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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 computationTue, 02 Dec 2014 10:56:23 +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/02/t1417518309udbp5l8dxzhjmpg.htm/, Retrieved Thu, 16 May 2024 07:51:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=262485, Retrieved Thu, 16 May 2024 07:51:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact96

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RM D  [Multiple Regression] [] [2014-11-12 15:17:36] [dacad244957cb51472792888970d4390]
-   PD      [Multiple Regression] [] [2014-12-02 10:56:23] [a4daf178ee9972867aacc2039fa7f163] [Current]
-   PD        [Multiple Regression] [] [2014-12-09 09:58:52] [dacad244957cb51472792888970d4390]
- RM D        [Central Tendency] [] [2014-12-09 10:04:13] [dacad244957cb51472792888970d4390]
- RM D        [Central Tendency] [] [2014-12-09 10:04:13] [dacad244957cb51472792888970d4390]
- RM            [Skewness and Kurtosis Test] [] [2014-12-09 11:06:18] [a30ebaf79f34e9d2b1bcdd5006125d11]
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Dataset

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

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 10 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]10 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time10 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 6.69006 + 4.4505jaarInd[t] -1.08891groepn[t] -0.711871gender[t] -0.00340893AMS.I[t] -0.0216481AMS.E[t] + 0.0523085NUMERACYTOT[t] + 0.0441796LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  6.69006 +  4.4505jaarInd[t] -1.08891groepn[t] -0.711871gender[t] -0.00340893AMS.I[t] -0.0216481AMS.E[t] +  0.0523085NUMERACYTOT[t] +  0.0441796LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  6.69006 +  4.4505jaarInd[t] -1.08891groepn[t] -0.711871gender[t] -0.00340893AMS.I[t] -0.0216481AMS.E[t] +  0.0523085NUMERACYTOT[t] +  0.0441796LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 6.69006 + 4.4505jaarInd[t] -1.08891groepn[t] -0.711871gender[t] -0.00340893AMS.I[t] -0.0216481AMS.E[t] + 0.0523085NUMERACYTOT[t] + 0.0441796LFM[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)6.690061.447814.6215.92631e-062.96316e-06
jaarInd4.45050.29979214.857.40449e-373.70225e-37
groepn-1.088910.335209-3.2480.001307230.000653614
gender-0.7118710.297642-2.3920.01745510.00872753
AMS.I-0.003408930.0149121-0.22860.8193510.409676
AMS.E-0.02164810.019027-1.1380.2562320.128116
NUMERACYTOT0.05230850.02833921.8460.06601540.0330077
LFM0.04417960.004315310.245.33858e-212.66929e-21

\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) & 6.69006 & 1.44781 & 4.621 & 5.92631e-06 & 2.96316e-06 \tabularnewline
jaarInd & 4.4505 & 0.299792 & 14.85 & 7.40449e-37 & 3.70225e-37 \tabularnewline
groepn & -1.08891 & 0.335209 & -3.248 & 0.00130723 & 0.000653614 \tabularnewline
gender & -0.711871 & 0.297642 & -2.392 & 0.0174551 & 0.00872753 \tabularnewline
AMS.I & -0.00340893 & 0.0149121 & -0.2286 & 0.819351 & 0.409676 \tabularnewline
AMS.E & -0.0216481 & 0.019027 & -1.138 & 0.256232 & 0.128116 \tabularnewline
NUMERACYTOT & 0.0523085 & 0.0283392 & 1.846 & 0.0660154 & 0.0330077 \tabularnewline
LFM & 0.0441796 & 0.0043153 & 10.24 & 5.33858e-21 & 2.66929e-21 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&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]6.69006[/C][C]1.44781[/C][C]4.621[/C][C]5.92631e-06[/C][C]2.96316e-06[/C][/ROW]
[ROW][C]jaarInd[/C][C]4.4505[/C][C]0.299792[/C][C]14.85[/C][C]7.40449e-37[/C][C]3.70225e-37[/C][/ROW]
[ROW][C]groepn[/C][C]-1.08891[/C][C]0.335209[/C][C]-3.248[/C][C]0.00130723[/C][C]0.000653614[/C][/ROW]
[ROW][C]gender[/C][C]-0.711871[/C][C]0.297642[/C][C]-2.392[/C][C]0.0174551[/C][C]0.00872753[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00340893[/C][C]0.0149121[/C][C]-0.2286[/C][C]0.819351[/C][C]0.409676[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0216481[/C][C]0.019027[/C][C]-1.138[/C][C]0.256232[/C][C]0.128116[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0523085[/C][C]0.0283392[/C][C]1.846[/C][C]0.0660154[/C][C]0.0330077[/C][/ROW]
[ROW][C]LFM[/C][C]0.0441796[/C][C]0.0043153[/C][C]10.24[/C][C]5.33858e-21[/C][C]2.66929e-21[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&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)6.690061.447814.6215.92631e-062.96316e-06
jaarInd4.45050.29979214.857.40449e-373.70225e-37
groepn-1.088910.335209-3.2480.001307230.000653614
gender-0.7118710.297642-2.3920.01745510.00872753
AMS.I-0.003408930.0149121-0.22860.8193510.409676
AMS.E-0.02164810.019027-1.1380.2562320.128116
NUMERACYTOT0.05230850.02833921.8460.06601540.0330077
LFM0.04417960.004315310.245.33858e-212.66929e-21






Multiple Linear Regression - Regression Statistics
Multiple R0.72937
R-squared0.531981
Adjusted R-squared0.519847
F-TEST (value)43.8428
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35206
Sum Squared Residuals1493.68

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.72937 \tabularnewline
R-squared & 0.531981 \tabularnewline
Adjusted R-squared & 0.519847 \tabularnewline
F-TEST (value) & 43.8428 \tabularnewline
F-TEST (DF numerator) & 7 \tabularnewline
F-TEST (DF denominator) & 270 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.35206 \tabularnewline
Sum Squared Residuals & 1493.68 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.72937[/C][/ROW]
[ROW][C]R-squared[/C][C]0.531981[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.519847[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]43.8428[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]7[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]270[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.35206[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1493.68[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&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 R0.72937
R-squared0.531981
Adjusted R-squared0.519847
F-TEST (value)43.8428
F-TEST (DF numerator)7
F-TEST (DF denominator)270
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.35206
Sum Squared Residuals1493.68






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.11140.788647
212.210.64451.55546
312.811.99540.804609
47.411.0458-3.6458
56.710.4318-3.73178
612.613.8288-1.22882
714.811.91432.8857
813.39.406643.89336
911.110.90750.192475
108.212.1235-3.92352
1111.411.7339-0.333889
126.411.0527-4.65271
1310.69.327011.27299
141212.5926-0.592593
156.37.07299-0.772991
1611.39.725011.57499
1711.911.56140.338633
189.310.4716-1.17163
199.611.6178-2.01784
20109.725750.274245
216.410.7271-4.3271
2213.810.92252.87752
2310.814.7286-3.92859
2413.812.38361.41637
2511.711.09290.607079
2610.914.4438-3.54384
2716.112.41963.68036
2813.410.30643.09364
299.911.0507-1.15072
3011.511.37160.128362
318.38.97675-0.676746
3211.712.0041-0.304062
33910.2723-1.27232
349.711.3034-1.60345
3510.89.020371.77963
3610.38.750331.54967
3710.411.0959-0.695907
3812.710.92171.77835
399.311.9103-2.61035
4011.812.0919-0.291895
415.99.73766-3.83766
4211.411.05760.342448
431311.65931.34074
4410.811.5814-0.781391
4512.38.016944.28306
4611.313.3836-2.0836
4711.89.045212.75479
487.99.24655-1.34655
4912.79.203293.49671
5012.39.428762.87124
5111.610.49161.10839
526.77.1887-0.4887
5310.910.9763-0.0762528
5412.112.1158-0.0157928
5513.39.77813.5219
5610.19.716770.383231
575.711.6802-5.98015
5814.310.05324.24678
5987.75610.243905
6013.310.20893.09108
619.312.0059-2.70595
6212.512.25510.244925
637.69.31004-1.71004
6415.913.34032.5597
659.213.3329-4.13286
669.18.448040.651963
6711.112.8223-1.72227
681313.8193-0.819322
6914.512.49872.0013
7012.210.7671.43301
7112.313.2776-0.977559
7211.410.60230.79769
738.89.70871-0.908709
7414.610.11784.48222
7512.610.65981.94025
76NANA0.998415
771310.99822.00179
7812.611.41811.18189
7913.212.29910.900923
809.911.4868-1.58675
817.77.686270.0137252
8210.57.774792.72521
8313.412.45880.94123
8410.916.1716-5.27164
854.35.41036-1.11036
8610.38.781121.51888
8711.89.368492.43151
8811.29.006822.19318
8911.413.1028-1.70284
908.67.14311.4569
9113.29.426513.77349
9212.617.5378-4.9378
935.67.20221-1.60221
949.911.6217-1.7217
958.810.9391-2.13913
967.710.0165-2.31655
97913-3.99999
987.35.74451.5555
9911.47.7023.698
10013.615.8163-2.21629
1017.95.67782.2222
10210.710.72-0.0199941
10310.310.6354-0.335398
1048.39.54417-1.24417
1059.65.037914.56209
10614.215.9341-1.73408
1078.55.061763.43824
10813.518.4768-4.97681
1094.96.79564-1.89564
1106.47.22813-0.82813
1119.69.188630.411369
11211.610.20911.39089
11311.118.1322-7.03218
1144.353.082711.26729
11512.710.0582.64204
11618.116.01652.08347
11717.8517.36420.485818
11816.616.9224-0.322359
11912.613.4619-0.861858
12017.114.67022.42983
12119.118.91250.187527
12216.115.11880.981152
12313.3511.27022.07985
12418.414.09224.30777
12514.717.2889-2.58886
12610.611.3688-0.768782
12712.611.37111.22887
12816.215.64760.552352
12913.610.38923.21084
13018.918.37190.528052
13114.113.82150.278547
13214.515.0085-0.508539
13316.1515.0411.10899
13414.7513.30051.44948
13514.814.56410.235916
13612.4512.20740.242562
13712.659.689612.96039
13817.3518.8809-1.53091
1398.66.291242.30876
14018.416.49071.90934
14116.117.7868-1.68682
14211.69.851.75
14317.7516.98480.765164
14415.2511.8873.36301
14517.6517.47790.172055
14616.3515.0251.32501
14717.6518.1014-0.451406
14813.613.4780.121986
14914.3514.4018-0.0518328
15014.7513.28631.46372
15118.2524.8425-6.59251
1529.98.041871.85813
1531613.74742.25258
15418.2518.6683-0.418306
15516.8515.42341.42656
15614.614.6546-0.0546135
15713.8511.5132.33698
15818.9517.87251.07746
15915.616.9314-1.33143
16014.8517.063-2.21299
16111.759.597752.15225
16218.4516.22942.22065
16315.916.0864-0.186408
16417.110.14616.95394
16516.114.6971.40298
16619.921.0951-1.19505
16710.958.737532.21247
16818.4517.69310.756864
16915.115.2115-0.111472
1701517.8841-2.88406
17111.359.814961.53504
17215.9513.60132.34866
17318.119.9903-1.89034
17414.615.6906-1.09064
17515.416.4473-1.04734
17615.412.3523.04802
17717.618.4983-0.898278
17813.3510.69162.65844
17919.120.151-1.05103
18015.3519.3621-4.01209
1817.69.09378-1.49378
18213.415.5393-2.1393
18313.910.64943.2506
18419.118.77040.329592
18515.2518.8055-3.55545
18612.912.56810.331875
18716.114.3581.742
18817.3519.9355-2.58549
18913.1516.8331-3.68308
19012.1511.92820.221832
19112.615.1905-2.59049
19210.358.865341.48466
19315.418.6654-3.26543
1949.66.477563.12244
19518.218.7114-0.511446
19613.612.78510.814855
19714.8516.4082-1.55819
19814.7514.4260.324036
19914.113.07781.0222
20014.914.13830.761676
20116.2516.6909-0.44085
20219.2518.8040.44602
20313.615.5004-1.90043
20413.613.6404-0.0403802
20515.6516.7918-1.14181
20612.7511.58441.16564
20714.615.1461-0.546115
2089.859.96047-0.110474
20912.658.644374.00563
21019.216.662.54003
21116.617.3791-0.779087
21211.211.4769-0.276851
21315.2516.9501-1.70008
21411.912.3079-0.407898
21513.213.14620.053794
21616.3517.1013-0.751286
21712.410.73651.66354
21815.8514.25781.59219
21918.1519.5518-1.4018
22011.1511.5246-0.374637
22115.6513.32462.32538
22217.7522.2833-4.53326
2237.659.55857-1.90857
22412.3510.9921.35805
22515.613.03432.56572
22619.317.34141.95865
22715.213.47621.72377
22817.115.18291.91714
22915.611.27534.3247
23018.415.3543.04601
23119.0516.53612.51389
23218.5515.21353.33648
23319.119.6116-0.51165
23413.116.3074-3.20736
23512.8515.4174-2.56739
2369.516.3301-6.83009
2374.55.29076-0.790756
23811.8513.016-1.16604
23913.613.51410.0858566
24011.712.5533-0.853281
24112.413.4369-1.03688
24213.3514.7742-1.42423
24311.410.90140.498612
24414.913.29421.60583
24519.922.8507-2.9507
24611.211.3854-0.185396
24714.613.80580.794177
24817.617.7547-0.154671
24914.0513.03221.01777
25016.117.2285-1.12852
25113.3516.5975-3.24748
25211.8512.9448-1.09485
25311.9511.36380.586205
25414.7513.72991.02015
25515.1518.489-3.33903
25613.212.08041.11957
25716.8521.6141-4.76411
2587.8513.4827-5.63266
2597.710.0375-2.33745
26012.619.2684-6.66835
2617.859.40625-1.55625
26210.9513.2547-2.30465
26312.3516.2515-3.90149
2649.959.434340.515657
26514.913.06581.83422
26616.6516.26070.389291
26713.413.7153-0.315294
26813.9512.89521.05478
26915.714.18461.51538
27016.8518.3233-1.4733
27110.9511.076-0.125959
27215.3516.3277-0.977684
27312.210.66271.53734
27415.112.93052.16946
27517.7517.05210.697948
27615.215.6831-0.483122
27714.613.76740.832608
27816.6520.0431-3.39313
