FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationWed, 10 Dec 2014 17:58:31 +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/10/t1418234541jv8h1s60e4tkwvw.htm/, Retrieved Sun, 19 May 2024 15:27:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=265549, Retrieved Sun, 19 May 2024 15:27:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact51

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Paper stat] [2014-12-10 17:58:31] [7de4f24d5c21ad7c83693f758b02221d] [Current]
Feedback Forum

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 2011 26 50 0 13 21 12 149 68
12.2 2011 57 62 1 8 22 8 139 39
12.8 2011 37 54 0 14 22 11 148 32
7.4 2011 67 71 1 16 18 13 158 62
6.7 2011 43 54 1 14 23 11 128 33
12.6 2011 52 65 1 13 12 10 224 52
14.8 2011 52 73 0 15 20 7 159 62
13.3 2011 43 52 1 13 22 10 105 77
11.1 2011 84 84 1 20 21 15 159 76
8.2 2011 67 42 1 17 19 12 167 41
11.4 2011 49 66 1 15 22 12 165 48
6.4 2011 70 65 1 16 15 10 159 63
10.6 2011 52 78 1 12 20 10 119 30
12.0 2011 58 73 0 17 19 14 176 78
6.3 2011 68 75 0 11 18 6 54 19
11.3 2011 62 72 0 16 15 12 91 31
11.9 2011 43 66 1 16 20 14 163 66
9.3 2011 56 70 0 15 21 11 124 35
9.6 2011 56 61 1 13 21 8 137 42
10.0 2011 74 81 0 14 15 12 121 45
6.4 2011 65 71 1 19 16 15 153 21
13.8 2011 63 69 1 16 23 13 148 25
10.8 2011 58 71 0 17 21 11 221 44
13.8 2011 57 72 1 10 18 12 188 69
11.7 2011 63 68 1 15 25 7 149 54
10.9 2011 53 70 1 14 9 11 244 74
16.1 2011 57 68 1 14 30 7 148 80
13.4 2011 51 61 0 16 20 12 92 42
9.9 2011 64 67 1 15 23 12 150 61
11.5 2011 53 76 0 17 16 13 153 41
8.3 2011 29 70 0 14 16 9 94 46
11.7 2011 54 60 0 16 19 11 156 39
9.0 2011 58 72 1 15 25 12 132 34
9.7 2011 43 69 1 16 18 15 161 51
10.8 2011 51 71 1 16 23 12 105 42
10.3 2011 53 62 1 10 21 6 97 31
10.4 2011 54 70 0 8 10 5 151 39
12.7 2011 56 64 1 17 14 13 131 20
9.3 2011 61 58 1 14 22 11 166 49
11.8 2011 47 76 0 10 26 6 157 53
5.9 2011 39 52 1 14 23 12 111 31
11.4 2011 48 59 1 12 23 10 145 39
13.0 2011 50 68 1 16 24 6 162 54
10.8 2011 35 76 1 16 24 12 163 49
12.3 2011 30 65 1 16 18 11 59 34
11.3 2011 68 67 0 8 23 6 187 46
11.8 2011 49 59 1 16 15 12 109 55
7.9 2011 61 69 1 15 19 12 90 42
12.7 2011 67 76 0 8 16 8 105 50
12.3 2011 47 63 1 13 25 10 83 13
11.6 2011 56 75 1 14 23 11 116 37
6.7 2011 50 63 1 13 17 7 42 25
10.9 2011 43 60 1 16 19 12 148 30
12.1 2011 67 73 1 19 21 13 155 28
13.3 2011 62 63 1 19 18 14 125 45
10.1 2011 57 70 1 14 27 12 116 35
5.7 2011 41 75 0 15 21 6 128 28
14.3 2011 54 66 1 13 13 14 138 41
8.0 2011 45 63 0 10 8 10 49 6
13.3 2011 48 63 1 16 29 12 96 45
9.3 2011 61 64 1 15 28 11 164 73
12.5 2011 56 70 0 11 23 10 162 17
7.6 2011 41 75 0 9 21 7 99 40
15.9 2011 43 61 1 16 19 12 202 64
9.2 2011 53 60 0 12 19 7 186 37
9.1 2011 44 62 1 12 20 12 66 25
11.1 2011 66 73 0 14 18 12 183 65
13.0 2011 58 61 1 14 19 10 214 100
14.5 2011 46 66 1 13 17 10 188 28
12.2 2011 37 64 0 15 19 12 104 35
12.3 2011 51 59 0 17 25 12 177 56
11.4 2011 51 64 0 14 19 12 126 29
8.8 2011 56 60 0 11 22 8 76 43
14.6 2011 66 56 1 9 23 10 99 59
12.6 2011 37 78 0 7 14 5 139 50
NA 2011 59 53 1 13 28 10 78 3
13.0 2011 42 67 0 15 16 10 162 59
12.6 2011 38 59 1 12 24 12 108 27
13.2 2011 66 66 0 15 20 11 159 61
9.9 2011 34 68 0 14 12 9 74 28
7.7 2011 53 71 1 16 24 12 110 51
10.5 2011 49 66 0 14 22 11 96 35
13.4 2011 55 73 0 13 12 10 116 29
10.9 2011 49 72 0 16 22 12 87 48
4.3 2011 59 71 1 13 20 10 97 25
10.3 2011 40 59 0 16 10 9 127 44
11.8 2011 58 64 1 16 23 11 106 64
11.2 2011 60 66 1 16 17 12 80 32
11.4 2011 63 78 0 10 22 7 74 20
8.6 2011 56 68 0 12 24 11 91 28
13.2 2011 54 73 0 12 18 12 133 34
12.6 2011 52 62 1 12 21 6 74 31
5.6 2011 34 65 1 12 20 9 114 26
9.9 2011 69 68 1 19 20 15 140 58
8.8 2011 32 65 0 14 22 10 95 23
7.7 2011 48 60 1 13 19 11 98 21
9.0 2011 67 71 0 16 20 12 121 21
7.3 2011 58 65 1 15 26 12 126 33
11.4 2011 57 68 1 12 23 12 98 16
13.6 2011 42 64 1 8 24 11 95 20
7.9 2011 64 74 1 10 21 9 110 37
10.7 2011 58 69 1 16 21 11 70 35
10.3 2011 66 76 0 16 19 12 102 33
8.3 2011 26 68 1 10 8 12 86 27
9.6 2011 61 72 1 18 17 14 130 41
14.2 2011 52 67 1 12 20 8 96 40
8.5 2011 51 63 0 16 11 10 102 35
13.5 2011 55 59 0 10 8 9 100 28
4.9 2011 50 73 0 14 15 10 94 32
6.4 2011 60 66 0 12 18 9 52 22
9.6 2011 56 62 0 11 18 10 98 44
11.6 2011 63 69 0 15 19 12 118 27
11.1 2011 61 66 1 7 19 11 99 17
4.35 2012 52 51 1 16 23 9 48 12
12.7 2012 16 56 1 16 22 11 50 45
18.1 2012 46 67 1 16 21 12 150 37
17.85 2012 56 69 1 16 25 12 154 37
16.6 2012 52 57 0 12 30 7 109 108
12.6 2012 55 56 1 15 17 12 68 10
17.1 2012 50 55 1 14 27 12 194 68
19.1 2012 59 63 0 15 23 12 158 72
16.1 2012 60 67 1 16 23 10 159 143
13.35 2012 52 65 0 13 18 15 67 9
18.4 2012 44 47 0 10 18 10 147 55
14.7 2012 67 76 1 17 23 15 39 17
10.6 2012 52 64 1 15 19 10 100 37
12.6 2012 55 68 1 18 15 15 111 27
16.2 2012 37 64 1 16 20 9 138 37
13.6 2012 54 65 1 20 16 15 101 58
18.9 2012 72 71 1 16 24 12 131 66
14.1 2012 51 63 1 17 25 13 101 21
14.5 2012 48 60 1 16 25 12 114 19
16.15 2012 60 68 0 15 19 12 165 78
14.75 2012 50 72 1 13 19 8 114 35
14.8 2012 63 70 1 16 16 9 111 48
12.45 2012 33 61 1 16 19 15 75 27
12.65 2012 67 61 1 16 19 12 82 43
17.35 2012 46 62 1 17 23 12 121 30
8.6 2012 54 71 1 20 21 15 32 25
18.4 2012 59 71 0 14 22 11 150 69
16.1 2012 61 51 1 17 19 12 117 72
11.6 2012 33 56 1 6 20 6 71 23
17.75 2012 47 70 1 16 20 14 165 13
15.25 2012 69 73 1 15 3 12 154 61
17.65 2012 52 76 1 16 23 12 126 43
16.35 2012 55 68 0 16 23 12 149 51
17.65 2012 41 48 0 14 20 11 145 67
13.6 2012 73 52 1 16 15 12 120 36
14.35 2012 52 60 0 16 16 12 109 44
14.75 2012 50 59 0 16 7 12 132 45
18.25 2012 51 57 1 14 24 12 172 34
9.9 2012 60 79 0 14 17 8 169 36
16 2012 56 60 1 16 24 8 114 72
18.25 2012 56 60 1 16 24 12 156 39
16.85 2012 29 59 0 15 19 12 172 43
14.6 2012 66 62 1 16 25 11 68 25
13.85 2012 66 59 1 16 20 10 89 56
18.95 2012 73 61 1 18 28 11 167 80
15.6 2012 55 71 0 15 23 12 113 40
14.85 2012 64 57 0 16 27 13 115 73
11.75 2012 40 66 0 16 18 12 78 34
18.45 2012 46 63 0 16 28 12 118 72
15.9 2012 58 69 1 17 21 10 87 42
17.1 2012 43 58 0 14 19 10 173 61
16.1 2012 61 59 1 18 23 11 2 23
19.9 2012 51 48 0 9 27 8 162 74
10.95 2012 50 66 1 15 22 12 49 16
18.45 2012 52 73 0 14 28 9 122 66
15.1 2012 54 67 1 15 25 12 96 9
15 2012 66 61 0 13 21 9 100 41
11.35 2012 61 68 0 16 22 11 82 57
15.95 2012 80 75 1 20 28 15 100 48
18.1 2012 51 62 0 14 20 8 115 51
14.6 2012 56 69 1 12 29 8 141 53
15.4 2012 56 58 1 15 25 11 165 29
15.4 2012 56 60 1 15 25 11 165 29
17.6 2012 53 74 1 15 20 11 110 55
13.35 2012 47 55 1 16 20 13 118 54
19.1 2012 25 62 0 11 16 7 158 43
15.35 2012 47 63 1 16 20 12 146 51
7.6 2012 46 69 0 7 20 8 49 20
13.4 2012 50 58 0 11 23 8 90 79
13.9 2012 39 58 0 9 18 4 121 39
19.1 2012 51 68 1 15 25 11 155 61
15.25 2012 58 72 0 16 18 10 104 55
12.9 2012 35 62 1 14 19 7 147 30
16.1 2012 58 62 0 15 25 12 110 55
17.35 2012 60 65 0 13 25 11 108 22
13.15 2012 62 69 0 13 25 9 113 37
12.15 2012 63 66 0 12 24 10 115 2
12.6 2012 53 72 1 16 19 8 61 38
10.35 2012 46 62 1 14 26 8 60 27
15.4 2012 67 75 1 16 10 11 109 56
9.6 2012 59 58 1 14 17 12 68 25
18.2 2012 64 66 0 15 13 10 111 39
13.6 2012 38 55 0 10 17 10 77 33
14.85 2012 50 47 1 16 30 12 73 43
14.75 2012 48 72 0 14 25 8 151 57
14.1 2012 48 62 0 16 4 11 89 43
14.9 2012 47 64 0 12 16 8 78 23
16.25 2012 66 64 0 16 21 10 110 44
19.25 2012 47 19 1 16 23 14 220 54
13.6 2012 63 50 1 15 22 9 65 28
13.6 2012 58 68 0 14 17 9 141 36
15.65 2012 44 70 0 16 20 10 117 39
12.75 2012 51 79 1 11 20 13 122 16
14.6 2012 43 69 0 15 22 12 63 23
9.85 2012 55 71 1 18 16 13 44 40
12.65 2012 38 48 1 13 23 8 52 24
19.2 2012 45 73 0 7 0 3 131 78
16.6 2012 50 74 1 7 18 8 101 57
11.2 2012 54 66 1 17 25 12 42 37
15.25 2012 57 71 1 18 23 11 152 27
11.9 2012 60 74 0 15 12 9 107 61
13.2 2012 55 78 0 8 18 12 77 27
16.35 2012 56 75 0 13 24 12 154 69
12.4 2012 49 53 1 13 11 12 103 34
15.85 2012 37 60 1 15 18 10 96 44
18.15 2012 59 70 1 18 23 13 175 34
11.15 2012 46 69 1 16 24 9 57 39
15.65 2012 51 65 0 14 29 12 112 51
17.75 2012 58 78 0 15 18 11 143 34
7.65 2012 64 78 0 19 15 14 49 31
12.35 2012 53 59 1 16 29 11 110 13
15.6 2012 48 72 1 12 16 9 131 12
19.3 2012 51 70 0 16 19 12 167 51
15.2 2012 47 63 0 11 22 8 56 24
17.1 2012 59 63 0 16 16 15 137 19
15.6 2012 62 71 1 15 23 12 86 30
18.4 2012 62 74 1 19 23 14 121 81
19.05 2012 51 67 0 15 19 12 149 42
18.55 2012 64 66 0 14 4 9 168 22
19.1 2012 52 62 0 14 20 9 140 85
13.1 2012 67 80 1 17 24 13 88 27
12.85 2012 50 73 1 16 20 13 168 25
9.5 2012 54 67 1 20 4 15 94 22
4.5 2012 58 61 1 16 24 11 51 19
11.85 2012 56 73 0 9 22 7 48 14
13.6 2012 63 74 1 13 16 10 145 45
11.7 2012 31 32 1 15 3 11 66 45
12.4 2012 65 69 1 19 15 14 85 28
13.35 2012 71 69 0 16 24 14 109 51
11.4 2012 50 84 0 17 17 13 63 41
14.9 2012 57 64 1 16 20 12 102 31
19.9 2012 47 58 0 9 27 8 162 74
11.2 2012 47 59 1 11 26 13 86 19
14.6 2012 57 78 1 14 23 9 114 51
17.6 2012 43 57 0 19 17 12 164 73
14.05 2012 41 60 1 13 20 13 119 24
16.1 2012 63 68 0 14 22 11 126 61
13.35 2012 63 68 1 15 19 11 132 23
11.85 2012 56 73 1 15 24 13 142 14
11.95 2012 51 69 0 14 19 12 83 54
14.75 2012 50 67 1 16 23 12 94 51
15.15 2012 22 60 0 17 15 10 81 62
13.2 2012 41 65 1 12 27 9 166 36
16.85 2012 59 66 0 15 26 10 110 59
7.85 2012 56 74 1 17 22 13 64 24
7.7 2012 66 81 0 15 22 13 93 26
12.6 2012 53 72 0 10 18 9 104 54
7.85 2012 42 55 1 16 15 11 105 39
10.95 2012 52 49 1 15 22 12 49 16
12.35 2012 54 74 0 11 27 8 88 36
9.95 2012 44 53 1 16 10 12 95 31
14.9 2012 62 64 1 16 20 12 102 31
16.65 2012 53 65 0 16 17 12 99 42
13.4 2012 50 57 1 14 23 9 63 39
13.95 2012 36 51 0 14 19 12 76 25
15.7 2012 76 80 0 16 13 12 109 31
16.85 2012 66 67 1 16 27 11 117 38
10.95 2012 62 70 1 18 23 12 57 31
15.35 2012 59 74 0 14 16 6 120 17
12.2 2012 47 75 1 20 25 7 73 22
15.1 2012 55 70 0 15 2 10 91 55
17.75 2012 58 69 0 16 26 12 108 62
15.2 2012 60 65 1 16 20 10 105 51
14.6 2012 44 55 0 16 23 12 117 30
16.65 2012 57 71 0 12 22 9 119 49
8.1 2012 45 65 1 8 24 3 31 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data X' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = -8694.8 + 4.32691Year[t] -0.00459758AMS.I[t] -0.0132811AMS.E[t] -0.622177gender[t] -0.110002CONFSTATTOT[t] + 0.0497582NUMERACYTOT[t] + 0.088336CONFSOFTTOT[t] + 0.0291354LFM[t] + 0.0361037CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  -8694.8 +  4.32691Year[t] -0.00459758AMS.I[t] -0.0132811AMS.E[t] -0.622177gender[t] -0.110002CONFSTATTOT[t] +  0.0497582NUMERACYTOT[t] +  0.088336CONFSOFTTOT[t] +  0.0291354LFM[t] +  0.0361037CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  -8694.8 +  4.32691Year[t] -0.00459758AMS.I[t] -0.0132811AMS.E[t] -0.622177gender[t] -0.110002CONFSTATTOT[t] +  0.0497582NUMERACYTOT[t] +  0.088336CONFSOFTTOT[t] +  0.0291354LFM[t] +  0.0361037CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&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] = -8694.8 + 4.32691Year[t] -0.00459758AMS.I[t] -0.0132811AMS.E[t] -0.622177gender[t] -0.110002CONFSTATTOT[t] + 0.0497582NUMERACYTOT[t] + 0.088336CONFSOFTTOT[t] + 0.0291354LFM[t] + 0.0361037CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-8694.8608.333-14.297.83546e-353.91773e-35
Year4.326910.30237814.316.8352e-353.4176e-35
AMS.I-0.004597580.0151545-0.30340.7618350.380917
AMS.E-0.01328110.0189466-0.7010.4839260.241963
gender-0.6221770.305041-2.040.0423660.021183
CONFSTATTOT-0.1100020.0690771-1.5920.1124630.0562317
NUMERACYTOT0.04975820.02807691.7720.07749580.0387479
CONFSOFTTOT0.0883360.08053941.0970.2737110.136856
LFM0.02913540.004073257.1538.1136e-124.0568e-12
CH0.03610370.008550274.2233.31232e-051.65616e-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) & -8694.8 & 608.333 & -14.29 & 7.83546e-35 & 3.91773e-35 \tabularnewline
Year & 4.32691 & 0.302378 & 14.31 & 6.8352e-35 & 3.4176e-35 \tabularnewline
AMS.I & -0.00459758 & 0.0151545 & -0.3034 & 0.761835 & 0.380917 \tabularnewline
AMS.E & -0.0132811 & 0.0189466 & -0.701 & 0.483926 & 0.241963 \tabularnewline
gender & -0.622177 & 0.305041 & -2.04 & 0.042366 & 0.021183 \tabularnewline
CONFSTATTOT & -0.110002 & 0.0690771 & -1.592 & 0.112463 & 0.0562317 \tabularnewline
NUMERACYTOT & 0.0497582 & 0.0280769 & 1.772 & 0.0774958 & 0.0387479 \tabularnewline
CONFSOFTTOT & 0.088336 & 0.0805394 & 1.097 & 0.273711 & 0.136856 \tabularnewline
LFM & 0.0291354 & 0.00407325 & 7.153 & 8.1136e-12 & 4.0568e-12 \tabularnewline
CH & 0.0361037 & 0.00855027 & 4.223 & 3.31232e-05 & 1.65616e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&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]-8694.8[/C][C]608.333[/C][C]-14.29[/C][C]7.83546e-35[/C][C]3.91773e-35[/C][/ROW]
[ROW][C]Year[/C][C]4.32691[/C][C]0.302378[/C][C]14.31[/C][C]6.8352e-35[/C][C]3.4176e-35[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00459758[/C][C]0.0151545[/C][C]-0.3034[/C][C]0.761835[/C][C]0.380917[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0132811[/C][C]0.0189466[/C][C]-0.701[/C][C]0.483926[/C][C]0.241963[/C][/ROW]
[ROW][C]gender[/C][C]-0.622177[/C][C]0.305041[/C][C]-2.04[/C][C]0.042366[/C][C]0.021183[/C][/ROW]
[ROW][C]CONFSTATTOT[/C][C]-0.110002[/C][C]0.0690771[/C][C]-1.592[/C][C]0.112463[/C][C]0.0562317[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0497582[/C][C]0.0280769[/C][C]1.772[/C][C]0.0774958[/C][C]0.0387479[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]0.088336[/C][C]0.0805394[/C][C]1.097[/C][C]0.273711[/C][C]0.136856[/C][/ROW]
[ROW][C]LFM[/C][C]0.0291354[/C][C]0.00407325[/C][C]7.153[/C][C]8.1136e-12[/C][C]4.0568e-12[/C][/ROW]
