FreeStatistics.org

Free Statistics

of Irreproducible Research!

Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 08 Dec 2014 10:49:05 +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/08/t1418035811yiyic38thdfpt3e.htm/, Retrieved Tue, 28 May 2024 12:25:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263930, Retrieved Tue, 28 May 2024 12:25:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact102

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-08 10:49:05] [003c997d057e54927bd887526d955d96] [Current]
Feedback Forum

Post a new message

Dataset

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

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&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]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&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'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = -8688.81 + 4.32351Year[t] -1.07879B_S[t] -0.0108052AMS.I[t] -0.0144224AMS.E[t] -0.601247gender[t] + 0.0465838CONFSOFTTOT[t] + 0.0440945NUMERACYTOT[t] + 0.0367745LFM[t] + 0.0330993CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  -8688.81 +  4.32351Year[t] -1.07879B_S[t] -0.0108052AMS.I[t] -0.0144224AMS.E[t] -0.601247gender[t] +  0.0465838CONFSOFTTOT[t] +  0.0440945NUMERACYTOT[t] +  0.0367745LFM[t] +  0.0330993CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  -8688.81 +  4.32351Year[t] -1.07879B_S[t] -0.0108052AMS.I[t] -0.0144224AMS.E[t] -0.601247gender[t] +  0.0465838CONFSOFTTOT[t] +  0.0440945NUMERACYTOT[t] +  0.0367745LFM[t] +  0.0330993CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&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] = -8688.81 + 4.32351Year[t] -1.07879B_S[t] -0.0108052AMS.I[t] -0.0144224AMS.E[t] -0.601247gender[t] + 0.0465838CONFSOFTTOT[t] + 0.0440945NUMERACYTOT[t] + 0.0367745LFM[t] + 0.0330993CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)-8688.81592.314-14.673.62883e-361.81442e-36
Year4.323510.29438614.693.15111e-361.57556e-36
B_S-1.078790.331686-3.2520.00129080.000645402
AMS.I-0.01080520.014906-0.72490.4691520.234576
AMS.E-0.01442240.0186427-0.77360.4398360.219918
gender-0.6012470.298002-2.0180.04463050.0223153
CONFSOFTTOT0.04658380.0645220.7220.4709340.235467
NUMERACYTOT0.04409450.02773761.590.1130810.0565407
LFM0.03677450.004605917.9844.17825e-142.08913e-14
CH0.03309930.008301223.9878.62532e-054.31266e-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) & -8688.81 & 592.314 & -14.67 & 3.62883e-36 & 1.81442e-36 \tabularnewline
Year & 4.32351 & 0.294386 & 14.69 & 3.15111e-36 & 1.57556e-36 \tabularnewline
B_S & -1.07879 & 0.331686 & -3.252 & 0.0012908 & 0.000645402 \tabularnewline
AMS.I & -0.0108052 & 0.014906 & -0.7249 & 0.469152 & 0.234576 \tabularnewline
AMS.E & -0.0144224 & 0.0186427 & -0.7736 & 0.439836 & 0.219918 \tabularnewline
gender & -0.601247 & 0.298002 & -2.018 & 0.0446305 & 0.0223153 \tabularnewline
CONFSOFTTOT & 0.0465838 & 0.064522 & 0.722 & 0.470934 & 0.235467 \tabularnewline
NUMERACYTOT & 0.0440945 & 0.0277376 & 1.59 & 0.113081 & 0.0565407 \tabularnewline
LFM & 0.0367745 & 0.00460591 & 7.984 & 4.17825e-14 & 2.08913e-14 \tabularnewline
CH & 0.0330993 & 0.00830122 & 3.987 & 8.62532e-05 & 4.31266e-05 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&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]-8688.81[/C][C]592.314[/C][C]-14.67[/C][C]3.62883e-36[/C][C]1.81442e-36[/C][/ROW]
[ROW][C]Year[/C][C]4.32351[/C][C]0.294386[/C][C]14.69[/C][C]3.15111e-36[/C][C]1.57556e-36[/C][/ROW]
[ROW][C]B_S[/C][C]-1.07879[/C][C]0.331686[/C][C]-3.252[/C][C]0.0012908[/C][C]0.000645402[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.0108052[/C][C]0.014906[/C][C]-0.7249[/C][C]0.469152[/C][C]0.234576[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0144224[/C][C]0.0186427[/C][C]-0.7736[/C][C]0.439836[/C][C]0.219918[/C][/ROW]
[ROW][C]gender[/C][C]-0.601247[/C][C]0.298002[/C][C]-2.018[/C][C]0.0446305[/C][C]0.0223153[/C][/ROW]
[ROW][C]CONFSOFTTOT[/C][C]0.0465838[/C][C]0.064522[/C][C]0.722[/C][C]0.470934[/C][C]0.235467[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0440945[/C][C]0.0277376[/C][C]1.59[/C][C]0.113081[/C][C]0.0565407[/C][/ROW]
[ROW][C]LFM[/C][C]0.0367745[/C][C]0.00460591[/C][C]7.984[/C][C]4.17825e-14[/C][C]2.08913e-14[/C][/ROW]
[ROW][C]CH[/C][C]0.0330993[/C][C]0.00830122[/C][C]3.987[/C][C]8.62532e-05[/C][C]4.31266e-05[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&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)-8688.81592.314-14.673.62883e-361.81442e-36
Year4.323510.29438614.693.15111e-361.57556e-36
B_S-1.078790.331686-3.2520.00129080.000645402
AMS.I-0.01080520.014906-0.72490.4691520.234576
AMS.E-0.01442240.0186427-0.77360.4398360.219918
gender-0.6012470.298002-2.0180.04463050.0223153
CONFSOFTTOT0.04658380.0645220.7220.4709340.235467
NUMERACYTOT0.04409450.02773761.590.1130810.0565407
LFM0.03677450.004605917.9844.17825e-142.08913e-14
CH0.03309930.008301223.9878.62532e-054.31266e-05






Multiple Linear Regression - Regression Statistics
Multiple R0.747276
R-squared0.558422
Adjusted R-squared0.543593
F-TEST (value)37.6571
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29316
Sum Squared Residuals1409.3

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.747276 \tabularnewline
R-squared & 0.558422 \tabularnewline
Adjusted R-squared & 0.543593 \tabularnewline
F-TEST (value) & 37.6571 \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 & 2.29316 \tabularnewline
Sum Squared Residuals & 1409.3 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.747276[/C][/ROW]
[ROW][C]R-squared[/C][C]0.558422[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.543593[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]37.6571[/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]2.29316[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1409.3[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.747276
R-squared0.558422
Adjusted R-squared0.543593
F-TEST (value)37.6571
F-TEST (DF numerator)9
F-TEST (DF denominator)268
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.29316
Sum Squared Residuals1409.3






