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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationThu, 11 Dec 2014 09:05:24 +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/11/t1418288899n1qifvsupo9nkr5.htm/, Retrieved Thu, 16 May 2024 09:58:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265642, Retrieved Thu, 16 May 2024 09:58:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [defmra] [2014-12-11 09:05:24] [7de4f24d5c21ad7c83693f758b02221d] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
12.9 2011 1 26 50 0 13 21 149 68
12.2 2011 1 57 62 1 8 22 139 39
12.8 2011 1 37 54 0 14 22 148 32
7.4 2011 1 67 71 1 16 18 158 62
6.7 2011 1 43 54 1 14 23 128 33
12.6 2011 1 52 65 1 13 12 224 52
14.8 2011 1 52 73 0 15 20 159 62
13.3 2011 1 43 52 1 13 22 105 77
11.1 2011 1 84 84 1 20 21 159 76
8.2 2011 1 67 42 1 17 19 167 41
11.4 2011 1 49 66 1 15 22 165 48
6.4 2011 1 70 65 1 16 15 159 63
10.6 2011 1 52 78 1 12 20 119 30
12.0 2011 1 58 73 0 17 19 176 78
6.3 2011 1 68 75 0 11 18 54 19
11.3 2011 0 62 72 0 16 15 91 31
11.9 2011 1 43 66 1 16 20 163 66
9.3 2011 1 56 70 0 15 21 124 35
9.6 2011 0 56 61 1 13 21 137 42
10.0 2011 1 74 81 0 14 15 121 45
6.4 2011 1 65 71 1 19 16 153 21
13.8 2011 1 63 69 1 16 23 148 25
10.8 2011 1 58 71 0 17 21 221 44
13.8 2011 1 57 72 1 10 18 188 69
11.7 2011 1 63 68 1 15 25 149 54
10.9 2011 1 53 70 1 14 9 244 74
16.1 2011 0 57 68 1 14 30 148 80
13.4 2011 0 51 61 0 16 20 92 42
9.9 2011 1 64 67 1 15 23 150 61
11.5 2011 1 53 76 0 17 16 153 41
8.3 2011 1 29 70 0 14 16 94 46
11.7 2011 1 54 60 0 16 19 156 39
9.0 2011 1 58 72 1 15 25 132 34
9.7 2011 1 43 69 1 16 18 161 51
10.8 2011 1 51 71 1 16 23 105 42
10.3 2011 1 53 62 1 10 21 97 31
10.4 2011 1 54 70 0 8 10 151 39
12.7 2011 0 56 64 1 17 14 131 20
9.3 2011 1 61 58 1 14 22 166 49
11.8 2011 1 47 76 0 10 26 157 53
5.9 2011 1 39 52 1 14 23 111 31
11.4 2011 1 48 59 1 12 23 145 39
13.0 2011 1 50 68 1 16 24 162 54
10.8 2011 1 35 76 1 16 24 163 49
12.3 2011 0 30 65 1 16 18 59 34
11.3 2011 1 68 67 0 8 23 187 46
11.8 2011 1 49 59 1 16 15 109 55
7.9 2011 0 61 69 1 15 19 90 42
12.7 2011 1 67 76 0 8 16 105 50
12.3 2011 0 47 63 1 13 25 83 13
11.6 2011 0 56 75 1 14 23 116 37
6.7 2011 0 50 63 1 13 17 42 25
10.9 2011 1 43 60 1 16 19 148 30
12.1 2011 0 67 73 1 19 21 155 28
13.3 2011 1 62 63 1 19 18 125 45
10.1 2011 1 57 70 1 14 27 116 35
5.7 2011 0 41 75 0 15 21 128 28
14.3 2011 1 54 66 1 13 13 138 41
8.0 2011 0 45 63 0 10 8 49 6
13.3 2011 0 48 63 1 16 29 96 45
9.3 2011 1 61 64 1 15 28 164 73
12.5 2011 1 56 70 0 11 23 162 17
7.6 2011 1 41 75 0 9 21 99 40
15.9 2011 1 43 61 1 16 19 202 64
9.2 2011 1 53 60 0 12 19 186 37
9.1 2011 0 44 62 1 12 20 66 25
11.1 2011 1 66 73 0 14 18 183 65
13.0 2011 1 58 61 1 14 19 214 100
14.5 2011 1 46 66 1 13 17 188 28
12.2 2011 0 37 64 0 15 19 104 35
12.3 2011 1 51 59 0 17 25 177 56
11.4 2011 1 51 64 0 14 19 126 29
8.8 2011 0 56 60 0 11 22 76 43
14.6 2011 0 66 56 1 9 23 99 59
12.6 2011 1 37 78 0 7 14 139 50
13.0 2011 1 42 67 0 15 16 162 59
12.6 2011 0 38 59 1 12 24 108 27
13.2 2011 1 66 66 0 15 20 159 61
9.9 2011 0 34 68 0 14 12 74 28
7.7 2011 1 53 71 1 16 24 110 51
10.5 2011 0 49 66 0 14 22 96 35
13.4 2011 0 55 73 0 13 12 116 29
10.9 2011 0 49 72 0 16 22 87 48
4.3 2011 0 59 71 1 13 20 97 25
10.3 2011 0 40 59 0 16 10 127 44
11.8 2011 0 58 64 1 16 23 106 64
11.2 2011 0 60 66 1 16 17 80 32
11.4 2011 0 63 78 0 10 22 74 20
8.6 2011 0 56 68 0 12 24 91 28
13.2 2011 0 54 73 0 12 18 133 34
12.6 2011 0 52 62 1 12 21 74 31
5.6 2011 0 34 65 1 12 20 114 26
9.9 2011 0 69 68 1 19 20 140 58
8.8 2011 0 32 65 0 14 22 95 23
7.7 2011 0 48 60 1 13 19 98 21
9.0 2011 0 67 71 0 16 20 121 21
7.3 2011 0 58 65 1 15 26 126 33
11.4 2011 0 57 68 1 12 23 98 16
13.6 2011 0 42 64 1 8 24 95 20
7.9 2011 0 64 74 1 10 21 110 37
10.7 2011 0 58 69 1 16 21 70 35
10.3 2011 0 66 76 0 16 19 102 33
8.3 2011 0 26 68 1 10 8 86 27
9.6 2011 0 61 72 1 18 17 130 41
14.2 2011 0 52 67 1 12 20 96 40
8.5 2011 0 51 63 0 16 11 102 35
13.5 2011 0 55 59 0 10 8 100 28
4.9 2011 0 50 73 0 14 15 94 32
6.4 2011 0 60 66 0 12 18 52 22
9.6 2011 0 56 62 0 11 18 98 44
11.6 2011 0 63 69 0 15 19 118 27
11.1 2011 0 61 66 1 7 19 99 17
4.35 2012 1 52 51 1 16 23 48 12
12.7 2012 1 16 56 1 16 22 50 45
18.1 2012 1 46 67 1 16 21 150 37
17.85 2012 1 56 69 1 16 25 154 37
16.6 2012 0 52 57 0 12 30 109 108
12.6 2012 0 55 56 1 15 17 68 10
17.1 2012 1 50 55 1 14 27 194 68
19.1 2012 1 59 63 0 15 23 158 72
16.1 2012 1 60 67 1 16 23 159 143
13.35 2012 1 52 65 0 13 18 67 9
18.4 2012 1 44 47 0 10 18 147 55
14.7 2012 1 67 76 1 17 23 39 17
10.6 2012 1 52 64 1 15 19 100 37
12.6 2012 1 55 68 1 18 15 111 27
16.2 2012 1 37 64 1 16 20 138 37
13.6 2012 1 54 65 1 20 16 101 58
18.9 2012 0 72 71 1 16 24 131 66
14.1 2012 1 51 63 1 17 25 101 21
14.5 2012 1 48 60 1 16 25 114 19
16.15 2012 1 60 68 0 15 19 165 78
14.75 2012 1 50 72 1 13 19 114 35
14.8 2012 1 63 70 1 16 16 111 48
12.45 2012 1 33 61 1 16 19 75 27
12.65 2012 1 67 61 1 16 19 82 43
17.35 2012 1 46 62 1 17 23 121 30
8.6 2012 1 54 71 1 20 21 32 25
18.4 2012 1 59 71 0 14 22 150 69
16.1 2012 1 61 51 1 17 19 117 72
11.6 2012 0 33 56 1 6 20 71 23
17.75 2012 1 47 70 1 16 20 165 13
15.25 2012 1 69 73 1 15 3 154 61
17.65 2012 1 52 76 1 16 23 126 43
16.35 2012 1 55 68 0 16 23 149 51
17.65 2012 1 41 48 0 14 20 145 67
13.6 2012 1 73 52 1 16 15 120 36
14.35 2012 1 52 60 0 16 16 109 44
14.75 2012 1 50 59 0 16 7 132 45
18.25 2012 1 51 57 1 14 24 172 34
9.9 2012 1 60 79 0 14 17 169 36
16 2012 1 56 60 1 16 24 114 72
18.25 2012 1 56 60 1 16 24 156 39
16.85 2012 1 29 59 0 15 19 172 43
14.6 2012 0 66 62 1 16 25 68 25
13.85 2012 0 66 59 1 16 20 89 56
18.95 2012 1 73 61 1 18 28 167 80
15.6 2012 1 55 71 0 15 23 113 40
14.85 2012 0 64 57 0 16 27 115 73
11.75 2012 0 40 66 0 16 18 78 34
18.45 2012 0 46 63 0 16 28 118 72
15.9 2012 0 58 69 1 17 21 87 42
17.1 2012 1 43 58 0 14 19 173 61
16.1 2012 1 61 59 1 18 23 2 23
19.9 2012 0 51 48 0 9 27 162 74
10.95 2012 0 50 66 1 15 22 49 16
18.45 2012 0 52 73 0 14 28 122 66
15.1 2012 0 54 67 1 15 25 96 9
15 2012 0 66 61 0 13 21 100 41
11.35 2012 0 61 68 0 16 22 82 57
15.95 2012 0 80 75 1 20 28 100 48
18.1 2012 0 51 62 0 14 20 115 51
14.6 2012 0 56 69 1 12 29 141 53
15.4 2012 1 56 58 1 15 25 165 29
15.4 2012 1 56 60 1 15 25 165 29
17.6 2012 0 53 74 1 15 20 110 55
13.35 2012 1 47 55 1 16 20 118 54
19.1 2012 1 25 62 0 11 16 158 43
15.35 2012 0 47 63 1 16 20 146 51
7.6 2012 1 46 69 0 7 20 49 20
13.4 2012 0 50 58 0 11 23 90 79
13.9 2012 0 39 58 0 9 18 121 39
19.1 2012 1 51 68 1 15 25 155 61
15.25 2012 0 58 72 0 16 18 104 55
12.9 2012 0 35 62 1 14 19 147 30
16.1 2012 0 58 62 0 15 25 110 55
17.35 2012 0 60 65 0 13 25 108 22
13.15 2012 0 62 69 0 13 25 113 37
12.15 2012 0 63 66 0 12 24 115 2
12.6 2012 0 53 72 1 16 19 61 38
10.35 2012 0 46 62 1 14 26 60 27
15.4 2012 0 67 75 1 16 10 109 56
9.6 2012 0 59 58 1 14 17 68 25
18.2 2012 0 64 66 0 15 13 111 39
13.6 2012 0 38 55 0 10 17 77 33
14.85 2012 0 50 47 1 16 30 73 43
14.75 2012 1 48 72 0 14 25 151 57
14.1 2012 0 48 62 0 16 4 89 43
14.9 2012 0 47 64 0 12 16 78 23
16.25 2012 0 66 64 0 16 21 110 44
19.25 2012 1 47 19 1 16 23 220 54
13.6 2012 0 63 50 1 15 22 65 28
13.6 2012 1 58 68 0 14 17 141 36
15.65 2012 0 44 70 0 16 20 117 39
12.75 2012 1 51 79 1 11 20 122 16
14.6 2012 0 43 69 0 15 22 63 23
9.85 2012 1 55 71 1 18 16 44 40
12.65 2012 0 38 48 1 13 23 52 24
19.2 2012 0 45 73 0 7 0 131 78
16.6 2012 0 50 74 1 7 18 101 57
11.2 2012 0 54 66 1 17 25 42 37
15.25 2012 1 57 71 1 18 23 152 27
11.9 2012 1 60 74 0 15 12 107 61
13.2 2012 0 55 78 0 8 18 77 27
16.35 2012 1 56 75 0 13 24 154 69
12.4 2012 1 49 53 1 13 11 103 34
15.85 2012 0 37 60 1 15 18 96 44
18.15 2012 1 59 70 1 18 23 175 34
11.15 2012 0 46 69 1 16 24 57 39
15.65 2012 0 51 65 0 14 29 112 51
17.75 2012 1 58 78 0 15 18 143 34
7.65 2012 0 64 78 0 19 15 49 31
12.35 2012 1 53 59 1 16 29 110 13
15.6 2012 1 48 72 1 12 16 131 12
19.3 2012 1 51 70 0 16 19 167 51
15.2 2012 0 47 63 0 11 22 56 24
17.1 2012 1 59 63 0 16 16 137 19
15.6 2012 0 62 71 1 15 23 86 30
18.4 2012 1 62 74 1 19 23 121 81
19.05 2012 1 51 67 0 15 19 149 42
18.55 2012 1 64 66 0 14 4 168 22
19.1 2012 1 52 62 0 14 20 140 85
13.1 2012 0 67 80 1 17 24 88 27
12.85 2012 1 50 73 1 16 20 168 25
9.5 2012 1 54 67 1 20 4 94 22
4.5 2012 1 58 61 1 16 24 51 19
11.85 2012 0 56 73 0 9 22 48 14
13.6 2012 1 63 74 1 13 16 145 45
11.7 2012 1 31 32 1 15 3 66 45
12.4 2012 0 65 69 1 19 15 85 28
13.35 2012 1 71 69 0 16 24 109 51
11.4 2012 0 50 84 0 17 17 63 41
14.9 2012 0 57 64 1 16 20 102 31
19.9 2012 0 47 58 0 9 27 162 74
11.2 2012 0 47 59 1 11 26 86 19
14.6 2012 0 57 78 1 14 23 114 51
17.6 2012 1 43 57 0 19 17 164 73
14.05 2012 1 41 60 1 13 20 119 24
16.1 2012 1 63 68 0 14 22 126 61
13.35 2012 1 63 68 1 15 19 132 23
11.85 2012 1 56 73 1 15 24 142 14
11.95 2012 1 51 69 0 14 19 83 54
14.75 2012 0 50 67 1 16 23 94 51
15.15 2012 0 22 60 0 17 15 81 62
13.2 2012 1 41 65 1 12 27 166 36
16.85 2012 0 59 66 0 15 26 110 59
7.85 2012 0 56 74 1 17 22 64 24
7.7 2012 1 66 81 0 15 22 93 26
12.6 2012 0 53 72 0 10 18 104 54
7.85 2012 0 42 55 1 16 15 105 39
10.95 2012 0 52 49 1 15 22 49 16
12.35 2012 0 54 74 0 11 27 88 36
9.95 2012 0 44 53 1 16 10 95 31
14.9 2012 0 62 64 1 16 20 102 31
16.65 2012 0 53 65 0 16 17 99 42
13.4 2012 0 50 57 1 14 23 63 39
13.95 2012 0 36 51 0 14 19 76 25
15.7 2012 0 76 80 0 16 13 109 31
16.85 2012 0 66 67 1 16 27 117 38
10.95 2012 0 62 70 1 18 23 57 31
15.35 2012 0 59 74 0 14 16 120 17
12.2 2012 0 47 75 1 20 25 73 22
15.1 2012 0 55 70 0 15 2 91 55
17.75 2012 0 58 69 0 16 26 108 62
15.2 2012 0 60 65 1 16 20 105 51
14.6 2012 1 44 55 0 16 23 117 30
16.65 2012 0 57 71 0 12 22 119 49
8.1 2012 0 45 65 1 8 24 31 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 10 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&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]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&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 time10 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = -8807.05 + 4.38272Year[t] -1.00738B_or_S[t] -0.00617263AMS.I[t] -0.0146209AMS.E[t] -0.500768gender[t] -0.0450798CONFSTATTOT[t] + 0.0425725NUMERACYTOT[t] + 0.0366636LFM[t] + 0.0332198CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  -8807.05 +  4.38272Year[t] -1.00738B_or_S[t] -0.00617263AMS.I[t] -0.0146209AMS.E[t] -0.500768gender[t] -0.0450798CONFSTATTOT[t] +  0.0425725NUMERACYTOT[t] +  0.0366636LFM[t] +  0.0332198CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  -8807.05 +  4.38272Year[t] -1.00738B_or_S[t] -0.00617263AMS.I[t] -0.0146209AMS.E[t] -0.500768gender[t] -0.0450798CONFSTATTOT[t] +  0.0425725NUMERACYTOT[t] +  0.0366636LFM[t] +  0.0332198CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&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] = -8807.05 + 4.38272Year[t] -1.00738B_or_S[t] -0.00617263AMS.I[t] -0.0146209AMS.E[t] -0.500768gender[t] -0.0450798CONFSTATTOT[t] + 0.0425725NUMERACYTOT[t] + 0.0366636LFM[t] + 0.0332198CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-8807.05600.568-14.663.77159e-361.8858e-36
Year4.382720.29852114.683.28409e-361.64204e-36
B_or_S-1.007380.32922-3.060.002438610.0012193
AMS.I-0.006172630.0148994-0.41430.6789950.339498
AMS.E-0.01462090.0186274-0.78490.4331980.216599
gender-0.5007680.30165-1.660.09806510.0490325
CONFSTATTOT-0.04507980.0549278-0.82070.4125420.206271
NUMERACYTOT0.04257250.02773271.5350.1259390.0629695
LFM0.03666360.004607297.9584.96761e-142.4838e-14
CH0.03321980.0083043948.19057e-054.09529e-05

\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) & -8807.05 & 600.568 & -14.66 & 3.77159e-36 & 1.8858e-36 \tabularnewline
Year & 4.38272 & 0.298521 & 14.68 & 3.28409e-36 & 1.64204e-36 \tabularnewline
B_or_S & -1.00738 & 0.32922 & -3.06 & 0.00243861 & 0.0012193 \tabularnewline
AMS.I & -0.00617263 & 0.0148994 & -0.4143 & 0.678995 & 0.339498 \tabularnewline
AMS.E & -0.0146209 & 0.0186274 & -0.7849 & 0.433198 & 0.216599 \tabularnewline
gender & -0.500768 & 0.30165 & -1.66 & 0.0980651 & 0.0490325 \tabularnewline
CONFSTATTOT & -0.0450798 & 0.0549278 & -0.8207 & 0.412542 & 0.206271 \tabularnewline
NUMERACYTOT & 0.0425725 & 0.0277327 & 1.535 & 0.125939 & 0.0629695 \tabularnewline
LFM & 0.0366636 & 0.00460729 & 7.958 & 4.96761e-14 & 2.4838e-14 \tabularnewline
CH & 0.0332198 & 0.00830439 & 4 & 8.19057e-05 & 4.09529e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&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]-8807.05[/C][C]600.568[/C][C]-14.66[/C][C]3.77159e-36[/C][C]1.8858e-36[/C][/ROW]
[ROW][C]Year[/C][C]4.38272[/C][C]0.298521[/C][C]14.68[/C][C]3.28409e-36[/C][C]1.64204e-36[/C][/ROW]
[ROW][C]B_or_S[/C][C]-1.00738[/C][C]0.32922[/C][C]-3.06[/C][C]0.00243861[/C][C]0.0012193[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00617263[/C][C]0.0148994[/C][C]-0.4143[/C][C]0.678995[/C][C]0.339498[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0146209[/C][C]0.0186274[/C][C]-0.7849[/C][C]0.433198[/C][C]0.216599[/C][/ROW]
