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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSat, 06 Dec 2014 11:27:18 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/06/t1417866406wdkrllo59rp5vpm.htm/, Retrieved Thu, 16 May 2024 20:34:00 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263590, Retrieved Thu, 16 May 2024 20:34:00 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact115

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2014-12-06 11:27:18] [d71ad52285d92a63edfc83f9fb1da7a1] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
'7.5' 0 26 50 0 21 21 149 18 68
'2.5' 0 51 68 0 23 26 152 7 55
6 1 57 62 0 22 22 139 31 39
'6.5' 0 37 54 0 21 22 148 39 32
1 1 67 71 0 21 18 158 46 62
1 1 43 54 0 21 23 128 31 33
'5.5' 1 52 65 0 21 12 224 67 52
'8.5' 0 52 73 0 21 20 159 35 62
'6.5' 1 43 52 0 23 22 105 52 77
'4.5' 1 84 84 0 22 21 159 77 76
2 1 67 42 0 25 19 167 37 41
5 1 49 66 0 21 22 165 32 48
'0.5' 1 70 65 0 23 15 159 36 63
5 1 52 78 0 22 20 119 38 30
5 0 58 73 0 21 19 176 69 78
'2.5' 0 68 75 0 21 18 54 21 19
5 0 62 72 1 25 15 91 26 31
'5.5' 1 43 66 0 21 20 163 54 66
'3.5' 0 56 70 0 21 21 124 36 35
3 1 56 61 1 20 21 137 42 42
4 0 74 81 0 24 15 121 23 45
'0.5' 1 65 71 0 23 16 153 34 21
'6.5' 1 63 69 0 21 23 148 112 25
'4.5' 0 58 71 0 24 21 221 35 44
'7.5' 1 57 72 0 23 18 188 47 69
'5.5' 1 63 68 0 21 25 149 47 54
4 1 53 70 0 22 9 244 37 74
'7.5' 1 57 68 1 20 30 148 109 80
7 0 51 61 1 18 20 92 24 42
4 1 64 67 0 21 23 150 20 61
'5.5' 0 53 76 0 22 16 153 22 41
'2.5' 0 29 70 0 22 16 94 23 46
'5.5' 0 54 60 0 21 19 156 32 39
'0.5' 1 51 77 0 23 25 146 7 63
'3.5' 1 58 72 0 21 25 132 30 34
'2.5' 1 43 69 0 25 18 161 92 51
'4.5' 1 51 71 0 22 23 105 43 42
'4.5' 1 53 62 0 22 21 97 55 31
'4.5' 0 54 70 0 20 10 151 16 39
6 1 56 64 1 21 14 131 49 20
'2.5' 1 61 58 0 21 22 166 71 49
5 0 47 76 0 21 26 157 43 53
0 1 39 52 0 22 23 111 29 31
5 1 48 59 0 21 23 145 56 39
'6.5' 1 50 68 0 24 24 162 46 54
5 1 35 76 0 22 24 163 19 49
6 1 30 65 1 22 18 59 23 34
'4.5' 0 68 67 0 21 23 187 59 46
'5.5' 1 49 59 0 22 15 109 30 55
1 1 61 69 1 19 19 90 61 42
'7.5' 0 67 76 0 22 16 105 7 50
6 1 47 63 1 23 25 83 38 13
5 1 56 75 1 20 23 116 32 37
1 1 50 63 1 20 17 42 16 25
5 1 43 60 0 23 19 148 19 30
'6.5' 1 67 73 1 20 21 155 22 28
7 1 62 63 0 23 18 125 48 45
'4.5' 1 57 70 0 21 27 116 23 35
0 0 41 75 1 22 21 128 26 28
'8.5' 1 54 66 0 21 13 138 33 41
'3.5' 0 45 63 1 21 8 49 9 6
'7.5' 1 48 63 1 19 29 96 24 45
'3.5' 1 61 64 0 22 28 164 34 73
6 0 56 70 0 21 23 162 48 17
'1.5' 0 41 75 0 21 21 99 18 40
9 1 43 61 0 21 19 202 43 64
'3.5' 0 53 60 0 21 19 186 33 37
'3.5' 1 44 62 1 21 20 66 28 25
4 0 66 73 0 21 18 183 71 65
'6.5' 1 58 61 0 22 19 214 26 100
'7.5' 1 46 66 0 22 17 188 67 28
6 0 37 64 1 18 19 104 34 35
5 0 51 59 0 21 25 177 80 56
'5.5' 0 51 64 0 23 19 126 29 29
'3.5' 0 56 60 1 19 22 76 16 43
'7.5' 1 66 56 1 19 23 99 59 59
1 1 45 66 0 23 26 157 58 52
'6.5' 0 37 78 0 21 14 139 32 50
'6.5' 0 42 67 0 21 16 162 43 59
'6.5' 1 38 59 1 21 24 108 38 27
7 0 66 66 0 20 20 159 29 61
'3.5' 0 34 68 1 19 12 74 36 28
'1.5' 1 53 71 0 21 24 110 32 51
4 0 49 66 1 19 22 96 35 35
'7.5' 0 55 73 1 19 12 116 21 29
'4.5' 0 49 72 1 19 22 87 29 48
0 1 59 71 1 20 20 97 12 25
'3.5' 0 40 59 1 19 10 127 37 44
'5.5' 1 58 64 1 19 23 106 37 64
5 1 60 66 1 19 17 80 47 32
'4.5' 0 63 78 1 20 22 74 51 20
'2.5' 0 56 68 1 19 24 91 32 28
'7.5' 0 54 73 1 18 18 133 21 34
7 1 52 62 1 19 21 74 13 31
0 1 34 65 1 21 20 114 14 26
'4.5' 1 69 68 1 18 20 140 -2 58
3 0 32 65 1 18 22 95 20 23
'1.5' 1 48 60 1 19 19 98 24 21
'3.5' 0 67 71 1 21 20 121 11 21
'2.5' 1 58 65 1 20 26 126 23 33
'5.5' 1 57 68 1 24 23 98 24 16
8 1 42 64 1 22 24 95 14 20
1 1 64 74 1 21 21 110 52 37
5 1 58 69 1 21 21 70 15 35
'4.5' 0 66 76 1 19 19 102 23 33
3 1 26 68 1 19 8 86 19 27
3 1 61 72 1 20 17 130 35 41
8 1 52 67 1 18 20 96 24 40
'2.5' 0 51 63 1 19 11 102 39 35
7 0 55 59 1 19 8 100 29 28
0 0 50 73 1 20 15 94 13 32
1 0 60 66 1 21 18 52 8 22
'3.5' 0 56 62 1 18 18 98 18 44
'5.5' 0 63 69 1 19 19 118 24 27
'5.5' 1 61 66 1 19 19 99 19 17
'0.5' 1 52 51 0 22 23 48 23 12
'7.5' 1 16 56 0 22 22 50 16 45
9 1 46 67 0 22 21 150 33 37
'9.5' 1 56 69 0 20 25 154 32 37
'8.5' 0 52 57 1 19 30 109 37 108
7 1 55 56 1 20 17 68 14 10
8 1 50 55 0 22 27 194 52 68
10 0 59 63 0 21 23 158 75 72
7 1 60 67 0 21 23 159 72 143
'8.5' 0 52 65 0 21 18 67 15 9
9 0 44 47 0 21 18 147 29 55
'9.5' 1 67 76 0 21 23 39 13 17
4 1 52 64 0 21 19 100 40 37
6 1 55 68 0 21 15 111 19 27
8 1 37 64 0 22 20 138 24 37
'5.5' 1 54 65 0 24 16 101 121 58
'9.5' 1 72 71 1 21 24 131 93 66
'7.5' 1 51 63 0 22 25 101 36 21
7 1 48 60 0 20 25 114 23 19
'7.5' 0 60 68 0 21 19 165 85 78
8 1 50 72 0 24 19 114 41 35
7 1 63 70 0 25 16 111 46 48
7 1 33 61 0 22 19 75 18 27
6 1 67 61 0 21 19 82 35 43
10 1 46 62 0 21 23 121 17 30
'2.5' 1 54 71 0 22 21 32 4 25
9 0 59 71 0 23 22 150 28 69
8 1 61 51 0 24 19 117 44 72
6 1 33 56 1 20 20 71 10 23
'8.5' 1 47 70 0 22 20 165 38 13
6 1 69 73 0 25 3 154 57 61
9 1 52 76 0 22 23 126 23 43
8 0 55 59 0 22 14 138 26 22
8 0 55 68 0 21 23 149 36 51
9 0 41 48 0 21 20 145 22 67
'5.5' 1 73 52 0 21 15 120 40 36
5 0 51 59 0 22 13 138 18 21
7 0 52 60 0 22 16 109 31 44
'5.5' 0 50 59 0 22 7 132 11 45
9 1 51 57 0 21 24 172 38 34
2 0 60 79 0 22 17 169 24 36
'8.5' 1 56 60 0 23 24 114 37 72
9 1 56 60 0 21 24 156 37 39
'8.5' 0 29 59 0 21 19 172 22 43
9 1 66 62 1 21 25 68 15 25
'7.5' 1 66 59 1 19 20 89 2 56
10 1 73 61 0 21 28 167 43 80
9 0 55 71 0 21 23 113 31 40
'7.5' 0 64 57 1 19 27 115 29 73
6 0 40 66 1 18 18 78 45 34
'10.5' 0 46 63 1 19 28 118 25 72
'8.5' 1 58 69 1 21 21 87 4 42
8 0 43 58 0 22 19 173 31 61
10 1 61 59 0 22 23 2 -4 23
'10.5' 0 51 48 1 19 27 162 66 74
'6.5' 1 50 66 1 20 22 49 61 16
'9.5' 0 52 73 1 19 28 122 32 66
'8.5' 1 54 67 1 21 25 96 31 9
'7.5' 0 66 61 1 19 21 100 39 41
5 0 61 68 1 20 22 82 19 57
8 1 80 75 1 21 28 100 31 48
10 0 51 62 1 19 20 115 36 51
7 1 56 69 1 21 29 141 42 53
'7.5' 1 56 58 0 21 25 165 21 29
'7.5' 1 56 60 0 21 25 165 21 29
'9.5' 1 53 74 1 19 20 110 25 55
6 1 47 55 0 25 20 118 32 54
10 0 25 62 0 21 16 158 26 43
7 1 47 63 1 20 20 146 28 51
3 0 46 69 0 25 20 49 32 20
6 0 50 58 1 19 23 90 41 79
7 0 39 58 1 20 18 121 29 39
10 1 51 68 0 22 25 155 33 61
7 0 58 72 1 19 18 104 17 55
'3.5' 1 35 62 1 20 19 147 13 30
8 0 58 62 1 19 25 110 32 55
10 0 60 65 1 19 25 108 30 22
'5.5' 0 62 69 1 18 25 113 34 37
6 0 63 66 1 19 24 115 59 2
'6.5' 1 53 72 1 21 19 61 13 38
'6.5' 1 46 62 1 19 26 60 23 27
'8.5' 1 67 75 1 20 10 109 10 56
4 1 59 58 1 20 17 68 5 25
'9.5' 0 64 66 1 19 13 111 31 39
8 0 38 55 1 19 17 77 19 33
'8.5' 1 50 47 1 22 30 73 32 43
'5.5' 0 48 72 0 21 25 151 30 57
7 0 48 62 1 19 4 89 25 43
9 0 47 64 1 19 16 78 48 23
8 0 66 64 1 19 21 110 35 44
10 1 47 19 0 23 23 220 67 54
8 1 63 50 1 19 22 65 15 28
6 0 58 68 0 20 17 141 22 36
8 0 44 70 1 19 20 117 18 39
5 1 51 79 0 22 20 122 33 16
9 0 43 69 1 19 22 63 46 23
'4.5' 1 55 71 0 25 16 44 24 40
'8.5' 1 38 48 1 19 23 52 14 24
7 1 56 66 1 20 16 62 23 29
'9.5' 0 45 73 1 19 0 131 12 78
'8.5' 1 50 74 1 19 18 101 38 57
'7.5' 1 54 66 1 20 25 42 12 37
'7.5' 1 57 71 0 20 23 152 28 27
5 0 60 74 0 21 12 107 41 61
7 0 55 78 1 19 18 77 12 27
8 0 56 75 0 21 24 154 31 69
'5.5' 1 49 53 0 23 11 103 33 34
'8.5' 1 37 60 1 19 18 96 34 44
'7.5' 0 43 50 0 21 14 154 41 21
'9.5' 1 59 70 0 22 23 175 21 34
7 1 46 69 1 20 24 57 20 39
8 0 51 65 1 18 29 112 44 51
'8.5' 0 58 78 0 21 18 143 52 34
'3.5' 0 64 78 1 20 15 49 7 31
'6.5' 1 53 59 0 21 29 110 29 13
'6.5' 1 48 72 0 21 16 131 11 12
'10.5' 0 51 70 0 21 19 167 26 51
'8.5' 0 47 63 1 19 22 56 24 24
8 0 59 63 0 21 16 137 7 19
10 1 62 71 1 19 23 86 60 30
10 1 62 74 0 21 23 121 13 81
'9.5' 0 51 67 0 21 19 149 20 42
9 0 64 66 0 22 4 168 52 22
10 0 52 62 0 21 20 140 28 85
'7.5' 1 67 80 1 22 24 88 25 27
'4.5' 1 50 73 0 22 20 168 39 25
'4.5' 1 54 67 0 22 4 94 9 22
'0.5' 1 58 61 0 22 24 51 19 19
'6.5' 0 56 73 1 21 22 48 13 14
'4.5' 1 63 74 0 22 16 145 60 45
'5.5' 1 31 32 0 23 3 66 19 45
5 1 65 69 1 19 15 85 34 28
6 0 71 69 0 22 24 109 14 51
4 0 50 84 1 21 17 63 17 41
8 1 57 64 1 19 20 102 45 31
'10.5' 0 47 58 1 19 27 162 66 74
'8.5' 1 54 60 0 20 23 128 24 24
'6.5' 1 47 59 1 20 26 86 48 19
8 1 57 78 1 18 23 114 29 51
'8.5' 0 43 57 0 21 17 164 -2 73
'5.5' 1 41 60 0 21 20 119 51 24
7 0 63 68 0 20 22 126 2 61
5 1 63 68 0 20 19 132 24 23
'3.5' 1 56 73 0 21 24 142 40 14
5 0 51 69 0 21 19 83 20 54
9 1 50 67 1 19 23 94 19 51
'8.5' 0 22 60 1 19 15 81 16 62
5 1 41 65 0 21 27 166 20 36
'9.5' 0 59 66 1 19 26 110 40 59
3 1 56 74 1 19 22 64 27 24
'1.5' 0 66 81 0 24 22 93 25 26
6 0 53 72 1 19 18 104 49 54
'0.5' 1 42 55 1 19 15 105 39 39
'6.5' 1 52 49 1 20 22 49 61 16
'7.5' 0 54 74 1 19 27 88 19 36
'4.5' 1 44 53 1 19 10 95 67 31
8 1 62 64 1 19 20 102 45 31
9 0 53 65 1 19 17 99 30 42
'7.5' 1 50 57 1 19 23 63 8 39
'8.5' 0 36 51 1 19 19 76 19 25
7 0 76 80 1 20 13 109 52 31
'9.5' 1 66 67 1 20 27 117 22 38
'6.5' 1 62 70 1 19 23 57 17 31
'9.5' 0 59 74 1 21 16 120 33 17
6 1 47 75 1 19 25 73 34 22
8 0 55 70 1 19 2 91 22 55
'9.5' 0 58 69 1 19 26 108 30 62
8 1 60 65 1 21 20 105 25 51
8 0 44 55 0 22 23 117 38 30
9 0 57 71 1 19 22 119 26 49
5 1 45 65 1 19 24 31 13 16

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 13.3976 -0.438104gender[t] + 0.00848541AMS.I[t] -0.0519583AMS.E[t] -0.109354studieprogramma[t] -0.309632age[t] + 0.0579997NUMERACYTOT[t] + 0.00326764LFM[t] -0.00342242PRH[t] + 0.0241078CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  13.3976 -0.438104gender[t] +  0.00848541AMS.I[t] -0.0519583AMS.E[t] -0.109354studieprogramma[t] -0.309632age[t] +  0.0579997NUMERACYTOT[t] +  0.00326764LFM[t] -0.00342242PRH[t] +  0.0241078CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  13.3976 -0.438104gender[t] +  0.00848541AMS.I[t] -0.0519583AMS.E[t] -0.109354studieprogramma[t] -0.309632age[t] +  0.0579997NUMERACYTOT[t] +  0.00326764LFM[t] -0.00342242PRH[t] +  0.0241078CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&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
Ex[t] = + 13.3976 -0.438104gender[t] + 0.00848541AMS.I[t] -0.0519583AMS.E[t] -0.109354studieprogramma[t] -0.309632age[t] + 0.0579997NUMERACYTOT[t] + 0.00326764LFM[t] -0.00342242PRH[t] + 0.0241078CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)13.39763.160744.2393.0682e-051.5341e-05
gender-0.4381040.314107-1.3950.1642090.0821046
AMS.I0.008485410.01545820.54890.58350.29175
AMS.E-0.05195830.0192375-2.7010.007343080.00367154
studieprogramma-0.1093540.447683-0.24430.8072060.403603
age-0.3096320.129308-2.3950.01730860.00865432
NUMERACYTOT0.05799970.02911431.9920.0473410.0236705
LFM0.003267640.004917970.66440.5069710.253486
PRH-0.003422420.0084993-0.40270.6875020.343751
CH0.02410780.008626312.7950.005559380.00277969

\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) & 13.3976 & 3.16074 & 4.239 & 3.0682e-05 & 1.5341e-05 \tabularnewline
gender & -0.438104 & 0.314107 & -1.395 & 0.164209 & 0.0821046 \tabularnewline
AMS.I & 0.00848541 & 0.0154582 & 0.5489 & 0.5835 & 0.29175 \tabularnewline
AMS.E & -0.0519583 & 0.0192375 & -2.701 & 0.00734308 & 0.00367154 \tabularnewline
studieprogramma & -0.109354 & 0.447683 & -0.2443 & 0.807206 & 0.403603 \tabularnewline
age & -0.309632 & 0.129308 & -2.395 & 0.0173086 & 0.00865432 \tabularnewline
NUMERACYTOT & 0.0579997 & 0.0291143 & 1.992 & 0.047341 & 0.0236705 \tabularnewline
LFM & 0.00326764 & 0.00491797 & 0.6644 & 0.506971 & 0.253486 \tabularnewline
PRH & -0.00342242 & 0.0084993 & -0.4027 & 0.687502 & 0.343751 \tabularnewline
CH & 0.0241078 & 0.00862631 & 2.795 & 0.00555938 & 0.00277969 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&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]13.3976[/C][C]3.16074[/C][C]4.239[/C][C]3.0682e-05[/C][C]1.5341e-05[/C][/ROW]
[ROW][C]gender[/C][C]-0.438104[/C][C]0.314107[/C][C]-1.395[/C][C]0.164209[/C][C]0.0821046[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.00848541[/C][C]0.0154582[/C][C]0.5489[/C][C]0.5835[/C][C]0.29175[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0519583[/C][C]0.0192375[/C][C]-2.701[/C][C]0.00734308[/C][C]0.00367154[/C][/ROW]
[ROW][C]studieprogramma[/C][C]-0.109354[/C][C]0.447683[/C][C]-0.2443[/C][C]0.807206[/C][C]0.403603[/C][/ROW]
[ROW][C]age[/C][C]-0.309632[/C][C]0.129308[/C][C]-2.395[/C][C]0.0173086[/C][C]0.00865432[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0579997[/C][C]0.0291143[/C][C]1.992[/C][C]0.047341[/C][C]0.0236705[/C][/ROW]
[ROW][C]LFM[/C][C]0.00326764[/C][C]0.00491797[/C][C]0.6644[/C][C]0.506971[/C][C]0.253486[/C][/ROW]
[ROW][C]PRH[/C][C]-0.00342242[/C][C]0.0084993[/C][C]-0.4027[/C][C]0.687502[/C][C]0.343751[/C][/ROW]
[ROW][C]CH[/C][C]0.0241078[/C][C]0.00862631[/C][C]2.795[/C][C]0.00555938[/C][C]0.00277969[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&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)13.39763.160744.2393.0682e-051.5341e-05
gender-0.4381040.314107-1.3950.1642090.0821046
AMS.I0.008485410.01545820.54890.58350.29175
AMS.E-0.05195830.0192375-2.7010.007343080.00367154
studieprogramma-0.1093540.447683-0.24430.8072060.403603
age-0.3096320.129308-2.3950.01730860.00865432
NUMERACYTOT0.05799970.02911431.9920.0473410.0236705
LFM0.003267640.004917970.66440.5069710.253486
PRH-0.003422420.0084993-0.40270.6875020.343751
CH0.02410780.008626312.7950.005559380.00277969






Multiple Linear Regression - Regression Statistics
Multiple R0.35449
R-squared0.125663
