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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, 08 Dec 2014 15:49:08 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/08/t1418053789i9fjyns26d1672l.htm/, Retrieved Tue, 28 May 2024 04:05:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264060, Retrieved Tue, 28 May 2024 04:05:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact88

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [] [2014-12-08 15:49:08] [6398a3f6f1f2f5e55f0ec79c736f94f8] [Current]
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Dataset

Dataseries X:
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Histogram
Boxplots 
12.9 1 1.00 0.50 0.67 149 68
12.2 1 0.89 0.50 0.83 139 39
12.8 1 0.89 0.40 1.00 148 32
7.4 1 0.89 0.50 0.83 158 62
6.7 1 0.89 0.70 0.67 128 33
12.6 1 0.78 0.30 0.00 224 52
14.8 1 0.89 0.40 0.83 159 62
13.3 1 1.00 0.40 0.50 105 77
11.1 1 0.89 0.70 0.83 159 76
8.2 1 0.78 0.60 0.33 167 41
11.4 1 1.00 0.60 0.50 165 48
6.4 1 0.78 0.20 0.67 159 63
10.6 1 0.89 0.40 1.00 119 30
12.0 1 0.89 0.40 0.50 176 78
6.3 1 0.89 0.50 0.67 54 19
11.3 0 0.89 0.30 0.17 91 31
11.9 1 0.89 0.40 0.83 163 66
9.3 1 0.67 0.70 0.67 124 35
9.6 0 1.00 0.50 0.67 137 42
10.0 1 0.78 0.20 0.67 121 45
6.4 1 0.78 0.30 0.50 153 21
13.8 1 0.89 0.60 1.00 148 25
10.8 1 0.78 0.60 0.83 221 44
13.8 1 0.89 0.20 0.83 188 69
11.7 1 0.89 0.70 1.00 149 54
10.9 1 0.33 0.20 0.67 244 74
16.1 0 1.00 1.00 1.00 148 80
13.4 0 0.89 0.40 0.83 92 42
9.9 1 0.89 0.40 1.00 150 61
11.5 1 0.67 0.20 0.83 153 41
8.3 1 0.56 0.40 0.67 94 46
11.7 1 0.89 0.40 0.67 156 39
9.0 1 0.89 0.70 1.00 132 34
9.7 1 1.00 0.20 0.67 161 51
10.8 1 0.78 0.60 1.00 105 42
10.3 1 0.78 0.30 1.00 97 31
10.4 1 0.33 0.30 0.50 151 39
12.7 0 0.78 0.20 0.67 131 20
9.3 1 0.89 0.50 0.83 166 49
11.8 1 0.89 0.70 1.00 157 53
5.9 1 0.78 0.60 1.00 111 31
11.4 1 0.89 0.40 1.00 145 39
13.0 1 0.89 0.60 1.00 162 54
10.8 1 1.00 0.40 1.00 163 49
12.3 0 0.67 0.30 0.83 59 34
11.3 1 1.00 0.50 0.83 187 46
11.8 1 0.89 0.20 0.50 109 55
7.9 0 0.89 0.30 0.83 90 42
12.7 1 0.89 0.50 0.17 105 50
12.3 0 0.78 0.70 0.83 83 13
11.6 0 0.89 0.40 1.00 116 37
6.7 0 0.78 0.30 1.00 42 25
10.9 1 0.78 0.20 0.67 148 30
12.1 0 1.00 0.50 1.00 155 28
13.3 1 0.78 0.40 1.00 125 45
10.1 1 1.00 0.60 1.00 116 35
5.7 0 0.78 0.40 0.83 128 28
14.3 1 0.67 0.40 0.33 138 41
8.0 0 0.33 0.20 0.33 49 6
13.3 0 1.00 0.90 1.00 96 45
9.3 1 1.00 0.80 1.00 164 73
12.5 1 0.78 0.80 0.83 162 17
7.6 1 0.67 0.30 1.00 99 40
15.9 1 1.00 0.20 0.83 202 64
9.2 1 0.89 0.40 0.67 186 37
9.1 0 0.89 0.20 0.83 66 25
11.1 1 0.78 0.20 0.67 183 65
13.0 1 1.00 0.10 0.83 214 100
14.5 1 0.56 0.40 0.67 188 28
12.2 0 0.67 0.50 1.00 104 35
12.3 1 0.89 0.80 0.83 177 56
11.4 1 0.89 0.40 0.67 126 29
8.8 0 0.89 0.60 0.83 76 43
14.6 0 0.89 0.50 0.83 99 59
12.6 1 0.78 0.30 0.67 139 50
NA 1 0.89 0.80 1.00 78 3
13.0 1 1.00 0.40 0.33 162 59
12.6 0 1.00 0.60 0.83 108 27
13.2 1 0.89 0.40 1.00 159 61
9.9 0 0.44 0.30 0.83 74 28
7.7 1 0.78 0.80 0.83 110 51
10.5 0 0.89 0.60 0.50 96 35
13.4 0 0.67 0.30 0.50 116 29
10.9 0 0.78 0.50 0.83 87 48
4.3 0 0.78 0.40 1.00 97 25
10.3 0 0.33 0.30 0.33 127 44
11.8 0 0.89 0.70 1.00 106 64
11.2 0 0.89 0.20 0.67 80 32
11.4 0 0.89 0.40 0.83 74 20
8.6 0 0.89 0.60 1.00 91 28
13.2 0 0.56 0.60 0.83 133 34
12.6 0 0.67 0.60 0.83 74 31
5.6 0 0.67 0.40 1.00 114 26
9.9 0 0.78 0.60 0.83 140 58
8.8 0 0.78 0.50 1.00 95 23
7.7 0 0.78 0.50 0.83 98 21
9.0 0 0.89 0.60 0.67 121 21
7.3 0 1.00 0.80 0.83 126 33
11.4 0 0.89 0.50 0.83 98 16
13.6 0 0.89 0.60 0.83 95 20
7.9 0 0.78 0.40 0.83 110 37
10.7 0 1.00 0.30 0.67 70 35
10.3 0 0.78 0.30 0.83 102 33
8.3 0 0.67 0.20 0.00 86 27
9.6 0 0.78 0.40 0.83 130 41
14.2 0 0.89 0.50 1.00 96 40
8.5 0 0.67 0.30 0.17 102 35
13.5 0 0.22 0.40 0.17 100 28
4.9 0 0.44 0.50 0.50 94 32
6.4 0 0.89 0.30 0.50 52 22
9.6 0 0.67 0.50 1.00 98 44
11.6 0 0.89 0.40 0.67 118 27
11.1 0 0.67 0.40 0.83 99 17
4.35 1 0.78 0.60 1.00 48 12
12.7 1 0.78 0.30 1.00 50 45
18.1 1 0.78 0.40 1.00 150 37
17.85 1 1.00 0.30 1.00 154 37
16.6 0 0.78 1.00 1.00 109 108
12.6 0 0.67 0.40 1.00 68 10
17.1 1 0.89 0.80 0.83 194 68
19.1 1 0.89 0.30 1.00 158 72
16.1 1 1.00 0.50 0.83 159 143
13.35 1 0.78 0.40 1.00 67 9
18.4 1 0.67 0.30 0.83 147 55
14.7 1 0.89 0.50 0.83 39 17
10.6 1 0.67 0.30 1.00 100 37
12.6 1 0.67 0.30 0.67 111 27
16.2 1 1.00 0.40 0.83 138 37
13.6 1 0.67 0.30 1.00 101 58
18.9 0 1.00 0.60 1.00 131 66
14.1 1 0.89 0.60 0.83 101 21
14.5 1 0.89 0.40 1.00 114 19
16.15 1 1.00 0.40 1.00 165 78
14.75 1 0.67 0.40 1.00 114 35
14.8 1 0.44 0.30 0.67 111 48
12.45 1 0.89 0.20 1.00 75 27
12.65 1 0.56 0.50 0.83 82 43
17.35 1 0.78 0.40 1.00 121 30
8.6 1 1.00 0.40 1.00 32 25
18.4 1 1.00 0.40 0.83 150 69
16.1 1 0.89 0.30 0.67 117 72
11.6 0 0.67 0.40 0.83 71 23
17.75 1 0.89 0.20 1.00 165 13
15.25 1 0.33 0.00 0.00 154 61
17.65 1 0.89 0.40 1.00 126 43
16.35 1 0.78 0.60 1.00 149 51
17.65 1 1.00 0.40 0.67 145 67
13.6 1 0.44 0.40 1.00 120 36
14.35 1 0.67 0.40 0.83 109 44
14.75 1 0.33 0.20 0.17 132 45
18.25 1 0.89 0.40 0.83 172 34
9.9 1 0.89 0.30 0.83 169 36
16 1 1.00 0.60 0.83 114 72
18.25 1 0.89 0.60 0.83 156 39
16.85 1 0.89 0.40 0.83 172 43
14.6 0 1.00 0.50 1.00 68 25
13.85 0 0.89 0.40 0.83 89 56
18.95 1 1.00 0.60 1.00 167 80
15.6 1 0.78 0.60 0.83 113 40
14.85 0 0.78 0.90 1.00 115 73
11.75 0 0.67 0.40 0.83 78 34
18.45 0 0.89 0.80 1.00 118 72
15.9 0 0.67 0.50 0.83 87 42
17.1 1 0.78 0.40 0.83 173 61
16.1 1 0.89 0.40 1.00 2 23
19.9 0 0.89 0.70 1.00 162 74
10.95 0 0.78 0.40 1.00 49 16
18.45 0 1.00 0.80 1.00 122 66
15.1 0 1.00 0.40 1.00 96 9
15 0 1.00 0.30 1.00 100 41
11.35 0 0.67 0.50 1.00 82 57
15.95 0 0.89 0.80 1.00 100 48
18.1 0 1.00 0.40 0.83 115 51
14.6 0 1.00 1.00 1.00 141 53
15.4 1 0.89 0.50 1.00 165 29
15.4 1 0.89 0.50 1.00 165 29
17.6 0 0.89 0.30 1.00 110 55
13.35 1 0.89 0.30 0.83 118 54
19.1 1 0.89 0.30 0.50 158 43
15.35 0 1.00 0.40 0.67 146 51
7.6 1 0.67 0.50 1.00 49 20
13.4 0 1.00 0.50 0.67 90 79
13.9 0 0.89 0.40 1.00 121 39
19.1 1 0.89 0.70 1.00 155 61
15.25 0 0.89 0.50 0.50 104 55
12.9 0 0.89 0.40 0.67 147 30
16.1 0 1.00 0.70 0.67 110 55
17.35 0 1.00 0.70 0.67 108 22
13.15 0 1.00 0.70 0.67 113 37
12.15 0 0.89 0.70 0.67 115 2
12.6 0 0.89 0.70 0.67 61 38
10.35 0 0.89 0.70 1.00 60 27
15.4 0 0.33 0.10 0.67 109 56
9.6 0 0.67 0.20 0.67 68 25
18.2 0 0.56 0.30 0.33 111 39
13.6 0 0.44 0.60 0.83 77 33
14.85 0 1.00 0.80 1.00 73 43
14.75 1 0.89 0.80 1.00 151 57
14.1 0 0.33 0.00 0.17 89 43
14.9 0 0.67 0.30 0.67 78 23
16.25 0 0.67 0.60 0.83 110 44
19.25 1 1.00 0.50 0.83 220 54
13.6 0 0.78 0.70 1.00 65 28
13.6 1 0.67 0.30 0.83 141 36
15.65 0 1.00 0.30 1.00 117 39
12.75 1 0.78 0.40 1.00 122 16
14.6 0 0.89 0.40 0.83 63 23
9.85 1 0.89 0.10 0.83 44 40
12.65 0 0.89 0.50 1.00 52 24
19.2 0 0.00 0.00 0.00 131 78
16.6 0 0.67 0.40 1.00 101 57
11.2 0 1.00 0.60 0.83 42 37
15.25 1 1.00 0.40 1.00 152 27
11.9 1 0.67 0.10 0.33 107 61
13.2 0 0.89 0.30 0.83 77 27
16.35 1 0.89 0.70 0.83 154 69
12.4 1 0.56 0.30 0.17 103 34
15.85 0 0.67 0.50 0.83 96 44
18.15 1 1.00 0.30 0.83 175 34
11.15 0 1.00 0.60 0.67 57 39
15.65 0 1.00 0.90 1.00 112 51
17.75 1 0.67 0.40 0.83 143 34
7.65 0 0.44 0.30 1.00 49 31
12.35 1 0.89 0.90 1.00 110 13
15.6 1 0.44 0.50 1.00 131 12
19.3 1 0.56 0.30 1.00 167 51
15.2 0 0.89 0.60 0.83 56 24
17.1 1 0.67 0.20 1.00 137 19
15.6 0 0.89 0.40 0.83 86 30
18.4 1 1.00 0.50 0.83 121 81
19.05 1 0.78 0.40 0.83 149 42
18.55 1 0.44 0.00 0.00 168 22
19.1 1 0.89 0.20 1.00 140 85
13.1 0 0.89 0.50 1.00 88 27
12.85 1 0.89 0.30 1.00 168 25
9.5 1 0.44 0.00 0.00 94 22
4.5 1 1.00 0.50 0.83 51 19
11.85 0 0.89 0.60 0.83 48 14
13.6 1 0.67 0.30 0.83 145 45
11.7 1 0.33 0.00 0.00 66 45
12.4 0 0.78 0.30 0.67 85 28
13.35 1 0.89 0.50 1.00 109 51
11.4 0 0.78 0.40 0.67 63 41
14.9 0 0.78 0.50 0.83 102 31
19.9 0 0.89 0.70 1.00 162 74
11.2 0 0.78 0.80 1.00 86 19
14.6 0 0.78 0.60 1.00 114 51
17.6 1 0.67 0.40 0.83 164 73
14.05 1 0.89 0.50 0.83 119 24
16.1 1 0.89 0.50 1.00 126 61
13.35 1 0.78 0.30 1.00 132 23
11.85 1 1.00 0.60 1.00 142 14
11.95 1 1.00 0.30 0.67 83 54
14.75 0 0.78 0.60 0.83 94 51
15.15 0 0.78 0.30 0.33 81 62
13.2 1 0.89 0.70 1.00 166 36
16.85 0 0.89 0.70 1.00 110 59
7.85 0 0.67 0.60 0.67 64 24
7.7 1 1.00 0.50 1.00 93 26
12.6 0 0.67 0.50 0.83 104 54
7.85 0 0.56 0.40 0.67 105 39
10.95 0 0.78 0.40 1.00 49 16
12.35 0 1.00 0.70 1.00 88 36
9.95 0 0.67 0.20 0.17 95 31
14.9 0 0.78 0.50 0.83 102 31