[ROW][C]CH[/C][C]0.0361037[/C][C]0.00855027[/C][C]4.223[/C][C]3.31232e-05[/C][C]1.65616e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&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)-8694.8608.333-14.297.83546e-353.91773e-35
Year4.326910.30237814.316.8352e-353.4176e-35
AMS.I-0.004597580.0151545-0.30340.7618350.380917
AMS.E-0.01328110.0189466-0.7010.4839260.241963
gender-0.6221770.305041-2.040.0423660.021183
CONFSTATTOT-0.1100020.0690771-1.5920.1124630.0562317
NUMERACYTOT0.04975820.02807691.7720.07749580.0387479
CONFSOFTTOT0.0883360.08053941.0970.2737110.136856
LFM0.02913540.004073257.1538.1136e-124.0568e-12
CH0.03610370.008550274.2233.31232e-051.65616e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.738441
R-squared0.545294
Adjusted R-squared0.530025
F-TEST (value)35.7103
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.32699
Sum Squared Residuals1451.19

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.738441 \tabularnewline
R-squared & 0.545294 \tabularnewline
Adjusted R-squared & 0.530025 \tabularnewline
F-TEST (value) & 35.7103 \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 & 2.32699 \tabularnewline
Sum Squared Residuals & 1451.19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.738441[/C][/ROW]
[ROW][C]R-squared[/C][C]0.545294[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.530025[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]35.7103[/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]2.32699[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1451.19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.738441
R-squared0.545294
Adjusted R-squared0.530025
F-TEST (value)35.7103
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.32699
Sum Squared Residuals1451.19






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.2988-0.39879
212.211.28280.917223
312.811.71761.08235
47.411.8639-4.46386
56.710.571-3.87104
612.613.3409-0.740863
714.812.23712.56292
813.311.4881.81205
911.112.0336-0.933576
108.211.6045-3.40448
1111.411.9322-0.53222
126.411.5807-5.18071
1310.69.822770.777226
141213.631-1.63104
156.37.77743-1.47743
1611.39.186852.11315
1711.912.5186-0.618554
189.310.6671-1.36709
199.610.7509-1.15093
201010.6117-0.611664
216.49.99428-3.59428
2213.810.53043.26958
2310.813.5757-2.77568
2413.813.5950.204981
2511.711.29930.400659
2610.914.4759-3.57591
2716.112.59533.50472
2813.410.05863.34142
299.911.932-2.03205
3011.511.37060.129372
318.39.99885-1.69885
3211.711.67630.0236684
33910.4935-1.49351
349.711.8677-2.1677
3510.89.831630.968372
3610.39.342220.957784
3710.411.3-0.900016
3812.79.395363.30464
399.312.0702-2.7702
4011.812.5972-0.797239
415.910.1368-4.23682
4211.411.32520.0747653
431311.48981.51023
4410.811.8311-1.03112
4512.38.041684.25832
4611.313.3123-2.01229
4711.810.1881.61198
487.99.28615-1.38615
4912.710.7811.91897
5012.38.521133.77887
5111.610.02721.57285
526.77.08296-0.382956
5310.910.6350.264952
5412.110.34161.75836
5513.310.17623.1238
5610.110.3041-0.204123
575.710.0918-4.39179
5814.310.81873.4813
5987.393290.606712
6013.310.09633.20369
619.312.9873-3.68728
6212.511.57560.924438
637.610.4285-2.82845
6415.913.42262.4774
659.212.5694-3.36945
669.18.524030.575971
6711.113.4324-2.33244
681315.0463-2.04633
6914.511.68862.81141
7012.210.24021.95975
7112.313.2059-0.905895
7211.410.71020.689761
738.89.91499-1.11499
7414.610.99423.60583
7512.611.62850.971525
76NANA0.592189
771310.48642.51361
7812.611.98290.61708
7913.211.87081.32919
809.912.5428-2.6428
817.77.296370.40363
8210.56.965993.53401
8313.412.59210.807856
8410.915.5521-4.65206
854.34.46507-0.165074
8610.39.127491.17251
8711.89.068682.73132
8811.28.576762.62324
8911.412.7587-1.35874
908.66.531632.06837
9113.29.05674.1433
9212.616.6998-4.09976
935.66.87184-1.27184
949.910.7371-0.837094
958.810.172-1.37202
967.78.63896-0.938959
97912.1253-3.12532
987.35.041252.25875
9911.47.521773.87823
10013.615.6927-2.09266
1017.95.565692.33431
10210.710.10710.592937
10310.310.8049-0.504919
1048.38.82277-0.522773
1059.64.883124.71688
10614.215.1462-0.946152
1078.54.592293.90771
10813.517.9956-4.49558
1094.96.63879-1.73879
1106.47.34315-0.943151
1119.68.173371.42663
11211.69.97731.6227
11311.118.1607-7.06072
1144.354.53644-0.186436
11512.79.865712.83429
11618.115.75872.34126
11717.8519.0581-1.20807
11816.615.91750.682513
11912.613.8264-1.22642
12017.115.58751.51253
12119.122.2134-3.11339
12216.115.65350.446544
12313.3512.00921.34078
12418.415.0483.35195
12514.717.755-3.05501
12610.611.4602-0.860186
12712.611.08251.51746
12816.216.7622-0.562241
12913.610.43583.16425
13018.918.26790.632083
13114.113.44980.650228
13214.516.088-1.588
13316.1515.3370.813026
13414.7513.84480.905235
13514.815.3745-0.574461
13612.4513.1847-0.734742
13712.659.523983.12602
13817.3519.8796-2.52958
1398.67.311731.28827
14018.417.80190.598117
14116.117.6847-1.58466
14211.68.768722.83128
14317.7517.7777-0.0276608
14415.2512.33552.91452
14517.6517.7091-0.0590572
14616.3515.88260.467445
14717.6518.1821-0.532075
14813.614.0126-0.412649
14914.3514.6435-0.293521
15014.7512.77751.97252
15118.2524.1992-5.94924
1529.99.223380.676617
1531613.4592.54101
15418.2518.3404-0.0903793
15516.8514.77852.07149
15614.614.7123-0.112283
15713.8512.2091.64101
15818.9518.38320.5668
15915.617.3548-1.75482
16014.8516.6734-1.82341
16111.759.920611.82939
16218.4515.79232.65771
16315.916.3016-0.401625
16417.111.27675.82332
16516.114.71791.38209
16619.920.6695-0.769503
16710.958.815132.13487
16818.4516.30372.14625
16915.114.72830.371741
1701518.1579-3.15793
17111.359.516821.83318
17215.9513.08392.86609
17318.119.4933-1.39334
17414.614.9082-0.308163
17515.415.6816-0.281601
17615.412.39693.00309
17717.619.3905-1.79049
17813.3510.61012.73992
17919.119.4034-0.303386
18015.3520.6418-5.29179
1817.610.2534-2.65343
18213.414.6809-1.28093
18313.911.26232.6377
18419.118.60.500003
18515.2517.0714-1.82136
18612.912.49260.407398
18716.113.27552.82446
18817.3519.1738-1.82378
18913.1514.9522-1.80225
19012.1511.70730.442691
19112.614.7143-2.11434
19210.358.868651.48135
19315.418.3241-2.92409
1949.65.68963.9104
19518.218.697-0.497042
19613.612.6840.916042
19714.8516.7292-1.87918
19814.7514.10020.649769
19914.112.35781.7422
20014.913.39641.50359
20116.2515.8280.421964
20219.2518.15661.09336
20313.615.2771-1.67707
20413.612.69150.908456
20515.6516.998-1.34796
20612.7511.14461.60536
20714.616.5607-1.9607
2089.859.506390.343612
20912.659.339543.31046
21019.217.53621.66382
21116.617.5846-0.984613
21211.210.60040.599578
21315.2518.0914-2.84138
21411.912.6432-0.743228
21513.214.3368-1.1368
21616.3517.7426-1.3926
21712.410.41351.98648
21815.8513.4542.39598
21918.1519.486-1.33602
22011.1511.4078-0.257832
22115.6513.14682.50325
22217.7522.1479-4.39785
2237.658.9176-1.2676
22412.3510.41021.93985
22515.613.02632.57371
22619.317.07482.22524
22715.212.96882.23117
22817.114.73112.36885
22915.612.9892.611
23018.415.37683.02324
23119.0515.41043.6396
23218.5516.72361.82644
23319.118.95670.14332
23413.115.5474-2.4474
23512.8515.3849-2.5349
2369.516.8169-7.31689
2374.54.98811-0.488113
23811.8513.3923-1.54228
23913.614.667-1.06698
24011.711.7812-0.0811741
24112.414.4332-2.03323
24213.3514.9826-1.63265
24311.410.09011.3099
24414.913.40351.49651
24519.922.44-2.53996
24611.211.18010.0198709
24714.614.21310.386921
24817.617.9277-0.327701
24914.0514.0951-0.045107
25016.116.8165-0.716528
25113.3515.9242-2.57419
25211.8514.5205-2.67051
25311.9511.42070.529299
25414.7513.99820.751782
25515.1518.1689-3.01887
25613.212.00241.19762
25716.8521.1799-4.32986
2587.8513.9502-6.10023
2597.710.4086-2.70855
26012.618.5677-5.9677
2617.858.83609-0.986087
26210.9513.0108-2.06085
26312.3515.4944-3.14443
2649.958.617111.33289
26514.912.62782.27216
26616.6516.22210.427935
26713.413.12760.27242
26813.9512.01811.93194
26915.713.30862.3914
27016.8518.0056-1.1556
27110.959.180211.76979
27215.3514.83720.512775
27312.210.82551.37454
27415.113.08382.01615
27517.7516.74581.00417
27615.215.5418-0.341775
27714.613.4891.11101
27816.6519.8558-3.20584
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 13.2988 & -0.39879 \tabularnewline
2 & 12.2 & 11.2828 & 0.917223 \tabularnewline
3 & 12.8 & 11.7176 & 1.08235 \tabularnewline
4 & 7.4 & 11.8639 & -4.46386 \tabularnewline
5 & 6.7 & 10.571 & -3.87104 \tabularnewline
6 & 12.6 & 13.3409 & -0.740863 \tabularnewline
7 & 14.8 & 12.2371 & 2.56292 \tabularnewline
8 & 13.3 & 11.488 & 1.81205 \tabularnewline
9 & 11.1 & 12.0336 & -0.933576 \tabularnewline
10 & 8.2 & 11.6045 & -3.40448 \tabularnewline
11 & 11.4 & 11.9322 & -0.53222 \tabularnewline
12 & 6.4 & 11.5807 & -5.18071 \tabularnewline
13 & 10.6 & 9.82277 & 0.777226 \tabularnewline
14 & 12 & 13.631 & -1.63104 \tabularnewline
15 & 6.3 & 7.77743 & -1.47743 \tabularnewline
16 & 11.3 & 9.18685 & 2.11315 \tabularnewline
17 & 11.9 & 12.5186 & -0.618554 \tabularnewline
18 & 9.3 & 10.6671 & -1.36709 \tabularnewline
19 & 9.6 & 10.7509 & -1.15093 \tabularnewline
20 & 10 & 10.6117 & -0.611664 \tabularnewline
21 & 6.4 & 9.99428 & -3.59428 \tabularnewline
22 & 13.8 & 10.5304 & 3.26958 \tabularnewline
23 & 10.8 & 13.5757 & -2.77568 \tabularnewline
24 & 13.8 & 13.595 & 0.204981 \tabularnewline
25 & 11.7 & 11.2993 & 0.400659 \tabularnewline
26 & 10.9 & 14.4759 & -3.57591 \tabularnewline
27 & 16.1 & 12.5953 & 3.50472 \tabularnewline
28 & 13.4 & 10.0586 & 3.34142 \tabularnewline
29 & 9.9 & 11.932 & -2.03205 \tabularnewline
30 & 11.5 & 11.3706 & 0.129372 \tabularnewline
31 & 8.3 & 9.99885 & -1.69885 \tabularnewline
32 & 11.7 & 11.6763 & 0.0236684 \tabularnewline
33 & 9 & 10.4935 & -1.49351 \tabularnewline
34 & 9.7 & 11.8677 & -2.1677 \tabularnewline
35 & 10.8 & 9.83163 & 0.968372 \tabularnewline
36 & 10.3 & 9.34222 & 0.957784 \tabularnewline
37 & 10.4 & 11.3 & -0.900016 \tabularnewline
38 & 12.7 & 9.39536 & 3.30464 \tabularnewline
39 & 9.3 & 12.0702 & -2.7702 \tabularnewline
40 & 11.8 & 12.5972 & -0.797239 \tabularnewline
41 & 5.9 & 10.1368 & -4.23682 \tabularnewline
42 & 11.4 & 11.3252 & 0.0747653 \tabularnewline
43 & 13 & 11.4898 & 1.51023 \tabularnewline
44 & 10.8 & 11.8311 & -1.03112 \tabularnewline
45 & 12.3 & 8.04168 & 4.25832 \tabularnewline
46 & 11.3 & 13.3123 & -2.01229 \tabularnewline
47 & 11.8 & 10.188 & 1.61198 \tabularnewline
48 & 7.9 & 9.28615 & -1.38615 \tabularnewline
49 & 12.7 & 10.781 & 1.91897 \tabularnewline
50 & 12.3 & 8.52113 & 3.77887 \tabularnewline
51 & 11.6 & 10.0272 & 1.57285 \tabularnewline
52 & 6.7 & 7.08296 & -0.382956 \tabularnewline
53 & 10.9 & 10.635 & 0.264952 \tabularnewline
54 & 12.1 & 10.3416 & 1.75836 \tabularnewline
55 & 13.3 & 10.1762 & 3.1238 \tabularnewline
56 & 10.1 & 10.3041 & -0.204123 \tabularnewline
57 & 5.7 & 10.0918 & -4.39179 \tabularnewline
58 & 14.3 & 10.8187 & 3.4813 \tabularnewline
59 & 8 & 7.39329 & 0.606712 \tabularnewline
60 & 13.3 & 10.0963 & 3.20369 \tabularnewline
61 & 9.3 & 12.9873 & -3.68728 \tabularnewline
62 & 12.5 & 11.5756 & 0.924438 \tabularnewline
63 & 7.6 & 10.4285 & -2.82845 \tabularnewline
64 & 15.9 & 13.4226 & 2.4774 \tabularnewline
65 & 9.2 & 12.5694 & -3.36945 \tabularnewline
66 & 9.1 & 8.52403 & 0.575971 \tabularnewline
67 & 11.1 & 13.4324 & -2.33244 \tabularnewline
68 & 13 & 15.0463 & -2.04633 \tabularnewline
69 & 14.5 & 11.6886 & 2.81141 \tabularnewline
70 & 12.2 & 10.2402 & 1.95975 \tabularnewline
71 & 12.3 & 13.2059 & -0.905895 \tabularnewline
72 & 11.4 & 10.7102 & 0.689761 \tabularnewline
73 & 8.8 & 9.91499 & -1.11499 \tabularnewline
74 & 14.6 & 10.9942 & 3.60583 \tabularnewline
75 & 12.6 & 11.6285 & 0.971525 \tabularnewline
76 & NA & NA & 0.592189 \tabularnewline
77 & 13 & 10.4864 & 2.51361 \tabularnewline
78 & 12.6 & 11.9829 & 0.61708 \tabularnewline
79 & 13.2 & 11.8708 & 1.32919 \tabularnewline
80 & 9.9 & 12.5428 & -2.6428 \tabularnewline
81 & 7.7 & 7.29637 & 0.40363 \tabularnewline
82 & 10.5 & 6.96599 & 3.53401 \tabularnewline
83 & 13.4 & 12.5921 & 0.807856 \tabularnewline
84 & 10.9 & 15.5521 & -4.65206 \tabularnewline
85 & 4.3 & 4.46507 & -0.165074 \tabularnewline
86 & 10.3 & 9.12749 & 1.17251 \tabularnewline
87 & 11.8 & 9.06868 & 2.73132 \tabularnewline
88 & 11.2 & 8.57676 & 2.62324 \tabularnewline
89 & 11.4 & 12.7587 & -1.35874 \tabularnewline
90 & 8.6 & 6.53163 & 2.06837 \tabularnewline
91 & 13.2 & 9.0567 & 4.1433 \tabularnewline
92 & 12.6 & 16.6998 & -4.09976 \tabularnewline
93 & 5.6 & 6.87184 & -1.27184 \tabularnewline
94 & 9.9 & 10.7371 & -0.837094 \tabularnewline
95 & 8.8 & 10.172 & -1.37202 \tabularnewline
96 & 7.7 & 8.63896 & -0.938959 \tabularnewline
97 & 9 & 12.1253 & -3.12532 \tabularnewline
98 & 7.3 & 5.04125 & 2.25875 \tabularnewline
99 & 11.4 & 7.52177 & 3.87823 \tabularnewline
100 & 13.6 & 15.6927 & -2.09266 \tabularnewline
101 & 7.9 & 5.56569 & 2.33431 \tabularnewline
102 & 10.7 & 10.1071 & 0.592937 \tabularnewline
103 & 10.3 & 10.8049 & -0.504919 \tabularnewline
104 & 8.3 & 8.82277 & -0.522773 \tabularnewline
105 & 9.6 & 4.88312 & 4.71688 \tabularnewline
106 & 14.2 & 15.1462 & -0.946152 \tabularnewline
107 & 8.5 & 4.59229 & 3.90771 \tabularnewline
108 & 13.5 & 17.9956 & -4.49558 \tabularnewline
109 & 4.9 & 6.63879 & -1.73879 \tabularnewline
110 & 6.4 & 7.34315 & -0.943151 \tabularnewline
111 & 9.6 & 8.17337 & 1.42663 \tabularnewline
112 & 11.6 & 9.9773 & 1.6227 \tabularnewline
113 & 11.1 & 18.1607 & -7.06072 \tabularnewline
114 & 4.35 & 4.53644 & -0.186436 \tabularnewline
115 & 12.7 & 9.86571 & 2.83429 \tabularnewline
116 & 18.1 & 15.7587 & 2.34126 \tabularnewline