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 12.1114 & 0.788647 \tabularnewline
2 & 12.2 & 10.6445 & 1.55546 \tabularnewline
3 & 12.8 & 11.9954 & 0.804609 \tabularnewline
4 & 7.4 & 11.0458 & -3.6458 \tabularnewline
5 & 6.7 & 10.4318 & -3.73178 \tabularnewline
6 & 12.6 & 13.8288 & -1.22882 \tabularnewline
7 & 14.8 & 11.9143 & 2.8857 \tabularnewline
8 & 13.3 & 9.40664 & 3.89336 \tabularnewline
9 & 11.1 & 10.9075 & 0.192475 \tabularnewline
10 & 8.2 & 12.1235 & -3.92352 \tabularnewline
11 & 11.4 & 11.7339 & -0.333889 \tabularnewline
12 & 6.4 & 11.0527 & -4.65271 \tabularnewline
13 & 10.6 & 9.32701 & 1.27299 \tabularnewline
14 & 12 & 12.5926 & -0.592593 \tabularnewline
15 & 6.3 & 7.07299 & -0.772991 \tabularnewline
16 & 11.3 & 9.72501 & 1.57499 \tabularnewline
17 & 11.9 & 11.5614 & 0.338633 \tabularnewline
18 & 9.3 & 10.4716 & -1.17163 \tabularnewline
19 & 9.6 & 11.6178 & -2.01784 \tabularnewline
20 & 10 & 9.72575 & 0.274245 \tabularnewline
21 & 6.4 & 10.7271 & -4.3271 \tabularnewline
22 & 13.8 & 10.9225 & 2.87752 \tabularnewline
23 & 10.8 & 14.7286 & -3.92859 \tabularnewline
24 & 13.8 & 12.3836 & 1.41637 \tabularnewline
25 & 11.7 & 11.0929 & 0.607079 \tabularnewline
26 & 10.9 & 14.4438 & -3.54384 \tabularnewline
27 & 16.1 & 12.4196 & 3.68036 \tabularnewline
28 & 13.4 & 10.3064 & 3.09364 \tabularnewline
29 & 9.9 & 11.0507 & -1.15072 \tabularnewline
30 & 11.5 & 11.3716 & 0.128362 \tabularnewline
31 & 8.3 & 8.97675 & -0.676746 \tabularnewline
32 & 11.7 & 12.0041 & -0.304062 \tabularnewline
33 & 9 & 10.2723 & -1.27232 \tabularnewline
34 & 9.7 & 11.3034 & -1.60345 \tabularnewline
35 & 10.8 & 9.02037 & 1.77963 \tabularnewline
36 & 10.3 & 8.75033 & 1.54967 \tabularnewline
37 & 10.4 & 11.0959 & -0.695907 \tabularnewline
38 & 12.7 & 10.9217 & 1.77835 \tabularnewline
39 & 9.3 & 11.9103 & -2.61035 \tabularnewline
40 & 11.8 & 12.0919 & -0.291895 \tabularnewline
41 & 5.9 & 9.73766 & -3.83766 \tabularnewline
42 & 11.4 & 11.0576 & 0.342448 \tabularnewline
43 & 13 & 11.6593 & 1.34074 \tabularnewline
44 & 10.8 & 11.5814 & -0.781391 \tabularnewline
45 & 12.3 & 8.01694 & 4.28306 \tabularnewline
46 & 11.3 & 13.3836 & -2.0836 \tabularnewline
47 & 11.8 & 9.04521 & 2.75479 \tabularnewline
48 & 7.9 & 9.24655 & -1.34655 \tabularnewline
49 & 12.7 & 9.20329 & 3.49671 \tabularnewline
50 & 12.3 & 9.42876 & 2.87124 \tabularnewline
51 & 11.6 & 10.4916 & 1.10839 \tabularnewline
52 & 6.7 & 7.1887 & -0.4887 \tabularnewline
53 & 10.9 & 10.9763 & -0.0762528 \tabularnewline
54 & 12.1 & 12.1158 & -0.0157928 \tabularnewline
55 & 13.3 & 9.7781 & 3.5219 \tabularnewline
56 & 10.1 & 9.71677 & 0.383231 \tabularnewline
57 & 5.7 & 11.6802 & -5.98015 \tabularnewline
58 & 14.3 & 10.0532 & 4.24678 \tabularnewline
59 & 8 & 7.7561 & 0.243905 \tabularnewline
60 & 13.3 & 10.2089 & 3.09108 \tabularnewline
61 & 9.3 & 12.0059 & -2.70595 \tabularnewline
62 & 12.5 & 12.2551 & 0.244925 \tabularnewline
63 & 7.6 & 9.31004 & -1.71004 \tabularnewline
64 & 15.9 & 13.3403 & 2.5597 \tabularnewline
65 & 9.2 & 13.3329 & -4.13286 \tabularnewline
66 & 9.1 & 8.44804 & 0.651963 \tabularnewline
67 & 11.1 & 12.8223 & -1.72227 \tabularnewline
68 & 13 & 13.8193 & -0.819322 \tabularnewline
69 & 14.5 & 12.4987 & 2.0013 \tabularnewline
70 & 12.2 & 10.767 & 1.43301 \tabularnewline
71 & 12.3 & 13.2776 & -0.977559 \tabularnewline
72 & 11.4 & 10.6023 & 0.79769 \tabularnewline
73 & 8.8 & 9.70871 & -0.908709 \tabularnewline
74 & 14.6 & 10.1178 & 4.48222 \tabularnewline
75 & 12.6 & 10.6598 & 1.94025 \tabularnewline
76 & NA & NA & 0.998415 \tabularnewline
77 & 13 & 10.9982 & 2.00179 \tabularnewline
78 & 12.6 & 11.4181 & 1.18189 \tabularnewline
79 & 13.2 & 12.2991 & 0.900923 \tabularnewline
80 & 9.9 & 11.4868 & -1.58675 \tabularnewline
81 & 7.7 & 7.68627 & 0.0137252 \tabularnewline
82 & 10.5 & 7.77479 & 2.72521 \tabularnewline
83 & 13.4 & 12.4588 & 0.94123 \tabularnewline
84 & 10.9 & 16.1716 & -5.27164 \tabularnewline
85 & 4.3 & 5.41036 & -1.11036 \tabularnewline
86 & 10.3 & 8.78112 & 1.51888 \tabularnewline
87 & 11.8 & 9.36849 & 2.43151 \tabularnewline
88 & 11.2 & 9.00682 & 2.19318 \tabularnewline
89 & 11.4 & 13.1028 & -1.70284 \tabularnewline
90 & 8.6 & 7.1431 & 1.4569 \tabularnewline
91 & 13.2 & 9.42651 & 3.77349 \tabularnewline
92 & 12.6 & 17.5378 & -4.9378 \tabularnewline
93 & 5.6 & 7.20221 & -1.60221 \tabularnewline
94 & 9.9 & 11.6217 & -1.7217 \tabularnewline
95 & 8.8 & 10.9391 & -2.13913 \tabularnewline
96 & 7.7 & 10.0165 & -2.31655 \tabularnewline
97 & 9 & 13 & -3.99999 \tabularnewline
98 & 7.3 & 5.7445 & 1.5555 \tabularnewline
99 & 11.4 & 7.702 & 3.698 \tabularnewline
100 & 13.6 & 15.8163 & -2.21629 \tabularnewline
101 & 7.9 & 5.6778 & 2.2222 \tabularnewline
102 & 10.7 & 10.72 & -0.0199941 \tabularnewline
103 & 10.3 & 10.6354 & -0.335398 \tabularnewline
104 & 8.3 & 9.54417 & -1.24417 \tabularnewline
105 & 9.6 & 5.03791 & 4.56209 \tabularnewline
106 & 14.2 & 15.9341 & -1.73408 \tabularnewline
107 & 8.5 & 5.06176 & 3.43824 \tabularnewline
108 & 13.5 & 18.4768 & -4.97681 \tabularnewline
109 & 4.9 & 6.79564 & -1.89564 \tabularnewline
110 & 6.4 & 7.22813 & -0.82813 \tabularnewline
111 & 9.6 & 9.18863 & 0.411369 \tabularnewline
112 & 11.6 & 10.2091 & 1.39089 \tabularnewline
113 & 11.1 & 18.1322 & -7.03218 \tabularnewline
114 & 4.35 & 3.08271 & 1.26729 \tabularnewline
115 & 12.7 & 10.058 & 2.64204 \tabularnewline
116 & 18.1 & 16.0165 & 2.08347 \tabularnewline
117 & 17.85 & 17.3642 & 0.485818 \tabularnewline
118 & 16.6 & 16.9224 & -0.322359 \tabularnewline
119 & 12.6 & 13.4619 & -0.861858 \tabularnewline
120 & 17.1 & 14.6702 & 2.42983 \tabularnewline
121 & 19.1 & 18.9125 & 0.187527 \tabularnewline
122 & 16.1 & 15.1188 & 0.981152 \tabularnewline
123 & 13.35 & 11.2702 & 2.07985 \tabularnewline
124 & 18.4 & 14.0922 & 4.30777 \tabularnewline
125 & 14.7 & 17.2889 & -2.58886 \tabularnewline
126 & 10.6 & 11.3688 & -0.768782 \tabularnewline
127 & 12.6 & 11.3711 & 1.22887 \tabularnewline
128 & 16.2 & 15.6476 & 0.552352 \tabularnewline
129 & 13.6 & 10.3892 & 3.21084 \tabularnewline
130 & 18.9 & 18.3719 & 0.528052 \tabularnewline
131 & 14.1 & 13.8215 & 0.278547 \tabularnewline
132 & 14.5 & 15.0085 & -0.508539 \tabularnewline
133 & 16.15 & 15.041 & 1.10899 \tabularnewline
134 & 14.75 & 13.3005 & 1.44948 \tabularnewline
135 & 14.8 & 14.5641 & 0.235916 \tabularnewline
136 & 12.45 & 12.2074 & 0.242562 \tabularnewline
137 & 12.65 & 9.68961 & 2.96039 \tabularnewline
138 & 17.35 & 18.8809 & -1.53091 \tabularnewline
139 & 8.6 & 6.29124 & 2.30876 \tabularnewline
140 & 18.4 & 16.4907 & 1.90934 \tabularnewline
141 & 16.1 & 17.7868 & -1.68682 \tabularnewline
142 & 11.6 & 9.85 & 1.75 \tabularnewline
143 & 17.75 & 16.9848 & 0.765164 \tabularnewline
144 & 15.25 & 11.887 & 3.36301 \tabularnewline
145 & 17.65 & 17.4779 & 0.172055 \tabularnewline
146 & 16.35 & 15.025 & 1.32501 \tabularnewline
147 & 17.65 & 18.1014 & -0.451406 \tabularnewline
148 & 13.6 & 13.478 & 0.121986 \tabularnewline
149 & 14.35 & 14.4018 & -0.0518328 \tabularnewline
150 & 14.75 & 13.2863 & 1.46372 \tabularnewline
151 & 18.25 & 24.8425 & -6.59251 \tabularnewline
152 & 9.9 & 8.04187 & 1.85813 \tabularnewline
153 & 16 & 13.7474 & 2.25258 \tabularnewline
154 & 18.25 & 18.6683 & -0.418306 \tabularnewline
155 & 16.85 & 15.4234 & 1.42656 \tabularnewline
156 & 14.6 & 14.6546 & -0.0546135 \tabularnewline
157 & 13.85 & 11.513 & 2.33698 \tabularnewline
158 & 18.95 & 17.8725 & 1.07746 \tabularnewline
159 & 15.6 & 16.9314 & -1.33143 \tabularnewline
160 & 14.85 & 17.063 & -2.21299 \tabularnewline
161 & 11.75 & 9.59775 & 2.15225 \tabularnewline
162 & 18.45 & 16.2294 & 2.22065 \tabularnewline
163 & 15.9 & 16.0864 & -0.186408 \tabularnewline
164 & 17.1 & 10.1461 & 6.95394 \tabularnewline
165 & 16.1 & 14.697 & 1.40298 \tabularnewline
166 & 19.9 & 21.0951 & -1.19505 \tabularnewline
167 & 10.95 & 8.73753 & 2.21247 \tabularnewline
168 & 18.45 & 17.6931 & 0.756864 \tabularnewline
169 & 15.1 & 15.2115 & -0.111472 \tabularnewline
170 & 15 & 17.8841 & -2.88406 \tabularnewline
171 & 11.35 & 9.81496 & 1.53504 \tabularnewline
172 & 15.95 & 13.6013 & 2.34866 \tabularnewline
173 & 18.1 & 19.9903 & -1.89034 \tabularnewline
174 & 14.6 & 15.6906 & -1.09064 \tabularnewline
175 & 15.4 & 16.4473 & -1.04734 \tabularnewline
176 & 15.4 & 12.352 & 3.04802 \tabularnewline
177 & 17.6 & 18.4983 & -0.898278 \tabularnewline
178 & 13.35 & 10.6916 & 2.65844 \tabularnewline
179 & 19.1 & 20.151 & -1.05103 \tabularnewline
180 & 15.35 & 19.3621 & -4.01209 \tabularnewline
181 & 7.6 & 9.09378 & -1.49378 \tabularnewline
182 & 13.4 & 15.5393 & -2.1393 \tabularnewline
183 & 13.9 & 10.6494 & 3.2506 \tabularnewline
184 & 19.1 & 18.7704 & 0.329592 \tabularnewline
185 & 15.25 & 18.8055 & -3.55545 \tabularnewline
186 & 12.9 & 12.5681 & 0.331875 \tabularnewline
187 & 16.1 & 14.358 & 1.742 \tabularnewline
188 & 17.35 & 19.9355 & -2.58549 \tabularnewline
189 & 13.15 & 16.8331 & -3.68308 \tabularnewline
190 & 12.15 & 11.9282 & 0.221832 \tabularnewline
191 & 12.6 & 15.1905 & -2.59049 \tabularnewline
192 & 10.35 & 8.86534 & 1.48466 \tabularnewline
193 & 15.4 & 18.6654 & -3.26543 \tabularnewline
194 & 9.6 & 6.47756 & 3.12244 \tabularnewline
195 & 18.2 & 18.7114 & -0.511446 \tabularnewline
196 & 13.6 & 12.7851 & 0.814855 \tabularnewline
197 & 14.85 & 16.4082 & -1.55819 \tabularnewline
198 & 14.75 & 14.426 & 0.324036 \tabularnewline
199 & 14.1 & 13.0778 & 1.0222 \tabularnewline
200 & 14.9 & 14.1383 & 0.761676 \tabularnewline
201 & 16.25 & 16.6909 & -0.44085 \tabularnewline
202 & 19.25 & 18.804 & 0.44602 \tabularnewline
203 & 13.6 & 15.5004 & -1.90043 \tabularnewline
204 & 13.6 & 13.6404 & -0.0403802 \tabularnewline
205 & 15.65 & 16.7918 & -1.14181 \tabularnewline
206 & 12.75 & 11.5844 & 1.16564 \tabularnewline
207 & 14.6 & 15.1461 & -0.546115 \tabularnewline
208 & 9.85 & 9.96047 & -0.110474 \tabularnewline
209 & 12.65 & 8.64437 & 4.00563 \tabularnewline
210 & 19.2 & 16.66 & 2.54003 \tabularnewline
211 & 16.6 & 17.3791 & -0.779087 \tabularnewline
212 & 11.2 & 11.4769 & -0.276851 \tabularnewline
213 & 15.25 & 16.9501 & -1.70008 \tabularnewline
214 & 11.9 & 12.3079 & -0.407898 \tabularnewline
215 & 13.2 & 13.1462 & 0.053794 \tabularnewline
216 & 16.35 & 17.1013 & -0.751286 \tabularnewline
217 & 12.4 & 10.7365 & 1.66354 \tabularnewline
218 & 15.85 & 14.2578 & 1.59219 \tabularnewline
219 & 18.15 & 19.5518 & -1.4018 \tabularnewline
220 & 11.15 & 11.5246 & -0.374637 \tabularnewline
221 & 15.65 & 13.3246 & 2.32538 \tabularnewline
222 & 17.75 & 22.2833 & -4.53326 \tabularnewline
223 & 7.65 & 9.55857 & -1.90857 \tabularnewline
224 & 12.35 & 10.992 & 1.35805 \tabularnewline
225 & 15.6 & 13.0343 & 2.56572 \tabularnewline
226 & 19.3 & 17.3414 & 1.95865 \tabularnewline
227 & 15.2 & 13.4762 & 1.72377 \tabularnewline
228 & 17.1 & 15.1829 & 1.91714 \tabularnewline
229 & 15.6 & 11.2753 & 4.3247 \tabularnewline
230 & 18.4 & 15.354 & 3.04601 \tabularnewline
231 & 19.05 & 16.5361 & 2.51389 \tabularnewline
232 & 18.55 & 15.2135 & 3.33648 \tabularnewline
233 & 19.1 & 19.6116 & -0.51165 \tabularnewline
234 & 13.1 & 16.3074 & -3.20736 \tabularnewline
235 & 12.85 & 15.4174 & -2.56739 \tabularnewline
236 & 9.5 & 16.3301 & -6.83009 \tabularnewline
237 & 4.5 & 5.29076 & -0.790756 \tabularnewline
238 & 11.85 & 13.016 & -1.16604 \tabularnewline
239 & 13.6 & 13.5141 & 0.0858566 \tabularnewline
240 & 11.7 & 12.5533 & -0.853281 \tabularnewline
241 & 12.4 & 13.4369 & -1.03688 \tabularnewline
242 & 13.35 & 14.7742 & -1.42423 \tabularnewline
243 & 11.4 & 10.9014 & 0.498612 \tabularnewline
244 & 14.9 & 13.2942 & 1.60583 \tabularnewline
245 & 19.9 & 22.8507 & -2.9507 \tabularnewline
246 & 11.2 & 11.3854 & -0.185396 \tabularnewline
247 & 14.6 & 13.8058 & 0.794177 \tabularnewline
248 & 17.6 & 17.7547 & -0.154671 \tabularnewline
249 & 14.05 & 13.0322 & 1.01777 \tabularnewline
250 & 16.1 & 17.2285 & -1.12852 \tabularnewline
251 & 13.35 & 16.5975 & -3.24748 \tabularnewline
252 & 11.85 & 12.9448 & -1.09485 \tabularnewline
253 & 11.95 & 11.3638 & 0.586205 \tabularnewline
254 & 14.75 & 13.7299 & 1.02015 \tabularnewline
255 & 15.15 & 18.489 & -3.33903 \tabularnewline
256 & 13.2 & 12.0804 & 1.11957 \tabularnewline
257 & 16.85 & 21.6141 & -4.76411 \tabularnewline
258 & 7.85 & 13.4827 & -5.63266 \tabularnewline
259 & 7.7 & 10.0375 & -2.33745 \tabularnewline
260 & 12.6 & 19.2684 & -6.66835 \tabularnewline
261 & 7.85 & 9.40625 & -1.55625 \tabularnewline
262 & 10.95 & 13.2547 & -2.30465 \tabularnewline
