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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 10:30:29 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418639801pqb2qeevdqrb43u.htm/, Retrieved Thu, 16 May 2024 12:01:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268054, Retrieved Thu, 16 May 2024 12:01:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact78

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [multiple regressi...] [2014-12-15 10:30:29] [563beb1edea669d15db48231c3b63ca2] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12.9 26 50 21 149 18
7.4 51 68 26 152 7
12.2 57 62 22 139 31
12.8 37 54 22 148 39
7.4 67 71 18 158 46
6.7 43 54 23 128 31
12.6 52 65 12 224 67
14.8 52 73 20 159 35
13.3 43 52 22 105 52
11.1 84 84 21 159 77
8.2 67 42 19 167 37
11.4 49 66 22 165 32
6.4 70 65 15 159 36
10.6 52 78 20 119 38
12.0 58 73 19 176 69
6.3 68 75 18 54 21
11.3 62 72 15 91 26
11.9 43 66 20 163 54
9.3 56 70 21 124 36
9.6 56 61 21 137 42
10.0 74 81 15 121 23
6.4 65 71 16 153 34
13.8 63 69 23 148 112
10.8 58 71 21 221 35
13.8 57 72 18 188 47
11.7 63 68 25 149 47
10.9 53 70 9 244 37
16.1 57 68 30 148 109
13.4 51 61 20 92 24
9.9 64 67 23 150 20
11.5 53 76 16 153 22
8.3 29 70 16 94 23
11.7 54 60 19 156 32
6.1 51 77 25 146 7
9.0 58 72 25 132 30
9.7 43 69 18 161 92
10.8 51 71 23 105 43
10.3 53 62 21 97 55
10.4 54 70 10 151 16
12.7 56 64 14 131 49
9.3 61 58 22 166 71
11.8 47 76 26 157 43
5.9 39 52 23 111 29
11.4 48 59 23 145 56
13.0 50 68 24 162 46
10.8 35 76 24 163 19
12.3 30 65 18 59 23
11.3 68 67 23 187 59
11.8 49 59 15 109 30
7.9 61 69 19 90 61
12.7 67 76 16 105 7
12.3 47 63 25 83 38
11.6 56 75 23 116 32
6.7 50 63 17 42 16
10.9 43 60 19 148 19
12.1 67 73 21 155 22
13.3 62 63 18 125 48
10.1 57 70 27 116 23
5.7 41 75 21 128 26
14.3 54 66 13 138 33
8.0 45 63 8 49 9
13.3 48 63 29 96 24
9.3 61 64 28 164 34
12.5 56 70 23 162 48
7.6 41 75 21 99 18
15.9 43 61 19 202 43
9.2 53 60 19 186 33
9.1 44 62 20 66 28
11.1 66 73 18 183 71
13.0 58 61 19 214 26
14.5 46 66 17 188 67
12.2 37 64 19 104 34
12.3 51 59 25 177 80
11.4 51 64 19 126 29
8.8 56 60 22 76 16
14.6 66 56 23 99 59
7.3 45 66 26 157 58
12.6 37 78 14 139 32
NA 59 53 28 78 47
13.0 42 67 16 162 43
12.6 38 59 24 108 38
13.2 66 66 20 159 29
9.9 34 68 12 74 36
7.7 53 71 24 110 32
10.5 49 66 22 96 35
13.4 55 73 12 116 21
10.9 49 72 22 87 29
4.3 59 71 20 97 12
10.3 40 59 10 127 37
11.8 58 64 23 106 37
11.2 60 66 17 80 47
11.4 63 78 22 74 51
8.6 56 68 24 91 32
13.2 54 73 18 133 21
12.6 52 62 21 74 13
5.6 34 65 20 114 14
9.9 69 68 20 140 -2
8.8 32 65 22 95 20
7.7 48 60 19 98 24
9.0 67 71 20 121 11
7.3 58 65 26 126 23
11.4 57 68 23 98 24
13.6 42 64 24 95 14
7.9 64 74 21 110 52
10.7 58 69 21 70 15
10.3 66 76 19 102 23
8.3 26 68 8 86 19
9.6 61 72 17 130 35
14.2 52 67 20 96 24
8.5 51 63 11 102 39
13.5 55 59 8 100 29
4.9 50 73 15 94 13
6.4 60 66 18 52 8
9.6 56 62 18 98 18
11.6 63 69 19 118 24
11.1 61 66 19 99 19
4.35 52 51 23 48 23
12.7 16 56 22 50 16
18.1 46 67 21 150 33
17.85 56 69 25 154 32
16.6 52 57 30 109 37
12.6 55 56 17 68 14
17.1 50 55 27 194 52
19.1 59 63 23 158 75
16.1 60 67 23 159 72
13.35 52 65 18 67 15
18.4 44 47 18 147 29
14.7 67 76 23 39 13
10.6 52 64 19 100 40
12.6 55 68 15 111 19
16.2 37 64 20 138 24
13.6 54 65 16 101 121
18.9 72 71 24 131 93
14.1 51 63 25 101 36
14.5 48 60 25 114 23
16.15 60 68 19 165 85
14.75 50 72 19 114 41
14.8 63 70 16 111 46
12.45 33 61 19 75 18
12.65 67 61 19 82 35
17.35 46 62 23 121 17
8.6 54 71 21 32 4
18.4 59 71 22 150 28
16.1 61 51 19 117 44
11.6 33 56 20 71 10
17.75 47 70 20 165 38
15.25 69 73 3 154 57
17.65 52 76 23 126 23
15.6 55 59 14 138 26
16.35 55 68 23 149 36
17.65 41 48 20 145 22
13.6 73 52 15 120 40
11.7 51 59 13 138 18
14.35 52 60 16 109 31
14.75 50 59 7 132 11
18.25 51 57 24 172 38
9.9 60 79 17 169 24
16 56 60 24 114 37
18.25 56 60 24 156 37
16.85 29 59 19 172 22
14.6 66 62 25 68 15
13.85 66 59 20 89 2
18.95 73 61 28 167 43
15.6 55 71 23 113 31
14.85 64 57 27 115 29
11.75 40 66 18 78 45
18.45 46 63 28 118 25
15.9 58 69 21 87 4
17.1 43 58 19 173 31
16.1 61 59 23 2 -4
19.9 51 48 27 162 66
10.95 50 66 22 49 61
18.45 52 73 28 122 32
15.1 54 67 25 96 31
15 66 61 21 100 39
11.35 61 68 22 82 19
15.95 80 75 28 100 31
18.1 51 62 20 115 36
14.6 56 69 29 141 42
15.4 56 58 25 165 21
15.4 56 60 25 165 21
17.6 53 74 20 110 25
13.35 47 55 20 118 32
19.1 25 62 16 158 26
15.35 47 63 20 146 28
7.6 46 69 20 49 32
13.4 50 58 23 90 41
13.9 39 58 18 121 29
19.1 51 68 25 155 33
15.25 58 72 18 104 17
12.9 35 62 19 147 13
16.1 58 62 25 110 32
17.35 60 65 25 108 30
13.15 62 69 25 113 34
12.15 63 66 24 115 59
12.6 53 72 19 61 13
10.35 46 62 26 60 23
15.4 67 75 10 109 10
9.6 59 58 17 68 5
18.2 64 66 13 111 31
13.6 38 55 17 77 19
14.85 50 47 30 73 32
14.75 48 72 25 151 30
14.1 48 62 4 89 25
14.9 47 64 16 78 48
16.25 66 64 21 110 35
19.25 47 19 23 220 67
13.6 63 50 22 65 15
13.6 58 68 17 141 22
15.65 44 70 20 117 18
12.75 51 79 20 122 33
14.6 43 69 22 63 46
9.85 55 71 16 44 24
12.65 38 48 23 52 14
11.9 56 66 16 62 23
19.2 45 73 0 131 12
16.6 50 74 18 101 38
11.2 54 66 25 42 12
15.25 57 71 23 152 28
11.9 60 74 12 107 41
13.2 55 78 18 77 12
16.35 56 75 24 154 31
12.4 49 53 11 103 33
15.85 37 60 18 96 34
14.35 43 50 14 154 41
18.15 59 70 23 175 21
11.15 46 69 24 57 20
15.65 51 65 29 112 44
17.75 58 78 18 143 52
7.65 64 78 15 49 7
12.35 53 59 29 110 29
15.6 48 72 16 131 11
19.3 51 70 19 167 26
15.2 47 63 22 56 24
17.1 59 63 16 137 7
15.6 62 71 23 86 60
18.4 62 74 23 121 13
19.05 51 67 19 149 20
18.55 64 66 4 168 52
19.1 52 62 20 140 28
13.1 67 80 24 88 25
12.85 50 73 20 168 39
9.5 54 67 4 94 9
4.5 58 61 24 51 19
11.85 56 73 22 48 13
13.6 63 74 16 145 60
11.7 31 32 3 66 19
12.4 65 69 15 85 34
13.35 71 69 24 109 14
11.4 50 84 17 63 17
14.9 57 64 20 102 45
19.9 47 58 27 162 66
17.75 54 60 23 128 24
11.2 47 59 26 86 48
14.6 57 78 23 114 29
17.6 43 57 17 164 -2
14.05 41 60 20 119 51
16.1 63 68 22 126 2
13.35 63 68 19 132 24
11.85 56 73 24 142 40
11.95 51 69 19 83 20
14.75 50 67 23 94 19
15.15 22 60 15 81 16
13.2 41 65 27 166 20
16.85 59 66 26 110 40
7.85 56 74 22 64 27
7.7 66 81 22 93 25
12.6 53 72 18 104 49
7.85 42 55 15 105 39
10.95 52 49 22 49 61
12.35 54 74 27 88 19
9.95 44 53 10 95 67
14.9 62 64 20 102 45
16.65 53 65 17 99 30
13.4 50 57 23 63 8
13.95 36 51 19 76 19
15.7 76 80 13 109 52
16.85 66 67 27 117 22
10.95 62 70 23 57 17
15.35 59 74 16 120 33
12.2 47 75 25 73 34
15.1 55 70 2 91 22
17.75 58 69 26 108 30
15.2 60 65 20 105 25
14.6 44 55 23 117 38
16.65 57 71 22 119 26
8.1 45 65 24 31 13

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.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 & 9 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'George Udny Yule' @ yule.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 12.0231 + 0.0142838AMS.I[t] -0.0581404AMS.E[t] + 0.0565001NUMERACYTOT[t] + 0.0231825LFM[t] + 0.00374276PRH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  12.0231 +  0.0142838AMS.I[t] -0.0581404AMS.E[t] +  0.0565001NUMERACYTOT[t] +  0.0231825LFM[t] +  0.00374276PRH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  12.0231 +  0.0142838AMS.I[t] -0.0581404AMS.E[t] +  0.0565001NUMERACYTOT[t] +  0.0231825LFM[t] +  0.00374276PRH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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] = + 12.0231 + 0.0142838AMS.I[t] -0.0581404AMS.E[t] + 0.0565001NUMERACYTOT[t] + 0.0231825LFM[t] + 0.00374276PRH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)12.02311.885546.3767.45388e-103.72694e-10
AMS.I0.01428380.02061450.69290.4889460.244473
AMS.E-0.05814040.0255016-2.280.02336750.0116838
NUMERACYTOT0.05650010.03802591.4860.1384490.0692243
LFM0.02318250.005243664.4211.40659e-057.03296e-06
PRH0.003742760.01123370.33320.7392540.369627

\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) & 12.0231 & 1.88554 & 6.376 & 7.45388e-10 & 3.72694e-10 \tabularnewline
AMS.I & 0.0142838 & 0.0206145 & 0.6929 & 0.488946 & 0.244473 \tabularnewline
AMS.E & -0.0581404 & 0.0255016 & -2.28 & 0.0233675 & 0.0116838 \tabularnewline
NUMERACYTOT & 0.0565001 & 0.0380259 & 1.486 & 0.138449 & 0.0692243 \tabularnewline
LFM & 0.0231825 & 0.00524366 & 4.421 & 1.40659e-05 & 7.03296e-06 \tabularnewline
PRH & 0.00374276 & 0.0112337 & 0.3332 & 0.739254 & 0.369627 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&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]12.0231[/C][C]1.88554[/C][C]6.376[/C][C]7.45388e-10[/C][C]3.72694e-10[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0142838[/C][C]0.0206145[/C][C]0.6929[/C][C]0.488946[/C][C]0.244473[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0581404[/C][C]0.0255016[/C][C]-2.28[/C][C]0.0233675[/C][C]0.0116838[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.0565001[/C][C]0.0380259[/C][C]1.486[/C][C]0.138449[/C][C]0.0692243[/C][/ROW]
[ROW][C]LFM[/C][C]0.0231825[/C][C]0.00524366[/C][C]4.421[/C][C]1.40659e-05[/C][C]7.03296e-06[/C][/ROW]
[ROW][C]PRH[/C][C]0.00374276[/C][C]0.0112337[/C][C]0.3332[/C][C]0.739254[/C][C]0.369627[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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)12.02311.885546.3767.45388e-103.72694e-10
AMS.I0.01428380.02061450.69290.4889460.244473
AMS.E-0.05814040.0255016-2.280.02336750.0116838
NUMERACYTOT0.05650010.03802591.4860.1384490.0692243
LFM0.02318250.005243664.4211.40659e-057.03296e-06
PRH0.003742760.01123370.33320.7392540.369627






Multiple Linear Regression - Regression Statistics
Multiple R0.325239
R-squared0.10578
Adjusted R-squared0.0898119
F-TEST (value)6.62442
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value7.56117e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.26402
Sum Squared Residuals2983.06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.325239 \tabularnewline
R-squared & 0.10578 \tabularnewline
Adjusted R-squared & 0.0898119 \tabularnewline
F-TEST (value) & 6.62442 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 280 \tabularnewline
p-value & 7.56117e-06 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.26402 \tabularnewline
Sum Squared Residuals & 2983.06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.325239[/C][/ROW]
[ROW][C]R-squared[/C][C]0.10578[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0898119[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]6.62442[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]280[/C][/ROW]
[ROW][C]p-value[/C][C]7.56117e-06[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.26402[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2983.06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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 R0.325239
R-squared0.10578
Adjusted R-squared0.0898119
F-TEST (value)6.62442
F-TEST (DF numerator)5
F-TEST (DF denominator)280
p-value7.56117e-06
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.26402
Sum Squared Residuals2983.06






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.1955-1.29552
27.413.817-6.41697
312.213.814-1.61397
412.814.232-1.432
57.413.7042-6.30415
66.713.8806-7.18061
712.615.1084-2.50838
814.813.46861.33138
913.313.4858-0.185791
1011.113.4999-2.39986
118.215.6217-7.42168
1211.414.0736-2.67362
136.413.9121-7.5121
1410.612.2619-1.66185
151214.0192-2.01918
166.310.9813-4.68132
1711.311.777-0.477008
1811.913.9109-2.01089
199.312.949-3.64904
209.613.7961-4.19613
211012.1094-2.1094
226.413.4018-7.00176
2313.814.061-0.260993
2410.815.1644-4.36442
2513.814.2024-0.402389
2611.714.012-2.31204
2710.915.0138-4.11383
2816.114.41771.6823
2913.412.55760.842372
309.913.8936-3.99359
3111.512.8947-1.39474
328.311.5367-3.23674
3311.714.1157-2.41574
346.113.0981-6.99811
35913.2503-4.25033
369.713.7193-4.01933
3710.812.5182-1.71821
3810.312.8165-2.51649
3910.412.85-2.45004
4012.713.1133-0.413312
419.314.8793-5.5793
4211.813.5454-1.74536
435.913.5382-7.63817
4411.414.149-2.749
451314.0675-1.06748
4610.813.3102-2.51022
4712.311.14331.15666
4811.314.9544-3.65444
4911.812.7794-0.979399
507.912.271-4.37096
5112.711.92580.774192
5212.312.5105-0.210468
5311.612.5709-0.970903
546.711.0685-4.3685
5510.913.7245-2.8245
5612.113.598-1.498
5713.313.3403-0.0403176
5810.113.0682-2.9682
595.712.4994-6.79938
6014.313.01441.28564
61810.6247-2.62465
6213.312.99970.300274
639.314.6846-5.38461
6412.513.9879-1.48788
657.611.7971-4.19714
6615.915.0080.891956
679.214.8007-5.60067
689.111.8117-2.71173
6911.114.2467-3.14672
701315.4369-2.43686
7114.514.41250.0875358
7212.212.4424-0.24235
7312.315.1365-2.83652
7411.413.1336-1.73362
758.812.3993-3.59933
7614.613.52541.07464
777.314.1543-6.85434
7812.612.14980.450215
79NANA-0.548117
801313.5375-0.537537
8112.613.4531-0.853124
8213.214.3834-1.18345
839.914.878-4.97802
847.79.68526-1.98526
8510.59.110231.38977
8613.414.4053-1.00532
8710.918.7615-7.86149
884.36.81183-2.51183
8910.311.5259-1.2259
9011.812.6339-0.833874
9111.211.3374-0.137417
9211.415.2548-3.85482
938.68.129050.470952
9413.212.71180.488184
9512.619.5548-6.95483
965.69.1232-3.5232
979.913.3212-3.42125
988.813.7555-4.95551
997.711.5284-3.8284
100915.2485-6.24852
1017.38.44494-1.14494
10211.410.31281.08723
10313.618.2661-4.66607
1047.98.90529-1.00529
10510.712.4714-1.77136
10610.312.9577-2.65774
1078.311.5135-3.21353
1089.67.71581.8842