117 & 17.85 & 19.0581 & -1.20807 \tabularnewline
118 & 16.6 & 15.9175 & 0.682513 \tabularnewline
119 & 12.6 & 13.8264 & -1.22642 \tabularnewline
120 & 17.1 & 15.5875 & 1.51253 \tabularnewline
121 & 19.1 & 22.2134 & -3.11339 \tabularnewline
122 & 16.1 & 15.6535 & 0.446544 \tabularnewline
123 & 13.35 & 12.0092 & 1.34078 \tabularnewline
124 & 18.4 & 15.048 & 3.35195 \tabularnewline
125 & 14.7 & 17.755 & -3.05501 \tabularnewline
126 & 10.6 & 11.4602 & -0.860186 \tabularnewline
127 & 12.6 & 11.0825 & 1.51746 \tabularnewline
128 & 16.2 & 16.7622 & -0.562241 \tabularnewline
129 & 13.6 & 10.4358 & 3.16425 \tabularnewline
130 & 18.9 & 18.2679 & 0.632083 \tabularnewline
131 & 14.1 & 13.4498 & 0.650228 \tabularnewline
132 & 14.5 & 16.088 & -1.588 \tabularnewline
133 & 16.15 & 15.337 & 0.813026 \tabularnewline
134 & 14.75 & 13.8448 & 0.905235 \tabularnewline
135 & 14.8 & 15.3745 & -0.574461 \tabularnewline
136 & 12.45 & 13.1847 & -0.734742 \tabularnewline
137 & 12.65 & 9.52398 & 3.12602 \tabularnewline
138 & 17.35 & 19.8796 & -2.52958 \tabularnewline
139 & 8.6 & 7.31173 & 1.28827 \tabularnewline
140 & 18.4 & 17.8019 & 0.598117 \tabularnewline
141 & 16.1 & 17.6847 & -1.58466 \tabularnewline
142 & 11.6 & 8.76872 & 2.83128 \tabularnewline
143 & 17.75 & 17.7777 & -0.0276608 \tabularnewline
144 & 15.25 & 12.3355 & 2.91452 \tabularnewline
145 & 17.65 & 17.7091 & -0.0590572 \tabularnewline
146 & 16.35 & 15.8826 & 0.467445 \tabularnewline
147 & 17.65 & 18.1821 & -0.532075 \tabularnewline
148 & 13.6 & 14.0126 & -0.412649 \tabularnewline
149 & 14.35 & 14.6435 & -0.293521 \tabularnewline
150 & 14.75 & 12.7775 & 1.97252 \tabularnewline
151 & 18.25 & 24.1992 & -5.94924 \tabularnewline
152 & 9.9 & 9.22338 & 0.676617 \tabularnewline
153 & 16 & 13.459 & 2.54101 \tabularnewline
154 & 18.25 & 18.3404 & -0.0903793 \tabularnewline
155 & 16.85 & 14.7785 & 2.07149 \tabularnewline
156 & 14.6 & 14.7123 & -0.112283 \tabularnewline
157 & 13.85 & 12.209 & 1.64101 \tabularnewline
158 & 18.95 & 18.3832 & 0.5668 \tabularnewline
159 & 15.6 & 17.3548 & -1.75482 \tabularnewline
160 & 14.85 & 16.6734 & -1.82341 \tabularnewline
161 & 11.75 & 9.92061 & 1.82939 \tabularnewline
162 & 18.45 & 15.7923 & 2.65771 \tabularnewline
163 & 15.9 & 16.3016 & -0.401625 \tabularnewline
164 & 17.1 & 11.2767 & 5.82332 \tabularnewline
165 & 16.1 & 14.7179 & 1.38209 \tabularnewline
166 & 19.9 & 20.6695 & -0.769503 \tabularnewline
167 & 10.95 & 8.81513 & 2.13487 \tabularnewline
168 & 18.45 & 16.3037 & 2.14625 \tabularnewline
169 & 15.1 & 14.7283 & 0.371741 \tabularnewline
170 & 15 & 18.1579 & -3.15793 \tabularnewline
171 & 11.35 & 9.51682 & 1.83318 \tabularnewline
172 & 15.95 & 13.0839 & 2.86609 \tabularnewline
173 & 18.1 & 19.4933 & -1.39334 \tabularnewline
174 & 14.6 & 14.9082 & -0.308163 \tabularnewline
175 & 15.4 & 15.6816 & -0.281601 \tabularnewline
176 & 15.4 & 12.3969 & 3.00309 \tabularnewline
177 & 17.6 & 19.3905 & -1.79049 \tabularnewline
178 & 13.35 & 10.6101 & 2.73992 \tabularnewline
179 & 19.1 & 19.4034 & -0.303386 \tabularnewline
180 & 15.35 & 20.6418 & -5.29179 \tabularnewline
181 & 7.6 & 10.2534 & -2.65343 \tabularnewline
182 & 13.4 & 14.6809 & -1.28093 \tabularnewline
183 & 13.9 & 11.2623 & 2.6377 \tabularnewline
184 & 19.1 & 18.6 & 0.500003 \tabularnewline
185 & 15.25 & 17.0714 & -1.82136 \tabularnewline
186 & 12.9 & 12.4926 & 0.407398 \tabularnewline
187 & 16.1 & 13.2755 & 2.82446 \tabularnewline
188 & 17.35 & 19.1738 & -1.82378 \tabularnewline
189 & 13.15 & 14.9522 & -1.80225 \tabularnewline
190 & 12.15 & 11.7073 & 0.442691 \tabularnewline
191 & 12.6 & 14.7143 & -2.11434 \tabularnewline
192 & 10.35 & 8.86865 & 1.48135 \tabularnewline
193 & 15.4 & 18.3241 & -2.92409 \tabularnewline
194 & 9.6 & 5.6896 & 3.9104 \tabularnewline
195 & 18.2 & 18.697 & -0.497042 \tabularnewline
196 & 13.6 & 12.684 & 0.916042 \tabularnewline
197 & 14.85 & 16.7292 & -1.87918 \tabularnewline
198 & 14.75 & 14.1002 & 0.649769 \tabularnewline
199 & 14.1 & 12.3578 & 1.7422 \tabularnewline
200 & 14.9 & 13.3964 & 1.50359 \tabularnewline
201 & 16.25 & 15.828 & 0.421964 \tabularnewline
202 & 19.25 & 18.1566 & 1.09336 \tabularnewline
203 & 13.6 & 15.2771 & -1.67707 \tabularnewline
204 & 13.6 & 12.6915 & 0.908456 \tabularnewline
205 & 15.65 & 16.998 & -1.34796 \tabularnewline
206 & 12.75 & 11.1446 & 1.60536 \tabularnewline
207 & 14.6 & 16.5607 & -1.9607 \tabularnewline
208 & 9.85 & 9.50639 & 0.343612 \tabularnewline
209 & 12.65 & 9.33954 & 3.31046 \tabularnewline
210 & 19.2 & 17.5362 & 1.66382 \tabularnewline
211 & 16.6 & 17.5846 & -0.984613 \tabularnewline
212 & 11.2 & 10.6004 & 0.599578 \tabularnewline
213 & 15.25 & 18.0914 & -2.84138 \tabularnewline
214 & 11.9 & 12.6432 & -0.743228 \tabularnewline
215 & 13.2 & 14.3368 & -1.1368 \tabularnewline
216 & 16.35 & 17.7426 & -1.3926 \tabularnewline
217 & 12.4 & 10.4135 & 1.98648 \tabularnewline
218 & 15.85 & 13.454 & 2.39598 \tabularnewline
219 & 18.15 & 19.486 & -1.33602 \tabularnewline
220 & 11.15 & 11.4078 & -0.257832 \tabularnewline
221 & 15.65 & 13.1468 & 2.50325 \tabularnewline
222 & 17.75 & 22.1479 & -4.39785 \tabularnewline
223 & 7.65 & 8.9176 & -1.2676 \tabularnewline
224 & 12.35 & 10.4102 & 1.93985 \tabularnewline
225 & 15.6 & 13.0263 & 2.57371 \tabularnewline
226 & 19.3 & 17.0748 & 2.22524 \tabularnewline
227 & 15.2 & 12.9688 & 2.23117 \tabularnewline
228 & 17.1 & 14.7311 & 2.36885 \tabularnewline
229 & 15.6 & 12.989 & 2.611 \tabularnewline
230 & 18.4 & 15.3768 & 3.02324 \tabularnewline
231 & 19.05 & 15.4104 & 3.6396 \tabularnewline
232 & 18.55 & 16.7236 & 1.82644 \tabularnewline
233 & 19.1 & 18.9567 & 0.14332 \tabularnewline
234 & 13.1 & 15.5474 & -2.4474 \tabularnewline
235 & 12.85 & 15.3849 & -2.5349 \tabularnewline
236 & 9.5 & 16.8169 & -7.31689 \tabularnewline
237 & 4.5 & 4.98811 & -0.488113 \tabularnewline
238 & 11.85 & 13.3923 & -1.54228 \tabularnewline
239 & 13.6 & 14.667 & -1.06698 \tabularnewline
240 & 11.7 & 11.7812 & -0.0811741 \tabularnewline
241 & 12.4 & 14.4332 & -2.03323 \tabularnewline
242 & 13.35 & 14.9826 & -1.63265 \tabularnewline
243 & 11.4 & 10.0901 & 1.3099 \tabularnewline
244 & 14.9 & 13.4035 & 1.49651 \tabularnewline
245 & 19.9 & 22.44 & -2.53996 \tabularnewline
246 & 11.2 & 11.1801 & 0.0198709 \tabularnewline
247 & 14.6 & 14.2131 & 0.386921 \tabularnewline
248 & 17.6 & 17.9277 & -0.327701 \tabularnewline
249 & 14.05 & 14.0951 & -0.045107 \tabularnewline
250 & 16.1 & 16.8165 & -0.716528 \tabularnewline
251 & 13.35 & 15.9242 & -2.57419 \tabularnewline
252 & 11.85 & 14.5205 & -2.67051 \tabularnewline
253 & 11.95 & 11.4207 & 0.529299 \tabularnewline
254 & 14.75 & 13.9982 & 0.751782 \tabularnewline
255 & 15.15 & 18.1689 & -3.01887 \tabularnewline
256 & 13.2 & 12.0024 & 1.19762 \tabularnewline
257 & 16.85 & 21.1799 & -4.32986 \tabularnewline
258 & 7.85 & 13.9502 & -6.10023 \tabularnewline
259 & 7.7 & 10.4086 & -2.70855 \tabularnewline
260 & 12.6 & 18.5677 & -5.9677 \tabularnewline
261 & 7.85 & 8.83609 & -0.986087 \tabularnewline
262 & 10.95 & 13.0108 & -2.06085 \tabularnewline
263 & 12.35 & 15.4944 & -3.14443 \tabularnewline
264 & 9.95 & 8.61711 & 1.33289 \tabularnewline
265 & 14.9 & 12.6278 & 2.27216 \tabularnewline
266 & 16.65 & 16.2221 & 0.427935 \tabularnewline
267 & 13.4 & 13.1276 & 0.27242 \tabularnewline
268 & 13.95 & 12.0181 & 1.93194 \tabularnewline
269 & 15.7 & 13.3086 & 2.3914 \tabularnewline
270 & 16.85 & 18.0056 & -1.1556 \tabularnewline
271 & 10.95 & 9.18021 & 1.76979 \tabularnewline
272 & 15.35 & 14.8372 & 0.512775 \tabularnewline
273 & 12.2 & 10.8255 & 1.37454 \tabularnewline
274 & 15.1 & 13.0838 & 2.01615 \tabularnewline
275 & 17.75 & 16.7458 & 1.00417 \tabularnewline
276 & 15.2 & 15.5418 & -0.341775 \tabularnewline
277 & 14.6 & 13.489 & 1.11101 \tabularnewline
278 & 16.65 & 19.8558 & -3.20584 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]13.2988[/C][C]-0.39879[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]11.2828[/C][C]0.917223[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.7176[/C][C]1.08235[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.8639[/C][C]-4.46386[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.571[/C][C]-3.87104[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.3409[/C][C]-0.740863[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.2371[/C][C]2.56292[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]11.488[/C][C]1.81205[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]12.0336[/C][C]-0.933576[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.6045[/C][C]-3.40448[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.9322[/C][C]-0.53222[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.5807[/C][C]-5.18071[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.82277[/C][C]0.777226[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.631[/C][C]-1.63104[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.77743[/C][C]-1.47743[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.18685[/C][C]2.11315[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.5186[/C][C]-0.618554[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.6671[/C][C]-1.36709[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]10.7509[/C][C]-1.15093[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]10.6117[/C][C]-0.611664[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]9.99428[/C][C]-3.59428[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.5304[/C][C]3.26958[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]13.5757[/C][C]-2.77568[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]13.595[/C][C]0.204981[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.2993[/C][C]0.400659[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.4759[/C][C]-3.57591[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.5953[/C][C]3.50472[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.0586[/C][C]3.34142[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.932[/C][C]-2.03205[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.3706[/C][C]0.129372[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.99885[/C][C]-1.69885[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.6763[/C][C]0.0236684[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.4935[/C][C]-1.49351[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.8677[/C][C]-2.1677[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.83163[/C][C]0.968372[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]9.34222[/C][C]0.957784[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.3[/C][C]-0.900016[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]9.39536[/C][C]3.30464[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]12.0702[/C][C]-2.7702[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.5972[/C][C]-0.797239[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]10.1368[/C][C]-4.23682[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.3252[/C][C]0.0747653[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.4898[/C][C]1.51023[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.8311[/C][C]-1.03112[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]8.04168[/C][C]4.25832[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.3123[/C][C]-2.01229[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]10.188[/C][C]1.61198[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.28615[/C][C]-1.38615[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]10.781[/C][C]1.91897[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]8.52113[/C][C]3.77887[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.0272[/C][C]1.57285[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.08296[/C][C]-0.382956[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.635[/C][C]0.264952[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]10.3416[/C][C]1.75836[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.1762[/C][C]3.1238[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]10.3041[/C][C]-0.204123[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]10.0918[/C][C]-4.39179[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.8187[/C][C]3.4813[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.39329[/C][C]0.606712[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.0963[/C][C]3.20369[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.9873[/C][C]-3.68728[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.5756[/C][C]0.924438[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]10.4285[/C][C]-2.82845[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.4226[/C][C]2.4774[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.5694[/C][C]-3.36945[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.52403[/C][C]0.575971[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.4324[/C][C]-2.33244[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.0463[/C][C]-2.04633[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.6886[/C][C]2.81141[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.2402[/C][C]1.95975[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.2059[/C][C]-0.905895[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.7102[/C][C]0.689761[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]9.91499[/C][C]-1.11499[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.9942[/C][C]3.60583[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.6285[/C][C]0.971525[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