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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 13:16:00 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418649473s3xnrv1g9j0j4yf.htm/, Retrieved Thu, 16 May 2024 21:56:29 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268316, Retrieved Thu, 16 May 2024 21:56:29 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact55

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-15 13:16:00] [08b6b59c0a3564dc58beca6de73ddb7e] [Current]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'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 & 10 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=268316&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'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=268316&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'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] = + 7.23146 + 4.37668year_num[t] -1.11752group_num[t] -0.552254gender[t] -0.0115929AMS.I[t] -0.0228181AMS.E[t] -0.0656884AMS.A[t] + 0.0442125NUMERACYTOT[t] + 0.0373358LFM[t] + 0.0315677CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  7.23146 +  4.37668year_num[t] -1.11752group_num[t] -0.552254gender[t] -0.0115929AMS.I[t] -0.0228181AMS.E[t] -0.0656884AMS.A[t] +  0.0442125NUMERACYTOT[t] +  0.0373358LFM[t] +  0.0315677CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  7.23146 +  4.37668year_num[t] -1.11752group_num[t] -0.552254gender[t] -0.0115929AMS.I[t] -0.0228181AMS.E[t] -0.0656884AMS.A[t] +  0.0442125NUMERACYTOT[t] +  0.0373358LFM[t] +  0.0315677CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268316&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&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] = + 7.23146 + 4.37668year_num[t] -1.11752group_num[t] -0.552254gender[t] -0.0115929AMS.I[t] -0.0228181AMS.E[t] -0.0656884AMS.A[t] + 0.0442125NUMERACYTOT[t] + 0.0373358LFM[t] + 0.0315677CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.231461.574694.5926.74932e-063.37466e-06
year_num4.376680.29376414.95.5588e-372.7794e-37
group_num-1.117520.330018-3.3860.0008147520.000407376
gender-0.5522540.291785-1.8930.05947880.0297394
AMS.I-0.01159290.0146792-0.78970.4303740.215187
AMS.E-0.02281810.0192693-1.1840.2373950.118697
AMS.A-0.06568840.0430832-1.5250.1285160.0642582
NUMERACYTOT0.04421250.02763391.60.1107910.0553955
LFM0.03733580.004604158.1091.83656e-149.18281e-15
CH0.03156770.00827113.8170.0001680628.40312e-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) & 7.23146 & 1.57469 & 4.592 & 6.74932e-06 & 3.37466e-06 \tabularnewline
year_num & 4.37668 & 0.293764 & 14.9 & 5.5588e-37 & 2.7794e-37 \tabularnewline
group_num & -1.11752 & 0.330018 & -3.386 & 0.000814752 & 0.000407376 \tabularnewline
gender & -0.552254 & 0.291785 & -1.893 & 0.0594788 & 0.0297394 \tabularnewline
AMS.I & -0.0115929 & 0.0146792 & -0.7897 & 0.430374 & 0.215187 \tabularnewline
AMS.E & -0.0228181 & 0.0192693 & -1.184 & 0.237395 & 0.118697 \tabularnewline
AMS.A & -0.0656884 & 0.0430832 & -1.525 & 0.128516 & 0.0642582 \tabularnewline
NUMERACYTOT & 0.0442125 & 0.0276339 & 1.6 & 0.110791 & 0.0553955 \tabularnewline
LFM & 0.0373358 & 0.00460415 & 8.109 & 1.83656e-14 & 9.18281e-15 \tabularnewline
CH & 0.0315677 & 0.0082711 & 3.817 & 0.000168062 & 8.40312e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&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]7.23146[/C][C]1.57469[/C][C]4.592[/C][C]6.74932e-06[/C][C]3.37466e-06[/C][/ROW]
[ROW][C]year_num[/C][C]4.37668[/C][C]0.293764[/C][C]14.9[/C][C]5.5588e-37[/C][C]2.7794e-37[/C][/ROW]
[ROW][C]group_num[/C][C]-1.11752[/C][C]0.330018[/C][C]-3.386[/C][C]0.000814752[/C][C]0.000407376[/C][/ROW]
[ROW][C]gender[/C][C]-0.552254[/C][C]0.291785[/C][C]-1.893[/C][C]0.0594788[/C][C]0.0297394[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.0115929[/C][C]0.0146792[/C][C]-0.7897[/C][C]0.430374[/C][C]0.215187[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0228181[/C][C]0.0192693[/C][C]-1.184[/C][C]0.237395[/C][C]0.118697[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0656884[/C][C]0.0430832[/C][C]-1.525[/C][C]0.128516[/C][C]0.0642582[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0442125[/C][C]0.0276339[/C][C]1.6[/C][C]0.110791[/C][C]0.0553955[/C][/ROW]
[ROW][C]LFM[/C][C]0.0373358[/C][C]0.00460415[/C][C]8.109[/C][C]1.83656e-14[/C][C]9.18281e-15[/C][/ROW]
[ROW][C]CH[/C][C]0.0315677[/C][C]0.0082711[/C][C]3.817[/C][C]0.000168062[/C][C]8.40312e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268316&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&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)7.231461.574694.5926.74932e-063.37466e-06
year_num4.376680.29376414.95.5588e-372.7794e-37
group_num-1.117520.330018-3.3860.0008147520.000407376
gender-0.5522540.291785-1.8930.05947880.0297394
AMS.I-0.01159290.0146792-0.78970.4303740.215187
AMS.E-0.02281810.0192693-1.1840.2373950.118697
AMS.A-0.06568840.0430832-1.5250.1285160.0642582
NUMERACYTOT0.04421250.02763391.60.1107910.0553955
LFM0.03733580.004604158.1091.83656e-149.18281e-15
CH0.03156770.00827113.8170.0001680628.40312e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.749245
R-squared0.561368
Adjusted R-squared0.546637
F-TEST (value)38.11
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2855
Sum Squared Residuals1399.9

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.749245 \tabularnewline
R-squared & 0.561368 \tabularnewline
Adjusted R-squared & 0.546637 \tabularnewline
F-TEST (value) & 38.11 \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 & 2.2855 \tabularnewline
Sum Squared Residuals & 1399.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.749245[/C][/ROW]
[ROW][C]R-squared[/C][C]0.561368[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.546637[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]38.11[/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]2.2855[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1399.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268316&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&T=3

As an alternative you can also use a QR Code:  
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The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.749245
R-squared0.561368
Adjusted R-squared0.546637
F-TEST (value)38.11
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.2855
Sum Squared Residuals1399.9






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.913.047-0.146971
212.210.61691.58309
312.811.63291.16707
47.411.5542-4.15421
56.710.4059-3.70587
612.613.4198-0.819781
714.812.09772.70227
813.310.47772.82227
911.111.6724-0.572415
108.211.9332-3.73325
1111.411.7418-0.341847
126.411.5926-5.1926
1310.68.927781.67222
141213.3865-1.3865
156.36.76326-0.46326
1611.39.186582.11342
1711.912.3479-0.447902
189.310.2677-0.967693
199.611.6133-2.01329
20109.615040.38496
216.410.008-3.60801
2213.810.06323.73684
2310.814.0617-3.26169
2413.812.98840.811633
2511.711.06150.638484
2610.914.9311-4.03111
2716.113.38452.71554
2813.410.23643.16357
299.911.5711-1.67107
3011.511.21660.283354
318.39.38974-1.08974
3211.711.22610.473854
3399.89352-0.893522
349.711.5771-1.87715
3510.89.087851.71215
3610.38.732741.56726
3710.410.9389-0.53888
3812.710.11982.58022
399.311.7885-2.48849
4011.812.2565-0.456484
415.99.80003-3.90003
4211.411.05790.34207
431311.98181.01818
4410.811.8527-1.05266
4512.38.460373.83963
4611.312.9849-1.68486
4711.89.656562.14344
487.99.66095-1.76095
4912.79.546343.15366
5012.39.048623.25138
5111.610.57171.02825
526.77.24543-0.545429
5310.910.74410.155876
5412.111.57340.526574
5513.310.0263.27402
5610.19.670440.429565
575.711.1763-5.47633
5814.39.66284.6372
5987.382050.617947
6013.310.70942.59059
619.312.7969-3.49688
6212.511.1411.35903
637.68.82937-1.22937
6415.913.74512.15495
659.212.4261-3.22605
669.18.300810.799186
6711.112.8378-1.73776
681315.2213-2.22132
6914.511.84862.65138
7012.210.90721.29275
7112.313.0668-0.766786
7211.410.25941.14059
738.89.7239-0.923903
7414.610.94913.65086
7512.611.02951.57052
76NANA0.743294
771310.90972.09033
7812.611.72630.873661
7913.212.50020.699781
809.912.0424-2.14242
817.77.75645-0.05645
8210.57.542352.95765
8313.412.99390.406101
8410.915.876-4.97603
854.35.33735-1.03735
8610.39.581470.718535
8711.89.563542.23646
8811.28.625432.57457
8911.412.7134-1.31337
908.66.911771.68823
9113.29.406063.79394
9212.617.0406-4.4406
935.67.57573-1.97573
949.910.8033-0.903315
958.810.6871-1.8871
967.79.33671-1.63671
97912.5937-3.59371
987.34.956472.34353
9911.47.508563.89144
10013.615.8894-2.28938
1017.95.950771.94923
10210.710.55940.140568
10310.310.9146-0.614632
1048.39.66593-1.36593
1059.65.416014.18399
10614.215.8423-1.64233
1078.54.561883.93812
10813.518.5063-5.00627
1094.96.63323-1.73323
1106.47.5485-1.1485
1119.68.76190.838095
11211.69.776231.82377
11311.117.7155-6.6155
1144.354.122320.227678
11512.79.647613.05239
11618.115.65932.44069
11717.8519.4972-1.64722
11816.615.62990.97011
11912.613.9245-1.32446
12017.115.29521.80483
12119.121.6559-2.55593
12216.114.47331.62671
12313.3511.41871.93132
12418.413.87434.52565
12514.717.454-2.75405
12610.611.0805-0.480474
12712.611.19381.40615
12816.216.4757-0.275662
12913.611.07392.52608
13018.917.78891.11108
13114.112.85161.24837
13214.515.5963-1.09632
13316.1515.05431.09575
13414.7513.66491.08508
13514.814.74370.0563077
13612.4512.566-0.115969
13712.659.509173.14083
13817.3519.0919-1.74191
1398.66.743641.85636
14018.417.32321.07683
14116.116.6458-0.545827
14211.68.838522.76148
14317.7517.25520.49479
14415.2511.88583.36416
14517.6517.52850.121497
14616.3515.57320.776798
14717.6517.9727-0.322713
14813.613.6719-0.0719316
14914.3514.5603-0.210314
15014.7512.44582.30422
15118.2524.1461-5.89609
1529.99.081890.818108
1531613.45832.54174
15418.2518.5646-0.314613
15516.8515.29661.55338
15614.615.341-0.740978
15713.8512.27021.57981
15818.9517.7531.19697
15915.617.7789-2.17892
16014.8517.257-2.407
16111.7510.45971.29035
16218.4516.59881.85118
16315.916.4307-0.530685
16417.110.43986.66021
16516.115.10860.991408
16619.920.0451-0.145072
16710.959.321851.62815
16818.4516.89631.55372
16915.115.2447-0.144675
1701518.1103-3.11034
17111.3510.04111.30887
17215.9513.58312.36688
17318.120.1577-2.05771
17414.614.8214-0.221393
17515.415.5758-0.175757
17615.412.88622.51379
17717.618.8575-1.25753
17813.3510.73722.61281
17919.120.506-1.40596
18015.3518.8868-3.53676
1817.610.1848-2.58481
18213.415.5487-2.14873
18313.911.15072.74926
18419.119.2951-0.195072
18515.2517.8755-2.62552
18612.912.61260.287374
18716.113.42032.67973
18817.3519.5474-2.19738
18913.1515.1985-2.04846
19012.1512.2715-0.121527
19112.615.3371-2.73714
19210.359.337511.01249
19315.418.6653-3.26535
1949.66.250563.34944
19518.218.9181-0.718068
19613.612.57781.02223
19714.8516.6709-1.82088
19814.7514.55290.197085
19914.112.88581.21418
20014.914.19430.705717
20116.2515.05611.19389
20219.2518.85530.394722
20313.615.1562-1.55625
20413.613.6717-0.0717165
20515.6516.0604-0.410359
20612.7511.47331.27667
20714.615.7808-1.1808
2089.859.64780.202196
20912.659.961262.68874
21019.217.35971.84032
21116.617.7712-1.17117
21211.210.82330.376696
21315.2517.6449-2.39486
21411.912.151-0.25098
21513.213.7063-0.506293
21616.3516.8593-0.509298
21712.411.11711.28291
21815.8513.71832.13168
21918.1519.9087-1.75873
22011.1511.8447-0.694703
22115.6512.88382.76619
22217.7521.8694-4.11937
2237.658.74871-1.09871
22412.359.94072.4093
22515.612.89312.70694
22619.316.43012.86986
22715.212.62852.57146
22817.115.06342.0366
22915.612.55983.04018
23018.415.1213.27896
23119.0515.5583.49201
23218.5516.32352.22655
23319.119.3899-0.289945
23413.115.6261-2.52611
23512.8515.2517-2.40169
2369.516.045-6.54496
2374.54.62445-0.124455
23811.8512.6542-0.80423
23913.614.5034-0.903399
24011.712.4201-0.720088
24112.413.621-1.22098
24213.3515.1971-1.84707
24311.410.84310.556915
24414.913.2671.63304
24519.922.3651-2.46513
24611.211.8357-0.635653
24714.614.6079-0.00786784
24817.616.80920.79083
24914.0513.43280.617188
25016.116.5724-0.472363
25113.3515.5997-2.24973
25211.8513.5401-1.69006
25311.9511.8240.12598
25414.7513.98050.769481
25515.1517.4068-2.25679
25613.212.62440.575626
25716.8521.5752-4.72519
2587.8512.8331-4.98307
2597.710.243-2.54303
26012.619.5501-6.95014
2617.858.62255-0.772548
26210.9513.2466-2.29656
26312.3515.6531-3.30305
2649.958.940991.00901
26514.913.20581.6942
26616.6516.63170.0183332