10914.217.9208-3.72081
1108.57.257221.24278
11113.520.1684-6.66835
1124.99.7953-4.8953
1136.49.37454-2.97454
1149.610.8102-1.21016
11511.612.9968-1.39683
11611.119.049-7.94904
1174.353.107791.24221
11812.78.172144.52786
11918.114.16373.93632
12017.8515.06222.78777
12116.616.14220.457843
12212.611.25711.3429
12317.112.4464.65396
12419.117.23971.86028
12516.114.36311.7369
12613.359.402363.94764
12718.414.51373.88628
12814.716.6863-1.98633
12910.610.3470.252967
13012.69.649632.95037
13116.215.31360.886392
13213.68.364555.23545
13318.917.77741.1226
13414.112.96171.13831
13514.512.49332.00667
13616.1513.82092.32906
13714.7512.45262.29742
13814.814.17750.622541
13912.4512.3390.110985
14012.658.543664.10634
14117.3519.3598-2.00977
1428.63.763054.83695
14318.416.17982.22021
14416.116.552-0.451989
14511.67.571954.02805
14617.7515.21742.53262
14715.2510.25384.99623
14817.6515.51592.13408
14915.612.99362.6064
15016.3513.09183.2582
15117.6517.8716-0.22163
15213.615.2223-1.62235
15311.710.17441.52565
15414.3512.40381.94623
15514.7511.42323.32681
15618.2521.6052-3.35521
1579.97.371862.52814
1581612.19553.80448
15918.2515.55032.69972
16016.8514.65622.19382
16114.613.48631.11372
16213.8510.03373.81633
16318.9516.06592.88411
16415.614.67330.926709
16514.8514.8508-0.000846216
16611.756.728425.02158
16718.4514.60823.84178
16815.913.26532.63474
16917.111.7955.30497
17016.111.68894.41108
17119.920.4573-0.557277
17210.955.551645.39836
17318.4516.00312.44693
17415.113.171.93001
1751515.8059-0.805945
17611.358.221553.12845
17715.9510.92765.0224
17818.117.37570.724264
17914.613.96710.632938
18015.414.65080.749219
18115.410.05145.3486
18217.617.732-0.132022
18313.357.689645.66036
18419.117.4011.69896
18515.3518.8042-3.45418
1867.67.104530.495473
18713.412.63860.761351
18813.98.727335.17267
18919.116.00713.09294
19015.2515.7983-0.548312
19112.910.12922.7708
19216.111.87954.2205
19317.3517.25640.0936131
19413.1514.3285-1.17853
19512.1510.68031.46968
19612.614.2715-1.67149
19710.356.698913.65109
19815.417.8493-2.44933
1999.63.923785.67622
20018.216.78481.41517
20113.612.26181.33821
20214.8513.6481.20204
20314.7512.13682.61317
20414.111.06533.03466
20514.911.76243.13758
20616.2515.24021.00981
20719.2518.4720.778034
20813.613.20960.390412
20913.610.44153.15852
21015.6515.14030.50974
21112.759.651283.09872
21214.615.4446-0.844599
2139.859.532540.317464
21412.6512.16310.486873
21511.94.203447.69656
21619.214.53564.66444
21716.616.7882-0.18824
21811.29.587351.61265
21915.2515.23970.0102794
22011.99.820732.07927
22113.210.35462.8454
22216.3516.7244-0.374375
22312.48.982953.41705
22415.8515.74480.105157
22514.3510.43113.91895
22618.1518.4207-0.270727
22711.158.872072.27793
22815.6510.74334.90667
22917.7520.512-2.76196
2307.658.94698-1.29698
23112.359.254693.09531
23215.610.0245.57596
23319.315.76263.53736
23415.211.40923.7908
23517.113.79853.30151
23615.69.959555.64045
23718.412.80875.59128
23819.0513.91535.13472
23918.5513.09155.4585
24019.117.81851.28149
24113.113.9137-0.81367
24212.8514.6879-1.83786
2439.516.9144-7.41442
2444.53.633160.866838
24511.8511.36060.48938
24613.614.2761-0.676063
24711.711.18510.514872
24812.412.01090.389144
24913.3512.28811.06188
25011.49.279332.12067
25114.99.850385.04962
25219.915.81274.08731
25317.7519.4565-1.7065
25411.28.953172.24683
25514.611.07823.52175
25617.616.74990.850088
25714.0511.09092.95909
25816.115.94290.157149
25913.3514.8764-1.52637
26011.8511.71240.137609
26111.959.591652.35835
26214.7511.23413.51591
26315.1516.2283-1.07826
26413.29.547373.65263
26516.8520.3483-3.49834
2667.8511.899-4.049
2677.77.305410.39459
26812.617.6029-5.00293
2697.859.42423-1.57423
27010.9510.72870.22129
27112.3514.9882-2.63825
2729.957.900752.04925
27314.910.61894.28113
27416.6515.46321.18677
27513.411.92861.47136
27613.9510.16353.78654
27715.712.24063.45938
27816.8517.4234-0.5734
27910.957.972872.97713
28015.3514.7160.634013
28112.28.143834.05617
28215.110.27494.82513
28317.7515.30872.44126
28415.214.20790.992056
28514.610.75833.84166
28616.6519.5601-2.91006
2878.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.1955 & -1.29552 \tabularnewline
2 & 7.4 & 13.817 & -6.41697 \tabularnewline
3 & 12.2 & 13.814 & -1.61397 \tabularnewline
4 & 12.8 & 14.232 & -1.432 \tabularnewline
5 & 7.4 & 13.7042 & -6.30415 \tabularnewline
6 & 6.7 & 13.8806 & -7.18061 \tabularnewline
7 & 12.6 & 15.1084 & -2.50838 \tabularnewline
8 & 14.8 & 13.4686 & 1.33138 \tabularnewline
9 & 13.3 & 13.4858 & -0.185791 \tabularnewline
10 & 11.1 & 13.4999 & -2.39986 \tabularnewline
11 & 8.2 & 15.6217 & -7.42168 \tabularnewline
12 & 11.4 & 14.0736 & -2.67362 \tabularnewline
13 & 6.4 & 13.9121 & -7.5121 \tabularnewline
14 & 10.6 & 12.2619 & -1.66185 \tabularnewline
15 & 12 & 14.0192 & -2.01918 \tabularnewline
16 & 6.3 & 10.9813 & -4.68132 \tabularnewline
17 & 11.3 & 11.777 & -0.477008 \tabularnewline
18 & 11.9 & 13.9109 & -2.01089 \tabularnewline
19 & 9.3 & 12.949 & -3.64904 \tabularnewline
20 & 9.6 & 13.7961 & -4.19613 \tabularnewline
21 & 10 & 12.1094 & -2.1094 \tabularnewline
22 & 6.4 & 13.4018 & -7.00176 \tabularnewline
23 & 13.8 & 14.061 & -0.260993 \tabularnewline
24 & 10.8 & 15.1644 & -4.36442 \tabularnewline
25 & 13.8 & 14.2024 & -0.402389 \tabularnewline
26 & 11.7 & 14.012 & -2.31204 \tabularnewline
27 & 10.9 & 15.0138 & -4.11383 \tabularnewline
28 & 16.1 & 14.4177 & 1.6823 \tabularnewline
29 & 13.4 & 12.5576 & 0.842372 \tabularnewline
30 & 9.9 & 13.8936 & -3.99359 \tabularnewline
31 & 11.5 & 12.8947 & -1.39474 \tabularnewline
32 & 8.3 & 11.5367 & -3.23674 \tabularnewline
33 & 11.7 & 14.1157 & -2.41574 \tabularnewline
34 & 6.1 & 13.0981 & -6.99811 \tabularnewline
35 & 9 & 13.2503 & -4.25033 \tabularnewline
36 & 9.7 & 13.7193 & -4.01933 \tabularnewline
37 & 10.8 & 12.5182 & -1.71821 \tabularnewline
38 & 10.3 & 12.8165 & -2.51649 \tabularnewline
39 & 10.4 & 12.85 & -2.45004 \tabularnewline
40 & 12.7 & 13.1133 & -0.413312 \tabularnewline
41 & 9.3 & 14.8793 & -5.5793 \tabularnewline
42 & 11.8 & 13.5454 & -1.74536 \tabularnewline
43 & 5.9 & 13.5382 & -7.63817 \tabularnewline
44 & 11.4 & 14.149 & -2.749 \tabularnewline
45 & 13 & 14.0675 & -1.06748 \tabularnewline
46 & 10.8 & 13.3102 & -2.51022 \tabularnewline
47 & 12.3 & 11.1433 & 1.15666 \tabularnewline
48 & 11.3 & 14.9544 & -3.65444 \tabularnewline
49 & 11.8 & 12.7794 & -0.979399 \tabularnewline
50 & 7.9 & 12.271 & -4.37096 \tabularnewline
51 & 12.7 & 11.9258 & 0.774192 \tabularnewline
52 & 12.3 & 12.5105 & -0.210468 \tabularnewline
53 & 11.6 & 12.5709 & -0.970903 \tabularnewline
54 & 6.7 & 11.0685 & -4.3685 \tabularnewline
55 & 10.9 & 13.7245 & -2.8245 \tabularnewline
56 & 12.1 & 13.598 & -1.498 \tabularnewline
57 & 13.3 & 13.3403 & -0.0403176 \tabularnewline
58 & 10.1 & 13.0682 & -2.9682 \tabularnewline
59 & 5.7 & 12.4994 & -6.79938 \tabularnewline
60 & 14.3 & 13.0144 & 1.28564 \tabularnewline
61 & 8 & 10.6247 & -2.62465 \tabularnewline
62 & 13.3 & 12.9997 & 0.300274 \tabularnewline
63 & 9.3 & 14.6846 & -5.38461 \tabularnewline
64 & 12.5 & 13.9879 & -1.48788 \tabularnewline
65 & 7.6 & 11.7971 & -4.19714 \tabularnewline
66 & 15.9 & 15.008 & 0.891956 \tabularnewline
67 & 9.2 & 14.8007 & -5.60067 \tabularnewline
68 & 9.1 & 11.8117 & -2.71173 \tabularnewline
69 & 11.1 & 14.2467 & -3.14672 \tabularnewline
70 & 13 & 15.4369 & -2.43686 \tabularnewline
71 & 14.5 & 14.4125 & 0.0875358 \tabularnewline
72 & 12.2 & 12.4424 & -0.24235 \tabularnewline
73 & 12.3 & 15.1365 & -2.83652 \tabularnewline
74 & 11.4 & 13.1336 & -1.73362 \tabularnewline
75 & 8.8 & 12.3993 & -3.59933 \tabularnewline
76 & 14.6 & 13.5254 & 1.07464 \tabularnewline
77 & 7.3 & 14.1543 & -6.85434 \tabularnewline
78 & 12.6 & 12.1498 & 0.450215 \tabularnewline
79 & NA & NA & -0.548117 \tabularnewline
80 & 13 & 13.5375 & -0.537537 \tabularnewline
81 & 12.6 & 13.4531 & -0.853124 \tabularnewline
82 & 13.2 & 14.3834 & -1.18345 \tabularnewline
83 & 9.9 & 14.878 & -4.97802 \tabularnewline
84 & 7.7 & 9.68526 & -1.98526 \tabularnewline
85 & 10.5 & 9.11023 & 1.38977 \tabularnewline
86 & 13.4 & 14.4053 & -1.00532 \tabularnewline
87 & 10.9 & 18.7615 & -7.86149 \tabularnewline
88 & 4.3 & 6.81183 & -2.51183 \tabularnewline
89 & 10.3 & 11.5259 & -1.2259 \tabularnewline
90 & 11.8 & 12.6339 & -0.833874 \tabularnewline
91 & 11.2 & 11.3374 & -0.137417 \tabularnewline
92 & 11.4 & 15.2548 & -3.85482 \tabularnewline
93 & 8.6 & 8.12905 & 0.470952 \tabularnewline
94 & 13.2 & 12.7118 & 0.488184 \tabularnewline
95 & 12.6 & 19.5548 & -6.95483 \tabularnewline
96 & 5.6 & 9.1232 & -3.5232 \tabularnewline
97 & 9.9 & 13.3212 & -3.42125 \tabularnewline
98 & 8.8 & 13.7555 & -4.95551 \tabularnewline
99 & 7.7 & 11.5284 & -3.8284 \tabularnewline
100 & 9 & 15.2485 & -6.24852 \tabularnewline
101 & 7.3 & 8.44494 & -1.14494 \tabularnewline
102 & 11.4 & 10.3128 & 1.08723 \tabularnewline
103 & 13.6 & 18.2661 & -4.66607 \tabularnewline
104 & 7.9 & 8.90529 & -1.00529 \tabularnewline
105 & 10.7 & 12.4714 & -1.77136 \tabularnewline
106 & 10.3 & 12.9577 & -2.65774 \tabularnewline
107 & 8.3 & 11.5135 & -3.21353 \tabularnewline
108 & 9.6 & 7.7158 & 1.8842 \tabularnewline
109 & 14.2 & 17.9208 & -3.72081 \tabularnewline
110 & 8.5 & 7.25722 & 1.24278 \tabularnewline
111 & 13.5 & 20.1684 & -6.66835 \tabularnewline
112 & 4.9 & 9.7953 & -4.8953 \tabularnewline
113 & 6.4 & 9.37454 & -2.97454 \tabularnewline
114 & 9.6 & 10.8102 & -1.21016 \tabularnewline
115 & 11.6 & 12.9968 & -1.39683 \tabularnewline
116 & 11.1 & 19.049 & -7.94904 \tabularnewline
117 & 4.35 & 3.10779 & 1.24221 \tabularnewline
118 & 12.7 & 8.17214 & 4.52786 \tabularnewline
119 & 18.1 & 14.1637 & 3.93632 \tabularnewline
120 & 17.85 & 15.0622 & 2.78777 \tabularnewline
121 & 16.6 & 16.1422 & 0.457843 \tabularnewline
122 & 12.6 & 11.2571 & 1.3429 \tabularnewline
123 & 17.1 & 12.446 & 4.65396 \tabularnewline
124 & 19.1 & 17.2397 & 1.86028 \tabularnewline
125 & 16.1 & 14.3631 & 1.7369 \tabularnewline
126 & 13.35 & 9.40236 & 3.94764 \tabularnewline
127 & 18.4 & 14.5137 & 3.88628 \tabularnewline
128 & 14.7 & 16.6863 & -1.98633 \tabularnewline
129 & 10.6 & 10.347 & 0.252967 \tabularnewline
130 & 12.6 & 9.64963 & 2.95037 \tabularnewline
131 & 16.2 & 15.3136 & 0.886392 \tabularnewline
132 & 13.6 & 8.36455 & 5.23545 \tabularnewline
133 & 18.9 & 17.7774 & 1.1226 \tabularnewline
134 & 14.1 & 12.9617 & 1.13831 \tabularnewline
135 & 14.5 & 12.4933 & 2.00667 \tabularnewline
136 & 16.15 & 13.8209 & 2.32906 \tabularnewline
137 & 14.75 & 12.4526 & 2.29742 \tabularnewline
138 & 14.8 & 14.1775 & 0.622541 \tabularnewline
139 & 12.45 & 12.339 & 0.110985 \tabularnewline
140 & 12.65 & 8.54366 & 4.10634 \tabularnewline
141 & 17.35 & 19.3598 & -2.00977 \tabularnewline
142 & 8.6 & 3.76305 & 4.83695 \tabularnewline
143 & 18.4 & 16.1798 & 2.22021 \tabularnewline
144 & 16.1 & 16.552 & -0.451989 \tabularnewline
145 & 11.6 & 7.57195 & 4.02805 \tabularnewline
146 & 17.75 & 15.2174 & 2.53262 \tabularnewline
147 & 15.25 & 10.2538 & 4.99623 \tabularnewline
148 & 17.65 & 15.5159 & 2.13408 \tabularnewline
149 & 15.6 & 12.9936 & 2.6064 \tabularnewline
150 & 16.35 & 13.0918 & 3.2582 \tabularnewline
151 & 17.65 & 17.8716 & -0.22163 \tabularnewline
152 & 13.6 & 15.2223 & -1.62235 \tabularnewline
153 & 11.7 & 10.1744 & 1.52565 \tabularnewline
154 & 14.35 & 12.4038 & 1.94623 \tabularnewline
155 & 14.75 & 11.4232 & 3.32681 \tabularnewline
156 & 18.25 & 21.6052 & -3.35521 \tabularnewline
157 & 9.9 & 7.37186 & 2.52814 \tabularnewline
158 & 16 & 12.1955 & 3.80448 \tabularnewline
159 & 18.25 & 15.5503 & 2.69972 \tabularnewline
160 & 16.85 & 14.6562 & 2.19382 \tabularnewline
161 & 14.6 & 13.4863 & 1.11372 \tabularnewline
162 & 13.85 & 10.0337 & 3.81633 \tabularnewline
163 & 18.95 & 16.0659 & 2.88411 \tabularnewline
164 & 15.6 & 14.6733 & 0.926709 \tabularnewline
165 & 14.85 & 14.8508 & -0.000846216 \tabularnewline
166 & 11.75 & 6.72842 & 5.02158 \tabularnewline
167 & 18.45 & 14.6082 & 3.84178 \tabularnewline
168 & 15.9 & 13.2653 & 2.63474 \tabularnewline
169 & 17.1 & 11.795 & 5.30497 \tabularnewline
170 & 16.1 & 11.6889 & 4.41108 \tabularnewline
171 & 19.9 & 20.4573 & -0.557277 \tabularnewline
172 & 10.95 & 5.55164 & 5.39836 \tabularnewline
173 & 18.45 & 16.0031 & 2.44693 \tabularnewline
174 & 15.1 & 13.17 & 1.93001 \tabularnewline
175 & 15 & 15.8059 & -0.805945 \tabularnewline
176 & 11.35 & 8.22155 & 3.12845 \tabularnewline
177 & 15.95 & 10.9276 & 5.0224 \tabularnewline
178 & 18.1 & 17.3757 & 0.724264 \tabularnewline
179 & 14.6 & 13.9671 & 0.632938 \tabularnewline
180 & 15.4 & 14.6508 & 0.749219 \tabularnewline
181 & 15.4 & 10.0514 & 5.3486 \tabularnewline
182 & 17.6 & 17.732 & -0.132022 \tabularnewline
183 & 13.35 & 7.68964 & 5.66036 \tabularnewline
184 & 19.1 & 17.401 & 1.69896 \tabularnewline
185 & 15.35 & 18.8042 & -3.45418 \tabularnewline
186 & 7.6 & 7.10453 & 0.495473 \tabularnewline
187 & 13.4 & 12.6386 & 0.761351 \tabularnewline
188 & 13.9 & 8.72733 & 5.17267 \tabularnewline
189 & 19.1 & 16.0071 & 3.09294 \tabularnewline
190 & 15.25 & 15.7983 & -0.548312 \tabularnewline
191 & 12.9 & 10.1292 & 2.7708 \tabularnewline
192 & 16.1 & 11.8795 & 4.2205 \tabularnewline
193 & 17.35 & 17.2564 & 0.0936131 \tabularnewline
194 & 13.15 & 14.3285 & -1.17853 \tabularnewline
195 & 12.15 & 10.6803 & 1.46968 \tabularnewline