263 & 12.35 & 16.2515 & -3.90149 \tabularnewline
264 & 9.95 & 9.43434 & 0.515657 \tabularnewline
265 & 14.9 & 13.0658 & 1.83422 \tabularnewline
266 & 16.65 & 16.2607 & 0.389291 \tabularnewline
267 & 13.4 & 13.7153 & -0.315294 \tabularnewline
268 & 13.95 & 12.8952 & 1.05478 \tabularnewline
269 & 15.7 & 14.1846 & 1.51538 \tabularnewline
270 & 16.85 & 18.3233 & -1.4733 \tabularnewline
271 & 10.95 & 11.076 & -0.125959 \tabularnewline
272 & 15.35 & 16.3277 & -0.977684 \tabularnewline
273 & 12.2 & 10.6627 & 1.53734 \tabularnewline
274 & 15.1 & 12.9305 & 2.16946 \tabularnewline
275 & 17.75 & 17.0521 & 0.697948 \tabularnewline
276 & 15.2 & 15.6831 & -0.483122 \tabularnewline
277 & 14.6 & 13.7674 & 0.832608 \tabularnewline
278 & 16.65 & 20.0431 & -3.39313 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12.9[/C][C]12.1114[/C][C]0.788647[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]10.6445[/C][C]1.55546[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]11.9954[/C][C]0.804609[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]11.0458[/C][C]-3.6458[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]10.4318[/C][C]-3.73178[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.8288[/C][C]-1.22882[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]11.9143[/C][C]2.8857[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]9.40664[/C][C]3.89336[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]10.9075[/C][C]0.192475[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]12.1235[/C][C]-3.92352[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]11.7339[/C][C]-0.333889[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]11.0527[/C][C]-4.65271[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]9.32701[/C][C]1.27299[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]12.5926[/C][C]-0.592593[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]7.07299[/C][C]-0.772991[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]9.72501[/C][C]1.57499[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]11.5614[/C][C]0.338633[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]10.4716[/C][C]-1.17163[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]11.6178[/C][C]-2.01784[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]9.72575[/C][C]0.274245[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]10.7271[/C][C]-4.3271[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]10.9225[/C][C]2.87752[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.7286[/C][C]-3.92859[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]12.3836[/C][C]1.41637[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]11.0929[/C][C]0.607079[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]14.4438[/C][C]-3.54384[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]12.4196[/C][C]3.68036[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]10.3064[/C][C]3.09364[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]11.0507[/C][C]-1.15072[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]11.3716[/C][C]0.128362[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]8.97675[/C][C]-0.676746[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]12.0041[/C][C]-0.304062[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]10.2723[/C][C]-1.27232[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]11.3034[/C][C]-1.60345[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]9.02037[/C][C]1.77963[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]8.75033[/C][C]1.54967[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]11.0959[/C][C]-0.695907[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]10.9217[/C][C]1.77835[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]11.9103[/C][C]-2.61035[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]12.0919[/C][C]-0.291895[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]9.73766[/C][C]-3.83766[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]11.0576[/C][C]0.342448[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]11.6593[/C][C]1.34074[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]11.5814[/C][C]-0.781391[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]8.01694[/C][C]4.28306[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]13.3836[/C][C]-2.0836[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]9.04521[/C][C]2.75479[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]9.24655[/C][C]-1.34655[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]9.20329[/C][C]3.49671[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]9.42876[/C][C]2.87124[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]10.4916[/C][C]1.10839[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]7.1887[/C][C]-0.4887[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]10.9763[/C][C]-0.0762528[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]12.1158[/C][C]-0.0157928[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]9.7781[/C][C]3.5219[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]9.71677[/C][C]0.383231[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]11.6802[/C][C]-5.98015[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]10.0532[/C][C]4.24678[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]7.7561[/C][C]0.243905[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]10.2089[/C][C]3.09108[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]12.0059[/C][C]-2.70595[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]12.2551[/C][C]0.244925[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]9.31004[/C][C]-1.71004[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]13.3403[/C][C]2.5597[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.3329[/C][C]-4.13286[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]8.44804[/C][C]0.651963[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]12.8223[/C][C]-1.72227[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]13.8193[/C][C]-0.819322[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]12.4987[/C][C]2.0013[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]10.767[/C][C]1.43301[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]13.2776[/C][C]-0.977559[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]10.6023[/C][C]0.79769[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]9.70871[/C][C]-0.908709[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]10.1178[/C][C]4.48222[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]10.6598[/C][C]1.94025[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]0.998415[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]10.9982[/C][C]2.00179[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]11.4181[/C][C]1.18189[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]12.2991[/C][C]0.900923[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]11.4868[/C][C]-1.58675[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]7.68627[/C][C]0.0137252[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]7.77479[/C][C]2.72521[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]12.4588[/C][C]0.94123[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]16.1716[/C][C]-5.27164[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]5.41036[/C][C]-1.11036[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]8.78112[/C][C]1.51888[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]9.36849[/C][C]2.43151[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]9.00682[/C][C]2.19318[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]13.1028[/C][C]-1.70284[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]7.1431[/C][C]1.4569[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]9.42651[/C][C]3.77349[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]17.5378[/C][C]-4.9378[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]7.20221[/C][C]-1.60221[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]11.6217[/C][C]-1.7217[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]10.9391[/C][C]-2.13913[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.0165[/C][C]-2.31655[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]13[/C][C]-3.99999[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]5.7445[/C][C]1.5555[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]7.702[/C][C]3.698[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]15.8163[/C][C]-2.21629[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]5.6778[/C][C]2.2222[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]10.72[/C][C]-0.0199941[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]10.6354[/C][C]-0.335398[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]9.54417[/C][C]-1.24417[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]5.03791[/C][C]4.56209[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]15.9341[/C][C]-1.73408[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]5.06176[/C][C]3.43824[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]18.4768[/C][C]-4.97681[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]6.79564[/C][C]-1.89564[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]7.22813[/C][C]-0.82813[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]9.18863[/C][C]0.411369[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]10.2091[/C][C]1.39089[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]18.1322[/C][C]-7.03218[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.08271[/C][C]1.26729[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]10.058[/C][C]2.64204[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]16.0165[/C][C]2.08347[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.3642[/C][C]0.485818[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]16.9224[/C][C]-0.322359[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]13.4619[/C][C]-0.861858[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]14.6702[/C][C]2.42983[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]18.9125[/C][C]0.187527[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]15.1188[/C][C]0.981152[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]11.2702[/C][C]2.07985[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]14.0922[/C][C]4.30777[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]17.2889[/C][C]-2.58886[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]11.3688[/C][C]-0.768782[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]11.3711[/C][C]1.22887[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]15.6476[/C][C]0.552352[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]10.3892[/C][C]3.21084[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]18.3719[/C][C]0.528052[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]13.8215[/C][C]0.278547[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]15.0085[/C][C]-0.508539[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]15.041[/C][C]1.10899[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]13.3005[/C][C]1.44948[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]14.5641[/C][C]0.235916[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]12.2074[/C][C]0.242562[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]9.68961[/C][C]2.96039[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]18.8809[/C][C]-1.53091[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]6.29124[/C][C]2.30876[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.4907[/C][C]1.90934[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]17.7868[/C][C]-1.68682[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]9.85[/C][C]1.75[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]16.9848[/C][C]0.765164[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]11.887[/C][C]3.36301[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]17.4779[/C][C]0.172055[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]15.025[/C][C]1.32501[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]18.1014[/C][C]-0.451406[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]13.478[/C][C]0.121986[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]14.4018[/C][C]-0.0518328[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]13.2863[/C][C]1.46372[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]24.8425[/C][C]-6.59251[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