26713.413.6811-0.281074
26813.9512.51181.43815
26915.714.11081.58921
27016.8518.435-1.58505
27110.9510.29720.65278
27215.3516.2122-0.862229
27312.211.3670.832968
27415.113.58751.51246
27517.7517.57880.17115
27615.215.3293-0.129303
27714.613.71420.885789
27816.6519.3393-2.6893
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 & 13.047 & -0.146971 \tabularnewline
2 & 12.2 & 10.6169 & 1.58309 \tabularnewline
3 & 12.8 & 11.6329 & 1.16707 \tabularnewline
4 & 7.4 & 11.5542 & -4.15421 \tabularnewline
5 & 6.7 & 10.4059 & -3.70587 \tabularnewline
6 & 12.6 & 13.4198 & -0.819781 \tabularnewline
7 & 14.8 & 12.0977 & 2.70227 \tabularnewline
8 & 13.3 & 10.4777 & 2.82227 \tabularnewline
9 & 11.1 & 11.6724 & -0.572415 \tabularnewline
10 & 8.2 & 11.9332 & -3.73325 \tabularnewline
11 & 11.4 & 11.7418 & -0.341847 \tabularnewline
12 & 6.4 & 11.5926 & -5.1926 \tabularnewline
13 & 10.6 & 8.92778 & 1.67222 \tabularnewline
14 & 12 & 13.3865 & -1.3865 \tabularnewline
15 & 6.3 & 6.76326 & -0.46326 \tabularnewline
16 & 11.3 & 9.18658 & 2.11342 \tabularnewline
17 & 11.9 & 12.3479 & -0.447902 \tabularnewline
18 & 9.3 & 10.2677 & -0.967693 \tabularnewline
19 & 9.6 & 11.6133 & -2.01329 \tabularnewline
20 & 10 & 9.61504 & 0.38496 \tabularnewline
21 & 6.4 & 10.008 & -3.60801 \tabularnewline
22 & 13.8 & 10.0632 & 3.73684 \tabularnewline
23 & 10.8 & 14.0617 & -3.26169 \tabularnewline
24 & 13.8 & 12.9884 & 0.811633 \tabularnewline
25 & 11.7 & 11.0615 & 0.638484 \tabularnewline
26 & 10.9 & 14.9311 & -4.03111 \tabularnewline
27 & 16.1 & 13.3845 & 2.71554 \tabularnewline
28 & 13.4 & 10.2364 & 3.16357 \tabularnewline
29 & 9.9 & 11.5711 & -1.67107 \tabularnewline
30 & 11.5 & 11.2166 & 0.283354 \tabularnewline
31 & 8.3 & 9.38974 & -1.08974 \tabularnewline
32 & 11.7 & 11.2261 & 0.473854 \tabularnewline
33 & 9 & 9.89352 & -0.893522 \tabularnewline
34 & 9.7 & 11.5771 & -1.87715 \tabularnewline
35 & 10.8 & 9.08785 & 1.71215 \tabularnewline
36 & 10.3 & 8.73274 & 1.56726 \tabularnewline
37 & 10.4 & 10.9389 & -0.53888 \tabularnewline
38 & 12.7 & 10.1198 & 2.58022 \tabularnewline
39 & 9.3 & 11.7885 & -2.48849 \tabularnewline
40 & 11.8 & 12.2565 & -0.456484 \tabularnewline
41 & 5.9 & 9.80003 & -3.90003 \tabularnewline
42 & 11.4 & 11.0579 & 0.34207 \tabularnewline
43 & 13 & 11.9818 & 1.01818 \tabularnewline
44 & 10.8 & 11.8527 & -1.05266 \tabularnewline
45 & 12.3 & 8.46037 & 3.83963 \tabularnewline
46 & 11.3 & 12.9849 & -1.68486 \tabularnewline
47 & 11.8 & 9.65656 & 2.14344 \tabularnewline
48 & 7.9 & 9.66095 & -1.76095 \tabularnewline
49 & 12.7 & 9.54634 & 3.15366 \tabularnewline
50 & 12.3 & 9.04862 & 3.25138 \tabularnewline
51 & 11.6 & 10.5717 & 1.02825 \tabularnewline
52 & 6.7 & 7.24543 & -0.545429 \tabularnewline
53 & 10.9 & 10.7441 & 0.155876 \tabularnewline
54 & 12.1 & 11.5734 & 0.526574 \tabularnewline
55 & 13.3 & 10.026 & 3.27402 \tabularnewline
56 & 10.1 & 9.67044 & 0.429565 \tabularnewline
57 & 5.7 & 11.1763 & -5.47633 \tabularnewline
58 & 14.3 & 9.6628 & 4.6372 \tabularnewline
59 & 8 & 7.38205 & 0.617947 \tabularnewline
60 & 13.3 & 10.7094 & 2.59059 \tabularnewline
61 & 9.3 & 12.7969 & -3.49688 \tabularnewline
62 & 12.5 & 11.141 & 1.35903 \tabularnewline
63 & 7.6 & 8.82937 & -1.22937 \tabularnewline
64 & 15.9 & 13.7451 & 2.15495 \tabularnewline
65 & 9.2 & 12.4261 & -3.22605 \tabularnewline
66 & 9.1 & 8.30081 & 0.799186 \tabularnewline
67 & 11.1 & 12.8378 & -1.73776 \tabularnewline
68 & 13 & 15.2213 & -2.22132 \tabularnewline
69 & 14.5 & 11.8486 & 2.65138 \tabularnewline
70 & 12.2 & 10.9072 & 1.29275 \tabularnewline
71 & 12.3 & 13.0668 & -0.766786 \tabularnewline
72 & 11.4 & 10.2594 & 1.14059 \tabularnewline
73 & 8.8 & 9.7239 & -0.923903 \tabularnewline
74 & 14.6 & 10.9491 & 3.65086 \tabularnewline
75 & 12.6 & 11.0295 & 1.57052 \tabularnewline
76 & NA & NA & 0.743294 \tabularnewline
77 & 13 & 10.9097 & 2.09033 \tabularnewline
78 & 12.6 & 11.7263 & 0.873661 \tabularnewline
79 & 13.2 & 12.5002 & 0.699781 \tabularnewline
80 & 9.9 & 12.0424 & -2.14242 \tabularnewline
81 & 7.7 & 7.75645 & -0.05645 \tabularnewline
82 & 10.5 & 7.54235 & 2.95765 \tabularnewline
83 & 13.4 & 12.9939 & 0.406101 \tabularnewline
84 & 10.9 & 15.876 & -4.97603 \tabularnewline
85 & 4.3 & 5.33735 & -1.03735 \tabularnewline
86 & 10.3 & 9.58147 & 0.718535 \tabularnewline
87 & 11.8 & 9.56354 & 2.23646 \tabularnewline
88 & 11.2 & 8.62543 & 2.57457 \tabularnewline
89 & 11.4 & 12.7134 & -1.31337 \tabularnewline
90 & 8.6 & 6.91177 & 1.68823 \tabularnewline
91 & 13.2 & 9.40606 & 3.79394 \tabularnewline
92 & 12.6 & 17.0406 & -4.4406 \tabularnewline
93 & 5.6 & 7.57573 & -1.97573 \tabularnewline
94 & 9.9 & 10.8033 & -0.903315 \tabularnewline
95 & 8.8 & 10.6871 & -1.8871 \tabularnewline
96 & 7.7 & 9.33671 & -1.63671 \tabularnewline
97 & 9 & 12.5937 & -3.59371 \tabularnewline
98 & 7.3 & 4.95647 & 2.34353 \tabularnewline
99 & 11.4 & 7.50856 & 3.89144 \tabularnewline
100 & 13.6 & 15.8894 & -2.28938 \tabularnewline
101 & 7.9 & 5.95077 & 1.94923 \tabularnewline
102 & 10.7 & 10.5594 & 0.140568 \tabularnewline
103 & 10.3 & 10.9146 & -0.614632 \tabularnewline
104 & 8.3 & 9.66593 & -1.36593 \tabularnewline
105 & 9.6 & 5.41601 & 4.18399 \tabularnewline
106 & 14.2 & 15.8423 & -1.64233 \tabularnewline
107 & 8.5 & 4.56188 & 3.93812 \tabularnewline
108 & 13.5 & 18.5063 & -5.00627 \tabularnewline
109 & 4.9 & 6.63323 & -1.73323 \tabularnewline
110 & 6.4 & 7.5485 & -1.1485 \tabularnewline
111 & 9.6 & 8.7619 & 0.838095 \tabularnewline
112 & 11.6 & 9.77623 & 1.82377 \tabularnewline
113 & 11.1 & 17.7155 & -6.6155 \tabularnewline
114 & 4.35 & 4.12232 & 0.227678 \tabularnewline
115 & 12.7 & 9.64761 & 3.05239 \tabularnewline
116 & 18.1 & 15.6593 & 2.44069 \tabularnewline
117 & 17.85 & 19.4972 & -1.64722 \tabularnewline
118 & 16.6 & 15.6299 & 0.97011 \tabularnewline
119 & 12.6 & 13.9245 & -1.32446 \tabularnewline
120 & 17.1 & 15.2952 & 1.80483 \tabularnewline
121 & 19.1 & 21.6559 & -2.55593 \tabularnewline
122 & 16.1 & 14.4733 & 1.62671 \tabularnewline
123 & 13.35 & 11.4187 & 1.93132 \tabularnewline
124 & 18.4 & 13.8743 & 4.52565 \tabularnewline
125 & 14.7 & 17.454 & -2.75405 \tabularnewline
126 & 10.6 & 11.0805 & -0.480474 \tabularnewline
127 & 12.6 & 11.1938 & 1.40615 \tabularnewline
128 & 16.2 & 16.4757 & -0.275662 \tabularnewline
129 & 13.6 & 11.0739 & 2.52608 \tabularnewline
130 & 18.9 & 17.7889 & 1.11108 \tabularnewline
131 & 14.1 & 12.8516 & 1.24837 \tabularnewline
132 & 14.5 & 15.5963 & -1.09632 \tabularnewline
133 & 16.15 & 15.0543 & 1.09575 \tabularnewline
134 & 14.75 & 13.6649 & 1.08508 \tabularnewline
135 & 14.8 & 14.7437 & 0.0563077 \tabularnewline
136 & 12.45 & 12.566 & -0.115969 \tabularnewline
137 & 12.65 & 9.50917 & 3.14083 \tabularnewline
138 & 17.35 & 19.0919 & -1.74191 \tabularnewline
139 & 8.6 & 6.74364 & 1.85636 \tabularnewline
140 & 18.4 & 17.3232 & 1.07683 \tabularnewline
141 & 16.1 & 16.6458 & -0.545827 \tabularnewline
142 & 11.6 & 8.83852 & 2.76148 \tabularnewline
143 & 17.75 & 17.2552 & 0.49479 \tabularnewline
144 & 15.25 & 11.8858 & 3.36416 \tabularnewline
145 & 17.65 & 17.5285 & 0.121497 \tabularnewline
146 & 16.35 & 15.5732 & 0.776798 \tabularnewline
147 & 17.65 & 17.9727 & -0.322713 \tabularnewline
148 & 13.6 & 13.6719 & -0.0719316 \tabularnewline
149 & 14.35 & 14.5603 & -0.210314 \tabularnewline
150 & 14.75 & 12.4458 & 2.30422 \tabularnewline
151 & 18.25 & 24.1461 & -5.89609 \tabularnewline
152 & 9.9 & 9.08189 & 0.818108 \tabularnewline
153 & 16 & 13.4583 & 2.54174 \tabularnewline
154 & 18.25 & 18.5646 & -0.314613 \tabularnewline
155 & 16.85 & 15.2966 & 1.55338 \tabularnewline
156 & 14.6 & 15.341 & -0.740978 \tabularnewline
157 & 13.85 & 12.2702 & 1.57981 \tabularnewline
158 & 18.95 & 17.753 & 1.19697 \tabularnewline
159 & 15.6 & 17.7789 & -2.17892 \tabularnewline
160 & 14.85 & 17.257 & -2.407 \tabularnewline
161 & 11.75 & 10.4597 & 1.29035 \tabularnewline
162 & 18.45 & 16.5988 & 1.85118 \tabularnewline
163 & 15.9 & 16.4307 & -0.530685 \tabularnewline
164 & 17.1 & 10.4398 & 6.66021 \tabularnewline
165 & 16.1 & 15.1086 & 0.991408 \tabularnewline
166 & 19.9 & 20.0451 & -0.145072 \tabularnewline
167 & 10.95 & 9.32185 & 1.62815 \tabularnewline
168 & 18.45 & 16.8963 & 1.55372 \tabularnewline
169 & 15.1 & 15.2447 & -0.144675 \tabularnewline
170 & 15 & 18.1103 & -3.11034 \tabularnewline
171 & 11.35 & 10.0411 & 1.30887 \tabularnewline
172 & 15.95 & 13.5831 & 2.36688 \tabularnewline
173 & 18.1 & 20.1577 & -2.05771 \tabularnewline
174 & 14.6 & 14.8214 & -0.221393 \tabularnewline
175 & 15.4 & 15.5758 & -0.175757 \tabularnewline
176 & 15.4 & 12.8862 & 2.51379 \tabularnewline
177 & 17.6 & 18.8575 & -1.25753 \tabularnewline
178 & 13.35 & 10.7372 & 2.61281 \tabularnewline
179 & 19.1 & 20.506 & -1.40596 \tabularnewline
180 & 15.35 & 18.8868 & -3.53676 \tabularnewline
181 & 7.6 & 10.1848 & -2.58481 \tabularnewline
182 & 13.4 & 15.5487 & -2.14873 \tabularnewline
183 & 13.9 & 11.1507 & 2.74926 \tabularnewline
184 & 19.1 & 19.2951 & -0.195072 \tabularnewline
185 & 15.25 & 17.8755 & -2.62552 \tabularnewline
186 & 12.9 & 12.6126 & 0.287374 \tabularnewline
187 & 16.1 & 13.4203 & 2.67973 \tabularnewline
188 & 17.35 & 19.5474 & -2.19738 \tabularnewline
189 & 13.15 & 15.1985 & -2.04846 \tabularnewline
190 & 12.15 & 12.2715 & -0.121527 \tabularnewline
191 & 12.6 & 15.3371 & -2.73714 \tabularnewline
192 & 10.35 & 9.33751 & 1.01249 \tabularnewline
193 & 15.4 & 18.6653 & -3.26535 \tabularnewline
194 & 9.6 & 6.25056 & 3.34944 \tabularnewline
195 & 18.2 & 18.9181 & -0.718068 \tabularnewline
196 & 13.6 & 12.5778 & 1.02223 \tabularnewline
197 & 14.85 & 16.6709 & -1.82088 \tabularnewline
198 & 14.75 & 14.5529 & 0.197085 \tabularnewline
199 & 14.1 & 12.8858 & 1.21418 \tabularnewline
200 & 14.9 & 14.1943 & 0.705717 \tabularnewline
201 & 16.25 & 15.0561 & 1.19389 \tabularnewline
202 & 19.25 & 18.8553 & 0.394722 \tabularnewline
203 & 13.6 & 15.1562 & -1.55625 \tabularnewline
204 & 13.6 & 13.6717 & -0.0717165 \tabularnewline
205 & 15.65 & 16.0604 & -0.410359 \tabularnewline
206 & 12.75 & 11.4733 & 1.27667 \tabularnewline
207 & 14.6 & 15.7808 & -1.1808 \tabularnewline
208 & 9.85 & 9.6478 & 0.202196 \tabularnewline
209 & 12.65 & 9.96126 & 2.68874 \tabularnewline
210 & 19.2 & 17.3597 & 1.84032 \tabularnewline
211 & 16.6 & 17.7712 & -1.17117 \tabularnewline
212 & 11.2 & 10.8233 & 0.376696 \tabularnewline
213 & 15.25 & 17.6449 & -2.39486 \tabularnewline
214 & 11.9 & 12.151 & -0.25098 \tabularnewline
215 & 13.2 & 13.7063 & -0.506293 \tabularnewline
216 & 16.35 & 16.8593 & -0.509298 \tabularnewline
217 & 12.4 & 11.1171 & 1.28291 \tabularnewline
218 & 15.85 & 13.7183 & 2.13168 \tabularnewline
219 & 18.15 & 19.9087 & -1.75873 \tabularnewline
220 & 11.15 & 11.8447 & -0.694703 \tabularnewline
221 & 15.65 & 12.8838 & 2.76619 \tabularnewline
222 & 17.75 & 21.8694 & -4.11937 \tabularnewline
223 & 7.65 & 8.74871 & -1.09871 \tabularnewline
224 & 12.35 & 9.9407 & 2.4093 \tabularnewline
225 & 15.6 & 12.8931 & 2.70694 \tabularnewline
226 & 19.3 & 16.4301 & 2.86986 \tabularnewline
227 & 15.2 & 12.6285 & 2.57146 \tabularnewline
228 & 17.1 & 15.0634 & 2.0366 \tabularnewline
229 & 15.6 & 12.5598 & 3.04018 \tabularnewline
230 & 18.4 & 15.121 & 3.27896 \tabularnewline
231 & 19.05 & 15.558 & 3.49201 \tabularnewline
232 & 18.55 & 16.3235 & 2.22655 \tabularnewline
233 & 19.1 & 19.3899 & -0.289945 \tabularnewline
234 & 13.1 & 15.6261 & -2.52611 \tabularnewline
235 & 12.85 & 15.2517 & -2.40169 \tabularnewline
236 & 9.5 & 16.045 & -6.54496 \tabularnewline
237 & 4.5 & 4.62445 & -0.124455 \tabularnewline
238 & 11.85 & 12.6542 & -0.80423 \tabularnewline
239 & 13.6 & 14.5034 & -0.903399 \tabularnewline
240 & 11.7 & 12.4201 & -0.720088 \tabularnewline
241 & 12.4 & 13.621 & -1.22098 \tabularnewline
242 & 13.35 & 15.1971 & -1.84707 \tabularnewline
243 & 11.4 & 10.8431 & 0.556915 \tabularnewline
244 & 14.9 & 13.267 & 1.63304 \tabularnewline
245 & 19.9 & 22.3651 & -2.46513 \tabularnewline
246 & 11.2 & 11.8357 & -0.635653 \tabularnewline
247 & 14.6 & 14.6079 & -0.00786784 \tabularnewline
248 & 17.6 & 16.8092 & 0.79083 \tabularnewline
249 & 14.05 & 13.4328 & 0.617188 \tabularnewline
250 & 16.1 & 16.5724 & -0.472363 \tabularnewline
251 & 13.35 & 15.5997 & -2.24973 \tabularnewline
252 & 11.85 & 13.5401 & -1.69006 \tabularnewline
253 & 11.95 & 11.824 & 0.12598 \tabularnewline
254 & 14.75 & 13.9805 & 0.769481 \tabularnewline
255 & 15.15 & 17.4068 & -2.25679 \tabularnewline