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.906-0.00604801
212.210.32691.87309
312.811.49871.30134
47.411.6056-4.20559
56.710.1743-3.47429
612.613.546-0.94601
714.812.18552.61447
813.310.7232.57699
911.111.96-0.860028
108.211.6572-3.45724
1111.411.796-0.396024
126.411.4576-5.05755
1310.69.121771.47823
141213.5574-1.55745
156.36.56444-0.264442
1611.39.65641.6436
1711.912.3881-0.488071
189.310.2352-0.935222
199.611.4126-1.81258
20109.884770.115232
216.410.0912-3.69124
2213.810.30573.49429
2310.814.0642-3.26421
2413.812.98760.812432
2511.711.12550.574526
2610.914.8411-3.94107
2716.113.31342.78663
2813.410.55522.84476
299.911.5423-1.64229
3011.511.31890.181146
318.39.47418-1.17418
3211.711.6220.0779516
33910.0676-1.06758
349.711.7332-2.03316
3510.89.341331.45867
3610.38.423541.87646
3710.410.6176-0.217598
3812.710.34472.35526
399.311.805-2.50503
4011.812.0428-0.242832
415.99.60157-3.70157
4211.410.82530.57467
431311.65331.34667
4410.811.8508-1.05081
4512.38.510093.78991
4611.312.685-1.38498
4711.89.760642.03936
487.99.61292-1.71292
4912.79.467383.23262
5012.38.804823.49518
5111.610.50081.09916
526.77.16934-0.469337
5310.910.59420.305847
5412.111.55210.547879
5513.310.04533.25466
5610.19.640120.459876
575.711.0865-5.38646
5814.310.21374.08629
5987.196050.803953
6013.310.60082.69919
619.312.7039-3.4039
6212.511.07851.42153
637.69.38499-1.78499
6415.913.69092.20907
659.212.4836-3.28355
669.18.496380.603619
6711.113.1609-2.06088
681315.0686-2.06855
6914.511.69862.80137
7012.210.82871.37125
7112.313.315-1.01499
7211.410.20911.19087
738.89.8622-1.0622
7414.610.72333.87675
7512.610.78511.81492
76NANA0.645481
771310.79162.20842
7812.611.68850.911547
7913.212.32010.879868
809.912.0456-2.14558
817.77.661750.0382548
8210.57.445323.05468
8313.413.02110.378886
8410.915.8513-4.95134
854.35.47555-1.17555
8610.39.663810.636185
8711.89.480062.31994
8811.28.445542.75446
8911.412.8299-1.42989
908.66.904521.69548
9113.29.267323.93268
9212.617.2197-4.61969
935.67.79306-2.19306
949.911.2793-1.37931
958.810.5357-1.73571
967.79.30951-1.60951
97912.7377-3.73767
987.35.180552.11945
9911.47.31994.0801
10013.615.7268-2.12682
1017.95.919751.98025
10210.710.60260.0974186
10310.310.8769-0.576894
1048.39.71251-1.41251
1059.65.151224.44878
10614.215.8724-1.67243
1078.54.702783.79722
10813.518.4219-4.92189
1094.96.52497-1.62497
1106.47.39228-0.992279
1119.68.725750.87425
11211.69.613091.98691
11311.117.4636-6.36361
1144.353.895380.45462
11512.79.777722.92228
11618.115.61432.4857
11717.8519.1934-1.34338
11816.616.23230.367655
11912.613.7163-1.11629
12017.115.23711.86295
12119.121.861-2.76096
12216.114.52141.57861
12313.3511.2992.05096
12418.414.0054.395
12514.717.2361-2.53608
12610.611.176-0.57604
12712.611.09311.5069
12816.216.5325-0.332539
12913.611.01132.58867
13018.917.87281.02719
13114.113.11380.986222
13214.515.7838-1.28377
13316.1514.79781.35222
13414.7513.47041.27957
13514.814.71720.0827931
13612.4512.44710.00291074
13712.659.339873.31013
13817.3519.1868-1.83676
1398.66.83751.7625
14018.417.40310.996869
14116.117.3635-1.26345
14211.68.779962.82004
14317.7517.49040.259552
14415.2511.98733.26271
14517.6517.48210.167896
14616.3515.52540.824551
14717.6517.7514-0.101418
14813.613.56860.0314365
14914.3514.4367-0.0866586
15014.7512.60992.14005
15118.2524.1075-5.85753
1529.98.851171.04883
1531613.33982.66024
15418.2518.3975-0.147482
15516.8515.07961.77039
15614.615.1542-0.554167
15713.8512.1831.66697
15818.9517.80091.14914
15915.617.7731-2.17311
16014.8517.1577-2.30767
16111.7510.50581.2442
16218.4516.40352.04646
16315.916.2-0.300026
16417.110.26666.83339
16516.115.0221.07804
16619.920.8125-0.912499
16710.959.30551.6445
16818.4516.78381.66615
16915.114.98210.11789
1701518.4901-3.49009
17111.3510.14751.20246
17215.9513.67172.2783
17318.119.9847-1.88465
17414.614.8161-0.21609
17515.415.5872-0.187245
17615.412.9142.48595
17717.618.9784-1.37838
17813.3510.36742.98261
17919.120.3256-1.22559
18015.3518.9928-3.64278
1817.610.2299-2.62989
18213.415.058-1.65798
18313.911.01732.88268
18419.119.1847-0.0846928
18515.2518.1344-2.88435
18612.912.9014-0.00139317
18716.113.57412.52589
18817.3519.532-2.182
18913.1515.282-2.13203
19012.1512.14440.00559233
19112.614.9721-2.37206
19210.359.453730.896269
19315.418.4568-3.05677
1949.66.263763.33624
19518.218.6308-0.430788
19613.613.01550.584451
19714.8516.474-1.62405
19814.7514.71740.0325786
19914.112.57231.52774
20014.914.00250.897531
20116.2516.17750.0725469
20219.2518.44860.801378
20313.614.9547-1.35469
20413.613.50150.0985208
20515.6516.1283-0.478346
20612.7511.39271.35735
20714.615.8001-1.2001
2089.859.684640.165358
20912.659.545143.10486
21019.217.25371.94625
21116.617.7892-1.18922
21211.210.73530.464663
21315.2517.5532-2.30322
21411.912.1541-0.25405
21513.213.7441-0.544096
21616.3517.0286-0.678577
21712.411.02511.37486
21815.8513.64882.20118
21918.1519.8664-1.71637
22011.1511.7513-0.601292
22115.6512.85512.79493
22217.7522.5204-4.7704
2237.658.55828-0.908275
22412.359.947582.40242
22515.612.9822.61796
22619.316.97532.32469
22715.212.64162.55838
22817.115.02892.07114
22915.612.67512.92485
23018.415.11553.28452
23119.0515.3753.67501
23218.5516.27342.27658
23319.119.41-0.309966
23413.115.5652-2.46521
23512.8515.2756-2.42557
2369.515.9838-6.48383
2374.54.61207-0.112065
23811.8512.9104-1.06036
23913.614.08-0.480038
24011.712.4627-0.762733
24112.413.7111-1.31108
24213.3515.3226-1.97258
24311.410.67310.726944
24414.913.7211.17905
24519.922.3788-2.47879
24611.211.667-0.466953
24714.614.48560.114352
24817.617.31490.285105
24914.0513.44020.609836
25016.116.4695-0.369508
25113.3515.6065-2.25652
25211.8513.6067-1.75671
25311.9511.90550.0445026
25414.7514.7503-0.000346634
25515.1517.8907-2.7407
25613.212.46620.733778
25716.8521.5453-4.69528
2587.8513.1414-5.29139
2597.710.409-2.70904
26012.619.323-6.723
2617.858.98607-1.13607
26210.9513.0355-2.08547
26312.3516.1738-3.8238
2649.959.169030.78097
26514.913.17461.72541
26616.6516.42280.22723
26713.413.4399-0.0398762
26813.9512.5371.41299
26915.713.92791.77207
27016.8518.4099-1.55993
27110.959.951140.998862
27215.3515.8957-0.54566
27312.211.31240.887627
27415.113.55271.54732
27517.7517.35540.394641
27615.215.2166-0.0165847
27714.613.79270.807264
27816.6519.4879-2.83794
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 & 12.906 & -0.00604801 \tabularnewline
2 & 12.2 & 10.3269 & 1.87309 \tabularnewline
3 & 12.8 & 11.4987 & 1.30134 \tabularnewline
4 & 7.4 & 11.6056 & -4.20559 \tabularnewline
5 & 6.7 & 10.1743 & -3.47429 \tabularnewline
6 & 12.6 & 13.546 & -0.94601 \tabularnewline
7 & 14.8 & 12.1855 & 2.61447 \tabularnewline
8 & 13.3 & 10.723 & 2.57699 \tabularnewline
9 & 11.1 & 11.96 & -0.860028 \tabularnewline
10 & 8.2 & 11.6572 & -3.45724 \tabularnewline
11 & 11.4 & 11.796 & -0.396024 \tabularnewline
12 & 6.4 & 11.4576 & -5.05755 \tabularnewline
13 & 10.6 & 9.12177 & 1.47823 \tabularnewline
14 & 12 & 13.5574 & -1.55745 \tabularnewline
15 & 6.3 & 6.56444 & -0.264442 \tabularnewline
16 & 11.3 & 9.6564 & 1.6436 \tabularnewline
17 & 11.9 & 12.3881 & -0.488071 \tabularnewline
18 & 9.3 & 10.2352 & -0.935222 \tabularnewline
19 & 9.6 & 11.4126 & -1.81258 \tabularnewline
20 & 10 & 9.88477 & 0.115232 \tabularnewline
21 & 6.4 & 10.0912 & -3.69124 \tabularnewline
22 & 13.8 & 10.3057 & 3.49429 \tabularnewline
23 & 10.8 & 14.0642 & -3.26421 \tabularnewline
24 & 13.8 & 12.9876 & 0.812432 \tabularnewline
25 & 11.7 & 11.1255 & 0.574526 \tabularnewline
26 & 10.9 & 14.8411 & -3.94107 \tabularnewline
27 & 16.1 & 13.3134 & 2.78663 \tabularnewline
28 & 13.4 & 10.5552 & 2.84476 \tabularnewline
29 & 9.9 & 11.5423 & -1.64229 \tabularnewline
30 & 11.5 & 11.3189 & 0.181146 \tabularnewline
31 & 8.3 & 9.47418 & -1.17418 \tabularnewline
32 & 11.7 & 11.622 & 0.0779516 \tabularnewline
33 & 9 & 10.0676 & -1.06758 \tabularnewline
34 & 9.7 & 11.7332 & -2.03316 \tabularnewline
35 & 10.8 & 9.34133 & 1.45867 \tabularnewline
36 & 10.3 & 8.42354 & 1.87646 \tabularnewline
37 & 10.4 & 10.6176 & -0.217598 \tabularnewline
38 & 12.7 & 10.3447 & 2.35526 \tabularnewline
39 & 9.3 & 11.805 & -2.50503 \tabularnewline
40 & 11.8 & 12.0428 & -0.242832 \tabularnewline
41 & 5.9 & 9.60157 & -3.70157 \tabularnewline
42 & 11.4 & 10.8253 & 0.57467 \tabularnewline
43 & 13 & 11.6533 & 1.34667 \tabularnewline
44 & 10.8 & 11.8508 & -1.05081 \tabularnewline
45 & 12.3 & 8.51009 & 3.78991 \tabularnewline
46 & 11.3 & 12.685 & -1.38498 \tabularnewline
47 & 11.8 & 9.76064 & 2.03936 \tabularnewline
48 & 7.9 & 9.61292 & -1.71292 \tabularnewline
49 & 12.7 & 9.46738 & 3.23262 \tabularnewline
50 & 12.3 & 8.80482 & 3.49518 \tabularnewline
51 & 11.6 & 10.5008 & 1.09916 \tabularnewline
52 & 6.7 & 7.16934 & -0.469337 \tabularnewline
53 & 10.9 & 10.5942 & 0.305847 \tabularnewline
54 & 12.1 & 11.5521 & 0.547879 \tabularnewline
55 & 13.3 & 10.0453 & 3.25466 \tabularnewline
56 & 10.1 & 9.64012 & 0.459876 \tabularnewline
57 & 5.7 & 11.0865 & -5.38646 \tabularnewline
58 & 14.3 & 10.2137 & 4.08629 \tabularnewline
59 & 8 & 7.19605 & 0.803953 \tabularnewline
60 & 13.3 & 10.6008 & 2.69919 \tabularnewline
61 & 9.3 & 12.7039 & -3.4039 \tabularnewline
62 & 12.5 & 11.0785 & 1.42153 \tabularnewline
63 & 7.6 & 9.38499 & -1.78499 \tabularnewline
64 & 15.9 & 13.6909 & 2.20907 \tabularnewline
65 & 9.2 & 12.4836 & -3.28355 \tabularnewline
66 & 9.1 & 8.49638 & 0.603619 \tabularnewline
67 & 11.1 & 13.1609 & -2.06088 \tabularnewline
68 & 13 & 15.0686 & -2.06855 \tabularnewline
69 & 14.5 & 11.6986 & 2.80137 \tabularnewline
70 & 12.2 & 10.8287 & 1.37125 \tabularnewline
71 & 12.3 & 13.315 & -1.01499 \tabularnewline
72 & 11.4 & 10.2091 & 1.19087 \tabularnewline
73 & 8.8 & 9.8622 & -1.0622 \tabularnewline
74 & 14.6 & 10.7233 & 3.87675 \tabularnewline
75 & 12.6 & 10.7851 & 1.81492 \tabularnewline
76 & NA & NA & 0.645481 \tabularnewline
77 & 13 & 10.7916 & 2.20842 \tabularnewline
78 & 12.6 & 11.6885 & 0.911547 \tabularnewline
79 & 13.2 & 12.3201 & 0.879868 \tabularnewline
80 & 9.9 & 12.0456 & -2.14558 \tabularnewline
81 & 7.7 & 7.66175 & 0.0382548 \tabularnewline
82 & 10.5 & 7.44532 & 3.05468 \tabularnewline
83 & 13.4 & 13.0211 & 0.378886 \tabularnewline
84 & 10.9 & 15.8513 & -4.95134 \tabularnewline
85 & 4.3 & 5.47555 & -1.17555 \tabularnewline
86 & 10.3 & 9.66381 & 0.636185 \tabularnewline
87 & 11.8 & 9.48006 & 2.31994 \tabularnewline
88 & 11.2 & 8.44554 & 2.75446 \tabularnewline
89 & 11.4 & 12.8299 & -1.42989 \tabularnewline
90 & 8.6 & 6.90452 & 1.69548 \tabularnewline
91 & 13.2 & 9.26732 & 3.93268 \tabularnewline
92 & 12.6 & 17.2197 & -4.61969 \tabularnewline
93 & 5.6 & 7.79306 & -2.19306 \tabularnewline
94 & 9.9 & 11.2793 & -1.37931 \tabularnewline
95 & 8.8 & 10.5357 & -1.73571 \tabularnewline
96 & 7.7 & 9.30951 & -1.60951 \tabularnewline
97 & 9 & 12.7377 & -3.73767 \tabularnewline
98 & 7.3 & 5.18055 & 2.11945 \tabularnewline
99 & 11.4 & 7.3199 & 4.0801 \tabularnewline
100 & 13.6 & 15.7268 & -2.12682 \tabularnewline
101 & 7.9 & 5.91975 & 1.98025 \tabularnewline
102 & 10.7 & 10.6026 & 0.0974186 \tabularnewline
103 & 10.3 & 10.8769 & -0.576894 \tabularnewline
104 & 8.3 & 9.71251 & -1.41251 \tabularnewline
105 & 9.6 & 5.15122 & 4.44878 \tabularnewline
106 & 14.2 & 15.8724 & -1.67243 \tabularnewline
107 & 8.5 & 4.70278 & 3.79722 \tabularnewline
108 & 13.5 & 18.4219 & -4.92189 \tabularnewline
109 & 4.9 & 6.52497 & -1.62497 \tabularnewline
110 & 6.4 & 7.39228 & -0.992279 \tabularnewline
111 & 9.6 & 8.72575 & 0.87425 \tabularnewline
112 & 11.6 & 9.61309 & 1.98691 \tabularnewline
113 & 11.1 & 17.4636 & -6.36361 \tabularnewline
114 & 4.35 & 3.89538 & 0.45462 \tabularnewline
115 & 12.7 & 9.77772 & 2.92228 \tabularnewline
116 & 18.1 & 15.6143 & 2.4857 \tabularnewline
117 & 17.85 & 19.1934 & -1.34338 \tabularnewline
118 & 16.6 & 16.2323 & 0.367655 \tabularnewline
119 & 12.6 & 13.7163 & -1.11629 \tabularnewline
120 & 17.1 & 15.2371 & 1.86295 \tabularnewline
121 & 19.1 & 21.861 & -2.76096 \tabularnewline
122 & 16.1 & 14.5214 & 1.57861 \tabularnewline
123 & 13.35 & 11.299 & 2.05096 \tabularnewline
124 & 18.4 & 14.005 & 4.395 \tabularnewline
125 & 14.7 & 17.2361 & -2.53608 \tabularnewline
126 & 10.6 & 11.176 & -0.57604 \tabularnewline
127 & 12.6 & 11.0931 & 1.5069 \tabularnewline
128 & 16.2 & 16.5325 & -0.332539 \tabularnewline
129 & 13.6 & 11.0113 & 2.58867 \tabularnewline
130 & 18.9 & 17.8728 & 1.02719 \tabularnewline
131 & 14.1 & 13.1138 & 0.986222 \tabularnewline
132 & 14.5 & 15.7838 & -1.28377 \tabularnewline
133 & 16.15 & 14.7978 & 1.35222 \tabularnewline
134 & 14.75 & 13.4704 & 1.27957 \tabularnewline
135 & 14.8 & 14.7172 & 0.0827931 \tabularnewline
136 & 12.45 & 12.4471 & 0.00291074 \tabularnewline
137 & 12.65 & 9.33987 & 3.31013 \tabularnewline
138 & 17.35 & 19.1868 & -1.83676 \tabularnewline
139 & 8.6 & 6.8375 & 1.7625 \tabularnewline
140 & 18.4 & 17.4031 & 0.996869 \tabularnewline
141 & 16.1 & 17.3635 & -1.26345 \tabularnewline
142 & 11.6 & 8.77996 & 2.82004 \tabularnewline
143 & 17.75 & 17.4904 & 0.259552 \tabularnewline
144 & 15.25 & 11.9873 & 3.26271 \tabularnewline
145 & 17.65 & 17.4821 & 0.167896 \tabularnewline
146 & 16.35 & 15.5254 & 0.824551 \tabularnewline
147 & 17.65 & 17.7514 & -0.101418 \tabularnewline
148 & 13.6 & 13.5686 & 0.0314365 \tabularnewline
149 & 14.35 & 14.4367 & -0.0866586 \tabularnewline
150 & 14.75 & 12.6099 & 2.14005 \tabularnewline
151 & 18.25 & 24.1075 & -5.85753 \tabularnewline
152 & 9.9 & 8.85117 & 1.04883 \tabularnewline
153 & 16 & 13.3398 & 2.66024 \tabularnewline
154 & 18.25 & 18.3975 & -0.147482 \tabularnewline
155 & 16.85 & 15.0796 & 1.77039 \tabularnewline
156 & 14.6 & 15.1542 & -0.554167 \tabularnewline
157 & 13.85 & 12.183 & 1.66697 \tabularnewline
158 & 18.95 & 17.8009 & 1.14914 \tabularnewline
159 & 15.6 & 17.7731 & -2.17311 \tabularnewline
160 & 14.85 & 17.1577 & -2.30767 \tabularnewline
161 & 11.75 & 10.5058 & 1.2442 \tabularnewline
162 & 18.45 & 16.4035 & 2.04646 \tabularnewline
163 & 15.9 & 16.2 & -0.300026 \tabularnewline
164 & 17.1 & 10.2666 & 6.83339 \tabularnewline
165 & 16.1 & 15.022 & 1.07804 \tabularnewline
166 & 19.9 & 20.8125 & -0.912499 \tabularnewline
167 & 10.95 & 9.3055 & 1.6445 \tabularnewline
168 & 18.45 & 16.7838 & 1.66615 \tabularnewline
169 & 15.1 & 14.9821 & 0.11789 \tabularnewline
170 & 15 & 18.4901 & -3.49009 \tabularnewline
171 & 11.35 & 10.1475 & 1.20246 \tabularnewline
172 & 15.95 & 13.6717 & 2.2783 \tabularnewline
173 & 18.1 & 19.9847 & -1.88465 \tabularnewline
174 & 14.6 & 14.8161 & -0.21609 \tabularnewline
175 & 15.4 & 15.5872 & -0.187245 \tabularnewline
176 & 15.4 & 12.914 & 2.48595 \tabularnewline
177 & 17.6 & 18.9784 & -1.37838 \tabularnewline
178 & 13.35 & 10.3674 & 2.98261 \tabularnewline
179 & 19.1 & 20.3256 & -1.22559 \tabularnewline
180 & 15.35 & 18.9928 & -3.64278 \tabularnewline
181 & 7.6 & 10.2299 & -2.62989 \tabularnewline
182 & 13.4 & 15.058 & -1.65798 \tabularnewline
183 & 13.9 & 11.0173 & 2.88268 \tabularnewline
184 & 19.1 & 19.1847 & -0.0846928 \tabularnewline
185 & 15.25 & 18.1344 & -2.88435 \tabularnewline
186 & 12.9 & 12.9014 & -0.00139317 \tabularnewline
187 & 16.1 & 13.5741 & 2.52589 \tabularnewline
188 & 17.35 & 19.532 & -2.182 \tabularnewline
189 & 13.15 & 15.282 & -2.13203 \tabularnewline
190 & 12.15 & 12.1444 & 0.00559233 \tabularnewline
191 & 12.6 & 14.9721 & -2.37206 \tabularnewline
192 & 10.35 & 9.45373 & 0.896269 \tabularnewline
193 & 15.4 & 18.4568 & -3.05677 \tabularnewline
194 & 9.6 & 6.26376 & 3.33624 \tabularnewline
195 & 18.2 & 18.6308 & -0.430788 \tabularnewline
196 & 13.6 & 13.0155 & 0.584451 \tabularnewline
197 & 14.85 & 16.474 & -1.62405 \tabularnewline
198 & 14.75 & 14.7174 & 0.0325786 \tabularnewline
199 & 14.1 & 12.5723 & 1.52774 \tabularnewline
200 & 14.9 & 14.0025 & 0.897531 \tabularnewline
201 & 16.25 & 16.1775 & 0.0725469 \tabularnewline
202 & 19.25 & 18.4486 & 0.801378 \tabularnewline
203 & 13.6 & 14.9547 & -1.35469 \tabularnewline
204 & 13.6 & 13.5015 & 0.0985208 \tabularnewline
205 & 15.65 & 16.1283 & -0.478346 \tabularnewline
206 & 12.75 & 11.3927 & 1.35735 \tabularnewline
207 & 14.6 & 15.8001 & -1.2001 \tabularnewline
208 & 9.85 & 9.68464 & 0.165358 \tabularnewline
209 & 12.65 & 9.54514 & 3.10486 \tabularnewline
210 & 19.2 & 17.2537 & 1.94625 \tabularnewline
211 & 16.6 & 17.7892 & -1.18922 \tabularnewline
212 & 11.2 & 10.7353 & 0.464663 \tabularnewline
213 & 15.25 & 17.5532 & -2.30322 \tabularnewline
214 & 11.9 & 12.1541 & -0.25405 \tabularnewline
215 & 13.2 & 13.7441 & -0.544096 \tabularnewline
216 & 16.35 & 17.0286 & -0.678577 \tabularnewline
217 & 12.4 & 11.0251 & 1.37486 \tabularnewline
218 & 15.85 & 13.6488 & 2.20118 \tabularnewline
219 & 18.15 & 19.8664 & -1.71637 \tabularnewline
220 & 11.15 & 11.7513 & -0.601292 \tabularnewline
221 & 15.65 & 12.8551 & 2.79493 \tabularnewline
222 & 17.75 & 22.5204 & -4.7704 \tabularnewline
223 & 7.65 & 8.55828 & -0.908275 \tabularnewline
224 & 12.35 & 9.94758 & 2.40242 \tabularnewline
225 & 15.6 & 12.982 & 2.61796 \tabularnewline
226 & 19.3 & 16.9753 & 2.32469 \tabularnewline
227 & 15.2 & 12.6416 & 2.55838 \tabularnewline
228 & 17.1 & 15.0289 & 2.07114 \tabularnewline
229 & 15.6 & 12.6751 & 2.92485 \tabularnewline
230 & 18.4 & 15.1155 & 3.28452 \tabularnewline
231 & 19.05 & 15.375 & 3.67501 \tabularnewline
232 & 18.55 & 16.2734 & 2.27658 \tabularnewline
233 & 19.1 & 19.41 & -0.309966 \tabularnewline
234 & 13.1 & 15.5652 & -2.46521 \tabularnewline
235 & 12.85 & 15.2756 & -2.42557 \tabularnewline
236 & 9.5 & 15.9838 & -6.48383 \tabularnewline
237 & 4.5 & 4.61207 & -0.112065 \tabularnewline
238 & 11.85 & 12.9104 & -1.06036 \tabularnewline
239 & 13.6 & 14.08 & -0.480038 \tabularnewline
240 & 11.7 & 12.4627 & -0.762733 \tabularnewline
241 & 12.4 & 13.7111 & -1.31108 \tabularnewline
242 & 13.35 & 15.3226 & -1.97258 \tabularnewline
243 & 11.4 & 10.6731 & 0.726944 \tabularnewline
244 & 14.9 & 13.721 & 1.17905 \tabularnewline
245 & 19.9 & 22.3788 & -2.47879 \tabularnewline
246 & 11.2 & 11.667 & -0.466953 \tabularnewline