[ROW][C]gender[/C][C]-0.500768[/C][C]0.30165[/C][C]-1.66[/C][C]0.0980651[/C][C]0.0490325[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]-0.0450798[/C][C]0.0549278[/C][C]-0.8207[/C][C]0.412542[/C][C]0.206271[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0425725[/C][C]0.0277327[/C][C]1.535[/C][C]0.125939[/C][C]0.0629695[/C][/ROW]
[ROW][C]LFM[/C][C]0.0366636[/C][C]0.00460729[/C][C]7.958[/C][C]4.96761e-14[/C][C]2.4838e-14[/C][/ROW]
[ROW][C]CH[/C][C]0.0332198[/C][C]0.00830439[/C][C]4[/C][C]8.19057e-05[/C][C]4.09529e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&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)-8807.05600.568-14.663.77159e-361.8858e-36
Year4.382720.29852114.683.28409e-361.64204e-36
B_or_S-1.007380.32922-3.060.002438610.0012193
AMS.I-0.006172630.0148994-0.41430.6789950.339498
AMS.E-0.01462090.0186274-0.78490.4331980.216599
gender-0.5007680.30165-1.660.09806510.0490325
CONFSTATTOT-0.04507980.0549278-0.82070.4125420.206271
NUMERACYTOT0.04257250.02773271.5350.1259390.0629695
LFM0.03666360.004607297.9584.96761e-142.4838e-14
CH0.03321980.0083043948.19057e-054.09529e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.747444
R-squared0.558672
Adjusted R-squared0.543851
F-TEST (value)37.6953
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29251
Sum Squared Residuals1408.5

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.747444 \tabularnewline
R-squared & 0.558672 \tabularnewline
Adjusted R-squared & 0.543851 \tabularnewline
F-TEST (value) & 37.6953 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 268 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.29251 \tabularnewline
Sum Squared Residuals & 1408.5 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.747444[/C][/ROW]
[ROW][C]R-squared[/C][C]0.558672[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.543851[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.6953[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]268[/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]2.29251[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1408.5[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.747444
R-squared0.558672
Adjusted R-squared0.543851
F-TEST (value)37.6953
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29251
Sum Squared Residuals1408.5






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.72770.172317
212.210.79811.40193
312.811.36621.43378
47.411.5345-4.1345
56.710.1709-3.47093
612.613.6822-1.08221
714.812.26552.5345
813.310.82112.47891
911.111.6886-0.588629
108.211.5883-3.38835
1111.411.7256-0.325645
126.411.5459-5.14587
1310.69.297291.30271
141213.2505-1.25053
156.36.95454-0.654544
1611.39.44491.8551
1711.912.1571-0.257085
189.310.1471-0.847085
199.611.5846-1.98461
20109.8870.113
216.49.78113-3.38113
2213.810.20553.59448
2310.813.8853-3.0853
2413.813.18450.615475
2511.711.35040.349595
2610.914.8942-3.99424
2716.113.47982.62018
2813.410.28863.11143
299.911.5429-1.64291
3011.511.03740.462582
318.39.41147-1.11147
3211.711.48150.218473
33910.0351-1.03511
349.711.4565-1.75645
3510.89.238561.56144
3610.38.88441.4156
3710.411.1295-0.729486
3812.710.11162.58839
399.311.8835-2.5835
4011.812.361-0.561029
415.99.53515-3.63515
4211.410.97970.420274
431311.81961.18038
4410.811.6658-0.865811
4512.38.298144.00186
4611.313.1928-1.8928
4711.89.664282.13572
487.99.53829-1.63829
4912.79.895852.80415
5012.38.838013.46199
5111.610.4841.11605
526.77.37434-0.674342
5310.910.45640.443628
5412.111.26570.834348
5513.39.772453.52755
5610.19.647350.45265
575.711.0881-5.38807
5814.310.17934.12067
5987.283530.716472
6013.310.40652.89345
619.312.7301-3.43008
6212.511.20781.29219
637.69.68656-2.08656
6415.913.55112.34894
659.212.7015-3.50149
669.18.478720.621279
6711.113.1186-2.0186
681315.1845-2.1845
6914.511.80032.69967
7012.210.54111.65894
7112.313.0597-0.759693
7211.410.09961.30038
738.810.0295-1.22948
7414.611.0333.56702
7512.611.25831.34172
761312.2550.745008
7712.610.33622.26378
7813.212.24820.951791
799.98.915720.984281
807.79.75108-2.05108
8110.510.31720.182767
8213.410.33123.06884
8310.910.24120.658767
844.39.34603-5.04603
8510.311.3097-1.00965
8611.811.07260.727424
8711.28.759272.44073
8811.48.930792.46921
898.610.0042-1.40423
9013.211.42721.77277
9112.68.964543.63546
925.610.2897-4.68966
939.911.7305-1.83048
948.810.0015-1.20149
957.79.43597-1.73597
96910.4092-1.40923
977.310.9342-3.63421
9811.49.312732.08727
9913.69.709583.89042
1007.910.3244-2.42438
10110.78.631062.06894
10210.310.00180.298246
1038.38.8811-0.581104
1049.610.7074-1.10737
10514.29.954444.24556
1068.510.0103-1.51027
10713.59.880963.61904
1084.99.73772-4.83772
1096.48.12415-1.72415
1109.610.6698-1.06976
11111.610.5551.045
11211.19.442271.65773
1134.3510.8211-6.4711
11412.712.09720.60278
11518.115.10922.99076
11617.8515.33522.51479
11716.618.1454-1.54543
11812.612.19330.40666
11917.118.2486-1.1486
12019.117.17451.92553
12116.118.9592-2.85924
12213.3511.63651.7135
12318.416.54551.85451
12414.710.1544.54596
12510.613.2428-2.64282
12612.612.9314-0.331392
12716.214.72611.47388
12813.613.5970.00298191
12918.916.29212.60787
13014.112.9341.16596
13114.513.45171.04832
13216.1517.3809-1.23087
13314.7513.67521.07479
13414.813.68311.11688
13512.4512.11010.339903
13612.6512.6884-0.038389
13717.3513.92663.42337
1388.610.0961-1.49612
13918.416.6671.73296
14016.115.07321.02685
14111.613.4044-1.80442
14217.7514.76932.98069
14315.2515.10220.147753
14417.6514.34523.30485
14516.3516.05340.29661
14617.6516.77950.870472
14713.613.7733-0.173328
14814.3514.19180.158214
14914.7514.71210.0379186
15018.2516.14942.1006
1519.915.9314-6.0314
1521615.12040.87962
15318.2515.5642.686
15416.8516.79780.0522406
15514.612.83151.76849
15613.8514.4623-0.612262
15718.9517.28991.66012
15815.614.36931.2307
15914.8516.8206-1.97061
16011.7513.8019-2.05189
16118.4516.96331.48666
16215.913.82452.07548
16317.117.4057-0.305663
16416.19.237326.86268
16519.919.10440.795589
16610.9511.7936-0.843568
16718.4516.81761.63241
16815.113.37261.72738
1691515.0166-0.0166022
17011.3514.724-3.37403
17115.9514.43971.51029
17218.115.88912.21093
17314.616.7481-2.1481
17415.415.6787-0.278664
17515.415.6494-0.249423
17617.615.1052.49501
17713.3514.6274-1.27745
17819.116.31792.7821
17915.3516.4448-1.09478
1807.611.6762-4.07615
18113.416.2302-2.83025
18213.915.9832-2.08322
18319.116.25972.84028
18415.2515.2539-0.00392853
18512.915.9201-3.02011
18616.115.96320.136794
18717.3514.82762.52242
18813.1515.4384-2.28836
18912.1514.3892-2.23919
19012.612.6853-0.0853264
19110.3512.8608-2.51083
19215.414.52970.870298
1939.612.6828-3.08278
19418.214.8623.33804
19513.614.1331-0.53309
19614.8514.14370.706275
19714.7516.4861-1.73607
19814.113.91730.182743
19914.913.51771.38232
20016.2515.30380.946205
20119.2519.02120.228802
20213.612.93250.667488
20313.615.078-1.47799
20415.6515.39980.250158
20512.7513.3616-0.611555
20614.613.03951.56049
2079.8510.9055-1.0555
20812.6512.63930.0107036
20919.216.71292.48706
21016.615.13551.46453
21111.212.2474-1.04741
21215.2514.7190.53103
21311.914.3039-2.40391
21413.213.6253-0.425289
21516.3516.904-0.553957
21612.413.1821-0.782079
21715.8514.44461.40541
21818.1515.7972.35295
21911.1512.8718-1.72183
22015.6516.1184-0.468369
22117.7514.93622.81384
2227.6512.0524-4.40244
22312.3513.2598-0.909759
22415.613.46412.13586
22519.316.53852.76151
22615.213.05942.14056
22717.114.30082.7992
22815.613.51062.08941
22918.415.25653.14354
23019.0515.66853.38149
23118.5515.04163.50841
23219.116.92162.17842
23313.113.2742-0.174224
23412.8515.2156-2.36556
2359.511.6043-2.10435
2364.511.023-6.52296
23711.8512.3223-0.47233
23813.614.9068-1.30677
23911.712.1784-0.478351
24012.412.8973-0.497316
24113.3514.516-1.16604
24211.413.0719-1.67192
24314.914.09080.809157
24419.918.98290.917107
24511.213.7213-2.52125
24614.615.2084-0.608387
24717.617.17840.421594
24814.0513.76670.283314
24916.115.54050.559468
25013.3513.8246-0.474596
25111.8514.0752-2.22522
25211.9513.6632-1.71319
25314.7514.5890.161006
25415.1514.86810.281927
25513.216.1585-2.95849
25616.8516.0740.775999
2577.8512.3651-4.51512
2587.712.9143-5.21427
25912.615.5221-2.92205
2607.8514.4779-6.62791
26110.9512.0298-1.07978
26212.3514.6401-2.29014
2639.9513.6495-3.69955
26414.914.060.84002
26516.6514.72941.92061
26613.413.29020.109846
26713.9513.80630.143677
26815.714.1991.50097
26916.8515.07191.77807
27010.9512.36-1.40995
27115.3514.54780.802206
27212.212.6621-0.462062
27315.114.1890.911018
27417.7516.01761.73244
27515.214.83210.367909
27614.614.44050.15949
27716.6515.9760.674034
2788.111.5798-3.47981

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.7277 & 0.172317 \tabularnewline
2 & 12.2 & 10.7981 & 1.40193 \tabularnewline
3 & 12.8 & 11.3662 & 1.43378 \tabularnewline
4 & 7.4 & 11.5345 & -4.1345 \tabularnewline
5 & 6.7 & 10.1709 & -3.47093 \tabularnewline
6 & 12.6 & 13.6822 & -1.08221 \tabularnewline
7 & 14.8 & 12.2655 & 2.5345 \tabularnewline
8 & 13.3 & 10.8211 & 2.47891 \tabularnewline
9 & 11.1 & 11.6886 & -0.588629 \tabularnewline
10 & 8.2 & 11.5883 & -3.38835 \tabularnewline
11 & 11.4 & 11.7256 & -0.325645 \tabularnewline
12 & 6.4 & 11.5459 & -5.14587 \tabularnewline
13 & 10.6 & 9.29729 & 1.30271 \tabularnewline
14 & 12 & 13.2505 & -1.25053 \tabularnewline
15 & 6.3 & 6.95454 & -0.654544 \tabularnewline
16 & 11.3 & 9.4449 & 1.8551 \tabularnewline
17 & 11.9 & 12.1571 & -0.257085 \tabularnewline
18 & 9.3 & 10.1471 & -0.847085 \tabularnewline
19 & 9.6 & 11.5846 & -1.98461 \tabularnewline
20 & 10 & 9.887 & 0.113 \tabularnewline
21 & 6.4 & 9.78113 & -3.38113 \tabularnewline
22 & 13.8 & 10.2055 & 3.59448 \tabularnewline
23 & 10.8 & 13.8853 & -3.0853 \tabularnewline
24 & 13.8 & 13.1845 & 0.615475 \tabularnewline
25 & 11.7 & 11.3504 & 0.349595 \tabularnewline
26 & 10.9 & 14.8942 & -3.99424 \tabularnewline
27 & 16.1 & 13.4798 & 2.62018 \tabularnewline
28 & 13.4 & 10.2886 & 3.11143 \tabularnewline
29 & 9.9 & 11.5429 & -1.64291 \tabularnewline
30 & 11.5 & 11.0374 & 0.462582 \tabularnewline
31 & 8.3 & 9.41147 & -1.11147 \tabularnewline
32 & 11.7 & 11.4815 & 0.218473 \tabularnewline
33 & 9 & 10.0351 & -1.03511 \tabularnewline
34 & 9.7 & 11.4565 & -1.75645 \tabularnewline
35 & 10.8 & 9.23856 & 1.56144 \tabularnewline
36 & 10.3 & 8.8844 & 1.4156 \tabularnewline
37 & 10.4 & 11.1295 & -0.729486 \tabularnewline
38 & 12.7 & 10.1116 & 2.58839 \tabularnewline
39 & 9.3 & 11.8835 & -2.5835 \tabularnewline
40 & 11.8 & 12.361 & -0.561029 \tabularnewline
41 & 5.9 & 9.53515 & -3.63515 \tabularnewline
42 & 11.4 & 10.9797 & 0.420274 \tabularnewline
43 & 13 & 11.8196 & 1.18038 \tabularnewline
44 & 10.8 & 11.6658 & -0.865811 \tabularnewline
45 & 12.3 & 8.29814 & 4.00186 \tabularnewline
46 & 11.3 & 13.1928 & -1.8928 \tabularnewline
47 & 11.8 & 9.66428 & 2.13572 \tabularnewline
48 & 7.9 & 9.53829 & -1.63829 \tabularnewline
49 & 12.7 & 9.89585 & 2.80415 \tabularnewline
50 & 12.3 & 8.83801 & 3.46199 \tabularnewline
51 & 11.6 & 10.484 & 1.11605 \tabularnewline
52 & 6.7 & 7.37434 & -0.674342 \tabularnewline
53 & 10.9 & 10.4564 & 0.443628 \tabularnewline
54 & 12.1 & 11.2657 & 0.834348 \tabularnewline
55 & 13.3 & 9.77245 & 3.52755 \tabularnewline
56 & 10.1 & 9.64735 & 0.45265 \tabularnewline
57 & 5.7 & 11.0881 & -5.38807 \tabularnewline
58 & 14.3 & 10.1793 & 4.12067 \tabularnewline
59 & 8 & 7.28353 & 0.716472 \tabularnewline
60 & 13.3 & 10.4065 & 2.89345 \tabularnewline
61 & 9.3 & 12.7301 & -3.43008 \tabularnewline
62 & 12.5 & 11.2078 & 1.29219 \tabularnewline
63 & 7.6 & 9.68656 & -2.08656 \tabularnewline
64 & 15.9 & 13.5511 & 2.34894 \tabularnewline
65 & 9.2 & 12.7015 & -3.50149 \tabularnewline
66 & 9.1 & 8.47872 & 0.621279 \tabularnewline
67 & 11.1 & 13.1186 & -2.0186 \tabularnewline
68 & 13 & 15.1845 & -2.1845 \tabularnewline
69 & 14.5 & 11.8003 & 2.69967 \tabularnewline
70 & 12.2 & 10.5411 & 1.65894 \tabularnewline
71 & 12.3 & 13.0597 & -0.759693 \tabularnewline
72 & 11.4 & 10.0996 & 1.30038 \tabularnewline
73 & 8.8 & 10.0295 & -1.22948 \tabularnewline
74 & 14.6 & 11.033 & 3.56702 \tabularnewline
75 & 12.6 & 11.2583 & 1.34172 \tabularnewline
76 & 13 & 12.255 & 0.745008 \tabularnewline
77 & 12.6 & 10.3362 & 2.26378 \tabularnewline
78 & 13.2 & 12.2482 & 0.951791 \tabularnewline
79 & 9.9 & 8.91572 & 0.984281 \tabularnewline
80 & 7.7 & 9.75108 & -2.05108 \tabularnewline
81 & 10.5 & 10.3172 & 0.182767 \tabularnewline
82 & 13.4 & 10.3312 & 3.06884 \tabularnewline
83 & 10.9 & 10.2412 & 0.658767 \tabularnewline
84 & 4.3 & 9.34603 & -5.04603 \tabularnewline
85 & 10.3 & 11.3097 & -1.00965 \tabularnewline
86 & 11.8 & 11.0726 & 0.727424 \tabularnewline
87 & 11.2 & 8.75927 & 2.44073 \tabularnewline
88 & 11.4 & 8.93079 & 2.46921 \tabularnewline
89 & 8.6 & 10.0042 & -1.40423 \tabularnewline
90 & 13.2 & 11.4272 & 1.77277 \tabularnewline
91 & 12.6 & 8.96454 & 3.63546 \tabularnewline
92 & 5.6 & 10.2897 & -4.68966 \tabularnewline
93 & 9.9 & 11.7305 & -1.83048 \tabularnewline
94 & 8.8 & 10.0015 & -1.20149 \tabularnewline
95 & 7.7 & 9.43597 & -1.73597 \tabularnewline
96 & 9 & 10.4092 & -1.40923 \tabularnewline
97 & 7.3 & 10.9342 & -3.63421 \tabularnewline
98 & 11.4 & 9.31273 & 2.08727 \tabularnewline
99 & 13.6 & 9.70958 & 3.89042 \tabularnewline
100 & 7.9 & 10.3244 & -2.42438 \tabularnewline