.592189[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.4864[/C][C]2.51361[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.9829[/C][C]0.61708[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]11.8708[/C][C]1.32919[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.5428[/C][C]-2.6428[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.29637[/C][C]0.40363[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]6.96599[/C][C]3.53401[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]12.5921[/C][C]0.807856[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]15.5521[/C][C]-4.65206[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]4.46507[/C][C]-0.165074[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]9.12749[/C][C]1.17251[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]9.06868[/C][C]2.73132[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]8.57676[/C][C]2.62324[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]12.7587[/C][C]-1.35874[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.53163[/C][C]2.06837[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.0567[/C][C]4.1433[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]16.6998[/C][C]-4.09976[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]6.87184[/C][C]-1.27184[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]10.7371[/C][C]-0.837094[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.172[/C][C]-1.37202[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]8.63896[/C][C]-0.938959[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.1253[/C][C]-3.12532[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.04125[/C][C]2.25875[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.52177[/C][C]3.87823[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]15.6927[/C][C]-2.09266[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]5.56569[/C][C]2.33431[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.1071[/C][C]0.592937[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.8049[/C][C]-0.504919[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]8.82277[/C][C]-0.522773[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]4.88312[/C][C]4.71688[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]15.1462[/C][C]-0.946152[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.59229[/C][C]3.90771[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]17.9956[/C][C]-4.49558[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]6.63879[/C][C]-1.73879[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.34315[/C][C]-0.943151[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.17337[/C][C]1.42663[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]9.9773[/C][C]1.6227[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]18.1607[/C][C]-7.06072[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.53644[/C][C]-0.186436[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.86571[/C][C]2.83429[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.7587[/C][C]2.34126[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]19.0581[/C][C]-1.20807[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.9175[/C][C]0.682513[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.8264[/C][C]-1.22642[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]15.5875[/C][C]1.51253[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]22.2134[/C][C]-3.11339[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.6535[/C][C]0.446544[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]12.0092[/C][C]1.34078[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]15.048[/C][C]3.35195[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.755[/C][C]-3.05501[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.4602[/C][C]-0.860186[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.0825[/C][C]1.51746[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.7622[/C][C]-0.562241[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.4358[/C][C]3.16425[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.2679[/C][C]0.632083[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.4498[/C][C]0.650228[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]16.088[/C][C]-1.588[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.337[/C][C]0.813026[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.8448[/C][C]0.905235[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]15.3745[/C][C]-0.574461[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]13.1847[/C][C]-0.734742[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.52398[/C][C]3.12602[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.8796[/C][C]-2.52958[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]7.31173[/C][C]1.28827[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.8019[/C][C]0.598117[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.6847[/C][C]-1.58466[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.76872[/C][C]2.83128[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.7777[/C][C]-0.0276608[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]12.3355[/C][C]2.91452[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]17.7091[/C][C]-0.0590572[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]15.8826[/C][C]0.467445[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.1821[/C][C]-0.532075[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]14.0126[/C][C]-0.412649[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.6435[/C][C]-0.293521[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.7775[/C][C]1.97252[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]24.1992[/C][C]-5.94924[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.22338[/C][C]0.676617[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.459[/C][C]2.54101[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.3404[/C][C]-0.0903793[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.7785[/C][C]2.07149[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.7123[/C][C]-0.112283[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.209[/C][C]1.64101[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]18.3832[/C][C]0.5668[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]17.3548[/C][C]-1.75482[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]16.6734[/C][C]-1.82341[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]9.92061[/C][C]1.82939[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.7923[/C][C]2.65771[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]16.3016[/C][C]-0.401625[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]11.2767[/C][C]5.82332[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]14.7179[/C][C]1.38209[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.6695[/C][C]-0.769503[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]8.81513[/C][C]2.13487[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.3037[/C][C]2.14625[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]14.7283[/C][C]0.371741[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]18.1579[/C][C]-3.15793[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]9.51682[/C][C]1.83318[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.0839[/C][C]2.86609[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]19.4933[/C][C]-1.39334[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.9082[/C][C]-0.308163[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.6816[/C][C]-0.281601[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.3969[/C][C]3.00309[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]19.3905[/C][C]-1.79049[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.6101[/C][C]2.73992[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]19.4034[/C][C]-0.303386[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]20.6418[/C][C]-5.29179[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]10.2534[/C][C]-2.65343[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]14.6809[/C][C]-1.28093[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.2623[/C][C]2.6377[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]18.6[/C][C]0.500003[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]17.0714[/C][C]-1.82136[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.4926[/C][C]0.407398[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]13.2755[/C][C]2.82446[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.1738[/C][C]-1.82378[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]14.9522[/C][C]-1.80225[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.7073[/C][C]0.442691[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.7143[/C][C]-2.11434[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.86865[/C][C]1.48135[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.3241[/C][C]-2.92409[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]5.6896[/C][C]3.9104[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.697[/C][C]-0.497042[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.684[/C][C]0.916042[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.7292[/C][C]-1.87918[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.1002[/C][C]0.649769[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.3578[/C][C]1.7422[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]13.3964[/C][C]1.50359[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]15.828[/C][C]0.421964[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.1566[/C][C]1.09336[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.2771[/C][C]-1.67707[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]12.6915[/C][C]0.908456[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.998[/C][C]-1.34796[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.1446[/C][C]1.60536[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]16.5607[/C][C]-1.9607[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.50639[/C][C]0.343612[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]9.33954[/C][C]3.31046[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.5362[/C][C]1.66382[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.5846[/C][C]-0.984613[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]10.6004[/C][C]0.599578[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]18.0914[/C][C]-2.84138[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.6432[/C][C]-0.743228[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]14.3368[/C][C]-1.1368[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.7426[/C][C]-1.3926[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]10.4135[/C][C]1.98648[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]13.454[/C][C]2.39598[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.486[/C][C]-1.33602[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.4078[/C][C]-0.257832[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]13.1468[/C][C]2.50325[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.1479[/C][C]-4.39785[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.9176[/C][C]-1.2676[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]10.4102[/C][C]1.93985[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.0263[/C][C]2.57371[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.0748[/C][C]2.22524[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]12.9688[/C][C]2.23117[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]14.7311[/C][C]2.36885[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.989[/C][C]2.611[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.3768[/C][C]3.02324[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]15.4104[/C][C]3.6396[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.7236[/C][C]1.82644[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.9567[/C][C]0.14332[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]15.5474[/C][C]-2.4474[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.3849[/C][C]-2.5349[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.8169[/C][C]-7.31689[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]4.98811[/C][C]-0.488113[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]13.3923[/C][C]-1.54228[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]14.667[/C][C]-1.06698[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]11.7812[/C][C]-0.0811741[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]14.4332[/C][C]-2.03323[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.9826[/C][C]-1.63265[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.0901[/C][C]1.3099[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.4035[/C][C]1.49651[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.44[/C][C]-2.53996[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.1801[/C][C]0.0198709[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]14.2131[/C][C]0.386921[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]17.9277[/C][C]-0.327701[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]14.0951[/C][C]-0.045107[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.8165[/C][C]-0.716528[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]15.9242[/C][C]-2.57419[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]14.5205[/C][C]-2.67051[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.4207[/C][C]0.529299[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.9982[/C][C]0.751782[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]18.1689[/C][C]-3.01887[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.0024[/C][C]1.19762[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.1799[/C][C]-4.32986[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]13.9502[/C][C]-6.10023[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.4086[/C][C]-2.70855[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]18.5677[/C][C]-5.9677[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.83609[/C][C]-0.986087[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.0108[/C][C]-2.06085[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.4944[/C][C]-3.14443[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.61711[/C][C]1.33289[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]12.6278[/C][C]2.27216[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.2221[/C][C]0.427935[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.1276[/C][C]0.27242[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]12.0181[/C][C]1.93194[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]13.3086[/C][C]2.3914[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.0056[/C][C]-1.1556[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]9.18021[/C][C]1.76979[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]14.8372[/C][C]0.512775[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.8255[/C][C]1.37454[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.0838[/C][C]2.01615[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]16.7458[/C][C]1.00417[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.5418[/C][C]-0.341775[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.489[/C][C]1.11101[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.8558[/C][C]-3.20584[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.2988-0.39879