247 & 14.6 & 14.4856 & 0.114352 \tabularnewline
248 & 17.6 & 17.3149 & 0.285105 \tabularnewline
249 & 14.05 & 13.4402 & 0.609836 \tabularnewline
250 & 16.1 & 16.4695 & -0.369508 \tabularnewline
251 & 13.35 & 15.6065 & -2.25652 \tabularnewline
252 & 11.85 & 13.6067 & -1.75671 \tabularnewline
253 & 11.95 & 11.9055 & 0.0445026 \tabularnewline
254 & 14.75 & 14.7503 & -0.000346634 \tabularnewline
255 & 15.15 & 17.8907 & -2.7407 \tabularnewline
256 & 13.2 & 12.4662 & 0.733778 \tabularnewline
257 & 16.85 & 21.5453 & -4.69528 \tabularnewline
258 & 7.85 & 13.1414 & -5.29139 \tabularnewline
259 & 7.7 & 10.409 & -2.70904 \tabularnewline
260 & 12.6 & 19.323 & -6.723 \tabularnewline
261 & 7.85 & 8.98607 & -1.13607 \tabularnewline
262 & 10.95 & 13.0355 & -2.08547 \tabularnewline
263 & 12.35 & 16.1738 & -3.8238 \tabularnewline
264 & 9.95 & 9.16903 & 0.78097 \tabularnewline
265 & 14.9 & 13.1746 & 1.72541 \tabularnewline
266 & 16.65 & 16.4228 & 0.22723 \tabularnewline
267 & 13.4 & 13.4399 & -0.0398762 \tabularnewline
268 & 13.95 & 12.537 & 1.41299 \tabularnewline
269 & 15.7 & 13.9279 & 1.77207 \tabularnewline
270 & 16.85 & 18.4099 & -1.55993 \tabularnewline
271 & 10.95 & 9.95114 & 0.998862 \tabularnewline
272 & 15.35 & 15.8957 & -0.54566 \tabularnewline
273 & 12.2 & 11.3124 & 0.887627 \tabularnewline
274 & 15.1 & 13.5527 & 1.54732 \tabularnewline
275 & 17.75 & 17.3554 & 0.394641 \tabularnewline
276 & 15.2 & 15.2166 & -0.0165847 \tabularnewline
277 & 14.6 & 13.7927 & 0.807264 \tabularnewline
278 & 16.65 & 19.4879 & -2.83794 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.906[/C][C]-0.00604801[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.3269[/C][C]1.87309[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.4987[/C][C]1.30134[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.6056[/C][C]-4.20559[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.1743[/C][C]-3.47429[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.546[/C][C]-0.94601[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]12.1855[/C][C]2.61447[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]10.723[/C][C]2.57699[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]11.96[/C][C]-0.860028[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]11.6572[/C][C]-3.45724[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.796[/C][C]-0.396024[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.4576[/C][C]-5.05755[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.12177[/C][C]1.47823[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]13.5574[/C][C]-1.55745[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]6.56444[/C][C]-0.264442[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.6564[/C][C]1.6436[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]12.3881[/C][C]-0.488071[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.2352[/C][C]-0.935222[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.4126[/C][C]-1.81258[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.88477[/C][C]0.115232[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.0912[/C][C]-3.69124[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.3057[/C][C]3.49429[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.0642[/C][C]-3.26421[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.9876[/C][C]0.812432[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.1255[/C][C]0.574526[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.8411[/C][C]-3.94107[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]13.3134[/C][C]2.78663[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.5552[/C][C]2.84476[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.5423[/C][C]-1.64229[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.3189[/C][C]0.181146[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]9.47418[/C][C]-1.17418[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]11.622[/C][C]0.0779516[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.0676[/C][C]-1.06758[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.7332[/C][C]-2.03316[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.34133[/C][C]1.45867[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]8.42354[/C][C]1.87646[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]10.6176[/C][C]-0.217598[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.3447[/C][C]2.35526[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.805[/C][C]-2.50503[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.0428[/C][C]-0.242832[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.60157[/C][C]-3.70157[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]10.8253[/C][C]0.57467[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.6533[/C][C]1.34667[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.8508[/C][C]-1.05081[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]8.51009[/C][C]3.78991[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]12.685[/C][C]-1.38498[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.76064[/C][C]2.03936[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.61292[/C][C]-1.71292[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.46738[/C][C]3.23262[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]8.80482[/C][C]3.49518[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.5008[/C][C]1.09916[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.16934[/C][C]-0.469337[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.5942[/C][C]0.305847[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]11.5521[/C][C]0.547879[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]10.0453[/C][C]3.25466[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.64012[/C][C]0.459876[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.0865[/C][C]-5.38646[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.2137[/C][C]4.08629[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.19605[/C][C]0.803953[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.6008[/C][C]2.69919[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.7039[/C][C]-3.4039[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.0785[/C][C]1.42153[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.38499[/C][C]-1.78499[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.6909[/C][C]2.20907[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]12.4836[/C][C]-3.28355[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.49638[/C][C]0.603619[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]13.1609[/C][C]-2.06088[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]15.0686[/C][C]-2.06855[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]11.6986[/C][C]2.80137[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.8287[/C][C]1.37125[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.315[/C][C]-1.01499[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.2091[/C][C]1.19087[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]9.8622[/C][C]-1.0622[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.7233[/C][C]3.87675[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.7851[/C][C]1.81492[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.645481[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.7916[/C][C]2.20842[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.6885[/C][C]0.911547[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]12.3201[/C][C]0.879868[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]12.0456[/C][C]-2.14558[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.66175[/C][C]0.0382548[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.44532[/C][C]3.05468[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]13.0211[/C][C]0.378886[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]15.8513[/C][C]-4.95134[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.47555[/C][C]-1.17555[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]9.66381[/C][C]0.636185[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]9.48006[/C][C]2.31994[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]8.44554[/C][C]2.75446[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]12.8299[/C][C]-1.42989[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]6.90452[/C][C]1.69548[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.26732[/C][C]3.93268[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]17.2197[/C][C]-4.61969[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.79306[/C][C]-2.19306[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.2793[/C][C]-1.37931[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.5357[/C][C]-1.73571[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]9.30951[/C][C]-1.60951[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]12.7377[/C][C]-3.73767[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.18055[/C][C]2.11945[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.3199[/C][C]4.0801[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]15.7268[/C][C]-2.12682[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]5.91975[/C][C]1.98025[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.6026[/C][C]0.0974186[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.8769[/C][C]-0.576894[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.71251[/C][C]-1.41251[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]5.15122[/C][C]4.44878[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]15.8724[/C][C]-1.67243[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]4.70278[/C][C]3.79722[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.4219[/C][C]-4.92189[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]6.52497[/C][C]-1.62497[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.39228[/C][C]-0.992279[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]8.72575[/C][C]0.87425[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]9.61309[/C][C]1.98691[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]17.4636[/C][C]-6.36361[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.89538[/C][C]0.45462[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]9.77772[/C][C]2.92228[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]15.6143[/C][C]2.4857[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]19.1934[/C][C]-1.34338[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.2323[/C][C]0.367655[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.7163[/C][C]-1.11629[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]15.2371[/C][C]1.86295[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.861[/C][C]-2.76096[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]14.5214[/C][C]1.57861[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]11.299[/C][C]2.05096[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.005[/C][C]4.395[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.2361[/C][C]-2.53608[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.176[/C][C]-0.57604[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.0931[/C][C]1.5069[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.5325[/C][C]-0.332539[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]11.0113[/C][C]2.58867[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]17.8728[/C][C]1.02719[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.1138[/C][C]0.986222[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]15.7838[/C][C]-1.28377[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.7978[/C][C]1.35222[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.4704[/C][C]1.27957[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.7172[/C][C]0.0827931[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.4471[/C][C]0.00291074[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.33987[/C][C]3.31013[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.1868[/C][C]-1.83676[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]6.8375[/C][C]1.7625[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]17.4031[/C][C]0.996869[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.3635[/C][C]-1.26345[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]8.77996[/C][C]2.82004[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]17.4904[/C][C]0.259552[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.9873[/C][C]3.26271[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]17.4821[/C][C]0.167896[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]15.5254[/C][C]0.824551[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]17.7514[/C][C]-0.101418[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.5686[/C][C]0.0314365[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.4367[/C][C]-0.0866586[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]12.6099[/C][C]2.14005[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]24.1075[/C][C]-5.85753[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.85117[/C][C]1.04883[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.3398[/C][C]2.66024[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.3975[/C][C]-0.147482[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.0796[/C][C]1.77039[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]15.1542[/C][C]-0.554167[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]12.183[/C][C]1.66697[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.8009[/C][C]1.14914[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]17.7731[/C][C]-2.17311[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]17.1577[/C][C]-2.30767[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]10.5058[/C][C]1.2442[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.4035[/C][C]2.04646[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]16.2[/C][C]-0.300026[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]10.2666[/C][C]6.83339[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]15.022[/C][C]1.07804[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.8125[/C][C]-0.912499[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]9.3055[/C][C]1.6445[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]16.7838[/C][C]1.66615[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]14.9821[/C][C]0.11789[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]18.4901[/C][C]-3.49009[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]10.1475[/C][C]1.20246[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.6717[/C][C]2.2783[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]19.9847[/C][C]-1.88465[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]14.8161[/C][C]-0.21609[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]15.5872[/C][C]-0.187245[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.914[/C][C]2.48595[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.9784[/C][C]-1.37838[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.3674[/C][C]2.98261[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.3256[/C][C]-1.22559[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.9928[/C][C]-3.64278[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]10.2299[/C][C]-2.62989[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.058[/C][C]-1.65798[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]11.0173[/C][C]2.88268[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]19.1847[/C][C]-0.0846928[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]18.1344[/C][C]-2.88435[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.9014[/C][C]-0.00139317[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]13.5741[/C][C]2.52589[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.532[/C][C]-2.182[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]15.282[/C][C]-2.13203[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]12.1444[/C][C]0.00559233[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]14.9721[/C][C]-2.37206[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.45373[/C][C]0.896269[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.4568[/C][C]-3.05677[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.26376[/C][C]3.33624[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.6308[/C][C]-0.430788[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]13.0155[/C][C]0.584451[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.474[/C][C]-1.62405[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.7174[/C][C]0.0325786[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]12.5723[/C][C]1.52774[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.0025[/C][C]0.897531[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]16.1775[/C][C]0.0725469[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.4486[/C][C]0.801378[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]14.9547[/C][C]-1.35469[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.5015[/C][C]0.0985208[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.1283[/C][C]-0.478346[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.3927[/C][C]1.35735[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.8001[/C][C]-1.2001[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.68464[/C][C]0.165358[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]9.54514[/C][C]3.10486[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.2537[/C][C]1.94625[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.7892[/C][C]-1.18922[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]10.7353[/C][C]0.464663[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]17.5532[/C][C]-2.30322[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.1541[/C][C]-0.25405[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]13.7441[/C][C]-0.544096[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.0286[/C][C]-0.678577[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]11.0251[/C][C]1.37486[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]13.6488[/C][C]2.20118[