Adjusted R-squared0.0971524
F-TEST (value)4.40754
F-TEST (DF numerator)9
F-TEST (DF denominator)276
p-value2.11858e-05
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.42938
Sum Squared Residuals1628.92

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.35449 \tabularnewline
R-squared & 0.125663 \tabularnewline
Adjusted R-squared & 0.0971524 \tabularnewline
F-TEST (value) & 4.40754 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 276 \tabularnewline
p-value & 2.11858e-05 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.42938 \tabularnewline
Sum Squared Residuals & 1628.92 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.35449[/C][/ROW]
[ROW][C]R-squared[/C][C]0.125663[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0971524[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.40754[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]276[/C][/ROW]
[ROW][C]p-value[/C][C]2.11858e-05[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.42938[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1628.92[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&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 R0.35449
R-squared0.125663
Adjusted R-squared0.0971524
F-TEST (value)4.40754
F-TEST (DF numerator)9
F-TEST (DF denominator)276
p-value2.11858e-05
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.42938
Sum Squared Residuals1628.92






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
17.57.80061-0.300614
22.56.48228-3.98228
365.974130.0258672
46.56.8011-0.301102
516.23422-5.23422
616.45804-5.45804
75.55.97341-0.473409
88.56.598041.90196
96.56.79841-0.298411
104.55.80207-1.30207
1126.11443-4.11443
1256.30655-1.30655
130.55.83976-5.33976
1454.678090.321905
1556.91587-1.91587
162.55.18207-2.68207
1754.158240.841765
185.56.49175-0.991754
193.56.07716-2.57716
2036.49766-3.49766
2144.65723-0.657227
220.54.5183-4.0183
236.55.443651.05635
244.55.65063-1.15063
257.55.741511.75849
265.56.53646-1.03646
2745.93687-1.93687
287.57.387170.11283
2977.36916-0.36916
3046.74533-2.74533
315.55.427650.0723549
322.55.46007-2.96007
335.56.67846-1.17846
340.55.69181-5.19181
353.55.80668-2.30668
362.54.48315-1.98315
374.55.43375-0.93375
384.55.46995-0.969951
394.55.98493-1.48493
4065.052220.94778
412.56.71795-4.21795
4256.49685-1.49685
4306.12147-6.12147
4456.35532-1.35532
456.55.485161.01484
4655.53661-0.536607
4764.893231.10677
484.56.84319-2.34319
495.55.94724-0.447244
5016.09945-5.09945
517.55.65791.8421
5264.758591.24141
5355.73131-0.731307
5415.47956-4.47956
5555.32913-0.32913
566.55.757260.742744
5775.463691.53631
584.56.01389-1.51389
5905.14964-5.14964
608.55.566582.93342
613.54.63239-1.13239
627.57.099440.400558
633.57.14324-3.64324
6465.842320.157679
651.55.79054-4.29054
6696.810412.18959
673.56.71636-3.21636
683.55.38232-1.88232
6946.62838-2.62838
706.57.59334-1.09334
717.55.154682.34532
7266.87272-0.872723
7357.36713-2.36713
745.55.497060.00293609
753.57.26912-3.76912
767.57.495420.00458378
7715.86665-4.86665
786.55.518590.981406
796.56.50304-0.00303994
806.55.870520.629484
8177.38661-0.386606
823.55.65018-2.15018
831.56.08931-4.58931
8446.70543-2.70543
857.55.781261.71874
864.56.69821-2.19821
8705.50767-5.50767
883.56.6082-3.1082
895.57.23057-1.73057
9055.905-0.904997
914.55.40284-0.902836
922.56.60209-4.10209
937.56.60650.893504
9476.349590.650405
9505.37046-5.37046
964.57.35164-2.85164
9736.68155-3.68155
981.56.10327-4.60327
993.55.68944-2.18944
1002.56.40891-3.90891
1015.54.327271.17273
10285.205942.79406
10315.33746-4.33746
10455.49405-0.49405
1054.56.16856-1.66856
10634.98547-1.98547
10735.71352-2.71352
10886.592651.40735
1092.56.2462-3.7462
11076.172910.82709
11105.63102-5.63102
11215.58274-4.58274
1133.57.33199-3.83199
1145.56.41103-0.911029
1155.55.82578-0.325779
1160.55.64036-5.14036
1177.55.843141.65686
11895.543893.45611
1199.56.392583.10742
1208.59.45801-0.958014
12175.615881.38412
12287.375420.624585
123107.451942.54806
12478.53967-1.53967
1258.55.387823.11218
12697.577641.42236
1279.54.903674.59633
12845.75697-1.75697
12965.209330.790671
13085.556982.44302
1315.54.85140.648602
1329.56.362653.13735
1337.55.470042.02996
13476.258480.741522
1357.57.101930.398073
13684.389543.61046
13774.406622.59338
13875.194511.80549
13966.14306-0.143064
140106.020553.97945
1412.54.82831-2.32831
14296.421392.57861
14386.465531.53447
14465.940090.0599083
1458.54.791813.70819
14663.963932.03607
14795.343623.65638
14885.691162.30884
14986.756011.24399
15097.922941.07706
1515.56.36791-0.867906
15255.60249-0.602486
15376.148240.851763
1545.55.82894-0.328939
15596.571982.42802
15625.31407-3.31407
1578.56.569261.93074
15896.530212.46979
1598.56.701221.79878
16095.910033.08997
1617.57.255620.244379
162107.858332.14167
16396.234422.76558
1647.58.58905-1.08905
16566.58955-0.58955
16610.58.181952.31805
1678.55.7562.744
16886.968741.03126
169105.508344.49166
17010.58.997421.50258
1716.55.265571.23443
1729.57.557751.94225
1738.55.199423.30058
1747.57.195510.304494
17556.93309-1.93309
17686.131651.86835
177107.258632.74137
17876.514610.485387
1797.56.535220.964783
1807.56.43131.0687
1819.56.331733.16827
18265.497660.502337
183106.277973.72203
18476.553670.446334
18534.15474-1.15474
18668.20819-2.20819
18776.693270.306728
188106.361283.63872
18976.807950.192045
1903.55.99414-2.49414
19187.70180.298195
192106.767653.23235
1935.57.25069-1.75069
19466.12462-0.124621
1956.55.229511.27049
1966.56.412280.0877213
1978.55.581122.91888
19845.93832-1.93832
1999.56.469853.03015
20086.83811.1619
2018.56.92611.5739
2025.56.77649-1.27649
20376.0650.935
20496.051782.94822
20587.158320.84168
206108.374941.62506
20787.015860.984144
20866.40325-0.403252
20986.562411.43759
21054.307060.692943
21196.063882.93612
2124.53.950280.549719
2138.56.830151.66985
21475.454421.54558
2159.56.261513.23849
2168.56.164592.33541
2177.56.12461.3754
2187.55.947231.55277
21955.93541-0.935411
22075.724621.27538
22186.926171.07383
2225.55.181230.318774
2238.56.465652.03435
2247.56.343431.15657
2259.55.664763.83524
22675.91271.0873
22787.89720.102801
2288.55.487683.01232
2293.55.3394-1.8394
2306.56.096980.403022
2316.54.731211.76879
23210.56.479194.02081
2338.56.486092.01391
23485.932332.06767
235105.937074.06293
236106.7763.224
2379.56.379813.12019
23894.832874.16713
239107.685932.31407
2407.54.694982.80502
2414.54.95707-0.457068
2424.54.163310.336692
2430.55.42194-4.92194
2446.55.194041.30596
2454.55.11855-0.61855
2465.55.84781-0.347811
24755.63995-0.639949
24866.53277-0.532769
24944.96783-0.967826
25086.212081.78792
25110.58.44392.0561
2528.56.356252.14375
2536.56.073540.426458
25486.544421.45558
2558.57.587160.912839
2565.55.6405-0.140498
25777.35781-0.357806
25855.77392-0.773921
2593.55.19605-1.69605
26056.34952-1.34952
26196.715812.28419
2628.57.0491.451
26356.33567-1.33567
2649.57.629511.87049
26535.56869-2.56869
2661.54.43896-2.93896
26766.6319-0.631902
2680.56.48563-5.98563
2696.56.165840.334164
2707.56.674920.82508
2714.55.99515-1.49515
27286.254511.74549
27396.697012.30299
2747.56.882440.617555
2758.56.948831.55117
27675.263361.73664
2779.56.525432.97457
2786.56.065540.434457
2799.55.058694.44131
28065.57160.428399
28185.898832.10117
2829.57.565161.93484
28386.126721.87328
28486.410821.58918
28596.956992.04301
28655.8062-0.806197

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 7.80061 & -0.300614 \tabularnewline
2 & 2.5 & 6.48228 & -3.98228 \tabularnewline
3 & 6 & 5.97413 & 0.0258672 \tabularnewline
4 & 6.5 & 6.8011 & -0.301102 \tabularnewline
5 & 1 & 6.23422 & -5.23422 \tabularnewline
6 & 1 & 6.45804 & -5.45804 \tabularnewline
7 & 5.5 & 5.97341 & -0.473409 \tabularnewline
8 & 8.5 & 6.59804 & 1.90196 \tabularnewline
9 & 6.5 & 6.79841 & -0.298411 \tabularnewline
10 & 4.5 & 5.80207 & -1.30207 \tabularnewline
11 & 2 & 6.11443 & -4.11443 \tabularnewline
12 & 5 & 6.30655 & -1.30655 \tabularnewline
13 & 0.5 & 5.83976 & -5.33976 \tabularnewline
14 & 5 & 4.67809 & 0.321905 \tabularnewline
15 & 5 & 6.91587 & -1.91587 \tabularnewline
16 & 2.5 & 5.18207 & -2.68207 \tabularnewline
17 & 5 & 4.15824 & 0.841765 \tabularnewline
18 & 5.5 & 6.49175 & -0.991754 \tabularnewline
19 & 3.5 & 6.07716 & -2.57716 \tabularnewline
20 & 3 & 6.49766 & -3.49766 \tabularnewline
21 & 4 & 4.65723 & -0.657227 \tabularnewline
22 & 0.5 & 4.5183 & -4.0183 \tabularnewline
23 & 6.5 & 5.44365 & 1.05635 \tabularnewline
24 & 4.5 & 5.65063 & -1.15063 \tabularnewline
25 & 7.5 & 5.74151 & 1.75849 \tabularnewline
26 & 5.5 & 6.53646 & -1.03646 \tabularnewline
27 & 4 & 5.93687 & -1.93687 \tabularnewline
28 & 7.5 & 7.38717 & 0.11283 \tabularnewline
29 & 7 & 7.36916 & -0.36916 \tabularnewline
30 & 4 & 6.74533 & -2.74533 \tabularnewline
31 & 5.5 & 5.42765 & 0.0723549 \tabularnewline
32 & 2.5 & 5.46007 & -2.96007 \tabularnewline
33 & 5.5 & 6.67846 & -1.17846 \tabularnewline
34 & 0.5 & 5.69181 & -5.19181 \tabularnewline
35 & 3.5 & 5.80668 & -2.30668 \tabularnewline
36 & 2.5 & 4.48315 & -1.98315 \tabularnewline
37 & 4.5 & 5.43375 & -0.93375 \tabularnewline
38 & 4.5 & 5.46995 & -0.969951 \tabularnewline
39 & 4.5 & 5.98493 & -1.48493 \tabularnewline
40 & 6 & 5.05222 & 0.94778 \tabularnewline
41 & 2.5 & 6.71795 & -4.21795 \tabularnewline
42 & 5 & 6.49685 & -1.49685 \tabularnewline
43 & 0 & 6.12147 & -6.12147 \tabularnewline
44 & 5 & 6.35532 & -1.35532 \tabularnewline
45 & 6.5 & 5.48516 & 1.01484 \tabularnewline
46 & 5 & 5.53661 & -0.536607 \tabularnewline
47 & 6 & 4.89323 & 1.10677 \tabularnewline
48 & 4.5 & 6.84319 & -2.34319 \tabularnewline
49 & 5.5 & 5.94724 & -0.447244 \tabularnewline
50 & 1 & 6.09945 & -5.09945 \tabularnewline
51 & 7.5 & 5.6579 & 1.8421 \tabularnewline
52 & 6 & 4.75859 & 1.24141 \tabularnewline
53 & 5 & 5.73131 & -0.731307 \tabularnewline
54 & 1 & 5.47956 & -4.47956 \tabularnewline
55 & 5 & 5.32913 & -0.32913 \tabularnewline
56 & 6.5 & 5.75726 & 0.742744 \tabularnewline
57 & 7 & 5.46369 & 1.53631 \tabularnewline
58 & 4.5 & 6.01389 & -1.51389 \tabularnewline
59 & 0 & 5.14964 & -5.14964 \tabularnewline
60 & 8.5 & 5.56658 & 2.93342 \tabularnewline
61 & 3.5 & 4.63239 & -1.13239 \tabularnewline
62 & 7.5 & 7.09944 & 0.400558 \tabularnewline
63 & 3.5 & 7.14324 & -3.64324 \tabularnewline
64 & 6 & 5.84232 & 0.157679 \tabularnewline
65 & 1.5 & 5.79054 & -4.29054 \tabularnewline
66 & 9 & 6.81041 & 2.18959 \tabularnewline
67 & 3.5 & 6.71636 & -3.21636 \tabularnewline
68 & 3.5 & 5.38232 & -1.88232 \tabularnewline
69 & 4 & 6.62838 & -2.62838 \tabularnewline
70 & 6.5 & 7.59334 & -1.09334 \tabularnewline
71 & 7.5 & 5.15468 & 2.34532 \tabularnewline
72 & 6 & 6.87272 & -0.872723 \tabularnewline
73 & 5 & 7.36713 & -2.36713 \tabularnewline
74 & 5.5 & 5.49706 & 0.00293609 \tabularnewline
75 & 3.5 & 7.26912 & -3.76912 \tabularnewline
76 & 7.5 & 7.49542 & 0.00458378 \tabularnewline
77 & 1 & 5.86665 & -4.86665 \tabularnewline
78 & 6.5 & 5.51859 & 0.981406 \tabularnewline
79 & 6.5 & 6.50304 & -0.00303994 \tabularnewline
80 & 6.5 & 5.87052 & 0.629484 \tabularnewline
81 & 7 & 7.38661 & -0.386606 \tabularnewline
82 & 3.5 & 5.65018 & -2.15018 \tabularnewline
83 & 1.5 & 6.08931 & -4.58931 \tabularnewline
84 & 4 & 6.70543 & -2.70543 \tabularnewline
85 & 7.5 & 5.78126 & 1.71874 \tabularnewline
86 & 4.5 & 6.69821 & -2.19821 \tabularnewline
87 & 0 & 5.50767 & -5.50767 \tabularnewline
88 & 3.5 & 6.6082 & -3.1082 \tabularnewline
89 & 5.5 & 7.23057 & -1.73057 \tabularnewline
90 & 5 & 5.905 & -0.904997 \tabularnewline
91 & 4.5 & 5.40284 & -0.902836 \tabularnewline
92 & 2.5 & 6.60209 & -4.10209 \tabularnewline
93 & 7.5 & 6.6065 & 0.893504 \tabularnewline
94 & 7 & 6.34959 & 0.650405 \tabularnewline
95 & 0 & 5.37046 & -5.37046 \tabularnewline
96 & 4.5 & 7.35164 & -2.85164 \tabularnewline
97 & 3 & 6.68155 & -3.68155 \tabularnewline
98 & 1.5 & 6.10327 & -4.60327 \tabularnewline
99 & 3.5 & 5.68944 & -2.18944 \tabularnewline
100 & 2.5 & 6.40891 & -3.90891 \tabularnewline
101 & 5.5 & 4.32727 & 1.17273 \tabularnewline
102 & 8 & 5.20594 & 2.79406 \tabularnewline
103 & 1 & 5.33746 & -4.33746 \tabularnewline
104 & 5 & 5.49405 & -0.49405 \tabularnewline
105 & 4.5 & 6.16856 & -1.66856 \tabularnewline
106 & 3 & 4.98547 & -1.98547 \tabularnewline
107 & 3 & 5.71352 & -2.71352 \tabularnewline
108 & 8 & 6.59265 & 1.40735 \tabularnewline
109 & 2.5 & 6.2462 & -3.7462 \tabularnewline
110 & 7 & 6.17291 & 0.82709 \tabularnewline
111 & 0 & 5.63102 & -5.63102 \tabularnewline
112 & 1 & 5.58274 & -4.58274 \tabularnewline
113 & 3.5 & 7.33199 & -3.83199 \tabularnewline
114 & 5.5 & 6.41103 & -0.911029 \tabularnewline
115 & 5.5 & 5.82578 & -0.325779 \tabularnewline
116 & 0.5 & 5.64036 & -5.14036 \tabularnewline
117 & 7.5 & 5.84314 & 1.65686 \tabularnewline
118 & 9 & 5.54389 & 3.45611 \tabularnewline
119 & 9.5 & 6.39258 & 3.10742 \tabularnewline
120 & 8.5 & 9.45801 & -0.958014 \tabularnewline
121 & 7 & 5.61588 & 1.38412 \tabularnewline
122 & 8 & 7.37542 & 0.624585 \tabularnewline
123 & 10 & 7.45194 & 2.54806 \tabularnewline
124 & 7 & 8.53967 & -1.53967 \tabularnewline
125 & 8.5 & 5.38782 & 3.11218 \tabularnewline
126 & 9 & 7.57764 & 1.42236 \tabularnewline
127 & 9.5 & 4.90367 & 4.59633 \tabularnewline
128 & 4 & 5.75697 & -1.75697 \tabularnewline
129 & 6 & 5.20933 & 0.790671 \tabularnewline
130 & 8 & 5.55698 & 2.44302 \tabularnewline
131 & 5.5 & 4.8514 & 0.648602 \tabularnewline
132 & 9.5 & 6.36265 & 3.13735 \tabularnewline
133 & 7.5 & 5.47004 & 2.02996 \tabularnewline