16.65 0 0.56 0.40 0.83 99 42
13.4 0 1.00 0.20 1.00 63 39
13.95 0 0.89 0.50 0.67 76 25
15.7 0 0.44 0.40 0.50 109 31
16.85 0 1.00 0.70 0.67 117 38
10.95 0 0.89 0.60 0.83 57 31
15.35 0 0.78 0.40 0.83 120 17
12.2 0 0.89 0.50 1.00 73 22
15.1 0 0.11 0.00 0.17 91 55
17.75 0 0.89 0.70 1.00 108 62
15.2 0 0.89 0.40 0.67 105 51
14.6 1 1.00 0.50 0.67 117 30
16.65 0 0.89 0.60 0.83 119 49
8.1 0 1.00 0.80 0.50 31 16

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'Sir Maurice George Kendall' @ kendall.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&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]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&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'Sir Maurice George Kendall' @ kendall.wessa.net






Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 7.84909 -0.834873Curus[t] -0.207284Calculation[t] -1.01383Algebraic_Reasoning[t] + 2.0974Graphical_Interpretation[t] + 0.020481LFM[t] + 0.051462CH[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
TOT[t] =  +  7.84909 -0.834873Curus[t] -0.207284Calculation[t] -1.01383Algebraic_Reasoning[t] +  2.0974Graphical_Interpretation[t] +  0.020481LFM[t] +  0.051462CH[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]TOT[t] =  +  7.84909 -0.834873Curus[t] -0.207284Calculation[t] -1.01383Algebraic_Reasoning[t] +  2.0974Graphical_Interpretation[t] +  0.020481LFM[t] +  0.051462CH[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
TOT[t] = + 7.84909 -0.834873Curus[t] -0.207284Calculation[t] -1.01383Algebraic_Reasoning[t] + 2.0974Graphical_Interpretation[t] + 0.020481LFM[t] + 0.051462CH[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.849091.037337.5675.99573e-132.99786e-13
Curus-0.8348730.449573-1.8570.06439110.0321955
Calculation-0.2072841.22066-0.16980.8652830.432642
Algebraic_Reasoning-1.013831.1589-0.87480.3824480.191224
Graphical_Interpretation2.09740.9120692.30.02223120.0111156
LFM0.0204810.006025873.3990.0007784480.000389224
CH0.0514620.01101564.6724.70805e-062.35402e-06

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 7.84909 & 1.03733 & 7.567 & 5.99573e-13 & 2.99786e-13 \tabularnewline
Curus & -0.834873 & 0.449573 & -1.857 & 0.0643911 & 0.0321955 \tabularnewline
Calculation & -0.207284 & 1.22066 & -0.1698 & 0.865283 & 0.432642 \tabularnewline
Algebraic_Reasoning & -1.01383 & 1.1589 & -0.8748 & 0.382448 & 0.191224 \tabularnewline
Graphical_Interpretation & 2.0974 & 0.912069 & 2.3 & 0.0222312 & 0.0111156 \tabularnewline
LFM & 0.020481 & 0.00602587 & 3.399 & 0.000778448 & 0.000389224 \tabularnewline
CH & 0.051462 & 0.0110156 & 4.672 & 4.70805e-06 & 2.35402e-06 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]7.84909[/C][C]1.03733[/C][C]7.567[/C][C]5.99573e-13[/C][C]2.99786e-13[/C][/ROW]
[ROW][C]Curus[/C][C]-0.834873[/C][C]0.449573[/C][C]-1.857[/C][C]0.0643911[/C][C]0.0321955[/C][/ROW]
[ROW][C]Calculation[/C][C]-0.207284[/C][C]1.22066[/C][C]-0.1698[/C][C]0.865283[/C][C]0.432642[/C][/ROW]
[ROW][C]Algebraic_Reasoning[/C][C]-1.01383[/C][C]1.1589[/C][C]-0.8748[/C][C]0.382448[/C][C]0.191224[/C][/ROW]
[ROW][C]Graphical_Interpretation[/C][C]2.0974[/C][C]0.912069[/C][C]2.3[/C][C]0.0222312[/C][C]0.0111156[/C][/ROW]
[ROW][C]LFM[/C][C]0.020481[/C][C]0.00602587[/C][C]3.399[/C][C]0.000778448[/C][C]0.000389224[/C][/ROW]
[ROW][C]CH[/C][C]0.051462[/C][C]0.0110156[/C][C]4.672[/C][C]4.70805e-06[/C][C]2.35402e-06[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)7.849091.037337.5675.99573e-132.99786e-13
Curus-0.8348730.449573-1.8570.06439110.0321955
Calculation-0.2072841.22066-0.16980.8652830.432642
Algebraic_Reasoning-1.013831.1589-0.87480.3824480.191224
Graphical_Interpretation2.09740.9120692.30.02223120.0111156
LFM0.0204810.006025873.3990.0007784480.000389224
CH0.0514620.01101564.6724.70805e-062.35402e-06






Multiple Linear Regression - Regression Statistics
Multiple R0.427388
R-squared0.18266
Adjusted R-squared0.164564
F-TEST (value)10.0939
F-TEST (DF numerator)6
F-TEST (DF denominator)271
p-value4.51526e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.10252
Sum Squared Residuals2608.54

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.427388 \tabularnewline
R-squared & 0.18266 \tabularnewline
Adjusted R-squared & 0.164564 \tabularnewline
F-TEST (value) & 10.0939 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 271 \tabularnewline
p-value & 4.51526e-10 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.10252 \tabularnewline
Sum Squared Residuals & 2608.54 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.427388[/C][/ROW]
[ROW][C]R-squared[/C][C]0.18266[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.164564[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.0939[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]271[/C][/ROW]
[ROW][C]p-value[/C][C]4.51526e-10[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.10252[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2608.54[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.427388
R-squared0.18266
Adjusted R-squared0.164564
F-TEST (value)10.0939
F-TEST (DF numerator)6
F-TEST (DF denominator)271
p-value4.51526e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.10252
Sum Squared Residuals2608.54






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
112.914.2564-1.35636
212.212.9175-0.717537
312.813.1996-0.399572
47.414.4903-7.0903
56.711.8451-5.14513
612.613.8122-1.21216
714.814.61220.187834
813.313.5632-0.263181
911.115.0285-3.92849
108.212.4666-4.26665
1111.413.0969-1.69688
126.414.5536-8.15361
1310.612.5027-1.9027
141215.0916-3.09159
156.39.81183-3.51183
1611.311.17610.123889
1711.914.8999-2.99994
189.311.9117-2.61173
199.613.5074-3.90745
201012.849-2.84902
216.411.8114-5.41138
2213.812.63661.16343
2310.814.7757-3.97571
2413.815.7691-1.96911
2511.714.0481-2.34807
2610.916.9539-6.05386
2716.115.87350.226478
2813.413.04560.354428
299.914.7329-4.83293
3011.513.6569-2.15695
318.312.1903-3.89033
3211.713.0315-1.33151
33912.6707-3.67065
349.713.9314-4.23143
3510.812.6535-1.85355
3610.312.2278-1.92776
3710.412.79-2.39001
3812.712.60220.0978494
399.313.9851-4.68514
4011.814.1605-2.36045
415.912.2103-6.31035
4211.413.4984-2.09836
431314.4157-1.4157
4410.814.3588-3.55884
4512.312.1050.195011
4611.314.2381-2.93806
4711.812.7385-0.938508
487.913.106-5.20599
4912.711.4031.29702
5012.311.08751.2125
5111.613.6364-2.03636
526.711.6274-4.92741
5310.912.6301-1.73007
5412.113.8478-1.74778
5513.313.4203-0.120317
5610.112.473-2.373
575.713.0852-7.38522
5814.312.09832.20173
5989.5824-1.5824
6013.313.10870.191276
619.315.2089-5.90888
6212.511.97510.524911
637.612.7547-5.15468
6415.915.77570.124263
659.213.543-4.34302
669.111.841-2.74098
6711.115.1481-4.04808
681317.9755-4.97552
6914.513.18921.31077
7012.213.2319-1.03189
7112.314.2665-1.96652
7211.411.9025-0.502464
738.812.5666-3.76657
7414.613.96240.63759
7512.613.3736-0.773603
76NANA-0.447724
771312.77580.224229
7812.614.3173-1.71726
7913.215.4511-2.25111
809.914.8598-4.95979
817.79.07236-1.37236
8210.59.422951.07705
8313.415.6734-2.27336
8410.919.2525-8.35248
854.37.0341-2.7341
8610.313.0169-2.71688
8711.812.7524-0.952363
8811.211.3448-0.14475
8911.415.2584-3.85841
908.68.73923-0.139235
9113.212.55370.646331
9212.620.0749-7.47492
935.610.3721-4.77209
949.913.5072-3.60721
958.813.1092-4.30917
967.710.7205-3.02047
97914.5504-5.55044
987.37.62906-0.329063
9911.49.572091.82791
10013.618.8797-5.27972
1017.99.17775-1.27775
10210.713.3114-2.61141
10310.312.6583-2.35829
1048.312.4952-4.19519
1059.68.679750.920254
10614.217.3529-3.15285
1078.56.243552.25645
10813.520.4717-6.97167
1094.99.10633-4.20633
1106.410.3722-3.97216
1119.610.4706-0.870565
11211.612.448-0.847992
11311.116.6923-5.59227
1144.353.635630.714375
11512.78.120654.57935
11618.113.90834.19165
11717.8517.81130.038698
11816.615.30941.2906
11912.610.73221.86776
12017.113.56423.53576
12119.121.6564-2.5564
12216.113.12982.97021
12313.359.103154.24685
12418.413.43734.96273
12514.716.7208-2.02078
12610.69.639310.96069
12712.69.272713.32729
12816.216.322-0.121963
12913.69.910413.68959
13018.915.91162.98844
13114.111.43422.66579
13214.514.24220.2578
13316.1514.10322.04679
13414.7512.71772.03231
13514.813.99990.800084
13612.4511.82440.625628
13712.657.866464.78354
13817.3519.1907-1.84074
1398.64.965273.63473
14018.416.33242.06762
14116.116.1833-0.0832958