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.8664[/C][C]-1.71637[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.7513[/C][C]-0.601292[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]12.8551[/C][C]2.79493[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.5204[/C][C]-4.7704[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]8.55828[/C][C]-0.908275[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]9.94758[/C][C]2.40242[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]12.982[/C][C]2.61796[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]16.9753[/C][C]2.32469[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]12.6416[/C][C]2.55838[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.0289[/C][C]2.07114[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]12.6751[/C][C]2.92485[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.1155[/C][C]3.28452[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]15.375[/C][C]3.67501[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]16.2734[/C][C]2.27658[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.41[/C][C]-0.309966[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]15.5652[/C][C]-2.46521[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.2756[/C][C]-2.42557[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]15.9838[/C][C]-6.48383[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]4.61207[/C][C]-0.112065[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]12.9104[/C][C]-1.06036[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]14.08[/C][C]-0.480038[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.4627[/C][C]-0.762733[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.7111[/C][C]-1.31108[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]15.3226[/C][C]-1.97258[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.6731[/C][C]0.726944[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.721[/C][C]1.17905[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.3788[/C][C]-2.47879[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.667[/C][C]-0.466953[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]14.4856[/C][C]0.114352[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]17.3149[/C][C]0.285105[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.4402[/C][C]0.609836[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]16.4695[/C][C]-0.369508[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]15.6065[/C][C]-2.25652[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]13.6067[/C][C]-1.75671[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.9055[/C][C]0.0445026[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]14.7503[/C][C]-0.000346634[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]17.8907[/C][C]-2.7407[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.4662[/C][C]0.733778[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.5453[/C][C]-4.69528[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]13.1414[/C][C]-5.29139[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.409[/C][C]-2.70904[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.323[/C][C]-6.723[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.98607[/C][C]-1.13607[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.0355[/C][C]-2.08547[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]16.1738[/C][C]-3.8238[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]9.16903[/C][C]0.78097[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.1746[/C][C]1.72541[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.4228[/C][C]0.22723[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.4399[/C][C]-0.0398762[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]12.537[/C][C]1.41299[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]13.9279[/C][C]1.77207[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.4099[/C][C]-1.55993[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]9.95114[/C][C]0.998862[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.8957[/C][C]-0.54566[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]11.3124[/C][C]0.887627[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]13.5527[/C][C]1.54732[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.3554[/C][C]0.394641[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.2166[/C][C]-0.0165847[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.7927[/C][C]0.807264[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]19.4879[/C][C]-2.83794[/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=263930&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.906-0.00604801
212.210.32691.87309
312.811.49871.30134
47.411.6056-4.20559
56.710.1743-3.47429
612.613.546-0.94601
714.812.18552.61447
813.310.7232.57699
911.111.96-0.860028
108.211.6572-3.45724
1111.411.796-0.396024
126.411.4576-5.05755
1310.69.121771.47823
141213.5574-1.55745
156.36.56444-0.264442
1611.39.65641.6436
1711.912.3881-0.488071
189.310.2352-0.935222
199.611.4126-1.81258
20109.884770.115232
216.410.0912-3.69124
2213.810.30573.49429
2310.814.0642-3.26421
2413.812.98760.812432
2511.711.12550.574526
2610.914.8411-3.94107
2716.113.31342.78663
2813.410.55522.84476
299.911.5423-1.64229
3011.511.31890.181146
318.39.47418-1.17418
3211.711.6220.0779516
33910.0676-1.06758
349.711.7332-2.03316
3510.89.341331.45867
3610.38.423541.87646
3710.410.6176-0.217598
3812.710.34472.35526
399.311.805-2.50503
4011.812.0428-0.242832
415.99.60157-3.70157
4211.410.82530.57467
431311.65331.34667
4410.811.8508-1.05081
4512.38.510093.78991
4611.312.685-1.38498
4711.89.760642.03936
487.99.61292-1.71292
4912.79.467383.23262
5012.38.804823.49518
5111.610.50081.09916
526.77.16934-0.469337
5310.910.59420.305847
5412.111.55210.547879
5513.310.04533.25466
5610.19.640120.459876
575.711.0865-5.38646
5814.310.21374.08629
5987.196050.803953
6013.310.60082.69919
619.312.7039-3.4039
6212.511.07851.42153
637.69.38499-1.78499
6415.913.69092.20907
659.212.4836-3.28355
669.18.496380.603619
6711.113.1609-2.06088
681315.0686-2.06855
6914.511.69862.80137
7012.210.82871.37125
7112.313.315-1.01499
7211.410.20911.19087
738.89.8622-1.0622
7414.610.72333.87675
7512.610.78511.81492
76NANA0.645481
771310.79162.20842
7812.611.68850.911547
7913.212.32010.879868
809.912.0456-2.14558
817.77.661750.0382548
8210.57.445323.05468
8313.413.02110.378886
8410.915.8513-4.95134
854.35.47555-1.17555
8610.39.663810.636185
8711.89.480062.31994
8811.28.445542.75446
8911.412.8299-1.42989
908.66.904521.69548
9113.29.267323.93268
9212.617.2197-4.61969
935.67.79306-2.19306
949.911.2793-1.37931
958.810.5357-1.73571
967.79.30951-1.60951
97912.7377-3.73767
987.35.180552.11945
9911.47.31994.0801
10013.615.7268-2.12682
1017.95.919751.98025
10210.710.60260.0974186
10310.310.8769-0.576894
1048.39.71251-1.41251
1059.65.151224.44878
10614.215.8724-1.67243
1078.54.702783.79722
10813.518.4219-4.92189
1094.96.52497-1.62497
1106.47.39228-0.992279
1119.68.725750.87425
11211.69.613091.98691
11311.117.4636-6.36361
1144.353.895380.45462
11512.79.777722.92228
11618.115.61432.4857
11717.8519.1934-1.34338
11816.616.23230.367655
11912.613.7163-1.11629
12017.115.23711.86295
12119.121.861-2.76096
12216.114.52141.57861
12313.3511.2992.05096
12418.414.0054.395
12514.717.2361-2.53608
12610.611.176-0.57604
12712.611.09311.5069
12816.216.5325-0.332539
12913.611.01132.58867
13018.917.87281.02719
13114.113.11380.986222
13214.515.7838-1.28377
13316.1514.79781.35222
13414.7513.47041.27957
13514.814.71720.0827931
13612.4512.44710.00291074
13712.659.339873.31013
13817.3519.1868-1.83676
1398.66.83751.7625
14018.417.40310.996869
14116.117.3635-1.26345
14211.68.779962.82004
14317.7517.49040.259552
14415.2511.98733.26271
14517.6517.48210.167896
14616.3515.52540.824551
14717.6517.7514-0.101418
14813.613.56860.0314365
14914.3514.4367-0.0866586
15014.7512.60992.14005
15118.2524.1075-5.85753
1529.98.851171.04883
1531613.33982.66024
15418.2518.3975-0.147482
15516.8515.07961.77039
15614.615.1542-0.554167
15713.8512.1831.66697
15818.9517.80091.14914
15915.617.7731-2.17311
16014.8517.1577-2.30767
16111.7510.50581.2442
16218.4516.40352.04646
16315.916.2-0.300026
16417.110.26666.83339
16516.115.0221.07804
16619.920.8125-0.912499
16710.959.30551.6445
16818.4516.78381.66615
16915.114.98210.11789
1701518.4901-3.49009
17111.3510.14751.20246
17215.9513.67172.2783
17318.119.9847-1.88465
17414.614.8161-0.21609
17515.415.5872-0.187245
17615.412.9142.48595
17717.618.9784-1.37838
17813.3510.36742.98261
17919.120.3256-1.22559
18015.3518.9928-3.64278
1817.610.2299-2.62989
18213.415.058-1.65798
18313.911.01732.88268
18419.119.1847-0.0846928
18515.2518.1344-2.88435
18612.912.9014-0.00139317
18716.113.57412.52589
18817.3519.532-2.182
18913.1515.282-2.13203
19012.1512.14440.00559233
19112.614.9721-2.37206
19210.359.453730.896269
19315.418.4568-3.05677
1949.66.263763.33624
19518.218.6308-0.430788
19613.613.01550.584451
19714.8516.474-1.62405
19814.7514.71740.0325786
19914.112.57231.52774
20014.914.00250.897531
20116.2516.17750.0725469
20219.2518.44860.801378
20313.614.9547-1.35469
20413.613.50150.0985208
20515.6516.1283-0.478346
20612.7511.39271.35735
20714.615.8001-1.2001
2089.859.684640.165358
20912.659.545143.10486
21019.217.25371.94625
21116.617.7892-1.18922
21211.210.73530.464663
21315.2517.5532-2.30322
21411.912.1541-0.25405
21513.213.7441-0.544096
21616.3517.0286-0.678577
21712.411.02511.37486
21815.8513.64882.20118
21918.1519.8664-1.71637
22011.1511.7513-0.601292
22115.6512.85512.79493
22217.7522.5204-4.7704
2237.658.55828-0.908275
22412.359.947582.40242
22515.612.9822.61796
22619.316.97532.32469
22715.212.64162.55838
22817.115.02892.07114
22915.612.67512.92485
23018.415.11553.28452
23119.0515.3753.67501
23218.5516.27342.27658
23319.119.41-0.309966
23413.115.5652-2.46521
23512.8515.2756-2.42557
2369.515.9838-6.48383
2374.54.61207-0.112065
23811.8512.9104-1.06036
23913.614.08-0.480038
24011.712.4627-0.762733
24112.413.7111-1.31108
24213.3515.3226-1.97258
24311.410.67310.726944
24414.913.7211.17905
24519.922.3788-2.47879
24611.211.667-0.466953
24714.614.48560.114352
24817.617.31490.285105
24914.0513.44020.609836
25016.116.4695-0.369508
25113.3515.6065-2.25652
25211.8513.6067-1.75671
25311.9511.90550.0445026
25414.7514.7503-0.000346634
25515.1517.8907-2.7407
25613.212.46620.733778
25716.8521.5453-4.69528
2587.8513.1414-5.29139
2597.710.409-2.70904
26012.619.323-6.723
2617.858.98607-1.13607
26210.9513.0355-2.08547
26312.3516.1738-3.8238
2649.959.169030.78097
26514.913.17461.72541
26616.6516.42280.22723
26713.413.4399-0.0398762
26813.9512.5371.41299
26915.713.92791.77207
27016.8518.4099-1.55993
27110.959.951140.998862
27215.3515.8957-0.54566
27312.211.31240.887627
27415.113.55271.54732
27517.7517.35540.394641
27615.215.2166-0.0165847
27714.613.79270.807264
27816.6519.4879-2.83794
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8820680.2358640.117932
140.7933890.4132220.206611
150.6867170.6265660.313283
160.5685640.8628730.431436
170.4575250.915050.542475
180.3516430.7032860.648357
190.601540.7969210.39846
200.5311350.937730.468865
210.4533480.9066960.546652
220.6841190.6317630.315881
230.7095350.5809310.290465
240.6797330.6405340.320267
250.6084270.7831470.391573
260.5606490.8787030.439351
270.4940830.9881660.505917
280.4744810.9489630.525519
290.4222660.8445310.577734
300.3585580.7171150.641442
310.4154290.8308570.584571
320.3672540.7345080.632746
330.3401410.6802830.659859
340.3001060.6002110.699894
350.2565650.513130.743435
360.2300040.4600080.769996
370.1916330.3832650.808367
380.2201460.4402930.779854
390.1954550.390910.804545
400.1858090.3716180.814191
410.2586110.5172210.741389
420.2254450.450890.774555
430.1923060.3846120.807694
440.1768230.3536470.823177
450.1594210.3188420.840579
460.1347530.2695060.865247
470.1511050.302210.848895
480.1900350.3800690.809965
490.2112660.4225310.788734
500.1999210.3998420.800079
510.1703350.340670.829665
520.1978330.3956670.802167
530.1746580.3493150.825342
540.1473320.2946650.852668
550.2328080.4656160.767192
560.1982990.3965980.801701
570.5063010.9873980.493699
580.6311450.737710.368855
590.5909180.8181640.409082
600.5695020.8609970.430498
610.6151360.7697290.384864
620.6073010.7853980.392699
630.6178120.7643750.382188
640.653830.6923410.34617
650.6579620.6840760.342038
660.6269230.7461530.373077
670.6057140.7885720.394286
680.5862920.8274150.413708
690.6356080.7287850.364392
700.6019870.7960260.398013
710.5676460.8647080.432354
720.5376570.9246860.462343
730.5153160.9693690.484684
740.5699280.8601450.430072
750.5533090.8933820.446691
760.520680.9586410.47932
770.4984860.9969720.501514
780.4785770.9571540.521423
790.4450960.8901920.554904
800.4619120.9238230.538088
810.426970.853940.57303
820.4419490.8838980.558051
830.4086540.8173080.591346
840.6030190.7939630.396981
850.5803540.8392920.419646
860.5427230.9145540.457277
870.5277230.9445550.472277
880.5265910.9468180.473409
890.5153620.9692750.484638
900.4958660.9917310.504134
910.540730.9185410.45927
920.6833330.6333330.316667
930.6829250.634150.317075
940.6702490.6595020.329751
950.6639840.6720310.336016
960.6467220.7065570.353278
970.7070040.5859930.292996
980.6955430.6089140.304457
990.7475110.5049770.252489
1000.7511790.4976430.248821
1010.734360.531280.26564
1020.7034080.5931840.296592
1030.6823150.635370.317685
1040.6653890.6692230.334611
1050.737670.524660.26233
1060.7250960.5498070.274904
1070.7781620.4436770.221838
1080.8673040.2653920.132696
1090.8665350.2669310.133465
1100.8548650.2902710.145135
1110.8393970.3212050.160603
1120.8235180.3529650.176482
1130.8634960.2730070.136504
1140.886780.226440.11322
1150.9373460.1253080.0626541
1160.9464260.1071470.0535737
1170.9382260.1235490.0617744
1180.9275430.1449130.0724566
1190.9194120.1611750.0805877
1200.9189820.1620360.0810178
1210.9291660.1416680.0708338
1220.9246230.1507550.0753773
1230.9245660.1508690.0754344
1240.9507910.09841820.0492091
1250.9551110.08977710.0448885
1260.9470870.1058270.0529134
1270.9408990.1182020.0591012
1280.9304040.1391920.0695958
1290.9303690.1392630.0696314
1300.9204620.1590750.0795375
1310.9091670.1816660.0908332
1320.9032950.193410.0967052
1330.8914060.2171880.108594
1340.8771190.2457610.122881
1350.8626810.2746390.137319
1360.8427740.3144520.157226
1370.8641120.2717770.135888
1380.8640250.271950.135975
1390.8527020.2945950.147298
1400.8344690.3310630.165531
1410.8231260.3537480.176874
1420.8344270.3311470.165573
1430.8134270.3731450.186573
1440.8340580.3318830.165942
1450.8110850.3778310.188915
1460.7893530.4212940.210647
1470.7649220.4701550.235078
1480.7370350.525930.262965
1490.7078420.5843170.292158
1500.6991610.6016770.300839
1510.8731620.2536770.126838
1520.8554780.2890440.144522
1530.8586830.2826350.141317
1540.837870.324260.16213
1550.8301920.3396150.169808
1560.8110180.3779640.188982
1570.7926390.4147220.207361
1580.7733280.4533440.226672
1590.7831960.4336080.216804
1600.7813910.4372170.218609
1610.7613360.4773280.238664
1620.7553340.4893310.244666
1630.730230.5395410.26977
1640.9574450.0851090.0425545
1650.9504490.09910170.0495508
1660.945990.1080190.0540095
1670.9386660.1226680.0613338
1680.9388780.1222440.061122
1690.9271370.1457270.0728633
1700.9475920.1048170.0524085
1710.9405130.1189750.0594874
1720.9373680.1252640.0626321
1730.9397060.1205870.0602936
1740.9282780.1434430.0717217
1750.915160.1696790.0848395
1760.9181420.1637150.0818577
1770.9078460.1843090.0921544
1780.9180410.1639190.0819593
1790.9124870.1750260.087513
1800.9232080.1535850.0767924
1810.9355810.1288380.0644191
1820.936760.126480.0632402
1830.9440850.1118290.0559145
1840.933530.1329390.0664696
1850.9491630.1016740.050837
1860.9387110.1225770.0612885
1870.9411530.1176940.0588469
1880.947640.1047210.0523605
1890.9520570.09588660.0479433
1900.9435180.1129630.0564817
1910.9405730.1188540.059427
1920.9287890.1424230.0712114
1930.9354730.1290550.0645273
1940.9403650.119270.0596349
1950.9278240.1443530.0721763
1960.9195210.1609580.0804789
1970.9200330.1599330.0799666
1980.9044030.1911930.0955967
1990.8949280.2101440.105072
2000.8761380.2477250.123862
2010.8780150.243970.121985
2020.860880.2782410.13912
2030.8595880.2808240.140412
2040.8360490.3279030.163951
2050.8155550.3688910.184445
2060.8293540.3412920.170646
2070.829210.3415810.17079
2080.8140430.3719140.185957
2090.8031980.3936040.196802
2100.802220.3955590.19778
2110.7876840.4246310.212316
2120.7557780.4884430.244222
2130.764160.4716790.23584
2140.7348860.5302280.265114
2150.7112060.5775880.288794
2160.673780.6524410.32622
2170.6745270.6509460.325473
2180.6574320.6851360.342568
2190.6276890.7446210.372311
2200.5903950.8192110.409605
2210.6007210.7985580.399279
2220.6773610.6452770.322639
2230.6396710.7206580.360329
2240.7259380.5481250.274062
2250.7203890.5592220.279611
2260.7697840.4604320.230216
2270.7839850.4320310.216015
2280.8187940.3624130.181206
2290.884050.2319010.11595
2300.9209860.1580290.0790143
2310.9262370.1475260.0737631
2320.9204380.1591240.0795619
2330.9079340.1841330.0920664
2340.8896540.2206920.110346
2350.8695270.2609460.130473
2360.9351710.1296570.0648285
2370.9200930.1598150.0799075
2380.8972040.2055930.102796
2390.877170.245660.12283
2400.8460520.3078960.153948
2410.8239550.352090.176045
2420.7880430.4239150.211957
2430.7633160.4733680.236684
2440.7312120.5375750.268788
2450.6913220.6173570.308678
2460.6363590.7272830.363641
2470.5766660.8466680.423334
2480.6597180.6805650.340282
2490.5948960.8102090.405104
2500.566060.867880.43394
2510.5365080.9269850.463492
2520.473790.947580.52621
2530.4426940.8853880.557306
2540.5080990.9838020.491901
2550.4628860.9257710.537114
2560.4182880.8365750.581712
2570.3583190.7166380.641681
2580.52460.95080.4754
2590.5636550.872690.436345
2600.8787230.2425540.121277
2610.8074430.3851130.192557
2620.8982960.2034080.101704
2630.990080.01984020.00992008
2640.9690940.06181210.0309061
2650.9283760.1432480.0716241
2660.8829180.2341640.117082