212.211.28280.917223
312.811.71761.08235
47.411.8639-4.46386
56.710.571-3.87104
612.613.3409-0.740863
714.812.23712.56292
813.311.4881.81205
911.112.0336-0.933576
108.211.6045-3.40448
1111.411.9322-0.53222
126.411.5807-5.18071
1310.69.822770.777226
141213.631-1.63104
156.37.77743-1.47743
1611.39.186852.11315
1711.912.5186-0.618554
189.310.6671-1.36709
199.610.7509-1.15093
201010.6117-0.611664
216.49.99428-3.59428
2213.810.53043.26958
2310.813.5757-2.77568
2413.813.5950.204981
2511.711.29930.400659
2610.914.4759-3.57591
2716.112.59533.50472
2813.410.05863.34142
299.911.932-2.03205
3011.511.37060.129372
318.39.99885-1.69885
3211.711.67630.0236684
33910.4935-1.49351
349.711.8677-2.1677
3510.89.831630.968372
3610.39.342220.957784
3710.411.3-0.900016
3812.79.395363.30464
399.312.0702-2.7702
4011.812.5972-0.797239
415.910.1368-4.23682
4211.411.32520.0747653
431311.48981.51023
4410.811.8311-1.03112
4512.38.041684.25832
4611.313.3123-2.01229
4711.810.1881.61198
487.99.28615-1.38615
4912.710.7811.91897
5012.38.521133.77887
5111.610.02721.57285
526.77.08296-0.382956
5310.910.6350.264952
5412.110.34161.75836
5513.310.17623.1238
5610.110.3041-0.204123
575.710.0918-4.39179
5814.310.81873.4813
5987.393290.606712
6013.310.09633.20369
619.312.9873-3.68728
6212.511.57560.924438
637.610.4285-2.82845
6415.913.42262.4774
659.212.5694-3.36945
669.18.524030.575971
6711.113.4324-2.33244
681315.0463-2.04633
6914.511.68862.81141
7012.210.24021.95975
7112.313.2059-0.905895
7211.410.71020.689761
738.89.91499-1.11499
7414.610.99423.60583
7512.611.62850.971525
76NANA0.592189
771310.48642.51361
7812.611.98290.61708
7913.211.87081.32919
809.912.5428-2.6428
817.77.296370.40363
8210.56.965993.53401
8313.412.59210.807856
8410.915.5521-4.65206
854.34.46507-0.165074
8610.39.127491.17251
8711.89.068682.73132
8811.28.576762.62324
8911.412.7587-1.35874
908.66.531632.06837
9113.29.05674.1433
9212.616.6998-4.09976
935.66.87184-1.27184
949.910.7371-0.837094
958.810.172-1.37202
967.78.63896-0.938959
97912.1253-3.12532
987.35.041252.25875
9911.47.521773.87823
10013.615.6927-2.09266
1017.95.565692.33431
10210.710.10710.592937
10310.310.8049-0.504919
1048.38.82277-0.522773
1059.64.883124.71688
10614.215.1462-0.946152
1078.54.592293.90771
10813.517.9956-4.49558
1094.96.63879-1.73879
1106.47.34315-0.943151
1119.68.173371.42663
11211.69.97731.6227
11311.118.1607-7.06072
1144.354.53644-0.186436
11512.79.865712.83429
11618.115.75872.34126
11717.8519.0581-1.20807
11816.615.91750.682513
11912.613.8264-1.22642
12017.115.58751.51253
12119.122.2134-3.11339
12216.115.65350.446544
12313.3512.00921.34078
12418.415.0483.35195
12514.717.755-3.05501
12610.611.4602-0.860186
12712.611.08251.51746
12816.216.7622-0.562241
12913.610.43583.16425
13018.918.26790.632083
13114.113.44980.650228
13214.516.088-1.588
13316.1515.3370.813026
13414.7513.84480.905235
13514.815.3745-0.574461
13612.4513.1847-0.734742
13712.659.523983.12602
13817.3519.8796-2.52958
1398.67.311731.28827
14018.417.80190.598117
14116.117.6847-1.58466
14211.68.768722.83128
14317.7517.7777-0.0276608
14415.2512.33552.91452
14517.6517.7091-0.0590572
14616.3515.88260.467445
14717.6518.1821-0.532075
14813.614.0126-0.412649
14914.3514.6435-0.293521
15014.7512.77751.97252
15118.2524.1992-5.94924
1529.99.223380.676617
1531613.4592.54101
15418.2518.3404-0.0903793
15516.8514.77852.07149
15614.614.7123-0.112283
15713.8512.2091.64101
15818.9518.38320.5668
15915.617.3548-1.75482
16014.8516.6734-1.82341
16111.759.920611.82939
16218.4515.79232.65771
16315.916.3016-0.401625
16417.111.27675.82332
16516.114.71791.38209
16619.920.6695-0.769503
16710.958.815132.13487
16818.4516.30372.14625
16915.114.72830.371741
1701518.1579-3.15793
17111.359.516821.83318
17215.9513.08392.86609
17318.119.4933-1.39334
17414.614.9082-0.308163
17515.415.6816-0.281601
17615.412.39693.00309
17717.619.3905-1.79049
17813.3510.61012.73992
17919.119.4034-0.303386
18015.3520.6418-5.29179
1817.610.2534-2.65343
18213.414.6809-1.28093
18313.911.26232.6377
18419.118.60.500003
18515.2517.0714-1.82136
18612.912.49260.407398
18716.113.27552.82446
18817.3519.1738-1.82378
18913.1514.9522-1.80225
19012.1511.70730.442691
19112.614.7143-2.11434
19210.358.868651.48135
19315.418.3241-2.92409
1949.65.68963.9104
19518.218.697-0.497042
19613.612.6840.916042
19714.8516.7292-1.87918
19814.7514.10020.649769
19914.112.35781.7422
20014.913.39641.50359
20116.2515.8280.421964
20219.2518.15661.09336
20313.615.2771-1.67707
20413.612.69150.908456
20515.6516.998-1.34796
20612.7511.14461.60536
20714.616.5607-1.9607
2089.859.506390.343612
20912.659.339543.31046
21019.217.53621.66382
21116.617.5846-0.984613
21211.210.60040.599578
21315.2518.0914-2.84138
21411.912.6432-0.743228
21513.214.3368-1.1368
21616.3517.7426-1.3926
21712.410.41351.98648
21815.8513.4542.39598
21918.1519.486-1.33602
22011.1511.4078-0.257832
22115.6513.14682.50325
22217.7522.1479-4.39785
2237.658.9176-1.2676
22412.3510.41021.93985
22515.613.02632.57371
22619.317.07482.22524
22715.212.96882.23117
22817.114.73112.36885
22915.612.9892.611
23018.415.37683.02324
23119.0515.41043.6396
23218.5516.72361.82644
23319.118.95670.14332
23413.115.5474-2.4474
23512.8515.3849-2.5349
2369.516.8169-7.31689
2374.54.98811-0.488113
23811.8513.3923-1.54228
23913.614.667-1.06698
24011.711.7812-0.0811741
24112.414.4332-2.03323
24213.3514.9826-1.63265
24311.410.09011.3099
24414.913.40351.49651
24519.922.44-2.53996
24611.211.18010.0198709
24714.614.21310.386921
24817.617.9277-0.327701
24914.0514.0951-0.045107
25016.116.8165-0.716528
25113.3515.9242-2.57419
25211.8514.5205-2.67051
25311.9511.42070.529299
25414.7513.99820.751782
25515.1518.1689-3.01887
25613.212.00241.19762
25716.8521.1799-4.32986
2587.8513.9502-6.10023
2597.710.4086-2.70855
26012.618.5677-5.9677
2617.858.83609-0.986087
26210.9513.0108-2.06085
26312.3515.4944-3.14443
2649.958.617111.33289
26514.912.62782.27216
26616.6516.22210.427935
26713.413.12760.27242
26813.9512.01811.93194
26915.713.30862.3914
27016.8518.0056-1.1556
27110.959.180211.76979
27215.3514.83720.512775
27312.210.82551.37454
27415.113.08382.01615
27517.7516.74581.00417
27615.215.5418-0.341775
27714.613.4891.11101
27816.6519.8558-3.20584
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8389370.3221270.161063
140.7441070.5117850.255893
150.6229610.7540780.377039
160.8507330.2985330.149267
170.7779620.4440770.222038
180.7206410.5587190.279359
190.6330940.7338130.366906
200.5412640.9174720.458736
210.4613360.9226720.538664
220.6758580.6482840.324142
230.6745790.6508430.325421
240.601470.797060.39853
250.5313110.9373780.468689
260.4749620.9499250.525038
270.4386220.8772440.561378
280.5279950.9440110.472005
290.4950350.990070.504965
300.4320450.8640890.567955
310.4624890.9249770.537511
320.4091610.8183210.590839
330.3933690.7867370.606631
340.3469030.6938060.653097
350.3010680.6021360.698932
360.2547080.5094160.745292
370.2099460.4198910.790054
380.4618110.9236220.538189
390.444610.8892190.55539
400.4345150.8690310.565485
410.5624330.8751350.437567
420.5126920.9746160.487308
430.4728780.9457550.527122
440.438850.8777010.56115
450.480730.9614610.51927
460.4412780.8825560.558722
470.418450.8369010.58155
480.3939350.787870.606065
490.3800150.760030.619985
500.4112570.8225140.588743
510.3733030.7466050.626697
520.3669470.7338950.633053
530.3285490.6570970.671451
540.3318560.6637120.668144
550.3953510.7907030.604649
560.3557780.7115570.644222
570.5348280.9303450.465172
580.6065240.7869530.393476
590.5645290.8709420.435471
600.5600480.8799050.439952
610.6137780.7724450.386222
620.5874360.8251280.412564
630.6397430.7205130.360257
640.6830250.633950.316975
650.687840.6243190.31216
660.6550170.6899670.344983
670.6385560.7228870.361444
680.6212910.7574180.378709
690.6586570.6826850.341343
700.6378870.7242250.362113
710.605380.7892390.39462
720.5691710.8616590.430829
730.5394490.9211020.460551
740.5880610.8238790.411939
750.556510.8869790.44349
760.5277730.9444550.472227
770.5089420.9821160.491058
780.4888420.9776840.511158
790.4543360.9086710.545664
800.4939980.9879960.506002
810.4546680.9093360.545332
820.5010790.9978410.498921
830.4635810.9271630.536419
840.6188380.7623240.381162
850.5826370.8347260.417363
860.5502130.8995730.449787
870.5458430.9083140.454157
880.5425420.9149160.457458
890.5282640.9434720.471736
900.5156480.9687040.484352
910.5712690.8574620.428731
920.6790470.6419060.320953
930.659040.6819210.34096
940.6363580.7272840.363642
950.6247940.7504130.375206
960.5981220.8037570.401878
970.6423390.7153220.357661
980.6266040.7467920.373396
990.6602570.6794860.339743
1000.6683870.6632270.331613
1010.6526080.6947850.347392
1020.6187270.7625460.381273
1030.6023630.7952740.397637
1040.5735820.8528360.426418
1050.6600230.6799550.339977
1060.634680.7306410.36532
1070.6911740.6176530.308826
1080.7863790.4272430.213621
1090.789950.42010.21005
1100.7772390.4455230.222761
1110.7603780.4792440.239622
1120.7326850.534630.267315
1130.808730.3825390.19127
1140.8326160.3347670.167384
1150.9044430.1911150.0955574
1160.9176580.1646850.0823424
1170.9055120.1889750.0944876
1180.8926710.2146590.107329
1190.8807010.2385980.119299
1200.8756560.2486890.124344
1210.8928750.214250.107125
1220.8821240.2357520.117876
1230.8739820.2520370.126018
1240.8982810.2034380.101719
1250.9091140.1817720.0908862
1260.8952110.2095780.104789
1270.8882790.2234420.111721
1280.8717390.2565230.128261
1290.8861760.2276480.113824
1300.8699250.2601510.130075
1310.8520440.2959130.147956
1320.8456750.308650.154325
1330.8260740.3478530.173926
1340.8062070.3875860.193793
1350.7893490.4213010.210651
1360.7659130.4681750.234087
1370.7884590.4230820.211541
1380.7959310.4081380.204069
1390.7773660.4452680.222634
1400.7543070.4913860.245693
1410.7443450.5113110.255655
1420.7620250.475950.237975
1430.7358770.5282470.264123
1440.7505660.4988680.249434
1450.7225620.5548760.277438
1460.6951520.6096970.304848
1470.6690860.6618270.330914
1480.6378580.7242840.362142
1490.6065350.7869290.393465
1500.595520.808960.40448
1510.8077650.384470.192235
1520.7872050.425590.212795
1530.7891280.4217450.210872
1540.7624760.4750480.237524
1550.7579470.4841070.242053
1560.7311920.5376160.268808
1570.7143830.5712340.285617
1580.6853040.6293930.314696
1590.6835470.6329060.316453
1600.6673350.665330.332665
1610.6517680.6964630.348232
1620.656640.686720.34336
1630.6316630.7366750.368337
1640.8306210.3387580.169379
1650.8113170.3773650.188683
1660.7992310.4015380.200769
1670.7880480.4239040.211952
1680.8045130.3909730.195487
1690.7783830.4432350.221617
1700.813230.3735410.18677
1710.803470.3930590.19653
1720.8075230.3849540.192477
1730.7980870.4038260.201913
1740.7735940.4528130.226406
1750.747370.5052610.25263
1760.7727240.4545510.227276
1770.7612410.4775190.238759
1780.7669250.4661510.233075
1790.7387470.5225070.261253
1800.8284680.3430630.171532
1810.8500050.2999890.149995
1820.8456850.3086290.154315
1830.8485320.3029360.151468
1840.82590.3482010.1741
1850.822770.354460.17723
1860.7969280.4061440.203072
1870.8152490.3695020.184751
1880.8156180.3687650.184382
1890.8076130.3847750.192387
1900.7832240.4335510.216776
1910.7727620.4544760.227238
1920.7527370.4945270.247263
1930.7568520.4862960.243148
1940.7920040.4159920.207996
1950.7633990.4732020.236601
1960.7484590.5030820.251541
1970.7724570.4550860.227543
1980.7430020.5139960.256998
1990.7298720.5402560.270128
2000.7017220.5965570.298278
2010.6804140.6391730.319586
2020.6551840.6896320.344816
2030.6729170.6541670.327083
2040.6371870.7256250.362813
2050.6070.7860010.393
2060.6333530.7332940.366647
2070.6072390.7855230.392761
2080.5821150.835770.417885