196 & 12.6 & 14.2715 & -1.67149 \tabularnewline
197 & 10.35 & 6.69891 & 3.65109 \tabularnewline
198 & 15.4 & 17.8493 & -2.44933 \tabularnewline
199 & 9.6 & 3.92378 & 5.67622 \tabularnewline
200 & 18.2 & 16.7848 & 1.41517 \tabularnewline
201 & 13.6 & 12.2618 & 1.33821 \tabularnewline
202 & 14.85 & 13.648 & 1.20204 \tabularnewline
203 & 14.75 & 12.1368 & 2.61317 \tabularnewline
204 & 14.1 & 11.0653 & 3.03466 \tabularnewline
205 & 14.9 & 11.7624 & 3.13758 \tabularnewline
206 & 16.25 & 15.2402 & 1.00981 \tabularnewline
207 & 19.25 & 18.472 & 0.778034 \tabularnewline
208 & 13.6 & 13.2096 & 0.390412 \tabularnewline
209 & 13.6 & 10.4415 & 3.15852 \tabularnewline
210 & 15.65 & 15.1403 & 0.50974 \tabularnewline
211 & 12.75 & 9.65128 & 3.09872 \tabularnewline
212 & 14.6 & 15.4446 & -0.844599 \tabularnewline
213 & 9.85 & 9.53254 & 0.317464 \tabularnewline
214 & 12.65 & 12.1631 & 0.486873 \tabularnewline
215 & 11.9 & 4.20344 & 7.69656 \tabularnewline
216 & 19.2 & 14.5356 & 4.66444 \tabularnewline
217 & 16.6 & 16.7882 & -0.18824 \tabularnewline
218 & 11.2 & 9.58735 & 1.61265 \tabularnewline
219 & 15.25 & 15.2397 & 0.0102794 \tabularnewline
220 & 11.9 & 9.82073 & 2.07927 \tabularnewline
221 & 13.2 & 10.3546 & 2.8454 \tabularnewline
222 & 16.35 & 16.7244 & -0.374375 \tabularnewline
223 & 12.4 & 8.98295 & 3.41705 \tabularnewline
224 & 15.85 & 15.7448 & 0.105157 \tabularnewline
225 & 14.35 & 10.4311 & 3.91895 \tabularnewline
226 & 18.15 & 18.4207 & -0.270727 \tabularnewline
227 & 11.15 & 8.87207 & 2.27793 \tabularnewline
228 & 15.65 & 10.7433 & 4.90667 \tabularnewline
229 & 17.75 & 20.512 & -2.76196 \tabularnewline
230 & 7.65 & 8.94698 & -1.29698 \tabularnewline
231 & 12.35 & 9.25469 & 3.09531 \tabularnewline
232 & 15.6 & 10.024 & 5.57596 \tabularnewline
233 & 19.3 & 15.7626 & 3.53736 \tabularnewline
234 & 15.2 & 11.4092 & 3.7908 \tabularnewline
235 & 17.1 & 13.7985 & 3.30151 \tabularnewline
236 & 15.6 & 9.95955 & 5.64045 \tabularnewline
237 & 18.4 & 12.8087 & 5.59128 \tabularnewline
238 & 19.05 & 13.9153 & 5.13472 \tabularnewline
239 & 18.55 & 13.0915 & 5.4585 \tabularnewline
240 & 19.1 & 17.8185 & 1.28149 \tabularnewline
241 & 13.1 & 13.9137 & -0.81367 \tabularnewline
242 & 12.85 & 14.6879 & -1.83786 \tabularnewline
243 & 9.5 & 16.9144 & -7.41442 \tabularnewline
244 & 4.5 & 3.63316 & 0.866838 \tabularnewline
245 & 11.85 & 11.3606 & 0.48938 \tabularnewline
246 & 13.6 & 14.2761 & -0.676063 \tabularnewline
247 & 11.7 & 11.1851 & 0.514872 \tabularnewline
248 & 12.4 & 12.0109 & 0.389144 \tabularnewline
249 & 13.35 & 12.2881 & 1.06188 \tabularnewline
250 & 11.4 & 9.27933 & 2.12067 \tabularnewline
251 & 14.9 & 9.85038 & 5.04962 \tabularnewline
252 & 19.9 & 15.8127 & 4.08731 \tabularnewline
253 & 17.75 & 19.4565 & -1.7065 \tabularnewline
254 & 11.2 & 8.95317 & 2.24683 \tabularnewline
255 & 14.6 & 11.0782 & 3.52175 \tabularnewline
256 & 17.6 & 16.7499 & 0.850088 \tabularnewline
257 & 14.05 & 11.0909 & 2.95909 \tabularnewline
258 & 16.1 & 15.9429 & 0.157149 \tabularnewline
259 & 13.35 & 14.8764 & -1.52637 \tabularnewline
260 & 11.85 & 11.7124 & 0.137609 \tabularnewline
261 & 11.95 & 9.59165 & 2.35835 \tabularnewline
262 & 14.75 & 11.2341 & 3.51591 \tabularnewline
263 & 15.15 & 16.2283 & -1.07826 \tabularnewline
264 & 13.2 & 9.54737 & 3.65263 \tabularnewline
265 & 16.85 & 20.3483 & -3.49834 \tabularnewline
266 & 7.85 & 11.899 & -4.049 \tabularnewline
267 & 7.7 & 7.30541 & 0.39459 \tabularnewline
268 & 12.6 & 17.6029 & -5.00293 \tabularnewline
269 & 7.85 & 9.42423 & -1.57423 \tabularnewline
270 & 10.95 & 10.7287 & 0.22129 \tabularnewline
271 & 12.35 & 14.9882 & -2.63825 \tabularnewline
272 & 9.95 & 7.90075 & 2.04925 \tabularnewline
273 & 14.9 & 10.6189 & 4.28113 \tabularnewline
274 & 16.65 & 15.4632 & 1.18677 \tabularnewline
275 & 13.4 & 11.9286 & 1.47136 \tabularnewline
276 & 13.95 & 10.1635 & 3.78654 \tabularnewline
277 & 15.7 & 12.2406 & 3.45938 \tabularnewline
278 & 16.85 & 17.4234 & -0.5734 \tabularnewline
279 & 10.95 & 7.97287 & 2.97713 \tabularnewline
280 & 15.35 & 14.716 & 0.634013 \tabularnewline
281 & 12.2 & 8.14383 & 4.05617 \tabularnewline
282 & 15.1 & 10.2749 & 4.82513 \tabularnewline
283 & 17.75 & 15.3087 & 2.44126 \tabularnewline
284 & 15.2 & 14.2079 & 0.992056 \tabularnewline
285 & 14.6 & 10.7583 & 3.84166 \tabularnewline
286 & 16.65 & 19.5601 & -2.91006 \tabularnewline
287 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&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]14.1955[/C][C]-1.29552[/C][/ROW]
[ROW][C]2[/C][C]7.4[/C][C]13.817[/C][C]-6.41697[/C][/ROW]
[ROW][C]3[/C][C]12.2[/C][C]13.814[/C][C]-1.61397[/C][/ROW]
[ROW][C]4[/C][C]12.8[/C][C]14.232[/C][C]-1.432[/C][/ROW]
[ROW][C]5[/C][C]7.4[/C][C]13.7042[/C][C]-6.30415[/C][/ROW]
[ROW][C]6[/C][C]6.7[/C][C]13.8806[/C][C]-7.18061[/C][/ROW]
[ROW][C]7[/C][C]12.6[/C][C]15.1084[/C][C]-2.50838[/C][/ROW]
[ROW][C]8[/C][C]14.8[/C][C]13.4686[/C][C]1.33138[/C][/ROW]
[ROW][C]9[/C][C]13.3[/C][C]13.4858[/C][C]-0.185791[/C][/ROW]
[ROW][C]10[/C][C]11.1[/C][C]13.4999[/C][C]-2.39986[/C][/ROW]
[ROW][C]11[/C][C]8.2[/C][C]15.6217[/C][C]-7.42168[/C][/ROW]
[ROW][C]12[/C][C]11.4[/C][C]14.0736[/C][C]-2.67362[/C][/ROW]
[ROW][C]13[/C][C]6.4[/C][C]13.9121[/C][C]-7.5121[/C][/ROW]
[ROW][C]14[/C][C]10.6[/C][C]12.2619[/C][C]-1.66185[/C][/ROW]
[ROW][C]15[/C][C]12[/C][C]14.0192[/C][C]-2.01918[/C][/ROW]
[ROW][C]16[/C][C]6.3[/C][C]10.9813[/C][C]-4.68132[/C][/ROW]
[ROW][C]17[/C][C]11.3[/C][C]11.777[/C][C]-0.477008[/C][/ROW]
[ROW][C]18[/C][C]11.9[/C][C]13.9109[/C][C]-2.01089[/C][/ROW]
[ROW][C]19[/C][C]9.3[/C][C]12.949[/C][C]-3.64904[/C][/ROW]
[ROW][C]20[/C][C]9.6[/C][C]13.7961[/C][C]-4.19613[/C][/ROW]
[ROW][C]21[/C][C]10[/C][C]12.1094[/C][C]-2.1094[/C][/ROW]
[ROW][C]22[/C][C]6.4[/C][C]13.4018[/C][C]-7.00176[/C][/ROW]
[ROW][C]23[/C][C]13.8[/C][C]14.061[/C][C]-0.260993[/C][/ROW]
[ROW][C]24[/C][C]10.8[/C][C]15.1644[/C][C]-4.36442[/C][/ROW]
[ROW][C]25[/C][C]13.8[/C][C]14.2024[/C][C]-0.402389[/C][/ROW]
[ROW][C]26[/C][C]11.7[/C][C]14.012[/C][C]-2.31204[/C][/ROW]
[ROW][C]27[/C][C]10.9[/C][C]15.0138[/C][C]-4.11383[/C][/ROW]
[ROW][C]28[/C][C]16.1[/C][C]14.4177[/C][C]1.6823[/C][/ROW]
[ROW][C]29[/C][C]13.4[/C][C]12.5576[/C][C]0.842372[/C][/ROW]
[ROW][C]30[/C][C]9.9[/C][C]13.8936[/C][C]-3.99359[/C][/ROW]
[ROW][C]31[/C][C]11.5[/C][C]12.8947[/C][C]-1.39474[/C][/ROW]
[ROW][C]32[/C][C]8.3[/C][C]11.5367[/C][C]-3.23674[/C][/ROW]
[ROW][C]33[/C][C]11.7[/C][C]14.1157[/C][C]-2.41574[/C][/ROW]
[ROW][C]34[/C][C]6.1[/C][C]13.0981[/C][C]-6.99811[/C][/ROW]
[ROW][C]35[/C][C]9[/C][C]13.2503[/C][C]-4.25033[/C][/ROW]
[ROW][C]36[/C][C]9.7[/C][C]13.7193[/C][C]-4.01933[/C][/ROW]
[ROW][C]37[/C][C]10.8[/C][C]12.5182[/C][C]-1.71821[/C][/ROW]
[ROW][C]38[/C][C]10.3[/C][C]12.8165[/C][C]-2.51649[/C][/ROW]
[ROW][C]39[/C][C]10.4[/C][C]12.85[/C][C]-2.45004[/C][/ROW]
[ROW][C]40[/C][C]12.7[/C][C]13.1133[/C][C]-0.413312[/C][/ROW]
[ROW][C]41[/C][C]9.3[/C][C]14.8793[/C][C]-5.5793[/C][/ROW]
[ROW][C]42[/C][C]11.8[/C][C]13.5454[/C][C]-1.74536[/C][/ROW]
[ROW][C]43[/C][C]5.9[/C][C]13.5382[/C][C]-7.63817[/C][/ROW]
[ROW][C]44[/C][C]11.4[/C][C]14.149[/C][C]-2.749[/C][/ROW]
[ROW][C]45[/C][C]13[/C][C]14.0675[/C][C]-1.06748[/C][/ROW]
[ROW][C]46[/C][C]10.8[/C][C]13.3102[/C][C]-2.51022[/C][/ROW]
[ROW][C]47[/C][C]12.3[/C][C]11.1433[/C][C]1.15666[/C][/ROW]
[ROW][C]48[/C][C]11.3[/C][C]14.9544[/C][C]-3.65444[/C][/ROW]
[ROW][C]49[/C][C]11.8[/C][C]12.7794[/C][C]-0.979399[/C][/ROW]
[ROW][C]50[/C][C]7.9[/C][C]12.271[/C][C]-4.37096[/C][/ROW]
[ROW][C]51[/C][C]12.7[/C][C]11.9258[/C][C]0.774192[/C][/ROW]
[ROW][C]52[/C][C]12.3[/C][C]12.5105[/C][C]-0.210468[/C][/ROW]
[ROW][C]53[/C][C]11.6[/C][C]12.5709[/C][C]-0.970903[/C][/ROW]
[ROW][C]54[/C][C]6.7[/C][C]11.0685[/C][C]-4.3685[/C][/ROW]
[ROW][C]55[/C][C]10.9[/C][C]13.7245[/C][C]-2.8245[/C][/ROW]
[ROW][C]56[/C][C]12.1[/C][C]13.598[/C][C]-1.498[/C][/ROW]
[ROW][C]57[/C][C]13.3[/C][C]13.3403[/C][C]-0.0403176[/C][/ROW]
[ROW][C]58[/C][C]10.1[/C][C]13.0682[/C][C]-2.9682[/C][/ROW]
[ROW][C]59[/C][C]5.7[/C][C]12.4994[/C][C]-6.79938[/C][/ROW]
[ROW][C]60[/C][C]14.3[/C][C]13.0144[/C][C]1.28564[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.6247[/C][C]-2.62465[/C][/ROW]
[ROW][C]62[/C][C]13.3[/C][C]12.9997[/C][C]0.300274[/C][/ROW]
[ROW][C]63[/C][C]9.3[/C][C]14.6846[/C][C]-5.38461[/C][/ROW]
[ROW][C]64[/C][C]12.5[/C][C]13.9879[/C][C]-1.48788[/C][/ROW]
[ROW][C]65[/C][C]7.6[/C][C]11.7971[/C][C]-4.19714[/C][/ROW]
[ROW][C]66[/C][C]15.9[/C][C]15.008[/C][C]0.891956[/C][/ROW]
[ROW][C]67[/C][C]9.2[/C][C]14.8007[/C][C]-5.60067[/C][/ROW]
[ROW][C]68[/C][C]9.1[/C][C]11.8117[/C][C]-2.71173[/C][/ROW]
[ROW][C]69[/C][C]11.1[/C][C]14.2467[/C][C]-3.14672[/C][/ROW]
[ROW][C]70[/C][C]13[/C][C]15.4369[/C][C]-2.43686[/C][/ROW]
[ROW][C]71[/C][C]14.5[/C][C]14.4125[/C][C]0.0875358[/C][/ROW]
[ROW][C]72[/C][C]12.2[/C][C]12.4424[/C][C]-0.24235[/C][/ROW]
[ROW][C]73[/C][C]12.3[/C][C]15.1365[/C][C]-2.83652[/C][/ROW]
[ROW][C]74[/C][C]11.4[/C][C]13.1336[/C][C]-1.73362[/C][/ROW]
[ROW][C]75[/C][C]8.8[/C][C]12.3993[/C][C]-3.59933[/C][/ROW]
[ROW][C]76[/C][C]14.6[/C][C]13.5254[/C][C]1.07464[/C][/ROW]
[ROW][C]77[/C][C]7.3[/C][C]14.1543[/C][C]-6.85434[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]12.1498[/C][C]0.450215[/C][/ROW]
[ROW][C]79[/C][C]NA[/C][C]NA[/C][C]-0.548117[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]13.5375[/C][C]-0.537537[/C][/ROW]
[ROW][C]81[/C][C]12.6[/C][C]13.4531[/C][C]-0.853124[/C][/ROW]
[ROW][C]82[/C][C]13.2[/C][C]14.3834[/C][C]-1.18345[/C][/ROW]
[ROW][C]83[/C][C]9.9[/C][C]14.878[/C][C]-4.97802[/C][/ROW]
[ROW][C]84[/C][C]7.7[/C][C]9.68526[/C][C]-1.98526[/C][/ROW]
[ROW][C]85[/C][C]10.5[/C][C]9.11023[/C][C]1.38977[/C][/ROW]
[ROW][C]86[/C][C]13.4[/C][C]14.4053[/C][C]-1.00532[/C][/ROW]
[ROW][C]87[/C][C]10.9[/C][C]18.7615[/C][C]-7.86149[/C][/ROW]
[ROW][C]88[/C][C]4.3[/C][C]6.81183[/C][C]-2.51183[/C][/ROW]
[ROW][C]89[/C][C]10.3[/C][C]11.5259[/C][C]-1.2259[/C][/ROW]
[ROW][C]90[/C][C]11.8[/C][C]12.6339[/C][C]-0.833874[/C][/ROW]
[ROW][C]91[/C][C]11.2[/C][C]11.3374[/C][C]-0.137417[/C][/ROW]
[ROW][C]92[/C][C]11.4[/C][C]15.2548[/C][C]-3.85482[/C][/ROW]
[ROW][C]93[/C][C]8.6[/C][C]8.12905[/C][C]0.470952[/C][/ROW]
[ROW][C]94[/C][C]13.2[/C][C]12.7118[/C][C]0.488184[/C][/ROW]
[ROW][C]95[/C][C]12.6[/C][C]19.5548[/C][C]-6.95483[/C][/ROW]
[ROW][C]96[/C][C]5.6[/C][C]9.1232[/C][C]-3.5232[/C][/ROW]
[ROW][C]97[/C][C]9.9[/C][C]13.3212[/C][C]-3.42125[/C][/ROW]
[ROW][C]98[/C][C]8.8[/C][C]13.7555[/C][C]-4.95551[/C][/ROW]
[ROW][C]99[/C][C]7.7[/C][C]11.5284[/C][C]-3.8284[/C][/ROW]
[ROW][C]100[/C][C]9[/C][C]15.2485[/C][C]-6.24852[/C][/ROW]
[ROW][C]101[/C][C]7.3[/C][C]8.44494[/C][C]-1.14494[/C][/ROW]
[ROW][C]102[/C][C]11.4[/C][C]10.3128[/C][C]1.08723[/C][/ROW]
[ROW][C]103[/C][C]13.6[/C][C]18.2661[/C][C]-4.66607[/C][/ROW]
[ROW][C]104[/C][C]7.9[/C][C]8.90529[/C][C]-1.00529[/C][/ROW]
[ROW][C]105[/C][C]10.7[/C][C]12.4714[/C][C]-1.77136[/C][/ROW]
[ROW][C]106[/C][C]10.3[/C][C]12.9577[/C][C]-2.65774[/C][/ROW]
[ROW][C]107[/C][C]8.3[/C][C]11.5135[/C][C]-3.21353[/C][/ROW]
[ROW][C]108[/C][C]9.6[/C][C]7.7158[/C][C]1.8842[/C][/ROW]
[ROW][C]109[/C][C]14.2[/C][C]17.9208[/C][C]-3.72081[/C][/ROW]
[ROW][C]110[/C][C]8.5[/C][C]7.25722[/C][C]1.24278[/C][/ROW]
[ROW][C]111[/C][C]13.5[/C][C]20.1684[/C][C]-6.66835[/C][/ROW]
[ROW][C]112[/C][C]4.9[/C][C]9.7953[/C][C]-4.8953[/C][/ROW]
[ROW][C]113[/C][C]6.4[/C][C]9.37454[/C][C]-2.97454[/C][/ROW]
[ROW][C]114[/C][C]9.6[/C][C]10.8102[/C][C]-1.21016[/C][/ROW]
[ROW][C]115[/C][C]11.6[/C][C]12.9968[/C][C]-1.39683[/C][/ROW]
[ROW][C]116[/C][C]11.1[/C][C]19.049[/C][C]-7.94904[/C][/ROW]
[ROW][C]117[/C][C]4.35[/C][C]3.10779[/C][C]1.24221[/C][/ROW]
[ROW][C]118[/C][C]12.7[/C][C]8.17214[/C][C]4.52786[/C][/ROW]
[ROW][C]119[/C][C]18.1[/C][C]14.1637[/C][C]3.93632[/C][/ROW]
[ROW][C]120[/C][C]17.85[/C][C]15.0622[/C][C]2.78777[/C][/ROW]
[ROW][C]121[/C][C]16.6[/C][C]16.1422[/C][C]0.457843[/C][/ROW]
[ROW][C]122[/C][C]12.6[/C][C]11.2571[/C][C]1.3429[/C][/ROW]
[ROW][C]123[/C][C]17.1[/C][C]12.446[/C][C]4.65396[/C][/ROW]
[ROW][C]124[/C][C]19.1[/C][C]17.2397[/C][C]1.86028[/C][/ROW]
[ROW][C]125[/C][C]16.1[/C][C]14.3631[/C][C]1.7369[/C][/ROW]
[ROW][C]126[/C][C]13.35[/C][C]9.40236[/C][C]3.94764[/C][/ROW]
[ROW][C]127[/C][C]18.4[/C][C]14.5137[/C][C]3.88628[/C][/ROW]
[ROW][C]128[/C][C]14.7[/C][C]16.6863[/C][C]-1.98633[/C][/ROW]
[ROW][C]129[/C][C]10.6[/C][C]10.347[/C][C]0.252967[/C][/ROW]
[ROW][C]130[/C][C]12.6[/C][C]9.64963[/C][C]2.95037[/C][/ROW]
[ROW][C]131[/C][C]16.2[/C][C]15.3136[/C][C]0.886392[/C][/ROW]
[ROW][C]132[/C][C]13.6[/C][C]8.36455[/C][C]5.23545[/C][/ROW]
[ROW][C]133[/C][C]18.9[/C][C]17.7774[/C][C]1.1226[/C][/ROW]
[ROW][C]134[/C][C]14.1[/C][C]12.9617[/C][C]1.13831[/C][/ROW]
[ROW][C]135[/C][C]14.5[/C][C]12.4933[/C][C]2.00667[/C][/ROW]
[ROW][C]136[/C][C]16.15[/C][C]13.8209[/C][C]2.32906[/C][/ROW]
[ROW][C]137[/C][C]14.75[/C][C]12.4526[/C][C]2.29742[/C][/ROW]
[ROW][C]138[/C][C]14.8[/C][C]14.1775[/C][C]0.622541[/C][/ROW]
[ROW][C]139[/C][C]12.45[/C][C]12.339[/C][C]0.110985[/C][/ROW]
[ROW][C]140[/C][C]12.65[/C][C]8.54366[/C][C]4.10634[/C][/ROW]
[ROW][C]141[/C][C]17.35[/C][C]19.3598[/C][C]-2.00977[/C][/ROW]
[ROW][C]142[/C][C]8.6[/C][C]3.76305[/C][C]4.83695[/C][/ROW]
[ROW][C]143[/C][C]18.4[/C][C]16.1798[/C][C]2.22021[/C][/ROW]
[ROW][C]144[/C][C]16.1[/C][C]16.552[/C][C]-0.451989[/C][/ROW]