14211.66.622744.97726
14317.7515.73912.01093
14415.2510.91514.33493
14517.6515.31792.33213
14616.3512.92443.42564
14717.6516.97520.67477
14813.611.95741.6426
14914.3511.71892.63111
15014.759.937484.81252
15118.2521.9303-3.68035
1529.97.879572.02043
1531610.91435.08567
15418.2515.30062.94936
15516.8514.16152.68845
15614.614.45460.145403
15713.8510.73333.11668
15818.9515.70793.24209
15915.615.7344-0.134401
16014.8515.4927-0.642745
16111.758.372963.37704
16218.4515.43743.01261
16315.913.67022.22976
16417.110.74626.35381
16516.112.37843.72157
16619.920.1562-0.256236
16710.957.323313.62669
16818.4515.1133.33699
16915.113.69311.4069
1701517.5635-2.56347
17111.358.869222.48078
17215.9511.8074.14301
17318.117.84070.259319
17414.612.4922.10802
17515.413.2922.10802
17615.412.34123.05882
17717.617.7121-0.112132
17813.357.273156.07685
17919.118.00631.09368
18015.3518.2486-2.89863
1817.68.64894-1.04894
18213.413.34170.058308
18313.99.331194.56881
18419.117.01682.08317
18515.2515.5689-0.318899
18612.910.22072.6793
18716.110.43155.66851
18817.3516.75580.59417
18913.1511.81841.33158
19012.1511.11511.03492
19112.613.9207-1.32066
19210.359.148861.20114
19315.417.392-1.99196
1949.63.801415.79859
19518.216.76571.43429
19613.611.38612.21388
19714.8514.2420.607966
19814.7512.82291.92708
19914.110.79253.30754
20014.912.012.89001
20116.2512.32563.92437
20219.2517.49731.75267
20313.613.05250.547519
20413.611.78831.81165
20515.6514.76650.883524
20612.759.623853.12615
20714.616.1788-1.57884
2089.858.755191.09481
20912.657.996144.65386
21019.217.0042.19601
21116.616.9386-0.338646
21211.28.951382.24862
21315.2516.1467-0.896746
21411.910.76781.13219
21513.211.41581.78415
21616.3514.75981.5902
21712.49.724642.67536
21815.8511.27754.57249
21918.1518.6132-0.463201
22011.159.245191.90481
22115.6510.78914.86086
22217.7522.25-4.50003
2237.656.23661.4134
22412.358.564053.78595
22515.611.03634.56372
22619.315.27924.02083
22715.210.65364.54636
22817.113.80513.29486
22915.611.88753.71252
23018.412.75095.64908
23119.0511.9967.05401
23218.5515.4163.13402
23319.118.44690.653108
23413.113.6003-0.500341
23512.8513.3304-0.480393
2369.515.0632-5.56317
2374.53.150711.34929
23811.8511.84760.00243667
23913.612.51341.08665
24011.711.27030.429662
24112.412.32720.0727914
24213.3514.0374-0.687379
24311.49.105722.29428
24414.911.17843.72157
24519.920.4129-0.512887
24611.210.73590.464095
24714.612.32632.27374
24817.615.2862.31401
24914.0512.091.95999
25016.115.28290.817098
25113.3513.4248-0.0748033
25211.8512.2869-0.436913
25311.9510.56971.38027
25414.7512.5252.22499
25515.1515.4199-0.269929
25613.210.69152.50851
25716.8520.053-3.20304
2587.8511.7902-3.94016
2597.78.95311-1.25311
26012.617.6403-5.04026
2617.858.10624-0.256236
26210.9511.2845-0.334483
26312.3513.805-1.45502
2649.957.655722.29428
26514.911.50733.39266
26616.6516.08380.566241
26713.410.85612.54394
26813.9510.47883.4712
26915.711.53924.16078
27016.8517.4599-0.60989
27110.957.955292.99471
27215.3515.03240.317632
27312.29.977032.22297
27415.111.80493.29508
27517.7515.98941.7606
27615.212.24542.95459
27714.611.7062.89397
27816.6517.8877-1.23775
2798.1NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12.9 & 14.2564 & -1.35636 \tabularnewline
2 & 12.2 & 12.9175 & -0.717537 \tabularnewline
3 & 12.8 & 13.1996 & -0.399572 \tabularnewline
4 & 7.4 & 14.4903 & -7.0903 \tabularnewline
5 & 6.7 & 11.8451 & -5.14513 \tabularnewline
6 & 12.6 & 13.8122 & -1.21216 \tabularnewline
7 & 14.8 & 14.6122 & 0.187834 \tabularnewline
8 & 13.3 & 13.5632 & -0.263181 \tabularnewline
9 & 11.1 & 15.0285 & -3.92849 \tabularnewline
10 & 8.2 & 12.4666 & -4.26665 \tabularnewline
11 & 11.4 & 13.0969 & -1.69688 \tabularnewline
12 & 6.4 & 14.5536 & -8.15361 \tabularnewline
13 & 10.6 & 12.5027 & -1.9027 \tabularnewline
14 & 12 & 15.0916 & -3.09159 \tabularnewline
15 & 6.3 & 9.81183 & -3.51183 \tabularnewline
16 & 11.3 & 11.1761 & 0.123889 \tabularnewline
17 & 11.9 & 14.8999 & -2.99994 \tabularnewline
18 & 9.3 & 11.9117 & -2.61173 \tabularnewline
19 & 9.6 & 13.5074 & -3.90745 \tabularnewline
20 & 10 & 12.849 & -2.84902 \tabularnewline
21 & 6.4 & 11.8114 & -5.41138 \tabularnewline
22 & 13.8 & 12.6366 & 1.16343 \tabularnewline
23 & 10.8 & 14.7757 & -3.97571 \tabularnewline
24 & 13.8 & 15.7691 & -1.96911 \tabularnewline
25 & 11.7 & 14.0481 & -2.34807 \tabularnewline
26 & 10.9 & 16.9539 & -6.05386 \tabularnewline
27 & 16.1 & 15.8735 & 0.226478 \tabularnewline
28 & 13.4 & 13.0456 & 0.354428 \tabularnewline
29 & 9.9 & 14.7329 & -4.83293 \tabularnewline
30 & 11.5 & 13.6569 & -2.15695 \tabularnewline
31 & 8.3 & 12.1903 & -3.89033 \tabularnewline
32 & 11.7 & 13.0315 & -1.33151 \tabularnewline
33 & 9 & 12.6707 & -3.67065 \tabularnewline
34 & 9.7 & 13.9314 & -4.23143 \tabularnewline
35 & 10.8 & 12.6535 & -1.85355 \tabularnewline
36 & 10.3 & 12.2278 & -1.92776 \tabularnewline
37 & 10.4 & 12.79 & -2.39001 \tabularnewline
38 & 12.7 & 12.6022 & 0.0978494 \tabularnewline
39 & 9.3 & 13.9851 & -4.68514 \tabularnewline
40 & 11.8 & 14.1605 & -2.36045 \tabularnewline
41 & 5.9 & 12.2103 & -6.31035 \tabularnewline
42 & 11.4 & 13.4984 & -2.09836 \tabularnewline
43 & 13 & 14.4157 & -1.4157 \tabularnewline
44 & 10.8 & 14.3588 & -3.55884 \tabularnewline
45 & 12.3 & 12.105 & 0.195011 \tabularnewline
46 & 11.3 & 14.2381 & -2.93806 \tabularnewline
47 & 11.8 & 12.7385 & -0.938508 \tabularnewline
48 & 7.9 & 13.106 & -5.20599 \tabularnewline
49 & 12.7 & 11.403 & 1.29702 \tabularnewline
50 & 12.3 & 11.0875 & 1.2125 \tabularnewline
51 & 11.6 & 13.6364 & -2.03636 \tabularnewline
52 & 6.7 & 11.6274 & -4.92741 \tabularnewline
53 & 10.9 & 12.6301 & -1.73007 \tabularnewline
54 & 12.1 & 13.8478 & -1.74778 \tabularnewline
55 & 13.3 & 13.4203 & -0.120317 \tabularnewline
56 & 10.1 & 12.473 & -2.373 \tabularnewline
57 & 5.7 & 13.0852 & -7.38522 \tabularnewline
58 & 14.3 & 12.0983 & 2.20173 \tabularnewline
59 & 8 & 9.5824 & -1.5824 \tabularnewline
60 & 13.3 & 13.1087 & 0.191276 \tabularnewline
61 & 9.3 & 15.2089 & -5.90888 \tabularnewline
62 & 12.5 & 11.9751 & 0.524911 \tabularnewline
63 & 7.6 & 12.7547 & -5.15468 \tabularnewline
64 & 15.9 & 15.7757 & 0.124263 \tabularnewline
65 & 9.2 & 13.543 & -4.34302 \tabularnewline
66 & 9.1 & 11.841 & -2.74098 \tabularnewline
67 & 11.1 & 15.1481 & -4.04808 \tabularnewline
68 & 13 & 17.9755 & -4.97552 \tabularnewline
69 & 14.5 & 13.1892 & 1.31077 \tabularnewline
70 & 12.2 & 13.2319 & -1.03189 \tabularnewline
71 & 12.3 & 14.2665 & -1.96652 \tabularnewline
72 & 11.4 & 11.9025 & -0.502464 \tabularnewline
73 & 8.8 & 12.5666 & -3.76657 \tabularnewline
74 & 14.6 & 13.9624 & 0.63759 \tabularnewline
75 & 12.6 & 13.3736 & -0.773603 \tabularnewline
76 & NA & NA & -0.447724 \tabularnewline
77 & 13 & 12.7758 & 0.224229 \tabularnewline
78 & 12.6 & 14.3173 & -1.71726 \tabularnewline
79 & 13.2 & 15.4511 & -2.25111 \tabularnewline
80 & 9.9 & 14.8598 & -4.95979 \tabularnewline
81 & 7.7 & 9.07236 & -1.37236 \tabularnewline
82 & 10.5 & 9.42295 & 1.07705 \tabularnewline
83 & 13.4 & 15.6734 & -2.27336 \tabularnewline
84 & 10.9 & 19.2525 & -8.35248 \tabularnewline
85 & 4.3 & 7.0341 & -2.7341 \tabularnewline
86 & 10.3 & 13.0169 & -2.71688 \tabularnewline
87 & 11.8 & 12.7524 & -0.952363 \tabularnewline
88 & 11.2 & 11.3448 & -0.14475 \tabularnewline
89 & 11.4 & 15.2584 & -3.85841 \tabularnewline
90 & 8.6 & 8.73923 & -0.139235 \tabularnewline
91 & 13.2 & 12.5537 & 0.646331 \tabularnewline
92 & 12.6 & 20.0749 & -7.47492 \tabularnewline
93 & 5.6 & 10.3721 & -4.77209 \tabularnewline
94 & 9.9 & 13.5072 & -3.60721 \tabularnewline
95 & 8.8 & 13.1092 & -4.30917 \tabularnewline
96 & 7.7 & 10.7205 & -3.02047 \tabularnewline
97 & 9 & 14.5504 & -5.55044 \tabularnewline
98 & 7.3 & 7.62906 & -0.329063 \tabularnewline
99 & 11.4 & 9.57209 & 1.82791 \tabularnewline
100 & 13.6 & 18.8797 & -5.27972 \tabularnewline
101 & 7.9 & 9.17775 & -1.27775 \tabularnewline
102 & 10.7 & 13.3114 & -2.61141 \tabularnewline
103 & 10.3 & 12.6583 & -2.35829 \tabularnewline
104 & 8.3 & 12.4952 & -4.19519 \tabularnewline
105 & 9.6 & 8.67975 & 0.920254 \tabularnewline
106 & 14.2 & 17.3529 & -3.15285 \tabularnewline
107 & 8.5 & 6.24355 & 2.25645 \tabularnewline
108 & 13.5 & 20.4717 & -6.97167 \tabularnewline
109 & 4.9 & 9.10633 & -4.20633 \tabularnewline
110 & 6.4 & 10.3722 & -3.97216 \tabularnewline
111 & 9.6 & 10.4706 & -0.870565 \tabularnewline