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.882068 & 0.235864 & 0.117932 \tabularnewline
14 & 0.793389 & 0.413222 & 0.206611 \tabularnewline
15 & 0.686717 & 0.626566 & 0.313283 \tabularnewline
16 & 0.568564 & 0.862873 & 0.431436 \tabularnewline
17 & 0.457525 & 0.91505 & 0.542475 \tabularnewline
18 & 0.351643 & 0.703286 & 0.648357 \tabularnewline
19 & 0.60154 & 0.796921 & 0.39846 \tabularnewline
20 & 0.531135 & 0.93773 & 0.468865 \tabularnewline
21 & 0.453348 & 0.906696 & 0.546652 \tabularnewline
22 & 0.684119 & 0.631763 & 0.315881 \tabularnewline
23 & 0.709535 & 0.580931 & 0.290465 \tabularnewline
24 & 0.679733 & 0.640534 & 0.320267 \tabularnewline
25 & 0.608427 & 0.783147 & 0.391573 \tabularnewline
26 & 0.560649 & 0.878703 & 0.439351 \tabularnewline
27 & 0.494083 & 0.988166 & 0.505917 \tabularnewline
28 & 0.474481 & 0.948963 & 0.525519 \tabularnewline
29 & 0.422266 & 0.844531 & 0.577734 \tabularnewline
30 & 0.358558 & 0.717115 & 0.641442 \tabularnewline
31 & 0.415429 & 0.830857 & 0.584571 \tabularnewline
32 & 0.367254 & 0.734508 & 0.632746 \tabularnewline
33 & 0.340141 & 0.680283 & 0.659859 \tabularnewline
34 & 0.300106 & 0.600211 & 0.699894 \tabularnewline
35 & 0.256565 & 0.51313 & 0.743435 \tabularnewline
36 & 0.230004 & 0.460008 & 0.769996 \tabularnewline
37 & 0.191633 & 0.383265 & 0.808367 \tabularnewline
38 & 0.220146 & 0.440293 & 0.779854 \tabularnewline
39 & 0.195455 & 0.39091 & 0.804545 \tabularnewline
40 & 0.185809 & 0.371618 & 0.814191 \tabularnewline
41 & 0.258611 & 0.517221 & 0.741389 \tabularnewline
42 & 0.225445 & 0.45089 & 0.774555 \tabularnewline
43 & 0.192306 & 0.384612 & 0.807694 \tabularnewline
44 & 0.176823 & 0.353647 & 0.823177 \tabularnewline
45 & 0.159421 & 0.318842 & 0.840579 \tabularnewline
46 & 0.134753 & 0.269506 & 0.865247 \tabularnewline
47 & 0.151105 & 0.30221 & 0.848895 \tabularnewline
48 & 0.190035 & 0.380069 & 0.809965 \tabularnewline
49 & 0.211266 & 0.422531 & 0.788734 \tabularnewline
50 & 0.199921 & 0.399842 & 0.800079 \tabularnewline
51 & 0.170335 & 0.34067 & 0.829665 \tabularnewline
52 & 0.197833 & 0.395667 & 0.802167 \tabularnewline
53 & 0.174658 & 0.349315 & 0.825342 \tabularnewline
54 & 0.147332 & 0.294665 & 0.852668 \tabularnewline
55 & 0.232808 & 0.465616 & 0.767192 \tabularnewline
56 & 0.198299 & 0.396598 & 0.801701 \tabularnewline
57 & 0.506301 & 0.987398 & 0.493699 \tabularnewline
58 & 0.631145 & 0.73771 & 0.368855 \tabularnewline
59 & 0.590918 & 0.818164 & 0.409082 \tabularnewline
60 & 0.569502 & 0.860997 & 0.430498 \tabularnewline
61 & 0.615136 & 0.769729 & 0.384864 \tabularnewline
62 & 0.607301 & 0.785398 & 0.392699 \tabularnewline
63 & 0.617812 & 0.764375 & 0.382188 \tabularnewline
64 & 0.65383 & 0.692341 & 0.34617 \tabularnewline
65 & 0.657962 & 0.684076 & 0.342038 \tabularnewline
66 & 0.626923 & 0.746153 & 0.373077 \tabularnewline
67 & 0.605714 & 0.788572 & 0.394286 \tabularnewline
68 & 0.586292 & 0.827415 & 0.413708 \tabularnewline
69 & 0.635608 & 0.728785 & 0.364392 \tabularnewline
70 & 0.601987 & 0.796026 & 0.398013 \tabularnewline
71 & 0.567646 & 0.864708 & 0.432354 \tabularnewline
72 & 0.537657 & 0.924686 & 0.462343 \tabularnewline
73 & 0.515316 & 0.969369 & 0.484684 \tabularnewline
74 & 0.569928 & 0.860145 & 0.430072 \tabularnewline
75 & 0.553309 & 0.893382 & 0.446691 \tabularnewline
76 & 0.52068 & 0.958641 & 0.47932 \tabularnewline
77 & 0.498486 & 0.996972 & 0.501514 \tabularnewline
78 & 0.478577 & 0.957154 & 0.521423 \tabularnewline
79 & 0.445096 & 0.890192 & 0.554904 \tabularnewline
80 & 0.461912 & 0.923823 & 0.538088 \tabularnewline
81 & 0.42697 & 0.85394 & 0.57303 \tabularnewline
82 & 0.441949 & 0.883898 & 0.558051 \tabularnewline
83 & 0.408654 & 0.817308 & 0.591346 \tabularnewline
84 & 0.603019 & 0.793963 & 0.396981 \tabularnewline
85 & 0.580354 & 0.839292 & 0.419646 \tabularnewline
86 & 0.542723 & 0.914554 & 0.457277 \tabularnewline
87 & 0.527723 & 0.944555 & 0.472277 \tabularnewline
88 & 0.526591 & 0.946818 & 0.473409 \tabularnewline
89 & 0.515362 & 0.969275 & 0.484638 \tabularnewline
90 & 0.495866 & 0.991731 & 0.504134 \tabularnewline
91 & 0.54073 & 0.918541 & 0.45927 \tabularnewline
92 & 0.683333 & 0.633333 & 0.316667 \tabularnewline
93 & 0.682925 & 0.63415 & 0.317075 \tabularnewline
94 & 0.670249 & 0.659502 & 0.329751 \tabularnewline
95 & 0.663984 & 0.672031 & 0.336016 \tabularnewline
96 & 0.646722 & 0.706557 & 0.353278 \tabularnewline
97 & 0.707004 & 0.585993 & 0.292996 \tabularnewline
98 & 0.695543 & 0.608914 & 0.304457 \tabularnewline
99 & 0.747511 & 0.504977 & 0.252489 \tabularnewline
100 & 0.751179 & 0.497643 & 0.248821 \tabularnewline
101 & 0.73436 & 0.53128 & 0.26564 \tabularnewline
102 & 0.703408 & 0.593184 & 0.296592 \tabularnewline
103 & 0.682315 & 0.63537 & 0.317685 \tabularnewline
104 & 0.665389 & 0.669223 & 0.334611 \tabularnewline
105 & 0.73767 & 0.52466 & 0.26233 \tabularnewline
106 & 0.725096 & 0.549807 & 0.274904 \tabularnewline
107 & 0.778162 & 0.443677 & 0.221838 \tabularnewline
108 & 0.867304 & 0.265392 & 0.132696 \tabularnewline
109 & 0.866535 & 0.266931 & 0.133465 \tabularnewline
110 & 0.854865 & 0.290271 & 0.145135 \tabularnewline
111 & 0.839397 & 0.321205 & 0.160603 \tabularnewline
112 & 0.823518 & 0.352965 & 0.176482 \tabularnewline
113 & 0.863496 & 0.273007 & 0.136504 \tabularnewline
114 & 0.88678 & 0.22644 & 0.11322 \tabularnewline
115 & 0.937346 & 0.125308 & 0.0626541 \tabularnewline
116 & 0.946426 & 0.107147 & 0.0535737 \tabularnewline
117 & 0.938226 & 0.123549 & 0.0617744 \tabularnewline
118 & 0.927543 & 0.144913 & 0.0724566 \tabularnewline
119 & 0.919412 & 0.161175 & 0.0805877 \tabularnewline
120 & 0.918982 & 0.162036 & 0.0810178 \tabularnewline
121 & 0.929166 & 0.141668 & 0.0708338 \tabularnewline
122 & 0.924623 & 0.150755 & 0.0753773 \tabularnewline
123 & 0.924566 & 0.150869 & 0.0754344 \tabularnewline
124 & 0.950791 & 0.0984182 & 0.0492091 \tabularnewline
125 & 0.955111 & 0.0897771 & 0.0448885 \tabularnewline
126 & 0.947087 & 0.105827 & 0.0529134 \tabularnewline
127 & 0.940899 & 0.118202 & 0.0591012 \tabularnewline
128 & 0.930404 & 0.139192 & 0.0695958 \tabularnewline
129 & 0.930369 & 0.139263 & 0.0696314 \tabularnewline
130 & 0.920462 & 0.159075 & 0.0795375 \tabularnewline
131 & 0.909167 & 0.181666 & 0.0908332 \tabularnewline
132 & 0.903295 & 0.19341 & 0.0967052 \tabularnewline
133 & 0.891406 & 0.217188 & 0.108594 \tabularnewline
134 & 0.877119 & 0.245761 & 0.122881 \tabularnewline
135 & 0.862681 & 0.274639 & 0.137319 \tabularnewline
136 & 0.842774 & 0.314452 & 0.157226 \tabularnewline
137 & 0.864112 & 0.271777 & 0.135888 \tabularnewline
138 & 0.864025 & 0.27195 & 0.135975 \tabularnewline
139 & 0.852702 & 0.294595 & 0.147298 \tabularnewline
140 & 0.834469 & 0.331063 & 0.165531 \tabularnewline
141 & 0.823126 & 0.353748 & 0.176874 \tabularnewline
142 & 0.834427 & 0.331147 & 0.165573 \tabularnewline
143 & 0.813427 & 0.373145 & 0.186573 \tabularnewline
144 & 0.834058 & 0.331883 & 0.165942 \tabularnewline
145 & 0.811085 & 0.377831 & 0.188915 \tabularnewline
146 & 0.789353 & 0.421294 & 0.210647 \tabularnewline
147 & 0.764922 & 0.470155 & 0.235078 \tabularnewline
148 & 0.737035 & 0.52593 & 0.262965 \tabularnewline
149 & 0.707842 & 0.584317 & 0.292158 \tabularnewline
150 & 0.699161 & 0.601677 & 0.300839 \tabularnewline
151 & 0.873162 & 0.253677 & 0.126838 \tabularnewline
152 & 0.855478 & 0.289044 & 0.144522 \tabularnewline
153 & 0.858683 & 0.282635 & 0.141317 \tabularnewline
154 & 0.83787 & 0.32426 & 0.16213 \tabularnewline
155 & 0.830192 & 0.339615 & 0.169808 \tabularnewline
156 & 0.811018 & 0.377964 & 0.188982 \tabularnewline
157 & 0.792639 & 0.414722 & 0.207361 \tabularnewline
158 & 0.773328 & 0.453344 & 0.226672 \tabularnewline
159 & 0.783196 & 0.433608 & 0.216804 \tabularnewline
160 & 0.781391 & 0.437217 & 0.218609 \tabularnewline
161 & 0.761336 & 0.477328 & 0.238664 \tabularnewline
162 & 0.755334 & 0.489331 & 0.244666 \tabularnewline
163 & 0.73023 & 0.539541 & 0.26977 \tabularnewline
164 & 0.957445 & 0.085109 & 0.0425545 \tabularnewline
165 & 0.950449 & 0.0991017 & 0.0495508 \tabularnewline
166 & 0.94599 & 0.108019 & 0.0540095 \tabularnewline
167 & 0.938666 & 0.122668 & 0.0613338 \tabularnewline
168 & 0.938878 & 0.122244 & 0.061122 \tabularnewline
169 & 0.927137 & 0.145727 & 0.0728633 \tabularnewline
170 & 0.947592 & 0.104817 & 0.0524085 \tabularnewline
171 & 0.940513 & 0.118975 & 0.0594874 \tabularnewline
172 & 0.937368 & 0.125264 & 0.0626321 \tabularnewline
173 & 0.939706 & 0.120587 & 0.0602936 \tabularnewline
174 & 0.928278 & 0.143443 & 0.0717217 \tabularnewline
175 & 0.91516 & 0.169679 & 0.0848395 \tabularnewline
176 & 0.918142 & 0.163715 & 0.0818577 \tabularnewline
177 & 0.907846 & 0.184309 & 0.0921544 \tabularnewline
178 & 0.918041 & 0.163919 & 0.0819593 \tabularnewline
179 & 0.912487 & 0.175026 & 0.087513 \tabularnewline
180 & 0.923208 & 0.153585 & 0.0767924 \tabularnewline
181 & 0.935581 & 0.128838 & 0.0644191 \tabularnewline
182 & 0.93676 & 0.12648 & 0.0632402 \tabularnewline
183 & 0.944085 & 0.111829 & 0.0559145 \tabularnewline
184 & 0.93353 & 0.132939 & 0.0664696 \tabularnewline
185 & 0.949163 & 0.101674 & 0.050837 \tabularnewline
186 & 0.938711 & 0.122577 & 0.0612885 \tabularnewline
187 & 0.941153 & 0.117694 & 0.0588469 \tabularnewline
188 & 0.94764 & 0.104721 & 0.0523605 \tabularnewline
189 & 0.952057 & 0.0958866 & 0.0479433 \tabularnewline
190 & 0.943518 & 0.112963 & 0.0564817 \tabularnewline
191 & 0.940573 & 0.118854 & 0.059427 \tabularnewline
192 & 0.928789 & 0.142423 & 0.0712114 \tabularnewline
193 & 0.935473 & 0.129055 & 0.0645273 \tabularnewline
194 & 0.940365 & 0.11927 & 0.0596349 \tabularnewline
195 & 0.927824 & 0.144353 & 0.0721763 \tabularnewline
196 & 0.919521 & 0.160958 & 0.0804789 \tabularnewline