[ROW][C]145[/C][C]11.6[/C][C]7.57195[/C][C]4.02805[/C][/ROW]
[ROW][C]146[/C][C]17.75[/C][C]15.2174[/C][C]2.53262[/C][/ROW]
[ROW][C]147[/C][C]15.25[/C][C]10.2538[/C][C]4.99623[/C][/ROW]
[ROW][C]148[/C][C]17.65[/C][C]15.5159[/C][C]2.13408[/C][/ROW]
[ROW][C]149[/C][C]15.6[/C][C]12.9936[/C][C]2.6064[/C][/ROW]
[ROW][C]150[/C][C]16.35[/C][C]13.0918[/C][C]3.2582[/C][/ROW]
[ROW][C]151[/C][C]17.65[/C][C]17.8716[/C][C]-0.22163[/C][/ROW]
[ROW][C]152[/C][C]13.6[/C][C]15.2223[/C][C]-1.62235[/C][/ROW]
[ROW][C]153[/C][C]11.7[/C][C]10.1744[/C][C]1.52565[/C][/ROW]
[ROW][C]154[/C][C]14.35[/C][C]12.4038[/C][C]1.94623[/C][/ROW]
[ROW][C]155[/C][C]14.75[/C][C]11.4232[/C][C]3.32681[/C][/ROW]
[ROW][C]156[/C][C]18.25[/C][C]21.6052[/C][C]-3.35521[/C][/ROW]
[ROW][C]157[/C][C]9.9[/C][C]7.37186[/C][C]2.52814[/C][/ROW]
[ROW][C]158[/C][C]16[/C][C]12.1955[/C][C]3.80448[/C][/ROW]
[ROW][C]159[/C][C]18.25[/C][C]15.5503[/C][C]2.69972[/C][/ROW]
[ROW][C]160[/C][C]16.85[/C][C]14.6562[/C][C]2.19382[/C][/ROW]
[ROW][C]161[/C][C]14.6[/C][C]13.4863[/C][C]1.11372[/C][/ROW]
[ROW][C]162[/C][C]13.85[/C][C]10.0337[/C][C]3.81633[/C][/ROW]
[ROW][C]163[/C][C]18.95[/C][C]16.0659[/C][C]2.88411[/C][/ROW]
[ROW][C]164[/C][C]15.6[/C][C]14.6733[/C][C]0.926709[/C][/ROW]
[ROW][C]165[/C][C]14.85[/C][C]14.8508[/C][C]-0.000846216[/C][/ROW]
[ROW][C]166[/C][C]11.75[/C][C]6.72842[/C][C]5.02158[/C][/ROW]
[ROW][C]167[/C][C]18.45[/C][C]14.6082[/C][C]3.84178[/C][/ROW]
[ROW][C]168[/C][C]15.9[/C][C]13.2653[/C][C]2.63474[/C][/ROW]
[ROW][C]169[/C][C]17.1[/C][C]11.795[/C][C]5.30497[/C][/ROW]
[ROW][C]170[/C][C]16.1[/C][C]11.6889[/C][C]4.41108[/C][/ROW]
[ROW][C]171[/C][C]19.9[/C][C]20.4573[/C][C]-0.557277[/C][/ROW]
[ROW][C]172[/C][C]10.95[/C][C]5.55164[/C][C]5.39836[/C][/ROW]
[ROW][C]173[/C][C]18.45[/C][C]16.0031[/C][C]2.44693[/C][/ROW]
[ROW][C]174[/C][C]15.1[/C][C]13.17[/C][C]1.93001[/C][/ROW]
[ROW][C]175[/C][C]15[/C][C]15.8059[/C][C]-0.805945[/C][/ROW]
[ROW][C]176[/C][C]11.35[/C][C]8.22155[/C][C]3.12845[/C][/ROW]
[ROW][C]177[/C][C]15.95[/C][C]10.9276[/C][C]5.0224[/C][/ROW]
[ROW][C]178[/C][C]18.1[/C][C]17.3757[/C][C]0.724264[/C][/ROW]
[ROW][C]179[/C][C]14.6[/C][C]13.9671[/C][C]0.632938[/C][/ROW]
[ROW][C]180[/C][C]15.4[/C][C]14.6508[/C][C]0.749219[/C][/ROW]
[ROW][C]181[/C][C]15.4[/C][C]10.0514[/C][C]5.3486[/C][/ROW]
[ROW][C]182[/C][C]17.6[/C][C]17.732[/C][C]-0.132022[/C][/ROW]
[ROW][C]183[/C][C]13.35[/C][C]7.68964[/C][C]5.66036[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.401[/C][C]1.69896[/C][/ROW]
[ROW][C]185[/C][C]15.35[/C][C]18.8042[/C][C]-3.45418[/C][/ROW]
[ROW][C]186[/C][C]7.6[/C][C]7.10453[/C][C]0.495473[/C][/ROW]
[ROW][C]187[/C][C]13.4[/C][C]12.6386[/C][C]0.761351[/C][/ROW]
[ROW][C]188[/C][C]13.9[/C][C]8.72733[/C][C]5.17267[/C][/ROW]
[ROW][C]189[/C][C]19.1[/C][C]16.0071[/C][C]3.09294[/C][/ROW]
[ROW][C]190[/C][C]15.25[/C][C]15.7983[/C][C]-0.548312[/C][/ROW]
[ROW][C]191[/C][C]12.9[/C][C]10.1292[/C][C]2.7708[/C][/ROW]
[ROW][C]192[/C][C]16.1[/C][C]11.8795[/C][C]4.2205[/C][/ROW]
[ROW][C]193[/C][C]17.35[/C][C]17.2564[/C][C]0.0936131[/C][/ROW]
[ROW][C]194[/C][C]13.15[/C][C]14.3285[/C][C]-1.17853[/C][/ROW]
[ROW][C]195[/C][C]12.15[/C][C]10.6803[/C][C]1.46968[/C][/ROW]
[ROW][C]196[/C][C]12.6[/C][C]14.2715[/C][C]-1.67149[/C][/ROW]
[ROW][C]197[/C][C]10.35[/C][C]6.69891[/C][C]3.65109[/C][/ROW]
[ROW][C]198[/C][C]15.4[/C][C]17.8493[/C][C]-2.44933[/C][/ROW]
[ROW][C]199[/C][C]9.6[/C][C]3.92378[/C][C]5.67622[/C][/ROW]
[ROW][C]200[/C][C]18.2[/C][C]16.7848[/C][C]1.41517[/C][/ROW]
[ROW][C]201[/C][C]13.6[/C][C]12.2618[/C][C]1.33821[/C][/ROW]
[ROW][C]202[/C][C]14.85[/C][C]13.648[/C][C]1.20204[/C][/ROW]
[ROW][C]203[/C][C]14.75[/C][C]12.1368[/C][C]2.61317[/C][/ROW]
[ROW][C]204[/C][C]14.1[/C][C]11.0653[/C][C]3.03466[/C][/ROW]
[ROW][C]205[/C][C]14.9[/C][C]11.7624[/C][C]3.13758[/C][/ROW]
[ROW][C]206[/C][C]16.25[/C][C]15.2402[/C][C]1.00981[/C][/ROW]
[ROW][C]207[/C][C]19.25[/C][C]18.472[/C][C]0.778034[/C][/ROW]
[ROW][C]208[/C][C]13.6[/C][C]13.2096[/C][C]0.390412[/C][/ROW]
[ROW][C]209[/C][C]13.6[/C][C]10.4415[/C][C]3.15852[/C][/ROW]
[ROW][C]210[/C][C]15.65[/C][C]15.1403[/C][C]0.50974[/C][/ROW]
[ROW][C]211[/C][C]12.75[/C][C]9.65128[/C][C]3.09872[/C][/ROW]
[ROW][C]212[/C][C]14.6[/C][C]15.4446[/C][C]-0.844599[/C][/ROW]
[ROW][C]213[/C][C]9.85[/C][C]9.53254[/C][C]0.317464[/C][/ROW]
[ROW][C]214[/C][C]12.65[/C][C]12.1631[/C][C]0.486873[/C][/ROW]
[ROW][C]215[/C][C]11.9[/C][C]4.20344[/C][C]7.69656[/C][/ROW]
[ROW][C]216[/C][C]19.2[/C][C]14.5356[/C][C]4.66444[/C][/ROW]
[ROW][C]217[/C][C]16.6[/C][C]16.7882[/C][C]-0.18824[/C][/ROW]
[ROW][C]218[/C][C]11.2[/C][C]9.58735[/C][C]1.61265[/C][/ROW]
[ROW][C]219[/C][C]15.25[/C][C]15.2397[/C][C]0.0102794[/C][/ROW]
[ROW][C]220[/C][C]11.9[/C][C]9.82073[/C][C]2.07927[/C][/ROW]
[ROW][C]221[/C][C]13.2[/C][C]10.3546[/C][C]2.8454[/C][/ROW]
[ROW][C]222[/C][C]16.35[/C][C]16.7244[/C][C]-0.374375[/C][/ROW]
[ROW][C]223[/C][C]12.4[/C][C]8.98295[/C][C]3.41705[/C][/ROW]
[ROW][C]224[/C][C]15.85[/C][C]15.7448[/C][C]0.105157[/C][/ROW]
[ROW][C]225[/C][C]14.35[/C][C]10.4311[/C][C]3.91895[/C][/ROW]
[ROW][C]226[/C][C]18.15[/C][C]18.4207[/C][C]-0.270727[/C][/ROW]
[ROW][C]227[/C][C]11.15[/C][C]8.87207[/C][C]2.27793[/C][/ROW]
[ROW][C]228[/C][C]15.65[/C][C]10.7433[/C][C]4.90667[/C][/ROW]
[ROW][C]229[/C][C]17.75[/C][C]20.512[/C][C]-2.76196[/C][/ROW]
[ROW][C]230[/C][C]7.65[/C][C]8.94698[/C][C]-1.29698[/C][/ROW]
[ROW][C]231[/C][C]12.35[/C][C]9.25469[/C][C]3.09531[/C][/ROW]
[ROW][C]232[/C][C]15.6[/C][C]10.024[/C][C]5.57596[/C][/ROW]
[ROW][C]233[/C][C]19.3[/C][C]15.7626[/C][C]3.53736[/C][/ROW]
[ROW][C]234[/C][C]15.2[/C][C]11.4092[/C][C]3.7908[/C][/ROW]
[ROW][C]235[/C][C]17.1[/C][C]13.7985[/C][C]3.30151[/C][/ROW]
[ROW][C]236[/C][C]15.6[/C][C]9.95955[/C][C]5.64045[/C][/ROW]
[ROW][C]237[/C][C]18.4[/C][C]12.8087[/C][C]5.59128[/C][/ROW]
[ROW][C]238[/C][C]19.05[/C][C]13.9153[/C][C]5.13472[/C][/ROW]
[ROW][C]239[/C][C]18.55[/C][C]13.0915[/C][C]5.4585[/C][/ROW]
[ROW][C]240[/C][C]19.1[/C][C]17.8185[/C][C]1.28149[/C][/ROW]
[ROW][C]241[/C][C]13.1[/C][C]13.9137[/C][C]-0.81367[/C][/ROW]
[ROW][C]242[/C][C]12.85[/C][C]14.6879[/C][C]-1.83786[/C][/ROW]
[ROW][C]243[/C][C]9.5[/C][C]16.9144[/C][C]-7.41442[/C][/ROW]
[ROW][C]244[/C][C]4.5[/C][C]3.63316[/C][C]0.866838[/C][/ROW]
[ROW][C]245[/C][C]11.85[/C][C]11.3606[/C][C]0.48938[/C][/ROW]
[ROW][C]246[/C][C]13.6[/C][C]14.2761[/C][C]-0.676063[/C][/ROW]
[ROW][C]247[/C][C]11.7[/C][C]11.1851[/C][C]0.514872[/C][/ROW]
[ROW][C]248[/C][C]12.4[/C][C]12.0109[/C][C]0.389144[/C][/ROW]
[ROW][C]249[/C][C]13.35[/C][C]12.2881[/C][C]1.06188[/C][/ROW]
[ROW][C]250[/C][C]11.4[/C][C]9.27933[/C][C]2.12067[/C][/ROW]
[ROW][C]251[/C][C]14.9[/C][C]9.85038[/C][C]5.04962[/C][/ROW]
[ROW][C]252[/C][C]19.9[/C][C]15.8127[/C][C]4.08731[/C][/ROW]
[ROW][C]253[/C][C]17.75[/C][C]19.4565[/C][C]-1.7065[/C][/ROW]
[ROW][C]254[/C][C]11.2[/C][C]8.95317[/C][C]2.24683[/C][/ROW]
[ROW][C]255[/C][C]14.6[/C][C]11.0782[/C][C]3.52175[/C][/ROW]
[ROW][C]256[/C][C]17.6[/C][C]16.7499[/C][C]0.850088[/C][/ROW]
[ROW][C]257[/C][C]14.05[/C][C]11.0909[/C][C]2.95909[/C][/ROW]
[ROW][C]258[/C][C]16.1[/C][C]15.9429[/C][C]0.157149[/C][/ROW]
[ROW][C]259[/C][C]13.35[/C][C]14.8764[/C][C]-1.52637[/C][/ROW]
[ROW][C]260[/C][C]11.85[/C][C]11.7124[/C][C]0.137609[/C][/ROW]
[ROW][C]261[/C][C]11.95[/C][C]9.59165[/C][C]2.35835[/C][/ROW]
[ROW][C]262[/C][C]14.75[/C][C]11.2341[/C][C]3.51591[/C][/ROW]
[ROW][C]263[/C][C]15.15[/C][C]16.2283[/C][C]-1.07826[/C][/ROW]
[ROW][C]264[/C][C]13.2[/C][C]9.54737[/C][C]3.65263[/C][/ROW]
[ROW][C]265[/C][C]16.85[/C][C]20.3483[/C][C]-3.49834[/C][/ROW]
[ROW][C]266[/C][C]7.85[/C][C]11.899[/C][C]-4.049[/C][/ROW]
[ROW][C]267[/C][C]7.7[/C][C]7.30541[/C][C]0.39459[/C][/ROW]
[ROW][C]268[/C][C]12.6[/C][C]17.6029[/C][C]-5.00293[/C][/ROW]
[ROW][C]269[/C][C]7.85[/C][C]9.42423[/C][C]-1.57423[/C][/ROW]
[ROW][C]270[/C][C]10.95[/C][C]10.7287[/C][C]0.22129[/C][/ROW]
[ROW][C]271[/C][C]12.35[/C][C]14.9882[/C][C]-2.63825[/C][/ROW]
[ROW][C]272[/C][C]9.95[/C][C]7.90075[/C][C]2.04925[/C][/ROW]
[ROW][C]273[/C][C]14.9[/C][C]10.6189[/C][C]4.28113[/C][/ROW]
[ROW][C]274[/C][C]16.65[/C][C]15.4632[/C][C]1.18677[/C][/ROW]
[ROW][C]275[/C][C]13.4[/C][C]11.9286[/C][C]1.47136[/C][/ROW]
[ROW][C]276[/C][C]13.95[/C][C]10.1635[/C][C]3.78654[/C][/ROW]
[ROW][C]277[/C][C]15.7[/C][C]12.2406[/C][C]3.45938[/C][/ROW]
[ROW][C]278[/C][C]16.85[/C][C]17.4234[/C][C]-0.5734[/C][/ROW]
[ROW][C]279[/C][C]10.95[/C][C]7.97287[/C][C]2.97713[/C][/ROW]
[ROW][C]280[/C][C]15.35[/C][C]14.716[/C][C]0.634013[/C][/ROW]
[ROW][C]281[/C][C]12.2[/C][C]8.14383[/C][C]4.05617[/C][/ROW]
[ROW][C]282[/C][C]15.1[/C][C]10.2749[/C][C]4.82513[/C][/ROW]
[ROW][C]283[/C][C]17.75[/C][C]15.3087[/C][C]2.44126[/C][/ROW]
[ROW][C]284[/C][C]15.2[/C][C]14.2079[/C][C]0.992056[/C][/ROW]
[ROW][C]285[/C][C]14.6[/C][C]10.7583[/C][C]3.84166[/C][/ROW]
[ROW][C]286[/C][C]16.65[/C][C]19.5601[/C][C]-2.91006[/C][/ROW]
[ROW][C]287[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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
112.914.1955-1.29552
27.413.817-6.41697
312.213.814-1.61397
412.814.232-1.432
57.413.7042-6.30415
66.713.8806-7.18061
712.615.1084-2.50838
814.813.46861.33138
913.313.4858-0.185791
1011.113.4999-2.39986
118.215.6217-7.42168
1211.414.0736-2.67362
136.413.9121-7.5121
1410.612.2619-1.66185
151214.0192-2.01918
166.310.9813-4.68132
1711.311.777-0.477008
1811.913.9109-2.01089
199.312.949-3.64904
209.613.7961-4.19613
211012.1094-2.1094
226.413.4018-7.00176
2313.814.061-0.260993
2410.815.1644-4.36442
2513.814.2024-0.402389
2611.714.012-2.31204
2710.915.0138-4.11383
2816.114.41771.6823
2913.412.55760.842372
309.913.8936-3.99359
3111.512.8947-1.39474
328.311.5367-3.23674
3311.714.1157-2.41574
346.113.0981-6.99811
35913.2503-4.25033
369.713.7193-4.01933
3710.812.5182-1.71821
3810.312.8165-2.51649
3910.412.85-2.45004
4012.713.1133-0.413312
419.314.8793-5.5793
4211.813.5454-1.74536
435.913.5382-7.63817
4411.414.149-2.749
451314.0675-1.06748
4610.813.3102-2.51022
4712.311.14331.15666
4811.314.9544-3.65444
4911.812.7794-0.979399
507.912.271-4.37096
5112.711.92580.774192
5212.312.5105-0.210468
5311.612.5709-0.970903
546.711.0685-4.3685
5510.913.7245-2.8245
5612.113.598-1.498
5713.313.3403-0.0403176
5810.113.0682-2.9682
595.712.4994-6.79938
6014.313.01441.28564
61810.6247-2.62465
6213.312.99970.300274
639.314.6846-5.38461
6412.513.9879-1.48788
657.611.7971-4.19714
6615.915.0080.891956
679.214.8007-5.60067
689.111.8117-2.71173
6911.114.2467-3.14672
701315.4369-2.43686
7114.514.41250.0875358
7212.212.4424-0.24235
7312.315.1365-2.83652
7411.413.1336-1.73362
758.812.3993-3.59933
7614.613.52541.07464
777.314.1543-6.85434
7812.612.14980.450215
79NANA-0.548117
801313.5375-0.537537
8112.613.4531-0.853124
8213.214.3834-1.18345
839.914.878-4.97802
847.79.68526-1.98526
8510.59.110231.38977
8613.414.4053-1.00532
8710.918.7615-7.86149
884.36.81183-2.51183
8910.311.5259-1.2259
9011.812.6339-0.833874
9111.211.3374-0.137417
9211.415.2548-3.85482
938.68.129050.470952
9413.212.71180.488184
9512.619.5548-6.95483
965.69.1232-3.5232
979.913.3212-3.42125
988.813.7555-4.95551
997.711.5284-3.8284
100915.2485-6.24852
1017.38.44494-1.14494
10211.410.31281.08723
10313.618.2661-4.66607
1047.98.90529-1.00529
10510.712.4714-1.77136
10610.312.9577-2.65774
1078.311.5135-3.21353
1089.67.71581.8842
10914.217.9208-3.72081
1108.57.257221.24278
11113.520.1684-6.66835
1124.99.7953-4.8953
1136.49.37454-2.97454
1149.610.8102-1.21016
11511.612.9968-1.39683
11611.119.049-7.94904
1174.353.107791.24221
11812.78.172144.52786
11918.114.16373.93632
12017.8515.06222.78777
12116.616.14220.457843
12212.611.25711.3429
12317.112.4464.65396
12419.117.23971.86028
12516.114.36311.7369
12613.359.402363.94764
12718.414.51373.88628
12814.716.6863-1.98633
12910.610.3470.252967
13012.69.649632.95037
13116.215.31360.886392
13213.68.364555.23545
13318.917.77741.1226
13414.112.96171.13831
13514.512.49332.00667
13616.1513.82092.32906
13714.7512.45262.29742
13814.814.17750.622541
13912.4512.3390.110985
14012.658.543664.10634
14117.3519.3598-2.00977
1428.63.763054.83695
14318.416.17982.22021
14416.116.552-0.451989
14511.67.571954.02805
14617.7515.21742.53262
14715.2510.25384.99623
14817.6515.51592.13408
14915.612.99362.6064
15016.3513.09183.2582
15117.6517.8716-0.22163
15213.615.2223-1.62235
15311.710.17441.52565
15414.3512.40381.94623
15514.7511.42323.32681
15618.2521.6052-3.35521
1579.97.371862.52814
1581612.19553.80448
15918.2515.55032.69972
16016.8514.65622.19382
16114.613.48631.11372
16213.8510.03373.81633
16318.9516.06592.88411
16415.614.67330.926709
16514.8514.8508-0.000846216
16611.756.728425.02158
16718.4514.60823.84178
16815.913.26532.63474
16917.111.7955.30497
17016.111.68894.41108
17119.920.4573-0.557277
17210.955.551645.39836
17318.4516.00312.44693
17415.113.171.93001
1751515.8059-0.805945
17611.358.221553.12845
17715.9510.92765.0224
17818.117.37570.724264
17914.613.96710.632938
18015.414.65080.749219
18115.410.05145.3486
18217.617.732-0.132022
18313.357.689645.66036
18419.117.4011.69896
18515.3518.8042-3.45418
1867.67.104530.495473
18713.412.63860.761351
18813.98.727335.17267
18919.116.00713.09294
19015.2515.7983-0.548312
19112.910.12922.7708
19216.111.87954.2205
19317.3517.25640.0936131
19413.1514.3285-1.17853
19512.1510.68031.46968
19612.614.2715-1.67149
19710.356.698913.65109