101 & 10.7 & 8.63106 & 2.06894 \tabularnewline
102 & 10.3 & 10.0018 & 0.298246 \tabularnewline
103 & 8.3 & 8.8811 & -0.581104 \tabularnewline
104 & 9.6 & 10.7074 & -1.10737 \tabularnewline
105 & 14.2 & 9.95444 & 4.24556 \tabularnewline
106 & 8.5 & 10.0103 & -1.51027 \tabularnewline
107 & 13.5 & 9.88096 & 3.61904 \tabularnewline
108 & 4.9 & 9.73772 & -4.83772 \tabularnewline
109 & 6.4 & 8.12415 & -1.72415 \tabularnewline
110 & 9.6 & 10.6698 & -1.06976 \tabularnewline
111 & 11.6 & 10.555 & 1.045 \tabularnewline
112 & 11.1 & 9.44227 & 1.65773 \tabularnewline
113 & 4.35 & 10.8211 & -6.4711 \tabularnewline
114 & 12.7 & 12.0972 & 0.60278 \tabularnewline
115 & 18.1 & 15.1092 & 2.99076 \tabularnewline
116 & 17.85 & 15.3352 & 2.51479 \tabularnewline
117 & 16.6 & 18.1454 & -1.54543 \tabularnewline
118 & 12.6 & 12.1933 & 0.40666 \tabularnewline
119 & 17.1 & 18.2486 & -1.1486 \tabularnewline
120 & 19.1 & 17.1745 & 1.92553 \tabularnewline
121 & 16.1 & 18.9592 & -2.85924 \tabularnewline
122 & 13.35 & 11.6365 & 1.7135 \tabularnewline
123 & 18.4 & 16.5455 & 1.85451 \tabularnewline
124 & 14.7 & 10.154 & 4.54596 \tabularnewline
125 & 10.6 & 13.2428 & -2.64282 \tabularnewline
126 & 12.6 & 12.9314 & -0.331392 \tabularnewline
127 & 16.2 & 14.7261 & 1.47388 \tabularnewline
128 & 13.6 & 13.597 & 0.00298191 \tabularnewline
129 & 18.9 & 16.2921 & 2.60787 \tabularnewline
130 & 14.1 & 12.934 & 1.16596 \tabularnewline
131 & 14.5 & 13.4517 & 1.04832 \tabularnewline
132 & 16.15 & 17.3809 & -1.23087 \tabularnewline
133 & 14.75 & 13.6752 & 1.07479 \tabularnewline
134 & 14.8 & 13.6831 & 1.11688 \tabularnewline
135 & 12.45 & 12.1101 & 0.339903 \tabularnewline
136 & 12.65 & 12.6884 & -0.038389 \tabularnewline
137 & 17.35 & 13.9266 & 3.42337 \tabularnewline
138 & 8.6 & 10.0961 & -1.49612 \tabularnewline
139 & 18.4 & 16.667 & 1.73296 \tabularnewline
140 & 16.1 & 15.0732 & 1.02685 \tabularnewline
141 & 11.6 & 13.4044 & -1.80442 \tabularnewline
142 & 17.75 & 14.7693 & 2.98069 \tabularnewline
143 & 15.25 & 15.1022 & 0.147753 \tabularnewline
144 & 17.65 & 14.3452 & 3.30485 \tabularnewline
145 & 16.35 & 16.0534 & 0.29661 \tabularnewline
146 & 17.65 & 16.7795 & 0.870472 \tabularnewline
147 & 13.6 & 13.7733 & -0.173328 \tabularnewline
148 & 14.35 & 14.1918 & 0.158214 \tabularnewline
149 & 14.75 & 14.7121 & 0.0379186 \tabularnewline
150 & 18.25 & 16.1494 & 2.1006 \tabularnewline
151 & 9.9 & 15.9314 & -6.0314 \tabularnewline
152 & 16 & 15.1204 & 0.87962 \tabularnewline
153 & 18.25 & 15.564 & 2.686 \tabularnewline
154 & 16.85 & 16.7978 & 0.0522406 \tabularnewline
155 & 14.6 & 12.8315 & 1.76849 \tabularnewline
156 & 13.85 & 14.4623 & -0.612262 \tabularnewline
157 & 18.95 & 17.2899 & 1.66012 \tabularnewline
158 & 15.6 & 14.3693 & 1.2307 \tabularnewline
159 & 14.85 & 16.8206 & -1.97061 \tabularnewline
160 & 11.75 & 13.8019 & -2.05189 \tabularnewline
161 & 18.45 & 16.9633 & 1.48666 \tabularnewline
162 & 15.9 & 13.8245 & 2.07548 \tabularnewline
163 & 17.1 & 17.4057 & -0.305663 \tabularnewline
164 & 16.1 & 9.23732 & 6.86268 \tabularnewline
165 & 19.9 & 19.1044 & 0.795589 \tabularnewline
166 & 10.95 & 11.7936 & -0.843568 \tabularnewline
167 & 18.45 & 16.8176 & 1.63241 \tabularnewline
168 & 15.1 & 13.3726 & 1.72738 \tabularnewline
169 & 15 & 15.0166 & -0.0166022 \tabularnewline
170 & 11.35 & 14.724 & -3.37403 \tabularnewline
171 & 15.95 & 14.4397 & 1.51029 \tabularnewline
172 & 18.1 & 15.8891 & 2.21093 \tabularnewline
173 & 14.6 & 16.7481 & -2.1481 \tabularnewline
174 & 15.4 & 15.6787 & -0.278664 \tabularnewline
175 & 15.4 & 15.6494 & -0.249423 \tabularnewline
176 & 17.6 & 15.105 & 2.49501 \tabularnewline
177 & 13.35 & 14.6274 & -1.27745 \tabularnewline
178 & 19.1 & 16.3179 & 2.7821 \tabularnewline
179 & 15.35 & 16.4448 & -1.09478 \tabularnewline
180 & 7.6 & 11.6762 & -4.07615 \tabularnewline
181 & 13.4 & 16.2302 & -2.83025 \tabularnewline
182 & 13.9 & 15.9832 & -2.08322 \tabularnewline
183 & 19.1 & 16.2597 & 2.84028 \tabularnewline
184 & 15.25 & 15.2539 & -0.00392853 \tabularnewline
185 & 12.9 & 15.9201 & -3.02011 \tabularnewline
186 & 16.1 & 15.9632 & 0.136794 \tabularnewline
187 & 17.35 & 14.8276 & 2.52242 \tabularnewline
188 & 13.15 & 15.4384 & -2.28836 \tabularnewline
189 & 12.15 & 14.3892 & -2.23919 \tabularnewline
190 & 12.6 & 12.6853 & -0.0853264 \tabularnewline
191 & 10.35 & 12.8608 & -2.51083 \tabularnewline
192 & 15.4 & 14.5297 & 0.870298 \tabularnewline
193 & 9.6 & 12.6828 & -3.08278 \tabularnewline
194 & 18.2 & 14.862 & 3.33804 \tabularnewline
195 & 13.6 & 14.1331 & -0.53309 \tabularnewline
196 & 14.85 & 14.1437 & 0.706275 \tabularnewline
197 & 14.75 & 16.4861 & -1.73607 \tabularnewline
198 & 14.1 & 13.9173 & 0.182743 \tabularnewline
199 & 14.9 & 13.5177 & 1.38232 \tabularnewline
200 & 16.25 & 15.3038 & 0.946205 \tabularnewline
201 & 19.25 & 19.0212 & 0.228802 \tabularnewline
202 & 13.6 & 12.9325 & 0.667488 \tabularnewline
203 & 13.6 & 15.078 & -1.47799 \tabularnewline
204 & 15.65 & 15.3998 & 0.250158 \tabularnewline
205 & 12.75 & 13.3616 & -0.611555 \tabularnewline
206 & 14.6 & 13.0395 & 1.56049 \tabularnewline
207 & 9.85 & 10.9055 & -1.0555 \tabularnewline
208 & 12.65 & 12.6393 & 0.0107036 \tabularnewline
209 & 19.2 & 16.7129 & 2.48706 \tabularnewline
210 & 16.6 & 15.1355 & 1.46453 \tabularnewline
211 & 11.2 & 12.2474 & -1.04741 \tabularnewline
212 & 15.25 & 14.719 & 0.53103 \tabularnewline
213 & 11.9 & 14.3039 & -2.40391 \tabularnewline
214 & 13.2 & 13.6253 & -0.425289 \tabularnewline
215 & 16.35 & 16.904 & -0.553957 \tabularnewline
216 & 12.4 & 13.1821 & -0.782079 \tabularnewline
217 & 15.85 & 14.4446 & 1.40541 \tabularnewline
218 & 18.15 & 15.797 & 2.35295 \tabularnewline
219 & 11.15 & 12.8718 & -1.72183 \tabularnewline
220 & 15.65 & 16.1184 & -0.468369 \tabularnewline
221 & 17.75 & 14.9362 & 2.81384 \tabularnewline
222 & 7.65 & 12.0524 & -4.40244 \tabularnewline
223 & 12.35 & 13.2598 & -0.909759 \tabularnewline
224 & 15.6 & 13.4641 & 2.13586 \tabularnewline
225 & 19.3 & 16.5385 & 2.76151 \tabularnewline
226 & 15.2 & 13.0594 & 2.14056 \tabularnewline
227 & 17.1 & 14.3008 & 2.7992 \tabularnewline
228 & 15.6 & 13.5106 & 2.08941 \tabularnewline
229 & 18.4 & 15.2565 & 3.14354 \tabularnewline
230 & 19.05 & 15.6685 & 3.38149 \tabularnewline
231 & 18.55 & 15.0416 & 3.50841 \tabularnewline
232 & 19.1 & 16.9216 & 2.17842 \tabularnewline
233 & 13.1 & 13.2742 & -0.174224 \tabularnewline
234 & 12.85 & 15.2156 & -2.36556 \tabularnewline
235 & 9.5 & 11.6043 & -2.10435 \tabularnewline
236 & 4.5 & 11.023 & -6.52296 \tabularnewline
237 & 11.85 & 12.3223 & -0.47233 \tabularnewline
238 & 13.6 & 14.9068 & -1.30677 \tabularnewline
239 & 11.7 & 12.1784 & -0.478351 \tabularnewline
240 & 12.4 & 12.8973 & -0.497316 \tabularnewline
241 & 13.35 & 14.516 & -1.16604 \tabularnewline
242 & 11.4 & 13.0719 & -1.67192 \tabularnewline
243 & 14.9 & 14.0908 & 0.809157 \tabularnewline
244 & 19.9 & 18.9829 & 0.917107 \tabularnewline
245 & 11.2 & 13.7213 & -2.52125 \tabularnewline
246 & 14.6 & 15.2084 & -0.608387 \tabularnewline
247 & 17.6 & 17.1784 & 0.421594 \tabularnewline
248 & 14.05 & 13.7667 & 0.283314 \tabularnewline
249 & 16.1 & 15.5405 & 0.559468 \tabularnewline
250 & 13.35 & 13.8246 & -0.474596 \tabularnewline
251 & 11.85 & 14.0752 & -2.22522 \tabularnewline
252 & 11.95 & 13.6632 & -1.71319 \tabularnewline
253 & 14.75 & 14.589 & 0.161006 \tabularnewline
254 & 15.15 & 14.8681 & 0.281927 \tabularnewline
255 & 13.2 & 16.1585 & -2.95849 \tabularnewline
256 & 16.85 & 16.074 & 0.775999 \tabularnewline
257 & 7.85 & 12.3651 & -4.51512 \tabularnewline
258 & 7.7 & 12.9143 & -5.21427 \tabularnewline
259 & 12.6 & 15.5221 & -2.92205 \tabularnewline
260 & 7.85 & 14.4779 & -6.62791 \tabularnewline
261 & 10.95 & 12.0298 & -1.07978 \tabularnewline
262 & 12.35 & 14.6401 & -2.29014 \tabularnewline
263 & 9.95 & 13.6495 & -3.69955 \tabularnewline
264 & 14.9 & 14.06 & 0.84002 \tabularnewline
265 & 16.65 & 14.7294 & 1.92061 \tabularnewline
266 & 13.4 & 13.2902 & 0.109846 \tabularnewline
267 & 13.95 & 13.8063 & 0.143677 \tabularnewline
268 & 15.7 & 14.199 & 1.50097 \tabularnewline
269 & 16.85 & 15.0719 & 1.77807 \tabularnewline
270 & 10.95 & 12.36 & -1.40995 \tabularnewline
271 & 15.35 & 14.5478 & 0.802206 \tabularnewline
272 & 12.2 & 12.6621 & -0.462062 \tabularnewline
273 & 15.1 & 14.189 & 0.911018 \tabularnewline
274 & 17.75 & 16.0176 & 1.73244 \tabularnewline
275 & 15.2 & 14.8321 & 0.367909 \tabularnewline
276 & 14.6 & 14.4405 & 0.15949 \tabularnewline
277 & 16.65 & 15.976 & 0.674034 \tabularnewline
278 & 8.1 & 11.5798 & -3.47981 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&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]12.7277[/C][C]0.172317[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.7981[/C][C]1.40193[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.3662[/C][C]1.43378[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.5345[/C][C]-4.1345[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.1709[/C][C]-3.47093[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.6822[/C][C]-1.08221[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.2655[/C][C]2.5345[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.8211[/C][C]2.47891[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.6886[/C][C]-0.588629[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.5883[/C][C]-3.38835[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.7256[/C][C]-0.325645[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.5459[/C][C]-5.14587[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.29729[/C][C]1.30271[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.2505[/C][C]-1.25053[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]6.95454[/C][C]-0.654544[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.4449[/C][C]1.8551[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.1571[/C][C]-0.257085[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.1471[/C][C]-0.847085[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.5846[/C][C]-1.98461[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.887[/C][C]0.113[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.78113[/C][C]-3.38113[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.2055[/C][C]3.59448[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.8853[/C][C]-3.0853[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]13.1845[/C][C]0.615475[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.3504[/C][C]0.349595[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.8942[/C][C]-3.99424[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.4798[/C][C]2.62018[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.2886[/C][C]3.11143[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.5429[/C][C]-1.64291[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.0374[/C][C]0.462582[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.41147[/C][C]-1.11147[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.4815[/C][C]0.218473[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.0351[/C][C]-1.03511[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.4565[/C][C]-1.75645[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.23856[/C][C]1.56144[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]8.8844[/C][C]1.4156[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.1295[/C][C]-0.729486[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.1116[/C][C]2.58839[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.8835[/C][C]-2.5835[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.361[/C][C]-0.561029[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.53515[/C][C]-3.63515[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.9797[/C][C]0.420274[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.8196[/C][C]1.18038[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.6658[/C][C]-0.865811[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]8.29814[/C][C]4.00186[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.1928[/C][C]-1.8928[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.66428[/C][C]2.13572[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.53829[/C][C]-1.63829[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.89585[/C][C]2.80415[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]8.83801[/C][C]3.46199[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.484[/C][C]1.11605[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.37434[/C][C]-0.674342[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.4564[/C][C]0.443628[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.2657[/C][C]0.834348[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]9.77245[/C][C]3.52755[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.64735[/C][C]0.45265[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.0881[/C][C]-5.38807[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.1793[/C][C]4.12067[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.28353[/C][C]0.716472[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.4065[/C][C]2.89345[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.7301[/C][C]-3.43008[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.2078[/C][C]1.29219[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.68656[/C][C]-2.08656[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.5511[/C][C]2.34894[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.7015[/C][C]-3.50149[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.47872[/C][C]0.621279[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.1186[/C][C]-2.0186[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.1845[/C][C]-2.1845[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.8003[/C][C]2.69967[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.5411[/C][C]1.65894[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0597[/C][C]-0.759693[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.0996[/C][C]1.30038[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]10.0295[/C][C]-1.22948[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]11.033[/C][C]3.56702[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.2583[/C][C]1.34172[/C][/ROW]
