5164890.741755
340.4573790.9147580.542621
350.4067240.8134480.593276
360.3546570.7093130.645343
370.3017660.6035320.698234
380.2641160.5282320.735884
390.2294550.4589090.770545
400.2121950.424390.787805
410.1844830.3689660.815517
420.1569670.3139350.843033
430.1892660.3785320.810734
440.1808830.3617670.819117
450.1869970.3739950.813003
460.1539230.3078460.846077
470.128760.2575210.87124
480.1136120.2272250.886388
490.09378770.1875750.906212
500.09937390.1987480.900626
510.1025650.2051290.897435
520.1085470.2170940.891453
530.08941880.1788380.910581
540.1323940.2647880.867606
550.1198220.2396430.880178
560.1151340.2302670.884866
570.144520.2890390.85548
580.120270.240540.87973
590.2340870.4681740.765913
600.2531080.5062170.746892
610.2201820.4403640.779818
620.2115490.4230980.788451
630.2162580.4325150.783742
640.2333360.4666730.766664
650.3081090.6162180.691891
660.3851130.7702250.614887
670.3615790.7231580.638421
680.3376020.6752040.662398
690.3032880.6065750.696712
700.2701490.5402990.729851
710.3606610.7213220.639339
720.3341120.6682230.665888
730.3000910.6001830.699909
740.2763050.552610.723695
750.2778790.5557570.722121
760.286390.572780.71361
770.3356390.6712790.664361
780.3146380.6292760.685362
790.2887050.5774110.711295
800.278160.556320.72184
810.2610110.5220220.738989
820.2342940.4685870.765706
830.2519880.5039750.748012
840.2227710.4455410.777229
850.2336440.4672880.766356
860.2067820.4135630.793218
870.3245860.6491710.675414
880.3021230.6042460.697877
890.2697510.5395020.730249
900.2442760.4885510.755724
910.2273180.4546360.772682
920.2139890.4279790.786011
930.214040.428080.78596
940.2101180.4202360.789882
950.2641070.5282150.735893
960.2451480.4902960.754852
970.2225490.4450980.777451
980.2134510.4269010.786549
990.1913910.3827810.808609
1000.1964130.3928260.803587
1010.1924050.384810.807595
1020.2289630.4579260.771037
1030.2234460.4468920.776554
1040.1983450.3966910.801655
1050.1739640.3479270.826036
1060.1614670.3229340.838533
1070.1419730.2839450.858027
1080.1687870.3375740.831213
1090.1605140.3210270.839486
1100.1850380.3700770.814962
1110.2675710.5351420.732429
1120.296330.5926590.70367
1130.2868990.5737990.713101
1140.2650670.5301350.734933
1150.243560.4871210.75644
1160.3556790.7113570.644321
1170.3986240.7972470.601376
1180.5912610.8174770.408739
1190.6614020.6771950.338598
1200.6533230.6933540.346677
1210.623840.7523210.37616
1220.6024430.7951150.397557
1230.6036710.7926580.396329
1240.6534060.6931880.346594
1250.6216660.7566680.378334
1260.6202430.7595140.379757
1270.6018880.7962250.398112
1280.6339190.7321620.366081
1290.6030570.7938850.396943
1300.5920840.8158320.407916
1310.5726540.8546920.427346
1320.5899690.8200620.410031
1330.5579940.8840120.442006
1340.5310460.9379080.468954
1350.5038580.9922840.496142
1360.4723880.9447760.527612
1370.4380630.8761260.561937
1380.4124960.8249920.587504
1390.4004520.8009040.599548
1400.4222510.8445010.577749
1410.5097040.9805910.490296
1420.4936270.9872540.506373
1430.4629920.9259840.537008
1440.4392070.8784140.560793
1450.5371850.9256290.462815
1460.5037140.9925720.496286
1470.5228090.9543830.477191
1480.501450.99710.49855
1490.4683480.9366970.531652
1500.4384710.8769430.561529
1510.4096020.8192040.590398
1520.4010610.8021220.598939
1530.3741550.7483090.625845
1540.3427240.6854480.657276
1550.3879020.7758040.612098
1560.4574930.9149850.542507
1570.4280360.8560720.571964
1580.4565260.9130520.543474
1590.4337680.8675350.566232
1600.404810.8096190.59519
1610.3849060.7698130.615094
1620.3642630.7285250.635737
1630.3329020.6658050.667098
1640.3425360.6850720.657464
1650.3421760.6843520.657824
1660.3182850.6365690.681715
1670.3000360.6000720.699964
1680.2724040.5448080.727596
1690.2660530.5321070.733947
1700.2572340.5144690.742766
1710.2395960.4791920.760404
1720.2258270.4516530.774173
1730.2347420.4694840.765258
1740.209070.4181390.79093
1750.2654750.5309510.734525
1760.240940.4818810.75906
1770.2403610.4807220.759639
1780.2155970.4311950.784403
1790.1981720.3963440.801828
1800.1828950.3657890.817105
1810.190820.3816390.80918
1820.1811810.3623630.818819
1830.2218930.4437870.778107
1840.1993660.3987320.800634
1850.322090.6441790.67791
1860.3824320.7648630.617568
1870.3525680.7051360.647432
1880.3806750.7613490.619325
1890.3475820.6951630.652418
1900.3191080.6382150.680892
1910.2880660.5761330.711934
1920.3100020.6200050.689998
1930.2931570.5863140.706843
1940.2636160.5272320.736384
1950.2393120.4786230.760688
1960.2486470.4972940.751353
1970.22490.4497990.7751
1980.2515610.5031230.748439
1990.2752540.5505080.724746
2000.2483890.4967780.751611
2010.2193660.4387330.780634
2020.2018780.4037550.798122
2030.1761660.3523310.823834
2040.1585940.3171890.841406
2050.1380090.2760180.861991
2060.1569680.3139360.843032
2070.1357590.2715180.864241
2080.1205270.2410550.879473
2090.1042860.2085730.895714
2100.08953690.1790740.910463
2110.07668730.1533750.923313
2120.0978920.1957840.902108
2130.08414140.1682830.915859
2140.0720650.144130.927935
2150.07528930.1505790.924711
2160.0730660.1461320.926934
2170.07109220.1421840.928908
2180.06477060.1295410.935229
2190.08956980.179140.91043
2200.07424750.1484950.925752
2210.06373980.127480.93626
2220.05368840.1073770.946312
2230.05325590.1065120.946744
2240.04281740.08563480.957183
2250.05930430.1186090.940696
2260.05432250.1086450.945677
2270.04368060.08736120.956319
2280.04796260.09592530.952037
2290.1097350.219470.890265
2300.09146380.1829280.908536
2310.1390550.278110.860945
2320.1665930.3331870.833407
2330.1529890.3059780.847011
2340.1716690.3433370.828331
2350.1723070.3446140.827693
2360.153410.3068190.84659
2370.2107230.4214470.789277
2380.3841080.7682150.615892
2390.3434390.6868780.656561
2400.3021770.6043540.697823
2410.2886340.5772670.711366
2420.2596570.5193140.740343