134 & 7 & 6.25848 & 0.741522 \tabularnewline
135 & 7.5 & 7.10193 & 0.398073 \tabularnewline
136 & 8 & 4.38954 & 3.61046 \tabularnewline
137 & 7 & 4.40662 & 2.59338 \tabularnewline
138 & 7 & 5.19451 & 1.80549 \tabularnewline
139 & 6 & 6.14306 & -0.143064 \tabularnewline
140 & 10 & 6.02055 & 3.97945 \tabularnewline
141 & 2.5 & 4.82831 & -2.32831 \tabularnewline
142 & 9 & 6.42139 & 2.57861 \tabularnewline
143 & 8 & 6.46553 & 1.53447 \tabularnewline
144 & 6 & 5.94009 & 0.0599083 \tabularnewline
145 & 8.5 & 4.79181 & 3.70819 \tabularnewline
146 & 6 & 3.96393 & 2.03607 \tabularnewline
147 & 9 & 5.34362 & 3.65638 \tabularnewline
148 & 8 & 5.69116 & 2.30884 \tabularnewline
149 & 8 & 6.75601 & 1.24399 \tabularnewline
150 & 9 & 7.92294 & 1.07706 \tabularnewline
151 & 5.5 & 6.36791 & -0.867906 \tabularnewline
152 & 5 & 5.60249 & -0.602486 \tabularnewline
153 & 7 & 6.14824 & 0.851763 \tabularnewline
154 & 5.5 & 5.82894 & -0.328939 \tabularnewline
155 & 9 & 6.57198 & 2.42802 \tabularnewline
156 & 2 & 5.31407 & -3.31407 \tabularnewline
157 & 8.5 & 6.56926 & 1.93074 \tabularnewline
158 & 9 & 6.53021 & 2.46979 \tabularnewline
159 & 8.5 & 6.70122 & 1.79878 \tabularnewline
160 & 9 & 5.91003 & 3.08997 \tabularnewline
161 & 7.5 & 7.25562 & 0.244379 \tabularnewline
162 & 10 & 7.85833 & 2.14167 \tabularnewline
163 & 9 & 6.23442 & 2.76558 \tabularnewline
164 & 7.5 & 8.58905 & -1.08905 \tabularnewline
165 & 6 & 6.58955 & -0.58955 \tabularnewline
166 & 10.5 & 8.18195 & 2.31805 \tabularnewline
167 & 8.5 & 5.756 & 2.744 \tabularnewline
168 & 8 & 6.96874 & 1.03126 \tabularnewline
169 & 10 & 5.50834 & 4.49166 \tabularnewline
170 & 10.5 & 8.99742 & 1.50258 \tabularnewline
171 & 6.5 & 5.26557 & 1.23443 \tabularnewline
172 & 9.5 & 7.55775 & 1.94225 \tabularnewline
173 & 8.5 & 5.19942 & 3.30058 \tabularnewline
174 & 7.5 & 7.19551 & 0.304494 \tabularnewline
175 & 5 & 6.93309 & -1.93309 \tabularnewline
176 & 8 & 6.13165 & 1.86835 \tabularnewline
177 & 10 & 7.25863 & 2.74137 \tabularnewline
178 & 7 & 6.51461 & 0.485387 \tabularnewline
179 & 7.5 & 6.53522 & 0.964783 \tabularnewline
180 & 7.5 & 6.4313 & 1.0687 \tabularnewline
181 & 9.5 & 6.33173 & 3.16827 \tabularnewline
182 & 6 & 5.49766 & 0.502337 \tabularnewline
183 & 10 & 6.27797 & 3.72203 \tabularnewline
184 & 7 & 6.55367 & 0.446334 \tabularnewline
185 & 3 & 4.15474 & -1.15474 \tabularnewline
186 & 6 & 8.20819 & -2.20819 \tabularnewline
187 & 7 & 6.69327 & 0.306728 \tabularnewline
188 & 10 & 6.36128 & 3.63872 \tabularnewline
189 & 7 & 6.80795 & 0.192045 \tabularnewline
190 & 3.5 & 5.99414 & -2.49414 \tabularnewline
191 & 8 & 7.7018 & 0.298195 \tabularnewline
192 & 10 & 6.76765 & 3.23235 \tabularnewline
193 & 5.5 & 7.25069 & -1.75069 \tabularnewline
194 & 6 & 6.12462 & -0.124621 \tabularnewline
195 & 6.5 & 5.22951 & 1.27049 \tabularnewline
196 & 6.5 & 6.41228 & 0.0877213 \tabularnewline
197 & 8.5 & 5.58112 & 2.91888 \tabularnewline
198 & 4 & 5.93832 & -1.93832 \tabularnewline
199 & 9.5 & 6.46985 & 3.03015 \tabularnewline
200 & 8 & 6.8381 & 1.1619 \tabularnewline
201 & 8.5 & 6.9261 & 1.5739 \tabularnewline
202 & 5.5 & 6.77649 & -1.27649 \tabularnewline
203 & 7 & 6.065 & 0.935 \tabularnewline
204 & 9 & 6.05178 & 2.94822 \tabularnewline
205 & 8 & 7.15832 & 0.84168 \tabularnewline
206 & 10 & 8.37494 & 1.62506 \tabularnewline
207 & 8 & 7.01586 & 0.984144 \tabularnewline
208 & 6 & 6.40325 & -0.403252 \tabularnewline
209 & 8 & 6.56241 & 1.43759 \tabularnewline
210 & 5 & 4.30706 & 0.692943 \tabularnewline
211 & 9 & 6.06388 & 2.93612 \tabularnewline
212 & 4.5 & 3.95028 & 0.549719 \tabularnewline
213 & 8.5 & 6.83015 & 1.66985 \tabularnewline
214 & 7 & 5.45442 & 1.54558 \tabularnewline
215 & 9.5 & 6.26151 & 3.23849 \tabularnewline
216 & 8.5 & 6.16459 & 2.33541 \tabularnewline
217 & 7.5 & 6.1246 & 1.3754 \tabularnewline
218 & 7.5 & 5.94723 & 1.55277 \tabularnewline
219 & 5 & 5.93541 & -0.935411 \tabularnewline
220 & 7 & 5.72462 & 1.27538 \tabularnewline
221 & 8 & 6.92617 & 1.07383 \tabularnewline
222 & 5.5 & 5.18123 & 0.318774 \tabularnewline
223 & 8.5 & 6.46565 & 2.03435 \tabularnewline
224 & 7.5 & 6.34343 & 1.15657 \tabularnewline
225 & 9.5 & 5.66476 & 3.83524 \tabularnewline
226 & 7 & 5.9127 & 1.0873 \tabularnewline
227 & 8 & 7.8972 & 0.102801 \tabularnewline
228 & 8.5 & 5.48768 & 3.01232 \tabularnewline
229 & 3.5 & 5.3394 & -1.8394 \tabularnewline
230 & 6.5 & 6.09698 & 0.403022 \tabularnewline
231 & 6.5 & 4.73121 & 1.76879 \tabularnewline
232 & 10.5 & 6.47919 & 4.02081 \tabularnewline
233 & 8.5 & 6.48609 & 2.01391 \tabularnewline
234 & 8 & 5.93233 & 2.06767 \tabularnewline
235 & 10 & 5.93707 & 4.06293 \tabularnewline
236 & 10 & 6.776 & 3.224 \tabularnewline
237 & 9.5 & 6.37981 & 3.12019 \tabularnewline
238 & 9 & 4.83287 & 4.16713 \tabularnewline
239 & 10 & 7.68593 & 2.31407 \tabularnewline
240 & 7.5 & 4.69498 & 2.80502 \tabularnewline
241 & 4.5 & 4.95707 & -0.457068 \tabularnewline
242 & 4.5 & 4.16331 & 0.336692 \tabularnewline
243 & 0.5 & 5.42194 & -4.92194 \tabularnewline
244 & 6.5 & 5.19404 & 1.30596 \tabularnewline
245 & 4.5 & 5.11855 & -0.61855 \tabularnewline
246 & 5.5 & 5.84781 & -0.347811 \tabularnewline
247 & 5 & 5.63995 & -0.639949 \tabularnewline
248 & 6 & 6.53277 & -0.532769 \tabularnewline
249 & 4 & 4.96783 & -0.967826 \tabularnewline
250 & 8 & 6.21208 & 1.78792 \tabularnewline
251 & 10.5 & 8.4439 & 2.0561 \tabularnewline
252 & 8.5 & 6.35625 & 2.14375 \tabularnewline
253 & 6.5 & 6.07354 & 0.426458 \tabularnewline
254 & 8 & 6.54442 & 1.45558 \tabularnewline
255 & 8.5 & 7.58716 & 0.912839 \tabularnewline
256 & 5.5 & 5.6405 & -0.140498 \tabularnewline
257 & 7 & 7.35781 & -0.357806 \tabularnewline
258 & 5 & 5.77392 & -0.773921 \tabularnewline
259 & 3.5 & 5.19605 & -1.69605 \tabularnewline
260 & 5 & 6.34952 & -1.34952 \tabularnewline
261 & 9 & 6.71581 & 2.28419 \tabularnewline
262 & 8.5 & 7.049 & 1.451 \tabularnewline
263 & 5 & 6.33567 & -1.33567 \tabularnewline
264 & 9.5 & 7.62951 & 1.87049 \tabularnewline
265 & 3 & 5.56869 & -2.56869 \tabularnewline
266 & 1.5 & 4.43896 & -2.93896 \tabularnewline
267 & 6 & 6.6319 & -0.631902 \tabularnewline
268 & 0.5 & 6.48563 & -5.98563 \tabularnewline
269 & 6.5 & 6.16584 & 0.334164 \tabularnewline
270 & 7.5 & 6.67492 & 0.82508 \tabularnewline
271 & 4.5 & 5.99515 & -1.49515 \tabularnewline
272 & 8 & 6.25451 & 1.74549 \tabularnewline
273 & 9 & 6.69701 & 2.30299 \tabularnewline
274 & 7.5 & 6.88244 & 0.617555 \tabularnewline
275 & 8.5 & 6.94883 & 1.55117 \tabularnewline
276 & 7 & 5.26336 & 1.73664 \tabularnewline
277 & 9.5 & 6.52543 & 2.97457 \tabularnewline
278 & 6.5 & 6.06554 & 0.434457 \tabularnewline
279 & 9.5 & 5.05869 & 4.44131 \tabularnewline
280 & 6 & 5.5716 & 0.428399 \tabularnewline
281 & 8 & 5.89883 & 2.10117 \tabularnewline
282 & 9.5 & 7.56516 & 1.93484 \tabularnewline
283 & 8 & 6.12672 & 1.87328 \tabularnewline
284 & 8 & 6.41082 & 1.58918 \tabularnewline
285 & 9 & 6.95699 & 2.04301 \tabularnewline
286 & 5 & 5.8062 & -0.806197 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&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]7.5[/C][C]7.80061[/C][C]-0.300614[/C][/ROW]
[ROW][C]2[/C][C]2.5[/C][C]6.48228[/C][C]-3.98228[/C][/ROW]
[ROW][C]3[/C][C]6[/C][C]5.97413[/C][C]0.0258672[/C][/ROW]
[ROW][C]4[/C][C]6.5[/C][C]6.8011[/C][C]-0.301102[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]6.23422[/C][C]-5.23422[/C][/ROW]
[ROW][C]6[/C][C]1[/C][C]6.45804[/C][C]-5.45804[/C][/ROW]
[ROW][C]7[/C][C]5.5[/C][C]5.97341[/C][C]-0.473409[/C][/ROW]
[ROW][C]8[/C][C]8.5[/C][C]6.59804[/C][C]1.90196[/C][/ROW]
[ROW][C]9[/C][C]6.5[/C][C]6.79841[/C][C]-0.298411[/C][/ROW]
[ROW][C]10[/C][C]4.5[/C][C]5.80207[/C][C]-1.30207[/C][/ROW]
[ROW][C]11[/C][C]2[/C][C]6.11443[/C][C]-4.11443[/C][/ROW]
[ROW][C]12[/C][C]5[/C][C]6.30655[/C][C]-1.30655[/C][/ROW]
[ROW][C]13[/C][C]0.5[/C][C]5.83976[/C][C]-5.33976[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]4.67809[/C][C]0.321905[/C][/ROW]
[ROW][C]15[/C][C]5[/C][C]6.91587[/C][C]-1.91587[/C][/ROW]
[ROW][C]16[/C][C]2.5[/C][C]5.18207[/C][C]-2.68207[/C][/ROW]
[ROW][C]17[/C][C]5[/C][C]4.15824[/C][C]0.841765[/C][/ROW]
[ROW][C]18[/C][C]5.5[/C][C]6.49175[/C][C]-0.991754[/C][/ROW]
[ROW][C]19[/C][C]3.5[/C][C]6.07716[/C][C]-2.57716[/C][/ROW]
[ROW][C]20[/C][C]3[/C][C]6.49766[/C][C]-3.49766[/C][/ROW]
[ROW][C]21[/C][C]4[/C][C]4.65723[/C][C]-0.657227[/C][/ROW]
[ROW][C]22[/C][C]0.5[/C][C]4.5183[/C][C]-4.0183[/C][/ROW]
[ROW][C]23[/C][C]6.5[/C][C]5.44365[/C][C]1.05635[/C][/ROW]
[ROW][C]24[/C][C]4.5[/C][C]5.65063[/C][C]-1.15063[/C][/ROW]
[ROW][C]25[/C][C]7.5[/C][C]5.74151[/C][C]1.75849[/C][/ROW]
[ROW][C]26[/C][C]5.5[/C][C]6.53646[/C][C]-1.03646[/C][/ROW]
[ROW][C]27[/C][C]4[/C][C]5.93687[/C][C]-1.93687[/C][/ROW]
[ROW][C]28[/C][C]7.5[/C][C]7.38717[/C][C]0.11283[/C][/ROW]
[ROW][C]29[/C][C]7[/C][C]7.36916[/C][C]-0.36916[/C][/ROW]
[ROW][C]30[/C][C]4[/C][C]6.74533[/C][C]-2.74533[/C][/ROW]
[ROW][C]31[/C][C]5.5[/C][C]5.42765[/C][C]0.0723549[/C][/ROW]
[ROW][C]32[/C][C]2.5[/C][C]5.46007[/C][C]-2.96007[/C][/ROW]
[ROW][C]33[/C][C]5.5[/C][C]6.67846[/C][C]-1.17846[/C][/ROW]
[ROW][C]34[/C][C]0.5[/C][C]5.69181[/C][C]-5.19181[/C][/ROW]
[ROW][C]35[/C][C]3.5[/C][C]5.80668[/C][C]-2.30668[/C][/ROW]
[ROW][C]36[/C][C]2.5[/C][C]4.48315[/C][C]-1.98315[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]5.43375[/C][C]-0.93375[/C][/ROW]
[ROW][C]38[/C][C]4.5[/C][C]5.46995[/C][C]-0.969951[/C][/ROW]
[ROW][C]39[/C][C]4.5[/C][C]5.98493[/C][C]-1.48493[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]5.05222[/C][C]0.94778[/C][/ROW]
[ROW][C]41[/C][C]2.5[/C][C]6.71795[/C][C]-4.21795[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]6.49685[/C][C]-1.49685[/C][/ROW]
[ROW][C]43[/C][C]0[/C][C]6.12147[/C][C]-6.12147[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]6.35532[/C][C]-1.35532[/C][/ROW]
[ROW][C]45[/C][C]6.5[/C][C]5.48516[/C][C]1.01484[/C][/ROW]
[ROW][C]46[/C][C]5[/C][C]5.53661[/C][C]-0.536607[/C][/ROW]
[ROW][C]47[/C][C]6[/C][C]4.89323[/C][C]1.10677[/C][/ROW]
[ROW][C]48[/C][C]4.5[/C][C]6.84319[/C][C]-2.34319[/C][/ROW]
[ROW][C]49[/C][C]5.5[/C][C]5.94724[/C][C]-0.447244[/C][/ROW]
[ROW][C]50[/C][C]1[/C][C]6.09945[/C][C]-5.09945[/C][/ROW]
[ROW][C]51[/C][C]7.5[/C][C]5.6579[/C][C]1.8421[/C][/ROW]
[ROW][C]52[/C][C]6[/C][C]4.75859[/C][C]1.24141[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]5.73131[/C][C]-0.731307[/C][/ROW]
[ROW][C]54[/C][C]1[/C][C]5.47956[/C][C]-4.47956[/C][/ROW]
[ROW][C]55[/C][C]5[/C][C]5.32913[/C][C]-0.32913[/C][/ROW]
[ROW][C]56[/C][C]6.5[/C][C]5.75726[/C][C]0.742744[/C][/ROW]
[ROW][C]57[/C][C]7[/C][C]5.46369[/C][C]1.53631[/C][/ROW]
[ROW][C]58[/C][C]4.5[/C][C]6.01389[/C][C]-1.51389[/C][/ROW]
[ROW][C]59[/C][C]0[/C][C]5.14964[/C][C]-5.14964[/C][/ROW]
[ROW][C]60[/C][C]8.5[/C][C]5.56658[/C][C]2.93342[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]4.63239[/C][C]-1.13239[/C][/ROW]
[ROW][C]62[/C][C]7.5[/C][C]7.09944[/C][C]0.400558[/C][/ROW]
[ROW][C]63[/C][C]3.5[/C][C]7.14324[/C][C]-3.64324[/C][/ROW]
[ROW][C]64[/C][C]6[/C][C]5.84232[/C][C]0.157679[/C][/ROW]
[ROW][C]65[/C][C]1.5[/C][C]5.79054[/C][C]-4.29054[/C][/ROW]
[ROW][C]66[/C][C]9[/C][C]6.81041[/C][C]2.18959[/C][/ROW]
[ROW][C]67[/C][C]3.5[/C][C]6.71636[/C][C]-3.21636[/C][/ROW]
[ROW][C]68[/C][C]3.5[/C][C]5.38232[/C][C]-1.88232[/C][/ROW]
[ROW][C]69[/C][C]4[/C][C]6.62838[/C][C]-2.62838[/C][/ROW]
[ROW][C]70[/C][C]6.5[/C][C]7.59334[/C][C]-1.09334[/C][/ROW]
[ROW][C]71[/C][C]7.5[/C][C]5.15468[/C][C]2.34532[/C][/ROW]
[ROW][C]72[/C][C]6[/C][C]6.87272[/C][C]-0.872723[/C][/ROW]
[ROW][C]73[/C][C]5[/C][C]7.36713[/C][C]-2.36713[/C][/ROW]
[ROW][C]74[/C][C]5.5[/C][C]5.49706[/C][C]0.00293609[/C][/ROW]
[ROW][C]75[/C][C]3.5[/C][C]7.26912[/C][C]-3.76912[/C][/ROW]
[ROW][C]76[/C][C]7.5[/C][C]7.49542[/C][C]0.00458378[/C][/ROW]
[ROW][C]77[/C][C]1[/C][C]5.86665[/C][C]-4.86665[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]5.51859[/C][C]0.981406[/C][/ROW]
[ROW][C]79[/C][C]6.5[/C][C]6.50304[/C][C]-0.00303994[/C][/ROW]
[ROW][C]80[/C][C]6.5[/C][C]5.87052[/C][C]0.629484[/C][/ROW]
[ROW][C]81[/C][C]7[/C][C]7.38661[/C][C]-0.386606[/C][/ROW]
[ROW][C]82[/C][C]3.5[/C][C]5.65018[/C][C]-2.15018[/C][/ROW]
[ROW][C]83[/C][C]1.5[/C][C]6.08931[/C][C]-4.58931[/C][/ROW]
[ROW][C]84[/C][C]4[/C][C]6.70543[/C][C]-2.70543[/C][/ROW]
[ROW][C]85[/C][C]7.5[/C][C]5.78126[/C][C]1.71874[/C][/ROW]
[ROW][C]86[/C][C]4.5[/C][C]6.69821[/C][C]-2.19821[/C][/ROW]
[ROW][C]87[/C][C]0[/C][C]5.50767[/C][C]-5.50767[/C][/ROW]
[ROW][C]88[/C][C]3.5[/C][C]6.6082[/C][C]-3.1082[/C][/ROW]
[ROW][C]89[/C][C]5.5[/C][C]7.23057[/C][C]-1.73057[/C][/ROW]
[ROW][C]90[/C][C]5[/C][C]5.905[/C][C]-0.904997[/C][/ROW]
[ROW][C]91[/C][C]4.5[/C][C]5.40284[/C][C]-0.902836[/C][/ROW]
[ROW][C]92[/C][C]2.5[/C][C]6.60209[/C][C]-4.10209[/C][/ROW]
[ROW][C]93[/C][C]7.5[/C][C]6.6065[/C][C]0.893504[/C][/ROW]
[ROW][C]94[/C][C]7[/C][C]6.34959[/C][C]0.650405[/C][/ROW]
[ROW][C]95[/C][C]0[/C][C]5.37046[/C][C]-5.37046[/C][/ROW]
[ROW][C]96[/C][C]4.5[/C][C]7.35164[/C][C]-2.85164[/C][/ROW]
[ROW][C]97[/C][C]3[/C][C]6.68155[/C][C]-3.68155[/C][/ROW]
[ROW][C]98[/C][C]1.5[/C][C]6.10327[/C][C]-4.60327[/C][/ROW]
[ROW][C]99[/C][C]3.5[/C][C]5.68944[/C][C]-2.18944[/C][/ROW]
[ROW][C]100[/C][C]2.5[/C][C]6.40891[/C][C]-3.90891[/C][/ROW]
[ROW][C]101[/C][C]5.5[/C][C]4.32727[/C][C]1.17273[/C][/ROW]
[ROW][C]102[/C][C]8[/C][C]5.20594[/C][C]2.79406[/C][/ROW]
[ROW][C]103[/C][C]1[/C][C]5.33746[/C][C]-4.33746[/C][/ROW]