[ROW][C]76[/C][C]13[/C][C]12.255[/C][C]0.745008[/C][/ROW]
[ROW][C]77[/C][C]12.6[/C][C]10.3362[/C][C]2.26378[/C][/ROW]
[ROW][C]78[/C][C]13.2[/C][C]12.2482[/C][C]0.951791[/C][/ROW]
[ROW][C]79[/C][C]9.9[/C][C]8.91572[/C][C]0.984281[/C][/ROW]
[ROW][C]80[/C][C]7.7[/C][C]9.75108[/C][C]-2.05108[/C][/ROW]
[ROW][C]81[/C][C]10.5[/C][C]10.3172[/C][C]0.182767[/C][/ROW]
[ROW][C]82[/C][C]13.4[/C][C]10.3312[/C][C]3.06884[/C][/ROW]
[ROW][C]83[/C][C]10.9[/C][C]10.2412[/C][C]0.658767[/C][/ROW]
[ROW][C]84[/C][C]4.3[/C][C]9.34603[/C][C]-5.04603[/C][/ROW]
[ROW][C]85[/C][C]10.3[/C][C]11.3097[/C][C]-1.00965[/C][/ROW]
[ROW][C]86[/C][C]11.8[/C][C]11.0726[/C][C]0.727424[/C][/ROW]
[ROW][C]87[/C][C]11.2[/C][C]8.75927[/C][C]2.44073[/C][/ROW]
[ROW][C]88[/C][C]11.4[/C][C]8.93079[/C][C]2.46921[/C][/ROW]
[ROW][C]89[/C][C]8.6[/C][C]10.0042[/C][C]-1.40423[/C][/ROW]
[ROW][C]90[/C][C]13.2[/C][C]11.4272[/C][C]1.77277[/C][/ROW]
[ROW][C]91[/C][C]12.6[/C][C]8.96454[/C][C]3.63546[/C][/ROW]
[ROW][C]92[/C][C]5.6[/C][C]10.2897[/C][C]-4.68966[/C][/ROW]
[ROW][C]93[/C][C]9.9[/C][C]11.7305[/C][C]-1.83048[/C][/ROW]
[ROW][C]94[/C][C]8.8[/C][C]10.0015[/C][C]-1.20149[/C][/ROW]
[ROW][C]95[/C][C]7.7[/C][C]9.43597[/C][C]-1.73597[/C][/ROW]
[ROW][C]96[/C][C]9[/C][C]10.4092[/C][C]-1.40923[/C][/ROW]
[ROW][C]97[/C][C]7.3[/C][C]10.9342[/C][C]-3.63421[/C][/ROW]
[ROW][C]98[/C][C]11.4[/C][C]9.31273[/C][C]2.08727[/C][/ROW]
[ROW][C]99[/C][C]13.6[/C][C]9.70958[/C][C]3.89042[/C][/ROW]
[ROW][C]100[/C][C]7.9[/C][C]10.3244[/C][C]-2.42438[/C][/ROW]
[ROW][C]101[/C][C]10.7[/C][C]8.63106[/C][C]2.06894[/C][/ROW]
[ROW][C]102[/C][C]10.3[/C][C]10.0018[/C][C]0.298246[/C][/ROW]
[ROW][C]103[/C][C]8.3[/C][C]8.8811[/C][C]-0.581104[/C][/ROW]
[ROW][C]104[/C][C]9.6[/C][C]10.7074[/C][C]-1.10737[/C][/ROW]
[ROW][C]105[/C][C]14.2[/C][C]9.95444[/C][C]4.24556[/C][/ROW]
[ROW][C]106[/C][C]8.5[/C][C]10.0103[/C][C]-1.51027[/C][/ROW]
[ROW][C]107[/C][C]13.5[/C][C]9.88096[/C][C]3.61904[/C][/ROW]
[ROW][C]108[/C][C]4.9[/C][C]9.73772[/C][C]-4.83772[/C][/ROW]
[ROW][C]109[/C][C]6.4[/C][C]8.12415[/C][C]-1.72415[/C][/ROW]
[ROW][C]110[/C][C]9.6[/C][C]10.6698[/C][C]-1.06976[/C][/ROW]
[ROW][C]111[/C][C]11.6[/C][C]10.555[/C][C]1.045[/C][/ROW]
[ROW][C]112[/C][C]11.1[/C][C]9.44227[/C][C]1.65773[/C][/ROW]
[ROW][C]113[/C][C]4.35[/C][C]10.8211[/C][C]-6.4711[/C][/ROW]
[ROW][C]114[/C][C]12.7[/C][C]12.0972[/C][C]0.60278[/C][/ROW]
[ROW][C]115[/C][C]18.1[/C][C]15.1092[/C][C]2.99076[/C][/ROW]
[ROW][C]116[/C][C]17.85[/C][C]15.3352[/C][C]2.51479[/C][/ROW]
[ROW][C]117[/C][C]16.6[/C][C]18.1454[/C][C]-1.54543[/C][/ROW]
[ROW][C]118[/C][C]12.6[/C][C]12.1933[/C][C]0.40666[/C][/ROW]
[ROW][C]119[/C][C]17.1[/C][C]18.2486[/C][C]-1.1486[/C][/ROW]
[ROW][C]120[/C][C]19.1[/C][C]17.1745[/C][C]1.92553[/C][/ROW]
[ROW][C]121[/C][C]16.1[/C][C]18.9592[/C][C]-2.85924[/C][/ROW]
[ROW][C]122[/C][C]13.35[/C][C]11.6365[/C][C]1.7135[/C][/ROW]
[ROW][C]123[/C][C]18.4[/C][C]16.5455[/C][C]1.85451[/C][/ROW]
[ROW][C]124[/C][C]14.7[/C][C]10.154[/C][C]4.54596[/C][/ROW]
[ROW][C]125[/C][C]10.6[/C][C]13.2428[/C][C]-2.64282[/C][/ROW]
[ROW][C]126[/C][C]12.6[/C][C]12.9314[/C][C]-0.331392[/C][/ROW]
[ROW][C]127[/C][C]16.2[/C][C]14.7261[/C][C]1.47388[/C][/ROW]
[ROW][C]128[/C][C]13.6[/C][C]13.597[/C][C]0.00298191[/C][/ROW]
[ROW][C]129[/C][C]18.9[/C][C]16.2921[/C][C]2.60787[/C][/ROW]
[ROW][C]130[/C][C]14.1[/C][C]12.934[/C][C]1.16596[/C][/ROW]
[ROW][C]131[/C][C]14.5[/C][C]13.4517[/C][C]1.04832[/C][/ROW]
[ROW][C]132[/C][C]16.15[/C][C]17.3809[/C][C]-1.23087[/C][/ROW]
[ROW][C]133[/C][C]14.75[/C][C]13.6752[/C][C]1.07479[/C][/ROW]
[ROW][C]134[/C][C]14.8[/C][C]13.6831[/C][C]1.11688[/C][/ROW]
[ROW][C]135[/C][C]12.45[/C][C]12.1101[/C][C]0.339903[/C][/ROW]
[ROW][C]136[/C][C]12.65[/C][C]12.6884[/C][C]-0.038389[/C][/ROW]
[ROW][C]137[/C][C]17.35[/C][C]13.9266[/C][C]3.42337[/C][/ROW]
[ROW][C]138[/C][C]8.6[/C][C]10.0961[/C][C]-1.49612[/C][/ROW]
[ROW][C]139[/C][C]18.4[/C][C]16.667[/C][C]1.73296[/C][/ROW]
[ROW][C]140[/C][C]16.1[/C][C]15.0732[/C][C]1.02685[/C][/ROW]
[ROW][C]141[/C][C]11.6[/C][C]13.4044[/C][C]-1.80442[/C][/ROW]
[ROW][C]142[/C][C]17.75[/C][C]14.7693[/C][C]2.98069[/C][/ROW]
[ROW][C]143[/C][C]15.25[/C][C]15.1022[/C][C]0.147753[/C][/ROW]
[ROW][C]144[/C][C]17.65[/C][C]14.3452[/C][C]3.30485[/C][/ROW]
[ROW][C]145[/C][C]16.35[/C][C]16.0534[/C][C]0.29661[/C][/ROW]
[ROW][C]146[/C][C]17.65[/C][C]16.7795[/C][C]0.870472[/C][/ROW]
[ROW][C]147[/C][C]13.6[/C][C]13.7733[/C][C]-0.173328[/C][/ROW]
[ROW][C]148[/C][C]14.35[/C][C]14.1918[/C][C]0.158214[/C][/ROW]
[ROW][C]149[/C][C]14.75[/C][C]14.7121[/C][C]0.0379186[/C][/ROW]
[ROW][C]150[/C][C]18.25[/C][C]16.1494[/C][C]2.1006[/C][/ROW]
[ROW][C]151[/C][C]9.9[/C][C]15.9314[/C][C]-6.0314[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.1204[/C][C]0.87962[/C][/ROW]
[ROW][C]153[/C][C]18.25[/C][C]15.564[/C][C]2.686[/C][/ROW]
[ROW][C]154[/C][C]16.85[/C][C]16.7978[/C][C]0.0522406[/C][/ROW]
[ROW][C]155[/C][C]14.6[/C][C]12.8315[/C][C]1.76849[/C][/ROW]
[ROW][C]156[/C][C]13.85[/C][C]14.4623[/C][C]-0.612262[/C][/ROW]
[ROW][C]157[/C][C]18.95[/C][C]17.2899[/C][C]1.66012[/C][/ROW]
[ROW][C]158[/C][C]15.6[/C][C]14.3693[/C][C]1.2307[/C][/ROW]
[ROW][C]159[/C][C]14.85[/C][C]16.8206[/C][C]-1.97061[/C][/ROW]
[ROW][C]160[/C][C]11.75[/C][C]13.8019[/C][C]-2.05189[/C][/ROW]
[ROW][C]161[/C][C]18.45[/C][C]16.9633[/C][C]1.48666[/C][/ROW]
[ROW][C]162[/C][C]15.9[/C][C]13.8245[/C][C]2.07548[/C][/ROW]
[ROW][C]163[/C][C]17.1[/C][C]17.4057[/C][C]-0.305663[/C][/ROW]
[ROW][C]164[/C][C]16.1[/C][C]9.23732[/C][C]6.86268[/C][/ROW]
[ROW][C]165[/C][C]19.9[/C][C]19.1044[/C][C]0.795589[/C][/ROW]
[ROW][C]166[/C][C]10.95[/C][C]11.7936[/C][C]-0.843568[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]16.8176[/C][C]1.63241[/C][/ROW]
[ROW][C]168[/C][C]15.1[/C][C]13.3726[/C][C]1.72738[/C][/ROW]
[ROW][C]169[/C][C]15[/C][C]15.0166[/C][C]-0.0166022[/C][/ROW]
[ROW][C]170[/C][C]11.35[/C][C]14.724[/C][C]-3.37403[/C][/ROW]
[ROW][C]171[/C][C]15.95[/C][C]14.4397[/C][C]1.51029[/C][/ROW]
[ROW][C]172[/C][C]18.1[/C][C]15.8891[/C][C]2.21093[/C][/ROW]
[ROW][C]173[/C][C]14.6[/C][C]16.7481[/C][C]-2.1481[/C][/ROW]
[ROW][C]174[/C][C]15.4[/C][C]15.6787[/C][C]-0.278664[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.6494[/C][C]-0.249423[/C][/ROW]
[ROW][C]176[/C][C]17.6[/C][C]15.105[/C][C]2.49501[/C][/ROW]
[ROW][C]177[/C][C]13.35[/C][C]14.6274[/C][C]-1.27745[/C][/ROW]
[ROW][C]178[/C][C]19.1[/C][C]16.3179[/C][C]2.7821[/C][/ROW]
[ROW][C]179[/C][C]15.35[/C][C]16.4448[/C][C]-1.09478[/C][/ROW]
[ROW][C]180[/C][C]7.6[/C][C]11.6762[/C][C]-4.07615[/C][/ROW]
[ROW][C]181[/C][C]13.4[/C][C]16.2302[/C][C]-2.83025[/C][/ROW]
[ROW][C]182[/C][C]13.9[/C][C]15.9832[/C][C]-2.08322[/C][/ROW]
[ROW][C]183[/C][C]19.1[/C][C]16.2597[/C][C]2.84028[/C][/ROW]
[ROW][C]184[/C][C]15.25[/C][C]15.2539[/C][C]-0.00392853[/C][/ROW]
[ROW][C]185[/C][C]12.9[/C][C]15.9201[/C][C]-3.02011[/C][/ROW]
[ROW][C]186[/C][C]16.1[/C][C]15.9632[/C][C]0.136794[/C][/ROW]
[ROW][C]187[/C][C]17.35[/C][C]14.8276[/C][C]2.52242[/C][/ROW]
[ROW][C]188[/C][C]13.15[/C][C]15.4384[/C][C]-2.28836[/C][/ROW]
[ROW][C]189[/C][C]12.15[/C][C]14.3892[/C][C]-2.23919[/C][/ROW]
[ROW][C]190[/C][C]12.6[/C][C]12.6853[/C][C]-0.0853264[/C][/ROW]
[ROW][C]191[/C][C]10.35[/C][C]12.8608[/C][C]-2.51083[/C][/ROW]
[ROW][C]192[/C][C]15.4[/C][C]14.5297[/C][C]0.870298[/C][/ROW]
[ROW][C]193[/C][C]9.6[/C][C]12.6828[/C][C]-3.08278[/C][/ROW]
[ROW][C]194[/C][C]18.2[/C][C]14.862[/C][C]3.33804[/C][/ROW]
[ROW][C]195[/C][C]13.6[/C][C]14.1331[/C][C]-0.53309[/C][/ROW]
[ROW][C]196[/C][C]14.85[/C][C]14.1437[/C][C]0.706275[/C][/ROW]
[ROW][C]197[/C][C]14.75[/C][C]16.4861[/C][C]-1.73607[/C][/ROW]
[ROW][C]198[/C][C]14.1[/C][C]13.9173[/C][C]0.182743[/C][/ROW]
[ROW][C]199[/C][C]14.9[/C][C]13.5177[/C][C]1.38232[/C][/ROW]
[ROW][C]200[/C][C]16.25[/C][C]15.3038[/C][C]0.946205[/C][/ROW]
[ROW][C]201[/C][C]19.25[/C][C]19.0212[/C][C]0.228802[/C][/ROW]
[ROW][C]202[/C][C]13.6[/C][C]12.9325[/C][C]0.667488[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.078[/C][C]-1.47799[/C][/ROW]
[ROW][C]204[/C][C]15.65[/C][C]15.3998[/C][C]0.250158[/C][/ROW]
[ROW][C]205[/C][C]12.75[/C][C]13.3616[/C][C]-0.611555[/C][/ROW]
[ROW][C]206[/C][C]14.6[/C][C]13.0395[/C][C]1.56049[/C][/ROW]
[ROW][C]207[/C][C]9.85[/C][C]10.9055[/C][C]-1.0555[/C][/ROW]
[ROW][C]208[/C][C]12.65[/C][C]12.6393[/C][C]0.0107036[/C][/ROW]
[ROW][C]209[/C][C]19.2[/C][C]16.7129[/C][C]2.48706[/C][/ROW]
[ROW][C]210[/C][C]16.6[/C][C]15.1355[/C][C]1.46453[/C][/ROW]
[ROW][C]211[/C][C]11.2[/C][C]12.2474[/C][C]-1.04741[/C][/ROW]
[ROW][C]212[/C][C]15.25[/C][C]14.719[/C][C]0.53103[/C][/ROW]
[ROW][C]213[/C][C]11.9[/C][C]14.3039[/C][C]-2.40391[/C][/ROW]
[ROW][C]214[/C][C]13.2[/C][C]13.6253[/C][C]-0.425289[/C][/ROW]
[ROW][C]215[/C][C]16.35[/C][C]16.904[/C][C]-0.553957[/C][/ROW]
[ROW][C]216[/C][C]12.4[/C][C]13.1821[/C][C]-0.782079[/C][/ROW]
[ROW][C]217[/C][C]15.85[/C][C]14.4446[/C][C]1.40541[/C][/ROW]
[ROW][C]218[/C][C]18.15[/C][C]15.797[/C][C]2.35295[/C][/ROW]
[ROW][C]219[/C][C]11.15[/C][C]12.8718[/C][C]-1.72183[/C][/ROW]
[ROW][C]220[/C][C]15.65[/C][C]16.1184[/C][C]-0.468369[/C][/ROW]
[ROW][C]221[/C][C]17.75[/C][C]14.9362[/C][C]2.81384[/C][/ROW]
[ROW][C]222[/C][C]7.65[/C][C]12.0524[/C][C]-4.40244[/C][/ROW]
[ROW][C]223[/C][C]12.35[/C][C]13.2598[/C][C]-0.909759[/C][/ROW]
[ROW][C]224[/C][C]15.6[/C][C]13.4641[/C][C]2.13586[/C][/ROW]
[ROW][C]225[/C][C]19.3[/C][C]16.5385[/C][C]2.76151[/C][/ROW]
[ROW][C]226[/C][C]15.2[/C][C]13.0594[/C][C]2.14056[/C][/ROW]
[ROW][C]227[/C][C]17.1[/C][C]14.3008[/C][C]2.7992[/C][/ROW]
[ROW][C]228[/C][C]15.6[/C][C]13.5106[/C][C]2.08941[/C][/ROW]
[ROW][C]229[/C][C]18.4[/C][C]15.2565[/C][C]3.14354[/C][/ROW]
[ROW][C]230[/C][C]19.05[/C][C]15.6685[/C][C]3.38149[/C][/ROW]
[ROW][C]231[/C][C]18.55[/C][C]15.0416[/C][C]3.50841[/C][/ROW]
[ROW][C]232[/C][C]19.1[/C][C]16.9216[/C][C]2.17842[/C][/ROW]
[ROW][C]233[/C][C]13.1[/C][C]13.2742[/C][C]-0.174224[/C][/ROW]
[ROW][C]234[/C][C]12.85[/C][C]15.2156[/C][C]-2.36556[/C][/ROW]
[ROW][C]235[/C][C]9.5[/C][C]11.6043[/C][C]-2.10435[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]11.023[/C][C]-6.52296[/C][/ROW]
[ROW][C]237[/C][C]11.85[/C][C]12.3223[/C][C]-0.47233[/C][/ROW]
[ROW][C]238[/C][C]13.6[/C][C]14.9068[/C][C]-1.30677[/C][/ROW]
[ROW][C]239[/C][C]11.7[/C][C]12.1784[/C][C]-0.478351[/C][/ROW]
[ROW][C]240[/C][C]12.4[/C][C]12.8973[/C][C]-0.497316[/C][/ROW]
[ROW][C]241[/C][C]13.35[/C][C]14.516[/C][C]-1.16604[/C][/ROW]
[ROW][C]242[/C][C]11.4[/C][C]13.0719[/C][C]-1.67192[/C][/ROW]
[ROW][C]243[/C][C]14.9[/C][C]14.0908[/C][C]0.809157[/C][/ROW]
[ROW][C]244[/C][C]19.9[/C][C]18.9829[/C][C]0.917107[/C][/ROW]
[ROW][C]245[/C][C]11.2[/C][C]13.7213[/C][C]-2.52125[/C][/ROW]
[ROW][C]246[/C][C]14.6[/C][C]15.2084[/C][C]-0.608387[/C][/ROW]
[ROW][C]247[/C][C]17.6[/C][C]17.1784[/C][C]0.421594[/C][/ROW]
[ROW][C]248[/C][C]14.05[/C][C]13.7667[/C][C]0.283314[/C][/ROW]
[ROW][C]249[/C][C]16.1[/C][C]15.5405[/C][C]0.559468[/C][/ROW]
[ROW][C]250[/C][C]13.35[/C][C]13.8246[/C][C]-0.474596[/C][/ROW]
[ROW][C]251[/C][C]11.85[/C][C]14.0752[/C][C]-2.22522[/C][/ROW]
[ROW][C]252[/C][C]11.95[/C][C]13.6632[/C][C]-1.71319[/C][/ROW]
[ROW][C]253[/C][C]14.75[/C][C]14.589[/C][C]0.161006[/C][/ROW]
[ROW][C]254[/C][C]15.15[/C][C]14.8681[/C][C]0.281927[/C][/ROW]
[ROW][C]255[/C][C]13.2[/C][C]16.1585[/C][C]-2.95849[/C][/ROW]
[ROW][C]256[/C][C]16.85[/C][C]16.074[/C][C]0.775999[/C][/ROW]
[ROW][C]257[/C][C]7.85[/C][C]12.3651[/C][C]-4.51512[/C][/ROW]
[ROW][C]258[/C][C]7.7[/C][C]12.9143[/C][C]-5.21427[/C][/ROW]
[ROW][C]259[/C][C]12.6[/C][C]15.5221[/C][C]-2.92205[/C][/ROW]
[ROW][C]260[/C][C]7.85[/C][C]14.4779[/C][C]-6.62791[/C][/ROW]
[ROW][C]261[/C][C]10.95[/C][C]12.0298[/C][C]-1.07978[/C][/ROW]
[ROW][C]262[/C][C]12.35[/C][C]14.6401[/C][C]-2.29014[/C][/ROW]
[ROW][C]263[/C][C]9.95[/C][C]13.6495[/C][C]-3.69955[/C][/ROW]
[ROW][C]264[/C][C]14.9[/C][C]14.06[/C][C]0.84002[/C][/ROW]
[ROW][C]265[/C][C]16.65[/C][C]14.7294[/C][C]1.92061[/C][/ROW]
[ROW][C]266[/C][C]13.4[/C][C]13.2902[/C][C]0.109846[/C][/ROW]
[ROW][C]267[/C][C]13.95[/C][C]13.8063[/C][C]0.143677[/C][/ROW]