]8.04187[/C][C]1.85813[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]13.7474[/C][C]2.25258[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]18.6683[/C][C]-0.418306[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]15.4234[/C][C]1.42656[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.6546[/C][C]-0.0546135[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]11.513[/C][C]2.33698[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]17.8725[/C][C]1.07746[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]16.9314[/C][C]-1.33143[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]17.063[/C][C]-2.21299[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]9.59775[/C][C]2.15225[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]16.2294[/C][C]2.22065[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]16.0864[/C][C]-0.186408[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]10.1461[/C][C]6.95394[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]14.697[/C][C]1.40298[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]21.0951[/C][C]-1.19505[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]8.73753[/C][C]2.21247[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]17.6931[/C][C]0.756864[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]15.2115[/C][C]-0.111472[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.8841[/C][C]-2.88406[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]9.81496[/C][C]1.53504[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]13.6013[/C][C]2.34866[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]19.9903[/C][C]-1.89034[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]15.6906[/C][C]-1.09064[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]16.4473[/C][C]-1.04734[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.352[/C][C]3.04802[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]18.4983[/C][C]-0.898278[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]10.6916[/C][C]2.65844[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]20.151[/C][C]-1.05103[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]19.3621[/C][C]-4.01209[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]9.09378[/C][C]-1.49378[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]15.5393[/C][C]-2.1393[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]10.6494[/C][C]3.2506[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]18.7704[/C][C]0.329592[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]18.8055[/C][C]-3.55545[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]12.5681[/C][C]0.331875[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]14.358[/C][C]1.742[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]19.9355[/C][C]-2.58549[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]16.8331[/C][C]-3.68308[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.9282[/C][C]0.221832[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]15.1905[/C][C]-2.59049[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]8.86534[/C][C]1.48466[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]18.6654[/C][C]-3.26543[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]6.47756[/C][C]3.12244[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]18.7114[/C][C]-0.511446[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]12.7851[/C][C]0.814855[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]16.4082[/C][C]-1.55819[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]14.426[/C][C]0.324036[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]13.0778[/C][C]1.0222[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]14.1383[/C][C]0.761676[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]16.6909[/C][C]-0.44085[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]18.804[/C][C]0.44602[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]15.5004[/C][C]-1.90043[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]13.6404[/C][C]-0.0403802[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]16.7918[/C][C]-1.14181[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]11.5844[/C][C]1.16564[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]15.1461[/C][C]-0.546115[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]9.96047[/C][C]-0.110474[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]8.64437[/C][C]4.00563[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]16.66[/C][C]2.54003[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]17.3791[/C][C]-0.779087[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]11.4769[/C][C]-0.276851[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]16.9501[/C][C]-1.70008[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]12.3079[/C][C]-0.407898[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]13.1462[/C][C]0.053794[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]17.1013[/C][C]-0.751286[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]10.7365[/C][C]1.66354[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]14.2578[/C][C]1.59219[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]19.5518[/C][C]-1.4018[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]11.5246[/C][C]-0.374637[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]13.3246[/C][C]2.32538[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.2833[/C][C]-4.53326[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]9.55857[/C][C]-1.90857[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]10.992[/C][C]1.35805[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]13.0343[/C][C]2.56572[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]17.3414[/C][C]1.95865[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]13.4762[/C][C]1.72377[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]15.1829[/C][C]1.91714[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]11.2753[/C][C]4.3247[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]15.354[/C][C]3.04601[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]16.5361[/C][C]2.51389[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.2135[/C][C]3.33648[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]19.6116[/C][C]-0.51165[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]16.3074[/C][C]-3.20736[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]15.4174[/C][C]-2.56739[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]16.3301[/C][C]-6.83009[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]5.29076[/C][C]-0.790756[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]13.016[/C][C]-1.16604[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]13.5141[/C][C]0.0858566[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]12.5533[/C][C]-0.853281[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]13.4369[/C][C]-1.03688[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.7742[/C][C]-1.42423[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]10.9014[/C][C]0.498612[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]13.2942[/C][C]1.60583[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]22.8507[/C][C]-2.9507[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]11.3854[/C][C]-0.185396[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]13.8058[/C][C]0.794177[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]17.7547[/C][C]-0.154671[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]13.0322[/C][C]1.01777[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]17.2285[/C][C]-1.12852[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]16.5975[/C][C]-3.24748[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.9448[/C][C]-1.09485[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]11.3638[/C][C]0.586205[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]13.7299[/C][C]1.02015[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]18.489[/C][C]-3.33903[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]12.0804[/C][C]1.11957[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]21.6141[/C][C]-4.76411[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]13.4827[/C][C]-5.63266[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]10.0375[/C][C]-2.33745[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]19.2684[/C][C]-6.66835[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]9.40625[/C][C]-1.55625[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]13.2547[/C][C]-2.30465[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]16.2515[/C][C]-3.90149[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]9.43434[/C][C]0.515657[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]13.0658[/C][C]1.83422[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.2607[/C][C]0.389291[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]13.7153[/C][C]-0.315294[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]12.8952[/C][C]1.05478[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]14.1846[/C][C]1.51538[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]18.3233[/C][C]-1.4733[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]11.076[/C][C]-0.125959[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]16.3277[/C][C]-0.977684[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]10.6627[/C][C]1.53734[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]12.9305[/C][C]2.16946[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]17.0521[/C][C]0.697948[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]15.6831[/C][C]-0.483122[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]13.7674[/C][C]0.832608[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]20.0431[/C][C]-3.39313[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.912.11140.788647
212.210.64451.55546
312.811.99540.804609
47.411.0458-3.6458
56.710.4318-3.73178
612.613.8288-1.22882
714.811.91432.8857
813.39.406643.89336
911.110.90750.192475
108.212.1235-3.92352
1111.411.7339-0.333889
126.411.0527-4.65271
1310.69.327011.27299
141212.5926-0.592593
156.37.07299-0.772991
1611.39.725011.57499
1711.911.56140.338633
189.310.4716-1.17163
199.611.6178-2.01784
20109.725750.274245
216.410.7271-4.3271
2213.810.92252.87752
2310.814.7286-3.92859
2413.812.38361.41637
2511.711.09290.607079
2610.914.4438-3.54384
2716.112.41963.68036
2813.410.30643.09364
299.911.0507-1.15072
3011.511.37160.128362
318.38.97675-0.676746
3211.712.0041-0.304062
33910.2723-1.27232
349.711.3034-1.60345
3510.89.020371.77963
3610.38.750331.54967
3710.411.0959-0.695907
3812.710.92171.77835
399.311.9103-2.61035
4011.812.0919-0.291895
415.99.73766-3.83766
4211.411.05760.342448
431311.65931.34074
4410.811.5814-0.781391
4512.38.016944.28306
4611.313.3836-2.0836
4711.89.045212.75479
487.99.24655-1.34655
4912.79.203293.49671
5012.39.428762.87124
5111.610.49161.10839
526.77.1887-0.4887
5310.910.9763-0.0762528
5412.112.1158-0.0157928
5513.39.77813.5219
5610.19.716770.383231
575.711.6802-5.98015
5814.310.05324.24678
5987.75610.243905
6013.310.20893.09108
619.312.0059-2.70595
6212.512.25510.244925
637.69.31004-1.71004
6415.913.34032.5597
659.213.3329-4.13286
669.18.448040.651963
6711.112.8223-1.72227
681313.8193-0.819322
6914.512.49872.0013
7012.210.7671.43301
7112.313.2776-0.977559
7211.410.60230.79769
738.89.70871-0.908709
7414.610.11784.48222
7512.610.65981.94025
76NANA0.998415
771310.99822.00179
7812.611.41811.18189
7913.212.29910.900923
809.911.4868-1.58675
817.77.686270.0137252
8210.57.774792.72521
8313.412.45880.94123
8410.916.1716-5.27164
854.35.41036-1.11036
8610.38.781121.51888
8711.89.368492.43151
8811.29.006822.19318
8911.413.1028-1.70284
908.67.14311.4569
9113.29.426513.77349
9212.617.5378-4.9378
935.67.20221-1.60221
949.911.6217-1.7217
958.810.9391-2.13913
967.710.0165-2.31655
97913-3.99999
987.35.74451.5555
9911.47.7023.698
10013.615.8163-2.21629
1017.95.67782.2222
10210.710.72-0.0199941
10310.310.6354-0.335398
1048.39.54417-1.24417
1059.65.037914.56209
10614.215.9341-1.73408
1078.55.061763.43824
10813.518.4768-4.97681
1094.96.79564-1.89564
1106.47.22813-0.82813
1119.69.188630.411369
11211.610.20911.39089
11311.118.1322-7.03218
1144.353.082711.26729
11512.710.0582.64204
11618.116.01652.08347
11717.8517.36420.485818
11816.616.9224-0.322359
11912.613.4619-0.861858
12017.114.67022.42983
12119.118.91250.187527
12216.115.11880.981152
12313.3511.27022.07985
12418.414.09224.30777