112 & 11.6 & 12.448 & -0.847992 \tabularnewline
113 & 11.1 & 16.6923 & -5.59227 \tabularnewline
114 & 4.35 & 3.63563 & 0.714375 \tabularnewline
115 & 12.7 & 8.12065 & 4.57935 \tabularnewline
116 & 18.1 & 13.9083 & 4.19165 \tabularnewline
117 & 17.85 & 17.8113 & 0.038698 \tabularnewline
118 & 16.6 & 15.3094 & 1.2906 \tabularnewline
119 & 12.6 & 10.7322 & 1.86776 \tabularnewline
120 & 17.1 & 13.5642 & 3.53576 \tabularnewline
121 & 19.1 & 21.6564 & -2.5564 \tabularnewline
122 & 16.1 & 13.1298 & 2.97021 \tabularnewline
123 & 13.35 & 9.10315 & 4.24685 \tabularnewline
124 & 18.4 & 13.4373 & 4.96273 \tabularnewline
125 & 14.7 & 16.7208 & -2.02078 \tabularnewline
126 & 10.6 & 9.63931 & 0.96069 \tabularnewline
127 & 12.6 & 9.27271 & 3.32729 \tabularnewline
128 & 16.2 & 16.322 & -0.121963 \tabularnewline
129 & 13.6 & 9.91041 & 3.68959 \tabularnewline
130 & 18.9 & 15.9116 & 2.98844 \tabularnewline
131 & 14.1 & 11.4342 & 2.66579 \tabularnewline
132 & 14.5 & 14.2422 & 0.2578 \tabularnewline
133 & 16.15 & 14.1032 & 2.04679 \tabularnewline
134 & 14.75 & 12.7177 & 2.03231 \tabularnewline
135 & 14.8 & 13.9999 & 0.800084 \tabularnewline
136 & 12.45 & 11.8244 & 0.625628 \tabularnewline
137 & 12.65 & 7.86646 & 4.78354 \tabularnewline
138 & 17.35 & 19.1907 & -1.84074 \tabularnewline
139 & 8.6 & 4.96527 & 3.63473 \tabularnewline
140 & 18.4 & 16.3324 & 2.06762 \tabularnewline
141 & 16.1 & 16.1833 & -0.0832958 \tabularnewline
142 & 11.6 & 6.62274 & 4.97726 \tabularnewline
143 & 17.75 & 15.7391 & 2.01093 \tabularnewline
144 & 15.25 & 10.9151 & 4.33493 \tabularnewline
145 & 17.65 & 15.3179 & 2.33213 \tabularnewline
146 & 16.35 & 12.9244 & 3.42564 \tabularnewline
147 & 17.65 & 16.9752 & 0.67477 \tabularnewline
148 & 13.6 & 11.9574 & 1.6426 \tabularnewline
149 & 14.35 & 11.7189 & 2.63111 \tabularnewline
150 & 14.75 & 9.93748 & 4.81252 \tabularnewline
151 & 18.25 & 21.9303 & -3.68035 \tabularnewline
152 & 9.9 & 7.87957 & 2.02043 \tabularnewline
153 & 16 & 10.9143 & 5.08567 \tabularnewline
154 & 18.25 & 15.3006 & 2.94936 \tabularnewline
155 & 16.85 & 14.1615 & 2.68845 \tabularnewline
156 & 14.6 & 14.4546 & 0.145403 \tabularnewline
157 & 13.85 & 10.7333 & 3.11668 \tabularnewline
158 & 18.95 & 15.7079 & 3.24209 \tabularnewline
159 & 15.6 & 15.7344 & -0.134401 \tabularnewline
160 & 14.85 & 15.4927 & -0.642745 \tabularnewline
161 & 11.75 & 8.37296 & 3.37704 \tabularnewline
162 & 18.45 & 15.4374 & 3.01261 \tabularnewline
163 & 15.9 & 13.6702 & 2.22976 \tabularnewline
164 & 17.1 & 10.7462 & 6.35381 \tabularnewline
165 & 16.1 & 12.3784 & 3.72157 \tabularnewline
166 & 19.9 & 20.1562 & -0.256236 \tabularnewline
167 & 10.95 & 7.32331 & 3.62669 \tabularnewline
168 & 18.45 & 15.113 & 3.33699 \tabularnewline
169 & 15.1 & 13.6931 & 1.4069 \tabularnewline
170 & 15 & 17.5635 & -2.56347 \tabularnewline
171 & 11.35 & 8.86922 & 2.48078 \tabularnewline
172 & 15.95 & 11.807 & 4.14301 \tabularnewline
173 & 18.1 & 17.8407 & 0.259319 \tabularnewline
174 & 14.6 & 12.492 & 2.10802 \tabularnewline
175 & 15.4 & 13.292 & 2.10802 \tabularnewline
176 & 15.4 & 12.3412 & 3.05882 \tabularnewline
177 & 17.6 & 17.7121 & -0.112132 \tabularnewline
178 & 13.35 & 7.27315 & 6.07685 \tabularnewline
179 & 19.1 & 18.0063 & 1.09368 \tabularnewline
180 & 15.35 & 18.2486 & -2.89863 \tabularnewline
181 & 7.6 & 8.64894 & -1.04894 \tabularnewline
182 & 13.4 & 13.3417 & 0.058308 \tabularnewline
183 & 13.9 & 9.33119 & 4.56881 \tabularnewline
184 & 19.1 & 17.0168 & 2.08317 \tabularnewline
185 & 15.25 & 15.5689 & -0.318899 \tabularnewline
186 & 12.9 & 10.2207 & 2.6793 \tabularnewline
187 & 16.1 & 10.4315 & 5.66851 \tabularnewline
188 & 17.35 & 16.7558 & 0.59417 \tabularnewline
189 & 13.15 & 11.8184 & 1.33158 \tabularnewline
190 & 12.15 & 11.1151 & 1.03492 \tabularnewline
191 & 12.6 & 13.9207 & -1.32066 \tabularnewline
192 & 10.35 & 9.14886 & 1.20114 \tabularnewline
193 & 15.4 & 17.392 & -1.99196 \tabularnewline
194 & 9.6 & 3.80141 & 5.79859 \tabularnewline
195 & 18.2 & 16.7657 & 1.43429 \tabularnewline
196 & 13.6 & 11.3861 & 2.21388 \tabularnewline
197 & 14.85 & 14.242 & 0.607966 \tabularnewline
198 & 14.75 & 12.8229 & 1.92708 \tabularnewline
199 & 14.1 & 10.7925 & 3.30754 \tabularnewline
200 & 14.9 & 12.01 & 2.89001 \tabularnewline
201 & 16.25 & 12.3256 & 3.92437 \tabularnewline
202 & 19.25 & 17.4973 & 1.75267 \tabularnewline
203 & 13.6 & 13.0525 & 0.547519 \tabularnewline
204 & 13.6 & 11.7883 & 1.81165 \tabularnewline
205 & 15.65 & 14.7665 & 0.883524 \tabularnewline
206 & 12.75 & 9.62385 & 3.12615 \tabularnewline
207 & 14.6 & 16.1788 & -1.57884 \tabularnewline
208 & 9.85 & 8.75519 & 1.09481 \tabularnewline
209 & 12.65 & 7.99614 & 4.65386 \tabularnewline
210 & 19.2 & 17.004 & 2.19601 \tabularnewline
211 & 16.6 & 16.9386 & -0.338646 \tabularnewline
212 & 11.2 & 8.95138 & 2.24862 \tabularnewline
213 & 15.25 & 16.1467 & -0.896746 \tabularnewline
214 & 11.9 & 10.7678 & 1.13219 \tabularnewline
215 & 13.2 & 11.4158 & 1.78415 \tabularnewline
216 & 16.35 & 14.7598 & 1.5902 \tabularnewline
217 & 12.4 & 9.72464 & 2.67536 \tabularnewline
218 & 15.85 & 11.2775 & 4.57249 \tabularnewline
219 & 18.15 & 18.6132 & -0.463201 \tabularnewline
220 & 11.15 & 9.24519 & 1.90481 \tabularnewline
221 & 15.65 & 10.7891 & 4.86086 \tabularnewline
222 & 17.75 & 22.25 & -4.50003 \tabularnewline
223 & 7.65 & 6.2366 & 1.4134 \tabularnewline
224 & 12.35 & 8.56405 & 3.78595 \tabularnewline
225 & 15.6 & 11.0363 & 4.56372 \tabularnewline
226 & 19.3 & 15.2792 & 4.02083 \tabularnewline
227 & 15.2 & 10.6536 & 4.54636 \tabularnewline
228 & 17.1 & 13.8051 & 3.29486 \tabularnewline
229 & 15.6 & 11.8875 & 3.71252 \tabularnewline
230 & 18.4 & 12.7509 & 5.64908 \tabularnewline
231 & 19.05 & 11.996 & 7.05401 \tabularnewline
232 & 18.55 & 15.416 & 3.13402 \tabularnewline
233 & 19.1 & 18.4469 & 0.653108 \tabularnewline
234 & 13.1 & 13.6003 & -0.500341 \tabularnewline
235 & 12.85 & 13.3304 & -0.480393 \tabularnewline
236 & 9.5 & 15.0632 & -5.56317 \tabularnewline
237 & 4.5 & 3.15071 & 1.34929 \tabularnewline
238 & 11.85 & 11.8476 & 0.00243667 \tabularnewline
239 & 13.6 & 12.5134 & 1.08665 \tabularnewline
240 & 11.7 & 11.2703 & 0.429662 \tabularnewline
241 & 12.4 & 12.3272 & 0.0727914 \tabularnewline
242 & 13.35 & 14.0374 & -0.687379 \tabularnewline
243 & 11.4 & 9.10572 & 2.29428 \tabularnewline
244 & 14.9 & 11.1784 & 3.72157 \tabularnewline
245 & 19.9 & 20.4129 & -0.512887 \tabularnewline
246 & 11.2 & 10.7359 & 0.464095 \tabularnewline
247 & 14.6 & 12.3263 & 2.27374 \tabularnewline
248 & 17.6 & 15.286 & 2.31401 \tabularnewline
249 & 14.05 & 12.09 & 1.95999 \tabularnewline
250 & 16.1 & 15.2829 & 0.817098 \tabularnewline
251 & 13.35 & 13.4248 & -0.0748033 \tabularnewline
252 & 11.85 & 12.2869 & -0.436913 \tabularnewline
253 & 11.95 & 10.5697 & 1.38027 \tabularnewline
254 & 14.75 & 12.525 & 2.22499 \tabularnewline
255 & 15.15 & 15.4199 & -0.269929 \tabularnewline
256 & 13.2 & 10.6915 & 2.50851 \tabularnewline
257 & 16.85 & 20.053 & -3.20304 \tabularnewline
258 & 7.85 & 11.7902 & -3.94016 \tabularnewline
259 & 7.7 & 8.95311 & -1.25311 \tabularnewline
260 & 12.6 & 17.6403 & -5.04026 \tabularnewline
261 & 7.85 & 8.10624 & -0.256236 \tabularnewline
262 & 10.95 & 11.2845 & -0.334483 \tabularnewline
263 & 12.35 & 13.805 & -1.45502 \tabularnewline
264 & 9.95 & 7.65572 & 2.29428 \tabularnewline
265 & 14.9 & 11.5073 & 3.39266 \tabularnewline
266 & 16.65 & 16.0838 & 0.566241 \tabularnewline
267 & 13.4 & 10.8561 & 2.54394 \tabularnewline
268 & 13.95 & 10.4788 & 3.4712 \tabularnewline
269 & 15.7 & 11.5392 & 4.16078 \tabularnewline
270 & 16.85 & 17.4599 & -0.60989 \tabularnewline
271 & 10.95 & 7.95529 & 2.99471 \tabularnewline
272 & 15.35 & 15.0324 & 0.317632 \tabularnewline
273 & 12.2 & 9.97703 & 2.22297 \tabularnewline
274 & 15.1 & 11.8049 & 3.29508 \tabularnewline
275 & 17.75 & 15.9894 & 1.7606 \tabularnewline
276 & 15.2 & 12.2454 & 2.95459 \tabularnewline
277 & 14.6 & 11.706 & 2.89397 \tabularnewline
278 & 16.65 & 17.8877 & -1.23775 \tabularnewline
279 & 8.1 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&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]14.2564[/C][C]-1.35636[/C][/ROW]
[ROW][C]2[/C][C]12.2[/C][C]12.9175[/C][C]-0.717537[/C][/ROW]
[ROW][C]3[/C][C]12.8[/C][C]13.1996[/C][C]-0.399572[/C][/ROW]
[ROW][C]4[/C][C]7.4[/C][C]14.4903[/C][C]-7.0903[/C][/ROW]