[ROW][C]268[/C][C]15.7[/C][C]14.199[/C][C]1.50097[/C][/ROW]
[ROW][C]269[/C][C]16.85[/C][C]15.0719[/C][C]1.77807[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]12.36[/C][C]-1.40995[/C][/ROW]
[ROW][C]271[/C][C]15.35[/C][C]14.5478[/C][C]0.802206[/C][/ROW]
[ROW][C]272[/C][C]12.2[/C][C]12.6621[/C][C]-0.462062[/C][/ROW]
[ROW][C]273[/C][C]15.1[/C][C]14.189[/C][C]0.911018[/C][/ROW]
[ROW][C]274[/C][C]17.75[/C][C]16.0176[/C][C]1.73244[/C][/ROW]
[ROW][C]275[/C][C]15.2[/C][C]14.8321[/C][C]0.367909[/C][/ROW]
[ROW][C]276[/C][C]14.6[/C][C]14.4405[/C][C]0.15949[/C][/ROW]
[ROW][C]277[/C][C]16.65[/C][C]15.976[/C][C]0.674034[/C][/ROW]
[ROW][C]278[/C][C]8.1[/C][C]11.5798[/C][C]-3.47981[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&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
112.912.72770.172317
212.210.79811.40193
312.811.36621.43378
47.411.5345-4.1345
56.710.1709-3.47093
612.613.6822-1.08221
714.812.26552.5345
813.310.82112.47891
911.111.6886-0.588629
108.211.5883-3.38835
1111.411.7256-0.325645
126.411.5459-5.14587
1310.69.297291.30271
141213.2505-1.25053
156.36.95454-0.654544
1611.39.44491.8551
1711.912.1571-0.257085
189.310.1471-0.847085
199.611.5846-1.98461
20109.8870.113
216.49.78113-3.38113
2213.810.20553.59448
2310.813.8853-3.0853
2413.813.18450.615475
2511.711.35040.349595
2610.914.8942-3.99424
2716.113.47982.62018
2813.410.28863.11143
299.911.5429-1.64291
3011.511.03740.462582
318.39.41147-1.11147
3211.711.48150.218473
33910.0351-1.03511
349.711.4565-1.75645
3510.89.238561.56144
3610.38.88441.4156
3710.411.1295-0.729486
3812.710.11162.58839
399.311.8835-2.5835
4011.812.361-0.561029
415.99.53515-3.63515
4211.410.97970.420274
431311.81961.18038
4410.811.6658-0.865811
4512.38.298144.00186
4611.313.1928-1.8928
4711.89.664282.13572
487.99.53829-1.63829
4912.79.895852.80415
5012.38.838013.46199
5111.610.4841.11605
526.77.37434-0.674342
5310.910.45640.443628
5412.111.26570.834348
5513.39.772453.52755
5610.19.647350.45265
575.711.0881-5.38807
5814.310.17934.12067
5987.283530.716472
6013.310.40652.89345
619.312.7301-3.43008
6212.511.20781.29219
637.69.68656-2.08656
6415.913.55112.34894
659.212.7015-3.50149
669.18.478720.621279
6711.113.1186-2.0186
681315.1845-2.1845
6914.511.80032.69967
7012.210.54111.65894
7112.313.0597-0.759693
7211.410.09961.30038
738.810.0295-1.22948
7414.611.0333.56702
7512.611.25831.34172
761312.2550.745008
7712.610.33622.26378
7813.212.24820.951791
799.98.915720.984281
807.79.75108-2.05108
8110.510.31720.182767
8213.410.33123.06884
8310.910.24120.658767
844.39.34603-5.04603
8510.311.3097-1.00965
8611.811.07260.727424
8711.28.759272.44073
8811.48.930792.46921
898.610.0042-1.40423
9013.211.42721.77277
9112.68.964543.63546
925.610.2897-4.68966
939.911.7305-1.83048
948.810.0015-1.20149
957.79.43597-1.73597
96910.4092-1.40923
977.310.9342-3.63421
9811.49.312732.08727
9913.69.709583.89042
1007.910.3244-2.42438
10110.78.631062.06894
10210.310.00180.298246
1038.38.8811-0.581104
1049.610.7074-1.10737
10514.29.954444.24556
1068.510.0103-1.51027
10713.59.880963.61904
1084.99.73772-4.83772
1096.48.12415-1.72415
1109.610.6698-1.06976
11111.610.5551.045
11211.19.442271.65773
1134.3510.8211-6.4711
11412.712.09720.60278
11518.115.10922.99076
11617.8515.33522.51479
11716.618.1454-1.54543
11812.612.19330.40666
11917.118.2486-1.1486
12019.117.17451.92553
12116.118.9592-2.85924
12213.3511.63651.7135
12318.416.54551.85451
12414.710.1544.54596
12510.613.2428-2.64282
12612.612.9314-0.331392
12716.214.72611.47388
12813.613.5970.00298191
12918.916.29212.60787
13014.112.9341.16596
13114.513.45171.04832
13216.1517.3809-1.23087
13314.7513.67521.07479
13414.813.68311.11688
13512.4512.11010.339903
13612.6512.6884-0.038389
13717.3513.92663.42337
1388.610.0961-1.49612
13918.416.6671.73296
14016.115.07321.02685
14111.613.4044-1.80442
14217.7514.76932.98069
14315.2515.10220.147753
14417.6514.34523.30485
14516.3516.05340.29661
14617.6516.77950.870472
14713.613.7733-0.173328
14814.3514.19180.158214
14914.7514.71210.0379186
15018.2516.14942.1006
1519.915.9314-6.0314
1521615.12040.87962
15318.2515.5642.686
15416.8516.79780.0522406
15514.612.83151.76849
15613.8514.4623-0.612262
15718.9517.28991.66012
15815.614.36931.2307
15914.8516.8206-1.97061
16011.7513.8019-2.05189
16118.4516.96331.48666
16215.913.82452.07548
16317.117.4057-0.305663
16416.19.237326.86268
16519.919.10440.795589
16610.9511.7936-0.843568
16718.4516.81761.63241
16815.113.37261.72738
1691515.0166-0.0166022
17011.3514.724-3.37403
17115.9514.43971.51029
17218.115.88912.21093
17314.616.7481-2.1481
17415.415.6787-0.278664
17515.415.6494-0.249423
17617.615.1052.49501
17713.3514.6274-1.27745
17819.116.31792.7821
17915.3516.4448-1.09478
1807.611.6762-4.07615
18113.416.2302-2.83025
18213.915.9832-2.08322
18319.116.25972.84028
18415.2515.2539-0.00392853
18512.915.9201-3.02011
18616.115.96320.136794
18717.3514.82762.52242
18813.1515.4384-2.28836
18912.1514.3892-2.23919
19012.612.6853-0.0853264
19110.3512.8608-2.51083
19215.414.52970.870298
1939.612.6828-3.08278
19418.214.8623.33804
19513.614.1331-0.53309
19614.8514.14370.706275
19714.7516.4861-1.73607
19814.113.91730.182743
19914.913.51771.38232
20016.2515.30380.946205
20119.2519.02120.228802
20213.612.93250.667488
20313.615.078-1.47799
20415.6515.39980.250158
20512.7513.3616-0.611555
20614.613.03951.56049
2079.8510.9055-1.0555
20812.6512.63930.0107036
20919.216.71292.48706
21016.615.13551.46453
21111.212.2474-1.04741
21215.2514.7190.53103
21311.914.3039-2.40391
21413.213.6253-0.425289
21516.3516.904-0.553957
21612.413.1821-0.782079
21715.8514.44461.40541
21818.1515.7972.35295
21911.1512.8718-1.72183
22015.6516.1184-0.468369
22117.7514.93622.81384
2227.6512.0524-4.40244
22312.3513.2598-0.909759
22415.613.46412.13586
22519.316.53852.76151
22615.213.05942.14056
22717.114.30082.7992
22815.613.51062.08941
22918.415.25653.14354
23019.0515.66853.38149
23118.5515.04163.50841
23219.116.92162.17842
23313.113.2742-0.174224
23412.8515.2156-2.36556
2359.511.6043-2.10435
2364.511.023-6.52296
23711.8512.3223-0.47233
23813.614.9068-1.30677
23911.712.1784-0.478351
24012.412.8973-0.497316
24113.3514.516-1.16604
24211.413.0719-1.67192
24314.914.09080.809157
24419.918.98290.917107
24511.213.7213-2.52125
24614.615.2084-0.608387
24717.617.17840.421594
24814.0513.76670.283314
24916.115.54050.559468
25013.3513.8246-0.474596
25111.8514.0752-2.22522
25211.9513.6632-1.71319
25314.7514.5890.161006
25415.1514.86810.281927
25513.216.1585-2.95849
25616.8516.0740.775999
2577.8512.3651-4.51512
2587.712.9143-5.21427
25912.615.5221-2.92205
2607.8514.4779-6.62791
26110.9512.0298-1.07978
26212.3514.6401-2.29014
2639.9513.6495-3.69955
26414.914.060.84002
26516.6514.72941.92061
26613.413.29020.109846
26713.9513.80630.143677
26815.714.1991.50097
26916.8515.07191.77807
27010.9512.36-1.40995
27115.3514.54780.802206
27212.212.6621-0.462062
27315.114.1890.911018
27417.7516.01761.73244
27515.214.83210.367909
27614.614.44050.15949
27716.6515.9760.674034
2788.111.5798-3.47981






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8750810.2498390.124919
140.8286980.3426040.171302
150.7299550.540090.270045
160.61930.7614010.3807
170.5069620.9860760.493038
180.4042560.8085120.595744
190.5556320.8887360.444368
200.4627340.9254690.537266
210.3827660.7655320.617234
220.630220.739560.36978
230.6569120.6861750.343088
240.5850810.8298390.414919
250.5087210.9825590.491279
260.4578720.9157440.542128
270.3907280.7814560.609272
280.3896850.779370.610315
290.3429530.6859070.657047
300.290120.580240.70988
310.3079830.6159660.692017
320.2680620.5361230.731938
330.2404670.4809340.759533
340.199170.3983390.80083
350.1748220.3496450.825178
360.1447490.2894980.855251
370.1133090.2266180.886691
380.156880.3137590.84312
390.1405550.2811090.859445
400.1493880.2987760.850612
410.2115790.4231580.788421
420.1786360.3572720.821364
430.1608390.3216790.839161
440.1422520.2845040.857748
450.1326410.2652810.867359
460.1192250.238450.880775
470.1406810.2813610.859319
480.1860170.3720350.813983
490.1881030.3762060.811897
500.1734390.3468780.826561
510.148550.2971010.85145
520.1682990.3365980.831701
530.1499770.2999540.850023
540.1271010.2542020.872899
550.2229540.4459090.777046
560.1893620.3787240.810638
570.4904630.9809250.509537
580.6143040.7713910.385696
590.5754070.8491870.424593
600.5592250.881550.440775
610.6056120.7887760.394388
620.5926890.8146210.407311
630.6209550.758090.379045
640.6601910.6796180.339809
650.6734520.6530950.326548
660.6427610.7144780.357239
670.6204770.7590470.379523
680.6043490.7913020.395651
690.6427570.7144850.357243
700.613260.773480.38674
710.5789910.8420190.421009
720.5536990.8926020.446301
730.536480.9270390.46352
740.5719110.8561780.428089
750.5400380.9199230.459962
760.5101560.9796880.489844
770.486940.973880.51306
780.4715520.9431050.528448
790.4377980.8755960.562202
800.4461770.8923540.553823
810.410.820.59
820.4237580.8475150.576242
830.3885590.7771170.611441
840.598850.8023010.40115
850.5733050.8533910.426695
860.5357890.9284220.464211
870.5245680.9508650.475432
880.5139590.9720820.486041
890.5030270.9939460.496973
900.4833490.9666980.516651
910.5130690.9738610.486931
920.673430.6531410.32657
930.6631820.6736360.336818
940.6471290.7057420.352871
950.6427170.7145660.357283
960.6215370.7569260.378463
970.6819080.6361840.318092
980.6677210.6645590.332279
990.7088990.5822020.291101
1000.7259090.5481820.274091
1010.7097720.5804560.290228
1020.677720.6445610.32228
1030.6592720.6814560.340728
1040.6373090.7253820.362691
1050.702470.5950590.29753
1060.6862950.627410.313705
1070.7332510.5334980.266749
1080.8336820.3326370.166318
1090.8354030.3291930.164597
1100.8248660.3502680.175134
1110.8099450.3801110.190055
1120.786450.4271010.21355
1130.8374390.3251230.162561
1140.8649250.270150.135075
1150.9206810.1586380.0793192
1160.9302570.1394870.0697434
1170.9225040.1549910.0774957
1180.9099560.1800880.0900439
1190.8996650.200670.100335
1200.8997750.200450.100225
1210.9125010.1749980.0874992
1220.9089710.1820580.0910291
1230.905510.1889810.0944904
1240.9413960.1172080.0586041
1250.9471570.1056850.0528426
1260.9373430.1253130.0626567
1270.929720.1405590.0702795
1280.9174170.1651660.0825831
1290.9168310.1663380.0831692
1300.9056580.1886850.0943423
1310.8928280.2143440.107172
1320.8861620.2276760.113838
1330.8722690.2554620.127731
1340.8556460.2887080.144354
1350.8383670.3232660.161633
1360.8162370.3675250.183763
1370.8414590.3170830.158541
1380.8331670.3336670.166833
1390.8191680.3616630.180832
1400.799390.401220.20061
1410.8043230.3913550.195677
1420.8169390.3661230.183061
1430.7939080.4121850.206092
1440.81570.3686010.1843
1450.7912510.4174980.208749
1460.7685210.4629580.231479
1470.7424770.5150460.257523
1480.7130690.5738620.286931
1490.6829270.6341460.317073
1500.6725670.6548650.327433
1510.8628160.2743690.137184
1520.844160.3116810.15584
1530.8476570.3046870.152343
1540.8257140.3485720.174286
1550.8182640.3634710.181736
1560.7981710.4036580.201829
1570.7798940.4402110.220106
1580.7596440.4807110.240356
1590.768930.462140.23107
1600.7655430.4689140.234457
1610.7444740.5110520.255526
1620.7381150.5237710.261885
1630.7124110.5751790.287589
1640.9540910.09181890.0459094
1650.9454690.1090630.0545314
1660.9406570.1186850.0593425
1670.9324710.1350590.0675294
1680.9327390.1345210.0672606
1690.9202780.1594440.0797218
1700.9417370.1165260.0582629
1710.9343280.1313430.0656715
1720.9304080.1391850.0695924
1730.9349630.1300730.0650365
1740.9229670.1540670.0770335
1750.9092480.1815040.0907519
1760.9119750.176050.0880252
1770.900690.198620.0993098
1780.9096650.180670.0903348
1790.9034590.1930830.0965415
1800.921480.157040.0785202
1810.9354230.1291540.0645772
1820.9375360.1249270.0624636
1830.9445060.1109870.0554936
1840.9338450.1323090.0661546
1850.949060.1018810.0509405
1860.9387540.1224930.0612465
1870.9408250.118350.0591752
1880.9469860.1060280.0530139
1890.951450.0970990.0485495
1900.943920.112160.0560802
1910.9414110.1171780.0585892
1920.929610.1407810.0703903
1930.9370980.1258040.062902
1940.9422050.1155910.0577954
1950.9301870.1396250.0698126
1960.921810.156380.0781901
1970.920020.159960.0799801
1980.904590.1908190.0954096
1990.8955490.2089030.104451
2000.8768920.2462160.123108
2010.8815250.2369490.118475
2020.865920.268160.13408
2030.8622070.2755870.137793
2040.8387670.3224650.161233
2050.816290.3674190.18371
2060.8260270.3479470.173973
2070.8236720.3526560.176328
2080.8119370.3761260.188063
2090.7959590.4080820.204041
2100.7967340.4065320.203266
2110.7791010.4417980.220899
2120.7466790.5066410.253321
2130.7469110.5061780.253089
2140.7153920.5692170.284608
2150.6914330.6171340.308567
2160.6534030.6931940.346597
2170.653170.693660.34683
2180.6335270.7329450.366473
2190.6049450.790110.395055
2200.5708710.8582590.429129
2210.5826990.8346010.417301
2220.669220.661560.33078
2230.6308860.7382290.369114
2240.7364160.5271670.263584
2250.7287760.5424480.271224
2260.7863630.4272740.213637
2270.7931040.4137930.206896
2280.8271550.3456910.172845
2290.8842860.2314290.115714
2300.9169830.1660340.0830171
2310.9294970.1410060.0705031
2320.926620.146760.0733799