2430.6452960.7094080.354704
2440.596650.80670.40335
2450.5472740.9054520.452726
2460.5370280.9259450.462972
2470.4831120.9662230.516888
2480.5345260.9309490.465474
2490.4883330.9766660.511667
2500.4565460.9130920.543454
2510.4392580.8785160.560742
2520.5927680.8144640.407232
2530.5392690.9214610.460731
2540.4903680.9807370.509632
2550.4329860.8659720.567014
2560.4958490.9916990.504151
2570.4326540.8653070.567346
2580.4173840.8347680.582616
2590.447040.894080.55296
2600.4253140.8506280.574686
2610.3722670.7445330.627733
2620.3335490.6670980.666451
2630.6051070.7897860.394893
2640.551070.897860.44893
2650.5885750.8228490.411425
2660.7803460.4393070.219654
2670.7579280.4841440.242072
2680.9052610.1894780.0947389
2690.8581840.2836330.141816
2700.9074960.1850080.0925038
2710.8424140.3151720.157586
2720.8651440.2697120.134856
2730.7749670.4500670.225033
2740.6190950.761810.380905

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
12 & 0.947409 & 0.105182 & 0.052591 \tabularnewline
13 & 0.959265 & 0.0814691 & 0.0407345 \tabularnewline
14 & 0.925146 & 0.149707 & 0.0748536 \tabularnewline
15 & 0.875653 & 0.248695 & 0.124347 \tabularnewline
16 & 0.84143 & 0.317141 & 0.15857 \tabularnewline
17 & 0.772218 & 0.455563 & 0.227782 \tabularnewline
18 & 0.69252 & 0.614961 & 0.30748 \tabularnewline
19 & 0.606608 & 0.786785 & 0.393392 \tabularnewline
20 & 0.520234 & 0.959531 & 0.479766 \tabularnewline
21 & 0.435924 & 0.871848 & 0.564076 \tabularnewline
22 & 0.381449 & 0.762898 & 0.618551 \tabularnewline
23 & 0.566213 & 0.867573 & 0.433787 \tabularnewline
24 & 0.494595 & 0.989189 & 0.505405 \tabularnewline
25 & 0.505886 & 0.988229 & 0.494114 \tabularnewline
26 & 0.433431 & 0.866861 & 0.566569 \tabularnewline
27 & 0.367564 & 0.735128 & 0.632436 \tabularnewline
28 & 0.358346 & 0.716692 & 0.641654 \tabularnewline
29 & 0.307183 & 0.614366 & 0.692817 \tabularnewline
30 & 0.25428 & 0.508559 & 0.74572 \tabularnewline
31 & 0.217288 & 0.434576 & 0.782712 \tabularnewline
32 & 0.311004 & 0.622008 & 0.688996 \tabularnewline
33 & 0.258245 & 0.516489 & 0.741755 \tabularnewline
34 & 0.457379 & 0.914758 & 0.542621 \tabularnewline
35 & 0.406724 & 0.813448 & 0.593276 \tabularnewline
36 & 0.354657 & 0.709313 & 0.645343 \tabularnewline
37 & 0.301766 & 0.603532 & 0.698234 \tabularnewline
38 & 0.264116 & 0.528232 & 0.735884 \tabularnewline
39 & 0.229455 & 0.458909 & 0.770545 \tabularnewline
40 & 0.212195 & 0.42439 & 0.787805 \tabularnewline
41 & 0.184483 & 0.368966 & 0.815517 \tabularnewline
42 & 0.156967 & 0.313935 & 0.843033 \tabularnewline
43 & 0.189266 & 0.378532 & 0.810734 \tabularnewline
44 & 0.180883 & 0.361767 & 0.819117 \tabularnewline
45 & 0.186997 & 0.373995 & 0.813003 \tabularnewline
46 & 0.153923 & 0.307846 & 0.846077 \tabularnewline
47 & 0.12876 & 0.257521 & 0.87124 \tabularnewline
48 & 0.113612 & 0.227225 & 0.886388 \tabularnewline
49 & 0.0937877 & 0.187575 & 0.906212 \tabularnewline
50 & 0.0993739 & 0.198748 & 0.900626 \tabularnewline
51 & 0.102565 & 0.205129 & 0.897435 \tabularnewline
52 & 0.108547 & 0.217094 & 0.891453 \tabularnewline
53 & 0.0894188 & 0.178838 & 0.910581 \tabularnewline
54 & 0.132394 & 0.264788 & 0.867606 \tabularnewline
55 & 0.119822 & 0.239643 & 0.880178 \tabularnewline
56 & 0.115134 & 0.230267 & 0.884866 \tabularnewline
57 & 0.14452 & 0.289039 & 0.85548 \tabularnewline
58 & 0.12027 & 0.24054 & 0.87973 \tabularnewline
59 & 0.234087 & 0.468174 & 0.765913 \tabularnewline
60 & 0.253108 & 0.506217 & 0.746892 \tabularnewline
61 & 0.220182 & 0.440364 & 0.779818 \tabularnewline
62 & 0.211549 & 0.423098 & 0.788451 \tabularnewline
63 & 0.216258 & 0.432515 & 0.783742 \tabularnewline
64 & 0.233336 & 0.466673 & 0.766664 \tabularnewline
65 & 0.308109 & 0.616218 & 0.691891 \tabularnewline
66 & 0.385113 & 0.770225 & 0.614887 \tabularnewline
67 & 0.361579 & 0.723158 & 0.638421 \tabularnewline
68 & 0.337602 & 0.675204 & 0.662398 \tabularnewline
69 & 0.303288 & 0.606575 & 0.696712 \tabularnewline
70 & 0.270149 & 0.540299 & 0.729851 \tabularnewline
71 & 0.360661 & 0.721322 & 0.639339 \tabularnewline
72 & 0.334112 & 0.668223 & 0.665888 \tabularnewline
73 & 0.300091 & 0.600183 & 0.699909 \tabularnewline
74 & 0.276305 & 0.55261 & 0.723695 \tabularnewline
75 & 0.277879 & 0.555757 & 0.722121 \tabularnewline
76 & 0.28639 & 0.57278 & 0.71361 \tabularnewline
77 & 0.335639 & 0.671279 & 0.664361 \tabularnewline
78 & 0.314638 & 0.629276 & 0.685362 \tabularnewline
79 & 0.288705 & 0.577411 & 0.711295 \tabularnewline
80 & 0.27816 & 0.55632 & 0.72184 \tabularnewline
81 & 0.261011 & 0.522022 & 0.738989 \tabularnewline
82 & 0.234294 & 0.468587 & 0.765706 \tabularnewline
83 & 0.251988 & 0.503975 & 0.748012 \tabularnewline
84 & 0.222771 & 0.445541 & 0.777229 \tabularnewline
85 & 0.233644 & 0.467288 & 0.766356 \tabularnewline
86 & 0.206782 & 0.413563 & 0.793218 \tabularnewline
87 & 0.324586 & 0.649171 & 0.675414 \tabularnewline
88 & 0.302123 & 0.604246 & 0.697877 \tabularnewline
89 & 0.269751 & 0.539502 & 0.730249 \tabularnewline
90 & 0.244276 & 0.488551 & 0.755724 \tabularnewline
91 & 0.227318 & 0.454636 & 0.772682 \tabularnewline
92 & 0.213989 & 0.427979 & 0.786011 \tabularnewline
93 & 0.21404 & 0.42808 & 0.78596 \tabularnewline
94 & 0.210118 & 0.420236 & 0.789882 \tabularnewline
95 & 0.264107 & 0.528215 & 0.735893 \tabularnewline
96 & 0.245148 & 0.490296 & 0.754852 \tabularnewline
97 & 0.222549 & 0.445098 & 0.777451 \tabularnewline
98 & 0.213451 & 0.426901 & 0.786549 \tabularnewline
99 & 0.191391 & 0.382781 & 0.808609 \tabularnewline
100 & 0.196413 & 0.392826 & 0.803587 \tabularnewline
101 & 0.192405 & 0.38481 & 0.807595 \tabularnewline
102 & 0.228963 & 0.457926 & 0.771037 \tabularnewline
103 & 0.223446 & 0.446892 & 0.776554 \tabularnewline
104 & 0.198345 & 0.396691 & 0.801655 \tabularnewline