256 & 13.2 & 12.6244 & 0.575626 \tabularnewline
257 & 16.85 & 21.5752 & -4.72519 \tabularnewline
258 & 7.85 & 12.8331 & -4.98307 \tabularnewline
259 & 7.7 & 10.243 & -2.54303 \tabularnewline
260 & 12.6 & 19.5501 & -6.95014 \tabularnewline
261 & 7.85 & 8.62255 & -0.772548 \tabularnewline
262 & 10.95 & 13.2466 & -2.29656 \tabularnewline
263 & 12.35 & 15.6531 & -3.30305 \tabularnewline
264 & 9.95 & 8.94099 & 1.00901 \tabularnewline
265 & 14.9 & 13.2058 & 1.6942 \tabularnewline
266 & 16.65 & 16.6317 & 0.0183332 \tabularnewline
267 & 13.4 & 13.6811 & -0.281074 \tabularnewline
268 & 13.95 & 12.5118 & 1.43815 \tabularnewline
269 & 15.7 & 14.1108 & 1.58921 \tabularnewline
270 & 16.85 & 18.435 & -1.58505 \tabularnewline
271 & 10.95 & 10.2972 & 0.65278 \tabularnewline
272 & 15.35 & 16.2122 & -0.862229 \tabularnewline
273 & 12.2 & 11.367 & 0.832968 \tabularnewline
274 & 15.1 & 13.5875 & 1.51246 \tabularnewline
275 & 17.75 & 17.5788 & 0.17115 \tabularnewline
276 & 15.2 & 15.3293 & -0.129303 \tabularnewline
277 & 14.6 & 13.7142 & 0.885789 \tabularnewline
278 & 16.65 & 19.3393 & -2.6893 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&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]13.047[/C][C]-0.146971[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.6169[/C][C]1.58309[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.6329[/C][C]1.16707[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.5542[/C][C]-4.15421[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.4059[/C][C]-3.70587[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.4198[/C][C]-0.819781[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.0977[/C][C]2.70227[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.4777[/C][C]2.82227[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.6724[/C][C]-0.572415[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.9332[/C][C]-3.73325[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.7418[/C][C]-0.341847[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.5926[/C][C]-5.1926[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]8.92778[/C][C]1.67222[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.3865[/C][C]-1.3865[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]6.76326[/C][C]-0.46326[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.18658[/C][C]2.11342[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.3479[/C][C]-0.447902[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.2677[/C][C]-0.967693[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.6133[/C][C]-2.01329[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.61504[/C][C]0.38496[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.008[/C][C]-3.60801[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.0632[/C][C]3.73684[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.0617[/C][C]-3.26169[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.9884[/C][C]0.811633[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.0615[/C][C]0.638484[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.9311[/C][C]-4.03111[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.3845[/C][C]2.71554[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.2364[/C][C]3.16357[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.5711[/C][C]-1.67107[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.2166[/C][C]0.283354[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.38974[/C][C]-1.08974[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.2261[/C][C]0.473854[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]9.89352[/C][C]-0.893522[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.5771[/C][C]-1.87715[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.08785[/C][C]1.71215[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]8.73274[/C][C]1.56726[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.9389[/C][C]-0.53888[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.1198[/C][C]2.58022[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.7885[/C][C]-2.48849[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.2565[/C][C]-0.456484[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.80003[/C][C]-3.90003[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.0579[/C][C]0.34207[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.9818[/C][C]1.01818[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.8527[/C][C]-1.05266[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]8.46037[/C][C]3.83963[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.9849[/C][C]-1.68486[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.65656[/C][C]2.14344[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.66095[/C][C]-1.76095[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.54634[/C][C]3.15366[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.04862[/C][C]3.25138[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.5717[/C][C]1.02825[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.24543[/C][C]-0.545429[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.7441[/C][C]0.155876[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.5734[/C][C]0.526574[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.026[/C][C]3.27402[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.67044[/C][C]0.429565[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.1763[/C][C]-5.47633[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]9.6628[/C][C]4.6372[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.38205[/C][C]0.617947[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.7094[/C][C]2.59059[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.7969[/C][C]-3.49688[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.141[/C][C]1.35903[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]8.82937[/C][C]-1.22937[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.7451[/C][C]2.15495[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.4261[/C][C]-3.22605[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.30081[/C][C]0.799186[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.8378[/C][C]-1.73776[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.2213[/C][C]-2.22132[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.8486[/C][C]2.65138[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.9072[/C][C]1.29275[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.0668[/C][C]-0.766786[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.2594[/C][C]1.14059[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]9.7239[/C][C]-0.923903[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.9491[/C][C]3.65086[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]11.0295[/C][C]1.57052[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.743294[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.9097[/C][C]2.09033[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.7263[/C][C]0.873661[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]12.5002[/C][C]0.699781[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.0424[/C][C]-2.14242[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.75645[/C][C]-0.05645[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.54235[/C][C]2.95765[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]12.9939[/C][C]0.406101[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]15.876[/C][C]-4.97603[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.33735[/C][C]-1.03735[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]9.58147[/C][C]0.718535[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]9.56354[/C][C]2.23646[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]8.62543[/C][C]2.57457[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]12.7134[/C][C]-1.31337[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.91177[/C][C]1.68823[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.40606[/C][C]3.79394[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]17.0406[/C][C]-4.4406[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.57573[/C][C]-1.97573[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]10.8033[/C][C]-0.903315[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.6871[/C][C]-1.8871[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.33671[/C][C]-1.63671[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.5937[/C][C]-3.59371[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]4.95647[/C][C]2.34353[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.50856[/C][C]3.89144[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]15.8894[/C][C]-2.28938[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]5.95077[/C][C]1.94923[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.5594[/C][C]0.140568[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.9146[/C][C]-0.614632[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.66593[/C][C]-1.36593[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]5.41601[/C][C]4.18399[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]15.8423[/C][C]-1.64233[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.56188[/C][C]3.93812[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.5063[/C][C]-5.00627[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]6.63323[/C][C]-1.73323[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.5485[/C][C]-1.1485[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.7619[/C][C]0.838095[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]9.77623[/C][C]1.82377[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.7155[/C][C]-6.6155[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]4.12232[/C][C]0.227678[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.64761[/C][C]3.05239[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.6593[/C][C]2.44069[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]19.4972[/C][C]-1.64722[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.6299[/C][C]0.97011[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.9245[/C][C]-1.32446[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]15.2952[/C][C]1.80483[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.6559[/C][C]-2.55593[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]14.4733[/C][C]1.62671[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]11.4187[/C][C]1.93132[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]13.8743[/C][C]4.52565[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.454[/C][C]-2.75405[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.0805[/C][C]-0.480474[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.1938[/C][C]1.40615[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.4757[/C][C]-0.275662[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]11.0739[/C][C]2.52608[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.7889[/C][C]1.11108[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]12.8516[/C][C]1.24837[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]15.5963[/C][C]-1.09632[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.0543[/C][C]1.09575[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.6649[/C][C]1.08508[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.7437[/C][C]0.0563077[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.566[/C][C]-0.115969[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.50917[/C][C]3.14083[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.0919[/C][C]-1.74191[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]6.74364[/C][C]1.85636[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.3232[/C][C]1.07683[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.6458[/C][C]-0.545827[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.83852[/C][C]2.76148[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.2552[/C][C]0.49479[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.8858[/C][C]3.36416[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]17.5285[/C][C]0.121497[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]15.5732[/C][C]0.776798[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.9727[/C][C]-0.322713[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.6719[/C][C]-0.0719316[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.5603[/C][C]-0.210314[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.4458[/C][C]2.30422[