2330.9122320.1755370.0877684
2340.8949740.2100520.105026
2350.8725240.2549510.127476
2360.9378620.1242760.0621381
2370.9327410.1345180.0672591
2380.9141990.1716030.0858013
2390.904360.1912790.0956397
2400.8769320.2461350.123068
2410.8615970.2768070.138403
2420.8274820.3450350.172518
2430.8008190.3983610.199181
2440.7563490.4873020.243651
2450.7157120.5685760.284288
2460.6663470.6673070.333653
2470.6184320.7631360.381568
2480.7168410.5663190.283159
2490.6580740.6838510.341926
2500.6499240.7001510.350076
2510.6127870.7744270.387213
2520.5583550.8832910.441645
2530.5111440.9777120.488856
2540.4847330.9694660.515267
2550.5031380.9937240.496862
2560.4630370.9260730.536963
2570.480010.9600190.51999
2580.6747490.6505020.325251
2590.639210.721580.36079
2600.9224080.1551830.0775917
2610.8699090.2601820.130091
2620.91610.16780.0838999
2630.9936910.01261830.00630913
2640.9777310.04453760.0222688
2650.9443940.1112130.0556064

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.875081 & 0.249839 & 0.124919 \tabularnewline
14 & 0.828698 & 0.342604 & 0.171302 \tabularnewline
15 & 0.729955 & 0.54009 & 0.270045 \tabularnewline
16 & 0.6193 & 0.761401 & 0.3807 \tabularnewline
17 & 0.506962 & 0.986076 & 0.493038 \tabularnewline
18 & 0.404256 & 0.808512 & 0.595744 \tabularnewline
19 & 0.555632 & 0.888736 & 0.444368 \tabularnewline
20 & 0.462734 & 0.925469 & 0.537266 \tabularnewline
21 & 0.382766 & 0.765532 & 0.617234 \tabularnewline
22 & 0.63022 & 0.73956 & 0.36978 \tabularnewline
23 & 0.656912 & 0.686175 & 0.343088 \tabularnewline
24 & 0.585081 & 0.829839 & 0.414919 \tabularnewline
25 & 0.508721 & 0.982559 & 0.491279 \tabularnewline
26 & 0.457872 & 0.915744 & 0.542128 \tabularnewline
27 & 0.390728 & 0.781456 & 0.609272 \tabularnewline
28 & 0.389685 & 0.77937 & 0.610315 \tabularnewline
29 & 0.342953 & 0.685907 & 0.657047 \tabularnewline
30 & 0.29012 & 0.58024 & 0.70988 \tabularnewline
31 & 0.307983 & 0.615966 & 0.692017 \tabularnewline
32 & 0.268062 & 0.536123 & 0.731938 \tabularnewline
33 & 0.240467 & 0.480934 & 0.759533 \tabularnewline
34 & 0.19917 & 0.398339 & 0.80083 \tabularnewline
35 & 0.174822 & 0.349645 & 0.825178 \tabularnewline
36 & 0.144749 & 0.289498 & 0.855251 \tabularnewline
37 & 0.113309 & 0.226618 & 0.886691 \tabularnewline
38 & 0.15688 & 0.313759 & 0.84312 \tabularnewline
39 & 0.140555 & 0.281109 & 0.859445 \tabularnewline
40 & 0.149388 & 0.298776 & 0.850612 \tabularnewline
41 & 0.211579 & 0.423158 & 0.788421 \tabularnewline
42 & 0.178636 & 0.357272 & 0.821364 \tabularnewline
43 & 0.160839 & 0.321679 & 0.839161 \tabularnewline
44 & 0.142252 & 0.284504 & 0.857748 \tabularnewline
45 & 0.132641 & 0.265281 & 0.867359 \tabularnewline
46 & 0.119225 & 0.23845 & 0.880775 \tabularnewline
47 & 0.140681 & 0.281361 & 0.859319 \tabularnewline
48 & 0.186017 & 0.372035 & 0.813983 \tabularnewline
49 & 0.188103 & 0.376206 & 0.811897 \tabularnewline
50 & 0.173439 & 0.346878 & 0.826561 \tabularnewline
51 & 0.14855 & 0.297101 & 0.85145 \tabularnewline
52 & 0.168299 & 0.336598 & 0.831701 \tabularnewline
53 & 0.149977 & 0.299954 & 0.850023 \tabularnewline
54 & 0.127101 & 0.254202 & 0.872899 \tabularnewline
55 & 0.222954 & 0.445909 & 0.777046 \tabularnewline
56 & 0.189362 & 0.378724 & 0.810638 \tabularnewline
57 & 0.490463 & 0.980925 & 0.509537 \tabularnewline
58 & 0.614304 & 0.771391 & 0.385696 \tabularnewline
59 & 0.575407 & 0.849187 & 0.424593 \tabularnewline
60 & 0.559225 & 0.88155 & 0.440775 \tabularnewline
61 & 0.605612 & 0.788776 & 0.394388 \tabularnewline
62 & 0.592689 & 0.814621 & 0.407311 \tabularnewline
63 & 0.620955 & 0.75809 & 0.379045 \tabularnewline
64 & 0.660191 & 0.679618 & 0.339809 \tabularnewline
65 & 0.673452 & 0.653095 & 0.326548 \tabularnewline
66 & 0.642761 & 0.714478 & 0.357239 \tabularnewline
67 & 0.620477 & 0.759047 & 0.379523 \tabularnewline
68 & 0.604349 & 0.791302 & 0.395651 \tabularnewline
69 & 0.642757 & 0.714485 & 0.357243 \tabularnewline
70 & 0.61326 & 0.77348 & 0.38674 \tabularnewline
71 & 0.578991 & 0.842019 & 0.421009 \tabularnewline
72 & 0.553699 & 0.892602 & 0.446301 \tabularnewline
73 & 0.53648 & 0.927039 & 0.46352 \tabularnewline
74 & 0.571911 & 0.856178 & 0.428089 \tabularnewline
75 & 0.540038 & 0.919923 & 0.459962 \tabularnewline
76 & 0.510156 & 0.979688 & 0.489844 \tabularnewline
77 & 0.48694 & 0.97388 & 0.51306 \tabularnewline
78 & 0.471552 & 0.943105 & 0.528448 \tabularnewline
79 & 0.437798 & 0.875596 & 0.562202 \tabularnewline
80 & 0.446177 & 0.892354 & 0.553823 \tabularnewline
81 & 0.41 & 0.82 & 0.59 \tabularnewline
82 & 0.423758 & 0.847515 & 0.576242 \tabularnewline
83 & 0.388559 & 0.777117 & 0.611441 \tabularnewline
84 & 0.59885 & 0.802301 & 0.40115 \tabularnewline
85 & 0.573305 & 0.853391 & 0.426695 \tabularnewline
86 & 0.535789 & 0.928422 & 0.464211 \tabularnewline
87 & 0.524568 & 0.950865 & 0.475432 \tabularnewline
88 & 0.513959 & 0.972082 & 0.486041 \tabularnewline
89 & 0.503027 & 0.993946 & 0.496973 \tabularnewline
90 & 0.483349 & 0.966698 & 0.516651 \tabularnewline
91 & 0.513069 & 0.973861 & 0.486931 \tabularnewline
92 & 0.67343 & 0.653141 & 0.32657 \tabularnewline
93 & 0.663182 & 0.673636 & 0.336818 \tabularnewline
94 & 0.647129 & 0.705742 & 0.352871 \tabularnewline
95 & 0.642717 & 0.714566 & 0.357283 \tabularnewline
96 & 0.621537 & 0.756926 & 0.378463 \tabularnewline
97 & 0.681908 & 0.636184 & 0.318092 \tabularnewline
98 & 0.667721 & 0.664559 & 0.332279 \tabularnewline
99 & 0.708899 & 0.582202 & 0.291101 \tabularnewline
100 & 0.725909 & 0.548182 & 0.274091 \tabularnewline
101 & 0.709772 & 0.580456 & 0.290228 \tabularnewline
102 & 0.67772 & 0.644561 & 0.32228 \tabularnewline
103 & 0.659272 & 0.681456 & 0.340728 \tabularnewline
104 & 0.637309 & 0.725382 & 0.362691 \tabularnewline
105 & 0.70247 & 0.595059 & 0.29753 \tabularnewline
106 & 0.686295 & 0.62741 & 0.313705 \tabularnewline
107 & 0.733251 & 0.533498 & 0.266749 \tabularnewline
108 & 0.833682 & 0.332637 & 0.166318 \tabularnewline
109 & 0.835403 & 0.329193 & 0.164597 \tabularnewline
110 & 0.824866 & 0.350268 & 0.175134 \tabularnewline
111 & 0.809945 & 0.380111 & 0.190055 \tabularnewline
112 & 0.78645 & 0.427101 & 0.21355 \tabularnewline
113 & 0.837439 & 0.325123 & 0.162561 \tabularnewline
114 & 0.864925 & 0.27015 & 0.135075 \tabularnewline
115 & 0.920681 & 0.158638 & 0.0793192 \tabularnewline
116 & 0.930257 & 0.139487 & 0.0697434 \tabularnewline
117 & 0.922504 & 0.154991 & 0.0774957 \tabularnewline
118 & 0.909956 & 0.180088 & 0.0900439 \tabularnewline
119 & 0.899665 & 0.20067 & 0.100335 \tabularnewline
120 & 0.899775 & 0.20045 & 0.100225 \tabularnewline
121 & 0.912501 & 0.174998 & 0.0874992 \tabularnewline
122 & 0.908971 & 0.182058 & 0.0910291 \tabularnewline
123 & 0.90551 & 0.188981 & 0.0944904 \tabularnewline
124 & 0.941396 & 0.117208 & 0.0586041 \tabularnewline
125 & 0.947157 & 0.105685 & 0.0528426 \tabularnewline
126 & 0.937343 & 0.125313 & 0.0626567 \tabularnewline
127 & 0.92972 & 0.140559 & 0.0702795 \tabularnewline
128 & 0.917417 & 0.165166 & 0.0825831 \tabularnewline
129 & 0.916831 & 0.166338 & 0.0831692 \tabularnewline
130 & 0.905658 & 0.188685 & 0.0943423 \tabularnewline
131 & 0.892828 & 0.214344 & 0.107172 \tabularnewline
132 & 0.886162 & 0.227676 & 0.113838 \tabularnewline
133 & 0.872269 & 0.255462 & 0.127731 \tabularnewline
134 & 0.855646 & 0.288708 & 0.144354 \tabularnewline
135 & 0.838367 & 0.323266 & 0.161633 \tabularnewline
136 & 0.816237 & 0.367525 & 0.183763 \tabularnewline
137 & 0.841459 & 0.317083 & 0.158541 \tabularnewline
138 & 0.833167 & 0.333667 & 0.166833 \tabularnewline
139 & 0.819168 & 0.361663 & 0.180832 \tabularnewline
140 & 0.79939 & 0.40122 & 0.20061 \tabularnewline
141 & 0.804323 & 0.391355 & 0.195677 \tabularnewline
142 & 0.816939 & 0.366123 & 0.183061 \tabularnewline
143 & 0.793908 & 0.412185 & 0.206092 \tabularnewline
144 & 0.8157 & 0.368601 & 0.1843 \tabularnewline
145 & 0.791251 & 0.417498 & 0.208749 \tabularnewline
146 & 0.768521 & 0.462958 & 0.231479 \tabularnewline
147 & 0.742477 & 0.515046 & 0.257523 \tabularnewline
148 & 0.713069 & 0.573862 & 0.286931 \tabularnewline
149 & 0.682927 & 0.634146 & 0.317073 \tabularnewline
150 & 0.672567 & 0.654865 & 0.327433 \tabularnewline
151 & 0.862816 & 0.274369 & 0.137184 \tabularnewline
152 & 0.84416 & 0.311681 & 0.15584 \tabularnewline
153 & 0.847657 & 0.304687 & 0.152343 \tabularnewline
154 & 0.825714 & 0.348572 & 0.174286 \tabularnewline
155 & 0.818264 & 0.363471 & 0.181736 \tabularnewline
156 & 0.798171 & 0.403658 & 0.201829 \tabularnewline
157 & 0.779894 & 0.440211 & 0.220106 \tabularnewline
158 & 0.759644 & 0.480711 & 0.240356 \tabularnewline
159 & 0.76893 & 0.46214 & 0.23107 \tabularnewline
160 & 0.765543 & 0.468914 & 0.234457 \tabularnewline
161 & 0.744474 & 0.511052 & 0.255526 \tabularnewline
162 & 0.738115 & 0.523771 & 0.261885 \tabularnewline
163 & 0.712411 & 0.575179 & 0.287589 \tabularnewline
164 & 0.954091 & 0.0918189 & 0.0459094 \tabularnewline
165 & 0.945469 & 0.109063 & 0.0545314 \tabularnewline
166 & 0.940657 & 0.118685 & 0.0593425 \tabularnewline
167 & 0.932471 & 0.135059 & 0.0675294 \tabularnewline
168 & 0.932739 & 0.134521 & 0.0672606 \tabularnewline
169 & 0.920278 & 0.159444 & 0.0797218 \tabularnewline
170 & 0.941737 & 0.116526 & 0.0582629 \tabularnewline
171 & 0.934328 & 0.131343 & 0.0656715 \tabularnewline
172 & 0.930408 & 0.139185 & 0.0695924 \tabularnewline
173 & 0.934963 & 0.130073 & 0.0650365 \tabularnewline
174 & 0.922967 & 0.154067 & 0.0770335 \tabularnewline
175 & 0.909248 & 0.181504 & 0.0907519 \tabularnewline
176 & 0.911975 & 0.17605 & 0.0880252 \tabularnewline
177 & 0.90069 & 0.19862 & 0.0993098 \tabularnewline
178 & 0.909665 & 0.18067 & 0.0903348 \tabularnewline
179 & 0.903459 & 0.193083 & 0.0965415 \tabularnewline
180 & 0.92148 & 0.15704 & 0.0785202 \tabularnewline
181 & 0.935423 & 0.129154 & 0.0645772 \tabularnewline
182 & 0.937536 & 0.124927 & 0.0624636 \tabularnewline
183 & 0.944506 & 0.110987 & 0.0554936 \tabularnewline
184 & 0.933845 & 0.132309 & 0.0661546 \tabularnewline
185 & 0.94906 & 0.101881 & 0.0509405 \tabularnewline
186 & 0.938754 & 0.122493 & 0.0612465 \tabularnewline
187 & 0.940825 & 0.11835 & 0.0591752 \tabularnewline
188 & 0.946986 & 0.106028 & 0.0530139 \tabularnewline
189 & 0.95145 & 0.097099 & 0.0485495 \tabularnewline
190 & 0.94392 & 0.11216 & 0.0560802 \tabularnewline
191 & 0.941411 & 0.117178 & 0.0585892 \tabularnewline
192 & 0.92961 & 0.140781 & 0.0703903 \tabularnewline
193 & 0.937098 & 0.125804 & 0.062902 \tabularnewline
194 & 0.942205 & 0.115591 & 0.0577954 \tabularnewline
195 & 0.930187 & 0.139625 & 0.0698126 \tabularnewline
196 & 0.92181 & 0.15638 & 0.0781901 \tabularnewline
197 & 0.92002 & 0.15996 & 0.0799801 \tabularnewline
198 & 0.90459 & 0.190819 & 0.0954096 \tabularnewline
199 & 0.895549 & 0.208903 & 0.104451 \tabularnewline
200 & 0.876892 & 0.246216 & 0.123108 \tabularnewline
201 & 0.881525 & 0.236949 & 0.118475 \tabularnewline
202 & 0.86592 & 0.26816 & 0.13408 \tabularnewline
203 & 0.862207 & 0.275587 & 0.137793 \tabularnewline
204 & 0.838767 & 0.322465 & 0.161233 \tabularnewline
205 & 0.81629 & 0.367419 & 0.18371 \tabularnewline
206 & 0.826027 & 0.347947 & 0.173973 \tabularnewline
207 & 0.823672 & 0.352656 & 0.176328 \tabularnewline
208 & 0.811937 & 0.376126 & 0.188063 \tabularnewline
209 & 0.795959 & 0.408082 & 0.204041 \tabularnewline
210 & 0.796734 & 0.406532 & 0.203266 \tabularnewline
211 & 0.779101 & 0.441798 & 0.220899 \tabularnewline
212 & 0.746679 & 0.506641 & 0.253321 \tabularnewline
213 & 0.746911 & 0.506178 & 0.253089 \tabularnewline
214 & 0.715392 & 0.569217 & 0.284608 \tabularnewline
215 & 0.691433 & 0.617134 & 0.308567 \tabularnewline
216 & 0.653403 & 0.693194 & 0.346597 \tabularnewline
217 & 0.65317 & 0.69366 & 0.34683 \tabularnewline
218 & 0.633527 & 0.732945 & 0.366473 \tabularnewline
219 & 0.604945 & 0.79011 & 0.395055 \tabularnewline
220 & 0.570871 & 0.858259 & 0.429129 \tabularnewline
221 & 0.582699 & 0.834601 & 0.417301 \tabularnewline
222 & 0.66922 & 0.66156 & 0.33078 \tabularnewline
223 & 0.630886 & 0.738229 & 0.369114 \tabularnewline
224 & 0.736416 & 0.527167 & 0.263584 \tabularnewline
225 & 0.728776 & 0.542448 & 0.271224 \tabularnewline
226 & 0.786363 & 0.427274 & 0.213637 \tabularnewline
227 & 0.793104 & 0.413793 & 0.206896 \tabularnewline
228 & 0.827155 & 0.345691 & 0.172845 \tabularnewline
229 & 0.884286 & 0.231429 & 0.115714 \tabularnewline
230 & 0.916983 & 0.166034 & 0.0830171 \tabularnewline
231 & 0.929497 & 0.141006 & 0.0705031 \tabularnewline
232 & 0.92662 & 0.14676 & 0.0733799 \tabularnewline
233 & 0.912232 & 0.175537 & 0.0877684 \tabularnewline
234 & 0.894974 & 0.210052 & 0.105026 \tabularnewline
235 & 0.872524 & 0.254951 & 0.127476 \tabularnewline
236 & 0.937862 & 0.124276 & 0.0621381 \tabularnewline
237 & 0.932741 & 0.134518 & 0.0672591 \tabularnewline
238 & 0.914199 & 0.171603 & 0.0858013 \tabularnewline
239 & 0.90436 & 0.191279 & 0.0956397 \tabularnewline
240 & 0.876932 & 0.246135 & 0.123068 \tabularnewline
241 & 0.861597 & 0.276807 & 0.138403 \tabularnewline
242 & 0.827482 & 0.345035 & 0.172518 \tabularnewline