105 & 0.173964 & 0.347927 & 0.826036 \tabularnewline
106 & 0.161467 & 0.322934 & 0.838533 \tabularnewline
107 & 0.141973 & 0.283945 & 0.858027 \tabularnewline
108 & 0.168787 & 0.337574 & 0.831213 \tabularnewline
109 & 0.160514 & 0.321027 & 0.839486 \tabularnewline
110 & 0.185038 & 0.370077 & 0.814962 \tabularnewline
111 & 0.267571 & 0.535142 & 0.732429 \tabularnewline
112 & 0.29633 & 0.592659 & 0.70367 \tabularnewline
113 & 0.286899 & 0.573799 & 0.713101 \tabularnewline
114 & 0.265067 & 0.530135 & 0.734933 \tabularnewline
115 & 0.24356 & 0.487121 & 0.75644 \tabularnewline
116 & 0.355679 & 0.711357 & 0.644321 \tabularnewline
117 & 0.398624 & 0.797247 & 0.601376 \tabularnewline
118 & 0.591261 & 0.817477 & 0.408739 \tabularnewline
119 & 0.661402 & 0.677195 & 0.338598 \tabularnewline
120 & 0.653323 & 0.693354 & 0.346677 \tabularnewline
121 & 0.62384 & 0.752321 & 0.37616 \tabularnewline
122 & 0.602443 & 0.795115 & 0.397557 \tabularnewline
123 & 0.603671 & 0.792658 & 0.396329 \tabularnewline
124 & 0.653406 & 0.693188 & 0.346594 \tabularnewline
125 & 0.621666 & 0.756668 & 0.378334 \tabularnewline
126 & 0.620243 & 0.759514 & 0.379757 \tabularnewline
127 & 0.601888 & 0.796225 & 0.398112 \tabularnewline
128 & 0.633919 & 0.732162 & 0.366081 \tabularnewline
129 & 0.603057 & 0.793885 & 0.396943 \tabularnewline
130 & 0.592084 & 0.815832 & 0.407916 \tabularnewline
131 & 0.572654 & 0.854692 & 0.427346 \tabularnewline
132 & 0.589969 & 0.820062 & 0.410031 \tabularnewline
133 & 0.557994 & 0.884012 & 0.442006 \tabularnewline
134 & 0.531046 & 0.937908 & 0.468954 \tabularnewline
135 & 0.503858 & 0.992284 & 0.496142 \tabularnewline
136 & 0.472388 & 0.944776 & 0.527612 \tabularnewline
137 & 0.438063 & 0.876126 & 0.561937 \tabularnewline
138 & 0.412496 & 0.824992 & 0.587504 \tabularnewline
139 & 0.400452 & 0.800904 & 0.599548 \tabularnewline
140 & 0.422251 & 0.844501 & 0.577749 \tabularnewline
141 & 0.509704 & 0.980591 & 0.490296 \tabularnewline
142 & 0.493627 & 0.987254 & 0.506373 \tabularnewline
143 & 0.462992 & 0.925984 & 0.537008 \tabularnewline
144 & 0.439207 & 0.878414 & 0.560793 \tabularnewline
145 & 0.537185 & 0.925629 & 0.462815 \tabularnewline
146 & 0.503714 & 0.992572 & 0.496286 \tabularnewline
147 & 0.522809 & 0.954383 & 0.477191 \tabularnewline
148 & 0.50145 & 0.9971 & 0.49855 \tabularnewline
149 & 0.468348 & 0.936697 & 0.531652 \tabularnewline
150 & 0.438471 & 0.876943 & 0.561529 \tabularnewline
151 & 0.409602 & 0.819204 & 0.590398 \tabularnewline
152 & 0.401061 & 0.802122 & 0.598939 \tabularnewline
153 & 0.374155 & 0.748309 & 0.625845 \tabularnewline
154 & 0.342724 & 0.685448 & 0.657276 \tabularnewline
155 & 0.387902 & 0.775804 & 0.612098 \tabularnewline
156 & 0.457493 & 0.914985 & 0.542507 \tabularnewline
157 & 0.428036 & 0.856072 & 0.571964 \tabularnewline
158 & 0.456526 & 0.913052 & 0.543474 \tabularnewline
159 & 0.433768 & 0.867535 & 0.566232 \tabularnewline
160 & 0.40481 & 0.809619 & 0.59519 \tabularnewline
161 & 0.384906 & 0.769813 & 0.615094 \tabularnewline
162 & 0.364263 & 0.728525 & 0.635737 \tabularnewline
163 & 0.332902 & 0.665805 & 0.667098 \tabularnewline
164 & 0.342536 & 0.685072 & 0.657464 \tabularnewline
165 & 0.342176 & 0.684352 & 0.657824 \tabularnewline
166 & 0.318285 & 0.636569 & 0.681715 \tabularnewline
167 & 0.300036 & 0.600072 & 0.699964 \tabularnewline
168 & 0.272404 & 0.544808 & 0.727596 \tabularnewline
169 & 0.266053 & 0.532107 & 0.733947 \tabularnewline
170 & 0.257234 & 0.514469 & 0.742766 \tabularnewline
171 & 0.239596 & 0.479192 & 0.760404 \tabularnewline
172 & 0.225827 & 0.451653 & 0.774173 \tabularnewline
173 & 0.234742 & 0.469484 & 0.765258 \tabularnewline
174 & 0.20907 & 0.418139 & 0.79093 \tabularnewline
175 & 0.265475 & 0.530951 & 0.734525 \tabularnewline
176 & 0.24094 & 0.481881 & 0.75906 \tabularnewline
177 & 0.240361 & 0.480722 & 0.759639 \tabularnewline
178 & 0.215597 & 0.431195 & 0.784403 \tabularnewline
179 & 0.198172 & 0.396344 & 0.801828 \tabularnewline
180 & 0.182895 & 0.365789 & 0.817105 \tabularnewline
181 & 0.19082 & 0.381639 & 0.80918 \tabularnewline
182 & 0.181181 & 0.362363 & 0.818819 \tabularnewline
183 & 0.221893 & 0.443787 & 0.778107 \tabularnewline
184 & 0.199366 & 0.398732 & 0.800634 \tabularnewline
185 & 0.32209 & 0.644179 & 0.67791 \tabularnewline
186 & 0.382432 & 0.764863 & 0.617568 \tabularnewline
187 & 0.352568 & 0.705136 & 0.647432 \tabularnewline
188 & 0.380675 & 0.761349 & 0.619325 \tabularnewline
189 & 0.347582 & 0.695163 & 0.652418 \tabularnewline
190 & 0.319108 & 0.638215 & 0.680892 \tabularnewline
191 & 0.288066 & 0.576133 & 0.711934 \tabularnewline
192 & 0.310002 & 0.620005 & 0.689998 \tabularnewline
193 & 0.293157 & 0.586314 & 0.706843 \tabularnewline
194 & 0.263616 & 0.527232 & 0.736384 \tabularnewline
195 & 0.239312 & 0.478623 & 0.760688 \tabularnewline
196 & 0.248647 & 0.497294 & 0.751353 \tabularnewline
197 & 0.2249 & 0.449799 & 0.7751 \tabularnewline
198 & 0.251561 & 0.503123 & 0.748439 \tabularnewline
199 & 0.275254 & 0.550508 & 0.724746 \tabularnewline
200 & 0.248389 & 0.496778 & 0.751611 \tabularnewline
201 & 0.219366 & 0.438733 & 0.780634 \tabularnewline
202 & 0.201878 & 0.403755 & 0.798122 \tabularnewline
203 & 0.176166 & 0.352331 & 0.823834 \tabularnewline
204 & 0.158594 & 0.317189 & 0.841406 \tabularnewline
205 & 0.138009 & 0.276018 & 0.861991 \tabularnewline
206 & 0.156968 & 0.313936 & 0.843032 \tabularnewline
207 & 0.135759 & 0.271518 & 0.864241 \tabularnewline
208 & 0.120527 & 0.241055 & 0.879473 \tabularnewline
209 & 0.104286 & 0.208573 & 0.895714 \tabularnewline
210 & 0.0895369 & 0.179074 & 0.910463 \tabularnewline
211 & 0.0766873 & 0.153375 & 0.923313 \tabularnewline
212 & 0.097892 & 0.195784 & 0.902108 \tabularnewline
213 & 0.0841414 & 0.168283 & 0.915859 \tabularnewline