12514.717.2889-2.58886
12610.611.3688-0.768782
12712.611.37111.22887
12816.215.64760.552352
12913.610.38923.21084
13018.918.37190.528052
13114.113.82150.278547
13214.515.0085-0.508539
13316.1515.0411.10899
13414.7513.30051.44948
13514.814.56410.235916
13612.4512.20740.242562
13712.659.689612.96039
13817.3518.8809-1.53091
1398.66.291242.30876
14018.416.49071.90934
14116.117.7868-1.68682
14211.69.851.75
14317.7516.98480.765164
14415.2511.8873.36301
14517.6517.47790.172055
14616.3515.0251.32501
14717.6518.1014-0.451406
14813.613.4780.121986
14914.3514.4018-0.0518328
15014.7513.28631.46372
15118.2524.8425-6.59251
1529.98.041871.85813
1531613.74742.25258
15418.2518.6683-0.418306
15516.8515.42341.42656
15614.614.6546-0.0546135
15713.8511.5132.33698
15818.9517.87251.07746
15915.616.9314-1.33143
16014.8517.063-2.21299
16111.759.597752.15225
16218.4516.22942.22065
16315.916.0864-0.186408
16417.110.14616.95394
16516.114.6971.40298
16619.921.0951-1.19505
16710.958.737532.21247
16818.4517.69310.756864
16915.115.2115-0.111472
1701517.8841-2.88406
17111.359.814961.53504
17215.9513.60132.34866
17318.119.9903-1.89034
17414.615.6906-1.09064
17515.416.4473-1.04734
17615.412.3523.04802
17717.618.4983-0.898278
17813.3510.69162.65844
17919.120.151-1.05103
18015.3519.3621-4.01209
1817.69.09378-1.49378
18213.415.5393-2.1393
18313.910.64943.2506
18419.118.77040.329592
18515.2518.8055-3.55545
18612.912.56810.331875
18716.114.3581.742
18817.3519.9355-2.58549
18913.1516.8331-3.68308
19012.1511.92820.221832
19112.615.1905-2.59049
19210.358.865341.48466
19315.418.6654-3.26543
1949.66.477563.12244
19518.218.7114-0.511446
19613.612.78510.814855
19714.8516.4082-1.55819
19814.7514.4260.324036
19914.113.07781.0222
20014.914.13830.761676
20116.2516.6909-0.44085
20219.2518.8040.44602
20313.615.5004-1.90043
20413.613.6404-0.0403802
20515.6516.7918-1.14181
20612.7511.58441.16564
20714.615.1461-0.546115
2089.859.96047-0.110474
20912.658.644374.00563
21019.216.662.54003
21116.617.3791-0.779087
21211.211.4769-0.276851
21315.2516.9501-1.70008
21411.912.3079-0.407898
21513.213.14620.053794
21616.3517.1013-0.751286
21712.410.73651.66354
21815.8514.25781.59219
21918.1519.5518-1.4018
22011.1511.5246-0.374637
22115.6513.32462.32538
22217.7522.2833-4.53326
2237.659.55857-1.90857
22412.3510.9921.35805
22515.613.03432.56572
22619.317.34141.95865
22715.213.47621.72377
22817.115.18291.91714
22915.611.27534.3247
23018.415.3543.04601
23119.0516.53612.51389
23218.5515.21353.33648
23319.119.6116-0.51165
23413.116.3074-3.20736
23512.8515.4174-2.56739
2369.516.3301-6.83009
2374.55.29076-0.790756
23811.8513.016-1.16604
23913.613.51410.0858566
24011.712.5533-0.853281
24112.413.4369-1.03688
24213.3514.7742-1.42423
24311.410.90140.498612
24414.913.29421.60583
24519.922.8507-2.9507
24611.211.3854-0.185396
24714.613.80580.794177
24817.617.7547-0.154671
24914.0513.03221.01777
25016.117.2285-1.12852
25113.3516.5975-3.24748
25211.8512.9448-1.09485
25311.9511.36380.586205
25414.7513.72991.02015
25515.1518.489-3.33903
25613.212.08041.11957
25716.8521.6141-4.76411
2587.8513.4827-5.63266
2597.710.0375-2.33745
26012.619.2684-6.66835
2617.859.40625-1.55625
26210.9513.2547-2.30465
26312.3516.2515-3.90149
2649.959.434340.515657
26514.913.06581.83422
26616.6516.26070.389291
26713.413.7153-0.315294
26813.9512.89521.05478
26915.714.18461.51538
27016.8518.3233-1.4733
27110.9511.076-0.125959
27215.3516.3277-0.977684
27312.210.66271.53734
27415.112.93052.16946
27517.7517.05210.697948
27615.215.6831-0.483122
27714.613.76740.832608
27816.6520.0431-3.39313
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
110.9314330.1371340.0685669
120.9369730.1260530.0630266
130.8887560.2224880.111244
140.8344990.3310030.165501
150.7690580.4618840.230942
160.6831620.6336770.316838
170.5906890.8186220.409311
180.5444960.9110090.455504
190.5503050.899390.449695
200.4741620.9483230.525838
210.5078840.9842330.492116
220.5727380.8545240.427262
230.6381410.7237190.361859
240.6340250.7319510.365975
250.5681160.8637680.431884
260.5141220.9717550.485878
270.4736440.9472880.526356
280.4504790.9009580.549521
290.3932350.786470.606765
300.3316540.6633080.668346
310.3551570.7103140.644843
320.3059210.6118420.694079
330.3097020.6194040.690298
340.2780660.5561320.721934
350.2361070.4722150.763893
360.2116250.423250.788375
370.1855260.3710520.814474
380.1715380.3430760.828462
390.1521240.3042480.847876
400.1410150.2820310.858985
410.2235390.4470780.776461
420.1896840.3793680.810316
430.1647870.3295740.835213
440.160620.321240.83938
450.1489860.2979720.851014
460.128620.2572410.87138
470.16980.3395990.8302
480.2006050.4012090.799395
490.2522570.5045130.747743
500.224410.448820.77559
510.1960180.3920360.803982
520.205840.4116790.79416
530.1747150.3494310.825285
540.146230.292460.85377
550.2234040.4468090.776596
560.191640.3832810.80836
570.5399920.9200160.460008
580.6502530.6994940.349747
590.6156430.7687130.384357
600.6085030.7829930.391497
610.6125670.7748660.387433
620.5758970.8482070.424103
630.5858160.8283680.414184
640.6317910.7364180.368209
650.6623250.6753490.337675
660.6316550.736690.368345
670.6033520.7932960.396648
680.5738650.852270.426135
690.5754830.8490350.424517
700.5435660.9128680.456434
710.5088120.9823750.491188
720.4755130.9510260.524487
730.4459950.8919890.554005
740.5322470.9355060.467753
750.5173330.9653330.482667
760.4923550.984710.507645
770.4659930.9319860.534007
780.4566940.9133890.543306
790.4232220.8464440.576778
800.4210.8419990.579
810.3857940.7715870.614206
820.391170.782340.60883
830.3583550.7167110.641645
840.5701340.8597320.429866
850.5421880.9156250.457812
860.513440.973120.48656
870.5013350.9973290.498665
880.486350.97270.51365
890.4782250.956450.521775
900.4557430.9114870.544257
910.4922330.9844670.507767
920.6561710.6876580.343829
930.6372210.7255580.362779
940.6295590.7408810.370441
950.6344530.7310950.365547
960.6317330.7365350.368267
970.7002440.5995130.299756
980.6760730.6478550.323927
990.7096810.5806380.290319
1000.712880.574240.28712
1010.7003420.5993160.299658
1020.6679520.6640970.332048
1030.6439010.7121980.356099
1040.6199580.7600840.380042
1050.7048810.5902380.295119
1060.687340.6253190.31266
1070.7346590.5306820.265341
1080.8235040.3529930.176496
1090.8230180.3539640.176982
1100.8035930.3928140.196407
1110.7822540.4354930.217746
1120.7580680.4838640.241932
1130.8200980.3598040.179902
1140.8721180.2557640.127882
1150.9191760.1616470.0808236
1160.9258140.1483720.0741861
1170.9157850.1684290.0842145
1180.9013370.1973260.0986629
1190.8888180.2223630.111182
1200.8952570.2094870.104743
1210.8788360.2423290.121164
1220.8634340.2731320.136566
1230.8614270.2771460.138573
1240.8949190.2101610.105081
1250.9037220.1925570.0962784
1260.8909530.2180950.109047
1270.8779010.2441990.122099
1280.8601480.2797040.139852
1290.8689740.2620520.131026
1300.8510790.2978420.148921
1310.830680.3386390.16932
1320.8110560.3778870.188944
1330.7914120.4171760.208588
1340.7725330.4549340.227467
1350.7517850.496430.248215
1360.7240880.5518240.275912
1370.7395340.5209320.260466
1380.735150.52970.26485
1390.7283710.5432580.271629
1400.7163570.5672860.283643
1410.7086950.582610.291305
1420.6921610.6156770.307839
1430.6620820.6758350.337918
1440.6946220.6107550.305378
1450.6633080.6733850.336692
1460.6404390.7191230.359561
1470.6106530.7786940.389347
1480.5768290.8463430.423171
1490.5427570.9144860.457243
1500.518410.9631810.48159
1510.7742960.4514080.225704
1520.7659920.4680160.234008
1530.7616050.476790.238395
1540.7344230.5311550.265577
1550.7176760.5646470.282324
1560.6885420.6229170.311458
1570.6820710.6358580.317929
1580.6568650.6862690.343135
1590.6422560.7154890.357744
1600.6426210.7147580.357379
1610.6340550.7318910.365945
1620.6329870.7340260.367013
1630.6008070.7983860.399193
1640.9149830.1700340.0850169
1650.9027610.1944780.0972392
1660.8954380.2091250.104562
1670.8899540.2200930.110046
1680.877890.2442190.12211
1690.8592510.2814980.140749
1700.8747570.2504860.125243
1710.8680340.2639330.131966
1720.863370.273260.13663
1730.8616140.2767710.138386
1740.8457920.3084160.154208
1750.8285240.3429510.171476
1760.8475260.3049490.152474
1770.8283180.3433630.171682
1780.8324830.3350330.167517
1790.8188080.3623840.181192
1800.8460150.307970.153985
1810.83390.33220.1661
1820.8421420.3157160.157858
1830.8748960.2502080.125104
1840.8545030.2909950.145497
1850.897380.2052410.10262
1860.8793360.2413280.120664
1870.8684920.2630160.131508
1880.8829190.2341610.117081
1890.926150.14770.0738498
1900.9175570.1648860.0824429
1910.9148650.170270.0851352
1920.9037960.1924080.096204
1930.9142970.1714070.0857034
1940.9165590.1668820.0834411
1950.9017860.1964290.0982143
1960.8948860.2102280.105114
1970.8876520.2246960.112348
1980.8692370.2615260.130763
1990.8502150.2995710.149785
2000.8264460.3471090.173554
2010.8295140.3409730.170486
2020.809720.380560.19028
2030.8132120.3735760.186788
2040.7890360.4219280.210964
2050.7627170.4745650.237283
2060.7493550.501290.250645
2070.7651810.4696380.234819
2080.7465050.5069910.253495
2090.7616460.4767090.238354
2100.7927910.4144180.207209
2110.7815510.4368970.218449
2120.7492310.5015370.250769
2130.7276020.5447950.272398
2140.6918830.6162340.308117
2150.655230.6895390.34477
2160.6168950.766210.383105
2170.6251490.7497030.374851
2180.5953160.8093680.404684
2190.5718690.8562620.428131
2200.536910.9261790.46309
2210.5292450.941510.470755
2220.6110110.7779770.388989
2230.5755020.8489960.424498
2240.6051790.7896420.394821
2250.5928770.8142460.407123
2260.6038370.7923260.396163
2270.5668930.8662140.433107
2280.5992580.8014840.400742
2290.8655210.2689570.134479
2300.8881110.2237780.111889
2310.8697420.2605160.130258
2320.9071330.1857330.0928666
2330.8933470.2133060.106653
2340.8832820.2334360.116718
2350.8617850.2764310.138215
2360.9218540.1562910.0781456
2370.9006110.1987780.0993891
2380.8773330.2453340.122667
2390.8743260.2513480.125674
2400.8436170.3127660.156383
2410.8113780.3772440.188622
2420.7731860.4536270.226814
2430.7416770.5166470.258323
2440.6973830.6052340.302617
2450.6850540.6298920.314946
2460.6486540.7026920.351346
2470.5930290.8139420.406971
2480.6366680.7266650.363332
2490.6043580.7912840.395642
2500.5838450.8323090.416155
2510.5299250.940150.470075
2520.5290350.941930.470965
2530.5199480.9601030.480052
2540.6021740.7956520.397826
2550.5721780.8556440.427822
2560.5059480.9881040.494052
2570.4957090.9914180.504291
2580.6897020.6205970.310298
2590.6829420.6341160.317058
2600.9076490.1847010.0923507
2610.8652610.2694770.134739
2620.9197220.1605560.0802782
2630.9846540.03069110.0153455
2640.9671110.06577730.0328887
2650.9426680.1146630.0573315
2660.9037270.1925450.0962726
2670.7988760.4022470.201124
2680.6032830.7934350.396717

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
11 & 0.931433 & 0.137134 & 0.0685669 \tabularnewline
12 & 0.936973 & 0.126053 & 0.0630266 \tabularnewline
13 & 0.888756 & 0.222488 & 0.111244 \tabularnewline
14 & 0.834499 & 0.331003 & 0.165501 \tabularnewline
15 & 0.769058 & 0.461884 & 0.230942 \tabularnewline
16 & 0.683162 & 0.633677 & 0.316838 \tabularnewline
17 & 0.590689 & 0.818622 & 0.409311 \tabularnewline
18 & 0.544496 & 0.911009 & 0.455504 \tabularnewline
19 & 0.550305 & 0.89939 & 0.449695 \tabularnewline
20 & 0.474162 & 0.948323 & 0.525838 \tabularnewline
21 & 0.507884 & 0.984233 & 0.492116 \tabularnewline
22 & 0.572738 & 0.854524 & 0.427262 \tabularnewline
23 & 0.638141 & 0.723719 & 0.361859 \tabularnewline
24 & 0.634025 & 0.731951 & 0.365975 \tabularnewline
25 & 0.568116 & 0.863768 & 0.431884 \tabularnewline
26 & 0.514122 & 0.971755 & 0.485878 \tabularnewline
27 & 0.473644 & 0.947288 & 0.526356 \tabularnewline
28 & 0.450479 & 0.900958 & 0.549521 \tabularnewline
29 & 0.393235 & 0.78647 & 0.606765 \tabularnewline
30 & 0.331654 & 0.663308 & 0.668346 \tabularnewline
31 & 0.355157 & 0.710314 & 0.644843 \tabularnewline
32 & 0.305921 & 0.611842 & 0.694079 \tabularnewline
33 & 0.309702 & 0.619404 & 0.690298 \tabularnewline
34 & 0.278066 & 0.556132 & 0.721934 \tabularnewline
35 & 0.236107 & 0.472215 & 0.763893 \tabularnewline
36 & 0.211625 & 0.42325 & 0.788375 \tabularnewline
37 & 0.185526 & 0.371052 & 0.814474 \tabularnewline
38 & 0.171538 & 0.343076 & 0.828462 \tabularnewline
39 & 0.152124 & 0.304248 & 0.847876 \tabularnewline
40 & 0.141015 & 0.282031 & 0.858985 \tabularnewline
41 & 0.223539 & 0.447078 & 0.776461 \tabularnewline