[ROW][C]5[/C][C]6.7[/C][C]11.8451[/C][C]-5.14513[/C][/ROW]
[ROW][C]6[/C][C]12.6[/C][C]13.8122[/C][C]-1.21216[/C][/ROW]
[ROW][C]7[/C][C]14.8[/C][C]14.6122[/C][C]0.187834[/C][/ROW]
[ROW][C]8[/C][C]13.3[/C][C]13.5632[/C][C]-0.263181[/C][/ROW]
[ROW][C]9[/C][C]11.1[/C][C]15.0285[/C][C]-3.92849[/C][/ROW]
[ROW][C]10[/C][C]8.2[/C][C]12.4666[/C][C]-4.26665[/C][/ROW]
[ROW][C]11[/C][C]11.4[/C][C]13.0969[/C][C]-1.69688[/C][/ROW]
[ROW][C]12[/C][C]6.4[/C][C]14.5536[/C][C]-8.15361[/C][/ROW]
[ROW][C]13[/C][C]10.6[/C][C]12.5027[/C][C]-1.9027[/C][/ROW]
[ROW][C]14[/C][C]12[/C][C]15.0916[/C][C]-3.09159[/C][/ROW]
[ROW][C]15[/C][C]6.3[/C][C]9.81183[/C][C]-3.51183[/C][/ROW]
[ROW][C]16[/C][C]11.3[/C][C]11.1761[/C][C]0.123889[/C][/ROW]
[ROW][C]17[/C][C]11.9[/C][C]14.8999[/C][C]-2.99994[/C][/ROW]
[ROW][C]18[/C][C]9.3[/C][C]11.9117[/C][C]-2.61173[/C][/ROW]
[ROW][C]19[/C][C]9.6[/C][C]13.5074[/C][C]-3.90745[/C][/ROW]
[ROW][C]20[/C][C]10[/C][C]12.849[/C][C]-2.84902[/C][/ROW]
[ROW][C]21[/C][C]6.4[/C][C]11.8114[/C][C]-5.41138[/C][/ROW]
[ROW][C]22[/C][C]13.8[/C][C]12.6366[/C][C]1.16343[/C][/ROW]
[ROW][C]23[/C][C]10.8[/C][C]14.7757[/C][C]-3.97571[/C][/ROW]
[ROW][C]24[/C][C]13.8[/C][C]15.7691[/C][C]-1.96911[/C][/ROW]
[ROW][C]25[/C][C]11.7[/C][C]14.0481[/C][C]-2.34807[/C][/ROW]
[ROW][C]26[/C][C]10.9[/C][C]16.9539[/C][C]-6.05386[/C][/ROW]
[ROW][C]27[/C][C]16.1[/C][C]15.8735[/C][C]0.226478[/C][/ROW]
[ROW][C]28[/C][C]13.4[/C][C]13.0456[/C][C]0.354428[/C][/ROW]
[ROW][C]29[/C][C]9.9[/C][C]14.7329[/C][C]-4.83293[/C][/ROW]
[ROW][C]30[/C][C]11.5[/C][C]13.6569[/C][C]-2.15695[/C][/ROW]
[ROW][C]31[/C][C]8.3[/C][C]12.1903[/C][C]-3.89033[/C][/ROW]
[ROW][C]32[/C][C]11.7[/C][C]13.0315[/C][C]-1.33151[/C][/ROW]
[ROW][C]33[/C][C]9[/C][C]12.6707[/C][C]-3.67065[/C][/ROW]
[ROW][C]34[/C][C]9.7[/C][C]13.9314[/C][C]-4.23143[/C][/ROW]
[ROW][C]35[/C][C]10.8[/C][C]12.6535[/C][C]-1.85355[/C][/ROW]
[ROW][C]36[/C][C]10.3[/C][C]12.2278[/C][C]-1.92776[/C][/ROW]
[ROW][C]37[/C][C]10.4[/C][C]12.79[/C][C]-2.39001[/C][/ROW]
[ROW][C]38[/C][C]12.7[/C][C]12.6022[/C][C]0.0978494[/C][/ROW]
[ROW][C]39[/C][C]9.3[/C][C]13.9851[/C][C]-4.68514[/C][/ROW]
[ROW][C]40[/C][C]11.8[/C][C]14.1605[/C][C]-2.36045[/C][/ROW]
[ROW][C]41[/C][C]5.9[/C][C]12.2103[/C][C]-6.31035[/C][/ROW]
[ROW][C]42[/C][C]11.4[/C][C]13.4984[/C][C]-2.09836[/C][/ROW]
[ROW][C]43[/C][C]13[/C][C]14.4157[/C][C]-1.4157[/C][/ROW]
[ROW][C]44[/C][C]10.8[/C][C]14.3588[/C][C]-3.55884[/C][/ROW]
[ROW][C]45[/C][C]12.3[/C][C]12.105[/C][C]0.195011[/C][/ROW]
[ROW][C]46[/C][C]11.3[/C][C]14.2381[/C][C]-2.93806[/C][/ROW]
[ROW][C]47[/C][C]11.8[/C][C]12.7385[/C][C]-0.938508[/C][/ROW]
[ROW][C]48[/C][C]7.9[/C][C]13.106[/C][C]-5.20599[/C][/ROW]
[ROW][C]49[/C][C]12.7[/C][C]11.403[/C][C]1.29702[/C][/ROW]
[ROW][C]50[/C][C]12.3[/C][C]11.0875[/C][C]1.2125[/C][/ROW]
[ROW][C]51[/C][C]11.6[/C][C]13.6364[/C][C]-2.03636[/C][/ROW]
[ROW][C]52[/C][C]6.7[/C][C]11.6274[/C][C]-4.92741[/C][/ROW]
[ROW][C]53[/C][C]10.9[/C][C]12.6301[/C][C]-1.73007[/C][/ROW]
[ROW][C]54[/C][C]12.1[/C][C]13.8478[/C][C]-1.74778[/C][/ROW]
[ROW][C]55[/C][C]13.3[/C][C]13.4203[/C][C]-0.120317[/C][/ROW]
[ROW][C]56[/C][C]10.1[/C][C]12.473[/C][C]-2.373[/C][/ROW]
[ROW][C]57[/C][C]5.7[/C][C]13.0852[/C][C]-7.38522[/C][/ROW]
[ROW][C]58[/C][C]14.3[/C][C]12.0983[/C][C]2.20173[/C][/ROW]
[ROW][C]59[/C][C]8[/C][C]9.5824[/C][C]-1.5824[/C][/ROW]
[ROW][C]60[/C][C]13.3[/C][C]13.1087[/C][C]0.191276[/C][/ROW]
[ROW][C]61[/C][C]9.3[/C][C]15.2089[/C][C]-5.90888[/C][/ROW]
[ROW][C]62[/C][C]12.5[/C][C]11.9751[/C][C]0.524911[/C][/ROW]
[ROW][C]63[/C][C]7.6[/C][C]12.7547[/C][C]-5.15468[/C][/ROW]
[ROW][C]64[/C][C]15.9[/C][C]15.7757[/C][C]0.124263[/C][/ROW]
[ROW][C]65[/C][C]9.2[/C][C]13.543[/C][C]-4.34302[/C][/ROW]
[ROW][C]66[/C][C]9.1[/C][C]11.841[/C][C]-2.74098[/C][/ROW]
[ROW][C]67[/C][C]11.1[/C][C]15.1481[/C][C]-4.04808[/C][/ROW]
[ROW][C]68[/C][C]13[/C][C]17.9755[/C][C]-4.97552[/C][/ROW]
[ROW][C]69[/C][C]14.5[/C][C]13.1892[/C][C]1.31077[/C][/ROW]
[ROW][C]70[/C][C]12.2[/C][C]13.2319[/C][C]-1.03189[/C][/ROW]
[ROW][C]71[/C][C]12.3[/C][C]14.2665[/C][C]-1.96652[/C][/ROW]
[ROW][C]72[/C][C]11.4[/C][C]11.9025[/C][C]-0.502464[/C][/ROW]
[ROW][C]73[/C][C]8.8[/C][C]12.5666[/C][C]-3.76657[/C][/ROW]
[ROW][C]74[/C][C]14.6[/C][C]13.9624[/C][C]0.63759[/C][/ROW]
[ROW][C]75[/C][C]12.6[/C][C]13.3736[/C][C]-0.773603[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]-0.447724[/C][/ROW]
[ROW][C]77[/C][C]13[/C][C]12.7758[/C][C]0.224229[/C][/ROW]
[ROW][C]78[/C][C]12.6[/C][C]14.3173[/C][C]-1.71726[/C][/ROW]
[ROW][C]79[/C][C]13.2[/C][C]15.4511[/C][C]-2.25111[/C][/ROW]
[ROW][C]80[/C][C]9.9[/C][C]14.8598[/C][C]-4.95979[/C][/ROW]
[ROW][C]81[/C][C]7.7[/C][C]9.07236[/C][C]-1.37236[/C][/ROW]
[ROW][C]82[/C][C]10.5[/C][C]9.42295[/C][C]1.07705[/C][/ROW]
[ROW][C]83[/C][C]13.4[/C][C]15.6734[/C][C]-2.27336[/C][/ROW]
[ROW][C]84[/C][C]10.9[/C][C]19.2525[/C][C]-8.35248[/C][/ROW]
[ROW][C]85[/C][C]4.3[/C][C]7.0341[/C][C]-2.7341[/C][/ROW]
[ROW][C]86[/C][C]10.3[/C][C]13.0169[/C][C]-2.71688[/C][/ROW]
[ROW][C]87[/C][C]11.8[/C][C]12.7524[/C][C]-0.952363[/C][/ROW]
[ROW][C]88[/C][C]11.2[/C][C]11.3448[/C][C]-0.14475[/C][/ROW]
[ROW][C]89[/C][C]11.4[/C][C]15.2584[/C][C]-3.85841[/C][/ROW]
[ROW][C]90[/C][C]8.6[/C][C]8.73923[/C][C]-0.139235[/C][/ROW]
[ROW][C]91[/C][C]13.2[/C][C]12.5537[/C][C]0.646331[/C][/ROW]
[ROW][C]92[/C][C]12.6[/C][C]20.0749[/C][C]-7.47492[/C][/ROW]
[ROW][C]93[/C][C]5.6[/C][C]10.3721[/C][C]-4.77209[/C][/ROW]
[ROW][C]94[/C][C]9.9[/C][C]13.5072[/C][C]-3.60721[/C][/ROW]
[ROW][C]95[/C][C]8.8[/C][C]13.1092[/C][C]-4.30917[/C][/ROW]
[ROW][C]96[/C][C]7.7[/C][C]10.7205[/C][C]-3.02047[/C][/ROW]
[ROW][C]97[/C][C]9[/C][C]14.5504[/C][C]-5.55044[/C][/ROW]
[ROW][C]98[/C][C]7.3[/C][C]7.62906[/C][C]-0.329063[/C][/ROW]
[ROW][C]99[/C][C]11.4[/C][C]9.57209[/C][C]1.82791[/C][/ROW]
[ROW][C]100[/C][C]13.6[/C][C]18.8797[/C][C]-5.27972[/C][/ROW]
[ROW][C]101[/C][C]7.9[/C][C]9.17775[/C][C]-1.27775[/C][/ROW]
[ROW][C]102[/C][C]10.7[/C][C]13.3114[/C][C]-2.61141[/C][/ROW]
[ROW][C]103[/C][C]10.3[/C][C]12.6583[/C][C]-2.35829[/C][/ROW]
[ROW][C]104[/C][C]8.3[/C][C]12.4952[/C][C]-4.19519[/C][/ROW]
[ROW][C]105[/C][C]9.6[/C][C]8.67975[/C][C]0.920254[/C][/ROW]
[ROW][C]106[/C][C]14.2[/C][C]17.3529[/C][C]-3.15285[/C][/ROW]
[ROW][C]107[/C][C]8.5[/C][C]6.24355[/C][C]2.25645[/C][/ROW]
[ROW][C]108[/C][C]13.5[/C][C]20.4717[/C][C]-6.97167[/C][/ROW]
[ROW][C]109[/C][C]4.9[/C][C]9.10633[/C][C]-4.20633[/C][/ROW]
[ROW][C]110[/C][C]6.4[/C][C]10.3722[/C][C]-3.97216[/C][/ROW]
[ROW][C]111[/C][C]9.6[/C][C]10.4706[/C][C]-0.870565[/C][/ROW]
[ROW][C]112[/C][C]11.6[/C][C]12.448[/C][C]-0.847992[/C][/ROW]
[ROW][C]113[/C][C]11.1[/C][C]16.6923[/C][C]-5.59227[/C][/ROW]
[ROW][C]114[/C][C]4.35[/C][C]3.63563[/C][C]0.714375[/C][/ROW]
[ROW][C]115[/C][C]12.7[/C][C]8.12065[/C][C]4.57935[/C][/ROW]
[ROW][C]116[/C][C]18.1[/C][C]13.9083[/C][C]4.19165[/C][/ROW]
[ROW][C]117[/C][C]17.85[/C][C]17.8113[/C][C]0.038698[/C][/ROW]
[ROW][C]118[/C][C]16.6[/C][C]15.3094[/C][C]1.2906[/C][/ROW]
[ROW][C]119[/C][C]12.6[/C][C]10.7322[/C][C]1.86776[/C][/ROW]
[ROW][C]120[/C][C]17.1[/C][C]13.5642[/C][C]3.53576[/C][/ROW]
[ROW][C]121[/C][C]19.1[/C][C]21.6564[/C][C]-2.5564[/C][/ROW]
[ROW][C]122[/C][C]16.1[/C][C]13.1298[/C][C]2.97021[/C][/ROW]
[ROW][C]123[/C][C]13.35[/C][C]9.10315[/C][C]4.24685[/C][/ROW]
[ROW][C]124[/C][C]18.4[/C][C]13.4373[/C][C]4.96273[/C][/ROW]
[ROW][C]125[/C][C]14.7[/C][C]16.7208[/C][C]-2.02078[/C][/ROW]
[ROW][C]126[/C][C]10.6[/C][C]9.63931[/C][C]0.96069[/C][/ROW]
[ROW][C]127[/C][C]12.6[/C][C]9.27271[/C][C]3.32729[/C][/ROW]
[ROW][C]128[/C][C]16.2[/C][C]16.322[/C][C]-0.121963[/C][/ROW]
[ROW][C]129[/C][C]13.6[/C][C]9.91041[/C][C]3.68959[/C][/ROW]
[ROW][C]130[/C][C]18.9[/C][C]15.9116[/C][C]2.98844[/C][/ROW]
[ROW][C]131[/C][C]14.1[/C][C]11.4342[/C][C]2.66579[/C][/ROW]
[ROW][C]132[/C][C]14.5[/C][C]14.2422[/C][C]0.2578[/C][/ROW]
[ROW][C]133[/C][C]16.15[/C][C]14.1032[/C][C]2.04679[/C][/ROW]
[ROW][C]134[/C][C]14.75[/C][C]12.7177[/C][C]2.03231[/C][/ROW]
[ROW][C]135[/C][C]14.8[/C][C]13.9999[/C][C]0.800084[/C][/ROW]
[ROW][C]136[/C][C]12.45[/C][C]11.8244[/C][C]0.625628[/C][/ROW]
[ROW][C]137[/C][C]12.65[/C][C]7.86646[/C][C]4.78354[/C][/ROW]
[ROW][C]138[/C][C]17.35[/C][C]19.1907[/C][C]-1.84074[/C][/ROW]
[ROW][C]139[/C][C]8.6[/C][C]4.96527[/C][C]3.63473[/C][/ROW]
[ROW][C]140[/C][C]18.4[/C][C]16.3324[/C][C]2.06762[/C][/ROW]
[ROW][C]141[/C][C]16.1[/C][C]16.1833[/C][C]-0.0832958[/C][/ROW]