214 & 0.072065 & 0.14413 & 0.927935 \tabularnewline
215 & 0.0752893 & 0.150579 & 0.924711 \tabularnewline
216 & 0.073066 & 0.146132 & 0.926934 \tabularnewline
217 & 0.0710922 & 0.142184 & 0.928908 \tabularnewline
218 & 0.0647706 & 0.129541 & 0.935229 \tabularnewline
219 & 0.0895698 & 0.17914 & 0.91043 \tabularnewline
220 & 0.0742475 & 0.148495 & 0.925752 \tabularnewline
221 & 0.0637398 & 0.12748 & 0.93626 \tabularnewline
222 & 0.0536884 & 0.107377 & 0.946312 \tabularnewline
223 & 0.0532559 & 0.106512 & 0.946744 \tabularnewline
224 & 0.0428174 & 0.0856348 & 0.957183 \tabularnewline
225 & 0.0593043 & 0.118609 & 0.940696 \tabularnewline
226 & 0.0543225 & 0.108645 & 0.945677 \tabularnewline
227 & 0.0436806 & 0.0873612 & 0.956319 \tabularnewline
228 & 0.0479626 & 0.0959253 & 0.952037 \tabularnewline
229 & 0.109735 & 0.21947 & 0.890265 \tabularnewline
230 & 0.0914638 & 0.182928 & 0.908536 \tabularnewline
231 & 0.139055 & 0.27811 & 0.860945 \tabularnewline
232 & 0.166593 & 0.333187 & 0.833407 \tabularnewline
233 & 0.152989 & 0.305978 & 0.847011 \tabularnewline
234 & 0.171669 & 0.343337 & 0.828331 \tabularnewline
235 & 0.172307 & 0.344614 & 0.827693 \tabularnewline
236 & 0.15341 & 0.306819 & 0.84659 \tabularnewline
237 & 0.210723 & 0.421447 & 0.789277 \tabularnewline
238 & 0.384108 & 0.768215 & 0.615892 \tabularnewline
239 & 0.343439 & 0.686878 & 0.656561 \tabularnewline
240 & 0.302177 & 0.604354 & 0.697823 \tabularnewline
241 & 0.288634 & 0.577267 & 0.711366 \tabularnewline
242 & 0.259657 & 0.519314 & 0.740343 \tabularnewline
243 & 0.645296 & 0.709408 & 0.354704 \tabularnewline
244 & 0.59665 & 0.8067 & 0.40335 \tabularnewline
245 & 0.547274 & 0.905452 & 0.452726 \tabularnewline
246 & 0.537028 & 0.925945 & 0.462972 \tabularnewline
247 & 0.483112 & 0.966223 & 0.516888 \tabularnewline
248 & 0.534526 & 0.930949 & 0.465474 \tabularnewline
249 & 0.488333 & 0.976666 & 0.511667 \tabularnewline
250 & 0.456546 & 0.913092 & 0.543454 \tabularnewline
251 & 0.439258 & 0.878516 & 0.560742 \tabularnewline
252 & 0.592768 & 0.814464 & 0.407232 \tabularnewline
253 & 0.539269 & 0.921461 & 0.460731 \tabularnewline
254 & 0.490368 & 0.980737 & 0.509632 \tabularnewline
255 & 0.432986 & 0.865972 & 0.567014 \tabularnewline
256 & 0.495849 & 0.991699 & 0.504151 \tabularnewline
257 & 0.432654 & 0.865307 & 0.567346 \tabularnewline
258 & 0.417384 & 0.834768 & 0.582616 \tabularnewline
259 & 0.44704 & 0.89408 & 0.55296 \tabularnewline
260 & 0.425314 & 0.850628 & 0.574686 \tabularnewline
261 & 0.372267 & 0.744533 & 0.627733 \tabularnewline
262 & 0.333549 & 0.667098 & 0.666451 \tabularnewline
263 & 0.605107 & 0.789786 & 0.394893 \tabularnewline
264 & 0.55107 & 0.89786 & 0.44893 \tabularnewline
265 & 0.588575 & 0.822849 & 0.411425 \tabularnewline
266 & 0.780346 & 0.439307 & 0.219654 \tabularnewline
267 & 0.757928 & 0.484144 & 0.242072 \tabularnewline
268 & 0.905261 & 0.189478 & 0.0947389 \tabularnewline
269 & 0.858184 & 0.283633 & 0.141816 \tabularnewline
270 & 0.907496 & 0.185008 & 0.0925038 \tabularnewline
271 & 0.842414 & 0.315172 & 0.157586 \tabularnewline
272 & 0.865144 & 0.269712 & 0.134856 \tabularnewline
273 & 0.774967 & 0.450067 & 0.225033 \tabularnewline
274 & 0.619095 & 0.76181 & 0.380905 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&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]12[/C][C]0.947409[/C][C]0.105182[/C][C]0.052591[/C][/ROW]
[ROW][C]13[/C][C]0.959265[/C][C]0.0814691[/C][C]0.0407345[/C][/ROW]
[ROW][C]14[/C][C]0.925146[/C][C]0.149707[/C][C]0.0748536[/C][/ROW]
[ROW][C]15[/C][C]0.875653[/C][C]0.248695[/C][C]0.124347[/C][/ROW]
[ROW][C]16[/C][C]0.84143[/C][C]0.317141[/C][C]0.15857[/C][/ROW]
[ROW][C]17[/C][C]0.772218[/C][C]0.455563[/C][C]0.227782[/C][/ROW]
[ROW][C]18[/C][C]0.69252[/C][C]0.614961[/C][C]0.30748[/C][/ROW]
[ROW][C]19[/C][C]0.606608[/C][C]0.786785[/C][C]0.393392[/C][/ROW]
[ROW][C]20[/C][C]0.520234[/C][C]0.959531[/C][C]0.479766[/C][/ROW]
[ROW][C]21[/C][C]0.435924[/C][C]0.871848[/C][C]0.564076[/C][/ROW]
[ROW][C]22[/C][C]0.381449[/C][C]0.762898[/C][C]0.618551[/C][/ROW]
[ROW][C]23[/C][C]0.566213[/C][C]0.867573[/C][C]0.433787[/C][/ROW]
[ROW][C]24[/C][C]0.494595[/C][C]0.989189[/C][C]0.505405[/C][/ROW]
[ROW][C]25[/C][C]0.505886[/C][C]0.988229[/C][C]0.494114[/C][/ROW]
[ROW][C]26[/C][C]0.433431[/C][C]0.866861[/C][C]0.566569[/C][/ROW]
[ROW][C]27[/C][C]0.367564[/C][C]0.735128[/C][C]0.632436[/C][/ROW]
[ROW][C]28[/C][C]0.358346[/C][C]0.716692[/C][C]0.641654[/C][/ROW]
[ROW][C]29[/C][C]0.307183[/C][C]0.614366[/C][C]0.692817[/C][/ROW]
[ROW][C]30[/C][C]0.25428[/C][C]0.508559[/C][C]0.74572[/C][/ROW]
[ROW][C]31[/C][C]0.217288[/C][C]0.434576[/C][C]0.782712[/C][/ROW]
[ROW][C]32[/C][C]0.311004[/C][C]0.622008[/C][C]0.688996[/C][/ROW]
[ROW][C]33[/C][C]0.258245[/C][C]0.516489[/C][C]0.741755[/C][/ROW]
[ROW][C]34[/C][C]0.457379[/C][C]0.914758[/C][C]0.542621[/C][/ROW]
[ROW][C]35[/C][C]0.406724[/C][C]0.813448[/C][C]0.593276[/C][/ROW]
[ROW][C]36[/C][C]0.354657[/C][C]0.709313[/C][C]0.645343[/C][/ROW]
[ROW][C]37[/C][C]0.301766[/C][C]0.603532[/C][C]0.698234[/C][/ROW]
[ROW][C]38[/C][C]0.264116[/C][C]0.528232[/C][C]0.735884[/C][/ROW]
[ROW][C]39[/C][C]0.229455[/C][C]0.458909[/C][C]0.770545[/C][/ROW]
[ROW][C]40[/C][C]0.212195[/C][C]0.42439[/C][C]0.787805[/C][/ROW]
[ROW][C]41[/C][C]0.184483[/C][C]0.368966[/C][C]0.815517[/C][/ROW]
[ROW][C]42[/C][C]0.156967[/C][C]0.313935[/C][C]0.843033[/C][/ROW]
[ROW][C]43[/C][C]0.189266[/C][C]0.378532[/C][C]0.810734[/C][/ROW]
[ROW][C]44[/C][C]0.180883[/C][C]0.361767[/C][C]0.819117[/C][/ROW]
[ROW][C]45[/C][C]0.186997[/C][C]0.373995[/C][C]0.813003[/C][/ROW]
[ROW][C]46[/C][C]0.153923[/C][C]0.307846[/C][C]0.846077[/C][/ROW]
[ROW][C]47[/C][C]0.12876[/C][C]0.257521[/C][C]0.87124[/C][/ROW]
[ROW][C]48[/C][C]0.113612[/C][C]0.227225[/C][C]0.886388[/C][/ROW]