[ROW][C]104[/C][C]5[/C][C]5.49405[/C][C]-0.49405[/C][/ROW]
[ROW][C]105[/C][C]4.5[/C][C]6.16856[/C][C]-1.66856[/C][/ROW]
[ROW][C]106[/C][C]3[/C][C]4.98547[/C][C]-1.98547[/C][/ROW]
[ROW][C]107[/C][C]3[/C][C]5.71352[/C][C]-2.71352[/C][/ROW]
[ROW][C]108[/C][C]8[/C][C]6.59265[/C][C]1.40735[/C][/ROW]
[ROW][C]109[/C][C]2.5[/C][C]6.2462[/C][C]-3.7462[/C][/ROW]
[ROW][C]110[/C][C]7[/C][C]6.17291[/C][C]0.82709[/C][/ROW]
[ROW][C]111[/C][C]0[/C][C]5.63102[/C][C]-5.63102[/C][/ROW]
[ROW][C]112[/C][C]1[/C][C]5.58274[/C][C]-4.58274[/C][/ROW]
[ROW][C]113[/C][C]3.5[/C][C]7.33199[/C][C]-3.83199[/C][/ROW]
[ROW][C]114[/C][C]5.5[/C][C]6.41103[/C][C]-0.911029[/C][/ROW]
[ROW][C]115[/C][C]5.5[/C][C]5.82578[/C][C]-0.325779[/C][/ROW]
[ROW][C]116[/C][C]0.5[/C][C]5.64036[/C][C]-5.14036[/C][/ROW]
[ROW][C]117[/C][C]7.5[/C][C]5.84314[/C][C]1.65686[/C][/ROW]
[ROW][C]118[/C][C]9[/C][C]5.54389[/C][C]3.45611[/C][/ROW]
[ROW][C]119[/C][C]9.5[/C][C]6.39258[/C][C]3.10742[/C][/ROW]
[ROW][C]120[/C][C]8.5[/C][C]9.45801[/C][C]-0.958014[/C][/ROW]
[ROW][C]121[/C][C]7[/C][C]5.61588[/C][C]1.38412[/C][/ROW]
[ROW][C]122[/C][C]8[/C][C]7.37542[/C][C]0.624585[/C][/ROW]
[ROW][C]123[/C][C]10[/C][C]7.45194[/C][C]2.54806[/C][/ROW]
[ROW][C]124[/C][C]7[/C][C]8.53967[/C][C]-1.53967[/C][/ROW]
[ROW][C]125[/C][C]8.5[/C][C]5.38782[/C][C]3.11218[/C][/ROW]
[ROW][C]126[/C][C]9[/C][C]7.57764[/C][C]1.42236[/C][/ROW]
[ROW][C]127[/C][C]9.5[/C][C]4.90367[/C][C]4.59633[/C][/ROW]
[ROW][C]128[/C][C]4[/C][C]5.75697[/C][C]-1.75697[/C][/ROW]
[ROW][C]129[/C][C]6[/C][C]5.20933[/C][C]0.790671[/C][/ROW]
[ROW][C]130[/C][C]8[/C][C]5.55698[/C][C]2.44302[/C][/ROW]
[ROW][C]131[/C][C]5.5[/C][C]4.8514[/C][C]0.648602[/C][/ROW]
[ROW][C]132[/C][C]9.5[/C][C]6.36265[/C][C]3.13735[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.47004[/C][C]2.02996[/C][/ROW]
[ROW][C]134[/C][C]7[/C][C]6.25848[/C][C]0.741522[/C][/ROW]
[ROW][C]135[/C][C]7.5[/C][C]7.10193[/C][C]0.398073[/C][/ROW]
[ROW][C]136[/C][C]8[/C][C]4.38954[/C][C]3.61046[/C][/ROW]
[ROW][C]137[/C][C]7[/C][C]4.40662[/C][C]2.59338[/C][/ROW]
[ROW][C]138[/C][C]7[/C][C]5.19451[/C][C]1.80549[/C][/ROW]
[ROW][C]139[/C][C]6[/C][C]6.14306[/C][C]-0.143064[/C][/ROW]
[ROW][C]140[/C][C]10[/C][C]6.02055[/C][C]3.97945[/C][/ROW]
[ROW][C]141[/C][C]2.5[/C][C]4.82831[/C][C]-2.32831[/C][/ROW]
[ROW][C]142[/C][C]9[/C][C]6.42139[/C][C]2.57861[/C][/ROW]
[ROW][C]143[/C][C]8[/C][C]6.46553[/C][C]1.53447[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]5.94009[/C][C]0.0599083[/C][/ROW]
[ROW][C]145[/C][C]8.5[/C][C]4.79181[/C][C]3.70819[/C][/ROW]
[ROW][C]146[/C][C]6[/C][C]3.96393[/C][C]2.03607[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]5.34362[/C][C]3.65638[/C][/ROW]
[ROW][C]148[/C][C]8[/C][C]5.69116[/C][C]2.30884[/C][/ROW]
[ROW][C]149[/C][C]8[/C][C]6.75601[/C][C]1.24399[/C][/ROW]
[ROW][C]150[/C][C]9[/C][C]7.92294[/C][C]1.07706[/C][/ROW]
[ROW][C]151[/C][C]5.5[/C][C]6.36791[/C][C]-0.867906[/C][/ROW]
[ROW][C]152[/C][C]5[/C][C]5.60249[/C][C]-0.602486[/C][/ROW]
[ROW][C]153[/C][C]7[/C][C]6.14824[/C][C]0.851763[/C][/ROW]
[ROW][C]154[/C][C]5.5[/C][C]5.82894[/C][C]-0.328939[/C][/ROW]
[ROW][C]155[/C][C]9[/C][C]6.57198[/C][C]2.42802[/C][/ROW]
[ROW][C]156[/C][C]2[/C][C]5.31407[/C][C]-3.31407[/C][/ROW]
[ROW][C]157[/C][C]8.5[/C][C]6.56926[/C][C]1.93074[/C][/ROW]
[ROW][C]158[/C][C]9[/C][C]6.53021[/C][C]2.46979[/C][/ROW]
[ROW][C]159[/C][C]8.5[/C][C]6.70122[/C][C]1.79878[/C][/ROW]
[ROW][C]160[/C][C]9[/C][C]5.91003[/C][C]3.08997[/C][/ROW]
[ROW][C]161[/C][C]7.5[/C][C]7.25562[/C][C]0.244379[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]7.85833[/C][C]2.14167[/C][/ROW]
[ROW][C]163[/C][C]9[/C][C]6.23442[/C][C]2.76558[/C][/ROW]
[ROW][C]164[/C][C]7.5[/C][C]8.58905[/C][C]-1.08905[/C][/ROW]
[ROW][C]165[/C][C]6[/C][C]6.58955[/C][C]-0.58955[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]8.18195[/C][C]2.31805[/C][/ROW]
[ROW][C]167[/C][C]8.5[/C][C]5.756[/C][C]2.744[/C][/ROW]
[ROW][C]168[/C][C]8[/C][C]6.96874[/C][C]1.03126[/C][/ROW]
[ROW][C]169[/C][C]10[/C][C]5.50834[/C][C]4.49166[/C][/ROW]
[ROW][C]170[/C][C]10.5[/C][C]8.99742[/C][C]1.50258[/C][/ROW]
[ROW][C]171[/C][C]6.5[/C][C]5.26557[/C][C]1.23443[/C][/ROW]
[ROW][C]172[/C][C]9.5[/C][C]7.55775[/C][C]1.94225[/C][/ROW]
[ROW][C]173[/C][C]8.5[/C][C]5.19942[/C][C]3.30058[/C][/ROW]
[ROW][C]174[/C][C]7.5[/C][C]7.19551[/C][C]0.304494[/C][/ROW]
[ROW][C]175[/C][C]5[/C][C]6.93309[/C][C]-1.93309[/C][/ROW]
[ROW][C]176[/C][C]8[/C][C]6.13165[/C][C]1.86835[/C][/ROW]
[ROW][C]177[/C][C]10[/C][C]7.25863[/C][C]2.74137[/C][/ROW]
[ROW][C]178[/C][C]7[/C][C]6.51461[/C][C]0.485387[/C][/ROW]
[ROW][C]179[/C][C]7.5[/C][C]6.53522[/C][C]0.964783[/C][/ROW]
[ROW][C]180[/C][C]7.5[/C][C]6.4313[/C][C]1.0687[/C][/ROW]
[ROW][C]181[/C][C]9.5[/C][C]6.33173[/C][C]3.16827[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]5.49766[/C][C]0.502337[/C][/ROW]
[ROW][C]183[/C][C]10[/C][C]6.27797[/C][C]3.72203[/C][/ROW]
[ROW][C]184[/C][C]7[/C][C]6.55367[/C][C]0.446334[/C][/ROW]
[ROW][C]185[/C][C]3[/C][C]4.15474[/C][C]-1.15474[/C][/ROW]
[ROW][C]186[/C][C]6[/C][C]8.20819[/C][C]-2.20819[/C][/ROW]
[ROW][C]187[/C][C]7[/C][C]6.69327[/C][C]0.306728[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]6.36128[/C][C]3.63872[/C][/ROW]
[ROW][C]189[/C][C]7[/C][C]6.80795[/C][C]0.192045[/C][/ROW]
[ROW][C]190[/C][C]3.5[/C][C]5.99414[/C][C]-2.49414[/C][/ROW]
[ROW][C]191[/C][C]8[/C][C]7.7018[/C][C]0.298195[/C][/ROW]
[ROW][C]192[/C][C]10[/C][C]6.76765[/C][C]3.23235[/C][/ROW]
[ROW][C]193[/C][C]5.5[/C][C]7.25069[/C][C]-1.75069[/C][/ROW]
[ROW][C]194[/C][C]6[/C][C]6.12462[/C][C]-0.124621[/C][/ROW]
[ROW][C]195[/C][C]6.5[/C][C]5.22951[/C][C]1.27049[/C][/ROW]
[ROW][C]196[/C][C]6.5[/C][C]6.41228[/C][C]0.0877213[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]5.58112[/C][C]2.91888[/C][/ROW]
[ROW][C]198[/C][C]4[/C][C]5.93832[/C][C]-1.93832[/C][/ROW]
[ROW][C]199[/C][C]9.5[/C][C]6.46985[/C][C]3.03015[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]6.8381[/C][C]1.1619[/C][/ROW]
[ROW][C]201[/C][C]8.5[/C][C]6.9261[/C][C]1.5739[/C][/ROW]
[ROW][C]202[/C][C]5.5[/C][C]6.77649[/C][C]-1.27649[/C][/ROW]
[ROW][C]203[/C][C]7[/C][C]6.065[/C][C]0.935[/C][/ROW]
[ROW][C]204[/C][C]9[/C][C]6.05178[/C][C]2.94822[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]7.15832[/C][C]0.84168[/C][/ROW]
[ROW][C]206[/C][C]10[/C][C]8.37494[/C][C]1.62506[/C][/ROW]
[ROW][C]207[/C][C]8[/C][C]7.01586[/C][C]0.984144[/C][/ROW]
[ROW][C]208[/C][C]6[/C][C]6.40325[/C][C]-0.403252[/C][/ROW]
[ROW][C]209[/C][C]8[/C][C]6.56241[/C][C]1.43759[/C][/ROW]
[ROW][C]210[/C][C]5[/C][C]4.30706[/C][C]0.692943[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]6.06388[/C][C]2.93612[/C][/ROW]
[ROW][C]212[/C][C]4.5[/C][C]3.95028[/C][C]0.549719[/C][/ROW]
[ROW][C]213[/C][C]8.5[/C][C]6.83015[/C][C]1.66985[/C][/ROW]
[ROW][C]214[/C][C]7[/C][C]5.45442[/C][C]1.54558[/C][/ROW]
[ROW][C]215[/C][C]9.5[/C][C]6.26151[/C][C]3.23849[/C][/ROW]
[ROW][C]216[/C][C]8.5[/C][C]6.16459[/C][C]2.33541[/C][/ROW]
[ROW][C]217[/C][C]7.5[/C][C]6.1246[/C][C]1.3754[/C][/ROW]
[ROW][C]218[/C][C]7.5[/C][C]5.94723[/C][C]1.55277[/C][/ROW]
[ROW][C]219[/C][C]5[/C][C]5.93541[/C][C]-0.935411[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]5.72462[/C][C]1.27538[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]6.92617[/C][C]1.07383[/C][/ROW]
[ROW][C]222[/C][C]5.5[/C][C]5.18123[/C][C]0.318774[/C][/ROW]
[ROW][C]223[/C][C]8.5[/C][C]6.46565[/C][C]2.03435[/C][/ROW]
[ROW][C]224[/C][C]7.5[/C][C]6.34343[/C][C]1.15657[/C][/ROW]
[ROW][C]225[/C][C]9.5[/C][C]5.66476[/C][C]3.83524[/C][/ROW]
[ROW][C]226[/C][C]7[/C][C]5.9127[/C][C]1.0873[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]7.8972[/C][C]0.102801[/C][/ROW]
[ROW][C]228[/C][C]8.5[/C][C]5.48768[/C][C]3.01232[/C][/ROW]
[ROW][C]229[/C][C]3.5[/C][C]5.3394[/C][C]-1.8394[/C][/ROW]
[ROW][C]230[/C][C]6.5[/C][C]6.09698[/C][C]0.403022[/C][/ROW]
[ROW][C]231[/C][C]6.5[/C][C]4.73121[/C][C]1.76879[/C][/ROW]
[ROW][C]232[/C][C]10.5[/C][C]6.47919[/C][C]4.02081[/C][/ROW]
[ROW][C]233[/C][C]8.5[/C][C]6.48609[/C][C]2.01391[/C][/ROW]
[ROW][C]234[/C][C]8[/C][C]5.93233[/C][C]2.06767[/C][/ROW]
[ROW][C]235[/C][C]10[/C][C]5.93707[/C][C]4.06293[/C][/ROW]
[ROW][C]236[/C][C]10[/C][C]6.776[/C][C]3.224[/C][/ROW]
[ROW][C]237[/C][C]9.5[/C][C]6.37981[/C][C]3.12019[/C][/ROW]
[ROW][C]238[/C][C]9[/C][C]4.83287[/C][C]4.16713[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]7.68593[/C][C]2.31407[/C][/ROW]
[ROW][C]240[/C][C]7.5[/C][C]4.69498[/C][C]2.80502[/C][/ROW]
[ROW][C]241[/C][C]4.5[/C][C]4.95707[/C][C]-0.457068[/C][/ROW]
[ROW][C]242[/C][C]4.5[/C][C]4.16331[/C][C]0.336692[/C][/ROW]
[ROW][C]243[/C][C]0.5[/C][C]5.42194[/C][C]-4.92194[/C][/ROW]
[ROW][C]244[/C][C]6.5[/C][C]5.19404[/C][C]1.30596[/C][/ROW]
[ROW][C]245[/C][C]4.5[/C][C]5.11855[/C][C]-0.61855[/C][/ROW]
[ROW][C]246[/C][C]5.5[/C][C]5.84781[/C][C]-0.347811[/C][/ROW]
[ROW][C]247[/C][C]5[/C][C]5.63995[/C][C]-0.639949[/C][/ROW]
[ROW][C]248[/C][C]6[/C][C]6.53277[/C][C]-0.532769[/C][/ROW]
[ROW][C]249[/C][C]4[/C][C]4.96783[/C][C]-0.967826[/C][/ROW]
[ROW][C]250[/C][C]8[/C][C]6.21208[/C][C]1.78792[/C][/ROW]
[ROW][C]251[/C][C]10.5[/C][C]8.4439[/C][C]2.0561[/C][/ROW]
[ROW][C]252[/C][C]8.5[/C][C]6.35625[/C][C]2.14375[/C][/ROW]
[ROW][C]253[/C][C]6.5[/C][C]6.07354[/C][C]0.426458[/C][/ROW]
[ROW][C]254[/C][C]8[/C][C]6.54442[/C][C]1.45558[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]7.58716[/C][C]0.912839[/C][/ROW]
[ROW][C]256[/C][C]5.5[/C][C]5.6405[/C][C]-0.140498[/C][/ROW]
[ROW][C]257[/C][C]7[/C][C]7.35781[/C][C]-0.357806[/C][/ROW]
[ROW][C]258[/C][C]5[/C][C]5.77392[/C][C]-0.773921[/C][/ROW]
[ROW][C]259[/C][C]3.5[/C][C]5.19605[/C][C]-1.69605[/C][/ROW]
[ROW][C]260[/C][C]5[/C][C]6.34952[/C][C]-1.34952[/C][/ROW]
[ROW][C]261[/C][C]9[/C][C]6.71581[/C][C]2.28419[/C][/ROW]
[ROW][C]262[/C][C]8.5[/C][C]7.049[/C][C]1.451[/C][/ROW]
[ROW][C]263[/C][C]5[/C][C]6.33567[/C][C]-1.33567[/C][/ROW]
[ROW][C]264[/C][C]9.5[/C][C]7.62951[/C][C]1.87049[/C][/ROW]
[ROW][C]265[/C][C]3[/C][C]5.56869[/C][C]-2.56869[/C][/ROW]
[ROW][C]266[/C][C]1.5[/C][C]4.43896[/C][C]-2.93896[/C][/ROW]
[ROW][C]267[/C][C]6[/C][C]6.6319[/C][C]-0.631902[/C][/ROW]
[ROW][C]268[/C][C]0.5[/C][C]6.48563[/C][C]-5.98563[/C][/ROW]
[ROW][C]269[/C][C]6.5[/C][C]6.16584[/C][C]0.334164[/C][/ROW]
[ROW][C]270[/C][C]7.5[/C][C]6.67492[/C][C]0.82508[/C][/ROW]
[ROW][C]271[/C][C]4.5[/C][C]5.99515[/C][C]-1.49515[/C][/ROW]
[ROW][C]272[/C][C]8[/C][C]6.25451[/C][C]1.74549[/C][/ROW]
[ROW][C]273[/C][C]9[/C][C]6.69701[/C][C]2.30299[/C][/ROW]
[ROW][C]274[/C][C]7.5[/C][C]6.88244[/C][C]0.617555[/C][/ROW]
[ROW][C]275[/C][C]8.5[/C][C]6.94883[/C][C]1.55117[/C][/ROW]
[ROW][C]276[/C][C]7[/C][C]5.26336[/C][C]1.73664[/C][/ROW]
[ROW][C]277[/C][C]9.5[/C][C]6.52543[/C][C]2.97457[/C][/ROW]
[ROW][C]278[/C][C]6.5[/C][C]6.06554[/C][C]0.434457[/C][/ROW]
[ROW][C]279[/C][C]9.5[/C][C]5.05869[/C][C]4.44131[/C][/ROW]
[ROW][C]280[/C][C]6[/C][C]5.5716[/C][C]0.428399[/C][/ROW]
[ROW][C]281[/C][C]8[/C][C]5.89883[/C][C]2.10117[/C][/ROW]
[ROW][C]282[/C][C]9.5[/C][C]7.56516[/C][C]1.93484[/C][/ROW]
[ROW][C]283[/C][C]8[/C][C]6.12672[/C][C]1.87328[/C][/ROW]
[ROW][C]284[/C][C]8[/C][C]6.41082[/C][C]1.58918[/C][/ROW]
[ROW][C]285[/C][C]9[/C][C]6.95699[/C][C]2.04301[/C][/ROW]
[ROW][C]286[/C][C]5[/C][C]5.8062[/C][C]-0.806197[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&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
17.57.80061-0.300614
22.56.48228-3.98228
365.974130.0258672
46.56.8011-0.301102
516.23422-5.23422
616.45804-5.45804
75.55.97341-0.473409
88.56.598041.90196
96.56.79841-0.298411
104.55.80207-1.30207
1126.11443-4.11443
1256.30655-1.30655
130.55.83976-5.33976
1454.678090.321905
1556.91587-1.91587
162.55.18207-2.68207
1754.158240.841765
185.56.49175-0.991754
193.56.07716-2.57716
2036.49766-3.49766
2144.65723-0.657227
220.54.5183-4.0183
236.55.443651.05635
244.55.65063-1.15063
257.55.741511.75849
265.56.53646-1.03646
2745.93687-1.93687
287.57.387170.11283
2977.36916-0.36916
3046.74533-2.74533
315.55.427650.0723549
322.55.46007-2.96007
335.56.67846-1.17846
340.55.69181-5.19181
353.55.80668-2.30668
362.54.48315-1.98315
374.55.43375-0.93375
384.55.46995-0.969951
394.55.98493-1.48493
4065.052220.94778
412.56.71795-4.21795
4256.49685-1.49685
4306.12147-6.12147
4456.35532-1.35532
456.55.485161.01484
4655.53661-0.536607
4764.893231.10677
484.56.84319-2.34319
495.55.94724-0.447244
5016.09945-5.09945
517.55.65791.8421
5264.758591.24141
5355.73131-0.731307
5415.47956-4.47956
5555.32913-0.32913
566.55.757260.742744
5775.463691.53631
584.56.01389-1.51389
5905.14964-5.14964
608.55.566582.93342
613.54.63239-1.13239
627.57.099440.400558
633.57.14324-3.64324
6465.842320.157679
651.55.79054-4.29054
6696.810412.18959
673.56.71636-3.21636
683.55.38232-1.88232
6946.62838-2.62838
706.57.59334-1.09334
717.55.154682.34532
7266.87272-0.872723
7357.36713-2.36713
745.55.497060.00293609
753.57.26912-3.76912
767.57.495420.00458378
7715.86665-4.86665
786.55.518590.981406
796.56.50304-0.00303994
806.55.870520.629484
8177.38661-0.386606
823.55.65018-2.15018
831.56.08931-4.58931
8446.70543-2.70543
857.55.781261.71874
864.56.69821-2.19821
8705.50767-5.50767
883.56.6082-3.1082
895.57.23057-1.73057
9055.905-0.904997
914.55.40284-0.902836
922.56.60209-4.10209
937.56.60650.893504
9476.349590.650405
9505.37046-5.37046
964.57.35164-2.85164
9736.68155-3.68155
981.56.10327-4.60327
993.55.68944-2.18944
1002.56.40891-3.90891
1015.54.327271.17273