[ROW][C]142[/C][C]11.6[/C][C]6.62274[/C][C]4.97726[/C][/ROW]
[ROW][C]143[/C][C]17.75[/C][C]15.7391[/C][C]2.01093[/C][/ROW]
[ROW][C]144[/C][C]15.25[/C][C]10.9151[/C][C]4.33493[/C][/ROW]
[ROW][C]145[/C][C]17.65[/C][C]15.3179[/C][C]2.33213[/C][/ROW]
[ROW][C]146[/C][C]16.35[/C][C]12.9244[/C][C]3.42564[/C][/ROW]
[ROW][C]147[/C][C]17.65[/C][C]16.9752[/C][C]0.67477[/C][/ROW]
[ROW][C]148[/C][C]13.6[/C][C]11.9574[/C][C]1.6426[/C][/ROW]
[ROW][C]149[/C][C]14.35[/C][C]11.7189[/C][C]2.63111[/C][/ROW]
[ROW][C]150[/C][C]14.75[/C][C]9.93748[/C][C]4.81252[/C][/ROW]
[ROW][C]151[/C][C]18.25[/C][C]21.9303[/C][C]-3.68035[/C][/ROW]
[ROW][C]152[/C][C]9.9[/C][C]7.87957[/C][C]2.02043[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]10.9143[/C][C]5.08567[/C][/ROW]
[ROW][C]154[/C][C]18.25[/C][C]15.3006[/C][C]2.94936[/C][/ROW]
[ROW][C]155[/C][C]16.85[/C][C]14.1615[/C][C]2.68845[/C][/ROW]
[ROW][C]156[/C][C]14.6[/C][C]14.4546[/C][C]0.145403[/C][/ROW]
[ROW][C]157[/C][C]13.85[/C][C]10.7333[/C][C]3.11668[/C][/ROW]
[ROW][C]158[/C][C]18.95[/C][C]15.7079[/C][C]3.24209[/C][/ROW]
[ROW][C]159[/C][C]15.6[/C][C]15.7344[/C][C]-0.134401[/C][/ROW]
[ROW][C]160[/C][C]14.85[/C][C]15.4927[/C][C]-0.642745[/C][/ROW]
[ROW][C]161[/C][C]11.75[/C][C]8.37296[/C][C]3.37704[/C][/ROW]
[ROW][C]162[/C][C]18.45[/C][C]15.4374[/C][C]3.01261[/C][/ROW]
[ROW][C]163[/C][C]15.9[/C][C]13.6702[/C][C]2.22976[/C][/ROW]
[ROW][C]164[/C][C]17.1[/C][C]10.7462[/C][C]6.35381[/C][/ROW]
[ROW][C]165[/C][C]16.1[/C][C]12.3784[/C][C]3.72157[/C][/ROW]
[ROW][C]166[/C][C]19.9[/C][C]20.1562[/C][C]-0.256236[/C][/ROW]
[ROW][C]167[/C][C]10.95[/C][C]7.32331[/C][C]3.62669[/C][/ROW]
[ROW][C]168[/C][C]18.45[/C][C]15.113[/C][C]3.33699[/C][/ROW]
[ROW][C]169[/C][C]15.1[/C][C]13.6931[/C][C]1.4069[/C][/ROW]
[ROW][C]170[/C][C]15[/C][C]17.5635[/C][C]-2.56347[/C][/ROW]
[ROW][C]171[/C][C]11.35[/C][C]8.86922[/C][C]2.48078[/C][/ROW]
[ROW][C]172[/C][C]15.95[/C][C]11.807[/C][C]4.14301[/C][/ROW]
[ROW][C]173[/C][C]18.1[/C][C]17.8407[/C][C]0.259319[/C][/ROW]
[ROW][C]174[/C][C]14.6[/C][C]12.492[/C][C]2.10802[/C][/ROW]
[ROW][C]175[/C][C]15.4[/C][C]13.292[/C][C]2.10802[/C][/ROW]
[ROW][C]176[/C][C]15.4[/C][C]12.3412[/C][C]3.05882[/C][/ROW]
[ROW][C]177[/C][C]17.6[/C][C]17.7121[/C][C]-0.112132[/C][/ROW]
[ROW][C]178[/C][C]13.35[/C][C]7.27315[/C][C]6.07685[/C][/ROW]
[ROW][C]179[/C][C]19.1[/C][C]18.0063[/C][C]1.09368[/C][/ROW]
[ROW][C]180[/C][C]15.35[/C][C]18.2486[/C][C]-2.89863[/C][/ROW]
[ROW][C]181[/C][C]7.6[/C][C]8.64894[/C][C]-1.04894[/C][/ROW]
[ROW][C]182[/C][C]13.4[/C][C]13.3417[/C][C]0.058308[/C][/ROW]
[ROW][C]183[/C][C]13.9[/C][C]9.33119[/C][C]4.56881[/C][/ROW]
[ROW][C]184[/C][C]19.1[/C][C]17.0168[/C][C]2.08317[/C][/ROW]
[ROW][C]185[/C][C]15.25[/C][C]15.5689[/C][C]-0.318899[/C][/ROW]
[ROW][C]186[/C][C]12.9[/C][C]10.2207[/C][C]2.6793[/C][/ROW]
[ROW][C]187[/C][C]16.1[/C][C]10.4315[/C][C]5.66851[/C][/ROW]
[ROW][C]188[/C][C]17.35[/C][C]16.7558[/C][C]0.59417[/C][/ROW]
[ROW][C]189[/C][C]13.15[/C][C]11.8184[/C][C]1.33158[/C][/ROW]
[ROW][C]190[/C][C]12.15[/C][C]11.1151[/C][C]1.03492[/C][/ROW]
[ROW][C]191[/C][C]12.6[/C][C]13.9207[/C][C]-1.32066[/C][/ROW]
[ROW][C]192[/C][C]10.35[/C][C]9.14886[/C][C]1.20114[/C][/ROW]
[ROW][C]193[/C][C]15.4[/C][C]17.392[/C][C]-1.99196[/C][/ROW]
[ROW][C]194[/C][C]9.6[/C][C]3.80141[/C][C]5.79859[/C][/ROW]
[ROW][C]195[/C][C]18.2[/C][C]16.7657[/C][C]1.43429[/C][/ROW]
[ROW][C]196[/C][C]13.6[/C][C]11.3861[/C][C]2.21388[/C][/ROW]
[ROW][C]197[/C][C]14.85[/C][C]14.242[/C][C]0.607966[/C][/ROW]
[ROW][C]198[/C][C]14.75[/C][C]12.8229[/C][C]1.92708[/C][/ROW]
[ROW][C]199[/C][C]14.1[/C][C]10.7925[/C][C]3.30754[/C][/ROW]
[ROW][C]200[/C][C]14.9[/C][C]12.01[/C][C]2.89001[/C][/ROW]
[ROW][C]201[/C][C]16.25[/C][C]12.3256[/C][C]3.92437[/C][/ROW]
[ROW][C]202[/C][C]19.25[/C][C]17.4973[/C][C]1.75267[/C][/ROW]
[ROW][C]203[/C][C]13.6[/C][C]13.0525[/C][C]0.547519[/C][/ROW]
[ROW][C]204[/C][C]13.6[/C][C]11.7883[/C][C]1.81165[/C][/ROW]
[ROW][C]205[/C][C]15.65[/C][C]14.7665[/C][C]0.883524[/C][/ROW]
[ROW][C]206[/C][C]12.75[/C][C]9.62385[/C][C]3.12615[/C][/ROW]
[ROW][C]207[/C][C]14.6[/C][C]16.1788[/C][C]-1.57884[/C][/ROW]
[ROW][C]208[/C][C]9.85[/C][C]8.75519[/C][C]1.09481[/C][/ROW]
[ROW][C]209[/C][C]12.65[/C][C]7.99614[/C][C]4.65386[/C][/ROW]
[ROW][C]210[/C][C]19.2[/C][C]17.004[/C][C]2.19601[/C][/ROW]
[ROW][C]211[/C][C]16.6[/C][C]16.9386[/C][C]-0.338646[/C][/ROW]
[ROW][C]212[/C][C]11.2[/C][C]8.95138[/C][C]2.24862[/C][/ROW]
[ROW][C]213[/C][C]15.25[/C][C]16.1467[/C][C]-0.896746[/C][/ROW]
[ROW][C]214[/C][C]11.9[/C][C]10.7678[/C][C]1.13219[/C][/ROW]
[ROW][C]215[/C][C]13.2[/C][C]11.4158[/C][C]1.78415[/C][/ROW]
[ROW][C]216[/C][C]16.35[/C][C]14.7598[/C][C]1.5902[/C][/ROW]
[ROW][C]217[/C][C]12.4[/C][C]9.72464[/C][C]2.67536[/C][/ROW]
[ROW][C]218[/C][C]15.85[/C][C]11.2775[/C][C]4.57249[/C][/ROW]
[ROW][C]219[/C][C]18.15[/C][C]18.6132[/C][C]-0.463201[/C][/ROW]
[ROW][C]220[/C][C]11.15[/C][C]9.24519[/C][C]1.90481[/C][/ROW]
[ROW][C]221[/C][C]15.65[/C][C]10.7891[/C][C]4.86086[/C][/ROW]
[ROW][C]222[/C][C]17.75[/C][C]22.25[/C][C]-4.50003[/C][/ROW]
[ROW][C]223[/C][C]7.65[/C][C]6.2366[/C][C]1.4134[/C][/ROW]
[ROW][C]224[/C][C]12.35[/C][C]8.56405[/C][C]3.78595[/C][/ROW]
[ROW][C]225[/C][C]15.6[/C][C]11.0363[/C][C]4.56372[/C][/ROW]
[ROW][C]226[/C][C]19.3[/C][C]15.2792[/C][C]4.02083[/C][/ROW]
[ROW][C]227[/C][C]15.2[/C][C]10.6536[/C][C]4.54636[/C][/ROW]
[ROW][C]228[/C][C]17.1[/C][C]13.8051[/C][C]3.29486[/C][/ROW]
[ROW][C]229[/C][C]15.6[/C][C]11.8875[/C][C]3.71252[/C][/ROW]
[ROW][C]230[/C][C]18.4[/C][C]12.7509[/C][C]5.64908[/C][/ROW]
[ROW][C]231[/C][C]19.05[/C][C]11.996[/C][C]7.05401[/C][/ROW]
[ROW][C]232[/C][C]18.55[/C][C]15.416[/C][C]3.13402[/C][/ROW]
[ROW][C]233[/C][C]19.1[/C][C]18.4469[/C][C]0.653108[/C][/ROW]
[ROW][C]234[/C][C]13.1[/C][C]13.6003[/C][C]-0.500341[/C][/ROW]
[ROW][C]235[/C][C]12.85[/C][C]13.3304[/C][C]-0.480393[/C][/ROW]
[ROW][C]236[/C][C]9.5[/C][C]15.0632[/C][C]-5.56317[/C][/ROW]
[ROW][C]237[/C][C]4.5[/C][C]3.15071[/C][C]1.34929[/C][/ROW]
[ROW][C]238[/C][C]11.85[/C][C]11.8476[/C][C]0.00243667[/C][/ROW]
[ROW][C]239[/C][C]13.6[/C][C]12.5134[/C][C]1.08665[/C][/ROW]
[ROW][C]240[/C][C]11.7[/C][C]11.2703[/C][C]0.429662[/C][/ROW]
[ROW][C]241[/C][C]12.4[/C][C]12.3272[/C][C]0.0727914[/C][/ROW]
[ROW][C]242[/C][C]13.35[/C][C]14.0374[/C][C]-0.687379[/C][/ROW]
[ROW][C]243[/C][C]11.4[/C][C]9.10572[/C][C]2.29428[/C][/ROW]
[ROW][C]244[/C][C]14.9[/C][C]11.1784[/C][C]3.72157[/C][/ROW]
[ROW][C]245[/C][C]19.9[/C][C]20.4129[/C][C]-0.512887[/C][/ROW]
[ROW][C]246[/C][C]11.2[/C][C]10.7359[/C][C]0.464095[/C][/ROW]
[ROW][C]247[/C][C]14.6[/C][C]12.3263[/C][C]2.27374[/C][/ROW]
[ROW][C]248[/C][C]17.6[/C][C]15.286[/C][C]2.31401[/C][/ROW]
[ROW][C]249[/C][C]14.05[/C][C]12.09[/C][C]1.95999[/C][/ROW]
[ROW][C]250[/C][C]16.1[/C][C]15.2829[/C][C]0.817098[/C][/ROW]
[ROW][C]251[/C][C]13.35[/C][C]13.4248[/C][C]-0.0748033[/C][/ROW]
[ROW][C]252[/C][C]11.85[/C][C]12.2869[/C][C]-0.436913[/C][/ROW]
[ROW][C]253[/C][C]11.95[/C][C]10.5697[/C][C]1.38027[/C][/ROW]
[ROW][C]254[/C][C]14.75[/C][C]12.525[/C][C]2.22499[/C][/ROW]
[ROW][C]255[/C][C]15.15[/C][C]15.4199[/C][C]-0.269929[/C][/ROW]
[ROW][C]256[/C][C]13.2[/C][C]10.6915[/C][C]2.50851[/C][/ROW]
[ROW][C]257[/C][C]16.85[/C][C]20.053[/C][C]-3.20304[/C][/ROW]
[ROW][C]258[/C][C]7.85[/C][C]11.7902[/C][C]-3.94016[/C][/ROW]
[ROW][C]259[/C][C]7.7[/C][C]8.95311[/C][C]-1.25311[/C][/ROW]
[ROW][C]260[/C][C]12.6[/C][C]17.6403[/C][C]-5.04026[/C][/ROW]
[ROW][C]261[/C][C]7.85[/C][C]8.10624[/C][C]-0.256236[/C][/ROW]
[ROW][C]262[/C][C]10.95[/C][C]11.2845[/C][C]-0.334483[/C][/ROW]
[ROW][C]263[/C][C]12.35[/C][C]13.805[/C][C]-1.45502[/C][/ROW]
[ROW][C]264[/C][C]9.95[/C][C]7.65572[/C][C]2.29428[/C][/ROW]
[ROW][C]265[/C][C]14.9[/C][C]11.5073[/C][C]3.39266[/C][/ROW]
[ROW][C]266[/C][C]16.65[/C][C]16.0838[/C][C]0.566241[/C][/ROW]
[ROW][C]267[/C][C]13.4[/C][C]10.8561[/C][C]2.54394[/C][/ROW]
[ROW][C]268[/C][C]13.95[/C][C]10.4788[/C][C]3.4712[/C][/ROW]
[ROW][C]269[/C][C]15.7[/C][C]11.5392[/C][C]4.16078[/C][/ROW]
[ROW][C]270[/C][C]16.85[/C][C]17.4599[/C][C]-0.60989[/C][/ROW]
[ROW][C]271[/C][C]10.95[/C][C]7.95529[/C][C]2.99471[/C][/ROW]
[ROW][C]272[/C][C]15.35[/C][C]15.0324[/C][C]0.317632[/C][/ROW]
[ROW][C]273[/C][C]12.2[/C][C]9.97703[/C][C]2.22297[/C][/ROW]
[ROW][C]274[/C][C]15.1[/C][C]11.8049[/C][C]3.29508[/C][/ROW]
[ROW][C]275[/C][C]17.75[/C][C]15.9894[/C][C]1.7606[/C][/ROW]