2090.5744480.8511040.425552
2100.5878910.8242190.412109
2110.5595340.8809310.440466
2120.5177880.9644230.482212
2130.590380.819240.40962
2140.5818980.8362040.418102
2150.5617610.8764780.438239
2160.5239150.952170.476085
2170.5472590.9054820.452741
2180.5262960.9474070.473704
2190.488160.9763210.51184
2200.4434630.8869270.556537
2210.4304370.8608740.569563
2220.4988550.9977110.501145
2230.4603630.9207270.539637
2240.5081080.9837830.491892
2250.4882690.9765370.511731
2260.5386270.9227460.461373
2270.5443290.9113430.455671
2280.6265360.7469270.373464
2290.6358450.728310.364155
2300.6644470.6711050.335553
2310.6635780.6728430.336422
2320.6212790.7574420.378721
2330.6083240.7833510.391676
2340.5708280.8583430.429172
2350.5338430.9323130.466157
2360.8600470.2799060.139953
2370.8399420.3201170.160058
2380.8093080.3813830.190692
2390.7758690.4482620.224131
2400.7325290.5349420.267471
2410.7583060.4833880.241694
2420.7241250.5517490.275875
2430.713240.573520.28676
2440.6623430.6753140.337657
2450.6334980.7330030.366502
2460.5929490.8141030.407051
2470.6118980.7762050.388102
2480.7588450.4823110.241155
2490.7461150.5077690.253885
2500.686710.6265810.31329
2510.6947940.6104120.305206
2520.6561450.687710.343855
2530.69210.6157990.3079
2540.6882740.6234520.311726
2550.7060610.5878780.293939
2560.7815470.4369050.218453
2570.8042970.3914060.195703
2580.8772750.245450.122725
2590.820030.3599390.17997
2600.9514950.09701060.0485053
2610.9214210.1571570.0785786
2620.8988520.2022970.101148
2630.9291650.1416710.0708355
2640.8572950.285410.142705
2650.7758160.4483670.224184
2660.6364450.727110.363555

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.838937 & 0.322127 & 0.161063 \tabularnewline
14 & 0.744107 & 0.511785 & 0.255893 \tabularnewline
15 & 0.622961 & 0.754078 & 0.377039 \tabularnewline
16 & 0.850733 & 0.298533 & 0.149267 \tabularnewline
17 & 0.777962 & 0.444077 & 0.222038 \tabularnewline
18 & 0.720641 & 0.558719 & 0.279359 \tabularnewline
19 & 0.633094 & 0.733813 & 0.366906 \tabularnewline
20 & 0.541264 & 0.917472 & 0.458736 \tabularnewline
21 & 0.461336 & 0.922672 & 0.538664 \tabularnewline
22 & 0.675858 & 0.648284 & 0.324142 \tabularnewline
23 & 0.674579 & 0.650843 & 0.325421 \tabularnewline
24 & 0.60147 & 0.79706 & 0.39853 \tabularnewline
25 & 0.531311 & 0.937378 & 0.468689 \tabularnewline
26 & 0.474962 & 0.949925 & 0.525038 \tabularnewline
27 & 0.438622 & 0.877244 & 0.561378 \tabularnewline
28 & 0.527995 & 0.944011 & 0.472005 \tabularnewline
29 & 0.495035 & 0.99007 & 0.504965 \tabularnewline
30 & 0.432045 & 0.864089 & 0.567955 \tabularnewline
31 & 0.462489 & 0.924977 & 0.537511 \tabularnewline
32 & 0.409161 & 0.818321 & 0.590839 \tabularnewline
33 & 0.393369 & 0.786737 & 0.606631 \tabularnewline
34 & 0.346903 & 0.693806 & 0.653097 \tabularnewline
35 & 0.301068 & 0.602136 & 0.698932 \tabularnewline
36 & 0.254708 & 0.509416 & 0.745292 \tabularnewline
37 & 0.209946 & 0.419891 & 0.790054 \tabularnewline
38 & 0.461811 & 0.923622 & 0.538189 \tabularnewline
39 & 0.44461 & 0.889219 & 0.55539 \tabularnewline
40 & 0.434515 & 0.869031 & 0.565485 \tabularnewline
41 & 0.562433 & 0.875135 & 0.437567 \tabularnewline
42 & 0.512692 & 0.974616 & 0.487308 \tabularnewline
43 & 0.472878 & 0.945755 & 0.527122 \tabularnewline
44 & 0.43885 & 0.877701 & 0.56115 \tabularnewline
45 & 0.48073 & 0.961461 & 0.51927 \tabularnewline
46 & 0.441278 & 0.882556 & 0.558722 \tabularnewline
47 & 0.41845 & 0.836901 & 0.58155 \tabularnewline
48 & 0.393935 & 0.78787 & 0.606065 \tabularnewline
49 & 0.380015 & 0.76003 & 0.619985 \tabularnewline
50 & 0.411257 & 0.822514 & 0.588743 \tabularnewline
51 & 0.373303 & 0.746605 & 0.626697 \tabularnewline
52 & 0.366947 & 0.733895 & 0.633053 \tabularnewline
53 & 0.328549 & 0.657097 & 0.671451 \tabularnewline
54 & 0.331856 & 0.663712 & 0.668144 \tabularnewline
55 & 0.395351 & 0.790703 & 0.604649 \tabularnewline
56 & 0.355778 & 0.711557 & 0.644222 \tabularnewline
57 & 0.534828 & 0.930345 & 0.465172 \tabularnewline
58 & 0.606524 & 0.786953 & 0.393476 \tabularnewline
59 & 0.564529 & 0.870942 & 0.435471 \tabularnewline
60 & 0.560048 & 0.879905 & 0.439952 \tabularnewline
61 & 0.613778 & 0.772445 & 0.386222 \tabularnewline
62 & 0.587436 & 0.825128 & 0.412564 \tabularnewline
63 & 0.639743 & 0.720513 & 0.360257 \tabularnewline
64 & 0.683025 & 0.63395 & 0.316975 \tabularnewline
65 & 0.68784 & 0.624319 & 0.31216 \tabularnewline
66 & 0.655017 & 0.689967 & 0.344983 \tabularnewline
67 & 0.638556 & 0.722887 & 0.361444 \tabularnewline
68 & 0.621291 & 0.757418 & 0.378709 \tabularnewline
69 & 0.658657 & 0.682685 & 0.341343 \tabularnewline
70 & 0.637887 & 0.724225 & 0.362113 \tabularnewline
71 & 0.60538 & 0.789239 & 0.39462 \tabularnewline
72 & 0.569171 & 0.861659 & 0.430829 \tabularnewline
73 & 0.539449 & 0.921102 & 0.460551 \tabularnewline
74 & 0.588061 & 0.823879 & 0.411939 \tabularnewline
75 & 0.55651 & 0.886979 & 0.44349 \tabularnewline
76 & 0.527773 & 0.944455 & 0.472227 \tabularnewline
77 & 0.508942 & 0.982116 & 0.491058 \tabularnewline
78 & 0.488842 & 0.977684 & 0.511158 \tabularnewline
79 & 0.454336 & 0.908671 & 0.545664 \tabularnewline
80 & 0.493998 & 0.987996 & 0.506002 \tabularnewline
81 & 0.454668 & 0.909336 & 0.545332 \tabularnewline
82 & 0.501079 & 0.997841 & 0.498921 \tabularnewline
83 & 0.463581 & 0.927163 & 0.536419 \tabularnewline
84 & 0.618838 & 0.762324 & 0.381162 \tabularnewline
85 & 0.582637 & 0.834726 & 0.417363 \tabularnewline
86 & 0.550213 & 0.899573 & 0.449787 \tabularnewline
87 & 0.545843 & 0.908314 & 0.454157 \tabularnewline
88 & 0.542542 & 0.914916 & 0.457458 \tabularnewline
89 & 0.528264 & 0.943472 & 0.471736 \tabularnewline
90 & 0.515648 & 0.968704 & 0.484352 \tabularnewline
91 & 0.571269 & 0.857462 & 0.428731 \tabularnewline
92 & 0.679047 & 0.641906 & 0.320953 \tabularnewline
93 & 0.65904 & 0.681921 & 0.34096 \tabularnewline
94 & 0.636358 & 0.727284 & 0.363642 \tabularnewline
95 & 0.624794 & 0.750413 & 0.375206 \tabularnewline
96 & 0.598122 & 0.803757 & 0.401878 \tabularnewline
97 & 0.642339 & 0.715322 & 0.357661 \tabularnewline
98 & 0.626604 & 0.746792 & 0.373396 \tabularnewline
99 & 0.660257 & 0.679486 & 0.339743 \tabularnewline
100 & 0.668387 & 0.663227 & 0.331613 \tabularnewline
101 & 0.652608 & 0.694785 & 0.347392 \tabularnewline
102 & 0.618727 & 0.762546 & 0.381273 \tabularnewline
103 & 0.602363 & 0.795274 & 0.397637 \tabularnewline
104 & 0.573582 & 0.852836 & 0.426418 \tabularnewline
105 & 0.660023 & 0.679955 & 0.339977 \tabularnewline
106 & 0.63468 & 0.730641 & 0.36532 \tabularnewline
107 & 0.691174 & 0.617653 & 0.308826 \tabularnewline
108 & 0.786379 & 0.427243 & 0.213621 \tabularnewline
109 & 0.78995 & 0.4201 & 0.21005 \tabularnewline
110 & 0.777239 & 0.445523 & 0.222761 \tabularnewline
111 & 0.760378 & 0.479244 & 0.239622 \tabularnewline
112 & 0.732685 & 0.53463 & 0.267315 \tabularnewline
113 & 0.80873 & 0.382539 & 0.19127 \tabularnewline
114 & 0.832616 & 0.334767 & 0.167384 \tabularnewline
115 & 0.904443 & 0.191115 & 0.0955574 \tabularnewline
116 & 0.917658 & 0.164685 & 0.0823424 \tabularnewline
117 & 0.905512 & 0.188975 & 0.0944876 \tabularnewline
118 & 0.892671 & 0.214659 & 0.107329 \tabularnewline
119 & 0.880701 & 0.238598 & 0.119299 \tabularnewline
120 & 0.875656 & 0.248689 & 0.124344 \tabularnewline
121 & 0.892875 & 0.21425 & 0.107125 \tabularnewline
122 & 0.882124 & 0.235752 & 0.117876 \tabularnewline
123 & 0.873982 & 0.252037 & 0.126018 \tabularnewline
124 & 0.898281 & 0.203438 & 0.101719 \tabularnewline
125 & 0.909114 & 0.181772 & 0.0908862 \tabularnewline
126 & 0.895211 & 0.209578 & 0.104789 \tabularnewline
127 & 0.888279 & 0.223442 & 0.111721 \tabularnewline
128 & 0.871739 & 0.256523 & 0.128261 \tabularnewline
129 & 0.886176 & 0.227648 & 0.113824 \tabularnewline
130 & 0.869925 & 0.260151 & 0.130075 \tabularnewline
131 & 0.852044 & 0.295913 & 0.147956 \tabularnewline
132 & 0.845675 & 0.30865 & 0.154325 \tabularnewline
133 & 0.826074 & 0.347853 & 0.173926 \tabularnewline
134 & 0.806207 & 0.387586 & 0.193793 \tabularnewline
135 & 0.789349 & 0.421301 & 0.210651 \tabularnewline
136 & 0.765913 & 0.468175 & 0.234087 \tabularnewline
137 & 0.788459 & 0.423082 & 0.211541 \tabularnewline
138 & 0.795931 & 0.408138 & 0.204069 \tabularnewline
139 & 0.777366 & 0.445268 & 0.222634 \tabularnewline
140 & 0.754307 & 0.491386 & 0.245693 \tabularnewline
141 & 0.744345 & 0.511311 & 0.255655 \tabularnewline
142 & 0.762025 & 0.47595 & 0.237975 \tabularnewline
143 & 0.735877 & 0.528247 & 0.264123 \tabularnewline
144 & 0.750566 & 0.498868 & 0.249434 \tabularnewline
145 & 0.722562 & 0.554876 & 0.277438 \tabularnewline
146 & 0.695152 & 0.609697 & 0.304848 \tabularnewline
147 & 0.669086 & 0.661827 & 0.330914 \tabularnewline
148 & 0.637858 & 0.724284 & 0.362142 \tabularnewline
149 & 0.606535 & 0.786929 & 0.393465 \tabularnewline
150 & 0.59552 & 0.80896 & 0.40448 \tabularnewline
151 & 0.807765 & 0.38447 & 0.192235 \tabularnewline
152 & 0.787205 & 0.42559 & 0.212795 \tabularnewline
153 & 0.789128 & 0.421745 & 0.210872 \tabularnewline
154 & 0.762476 & 0.475048 & 0.237524 \tabularnewline
155 & 0.757947 & 0.484107 & 0.242053 \tabularnewline
156 & 0.731192 & 0.537616 & 0.268808 \tabularnewline
157 & 0.714383 & 0.571234 & 0.285617 \tabularnewline
158 & 0.685304 & 0.629393 & 0.314696 \tabularnewline
159 & 0.683547 & 0.632906 & 0.316453 \tabularnewline
160 & 0.667335 & 0.66533 & 0.332665 \tabularnewline
161 & 0.651768 & 0.696463 & 0.348232 \tabularnewline
162 & 0.65664 & 0.68672 & 0.34336 \tabularnewline
163 & 0.631663 & 0.736675 & 0.368337 \tabularnewline
164 & 0.830621 & 0.338758 & 0.169379 \tabularnewline
165 & 0.811317 & 0.377365 & 0.188683 \tabularnewline
166 & 0.799231 & 0.401538 & 0.200769 \tabularnewline
167 & 0.788048 & 0.423904 & 0.211952 \tabularnewline
168 & 0.804513 & 0.390973 & 0.195487 \tabularnewline
169 & 0.778383 & 0.443235 & 0.221617 \tabularnewline
170 & 0.81323 & 0.373541 & 0.18677 \tabularnewline
171 & 0.80347 & 0.393059 & 0.19653 \tabularnewline
172 & 0.807523 & 0.384954 & 0.192477 \tabularnewline
173 & 0.798087 & 0.403826 & 0.201913 \tabularnewline
174 & 0.773594 & 0.452813 & 0.226406 \tabularnewline
175 & 0.74737 & 0.505261 & 0.25263 \tabularnewline
176 & 0.772724 & 0.454551 & 0.227276 \tabularnewline
177 & 0.761241 & 0.477519 & 0.238759 \tabularnewline
178 & 0.766925 & 0.466151 & 0.233075 \tabularnewline
179 & 0.738747 & 0.522507 & 0.261253 \tabularnewline
180 & 0.828468 & 0.343063 & 0.171532 \tabularnewline
181 & 0.850005 & 0.299989 & 0.149995 \tabularnewline
182 & 0.845685 & 0.308629 & 0.154315 \tabularnewline
183 & 0.848532 & 0.302936 & 0.151468 \tabularnewline
184 & 0.8259 & 0.348201 & 0.1741 \tabularnewline
185 & 0.82277 & 0.35446 & 0.17723 \tabularnewline
186 & 0.796928 & 0.406144 & 0.203072 \tabularnewline
187 & 0.815249 & 0.369502 & 0.184751 \tabularnewline
188 & 0.815618 & 0.368765 & 0.184382 \tabularnewline
189 & 0.807613 & 0.384775 & 0.192387 \tabularnewline
190 & 0.783224 & 0.433551 & 0.216776 \tabularnewline
191 & 0.772762 & 0.454476 & 0.227238 \tabularnewline
192 & 0.752737 & 0.494527 & 0.247263 \tabularnewline
193 & 0.756852 & 0.486296 & 0.243148 \tabularnewline
194 & 0.792004 & 0.415992 & 0.207996 \tabularnewline
195 & 0.763399 & 0.473202 & 0.236601 \tabularnewline
196 & 0.748459 & 0.503082 & 0.251541 \tabularnewline
197 & 0.772457 & 0.455086 & 0.227543 \tabularnewline
198 & 0.743002 & 0.513996 & 0.256998 \tabularnewline
199 & 0.729872 & 0.540256 & 0.270128 \tabularnewline
200 & 0.701722 & 0.596557 & 0.298278 \tabularnewline
201 & 0.680414 & 0.639173 & 0.319586 \tabularnewline
202 & 0.655184 & 0.689632 & 0.344816 \tabularnewline
203 & 0.672917 & 0.654167 & 0.327083 \tabularnewline
204 & 0.637187 & 0.725625 & 0.362813 \tabularnewline
205 & 0.607 & 0.786001 & 0.393 \tabularnewline
206 & 0.633353 & 0.733294 & 0.366647 \tabularnewline
207 & 0.607239 & 0.785523 & 0.392761 \tabularnewline
208 & 0.582115 & 0.83577 & 0.417885 \tabularnewline
209 & 0.574448 & 0.851104 & 0.425552 \tabularnewline
210 & 0.587891 & 0.824219 & 0.412109 \tabularnewline
211 & 0.559534 & 0.880931 & 0.440466 \tabularnewline
212 & 0.517788 & 0.964423 & 0.482212 \tabularnewline
213 & 0.59038 & 0.81924 & 0.40962 \tabularnewline
214 & 0.581898 & 0.836204 & 0.418102 \tabularnewline
215 & 0.561761 & 0.876478 & 0.438239 \tabularnewline
216 & 0.523915 & 0.95217 & 0.476085 \tabularnewline
217 & 0.547259 & 0.905482 & 0.452741 \tabularnewline
218 & 0.526296 & 0.947407 & 0.473704 \tabularnewline
219 & 0.48816 & 0.976321 & 0.51184 \tabularnewline
220 & 0.443463 & 0.886927 & 0.556537 \tabularnewline
221 & 0.430437 & 0.860874 & 0.569563 \tabularnewline
222 & 0.498855 & 0.997711 & 0.501145 \tabularnewline
223 & 0.460363 & 0.920727 & 0.539637 \tabularnewline
224 & 0.508108 & 0.983783 & 0.491892 \tabularnewline
225 & 0.488269 & 0.976537 & 0.511731 \tabularnewline
226 & 0.538627 & 0.922746 & 0.461373 \tabularnewline
227 & 0.544329 & 0.911343 & 0.455671 \tabularnewline
228 & 0.626536 & 0.746927 & 0.373464 \tabularnewline
229 & 0.635845 & 0.72831 & 0.364155 \tabularnewline
230 & 0.664447 & 0.671105 & 0.335553 \tabularnewline
231 & 0.663578 & 0.672843 & 0.336422 \tabularnewline
232 & 0.621279 & 0.757442 & 0.378721 \tabularnewline
233 & 0.608324 & 0.783351 & 0.391676 \tabularnewline
234 & 0.570828 & 0.858343 & 0.429172 \tabularnewline
235 & 0.533843 & 0.932313 & 0.466157 \tabularnewline
236 & 0.860047 & 0.279906 & 0.139953 \tabularnewline