42 & 0.189684 & 0.379368 & 0.810316 \tabularnewline
43 & 0.164787 & 0.329574 & 0.835213 \tabularnewline
44 & 0.16062 & 0.32124 & 0.83938 \tabularnewline
45 & 0.148986 & 0.297972 & 0.851014 \tabularnewline
46 & 0.12862 & 0.257241 & 0.87138 \tabularnewline
47 & 0.1698 & 0.339599 & 0.8302 \tabularnewline
48 & 0.200605 & 0.401209 & 0.799395 \tabularnewline
49 & 0.252257 & 0.504513 & 0.747743 \tabularnewline
50 & 0.22441 & 0.44882 & 0.77559 \tabularnewline
51 & 0.196018 & 0.392036 & 0.803982 \tabularnewline
52 & 0.20584 & 0.411679 & 0.79416 \tabularnewline
53 & 0.174715 & 0.349431 & 0.825285 \tabularnewline
54 & 0.14623 & 0.29246 & 0.85377 \tabularnewline
55 & 0.223404 & 0.446809 & 0.776596 \tabularnewline
56 & 0.19164 & 0.383281 & 0.80836 \tabularnewline
57 & 0.539992 & 0.920016 & 0.460008 \tabularnewline
58 & 0.650253 & 0.699494 & 0.349747 \tabularnewline
59 & 0.615643 & 0.768713 & 0.384357 \tabularnewline
60 & 0.608503 & 0.782993 & 0.391497 \tabularnewline
61 & 0.612567 & 0.774866 & 0.387433 \tabularnewline
62 & 0.575897 & 0.848207 & 0.424103 \tabularnewline
63 & 0.585816 & 0.828368 & 0.414184 \tabularnewline
64 & 0.631791 & 0.736418 & 0.368209 \tabularnewline
65 & 0.662325 & 0.675349 & 0.337675 \tabularnewline
66 & 0.631655 & 0.73669 & 0.368345 \tabularnewline
67 & 0.603352 & 0.793296 & 0.396648 \tabularnewline
68 & 0.573865 & 0.85227 & 0.426135 \tabularnewline
69 & 0.575483 & 0.849035 & 0.424517 \tabularnewline
70 & 0.543566 & 0.912868 & 0.456434 \tabularnewline
71 & 0.508812 & 0.982375 & 0.491188 \tabularnewline
72 & 0.475513 & 0.951026 & 0.524487 \tabularnewline
73 & 0.445995 & 0.891989 & 0.554005 \tabularnewline
74 & 0.532247 & 0.935506 & 0.467753 \tabularnewline
75 & 0.517333 & 0.965333 & 0.482667 \tabularnewline
76 & 0.492355 & 0.98471 & 0.507645 \tabularnewline
77 & 0.465993 & 0.931986 & 0.534007 \tabularnewline
78 & 0.456694 & 0.913389 & 0.543306 \tabularnewline
79 & 0.423222 & 0.846444 & 0.576778 \tabularnewline
80 & 0.421 & 0.841999 & 0.579 \tabularnewline
81 & 0.385794 & 0.771587 & 0.614206 \tabularnewline
82 & 0.39117 & 0.78234 & 0.60883 \tabularnewline
83 & 0.358355 & 0.716711 & 0.641645 \tabularnewline
84 & 0.570134 & 0.859732 & 0.429866 \tabularnewline
85 & 0.542188 & 0.915625 & 0.457812 \tabularnewline
86 & 0.51344 & 0.97312 & 0.48656 \tabularnewline
87 & 0.501335 & 0.997329 & 0.498665 \tabularnewline
88 & 0.48635 & 0.9727 & 0.51365 \tabularnewline
89 & 0.478225 & 0.95645 & 0.521775 \tabularnewline
90 & 0.455743 & 0.911487 & 0.544257 \tabularnewline
91 & 0.492233 & 0.984467 & 0.507767 \tabularnewline
92 & 0.656171 & 0.687658 & 0.343829 \tabularnewline
93 & 0.637221 & 0.725558 & 0.362779 \tabularnewline
94 & 0.629559 & 0.740881 & 0.370441 \tabularnewline
95 & 0.634453 & 0.731095 & 0.365547 \tabularnewline
96 & 0.631733 & 0.736535 & 0.368267 \tabularnewline
97 & 0.700244 & 0.599513 & 0.299756 \tabularnewline
98 & 0.676073 & 0.647855 & 0.323927 \tabularnewline
99 & 0.709681 & 0.580638 & 0.290319 \tabularnewline
100 & 0.71288 & 0.57424 & 0.28712 \tabularnewline
101 & 0.700342 & 0.599316 & 0.299658 \tabularnewline
102 & 0.667952 & 0.664097 & 0.332048 \tabularnewline
103 & 0.643901 & 0.712198 & 0.356099 \tabularnewline
104 & 0.619958 & 0.760084 & 0.380042 \tabularnewline
105 & 0.704881 & 0.590238 & 0.295119 \tabularnewline
106 & 0.68734 & 0.625319 & 0.31266 \tabularnewline
107 & 0.734659 & 0.530682 & 0.265341 \tabularnewline
108 & 0.823504 & 0.352993 & 0.176496 \tabularnewline
109 & 0.823018 & 0.353964 & 0.176982 \tabularnewline
110 & 0.803593 & 0.392814 & 0.196407 \tabularnewline
111 & 0.782254 & 0.435493 & 0.217746 \tabularnewline
112 & 0.758068 & 0.483864 & 0.241932 \tabularnewline
113 & 0.820098 & 0.359804 & 0.179902 \tabularnewline
114 & 0.872118 & 0.255764 & 0.127882 \tabularnewline
115 & 0.919176 & 0.161647 & 0.0808236 \tabularnewline
116 & 0.925814 & 0.148372 & 0.0741861 \tabularnewline
117 & 0.915785 & 0.168429 & 0.0842145 \tabularnewline
118 & 0.901337 & 0.197326 & 0.0986629 \tabularnewline
119 & 0.888818 & 0.222363 & 0.111182 \tabularnewline
120 & 0.895257 & 0.209487 & 0.104743 \tabularnewline
121 & 0.878836 & 0.242329 & 0.121164 \tabularnewline
122 & 0.863434 & 0.273132 & 0.136566 \tabularnewline
123 & 0.861427 & 0.277146 & 0.138573 \tabularnewline
124 & 0.894919 & 0.210161 & 0.105081 \tabularnewline
125 & 0.903722 & 0.192557 & 0.0962784 \tabularnewline
126 & 0.890953 & 0.218095 & 0.109047 \tabularnewline
127 & 0.877901 & 0.244199 & 0.122099 \tabularnewline
128 & 0.860148 & 0.279704 & 0.139852 \tabularnewline
129 & 0.868974 & 0.262052 & 0.131026 \tabularnewline
130 & 0.851079 & 0.297842 & 0.148921 \tabularnewline
131 & 0.83068 & 0.338639 & 0.16932 \tabularnewline
132 & 0.811056 & 0.377887 & 0.188944 \tabularnewline
133 & 0.791412 & 0.417176 & 0.208588 \tabularnewline
134 & 0.772533 & 0.454934 & 0.227467 \tabularnewline
135 & 0.751785 & 0.49643 & 0.248215 \tabularnewline
136 & 0.724088 & 0.551824 & 0.275912 \tabularnewline
137 & 0.739534 & 0.520932 & 0.260466 \tabularnewline
138 & 0.73515 & 0.5297 & 0.26485 \tabularnewline
139 & 0.728371 & 0.543258 & 0.271629 \tabularnewline
140 & 0.716357 & 0.567286 & 0.283643 \tabularnewline
141 & 0.708695 & 0.58261 & 0.291305 \tabularnewline
142 & 0.692161 & 0.615677 & 0.307839 \tabularnewline
143 & 0.662082 & 0.675835 & 0.337918 \tabularnewline
144 & 0.694622 & 0.610755 & 0.305378 \tabularnewline
145 & 0.663308 & 0.673385 & 0.336692 \tabularnewline
146 & 0.640439 & 0.719123 & 0.359561 \tabularnewline
147 & 0.610653 & 0.778694 & 0.389347 \tabularnewline
148 & 0.576829 & 0.846343 & 0.423171 \tabularnewline
149 & 0.542757 & 0.914486 & 0.457243 \tabularnewline
150 & 0.51841 & 0.963181 & 0.48159 \tabularnewline
151 & 0.774296 & 0.451408 & 0.225704 \tabularnewline
152 & 0.765992 & 0.468016 & 0.234008 \tabularnewline
153 & 0.761605 & 0.47679 & 0.238395 \tabularnewline
154 & 0.734423 & 0.531155 & 0.265577 \tabularnewline
155 & 0.717676 & 0.564647 & 0.282324 \tabularnewline
156 & 0.688542 & 0.622917 & 0.311458 \tabularnewline
157 & 0.682071 & 0.635858 & 0.317929 \tabularnewline
158 & 0.656865 & 0.686269 & 0.343135 \tabularnewline
159 & 0.642256 & 0.715489 & 0.357744 \tabularnewline
160 & 0.642621 & 0.714758 & 0.357379 \tabularnewline
161 & 0.634055 & 0.731891 & 0.365945 \tabularnewline
162 & 0.632987 & 0.734026 & 0.367013 \tabularnewline
163 & 0.600807 & 0.798386 & 0.399193 \tabularnewline
164 & 0.914983 & 0.170034 & 0.0850169 \tabularnewline
165 & 0.902761 & 0.194478 & 0.0972392 \tabularnewline
166 & 0.895438 & 0.209125 & 0.104562 \tabularnewline
167 & 0.889954 & 0.220093 & 0.110046 \tabularnewline
168 & 0.87789 & 0.244219 & 0.12211 \tabularnewline
169 & 0.859251 & 0.281498 & 0.140749 \tabularnewline
170 & 0.874757 & 0.250486 & 0.125243 \tabularnewline
171 & 0.868034 & 0.263933 & 0.131966 \tabularnewline
172 & 0.86337 & 0.27326 & 0.13663 \tabularnewline
173 & 0.861614 & 0.276771 & 0.138386 \tabularnewline
174 & 0.845792 & 0.308416 & 0.154208 \tabularnewline
175 & 0.828524 & 0.342951 & 0.171476 \tabularnewline
176 & 0.847526 & 0.304949 & 0.152474 \tabularnewline
177 & 0.828318 & 0.343363 & 0.171682 \tabularnewline
178 & 0.832483 & 0.335033 & 0.167517 \tabularnewline
179 & 0.818808 & 0.362384 & 0.181192 \tabularnewline
180 & 0.846015 & 0.30797 & 0.153985 \tabularnewline
181 & 0.8339 & 0.3322 & 0.1661 \tabularnewline
182 & 0.842142 & 0.315716 & 0.157858 \tabularnewline
183 & 0.874896 & 0.250208 & 0.125104 \tabularnewline
184 & 0.854503 & 0.290995 & 0.145497 \tabularnewline
185 & 0.89738 & 0.205241 & 0.10262 \tabularnewline
186 & 0.879336 & 0.241328 & 0.120664 \tabularnewline
187 & 0.868492 & 0.263016 & 0.131508 \tabularnewline
188 & 0.882919 & 0.234161 & 0.117081 \tabularnewline
189 & 0.92615 & 0.1477 & 0.0738498 \tabularnewline
190 & 0.917557 & 0.164886 & 0.0824429 \tabularnewline
191 & 0.914865 & 0.17027 & 0.0851352 \tabularnewline
192 & 0.903796 & 0.192408 & 0.096204 \tabularnewline
193 & 0.914297 & 0.171407 & 0.0857034 \tabularnewline
194 & 0.916559 & 0.166882 & 0.0834411 \tabularnewline
195 & 0.901786 & 0.196429 & 0.0982143 \tabularnewline
196 & 0.894886 & 0.210228 & 0.105114 \tabularnewline
197 & 0.887652 & 0.224696 & 0.112348 \tabularnewline
198 & 0.869237 & 0.261526 & 0.130763 \tabularnewline
199 & 0.850215 & 0.299571 & 0.149785 \tabularnewline
200 & 0.826446 & 0.347109 & 0.173554 \tabularnewline
201 & 0.829514 & 0.340973 & 0.170486 \tabularnewline
202 & 0.80972 & 0.38056 & 0.19028 \tabularnewline
203 & 0.813212 & 0.373576 & 0.186788 \tabularnewline
204 & 0.789036 & 0.421928 & 0.210964 \tabularnewline
205 & 0.762717 & 0.474565 & 0.237283 \tabularnewline
206 & 0.749355 & 0.50129 & 0.250645 \tabularnewline
207 & 0.765181 & 0.469638 & 0.234819 \tabularnewline
208 & 0.746505 & 0.506991 & 0.253495 \tabularnewline
209 & 0.761646 & 0.476709 & 0.238354 \tabularnewline
210 & 0.792791 & 0.414418 & 0.207209 \tabularnewline
211 & 0.781551 & 0.436897 & 0.218449 \tabularnewline
212 & 0.749231 & 0.501537 & 0.250769 \tabularnewline
213 & 0.727602 & 0.544795 & 0.272398 \tabularnewline
214 & 0.691883 & 0.616234 & 0.308117 \tabularnewline
215 & 0.65523 & 0.689539 & 0.34477 \tabularnewline
216 & 0.616895 & 0.76621 & 0.383105 \tabularnewline
217 & 0.625149 & 0.749703 & 0.374851 \tabularnewline
218 & 0.595316 & 0.809368 & 0.404684 \tabularnewline
219 & 0.571869 & 0.856262 & 0.428131 \tabularnewline
220 & 0.53691 & 0.926179 & 0.46309 \tabularnewline
221 & 0.529245 & 0.94151 & 0.470755 \tabularnewline
222 & 0.611011 & 0.777977 & 0.388989 \tabularnewline
223 & 0.575502 & 0.848996 & 0.424498 \tabularnewline
224 & 0.605179 & 0.789642 & 0.394821 \tabularnewline
225 & 0.592877 & 0.814246 & 0.407123 \tabularnewline
226 & 0.603837 & 0.792326 & 0.396163 \tabularnewline
227 & 0.566893 & 0.866214 & 0.433107 \tabularnewline
228 & 0.599258 & 0.801484 & 0.400742 \tabularnewline
229 & 0.865521 & 0.268957 & 0.134479 \tabularnewline
230 & 0.888111 & 0.223778 & 0.111889 \tabularnewline
231 & 0.869742 & 0.260516 & 0.130258 \tabularnewline
232 & 0.907133 & 0.185733 & 0.0928666 \tabularnewline
233 & 0.893347 & 0.213306 & 0.106653 \tabularnewline
234 & 0.883282 & 0.233436 & 0.116718 \tabularnewline
235 & 0.861785 & 0.276431 & 0.138215 \tabularnewline
236 & 0.921854 & 0.156291 & 0.0781456 \tabularnewline
237 & 0.900611 & 0.198778 & 0.0993891 \tabularnewline
238 & 0.877333 & 0.245334 & 0.122667 \tabularnewline
239 & 0.874326 & 0.251348 & 0.125674 \tabularnewline
240 & 0.843617 & 0.312766 & 0.156383 \tabularnewline
241 & 0.811378 & 0.377244 & 0.188622 \tabularnewline
242 & 0.773186 & 0.453627 & 0.226814 \tabularnewline
243 & 0.741677 & 0.516647 & 0.258323 \tabularnewline
244 & 0.697383 & 0.605234 & 0.302617 \tabularnewline
245 & 0.685054 & 0.629892 & 0.314946 \tabularnewline
246 & 0.648654 & 0.702692 & 0.351346 \tabularnewline
247 & 0.593029 & 0.813942 & 0.406971 \tabularnewline
248 & 0.636668 & 0.726665 & 0.363332 \tabularnewline
249 & 0.604358 & 0.791284 & 0.395642 \tabularnewline
250 & 0.583845 & 0.832309 & 0.416155 \tabularnewline
251 & 0.529925 & 0.94015 & 0.470075 \tabularnewline
252 & 0.529035 & 0.94193 & 0.470965 \tabularnewline
253 & 0.519948 & 0.960103 & 0.480052 \tabularnewline
254 & 0.602174 & 0.795652 & 0.397826 \tabularnewline
255 & 0.572178 & 0.855644 & 0.427822 \tabularnewline
256 & 0.505948 & 0.988104 & 0.494052 \tabularnewline
257 & 0.495709 & 0.991418 & 0.504291 \tabularnewline
258 & 0.689702 & 0.620597 & 0.310298 \tabularnewline
259 & 0.682942 & 0.634116 & 0.317058 \tabularnewline
260 & 0.907649 & 0.184701 & 0.0923507 \tabularnewline
261 & 0.865261 & 0.269477 & 0.134739 \tabularnewline
262 & 0.919722 & 0.160556 & 0.0802782 \tabularnewline
263 & 0.984654 & 0.0306911 & 0.0153455 \tabularnewline
264 & 0.967111 & 0.0657773 & 0.0328887 \tabularnewline
265 & 0.942668 & 0.114663 & 0.0573315 \tabularnewline
266 & 0.903727 & 0.192545 & 0.0962726 \tabularnewline
267 & 0.798876 & 0.402247 & 0.201124 \tabularnewline
268 & 0.603283 & 0.793435 & 0.396717 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&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]11[/C][C]0.931433[/C][C]0.137134[/C][C]0.0685669[/C][/ROW]
[ROW][C]12[/C][C]0.936973[/C][C]0.126053[/C][C]0.0630266[/C][/ROW]
[ROW][C]13[/C][C]0.888756[/C][C]0.222488[/C][C]0.111244[/C][/ROW]
[ROW][C]14[/C][C]0.834499[/C][C]0.331003[/C][C]0.165501[/C][/ROW]
[ROW][C]15[/C][C]0.769058[/C][C]0.461884[/C][C]0.230942[/C][/ROW]