10285.205942.79406
10315.33746-4.33746
10455.49405-0.49405
1054.56.16856-1.66856
10634.98547-1.98547
10735.71352-2.71352
10886.592651.40735
1092.56.2462-3.7462
11076.172910.82709
11105.63102-5.63102
11215.58274-4.58274
1133.57.33199-3.83199
1145.56.41103-0.911029
1155.55.82578-0.325779
1160.55.64036-5.14036
1177.55.843141.65686
11895.543893.45611
1199.56.392583.10742
1208.59.45801-0.958014
12175.615881.38412
12287.375420.624585
123107.451942.54806
12478.53967-1.53967
1258.55.387823.11218
12697.577641.42236
1279.54.903674.59633
12845.75697-1.75697
12965.209330.790671
13085.556982.44302
1315.54.85140.648602
1329.56.362653.13735
1337.55.470042.02996
13476.258480.741522
1357.57.101930.398073
13684.389543.61046
13774.406622.59338
13875.194511.80549
13966.14306-0.143064
140106.020553.97945
1412.54.82831-2.32831
14296.421392.57861
14386.465531.53447
14465.940090.0599083
1458.54.791813.70819
14663.963932.03607
14795.343623.65638
14885.691162.30884
14986.756011.24399
15097.922941.07706
1515.56.36791-0.867906
15255.60249-0.602486
15376.148240.851763
1545.55.82894-0.328939
15596.571982.42802
15625.31407-3.31407
1578.56.569261.93074
15896.530212.46979
1598.56.701221.79878
16095.910033.08997
1617.57.255620.244379
162107.858332.14167
16396.234422.76558
1647.58.58905-1.08905
16566.58955-0.58955
16610.58.181952.31805
1678.55.7562.744
16886.968741.03126
169105.508344.49166
17010.58.997421.50258
1716.55.265571.23443
1729.57.557751.94225
1738.55.199423.30058
1747.57.195510.304494
17556.93309-1.93309
17686.131651.86835
177107.258632.74137
17876.514610.485387
1797.56.535220.964783
1807.56.43131.0687
1819.56.331733.16827
18265.497660.502337
183106.277973.72203
18476.553670.446334
18534.15474-1.15474
18668.20819-2.20819
18776.693270.306728
188106.361283.63872
18976.807950.192045
1903.55.99414-2.49414
19187.70180.298195
192106.767653.23235
1935.57.25069-1.75069
19466.12462-0.124621
1956.55.229511.27049
1966.56.412280.0877213
1978.55.581122.91888
19845.93832-1.93832
1999.56.469853.03015
20086.83811.1619
2018.56.92611.5739
2025.56.77649-1.27649
20376.0650.935
20496.051782.94822
20587.158320.84168
206108.374941.62506
20787.015860.984144
20866.40325-0.403252
20986.562411.43759
21054.307060.692943
21196.063882.93612
2124.53.950280.549719
2138.56.830151.66985
21475.454421.54558
2159.56.261513.23849
2168.56.164592.33541
2177.56.12461.3754
2187.55.947231.55277
21955.93541-0.935411
22075.724621.27538
22186.926171.07383
2225.55.181230.318774
2238.56.465652.03435
2247.56.343431.15657
2259.55.664763.83524
22675.91271.0873
22787.89720.102801
2288.55.487683.01232
2293.55.3394-1.8394
2306.56.096980.403022
2316.54.731211.76879
23210.56.479194.02081
2338.56.486092.01391
23485.932332.06767
235105.937074.06293
236106.7763.224
2379.56.379813.12019
23894.832874.16713
239107.685932.31407
2407.54.694982.80502
2414.54.95707-0.457068
2424.54.163310.336692
2430.55.42194-4.92194
2446.55.194041.30596
2454.55.11855-0.61855
2465.55.84781-0.347811
24755.63995-0.639949
24866.53277-0.532769
24944.96783-0.967826
25086.212081.78792
25110.58.44392.0561
2528.56.356252.14375
2536.56.073540.426458
25486.544421.45558
2558.57.587160.912839
2565.55.6405-0.140498
25777.35781-0.357806
25855.77392-0.773921
2593.55.19605-1.69605
26056.34952-1.34952
26196.715812.28419
2628.57.0491.451
26356.33567-1.33567
2649.57.629511.87049
26535.56869-2.56869
2661.54.43896-2.93896
26766.6319-0.631902
2680.56.48563-5.98563
2696.56.165840.334164
2707.56.674920.82508
2714.55.99515-1.49515
27286.254511.74549
27396.697012.30299
2747.56.882440.617555
2758.56.948831.55117
27675.263361.73664
2779.56.525432.97457
2786.56.065540.434457
2799.55.058694.44131
28065.57160.428399
28185.898832.10117
2829.57.565161.93484
28386.126721.87328
28486.410821.58918
28596.956992.04301
28655.8062-0.806197






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.8939210.2121580.106079
140.8085760.3828470.191424
150.7970340.4059310.202966
160.7055580.5888840.294442
170.5999580.8000840.400042
180.5028680.9942650.497132
190.4279660.8559330.572034
200.3414430.6828870.658557
210.2648590.5297180.735141
220.2559580.5119170.744042
230.1905590.3811180.809441
240.1411330.2822650.858867
250.1533560.3067130.846644
260.1538130.3076270.846187
270.1145330.2290660.885467
280.08636460.1727290.913635
290.1107650.2215310.889235
300.09635680.1927140.903643
310.07103420.1420680.928966
320.1472560.2945110.852744
330.1182750.2365490.881725
340.1494940.2989880.850506
350.1202560.2405120.879744
360.1363770.2727550.863623
370.1129560.2259120.887044
380.09112830.1822570.908872
390.0701390.1402780.929861
400.06325830.1265170.936742
410.07352090.1470420.926479
420.05990560.1198110.940094
430.09816080.1963220.901839
440.08033430.1606690.919666
450.09496460.1899290.905035
460.07770660.1554130.922293
470.06556260.1311250.934437
480.05524750.1104950.944752
490.05315010.10630.94685
500.1144570.2289130.885543
510.1627110.3254230.837289
520.1575390.3150780.842461
530.1309370.2618730.869063
540.1510570.3021150.848943
550.1393050.2786110.860695
560.1420730.2841470.857927
570.1833540.3667090.816646
580.1638550.3277110.836145
590.3492190.6984390.650781
600.4498650.899730.550135
610.4090550.8181090.590945
620.4120170.8240340.587983
630.4132850.826570.586715
640.3831490.7662970.616851
650.442640.8852790.55736
660.4813860.9627730.518614
670.4826450.9652890.517355
680.4499250.8998490.550075
690.4485710.8971410.551429
700.4243680.8487360.575632
710.4264040.8528070.573596
720.3871270.7742530.612873
730.3736820.7473630.626318
740.351660.7033210.64834
750.3441990.6883970.655801
760.3372070.6744140.662793
770.4543340.9086680.545666
780.4239510.8479010.576049
790.3909850.781970.609015
800.3694340.7388670.630566
810.3560420.7120850.643958
820.3511340.7022690.648866
830.4160890.8321780.583911
840.4044310.8088610.595569
850.4001240.8002470.599876
860.3789880.7579760.621012
870.4996390.9992780.500361
880.5280150.9439710.471985
890.5031820.9936370.496818
900.4696570.9393140.530343
910.4365070.8730140.563493
920.4698020.9396050.530198
930.4585860.9171720.541414
940.4639190.9278390.536081
950.6162430.7675140.383757
960.6114950.777010.388505
970.6399780.7200440.360022
980.7071470.5857070.292853
990.6968970.6062060.303103
1000.7397320.5205350.260268
1010.7438450.512310.256155
1020.7989250.4021510.201075
1030.867310.265380.13269
1040.8555880.2888230.144412
1050.8448950.3102110.155105
1060.8437420.3125160.156258
1070.8621240.2757520.137876
1080.8738670.2522670.126133
1090.9001210.1997580.0998788
1100.8942910.2114180.105709
1110.9605980.07880420.0394021
1120.9761850.04762990.0238149
1130.9822630.03547420.0177371
1140.9811010.03779780.0188989
1150.9793810.04123840.0206192
1160.9892640.02147270.0107363
1170.9910440.01791250.00895623
1180.9944190.01116280.00558138
1190.9965910.006818450.00340923
1200.996430.007140920.00357046
1210.9967270.006546750.00327338
1220.9963520.007295760.00364788
1230.9972430.005514260.00275713
1240.9970870.005826950.00291347
1250.9985860.002828180.00141409
1260.9985470.002905390.0014527
1270.9997240.000551740.00027587
1280.9997040.0005925360.000296268
1290.9996230.0007542520.000377126
1300.9996330.0007342330.000367117
1310.9995060.0009884870.000494243
1320.9996380.000723840.00036192
1330.9996320.0007358460.000367923
1340.9995350.0009297680.000464884
1350.9994080.001183960.000591978
1360.999570.0008600670.000430034
1370.9995620.0008750090.000437504
1380.9995190.0009611770.000480588
1390.9993560.001288740.000644372
1400.9996930.0006144310.000307215
1410.9996880.0006244050.000312203
1420.9997260.0005470810.00027354
1430.9996750.00064910.00032455
1440.9995850.0008295610.00041478
1450.999690.000620820.00031041
1460.9996030.00079430.00039715
1470.9997340.0005313670.000265683
1480.9997340.0005314370.000265718
1490.9996780.0006440070.000322004
1500.9996160.0007675060.000383753
1510.9995260.0009488760.000474438
1520.9994160.001168170.000584086
1530.9992430.001513640.00075682
1540.9990570.001886320.000943158
1550.9990230.001953540.00097677
1560.999640.0007201840.000360092
1570.9995980.0008043610.000402181
1580.9995910.000818930.000409465
1590.9995080.0009842320.000492116
1600.9996530.0006941810.00034709
1610.9995820.000836220.00041811
1620.9995470.0009066080.000453304
1630.9996170.000765940.00038297
1640.9996090.0007814050.000390703
1650.9994990.001002840.000501421
1660.9995350.0009298440.000464922
1670.9995710.0008584560.000429228
1680.9994390.001121310.000560655
1690.9999170.0001664678.32337e-05
1700.9999010.0001976289.8814e-05
1710.9998790.0002415710.000120785
1720.9998650.0002709560.000135478
1730.9998930.0002148490.000107425
1740.9998580.0002842660.000142133
1750.9998830.0002333650.000116683
1760.9998550.0002890150.000144508
1770.999860.0002794340.000139717
1780.9998270.000345370.000172685
1790.999760.0004794690.000239735
1800.999670.0006601350.000330067
1810.9997210.0005581060.000279053
1820.9996070.0007857390.00039287
1830.999730.0005401370.000270069
1840.9996820.0006365760.000318288
1850.9995780.0008430840.000421542
1860.9996910.0006174550.000308727
1870.9996240.0007515560.000375778
1880.9997140.0005718750.000285938
1890.9996580.0006840420.000342021
1900.999910.0001792578.96285e-05
1910.9998860.0002279990.000113999
1920.9998960.0002070660.000103533
1930.9999290.0001425867.1293e-05
1940.9999160.0001675998.37996e-05
1950.9998840.0002318920.000115946
1960.999830.0003408640.000170432
1970.9998170.0003664280.000183214
1980.9998650.0002699060.000134953
1990.9998560.0002874410.000143721
2000.9997990.000401350.000200675
2010.999720.0005596730.000279836
2020.9997320.0005350440.000267522
2030.999640.0007195530.000359776
2040.9996880.0006239030.000311951
2050.9995910.0008177870.000408894
2060.9995020.0009969770.000498489
2070.9992940.001412670.000706337
2080.9991120.001775950.000887975
2090.9988640.002271720.00113586
2100.9984310.003138120.00156906
2110.9989520.002096470.00104824
2120.9989040.00219270.00109635
2130.9987310.002537920.00126896
2140.9984060.003187880.00159394
2150.9981390.003721080.00186054
2160.9979180.004163360.00208168
2170.9976570.004685140.00234257
2180.996890.006220830.00311042
2190.9957520.008496110.00424805
2200.9943280.01134310.00567153
2210.9924080.01518330.00759167
2220.9897720.0204560.010228
2230.9882320.02353630.0117682
2240.9846820.03063620.0153181
2250.9845050.03098910.0154945
2260.9824310.0351380.017569
2270.9795110.04097750.0204888
2280.9812010.03759830.0187991
2290.9825180.03496430.0174822
2300.9775020.04499660.0224983
2310.9752770.04944540.0247227
2320.9790730.04185320.0209266
2330.9769840.04603290.0230165
2340.970510.05897910.0294896
2350.987890.02422070.0121104
2360.9951720.009656380.00482819
2370.9951230.009753070.00487653
2380.995750.008500910.00425045
2390.9963320.007335740.00366787
2400.9962240.007551310.00377566
2410.9943660.01126780.00563389
2420.9932130.01357350.00678673
2430.9956080.008783850.00439192
2440.9934510.01309830.00654915
2450.9914790.0170430.00852149
2460.9899120.02017590.0100879
2470.9864250.02715080.0135754
2480.98150.03700020.0185001
2490.9739470.05210650.0260532
2500.9666790.06664150.0333207
2510.9540340.09193240.0459662
2520.9627280.07454350.0372718
2530.9469660.1060680.0530342
2540.936650.1267010.0633503
2550.9128660.1742670.0871335
2560.929440.1411210.0705604
2570.9096370.1807270.0903634
2580.8774950.245010.122505
2590.8401060.3197870.159894
2600.7954820.4090360.204518
2610.7994430.4011130.200557
2620.814310.3713810.18569
2630.7597920.4804170.240208
2640.6892940.6214120.310706
2650.653870.6922590.34613
2660.8499880.3000230.150012
2670.7888360.4223280.211164
2680.9987060.002587140.00129357
2690.9990310.001938970.000969483
2700.9988760.002248010.001124
2710.9984720.003056330.00152817
2720.9940090.0119820.00599099
2730.9790480.04190490.0209524

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.893921 & 0.212158 & 0.106079 \tabularnewline
14 & 0.808576 & 0.382847 & 0.191424 \tabularnewline
15 & 0.797034 & 0.405931 & 0.202966 \tabularnewline
16 & 0.705558 & 0.588884 & 0.294442 \tabularnewline
17 & 0.599958 & 0.800084 & 0.400042 \tabularnewline
18 & 0.502868 & 0.994265 & 0.497132 \tabularnewline
19 & 0.427966 & 0.855933 & 0.572034 \tabularnewline
20 & 0.341443 & 0.682887 & 0.658557 \tabularnewline
21 & 0.264859 & 0.529718 & 0.735141 \tabularnewline
22 & 0.255958 & 0.511917 & 0.744042 \tabularnewline
23 & 0.190559 & 0.381118 & 0.809441 \tabularnewline
24 & 0.141133 & 0.282265 & 0.858867 \tabularnewline
25 & 0.153356 & 0.306713 & 0.846644 \tabularnewline
26 & 0.153813 & 0.307627 & 0.846187 \tabularnewline
27 & 0.114533 & 0.229066 & 0.885467 \tabularnewline
28 & 0.0863646 & 0.172729 & 0.913635 \tabularnewline
29 & 0.110765 & 0.221531 & 0.889235 \tabularnewline
30 & 0.0963568 & 0.192714 & 0.903643 \tabularnewline
31 & 0.0710342 & 0.142068 & 0.928966 \tabularnewline
32 & 0.147256 & 0.294511 & 0.852744 \tabularnewline
33 & 0.118275 & 0.236549 & 0.881725 \tabularnewline
34 & 0.149494 & 0.298988 & 0.850506 \tabularnewline
35 & 0.120256 & 0.240512 & 0.879744 \tabularnewline
36 & 0.136377 & 0.272755 & 0.863623 \tabularnewline
37 & 0.112956 & 0.225912 & 0.887044 \tabularnewline
38 & 0.0911283 & 0.182257 & 0.908872 \tabularnewline
39 & 0.070139 & 0.140278 & 0.929861 \tabularnewline
40 & 0.0632583 & 0.126517 & 0.936742 \tabularnewline
41 & 0.0735209 & 0.147042 & 0.926479 \tabularnewline
42 & 0.0599056 & 0.119811 & 0.940094 \tabularnewline