237 & 0.839942 & 0.320117 & 0.160058 \tabularnewline
238 & 0.809308 & 0.381383 & 0.190692 \tabularnewline
239 & 0.775869 & 0.448262 & 0.224131 \tabularnewline
240 & 0.732529 & 0.534942 & 0.267471 \tabularnewline
241 & 0.758306 & 0.483388 & 0.241694 \tabularnewline
242 & 0.724125 & 0.551749 & 0.275875 \tabularnewline
243 & 0.71324 & 0.57352 & 0.28676 \tabularnewline
244 & 0.662343 & 0.675314 & 0.337657 \tabularnewline
245 & 0.633498 & 0.733003 & 0.366502 \tabularnewline
246 & 0.592949 & 0.814103 & 0.407051 \tabularnewline
247 & 0.611898 & 0.776205 & 0.388102 \tabularnewline
248 & 0.758845 & 0.482311 & 0.241155 \tabularnewline
249 & 0.746115 & 0.507769 & 0.253885 \tabularnewline
250 & 0.68671 & 0.626581 & 0.31329 \tabularnewline
251 & 0.694794 & 0.610412 & 0.305206 \tabularnewline
252 & 0.656145 & 0.68771 & 0.343855 \tabularnewline
253 & 0.6921 & 0.615799 & 0.3079 \tabularnewline
254 & 0.688274 & 0.623452 & 0.311726 \tabularnewline
255 & 0.706061 & 0.587878 & 0.293939 \tabularnewline
256 & 0.781547 & 0.436905 & 0.218453 \tabularnewline
257 & 0.804297 & 0.391406 & 0.195703 \tabularnewline
258 & 0.877275 & 0.24545 & 0.122725 \tabularnewline
259 & 0.82003 & 0.359939 & 0.17997 \tabularnewline
260 & 0.951495 & 0.0970106 & 0.0485053 \tabularnewline
261 & 0.921421 & 0.157157 & 0.0785786 \tabularnewline
262 & 0.898852 & 0.202297 & 0.101148 \tabularnewline
263 & 0.929165 & 0.141671 & 0.0708355 \tabularnewline
264 & 0.857295 & 0.28541 & 0.142705 \tabularnewline
265 & 0.775816 & 0.448367 & 0.224184 \tabularnewline
266 & 0.636445 & 0.72711 & 0.363555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&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]0.838937[/C][C]0.322127[/C][C]0.161063[/C][/ROW]
[ROW][C]14[/C][C]0.744107[/C][C]0.511785[/C][C]0.255893[/C][/ROW]
[ROW][C]15[/C][C]0.622961[/C][C]0.754078[/C][C]0.377039[/C][/ROW]
[ROW][C]16[/C][C]0.850733[/C][C]0.298533[/C][C]0.149267[/C][/ROW]
[ROW][C]17[/C][C]0.777962[/C][C]0.444077[/C][C]0.222038[/C][/ROW]
[ROW][C]18[/C][C]0.720641[/C][C]0.558719[/C][C]0.279359[/C][/ROW]
[ROW][C]19[/C][C]0.633094[/C][C]0.733813[/C][C]0.366906[/C][/ROW]
[ROW][C]20[/C][C]0.541264[/C][C]0.917472[/C][C]0.458736[/C][/ROW]
[ROW][C]21[/C][C]0.461336[/C][C]0.922672[/C][C]0.538664[/C][/ROW]
[ROW][C]22[/C][C]0.675858[/C][C]0.648284[/C][C]0.324142[/C][/ROW]
[ROW][C]23[/C][C]0.674579[/C][C]0.650843[/C][C]0.325421[/C][/ROW]
[ROW][C]24[/C][C]0.60147[/C][C]0.79706[/C][C]0.39853[/C][/ROW]
[ROW][C]25[/C][C]0.531311[/C][C]0.937378[/C][C]0.468689[/C][/ROW]
[ROW][C]26[/C][C]0.474962[/C][C]0.949925[/C][C]0.525038[/C][/ROW]
[ROW][C]27[/C][C]0.438622[/C][C]0.877244[/C][C]0.561378[/C][/ROW]
[ROW][C]28[/C][C]0.527995[/C][C]0.944011[/C][C]0.472005[/C][/ROW]
[ROW][C]29[/C][C]0.495035[/C][C]0.99007[/C][C]0.504965[/C][/ROW]
[ROW][C]30[/C][C]0.432045[/C][C]0.864089[/C][C]0.567955[/C][/ROW]
[ROW][C]31[/C][C]0.462489[/C][C]0.924977[/C][C]0.537511[/C][/ROW]
[ROW][C]32[/C][C]0.409161[/C][C]0.818321[/C][C]0.590839[/C][/ROW]
[ROW][C]33[/C][C]0.393369[/C][C]0.786737[/C][C]0.606631[/C][/ROW]
[ROW][C]34[/C][C]0.346903[/C][C]0.693806[/C][C]0.653097[/C][/ROW]
[ROW][C]35[/C][C]0.301068[/C][C]0.602136[/C][C]0.698932[/C][/ROW]
[ROW][C]36[/C][C]0.254708[/C][C]0.509416[/C][C]0.745292[/C][/ROW]
[ROW][C]37[/C][C]0.209946[/C][C]0.419891[/C][C]0.790054[/C][/ROW]
[ROW][C]38[/C][C]0.461811[/C][C]0.923622[/C][C]0.538189[/C][/ROW]
[ROW][C]39[/C][C]0.44461[/C][C]0.889219[/C][C]0.55539[/C][/ROW]
[ROW][C]40[/C][C]0.434515[/C][C]0.869031[/C][C]0.565485[/C][/ROW]
[ROW][C]41[/C][C]0.562433[/C][C]0.875135[/C][C]0.437567[/C][/ROW]
[ROW][C]42[/C][C]0.512692[/C][C]0.974616[/C][C]0.487308[/C][/ROW]
[ROW][C]43[/C][C]0.472878[/C][C]0.945755[/C][C]0.527122[/C][/ROW]
[ROW][C]44[/C][C]0.43885[/C][C]0.877701[/C][C]0.56115[/C][/ROW]
[ROW][C]45[/C][C]0.48073[/C][C]0.961461[/C][C]0.51927[/C][/ROW]
[ROW][C]46[/C][C]0.441278[/C][C]0.882556[/C][C]0.558722[/C][/ROW]
[ROW][C]47[/C][C]0.41845[/C][C]0.836901[/C][C]0.58155[/C][/ROW]
[ROW][C]48[/C][C]0.393935[/C][C]0.78787[/C][C]0.606065[/C][/ROW]
[ROW][C]49[/C][C]0.380015[/C][C]0.76003[/C][C]0.619985[/C][/ROW]
[ROW][C]50[/C][C]0.411257[/C][C]0.822514[/C][C]0.588743[/C][/ROW]
[ROW][C]51[/C][C]0.373303[/C][C]0.746605[/C][C]0.626697[/C][/ROW]
[ROW][C]52[/C][C]0.366947[/C][C]0.733895[/C][C]0.633053[/C][/ROW]
[ROW][C]53[/C][C]0.328549[/C][C]0.657097[/C][C]0.671451[/C][/ROW]
[ROW][C]54[/C][C]0.331856[/C][C]0.663712[/C][C]0.668144[/C][/ROW]
[ROW][C]55[/C][C]0.395351[/C][C]0.790703[/C][C]0.604649[/C][/ROW]
[ROW][C]56[/C][C]0.355778[/C][C]0.711557[/C][C]0.644222[/C][/ROW]
[ROW][C]57[/C][C]0.534828[/C][C]0.930345[/C][C]0.465172[/C][/ROW]
[ROW][C]58[/C][C]0.606524[/C][C]0.786953[/C][C]0.393476[/C][/ROW]
[ROW][C]59[/C][C]0.564529[/C][C]0.870942[/C][C]0.435471[/C][/ROW]
[ROW][C]60[/C][C]0.560048[/C][C]0.879905[/C][C]0.439952[/C][/ROW]
[ROW][C]61[/C][C]0.613778[/C][C]0.772445[/C][C]0.386222[/C][/ROW]
[ROW][C]62[/C][C]0.587436[/C][C]0.825128[/C][C]0.412564[/C][/ROW]
[ROW][C]63[/C][C]0.639743[/C][C]0.720513[/C][C]0.360257[/C][/ROW]
[ROW][C]64[/C][C]0.683025[/C][C]0.63395[/C][C]0.316975[/C][/ROW]
[ROW][C]65[/C][C]0.68784[/C][C]0.624319[/C][C]0.31216[/C][/ROW]
[ROW][C]66[/C][C]0.655017[/C][C]0.689967[/C][C]0.344983[/C][/ROW]
[ROW][C]67[/C][C]0.638556[/C][C]0.722887[/C][C]0.361444[/C][/ROW]
[ROW][C]68[/C][C]0.621291[/C][C]0.757418[/C][C]0.378709[/C][/ROW]
[ROW][C]69[/C][C]0.658657[/C][C]0.682685[/C][C]0.341343[/C][/ROW]
[ROW][C]70[/C][C]0.637887[/C][C]0.724225[/C][C]0.362113[/C][/ROW]
[ROW][C]71[/C][C]0.60538[/C][C]0.789239[/C][C]0.39462[/C][/ROW]
[ROW][C]72[/C][C]0.569171[/C][C]0.861659[/C][C]0.430829[/C][/ROW]
[ROW][C]73[/C][C]0.539449[/C][C]0.921102[/C][C]0.460551[/C][/ROW]
[ROW][C]74[/C][C]0.588061[/C][C]0.823879[/C][C]0.411939[/C][/ROW]
[ROW][C]75[/C][C]0.55651[/C][C]0.886979[/C][C]0.44349[/C][/ROW]
[ROW][C]76[/C][C]0.527773[/C][C]0.944455[/C][C]0.472227[/C][/ROW]
[ROW][C]77[/C][C]0.508942[/C][C]0.982116[/C][C]0.491058[/C][/ROW]
[ROW][C]78[/C][C]0.488842[/C][C]0.977684[/C][C]0.511158[/C][/ROW]
[ROW][C]79[/C][C]0.454336[/C][C]0.908671[/C][C]0.545664[/C][/ROW]
[ROW][C]80[/C][C]0.493998[/C][C]0.987996[/C][C]0.506002[/C][/ROW]
[ROW][C]81[/C][C]0.454668[/C][C]0.909336[/C][C]0.545332[/C][/ROW]
[ROW][C]82[/C][C]0.501079[/C][C]0.997841[/C][C]0.498921[/C][/ROW]
[ROW][C]83[/C][C]0.463581[/C][C]0.927163[/C][C]0.536419[/C][/ROW]
[ROW][C]84[/C][C]0.618838[/C][C]0.762324[/C][C]0.381162[/C][/ROW]
[ROW][C]85[/C][C]0.582637[/C][C]0.834726[/C][C]0.417363[/C][/ROW]
[ROW][C]86[/C][C]0.550213[/C][C]0.899573[/C][C]0.449787[/C][/ROW]
[ROW][C]87[/C][C]0.545843[/C][C]0.908314[/C][C]0.454157[/C][/ROW]
[ROW][C]88[/C][C]0.542542[/C][C]0.914916[/C][C]0.457458[/C][/ROW]
[ROW][C]89[/C][C]0.528264[/C][C]0.943472[/C][C]0.471736[/C][/ROW]
[ROW][C]90[/C][C]0.515648[/C][C]0.968704[/C][C]0.484352[/C][/ROW]
[ROW][C]91[/C][C]0.571269[/C][C]0.857462[/C][C]0.428731[/C][/ROW]
[ROW][C]92[/C][C]0.679047[/C][C]0.641906[/C][C]0.320953[/C][/ROW]
[ROW][C]93[/C][C]0.65904[/C][C]0.681921[/C][C]0.34096[/C][/ROW]
[ROW][C]94[/C][C]0.636358[/C][C]0.727284[/C][C]0.363642[/C][/ROW]
[ROW][C]95[/C][C]0.624794[/C][C]0.750413[/C][C]0.375206[/C][/ROW]
[ROW][C]96[/C][C]0.598122[/C][C]0.803757[/C][C]0.401878[/C][/ROW]
[ROW][C]97[/C][C]0.642339[/C][C]0.715322[/C][C]0.357661[/C][/ROW]
[ROW][C]98[/C][C]0.626604[/C][C]0.746792[/C][C]0.373396[/C][/ROW]
[ROW][C]99[/C][C]0.660257[/C][C]0.679486[/C][C]0.339743[/C][/ROW]
[ROW][C]100[/C][C]0.668387[/C][C]0.663227[/C][C]0.331613[/C][/ROW]
[ROW][C]101[/C][C]0.652608[/C][C]0.694785[/C][C]0.347392[/C][/ROW]
[ROW][C]102[/C][C]0.618727[/C][C]0.762546[/C][C]0.381273[/C][/ROW]
[ROW][C]103[/C][C]0.602363[/C][C]0.795274[/C][C]0.397637[/C][/ROW]
[ROW][C]104[/C][C]0.573582[/C][C]0.852836[/C][C]0.426418[/C][/ROW]
[ROW][C]105[/C][C]0.660023[/C][C]0.679955[/C][C]0.339977[/C][/ROW]
[ROW][C]106[/C][C]0.63468[/C][C]0.730641[/C][C]0.36532[/C][/ROW]
[ROW][C]107[/C][C]0.691174[/C][C]0.617653[/C][C]0.308826[/C][/ROW]
[ROW][C]108[/C][C]0.786379[/C][C]0.427243[/C][C]0.213621[/C][/ROW]
[ROW][C]109[/C][C]0.78995[/C][C]0.4201[/C][C]0.21005[/C][/ROW]
[ROW][C]110[/C][C]0.777239[/C][C]0.445523[/C][C]0.222761[/C][/ROW]
[ROW][C]111[/C][C]0.760378[/C][C]0.479244[/C][C]0.239622[/C][/ROW]
[ROW][C]112[/C][C]0.732685[/C][C]0.53463[/C][C]0.267315[/C][/ROW]
[ROW][C]113[/C][C]0.80873[/C][C]0.382539[/C][C]0.19127[/C][/ROW]
[ROW][C]114[/C][C]0.832616[/C][C]0.334767[/C][C]0.167384[/C][/ROW]
[ROW][C]115[/C][C]0.904443[/C][C]0.191115[/C][C]0.0955574[/C][/ROW]
[ROW][C]116[/C][C]0.917658[/C][C]0.164685[/C][C]0.0823424[/C][/ROW]
[ROW][C]117[/C][C]0.905512[/C][C]0.188975[/C][C]0.0944876[/C][/ROW]
[ROW][C]118[/C][C]0.892671[/C][C]0.214659[/C][C]0.107329[/C][/ROW]
[ROW][C]119[/C][C]0.880701[/C][C]0.238598[/C][C]0.119299[/C][/ROW]
[ROW][C]120[/C][C]0.875656[/C][C]0.248689[/C][C]0.124344[/C][/ROW]
[ROW][C]121[/C][C]0.892875[/C][C]0.21425[/C][C]0.107125[/C][/ROW]
[ROW][C]122[/C][C]0.882124[/C][C]0.235752[/C][C]0.117876[/C][/ROW]
[ROW][C]123[/C][C]0.873982[/C][C]0.252037[/C][C]0.126018[/C][/ROW]
[ROW][C]124[/C][C]0.898281[/C][C]0.203438[/C][C]0.101719[/C][/ROW]
[ROW][C]125[/C][C]0.909114[/C][C]0.181772[/C][C]0.0908862[/C][/ROW]
[ROW][C]126[/C][C]0.895211[/C][C]0.209578[/C][C]0.104789[/C][/ROW]
[ROW][C]127[/C][C]0.888279[/C][C]0.223442[/C][C]0.111721[/C][/ROW]
[ROW][C]128[/C][C]0.871739[/C][C]0.256523[/C][C]0.128261[/C][/ROW]
[ROW][C]129[/C][C]0.886176[/C][C]0.227648[/C][C]0.113824[/C][/ROW]
[ROW][C]130[/C][C]0.869925[/C][C]0.260151[/C][C]0.130075[/C][/ROW]
[ROW][C]131[/C][C]0.852044[/C][C]0.295913[/C][C]0.147956[/C][/ROW]
[ROW][C]132[/C][C]0.845675[/C][C]0.30865[/C][C]0.154325[/C][/ROW]
[ROW][C]133[/C][C]0.826074[/C][C]0.347853[/C][C]0.173926[/C][/ROW]
[ROW][C]134[/C][C]0.806207[/C][C]0.387586[/C][C]0.193793[/C][/ROW]
[ROW][C]135[/C][C]0.789349[/C][C]0.421301[/C][C]0.210651[/C][/ROW]
[ROW][C]136[/C][C]0.765913[/C][C]0.468175[/C][C]0.234087[/C][/ROW]
[ROW][C]137[/C][C]0.788459[/C][C]0.423082[/C][C]0.211541[/C][/ROW]
[ROW][C]138[/C][C]0.795931[/C][C]0.408138[/C][C]0.204069[/C][/ROW]
[ROW][C]139[/C][C]0.777366[/C][C]0.445268[/C][C]0.222634[/C][/ROW]
[ROW][C]140[/C][C]0.754307[/C][C]0.491386[/C][C]0.245693[/C][/ROW]
[ROW][C]141[/C][C]0.744345[/C][C]0.511311[/C][C]0.255655[/C][/ROW]
[ROW][C]142[/C][C]0.762025[/C][C]0.47595[/C][C]0.237975[/C][/ROW]
[ROW][C]143[/C][C]0.735877[/C][C]0.528247[/C][C]0.264123[/C][/ROW]
[ROW][C]144[/C][C]0.750566[/C][C]0.498868[/C][C]0.249434[/C][/ROW]
[ROW][C]145[/C][C]0.722562[/C][C]0.554876[/C][C]0.277438[/C][/ROW]
[ROW][C]146[/C][C]0.695152[/C][C]0.609697[/C][C]0.304848[/C][/ROW]
[ROW][C]147[/C][C]0.669086[/C][C]0.661827[/C][C]0.330914[/C][/ROW]
[ROW][C]148[/C][C]0.637858[/C][C]0.724284[/C][C]0.362142[/C][/ROW]
[ROW][C]149[/C][C]0.606535[/C][C]0.786929[/C][C]0.393465[/C][/ROW]
[ROW][C]150[/C][C]0.59552[/C][C]0.80896[/C][C]0.40448[/C][/ROW]
[ROW][C]151[/C][C]0.807765[/C][C]0.38447[/C][C]0.192235[/C][/ROW]
[ROW][C]152[/C][C]0.787205[/C][C]0.42559[/C][C]0.212795[/C][/ROW]
[ROW][C]153[/C][C]0.789128[/C][C]0.421745[/C][C]0.210872[/C][/ROW]
[ROW][C]154[/C][C]0.762476[/C][C]0.475048[/C][C]0.237524[/C][/ROW]
[ROW][C]155[/C][C]0.757947[/C][C]0.484107[/C][C]0.242053[/C][/ROW]
[ROW][C]156[/C][C]0.731192[/C][C]0.537616[/C][C]0.268808[/C][/ROW]
[ROW][C]157[/C][C]0.714383[/C][C]0.571234[/C][C]0.285617[/C][/ROW]
[ROW][C]158[/C][C]0.685304[/C][C]0.629393[/C][C]0.314696[/C][/ROW]
[ROW][C]159[/C][C]0.683547[/C][C]0.632906[/C][C]0.316453[/C][/ROW]
[ROW][C]160[/C][C]0.667335[/C][C]0.66533[/C][C]0.332665[/C][/ROW]
[ROW][C]161[/C][C]0.651768[/C][C]0.696463[/C][C]0.348232[/C][/ROW]
[ROW][C]162[/C][C]0.65664[/C][C]0.68672[/C][C]0.34336[/C][/ROW]
[ROW][C]163[/C][C]0.631663[/C][C]0.736675[/C][C]0.368337[/C][/ROW]
[ROW][C]164[/C][C]0.830621[/C][C]0.338758[/C][C]0.169379[/C][/ROW]
[ROW][C]165[/C][C]0.811317[/C][C]0.377365[/C][C]0.188683[/C][/ROW]
[ROW][C]166[/C][C]0.799231[/C][C]0.401538[/C][C]0.200769[/C][/ROW]
[ROW][C]167[/C][C]0.788048[/C][C]0.423904[/C][C]0.211952[/C][/ROW]
[ROW][C]168[/C][C]0.804513[/C][C]0.390973[/C][C]0.195487[/C][/ROW]
[ROW][C]169[/C][C]0.778383[/C][C]0.443235[/C][C]0.221617[/C][/ROW]
[ROW][C]170[/C][C]0.81323[/C][C]0.373541[/C][C]0.18677[/C][/ROW]
[ROW][C]171[/C][C]0.80347[/C][C]0.393059[/C][C]0.19653[/C][/ROW]
[ROW][C]172[/C][C]0.807523[/C][C]0.384954[/C][C]0.192477[/C][/ROW]
[ROW][C]173[/C][C]0.798087[/C][C]0.403826[/C][C]0.201913[/C][/ROW]
[ROW][C]174[/C][C]0.773594[/C][C]0.452813[/C][C]0.226406[/C][/ROW]
[ROW][C]175[/C][C]0.74737[/C][C]0.505261[/C][C]0.25263[/C][/ROW]
[ROW][C]176[/C][C]0.772724[/C][C]0.454551[/C][C]0.227276[/C][/ROW]
[ROW][C]177[/C][C]0.761241[/C][C]0.477519[/C][C]0.238759[/C][/ROW]
[ROW][C]178[/C][C]0.766925[/C][C]0.466151[/C][C]0.233075[/C][/ROW]
[ROW][C]179[/C][C]0.738747[/C][C]0.522507[/C][C]0.261253[/C][/ROW]
[ROW][C]180[/C][C]0.828468[/C][C]0.343063[/C][C]0.171532[/C][/ROW]
[ROW][C]181[/C][C]0.850005[/C][C]0.299989[/C][C]0.149995[/C][/ROW]
[ROW][C]182[/C][C]0.845685[/C][C]0.308629[/C][C]0.154315[/C][/ROW]
[ROW][C]183[/C][C]0.848532[/C][C]0.302936[/C][C]0.151468[/C][/ROW]
[ROW][C]184[/C][C]0.8259[/C][C]0.348201[/C][C]0.1741[/C][/ROW]
[ROW][C]185[/C][C]0.82277[/C][C]0.35446[/C][C]0.17723[/C][/ROW]
[ROW][C]186[/C][C]0.796928[/C][C]0.406144[/C][C]0.203072[/C][/ROW]
[ROW][C]187[/C][C]0.815249[/C][C]0.369502[/C][C]0.184751[/C][/ROW]
[ROW][C]188[/C][C]0.815618[/C][C]0.368765[/C][C]0.184382[/C][/ROW]
[ROW][C]189[/C][C]0.807613[/C][C]0.384775[/C][C]0.192387[/C][/ROW]