[ROW][C]16[/C][C]0.683162[/C][C]0.633677[/C][C]0.316838[/C][/ROW]
[ROW][C]17[/C][C]0.590689[/C][C]0.818622[/C][C]0.409311[/C][/ROW]
[ROW][C]18[/C][C]0.544496[/C][C]0.911009[/C][C]0.455504[/C][/ROW]
[ROW][C]19[/C][C]0.550305[/C][C]0.89939[/C][C]0.449695[/C][/ROW]
[ROW][C]20[/C][C]0.474162[/C][C]0.948323[/C][C]0.525838[/C][/ROW]
[ROW][C]21[/C][C]0.507884[/C][C]0.984233[/C][C]0.492116[/C][/ROW]
[ROW][C]22[/C][C]0.572738[/C][C]0.854524[/C][C]0.427262[/C][/ROW]
[ROW][C]23[/C][C]0.638141[/C][C]0.723719[/C][C]0.361859[/C][/ROW]
[ROW][C]24[/C][C]0.634025[/C][C]0.731951[/C][C]0.365975[/C][/ROW]
[ROW][C]25[/C][C]0.568116[/C][C]0.863768[/C][C]0.431884[/C][/ROW]
[ROW][C]26[/C][C]0.514122[/C][C]0.971755[/C][C]0.485878[/C][/ROW]
[ROW][C]27[/C][C]0.473644[/C][C]0.947288[/C][C]0.526356[/C][/ROW]
[ROW][C]28[/C][C]0.450479[/C][C]0.900958[/C][C]0.549521[/C][/ROW]
[ROW][C]29[/C][C]0.393235[/C][C]0.78647[/C][C]0.606765[/C][/ROW]
[ROW][C]30[/C][C]0.331654[/C][C]0.663308[/C][C]0.668346[/C][/ROW]
[ROW][C]31[/C][C]0.355157[/C][C]0.710314[/C][C]0.644843[/C][/ROW]
[ROW][C]32[/C][C]0.305921[/C][C]0.611842[/C][C]0.694079[/C][/ROW]
[ROW][C]33[/C][C]0.309702[/C][C]0.619404[/C][C]0.690298[/C][/ROW]
[ROW][C]34[/C][C]0.278066[/C][C]0.556132[/C][C]0.721934[/C][/ROW]
[ROW][C]35[/C][C]0.236107[/C][C]0.472215[/C][C]0.763893[/C][/ROW]
[ROW][C]36[/C][C]0.211625[/C][C]0.42325[/C][C]0.788375[/C][/ROW]
[ROW][C]37[/C][C]0.185526[/C][C]0.371052[/C][C]0.814474[/C][/ROW]
[ROW][C]38[/C][C]0.171538[/C][C]0.343076[/C][C]0.828462[/C][/ROW]
[ROW][C]39[/C][C]0.152124[/C][C]0.304248[/C][C]0.847876[/C][/ROW]
[ROW][C]40[/C][C]0.141015[/C][C]0.282031[/C][C]0.858985[/C][/ROW]
[ROW][C]41[/C][C]0.223539[/C][C]0.447078[/C][C]0.776461[/C][/ROW]
[ROW][C]42[/C][C]0.189684[/C][C]0.379368[/C][C]0.810316[/C][/ROW]
[ROW][C]43[/C][C]0.164787[/C][C]0.329574[/C][C]0.835213[/C][/ROW]
[ROW][C]44[/C][C]0.16062[/C][C]0.32124[/C][C]0.83938[/C][/ROW]
[ROW][C]45[/C][C]0.148986[/C][C]0.297972[/C][C]0.851014[/C][/ROW]
[ROW][C]46[/C][C]0.12862[/C][C]0.257241[/C][C]0.87138[/C][/ROW]
[ROW][C]47[/C][C]0.1698[/C][C]0.339599[/C][C]0.8302[/C][/ROW]
[ROW][C]48[/C][C]0.200605[/C][C]0.401209[/C][C]0.799395[/C][/ROW]
[ROW][C]49[/C][C]0.252257[/C][C]0.504513[/C][C]0.747743[/C][/ROW]
[ROW][C]50[/C][C]0.22441[/C][C]0.44882[/C][C]0.77559[/C][/ROW]
[ROW][C]51[/C][C]0.196018[/C][C]0.392036[/C][C]0.803982[/C][/ROW]
[ROW][C]52[/C][C]0.20584[/C][C]0.411679[/C][C]0.79416[/C][/ROW]
[ROW][C]53[/C][C]0.174715[/C][C]0.349431[/C][C]0.825285[/C][/ROW]
[ROW][C]54[/C][C]0.14623[/C][C]0.29246[/C][C]0.85377[/C][/ROW]
[ROW][C]55[/C][C]0.223404[/C][C]0.446809[/C][C]0.776596[/C][/ROW]
[ROW][C]56[/C][C]0.19164[/C][C]0.383281[/C][C]0.80836[/C][/ROW]
[ROW][C]57[/C][C]0.539992[/C][C]0.920016[/C][C]0.460008[/C][/ROW]
[ROW][C]58[/C][C]0.650253[/C][C]0.699494[/C][C]0.349747[/C][/ROW]
[ROW][C]59[/C][C]0.615643[/C][C]0.768713[/C][C]0.384357[/C][/ROW]
[ROW][C]60[/C][C]0.608503[/C][C]0.782993[/C][C]0.391497[/C][/ROW]
[ROW][C]61[/C][C]0.612567[/C][C]0.774866[/C][C]0.387433[/C][/ROW]
[ROW][C]62[/C][C]0.575897[/C][C]0.848207[/C][C]0.424103[/C][/ROW]
[ROW][C]63[/C][C]0.585816[/C][C]0.828368[/C][C]0.414184[/C][/ROW]
[ROW][C]64[/C][C]0.631791[/C][C]0.736418[/C][C]0.368209[/C][/ROW]
[ROW][C]65[/C][C]0.662325[/C][C]0.675349[/C][C]0.337675[/C][/ROW]
[ROW][C]66[/C][C]0.631655[/C][C]0.73669[/C][C]0.368345[/C][/ROW]
[ROW][C]67[/C][C]0.603352[/C][C]0.793296[/C][C]0.396648[/C][/ROW]
[ROW][C]68[/C][C]0.573865[/C][C]0.85227[/C][C]0.426135[/C][/ROW]
[ROW][C]69[/C][C]0.575483[/C][C]0.849035[/C][C]0.424517[/C][/ROW]
[ROW][C]70[/C][C]0.543566[/C][C]0.912868[/C][C]0.456434[/C][/ROW]
[ROW][C]71[/C][C]0.508812[/C][C]0.982375[/C][C]0.491188[/C][/ROW]
[ROW][C]72[/C][C]0.475513[/C][C]0.951026[/C][C]0.524487[/C][/ROW]
[ROW][C]73[/C][C]0.445995[/C][C]0.891989[/C][C]0.554005[/C][/ROW]
[ROW][C]74[/C][C]0.532247[/C][C]0.935506[/C][C]0.467753[/C][/ROW]
[ROW][C]75[/C][C]0.517333[/C][C]0.965333[/C][C]0.482667[/C][/ROW]
[ROW][C]76[/C][C]0.492355[/C][C]0.98471[/C][C]0.507645[/C][/ROW]
[ROW][C]77[/C][C]0.465993[/C][C]0.931986[/C][C]0.534007[/C][/ROW]
[ROW][C]78[/C][C]0.456694[/C][C]0.913389[/C][C]0.543306[/C][/ROW]
[ROW][C]79[/C][C]0.423222[/C][C]0.846444[/C][C]0.576778[/C][/ROW]
[ROW][C]80[/C][C]0.421[/C][C]0.841999[/C][C]0.579[/C][/ROW]
[ROW][C]81[/C][C]0.385794[/C][C]0.771587[/C][C]0.614206[/C][/ROW]
[ROW][C]82[/C][C]0.39117[/C][C]0.78234[/C][C]0.60883[/C][/ROW]
[ROW][C]83[/C][C]0.358355[/C][C]0.716711[/C][C]0.641645[/C][/ROW]
[ROW][C]84[/C][C]0.570134[/C][C]0.859732[/C][C]0.429866[/C][/ROW]
[ROW][C]85[/C][C]0.542188[/C][C]0.915625[/C][C]0.457812[/C][/ROW]
[ROW][C]86[/C][C]0.51344[/C][C]0.97312[/C][C]0.48656[/C][/ROW]
[ROW][C]87[/C][C]0.501335[/C][C]0.997329[/C][C]0.498665[/C][/ROW]
[ROW][C]88[/C][C]0.48635[/C][C]0.9727[/C][C]0.51365[/C][/ROW]
[ROW][C]89[/C][C]0.478225[/C][C]0.95645[/C][C]0.521775[/C][/ROW]
[ROW][C]90[/C][C]0.455743[/C][C]0.911487[/C][C]0.544257[/C][/ROW]
[ROW][C]91[/C][C]0.492233[/C][C]0.984467[/C][C]0.507767[/C][/ROW]
[ROW][C]92[/C][C]0.656171[/C][C]0.687658[/C][C]0.343829[/C][/ROW]
[ROW][C]93[/C][C]0.637221[/C][C]0.725558[/C][C]0.362779[/C][/ROW]
[ROW][C]94[/C][C]0.629559[/C][C]0.740881[/C][C]0.370441[/C][/ROW]
[ROW][C]95[/C][C]0.634453[/C][C]0.731095[/C][C]0.365547[/C][/ROW]
[ROW][C]96[/C][C]0.631733[/C][C]0.736535[/C][C]0.368267[/C][/ROW]
[ROW][C]97[/C][C]0.700244[/C][C]0.599513[/C][C]0.299756[/C][/ROW]
[ROW][C]98[/C][C]0.676073[/C][C]0.647855[/C][C]0.323927[/C][/ROW]
[ROW][C]99[/C][C]0.709681[/C][C]0.580638[/C][C]0.290319[/C][/ROW]
[ROW][C]100[/C][C]0.71288[/C][C]0.57424[/C][C]0.28712[/C][/ROW]
[ROW][C]101[/C][C]0.700342[/C][C]0.599316[/C][C]0.299658[/C][/ROW]
[ROW][C]102[/C][C]0.667952[/C][C]0.664097[/C][C]0.332048[/C][/ROW]
[ROW][C]103[/C][C]0.643901[/C][C]0.712198[/C][C]0.356099[/C][/ROW]
[ROW][C]104[/C][C]0.619958[/C][C]0.760084[/C][C]0.380042[/C][/ROW]
[ROW][C]105[/C][C]0.704881[/C][C]0.590238[/C][C]0.295119[/C][/ROW]
[ROW][C]106[/C][C]0.68734[/C][C]0.625319[/C][C]0.31266[/C][/ROW]
[ROW][C]107[/C][C]0.734659[/C][C]0.530682[/C][C]0.265341[/C][/ROW]
[ROW][C]108[/C][C]0.823504[/C][C]0.352993[/C][C]0.176496[/C][/ROW]
[ROW][C]109[/C][C]0.823018[/C][C]0.353964[/C][C]0.176982[/C][/ROW]
[ROW][C]110[/C][C]0.803593[/C][C]0.392814[/C][C]0.196407[/C][/ROW]
[ROW][C]111[/C][C]0.782254[/C][C]0.435493[/C][C]0.217746[/C][/ROW]
[ROW][C]112[/C][C]0.758068[/C][C]0.483864[/C][C]0.241932[/C][/ROW]
[ROW][C]113[/C][C]0.820098[/C][C]0.359804[/C][C]0.179902[/C][/ROW]
[ROW][C]114[/C][C]0.872118[/C][C]0.255764[/C][C]0.127882[/C][/ROW]
[ROW][C]115[/C][C]0.919176[/C][C]0.161647[/C][C]0.0808236[/C][/ROW]
[ROW][C]116[/C][C]0.925814[/C][C]0.148372[/C][C]0.0741861[/C][/ROW]
[ROW][C]117[/C][C]0.915785[/C][C]0.168429[/C][C]0.0842145[/C][/ROW]
[ROW][C]118[/C][C]0.901337[/C][C]0.197326[/C][C]0.0986629[/C][/ROW]
[ROW][C]119[/C][C]0.888818[/C][C]0.222363[/C][C]0.111182[/C][/ROW]
[ROW][C]120[/C][C]0.895257[/C][C]0.209487[/C][C]0.104743[/C][/ROW]
[ROW][C]121[/C][C]0.878836[/C][C]0.242329[/C][C]0.121164[/C][/ROW]
[ROW][C]122[/C][C]0.863434[/C][C]0.273132[/C][C]0.136566[/C][/ROW]
[ROW][C]123[/C][C]0.861427[/C][C]0.277146[/C][C]0.138573[/C][/ROW]
[ROW][C]124[/C][C]0.894919[/C][C]0.210161[/C][C]0.105081[/C][/ROW]
[ROW][C]125[/C][C]0.903722[/C][C]0.192557[/C][C]0.0962784[/C][/ROW]
[ROW][C]126[/C][C]0.890953[/C][C]0.218095[/C][C]0.109047[/C][/ROW]
[ROW][C]127[/C][C]0.877901[/C][C]0.244199[/C][C]0.122099[/C][/ROW]
[ROW][C]128[/C][C]0.860148[/C][C]0.279704[/C][C]0.139852[/C][/ROW]
[ROW][C]129[/C][C]0.868974[/C][C]0.262052[/C][C]0.131026[/C][/ROW]
[ROW][C]130[/C][C]0.851079[/C][C]0.297842[/C][C]0.148921[/C][/ROW]
[ROW][C]131[/C][C]0.83068[/C][C]0.338639[/C][C]0.16932[/C][/ROW]
[ROW][C]132[/C][C]0.811056[/C][C]0.377887[/C][C]0.188944[/C][/ROW]
[ROW][C]133[/C][C]0.791412[/C][C]0.417176[/C][C]0.208588[/C][/ROW]
[ROW][C]134[/C][C]0.772533[/C][C]0.454934[/C][C]0.227467[/C][/ROW]
[ROW][C]135[/C][C]0.751785[/C][C]0.49643[/C][C]0.248215[/C][/ROW]
[ROW][C]136[/C][C]0.724088[/C][C]0.551824[/C][C]0.275912[/C][/ROW]
[ROW][C]137[/C][C]0.739534[/C][C]0.520932[/C][C]0.260466[/C][/ROW]
[ROW][C]138[/C][C]0.73515[/C][C]0.5297[/C][C]0.26485[/C][/ROW]
[ROW][C]139[/C][C]0.728371[/C][C]0.543258[/C][C]0.271629[/C][/ROW]
[ROW][C]140[/C][C]0.716357[/C][C]0.567286[/C][C]0.283643[/C][/ROW]
[ROW][C]141[/C][C]0.708695[/C][C]0.58261[/C][C]0.291305[/C][/ROW]
[ROW][C]142[/C][C]0.692161[/C][C]0.615677[/C][C]0.307839[/C][/ROW]
[ROW][C]143[/C][C]0.662082[/C][C]0.675835[/C][C]0.337918[/C][/ROW]
[ROW][C]144[/C][C]0.694622[/C][C]0.610755[/C][C]0.305378[/C][/ROW]
[ROW][C]145[/C][C]0.663308[/C][C]0.673385[/C][C]0.336692[/C][/ROW]
[ROW][C]146[/C][C]0.640439[/C][C]0.719123[/C][C]0.359561[/C][/ROW]
[ROW][C]147[/C][C]0.610653[/C][C]0.778694[/C][C]0.389347[/C][/ROW]
[ROW][C]148[/C][C]0.576829[/C][C]0.846343[/C][C]0.423171[/C][/ROW]
[ROW][C]149[/C][C]0.542757[/C][C]0.914486[/C][C]0.457243[/C][/ROW]
[ROW][C]150[/C][C]0.51841[/C][C]0.963181[/C][C]0.48159[/C][/ROW]
[ROW][C]151[/C][C]0.774296[/C][C]0.451408[/C][C]0.225704[/C][/ROW]
[ROW][C]152[/C][C]0.765992[/C][C]0.468016[/C][C]0.234008[/C][/ROW]
[ROW][C]153[/C][C]0.761605[/C][C]0.47679[/C][C]0.238395[/C][/ROW]
[ROW][C]154[/C][C]0.734423[/C][C]0.531155[/C][C]0.265577[/C][/ROW]
[ROW][C]155[/C][C]0.717676[/C][C]0.564647[/C][C]0.282324[/C][/ROW]
[ROW][C]156[/C][C]0.688542[/C][C]0.622917[/C][C]0.311458[/C][/ROW]
[ROW][C]157[/C][C]0.682071[/C][C]0.635858[/C][C]0.317929[/C][/ROW]
[ROW][C]158[/C][C]0.656865[/C][C]0.686269[/C][C]0.343135[/C][/ROW]
[ROW][C]159[/C][C]0.642256[/C][C]0.715489[/C][C]0.357744[/C][/ROW]
[ROW][C]160[/C][C]0.642621[/C][C]0.714758[/C][C]0.357379[/C][/ROW]
[ROW][C]161[/C][C]0.634055[/C][C]0.731891[/C][C]0.365945[/C][/ROW]
[ROW][C]162[/C][C]0.632987[/C][C]0.734026[/C][C]0.367013[/C][/ROW]
[ROW][C]163[/C][C]0.600807[/C][C]0.798386[/C][C]0.399193[/C][/ROW]
[ROW][C]164[/C][C]0.914983[/C][C]0.170034[/C][C]0.0850169[/C][/ROW]
[ROW][C]165[/C][C]0.902761[/C][C]0.194478[/C][C]0.0972392[/C][/ROW]
[ROW][C]166[/C][C]0.895438[/C][C]0.209125[/C][C]0.104562[/C][/ROW]
[ROW][C]167[/C][C]0.889954[/C][C]0.220093[/C][C]0.110046[/C][/ROW]
[ROW][C]168[/C][C]0.87789[/C][C]0.244219[/C][C]0.12211[/C][/ROW]
[ROW][C]169[/C][C]0.859251[/C][C]0.281498[/C][C]0.140749[/C][/ROW]
[ROW][C]170[/C][C]0.874757[/C][C]0.250486[/C][C]0.125243[/C][/ROW]
[ROW][C]171[/C][C]0.868034[/C][C]0.263933[/C][C]0.131966[/C][/ROW]
[ROW][C]172[/C][C]0.86337[/C][C]0.27326[/C][C]0.13663[/C][/ROW]
[ROW][C]173[/C][C]0.861614[/C][C]0.276771[/C][C]0.138386[/C][/ROW]
[ROW][C]174[/C][C]0.845792[/C][C]0.308416[/C][C]0.154208[/C][/ROW]
[ROW][C]175[/C][C]0.828524[/C][C]0.342951[/C][C]0.171476[/C][/ROW]
[ROW][C]176[/C][C]0.847526[/C][C]0.304949[/C][C]0.152474[/C][/ROW]
[ROW][C]177[/C][C]0.828318[/C][C]0.343363[/C][C]0.171682[/C][/ROW]
[ROW][C]178[/C][C]0.832483[/C][C]0.335033[/C][C]0.167517[/C][/ROW]
[ROW][C]179[/C][C]0.818808[/C][C]0.362384[/C][C]0.181192[/C][/ROW]
[ROW][C]180[/C][C]0.846015[/C][C]0.30797[/C][C]0.153985[/C][/ROW]
[ROW][C]181[/C][C]0.8339[/C][C]0.3322[/C][C]0.1661[/C][/ROW]
[ROW][C]182[/C][C]0.842142[/C][C]0.315716[/C][C]0.157858[/C][/ROW]
[ROW][C]183[/C][C]0.874896[/C][C]0.250208[/C][C]0.125104[/C][/ROW]
[ROW][C]184[/C][C]0.854503[/C][C]0.290995[/C][C]0.145497[/C][/ROW]
[ROW][C]185[/C][C]0.89738[/C][C]0.205241[/C][C]0.10262[/C][/ROW]
[ROW][C]186[/C][C]0.879336[/C][C]0.241328[/C][C]0.120664[/C][/ROW]
[ROW][C]187[/C][C]0.868492[/C][C]0.263016[/C][C]0.131508[/C][/ROW]
[ROW][C]188[/C][C]0.882919[/C][C]0.234161[/C][C]0.117081[/C][/ROW]
[ROW][C]189[/C][C]0.92615[/C][C]0.1477[/C][C]0.0738498[/C][/ROW]
[ROW][C]190[/C][C]0.917557[/C][C]0.164886[/C][C]0.0824429[/C][/ROW]
[ROW][C]191[/C][C]0.914865[/C][C]0.17027[/C][C]0.0851352[/C][/ROW]
[ROW][C]192[/C][C]0.903796[/C][C]0.192408[/C][C]0.096204[/C][/ROW]
[ROW][C]193[/C][C]0.914297[/C][C]0.171407[/C][C]0.0857034[/C][/ROW]
[ROW][C]194[/C][C]0.916559[/C][C]0.166882[/C][C]0.0834411[/C][/ROW]
[ROW][C]195[/C][C]0.901786[/C][C]0.196429[/C][C]0.0982143[/C][/ROW]
[ROW][C]196[/C][C]0.894886[/C][C]0.210228[/C][C]0.105114[/C][/ROW]
[ROW][C]197[/C][C]0.887652[/C][C]0.224696[/C][C]0.112348[/C][/ROW]
[ROW][C]198[/C][C]0.869237[/C][C]0.261526[/C][C]0.130763[/C][/ROW]
[ROW][C]199[/C][C]0.850215[/C][C]0.299571[/C][C]0.149785[/C][/ROW]
[ROW][C]200[/C][C]0.826446[/C][C]0.347109[/C][C]0.173554[/C][/ROW]
[ROW][C]201[/C][C]0.829514[/C][C]0.340973[/C][C]0.170486[/C][/ROW]
[ROW][C]202[/C][C]0.80972[/C][C]0.38056[/C][C]0.19028[/C][/ROW]