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]24.1461[/C][C]-5.89609[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]9.08189[/C][C]0.818108[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.4583[/C][C]2.54174[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.5646[/C][C]-0.314613[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.2966[/C][C]1.55338[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]15.341[/C][C]-0.740978[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.2702[/C][C]1.57981[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.753[/C][C]1.19697[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]17.7789[/C][C]-2.17892[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]17.257[/C][C]-2.407[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]10.4597[/C][C]1.29035[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.5988[/C][C]1.85118[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]16.4307[/C][C]-0.530685[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]10.4398[/C][C]6.66021[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]15.1086[/C][C]0.991408[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.0451[/C][C]-0.145072[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]9.32185[/C][C]1.62815[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.8963[/C][C]1.55372[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.2447[/C][C]-0.144675[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]18.1103[/C][C]-3.11034[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.0411[/C][C]1.30887[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.5831[/C][C]2.36688[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]20.1577[/C][C]-2.05771[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.8214[/C][C]-0.221393[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.5758[/C][C]-0.175757[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.8862[/C][C]2.51379[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.8575[/C][C]-1.25753[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.7372[/C][C]2.61281[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.506[/C][C]-1.40596[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.8868[/C][C]-3.53676[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]10.1848[/C][C]-2.58481[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.5487[/C][C]-2.14873[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.1507[/C][C]2.74926[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]19.2951[/C][C]-0.195072[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]17.8755[/C][C]-2.62552[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.6126[/C][C]0.287374[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]13.4203[/C][C]2.67973[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.5474[/C][C]-2.19738[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]15.1985[/C][C]-2.04846[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.2715[/C][C]-0.121527[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.3371[/C][C]-2.73714[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.33751[/C][C]1.01249[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.6653[/C][C]-3.26535[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.25056[/C][C]3.34944[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.9181[/C][C]-0.718068[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.5778[/C][C]1.02223[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.6709[/C][C]-1.82088[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.5529[/C][C]0.197085[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.8858[/C][C]1.21418[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.1943[/C][C]0.705717[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]15.0561[/C][C]1.19389[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.8553[/C][C]0.394722[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.1562[/C][C]-1.55625[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.6717[/C][C]-0.0717165[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.0604[/C][C]-0.410359[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.4733[/C][C]1.27667[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.7808[/C][C]-1.1808[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.6478[/C][C]0.202196[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]9.96126[/C][C]2.68874[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.3597[/C][C]1.84032[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.7712[/C][C]-1.17117[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]10.8233[/C][C]0.376696[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.6449[/C][C]-2.39486[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.151[/C][C]-0.25098[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]13.7063[/C][C]-0.506293[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]16.8593[/C][C]-0.509298[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]11.1171[/C][C]1.28291[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]13.7183[/C][C]2.13168[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.9087[/C][C]-1.75873[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.8447[/C][C]-0.694703[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]12.8838[/C][C]2.76619[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]21.8694[/C][C]-4.11937[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.74871[/C][C]-1.09871[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.9407[/C][C]2.4093[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]12.8931[/C][C]2.70694[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]16.4301[/C][C]2.86986[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]12.6285[/C][C]2.57146[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.0634[/C][C]2.0366[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.5598[/C][C]3.04018[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.121[/C][C]3.27896[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]15.558[/C][C]3.49201[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.3235[/C][C]2.22655[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.3899[/C][C]-0.289945[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]15.6261[/C][C]-2.52611[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.2517[/C][C]-2.40169[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.045[/C][C]-6.54496[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]4.62445[/C][C]-0.124455[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]12.6542[/C][C]-0.80423[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]14.5034[/C][C]-0.903399[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.4201[/C][C]-0.720088[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.621[/C][C]-1.22098[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.1971[/C][C]-1.84707[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.8431[/C][C]0.556915[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.267[/C][C]1.63304[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.3651[/C][C]-2.46513[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.8357[/C][C]-0.635653[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]14.6079[/C][C]-0.00786784[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]16.8092[/C][C]0.79083[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.4328[/C][C]0.617188[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.5724[/C][C]-0.472363[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]15.5997[/C][C]-2.24973[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.5401[/C][C]-1.69006[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.824[/C][C]0.12598[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.9805[/C][C]0.769481[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]17.4068[/C][C]-2.25679[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.6244[/C][C]0.575626[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.5752[/C][C]-4.72519[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]12.8331[/C][C]-4.98307[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.243[/C][C]-2.54303[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.5501[/C][C]-6.95014[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.62255[/C][C]-0.772548[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.2466[/C][C]-2.29656[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]15.6531[/C][C]-3.30305[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]8.94099[/C][C]1.00901[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.2058[/C][C]1.6942[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.6317[/C][C]0.0183332[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.6811[/C][C]-0.281074[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]12.5118[/C][C]1.43815[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]14.1108[/C][C]1.58921[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.435[/C][C]-1.58505[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]10.2972[/C][C]0.65278[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.2122[/C][C]-0.862229[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]11.367[/C][C]0.832968[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.5875[/C][C]1.51246[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.5788[/C][C]0.17115[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.3293[/C][C]-0.129303[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.7142[/C][C]0.885789[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.3393[/C][C]-2.6893[/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=268316&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&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
112.913.047-0.146971
212.210.61691.58309
312.811.63291.16707
47.411.5542-4.15421
56.710.4059-3.70587
612.613.4198-0.819781
714.812.09772.70227
813.310.47772.82227
911.111.6724-0.572415
108.211.9332-3.73325
1111.411.7418-0.341847
126.411.5926-5.1926
1310.68.927781.67222
141213.3865-1.3865
156.36.76326-0.46326
1611.39.186582.11342
1711.912.3479-0.447902
189.310.2677-0.967693
199.611.6133-2.01329
20109.615040.38496
216.410.008-3.60801
2213.810.06323.73684
2310.814.0617-3.26169
2413.812.98840.811633
2511.711.06150.638484
2610.914.9311-4.03111
2716.113.38452.71554
2813.410.23643.16357
299.911.5711-1.67107
3011.511.21660.283354
318.39.38974-1.08974
3211.711.22610.473854
3399.89352-0.893522
349.711.5771-1.87715
3510.89.087851.71215
3610.38.732741.56726
3710.410.9389-0.53888
3812.710.11982.58022
399.311.7885-2.48849
4011.812.2565-0.456484
415.99.80003-3.90003
4211.411.05790.34207
431311.98181.01818
4410.811.8527-1.05266
4512.38.460373.83963
4611.312.9849-1.68486
4711.89.656562.14344
487.99.66095-1.76095
4912.79.546343.15366
5012.39.048623.25138
5111.610.57171.02825
526.77.24543-0.545429
5310.910.74410.155876
5412.111.57340.526574
5513.310.0263.27402
5610.19.670440.429565
575.711.1763-5.47633
5814.39.66284.6372
5987.382050.617947
6013.310.70942.59059
619.312.7969-3.49688
6212.511.1411.35903
637.68.82937-1.22937
6415.913.74512.15495
659.212.4261-3.22605
669.18.300810.799186
6711.112.8378-1.73776
681315.2213-2.22132
6914.511.84862.65138
7012.210.90721.29275
7112.313.0668-0.766786
7211.410.25941.14059
738.89.7239-0.923903
7414.610.94913.65086
7512.611.02951.57052
76NANA0.743294
771310.90972.09033
7812.611.72630.873661
7913.212.50020.699781
809.912.0424-2.14242
817.77.75645-0.05645
8210.57.542352.95765
8313.412.99390.406101
8410.915.876-4.97603
854.35.33735-1.03735
8610.39.581470.718535
8711.89.563542.23646
8811.28.625432.57457
8911.412.7134-1.31337
908.66.911771.68823
9113.29.406063.79394
9212.617.0406-4.4406
935.67.57573-1.97573
949.910.8033-0.903315
958.810.6871-1.8871
967.79.33671-1.63671
97912.5937-3.59371
987.34.956472.34353
9911.47.508563.89144
10013.615.8894-2.28938
1017.95.950771.94923
10210.710.55940.140568
10310.310.9146-0.614632
1048.39.66593-1.36593
1059.65.416014.18399
10614.215.8423-1.64233
1078.54.561883.93812
10813.518.5063-5.00627
1094.96.63323-1.73323
1106.47.5485-1.1485
1119.68.76190.838095
11211.69.776231.82377
11311.117.7155-6.6155
1144.354.122320.227678
11512.79.647613.05239
11618.115.65932.44069
11717.8519.4972-1.64722
11816.615.62990.97011
11912.613.9245-1.32446
12017.115.29521.80483
12119.121.6559-2.55593
12216.114.47331.62671
12313.3511.41871.93132
12418.413.87434.52565