19815.417.8493-2.44933
1999.63.923785.67622
20018.216.78481.41517
20113.612.26181.33821
20214.8513.6481.20204
20314.7512.13682.61317
20414.111.06533.03466
20514.911.76243.13758
20616.2515.24021.00981
20719.2518.4720.778034
20813.613.20960.390412
20913.610.44153.15852
21015.6515.14030.50974
21112.759.651283.09872
21214.615.4446-0.844599
2139.859.532540.317464
21412.6512.16310.486873
21511.94.203447.69656
21619.214.53564.66444
21716.616.7882-0.18824
21811.29.587351.61265
21915.2515.23970.0102794
22011.99.820732.07927
22113.210.35462.8454
22216.3516.7244-0.374375
22312.48.982953.41705
22415.8515.74480.105157
22514.3510.43113.91895
22618.1518.4207-0.270727
22711.158.872072.27793
22815.6510.74334.90667
22917.7520.512-2.76196
2307.658.94698-1.29698
23112.359.254693.09531
23215.610.0245.57596
23319.315.76263.53736
23415.211.40923.7908
23517.113.79853.30151
23615.69.959555.64045
23718.412.80875.59128
23819.0513.91535.13472
23918.5513.09155.4585
24019.117.81851.28149
24113.113.9137-0.81367
24212.8514.6879-1.83786
2439.516.9144-7.41442
2444.53.633160.866838
24511.8511.36060.48938
24613.614.2761-0.676063
24711.711.18510.514872
24812.412.01090.389144
24913.3512.28811.06188
25011.49.279332.12067
25114.99.850385.04962
25219.915.81274.08731
25317.7519.4565-1.7065
25411.28.953172.24683
25514.611.07823.52175
25617.616.74990.850088
25714.0511.09092.95909
25816.115.94290.157149
25913.3514.8764-1.52637
26011.8511.71240.137609
26111.959.591652.35835
26214.7511.23413.51591
26315.1516.2283-1.07826
26413.29.547373.65263
26516.8520.3483-3.49834
2667.8511.899-4.049
2677.77.305410.39459
26812.617.6029-5.00293
2697.859.42423-1.57423
27010.9510.72870.22129
27112.3514.9882-2.63825
2729.957.900752.04925
27314.910.61894.28113
27416.6515.46321.18677
27513.411.92861.47136
27613.9510.16353.78654
27715.712.24063.45938
27816.8517.4234-0.5734
27910.957.972872.97713
28015.3514.7160.634013
28112.28.143834.05617
28215.110.27494.82513
28317.7515.30872.44126
28415.214.20790.992056
28514.610.75833.84166
28616.6519.5601-2.91006
2878.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.6705830.6588340.329417
100.5123810.9752390.487619
110.5484340.9031320.451566
120.4232870.8465740.576713
130.3491920.6983840.650808
140.2530940.5061880.746906
150.1901680.3803350.809832
160.1304240.2608490.869576
170.142010.2840190.85799
180.1073620.2147240.892638
190.07586190.1517240.924138
200.05132170.1026430.948678
210.0432950.086590.956705
220.05178130.1035630.948219
230.03376440.06752890.966236
240.02342050.04684090.97658
250.02227770.04455530.977722
260.01763870.03527740.982361
270.01224310.02448610.987757
280.008060870.01612170.991939
290.01340370.02680740.986596
300.01037530.02075060.989625
310.007031740.01406350.992968
320.01350130.02700270.986499
330.01065410.02130830.989346
340.01767120.03534230.982329
350.01348070.02696130.986519
360.03130730.06261460.968693
370.02250080.04500170.977499
380.01654090.03308190.983459
390.01324490.02648990.986755
400.0112970.02259390.988703
410.01262540.02525090.987375
420.009040690.01808140.990959
430.02113240.04226480.978868
440.01600440.03200880.983996
450.01338330.02676650.986617
460.01009510.02019020.989905
470.008354560.01670910.991645
480.006828360.01365670.993172
490.005691040.01138210.994309
500.00669420.01338840.993306
510.01153570.02307140.988464
520.009641970.01928390.990358
530.007510670.01502130.992489
540.007531810.01506360.992468
550.005931430.01186290.994069
560.005973020.0119460.994027
570.006439940.01287990.99356
580.004995660.009991310.995004
590.01477040.02954080.98523
600.01895010.03790030.98105
610.01542970.03085950.98457
620.0170340.0340680.982966
630.01783630.03567270.982164
640.01517960.03035930.98482
650.0163570.03271390.983643
660.0215540.0431080.978446
670.02595250.0519050.974048
680.02130580.04261160.978694
690.02039290.04078580.979607
700.02205740.04411480.977943
710.01967560.03935120.980324
720.01620170.03240340.983798
730.01523090.03046180.984769
740.01292970.02585950.98707
750.01086830.02173670.989132
760.01395350.02790710.986046
770.03705220.07410440.962948
780.03217640.06435280.967824
790.02857820.05715630.971422
800.02473910.04947820.975261
810.02700780.05401570.972992
820.02213520.04427050.977865
830.02766290.05532590.972337
840.02336570.04673140.976634
850.02553740.05107480.974463
860.02127010.04254020.97873
870.05424150.1084830.945759
880.05130560.1026110.948694
890.04661320.09322630.953387
900.03916470.07832940.960835
910.0331890.0663780.966811
920.03338210.06676420.966618
930.03515140.07030290.964849
940.03740760.07481520.962592
950.08348750.1669750.916513
960.08907140.1781430.910929
970.09059070.1811810.909409
980.1097330.2194650.890267
990.1177760.2355520.882224
1000.1819090.3638170.818091
1010.1741310.3482620.825869
1020.1952850.390570.804715
1030.2493020.4986030.750698
1040.2328920.4657840.767108
1050.2246590.4493180.775341
1060.2297020.4594040.770298
1070.2521390.5042780.747861
1080.2838560.5677110.716144
1090.3121310.6242630.687869
1100.314630.6292590.68537
1110.5052210.9895580.494779
1120.5497920.9004160.450208
1130.557740.884520.44226
1140.5605570.8788860.439443
1150.5548820.8902370.445118
1160.7432950.513410.256705
1170.7440120.5119750.255988
1180.8471710.3056590.152829
1190.9098130.1803730.0901867
1200.9358660.1282680.0641342
1210.9351210.1297590.0648795
1220.9436650.112670.0563349
1230.9652680.06946350.0347317
1240.9650260.06994810.034974
1250.9674890.06502240.0325112
1260.9800690.03986250.0199312
1270.9892550.02148970.0107448
1280.9890660.02186780.0109339
1290.9883820.02323650.0116183
1300.9902310.01953810.00976903
1310.9877550.02449080.0122454
1320.9929030.01419420.00709711
1330.9920460.01590720.00795358
1340.9915620.01687620.00843811
1350.9905770.01884630.00942315
1360.9903380.01932380.00966191
1370.9901810.01963740.00981872
1380.9883740.02325220.0116261
1390.9862530.02749310.0137466
1400.9910150.01796910.00898455
1410.9897330.02053350.0102667
1420.9941520.01169620.00584809
1430.9940680.0118640.00593198
1440.9927550.01448940.00724472
1450.9942950.01141030.00570517
1460.9940490.01190220.00595111
1470.9964390.007121170.00356059
1480.9963530.007294650.00364733
1490.9963330.00733350.00366675
1500.9967560.006488590.0032443
1510.9961540.007692950.00384647
1520.9965710.006858780.00342939
1530.9959850.008030150.00401508
1540.9956420.008716920.00435846
1550.9958620.008276930.00413847
1560.9985320.002935930.00146797
1570.9984360.003127170.00156358
1580.9986080.002783380.00139169
1590.9985010.002997950.00149897
1600.9984590.0030820.001541
1610.9981710.003658040.00182902
1620.99830.003399590.0016998
1630.9982290.003541930.00177096
1640.9977660.004467840.00223392
1650.9971090.005782410.00289121
1660.9981120.003775620.00188781
1670.9984370.003125170.00156258
1680.9982330.003533960.00176698
1690.9995970.0008067770.000403388
1700.9996320.0007361210.000368061
1710.9994940.001011860.000505929
1720.9997010.0005980930.000299047
1730.9996530.0006948150.000347407
1740.9995660.0008680450.000434023
1750.9994470.00110540.000552701
1760.9994360.001128510.000564253
1770.999630.0007393450.000369672
1780.999520.000959080.00047954
1790.9994320.001136630.000568317
1800.9993420.001316590.000658293
1810.999590.0008191510.000409576
1820.9994730.00105480.000527398
1830.9996210.0007588840.000379442
1840.9995180.0009630610.00048153
1850.999570.000859790.000429895
1860.9994020.001195810.000597903
1870.9992140.001572950.000786475
1880.9993430.001313240.000656619
1890.9992710.001458860.000729428
1900.9993330.001334710.000667356
1910.9992230.001554420.000777211
1920.9993530.001294450.000647226
1930.9991460.001707470.000853734
1940.9990070.00198560.0009928
1950.9987260.002547870.00127394
1960.9984030.003193760.00159688
1970.9983660.003268560.00163428
1980.9982940.003411020.00170551
1990.9989950.002009410.00100471
2000.9986640.002672340.00133617
2010.9984420.003115370.00155768
2020.9981470.003705350.00185268
2030.9977820.004436510.00221825
2040.9977180.004564260.00228213
2050.9975270.004945060.00247253
2060.9968060.006387170.00319359
2070.996070.007859180.00392959
2080.9956570.008686060.00434303
2090.9948010.01039820.00519909
2100.9941280.0117440.00587202
2110.9944590.01108120.0055406
2120.9926330.01473420.00736708
2130.9907990.01840250.00920123
2140.988010.023980.01199
2150.9937320.01253630.00626817
2160.9947740.01045190.00522597
2170.993030.01394070.00697035
2180.9916280.01674430.00837216
2190.9896320.02073630.0103682
2200.9872340.02553120.0127656
2210.9843880.03122440.0156122
2220.9804490.03910190.019551
2230.9802060.03958870.0197944
2240.9787010.04259880.0212994
2250.9751080.04978440.0248922
2260.967890.06422070.0321103
2270.9609590.07808150.0390407
2280.9601370.07972570.0398629
2290.9584070.08318650.0415932
2300.954760.09047910.0452396
2310.945410.109180.0545901
2320.9438340.1123310.0561657
2330.9557060.08858760.0442938
2340.9472370.1055260.0527631
2350.9511170.09776580.0488829
2360.9578970.08420680.0421034
2370.959340.08131960.0406598
2380.9552250.08955030.0447751
2390.9604940.07901170.0395058
2400.9491360.1017290.0508644
2410.9564760.08704770.0435238
2420.9602830.07943310.0397165
2430.9909830.0180330.00901652
2440.9876340.02473130.0123656
2450.9844150.03116920.0155846
2460.9793290.04134190.020671
2470.9716780.05664480.0283224
2480.9659730.06805450.0340272
2490.956290.08742090.0437105
2500.9438680.1122640.056132
2510.9586820.08263690.0413184
2520.9535440.09291230.0464562
2530.938180.123640.0618201
2540.9216260.1567490.0783744
2550.8996270.2007460.100373
2560.8724260.2551470.127574
2570.8397190.3205620.160281
2580.8362270.3275450.163773
2590.8321970.3356060.167803
2600.7896670.4206660.210333
2610.7460850.5078290.253915
2620.841470.3170590.15853
2630.8688720.2622560.131128
2640.8451030.3097950.154897
2650.8389090.3221830.161091
2660.9742070.05158590.025793
2670.957520.08495990.04248
2680.9979040.00419140.0020957
2690.9979680.004063360.00203168
2700.99790.004199420.00209971
2710.9976560.004687630.00234382
2720.993860.01228060.00614028
2730.9920480.01590490.00795243
2740.9833030.0333940.016697
2750.9782530.0434940.021747
2760.9414350.117130.0585652
2770.8557250.288550.144275
2780.7071540.5856920.292846

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.670583 & 0.658834 & 0.329417 \tabularnewline
10 & 0.512381 & 0.975239 & 0.487619 \tabularnewline
11 & 0.548434 & 0.903132 & 0.451566 \tabularnewline
12 & 0.423287 & 0.846574 & 0.576713 \tabularnewline
13 & 0.349192 & 0.698384 & 0.650808 \tabularnewline
14 & 0.253094 & 0.506188 & 0.746906 \tabularnewline
15 & 0.190168 & 0.380335 & 0.809832 \tabularnewline
16 & 0.130424 & 0.260849 & 0.869576 \tabularnewline
17 & 0.14201 & 0.284019 & 0.85799 \tabularnewline
18 & 0.107362 & 0.214724 & 0.892638 \tabularnewline
19 & 0.0758619 & 0.151724 & 0.924138 \tabularnewline
20 & 0.0513217 & 0.102643 & 0.948678 \tabularnewline
21 & 0.043295 & 0.08659 & 0.956705 \tabularnewline
22 & 0.0517813 & 0.103563 & 0.948219 \tabularnewline
23 & 0.0337644 & 0.0675289 & 0.966236 \tabularnewline
24 & 0.0234205 & 0.0468409 & 0.97658 \tabularnewline
25 & 0.0222777 & 0.0445553 & 0.977722 \tabularnewline
26 & 0.0176387 & 0.0352774 & 0.982361 \tabularnewline
27 & 0.0122431 & 0.0244861 & 0.987757 \tabularnewline
28 & 0.00806087 & 0.0161217 & 0.991939 \tabularnewline
29 & 0.0134037 & 0.0268074 & 0.986596 \tabularnewline
30 & 0.0103753 & 0.0207506 & 0.989625 \tabularnewline
31 & 0.00703174 & 0.0140635 & 0.992968 \tabularnewline
32 & 0.0135013 & 0.0270027 & 0.986499 \tabularnewline
33 & 0.0106541 & 0.0213083 & 0.989346 \tabularnewline
34 & 0.0176712 & 0.0353423 & 0.982329 \tabularnewline
35 & 0.0134807 & 0.0269613 & 0.986519 \tabularnewline
36 & 0.0313073 & 0.0626146 & 0.968693 \tabularnewline
37 & 0.0225008 & 0.0450017 & 0.977499 \tabularnewline
38 & 0.0165409 & 0.0330819 & 0.983459 \tabularnewline
39 & 0.0132449 & 0.0264899 & 0.986755 \tabularnewline
40 & 0.011297 & 0.0225939 & 0.988703 \tabularnewline
41 & 0.0126254 & 0.0252509 & 0.987375 \tabularnewline
42 & 0.00904069 & 0.0180814 & 0.990959 \tabularnewline
43 & 0.0211324 & 0.0422648 & 0.978868 \tabularnewline
44 & 0.0160044 & 0.0320088 & 0.983996 \tabularnewline
45 & 0.0133833 & 0.0267665 & 0.986617 \tabularnewline
46 & 0.0100951 & 0.0201902 & 0.989905 \tabularnewline
47 & 0.00835456 & 0.0167091 & 0.991645 \tabularnewline
48 & 0.00682836 & 0.0136567 & 0.993172 \tabularnewline
49 & 0.00569104 & 0.0113821 & 0.994309 \tabularnewline
50 & 0.0066942 & 0.0133884 & 0.993306 \tabularnewline
51 & 0.0115357 & 0.0230714 & 0.988464 \tabularnewline
52 & 0.00964197 & 0.0192839 & 0.990358 \tabularnewline
53 & 0.00751067 & 0.0150213 & 0.992489 \tabularnewline
54 & 0.00753181 & 0.0150636 & 0.992468 \tabularnewline
55 & 0.00593143 & 0.0118629 & 0.994069 \tabularnewline
56 & 0.00597302 & 0.011946 & 0.994027 \tabularnewline
57 & 0.00643994 & 0.0128799 & 0.99356 \tabularnewline
58 & 0.00499566 & 0.00999131 & 0.995004 \tabularnewline
59 & 0.0147704 & 0.0295408 & 0.98523 \tabularnewline
60 & 0.0189501 & 0.0379003 & 0.98105 \tabularnewline
61 & 0.0154297 & 0.0308595 & 0.98457 \tabularnewline
62 & 0.017034 & 0.034068 & 0.982966 \tabularnewline
63 & 0.0178363 & 0.0356727 & 0.982164 \tabularnewline
64 & 0.0151796 & 0.0303593 & 0.98482 \tabularnewline
65 & 0.016357 & 0.0327139 & 0.983643 \tabularnewline