197 & 0.920033 & 0.159933 & 0.0799666 \tabularnewline
198 & 0.904403 & 0.191193 & 0.0955967 \tabularnewline
199 & 0.894928 & 0.210144 & 0.105072 \tabularnewline
200 & 0.876138 & 0.247725 & 0.123862 \tabularnewline
201 & 0.878015 & 0.24397 & 0.121985 \tabularnewline
202 & 0.86088 & 0.278241 & 0.13912 \tabularnewline
203 & 0.859588 & 0.280824 & 0.140412 \tabularnewline
204 & 0.836049 & 0.327903 & 0.163951 \tabularnewline
205 & 0.815555 & 0.368891 & 0.184445 \tabularnewline
206 & 0.829354 & 0.341292 & 0.170646 \tabularnewline
207 & 0.82921 & 0.341581 & 0.17079 \tabularnewline
208 & 0.814043 & 0.371914 & 0.185957 \tabularnewline
209 & 0.803198 & 0.393604 & 0.196802 \tabularnewline
210 & 0.80222 & 0.395559 & 0.19778 \tabularnewline
211 & 0.787684 & 0.424631 & 0.212316 \tabularnewline
212 & 0.755778 & 0.488443 & 0.244222 \tabularnewline
213 & 0.76416 & 0.471679 & 0.23584 \tabularnewline
214 & 0.734886 & 0.530228 & 0.265114 \tabularnewline
215 & 0.711206 & 0.577588 & 0.288794 \tabularnewline
216 & 0.67378 & 0.652441 & 0.32622 \tabularnewline
217 & 0.674527 & 0.650946 & 0.325473 \tabularnewline
218 & 0.657432 & 0.685136 & 0.342568 \tabularnewline
219 & 0.627689 & 0.744621 & 0.372311 \tabularnewline
220 & 0.590395 & 0.819211 & 0.409605 \tabularnewline
221 & 0.600721 & 0.798558 & 0.399279 \tabularnewline
222 & 0.677361 & 0.645277 & 0.322639 \tabularnewline
223 & 0.639671 & 0.720658 & 0.360329 \tabularnewline
224 & 0.725938 & 0.548125 & 0.274062 \tabularnewline
225 & 0.720389 & 0.559222 & 0.279611 \tabularnewline
226 & 0.769784 & 0.460432 & 0.230216 \tabularnewline
227 & 0.783985 & 0.432031 & 0.216015 \tabularnewline
228 & 0.818794 & 0.362413 & 0.181206 \tabularnewline
229 & 0.88405 & 0.231901 & 0.11595 \tabularnewline
230 & 0.920986 & 0.158029 & 0.0790143 \tabularnewline
231 & 0.926237 & 0.147526 & 0.0737631 \tabularnewline
232 & 0.920438 & 0.159124 & 0.0795619 \tabularnewline
233 & 0.907934 & 0.184133 & 0.0920664 \tabularnewline
234 & 0.889654 & 0.220692 & 0.110346 \tabularnewline
235 & 0.869527 & 0.260946 & 0.130473 \tabularnewline
236 & 0.935171 & 0.129657 & 0.0648285 \tabularnewline
237 & 0.920093 & 0.159815 & 0.0799075 \tabularnewline
238 & 0.897204 & 0.205593 & 0.102796 \tabularnewline
239 & 0.87717 & 0.24566 & 0.12283 \tabularnewline
240 & 0.846052 & 0.307896 & 0.153948 \tabularnewline
241 & 0.823955 & 0.35209 & 0.176045 \tabularnewline
242 & 0.788043 & 0.423915 & 0.211957 \tabularnewline
243 & 0.763316 & 0.473368 & 0.236684 \tabularnewline
244 & 0.731212 & 0.537575 & 0.268788 \tabularnewline
245 & 0.691322 & 0.617357 & 0.308678 \tabularnewline
246 & 0.636359 & 0.727283 & 0.363641 \tabularnewline
247 & 0.576666 & 0.846668 & 0.423334 \tabularnewline
248 & 0.659718 & 0.680565 & 0.340282 \tabularnewline
249 & 0.594896 & 0.810209 & 0.405104 \tabularnewline
250 & 0.56606 & 0.86788 & 0.43394 \tabularnewline
251 & 0.536508 & 0.926985 & 0.463492 \tabularnewline
252 & 0.47379 & 0.94758 & 0.52621 \tabularnewline
253 & 0.442694 & 0.885388 & 0.557306 \tabularnewline
254 & 0.508099 & 0.983802 & 0.491901 \tabularnewline
255 & 0.462886 & 0.925771 & 0.537114 \tabularnewline
256 & 0.418288 & 0.836575 & 0.581712 \tabularnewline
257 & 0.358319 & 0.716638 & 0.641681 \tabularnewline
258 & 0.5246 & 0.9508 & 0.4754 \tabularnewline
259 & 0.563655 & 0.87269 & 0.436345 \tabularnewline
260 & 0.878723 & 0.242554 & 0.121277 \tabularnewline
261 & 0.807443 & 0.385113 & 0.192557 \tabularnewline
262 & 0.898296 & 0.203408 & 0.101704 \tabularnewline
263 & 0.99008 & 0.0198402 & 0.00992008 \tabularnewline
264 & 0.969094 & 0.0618121 & 0.0309061 \tabularnewline
265 & 0.928376 & 0.143248 & 0.0716241 \tabularnewline
266 & 0.882918 & 0.234164 & 0.117082 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&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]0.882068[/C][C]0.235864[/C][C]0.117932[/C][/ROW]
[ROW][C]14[/C][C]0.793389[/C][C]0.413222[/C][C]0.206611[/C][/ROW]
[ROW][C]15[/C][C]0.686717[/C][C]0.626566[/C][C]0.313283[/C][/ROW]
[ROW][C]16[/C][C]0.568564[/C][C]0.862873[/C][C]0.431436[/C][/ROW]
[ROW][C]17[/C][C]0.457525[/C][C]0.91505[/C][C]0.542475[/C][/ROW]
[ROW][C]18[/C][C]0.351643[/C][C]0.703286[/C][C]0.648357[/C][/ROW]
[ROW][C]19[/C][C]0.60154[/C][C]0.796921[/C][C]0.39846[/C][/ROW]
[ROW][C]20[/C][C]0.531135[/C][C]0.93773[/C][C]0.468865[/C][/ROW]
[ROW][C]21[/C][C]0.453348[/C][C]0.906696[/C][C]0.546652[/C][/ROW]
[ROW][C]22[/C][C]0.684119[/C][C]0.631763[/C][C]0.315881[/C][/ROW]
[ROW][C]23[/C][C]0.709535[/C][C]0.580931[/C][C]0.290465[/C][/ROW]
[ROW][C]24[/C][C]0.679733[/C][C]0.640534[/C][C]0.320267[/C][/ROW]
[ROW][C]25[/C][C]0.608427[/C][C]0.783147[/C][C]0.391573[/C][/ROW]
[ROW][C]26[/C][C]0.560649[/C][C]0.878703[/C][C]0.439351[/C][/ROW]
[ROW][C]27[/C][C]0.494083[/C][C]0.988166[/C][C]0.505917[/C][/ROW]
[ROW][C]28[/C][C]0.474481[/C][C]0.948963[/C][C]0.525519[/C][/ROW]
[ROW][C]29[/C][C]0.422266[/C][C]0.844531[/C][C]0.577734[/C][/ROW]
[ROW][C]30[/C][C]0.358558[/C][C]0.717115[/C][C]0.641442[/C][/ROW]
[ROW][C]31[/C][C]0.415429[/C][C]0.830857[/C][C]0.584571[/C][/ROW]
[ROW][C]32[/C][C]0.367254[/C][C]0.734508[/C][C]0.632746[/C][/ROW]
[ROW][C]33[/C][C]0.340141[/C][C]0.680283[/C][C]0.659859[/C][/ROW]
[ROW][C]34[/C][C]0.300106[/C][C]0.600211[/C][C]0.699894[/C][/ROW]
[ROW][C]35[/C][C]0.256565[/C][C]0.51313[/C][C]0.743435[/C][/ROW]
[ROW][C]36[/C][C]0.230004[/C][C]0.460008[/C][C]0.769996[/C][/ROW]
[ROW][C]37[/C][C]0.191633[/C][C]0.383265[/C][C]0.808367[/C][/ROW]
[ROW][C]38[/C][C]0.220146[/C][C]0.440293[/C][C]0.779854[/C][/ROW]
[ROW][C]39[/C][C]0.195455[/C][C]0.39091[/C][C]0.804545[/C][/ROW]
[ROW][C]40[/C][C]0.185809[/C][C]0.371618[/C][C]0.814191[/C][/ROW]
[ROW][C]41[/C][C]0.258611[/C][C]0.517221[/C][C]0.741389[/C][/ROW]
[ROW][C]42[/C][C]0.225445[/C][C]0.45089[/C][C]0.774555[/C][/ROW]
[ROW][C]43[/C][C]0.192306[/C][C]0.384612[/C][C]0.807694[/C][/ROW]
[ROW][C]44[/C][C]0.176823[/C][C]0.353647[/C][C]0.823177[/C][/ROW]
[ROW][C]45[/C][C]0.159421[/C][C]0.318842[/C][C]0.840579[/C][/ROW]
[ROW][C]46[/C][C]0.134753[/C][C]0.269506[/C][C]0.865247[/C][/ROW]
[ROW][C]47[/C][C]0.151105[/C][C]0.30221[/C][C]0.848895[/C][/ROW]
[ROW][C]48[/C][C]0.190035[/C][C]0.380069[/C][C]0.809965[/C][/ROW]
[ROW][C]49[/C][C]0.211266[/C][C]0.422531[/C][C]0.788734[/C][/ROW]
[ROW][C]50[/C][C]0.199921[/C][C]0.399842[/C][C]0.800079[/C][/ROW]
[ROW][C]51[/C][C]0.170335[/C][C]0.34067[/C][C]0.829665[/C][/ROW]
[ROW][C]52[/C][C]0.197833[/C][C]0.395667[/C][C]0.802167[/C][/ROW]
[ROW][C]53[/C][C]0.174658[/C][C]0.349315[/C][C]0.825342[/C][/ROW]
[ROW][C]54[/C][C]0.147332[/C][C]0.294665[/C][C]0.852668[/C][/ROW]
[ROW][C]55[/C][C]0.232808[/C][C]0.465616[/C][C]0.767192[/C][/ROW]
[ROW][C]56[/C][C]0.198299[/C][C]0.396598[/C][C]0.801701[/C][/ROW]
[ROW][C]57[/C][C]0.506301[/C][C]0.987398[/C][C]0.493699[/C][/ROW]
[ROW][C]58[/C][C]0.631145[/C][C]0.73771[/C][C]0.368855[/C][/ROW]
[ROW][C]59[/C][C]0.590918[/C][C]0.818164[/C][C]0.409082[/C][/ROW]
[ROW][C]60[/C][C]0.569502[/C][C]0.860997[/C][C]0.430498[/C][/ROW]
[ROW][C]61[/C][C]0.615136[/C][C]0.769729[/C][C]0.384864[/C][/ROW]
[ROW][C]62[/C][C]0.607301[/C][C]0.785398[/C][C]0.392699[/C][/ROW]
[ROW][C]63[/C][C]0.617812[/C][C]0.764375[/C][C]0.382188[/C][/ROW]
[ROW][C]64[/C][C]0.65383[/C][C]0.692341[/C][C]0.34617[/C][/ROW]
[ROW][C]65[/C][C]0.657962[/C][C]0.684076[/C][C]0.342038[/C][/ROW]
[ROW][C]66[/C][C]0.626923[/C][C]0.746153[/C][C]0.373077[/C][/ROW]
[ROW][C]67[/C][C]0.605714[/C][C]0.788572[/C][C]0.394286[/C][/ROW]
[ROW][C]68[/C][C]0.586292[/C][C]0.827415[/C][C]0.413708[/C][/ROW]
[ROW][C]69[/C][C]0.635608[/C][C]0.728785[/C][C]0.364392[/C][/ROW]
[ROW][C]70[/C][C]0.601987[/C][C]0.796026[/C][C]0.398013[/C][/ROW]
[ROW][C]71[/C][C]0.567646[/C][C]0.864708[/C][C]0.432354[/C][/ROW]
[ROW][C]72[/C][C]0.537657[/C][C]0.924686[/C][C]0.462343[/C][/ROW]
[ROW][C]73[/C][C]0.515316[/C][C]0.969369[/C][C]0.484684[/C][/ROW]
[ROW][C]74[/C][C]0.569928[/C][C]0.860145[/C][C]0.430072[/C][/ROW]
[ROW][C]75[/C][C]0.553309[/C][C]0.893382[/C][C]0.446691[/C][/ROW]
[ROW][C]76[/C][C]0.52068[/C][C]0.958641[/C][C]0.47932[/C][/ROW]
[ROW][C]77[/C][C]0.498486[/C][C]0.996972[/C][C]0.501514[/C][/ROW]
[ROW][C]78[/C][C]0.478577[/C][C]0.957154[/C][C]0.521423[/C][/ROW]
[ROW][C]79[/C][C]0.445096[/C][C]0.890192[/C][C]0.554904[/C][/ROW]
[ROW][C]80[/C][C]0.461912[/C][C]0.923823[/C][C]0.538088[/C][/ROW]
[ROW][C]81[/C][C]0.42697[/C][C]0.85394[/C][C]0.57303[/C][/ROW]
[ROW][C]82[/C][C]0.441949[/C][C]0.883898[/C][C]0.558051[/C][/ROW]
[ROW][C]83[/C][C]0.408654[/C][C]0.817308[/C][C]0.591346[/C][/ROW]
[ROW][C]84[/C][C]0.603019[/C][C]0.793963[/C][C]0.396981[/C][/ROW]
[ROW][C]85[/C][C]0.580354[/C][C]0.839292[/C][C]0.419646[/C][/ROW]
[ROW][C]86[/C][C]0.542723[/C][C]0.914554[/C][C]0.457277[/C][/ROW]
[ROW][C]87[/C][C]0.527723[/C][C]0.944555[/C][C]0.472277[/C][/ROW]
[ROW][C]88[/C][C]0.526591[/C][C]0.946818[/C][C]0.473409[/C][/ROW]
[ROW][C]89[/C][C]0.515362[/C][C]0.969275[/C][C]0.484638[/C][/ROW]
[ROW][C]90[/C][C]0.495866[/C][C]0.991731[/C][C]0.504134[/C][/ROW]
[ROW][C]91[/C][C]0.54073[/C][C]0.918541[/C][C]0.45927[/C][/ROW]
[ROW][C]92[/C][C]0.683333[/C][C]0.633333[/C][C]0.316667[/C][/ROW]
[ROW][C]93[/C][C]0.682925[/C][C]0.63415[/C][C]0.317075[/C][/ROW]
[ROW][C]94[/C][C]0.670249[/C][C]0.659502[/C][C]0.329751[/C][/ROW]
[ROW][C]95[/C][C]0.663984[/C][C]0.672031[/C][C]0.336016[/C][/ROW]
[ROW][C]96[/C][C]0.646722[/C][C]0.706557[/C][C]0.353278[/C][/ROW]
[ROW][C]97[/C][C]0.707004[/C][C]0.585993[/C][C]0.292996[/C][/ROW]
[ROW][C]98[/C][C]0.695543[/C][C]0.608914[/C][C]0.304457[/C][/ROW]
[ROW][C]99[/C][C]0.747511[/C][C]0.504977[/C][C]0.252489[/C][/ROW]
[ROW][C]100[/C][C]0.751179[/C][C]0.497643[/C][C]0.248821[/C][/ROW]
[ROW][C]101[/C][C]0.73436[/C][C]0.53128[/C][C]0.26564[/C][/ROW]
[ROW][C]102[/C][C]0.703408[/C][C]0.593184[/C][C]0.296592[/C][/ROW]
[ROW][C]103[/C][C]0.682315[/C][C]0.63537[/C][C]0.317685[/C][/ROW]