43 & 0.0981608 & 0.196322 & 0.901839 \tabularnewline
44 & 0.0803343 & 0.160669 & 0.919666 \tabularnewline
45 & 0.0949646 & 0.189929 & 0.905035 \tabularnewline
46 & 0.0777066 & 0.155413 & 0.922293 \tabularnewline
47 & 0.0655626 & 0.131125 & 0.934437 \tabularnewline
48 & 0.0552475 & 0.110495 & 0.944752 \tabularnewline
49 & 0.0531501 & 0.1063 & 0.94685 \tabularnewline
50 & 0.114457 & 0.228913 & 0.885543 \tabularnewline
51 & 0.162711 & 0.325423 & 0.837289 \tabularnewline
52 & 0.157539 & 0.315078 & 0.842461 \tabularnewline
53 & 0.130937 & 0.261873 & 0.869063 \tabularnewline
54 & 0.151057 & 0.302115 & 0.848943 \tabularnewline
55 & 0.139305 & 0.278611 & 0.860695 \tabularnewline
56 & 0.142073 & 0.284147 & 0.857927 \tabularnewline
57 & 0.183354 & 0.366709 & 0.816646 \tabularnewline
58 & 0.163855 & 0.327711 & 0.836145 \tabularnewline
59 & 0.349219 & 0.698439 & 0.650781 \tabularnewline
60 & 0.449865 & 0.89973 & 0.550135 \tabularnewline
61 & 0.409055 & 0.818109 & 0.590945 \tabularnewline
62 & 0.412017 & 0.824034 & 0.587983 \tabularnewline
63 & 0.413285 & 0.82657 & 0.586715 \tabularnewline
64 & 0.383149 & 0.766297 & 0.616851 \tabularnewline
65 & 0.44264 & 0.885279 & 0.55736 \tabularnewline
66 & 0.481386 & 0.962773 & 0.518614 \tabularnewline
67 & 0.482645 & 0.965289 & 0.517355 \tabularnewline
68 & 0.449925 & 0.899849 & 0.550075 \tabularnewline
69 & 0.448571 & 0.897141 & 0.551429 \tabularnewline
70 & 0.424368 & 0.848736 & 0.575632 \tabularnewline
71 & 0.426404 & 0.852807 & 0.573596 \tabularnewline
72 & 0.387127 & 0.774253 & 0.612873 \tabularnewline
73 & 0.373682 & 0.747363 & 0.626318 \tabularnewline
74 & 0.35166 & 0.703321 & 0.64834 \tabularnewline
75 & 0.344199 & 0.688397 & 0.655801 \tabularnewline
76 & 0.337207 & 0.674414 & 0.662793 \tabularnewline
77 & 0.454334 & 0.908668 & 0.545666 \tabularnewline
78 & 0.423951 & 0.847901 & 0.576049 \tabularnewline
79 & 0.390985 & 0.78197 & 0.609015 \tabularnewline
80 & 0.369434 & 0.738867 & 0.630566 \tabularnewline
81 & 0.356042 & 0.712085 & 0.643958 \tabularnewline
82 & 0.351134 & 0.702269 & 0.648866 \tabularnewline
83 & 0.416089 & 0.832178 & 0.583911 \tabularnewline
84 & 0.404431 & 0.808861 & 0.595569 \tabularnewline
85 & 0.400124 & 0.800247 & 0.599876 \tabularnewline
86 & 0.378988 & 0.757976 & 0.621012 \tabularnewline
87 & 0.499639 & 0.999278 & 0.500361 \tabularnewline
88 & 0.528015 & 0.943971 & 0.471985 \tabularnewline
89 & 0.503182 & 0.993637 & 0.496818 \tabularnewline
90 & 0.469657 & 0.939314 & 0.530343 \tabularnewline
91 & 0.436507 & 0.873014 & 0.563493 \tabularnewline
92 & 0.469802 & 0.939605 & 0.530198 \tabularnewline
93 & 0.458586 & 0.917172 & 0.541414 \tabularnewline
94 & 0.463919 & 0.927839 & 0.536081 \tabularnewline
95 & 0.616243 & 0.767514 & 0.383757 \tabularnewline
96 & 0.611495 & 0.77701 & 0.388505 \tabularnewline
97 & 0.639978 & 0.720044 & 0.360022 \tabularnewline
98 & 0.707147 & 0.585707 & 0.292853 \tabularnewline
99 & 0.696897 & 0.606206 & 0.303103 \tabularnewline
100 & 0.739732 & 0.520535 & 0.260268 \tabularnewline
101 & 0.743845 & 0.51231 & 0.256155 \tabularnewline
102 & 0.798925 & 0.402151 & 0.201075 \tabularnewline
103 & 0.86731 & 0.26538 & 0.13269 \tabularnewline
104 & 0.855588 & 0.288823 & 0.144412 \tabularnewline
105 & 0.844895 & 0.310211 & 0.155105 \tabularnewline
106 & 0.843742 & 0.312516 & 0.156258 \tabularnewline
107 & 0.862124 & 0.275752 & 0.137876 \tabularnewline
108 & 0.873867 & 0.252267 & 0.126133 \tabularnewline
109 & 0.900121 & 0.199758 & 0.0998788 \tabularnewline
110 & 0.894291 & 0.211418 & 0.105709 \tabularnewline
111 & 0.960598 & 0.0788042 & 0.0394021 \tabularnewline
112 & 0.976185 & 0.0476299 & 0.0238149 \tabularnewline
113 & 0.982263 & 0.0354742 & 0.0177371 \tabularnewline
114 & 0.981101 & 0.0377978 & 0.0188989 \tabularnewline
115 & 0.979381 & 0.0412384 & 0.0206192 \tabularnewline
116 & 0.989264 & 0.0214727 & 0.0107363 \tabularnewline
117 & 0.991044 & 0.0179125 & 0.00895623 \tabularnewline
118 & 0.994419 & 0.0111628 & 0.00558138 \tabularnewline
119 & 0.996591 & 0.00681845 & 0.00340923 \tabularnewline
120 & 0.99643 & 0.00714092 & 0.00357046 \tabularnewline
121 & 0.996727 & 0.00654675 & 0.00327338 \tabularnewline
122 & 0.996352 & 0.00729576 & 0.00364788 \tabularnewline
123 & 0.997243 & 0.00551426 & 0.00275713 \tabularnewline
124 & 0.997087 & 0.00582695 & 0.00291347 \tabularnewline
125 & 0.998586 & 0.00282818 & 0.00141409 \tabularnewline
126 & 0.998547 & 0.00290539 & 0.0014527 \tabularnewline
127 & 0.999724 & 0.00055174 & 0.00027587 \tabularnewline
128 & 0.999704 & 0.000592536 & 0.000296268 \tabularnewline
129 & 0.999623 & 0.000754252 & 0.000377126 \tabularnewline
130 & 0.999633 & 0.000734233 & 0.000367117 \tabularnewline
131 & 0.999506 & 0.000988487 & 0.000494243 \tabularnewline
132 & 0.999638 & 0.00072384 & 0.00036192 \tabularnewline
133 & 0.999632 & 0.000735846 & 0.000367923 \tabularnewline
134 & 0.999535 & 0.000929768 & 0.000464884 \tabularnewline
135 & 0.999408 & 0.00118396 & 0.000591978 \tabularnewline
136 & 0.99957 & 0.000860067 & 0.000430034 \tabularnewline
137 & 0.999562 & 0.000875009 & 0.000437504 \tabularnewline
138 & 0.999519 & 0.000961177 & 0.000480588 \tabularnewline
139 & 0.999356 & 0.00128874 & 0.000644372 \tabularnewline
140 & 0.999693 & 0.000614431 & 0.000307215 \tabularnewline
141 & 0.999688 & 0.000624405 & 0.000312203 \tabularnewline
142 & 0.999726 & 0.000547081 & 0.00027354 \tabularnewline
143 & 0.999675 & 0.0006491 & 0.00032455 \tabularnewline
144 & 0.999585 & 0.000829561 & 0.00041478 \tabularnewline
145 & 0.99969 & 0.00062082 & 0.00031041 \tabularnewline
146 & 0.999603 & 0.0007943 & 0.00039715 \tabularnewline
147 & 0.999734 & 0.000531367 & 0.000265683 \tabularnewline
148 & 0.999734 & 0.000531437 & 0.000265718 \tabularnewline
149 & 0.999678 & 0.000644007 & 0.000322004 \tabularnewline
150 & 0.999616 & 0.000767506 & 0.000383753 \tabularnewline
151 & 0.999526 & 0.000948876 & 0.000474438 \tabularnewline
152 & 0.999416 & 0.00116817 & 0.000584086 \tabularnewline
153 & 0.999243 & 0.00151364 & 0.00075682 \tabularnewline
154 & 0.999057 & 0.00188632 & 0.000943158 \tabularnewline
155 & 0.999023 & 0.00195354 & 0.00097677 \tabularnewline
156 & 0.99964 & 0.000720184 & 0.000360092 \tabularnewline
157 & 0.999598 & 0.000804361 & 0.000402181 \tabularnewline
158 & 0.999591 & 0.00081893 & 0.000409465 \tabularnewline
159 & 0.999508 & 0.000984232 & 0.000492116 \tabularnewline
160 & 0.999653 & 0.000694181 & 0.00034709 \tabularnewline
161 & 0.999582 & 0.00083622 & 0.00041811 \tabularnewline
162 & 0.999547 & 0.000906608 & 0.000453304 \tabularnewline
163 & 0.999617 & 0.00076594 & 0.00038297 \tabularnewline
164 & 0.999609 & 0.000781405 & 0.000390703 \tabularnewline
165 & 0.999499 & 0.00100284 & 0.000501421 \tabularnewline
166 & 0.999535 & 0.000929844 & 0.000464922 \tabularnewline
167 & 0.999571 & 0.000858456 & 0.000429228 \tabularnewline
168 & 0.999439 & 0.00112131 & 0.000560655 \tabularnewline
169 & 0.999917 & 0.000166467 & 8.32337e-05 \tabularnewline
170 & 0.999901 & 0.000197628 & 9.8814e-05 \tabularnewline
171 & 0.999879 & 0.000241571 & 0.000120785 \tabularnewline
172 & 0.999865 & 0.000270956 & 0.000135478 \tabularnewline
173 & 0.999893 & 0.000214849 & 0.000107425 \tabularnewline
174 & 0.999858 & 0.000284266 & 0.000142133 \tabularnewline
175 & 0.999883 & 0.000233365 & 0.000116683 \tabularnewline
176 & 0.999855 & 0.000289015 & 0.000144508 \tabularnewline
177 & 0.99986 & 0.000279434 & 0.000139717 \tabularnewline
178 & 0.999827 & 0.00034537 & 0.000172685 \tabularnewline
179 & 0.99976 & 0.000479469 & 0.000239735 \tabularnewline
180 & 0.99967 & 0.000660135 & 0.000330067 \tabularnewline
181 & 0.999721 & 0.000558106 & 0.000279053 \tabularnewline
182 & 0.999607 & 0.000785739 & 0.00039287 \tabularnewline
183 & 0.99973 & 0.000540137 & 0.000270069 \tabularnewline
184 & 0.999682 & 0.000636576 & 0.000318288 \tabularnewline
185 & 0.999578 & 0.000843084 & 0.000421542 \tabularnewline
186 & 0.999691 & 0.000617455 & 0.000308727 \tabularnewline
187 & 0.999624 & 0.000751556 & 0.000375778 \tabularnewline
188 & 0.999714 & 0.000571875 & 0.000285938 \tabularnewline
189 & 0.999658 & 0.000684042 & 0.000342021 \tabularnewline
190 & 0.99991 & 0.000179257 & 8.96285e-05 \tabularnewline
191 & 0.999886 & 0.000227999 & 0.000113999 \tabularnewline
192 & 0.999896 & 0.000207066 & 0.000103533 \tabularnewline
193 & 0.999929 & 0.000142586 & 7.1293e-05 \tabularnewline
194 & 0.999916 & 0.000167599 & 8.37996e-05 \tabularnewline
195 & 0.999884 & 0.000231892 & 0.000115946 \tabularnewline
196 & 0.99983 & 0.000340864 & 0.000170432 \tabularnewline
197 & 0.999817 & 0.000366428 & 0.000183214 \tabularnewline
198 & 0.999865 & 0.000269906 & 0.000134953 \tabularnewline
199 & 0.999856 & 0.000287441 & 0.000143721 \tabularnewline
200 & 0.999799 & 0.00040135 & 0.000200675 \tabularnewline
201 & 0.99972 & 0.000559673 & 0.000279836 \tabularnewline
202 & 0.999732 & 0.000535044 & 0.000267522 \tabularnewline
203 & 0.99964 & 0.000719553 & 0.000359776 \tabularnewline
204 & 0.999688 & 0.000623903 & 0.000311951 \tabularnewline
205 & 0.999591 & 0.000817787 & 0.000408894 \tabularnewline
206 & 0.999502 & 0.000996977 & 0.000498489 \tabularnewline
207 & 0.999294 & 0.00141267 & 0.000706337 \tabularnewline
208 & 0.999112 & 0.00177595 & 0.000887975 \tabularnewline
209 & 0.998864 & 0.00227172 & 0.00113586 \tabularnewline
210 & 0.998431 & 0.00313812 & 0.00156906 \tabularnewline
211 & 0.998952 & 0.00209647 & 0.00104824 \tabularnewline
212 & 0.998904 & 0.0021927 & 0.00109635 \tabularnewline
213 & 0.998731 & 0.00253792 & 0.00126896 \tabularnewline
214 & 0.998406 & 0.00318788 & 0.00159394 \tabularnewline
215 & 0.998139 & 0.00372108 & 0.00186054 \tabularnewline
216 & 0.997918 & 0.00416336 & 0.00208168 \tabularnewline
217 & 0.997657 & 0.00468514 & 0.00234257 \tabularnewline
218 & 0.99689 & 0.00622083 & 0.00311042 \tabularnewline
219 & 0.995752 & 0.00849611 & 0.00424805 \tabularnewline
220 & 0.994328 & 0.0113431 & 0.00567153 \tabularnewline
221 & 0.992408 & 0.0151833 & 0.00759167 \tabularnewline
222 & 0.989772 & 0.020456 & 0.010228 \tabularnewline
223 & 0.988232 & 0.0235363 & 0.0117682 \tabularnewline
224 & 0.984682 & 0.0306362 & 0.0153181 \tabularnewline
225 & 0.984505 & 0.0309891 & 0.0154945 \tabularnewline
226 & 0.982431 & 0.035138 & 0.017569 \tabularnewline
227 & 0.979511 & 0.0409775 & 0.0204888 \tabularnewline
228 & 0.981201 & 0.0375983 & 0.0187991 \tabularnewline
229 & 0.982518 & 0.0349643 & 0.0174822 \tabularnewline
230 & 0.977502 & 0.0449966 & 0.0224983 \tabularnewline
231 & 0.975277 & 0.0494454 & 0.0247227 \tabularnewline
232 & 0.979073 & 0.0418532 & 0.0209266 \tabularnewline
233 & 0.976984 & 0.0460329 & 0.0230165 \tabularnewline
234 & 0.97051 & 0.0589791 & 0.0294896 \tabularnewline
235 & 0.98789 & 0.0242207 & 0.0121104 \tabularnewline
236 & 0.995172 & 0.00965638 & 0.00482819 \tabularnewline
237 & 0.995123 & 0.00975307 & 0.00487653 \tabularnewline
238 & 0.99575 & 0.00850091 & 0.00425045 \tabularnewline
239 & 0.996332 & 0.00733574 & 0.00366787 \tabularnewline
240 & 0.996224 & 0.00755131 & 0.00377566 \tabularnewline
241 & 0.994366 & 0.0112678 & 0.00563389 \tabularnewline
242 & 0.993213 & 0.0135735 & 0.00678673 \tabularnewline
243 & 0.995608 & 0.00878385 & 0.00439192 \tabularnewline
244 & 0.993451 & 0.0130983 & 0.00654915 \tabularnewline
245 & 0.991479 & 0.017043 & 0.00852149 \tabularnewline
246 & 0.989912 & 0.0201759 & 0.0100879 \tabularnewline
247 & 0.986425 & 0.0271508 & 0.0135754 \tabularnewline
248 & 0.9815 & 0.0370002 & 0.0185001 \tabularnewline
249 & 0.973947 & 0.0521065 & 0.0260532 \tabularnewline
250 & 0.966679 & 0.0666415 & 0.0333207 \tabularnewline
251 & 0.954034 & 0.0919324 & 0.0459662 \tabularnewline
252 & 0.962728 & 0.0745435 & 0.0372718 \tabularnewline
253 & 0.946966 & 0.106068 & 0.0530342 \tabularnewline
254 & 0.93665 & 0.126701 & 0.0633503 \tabularnewline
255 & 0.912866 & 0.174267 & 0.0871335 \tabularnewline
256 & 0.92944 & 0.141121 & 0.0705604 \tabularnewline
257 & 0.909637 & 0.180727 & 0.0903634 \tabularnewline
258 & 0.877495 & 0.24501 & 0.122505 \tabularnewline
259 & 0.840106 & 0.319787 & 0.159894 \tabularnewline
260 & 0.795482 & 0.409036 & 0.204518 \tabularnewline
261 & 0.799443 & 0.401113 & 0.200557 \tabularnewline
262 & 0.81431 & 0.371381 & 0.18569 \tabularnewline
263 & 0.759792 & 0.480417 & 0.240208 \tabularnewline
264 & 0.689294 & 0.621412 & 0.310706 \tabularnewline
265 & 0.65387 & 0.692259 & 0.34613 \tabularnewline
266 & 0.849988 & 0.300023 & 0.150012 \tabularnewline
267 & 0.788836 & 0.422328 & 0.211164 \tabularnewline
268 & 0.998706 & 0.00258714 & 0.00129357 \tabularnewline
269 & 0.999031 & 0.00193897 & 0.000969483 \tabularnewline
270 & 0.998876 & 0.00224801 & 0.001124 \tabularnewline
271 & 0.998472 & 0.00305633 & 0.00152817 \tabularnewline
272 & 0.994009 & 0.011982 & 0.00599099 \tabularnewline
273 & 0.979048 & 0.0419049 & 0.0209524 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&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]0.893921[/C][C]0.212158[/C][C]0.106079[/C][/ROW]
[ROW][C]14[/C][C]0.808576[/C][C]0.382847[/C][C]0.191424[/C][/ROW]
[ROW][C]15[/C][C]0.797034[/C][C]0.405931[/C][C]0.202966[/C][/ROW]
[ROW][C]16[/C][C]0.705558[/C][C]0.588884[/C][C]0.294442[/C][/ROW]
[ROW][C]17[/C][C]0.599958[/C][C]0.800084[/C][C]0.400042[/C][/ROW]
[ROW][C]18[/C][C]0.502868[/C][C]0.994265[/C][C]0.497132[/C][/ROW]