12514.717.454-2.75405
12610.611.0805-0.480474
12712.611.19381.40615
12816.216.4757-0.275662
12913.611.07392.52608
13018.917.78891.11108
13114.112.85161.24837
13214.515.5963-1.09632
13316.1515.05431.09575
13414.7513.66491.08508
13514.814.74370.0563077
13612.4512.566-0.115969
13712.659.509173.14083
13817.3519.0919-1.74191
1398.66.743641.85636
14018.417.32321.07683
14116.116.6458-0.545827
14211.68.838522.76148
14317.7517.25520.49479
14415.2511.88583.36416
14517.6517.52850.121497
14616.3515.57320.776798
14717.6517.9727-0.322713
14813.613.6719-0.0719316
14914.3514.5603-0.210314
15014.7512.44582.30422
15118.2524.1461-5.89609
1529.99.081890.818108
1531613.45832.54174
15418.2518.5646-0.314613
15516.8515.29661.55338
15614.615.341-0.740978
15713.8512.27021.57981
15818.9517.7531.19697
15915.617.7789-2.17892
16014.8517.257-2.407
16111.7510.45971.29035
16218.4516.59881.85118
16315.916.4307-0.530685
16417.110.43986.66021
16516.115.10860.991408
16619.920.0451-0.145072
16710.959.321851.62815
16818.4516.89631.55372
16915.115.2447-0.144675
1701518.1103-3.11034
17111.3510.04111.30887
17215.9513.58312.36688
17318.120.1577-2.05771
17414.614.8214-0.221393
17515.415.5758-0.175757
17615.412.88622.51379
17717.618.8575-1.25753
17813.3510.73722.61281
17919.120.506-1.40596
18015.3518.8868-3.53676
1817.610.1848-2.58481
18213.415.5487-2.14873
18313.911.15072.74926
18419.119.2951-0.195072
18515.2517.8755-2.62552
18612.912.61260.287374
18716.113.42032.67973
18817.3519.5474-2.19738
18913.1515.1985-2.04846
19012.1512.2715-0.121527
19112.615.3371-2.73714
19210.359.337511.01249
19315.418.6653-3.26535
1949.66.250563.34944
19518.218.9181-0.718068
19613.612.57781.02223
19714.8516.6709-1.82088
19814.7514.55290.197085
19914.112.88581.21418
20014.914.19430.705717
20116.2515.05611.19389
20219.2518.85530.394722
20313.615.1562-1.55625
20413.613.6717-0.0717165
20515.6516.0604-0.410359
20612.7511.47331.27667
20714.615.7808-1.1808
2089.859.64780.202196
20912.659.961262.68874
21019.217.35971.84032
21116.617.7712-1.17117
21211.210.82330.376696
21315.2517.6449-2.39486
21411.912.151-0.25098
21513.213.7063-0.506293
21616.3516.8593-0.509298
21712.411.11711.28291
21815.8513.71832.13168
21918.1519.9087-1.75873
22011.1511.8447-0.694703
22115.6512.88382.76619
22217.7521.8694-4.11937
2237.658.74871-1.09871
22412.359.94072.4093
22515.612.89312.70694
22619.316.43012.86986
22715.212.62852.57146
22817.115.06342.0366
22915.612.55983.04018
23018.415.1213.27896
23119.0515.5583.49201
23218.5516.32352.22655
23319.119.3899-0.289945
23413.115.6261-2.52611
23512.8515.2517-2.40169
2369.516.045-6.54496
2374.54.62445-0.124455
23811.8512.6542-0.80423
23913.614.5034-0.903399
24011.712.4201-0.720088
24112.413.621-1.22098
24213.3515.1971-1.84707
24311.410.84310.556915
24414.913.2671.63304
24519.922.3651-2.46513
24611.211.8357-0.635653
24714.614.6079-0.00786784
24817.616.80920.79083
24914.0513.43280.617188
25016.116.5724-0.472363
25113.3515.5997-2.24973
25211.8513.5401-1.69006
25311.9511.8240.12598
25414.7513.98050.769481
25515.1517.4068-2.25679
25613.212.62440.575626
25716.8521.5752-4.72519
2587.8512.8331-4.98307
2597.710.243-2.54303
26012.619.5501-6.95014
2617.858.62255-0.772548
26210.9513.2466-2.29656
26312.3515.6531-3.30305
2649.958.940991.00901
26514.913.20581.6942
26616.6516.63170.0183332
26713.413.6811-0.281074
26813.9512.51181.43815
26915.714.11081.58921
27016.8518.435-1.58505
27110.9510.29720.65278
27215.3516.2122-0.862229
27312.211.3670.832968
27415.113.58751.51246
27517.7517.57880.17115
27615.215.3293-0.129303
27714.613.71420.885789
27816.6519.3393-2.6893
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.6761960.6476080.323804
140.5399510.9200980.460049
150.3975840.7951670.602416
160.2754260.5508520.724574
170.2554480.5108960.744552
180.1977710.3955430.802229
190.1358010.2716020.864199
200.09108990.182180.90891
210.05993090.1198620.940069
220.04453960.08907910.95546
230.1236490.2472990.876351
240.2007530.4015070.799247
250.1973530.3947060.802647
260.1584410.3168820.841559
270.1268950.2537890.873105
280.1003910.2007820.899609
290.07386560.1477310.926134
300.05936730.1187350.940633
310.08692440.1738490.913076
320.08774290.1754860.912257
330.09372060.1874410.906279
340.07431550.1486310.925684
350.05481520.109630.945185
360.06062310.1212460.939377
370.06203670.1240730.937963
380.06893580.1378720.931064
390.06521560.1304310.934784
400.05161430.1032290.948386
410.06837060.1367410.931629
420.06479050.1295810.935209
430.06045430.1209090.939546
440.05128230.1025650.948718
450.04897590.09795180.951024
460.03824450.07648890.961756
470.04194970.08389930.95805
480.03921060.07842130.960789
490.0694080.1388160.930592
500.08337180.1667440.916628
510.06598640.1319730.934014
520.08011460.1602290.919885
530.07276650.1455330.927233
540.06112460.1222490.938875
550.1345810.2691620.865419
560.1104270.2208540.889573
570.4027330.8054660.597267
580.4492110.8984220.550789
590.4122780.8245560.587722
600.4083130.8166270.591687
610.4476450.8952890.552355
620.4409130.8818260.559087
630.5897870.8204250.410213
640.6329020.7341950.367098
650.6616540.6766930.338346
660.6354140.7291720.364586
670.6110140.7779720.388986
680.5936470.8127070.406353
690.6395540.7208910.360446
700.6119220.7761550.388078
710.5759890.8480230.424011
720.5560370.8879260.443963
730.5427140.9145720.457286
740.6023280.7953440.397672
750.5841940.8316120.415806
760.551840.896320.44816
770.5294310.9411380.470569
780.5156850.9686310.484315
790.4796460.9592920.520354
800.4895570.9791140.510443
810.4515950.9031890.548405
820.4721140.9442280.527886
830.4358910.8717830.564109
840.6376670.7246660.362333
850.6197710.7604570.380229
860.5832570.8334870.416743
870.5700270.8599470.429973
880.5681730.8636540.431827
890.5552550.8894890.444745
900.5391760.9216480.460824
910.5751490.8497010.424851
920.7197770.5604460.280223
930.7142090.5715820.285791
940.698010.603980.30199
950.6941780.6116450.305822
960.677330.6453390.32267
970.7297920.5404170.270208
980.7233130.5533740.276687
990.76890.46220.2311
1000.7760010.4479990.223999
1010.7603740.4792510.239626
1020.7309760.5380480.269024
1030.7109020.5781960.289098
1040.6928840.6142330.307116
1050.7544020.4911950.245598
1060.7414430.5171140.258557
1070.799290.4014190.20071
1080.8822280.2355450.117772
1090.8815880.2368230.118412
1100.8711310.2577380.128869
1110.8565090.2869820.143491
1120.8418250.3163510.158175
1130.8875060.2249870.112494
1140.9067840.1864320.0932162
1150.9506230.0987550.0493775
1160.9580290.08394290.0419715
1170.9522810.09543780.0477189
1180.9449710.1100580.0550288
1190.9403720.1192560.0596278
1200.9405540.1188930.0594465
1210.9471060.1057870.0528935
1220.9441740.1116530.0558263
1230.9434140.1131730.0565863
1240.9662310.06753880.0337694
1250.9707270.05854580.0292729
1260.9648360.07032740.0351637
1270.959790.08042090.0402104
1280.95190.09619930.0480997
1290.9514360.09712880.0485644
1300.9440580.1118830.0559416
1310.9364850.1270290.0635147
1320.930680.1386390.0693197
1330.9204450.1591090.0795547
1340.9083920.1832150.0916075
1350.8951320.2097350.104868
1360.8785660.2428680.121434
1370.8931670.2136650.106833
1380.8918120.2163750.108188
1390.8829130.2341740.117087
1400.8673210.2653590.132679
1410.8592520.2814960.140748
1420.8662170.2675660.133783
1430.8467890.3064210.153211
1440.8672050.2655890.132795
1450.8473560.3052880.152644
1460.8281610.3436780.171839
1470.8077130.3845750.192287
1480.7827710.4344580.217229
1490.757080.4858390.24292
1500.7518040.4963910.248196
1510.9009590.1980820.0990411
1520.8856110.2287780.114389
1530.8862180.2275630.113782
1540.8685940.2628110.131406
1550.8595540.2808910.140446
1560.8436380.3127250.156362
1570.826960.346080.17304
1580.8096080.3807840.190392
1590.8223640.3552720.177636
1600.8240740.3518520.175926
1610.8051180.3897650.194882
1620.7968190.4063630.203181
1630.7771730.4456540.222827
1640.9676530.06469380.0323469
1650.9621070.07578670.0378933
1660.9605010.07899890.0394994
1670.9546210.09075870.0453793
1680.9536050.09279060.0463953
1690.9445520.1108970.0554483
1700.9566890.08662180.0433109
1710.9506020.09879630.0493981
1720.9488860.1022270.0511137
1730.9523920.09521530.0476076
1740.9428950.114210.0571049
1750.9318410.1363180.0681588
1760.9345530.1308930.0654465
1770.925520.1489590.0744797
1780.9293130.1413730.0706866
1790.9279260.1441470.0720737
1800.9351860.1296280.0648141
1810.9451320.1097370.0548683
1820.9496230.1007530.0503767
1830.9536160.09276740.0463837
1840.9448370.1103260.0551628
1850.9539750.09204960.0460248
1860.9442690.1114620.0557312
1870.9480880.1038240.0519121
1880.9529620.09407620.0470381
1890.9551950.08961090.0448054
1900.9482370.1035260.0517631
1910.9479870.1040250.0520125
1920.9376770.1246470.0623234
1930.9473620.1052750.0526375
1940.9526420.09471650.0473583
1950.943190.113620.0568098
1960.938620.1227590.0613797
1970.9396910.1206190.0603094
1980.9269250.1461510.0730755
1990.9172260.1655490.0827744
2000.9011430.1977140.0988568
2010.8922360.2155290.107764
2020.8763840.2472320.123616
2030.8740290.2519430.125971
2040.853980.2920410.14602
2050.8327280.3345440.167272
2060.8324840.3350320.167516
2070.8282110.3435780.171789
2080.8188170.3623670.181183
2090.8055880.3888240.194412
2100.8076630.3846740.192337
2110.790670.418660.20933
2120.7590790.4818410.240921
2130.7601570.4796870.239843
2140.7271070.5457860.272893
2150.7053260.5893470.294674
2160.6677340.6645310.332266
2170.6628370.6743260.337163
2180.6413140.7173710.358686
2190.6122010.7755970.387799
2200.582110.8357790.41789
2210.5914550.817090.408545
2220.6619020.6761970.338098
2230.6245880.7508240.375412
2240.7190890.5618220.280911
2250.713670.5726590.28633
2260.7822990.4354030.217701
2270.791910.4161790.20809
2280.8227650.3544690.177235
2290.8831810.2336380.116819
2300.9155480.1689030.0844517
2310.9267060.1465880.0732942
2320.9222370.1555270.0777634
2330.9082310.1835370.0917686
2340.8917150.2165690.108285
2350.8706770.2586460.129323
2360.9334740.1330530.0665264
2370.9219030.1561950.0780974
2380.8995360.2009270.100464
2390.8781790.2436420.121821
2400.8467360.3065290.153264
2410.8243250.3513510.175675
2420.7864910.4270190.213509
2430.7576680.4846640.242332
2440.7198880.5602240.280112
2450.6839890.6320210.316011
2460.6289790.7420410.371021
2470.5684630.8630740.431537
2480.6424630.7150750.357537
2490.5784260.8431490.421574
2500.5572890.8854210.442711
2510.5158060.9683890.484194
2520.4554050.9108110.544595
2530.4119880.8239760.588012
2540.4515170.9030330.548483
2550.4572260.9144510.542774
2560.3995680.7991360.600432
2570.4184330.8368660.581567
2580.5886920.8226160.411308
2590.5769720.8460550.423028
2600.9562550.08749010.043745
2610.9219250.156150.0780751
2620.9757790.04844170.0242208
2630.9898640.0202720.010136
2640.9731270.05374660.0268733
2650.9470890.1058220.0529112
2660.8788670.2422660.121133

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.676196 & 0.647608 & 0.323804 \tabularnewline
14 & 0.539951 & 0.920098 & 0.460049 \tabularnewline
15 & 0.397584 & 0.795167 & 0.602416 \tabularnewline
16 & 0.275426 & 0.550852 & 0.724574 \tabularnewline
17 & 0.255448 & 0.510896 & 0.744552 \tabularnewline
18 & 0.197771 & 0.395543 & 0.802229 \tabularnewline
19 & 0.135801 & 0.271602 & 0.864199 \tabularnewline
20 & 0.0910899 & 0.18218 & 0.90891 \tabularnewline
21 & 0.0599309 & 0.119862 & 0.940069 \tabularnewline
22 & 0.0445396 & 0.0890791 & 0.95546 \tabularnewline
23 & 0.123649 & 0.247299 & 0.876351 \tabularnewline
24 & 0.200753 & 0.401507 & 0.799247 \tabularnewline
25 & 0.197353 & 0.394706 & 0.802647 \tabularnewline
26 & 0.158441 & 0.316882 & 0.841559 \tabularnewline
27 & 0.126895 & 0.253789 & 0.873105 \tabularnewline
28 & 0.100391 & 0.200782 & 0.899609 \tabularnewline
29 & 0.0738656 & 0.147731 & 0.926134 \tabularnewline
30 & 0.0593673 & 0.118735 & 0.940633 \tabularnewline
31 & 0.0869244 & 0.173849 & 0.913076 \tabularnewline
32 & 0.0877429 & 0.175486 & 0.912257 \tabularnewline
33 & 0.0937206 & 0.187441 & 0.906279 \tabularnewline
34 & 0.0743155 & 0.148631 & 0.925684 \tabularnewline
35 & 0.0548152 & 0.10963 & 0.945185 \tabularnewline
36 & 0.0606231 & 0.121246 & 0.939377 \tabularnewline
37 & 0.0620367 & 0.124073 & 0.937963 \tabularnewline
38 & 0.0689358 & 0.137872 & 0.931064 \tabularnewline
39 & 0.0652156 & 0.130431 & 0.934784 \tabularnewline
40 & 0.0516143 & 0.103229 & 0.948386 \tabularnewline
41 & 0.0683706 & 0.136741 & 0.931629 \tabularnewline
42 & 0.0647905 & 0.129581 & 0.935209 \tabularnewline