[ROW][C]49[/C][C]0.0937877[/C][C]0.187575[/C][C]0.906212[/C][/ROW]
[ROW][C]50[/C][C]0.0993739[/C][C]0.198748[/C][C]0.900626[/C][/ROW]
[ROW][C]51[/C][C]0.102565[/C][C]0.205129[/C][C]0.897435[/C][/ROW]
[ROW][C]52[/C][C]0.108547[/C][C]0.217094[/C][C]0.891453[/C][/ROW]
[ROW][C]53[/C][C]0.0894188[/C][C]0.178838[/C][C]0.910581[/C][/ROW]
[ROW][C]54[/C][C]0.132394[/C][C]0.264788[/C][C]0.867606[/C][/ROW]
[ROW][C]55[/C][C]0.119822[/C][C]0.239643[/C][C]0.880178[/C][/ROW]
[ROW][C]56[/C][C]0.115134[/C][C]0.230267[/C][C]0.884866[/C][/ROW]
[ROW][C]57[/C][C]0.14452[/C][C]0.289039[/C][C]0.85548[/C][/ROW]
[ROW][C]58[/C][C]0.12027[/C][C]0.24054[/C][C]0.87973[/C][/ROW]
[ROW][C]59[/C][C]0.234087[/C][C]0.468174[/C][C]0.765913[/C][/ROW]
[ROW][C]60[/C][C]0.253108[/C][C]0.506217[/C][C]0.746892[/C][/ROW]
[ROW][C]61[/C][C]0.220182[/C][C]0.440364[/C][C]0.779818[/C][/ROW]
[ROW][C]62[/C][C]0.211549[/C][C]0.423098[/C][C]0.788451[/C][/ROW]
[ROW][C]63[/C][C]0.216258[/C][C]0.432515[/C][C]0.783742[/C][/ROW]
[ROW][C]64[/C][C]0.233336[/C][C]0.466673[/C][C]0.766664[/C][/ROW]
[ROW][C]65[/C][C]0.308109[/C][C]0.616218[/C][C]0.691891[/C][/ROW]
[ROW][C]66[/C][C]0.385113[/C][C]0.770225[/C][C]0.614887[/C][/ROW]
[ROW][C]67[/C][C]0.361579[/C][C]0.723158[/C][C]0.638421[/C][/ROW]
[ROW][C]68[/C][C]0.337602[/C][C]0.675204[/C][C]0.662398[/C][/ROW]
[ROW][C]69[/C][C]0.303288[/C][C]0.606575[/C][C]0.696712[/C][/ROW]
[ROW][C]70[/C][C]0.270149[/C][C]0.540299[/C][C]0.729851[/C][/ROW]
[ROW][C]71[/C][C]0.360661[/C][C]0.721322[/C][C]0.639339[/C][/ROW]
[ROW][C]72[/C][C]0.334112[/C][C]0.668223[/C][C]0.665888[/C][/ROW]
[ROW][C]73[/C][C]0.300091[/C][C]0.600183[/C][C]0.699909[/C][/ROW]
[ROW][C]74[/C][C]0.276305[/C][C]0.55261[/C][C]0.723695[/C][/ROW]
[ROW][C]75[/C][C]0.277879[/C][C]0.555757[/C][C]0.722121[/C][/ROW]
[ROW][C]76[/C][C]0.28639[/C][C]0.57278[/C][C]0.71361[/C][/ROW]
[ROW][C]77[/C][C]0.335639[/C][C]0.671279[/C][C]0.664361[/C][/ROW]
[ROW][C]78[/C][C]0.314638[/C][C]0.629276[/C][C]0.685362[/C][/ROW]
[ROW][C]79[/C][C]0.288705[/C][C]0.577411[/C][C]0.711295[/C][/ROW]
[ROW][C]80[/C][C]0.27816[/C][C]0.55632[/C][C]0.72184[/C][/ROW]
[ROW][C]81[/C][C]0.261011[/C][C]0.522022[/C][C]0.738989[/C][/ROW]
[ROW][C]82[/C][C]0.234294[/C][C]0.468587[/C][C]0.765706[/C][/ROW]
[ROW][C]83[/C][C]0.251988[/C][C]0.503975[/C][C]0.748012[/C][/ROW]
[ROW][C]84[/C][C]0.222771[/C][C]0.445541[/C][C]0.777229[/C][/ROW]
[ROW][C]85[/C][C]0.233644[/C][C]0.467288[/C][C]0.766356[/C][/ROW]
[ROW][C]86[/C][C]0.206782[/C][C]0.413563[/C][C]0.793218[/C][/ROW]
[ROW][C]87[/C][C]0.324586[/C][C]0.649171[/C][C]0.675414[/C][/ROW]
[ROW][C]88[/C][C]0.302123[/C][C]0.604246[/C][C]0.697877[/C][/ROW]
[ROW][C]89[/C][C]0.269751[/C][C]0.539502[/C][C]0.730249[/C][/ROW]
[ROW][C]90[/C][C]0.244276[/C][C]0.488551[/C][C]0.755724[/C][/ROW]
[ROW][C]91[/C][C]0.227318[/C][C]0.454636[/C][C]0.772682[/C][/ROW]
[ROW][C]92[/C][C]0.213989[/C][C]0.427979[/C][C]0.786011[/C][/ROW]
[ROW][C]93[/C][C]0.21404[/C][C]0.42808[/C][C]0.78596[/C][/ROW]
[ROW][C]94[/C][C]0.210118[/C][C]0.420236[/C][C]0.789882[/C][/ROW]
[ROW][C]95[/C][C]0.264107[/C][C]0.528215[/C][C]0.735893[/C][/ROW]
[ROW][C]96[/C][C]0.245148[/C][C]0.490296[/C][C]0.754852[/C][/ROW]
[ROW][C]97[/C][C]0.222549[/C][C]0.445098[/C][C]0.777451[/C][/ROW]
[ROW][C]98[/C][C]0.213451[/C][C]0.426901[/C][C]0.786549[/C][/ROW]
[ROW][C]99[/C][C]0.191391[/C][C]0.382781[/C][C]0.808609[/C][/ROW]
[ROW][C]100[/C][C]0.196413[/C][C]0.392826[/C][C]0.803587[/C][/ROW]
[ROW][C]101[/C][C]0.192405[/C][C]0.38481[/C][C]0.807595[/C][/ROW]
[ROW][C]102[/C][C]0.228963[/C][C]0.457926[/C][C]0.771037[/C][/ROW]
[ROW][C]103[/C][C]0.223446[/C][C]0.446892[/C][C]0.776554[/C][/ROW]
[ROW][C]104[/C][C]0.198345[/C][C]0.396691[/C][C]0.801655[/C][/ROW]
[ROW][C]105[/C][C]0.173964[/C][C]0.347927[/C][C]0.826036[/C][/ROW]
[ROW][C]106[/C][C]0.161467[/C][C]0.322934[/C][C]0.838533[/C][/ROW]
[ROW][C]107[/C][C]0.141973[/C][C]0.283945[/C][C]0.858027[/C][/ROW]
[ROW][C]108[/C][C]0.168787[/C][C]0.337574[/C][C]0.831213[/C][/ROW]
[ROW][C]109[/C][C]0.160514[/C][C]0.321027[/C][C]0.839486[/C][/ROW]
[ROW][C]110[/C][C]0.185038[/C][C]0.370077[/C][C]0.814962[/C][/ROW]
[ROW][C]111[/C][C]0.267571[/C][C]0.535142[/C][C]0.732429[/C][/ROW]
[ROW][C]112[/C][C]0.29633[/C][C]0.592659[/C][C]0.70367[/C][/ROW]
[ROW][C]113[/C][C]0.286899[/C][C]0.573799[/C][C]0.713101[/C][/ROW]
[ROW][C]114[/C][C]0.265067[/C][C]0.530135[/C][C]0.734933[/C][/ROW]
[ROW][C]115[/C][C]0.24356[/C][C]0.487121[/C][C]0.75644[/C][/ROW]
[ROW][C]116[/C][C]0.355679[/C][C]0.711357[/C][C]0.644321[/C][/ROW]
[ROW][C]117[/C][C]0.398624[/C][C]0.797247[/C][C]0.601376[/C][/ROW]
[ROW][C]118[/C][C]0.591261[/C][C]0.817477[/C][C]0.408739[/C][/ROW]
[ROW][C]119[/C][C]0.661402[/C][C]0.677195[/C][C]0.338598[/C][/ROW]
[ROW][C]120[/C][C]0.653323[/C][C]0.693354[/C][C]0.346677[/C][/ROW]
[ROW][C]121[/C][C]0.62384[/C][C]0.752321[/C][C]0.37616[/C][/ROW]
[ROW][C]122[/C][C]0.602443[/C][C]0.795115[/C][C]0.397557[/C][/ROW]
[ROW][C]123[/C][C]0.603671[/C][C]0.792658[/C][C]0.396329[/C][/ROW]
[ROW][C]124[/C][C]0.653406[/C][C]0.693188[/C][C]0.346594[/C][/ROW]
[ROW][C]125[/C][C]0.621666[/C][C]0.756668[/C][C]0.378334[/C][/ROW]
[ROW][C]126[/C][C]0.620243[/C][C]0.759514[/C][C]0.379757[/C][/ROW]
[ROW][C]127[/C][C]0.601888[/C][C]0.796225[/C][C]0.398112[/C][/ROW]
[ROW][C]128[/C][C]0.633919[/C][C]0.732162[/C][C]0.366081[/C][/ROW]
[ROW][C]129[/C][C]0.603057[/C][C]0.793885[/C][C]0.396943[/C][/ROW]
[ROW][C]130[/C][C]0.592084[/C][C]0.815832[/C][C]0.407916[/C][/ROW]
[ROW][C]131[/C][C]0.572654[/C][C]0.854692[/C][C]0.427346[/C][/ROW]
[ROW][C]132[/C][C]0.589969[/C][C]0.820062[/C][C]0.410031[/C][/ROW]
[ROW][C]133[/C][C]0.557994[/C][C]0.884012[/C][C]0.442006[/C][/ROW]
[ROW][C]134[/C][C]0.531046[/C][C]0.937908[/C][C]0.468954[/C][/ROW]
[ROW][C]135[/C][C]0.503858[/C][C]0.992284[/C][C]0.496142[/C][/ROW]