[ROW][C]276[/C][C]15.2[/C][C]12.2454[/C][C]2.95459[/C][/ROW]
[ROW][C]277[/C][C]14.6[/C][C]11.706[/C][C]2.89397[/C][/ROW]
[ROW][C]278[/C][C]16.65[/C][C]17.8877[/C][C]-1.23775[/C][/ROW]
[ROW][C]279[/C][C]8.1[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&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
112.914.2564-1.35636
212.212.9175-0.717537
312.813.1996-0.399572
47.414.4903-7.0903
56.711.8451-5.14513
612.613.8122-1.21216
714.814.61220.187834
813.313.5632-0.263181
911.115.0285-3.92849
108.212.4666-4.26665
1111.413.0969-1.69688
126.414.5536-8.15361
1310.612.5027-1.9027
141215.0916-3.09159
156.39.81183-3.51183
1611.311.17610.123889
1711.914.8999-2.99994
189.311.9117-2.61173
199.613.5074-3.90745
201012.849-2.84902
216.411.8114-5.41138
2213.812.63661.16343
2310.814.7757-3.97571
2413.815.7691-1.96911
2511.714.0481-2.34807
2610.916.9539-6.05386
2716.115.87350.226478
2813.413.04560.354428
299.914.7329-4.83293
3011.513.6569-2.15695
318.312.1903-3.89033
3211.713.0315-1.33151
33912.6707-3.67065
349.713.9314-4.23143
3510.812.6535-1.85355
3610.312.2278-1.92776
3710.412.79-2.39001
3812.712.60220.0978494
399.313.9851-4.68514
4011.814.1605-2.36045
415.912.2103-6.31035
4211.413.4984-2.09836
431314.4157-1.4157
4410.814.3588-3.55884
4512.312.1050.195011
4611.314.2381-2.93806
4711.812.7385-0.938508
487.913.106-5.20599
4912.711.4031.29702
5012.311.08751.2125
5111.613.6364-2.03636
526.711.6274-4.92741
5310.912.6301-1.73007
5412.113.8478-1.74778
5513.313.4203-0.120317
5610.112.473-2.373
575.713.0852-7.38522
5814.312.09832.20173
5989.5824-1.5824
6013.313.10870.191276
619.315.2089-5.90888
6212.511.97510.524911
637.612.7547-5.15468
6415.915.77570.124263
659.213.543-4.34302
669.111.841-2.74098
6711.115.1481-4.04808
681317.9755-4.97552
6914.513.18921.31077
7012.213.2319-1.03189
7112.314.2665-1.96652
7211.411.9025-0.502464
738.812.5666-3.76657
7414.613.96240.63759
7512.613.3736-0.773603
76NANA-0.447724
771312.77580.224229
7812.614.3173-1.71726
7913.215.4511-2.25111
809.914.8598-4.95979
817.79.07236-1.37236
8210.59.422951.07705
8313.415.6734-2.27336
8410.919.2525-8.35248
854.37.0341-2.7341
8610.313.0169-2.71688
8711.812.7524-0.952363
8811.211.3448-0.14475
8911.415.2584-3.85841
908.68.73923-0.139235
9113.212.55370.646331
9212.620.0749-7.47492
935.610.3721-4.77209
949.913.5072-3.60721
958.813.1092-4.30917
967.710.7205-3.02047
97914.5504-5.55044
987.37.62906-0.329063
9911.49.572091.82791
10013.618.8797-5.27972
1017.99.17775-1.27775
10210.713.3114-2.61141
10310.312.6583-2.35829
1048.312.4952-4.19519
1059.68.679750.920254
10614.217.3529-3.15285
1078.56.243552.25645
10813.520.4717-6.97167
1094.99.10633-4.20633
1106.410.3722-3.97216
1119.610.4706-0.870565
11211.612.448-0.847992
11311.116.6923-5.59227
1144.353.635630.714375
11512.78.120654.57935
11618.113.90834.19165
11717.8517.81130.038698
11816.615.30941.2906
11912.610.73221.86776
12017.113.56423.53576
12119.121.6564-2.5564
12216.113.12982.97021
12313.359.103154.24685
12418.413.43734.96273
12514.716.7208-2.02078
12610.69.639310.96069
12712.69.272713.32729
12816.216.322-0.121963
12913.69.910413.68959
13018.915.91162.98844
13114.111.43422.66579
13214.514.24220.2578
13316.1514.10322.04679
13414.7512.71772.03231
13514.813.99990.800084
13612.4511.82440.625628
13712.657.866464.78354
13817.3519.1907-1.84074
1398.64.965273.63473
14018.416.33242.06762
14116.116.1833-0.0832958
14211.66.622744.97726
14317.7515.73912.01093
14415.2510.91514.33493
14517.6515.31792.33213
14616.3512.92443.42564
14717.6516.97520.67477
14813.611.95741.6426
14914.3511.71892.63111
15014.759.937484.81252
15118.2521.9303-3.68035
1529.97.879572.02043
1531610.91435.08567
15418.2515.30062.94936
15516.8514.16152.68845
15614.614.45460.145403
15713.8510.73333.11668
15818.9515.70793.24209
15915.615.7344-0.134401
16014.8515.4927-0.642745
16111.758.372963.37704
16218.4515.43743.01261
16315.913.67022.22976
16417.110.74626.35381
16516.112.37843.72157
16619.920.1562-0.256236
16710.957.323313.62669
16818.4515.1133.33699
16915.113.69311.4069
1701517.5635-2.56347
17111.358.869222.48078
17215.9511.8074.14301
17318.117.84070.259319
17414.612.4922.10802
17515.413.2922.10802
17615.412.34123.05882
17717.617.7121-0.112132
17813.357.273156.07685
17919.118.00631.09368
18015.3518.2486-2.89863
1817.68.64894-1.04894
18213.413.34170.058308
18313.99.331194.56881
18419.117.01682.08317
18515.2515.5689-0.318899
18612.910.22072.6793
18716.110.43155.66851
18817.3516.75580.59417
18913.1511.81841.33158
19012.1511.11511.03492
19112.613.9207-1.32066
19210.359.148861.20114
19315.417.392-1.99196
1949.63.801415.79859
19518.216.76571.43429
19613.611.38612.21388
19714.8514.2420.607966
19814.7512.82291.92708
19914.110.79253.30754
20014.912.012.89001
20116.2512.32563.92437
20219.2517.49731.75267
20313.613.05250.547519
20413.611.78831.81165
20515.6514.76650.883524
20612.759.623853.12615
20714.616.1788-1.57884
2089.858.755191.09481
20912.657.996144.65386
21019.217.0042.19601
21116.616.9386-0.338646
21211.28.951382.24862
21315.2516.1467-0.896746
21411.910.76781.13219
21513.211.41581.78415
21616.3514.75981.5902
21712.49.724642.67536
21815.8511.27754.57249
21918.1518.6132-0.463201
22011.159.245191.90481
22115.6510.78914.86086
22217.7522.25-4.50003
2237.656.23661.4134
22412.358.564053.78595
22515.611.03634.56372
22619.315.27924.02083
22715.210.65364.54636
22817.113.80513.29486
22915.611.88753.71252
23018.412.75095.64908
23119.0511.9967.05401
23218.5515.4163.13402
23319.118.44690.653108
23413.113.6003-0.500341
23512.8513.3304-0.480393
2369.515.0632-5.56317
2374.53.150711.34929
23811.8511.84760.00243667
23913.612.51341.08665
24011.711.27030.429662
24112.412.32720.0727914
24213.3514.0374-0.687379
24311.49.105722.29428
24414.911.17843.72157
24519.920.4129-0.512887
24611.210.73590.464095
24714.612.32632.27374
24817.615.2862.31401
24914.0512.091.95999
25016.115.28290.817098
25113.3513.4248-0.0748033
25211.8512.2869-0.436913
25311.9510.56971.38027
25414.7512.5252.22499
25515.1515.4199-0.269929
25613.210.69152.50851
25716.8520.053-3.20304
2587.8511.7902-3.94016
2597.78.95311-1.25311
26012.617.6403-5.04026
2617.858.10624-0.256236
26210.9511.2845-0.334483
26312.3513.805-1.45502
2649.957.655722.29428
26514.911.50733.39266
26616.6516.08380.566241
26713.410.85612.54394
26813.9510.47883.4712
26915.711.53924.16078
27016.8517.4599-0.60989
27110.957.955292.99471
27215.3515.03240.317632
27312.29.977032.22297
27415.111.80493.29508
27517.7515.98941.7606
27615.212.24542.95459
27714.611.7062.89397
27816.6517.8877-1.23775
2798.1NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.5849960.8300090.415004
110.4210620.8421240.578938
120.6570320.6859370.342968
130.536250.92750.46375
140.4212730.8425470.578727
150.3189830.6379660.681017
160.2292280.4584570.770772
170.1605650.3211310.839435
180.274260.5485210.72574
190.2776020.5552040.722398
200.2116080.4232160.788392
210.2231510.4463010.776849
220.2665240.5330480.733476
230.2133030.4266060.786697
240.1684290.3368580.831571
250.1299510.2599020.870049
260.1189230.2378470.881077
270.102990.205980.89701
280.08446490.168930.915535
290.08065770.1613150.919342
300.06800830.1360170.931992
310.05224430.1044890.947756
320.03997410.07994820.960026
330.03240790.06481580.967592
340.0312390.0624780.968761
350.02356040.04712090.97644
360.01710130.03420260.982899
370.01647470.03294940.983525
380.01191270.02382530.988087
390.01140650.02281290.988594
400.008222580.01644520.991777
410.01471020.02942040.98529
420.01086080.02172150.989139
430.008779250.01755850.991221
440.007152330.01430470.992848
450.005163980.0103280.994836
460.003905970.007811930.996094
470.003144210.006288410.996856
480.008176030.01635210.991824
490.00977490.01954980.990225
500.008509170.01701830.991491
510.006280450.01256090.99372
520.00931420.01862840.990686
530.007574470.01514890.992426
540.005558810.01111760.994441
550.006354510.0127090.993645
560.004848480.009696970.995152
570.01777540.03555090.982225
580.02829140.05658270.971709
590.0217920.04358390.978208
600.0176580.0353160.982342
610.0272990.05459790.972701
620.02692440.05384870.973076
630.02852160.05704330.971478
640.03482380.06964770.965176
650.03986540.07973080.960135
660.03359910.06719820.966401
670.03415850.0683170.965841
680.04211720.08423450.957883
690.05761020.115220.94239
700.04965870.09931740.950341
710.04518160.09036310.954818