[ROW][C]104[/C][C]0.665389[/C][C]0.669223[/C][C]0.334611[/C][/ROW]
[ROW][C]105[/C][C]0.73767[/C][C]0.52466[/C][C]0.26233[/C][/ROW]
[ROW][C]106[/C][C]0.725096[/C][C]0.549807[/C][C]0.274904[/C][/ROW]
[ROW][C]107[/C][C]0.778162[/C][C]0.443677[/C][C]0.221838[/C][/ROW]
[ROW][C]108[/C][C]0.867304[/C][C]0.265392[/C][C]0.132696[/C][/ROW]
[ROW][C]109[/C][C]0.866535[/C][C]0.266931[/C][C]0.133465[/C][/ROW]
[ROW][C]110[/C][C]0.854865[/C][C]0.290271[/C][C]0.145135[/C][/ROW]
[ROW][C]111[/C][C]0.839397[/C][C]0.321205[/C][C]0.160603[/C][/ROW]
[ROW][C]112[/C][C]0.823518[/C][C]0.352965[/C][C]0.176482[/C][/ROW]
[ROW][C]113[/C][C]0.863496[/C][C]0.273007[/C][C]0.136504[/C][/ROW]
[ROW][C]114[/C][C]0.88678[/C][C]0.22644[/C][C]0.11322[/C][/ROW]
[ROW][C]115[/C][C]0.937346[/C][C]0.125308[/C][C]0.0626541[/C][/ROW]
[ROW][C]116[/C][C]0.946426[/C][C]0.107147[/C][C]0.0535737[/C][/ROW]
[ROW][C]117[/C][C]0.938226[/C][C]0.123549[/C][C]0.0617744[/C][/ROW]
[ROW][C]118[/C][C]0.927543[/C][C]0.144913[/C][C]0.0724566[/C][/ROW]
[ROW][C]119[/C][C]0.919412[/C][C]0.161175[/C][C]0.0805877[/C][/ROW]
[ROW][C]120[/C][C]0.918982[/C][C]0.162036[/C][C]0.0810178[/C][/ROW]
[ROW][C]121[/C][C]0.929166[/C][C]0.141668[/C][C]0.0708338[/C][/ROW]
[ROW][C]122[/C][C]0.924623[/C][C]0.150755[/C][C]0.0753773[/C][/ROW]
[ROW][C]123[/C][C]0.924566[/C][C]0.150869[/C][C]0.0754344[/C][/ROW]
[ROW][C]124[/C][C]0.950791[/C][C]0.0984182[/C][C]0.0492091[/C][/ROW]
[ROW][C]125[/C][C]0.955111[/C][C]0.0897771[/C][C]0.0448885[/C][/ROW]
[ROW][C]126[/C][C]0.947087[/C][C]0.105827[/C][C]0.0529134[/C][/ROW]
[ROW][C]127[/C][C]0.940899[/C][C]0.118202[/C][C]0.0591012[/C][/ROW]
[ROW][C]128[/C][C]0.930404[/C][C]0.139192[/C][C]0.0695958[/C][/ROW]
[ROW][C]129[/C][C]0.930369[/C][C]0.139263[/C][C]0.0696314[/C][/ROW]
[ROW][C]130[/C][C]0.920462[/C][C]0.159075[/C][C]0.0795375[/C][/ROW]
[ROW][C]131[/C][C]0.909167[/C][C]0.181666[/C][C]0.0908332[/C][/ROW]
[ROW][C]132[/C][C]0.903295[/C][C]0.19341[/C][C]0.0967052[/C][/ROW]
[ROW][C]133[/C][C]0.891406[/C][C]0.217188[/C][C]0.108594[/C][/ROW]
[ROW][C]134[/C][C]0.877119[/C][C]0.245761[/C][C]0.122881[/C][/ROW]
[ROW][C]135[/C][C]0.862681[/C][C]0.274639[/C][C]0.137319[/C][/ROW]
[ROW][C]136[/C][C]0.842774[/C][C]0.314452[/C][C]0.157226[/C][/ROW]
[ROW][C]137[/C][C]0.864112[/C][C]0.271777[/C][C]0.135888[/C][/ROW]
[ROW][C]138[/C][C]0.864025[/C][C]0.27195[/C][C]0.135975[/C][/ROW]
[ROW][C]139[/C][C]0.852702[/C][C]0.294595[/C][C]0.147298[/C][/ROW]
[ROW][C]140[/C][C]0.834469[/C][C]0.331063[/C][C]0.165531[/C][/ROW]
[ROW][C]141[/C][C]0.823126[/C][C]0.353748[/C][C]0.176874[/C][/ROW]
[ROW][C]142[/C][C]0.834427[/C][C]0.331147[/C][C]0.165573[/C][/ROW]
[ROW][C]143[/C][C]0.813427[/C][C]0.373145[/C][C]0.186573[/C][/ROW]
[ROW][C]144[/C][C]0.834058[/C][C]0.331883[/C][C]0.165942[/C][/ROW]
[ROW][C]145[/C][C]0.811085[/C][C]0.377831[/C][C]0.188915[/C][/ROW]
[ROW][C]146[/C][C]0.789353[/C][C]0.421294[/C][C]0.210647[/C][/ROW]
[ROW][C]147[/C][C]0.764922[/C][C]0.470155[/C][C]0.235078[/C][/ROW]
[ROW][C]148[/C][C]0.737035[/C][C]0.52593[/C][C]0.262965[/C][/ROW]
[ROW][C]149[/C][C]0.707842[/C][C]0.584317[/C][C]0.292158[/C][/ROW]
[ROW][C]150[/C][C]0.699161[/C][C]0.601677[/C][C]0.300839[/C][/ROW]
[ROW][C]151[/C][C]0.873162[/C][C]0.253677[/C][C]0.126838[/C][/ROW]
[ROW][C]152[/C][C]0.855478[/C][C]0.289044[/C][C]0.144522[/C][/ROW]
[ROW][C]153[/C][C]0.858683[/C][C]0.282635[/C][C]0.141317[/C][/ROW]
[ROW][C]154[/C][C]0.83787[/C][C]0.32426[/C][C]0.16213[/C][/ROW]
[ROW][C]155[/C][C]0.830192[/C][C]0.339615[/C][C]0.169808[/C][/ROW]
[ROW][C]156[/C][C]0.811018[/C][C]0.377964[/C][C]0.188982[/C][/ROW]
[ROW][C]157[/C][C]0.792639[/C][C]0.414722[/C][C]0.207361[/C][/ROW]
[ROW][C]158[/C][C]0.773328[/C][C]0.453344[/C][C]0.226672[/C][/ROW]
[ROW][C]159[/C][C]0.783196[/C][C]0.433608[/C][C]0.216804[/C][/ROW]
[ROW][C]160[/C][C]0.781391[/C][C]0.437217[/C][C]0.218609[/C][/ROW]
[ROW][C]161[/C][C]0.761336[/C][C]0.477328[/C][C]0.238664[/C][/ROW]
[ROW][C]162[/C][C]0.755334[/C][C]0.489331[/C][C]0.244666[/C][/ROW]
[ROW][C]163[/C][C]0.73023[/C][C]0.539541[/C][C]0.26977[/C][/ROW]
[ROW][C]164[/C][C]0.957445[/C][C]0.085109[/C][C]0.0425545[/C][/ROW]
[ROW][C]165[/C][C]0.950449[/C][C]0.0991017[/C][C]0.0495508[/C][/ROW]
[ROW][C]166[/C][C]0.94599[/C][C]0.108019[/C][C]0.0540095[/C][/ROW]
[ROW][C]167[/C][C]0.938666[/C][C]0.122668[/C][C]0.0613338[/C][/ROW]
[ROW][C]168[/C][C]0.938878[/C][C]0.122244[/C][C]0.061122[/C][/ROW]
[ROW][C]169[/C][C]0.927137[/C][C]0.145727[/C][C]0.0728633[/C][/ROW]
[ROW][C]170[/C][C]0.947592[/C][C]0.104817[/C][C]0.0524085[/C][/ROW]
[ROW][C]171[/C][C]0.940513[/C][C]0.118975[/C][C]0.0594874[/C][/ROW]
[ROW][C]172[/C][C]0.937368[/C][C]0.125264[/C][C]0.0626321[/C][/ROW]
[ROW][C]173[/C][C]0.939706[/C][C]0.120587[/C][C]0.0602936[/C][/ROW]
[ROW][C]174[/C][C]0.928278[/C][C]0.143443[/C][C]0.0717217[/C][/ROW]
[ROW][C]175[/C][C]0.91516[/C][C]0.169679[/C][C]0.0848395[/C][/ROW]
[ROW][C]176[/C][C]0.918142[/C][C]0.163715[/C][C]0.0818577[/C][/ROW]
[ROW][C]177[/C][C]0.907846[/C][C]0.184309[/C][C]0.0921544[/C][/ROW]
[ROW][C]178[/C][C]0.918041[/C][C]0.163919[/C][C]0.0819593[/C][/ROW]
[ROW][C]179[/C][C]0.912487[/C][C]0.175026[/C][C]0.087513[/C][/ROW]
[ROW][C]180[/C][C]0.923208[/C][C]0.153585[/C][C]0.0767924[/C][/ROW]
[ROW][C]181[/C][C]0.935581[/C][C]0.128838[/C][C]0.0644191[/C][/ROW]
[ROW][C]182[/C][C]0.93676[/C][C]0.12648[/C][C]0.0632402[/C][/ROW]
[ROW][C]183[/C][C]0.944085[/C][C]0.111829[/C][C]0.0559145[/C][/ROW]
[ROW][C]184[/C][C]0.93353[/C][C]0.132939[/C][C]0.0664696[/C][/ROW]
[ROW][C]185[/C][C]0.949163[/C][C]0.101674[/C][C]0.050837[/C][/ROW]
[ROW][C]186[/C][C]0.938711[/C][C]0.122577[/C][C]0.0612885[/C][/ROW]
[ROW][C]187[/C][C]0.941153[/C][C]0.117694[/C][C]0.0588469[/C][/ROW]
[ROW][C]188[/C][C]0.94764[/C][C]0.104721[/C][C]0.0523605[/C][/ROW]
[ROW][C]189[/C][C]0.952057[/C][C]0.0958866[/C][C]0.0479433[/C][/ROW]
[ROW][C]190[/C][C]0.943518[/C][C]0.112963[/C][C]0.0564817[/C][/ROW]
[ROW][C]191[/C][C]0.940573[/C][C]0.118854[/C][C]0.059427[/C][/ROW]
[ROW][C]192[/C][C]0.928789[/C][C]0.142423[/C][C]0.0712114[/C][/ROW]
[ROW][C]193[/C][C]0.935473[/C][C]0.129055[/C][C]0.0645273[/C][/ROW]
[ROW][C]194[/C][C]0.940365[/C][C]0.11927[/C][C]0.0596349[/C][/ROW]
[ROW][C]195[/C][C]0.927824[/C][C]0.144353[/C][C]0.0721763[/C][/ROW]
[ROW][C]196[/C][C]0.919521[/C][C]0.160958[/C][C]0.0804789[/C][/ROW]
[ROW][C]197[/C][C]0.920033[/C][C]0.159933[/C][C]0.0799666[/C][/ROW]
[ROW][C]198[/C][C]0.904403[/C][C]0.191193[/C][C]0.0955967[/C][/ROW]
[ROW][C]199[/C][C]0.894928[/C][C]0.210144[/C][C]0.105072[/C][/ROW]
[ROW][C]200[/C][C]0.876138[/C][C]0.247725[/C][C]0.123862[/C][/ROW]
[ROW][C]201[/C][C]0.878015[/C][C]0.24397[/C][C]0.121985[/C][/ROW]
[ROW][C]202[/C][C]0.86088[/C][C]0.278241[/C][C]0.13912[/C][/ROW]
[ROW][C]203[/C][C]0.859588[/C][C]0.280824[/C][C]0.140412[/C][/ROW]
[ROW][C]204[/C][C]0.836049[/C][C]0.327903[/C][C]0.163951[/C][/ROW]
[ROW][C]205[/C][C]0.815555[/C][C]0.368891[/C][C]0.184445[/C][/ROW]
[ROW][C]206[/C][C]0.829354[/C][C]0.341292[/C][C]0.170646[/C][/ROW]
[ROW][C]207[/C][C]0.82921[/C][C]0.341581[/C][C]0.17079[/C][/ROW]
[ROW][C]208[/C][C]0.814043[/C][C]0.371914[/C][C]0.185957[/C][/ROW]
[ROW][C]209[/C][C]0.803198[/C][C]0.393604[/C][C]0.196802[/C][/ROW]
[ROW][C]210[/C][C]0.80222[/C][C]0.395559[/C][C]0.19778[/C][/ROW]
[ROW][C]211[/C][C]0.787684[/C][C]0.424631[/C][C]0.212316[/C][/ROW]
[ROW][C]212[/C][C]0.755778[/C][C]0.488443[/C][C]0.244222[/C][/ROW]
[ROW][C]213[/C][C]0.76416[/C][C]0.471679[/C][C]0.23584[/C][/ROW]
[ROW][C]214[/C][C]0.734886[/C][C]0.530228[/C][C]0.265114[/C][/ROW]
[ROW][C]215[/C][C]0.711206[/C][C]0.577588[/C][C]0.288794[/C][/ROW]
[ROW][C]216[/C][C]0.67378[/C][C]0.652441[/C][C]0.32622[/C][/ROW]
[ROW][C]217[/C][C]0.674527[/C][C]0.650946[/C][C]0.325473[/C][/ROW]
[ROW][C]218[/C][C]0.657432[/C][C]0.685136[/C][C]0.342568[/C][/ROW]
[ROW][C]219[/C][C]0.627689[/C][C]0.744621[/C][C]0.372311[/C][/ROW]
[ROW][C]220[/C][C]0.590395[/C][C]0.819211[/C][C]0.409605[/C][/ROW]
[ROW][C]221[/C][C]0.600721[/C][C]0.798558[/C][C]0.399279[/C][/ROW]
[ROW][C]222[/C][C]0.677361[/C][C]0.645277[/C][C]0.322639[/C][/ROW]
[ROW][C]223[/C][C]0.639671[/C][C]0.720658[/C][C]0.360329[/C][/ROW]
[ROW][C]224[/C][C]0.725938[/C][C]0.548125[/C][C]0.274062[/C][/ROW]
[ROW][C]225[/C][C]0.720389[/C][C]0.559222[/C][C]0.279611[/C][/ROW]
[ROW][C]226[/C][C]0.769784[/C][C]0.460432[/C][C]0.230216[/C][/ROW]
[ROW][C]227[/C][C]0.783985[/C][C]0.432031[/C][C]0.216015[/C][/ROW]
[ROW][C]228[/C][C]0.818794[/C][C]0.362413[/C][C]0.181206[/C][/ROW]
[ROW][C]229[/C][C]0.88405[/C][C]0.231901[/C][C]0.11595[/C][/ROW]
[ROW][C]230[/C][C]0.920986[/C][C]0.158029[/C][C]0.0790143[/C][/ROW]
[ROW][C]231[/C][C]0.926237[/C][C]0.147526[/C][C]0.0737631[/C][/ROW]
[ROW][C]232[/C][C]0.920438[/C][C]0.159124[/C][C]0.0795619[/C][/ROW]
[ROW][C]233[/C][C]0.907934[/C][C]0.184133[/C][C]0.0920664[/C][/ROW]
[ROW][C]234[/C][C]0.889654[/C][C]0.220692[/C][C]0.110346[/C][/ROW]
[ROW][C]235[/C][C]0.869527[/C][C]0.260946[/C][C]0.130473[/C][/ROW]
[ROW][C]236[/C][C]0.935171[/C][C]0.129657[/C][C]0.0648285[/C][/ROW]
[ROW][C]237[/C][C]0.920093[/C][C]0.159815[/C][C]0.0799075[/C][/ROW]
[ROW][C]238[/C][C]0.897204[/C][C]0.205593[/C][C]0.102796[/C][/ROW]
[ROW][C]239[/C][C]0.87717[/C][C]0.24566[/C][C]0.12283[/C][/ROW]
[ROW][C]240[/C][C]0.846052[/C][C]0.307896[/C][C]0.153948[/C][/ROW]
[ROW][C]241[/C][C]0.823955[/C][C]0.35209[/C][C]0.176045[/C][/ROW]
[ROW][C]242[/C][C]0.788043[/C][C]0.423915[/C][C]0.211957[/C][/ROW]
[ROW][C]243[/C][C]0.763316[/C][C]0.473368[/C][C]0.236684[/C][/ROW]
[ROW][C]244[/C][C]0.731212[/C][C]0.537575[/C][C]0.268788[/C][/ROW]
[ROW][C]245[/C][C]0.691322[/C][C]0.617357[/C][C]0.308678[/C][/ROW]
[ROW][C]246[/C][C]0.636359[/C][C]0.727283[/C][C]0.363641[/C][/ROW]
[ROW][C]247[/C][C]0.576666[/C][C]0.846668[/C][C]0.423334[/C][/ROW]
[ROW][C]248[/C][C]0.659718[/C][C]0.680565[/C][C]0.340282[/C][/ROW]