[ROW][C]136[/C][C]0.472388[/C][C]0.944776[/C][C]0.527612[/C][/ROW]
[ROW][C]137[/C][C]0.438063[/C][C]0.876126[/C][C]0.561937[/C][/ROW]
[ROW][C]138[/C][C]0.412496[/C][C]0.824992[/C][C]0.587504[/C][/ROW]
[ROW][C]139[/C][C]0.400452[/C][C]0.800904[/C][C]0.599548[/C][/ROW]
[ROW][C]140[/C][C]0.422251[/C][C]0.844501[/C][C]0.577749[/C][/ROW]
[ROW][C]141[/C][C]0.509704[/C][C]0.980591[/C][C]0.490296[/C][/ROW]
[ROW][C]142[/C][C]0.493627[/C][C]0.987254[/C][C]0.506373[/C][/ROW]
[ROW][C]143[/C][C]0.462992[/C][C]0.925984[/C][C]0.537008[/C][/ROW]
[ROW][C]144[/C][C]0.439207[/C][C]0.878414[/C][C]0.560793[/C][/ROW]
[ROW][C]145[/C][C]0.537185[/C][C]0.925629[/C][C]0.462815[/C][/ROW]
[ROW][C]146[/C][C]0.503714[/C][C]0.992572[/C][C]0.496286[/C][/ROW]
[ROW][C]147[/C][C]0.522809[/C][C]0.954383[/C][C]0.477191[/C][/ROW]
[ROW][C]148[/C][C]0.50145[/C][C]0.9971[/C][C]0.49855[/C][/ROW]
[ROW][C]149[/C][C]0.468348[/C][C]0.936697[/C][C]0.531652[/C][/ROW]
[ROW][C]150[/C][C]0.438471[/C][C]0.876943[/C][C]0.561529[/C][/ROW]
[ROW][C]151[/C][C]0.409602[/C][C]0.819204[/C][C]0.590398[/C][/ROW]
[ROW][C]152[/C][C]0.401061[/C][C]0.802122[/C][C]0.598939[/C][/ROW]
[ROW][C]153[/C][C]0.374155[/C][C]0.748309[/C][C]0.625845[/C][/ROW]
[ROW][C]154[/C][C]0.342724[/C][C]0.685448[/C][C]0.657276[/C][/ROW]
[ROW][C]155[/C][C]0.387902[/C][C]0.775804[/C][C]0.612098[/C][/ROW]
[ROW][C]156[/C][C]0.457493[/C][C]0.914985[/C][C]0.542507[/C][/ROW]
[ROW][C]157[/C][C]0.428036[/C][C]0.856072[/C][C]0.571964[/C][/ROW]
[ROW][C]158[/C][C]0.456526[/C][C]0.913052[/C][C]0.543474[/C][/ROW]
[ROW][C]159[/C][C]0.433768[/C][C]0.867535[/C][C]0.566232[/C][/ROW]
[ROW][C]160[/C][C]0.40481[/C][C]0.809619[/C][C]0.59519[/C][/ROW]
[ROW][C]161[/C][C]0.384906[/C][C]0.769813[/C][C]0.615094[/C][/ROW]
[ROW][C]162[/C][C]0.364263[/C][C]0.728525[/C][C]0.635737[/C][/ROW]
[ROW][C]163[/C][C]0.332902[/C][C]0.665805[/C][C]0.667098[/C][/ROW]
[ROW][C]164[/C][C]0.342536[/C][C]0.685072[/C][C]0.657464[/C][/ROW]
[ROW][C]165[/C][C]0.342176[/C][C]0.684352[/C][C]0.657824[/C][/ROW]
[ROW][C]166[/C][C]0.318285[/C][C]0.636569[/C][C]0.681715[/C][/ROW]
[ROW][C]167[/C][C]0.300036[/C][C]0.600072[/C][C]0.699964[/C][/ROW]
[ROW][C]168[/C][C]0.272404[/C][C]0.544808[/C][C]0.727596[/C][/ROW]
[ROW][C]169[/C][C]0.266053[/C][C]0.532107[/C][C]0.733947[/C][/ROW]
[ROW][C]170[/C][C]0.257234[/C][C]0.514469[/C][C]0.742766[/C][/ROW]
[ROW][C]171[/C][C]0.239596[/C][C]0.479192[/C][C]0.760404[/C][/ROW]
[ROW][C]172[/C][C]0.225827[/C][C]0.451653[/C][C]0.774173[/C][/ROW]
[ROW][C]173[/C][C]0.234742[/C][C]0.469484[/C][C]0.765258[/C][/ROW]
[ROW][C]174[/C][C]0.20907[/C][C]0.418139[/C][C]0.79093[/C][/ROW]
[ROW][C]175[/C][C]0.265475[/C][C]0.530951[/C][C]0.734525[/C][/ROW]
[ROW][C]176[/C][C]0.24094[/C][C]0.481881[/C][C]0.75906[/C][/ROW]
[ROW][C]177[/C][C]0.240361[/C][C]0.480722[/C][C]0.759639[/C][/ROW]
[ROW][C]178[/C][C]0.215597[/C][C]0.431195[/C][C]0.784403[/C][/ROW]
[ROW][C]179[/C][C]0.198172[/C][C]0.396344[/C][C]0.801828[/C][/ROW]
[ROW][C]180[/C][C]0.182895[/C][C]0.365789[/C][C]0.817105[/C][/ROW]
[ROW][C]181[/C][C]0.19082[/C][C]0.381639[/C][C]0.80918[/C][/ROW]
[ROW][C]182[/C][C]0.181181[/C][C]0.362363[/C][C]0.818819[/C][/ROW]
[ROW][C]183[/C][C]0.221893[/C][C]0.443787[/C][C]0.778107[/C][/ROW]
[ROW][C]184[/C][C]0.199366[/C][C]0.398732[/C][C]0.800634[/C][/ROW]
[ROW][C]185[/C][C]0.32209[/C][C]0.644179[/C][C]0.67791[/C][/ROW]
[ROW][C]186[/C][C]0.382432[/C][C]0.764863[/C][C]0.617568[/C][/ROW]
[ROW][C]187[/C][C]0.352568[/C][C]0.705136[/C][C]0.647432[/C][/ROW]
[ROW][C]188[/C][C]0.380675[/C][C]0.761349[/C][C]0.619325[/C][/ROW]
[ROW][C]189[/C][C]0.347582[/C][C]0.695163[/C][C]0.652418[/C][/ROW]
[ROW][C]190[/C][C]0.319108[/C][C]0.638215[/C][C]0.680892[/C][/ROW]
[ROW][C]191[/C][C]0.288066[/C][C]0.576133[/C][C]0.711934[/C][/ROW]
[ROW][C]192[/C][C]0.310002[/C][C]0.620005[/C][C]0.689998[/C][/ROW]
[ROW][C]193[/C][C]0.293157[/C][C]0.586314[/C][C]0.706843[/C][/ROW]
[ROW][C]194[/C][C]0.263616[/C][C]0.527232[/C][C]0.736384[/C][/ROW]
[ROW][C]195[/C][C]0.239312[/C][C]0.478623[/C][C]0.760688[/C][/ROW]
[ROW][C]196[/C][C]0.248647[/C][C]0.497294[/C][C]0.751353[/C][/ROW]
[ROW][C]197[/C][C]0.2249[/C][C]0.449799[/C][C]0.7751[/C][/ROW]
[ROW][C]198[/C][C]0.251561[/C][C]0.503123[/C][C]0.748439[/C][/ROW]
[ROW][C]199[/C][C]0.275254[/C][C]0.550508[/C][C]0.724746[/C][/ROW]
[ROW][C]200[/C][C]0.248389[/C][C]0.496778[/C][C]0.751611[/C][/ROW]
[ROW][C]201[/C][C]0.219366[/C][C]0.438733[/C][C]0.780634[/C][/ROW]
[ROW][C]202[/C][C]0.201878[/C][C]0.403755[/C][C]0.798122[/C][/ROW]
[ROW][C]203[/C][C]0.176166[/C][C]0.352331[/C][C]0.823834[/C][/ROW]
[ROW][C]204[/C][C]0.158594[/C][C]0.317189[/C][C]0.841406[/C][/ROW]
[ROW][C]205[/C][C]0.138009[/C][C]0.276018[/C][C]0.861991[/C][/ROW]
[ROW][C]206[/C][C]0.156968[/C][C]0.313936[/C][C]0.843032[/C][/ROW]
[ROW][C]207[/C][C]0.135759[/C][C]0.271518[/C][C]0.864241[/C][/ROW]
[ROW][C]208[/C][C]0.120527[/C][C]0.241055[/C][C]0.879473[/C][/ROW]
[ROW][C]209[/C][C]0.104286[/C][C]0.208573[/C][C]0.895714[/C][/ROW]
[ROW][C]210[/C][C]0.0895369[/C][C]0.179074[/C][C]0.910463[/C][/ROW]
[ROW][C]211[/C][C]0.0766873[/C][C]0.153375[/C][C]0.923313[/C][/ROW]
[ROW][C]212[/C][C]0.097892[/C][C]0.195784[/C][C]0.902108[/C][/ROW]
[ROW][C]213[/C][C]0.0841414[/C][C]0.168283[/C][C]0.915859[/C][/ROW]
[ROW][C]214[/C][C]0.072065[/C][C]0.14413[/C][C]0.927935[/C][/ROW]
[ROW][C]215[/C][C]0.0752893[/C][C]0.150579[/C][C]0.924711[/C][/ROW]
[ROW][C]216[/C][C]0.073066[/C][C]0.146132[/C][C]0.926934[/C][/ROW]
[ROW][C]217[/C][C]0.0710922[/C][C]0.142184[/C][C]0.928908[/C][/ROW]
[ROW][C]218[/C][C]0.0647706[/C][C]0.129541[/C][C]0.935229[/C][/ROW]
[ROW][C]219[/C][C]0.0895698[/C][C]0.17914[/C][C]0.91043[/C][/ROW]
[ROW][C]220[/C][C]0.0742475[/C][C]0.148495[/C][C]0.925752[/C][/ROW]
[ROW][C]221[/C][C]0.0637398[/C][C]0.12748[/C][C]0.93626[/C][/ROW]
[ROW][C]222[/C][C]0.0536884[/C][C]0.107377[/C][C]0.946312[/C][/ROW]