66 & 0.021554 & 0.043108 & 0.978446 \tabularnewline
67 & 0.0259525 & 0.051905 & 0.974048 \tabularnewline
68 & 0.0213058 & 0.0426116 & 0.978694 \tabularnewline
69 & 0.0203929 & 0.0407858 & 0.979607 \tabularnewline
70 & 0.0220574 & 0.0441148 & 0.977943 \tabularnewline
71 & 0.0196756 & 0.0393512 & 0.980324 \tabularnewline
72 & 0.0162017 & 0.0324034 & 0.983798 \tabularnewline
73 & 0.0152309 & 0.0304618 & 0.984769 \tabularnewline
74 & 0.0129297 & 0.0258595 & 0.98707 \tabularnewline
75 & 0.0108683 & 0.0217367 & 0.989132 \tabularnewline
76 & 0.0139535 & 0.0279071 & 0.986046 \tabularnewline
77 & 0.0370522 & 0.0741044 & 0.962948 \tabularnewline
78 & 0.0321764 & 0.0643528 & 0.967824 \tabularnewline
79 & 0.0285782 & 0.0571563 & 0.971422 \tabularnewline
80 & 0.0247391 & 0.0494782 & 0.975261 \tabularnewline
81 & 0.0270078 & 0.0540157 & 0.972992 \tabularnewline
82 & 0.0221352 & 0.0442705 & 0.977865 \tabularnewline
83 & 0.0276629 & 0.0553259 & 0.972337 \tabularnewline
84 & 0.0233657 & 0.0467314 & 0.976634 \tabularnewline
85 & 0.0255374 & 0.0510748 & 0.974463 \tabularnewline
86 & 0.0212701 & 0.0425402 & 0.97873 \tabularnewline
87 & 0.0542415 & 0.108483 & 0.945759 \tabularnewline
88 & 0.0513056 & 0.102611 & 0.948694 \tabularnewline
89 & 0.0466132 & 0.0932263 & 0.953387 \tabularnewline
90 & 0.0391647 & 0.0783294 & 0.960835 \tabularnewline
91 & 0.033189 & 0.066378 & 0.966811 \tabularnewline
92 & 0.0333821 & 0.0667642 & 0.966618 \tabularnewline
93 & 0.0351514 & 0.0703029 & 0.964849 \tabularnewline
94 & 0.0374076 & 0.0748152 & 0.962592 \tabularnewline
95 & 0.0834875 & 0.166975 & 0.916513 \tabularnewline
96 & 0.0890714 & 0.178143 & 0.910929 \tabularnewline
97 & 0.0905907 & 0.181181 & 0.909409 \tabularnewline
98 & 0.109733 & 0.219465 & 0.890267 \tabularnewline
99 & 0.117776 & 0.235552 & 0.882224 \tabularnewline
100 & 0.181909 & 0.363817 & 0.818091 \tabularnewline
101 & 0.174131 & 0.348262 & 0.825869 \tabularnewline
102 & 0.195285 & 0.39057 & 0.804715 \tabularnewline
103 & 0.249302 & 0.498603 & 0.750698 \tabularnewline
104 & 0.232892 & 0.465784 & 0.767108 \tabularnewline
105 & 0.224659 & 0.449318 & 0.775341 \tabularnewline
106 & 0.229702 & 0.459404 & 0.770298 \tabularnewline
107 & 0.252139 & 0.504278 & 0.747861 \tabularnewline
108 & 0.283856 & 0.567711 & 0.716144 \tabularnewline
109 & 0.312131 & 0.624263 & 0.687869 \tabularnewline
110 & 0.31463 & 0.629259 & 0.68537 \tabularnewline
111 & 0.505221 & 0.989558 & 0.494779 \tabularnewline
112 & 0.549792 & 0.900416 & 0.450208 \tabularnewline
113 & 0.55774 & 0.88452 & 0.44226 \tabularnewline
114 & 0.560557 & 0.878886 & 0.439443 \tabularnewline
115 & 0.554882 & 0.890237 & 0.445118 \tabularnewline
116 & 0.743295 & 0.51341 & 0.256705 \tabularnewline
117 & 0.744012 & 0.511975 & 0.255988 \tabularnewline
118 & 0.847171 & 0.305659 & 0.152829 \tabularnewline
119 & 0.909813 & 0.180373 & 0.0901867 \tabularnewline
120 & 0.935866 & 0.128268 & 0.0641342 \tabularnewline
121 & 0.935121 & 0.129759 & 0.0648795 \tabularnewline
122 & 0.943665 & 0.11267 & 0.0563349 \tabularnewline
123 & 0.965268 & 0.0694635 & 0.0347317 \tabularnewline
124 & 0.965026 & 0.0699481 & 0.034974 \tabularnewline
125 & 0.967489 & 0.0650224 & 0.0325112 \tabularnewline
126 & 0.980069 & 0.0398625 & 0.0199312 \tabularnewline
127 & 0.989255 & 0.0214897 & 0.0107448 \tabularnewline
128 & 0.989066 & 0.0218678 & 0.0109339 \tabularnewline
129 & 0.988382 & 0.0232365 & 0.0116183 \tabularnewline
130 & 0.990231 & 0.0195381 & 0.00976903 \tabularnewline
131 & 0.987755 & 0.0244908 & 0.0122454 \tabularnewline
132 & 0.992903 & 0.0141942 & 0.00709711 \tabularnewline
133 & 0.992046 & 0.0159072 & 0.00795358 \tabularnewline
134 & 0.991562 & 0.0168762 & 0.00843811 \tabularnewline
135 & 0.990577 & 0.0188463 & 0.00942315 \tabularnewline
136 & 0.990338 & 0.0193238 & 0.00966191 \tabularnewline
137 & 0.990181 & 0.0196374 & 0.00981872 \tabularnewline
138 & 0.988374 & 0.0232522 & 0.0116261 \tabularnewline
139 & 0.986253 & 0.0274931 & 0.0137466 \tabularnewline
140 & 0.991015 & 0.0179691 & 0.00898455 \tabularnewline
141 & 0.989733 & 0.0205335 & 0.0102667 \tabularnewline
142 & 0.994152 & 0.0116962 & 0.00584809 \tabularnewline
143 & 0.994068 & 0.011864 & 0.00593198 \tabularnewline
144 & 0.992755 & 0.0144894 & 0.00724472 \tabularnewline
145 & 0.994295 & 0.0114103 & 0.00570517 \tabularnewline
146 & 0.994049 & 0.0119022 & 0.00595111 \tabularnewline
147 & 0.996439 & 0.00712117 & 0.00356059 \tabularnewline
148 & 0.996353 & 0.00729465 & 0.00364733 \tabularnewline
149 & 0.996333 & 0.0073335 & 0.00366675 \tabularnewline
150 & 0.996756 & 0.00648859 & 0.0032443 \tabularnewline
151 & 0.996154 & 0.00769295 & 0.00384647 \tabularnewline
152 & 0.996571 & 0.00685878 & 0.00342939 \tabularnewline
153 & 0.995985 & 0.00803015 & 0.00401508 \tabularnewline
154 & 0.995642 & 0.00871692 & 0.00435846 \tabularnewline
155 & 0.995862 & 0.00827693 & 0.00413847 \tabularnewline
156 & 0.998532 & 0.00293593 & 0.00146797 \tabularnewline
157 & 0.998436 & 0.00312717 & 0.00156358 \tabularnewline
158 & 0.998608 & 0.00278338 & 0.00139169 \tabularnewline
159 & 0.998501 & 0.00299795 & 0.00149897 \tabularnewline
160 & 0.998459 & 0.003082 & 0.001541 \tabularnewline
161 & 0.998171 & 0.00365804 & 0.00182902 \tabularnewline
162 & 0.9983 & 0.00339959 & 0.0016998 \tabularnewline
163 & 0.998229 & 0.00354193 & 0.00177096 \tabularnewline
164 & 0.997766 & 0.00446784 & 0.00223392 \tabularnewline
165 & 0.997109 & 0.00578241 & 0.00289121 \tabularnewline
166 & 0.998112 & 0.00377562 & 0.00188781 \tabularnewline
167 & 0.998437 & 0.00312517 & 0.00156258 \tabularnewline
168 & 0.998233 & 0.00353396 & 0.00176698 \tabularnewline
169 & 0.999597 & 0.000806777 & 0.000403388 \tabularnewline
170 & 0.999632 & 0.000736121 & 0.000368061 \tabularnewline
171 & 0.999494 & 0.00101186 & 0.000505929 \tabularnewline
172 & 0.999701 & 0.000598093 & 0.000299047 \tabularnewline
173 & 0.999653 & 0.000694815 & 0.000347407 \tabularnewline
174 & 0.999566 & 0.000868045 & 0.000434023 \tabularnewline
175 & 0.999447 & 0.0011054 & 0.000552701 \tabularnewline
176 & 0.999436 & 0.00112851 & 0.000564253 \tabularnewline
177 & 0.99963 & 0.000739345 & 0.000369672 \tabularnewline
178 & 0.99952 & 0.00095908 & 0.00047954 \tabularnewline
179 & 0.999432 & 0.00113663 & 0.000568317 \tabularnewline
180 & 0.999342 & 0.00131659 & 0.000658293 \tabularnewline
181 & 0.99959 & 0.000819151 & 0.000409576 \tabularnewline
182 & 0.999473 & 0.0010548 & 0.000527398 \tabularnewline
183 & 0.999621 & 0.000758884 & 0.000379442 \tabularnewline
184 & 0.999518 & 0.000963061 & 0.00048153 \tabularnewline
185 & 0.99957 & 0.00085979 & 0.000429895 \tabularnewline
186 & 0.999402 & 0.00119581 & 0.000597903 \tabularnewline
187 & 0.999214 & 0.00157295 & 0.000786475 \tabularnewline
188 & 0.999343 & 0.00131324 & 0.000656619 \tabularnewline
189 & 0.999271 & 0.00145886 & 0.000729428 \tabularnewline
190 & 0.999333 & 0.00133471 & 0.000667356 \tabularnewline
191 & 0.999223 & 0.00155442 & 0.000777211 \tabularnewline
192 & 0.999353 & 0.00129445 & 0.000647226 \tabularnewline
193 & 0.999146 & 0.00170747 & 0.000853734 \tabularnewline
194 & 0.999007 & 0.0019856 & 0.0009928 \tabularnewline
195 & 0.998726 & 0.00254787 & 0.00127394 \tabularnewline
196 & 0.998403 & 0.00319376 & 0.00159688 \tabularnewline
197 & 0.998366 & 0.00326856 & 0.00163428 \tabularnewline
198 & 0.998294 & 0.00341102 & 0.00170551 \tabularnewline
199 & 0.998995 & 0.00200941 & 0.00100471 \tabularnewline
200 & 0.998664 & 0.00267234 & 0.00133617 \tabularnewline
201 & 0.998442 & 0.00311537 & 0.00155768 \tabularnewline
202 & 0.998147 & 0.00370535 & 0.00185268 \tabularnewline
203 & 0.997782 & 0.00443651 & 0.00221825 \tabularnewline
204 & 0.997718 & 0.00456426 & 0.00228213 \tabularnewline
205 & 0.997527 & 0.00494506 & 0.00247253 \tabularnewline
206 & 0.996806 & 0.00638717 & 0.00319359 \tabularnewline
207 & 0.99607 & 0.00785918 & 0.00392959 \tabularnewline
208 & 0.995657 & 0.00868606 & 0.00434303 \tabularnewline
209 & 0.994801 & 0.0103982 & 0.00519909 \tabularnewline
210 & 0.994128 & 0.011744 & 0.00587202 \tabularnewline
211 & 0.994459 & 0.0110812 & 0.0055406 \tabularnewline
212 & 0.992633 & 0.0147342 & 0.00736708 \tabularnewline
213 & 0.990799 & 0.0184025 & 0.00920123 \tabularnewline
214 & 0.98801 & 0.02398 & 0.01199 \tabularnewline
215 & 0.993732 & 0.0125363 & 0.00626817 \tabularnewline
216 & 0.994774 & 0.0104519 & 0.00522597 \tabularnewline
217 & 0.99303 & 0.0139407 & 0.00697035 \tabularnewline
218 & 0.991628 & 0.0167443 & 0.00837216 \tabularnewline
219 & 0.989632 & 0.0207363 & 0.0103682 \tabularnewline
220 & 0.987234 & 0.0255312 & 0.0127656 \tabularnewline
221 & 0.984388 & 0.0312244 & 0.0156122 \tabularnewline
222 & 0.980449 & 0.0391019 & 0.019551 \tabularnewline
223 & 0.980206 & 0.0395887 & 0.0197944 \tabularnewline
224 & 0.978701 & 0.0425988 & 0.0212994 \tabularnewline
225 & 0.975108 & 0.0497844 & 0.0248922 \tabularnewline
226 & 0.96789 & 0.0642207 & 0.0321103 \tabularnewline
227 & 0.960959 & 0.0780815 & 0.0390407 \tabularnewline
228 & 0.960137 & 0.0797257 & 0.0398629 \tabularnewline
229 & 0.958407 & 0.0831865 & 0.0415932 \tabularnewline
230 & 0.95476 & 0.0904791 & 0.0452396 \tabularnewline
231 & 0.94541 & 0.10918 & 0.0545901 \tabularnewline
232 & 0.943834 & 0.112331 & 0.0561657 \tabularnewline
233 & 0.955706 & 0.0885876 & 0.0442938 \tabularnewline
234 & 0.947237 & 0.105526 & 0.0527631 \tabularnewline
235 & 0.951117 & 0.0977658 & 0.0488829 \tabularnewline
236 & 0.957897 & 0.0842068 & 0.0421034 \tabularnewline
237 & 0.95934 & 0.0813196 & 0.0406598 \tabularnewline
238 & 0.955225 & 0.0895503 & 0.0447751 \tabularnewline
239 & 0.960494 & 0.0790117 & 0.0395058 \tabularnewline
240 & 0.949136 & 0.101729 & 0.0508644 \tabularnewline
241 & 0.956476 & 0.0870477 & 0.0435238 \tabularnewline
242 & 0.960283 & 0.0794331 & 0.0397165 \tabularnewline
243 & 0.990983 & 0.018033 & 0.00901652 \tabularnewline
244 & 0.987634 & 0.0247313 & 0.0123656 \tabularnewline
245 & 0.984415 & 0.0311692 & 0.0155846 \tabularnewline
246 & 0.979329 & 0.0413419 & 0.020671 \tabularnewline
247 & 0.971678 & 0.0566448 & 0.0283224 \tabularnewline
248 & 0.965973 & 0.0680545 & 0.0340272 \tabularnewline
249 & 0.95629 & 0.0874209 & 0.0437105 \tabularnewline
250 & 0.943868 & 0.112264 & 0.056132 \tabularnewline
251 & 0.958682 & 0.0826369 & 0.0413184 \tabularnewline
252 & 0.953544 & 0.0929123 & 0.0464562 \tabularnewline
253 & 0.93818 & 0.12364 & 0.0618201 \tabularnewline
254 & 0.921626 & 0.156749 & 0.0783744 \tabularnewline
255 & 0.899627 & 0.200746 & 0.100373 \tabularnewline
256 & 0.872426 & 0.255147 & 0.127574 \tabularnewline
257 & 0.839719 & 0.320562 & 0.160281 \tabularnewline
258 & 0.836227 & 0.327545 & 0.163773 \tabularnewline
259 & 0.832197 & 0.335606 & 0.167803 \tabularnewline
260 & 0.789667 & 0.420666 & 0.210333 \tabularnewline
261 & 0.746085 & 0.507829 & 0.253915 \tabularnewline
262 & 0.84147 & 0.317059 & 0.15853 \tabularnewline
263 & 0.868872 & 0.262256 & 0.131128 \tabularnewline
264 & 0.845103 & 0.309795 & 0.154897 \tabularnewline
265 & 0.838909 & 0.322183 & 0.161091 \tabularnewline
266 & 0.974207 & 0.0515859 & 0.025793 \tabularnewline
267 & 0.95752 & 0.0849599 & 0.04248 \tabularnewline
268 & 0.997904 & 0.0041914 & 0.0020957 \tabularnewline
269 & 0.997968 & 0.00406336 & 0.00203168 \tabularnewline
270 & 0.9979 & 0.00419942 & 0.00209971 \tabularnewline
271 & 0.997656 & 0.00468763 & 0.00234382 \tabularnewline
272 & 0.99386 & 0.0122806 & 0.00614028 \tabularnewline
273 & 0.992048 & 0.0159049 & 0.00795243 \tabularnewline
274 & 0.983303 & 0.033394 & 0.016697 \tabularnewline
275 & 0.978253 & 0.043494 & 0.021747 \tabularnewline
276 & 0.941435 & 0.11713 & 0.0585652 \tabularnewline
277 & 0.855725 & 0.28855 & 0.144275 \tabularnewline
278 & 0.707154 & 0.585692 & 0.292846 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&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]9[/C][C]0.670583[/C][C]0.658834[/C][C]0.329417[/C][/ROW]
[ROW][C]10[/C][C]0.512381[/C][C]0.975239[/C][C]0.487619[/C][/ROW]
[ROW][C]11[/C][C]0.548434[/C][C]0.903132[/C][C]0.451566[/C][/ROW]
[ROW][C]12[/C][C]0.423287[/C][C]0.846574[/C][C]0.576713[/C][/ROW]
[ROW][C]13[/C][C]0.349192[/C][C]0.698384[/C][C]0.650808[/C][/ROW]
[ROW][C]14[/C][C]0.253094[/C][C]0.506188[/C][C]0.746906[/C][/ROW]
[ROW][C]15[/C][C]0.190168[/C][C]0.380335[/C][C]0.809832[/C][/ROW]
[ROW][C]16[/C][C]0.130424[/C][C]0.260849[/C][C]0.869576[/C][/ROW]
[ROW][C]17[/C][C]0.14201[/C][C]0.284019[/C][C]0.85799[/C][/ROW]
[ROW][C]18[/C][C]0.107362[/C][C]0.214724[/C][C]0.892638[/C][/ROW]
[ROW][C]19[/C][C]0.0758619[/C][C]0.151724[/C][C]0.924138[/C][/ROW]
[ROW][C]20[/C][C]0.0513217[/C][C]0.102643[/C][C]0.948678[/C][/ROW]
[ROW][C]21[/C][C]0.043295[/C][C]0.08659[/C][C]0.956705[/C][/ROW]
[ROW][C]22[/C][C]0.0517813[/C][C]0.103563[/C][C]0.948219[/C][/ROW]
[ROW][C]23[/C][C]0.0337644[/C][C]0.0675289[/C][C]0.966236[/C][/ROW]
[ROW][C]24[/C][C]0.0234205[/C][C]0.0468409[/C][C]0.97658[/C][/ROW]
[ROW][C]25[/C][C]0.0222777[/C][C]0.0445553[/C][C]0.977722[/C][/ROW]
[ROW][C]26[/C][C]0.0176387[/C][C]0.0352774[/C][C]0.982361[/C][/ROW]
[ROW][C]27[/C][C]0.0122431[/C][C]0.0244861[/C][C]0.987757[/C][/ROW]
[ROW][C]28[/C][C]0.00806087[/C][C]0.0161217[/C][C]0.991939[/C][/ROW]
[ROW][C]29[/C][C]0.0134037[/C][C]0.0268074[/C][C]0.986596[/C][/ROW]