[ROW][C]249[/C][C]0.594896[/C][C]0.810209[/C][C]0.405104[/C][/ROW]
[ROW][C]250[/C][C]0.56606[/C][C]0.86788[/C][C]0.43394[/C][/ROW]
[ROW][C]251[/C][C]0.536508[/C][C]0.926985[/C][C]0.463492[/C][/ROW]
[ROW][C]252[/C][C]0.47379[/C][C]0.94758[/C][C]0.52621[/C][/ROW]
[ROW][C]253[/C][C]0.442694[/C][C]0.885388[/C][C]0.557306[/C][/ROW]
[ROW][C]254[/C][C]0.508099[/C][C]0.983802[/C][C]0.491901[/C][/ROW]
[ROW][C]255[/C][C]0.462886[/C][C]0.925771[/C][C]0.537114[/C][/ROW]
[ROW][C]256[/C][C]0.418288[/C][C]0.836575[/C][C]0.581712[/C][/ROW]
[ROW][C]257[/C][C]0.358319[/C][C]0.716638[/C][C]0.641681[/C][/ROW]
[ROW][C]258[/C][C]0.5246[/C][C]0.9508[/C][C]0.4754[/C][/ROW]
[ROW][C]259[/C][C]0.563655[/C][C]0.87269[/C][C]0.436345[/C][/ROW]
[ROW][C]260[/C][C]0.878723[/C][C]0.242554[/C][C]0.121277[/C][/ROW]
[ROW][C]261[/C][C]0.807443[/C][C]0.385113[/C][C]0.192557[/C][/ROW]
[ROW][C]262[/C][C]0.898296[/C][C]0.203408[/C][C]0.101704[/C][/ROW]
[ROW][C]263[/C][C]0.99008[/C][C]0.0198402[/C][C]0.00992008[/C][/ROW]
[ROW][C]264[/C][C]0.969094[/C][C]0.0618121[/C][C]0.0309061[/C][/ROW]
[ROW][C]265[/C][C]0.928376[/C][C]0.143248[/C][C]0.0716241[/C][/ROW]
[ROW][C]266[/C][C]0.882918[/C][C]0.234164[/C][C]0.117082[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&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
130.8820680.2358640.117932
140.7933890.4132220.206611
150.6867170.6265660.313283
160.5685640.8628730.431436
170.4575250.915050.542475
180.3516430.7032860.648357
190.601540.7969210.39846
200.5311350.937730.468865
210.4533480.9066960.546652
220.6841190.6317630.315881
230.7095350.5809310.290465
240.6797330.6405340.320267
250.6084270.7831470.391573
260.5606490.8787030.439351
270.4940830.9881660.505917
280.4744810.9489630.525519
290.4222660.8445310.577734
300.3585580.7171150.641442
310.4154290.8308570.584571
320.3672540.7345080.632746
330.3401410.6802830.659859
340.3001060.6002110.699894
350.2565650.513130.743435
360.2300040.4600080.769996
370.1916330.3832650.808367
380.2201460.4402930.779854
390.1954550.390910.804545
400.1858090.3716180.814191
410.2586110.5172210.741389
420.2254450.450890.774555
430.1923060.3846120.807694
440.1768230.3536470.823177
450.1594210.3188420.840579
460.1347530.2695060.865247
470.1511050.302210.848895
480.1900350.3800690.809965
490.2112660.4225310.788734
500.1999210.3998420.800079
510.1703350.340670.829665
520.1978330.3956670.802167
530.1746580.3493150.825342
540.1473320.2946650.852668
550.2328080.4656160.767192
560.1982990.3965980.801701
570.5063010.9873980.493699
580.6311450.737710.368855
590.5909180.8181640.409082
600.5695020.8609970.430498
610.6151360.7697290.384864
620.6073010.7853980.392699
630.6178120.7643750.382188
640.653830.6923410.34617
650.6579620.6840760.342038
660.6269230.7461530.373077
670.6057140.7885720.394286
680.5862920.8274150.413708
690.6356080.7287850.364392
700.6019870.7960260.398013
710.5676460.8647080.432354
720.5376570.9246860.462343
730.5153160.9693690.484684
740.5699280.8601450.430072
750.5533090.8933820.446691
760.520680.9586410.47932
770.4984860.9969720.501514
780.4785770.9571540.521423
790.4450960.8901920.554904
800.4619120.9238230.538088
810.426970.853940.57303
820.4419490.8838980.558051
830.4086540.8173080.591346
840.6030190.7939630.396981
850.5803540.8392920.419646
860.5427230.9145540.457277
870.5277230.9445550.472277
880.5265910.9468180.473409
890.5153620.9692750.484638
900.4958660.9917310.504134
910.540730.9185410.45927
920.6833330.6333330.316667
930.6829250.634150.317075
940.6702490.6595020.329751
950.6639840.6720310.336016
960.6467220.7065570.353278
970.7070040.5859930.292996
980.6955430.6089140.304457
990.7475110.5049770.252489
1000.7511790.4976430.248821
1010.734360.531280.26564
1020.7034080.5931840.296592
1030.6823150.635370.317685
1040.6653890.6692230.334611
1050.737670.524660.26233
1060.7250960.5498070.274904
1070.7781620.4436770.221838
1080.8673040.2653920.132696
1090.8665350.2669310.133465
1100.8548650.2902710.145135
1110.8393970.3212050.160603
1120.8235180.3529650.176482
1130.8634960.2730070.136504
1140.886780.226440.11322
1150.9373460.1253080.0626541
1160.9464260.1071470.0535737
1170.9382260.1235490.0617744
1180.9275430.1449130.0724566
1190.9194120.1611750.0805877
1200.9189820.1620360.0810178
1210.9291660.1416680.0708338
1220.9246230.1507550.0753773
1230.9245660.1508690.0754344
1240.9507910.09841820.0492091
1250.9551110.08977710.0448885
1260.9470870.1058270.0529134
1270.9408990.1182020.0591012
1280.9304040.1391920.0695958
1290.9303690.1392630.0696314
1300.9204620.1590750.0795375
1310.9091670.1816660.0908332
1320.9032950.193410.0967052
1330.8914060.2171880.108594
1340.8771190.2457610.122881
1350.8626810.2746390.137319
1360.8427740.3144520.157226
1370.8641120.2717770.135888
1380.8640250.271950.135975
1390.8527020.2945950.147298
1400.8344690.3310630.165531
1410.8231260.3537480.176874
1420.8344270.3311470.165573
1430.8134270.3731450.186573
1440.8340580.3318830.165942
1450.8110850.3778310.188915
1460.7893530.4212940.210647
1470.7649220.4701550.235078
1480.7370350.525930.262965
1490.7078420.5843170.292158
1500.6991610.6016770.300839
1510.8731620.2536770.126838
1520.8554780.2890440.144522
1530.8586830.2826350.141317
1540.837870.324260.16213
1550.8301920.3396150.169808
1560.8110180.3779640.188982
1570.7926390.4147220.207361
1580.7733280.4533440.226672
1590.7831960.4336080.216804
1600.7813910.4372170.218609
1610.7613360.4773280.238664
1620.7553340.4893310.244666
1630.730230.5395410.26977
1640.9574450.0851090.0425545
1650.9504490.09910170.0495508
1660.945990.1080190.0540095
1670.9386660.1226680.0613338
1680.9388780.1222440.061122
1690.9271370.1457270.0728633
1700.9475920.1048170.0524085
1710.9405130.1189750.0594874
1720.9373680.1252640.0626321
1730.9397060.1205870.0602936
1740.9282780.1434430.0717217
1750.915160.1696790.0848395
1760.9181420.1637150.0818577
1770.9078460.1843090.0921544
1780.9180410.1639190.0819593
1790.9124870.1750260.087513
1800.9232080.1535850.0767924
1810.9355810.1288380.0644191
1820.936760.126480.0632402
1830.9440850.1118290.0559145
1840.933530.1329390.0664696
1850.9491630.1016740.050837
1860.9387110.1225770.0612885
1870.9411530.1176940.0588469
1880.947640.1047210.0523605
1890.9520570.09588660.0479433
1900.9435180.1129630.0564817
1910.9405730.1188540.059427
1920.9287890.1424230.0712114
1930.9354730.1290550.0645273
1940.9403650.119270.0596349
1950.9278240.1443530.0721763
1960.9195210.1609580.0804789
1970.9200330.1599330.0799666
1980.9044030.1911930.0955967
1990.8949280.2101440.105072
2000.8761380.2477250.123862
2010.8780150.243970.121985
2020.860880.2782410.13912
2030.8595880.2808240.140412
2040.8360490.3279030.163951
2050.8155550.3688910.184445
2060.8293540.3412920.170646
2070.829210.3415810.17079
2080.8140430.3719140.185957
2090.8031980.3936040.196802
2100.802220.3955590.19778
2110.7876840.4246310.212316
2120.7557780.4884430.244222
2130.764160.4716790.23584
2140.7348860.5302280.265114
2150.7112060.5775880.288794
2160.673780.6524410.32622
2170.6745270.6509460.325473
2180.6574320.6851360.342568
2190.6276890.7446210.372311
2200.5903950.8192110.409605
2210.6007210.7985580.399279
2220.6773610.6452770.322639
2230.6396710.7206580.360329
2240.7259380.5481250.274062
2250.7203890.5592220.279611
2260.7697840.4604320.230216
2270.7839850.4320310.216015
2280.8187940.3624130.181206
2290.884050.2319010.11595
2300.9209860.1580290.0790143
2310.9262370.1475260.0737631
2320.9204380.1591240.0795619
2330.9079340.1841330.0920664
2340.8896540.2206920.110346
2350.8695270.2609460.130473
2360.9351710.1296570.0648285
2370.9200930.1598150.0799075
2380.8972040.2055930.102796
2390.877170.245660.12283
2400.8460520.3078960.153948
2410.8239550.352090.176045
2420.7880430.4239150.211957
2430.7633160.4733680.236684
2440.7312120.5375750.268788
2450.6913220.6173570.308678
2460.6363590.7272830.363641
2470.5766660.8466680.423334
2480.6597180.6805650.340282
2490.5948960.8102090.405104
2500.566060.867880.43394
2510.5365080.9269850.463492
2520.473790.947580.52621
2530.4426940.8853880.557306
2540.5080990.9838020.491901
2550.4628860.9257710.537114
2560.4182880.8365750.581712
2570.3583190.7166380.641681
2580.52460.95080.4754
2590.5636550.872690.436345
2600.8787230.2425540.121277
2610.8074430.3851130.192557
2620.8982960.2034080.101704
2630.990080.01984020.00992008
2640.9690940.06181210.0309061
2650.9283760.1432480.0716241
2660.8829180.2341640.117082






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00393701OK
10% type I error level70.0275591OK

\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 & 1 & 0.00393701 & OK \tabularnewline
10% type I error level & 7 & 0.0275591 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263930&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]1[/C][C]0.00393701[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]7[/C][C]0.0275591[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263930&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263930&T=6

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


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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00393701OK
10% type I error level70.0275591OK


Figures (Output of Computation)

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


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


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


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


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


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


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


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


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


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


Input Parameters & R Code

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