43 & 0.0604543 & 0.120909 & 0.939546 \tabularnewline
44 & 0.0512823 & 0.102565 & 0.948718 \tabularnewline
45 & 0.0489759 & 0.0979518 & 0.951024 \tabularnewline
46 & 0.0382445 & 0.0764889 & 0.961756 \tabularnewline
47 & 0.0419497 & 0.0838993 & 0.95805 \tabularnewline
48 & 0.0392106 & 0.0784213 & 0.960789 \tabularnewline
49 & 0.069408 & 0.138816 & 0.930592 \tabularnewline
50 & 0.0833718 & 0.166744 & 0.916628 \tabularnewline
51 & 0.0659864 & 0.131973 & 0.934014 \tabularnewline
52 & 0.0801146 & 0.160229 & 0.919885 \tabularnewline
53 & 0.0727665 & 0.145533 & 0.927233 \tabularnewline
54 & 0.0611246 & 0.122249 & 0.938875 \tabularnewline
55 & 0.134581 & 0.269162 & 0.865419 \tabularnewline
56 & 0.110427 & 0.220854 & 0.889573 \tabularnewline
57 & 0.402733 & 0.805466 & 0.597267 \tabularnewline
58 & 0.449211 & 0.898422 & 0.550789 \tabularnewline
59 & 0.412278 & 0.824556 & 0.587722 \tabularnewline
60 & 0.408313 & 0.816627 & 0.591687 \tabularnewline
61 & 0.447645 & 0.895289 & 0.552355 \tabularnewline
62 & 0.440913 & 0.881826 & 0.559087 \tabularnewline
63 & 0.589787 & 0.820425 & 0.410213 \tabularnewline
64 & 0.632902 & 0.734195 & 0.367098 \tabularnewline
65 & 0.661654 & 0.676693 & 0.338346 \tabularnewline
66 & 0.635414 & 0.729172 & 0.364586 \tabularnewline
67 & 0.611014 & 0.777972 & 0.388986 \tabularnewline
68 & 0.593647 & 0.812707 & 0.406353 \tabularnewline
69 & 0.639554 & 0.720891 & 0.360446 \tabularnewline
70 & 0.611922 & 0.776155 & 0.388078 \tabularnewline
71 & 0.575989 & 0.848023 & 0.424011 \tabularnewline
72 & 0.556037 & 0.887926 & 0.443963 \tabularnewline
73 & 0.542714 & 0.914572 & 0.457286 \tabularnewline
74 & 0.602328 & 0.795344 & 0.397672 \tabularnewline
75 & 0.584194 & 0.831612 & 0.415806 \tabularnewline
76 & 0.55184 & 0.89632 & 0.44816 \tabularnewline
77 & 0.529431 & 0.941138 & 0.470569 \tabularnewline
78 & 0.515685 & 0.968631 & 0.484315 \tabularnewline
79 & 0.479646 & 0.959292 & 0.520354 \tabularnewline
80 & 0.489557 & 0.979114 & 0.510443 \tabularnewline
81 & 0.451595 & 0.903189 & 0.548405 \tabularnewline
82 & 0.472114 & 0.944228 & 0.527886 \tabularnewline
83 & 0.435891 & 0.871783 & 0.564109 \tabularnewline
84 & 0.637667 & 0.724666 & 0.362333 \tabularnewline
85 & 0.619771 & 0.760457 & 0.380229 \tabularnewline
86 & 0.583257 & 0.833487 & 0.416743 \tabularnewline
87 & 0.570027 & 0.859947 & 0.429973 \tabularnewline
88 & 0.568173 & 0.863654 & 0.431827 \tabularnewline
89 & 0.555255 & 0.889489 & 0.444745 \tabularnewline
90 & 0.539176 & 0.921648 & 0.460824 \tabularnewline
91 & 0.575149 & 0.849701 & 0.424851 \tabularnewline
92 & 0.719777 & 0.560446 & 0.280223 \tabularnewline
93 & 0.714209 & 0.571582 & 0.285791 \tabularnewline
94 & 0.69801 & 0.60398 & 0.30199 \tabularnewline
95 & 0.694178 & 0.611645 & 0.305822 \tabularnewline
96 & 0.67733 & 0.645339 & 0.32267 \tabularnewline
97 & 0.729792 & 0.540417 & 0.270208 \tabularnewline
98 & 0.723313 & 0.553374 & 0.276687 \tabularnewline
99 & 0.7689 & 0.4622 & 0.2311 \tabularnewline
100 & 0.776001 & 0.447999 & 0.223999 \tabularnewline
101 & 0.760374 & 0.479251 & 0.239626 \tabularnewline
102 & 0.730976 & 0.538048 & 0.269024 \tabularnewline
103 & 0.710902 & 0.578196 & 0.289098 \tabularnewline
104 & 0.692884 & 0.614233 & 0.307116 \tabularnewline
105 & 0.754402 & 0.491195 & 0.245598 \tabularnewline
106 & 0.741443 & 0.517114 & 0.258557 \tabularnewline
107 & 0.79929 & 0.401419 & 0.20071 \tabularnewline
108 & 0.882228 & 0.235545 & 0.117772 \tabularnewline
109 & 0.881588 & 0.236823 & 0.118412 \tabularnewline
110 & 0.871131 & 0.257738 & 0.128869 \tabularnewline
111 & 0.856509 & 0.286982 & 0.143491 \tabularnewline
112 & 0.841825 & 0.316351 & 0.158175 \tabularnewline
113 & 0.887506 & 0.224987 & 0.112494 \tabularnewline
114 & 0.906784 & 0.186432 & 0.0932162 \tabularnewline
115 & 0.950623 & 0.098755 & 0.0493775 \tabularnewline
116 & 0.958029 & 0.0839429 & 0.0419715 \tabularnewline
117 & 0.952281 & 0.0954378 & 0.0477189 \tabularnewline
118 & 0.944971 & 0.110058 & 0.0550288 \tabularnewline
119 & 0.940372 & 0.119256 & 0.0596278 \tabularnewline
120 & 0.940554 & 0.118893 & 0.0594465 \tabularnewline
121 & 0.947106 & 0.105787 & 0.0528935 \tabularnewline
122 & 0.944174 & 0.111653 & 0.0558263 \tabularnewline
123 & 0.943414 & 0.113173 & 0.0565863 \tabularnewline
124 & 0.966231 & 0.0675388 & 0.0337694 \tabularnewline
125 & 0.970727 & 0.0585458 & 0.0292729 \tabularnewline
126 & 0.964836 & 0.0703274 & 0.0351637 \tabularnewline
127 & 0.95979 & 0.0804209 & 0.0402104 \tabularnewline
128 & 0.9519 & 0.0961993 & 0.0480997 \tabularnewline
129 & 0.951436 & 0.0971288 & 0.0485644 \tabularnewline
130 & 0.944058 & 0.111883 & 0.0559416 \tabularnewline
131 & 0.936485 & 0.127029 & 0.0635147 \tabularnewline
132 & 0.93068 & 0.138639 & 0.0693197 \tabularnewline
133 & 0.920445 & 0.159109 & 0.0795547 \tabularnewline
134 & 0.908392 & 0.183215 & 0.0916075 \tabularnewline
135 & 0.895132 & 0.209735 & 0.104868 \tabularnewline
136 & 0.878566 & 0.242868 & 0.121434 \tabularnewline
137 & 0.893167 & 0.213665 & 0.106833 \tabularnewline
138 & 0.891812 & 0.216375 & 0.108188 \tabularnewline
139 & 0.882913 & 0.234174 & 0.117087 \tabularnewline
140 & 0.867321 & 0.265359 & 0.132679 \tabularnewline
141 & 0.859252 & 0.281496 & 0.140748 \tabularnewline
142 & 0.866217 & 0.267566 & 0.133783 \tabularnewline
143 & 0.846789 & 0.306421 & 0.153211 \tabularnewline
144 & 0.867205 & 0.265589 & 0.132795 \tabularnewline
145 & 0.847356 & 0.305288 & 0.152644 \tabularnewline
146 & 0.828161 & 0.343678 & 0.171839 \tabularnewline
147 & 0.807713 & 0.384575 & 0.192287 \tabularnewline
148 & 0.782771 & 0.434458 & 0.217229 \tabularnewline
149 & 0.75708 & 0.485839 & 0.24292 \tabularnewline
150 & 0.751804 & 0.496391 & 0.248196 \tabularnewline
151 & 0.900959 & 0.198082 & 0.0990411 \tabularnewline
152 & 0.885611 & 0.228778 & 0.114389 \tabularnewline
153 & 0.886218 & 0.227563 & 0.113782 \tabularnewline
154 & 0.868594 & 0.262811 & 0.131406 \tabularnewline
155 & 0.859554 & 0.280891 & 0.140446 \tabularnewline
156 & 0.843638 & 0.312725 & 0.156362 \tabularnewline
157 & 0.82696 & 0.34608 & 0.17304 \tabularnewline
158 & 0.809608 & 0.380784 & 0.190392 \tabularnewline
159 & 0.822364 & 0.355272 & 0.177636 \tabularnewline
160 & 0.824074 & 0.351852 & 0.175926 \tabularnewline
161 & 0.805118 & 0.389765 & 0.194882 \tabularnewline
162 & 0.796819 & 0.406363 & 0.203181 \tabularnewline
163 & 0.777173 & 0.445654 & 0.222827 \tabularnewline
164 & 0.967653 & 0.0646938 & 0.0323469 \tabularnewline
165 & 0.962107 & 0.0757867 & 0.0378933 \tabularnewline
166 & 0.960501 & 0.0789989 & 0.0394994 \tabularnewline
167 & 0.954621 & 0.0907587 & 0.0453793 \tabularnewline
168 & 0.953605 & 0.0927906 & 0.0463953 \tabularnewline
169 & 0.944552 & 0.110897 & 0.0554483 \tabularnewline
170 & 0.956689 & 0.0866218 & 0.0433109 \tabularnewline
171 & 0.950602 & 0.0987963 & 0.0493981 \tabularnewline
172 & 0.948886 & 0.102227 & 0.0511137 \tabularnewline
173 & 0.952392 & 0.0952153 & 0.0476076 \tabularnewline
174 & 0.942895 & 0.11421 & 0.0571049 \tabularnewline
175 & 0.931841 & 0.136318 & 0.0681588 \tabularnewline
176 & 0.934553 & 0.130893 & 0.0654465 \tabularnewline
177 & 0.92552 & 0.148959 & 0.0744797 \tabularnewline
178 & 0.929313 & 0.141373 & 0.0706866 \tabularnewline
179 & 0.927926 & 0.144147 & 0.0720737 \tabularnewline
180 & 0.935186 & 0.129628 & 0.0648141 \tabularnewline
181 & 0.945132 & 0.109737 & 0.0548683 \tabularnewline
182 & 0.949623 & 0.100753 & 0.0503767 \tabularnewline
183 & 0.953616 & 0.0927674 & 0.0463837 \tabularnewline
184 & 0.944837 & 0.110326 & 0.0551628 \tabularnewline
185 & 0.953975 & 0.0920496 & 0.0460248 \tabularnewline
186 & 0.944269 & 0.111462 & 0.0557312 \tabularnewline
187 & 0.948088 & 0.103824 & 0.0519121 \tabularnewline
188 & 0.952962 & 0.0940762 & 0.0470381 \tabularnewline
189 & 0.955195 & 0.0896109 & 0.0448054 \tabularnewline
190 & 0.948237 & 0.103526 & 0.0517631 \tabularnewline
191 & 0.947987 & 0.104025 & 0.0520125 \tabularnewline
192 & 0.937677 & 0.124647 & 0.0623234 \tabularnewline
193 & 0.947362 & 0.105275 & 0.0526375 \tabularnewline
194 & 0.952642 & 0.0947165 & 0.0473583 \tabularnewline
195 & 0.94319 & 0.11362 & 0.0568098 \tabularnewline
196 & 0.93862 & 0.122759 & 0.0613797 \tabularnewline
197 & 0.939691 & 0.120619 & 0.0603094 \tabularnewline
198 & 0.926925 & 0.146151 & 0.0730755 \tabularnewline
199 & 0.917226 & 0.165549 & 0.0827744 \tabularnewline
200 & 0.901143 & 0.197714 & 0.0988568 \tabularnewline
201 & 0.892236 & 0.215529 & 0.107764 \tabularnewline
202 & 0.876384 & 0.247232 & 0.123616 \tabularnewline
203 & 0.874029 & 0.251943 & 0.125971 \tabularnewline
204 & 0.85398 & 0.292041 & 0.14602 \tabularnewline
205 & 0.832728 & 0.334544 & 0.167272 \tabularnewline
206 & 0.832484 & 0.335032 & 0.167516 \tabularnewline
207 & 0.828211 & 0.343578 & 0.171789 \tabularnewline
208 & 0.818817 & 0.362367 & 0.181183 \tabularnewline
209 & 0.805588 & 0.388824 & 0.194412 \tabularnewline
210 & 0.807663 & 0.384674 & 0.192337 \tabularnewline
211 & 0.79067 & 0.41866 & 0.20933 \tabularnewline
212 & 0.759079 & 0.481841 & 0.240921 \tabularnewline
213 & 0.760157 & 0.479687 & 0.239843 \tabularnewline
214 & 0.727107 & 0.545786 & 0.272893 \tabularnewline
215 & 0.705326 & 0.589347 & 0.294674 \tabularnewline
216 & 0.667734 & 0.664531 & 0.332266 \tabularnewline
217 & 0.662837 & 0.674326 & 0.337163 \tabularnewline
218 & 0.641314 & 0.717371 & 0.358686 \tabularnewline
219 & 0.612201 & 0.775597 & 0.387799 \tabularnewline
220 & 0.58211 & 0.835779 & 0.41789 \tabularnewline
221 & 0.591455 & 0.81709 & 0.408545 \tabularnewline
222 & 0.661902 & 0.676197 & 0.338098 \tabularnewline
223 & 0.624588 & 0.750824 & 0.375412 \tabularnewline
224 & 0.719089 & 0.561822 & 0.280911 \tabularnewline
225 & 0.71367 & 0.572659 & 0.28633 \tabularnewline
226 & 0.782299 & 0.435403 & 0.217701 \tabularnewline
227 & 0.79191 & 0.416179 & 0.20809 \tabularnewline
228 & 0.822765 & 0.354469 & 0.177235 \tabularnewline
229 & 0.883181 & 0.233638 & 0.116819 \tabularnewline
230 & 0.915548 & 0.168903 & 0.0844517 \tabularnewline
231 & 0.926706 & 0.146588 & 0.0732942 \tabularnewline
232 & 0.922237 & 0.155527 & 0.0777634 \tabularnewline
233 & 0.908231 & 0.183537 & 0.0917686 \tabularnewline
234 & 0.891715 & 0.216569 & 0.108285 \tabularnewline
235 & 0.870677 & 0.258646 & 0.129323 \tabularnewline
236 & 0.933474 & 0.133053 & 0.0665264 \tabularnewline
237 & 0.921903 & 0.156195 & 0.0780974 \tabularnewline
238 & 0.899536 & 0.200927 & 0.100464 \tabularnewline
239 & 0.878179 & 0.243642 & 0.121821 \tabularnewline
240 & 0.846736 & 0.306529 & 0.153264 \tabularnewline
241 & 0.824325 & 0.351351 & 0.175675 \tabularnewline
242 & 0.786491 & 0.427019 & 0.213509 \tabularnewline
243 & 0.757668 & 0.484664 & 0.242332 \tabularnewline
244 & 0.719888 & 0.560224 & 0.280112 \tabularnewline
245 & 0.683989 & 0.632021 & 0.316011 \tabularnewline
246 & 0.628979 & 0.742041 & 0.371021 \tabularnewline
247 & 0.568463 & 0.863074 & 0.431537 \tabularnewline
248 & 0.642463 & 0.715075 & 0.357537 \tabularnewline
249 & 0.578426 & 0.843149 & 0.421574 \tabularnewline
250 & 0.557289 & 0.885421 & 0.442711 \tabularnewline
251 & 0.515806 & 0.968389 & 0.484194 \tabularnewline
252 & 0.455405 & 0.910811 & 0.544595 \tabularnewline
253 & 0.411988 & 0.823976 & 0.588012 \tabularnewline
254 & 0.451517 & 0.903033 & 0.548483 \tabularnewline
255 & 0.457226 & 0.914451 & 0.542774 \tabularnewline
256 & 0.399568 & 0.799136 & 0.600432 \tabularnewline
257 & 0.418433 & 0.836866 & 0.581567 \tabularnewline
258 & 0.588692 & 0.822616 & 0.411308 \tabularnewline
259 & 0.576972 & 0.846055 & 0.423028 \tabularnewline
260 & 0.956255 & 0.0874901 & 0.043745 \tabularnewline
261 & 0.921925 & 0.15615 & 0.0780751 \tabularnewline
262 & 0.975779 & 0.0484417 & 0.0242208 \tabularnewline
263 & 0.989864 & 0.020272 & 0.010136 \tabularnewline
264 & 0.973127 & 0.0537466 & 0.0268733 \tabularnewline
265 & 0.947089 & 0.105822 & 0.0529112 \tabularnewline
266 & 0.878867 & 0.242266 & 0.121133 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&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]0.676196[/C][C]0.647608[/C][C]0.323804[/C][/ROW]
[ROW][C]14[/C][C]0.539951[/C][C]0.920098[/C][C]0.460049[/C][/ROW]
[ROW][C]15[/C][C]0.397584[/C][C]0.795167[/C][C]0.602416[/C][/ROW]
[ROW][C]16[/C][C]0.275426[/C][C]0.550852[/C][C]0.724574[/C][/ROW]
[ROW][C]17[/C][C]0.255448[/C][C]0.510896[/C][C]0.744552[/C][/ROW]
[ROW][C]18[/C][C]0.197771[/C][C]0.395543[/C][C]0.802229[/C][/ROW]