243 & 0.800819 & 0.398361 & 0.199181 \tabularnewline
244 & 0.756349 & 0.487302 & 0.243651 \tabularnewline
245 & 0.715712 & 0.568576 & 0.284288 \tabularnewline
246 & 0.666347 & 0.667307 & 0.333653 \tabularnewline
247 & 0.618432 & 0.763136 & 0.381568 \tabularnewline
248 & 0.716841 & 0.566319 & 0.283159 \tabularnewline
249 & 0.658074 & 0.683851 & 0.341926 \tabularnewline
250 & 0.649924 & 0.700151 & 0.350076 \tabularnewline
251 & 0.612787 & 0.774427 & 0.387213 \tabularnewline
252 & 0.558355 & 0.883291 & 0.441645 \tabularnewline
253 & 0.511144 & 0.977712 & 0.488856 \tabularnewline
254 & 0.484733 & 0.969466 & 0.515267 \tabularnewline
255 & 0.503138 & 0.993724 & 0.496862 \tabularnewline
256 & 0.463037 & 0.926073 & 0.536963 \tabularnewline
257 & 0.48001 & 0.960019 & 0.51999 \tabularnewline
258 & 0.674749 & 0.650502 & 0.325251 \tabularnewline
259 & 0.63921 & 0.72158 & 0.36079 \tabularnewline
260 & 0.922408 & 0.155183 & 0.0775917 \tabularnewline
261 & 0.869909 & 0.260182 & 0.130091 \tabularnewline
262 & 0.9161 & 0.1678 & 0.0838999 \tabularnewline
263 & 0.993691 & 0.0126183 & 0.00630913 \tabularnewline
264 & 0.977731 & 0.0445376 & 0.0222688 \tabularnewline
265 & 0.944394 & 0.111213 & 0.0556064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&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]13[/C][C]0.875081[/C][C]0.249839[/C][C]0.124919[/C][/ROW]
[ROW][C]14[/C][C]0.828698[/C][C]0.342604[/C][C]0.171302[/C][/ROW]
[ROW][C]15[/C][C]0.729955[/C][C]0.54009[/C][C]0.270045[/C][/ROW]
[ROW][C]16[/C][C]0.6193[/C][C]0.761401[/C][C]0.3807[/C][/ROW]
[ROW][C]17[/C][C]0.506962[/C][C]0.986076[/C][C]0.493038[/C][/ROW]
[ROW][C]18[/C][C]0.404256[/C][C]0.808512[/C][C]0.595744[/C][/ROW]
[ROW][C]19[/C][C]0.555632[/C][C]0.888736[/C][C]0.444368[/C][/ROW]
[ROW][C]20[/C][C]0.462734[/C][C]0.925469[/C][C]0.537266[/C][/ROW]
[ROW][C]21[/C][C]0.382766[/C][C]0.765532[/C][C]0.617234[/C][/ROW]
[ROW][C]22[/C][C]0.63022[/C][C]0.73956[/C][C]0.36978[/C][/ROW]
[ROW][C]23[/C][C]0.656912[/C][C]0.686175[/C][C]0.343088[/C][/ROW]
[ROW][C]24[/C][C]0.585081[/C][C]0.829839[/C][C]0.414919[/C][/ROW]
[ROW][C]25[/C][C]0.508721[/C][C]0.982559[/C][C]0.491279[/C][/ROW]
[ROW][C]26[/C][C]0.457872[/C][C]0.915744[/C][C]0.542128[/C][/ROW]
[ROW][C]27[/C][C]0.390728[/C][C]0.781456[/C][C]0.609272[/C][/ROW]
[ROW][C]28[/C][C]0.389685[/C][C]0.77937[/C][C]0.610315[/C][/ROW]
[ROW][C]29[/C][C]0.342953[/C][C]0.685907[/C][C]0.657047[/C][/ROW]
[ROW][C]30[/C][C]0.29012[/C][C]0.58024[/C][C]0.70988[/C][/ROW]
[ROW][C]31[/C][C]0.307983[/C][C]0.615966[/C][C]0.692017[/C][/ROW]
[ROW][C]32[/C][C]0.268062[/C][C]0.536123[/C][C]0.731938[/C][/ROW]
[ROW][C]33[/C][C]0.240467[/C][C]0.480934[/C][C]0.759533[/C][/ROW]
[ROW][C]34[/C][C]0.19917[/C][C]0.398339[/C][C]0.80083[/C][/ROW]
[ROW][C]35[/C][C]0.174822[/C][C]0.349645[/C][C]0.825178[/C][/ROW]
[ROW][C]36[/C][C]0.144749[/C][C]0.289498[/C][C]0.855251[/C][/ROW]
[ROW][C]37[/C][C]0.113309[/C][C]0.226618[/C][C]0.886691[/C][/ROW]
[ROW][C]38[/C][C]0.15688[/C][C]0.313759[/C][C]0.84312[/C][/ROW]
[ROW][C]39[/C][C]0.140555[/C][C]0.281109[/C][C]0.859445[/C][/ROW]
[ROW][C]40[/C][C]0.149388[/C][C]0.298776[/C][C]0.850612[/C][/ROW]
[ROW][C]41[/C][C]0.211579[/C][C]0.423158[/C][C]0.788421[/C][/ROW]
[ROW][C]42[/C][C]0.178636[/C][C]0.357272[/C][C]0.821364[/C][/ROW]
[ROW][C]43[/C][C]0.160839[/C][C]0.321679[/C][C]0.839161[/C][/ROW]
[ROW][C]44[/C][C]0.142252[/C][C]0.284504[/C][C]0.857748[/C][/ROW]
[ROW][C]45[/C][C]0.132641[/C][C]0.265281[/C][C]0.867359[/C][/ROW]
[ROW][C]46[/C][C]0.119225[/C][C]0.23845[/C][C]0.880775[/C][/ROW]
[ROW][C]47[/C][C]0.140681[/C][C]0.281361[/C][C]0.859319[/C][/ROW]
[ROW][C]48[/C][C]0.186017[/C][C]0.372035[/C][C]0.813983[/C][/ROW]
[ROW][C]49[/C][C]0.188103[/C][C]0.376206[/C][C]0.811897[/C][/ROW]
[ROW][C]50[/C][C]0.173439[/C][C]0.346878[/C][C]0.826561[/C][/ROW]
[ROW][C]51[/C][C]0.14855[/C][C]0.297101[/C][C]0.85145[/C][/ROW]
[ROW][C]52[/C][C]0.168299[/C][C]0.336598[/C][C]0.831701[/C][/ROW]
[ROW][C]53[/C][C]0.149977[/C][C]0.299954[/C][C]0.850023[/C][/ROW]
[ROW][C]54[/C][C]0.127101[/C][C]0.254202[/C][C]0.872899[/C][/ROW]
[ROW][C]55[/C][C]0.222954[/C][C]0.445909[/C][C]0.777046[/C][/ROW]
[ROW][C]56[/C][C]0.189362[/C][C]0.378724[/C][C]0.810638[/C][/ROW]
[ROW][C]57[/C][C]0.490463[/C][C]0.980925[/C][C]0.509537[/C][/ROW]
[ROW][C]58[/C][C]0.614304[/C][C]0.771391[/C][C]0.385696[/C][/ROW]
[ROW][C]59[/C][C]0.575407[/C][C]0.849187[/C][C]0.424593[/C][/ROW]
[ROW][C]60[/C][C]0.559225[/C][C]0.88155[/C][C]0.440775[/C][/ROW]
[ROW][C]61[/C][C]0.605612[/C][C]0.788776[/C][C]0.394388[/C][/ROW]
[ROW][C]62[/C][C]0.592689[/C][C]0.814621[/C][C]0.407311[/C][/ROW]
[ROW][C]63[/C][C]0.620955[/C][C]0.75809[/C][C]0.379045[/C][/ROW]
[ROW][C]64[/C][C]0.660191[/C][C]0.679618[/C][C]0.339809[/C][/ROW]
[ROW][C]65[/C][C]0.673452[/C][C]0.653095[/C][C]0.326548[/C][/ROW]
[ROW][C]66[/C][C]0.642761[/C][C]0.714478[/C][C]0.357239[/C][/ROW]
[ROW][C]67[/C][C]0.620477[/C][C]0.759047[/C][C]0.379523[/C][/ROW]
[ROW][C]68[/C][C]0.604349[/C][C]0.791302[/C][C]0.395651[/C][/ROW]
[ROW][C]69[/C][C]0.642757[/C][C]0.714485[/C][C]0.357243[/C][/ROW]
[ROW][C]70[/C][C]0.61326[/C][C]0.77348[/C][C]0.38674[/C][/ROW]
[ROW][C]71[/C][C]0.578991[/C][C]0.842019[/C][C]0.421009[/C][/ROW]
[ROW][C]72[/C][C]0.553699[/C][C]0.892602[/C][C]0.446301[/C][/ROW]
[ROW][C]73[/C][C]0.53648[/C][C]0.927039[/C][C]0.46352[/C][/ROW]
[ROW][C]74[/C][C]0.571911[/C][C]0.856178[/C][C]0.428089[/C][/ROW]
[ROW][C]75[/C][C]0.540038[/C][C]0.919923[/C][C]0.459962[/C][/ROW]
[ROW][C]76[/C][C]0.510156[/C][C]0.979688[/C][C]0.489844[/C][/ROW]
[ROW][C]77[/C][C]0.48694[/C][C]0.97388[/C][C]0.51306[/C][/ROW]
[ROW][C]78[/C][C]0.471552[/C][C]0.943105[/C][C]0.528448[/C][/ROW]
[ROW][C]79[/C][C]0.437798[/C][C]0.875596[/C][C]0.562202[/C][/ROW]
[ROW][C]80[/C][C]0.446177[/C][C]0.892354[/C][C]0.553823[/C][/ROW]
[ROW][C]81[/C][C]0.41[/C][C]0.82[/C][C]0.59[/C][/ROW]
[ROW][C]82[/C][C]0.423758[/C][C]0.847515[/C][C]0.576242[/C][/ROW]
[ROW][C]83[/C][C]0.388559[/C][C]0.777117[/C][C]0.611441[/C][/ROW]
[ROW][C]84[/C][C]0.59885[/C][C]0.802301[/C][C]0.40115[/C][/ROW]
[ROW][C]85[/C][C]0.573305[/C][C]0.853391[/C][C]0.426695[/C][/ROW]
[ROW][C]86[/C][C]0.535789[/C][C]0.928422[/C][C]0.464211[/C][/ROW]
[ROW][C]87[/C][C]0.524568[/C][C]0.950865[/C][C]0.475432[/C][/ROW]
[ROW][C]88[/C][C]0.513959[/C][C]0.972082[/C][C]0.486041[/C][/ROW]
[ROW][C]89[/C][C]0.503027[/C][C]0.993946[/C][C]0.496973[/C][/ROW]
[ROW][C]90[/C][C]0.483349[/C][C]0.966698[/C][C]0.516651[/C][/ROW]
[ROW][C]91[/C][C]0.513069[/C][C]0.973861[/C][C]0.486931[/C][/ROW]
[ROW][C]92[/C][C]0.67343[/C][C]0.653141[/C][C]0.32657[/C][/ROW]
[ROW][C]93[/C][C]0.663182[/C][C]0.673636[/C][C]0.336818[/C][/ROW]
[ROW][C]94[/C][C]0.647129[/C][C]0.705742[/C][C]0.352871[/C][/ROW]
[ROW][C]95[/C][C]0.642717[/C][C]0.714566[/C][C]0.357283[/C][/ROW]
[ROW][C]96[/C][C]0.621537[/C][C]0.756926[/C][C]0.378463[/C][/ROW]
[ROW][C]97[/C][C]0.681908[/C][C]0.636184[/C][C]0.318092[/C][/ROW]
[ROW][C]98[/C][C]0.667721[/C][C]0.664559[/C][C]0.332279[/C][/ROW]
[ROW][C]99[/C][C]0.708899[/C][C]0.582202[/C][C]0.291101[/C][/ROW]
[ROW][C]100[/C][C]0.725909[/C][C]0.548182[/C][C]0.274091[/C][/ROW]
[ROW][C]101[/C][C]0.709772[/C][C]0.580456[/C][C]0.290228[/C][/ROW]
[ROW][C]102[/C][C]0.67772[/C][C]0.644561[/C][C]0.32228[/C][/ROW]
[ROW][C]103[/C][C]0.659272[/C][C]0.681456[/C][C]0.340728[/C][/ROW]
[ROW][C]104[/C][C]0.637309[/C][C]0.725382[/C][C]0.362691[/C][/ROW]
[ROW][C]105[/C][C]0.70247[/C][C]0.595059[/C][C]0.29753[/C][/ROW]
[ROW][C]106[/C][C]0.686295[/C][C]0.62741[/C][C]0.313705[/C][/ROW]
[ROW][C]107[/C][C]0.733251[/C][C]0.533498[/C][C]0.266749[/C][/ROW]
[ROW][C]108[/C][C]0.833682[/C][C]0.332637[/C][C]0.166318[/C][/ROW]
[ROW][C]109[/C][C]0.835403[/C][C]0.329193[/C][C]0.164597[/C][/ROW]
[ROW][C]110[/C][C]0.824866[/C][C]0.350268[/C][C]0.175134[/C][/ROW]
[ROW][C]111[/C][C]0.809945[/C][C]0.380111[/C][C]0.190055[/C][/ROW]
[ROW][C]112[/C][C]0.78645[/C][C]0.427101[/C][C]0.21355[/C][/ROW]
[ROW][C]113[/C][C]0.837439[/C][C]0.325123[/C][C]0.162561[/C][/ROW]
[ROW][C]114[/C][C]0.864925[/C][C]0.27015[/C][C]0.135075[/C][/ROW]
[ROW][C]115[/C][C]0.920681[/C][C]0.158638[/C][C]0.0793192[/C][/ROW]
[ROW][C]116[/C][C]0.930257[/C][C]0.139487[/C][C]0.0697434[/C][/ROW]
[ROW][C]117[/C][C]0.922504[/C][C]0.154991[/C][C]0.0774957[/C][/ROW]
[ROW][C]118[/C][C]0.909956[/C][C]0.180088[/C][C]0.0900439[/C][/ROW]
[ROW][C]119[/C][C]0.899665[/C][C]0.20067[/C][C]0.100335[/C][/ROW]
[ROW][C]120[/C][C]0.899775[/C][C]0.20045[/C][C]0.100225[/C][/ROW]
[ROW][C]121[/C][C]0.912501[/C][C]0.174998[/C][C]0.0874992[/C][/ROW]
[ROW][C]122[/C][C]0.908971[/C][C]0.182058[/C][C]0.0910291[/C][/ROW]
[ROW][C]123[/C][C]0.90551[/C][C]0.188981[/C][C]0.0944904[/C][/ROW]
[ROW][C]124[/C][C]0.941396[/C][C]0.117208[/C][C]0.0586041[/C][/ROW]
[ROW][C]125[/C][C]0.947157[/C][C]0.105685[/C][C]0.0528426[/C][/ROW]
[ROW][C]126[/C][C]0.937343[/C][C]0.125313[/C][C]0.0626567[/C][/ROW]
[ROW][C]127[/C][C]0.92972[/C][C]0.140559[/C][C]0.0702795[/C][/ROW]
[ROW][C]128[/C][C]0.917417[/C][C]0.165166[/C][C]0.0825831[/C][/ROW]
[ROW][C]129[/C][C]0.916831[/C][C]0.166338[/C][C]0.0831692[/C][/ROW]
[ROW][C]130[/C][C]0.905658[/C][C]0.188685[/C][C]0.0943423[/C][/ROW]
[ROW][C]131[/C][C]0.892828[/C][C]0.214344[/C][C]0.107172[/C][/ROW]
[ROW][C]132[/C][C]0.886162[/C][C]0.227676[/C][C]0.113838[/C][/ROW]
[ROW][C]133[/C][C]0.872269[/C][C]0.255462[/C][C]0.127731[/C][/ROW]
[ROW][C]134[/C][C]0.855646[/C][C]0.288708[/C][C]0.144354[/C][/ROW]
[ROW][C]135[/C][C]0.838367[/C][C]0.323266[/C][C]0.161633[/C][/ROW]
[ROW][C]136[/C][C]0.816237[/C][C]0.367525[/C][C]0.183763[/C][/ROW]
[ROW][C]137[/C][C]0.841459[/C][C]0.317083[/C][C]0.158541[/C][/ROW]
[ROW][C]138[/C][C]0.833167[/C][C]0.333667[/C][C]0.166833[/C][/ROW]
[ROW][C]139[/C][C]0.819168[/C][C]0.361663[/C][C]0.180832[/C][/ROW]
[ROW][C]140[/C][C]0.79939[/C][C]0.40122[/C][C]0.20061[/C][/ROW]
[ROW][C]141[/C][C]0.804323[/C][C]0.391355[/C][C]0.195677[/C][/ROW]
[ROW][C]142[/C][C]0.816939[/C][C]0.366123[/C][C]0.183061[/C][/ROW]
[ROW][C]143[/C][C]0.793908[/C][C]0.412185[/C][C]0.206092[/C][/ROW]
[ROW][C]144[/C][C]0.8157[/C][C]0.368601[/C][C]0.1843[/C][/ROW]
[ROW][C]145[/C][C]0.791251[/C][C]0.417498[/C][C]0.208749[/C][/ROW]
[ROW][C]146[/C][C]0.768521[/C][C]0.462958[/C][C]0.231479[/C][/ROW]
[ROW][C]147[/C][C]0.742477[/C][C]0.515046[/C][C]0.257523[/C][/ROW]
[ROW][C]148[/C][C]0.713069[/C][C]0.573862[/C][C]0.286931[/C][/ROW]
[ROW][C]149[/C][C]0.682927[/C][C]0.634146[/C][C]0.317073[/C][/ROW]
[ROW][C]150[/C][C]0.672567[/C][C]0.654865[/C][C]0.327433[/C][/ROW]
[ROW][C]151[/C][C]0.862816[/C][C]0.274369[/C][C]0.137184[/C][/ROW]
[ROW][C]152[/C][C]0.84416[/C][C]0.311681[/C][C]0.15584[/C][/ROW]
[ROW][C]153[/C][C]0.847657[/C][C]0.304687[/C][C]0.152343[/C][/ROW]
[ROW][C]154[/C][C]0.825714[/C][C]0.348572[/C][C]0.174286[/C][/ROW]
[ROW][C]155[/C][C]0.818264[/C][C]0.363471[/C][C]0.181736[/C][/ROW]
[ROW][C]156[/C][C]0.798171[/C][C]0.403658[/C][C]0.201829[/C][/ROW]
[ROW][C]157[/C][C]0.779894[/C][C]0.440211[/C][C]0.220106[/C][/ROW]
[ROW][C]158[/C][C]0.759644[/C][C]0.480711[/C][C]0.240356[/C][/ROW]
[ROW][C]159[/C][C]0.76893[/C][C]0.46214[/C][C]0.23107[/C][/ROW]
[ROW][C]160[/C][C]0.765543[/C][C]0.468914[/C][C]0.234457[/C][/ROW]
[ROW][C]161[/C][C]0.744474[/C][C]0.511052[/C][C]0.255526[/C][/ROW]
[ROW][C]162[/C][C]0.738115[/C][C]0.523771[/C][C]0.261885[/C][/ROW]
[ROW][C]163[/C][C]0.712411[/C][C]0.575179[/C][C]0.287589[/C][/ROW]
[ROW][C]164[/C][C]0.954091[/C][C]0.0918189[/C][C]0.0459094[/C][/ROW]
[ROW][C]165[/C][C]0.945469[/C][C]0.109063[/C][C]0.0545314[/C][/ROW]
[ROW][C]166[/C][C]0.940657[/C][C]0.118685[/C][C]0.0593425[/C][/ROW]
[ROW][C]167[/C][C]0.932471[/C][C]0.135059[/C][C]0.0675294[/C][/ROW]
[ROW][C]168[/C][C]0.932739[/C][C]0.134521[/C][C]0.0672606[/C][/ROW]
[ROW][C]169[/C][C]0.920278[/C][C]0.159444[/C][C]0.0797218[/C][/ROW]
[ROW][C]170[/C][C]0.941737[/C][C]0.116526[/C][C]0.0582629[/C][/ROW]
[ROW][C]171[/C][C]0.934328[/C][C]0.131343[/C][C]0.0656715[/C][/ROW]
[ROW][C]172[/C][C]0.930408[/C][C]0.139185[/C][C]0.0695924[/C][/ROW]
[ROW][C]173[/C][C]0.934963[/C][C]0.130073[/C][C]0.0650365[/C][/ROW]
[ROW][C]174[/C][C]0.922967[/C][C]0.154067[/C][C]0.0770335[/C][/ROW]
[ROW][C]175[/C][C]0.909248[/C][C]0.181504[/C][C]0.0907519[/C][/ROW]
[ROW][C]176[/C][C]0.911975[/C][C]0.17605[/C][C]0.0880252[/C][/ROW]
[ROW][C]177[/C][C]0.90069[/C][C]0.19862[/C][C]0.0993098[/C][/ROW]
[ROW][C]178[/C][C]0.909665[/C][C]0.18067[/C][C]0.0903348[/C][/ROW]
[ROW][C]179[/C][C]0.903459[/C][C]0.193083[/C][C]0.0965415[/C][/ROW]
[ROW][C]180[/C][C]0.92148[/C][C]0.15704[/C][C]0.0785202[/C][/ROW]
[ROW][C]181[/C][C]0.935423[/C][C]0.129154[/C][C]0.0645772[/C][/ROW]
[ROW][C]182[/C][C]0.937536[/C][C]0.124927[/C][C]0.0624636[/C][/ROW]
[ROW][C]183[/C][C]0.944506[/C][C]0.110987[/C][C]0.0554936[/C][/ROW]
[ROW][C]184[/C][C]0.933845[/C][C]0.132309[/C][C]0.0661546[/C][/ROW]
[ROW][C]185[/C][C]0.94906[/C][C]0.101881[/C][C]0.0509405[/C][/ROW]
[ROW][C]186[/C][C]0.938754[/C][C]0.122493[/C][C]0.0612465[/C][/ROW]
[ROW][C]187[/C][C]0.940825[/C][C]0.11835[/C][C]0.0591752[/C][/ROW]
[ROW][C]188[/C][C]0.946986[/C][C]0.106028[/C][C]0.0530139[/C][/ROW]