[ROW][C]30[/C][C]0.0103753[/C][C]0.0207506[/C][C]0.989625[/C][/ROW]
[ROW][C]31[/C][C]0.00703174[/C][C]0.0140635[/C][C]0.992968[/C][/ROW]
[ROW][C]32[/C][C]0.0135013[/C][C]0.0270027[/C][C]0.986499[/C][/ROW]
[ROW][C]33[/C][C]0.0106541[/C][C]0.0213083[/C][C]0.989346[/C][/ROW]
[ROW][C]34[/C][C]0.0176712[/C][C]0.0353423[/C][C]0.982329[/C][/ROW]
[ROW][C]35[/C][C]0.0134807[/C][C]0.0269613[/C][C]0.986519[/C][/ROW]
[ROW][C]36[/C][C]0.0313073[/C][C]0.0626146[/C][C]0.968693[/C][/ROW]
[ROW][C]37[/C][C]0.0225008[/C][C]0.0450017[/C][C]0.977499[/C][/ROW]
[ROW][C]38[/C][C]0.0165409[/C][C]0.0330819[/C][C]0.983459[/C][/ROW]
[ROW][C]39[/C][C]0.0132449[/C][C]0.0264899[/C][C]0.986755[/C][/ROW]
[ROW][C]40[/C][C]0.011297[/C][C]0.0225939[/C][C]0.988703[/C][/ROW]
[ROW][C]41[/C][C]0.0126254[/C][C]0.0252509[/C][C]0.987375[/C][/ROW]
[ROW][C]42[/C][C]0.00904069[/C][C]0.0180814[/C][C]0.990959[/C][/ROW]
[ROW][C]43[/C][C]0.0211324[/C][C]0.0422648[/C][C]0.978868[/C][/ROW]
[ROW][C]44[/C][C]0.0160044[/C][C]0.0320088[/C][C]0.983996[/C][/ROW]
[ROW][C]45[/C][C]0.0133833[/C][C]0.0267665[/C][C]0.986617[/C][/ROW]
[ROW][C]46[/C][C]0.0100951[/C][C]0.0201902[/C][C]0.989905[/C][/ROW]
[ROW][C]47[/C][C]0.00835456[/C][C]0.0167091[/C][C]0.991645[/C][/ROW]
[ROW][C]48[/C][C]0.00682836[/C][C]0.0136567[/C][C]0.993172[/C][/ROW]
[ROW][C]49[/C][C]0.00569104[/C][C]0.0113821[/C][C]0.994309[/C][/ROW]
[ROW][C]50[/C][C]0.0066942[/C][C]0.0133884[/C][C]0.993306[/C][/ROW]
[ROW][C]51[/C][C]0.0115357[/C][C]0.0230714[/C][C]0.988464[/C][/ROW]
[ROW][C]52[/C][C]0.00964197[/C][C]0.0192839[/C][C]0.990358[/C][/ROW]
[ROW][C]53[/C][C]0.00751067[/C][C]0.0150213[/C][C]0.992489[/C][/ROW]
[ROW][C]54[/C][C]0.00753181[/C][C]0.0150636[/C][C]0.992468[/C][/ROW]
[ROW][C]55[/C][C]0.00593143[/C][C]0.0118629[/C][C]0.994069[/C][/ROW]
[ROW][C]56[/C][C]0.00597302[/C][C]0.011946[/C][C]0.994027[/C][/ROW]
[ROW][C]57[/C][C]0.00643994[/C][C]0.0128799[/C][C]0.99356[/C][/ROW]
[ROW][C]58[/C][C]0.00499566[/C][C]0.00999131[/C][C]0.995004[/C][/ROW]
[ROW][C]59[/C][C]0.0147704[/C][C]0.0295408[/C][C]0.98523[/C][/ROW]
[ROW][C]60[/C][C]0.0189501[/C][C]0.0379003[/C][C]0.98105[/C][/ROW]
[ROW][C]61[/C][C]0.0154297[/C][C]0.0308595[/C][C]0.98457[/C][/ROW]
[ROW][C]62[/C][C]0.017034[/C][C]0.034068[/C][C]0.982966[/C][/ROW]
[ROW][C]63[/C][C]0.0178363[/C][C]0.0356727[/C][C]0.982164[/C][/ROW]
[ROW][C]64[/C][C]0.0151796[/C][C]0.0303593[/C][C]0.98482[/C][/ROW]
[ROW][C]65[/C][C]0.016357[/C][C]0.0327139[/C][C]0.983643[/C][/ROW]
[ROW][C]66[/C][C]0.021554[/C][C]0.043108[/C][C]0.978446[/C][/ROW]
[ROW][C]67[/C][C]0.0259525[/C][C]0.051905[/C][C]0.974048[/C][/ROW]
[ROW][C]68[/C][C]0.0213058[/C][C]0.0426116[/C][C]0.978694[/C][/ROW]
[ROW][C]69[/C][C]0.0203929[/C][C]0.0407858[/C][C]0.979607[/C][/ROW]
[ROW][C]70[/C][C]0.0220574[/C][C]0.0441148[/C][C]0.977943[/C][/ROW]
[ROW][C]71[/C][C]0.0196756[/C][C]0.0393512[/C][C]0.980324[/C][/ROW]
[ROW][C]72[/C][C]0.0162017[/C][C]0.0324034[/C][C]0.983798[/C][/ROW]
[ROW][C]73[/C][C]0.0152309[/C][C]0.0304618[/C][C]0.984769[/C][/ROW]
[ROW][C]74[/C][C]0.0129297[/C][C]0.0258595[/C][C]0.98707[/C][/ROW]
[ROW][C]75[/C][C]0.0108683[/C][C]0.0217367[/C][C]0.989132[/C][/ROW]
[ROW][C]76[/C][C]0.0139535[/C][C]0.0279071[/C][C]0.986046[/C][/ROW]
[ROW][C]77[/C][C]0.0370522[/C][C]0.0741044[/C][C]0.962948[/C][/ROW]
[ROW][C]78[/C][C]0.0321764[/C][C]0.0643528[/C][C]0.967824[/C][/ROW]
[ROW][C]79[/C][C]0.0285782[/C][C]0.0571563[/C][C]0.971422[/C][/ROW]
[ROW][C]80[/C][C]0.0247391[/C][C]0.0494782[/C][C]0.975261[/C][/ROW]
[ROW][C]81[/C][C]0.0270078[/C][C]0.0540157[/C][C]0.972992[/C][/ROW]
[ROW][C]82[/C][C]0.0221352[/C][C]0.0442705[/C][C]0.977865[/C][/ROW]
[ROW][C]83[/C][C]0.0276629[/C][C]0.0553259[/C][C]0.972337[/C][/ROW]
[ROW][C]84[/C][C]0.0233657[/C][C]0.0467314[/C][C]0.976634[/C][/ROW]
[ROW][C]85[/C][C]0.0255374[/C][C]0.0510748[/C][C]0.974463[/C][/ROW]
[ROW][C]86[/C][C]0.0212701[/C][C]0.0425402[/C][C]0.97873[/C][/ROW]
[ROW][C]87[/C][C]0.0542415[/C][C]0.108483[/C][C]0.945759[/C][/ROW]
[ROW][C]88[/C][C]0.0513056[/C][C]0.102611[/C][C]0.948694[/C][/ROW]
[ROW][C]89[/C][C]0.0466132[/C][C]0.0932263[/C][C]0.953387[/C][/ROW]
[ROW][C]90[/C][C]0.0391647[/C][C]0.0783294[/C][C]0.960835[/C][/ROW]
[ROW][C]91[/C][C]0.033189[/C][C]0.066378[/C][C]0.966811[/C][/ROW]
[ROW][C]92[/C][C]0.0333821[/C][C]0.0667642[/C][C]0.966618[/C][/ROW]
[ROW][C]93[/C][C]0.0351514[/C][C]0.0703029[/C][C]0.964849[/C][/ROW]
[ROW][C]94[/C][C]0.0374076[/C][C]0.0748152[/C][C]0.962592[/C][/ROW]
[ROW][C]95[/C][C]0.0834875[/C][C]0.166975[/C][C]0.916513[/C][/ROW]
[ROW][C]96[/C][C]0.0890714[/C][C]0.178143[/C][C]0.910929[/C][/ROW]
[ROW][C]97[/C][C]0.0905907[/C][C]0.181181[/C][C]0.909409[/C][/ROW]
[ROW][C]98[/C][C]0.109733[/C][C]0.219465[/C][C]0.890267[/C][/ROW]
[ROW][C]99[/C][C]0.117776[/C][C]0.235552[/C][C]0.882224[/C][/ROW]
[ROW][C]100[/C][C]0.181909[/C][C]0.363817[/C][C]0.818091[/C][/ROW]
[ROW][C]101[/C][C]0.174131[/C][C]0.348262[/C][C]0.825869[/C][/ROW]
[ROW][C]102[/C][C]0.195285[/C][C]0.39057[/C][C]0.804715[/C][/ROW]
[ROW][C]103[/C][C]0.249302[/C][C]0.498603[/C][C]0.750698[/C][/ROW]
[ROW][C]104[/C][C]0.232892[/C][C]0.465784[/C][C]0.767108[/C][/ROW]
[ROW][C]105[/C][C]0.224659[/C][C]0.449318[/C][C]0.775341[/C][/ROW]
[ROW][C]106[/C][C]0.229702[/C][C]0.459404[/C][C]0.770298[/C][/ROW]
[ROW][C]107[/C][C]0.252139[/C][C]0.504278[/C][C]0.747861[/C][/ROW]
[ROW][C]108[/C][C]0.283856[/C][C]0.567711[/C][C]0.716144[/C][/ROW]
[ROW][C]109[/C][C]0.312131[/C][C]0.624263[/C][C]0.687869[/C][/ROW]
[ROW][C]110[/C][C]0.31463[/C][C]0.629259[/C][C]0.68537[/C][/ROW]
[ROW][C]111[/C][C]0.505221[/C][C]0.989558[/C][C]0.494779[/C][/ROW]
[ROW][C]112[/C][C]0.549792[/C][C]0.900416[/C][C]0.450208[/C][/ROW]
[ROW][C]113[/C][C]0.55774[/C][C]0.88452[/C][C]0.44226[/C][/ROW]
[ROW][C]114[/C][C]0.560557[/C][C]0.878886[/C][C]0.439443[/C][/ROW]
[ROW][C]115[/C][C]0.554882[/C][C]0.890237[/C][C]0.445118[/C][/ROW]
[ROW][C]116[/C][C]0.743295[/C][C]0.51341[/C][C]0.256705[/C][/ROW]
[ROW][C]117[/C][C]0.744012[/C][C]0.511975[/C][C]0.255988[/C][/ROW]
[ROW][C]118[/C][C]0.847171[/C][C]0.305659[/C][C]0.152829[/C][/ROW]
[ROW][C]119[/C][C]0.909813[/C][C]0.180373[/C][C]0.0901867[/C][/ROW]
[ROW][C]120[/C][C]0.935866[/C][C]0.128268[/C][C]0.0641342[/C][/ROW]
[ROW][C]121[/C][C]0.935121[/C][C]0.129759[/C][C]0.0648795[/C][/ROW]
[ROW][C]122[/C][C]0.943665[/C][C]0.11267[/C][C]0.0563349[/C][/ROW]
[ROW][C]123[/C][C]0.965268[/C][C]0.0694635[/C][C]0.0347317[/C][/ROW]
[ROW][C]124[/C][C]0.965026[/C][C]0.0699481[/C][C]0.034974[/C][/ROW]
[ROW][C]125[/C][C]0.967489[/C][C]0.0650224[/C][C]0.0325112[/C][/ROW]
[ROW][C]126[/C][C]0.980069[/C][C]0.0398625[/C][C]0.0199312[/C][/ROW]
[ROW][C]127[/C][C]0.989255[/C][C]0.0214897[/C][C]0.0107448[/C][/ROW]
[ROW][C]128[/C][C]0.989066[/C][C]0.0218678[/C][C]0.0109339[/C][/ROW]
[ROW][C]129[/C][C]0.988382[/C][C]0.0232365[/C][C]0.0116183[/C][/ROW]
[ROW][C]130[/C][C]0.990231[/C][C]0.0195381[/C][C]0.00976903[/C][/ROW]
[ROW][C]131[/C][C]0.987755[/C][C]0.0244908[/C][C]0.0122454[/C][/ROW]
[ROW][C]132[/C][C]0.992903[/C][C]0.0141942[/C][C]0.00709711[/C][/ROW]
[ROW][C]133[/C][C]0.992046[/C][C]0.0159072[/C][C]0.00795358[/C][/ROW]
[ROW][C]134[/C][C]0.991562[/C][C]0.0168762[/C][C]0.00843811[/C][/ROW]
[ROW][C]135[/C][C]0.990577[/C][C]0.0188463[/C][C]0.00942315[/C][/ROW]
[ROW][C]136[/C][C]0.990338[/C][C]0.0193238[/C][C]0.00966191[/C][/ROW]
[ROW][C]137[/C][C]0.990181[/C][C]0.0196374[/C][C]0.00981872[/C][/ROW]
[ROW][C]138[/C][C]0.988374[/C][C]0.0232522[/C][C]0.0116261[/C][/ROW]
[ROW][C]139[/C][C]0.986253[/C][C]0.0274931[/C][C]0.0137466[/C][/ROW]
[ROW][C]140[/C][C]0.991015[/C][C]0.0179691[/C][C]0.00898455[/C][/ROW]
[ROW][C]141[/C][C]0.989733[/C][C]0.0205335[/C][C]0.0102667[/C][/ROW]
[ROW][C]142[/C][C]0.994152[/C][C]0.0116962[/C][C]0.00584809[/C][/ROW]
[ROW][C]143[/C][C]0.994068[/C][C]0.011864[/C][C]0.00593198[/C][/ROW]
[ROW][C]144[/C][C]0.992755[/C][C]0.0144894[/C][C]0.00724472[/C][/ROW]
[ROW][C]145[/C][C]0.994295[/C][C]0.0114103[/C][C]0.00570517[/C][/ROW]
[ROW][C]146[/C][C]0.994049[/C][C]0.0119022[/C][C]0.00595111[/C][/ROW]
[ROW][C]147[/C][C]0.996439[/C][C]0.00712117[/C][C]0.00356059[/C][/ROW]
[ROW][C]148[/C][C]0.996353[/C][C]0.00729465[/C][C]0.00364733[/C][/ROW]
[ROW][C]149[/C][C]0.996333[/C][C]0.0073335[/C][C]0.00366675[/C][/ROW]
[ROW][C]150[/C][C]0.996756[/C][C]0.00648859[/C][C]0.0032443[/C][/ROW]
[ROW][C]151[/C][C]0.996154[/C][C]0.00769295[/C][C]0.00384647[/C][/ROW]
[ROW][C]152[/C][C]0.996571[/C][C]0.00685878[/C][C]0.00342939[/C][/ROW]
[ROW][C]153[/C][C]0.995985[/C][C]0.00803015[/C][C]0.00401508[/C][/ROW]
[ROW][C]154[/C][C]0.995642[/C][C]0.00871692[/C][C]0.00435846[/C][/ROW]
[ROW][C]155[/C][C]0.995862[/C][C]0.00827693[/C][C]0.00413847[/C][/ROW]
[ROW][C]156[/C][C]0.998532[/C][C]0.00293593[/C][C]0.00146797[/C][/ROW]
[ROW][C]157[/C][C]0.998436[/C][C]0.00312717[/C][C]0.00156358[/C][/ROW]
[ROW][C]158[/C][C]0.998608[/C][C]0.00278338[/C][C]0.00139169[/C][/ROW]
[ROW][C]159[/C][C]0.998501[/C][C]0.00299795[/C][C]0.00149897[/C][/ROW]
[ROW][C]160[/C][C]0.998459[/C][C]0.003082[/C][C]0.001541[/C][/ROW]
[ROW][C]161[/C][C]0.998171[/C][C]0.00365804[/C][C]0.00182902[/C][/ROW]
[ROW][C]162[/C][C]0.9983[/C][C]0.00339959[/C][C]0.0016998[/C][/ROW]
[ROW][C]163[/C][C]0.998229[/C][C]0.00354193[/C][C]0.00177096[/C][/ROW]
[ROW][C]164[/C][C]0.997766[/C][C]0.00446784[/C][C]0.00223392[/C][/ROW]
[ROW][C]165[/C][C]0.997109[/C][C]0.00578241[/C][C]0.00289121[/C][/ROW]
[ROW][C]166[/C][C]0.998112[/C][C]0.00377562[/C][C]0.00188781[/C][/ROW]
[ROW][C]167[/C][C]0.998437[/C][C]0.00312517[/C][C]0.00156258[/C][/ROW]
[ROW][C]168[/C][C]0.998233[/C][C]0.00353396[/C][C]0.00176698[/C][/ROW]
[ROW][C]169[/C][C]0.999597[/C][C]0.000806777[/C][C]0.000403388[/C][/ROW]
[ROW][C]170[/C][C]0.999632[/C][C]0.000736121[/C][C]0.000368061[/C][/ROW]
[ROW][C]171[/C][C]0.999494[/C][C]0.00101186[/C][C]0.000505929[/C][/ROW]
[ROW][C]172[/C][C]0.999701[/C][C]0.000598093[/C][C]0.000299047[/C][/ROW]
[ROW][C]173[/C][C]0.999653[/C][C]0.000694815[/C][C]0.000347407[/C][/ROW]
[ROW][C]174[/C][C]0.999566[/C][C]0.000868045[/C][C]0.000434023[/C][/ROW]
[ROW][C]175[/C][C]0.999447[/C][C]0.0011054[/C][C]0.000552701[/C][/ROW]
[ROW][C]176[/C][C]0.999436[/C][C]0.00112851[/C][C]0.000564253[/C][/ROW]
[ROW][C]177[/C][C]0.99963[/C][C]0.000739345[/C][C]0.000369672[/C][/ROW]
[ROW][C]178[/C][C]0.99952[/C][C]0.00095908[/C][C]0.00047954[/C][/ROW]
[ROW][C]179[/C][C]0.999432[/C][C]0.00113663[/C][C]0.000568317[/C][/ROW]
[ROW][C]180[/C][C]0.999342[/C][C]0.00131659[/C][C]0.000658293[/C][/ROW]
[ROW][C]181[/C][C]0.99959[/C][C]0.000819151[/C][C]0.000409576[/C][/ROW]
[ROW][C]182[/C][C]0.999473[/C][C]0.0010548[/C][C]0.000527398[/C][/ROW]
[ROW][C]183[/C][C]0.999621[/C][C]0.000758884[/C][C]0.000379442[/C][/ROW]
[ROW][C]184[/C][C]0.999518[/C][C]0.000963061[/C][C]0.00048153[/C][/ROW]
[ROW][C]185[/C][C]0.99957[/C][C]0.00085979[/C][C]0.000429895[/C][/ROW]
[ROW][C]186[/C][C]0.999402[/C][C]0.00119581[/C][C]0.000597903[/C][/ROW]
[ROW][C]187[/C][C]0.999214[/C][C]0.00157295[/C][C]0.000786475[/C][/ROW]
[ROW][C]188[/C][C]0.999343[/C][C]0.00131324[/C][C]0.000656619[/C][/ROW]
[ROW][C]189[/C][C]0.999271[/C][C]0.00145886[/C][C]0.000729428[/C][/ROW]
[ROW][C]190[/C][C]0.999333[/C][C]0.00133471[/C][C]0.000667356[/C][/ROW]
[ROW][C]191[/C][C]0.999223[/C][C]0.00155442[/C][C]0.000777211[/C][/ROW]
[ROW][C]192[/C][C]0.999353[/C][C]0.00129445[/C][C]0.000647226[/C][/ROW]
[ROW][C]193[/C][C]0.999146[/C][C]0.00170747[/C][C]0.000853734[/C][/ROW]
[ROW][C]194[/C][C]0.999007[/C][C]0.0019856[/C][C]0.0009928[/C][/ROW]
[ROW][C]195[/C][C]0.998726[/C][C]0.00254787[/C][C]0.00127394[/C][/ROW]
[ROW][C]196[/C][C]0.998403[/C][C]0.00319376[/C][C]0.00159688[/C][/ROW]
[ROW][C]197[/C][C]0.998366[/C][C]0.00326856[/C][C]0.00163428[/C][/ROW]
[ROW][C]198[/C][C]0.998294[/C][C]0.00341102[/C][C]0.00170551[/C][/ROW]
[ROW][C]199[/C][C]0.998995[/C][C]0.00200941[/C][C]0.00100471[/C][/ROW]
[ROW][C]200[/C][C]0.998664[/C][C]0.00267234[/C][C]0.00133617[/C][/ROW]
[ROW][C]201[/C][C]0.998442[/C][C]0.00311537[/C][C]0.00155768[/C][/ROW]
[ROW][C]202[/C][C]0.998147[/C][C]0.00370535[/C][C]0.00185268[/C][/ROW]
[ROW][C]203[/C][C]0.997782[/C][C]0.00443651[/C][C]0.00221825[/C][/ROW]
[ROW][C]204[/C][C]0.997718[/C][C]0.00456426[/C][C]0.00228213[/C][/ROW]
[ROW][C]205[/C][C]0.997527[/C][C]0.00494506[/C][C]0.00247253[/C][/ROW]
[ROW][C]206[/C][C]0.996806[/C][C]0.00638717[/C][C]0.00319359[/C][/ROW]
[ROW][C]207[/C][C]0.99607[/C][C]0.00785918[/C][C]0.00392959[/C][/ROW]
[ROW][C]208[/C][C]0.995657[/C][C]0.00868606[/C][C]0.00434303[/C][/ROW]
[ROW][C]209[/C][C]0.994801[/C][C]0.0103982[/C][C]0.00519909[/C][/ROW]
[ROW][C]210[/C][C]0.994128[/C][C]0.011744[/C][C]0.00587202[/C][/ROW]
[ROW][C]211[/C][C]0.994459[/C][C]0.0110812[/C][C]0.0055406[/C][/ROW]
[ROW][C]212[/C][C]0.992633[/C][C]0.0147342[/C][C]0.00736708[/C][/ROW]
[ROW][C]213[/C][C]0.990799[/C][C]0.0184025[/C][C]0.00920123[/C][/ROW]
[ROW][C]214[/C][C]0.98801[/C][C]0.02398[/C][C]0.01199[/C][/ROW]
[ROW][C]215[/C][C]0.993732[/C][C]0.0125363[/C][C]0.00626817[/C][/ROW]
[ROW][C]216[/C][C]0.994774[/C][C]0.0104519[/C][C]0.00522597[/C][/ROW]
[ROW][C]217[/C][C]0.99303[/C][C]0.0139407[/C][C]0.00697035[/C][/ROW]
[ROW][C]218[/C][C]0.991628[/C][C]0.0167443[/C][C]0.00837216[/C][/ROW]
[ROW][C]219[/C][C]0.989632[/C][C]0.0207363[/C][C]0.0103682[/C][/ROW]