[ROW][C]190[/C][C]0.783224[/C][C]0.433551[/C][C]0.216776[/C][/ROW]
[ROW][C]191[/C][C]0.772762[/C][C]0.454476[/C][C]0.227238[/C][/ROW]
[ROW][C]192[/C][C]0.752737[/C][C]0.494527[/C][C]0.247263[/C][/ROW]
[ROW][C]193[/C][C]0.756852[/C][C]0.486296[/C][C]0.243148[/C][/ROW]
[ROW][C]194[/C][C]0.792004[/C][C]0.415992[/C][C]0.207996[/C][/ROW]
[ROW][C]195[/C][C]0.763399[/C][C]0.473202[/C][C]0.236601[/C][/ROW]
[ROW][C]196[/C][C]0.748459[/C][C]0.503082[/C][C]0.251541[/C][/ROW]
[ROW][C]197[/C][C]0.772457[/C][C]0.455086[/C][C]0.227543[/C][/ROW]
[ROW][C]198[/C][C]0.743002[/C][C]0.513996[/C][C]0.256998[/C][/ROW]
[ROW][C]199[/C][C]0.729872[/C][C]0.540256[/C][C]0.270128[/C][/ROW]
[ROW][C]200[/C][C]0.701722[/C][C]0.596557[/C][C]0.298278[/C][/ROW]
[ROW][C]201[/C][C]0.680414[/C][C]0.639173[/C][C]0.319586[/C][/ROW]
[ROW][C]202[/C][C]0.655184[/C][C]0.689632[/C][C]0.344816[/C][/ROW]
[ROW][C]203[/C][C]0.672917[/C][C]0.654167[/C][C]0.327083[/C][/ROW]
[ROW][C]204[/C][C]0.637187[/C][C]0.725625[/C][C]0.362813[/C][/ROW]
[ROW][C]205[/C][C]0.607[/C][C]0.786001[/C][C]0.393[/C][/ROW]
[ROW][C]206[/C][C]0.633353[/C][C]0.733294[/C][C]0.366647[/C][/ROW]
[ROW][C]207[/C][C]0.607239[/C][C]0.785523[/C][C]0.392761[/C][/ROW]
[ROW][C]208[/C][C]0.582115[/C][C]0.83577[/C][C]0.417885[/C][/ROW]
[ROW][C]209[/C][C]0.574448[/C][C]0.851104[/C][C]0.425552[/C][/ROW]
[ROW][C]210[/C][C]0.587891[/C][C]0.824219[/C][C]0.412109[/C][/ROW]
[ROW][C]211[/C][C]0.559534[/C][C]0.880931[/C][C]0.440466[/C][/ROW]
[ROW][C]212[/C][C]0.517788[/C][C]0.964423[/C][C]0.482212[/C][/ROW]
[ROW][C]213[/C][C]0.59038[/C][C]0.81924[/C][C]0.40962[/C][/ROW]
[ROW][C]214[/C][C]0.581898[/C][C]0.836204[/C][C]0.418102[/C][/ROW]
[ROW][C]215[/C][C]0.561761[/C][C]0.876478[/C][C]0.438239[/C][/ROW]
[ROW][C]216[/C][C]0.523915[/C][C]0.95217[/C][C]0.476085[/C][/ROW]
[ROW][C]217[/C][C]0.547259[/C][C]0.905482[/C][C]0.452741[/C][/ROW]
[ROW][C]218[/C][C]0.526296[/C][C]0.947407[/C][C]0.473704[/C][/ROW]
[ROW][C]219[/C][C]0.48816[/C][C]0.976321[/C][C]0.51184[/C][/ROW]
[ROW][C]220[/C][C]0.443463[/C][C]0.886927[/C][C]0.556537[/C][/ROW]
[ROW][C]221[/C][C]0.430437[/C][C]0.860874[/C][C]0.569563[/C][/ROW]
[ROW][C]222[/C][C]0.498855[/C][C]0.997711[/C][C]0.501145[/C][/ROW]
[ROW][C]223[/C][C]0.460363[/C][C]0.920727[/C][C]0.539637[/C][/ROW]
[ROW][C]224[/C][C]0.508108[/C][C]0.983783[/C][C]0.491892[/C][/ROW]
[ROW][C]225[/C][C]0.488269[/C][C]0.976537[/C][C]0.511731[/C][/ROW]
[ROW][C]226[/C][C]0.538627[/C][C]0.922746[/C][C]0.461373[/C][/ROW]
[ROW][C]227[/C][C]0.544329[/C][C]0.911343[/C][C]0.455671[/C][/ROW]
[ROW][C]228[/C][C]0.626536[/C][C]0.746927[/C][C]0.373464[/C][/ROW]
[ROW][C]229[/C][C]0.635845[/C][C]0.72831[/C][C]0.364155[/C][/ROW]
[ROW][C]230[/C][C]0.664447[/C][C]0.671105[/C][C]0.335553[/C][/ROW]
[ROW][C]231[/C][C]0.663578[/C][C]0.672843[/C][C]0.336422[/C][/ROW]
[ROW][C]232[/C][C]0.621279[/C][C]0.757442[/C][C]0.378721[/C][/ROW]
[ROW][C]233[/C][C]0.608324[/C][C]0.783351[/C][C]0.391676[/C][/ROW]
[ROW][C]234[/C][C]0.570828[/C][C]0.858343[/C][C]0.429172[/C][/ROW]
[ROW][C]235[/C][C]0.533843[/C][C]0.932313[/C][C]0.466157[/C][/ROW]
[ROW][C]236[/C][C]0.860047[/C][C]0.279906[/C][C]0.139953[/C][/ROW]
[ROW][C]237[/C][C]0.839942[/C][C]0.320117[/C][C]0.160058[/C][/ROW]
[ROW][C]238[/C][C]0.809308[/C][C]0.381383[/C][C]0.190692[/C][/ROW]
[ROW][C]239[/C][C]0.775869[/C][C]0.448262[/C][C]0.224131[/C][/ROW]
[ROW][C]240[/C][C]0.732529[/C][C]0.534942[/C][C]0.267471[/C][/ROW]
[ROW][C]241[/C][C]0.758306[/C][C]0.483388[/C][C]0.241694[/C][/ROW]
[ROW][C]242[/C][C]0.724125[/C][C]0.551749[/C][C]0.275875[/C][/ROW]
[ROW][C]243[/C][C]0.71324[/C][C]0.57352[/C][C]0.28676[/C][/ROW]
[ROW][C]244[/C][C]0.662343[/C][C]0.675314[/C][C]0.337657[/C][/ROW]
[ROW][C]245[/C][C]0.633498[/C][C]0.733003[/C][C]0.366502[/C][/ROW]
[ROW][C]246[/C][C]0.592949[/C][C]0.814103[/C][C]0.407051[/C][/ROW]
[ROW][C]247[/C][C]0.611898[/C][C]0.776205[/C][C]0.388102[/C][/ROW]
[ROW][C]248[/C][C]0.758845[/C][C]0.482311[/C][C]0.241155[/C][/ROW]
[ROW][C]249[/C][C]0.746115[/C][C]0.507769[/C][C]0.253885[/C][/ROW]
[ROW][C]250[/C][C]0.68671[/C][C]0.626581[/C][C]0.31329[/C][/ROW]
[ROW][C]251[/C][C]0.694794[/C][C]0.610412[/C][C]0.305206[/C][/ROW]
[ROW][C]252[/C][C]0.656145[/C][C]0.68771[/C][C]0.343855[/C][/ROW]
[ROW][C]253[/C][C]0.6921[/C][C]0.615799[/C][C]0.3079[/C][/ROW]
[ROW][C]254[/C][C]0.688274[/C][C]0.623452[/C][C]0.311726[/C][/ROW]
[ROW][C]255[/C][C]0.706061[/C][C]0.587878[/C][C]0.293939[/C][/ROW]
[ROW][C]256[/C][C]0.781547[/C][C]0.436905[/C][C]0.218453[/C][/ROW]
[ROW][C]257[/C][C]0.804297[/C][C]0.391406[/C][C]0.195703[/C][/ROW]
[ROW][C]258[/C][C]0.877275[/C][C]0.24545[/C][C]0.122725[/C][/ROW]
[ROW][C]259[/C][C]0.82003[/C][C]0.359939[/C][C]0.17997[/C][/ROW]
[ROW][C]260[/C][C]0.951495[/C][C]0.0970106[/C][C]0.0485053[/C][/ROW]
[ROW][C]261[/C][C]0.921421[/C][C]0.157157[/C][C]0.0785786[/C][/ROW]
[ROW][C]262[/C][C]0.898852[/C][C]0.202297[/C][C]0.101148[/C][/ROW]
[ROW][C]263[/C][C]0.929165[/C][C]0.141671[/C][C]0.0708355[/C][/ROW]
[ROW][C]264[/C][C]0.857295[/C][C]0.28541[/C][C]0.142705[/C][/ROW]
[ROW][C]265[/C][C]0.775816[/C][C]0.448367[/C][C]0.224184[/C][/ROW]
[ROW][C]266[/C][C]0.636445[/C][C]0.72711[/C][C]0.363555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&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
130.8389370.3221270.161063
140.7441070.5117850.255893
150.6229610.7540780.377039
160.8507330.2985330.149267
170.7779620.4440770.222038
180.7206410.5587190.279359
190.6330940.7338130.366906
200.5412640.9174720.458736
210.4613360.9226720.538664
220.6758580.6482840.324142
230.6745790.6508430.325421
240.601470.797060.39853
250.5313110.9373780.468689
260.4749620.9499250.525038
270.4386220.8772440.561378
280.5279950.9440110.472005
290.4950350.990070.504965
300.4320450.8640890.567955
310.4624890.9249770.537511
320.4091610.8183210.590839
330.3933690.7867370.606631
340.3469030.6938060.653097
350.3010680.6021360.698932
360.2547080.5094160.745292
370.2099460.4198910.790054
380.4618110.9236220.538189
390.444610.8892190.55539
400.4345150.8690310.565485
410.5624330.8751350.437567
420.5126920.9746160.487308
430.4728780.9457550.527122
440.438850.8777010.56115
450.480730.9614610.51927
460.4412780.8825560.558722
470.418450.8369010.58155
480.3939350.787870.606065
490.3800150.760030.619985
500.4112570.8225140.588743
510.3733030.7466050.626697
520.3669470.7338950.633053
530.3285490.6570970.671451
540.3318560.6637120.668144
550.3953510.7907030.604649
560.3557780.7115570.644222
570.5348280.9303450.465172
580.6065240.7869530.393476
590.5645290.8709420.435471
600.5600480.8799050.439952
610.6137780.7724450.386222
620.5874360.8251280.412564
630.6397430.7205130.360257
640.6830250.633950.316975
650.687840.6243190.31216
660.6550170.6899670.344983
670.6385560.7228870.361444
680.6212910.7574180.378709
690.6586570.6826850.341343
700.6378870.7242250.362113
710.605380.7892390.39462
720.5691710.8616590.430829
730.5394490.9211020.460551
740.5880610.8238790.411939
750.556510.8869790.44349
760.5277730.9444550.472227
770.5089420.9821160.491058
780.4888420.9776840.511158
790.4543360.9086710.545664
800.4939980.9879960.506002
810.4546680.9093360.545332
820.5010790.9978410.498921
830.4635810.9271630.536419
840.6188380.7623240.381162
850.5826370.8347260.417363
860.5502130.8995730.449787
870.5458430.9083140.454157
880.5425420.9149160.457458
890.5282640.9434720.471736
900.5156480.9687040.484352
910.5712690.8574620.428731
920.6790470.6419060.320953
930.659040.6819210.34096
940.6363580.7272840.363642
950.6247940.7504130.375206
960.5981220.8037570.401878
970.6423390.7153220.357661
980.6266040.7467920.373396
990.6602570.6794860.339743
1000.6683870.6632270.331613
1010.6526080.6947850.347392
1020.6187270.7625460.381273
1030.6023630.7952740.397637
1040.5735820.8528360.426418
1050.6600230.6799550.339977
1060.634680.7306410.36532
1070.6911740.6176530.308826
1080.7863790.4272430.213621
1090.789950.42010.21005
1100.7772390.4455230.222761
1110.7603780.4792440.239622
1120.7326850.534630.267315
1130.808730.3825390.19127
1140.8326160.3347670.167384
1150.9044430.1911150.0955574
1160.9176580.1646850.0823424
1170.9055120.1889750.0944876
1180.8926710.2146590.107329
1190.8807010.2385980.119299
1200.8756560.2486890.124344
1210.8928750.214250.107125
1220.8821240.2357520.117876
1230.8739820.2520370.126018
1240.8982810.2034380.101719
1250.9091140.1817720.0908862
1260.8952110.2095780.104789
1270.8882790.2234420.111721
1280.8717390.2565230.128261
1290.8861760.2276480.113824
1300.8699250.2601510.130075
1310.8520440.2959130.147956
1320.8456750.308650.154325
1330.8260740.3478530.173926
1340.8062070.3875860.193793
1350.7893490.4213010.210651
1360.7659130.4681750.234087
1370.7884590.4230820.211541
1380.7959310.4081380.204069
1390.7773660.4452680.222634
1400.7543070.4913860.245693
1410.7443450.5113110.255655
1420.7620250.475950.237975
1430.7358770.5282470.264123
1440.7505660.4988680.249434
1450.7225620.5548760.277438
1460.6951520.6096970.304848
1470.6690860.6618270.330914
1480.6378580.7242840.362142
1490.6065350.7869290.393465
1500.595520.808960.40448
1510.8077650.384470.192235
1520.7872050.425590.212795
1530.7891280.4217450.210872
1540.7624760.4750480.237524
1550.7579470.4841070.242053
1560.7311920.5376160.268808
1570.7143830.5712340.285617
1580.6853040.6293930.314696
1590.6835470.6329060.316453
1600.6673350.665330.332665
1610.6517680.6964630.348232
1620.656640.686720.34336
1630.6316630.7366750.368337
1640.8306210.3387580.169379
1650.8113170.3773650.188683
1660.7992310.4015380.200769
1670.7880480.4239040.211952
1680.8045130.3909730.195487
1690.7783830.4432350.221617
1700.813230.3735410.18677
1710.803470.3930590.19653
1720.8075230.3849540.192477
1730.7980870.4038260.201913
1740.7735940.4528130.226406
1750.747370.5052610.25263
1760.7727240.4545510.227276
1770.7612410.4775190.238759
1780.7669250.4661510.233075
1790.7387470.5225070.261253
1800.8284680.3430630.171532
1810.8500050.2999890.149995
1820.8456850.3086290.154315
1830.8485320.3029360.151468
1840.82590.3482010.1741
1850.822770.354460.17723
1860.7969280.4061440.203072
1870.8152490.3695020.184751
1880.8156180.3687650.184382
1890.8076130.3847750.192387
1900.7832240.4335510.216776
1910.7727620.4544760.227238
1920.7527370.4945270.247263
1930.7568520.4862960.243148
1940.7920040.4159920.207996
1950.7633990.4732020.236601
1960.7484590.5030820.251541
1970.7724570.4550860.227543
1980.7430020.5139960.256998
1990.7298720.5402560.270128
2000.7017220.5965570.298278
2010.6804140.6391730.319586
2020.6551840.6896320.344816
2030.6729170.6541670.327083
2040.6371870.7256250.362813
2050.6070.7860010.393
2060.6333530.7332940.366647
2070.6072390.7855230.392761
2080.5821150.835770.417885
2090.5744480.8511040.425552
2100.5878910.8242190.412109
2110.5595340.8809310.440466
2120.5177880.9644230.482212
2130.590380.819240.40962
2140.5818980.8362040.418102
2150.5617610.8764780.438239
2160.5239150.952170.476085
2170.5472590.9054820.452741
2180.5262960.9474070.473704
2190.488160.9763210.51184
2200.4434630.8869270.556537
2210.4304370.8608740.569563
2220.4988550.9977110.501145
2230.4603630.9207270.539637
2240.5081080.9837830.491892
2250.4882690.9765370.511731
2260.5386270.9227460.461373
2270.5443290.9113430.455671
2280.6265360.7469270.373464
2290.6358450.728310.364155
2300.6644470.6711050.335553
2310.6635780.6728430.336422
2320.6212790.7574420.378721
2330.6083240.7833510.391676
2340.5708280.8583430.429172
2350.5338430.9323130.466157
2360.8600470.2799060.139953
2370.8399420.3201170.160058
2380.8093080.3813830.190692
2390.7758690.4482620.224131
2400.7325290.5349420.267471
2410.7583060.4833880.241694
2420.7241250.5517490.275875
2430.713240.573520.28676
2440.6623430.6753140.337657
2450.6334980.7330030.366502
2460.5929490.8141030.407051
2470.6118980.7762050.388102
2480.7588450.4823110.241155
2490.7461150.5077690.253885
2500.686710.6265810.31329
2510.6947940.6104120.305206
2520.6561450.687710.343855
2530.69210.6157990.3079
2540.6882740.6234520.311726
2550.7060610.5878780.293939
2560.7815470.4369050.218453
2570.8042970.3914060.195703
2580.8772750.245450.122725
2590.820030.3599390.17997
2600.9514950.09701060.0485053
2610.9214210.1571570.0785786
2620.8988520.2022970.101148
2630.9291650.1416710.0708355
2640.8572950.285410.142705
2650.7758160.4483670.224184
2660.6364450.727110.363555






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level10.00393701OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 0 & 0 & OK \tabularnewline
10% type I error level & 1 & 0.00393701 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=265549&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]1[/C][C]0.00393701[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=265549&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=265549&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level10.00393701OK


Figures (Output of Computation)

Figure 1
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 2
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 3
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 4
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 5
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 6
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 7
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 8
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 9
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Figure 10
PNG link  
QR Code
Postscript link  
QR Code
PDF link  
QR Code


Input Parameters & R Code

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