[ROW][C]189[/C][C]0.95145[/C][C]0.097099[/C][C]0.0485495[/C][/ROW]
[ROW][C]190[/C][C]0.94392[/C][C]0.11216[/C][C]0.0560802[/C][/ROW]
[ROW][C]191[/C][C]0.941411[/C][C]0.117178[/C][C]0.0585892[/C][/ROW]
[ROW][C]192[/C][C]0.92961[/C][C]0.140781[/C][C]0.0703903[/C][/ROW]
[ROW][C]193[/C][C]0.937098[/C][C]0.125804[/C][C]0.062902[/C][/ROW]
[ROW][C]194[/C][C]0.942205[/C][C]0.115591[/C][C]0.0577954[/C][/ROW]
[ROW][C]195[/C][C]0.930187[/C][C]0.139625[/C][C]0.0698126[/C][/ROW]
[ROW][C]196[/C][C]0.92181[/C][C]0.15638[/C][C]0.0781901[/C][/ROW]
[ROW][C]197[/C][C]0.92002[/C][C]0.15996[/C][C]0.0799801[/C][/ROW]
[ROW][C]198[/C][C]0.90459[/C][C]0.190819[/C][C]0.0954096[/C][/ROW]
[ROW][C]199[/C][C]0.895549[/C][C]0.208903[/C][C]0.104451[/C][/ROW]
[ROW][C]200[/C][C]0.876892[/C][C]0.246216[/C][C]0.123108[/C][/ROW]
[ROW][C]201[/C][C]0.881525[/C][C]0.236949[/C][C]0.118475[/C][/ROW]
[ROW][C]202[/C][C]0.86592[/C][C]0.26816[/C][C]0.13408[/C][/ROW]
[ROW][C]203[/C][C]0.862207[/C][C]0.275587[/C][C]0.137793[/C][/ROW]
[ROW][C]204[/C][C]0.838767[/C][C]0.322465[/C][C]0.161233[/C][/ROW]
[ROW][C]205[/C][C]0.81629[/C][C]0.367419[/C][C]0.18371[/C][/ROW]
[ROW][C]206[/C][C]0.826027[/C][C]0.347947[/C][C]0.173973[/C][/ROW]
[ROW][C]207[/C][C]0.823672[/C][C]0.352656[/C][C]0.176328[/C][/ROW]
[ROW][C]208[/C][C]0.811937[/C][C]0.376126[/C][C]0.188063[/C][/ROW]
[ROW][C]209[/C][C]0.795959[/C][C]0.408082[/C][C]0.204041[/C][/ROW]
[ROW][C]210[/C][C]0.796734[/C][C]0.406532[/C][C]0.203266[/C][/ROW]
[ROW][C]211[/C][C]0.779101[/C][C]0.441798[/C][C]0.220899[/C][/ROW]
[ROW][C]212[/C][C]0.746679[/C][C]0.506641[/C][C]0.253321[/C][/ROW]
[ROW][C]213[/C][C]0.746911[/C][C]0.506178[/C][C]0.253089[/C][/ROW]
[ROW][C]214[/C][C]0.715392[/C][C]0.569217[/C][C]0.284608[/C][/ROW]
[ROW][C]215[/C][C]0.691433[/C][C]0.617134[/C][C]0.308567[/C][/ROW]
[ROW][C]216[/C][C]0.653403[/C][C]0.693194[/C][C]0.346597[/C][/ROW]
[ROW][C]217[/C][C]0.65317[/C][C]0.69366[/C][C]0.34683[/C][/ROW]
[ROW][C]218[/C][C]0.633527[/C][C]0.732945[/C][C]0.366473[/C][/ROW]
[ROW][C]219[/C][C]0.604945[/C][C]0.79011[/C][C]0.395055[/C][/ROW]
[ROW][C]220[/C][C]0.570871[/C][C]0.858259[/C][C]0.429129[/C][/ROW]
[ROW][C]221[/C][C]0.582699[/C][C]0.834601[/C][C]0.417301[/C][/ROW]
[ROW][C]222[/C][C]0.66922[/C][C]0.66156[/C][C]0.33078[/C][/ROW]
[ROW][C]223[/C][C]0.630886[/C][C]0.738229[/C][C]0.369114[/C][/ROW]
[ROW][C]224[/C][C]0.736416[/C][C]0.527167[/C][C]0.263584[/C][/ROW]
[ROW][C]225[/C][C]0.728776[/C][C]0.542448[/C][C]0.271224[/C][/ROW]
[ROW][C]226[/C][C]0.786363[/C][C]0.427274[/C][C]0.213637[/C][/ROW]
[ROW][C]227[/C][C]0.793104[/C][C]0.413793[/C][C]0.206896[/C][/ROW]
[ROW][C]228[/C][C]0.827155[/C][C]0.345691[/C][C]0.172845[/C][/ROW]
[ROW][C]229[/C][C]0.884286[/C][C]0.231429[/C][C]0.115714[/C][/ROW]
[ROW][C]230[/C][C]0.916983[/C][C]0.166034[/C][C]0.0830171[/C][/ROW]
[ROW][C]231[/C][C]0.929497[/C][C]0.141006[/C][C]0.0705031[/C][/ROW]
[ROW][C]232[/C][C]0.92662[/C][C]0.14676[/C][C]0.0733799[/C][/ROW]
[ROW][C]233[/C][C]0.912232[/C][C]0.175537[/C][C]0.0877684[/C][/ROW]
[ROW][C]234[/C][C]0.894974[/C][C]0.210052[/C][C]0.105026[/C][/ROW]
[ROW][C]235[/C][C]0.872524[/C][C]0.254951[/C][C]0.127476[/C][/ROW]
[ROW][C]236[/C][C]0.937862[/C][C]0.124276[/C][C]0.0621381[/C][/ROW]
[ROW][C]237[/C][C]0.932741[/C][C]0.134518[/C][C]0.0672591[/C][/ROW]
[ROW][C]238[/C][C]0.914199[/C][C]0.171603[/C][C]0.0858013[/C][/ROW]
[ROW][C]239[/C][C]0.90436[/C][C]0.191279[/C][C]0.0956397[/C][/ROW]
[ROW][C]240[/C][C]0.876932[/C][C]0.246135[/C][C]0.123068[/C][/ROW]
[ROW][C]241[/C][C]0.861597[/C][C]0.276807[/C][C]0.138403[/C][/ROW]
[ROW][C]242[/C][C]0.827482[/C][C]0.345035[/C][C]0.172518[/C][/ROW]
[ROW][C]243[/C][C]0.800819[/C][C]0.398361[/C][C]0.199181[/C][/ROW]
[ROW][C]244[/C][C]0.756349[/C][C]0.487302[/C][C]0.243651[/C][/ROW]
[ROW][C]245[/C][C]0.715712[/C][C]0.568576[/C][C]0.284288[/C][/ROW]
[ROW][C]246[/C][C]0.666347[/C][C]0.667307[/C][C]0.333653[/C][/ROW]
[ROW][C]247[/C][C]0.618432[/C][C]0.763136[/C][C]0.381568[/C][/ROW]
[ROW][C]248[/C][C]0.716841[/C][C]0.566319[/C][C]0.283159[/C][/ROW]
[ROW][C]249[/C][C]0.658074[/C][C]0.683851[/C][C]0.341926[/C][/ROW]
[ROW][C]250[/C][C]0.649924[/C][C]0.700151[/C][C]0.350076[/C][/ROW]
[ROW][C]251[/C][C]0.612787[/C][C]0.774427[/C][C]0.387213[/C][/ROW]
[ROW][C]252[/C][C]0.558355[/C][C]0.883291[/C][C]0.441645[/C][/ROW]
[ROW][C]253[/C][C]0.511144[/C][C]0.977712[/C][C]0.488856[/C][/ROW]
[ROW][C]254[/C][C]0.484733[/C][C]0.969466[/C][C]0.515267[/C][/ROW]
[ROW][C]255[/C][C]0.503138[/C][C]0.993724[/C][C]0.496862[/C][/ROW]
[ROW][C]256[/C][C]0.463037[/C][C]0.926073[/C][C]0.536963[/C][/ROW]
[ROW][C]257[/C][C]0.48001[/C][C]0.960019[/C][C]0.51999[/C][/ROW]
[ROW][C]258[/C][C]0.674749[/C][C]0.650502[/C][C]0.325251[/C][/ROW]
[ROW][C]259[/C][C]0.63921[/C][C]0.72158[/C][C]0.36079[/C][/ROW]
[ROW][C]260[/C][C]0.922408[/C][C]0.155183[/C][C]0.0775917[/C][/ROW]
[ROW][C]261[/C][C]0.869909[/C][C]0.260182[/C][C]0.130091[/C][/ROW]
[ROW][C]262[/C][C]0.9161[/C][C]0.1678[/C][C]0.0838999[/C][/ROW]
[ROW][C]263[/C][C]0.993691[/C][C]0.0126183[/C][C]0.00630913[/C][/ROW]
[ROW][C]264[/C][C]0.977731[/C][C]0.0445376[/C][C]0.0222688[/C][/ROW]
[ROW][C]265[/C][C]0.944394[/C][C]0.111213[/C][C]0.0556064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&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
130.8750810.2498390.124919
140.8286980.3426040.171302
150.7299550.540090.270045
160.61930.7614010.3807
170.5069620.9860760.493038
180.4042560.8085120.595744
190.5556320.8887360.444368
200.4627340.9254690.537266
210.3827660.7655320.617234
220.630220.739560.36978
230.6569120.6861750.343088
240.5850810.8298390.414919
250.5087210.9825590.491279
260.4578720.9157440.542128
270.3907280.7814560.609272
280.3896850.779370.610315
290.3429530.6859070.657047
300.290120.580240.70988
310.3079830.6159660.692017
320.2680620.5361230.731938
330.2404670.4809340.759533
340.199170.3983390.80083
350.1748220.3496450.825178
360.1447490.2894980.855251
370.1133090.2266180.886691
380.156880.3137590.84312
390.1405550.2811090.859445
400.1493880.2987760.850612
410.2115790.4231580.788421
420.1786360.3572720.821364
430.1608390.3216790.839161
440.1422520.2845040.857748
450.1326410.2652810.867359
460.1192250.238450.880775
470.1406810.2813610.859319
480.1860170.3720350.813983
490.1881030.3762060.811897
500.1734390.3468780.826561
510.148550.2971010.85145
520.1682990.3365980.831701
530.1499770.2999540.850023
540.1271010.2542020.872899
550.2229540.4459090.777046
560.1893620.3787240.810638
570.4904630.9809250.509537
580.6143040.7713910.385696
590.5754070.8491870.424593
600.5592250.881550.440775
610.6056120.7887760.394388
620.5926890.8146210.407311
630.6209550.758090.379045
640.6601910.6796180.339809
650.6734520.6530950.326548
660.6427610.7144780.357239
670.6204770.7590470.379523
680.6043490.7913020.395651
690.6427570.7144850.357243
700.613260.773480.38674
710.5789910.8420190.421009
720.5536990.8926020.446301
730.536480.9270390.46352
740.5719110.8561780.428089
750.5400380.9199230.459962
760.5101560.9796880.489844
770.486940.973880.51306
780.4715520.9431050.528448
790.4377980.8755960.562202
800.4461770.8923540.553823
810.410.820.59
820.4237580.8475150.576242
830.3885590.7771170.611441
840.598850.8023010.40115
850.5733050.8533910.426695
860.5357890.9284220.464211
870.5245680.9508650.475432
880.5139590.9720820.486041
890.5030270.9939460.496973
900.4833490.9666980.516651
910.5130690.9738610.486931
920.673430.6531410.32657
930.6631820.6736360.336818
940.6471290.7057420.352871
950.6427170.7145660.357283
960.6215370.7569260.378463
970.6819080.6361840.318092
980.6677210.6645590.332279
990.7088990.5822020.291101
1000.7259090.5481820.274091
1010.7097720.5804560.290228
1020.677720.6445610.32228
1030.6592720.6814560.340728
1040.6373090.7253820.362691
1050.702470.5950590.29753
1060.6862950.627410.313705
1070.7332510.5334980.266749
1080.8336820.3326370.166318
1090.8354030.3291930.164597
1100.8248660.3502680.175134
1110.8099450.3801110.190055
1120.786450.4271010.21355
1130.8374390.3251230.162561
1140.8649250.270150.135075
1150.9206810.1586380.0793192
1160.9302570.1394870.0697434
1170.9225040.1549910.0774957
1180.9099560.1800880.0900439
1190.8996650.200670.100335
1200.8997750.200450.100225
1210.9125010.1749980.0874992
1220.9089710.1820580.0910291
1230.905510.1889810.0944904
1240.9413960.1172080.0586041
1250.9471570.1056850.0528426
1260.9373430.1253130.0626567
1270.929720.1405590.0702795
1280.9174170.1651660.0825831
1290.9168310.1663380.0831692
1300.9056580.1886850.0943423
1310.8928280.2143440.107172
1320.8861620.2276760.113838
1330.8722690.2554620.127731
1340.8556460.2887080.144354
1350.8383670.3232660.161633
1360.8162370.3675250.183763
1370.8414590.3170830.158541
1380.8331670.3336670.166833
1390.8191680.3616630.180832
1400.799390.401220.20061
1410.8043230.3913550.195677
1420.8169390.3661230.183061
1430.7939080.4121850.206092
1440.81570.3686010.1843
1450.7912510.4174980.208749
1460.7685210.4629580.231479
1470.7424770.5150460.257523
1480.7130690.5738620.286931
1490.6829270.6341460.317073
1500.6725670.6548650.327433
1510.8628160.2743690.137184
1520.844160.3116810.15584
1530.8476570.3046870.152343
1540.8257140.3485720.174286
1550.8182640.3634710.181736
1560.7981710.4036580.201829
1570.7798940.4402110.220106
1580.7596440.4807110.240356
1590.768930.462140.23107
1600.7655430.4689140.234457
1610.7444740.5110520.255526
1620.7381150.5237710.261885
1630.7124110.5751790.287589
1640.9540910.09181890.0459094
1650.9454690.1090630.0545314
1660.9406570.1186850.0593425
1670.9324710.1350590.0675294
1680.9327390.1345210.0672606
1690.9202780.1594440.0797218
1700.9417370.1165260.0582629
1710.9343280.1313430.0656715
1720.9304080.1391850.0695924
1730.9349630.1300730.0650365
1740.9229670.1540670.0770335
1750.9092480.1815040.0907519
1760.9119750.176050.0880252
1770.900690.198620.0993098
1780.9096650.180670.0903348
1790.9034590.1930830.0965415
1800.921480.157040.0785202
1810.9354230.1291540.0645772
1820.9375360.1249270.0624636
1830.9445060.1109870.0554936
1840.9338450.1323090.0661546
1850.949060.1018810.0509405
1860.9387540.1224930.0612465
1870.9408250.118350.0591752
1880.9469860.1060280.0530139
1890.951450.0970990.0485495
1900.943920.112160.0560802
1910.9414110.1171780.0585892
1920.929610.1407810.0703903
1930.9370980.1258040.062902
1940.9422050.1155910.0577954
1950.9301870.1396250.0698126
1960.921810.156380.0781901
1970.920020.159960.0799801
1980.904590.1908190.0954096
1990.8955490.2089030.104451
2000.8768920.2462160.123108
2010.8815250.2369490.118475
2020.865920.268160.13408
2030.8622070.2755870.137793
2040.8387670.3224650.161233
2050.816290.3674190.18371
2060.8260270.3479470.173973
2070.8236720.3526560.176328
2080.8119370.3761260.188063
2090.7959590.4080820.204041
2100.7967340.4065320.203266
2110.7791010.4417980.220899
2120.7466790.5066410.253321
2130.7469110.5061780.253089
2140.7153920.5692170.284608
2150.6914330.6171340.308567
2160.6534030.6931940.346597
2170.653170.693660.34683
2180.6335270.7329450.366473
2190.6049450.790110.395055
2200.5708710.8582590.429129
2210.5826990.8346010.417301
2220.669220.661560.33078
2230.6308860.7382290.369114
2240.7364160.5271670.263584
2250.7287760.5424480.271224
2260.7863630.4272740.213637
2270.7931040.4137930.206896
2280.8271550.3456910.172845
2290.8842860.2314290.115714
2300.9169830.1660340.0830171
2310.9294970.1410060.0705031
2320.926620.146760.0733799
2330.9122320.1755370.0877684
2340.8949740.2100520.105026
2350.8725240.2549510.127476
2360.9378620.1242760.0621381
2370.9327410.1345180.0672591
2380.9141990.1716030.0858013
2390.904360.1912790.0956397
2400.8769320.2461350.123068
2410.8615970.2768070.138403
2420.8274820.3450350.172518
2430.8008190.3983610.199181
2440.7563490.4873020.243651
2450.7157120.5685760.284288
2460.6663470.6673070.333653
2470.6184320.7631360.381568
2480.7168410.5663190.283159
2490.6580740.6838510.341926
2500.6499240.7001510.350076
2510.6127870.7744270.387213
2520.5583550.8832910.441645
2530.5111440.9777120.488856
2540.4847330.9694660.515267
2550.5031380.9937240.496862
2560.4630370.9260730.536963
2570.480010.9600190.51999
2580.6747490.6505020.325251
2590.639210.721580.36079
2600.9224080.1551830.0775917
2610.8699090.2601820.130091
2620.91610.16780.0838999
2630.9936910.01261830.00630913
2640.9777310.04453760.0222688
2650.9443940.1112130.0556064






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00790514OK
10% type I error level40.0158103OK

\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 & 2 & 0.00790514 & OK \tabularnewline
10% type I error level & 4 & 0.0158103 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265642&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]2[/C][C]0.00790514[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]4[/C][C]0.0158103[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265642&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265642&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00790514OK
10% type I error level40.0158103OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
par3 <- 'No Linear Trend'
par2 <- 'Do not include Seasonal Dummies'
par1 <- ''
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')
}