[ROW][C]220[/C][C]0.987234[/C][C]0.0255312[/C][C]0.0127656[/C][/ROW]
[ROW][C]221[/C][C]0.984388[/C][C]0.0312244[/C][C]0.0156122[/C][/ROW]
[ROW][C]222[/C][C]0.980449[/C][C]0.0391019[/C][C]0.019551[/C][/ROW]
[ROW][C]223[/C][C]0.980206[/C][C]0.0395887[/C][C]0.0197944[/C][/ROW]
[ROW][C]224[/C][C]0.978701[/C][C]0.0425988[/C][C]0.0212994[/C][/ROW]
[ROW][C]225[/C][C]0.975108[/C][C]0.0497844[/C][C]0.0248922[/C][/ROW]
[ROW][C]226[/C][C]0.96789[/C][C]0.0642207[/C][C]0.0321103[/C][/ROW]
[ROW][C]227[/C][C]0.960959[/C][C]0.0780815[/C][C]0.0390407[/C][/ROW]
[ROW][C]228[/C][C]0.960137[/C][C]0.0797257[/C][C]0.0398629[/C][/ROW]
[ROW][C]229[/C][C]0.958407[/C][C]0.0831865[/C][C]0.0415932[/C][/ROW]
[ROW][C]230[/C][C]0.95476[/C][C]0.0904791[/C][C]0.0452396[/C][/ROW]
[ROW][C]231[/C][C]0.94541[/C][C]0.10918[/C][C]0.0545901[/C][/ROW]
[ROW][C]232[/C][C]0.943834[/C][C]0.112331[/C][C]0.0561657[/C][/ROW]
[ROW][C]233[/C][C]0.955706[/C][C]0.0885876[/C][C]0.0442938[/C][/ROW]
[ROW][C]234[/C][C]0.947237[/C][C]0.105526[/C][C]0.0527631[/C][/ROW]
[ROW][C]235[/C][C]0.951117[/C][C]0.0977658[/C][C]0.0488829[/C][/ROW]
[ROW][C]236[/C][C]0.957897[/C][C]0.0842068[/C][C]0.0421034[/C][/ROW]
[ROW][C]237[/C][C]0.95934[/C][C]0.0813196[/C][C]0.0406598[/C][/ROW]
[ROW][C]238[/C][C]0.955225[/C][C]0.0895503[/C][C]0.0447751[/C][/ROW]
[ROW][C]239[/C][C]0.960494[/C][C]0.0790117[/C][C]0.0395058[/C][/ROW]
[ROW][C]240[/C][C]0.949136[/C][C]0.101729[/C][C]0.0508644[/C][/ROW]
[ROW][C]241[/C][C]0.956476[/C][C]0.0870477[/C][C]0.0435238[/C][/ROW]
[ROW][C]242[/C][C]0.960283[/C][C]0.0794331[/C][C]0.0397165[/C][/ROW]
[ROW][C]243[/C][C]0.990983[/C][C]0.018033[/C][C]0.00901652[/C][/ROW]
[ROW][C]244[/C][C]0.987634[/C][C]0.0247313[/C][C]0.0123656[/C][/ROW]
[ROW][C]245[/C][C]0.984415[/C][C]0.0311692[/C][C]0.0155846[/C][/ROW]
[ROW][C]246[/C][C]0.979329[/C][C]0.0413419[/C][C]0.020671[/C][/ROW]
[ROW][C]247[/C][C]0.971678[/C][C]0.0566448[/C][C]0.0283224[/C][/ROW]
[ROW][C]248[/C][C]0.965973[/C][C]0.0680545[/C][C]0.0340272[/C][/ROW]
[ROW][C]249[/C][C]0.95629[/C][C]0.0874209[/C][C]0.0437105[/C][/ROW]
[ROW][C]250[/C][C]0.943868[/C][C]0.112264[/C][C]0.056132[/C][/ROW]
[ROW][C]251[/C][C]0.958682[/C][C]0.0826369[/C][C]0.0413184[/C][/ROW]
[ROW][C]252[/C][C]0.953544[/C][C]0.0929123[/C][C]0.0464562[/C][/ROW]
[ROW][C]253[/C][C]0.93818[/C][C]0.12364[/C][C]0.0618201[/C][/ROW]
[ROW][C]254[/C][C]0.921626[/C][C]0.156749[/C][C]0.0783744[/C][/ROW]
[ROW][C]255[/C][C]0.899627[/C][C]0.200746[/C][C]0.100373[/C][/ROW]
[ROW][C]256[/C][C]0.872426[/C][C]0.255147[/C][C]0.127574[/C][/ROW]
[ROW][C]257[/C][C]0.839719[/C][C]0.320562[/C][C]0.160281[/C][/ROW]
[ROW][C]258[/C][C]0.836227[/C][C]0.327545[/C][C]0.163773[/C][/ROW]
[ROW][C]259[/C][C]0.832197[/C][C]0.335606[/C][C]0.167803[/C][/ROW]
[ROW][C]260[/C][C]0.789667[/C][C]0.420666[/C][C]0.210333[/C][/ROW]
[ROW][C]261[/C][C]0.746085[/C][C]0.507829[/C][C]0.253915[/C][/ROW]
[ROW][C]262[/C][C]0.84147[/C][C]0.317059[/C][C]0.15853[/C][/ROW]
[ROW][C]263[/C][C]0.868872[/C][C]0.262256[/C][C]0.131128[/C][/ROW]
[ROW][C]264[/C][C]0.845103[/C][C]0.309795[/C][C]0.154897[/C][/ROW]
[ROW][C]265[/C][C]0.838909[/C][C]0.322183[/C][C]0.161091[/C][/ROW]
[ROW][C]266[/C][C]0.974207[/C][C]0.0515859[/C][C]0.025793[/C][/ROW]
[ROW][C]267[/C][C]0.95752[/C][C]0.0849599[/C][C]0.04248[/C][/ROW]
[ROW][C]268[/C][C]0.997904[/C][C]0.0041914[/C][C]0.0020957[/C][/ROW]
[ROW][C]269[/C][C]0.997968[/C][C]0.00406336[/C][C]0.00203168[/C][/ROW]
[ROW][C]270[/C][C]0.9979[/C][C]0.00419942[/C][C]0.00209971[/C][/ROW]
[ROW][C]271[/C][C]0.997656[/C][C]0.00468763[/C][C]0.00234382[/C][/ROW]
[ROW][C]272[/C][C]0.99386[/C][C]0.0122806[/C][C]0.00614028[/C][/ROW]
[ROW][C]273[/C][C]0.992048[/C][C]0.0159049[/C][C]0.00795243[/C][/ROW]
[ROW][C]274[/C][C]0.983303[/C][C]0.033394[/C][C]0.016697[/C][/ROW]
[ROW][C]275[/C][C]0.978253[/C][C]0.043494[/C][C]0.021747[/C][/ROW]
[ROW][C]276[/C][C]0.941435[/C][C]0.11713[/C][C]0.0585652[/C][/ROW]
[ROW][C]277[/C][C]0.855725[/C][C]0.28855[/C][C]0.144275[/C][/ROW]
[ROW][C]278[/C][C]0.707154[/C][C]0.585692[/C][C]0.292846[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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
90.6705830.6588340.329417
100.5123810.9752390.487619
110.5484340.9031320.451566
120.4232870.8465740.576713
130.3491920.6983840.650808
140.2530940.5061880.746906
150.1901680.3803350.809832
160.1304240.2608490.869576
170.142010.2840190.85799
180.1073620.2147240.892638
190.07586190.1517240.924138
200.05132170.1026430.948678
210.0432950.086590.956705
220.05178130.1035630.948219
230.03376440.06752890.966236
240.02342050.04684090.97658
250.02227770.04455530.977722
260.01763870.03527740.982361
270.01224310.02448610.987757
280.008060870.01612170.991939
290.01340370.02680740.986596
300.01037530.02075060.989625
310.007031740.01406350.992968
320.01350130.02700270.986499
330.01065410.02130830.989346
340.01767120.03534230.982329
350.01348070.02696130.986519
360.03130730.06261460.968693
370.02250080.04500170.977499
380.01654090.03308190.983459
390.01324490.02648990.986755
400.0112970.02259390.988703
410.01262540.02525090.987375
420.009040690.01808140.990959
430.02113240.04226480.978868
440.01600440.03200880.983996
450.01338330.02676650.986617
460.01009510.02019020.989905
470.008354560.01670910.991645
480.006828360.01365670.993172
490.005691040.01138210.994309
500.00669420.01338840.993306
510.01153570.02307140.988464
520.009641970.01928390.990358
530.007510670.01502130.992489
540.007531810.01506360.992468
550.005931430.01186290.994069
560.005973020.0119460.994027
570.006439940.01287990.99356
580.004995660.009991310.995004
590.01477040.02954080.98523
600.01895010.03790030.98105
610.01542970.03085950.98457
620.0170340.0340680.982966
630.01783630.03567270.982164
640.01517960.03035930.98482
650.0163570.03271390.983643
660.0215540.0431080.978446
670.02595250.0519050.974048
680.02130580.04261160.978694
690.02039290.04078580.979607
700.02205740.04411480.977943
710.01967560.03935120.980324
720.01620170.03240340.983798
730.01523090.03046180.984769
740.01292970.02585950.98707
750.01086830.02173670.989132
760.01395350.02790710.986046
770.03705220.07410440.962948
780.03217640.06435280.967824
790.02857820.05715630.971422
800.02473910.04947820.975261
810.02700780.05401570.972992
820.02213520.04427050.977865
830.02766290.05532590.972337
840.02336570.04673140.976634
850.02553740.05107480.974463
860.02127010.04254020.97873
870.05424150.1084830.945759
880.05130560.1026110.948694
890.04661320.09322630.953387
900.03916470.07832940.960835
910.0331890.0663780.966811
920.03338210.06676420.966618
930.03515140.07030290.964849
940.03740760.07481520.962592
950.08348750.1669750.916513
960.08907140.1781430.910929
970.09059070.1811810.909409
980.1097330.2194650.890267
990.1177760.2355520.882224
1000.1819090.3638170.818091
1010.1741310.3482620.825869
1020.1952850.390570.804715
1030.2493020.4986030.750698
1040.2328920.4657840.767108
1050.2246590.4493180.775341
1060.2297020.4594040.770298
1070.2521390.5042780.747861
1080.2838560.5677110.716144
1090.3121310.6242630.687869
1100.314630.6292590.68537
1110.5052210.9895580.494779
1120.5497920.9004160.450208
1130.557740.884520.44226
1140.5605570.8788860.439443
1150.5548820.8902370.445118
1160.7432950.513410.256705
1170.7440120.5119750.255988
1180.8471710.3056590.152829
1190.9098130.1803730.0901867
1200.9358660.1282680.0641342
1210.9351210.1297590.0648795
1220.9436650.112670.0563349
1230.9652680.06946350.0347317
1240.9650260.06994810.034974
1250.9674890.06502240.0325112
1260.9800690.03986250.0199312
1270.9892550.02148970.0107448
1280.9890660.02186780.0109339
1290.9883820.02323650.0116183
1300.9902310.01953810.00976903
1310.9877550.02449080.0122454
1320.9929030.01419420.00709711
1330.9920460.01590720.00795358
1340.9915620.01687620.00843811
1350.9905770.01884630.00942315
1360.9903380.01932380.00966191
1370.9901810.01963740.00981872
1380.9883740.02325220.0116261
1390.9862530.02749310.0137466
1400.9910150.01796910.00898455
1410.9897330.02053350.0102667
1420.9941520.01169620.00584809
1430.9940680.0118640.00593198
1440.9927550.01448940.00724472
1450.9942950.01141030.00570517
1460.9940490.01190220.00595111
1470.9964390.007121170.00356059
1480.9963530.007294650.00364733
1490.9963330.00733350.00366675
1500.9967560.006488590.0032443
1510.9961540.007692950.00384647
1520.9965710.006858780.00342939
1530.9959850.008030150.00401508
1540.9956420.008716920.00435846
1550.9958620.008276930.00413847
1560.9985320.002935930.00146797
1570.9984360.003127170.00156358
1580.9986080.002783380.00139169
1590.9985010.002997950.00149897
1600.9984590.0030820.001541
1610.9981710.003658040.00182902
1620.99830.003399590.0016998
1630.9982290.003541930.00177096
1640.9977660.004467840.00223392
1650.9971090.005782410.00289121
1660.9981120.003775620.00188781
1670.9984370.003125170.00156258
1680.9982330.003533960.00176698
1690.9995970.0008067770.000403388
1700.9996320.0007361210.000368061
1710.9994940.001011860.000505929
1720.9997010.0005980930.000299047
1730.9996530.0006948150.000347407
1740.9995660.0008680450.000434023
1750.9994470.00110540.000552701
1760.9994360.001128510.000564253
1770.999630.0007393450.000369672
1780.999520.000959080.00047954
1790.9994320.001136630.000568317
1800.9993420.001316590.000658293
1810.999590.0008191510.000409576
1820.9994730.00105480.000527398
1830.9996210.0007588840.000379442
1840.9995180.0009630610.00048153
1850.999570.000859790.000429895
1860.9994020.001195810.000597903
1870.9992140.001572950.000786475
1880.9993430.001313240.000656619
1890.9992710.001458860.000729428
1900.9993330.001334710.000667356
1910.9992230.001554420.000777211
1920.9993530.001294450.000647226
1930.9991460.001707470.000853734
1940.9990070.00198560.0009928
1950.9987260.002547870.00127394
1960.9984030.003193760.00159688
1970.9983660.003268560.00163428
1980.9982940.003411020.00170551
1990.9989950.002009410.00100471
2000.9986640.002672340.00133617
2010.9984420.003115370.00155768
2020.9981470.003705350.00185268
2030.9977820.004436510.00221825
2040.9977180.004564260.00228213
2050.9975270.004945060.00247253
2060.9968060.006387170.00319359
2070.996070.007859180.00392959
2080.9956570.008686060.00434303
2090.9948010.01039820.00519909
2100.9941280.0117440.00587202
2110.9944590.01108120.0055406
2120.9926330.01473420.00736708
2130.9907990.01840250.00920123
2140.988010.023980.01199
2150.9937320.01253630.00626817
2160.9947740.01045190.00522597
2170.993030.01394070.00697035
2180.9916280.01674430.00837216
2190.9896320.02073630.0103682
2200.9872340.02553120.0127656
2210.9843880.03122440.0156122
2220.9804490.03910190.019551
2230.9802060.03958870.0197944
2240.9787010.04259880.0212994
2250.9751080.04978440.0248922
2260.967890.06422070.0321103
2270.9609590.07808150.0390407
2280.9601370.07972570.0398629
2290.9584070.08318650.0415932
2300.954760.09047910.0452396
2310.945410.109180.0545901
2320.9438340.1123310.0561657
2330.9557060.08858760.0442938
2340.9472370.1055260.0527631
2350.9511170.09776580.0488829
2360.9578970.08420680.0421034
2370.959340.08131960.0406598
2380.9552250.08955030.0447751
2390.9604940.07901170.0395058
2400.9491360.1017290.0508644
2410.9564760.08704770.0435238
2420.9602830.07943310.0397165
2430.9909830.0180330.00901652
2440.9876340.02473130.0123656
2450.9844150.03116920.0155846
2460.9793290.04134190.020671
2470.9716780.05664480.0283224
2480.9659730.06805450.0340272
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2500.9438680.1122640.056132
2510.9586820.08263690.0413184
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2550.8996270.2007460.100373
2560.8724260.2551470.127574
2570.8397190.3205620.160281
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2590.8321970.3356060.167803
2600.7896670.4206660.210333
2610.7460850.5078290.253915
2620.841470.3170590.15853
2630.8688720.2622560.131128
2640.8451030.3097950.154897
2650.8389090.3221830.161091
2660.9742070.05158590.025793
2670.957520.08495990.04248
2680.9979040.00419140.0020957
2690.9979680.004063360.00203168
2700.99790.004199420.00209971
2710.9976560.004687630.00234382
2720.993860.01228060.00614028
2730.9920480.01590490.00795243
2740.9833030.0333940.016697
2750.9782530.0434940.021747
2760.9414350.117130.0585652
2770.8557250.288550.144275
2780.7071540.5856920.292846






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level670.248148NOK
5% type I error level1670.618519NOK
10% type I error level2060.762963NOK

\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 & 67 & 0.248148 & NOK \tabularnewline
5% type I error level & 167 & 0.618519 & NOK \tabularnewline
10% type I error level & 206 & 0.762963 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268054&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]67[/C][C]0.248148[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]167[/C][C]0.618519[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]206[/C][C]0.762963[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268054&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268054&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 level670.248148NOK
5% type I error level1670.618519NOK
10% type I error level2060.762963NOK


Figures (Output of Computation)

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Input Parameters & R Code

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