[ROW][C]19[/C][C]0.427966[/C][C]0.855933[/C][C]0.572034[/C][/ROW]
[ROW][C]20[/C][C]0.341443[/C][C]0.682887[/C][C]0.658557[/C][/ROW]
[ROW][C]21[/C][C]0.264859[/C][C]0.529718[/C][C]0.735141[/C][/ROW]
[ROW][C]22[/C][C]0.255958[/C][C]0.511917[/C][C]0.744042[/C][/ROW]
[ROW][C]23[/C][C]0.190559[/C][C]0.381118[/C][C]0.809441[/C][/ROW]
[ROW][C]24[/C][C]0.141133[/C][C]0.282265[/C][C]0.858867[/C][/ROW]
[ROW][C]25[/C][C]0.153356[/C][C]0.306713[/C][C]0.846644[/C][/ROW]
[ROW][C]26[/C][C]0.153813[/C][C]0.307627[/C][C]0.846187[/C][/ROW]
[ROW][C]27[/C][C]0.114533[/C][C]0.229066[/C][C]0.885467[/C][/ROW]
[ROW][C]28[/C][C]0.0863646[/C][C]0.172729[/C][C]0.913635[/C][/ROW]
[ROW][C]29[/C][C]0.110765[/C][C]0.221531[/C][C]0.889235[/C][/ROW]
[ROW][C]30[/C][C]0.0963568[/C][C]0.192714[/C][C]0.903643[/C][/ROW]
[ROW][C]31[/C][C]0.0710342[/C][C]0.142068[/C][C]0.928966[/C][/ROW]
[ROW][C]32[/C][C]0.147256[/C][C]0.294511[/C][C]0.852744[/C][/ROW]
[ROW][C]33[/C][C]0.118275[/C][C]0.236549[/C][C]0.881725[/C][/ROW]
[ROW][C]34[/C][C]0.149494[/C][C]0.298988[/C][C]0.850506[/C][/ROW]
[ROW][C]35[/C][C]0.120256[/C][C]0.240512[/C][C]0.879744[/C][/ROW]
[ROW][C]36[/C][C]0.136377[/C][C]0.272755[/C][C]0.863623[/C][/ROW]
[ROW][C]37[/C][C]0.112956[/C][C]0.225912[/C][C]0.887044[/C][/ROW]
[ROW][C]38[/C][C]0.0911283[/C][C]0.182257[/C][C]0.908872[/C][/ROW]
[ROW][C]39[/C][C]0.070139[/C][C]0.140278[/C][C]0.929861[/C][/ROW]
[ROW][C]40[/C][C]0.0632583[/C][C]0.126517[/C][C]0.936742[/C][/ROW]
[ROW][C]41[/C][C]0.0735209[/C][C]0.147042[/C][C]0.926479[/C][/ROW]
[ROW][C]42[/C][C]0.0599056[/C][C]0.119811[/C][C]0.940094[/C][/ROW]
[ROW][C]43[/C][C]0.0981608[/C][C]0.196322[/C][C]0.901839[/C][/ROW]
[ROW][C]44[/C][C]0.0803343[/C][C]0.160669[/C][C]0.919666[/C][/ROW]
[ROW][C]45[/C][C]0.0949646[/C][C]0.189929[/C][C]0.905035[/C][/ROW]
[ROW][C]46[/C][C]0.0777066[/C][C]0.155413[/C][C]0.922293[/C][/ROW]
[ROW][C]47[/C][C]0.0655626[/C][C]0.131125[/C][C]0.934437[/C][/ROW]
[ROW][C]48[/C][C]0.0552475[/C][C]0.110495[/C][C]0.944752[/C][/ROW]
[ROW][C]49[/C][C]0.0531501[/C][C]0.1063[/C][C]0.94685[/C][/ROW]
[ROW][C]50[/C][C]0.114457[/C][C]0.228913[/C][C]0.885543[/C][/ROW]
[ROW][C]51[/C][C]0.162711[/C][C]0.325423[/C][C]0.837289[/C][/ROW]
[ROW][C]52[/C][C]0.157539[/C][C]0.315078[/C][C]0.842461[/C][/ROW]
[ROW][C]53[/C][C]0.130937[/C][C]0.261873[/C][C]0.869063[/C][/ROW]
[ROW][C]54[/C][C]0.151057[/C][C]0.302115[/C][C]0.848943[/C][/ROW]
[ROW][C]55[/C][C]0.139305[/C][C]0.278611[/C][C]0.860695[/C][/ROW]
[ROW][C]56[/C][C]0.142073[/C][C]0.284147[/C][C]0.857927[/C][/ROW]
[ROW][C]57[/C][C]0.183354[/C][C]0.366709[/C][C]0.816646[/C][/ROW]
[ROW][C]58[/C][C]0.163855[/C][C]0.327711[/C][C]0.836145[/C][/ROW]
[ROW][C]59[/C][C]0.349219[/C][C]0.698439[/C][C]0.650781[/C][/ROW]
[ROW][C]60[/C][C]0.449865[/C][C]0.89973[/C][C]0.550135[/C][/ROW]
[ROW][C]61[/C][C]0.409055[/C][C]0.818109[/C][C]0.590945[/C][/ROW]
[ROW][C]62[/C][C]0.412017[/C][C]0.824034[/C][C]0.587983[/C][/ROW]
[ROW][C]63[/C][C]0.413285[/C][C]0.82657[/C][C]0.586715[/C][/ROW]
[ROW][C]64[/C][C]0.383149[/C][C]0.766297[/C][C]0.616851[/C][/ROW]
[ROW][C]65[/C][C]0.44264[/C][C]0.885279[/C][C]0.55736[/C][/ROW]
[ROW][C]66[/C][C]0.481386[/C][C]0.962773[/C][C]0.518614[/C][/ROW]
[ROW][C]67[/C][C]0.482645[/C][C]0.965289[/C][C]0.517355[/C][/ROW]
[ROW][C]68[/C][C]0.449925[/C][C]0.899849[/C][C]0.550075[/C][/ROW]
[ROW][C]69[/C][C]0.448571[/C][C]0.897141[/C][C]0.551429[/C][/ROW]
[ROW][C]70[/C][C]0.424368[/C][C]0.848736[/C][C]0.575632[/C][/ROW]
[ROW][C]71[/C][C]0.426404[/C][C]0.852807[/C][C]0.573596[/C][/ROW]
[ROW][C]72[/C][C]0.387127[/C][C]0.774253[/C][C]0.612873[/C][/ROW]
[ROW][C]73[/C][C]0.373682[/C][C]0.747363[/C][C]0.626318[/C][/ROW]
[ROW][C]74[/C][C]0.35166[/C][C]0.703321[/C][C]0.64834[/C][/ROW]
[ROW][C]75[/C][C]0.344199[/C][C]0.688397[/C][C]0.655801[/C][/ROW]
[ROW][C]76[/C][C]0.337207[/C][C]0.674414[/C][C]0.662793[/C][/ROW]
[ROW][C]77[/C][C]0.454334[/C][C]0.908668[/C][C]0.545666[/C][/ROW]
[ROW][C]78[/C][C]0.423951[/C][C]0.847901[/C][C]0.576049[/C][/ROW]
[ROW][C]79[/C][C]0.390985[/C][C]0.78197[/C][C]0.609015[/C][/ROW]
[ROW][C]80[/C][C]0.369434[/C][C]0.738867[/C][C]0.630566[/C][/ROW]
[ROW][C]81[/C][C]0.356042[/C][C]0.712085[/C][C]0.643958[/C][/ROW]
[ROW][C]82[/C][C]0.351134[/C][C]0.702269[/C][C]0.648866[/C][/ROW]
[ROW][C]83[/C][C]0.416089[/C][C]0.832178[/C][C]0.583911[/C][/ROW]
[ROW][C]84[/C][C]0.404431[/C][C]0.808861[/C][C]0.595569[/C][/ROW]
[ROW][C]85[/C][C]0.400124[/C][C]0.800247[/C][C]0.599876[/C][/ROW]
[ROW][C]86[/C][C]0.378988[/C][C]0.757976[/C][C]0.621012[/C][/ROW]
[ROW][C]87[/C][C]0.499639[/C][C]0.999278[/C][C]0.500361[/C][/ROW]
[ROW][C]88[/C][C]0.528015[/C][C]0.943971[/C][C]0.471985[/C][/ROW]
[ROW][C]89[/C][C]0.503182[/C][C]0.993637[/C][C]0.496818[/C][/ROW]
[ROW][C]90[/C][C]0.469657[/C][C]0.939314[/C][C]0.530343[/C][/ROW]
[ROW][C]91[/C][C]0.436507[/C][C]0.873014[/C][C]0.563493[/C][/ROW]
[ROW][C]92[/C][C]0.469802[/C][C]0.939605[/C][C]0.530198[/C][/ROW]
[ROW][C]93[/C][C]0.458586[/C][C]0.917172[/C][C]0.541414[/C][/ROW]
[ROW][C]94[/C][C]0.463919[/C][C]0.927839[/C][C]0.536081[/C][/ROW]
[ROW][C]95[/C][C]0.616243[/C][C]0.767514[/C][C]0.383757[/C][/ROW]
[ROW][C]96[/C][C]0.611495[/C][C]0.77701[/C][C]0.388505[/C][/ROW]
[ROW][C]97[/C][C]0.639978[/C][C]0.720044[/C][C]0.360022[/C][/ROW]
[ROW][C]98[/C][C]0.707147[/C][C]0.585707[/C][C]0.292853[/C][/ROW]
[ROW][C]99[/C][C]0.696897[/C][C]0.606206[/C][C]0.303103[/C][/ROW]
[ROW][C]100[/C][C]0.739732[/C][C]0.520535[/C][C]0.260268[/C][/ROW]
[ROW][C]101[/C][C]0.743845[/C][C]0.51231[/C][C]0.256155[/C][/ROW]
[ROW][C]102[/C][C]0.798925[/C][C]0.402151[/C][C]0.201075[/C][/ROW]
[ROW][C]103[/C][C]0.86731[/C][C]0.26538[/C][C]0.13269[/C][/ROW]
[ROW][C]104[/C][C]0.855588[/C][C]0.288823[/C][C]0.144412[/C][/ROW]
[ROW][C]105[/C][C]0.844895[/C][C]0.310211[/C][C]0.155105[/C][/ROW]
[ROW][C]106[/C][C]0.843742[/C][C]0.312516[/C][C]0.156258[/C][/ROW]
[ROW][C]107[/C][C]0.862124[/C][C]0.275752[/C][C]0.137876[/C][/ROW]
[ROW][C]108[/C][C]0.873867[/C][C]0.252267[/C][C]0.126133[/C][/ROW]
[ROW][C]109[/C][C]0.900121[/C][C]0.199758[/C][C]0.0998788[/C][/ROW]
[ROW][C]110[/C][C]0.894291[/C][C]0.211418[/C][C]0.105709[/C][/ROW]
[ROW][C]111[/C][C]0.960598[/C][C]0.0788042[/C][C]0.0394021[/C][/ROW]
[ROW][C]112[/C][C]0.976185[/C][C]0.0476299[/C][C]0.0238149[/C][/ROW]
[ROW][C]113[/C][C]0.982263[/C][C]0.0354742[/C][C]0.0177371[/C][/ROW]
[ROW][C]114[/C][C]0.981101[/C][C]0.0377978[/C][C]0.0188989[/C][/ROW]
[ROW][C]115[/C][C]0.979381[/C][C]0.0412384[/C][C]0.0206192[/C][/ROW]
[ROW][C]116[/C][C]0.989264[/C][C]0.0214727[/C][C]0.0107363[/C][/ROW]
[ROW][C]117[/C][C]0.991044[/C][C]0.0179125[/C][C]0.00895623[/C][/ROW]
[ROW][C]118[/C][C]0.994419[/C][C]0.0111628[/C][C]0.00558138[/C][/ROW]
[ROW][C]119[/C][C]0.996591[/C][C]0.00681845[/C][C]0.00340923[/C][/ROW]
[ROW][C]120[/C][C]0.99643[/C][C]0.00714092[/C][C]0.00357046[/C][/ROW]
[ROW][C]121[/C][C]0.996727[/C][C]0.00654675[/C][C]0.00327338[/C][/ROW]
[ROW][C]122[/C][C]0.996352[/C][C]0.00729576[/C][C]0.00364788[/C][/ROW]
[ROW][C]123[/C][C]0.997243[/C][C]0.00551426[/C][C]0.00275713[/C][/ROW]
[ROW][C]124[/C][C]0.997087[/C][C]0.00582695[/C][C]0.00291347[/C][/ROW]
[ROW][C]125[/C][C]0.998586[/C][C]0.00282818[/C][C]0.00141409[/C][/ROW]
[ROW][C]126[/C][C]0.998547[/C][C]0.00290539[/C][C]0.0014527[/C][/ROW]
[ROW][C]127[/C][C]0.999724[/C][C]0.00055174[/C][C]0.00027587[/C][/ROW]
[ROW][C]128[/C][C]0.999704[/C][C]0.000592536[/C][C]0.000296268[/C][/ROW]
[ROW][C]129[/C][C]0.999623[/C][C]0.000754252[/C][C]0.000377126[/C][/ROW]
[ROW][C]130[/C][C]0.999633[/C][C]0.000734233[/C][C]0.000367117[/C][/ROW]
[ROW][C]131[/C][C]0.999506[/C][C]0.000988487[/C][C]0.000494243[/C][/ROW]
[ROW][C]132[/C][C]0.999638[/C][C]0.00072384[/C][C]0.00036192[/C][/ROW]
[ROW][C]133[/C][C]0.999632[/C][C]0.000735846[/C][C]0.000367923[/C][/ROW]
[ROW][C]134[/C][C]0.999535[/C][C]0.000929768[/C][C]0.000464884[/C][/ROW]
[ROW][C]135[/C][C]0.999408[/C][C]0.00118396[/C][C]0.000591978[/C][/ROW]
[ROW][C]136[/C][C]0.99957[/C][C]0.000860067[/C][C]0.000430034[/C][/ROW]
[ROW][C]137[/C][C]0.999562[/C][C]0.000875009[/C][C]0.000437504[/C][/ROW]
[ROW][C]138[/C][C]0.999519[/C][C]0.000961177[/C][C]0.000480588[/C][/ROW]
[ROW][C]139[/C][C]0.999356[/C][C]0.00128874[/C][C]0.000644372[/C][/ROW]
[ROW][C]140[/C][C]0.999693[/C][C]0.000614431[/C][C]0.000307215[/C][/ROW]
[ROW][C]141[/C][C]0.999688[/C][C]0.000624405[/C][C]0.000312203[/C][/ROW]
[ROW][C]142[/C][C]0.999726[/C][C]0.000547081[/C][C]0.00027354[/C][/ROW]
[ROW][C]143[/C][C]0.999675[/C][C]0.0006491[/C][C]0.00032455[/C][/ROW]
[ROW][C]144[/C][C]0.999585[/C][C]0.000829561[/C][C]0.00041478[/C][/ROW]
[ROW][C]145[/C][C]0.99969[/C][C]0.00062082[/C][C]0.00031041[/C][/ROW]
[ROW][C]146[/C][C]0.999603[/C][C]0.0007943[/C][C]0.00039715[/C][/ROW]
[ROW][C]147[/C][C]0.999734[/C][C]0.000531367[/C][C]0.000265683[/C][/ROW]
[ROW][C]148[/C][C]0.999734[/C][C]0.000531437[/C][C]0.000265718[/C][/ROW]
[ROW][C]149[/C][C]0.999678[/C][C]0.000644007[/C][C]0.000322004[/C][/ROW]
[ROW][C]150[/C][C]0.999616[/C][C]0.000767506[/C][C]0.000383753[/C][/ROW]
[ROW][C]151[/C][C]0.999526[/C][C]0.000948876[/C][C]0.000474438[/C][/ROW]
[ROW][C]152[/C][C]0.999416[/C][C]0.00116817[/C][C]0.000584086[/C][/ROW]
[ROW][C]153[/C][C]0.999243[/C][C]0.00151364[/C][C]0.00075682[/C][/ROW]
[ROW][C]154[/C][C]0.999057[/C][C]0.00188632[/C][C]0.000943158[/C][/ROW]
[ROW][C]155[/C][C]0.999023[/C][C]0.00195354[/C][C]0.00097677[/C][/ROW]
[ROW][C]156[/C][C]0.99964[/C][C]0.000720184[/C][C]0.000360092[/C][/ROW]
[ROW][C]157[/C][C]0.999598[/C][C]0.000804361[/C][C]0.000402181[/C][/ROW]
[ROW][C]158[/C][C]0.999591[/C][C]0.00081893[/C][C]0.000409465[/C][/ROW]
[ROW][C]159[/C][C]0.999508[/C][C]0.000984232[/C][C]0.000492116[/C][/ROW]
[ROW][C]160[/C][C]0.999653[/C][C]0.000694181[/C][C]0.00034709[/C][/ROW]
[ROW][C]161[/C][C]0.999582[/C][C]0.00083622[/C][C]0.00041811[/C][/ROW]
[ROW][C]162[/C][C]0.999547[/C][C]0.000906608[/C][C]0.000453304[/C][/ROW]
[ROW][C]163[/C][C]0.999617[/C][C]0.00076594[/C][C]0.00038297[/C][/ROW]
[ROW][C]164[/C][C]0.999609[/C][C]0.000781405[/C][C]0.000390703[/C][/ROW]
[ROW][C]165[/C][C]0.999499[/C][C]0.00100284[/C][C]0.000501421[/C][/ROW]
[ROW][C]166[/C][C]0.999535[/C][C]0.000929844[/C][C]0.000464922[/C][/ROW]
[ROW][C]167[/C][C]0.999571[/C][C]0.000858456[/C][C]0.000429228[/C][/ROW]
[ROW][C]168[/C][C]0.999439[/C][C]0.00112131[/C][C]0.000560655[/C][/ROW]
[ROW][C]169[/C][C]0.999917[/C][C]0.000166467[/C][C]8.32337e-05[/C][/ROW]
[ROW][C]170[/C][C]0.999901[/C][C]0.000197628[/C][C]9.8814e-05[/C][/ROW]
[ROW][C]171[/C][C]0.999879[/C][C]0.000241571[/C][C]0.000120785[/C][/ROW]
[ROW][C]172[/C][C]0.999865[/C][C]0.000270956[/C][C]0.000135478[/C][/ROW]
[ROW][C]173[/C][C]0.999893[/C][C]0.000214849[/C][C]0.000107425[/C][/ROW]
[ROW][C]174[/C][C]0.999858[/C][C]0.000284266[/C][C]0.000142133[/C][/ROW]
[ROW][C]175[/C][C]0.999883[/C][C]0.000233365[/C][C]0.000116683[/C][/ROW]
[ROW][C]176[/C][C]0.999855[/C][C]0.000289015[/C][C]0.000144508[/C][/ROW]
[ROW][C]177[/C][C]0.99986[/C][C]0.000279434[/C][C]0.000139717[/C][/ROW]
[ROW][C]178[/C][C]0.999827[/C][C]0.00034537[/C][C]0.000172685[/C][/ROW]
[ROW][C]179[/C][C]0.99976[/C][C]0.000479469[/C][C]0.000239735[/C][/ROW]
[ROW][C]180[/C][C]0.99967[/C][C]0.000660135[/C][C]0.000330067[/C][/ROW]
[ROW][C]181[/C][C]0.999721[/C][C]0.000558106[/C][C]0.000279053[/C][/ROW]
[ROW][C]182[/C][C]0.999607[/C][C]0.000785739[/C][C]0.00039287[/C][/ROW]
[ROW][C]183[/C][C]0.99973[/C][C]0.000540137[/C][C]0.000270069[/C][/ROW]
[ROW][C]184[/C][C]0.999682[/C][C]0.000636576[/C][C]0.000318288[/C][/ROW]
[ROW][C]185[/C][C]0.999578[/C][C]0.000843084[/C][C]0.000421542[/C][/ROW]
[ROW][C]186[/C][C]0.999691[/C][C]0.000617455[/C][C]0.000308727[/C][/ROW]
[ROW][C]187[/C][C]0.999624[/C][C]0.000751556[/C][C]0.000375778[/C][/ROW]
[ROW][C]188[/C][C]0.999714[/C][C]0.000571875[/C][C]0.000285938[/C][/ROW]
[ROW][C]189[/C][C]0.999658[/C][C]0.000684042[/C][C]0.000342021[/C][/ROW]
[ROW][C]190[/C][C]0.99991[/C][C]0.000179257[/C][C]8.96285e-05[/C][/ROW]
[ROW][C]191[/C][C]0.999886[/C][C]0.000227999[/C][C]0.000113999[/C][/ROW]
[ROW][C]192[/C][C]0.999896[/C][C]0.000207066[/C][C]0.000103533[/C][/ROW]
[ROW][C]193[/C][C]0.999929[/C][C]0.000142586[/C][C]7.1293e-05[/C][/ROW]
[ROW][C]194[/C][C]0.999916[/C][C]0.000167599[/C][C]8.37996e-05[/C][/ROW]
[ROW][C]195[/C][C]0.999884[/C][C]0.000231892[/C][C]0.000115946[/C][/ROW]
[ROW][C]196[/C][C]0.99983[/C][C]0.000340864[/C][C]0.000170432[/C][/ROW]
[ROW][C]197[/C][C]0.999817[/C][C]0.000366428[/C][C]0.000183214[/C][/ROW]
[ROW][C]198[/C][C]0.999865[/C][C]0.000269906[/C][C]0.000134953[/C][/ROW]
[ROW][C]199[/C][C]0.999856[/C][C]0.000287441[/C][C]0.000143721[/C][/ROW]
[ROW][C]200[/C][C]0.999799[/C][C]0.00040135[/C][C]0.000200675[/C][/ROW]
[ROW][C]201[/C][C]0.99972[/C][C]0.000559673[/C][C]0.000279836[/C][/ROW]
[ROW][C]202[/C][C]0.999732[/C][C]0.000535044[/C][C]0.000267522[/C][/ROW]
[ROW][C]203[/C][C]0.99964[/C][C]0.000719553[/C][C]0.000359776[/C][/ROW]
[ROW][C]204[/C][C]0.999688[/C][C]0.000623903[/C][C]0.000311951[/C][/ROW]
[ROW][C]205[/C][C]0.999591[/C][C]0.000817787[/C][C]0.000408894[/C][/ROW]
[ROW][C]206[/C][C]0.999502[/C][C]0.000996977[/C][C]0.000498489[/C][/ROW]
[ROW][C]207[/C][C]0.999294[/C][C]0.00141267[/C][C]0.000706337[/C][/ROW]
[ROW][C]208[/C][C]0.999112[/C][C]0.00177595[/C][C]0.000887975[/C][/ROW]
[ROW][C]209[/C][C]0.998864[/C][C]0.00227172[/C][C]0.00113586[/C][/ROW]
[ROW][C]210[/C][C]0.998431[/C][C]0.00313812[/C][C]0.00156906[/C][/ROW]