[ROW][C]223[/C][C]0.0532559[/C][C]0.106512[/C][C]0.946744[/C][/ROW]
[ROW][C]224[/C][C]0.0428174[/C][C]0.0856348[/C][C]0.957183[/C][/ROW]
[ROW][C]225[/C][C]0.0593043[/C][C]0.118609[/C][C]0.940696[/C][/ROW]
[ROW][C]226[/C][C]0.0543225[/C][C]0.108645[/C][C]0.945677[/C][/ROW]
[ROW][C]227[/C][C]0.0436806[/C][C]0.0873612[/C][C]0.956319[/C][/ROW]
[ROW][C]228[/C][C]0.0479626[/C][C]0.0959253[/C][C]0.952037[/C][/ROW]
[ROW][C]229[/C][C]0.109735[/C][C]0.21947[/C][C]0.890265[/C][/ROW]
[ROW][C]230[/C][C]0.0914638[/C][C]0.182928[/C][C]0.908536[/C][/ROW]
[ROW][C]231[/C][C]0.139055[/C][C]0.27811[/C][C]0.860945[/C][/ROW]
[ROW][C]232[/C][C]0.166593[/C][C]0.333187[/C][C]0.833407[/C][/ROW]
[ROW][C]233[/C][C]0.152989[/C][C]0.305978[/C][C]0.847011[/C][/ROW]
[ROW][C]234[/C][C]0.171669[/C][C]0.343337[/C][C]0.828331[/C][/ROW]
[ROW][C]235[/C][C]0.172307[/C][C]0.344614[/C][C]0.827693[/C][/ROW]
[ROW][C]236[/C][C]0.15341[/C][C]0.306819[/C][C]0.84659[/C][/ROW]
[ROW][C]237[/C][C]0.210723[/C][C]0.421447[/C][C]0.789277[/C][/ROW]
[ROW][C]238[/C][C]0.384108[/C][C]0.768215[/C][C]0.615892[/C][/ROW]
[ROW][C]239[/C][C]0.343439[/C][C]0.686878[/C][C]0.656561[/C][/ROW]
[ROW][C]240[/C][C]0.302177[/C][C]0.604354[/C][C]0.697823[/C][/ROW]
[ROW][C]241[/C][C]0.288634[/C][C]0.577267[/C][C]0.711366[/C][/ROW]
[ROW][C]242[/C][C]0.259657[/C][C]0.519314[/C][C]0.740343[/C][/ROW]
[ROW][C]243[/C][C]0.645296[/C][C]0.709408[/C][C]0.354704[/C][/ROW]
[ROW][C]244[/C][C]0.59665[/C][C]0.8067[/C][C]0.40335[/C][/ROW]
[ROW][C]245[/C][C]0.547274[/C][C]0.905452[/C][C]0.452726[/C][/ROW]
[ROW][C]246[/C][C]0.537028[/C][C]0.925945[/C][C]0.462972[/C][/ROW]
[ROW][C]247[/C][C]0.483112[/C][C]0.966223[/C][C]0.516888[/C][/ROW]
[ROW][C]248[/C][C]0.534526[/C][C]0.930949[/C][C]0.465474[/C][/ROW]
[ROW][C]249[/C][C]0.488333[/C][C]0.976666[/C][C]0.511667[/C][/ROW]
[ROW][C]250[/C][C]0.456546[/C][C]0.913092[/C][C]0.543454[/C][/ROW]
[ROW][C]251[/C][C]0.439258[/C][C]0.878516[/C][C]0.560742[/C][/ROW]
[ROW][C]252[/C][C]0.592768[/C][C]0.814464[/C][C]0.407232[/C][/ROW]
[ROW][C]253[/C][C]0.539269[/C][C]0.921461[/C][C]0.460731[/C][/ROW]
[ROW][C]254[/C][C]0.490368[/C][C]0.980737[/C][C]0.509632[/C][/ROW]
[ROW][C]255[/C][C]0.432986[/C][C]0.865972[/C][C]0.567014[/C][/ROW]
[ROW][C]256[/C][C]0.495849[/C][C]0.991699[/C][C]0.504151[/C][/ROW]
[ROW][C]257[/C][C]0.432654[/C][C]0.865307[/C][C]0.567346[/C][/ROW]
[ROW][C]258[/C][C]0.417384[/C][C]0.834768[/C][C]0.582616[/C][/ROW]
[ROW][C]259[/C][C]0.44704[/C][C]0.89408[/C][C]0.55296[/C][/ROW]
[ROW][C]260[/C][C]0.425314[/C][C]0.850628[/C][C]0.574686[/C][/ROW]
[ROW][C]261[/C][C]0.372267[/C][C]0.744533[/C][C]0.627733[/C][/ROW]
[ROW][C]262[/C][C]0.333549[/C][C]0.667098[/C][C]0.666451[/C][/ROW]
[ROW][C]263[/C][C]0.605107[/C][C]0.789786[/C][C]0.394893[/C][/ROW]
[ROW][C]264[/C][C]0.55107[/C][C]0.89786[/C][C]0.44893[/C][/ROW]
[ROW][C]265[/C][C]0.588575[/C][C]0.822849[/C][C]0.411425[/C][/ROW]
[ROW][C]266[/C][C]0.780346[/C][C]0.439307[/C][C]0.219654[/C][/ROW]
[ROW][C]267[/C][C]0.757928[/C][C]0.484144[/C][C]0.242072[/C][/ROW]
[ROW][C]268[/C][C]0.905261[/C][C]0.189478[/C][C]0.0947389[/C][/ROW]
[ROW][C]269[/C][C]0.858184[/C][C]0.283633[/C][C]0.141816[/C][/ROW]
[ROW][C]270[/C][C]0.907496[/C][C]0.185008[/C][C]0.0925038[/C][/ROW]
[ROW][C]271[/C][C]0.842414[/C][C]0.315172[/C][C]0.157586[/C][/ROW]
[ROW][C]272[/C][C]0.865144[/C][C]0.269712[/C][C]0.134856[/C][/ROW]
[ROW][C]273[/C][C]0.774967[/C][C]0.450067[/C][C]0.225033[/C][/ROW]
[ROW][C]274[/C][C]0.619095[/C][C]0.76181[/C][C]0.380905[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&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
120.9474090.1051820.052591
130.9592650.08146910.0407345
140.9251460.1497070.0748536
150.8756530.2486950.124347
160.841430.3171410.15857
170.7722180.4555630.227782
180.692520.6149610.30748
190.6066080.7867850.393392
200.5202340.9595310.479766
210.4359240.8718480.564076
220.3814490.7628980.618551
230.5662130.8675730.433787
240.4945950.9891890.505405
250.5058860.9882290.494114
260.4334310.8668610.566569
270.3675640.7351280.632436
280.3583460.7166920.641654
290.3071830.6143660.692817
300.254280.5085590.74572
310.2172880.4345760.782712
320.3110040.6220080.688996
330.2582450.5164890.741755
340.4573790.9147580.542621
350.4067240.8134480.593276
360.3546570.7093130.645343
370.3017660.6035320.698234
380.2641160.5282320.735884
390.2294550.4589090.770545
400.2121950.424390.787805
410.1844830.3689660.815517
420.1569670.3139350.843033
430.1892660.3785320.810734
440.1808830.3617670.819117
450.1869970.3739950.813003
460.1539230.3078460.846077
470.128760.2575210.87124
480.1136120.2272250.886388
490.09378770.1875750.906212
500.09937390.1987480.900626
510.1025650.2051290.897435
520.1085470.2170940.891453
530.08941880.1788380.910581
540.1323940.2647880.867606
550.1198220.2396430.880178
560.1151340.2302670.884866
570.144520.2890390.85548
580.120270.240540.87973
590.2340870.4681740.765913
600.2531080.5062170.746892
610.2201820.4403640.779818
620.2115490.4230980.788451
630.2162580.4325150.783742
640.2333360.4666730.766664
650.3081090.6162180.691891
660.3851130.7702250.614887
670.3615790.7231580.638421
680.3376020.6752040.662398
690.3032880.6065750.696712
700.2701490.5402990.729851
710.3606610.7213220.639339
720.3341120.6682230.665888
730.3000910.6001830.699909
740.2763050.552610.723695
750.2778790.5557570.722121
760.286390.572780.71361
770.3356390.6712790.664361
780.3146380.6292760.685362
790.2887050.5774110.711295
800.278160.556320.72184
810.2610110.5220220.738989
820.2342940.4685870.765706
830.2519880.5039750.748012
840.2227710.4455410.777229
850.2336440.4672880.766356
860.2067820.4135630.793218
870.3245860.6491710.675414
880.3021230.6042460.697877
890.2697510.5395020.730249
900.2442760.4885510.755724
910.2273180.4546360.772682