[ROW][C]19[/C][C]0.135801[/C][C]0.271602[/C][C]0.864199[/C][/ROW]
[ROW][C]20[/C][C]0.0910899[/C][C]0.18218[/C][C]0.90891[/C][/ROW]
[ROW][C]21[/C][C]0.0599309[/C][C]0.119862[/C][C]0.940069[/C][/ROW]
[ROW][C]22[/C][C]0.0445396[/C][C]0.0890791[/C][C]0.95546[/C][/ROW]
[ROW][C]23[/C][C]0.123649[/C][C]0.247299[/C][C]0.876351[/C][/ROW]
[ROW][C]24[/C][C]0.200753[/C][C]0.401507[/C][C]0.799247[/C][/ROW]
[ROW][C]25[/C][C]0.197353[/C][C]0.394706[/C][C]0.802647[/C][/ROW]
[ROW][C]26[/C][C]0.158441[/C][C]0.316882[/C][C]0.841559[/C][/ROW]
[ROW][C]27[/C][C]0.126895[/C][C]0.253789[/C][C]0.873105[/C][/ROW]
[ROW][C]28[/C][C]0.100391[/C][C]0.200782[/C][C]0.899609[/C][/ROW]
[ROW][C]29[/C][C]0.0738656[/C][C]0.147731[/C][C]0.926134[/C][/ROW]
[ROW][C]30[/C][C]0.0593673[/C][C]0.118735[/C][C]0.940633[/C][/ROW]
[ROW][C]31[/C][C]0.0869244[/C][C]0.173849[/C][C]0.913076[/C][/ROW]
[ROW][C]32[/C][C]0.0877429[/C][C]0.175486[/C][C]0.912257[/C][/ROW]
[ROW][C]33[/C][C]0.0937206[/C][C]0.187441[/C][C]0.906279[/C][/ROW]
[ROW][C]34[/C][C]0.0743155[/C][C]0.148631[/C][C]0.925684[/C][/ROW]
[ROW][C]35[/C][C]0.0548152[/C][C]0.10963[/C][C]0.945185[/C][/ROW]
[ROW][C]36[/C][C]0.0606231[/C][C]0.121246[/C][C]0.939377[/C][/ROW]
[ROW][C]37[/C][C]0.0620367[/C][C]0.124073[/C][C]0.937963[/C][/ROW]
[ROW][C]38[/C][C]0.0689358[/C][C]0.137872[/C][C]0.931064[/C][/ROW]
[ROW][C]39[/C][C]0.0652156[/C][C]0.130431[/C][C]0.934784[/C][/ROW]
[ROW][C]40[/C][C]0.0516143[/C][C]0.103229[/C][C]0.948386[/C][/ROW]
[ROW][C]41[/C][C]0.0683706[/C][C]0.136741[/C][C]0.931629[/C][/ROW]
[ROW][C]42[/C][C]0.0647905[/C][C]0.129581[/C][C]0.935209[/C][/ROW]
[ROW][C]43[/C][C]0.0604543[/C][C]0.120909[/C][C]0.939546[/C][/ROW]
[ROW][C]44[/C][C]0.0512823[/C][C]0.102565[/C][C]0.948718[/C][/ROW]
[ROW][C]45[/C][C]0.0489759[/C][C]0.0979518[/C][C]0.951024[/C][/ROW]
[ROW][C]46[/C][C]0.0382445[/C][C]0.0764889[/C][C]0.961756[/C][/ROW]
[ROW][C]47[/C][C]0.0419497[/C][C]0.0838993[/C][C]0.95805[/C][/ROW]
[ROW][C]48[/C][C]0.0392106[/C][C]0.0784213[/C][C]0.960789[/C][/ROW]
[ROW][C]49[/C][C]0.069408[/C][C]0.138816[/C][C]0.930592[/C][/ROW]
[ROW][C]50[/C][C]0.0833718[/C][C]0.166744[/C][C]0.916628[/C][/ROW]
[ROW][C]51[/C][C]0.0659864[/C][C]0.131973[/C][C]0.934014[/C][/ROW]
[ROW][C]52[/C][C]0.0801146[/C][C]0.160229[/C][C]0.919885[/C][/ROW]
[ROW][C]53[/C][C]0.0727665[/C][C]0.145533[/C][C]0.927233[/C][/ROW]
[ROW][C]54[/C][C]0.0611246[/C][C]0.122249[/C][C]0.938875[/C][/ROW]
[ROW][C]55[/C][C]0.134581[/C][C]0.269162[/C][C]0.865419[/C][/ROW]
[ROW][C]56[/C][C]0.110427[/C][C]0.220854[/C][C]0.889573[/C][/ROW]
[ROW][C]57[/C][C]0.402733[/C][C]0.805466[/C][C]0.597267[/C][/ROW]
[ROW][C]58[/C][C]0.449211[/C][C]0.898422[/C][C]0.550789[/C][/ROW]
[ROW][C]59[/C][C]0.412278[/C][C]0.824556[/C][C]0.587722[/C][/ROW]
[ROW][C]60[/C][C]0.408313[/C][C]0.816627[/C][C]0.591687[/C][/ROW]
[ROW][C]61[/C][C]0.447645[/C][C]0.895289[/C][C]0.552355[/C][/ROW]
[ROW][C]62[/C][C]0.440913[/C][C]0.881826[/C][C]0.559087[/C][/ROW]
[ROW][C]63[/C][C]0.589787[/C][C]0.820425[/C][C]0.410213[/C][/ROW]
[ROW][C]64[/C][C]0.632902[/C][C]0.734195[/C][C]0.367098[/C][/ROW]
[ROW][C]65[/C][C]0.661654[/C][C]0.676693[/C][C]0.338346[/C][/ROW]
[ROW][C]66[/C][C]0.635414[/C][C]0.729172[/C][C]0.364586[/C][/ROW]
[ROW][C]67[/C][C]0.611014[/C][C]0.777972[/C][C]0.388986[/C][/ROW]
[ROW][C]68[/C][C]0.593647[/C][C]0.812707[/C][C]0.406353[/C][/ROW]
[ROW][C]69[/C][C]0.639554[/C][C]0.720891[/C][C]0.360446[/C][/ROW]
[ROW][C]70[/C][C]0.611922[/C][C]0.776155[/C][C]0.388078[/C][/ROW]
[ROW][C]71[/C][C]0.575989[/C][C]0.848023[/C][C]0.424011[/C][/ROW]
[ROW][C]72[/C][C]0.556037[/C][C]0.887926[/C][C]0.443963[/C][/ROW]
[ROW][C]73[/C][C]0.542714[/C][C]0.914572[/C][C]0.457286[/C][/ROW]
[ROW][C]74[/C][C]0.602328[/C][C]0.795344[/C][C]0.397672[/C][/ROW]
[ROW][C]75[/C][C]0.584194[/C][C]0.831612[/C][C]0.415806[/C][/ROW]
[ROW][C]76[/C][C]0.55184[/C][C]0.89632[/C][C]0.44816[/C][/ROW]
[ROW][C]77[/C][C]0.529431[/C][C]0.941138[/C][C]0.470569[/C][/ROW]
[ROW][C]78[/C][C]0.515685[/C][C]0.968631[/C][C]0.484315[/C][/ROW]
[ROW][C]79[/C][C]0.479646[/C][C]0.959292[/C][C]0.520354[/C][/ROW]
[ROW][C]80[/C][C]0.489557[/C][C]0.979114[/C][C]0.510443[/C][/ROW]
[ROW][C]81[/C][C]0.451595[/C][C]0.903189[/C][C]0.548405[/C][/ROW]
[ROW][C]82[/C][C]0.472114[/C][C]0.944228[/C][C]0.527886[/C][/ROW]
[ROW][C]83[/C][C]0.435891[/C][C]0.871783[/C][C]0.564109[/C][/ROW]
[ROW][C]84[/C][C]0.637667[/C][C]0.724666[/C][C]0.362333[/C][/ROW]
[ROW][C]85[/C][C]0.619771[/C][C]0.760457[/C][C]0.380229[/C][/ROW]
[ROW][C]86[/C][C]0.583257[/C][C]0.833487[/C][C]0.416743[/C][/ROW]
[ROW][C]87[/C][C]0.570027[/C][C]0.859947[/C][C]0.429973[/C][/ROW]
[ROW][C]88[/C][C]0.568173[/C][C]0.863654[/C][C]0.431827[/C][/ROW]
[ROW][C]89[/C][C]0.555255[/C][C]0.889489[/C][C]0.444745[/C][/ROW]
[ROW][C]90[/C][C]0.539176[/C][C]0.921648[/C][C]0.460824[/C][/ROW]
[ROW][C]91[/C][C]0.575149[/C][C]0.849701[/C][C]0.424851[/C][/ROW]
[ROW][C]92[/C][C]0.719777[/C][C]0.560446[/C][C]0.280223[/C][/ROW]
[ROW][C]93[/C][C]0.714209[/C][C]0.571582[/C][C]0.285791[/C][/ROW]
[ROW][C]94[/C][C]0.69801[/C][C]0.60398[/C][C]0.30199[/C][/ROW]
[ROW][C]95[/C][C]0.694178[/C][C]0.611645[/C][C]0.305822[/C][/ROW]
[ROW][C]96[/C][C]0.67733[/C][C]0.645339[/C][C]0.32267[/C][/ROW]
[ROW][C]97[/C][C]0.729792[/C][C]0.540417[/C][C]0.270208[/C][/ROW]
[ROW][C]98[/C][C]0.723313[/C][C]0.553374[/C][C]0.276687[/C][/ROW]
[ROW][C]99[/C][C]0.7689[/C][C]0.4622[/C][C]0.2311[/C][/ROW]
[ROW][C]100[/C][C]0.776001[/C][C]0.447999[/C][C]0.223999[/C][/ROW]
[ROW][C]101[/C][C]0.760374[/C][C]0.479251[/C][C]0.239626[/C][/ROW]
[ROW][C]102[/C][C]0.730976[/C][C]0.538048[/C][C]0.269024[/C][/ROW]
[ROW][C]103[/C][C]0.710902[/C][C]0.578196[/C][C]0.289098[/C][/ROW]
[ROW][C]104[/C][C]0.692884[/C][C]0.614233[/C][C]0.307116[/C][/ROW]
[ROW][C]105[/C][C]0.754402[/C][C]0.491195[/C][C]0.245598[/C][/ROW]
[ROW][C]106[/C][C]0.741443[/C][C]0.517114[/C][C]0.258557[/C][/ROW]
[ROW][C]107[/C][C]0.79929[/C][C]0.401419[/C][C]0.20071[/C][/ROW]
[ROW][C]108[/C][C]0.882228[/C][C]0.235545[/C][C]0.117772[/C][/ROW]
[ROW][C]109[/C][C]0.881588[/C][C]0.236823[/C][C]0.118412[/C][/ROW]
[ROW][C]110[/C][C]0.871131[/C][C]0.257738[/C][C]0.128869[/C][/ROW]
[ROW][C]111[/C][C]0.856509[/C][C]0.286982[/C][C]0.143491[/C][/ROW]
[ROW][C]112[/C][C]0.841825[/C][C]0.316351[/C][C]0.158175[/C][/ROW]
[ROW][C]113[/C][C]0.887506[/C][C]0.224987[/C][C]0.112494[/C][/ROW]
[ROW][C]114[/C][C]0.906784[/C][C]0.186432[/C][C]0.0932162[/C][/ROW]
[ROW][C]115[/C][C]0.950623[/C][C]0.098755[/C][C]0.0493775[/C][/ROW]
[ROW][C]116[/C][C]0.958029[/C][C]0.0839429[/C][C]0.0419715[/C][/ROW]
[ROW][C]117[/C][C]0.952281[/C][C]0.0954378[/C][C]0.0477189[/C][/ROW]
[ROW][C]118[/C][C]0.944971[/C][C]0.110058[/C][C]0.0550288[/C][/ROW]
[ROW][C]119[/C][C]0.940372[/C][C]0.119256[/C][C]0.0596278[/C][/ROW]
[ROW][C]120[/C][C]0.940554[/C][C]0.118893[/C][C]0.0594465[/C][/ROW]
[ROW][C]121[/C][C]0.947106[/C][C]0.105787[/C][C]0.0528935[/C][/ROW]
[ROW][C]122[/C][C]0.944174[/C][C]0.111653[/C][C]0.0558263[/C][/ROW]
[ROW][C]123[/C][C]0.943414[/C][C]0.113173[/C][C]0.0565863[/C][/ROW]
[ROW][C]124[/C][C]0.966231[/C][C]0.0675388[/C][C]0.0337694[/C][/ROW]
[ROW][C]125[/C][C]0.970727[/C][C]0.0585458[/C][C]0.0292729[/C][/ROW]
[ROW][C]126[/C][C]0.964836[/C][C]0.0703274[/C][C]0.0351637[/C][/ROW]
[ROW][C]127[/C][C]0.95979[/C][C]0.0804209[/C][C]0.0402104[/C][/ROW]
[ROW][C]128[/C][C]0.9519[/C][C]0.0961993[/C][C]0.0480997[/C][/ROW]
[ROW][C]129[/C][C]0.951436[/C][C]0.0971288[/C][C]0.0485644[/C][/ROW]
[ROW][C]130[/C][C]0.944058[/C][C]0.111883[/C][C]0.0559416[/C][/ROW]
[ROW][C]131[/C][C]0.936485[/C][C]0.127029[/C][C]0.0635147[/C][/ROW]
[ROW][C]132[/C][C]0.93068[/C][C]0.138639[/C][C]0.0693197[/C][/ROW]
[ROW][C]133[/C][C]0.920445[/C][C]0.159109[/C][C]0.0795547[/C][/ROW]
[ROW][C]134[/C][C]0.908392[/C][C]0.183215[/C][C]0.0916075[/C][/ROW]
[ROW][C]135[/C][C]0.895132[/C][C]0.209735[/C][C]0.104868[/C][/ROW]
[ROW][C]136[/C][C]0.878566[/C][C]0.242868[/C][C]0.121434[/C][/ROW]
[ROW][C]137[/C][C]0.893167[/C][C]0.213665[/C][C]0.106833[/C][/ROW]
[ROW][C]138[/C][C]0.891812[/C][C]0.216375[/C][C]0.108188[/C][/ROW]
[ROW][C]139[/C][C]0.882913[/C][C]0.234174[/C][C]0.117087[/C][/ROW]
[ROW][C]140[/C][C]0.867321[/C][C]0.265359[/C][C]0.132679[/C][/ROW]
[ROW][C]141[/C][C]0.859252[/C][C]0.281496[/C][C]0.140748[/C][/ROW]
[ROW][C]142[/C][C]0.866217[/C][C]0.267566[/C][C]0.133783[/C][/ROW]
[ROW][C]143[/C][C]0.846789[/C][C]0.306421[/C][C]0.153211[/C][/ROW]
[ROW][C]144[/C][C]0.867205[/C][C]0.265589[/C][C]0.132795[/C][/ROW]
[ROW][C]145[/C][C]0.847356[/C][C]0.305288[/C][C]0.152644[/C][/ROW]
[ROW][C]146[/C][C]0.828161[/C][C]0.343678[/C][C]0.171839[/C][/ROW]
[ROW][C]147[/C][C]0.807713[/C][C]0.384575[/C][C]0.192287[/C][/ROW]
[ROW][C]148[/C][C]0.782771[/C][C]0.434458[/C][C]0.217229[/C][/ROW]
[ROW][C]149[/C][C]0.75708[/C][C]0.485839[/C][C]0.24292[/C][/ROW]
[ROW][C]150[/C][C]0.751804[/C][C]0.496391[/C][C]0.248196[/C][/ROW]
[ROW][C]151[/C][C]0.900959[/C][C]0.198082[/C][C]0.0990411[/C][/ROW]
[ROW][C]152[/C][C]0.885611[/C][C]0.228778[/C][C]0.114389[/C][/ROW]
[ROW][C]153[/C][C]0.886218[/C][C]0.227563[/C][C]0.113782[/C][/ROW]
[ROW][C]154[/C][C]0.868594[/C][C]0.262811[/C][C]0.131406[/C][/ROW]
[ROW][C]155[/C][C]0.859554[/C][C]0.280891[/C][C]0.140446[/C][/ROW]
[ROW][C]156[/C][C]0.843638[/C][C]0.312725[/C][C]0.156362[/C][/ROW]
[ROW][C]157[/C][C]0.82696[/C][C]0.34608[/C][C]0.17304[/C][/ROW]
[ROW][C]158[/C][C]0.809608[/C][C]0.380784[/C][C]0.190392[/C][/ROW]
[ROW][C]159[/C][C]0.822364[/C][C]0.355272[/C][C]0.177636[/C][/ROW]
[ROW][C]160[/C][C]0.824074[/C][C]0.351852[/C][C]0.175926[/C][/ROW]
[ROW][C]161[/C][C]0.805118[/C][C]0.389765[/C][C]0.194882[/C][/ROW]
[ROW][C]162[/C][C]0.796819[/C][C]0.406363[/C][C]0.203181[/C][/ROW]
[ROW][C]163[/C][C]0.777173[/C][C]0.445654[/C][C]0.222827[/C][/ROW]
[ROW][C]164[/C][C]0.967653[/C][C]0.0646938[/C][C]0.0323469[/C][/ROW]
[ROW][C]165[/C][C]0.962107[/C][C]0.0757867[/C][C]0.0378933[/C][/ROW]
[ROW][C]166[/C][C]0.960501[/C][C]0.0789989[/C][C]0.0394994[/C][/ROW]
[ROW][C]167[/C][C]0.954621[/C][C]0.0907587[/C][C]0.0453793[/C][/ROW]
[ROW][C]168[/C][C]0.953605[/C][C]0.0927906[/C][C]0.0463953[/C][/ROW]
[ROW][C]169[/C][C]0.944552[/C][C]0.110897[/C][C]0.0554483[/C][/ROW]
[ROW][C]170[/C][C]0.956689[/C][C]0.0866218[/C][C]0.0433109[/C][/ROW]
[ROW][C]171[/C][C]0.950602[/C][C]0.0987963[/C][C]0.0493981[/C][/ROW]
[ROW][C]172[/C][C]0.948886[/C][C]0.102227[/C][C]0.0511137[/C][/ROW]
[ROW][C]173[/C][C]0.952392[/C][C]0.0952153[/C][C]0.0476076[/C][/ROW]
[ROW][C]174[/C][C]0.942895[/C][C]0.11421[/C][C]0.0571049[/C][/ROW]
[ROW][C]175[/C][C]0.931841[/C][C]0.136318[/C][C]0.0681588[/C][/ROW]
[ROW][C]176[/C][C]0.934553[/C][C]0.130893[/C][C]0.0654465[/C][/ROW]
[ROW][C]177[/C][C]0.92552[/C][C]0.148959[/C][C]0.0744797[/C][/ROW]
[ROW][C]178[/C][C]0.929313[/C][C]0.141373[/C][C]0.0706866[/C][/ROW]
[ROW][C]179[/C][C]0.927926[/C][C]0.144147[/C][C]0.0720737[/C][/ROW]
[ROW][C]180[/C][C]0.935186[/C][C]0.129628[/C][C]0.0648141[/C][/ROW]
[ROW][C]181[/C][C]0.945132[/C][C]0.109737[/C][C]0.0548683[/C][/ROW]
[ROW][C]182[/C][C]0.949623[/C][C]0.100753[/C][C]0.0503767[/C][/ROW]
[ROW][C]183[/C][C]0.953616[/C][C]0.0927674[/C][C]0.0463837[/C][/ROW]
[ROW][C]184[/C][C]0.944837[/C][C]0.110326[/C][C]0.0551628[/C][/ROW]
[ROW][C]185[/C][C]0.953975[/C][C]0.0920496[/C][C]0.0460248[/C][/ROW]
[ROW][C]186[/C][C]0.944269[/C][C]0.111462[/C][C]0.0557312[/C][/ROW]
[ROW][C]187[/C][C]0.948088[/C][C]0.103824[/C][C]0.0519121[/C][/ROW]
[ROW][C]188[/C][C]0.952962[/C][C]0.0940762[/C][C]0.0470381[/C][/ROW]
[ROW][C]189[/C][C]0.955195[/C][C]0.0896109[/C][C]0.0448054[/C][/ROW]
[ROW][C]190[/C][C]0.948237[/C][C]0.103526[/C][C]0.0517631[/C][/ROW]
[ROW][C]191[/C][C]0.947987[/C][C]0.104025[/C][C]0.0520125[/C][/ROW]
[ROW][C]192[/C][C]0.937677[/C][C]0.124647[/C][C]0.0623234[/C][/ROW]
[ROW][C]193[/C][C]0.947362[/C][C]0.105275[/C][C]0.0526375[/C][/ROW]
[ROW][C]194[/C][C]0.952642[/C][C]0.0947165[/C][C]0.0473583[/C][/ROW]
[ROW][C]195[/C][C]0.94319[/C][C]0.11362[/C][C]0.0568098[/C][/ROW]
[ROW][C]196[/C][C]0.93862[/C][C]0.122759[/C][C]0.0613797[/C][/ROW]
[ROW][C]197[/C][C]0.939691[/C][C]0.120619[/C][C]0.0603094[/C][/ROW]
[ROW][C]198[/C][C]0.926925[/C][C]0.146151[/C][C]0.0730755[/C][/ROW]
[ROW][C]199[/C][C]0.917226[/C][C]0.165549[/C][C]0.0827744[/C][/ROW]
[ROW][C]200[/C][C]0.901143[/C][C]0.197714[/C][C]0.0988568[/C][/ROW]
[ROW][C]201[/C][C]0.892236[/C][C]0.215529[/C][C]0.107764[/C][/ROW]
[ROW][C]202[/C][C]0.876384[/C][C]0.247232[/C][C]0.123616[/C][/ROW]
[ROW][C]203[/C][C]0.874029[/C][C]0.251943[/C][C]0.125971[/C][/ROW]