[ROW][C]203[/C][C]0.813212[/C][C]0.373576[/C][C]0.186788[/C][/ROW]
[ROW][C]204[/C][C]0.789036[/C][C]0.421928[/C][C]0.210964[/C][/ROW]
[ROW][C]205[/C][C]0.762717[/C][C]0.474565[/C][C]0.237283[/C][/ROW]
[ROW][C]206[/C][C]0.749355[/C][C]0.50129[/C][C]0.250645[/C][/ROW]
[ROW][C]207[/C][C]0.765181[/C][C]0.469638[/C][C]0.234819[/C][/ROW]
[ROW][C]208[/C][C]0.746505[/C][C]0.506991[/C][C]0.253495[/C][/ROW]
[ROW][C]209[/C][C]0.761646[/C][C]0.476709[/C][C]0.238354[/C][/ROW]
[ROW][C]210[/C][C]0.792791[/C][C]0.414418[/C][C]0.207209[/C][/ROW]
[ROW][C]211[/C][C]0.781551[/C][C]0.436897[/C][C]0.218449[/C][/ROW]
[ROW][C]212[/C][C]0.749231[/C][C]0.501537[/C][C]0.250769[/C][/ROW]
[ROW][C]213[/C][C]0.727602[/C][C]0.544795[/C][C]0.272398[/C][/ROW]
[ROW][C]214[/C][C]0.691883[/C][C]0.616234[/C][C]0.308117[/C][/ROW]
[ROW][C]215[/C][C]0.65523[/C][C]0.689539[/C][C]0.34477[/C][/ROW]
[ROW][C]216[/C][C]0.616895[/C][C]0.76621[/C][C]0.383105[/C][/ROW]
[ROW][C]217[/C][C]0.625149[/C][C]0.749703[/C][C]0.374851[/C][/ROW]
[ROW][C]218[/C][C]0.595316[/C][C]0.809368[/C][C]0.404684[/C][/ROW]
[ROW][C]219[/C][C]0.571869[/C][C]0.856262[/C][C]0.428131[/C][/ROW]
[ROW][C]220[/C][C]0.53691[/C][C]0.926179[/C][C]0.46309[/C][/ROW]
[ROW][C]221[/C][C]0.529245[/C][C]0.94151[/C][C]0.470755[/C][/ROW]
[ROW][C]222[/C][C]0.611011[/C][C]0.777977[/C][C]0.388989[/C][/ROW]
[ROW][C]223[/C][C]0.575502[/C][C]0.848996[/C][C]0.424498[/C][/ROW]
[ROW][C]224[/C][C]0.605179[/C][C]0.789642[/C][C]0.394821[/C][/ROW]
[ROW][C]225[/C][C]0.592877[/C][C]0.814246[/C][C]0.407123[/C][/ROW]
[ROW][C]226[/C][C]0.603837[/C][C]0.792326[/C][C]0.396163[/C][/ROW]
[ROW][C]227[/C][C]0.566893[/C][C]0.866214[/C][C]0.433107[/C][/ROW]
[ROW][C]228[/C][C]0.599258[/C][C]0.801484[/C][C]0.400742[/C][/ROW]
[ROW][C]229[/C][C]0.865521[/C][C]0.268957[/C][C]0.134479[/C][/ROW]
[ROW][C]230[/C][C]0.888111[/C][C]0.223778[/C][C]0.111889[/C][/ROW]
[ROW][C]231[/C][C]0.869742[/C][C]0.260516[/C][C]0.130258[/C][/ROW]
[ROW][C]232[/C][C]0.907133[/C][C]0.185733[/C][C]0.0928666[/C][/ROW]
[ROW][C]233[/C][C]0.893347[/C][C]0.213306[/C][C]0.106653[/C][/ROW]
[ROW][C]234[/C][C]0.883282[/C][C]0.233436[/C][C]0.116718[/C][/ROW]
[ROW][C]235[/C][C]0.861785[/C][C]0.276431[/C][C]0.138215[/C][/ROW]
[ROW][C]236[/C][C]0.921854[/C][C]0.156291[/C][C]0.0781456[/C][/ROW]
[ROW][C]237[/C][C]0.900611[/C][C]0.198778[/C][C]0.0993891[/C][/ROW]
[ROW][C]238[/C][C]0.877333[/C][C]0.245334[/C][C]0.122667[/C][/ROW]
[ROW][C]239[/C][C]0.874326[/C][C]0.251348[/C][C]0.125674[/C][/ROW]
[ROW][C]240[/C][C]0.843617[/C][C]0.312766[/C][C]0.156383[/C][/ROW]
[ROW][C]241[/C][C]0.811378[/C][C]0.377244[/C][C]0.188622[/C][/ROW]
[ROW][C]242[/C][C]0.773186[/C][C]0.453627[/C][C]0.226814[/C][/ROW]
[ROW][C]243[/C][C]0.741677[/C][C]0.516647[/C][C]0.258323[/C][/ROW]
[ROW][C]244[/C][C]0.697383[/C][C]0.605234[/C][C]0.302617[/C][/ROW]
[ROW][C]245[/C][C]0.685054[/C][C]0.629892[/C][C]0.314946[/C][/ROW]
[ROW][C]246[/C][C]0.648654[/C][C]0.702692[/C][C]0.351346[/C][/ROW]
[ROW][C]247[/C][C]0.593029[/C][C]0.813942[/C][C]0.406971[/C][/ROW]
[ROW][C]248[/C][C]0.636668[/C][C]0.726665[/C][C]0.363332[/C][/ROW]
[ROW][C]249[/C][C]0.604358[/C][C]0.791284[/C][C]0.395642[/C][/ROW]
[ROW][C]250[/C][C]0.583845[/C][C]0.832309[/C][C]0.416155[/C][/ROW]
[ROW][C]251[/C][C]0.529925[/C][C]0.94015[/C][C]0.470075[/C][/ROW]
[ROW][C]252[/C][C]0.529035[/C][C]0.94193[/C][C]0.470965[/C][/ROW]
[ROW][C]253[/C][C]0.519948[/C][C]0.960103[/C][C]0.480052[/C][/ROW]
[ROW][C]254[/C][C]0.602174[/C][C]0.795652[/C][C]0.397826[/C][/ROW]
[ROW][C]255[/C][C]0.572178[/C][C]0.855644[/C][C]0.427822[/C][/ROW]
[ROW][C]256[/C][C]0.505948[/C][C]0.988104[/C][C]0.494052[/C][/ROW]
[ROW][C]257[/C][C]0.495709[/C][C]0.991418[/C][C]0.504291[/C][/ROW]
[ROW][C]258[/C][C]0.689702[/C][C]0.620597[/C][C]0.310298[/C][/ROW]
[ROW][C]259[/C][C]0.682942[/C][C]0.634116[/C][C]0.317058[/C][/ROW]
[ROW][C]260[/C][C]0.907649[/C][C]0.184701[/C][C]0.0923507[/C][/ROW]
[ROW][C]261[/C][C]0.865261[/C][C]0.269477[/C][C]0.134739[/C][/ROW]
[ROW][C]262[/C][C]0.919722[/C][C]0.160556[/C][C]0.0802782[/C][/ROW]
[ROW][C]263[/C][C]0.984654[/C][C]0.0306911[/C][C]0.0153455[/C][/ROW]
[ROW][C]264[/C][C]0.967111[/C][C]0.0657773[/C][C]0.0328887[/C][/ROW]
[ROW][C]265[/C][C]0.942668[/C][C]0.114663[/C][C]0.0573315[/C][/ROW]
[ROW][C]266[/C][C]0.903727[/C][C]0.192545[/C][C]0.0962726[/C][/ROW]
[ROW][C]267[/C][C]0.798876[/C][C]0.402247[/C][C]0.201124[/C][/ROW]
[ROW][C]268[/C][C]0.603283[/C][C]0.793435[/C][C]0.396717[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&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
110.9314330.1371340.0685669
120.9369730.1260530.0630266
130.8887560.2224880.111244
140.8344990.3310030.165501
150.7690580.4618840.230942
160.6831620.6336770.316838
170.5906890.8186220.409311
180.5444960.9110090.455504
190.5503050.899390.449695
200.4741620.9483230.525838
210.5078840.9842330.492116
220.5727380.8545240.427262
230.6381410.7237190.361859
240.6340250.7319510.365975
250.5681160.8637680.431884
260.5141220.9717550.485878
270.4736440.9472880.526356
280.4504790.9009580.549521
290.3932350.786470.606765
300.3316540.6633080.668346
310.3551570.7103140.644843
320.3059210.6118420.694079
330.3097020.6194040.690298
340.2780660.5561320.721934
350.2361070.4722150.763893
360.2116250.423250.788375
370.1855260.3710520.814474
380.1715380.3430760.828462
390.1521240.3042480.847876
400.1410150.2820310.858985
410.2235390.4470780.776461
420.1896840.3793680.810316
430.1647870.3295740.835213
440.160620.321240.83938
450.1489860.2979720.851014
460.128620.2572410.87138
470.16980.3395990.8302
480.2006050.4012090.799395
490.2522570.5045130.747743
500.224410.448820.77559
510.1960180.3920360.803982
520.205840.4116790.79416
530.1747150.3494310.825285
540.146230.292460.85377
550.2234040.4468090.776596
560.191640.3832810.80836
570.5399920.9200160.460008
580.6502530.6994940.349747
590.6156430.7687130.384357
600.6085030.7829930.391497
610.6125670.7748660.387433
620.5758970.8482070.424103
630.5858160.8283680.414184
640.6317910.7364180.368209
650.6623250.6753490.337675
660.6316550.736690.368345
670.6033520.7932960.396648
680.5738650.852270.426135
690.5754830.8490350.424517
700.5435660.9128680.456434
710.5088120.9823750.491188
720.4755130.9510260.524487
730.4459950.8919890.554005
740.5322470.9355060.467753
750.5173330.9653330.482667
760.4923550.984710.507645
770.4659930.9319860.534007
780.4566940.9133890.543306
790.4232220.8464440.576778
800.4210.8419990.579
810.3857940.7715870.614206
820.391170.782340.60883
830.3583550.7167110.641645
840.5701340.8597320.429866
850.5421880.9156250.457812
860.513440.973120.48656
870.5013350.9973290.498665
880.486350.97270.51365
890.4782250.956450.521775
900.4557430.9114870.544257
910.4922330.9844670.507767
920.6561710.6876580.343829
930.6372210.7255580.362779
940.6295590.7408810.370441
950.6344530.7310950.365547
960.6317330.7365350.368267
970.7002440.5995130.299756
980.6760730.6478550.323927
990.7096810.5806380.290319
1000.712880.574240.28712
1010.7003420.5993160.299658
1020.6679520.6640970.332048
1030.6439010.7121980.356099
1040.6199580.7600840.380042
1050.7048810.5902380.295119
1060.687340.6253190.31266
1070.7346590.5306820.265341
1080.8235040.3529930.176496
1090.8230180.3539640.176982
1100.8035930.3928140.196407
1110.7822540.4354930.217746
1120.7580680.4838640.241932
1130.8200980.3598040.179902
1140.8721180.2557640.127882
1150.9191760.1616470.0808236
1160.9258140.1483720.0741861
1170.9157850.1684290.0842145
1180.9013370.1973260.0986629
1190.8888180.2223630.111182
1200.8952570.2094870.104743
1210.8788360.2423290.121164
1220.8634340.2731320.136566
1230.8614270.2771460.138573
1240.8949190.2101610.105081
1250.9037220.1925570.0962784
1260.8909530.2180950.109047
1270.8779010.2441990.122099
1280.8601480.2797040.139852
1290.8689740.2620520.131026
1300.8510790.2978420.148921
1310.830680.3386390.16932
1320.8110560.3778870.188944
1330.7914120.4171760.208588
1340.7725330.4549340.227467
1350.7517850.496430.248215
1360.7240880.5518240.275912
1370.7395340.5209320.260466
1380.735150.52970.26485
1390.7283710.5432580.271629
1400.7163570.5672860.283643
1410.7086950.582610.291305
1420.6921610.6156770.307839
1430.6620820.6758350.337918
1440.6946220.6107550.305378
1450.6633080.6733850.336692
1460.6404390.7191230.359561
1470.6106530.7786940.389347
1480.5768290.8463430.423171
1490.5427570.9144860.457243
1500.518410.9631810.48159
1510.7742960.4514080.225704
1520.7659920.4680160.234008
1530.7616050.476790.238395
1540.7344230.5311550.265577
1550.7176760.5646470.282324
1560.6885420.6229170.311458
1570.6820710.6358580.317929
1580.6568650.6862690.343135
1590.6422560.7154890.357744
1600.6426210.7147580.357379
1610.6340550.7318910.365945
1620.6329870.7340260.367013
1630.6008070.7983860.399193
1640.9149830.1700340.0850169
1650.9027610.1944780.0972392
1660.8954380.2091250.104562
1670.8899540.2200930.110046
1680.877890.2442190.12211
1690.8592510.2814980.140749
1700.8747570.2504860.125243
1710.8680340.2639330.131966
1720.863370.273260.13663
1730.8616140.2767710.138386
1740.8457920.3084160.154208
1750.8285240.3429510.171476
1760.8475260.3049490.152474
1770.8283180.3433630.171682
1780.8324830.3350330.167517
1790.8188080.3623840.181192
1800.8460150.307970.153985
1810.83390.33220.1661
1820.8421420.3157160.157858
1830.8748960.2502080.125104
1840.8545030.2909950.145497
1850.897380.2052410.10262
1860.8793360.2413280.120664
1870.8684920.2630160.131508
1880.8829190.2341610.117081
1890.926150.14770.0738498
1900.9175570.1648860.0824429
1910.9148650.170270.0851352
1920.9037960.1924080.096204
1930.9142970.1714070.0857034
1940.9165590.1668820.0834411
1950.9017860.1964290.0982143
1960.8948860.2102280.105114
1970.8876520.2246960.112348
1980.8692370.2615260.130763
1990.8502150.2995710.149785
2000.8264460.3471090.173554
2010.8295140.3409730.170486
2020.809720.380560.19028
2030.8132120.3735760.186788
2040.7890360.4219280.210964
2050.7627170.4745650.237283
2060.7493550.501290.250645
2070.7651810.4696380.234819
2080.7465050.5069910.253495
2090.7616460.4767090.238354
2100.7927910.4144180.207209
2110.7815510.4368970.218449
2120.7492310.5015370.250769
2130.7276020.5447950.272398
2140.6918830.6162340.308117
2150.655230.6895390.34477
2160.6168950.766210.383105
2170.6251490.7497030.374851
2180.5953160.8093680.404684
2190.5718690.8562620.428131
2200.536910.9261790.46309
2210.5292450.941510.470755
2220.6110110.7779770.388989
2230.5755020.8489960.424498
2240.6051790.7896420.394821
2250.5928770.8142460.407123
2260.6038370.7923260.396163
2270.5668930.8662140.433107
2280.5992580.8014840.400742
2290.8655210.2689570.134479
2300.8881110.2237780.111889
2310.8697420.2605160.130258
2320.9071330.1857330.0928666
2330.8933470.2133060.106653
2340.8832820.2334360.116718
2350.8617850.2764310.138215
2360.9218540.1562910.0781456
2370.9006110.1987780.0993891
2380.8773330.2453340.122667
2390.8743260.2513480.125674
2400.8436170.3127660.156383
2410.8113780.3772440.188622
2420.7731860.4536270.226814
2430.7416770.5166470.258323
2440.6973830.6052340.302617
2450.6850540.6298920.314946
2460.6486540.7026920.351346
2470.5930290.8139420.406971
2480.6366680.7266650.363332
2490.6043580.7912840.395642
2500.5838450.8323090.416155
2510.5299250.940150.470075
2520.5290350.941930.470965
2530.5199480.9601030.480052
2540.6021740.7956520.397826
2550.5721780.8556440.427822
2560.5059480.9881040.494052
2570.4957090.9914180.504291
2580.6897020.6205970.310298
2590.6829420.6341160.317058
2600.9076490.1847010.0923507
2610.8652610.2694770.134739
2620.9197220.1605560.0802782
2630.9846540.03069110.0153455
2640.9671110.06577730.0328887
2650.9426680.1146630.0573315
2660.9037270.1925450.0962726
2670.7988760.4022470.201124
2680.6032830.7934350.396717






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00387597OK
10% type I error level20.00775194OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 1 & 0.00387597 & OK \tabularnewline
10% type I error level & 2 & 0.00775194 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=262485&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]1[/C][C]0.00387597[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.00775194[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=262485&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=262485&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level10.00387597OK
10% type I error level20.00775194OK


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')
}