920.2139890.4279790.786011
930.214040.428080.78596
940.2101180.4202360.789882
950.2641070.5282150.735893
960.2451480.4902960.754852
970.2225490.4450980.777451
980.2134510.4269010.786549
990.1913910.3827810.808609
1000.1964130.3928260.803587
1010.1924050.384810.807595
1020.2289630.4579260.771037
1030.2234460.4468920.776554
1040.1983450.3966910.801655
1050.1739640.3479270.826036
1060.1614670.3229340.838533
1070.1419730.2839450.858027
1080.1687870.3375740.831213
1090.1605140.3210270.839486
1100.1850380.3700770.814962
1110.2675710.5351420.732429
1120.296330.5926590.70367
1130.2868990.5737990.713101
1140.2650670.5301350.734933
1150.243560.4871210.75644
1160.3556790.7113570.644321
1170.3986240.7972470.601376
1180.5912610.8174770.408739
1190.6614020.6771950.338598
1200.6533230.6933540.346677
1210.623840.7523210.37616
1220.6024430.7951150.397557
1230.6036710.7926580.396329
1240.6534060.6931880.346594
1250.6216660.7566680.378334
1260.6202430.7595140.379757
1270.6018880.7962250.398112
1280.6339190.7321620.366081
1290.6030570.7938850.396943
1300.5920840.8158320.407916
1310.5726540.8546920.427346
1320.5899690.8200620.410031
1330.5579940.8840120.442006
1340.5310460.9379080.468954
1350.5038580.9922840.496142
1360.4723880.9447760.527612
1370.4380630.8761260.561937
1380.4124960.8249920.587504
1390.4004520.8009040.599548
1400.4222510.8445010.577749
1410.5097040.9805910.490296
1420.4936270.9872540.506373
1430.4629920.9259840.537008
1440.4392070.8784140.560793
1450.5371850.9256290.462815
1460.5037140.9925720.496286
1470.5228090.9543830.477191
1480.501450.99710.49855
1490.4683480.9366970.531652
1500.4384710.8769430.561529
1510.4096020.8192040.590398
1520.4010610.8021220.598939
1530.3741550.7483090.625845
1540.3427240.6854480.657276
1550.3879020.7758040.612098
1560.4574930.9149850.542507
1570.4280360.8560720.571964
1580.4565260.9130520.543474
1590.4337680.8675350.566232
1600.404810.8096190.59519
1610.3849060.7698130.615094
1620.3642630.7285250.635737
1630.3329020.6658050.667098
1640.3425360.6850720.657464
1650.3421760.6843520.657824
1660.3182850.6365690.681715
1670.3000360.6000720.699964
1680.2724040.5448080.727596
1690.2660530.5321070.733947
1700.2572340.5144690.742766
1710.2395960.4791920.760404
1720.2258270.4516530.774173
1730.2347420.4694840.765258
1740.209070.4181390.79093
1750.2654750.5309510.734525
1760.240940.4818810.75906
1770.2403610.4807220.759639
1780.2155970.4311950.784403
1790.1981720.3963440.801828
1800.1828950.3657890.817105
1810.190820.3816390.80918
1820.1811810.3623630.818819
1830.2218930.4437870.778107
1840.1993660.3987320.800634
1850.322090.6441790.67791
1860.3824320.7648630.617568
1870.3525680.7051360.647432
1880.3806750.7613490.619325
1890.3475820.6951630.652418
1900.3191080.6382150.680892
1910.2880660.5761330.711934
1920.3100020.6200050.689998
1930.2931570.5863140.706843
1940.2636160.5272320.736384
1950.2393120.4786230.760688
1960.2486470.4972940.751353
1970.22490.4497990.7751
1980.2515610.5031230.748439
1990.2752540.5505080.724746
2000.2483890.4967780.751611
2010.2193660.4387330.780634
2020.2018780.4037550.798122
2030.1761660.3523310.823834
2040.1585940.3171890.841406
2050.1380090.2760180.861991
2060.1569680.3139360.843032
2070.1357590.2715180.864241
2080.1205270.2410550.879473
2090.1042860.2085730.895714
2100.08953690.1790740.910463
2110.07668730.1533750.923313
2120.0978920.1957840.902108
2130.08414140.1682830.915859
2140.0720650.144130.927935
2150.07528930.1505790.924711
2160.0730660.1461320.926934
2170.07109220.1421840.928908
2180.06477060.1295410.935229
2190.08956980.179140.91043
2200.07424750.1484950.925752
2210.06373980.127480.93626
2220.05368840.1073770.946312
2230.05325590.1065120.946744
2240.04281740.08563480.957183
2250.05930430.1186090.940696
2260.05432250.1086450.945677
2270.04368060.08736120.956319
2280.04796260.09592530.952037
2290.1097350.219470.890265
2300.09146380.1829280.908536
2310.1390550.278110.860945
2320.1665930.3331870.833407
2330.1529890.3059780.847011
2340.1716690.3433370.828331
2350.1723070.3446140.827693
2360.153410.3068190.84659
2370.2107230.4214470.789277
2380.3841080.7682150.615892
2390.3434390.6868780.656561
2400.3021770.6043540.697823
2410.2886340.5772670.711366
2420.2596570.5193140.740343
2430.6452960.7094080.354704
2440.596650.80670.40335
2450.5472740.9054520.452726
2460.5370280.9259450.462972
2470.4831120.9662230.516888
2480.5345260.9309490.465474
2490.4883330.9766660.511667
2500.4565460.9130920.543454
2510.4392580.8785160.560742
2520.5927680.8144640.407232
2530.5392690.9214610.460731
2540.4903680.9807370.509632
2550.4329860.8659720.567014
2560.4958490.9916990.504151
2570.4326540.8653070.567346
2580.4173840.8347680.582616
2590.447040.894080.55296
2600.4253140.8506280.574686
2610.3722670.7445330.627733
2620.3335490.6670980.666451
2630.6051070.7897860.394893
2640.551070.897860.44893
2650.5885750.8228490.411425
2660.7803460.4393070.219654
2670.7579280.4841440.242072
2680.9052610.1894780.0947389
2690.8581840.2836330.141816
2700.9074960.1850080.0925038
2710.8424140.3151720.157586
2720.8651440.2697120.134856
2730.7749670.4500670.225033
2740.6190950.761810.380905






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level40.0152091OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 4 & 0.0152091 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263679&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]4[/C][C]0.0152091[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263679&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263679&T=6

As an alternative you can also use a QR Code:  
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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 level00OK
5% type I error level00OK
10% type I error level40.0152091OK


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')
}