[ROW][C]211[/C][C]0.998952[/C][C]0.00209647[/C][C]0.00104824[/C][/ROW]
[ROW][C]212[/C][C]0.998904[/C][C]0.0021927[/C][C]0.00109635[/C][/ROW]
[ROW][C]213[/C][C]0.998731[/C][C]0.00253792[/C][C]0.00126896[/C][/ROW]
[ROW][C]214[/C][C]0.998406[/C][C]0.00318788[/C][C]0.00159394[/C][/ROW]
[ROW][C]215[/C][C]0.998139[/C][C]0.00372108[/C][C]0.00186054[/C][/ROW]
[ROW][C]216[/C][C]0.997918[/C][C]0.00416336[/C][C]0.00208168[/C][/ROW]
[ROW][C]217[/C][C]0.997657[/C][C]0.00468514[/C][C]0.00234257[/C][/ROW]
[ROW][C]218[/C][C]0.99689[/C][C]0.00622083[/C][C]0.00311042[/C][/ROW]
[ROW][C]219[/C][C]0.995752[/C][C]0.00849611[/C][C]0.00424805[/C][/ROW]
[ROW][C]220[/C][C]0.994328[/C][C]0.0113431[/C][C]0.00567153[/C][/ROW]
[ROW][C]221[/C][C]0.992408[/C][C]0.0151833[/C][C]0.00759167[/C][/ROW]
[ROW][C]222[/C][C]0.989772[/C][C]0.020456[/C][C]0.010228[/C][/ROW]
[ROW][C]223[/C][C]0.988232[/C][C]0.0235363[/C][C]0.0117682[/C][/ROW]
[ROW][C]224[/C][C]0.984682[/C][C]0.0306362[/C][C]0.0153181[/C][/ROW]
[ROW][C]225[/C][C]0.984505[/C][C]0.0309891[/C][C]0.0154945[/C][/ROW]
[ROW][C]226[/C][C]0.982431[/C][C]0.035138[/C][C]0.017569[/C][/ROW]
[ROW][C]227[/C][C]0.979511[/C][C]0.0409775[/C][C]0.0204888[/C][/ROW]
[ROW][C]228[/C][C]0.981201[/C][C]0.0375983[/C][C]0.0187991[/C][/ROW]
[ROW][C]229[/C][C]0.982518[/C][C]0.0349643[/C][C]0.0174822[/C][/ROW]
[ROW][C]230[/C][C]0.977502[/C][C]0.0449966[/C][C]0.0224983[/C][/ROW]
[ROW][C]231[/C][C]0.975277[/C][C]0.0494454[/C][C]0.0247227[/C][/ROW]
[ROW][C]232[/C][C]0.979073[/C][C]0.0418532[/C][C]0.0209266[/C][/ROW]
[ROW][C]233[/C][C]0.976984[/C][C]0.0460329[/C][C]0.0230165[/C][/ROW]
[ROW][C]234[/C][C]0.97051[/C][C]0.0589791[/C][C]0.0294896[/C][/ROW]
[ROW][C]235[/C][C]0.98789[/C][C]0.0242207[/C][C]0.0121104[/C][/ROW]
[ROW][C]236[/C][C]0.995172[/C][C]0.00965638[/C][C]0.00482819[/C][/ROW]
[ROW][C]237[/C][C]0.995123[/C][C]0.00975307[/C][C]0.00487653[/C][/ROW]
[ROW][C]238[/C][C]0.99575[/C][C]0.00850091[/C][C]0.00425045[/C][/ROW]
[ROW][C]239[/C][C]0.996332[/C][C]0.00733574[/C][C]0.00366787[/C][/ROW]
[ROW][C]240[/C][C]0.996224[/C][C]0.00755131[/C][C]0.00377566[/C][/ROW]
[ROW][C]241[/C][C]0.994366[/C][C]0.0112678[/C][C]0.00563389[/C][/ROW]
[ROW][C]242[/C][C]0.993213[/C][C]0.0135735[/C][C]0.00678673[/C][/ROW]
[ROW][C]243[/C][C]0.995608[/C][C]0.00878385[/C][C]0.00439192[/C][/ROW]
[ROW][C]244[/C][C]0.993451[/C][C]0.0130983[/C][C]0.00654915[/C][/ROW]
[ROW][C]245[/C][C]0.991479[/C][C]0.017043[/C][C]0.00852149[/C][/ROW]
[ROW][C]246[/C][C]0.989912[/C][C]0.0201759[/C][C]0.0100879[/C][/ROW]
[ROW][C]247[/C][C]0.986425[/C][C]0.0271508[/C][C]0.0135754[/C][/ROW]
[ROW][C]248[/C][C]0.9815[/C][C]0.0370002[/C][C]0.0185001[/C][/ROW]
[ROW][C]249[/C][C]0.973947[/C][C]0.0521065[/C][C]0.0260532[/C][/ROW]
[ROW][C]250[/C][C]0.966679[/C][C]0.0666415[/C][C]0.0333207[/C][/ROW]
[ROW][C]251[/C][C]0.954034[/C][C]0.0919324[/C][C]0.0459662[/C][/ROW]
[ROW][C]252[/C][C]0.962728[/C][C]0.0745435[/C][C]0.0372718[/C][/ROW]
[ROW][C]253[/C][C]0.946966[/C][C]0.106068[/C][C]0.0530342[/C][/ROW]
[ROW][C]254[/C][C]0.93665[/C][C]0.126701[/C][C]0.0633503[/C][/ROW]
[ROW][C]255[/C][C]0.912866[/C][C]0.174267[/C][C]0.0871335[/C][/ROW]
[ROW][C]256[/C][C]0.92944[/C][C]0.141121[/C][C]0.0705604[/C][/ROW]
[ROW][C]257[/C][C]0.909637[/C][C]0.180727[/C][C]0.0903634[/C][/ROW]
[ROW][C]258[/C][C]0.877495[/C][C]0.24501[/C][C]0.122505[/C][/ROW]
[ROW][C]259[/C][C]0.840106[/C][C]0.319787[/C][C]0.159894[/C][/ROW]
[ROW][C]260[/C][C]0.795482[/C][C]0.409036[/C][C]0.204518[/C][/ROW]
[ROW][C]261[/C][C]0.799443[/C][C]0.401113[/C][C]0.200557[/C][/ROW]
[ROW][C]262[/C][C]0.81431[/C][C]0.371381[/C][C]0.18569[/C][/ROW]
[ROW][C]263[/C][C]0.759792[/C][C]0.480417[/C][C]0.240208[/C][/ROW]
[ROW][C]264[/C][C]0.689294[/C][C]0.621412[/C][C]0.310706[/C][/ROW]
[ROW][C]265[/C][C]0.65387[/C][C]0.692259[/C][C]0.34613[/C][/ROW]
[ROW][C]266[/C][C]0.849988[/C][C]0.300023[/C][C]0.150012[/C][/ROW]
[ROW][C]267[/C][C]0.788836[/C][C]0.422328[/C][C]0.211164[/C][/ROW]
[ROW][C]268[/C][C]0.998706[/C][C]0.00258714[/C][C]0.00129357[/C][/ROW]
[ROW][C]269[/C][C]0.999031[/C][C]0.00193897[/C][C]0.000969483[/C][/ROW]
[ROW][C]270[/C][C]0.998876[/C][C]0.00224801[/C][C]0.001124[/C][/ROW]
[ROW][C]271[/C][C]0.998472[/C][C]0.00305633[/C][C]0.00152817[/C][/ROW]
[ROW][C]272[/C][C]0.994009[/C][C]0.011982[/C][C]0.00599099[/C][/ROW]
[ROW][C]273[/C][C]0.979048[/C][C]0.0419049[/C][C]0.0209524[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&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
130.8939210.2121580.106079
140.8085760.3828470.191424
150.7970340.4059310.202966
160.7055580.5888840.294442
170.5999580.8000840.400042
180.5028680.9942650.497132
190.4279660.8559330.572034
200.3414430.6828870.658557
210.2648590.5297180.735141
220.2559580.5119170.744042
230.1905590.3811180.809441
240.1411330.2822650.858867
250.1533560.3067130.846644
260.1538130.3076270.846187
270.1145330.2290660.885467
280.08636460.1727290.913635
290.1107650.2215310.889235
300.09635680.1927140.903643
310.07103420.1420680.928966
320.1472560.2945110.852744
330.1182750.2365490.881725
340.1494940.2989880.850506
350.1202560.2405120.879744
360.1363770.2727550.863623
370.1129560.2259120.887044
380.09112830.1822570.908872
390.0701390.1402780.929861
400.06325830.1265170.936742
410.07352090.1470420.926479
420.05990560.1198110.940094
430.09816080.1963220.901839
440.08033430.1606690.919666
450.09496460.1899290.905035
460.07770660.1554130.922293
470.06556260.1311250.934437
480.05524750.1104950.944752
490.05315010.10630.94685
500.1144570.2289130.885543
510.1627110.3254230.837289
520.1575390.3150780.842461
530.1309370.2618730.869063
540.1510570.3021150.848943
550.1393050.2786110.860695
560.1420730.2841470.857927
570.1833540.3667090.816646
580.1638550.3277110.836145
590.3492190.6984390.650781
600.4498650.899730.550135
610.4090550.8181090.590945
620.4120170.8240340.587983
630.4132850.826570.586715
640.3831490.7662970.616851
650.442640.8852790.55736
660.4813860.9627730.518614
670.4826450.9652890.517355
680.4499250.8998490.550075
690.4485710.8971410.551429
700.4243680.8487360.575632
710.4264040.8528070.573596
720.3871270.7742530.612873
730.3736820.7473630.626318
740.351660.7033210.64834
750.3441990.6883970.655801
760.3372070.6744140.662793
770.4543340.9086680.545666
780.4239510.8479010.576049
790.3909850.781970.609015
800.3694340.7388670.630566
810.3560420.7120850.643958
820.3511340.7022690.648866
830.4160890.8321780.583911
840.4044310.8088610.595569
850.4001240.8002470.599876
860.3789880.7579760.621012
870.4996390.9992780.500361
880.5280150.9439710.471985
890.5031820.9936370.496818
900.4696570.9393140.530343
910.4365070.8730140.563493
920.4698020.9396050.530198
930.4585860.9171720.541414
940.4639190.9278390.536081
950.6162430.7675140.383757
960.6114950.777010.388505
970.6399780.7200440.360022
980.7071470.5857070.292853
990.6968970.6062060.303103
1000.7397320.5205350.260268
1010.7438450.512310.256155
1020.7989250.4021510.201075
1030.867310.265380.13269
1040.8555880.2888230.144412
1050.8448950.3102110.155105
1060.8437420.3125160.156258
1070.8621240.2757520.137876
1080.8738670.2522670.126133
1090.9001210.1997580.0998788
1100.8942910.2114180.105709
1110.9605980.07880420.0394021
1120.9761850.04762990.0238149
1130.9822630.03547420.0177371
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1190.9965910.006818450.00340923
1200.996430.007140920.00357046
1210.9967270.006546750.00327338
1220.9963520.007295760.00364788
1230.9972430.005514260.00275713
1240.9970870.005826950.00291347
1250.9985860.002828180.00141409
1260.9985470.002905390.0014527
1270.9997240.000551740.00027587
1280.9997040.0005925360.000296268
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1300.9996330.0007342330.000367117
1310.9995060.0009884870.000494243
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1330.9996320.0007358460.000367923
1340.9995350.0009297680.000464884
1350.9994080.001183960.000591978
1360.999570.0008600670.000430034
1370.9995620.0008750090.000437504
1380.9995190.0009611770.000480588
1390.9993560.001288740.000644372
1400.9996930.0006144310.000307215
1410.9996880.0006244050.000312203
1420.9997260.0005470810.00027354
1430.9996750.00064910.00032455
1440.9995850.0008295610.00041478
1450.999690.000620820.00031041
1460.9996030.00079430.00039715
1470.9997340.0005313670.000265683
1480.9997340.0005314370.000265718
1490.9996780.0006440070.000322004
1500.9996160.0007675060.000383753
1510.9995260.0009488760.000474438
1520.9994160.001168170.000584086
1530.9992430.001513640.00075682
1540.9990570.001886320.000943158
1550.9990230.001953540.00097677
1560.999640.0007201840.000360092
1570.9995980.0008043610.000402181
1580.9995910.000818930.000409465
1590.9995080.0009842320.000492116
1600.9996530.0006941810.00034709
1610.9995820.000836220.00041811
1620.9995470.0009066080.000453304
1630.9996170.000765940.00038297
1640.9996090.0007814050.000390703
1650.9994990.001002840.000501421
1660.9995350.0009298440.000464922
1670.9995710.0008584560.000429228
1680.9994390.001121310.000560655
1690.9999170.0001664678.32337e-05
1700.9999010.0001976289.8814e-05
1710.9998790.0002415710.000120785
1720.9998650.0002709560.000135478
1730.9998930.0002148490.000107425
1740.9998580.0002842660.000142133
1750.9998830.0002333650.000116683
1760.9998550.0002890150.000144508
1770.999860.0002794340.000139717
1780.9998270.000345370.000172685
1790.999760.0004794690.000239735
1800.999670.0006601350.000330067
1810.9997210.0005581060.000279053
1820.9996070.0007857390.00039287
1830.999730.0005401370.000270069
1840.9996820.0006365760.000318288
1850.9995780.0008430840.000421542
1860.9996910.0006174550.000308727
1870.9996240.0007515560.000375778
1880.9997140.0005718750.000285938
1890.9996580.0006840420.000342021
1900.999910.0001792578.96285e-05
1910.9998860.0002279990.000113999
1920.9998960.0002070660.000103533
1930.9999290.0001425867.1293e-05
1940.9999160.0001675998.37996e-05
1950.9998840.0002318920.000115946
1960.999830.0003408640.000170432
1970.9998170.0003664280.000183214
1980.9998650.0002699060.000134953
1990.9998560.0002874410.000143721
2000.9997990.000401350.000200675
2010.999720.0005596730.000279836
2020.9997320.0005350440.000267522
2030.999640.0007195530.000359776
2040.9996880.0006239030.000311951
2050.9995910.0008177870.000408894
2060.9995020.0009969770.000498489
2070.9992940.001412670.000706337
2080.9991120.001775950.000887975
2090.9988640.002271720.00113586
2100.9984310.003138120.00156906
2110.9989520.002096470.00104824
2120.9989040.00219270.00109635
2130.9987310.002537920.00126896
2140.9984060.003187880.00159394
2150.9981390.003721080.00186054
2160.9979180.004163360.00208168
2170.9976570.004685140.00234257
2180.996890.006220830.00311042
2190.9957520.008496110.00424805
2200.9943280.01134310.00567153
2210.9924080.01518330.00759167
2220.9897720.0204560.010228
2230.9882320.02353630.0117682
2240.9846820.03063620.0153181
2250.9845050.03098910.0154945
2260.9824310.0351380.017569
2270.9795110.04097750.0204888
2280.9812010.03759830.0187991
2290.9825180.03496430.0174822
2300.9775020.04499660.0224983
2310.9752770.04944540.0247227
2320.9790730.04185320.0209266
2330.9769840.04603290.0230165
2340.970510.05897910.0294896
2350.987890.02422070.0121104
2360.9951720.009656380.00482819
2370.9951230.009753070.00487653
2380.995750.008500910.00425045
2390.9963320.007335740.00366787
2400.9962240.007551310.00377566
2410.9943660.01126780.00563389
2420.9932130.01357350.00678673
2430.9956080.008783850.00439192
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2450.9914790.0170430.00852149
2460.9899120.02017590.0100879
2470.9864250.02715080.0135754
2480.98150.03700020.0185001
2490.9739470.05210650.0260532
2500.9666790.06664150.0333207
2510.9540340.09193240.0459662
2520.9627280.07454350.0372718
2530.9469660.1060680.0530342
2540.936650.1267010.0633503
2550.9128660.1742670.0871335
2560.929440.1411210.0705604
2570.9096370.1807270.0903634
2580.8774950.245010.122505
2590.8401060.3197870.159894
2600.7954820.4090360.204518
2610.7994430.4011130.200557
2620.814310.3713810.18569
2630.7597920.4804170.240208
2640.6892940.6214120.310706
2650.653870.6922590.34613
2660.8499880.3000230.150012
2670.7888360.4223280.211164
2680.9987060.002587140.00129357
2690.9990310.001938970.000969483
2700.9988760.002248010.001124
2710.9984720.003056330.00152817
2720.9940090.0119820.00599099
2730.9790480.04190490.0209524






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1110.425287NOK
5% type I error level1420.544061NOK
10% type I error level1480.56705NOK

\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 & 111 & 0.425287 & NOK \tabularnewline
5% type I error level & 142 & 0.544061 & NOK \tabularnewline
10% type I error level & 148 & 0.56705 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263590&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]111[/C][C]0.425287[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]142[/C][C]0.544061[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]148[/C][C]0.56705[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263590&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263590&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1110.425287NOK
5% type I error level1420.544061NOK
10% type I error level1480.56705NOK


Figures (Output of Computation)

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Input Parameters & R Code

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