[ROW][C]204[/C][C]0.85398[/C][C]0.292041[/C][C]0.14602[/C][/ROW]
[ROW][C]205[/C][C]0.832728[/C][C]0.334544[/C][C]0.167272[/C][/ROW]
[ROW][C]206[/C][C]0.832484[/C][C]0.335032[/C][C]0.167516[/C][/ROW]
[ROW][C]207[/C][C]0.828211[/C][C]0.343578[/C][C]0.171789[/C][/ROW]
[ROW][C]208[/C][C]0.818817[/C][C]0.362367[/C][C]0.181183[/C][/ROW]
[ROW][C]209[/C][C]0.805588[/C][C]0.388824[/C][C]0.194412[/C][/ROW]
[ROW][C]210[/C][C]0.807663[/C][C]0.384674[/C][C]0.192337[/C][/ROW]
[ROW][C]211[/C][C]0.79067[/C][C]0.41866[/C][C]0.20933[/C][/ROW]
[ROW][C]212[/C][C]0.759079[/C][C]0.481841[/C][C]0.240921[/C][/ROW]
[ROW][C]213[/C][C]0.760157[/C][C]0.479687[/C][C]0.239843[/C][/ROW]
[ROW][C]214[/C][C]0.727107[/C][C]0.545786[/C][C]0.272893[/C][/ROW]
[ROW][C]215[/C][C]0.705326[/C][C]0.589347[/C][C]0.294674[/C][/ROW]
[ROW][C]216[/C][C]0.667734[/C][C]0.664531[/C][C]0.332266[/C][/ROW]
[ROW][C]217[/C][C]0.662837[/C][C]0.674326[/C][C]0.337163[/C][/ROW]
[ROW][C]218[/C][C]0.641314[/C][C]0.717371[/C][C]0.358686[/C][/ROW]
[ROW][C]219[/C][C]0.612201[/C][C]0.775597[/C][C]0.387799[/C][/ROW]
[ROW][C]220[/C][C]0.58211[/C][C]0.835779[/C][C]0.41789[/C][/ROW]
[ROW][C]221[/C][C]0.591455[/C][C]0.81709[/C][C]0.408545[/C][/ROW]
[ROW][C]222[/C][C]0.661902[/C][C]0.676197[/C][C]0.338098[/C][/ROW]
[ROW][C]223[/C][C]0.624588[/C][C]0.750824[/C][C]0.375412[/C][/ROW]
[ROW][C]224[/C][C]0.719089[/C][C]0.561822[/C][C]0.280911[/C][/ROW]
[ROW][C]225[/C][C]0.71367[/C][C]0.572659[/C][C]0.28633[/C][/ROW]
[ROW][C]226[/C][C]0.782299[/C][C]0.435403[/C][C]0.217701[/C][/ROW]
[ROW][C]227[/C][C]0.79191[/C][C]0.416179[/C][C]0.20809[/C][/ROW]
[ROW][C]228[/C][C]0.822765[/C][C]0.354469[/C][C]0.177235[/C][/ROW]
[ROW][C]229[/C][C]0.883181[/C][C]0.233638[/C][C]0.116819[/C][/ROW]
[ROW][C]230[/C][C]0.915548[/C][C]0.168903[/C][C]0.0844517[/C][/ROW]
[ROW][C]231[/C][C]0.926706[/C][C]0.146588[/C][C]0.0732942[/C][/ROW]
[ROW][C]232[/C][C]0.922237[/C][C]0.155527[/C][C]0.0777634[/C][/ROW]
[ROW][C]233[/C][C]0.908231[/C][C]0.183537[/C][C]0.0917686[/C][/ROW]
[ROW][C]234[/C][C]0.891715[/C][C]0.216569[/C][C]0.108285[/C][/ROW]
[ROW][C]235[/C][C]0.870677[/C][C]0.258646[/C][C]0.129323[/C][/ROW]
[ROW][C]236[/C][C]0.933474[/C][C]0.133053[/C][C]0.0665264[/C][/ROW]
[ROW][C]237[/C][C]0.921903[/C][C]0.156195[/C][C]0.0780974[/C][/ROW]
[ROW][C]238[/C][C]0.899536[/C][C]0.200927[/C][C]0.100464[/C][/ROW]
[ROW][C]239[/C][C]0.878179[/C][C]0.243642[/C][C]0.121821[/C][/ROW]
[ROW][C]240[/C][C]0.846736[/C][C]0.306529[/C][C]0.153264[/C][/ROW]
[ROW][C]241[/C][C]0.824325[/C][C]0.351351[/C][C]0.175675[/C][/ROW]
[ROW][C]242[/C][C]0.786491[/C][C]0.427019[/C][C]0.213509[/C][/ROW]
[ROW][C]243[/C][C]0.757668[/C][C]0.484664[/C][C]0.242332[/C][/ROW]
[ROW][C]244[/C][C]0.719888[/C][C]0.560224[/C][C]0.280112[/C][/ROW]
[ROW][C]245[/C][C]0.683989[/C][C]0.632021[/C][C]0.316011[/C][/ROW]
[ROW][C]246[/C][C]0.628979[/C][C]0.742041[/C][C]0.371021[/C][/ROW]
[ROW][C]247[/C][C]0.568463[/C][C]0.863074[/C][C]0.431537[/C][/ROW]
[ROW][C]248[/C][C]0.642463[/C][C]0.715075[/C][C]0.357537[/C][/ROW]
[ROW][C]249[/C][C]0.578426[/C][C]0.843149[/C][C]0.421574[/C][/ROW]
[ROW][C]250[/C][C]0.557289[/C][C]0.885421[/C][C]0.442711[/C][/ROW]
[ROW][C]251[/C][C]0.515806[/C][C]0.968389[/C][C]0.484194[/C][/ROW]
[ROW][C]252[/C][C]0.455405[/C][C]0.910811[/C][C]0.544595[/C][/ROW]
[ROW][C]253[/C][C]0.411988[/C][C]0.823976[/C][C]0.588012[/C][/ROW]
[ROW][C]254[/C][C]0.451517[/C][C]0.903033[/C][C]0.548483[/C][/ROW]
[ROW][C]255[/C][C]0.457226[/C][C]0.914451[/C][C]0.542774[/C][/ROW]
[ROW][C]256[/C][C]0.399568[/C][C]0.799136[/C][C]0.600432[/C][/ROW]
[ROW][C]257[/C][C]0.418433[/C][C]0.836866[/C][C]0.581567[/C][/ROW]
[ROW][C]258[/C][C]0.588692[/C][C]0.822616[/C][C]0.411308[/C][/ROW]
[ROW][C]259[/C][C]0.576972[/C][C]0.846055[/C][C]0.423028[/C][/ROW]
[ROW][C]260[/C][C]0.956255[/C][C]0.0874901[/C][C]0.043745[/C][/ROW]
[ROW][C]261[/C][C]0.921925[/C][C]0.15615[/C][C]0.0780751[/C][/ROW]
[ROW][C]262[/C][C]0.975779[/C][C]0.0484417[/C][C]0.0242208[/C][/ROW]
[ROW][C]263[/C][C]0.989864[/C][C]0.020272[/C][C]0.010136[/C][/ROW]
[ROW][C]264[/C][C]0.973127[/C][C]0.0537466[/C][C]0.0268733[/C][/ROW]
[ROW][C]265[/C][C]0.947089[/C][C]0.105822[/C][C]0.0529112[/C][/ROW]
[ROW][C]266[/C][C]0.878867[/C][C]0.242266[/C][C]0.121133[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268316&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&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
130.6761960.6476080.323804
140.5399510.9200980.460049
150.3975840.7951670.602416
160.2754260.5508520.724574
170.2554480.5108960.744552
180.1977710.3955430.802229
190.1358010.2716020.864199
200.09108990.182180.90891
210.05993090.1198620.940069
220.04453960.08907910.95546
230.1236490.2472990.876351
240.2007530.4015070.799247
250.1973530.3947060.802647
260.1584410.3168820.841559
270.1268950.2537890.873105
280.1003910.2007820.899609
290.07386560.1477310.926134
300.05936730.1187350.940633
310.08692440.1738490.913076
320.08774290.1754860.912257
330.09372060.1874410.906279
340.07431550.1486310.925684
350.05481520.109630.945185
360.06062310.1212460.939377
370.06203670.1240730.937963
380.06893580.1378720.931064
390.06521560.1304310.934784
400.05161430.1032290.948386
410.06837060.1367410.931629
420.06479050.1295810.935209
430.06045430.1209090.939546
440.05128230.1025650.948718
450.04897590.09795180.951024
460.03824450.07648890.961756
470.04194970.08389930.95805
480.03921060.07842130.960789
490.0694080.1388160.930592
500.08337180.1667440.916628
510.06598640.1319730.934014
520.08011460.1602290.919885
530.07276650.1455330.927233
540.06112460.1222490.938875
550.1345810.2691620.865419
560.1104270.2208540.889573
570.4027330.8054660.597267
580.4492110.8984220.550789
590.4122780.8245560.587722
600.4083130.8166270.591687
610.4476450.8952890.552355
620.4409130.8818260.559087
630.5897870.8204250.410213
640.6329020.7341950.367098
650.6616540.6766930.338346
660.6354140.7291720.364586
670.6110140.7779720.388986
680.5936470.8127070.406353
690.6395540.7208910.360446
700.6119220.7761550.388078
710.5759890.8480230.424011
720.5560370.8879260.443963
730.5427140.9145720.457286
740.6023280.7953440.397672
750.5841940.8316120.415806
760.551840.896320.44816
770.5294310.9411380.470569
780.5156850.9686310.484315
790.4796460.9592920.520354
800.4895570.9791140.510443
810.4515950.9031890.548405
820.4721140.9442280.527886
830.4358910.8717830.564109
840.6376670.7246660.362333
850.6197710.7604570.380229
860.5832570.8334870.416743
870.5700270.8599470.429973
880.5681730.8636540.431827
890.5552550.8894890.444745
900.5391760.9216480.460824
910.5751490.8497010.424851
920.7197770.5604460.280223
930.7142090.5715820.285791
940.698010.603980.30199
950.6941780.6116450.305822
960.677330.6453390.32267
970.7297920.5404170.270208
980.7233130.5533740.276687
990.76890.46220.2311
1000.7760010.4479990.223999
1010.7603740.4792510.239626
1020.7309760.5380480.269024
1030.7109020.5781960.289098
1040.6928840.6142330.307116
1050.7544020.4911950.245598
1060.7414430.5171140.258557
1070.799290.4014190.20071
1080.8822280.2355450.117772
1090.8815880.2368230.118412
1100.8711310.2577380.128869
1110.8565090.2869820.143491
1120.8418250.3163510.158175
1130.8875060.2249870.112494
1140.9067840.1864320.0932162
1150.9506230.0987550.0493775
1160.9580290.08394290.0419715
1170.9522810.09543780.0477189
1180.9449710.1100580.0550288
1190.9403720.1192560.0596278
1200.9405540.1188930.0594465
1210.9471060.1057870.0528935
1220.9441740.1116530.0558263
1230.9434140.1131730.0565863
1240.9662310.06753880.0337694
1250.9707270.05854580.0292729
1260.9648360.07032740.0351637
1270.959790.08042090.0402104
1280.95190.09619930.0480997
1290.9514360.09712880.0485644
1300.9440580.1118830.0559416
1310.9364850.1270290.0635147
1320.930680.1386390.0693197
1330.9204450.1591090.0795547
1340.9083920.1832150.0916075
1350.8951320.2097350.104868
1360.8785660.2428680.121434
1370.8931670.2136650.106833
1380.8918120.2163750.108188
1390.8829130.2341740.117087
1400.8673210.2653590.132679
1410.8592520.2814960.140748
1420.8662170.2675660.133783
1430.8467890.3064210.153211
1440.8672050.2655890.132795
1450.8473560.3052880.152644
1460.8281610.3436780.171839
1470.8077130.3845750.192287
1480.7827710.4344580.217229
1490.757080.4858390.24292
1500.7518040.4963910.248196
1510.9009590.1980820.0990411
1520.8856110.2287780.114389
1530.8862180.2275630.113782
1540.8685940.2628110.131406
1550.8595540.2808910.140446
1560.8436380.3127250.156362
1570.826960.346080.17304
1580.8096080.3807840.190392
1590.8223640.3552720.177636
1600.8240740.3518520.175926
1610.8051180.3897650.194882
1620.7968190.4063630.203181
1630.7771730.4456540.222827
1640.9676530.06469380.0323469
1650.9621070.07578670.0378933
1660.9605010.07899890.0394994
1670.9546210.09075870.0453793
1680.9536050.09279060.0463953
1690.9445520.1108970.0554483
1700.9566890.08662180.0433109
1710.9506020.09879630.0493981
1720.9488860.1022270.0511137
1730.9523920.09521530.0476076
1740.9428950.114210.0571049
1750.9318410.1363180.0681588
1760.9345530.1308930.0654465
1770.925520.1489590.0744797
1780.9293130.1413730.0706866
1790.9279260.1441470.0720737
1800.9351860.1296280.0648141
1810.9451320.1097370.0548683
1820.9496230.1007530.0503767
1830.9536160.09276740.0463837
1840.9448370.1103260.0551628
1850.9539750.09204960.0460248
1860.9442690.1114620.0557312
1870.9480880.1038240.0519121
1880.9529620.09407620.0470381
1890.9551950.08961090.0448054
1900.9482370.1035260.0517631
1910.9479870.1040250.0520125
1920.9376770.1246470.0623234
1930.9473620.1052750.0526375
1940.9526420.09471650.0473583
1950.943190.113620.0568098
1960.938620.1227590.0613797
1970.9396910.1206190.0603094
1980.9269250.1461510.0730755
1990.9172260.1655490.0827744
2000.9011430.1977140.0988568
2010.8922360.2155290.107764
2020.8763840.2472320.123616
2030.8740290.2519430.125971
2040.853980.2920410.14602
2050.8327280.3345440.167272
2060.8324840.3350320.167516
2070.8282110.3435780.171789
2080.8188170.3623670.181183
2090.8055880.3888240.194412
2100.8076630.3846740.192337
2110.790670.418660.20933
2120.7590790.4818410.240921
2130.7601570.4796870.239843
2140.7271070.5457860.272893
2150.7053260.5893470.294674
2160.6677340.6645310.332266
2170.6628370.6743260.337163
2180.6413140.7173710.358686
2190.6122010.7755970.387799
2200.582110.8357790.41789
2210.5914550.817090.408545
2220.6619020.6761970.338098
2230.6245880.7508240.375412
2240.7190890.5618220.280911
2250.713670.5726590.28633
2260.7822990.4354030.217701
2270.791910.4161790.20809
2280.8227650.3544690.177235
2290.8831810.2336380.116819
2300.9155480.1689030.0844517
2310.9267060.1465880.0732942
2320.9222370.1555270.0777634
2330.9082310.1835370.0917686
2340.8917150.2165690.108285
2350.8706770.2586460.129323
2360.9334740.1330530.0665264
2370.9219030.1561950.0780974
2380.8995360.2009270.100464
2390.8781790.2436420.121821
2400.8467360.3065290.153264
2410.8243250.3513510.175675
2420.7864910.4270190.213509
2430.7576680.4846640.242332
2440.7198880.5602240.280112
2450.6839890.6320210.316011
2460.6289790.7420410.371021
2470.5684630.8630740.431537
2480.6424630.7150750.357537
2490.5784260.8431490.421574
2500.5572890.8854210.442711
2510.5158060.9683890.484194
2520.4554050.9108110.544595
2530.4119880.8239760.588012
2540.4515170.9030330.548483
2550.4572260.9144510.542774
2560.3995680.7991360.600432
2570.4184330.8368660.581567
2580.5886920.8226160.411308
2590.5769720.8460550.423028
2600.9562550.08749010.043745
2610.9219250.156150.0780751
2620.9757790.04844170.0242208
2630.9898640.0202720.010136
2640.9731270.05374660.0268733
2650.9470890.1058220.0529112
2660.8788670.2422660.121133






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00787402OK
10% type I error level310.122047NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 2 & 0.00787402 & OK \tabularnewline
10% type I error level & 31 & 0.122047 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268316&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]2[/C][C]0.00787402[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]31[/C][C]0.122047[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268316&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268316&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level20.00787402OK
10% type I error level310.122047NOK


Figures (Output of Computation)

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Input Parameters & R Code

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