720.03968810.07937620.960312
730.03958780.07917570.960412
740.04058640.08117270.959414
750.03845990.07691970.96154
760.03479040.06958070.96521
770.02909730.05819450.970903
780.02858830.05717660.971412
790.02315280.04630560.976847
800.03163110.06326230.968369
810.02635140.05270280.973649
820.02505640.05011280.974944
830.02081790.04163570.979182
840.08433240.1686650.915668
850.07823650.1564730.921763
860.07074860.1414970.929251
870.05994430.1198890.940056
880.05149030.1029810.94851
890.05383870.1076770.946161
900.05054920.1010980.949451
910.04851570.09703150.951484
920.1181030.2362060.881897
930.1500430.3000870.849957
940.1520530.3041050.847947
950.1766210.3532430.823379
960.1878470.3756950.812153
970.2969570.5939130.703043
980.2779440.5558870.722056
990.2934240.5868480.706576
1000.3763920.7527850.623608
1010.3485310.6970620.651469
1020.3455880.6911760.654412
1030.3534150.706830.646585
1040.4147850.829570.585215
1050.4316170.8632350.568383
1060.4692620.9385230.530738
1070.4982080.9964170.501792
1080.7269340.5461320.273066
1090.7798960.4402080.220104
1100.80890.38220.1911
1110.8087520.3824950.191248
1120.8043420.3913150.195658
1130.8682050.263590.131795
1140.8798840.2402310.120116
1150.949130.1017410.0508703
1160.9731650.05366940.0268347
1170.9744060.05118820.0255941
1180.9751890.04962160.0248108
1190.9794090.04118260.0205913
1200.9885140.02297160.0114858
1210.9907040.0185930.00929649
1220.9935520.01289650.00644827
1230.9969180.006163850.00308193
1240.999080.001840120.000920061
1250.9990340.001932960.000966479
1260.9988760.002248380.00112419
1270.9991110.001778130.000889067
1280.9989160.002167910.00108396
1290.9993750.001249750.000624874
1300.9994390.001121080.000560542
1310.9994590.001081760.000540879
1320.9994650.001069740.000534871
1330.9994470.001106530.000553266
1340.9994370.00112620.0005631
1350.9992680.001464620.000732309
1360.9990590.001881820.000940911
1370.9995330.0009344890.000467245
1380.9994310.001137860.000568931
1390.9995460.0009072930.000453646
1400.9994870.001026780.000513392
1410.9993410.001317390.000658694
1420.9996160.0007676780.000383839
1430.9996120.0007763040.000388152
1440.9997470.000506760.00025338
1450.9997250.000549770.000274885
1460.999740.0005195310.000259765
1470.9996610.000677470.000338735
1480.9995770.0008458780.000422939
1490.999530.000940480.00047024
1500.9996750.0006501650.000325083
1510.9999180.000164428.22098e-05
1520.9998990.0002020860.000101043
1530.9999390.0001210196.05094e-05
1540.9999330.0001330196.65097e-05
1550.999940.0001203226.01611e-05
1560.9999220.0001551277.75634e-05
1570.9999180.000163538.17652e-05
1580.9999190.0001614658.07326e-05
1590.9999070.000185979.29851e-05
1600.999880.0002390910.000119545
1610.9998980.0002047280.000102364
1620.9999070.0001867819.33904e-05
1630.9998890.0002211790.000110589
1640.9999983.44081e-061.72041e-06
1650.9999992.95198e-061.47599e-06
1660.9999984.55857e-062.27928e-06
1670.9999984.20978e-062.10489e-06
1680.9999983.71878e-061.85939e-06
1690.9999975.28623e-062.64311e-06
1700.9999984.55833e-062.27917e-06
1710.9999975.50132e-062.75066e-06
1720.9999984.4058e-062.2029e-06
1730.9999984.32344e-062.16172e-06
1740.9999975.91365e-062.95683e-06
1750.9999968.10815e-064.05408e-06
1760.9999968.74484e-064.37242e-06
1770.9999941.26564e-056.32818e-06
1780.9999976.02504e-063.01252e-06
1790.9999976.3384e-063.1692e-06
1800.9999968.15986e-064.07993e-06
1810.9999968.79708e-064.39854e-06
1820.9999951.04593e-055.22965e-06
1830.9999959.12837e-064.56419e-06
1840.9999941.26503e-056.32513e-06
1850.9999976.65862e-063.32931e-06
1860.9999959.18579e-064.59289e-06
1870.9999984.44045e-062.22023e-06
1880.9999975.63566e-062.81783e-06
1890.9999967.81053e-063.90526e-06
1900.9999941.18701e-055.93505e-06
1910.9999911.71238e-058.5619e-06
1920.9999892.16529e-051.08265e-05
1930.9999892.10898e-051.05449e-05
1940.9999941.10069e-055.50347e-06
1950.9999921.57658e-057.88288e-06
1960.9999911.88497e-059.42486e-06
1970.9999872.64949e-051.32474e-05
1980.9999813.70296e-051.85148e-05
1990.9999823.6062e-051.8031e-05
2000.9999764.74426e-052.37213e-05
2010.9999745.10688e-052.55344e-05
2020.999976.0297e-053.01485e-05
2030.999968.03691e-054.01845e-05
2040.9999430.0001149545.74769e-05
2050.9999120.0001755518.77754e-05
2060.9999280.0001436697.18345e-05
2070.9998940.0002118460.000105923
2080.9998720.0002554830.000127741
2090.9998610.0002784360.000139218
2100.9998070.0003855340.000192767
2110.9997190.0005628860.000281443
2120.9996010.0007978760.000398938
2130.9995510.000898920.00044946
2140.9993460.001307930.000653964
2150.9991260.001747190.000873594
2160.9987440.00251130.00125565
2170.9984480.003104260.00155213
2180.9980850.003829170.00191458
2190.997250.005499550.00274978
2200.9961640.00767260.0038363
2210.9966320.006736720.00336836
2220.9972880.005423280.00271164
2230.9965170.006965660.00348283
2240.9973220.005355130.00267757
2250.997250.005500650.00275032
2260.9988780.002243750.00112187
2270.9993680.001264980.000632492
2280.999350.001300390.000650194
2290.9992530.001493440.000746719
2300.9996660.0006680630.000334032
2310.9998710.0002580480.000129024
2320.9998130.000373980.00018699
2330.9996870.000625910.000312955
2340.9996250.0007509710.000375486
2350.9993840.001232250.000616127
2360.9996290.0007424680.000371234
2370.9995940.0008124650.000406232
2380.9994010.001197540.000598771
2390.9993130.00137320.000686598
2400.9988750.002250460.00112523
2410.9981430.003714780.00185739
2420.997110.005779480.00288974
2430.9958210.008357040.00417852
2440.9938490.01230280.00615142
2450.990380.0192410.00962048
2460.986640.02671930.0133597
2470.9800670.03986530.0199326
2480.9792940.04141160.0207058
2490.9727790.05444220.0272211
2500.9624160.07516860.0375843
2510.9451860.1096280.0548138
2520.9226560.1546880.0773442
2530.8927980.2144030.107202
2540.8565140.2869720.143486
2550.8270740.3458530.172926
2560.7754570.4490850.224543
2570.762990.4740210.23701
2580.8238430.3523130.176157
2590.833110.333780.16689
2600.9988810.002238760.00111938
2610.9971950.005610010.00280501
2620.9983910.003217140.00160857
2630.9996820.0006368340.000318417
2640.9988840.002232910.00111645
2650.9976140.004771320.00238566
2660.9948070.01038540.00519268
2670.998940.002120910.00106046
2680.9935190.0129620.00648098
2690.9821390.03572230.0178611

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.584996 & 0.830009 & 0.415004 \tabularnewline
11 & 0.421062 & 0.842124 & 0.578938 \tabularnewline
12 & 0.657032 & 0.685937 & 0.342968 \tabularnewline
13 & 0.53625 & 0.9275 & 0.46375 \tabularnewline
14 & 0.421273 & 0.842547 & 0.578727 \tabularnewline
15 & 0.318983 & 0.637966 & 0.681017 \tabularnewline
16 & 0.229228 & 0.458457 & 0.770772 \tabularnewline
17 & 0.160565 & 0.321131 & 0.839435 \tabularnewline
18 & 0.27426 & 0.548521 & 0.72574 \tabularnewline
19 & 0.277602 & 0.555204 & 0.722398 \tabularnewline
20 & 0.211608 & 0.423216 & 0.788392 \tabularnewline
21 & 0.223151 & 0.446301 & 0.776849 \tabularnewline
22 & 0.266524 & 0.533048 & 0.733476 \tabularnewline
23 & 0.213303 & 0.426606 & 0.786697 \tabularnewline
24 & 0.168429 & 0.336858 & 0.831571 \tabularnewline
25 & 0.129951 & 0.259902 & 0.870049 \tabularnewline
26 & 0.118923 & 0.237847 & 0.881077 \tabularnewline
27 & 0.10299 & 0.20598 & 0.89701 \tabularnewline
28 & 0.0844649 & 0.16893 & 0.915535 \tabularnewline
29 & 0.0806577 & 0.161315 & 0.919342 \tabularnewline
30 & 0.0680083 & 0.136017 & 0.931992 \tabularnewline
31 & 0.0522443 & 0.104489 & 0.947756 \tabularnewline
32 & 0.0399741 & 0.0799482 & 0.960026 \tabularnewline
33 & 0.0324079 & 0.0648158 & 0.967592 \tabularnewline
34 & 0.031239 & 0.062478 & 0.968761 \tabularnewline
35 & 0.0235604 & 0.0471209 & 0.97644 \tabularnewline
36 & 0.0171013 & 0.0342026 & 0.982899 \tabularnewline
37 & 0.0164747 & 0.0329494 & 0.983525 \tabularnewline
38 & 0.0119127 & 0.0238253 & 0.988087 \tabularnewline
39 & 0.0114065 & 0.0228129 & 0.988594 \tabularnewline
40 & 0.00822258 & 0.0164452 & 0.991777 \tabularnewline
41 & 0.0147102 & 0.0294204 & 0.98529 \tabularnewline
42 & 0.0108608 & 0.0217215 & 0.989139 \tabularnewline
43 & 0.00877925 & 0.0175585 & 0.991221 \tabularnewline
44 & 0.00715233 & 0.0143047 & 0.992848 \tabularnewline
45 & 0.00516398 & 0.010328 & 0.994836 \tabularnewline
46 & 0.00390597 & 0.00781193 & 0.996094 \tabularnewline
47 & 0.00314421 & 0.00628841 & 0.996856 \tabularnewline
48 & 0.00817603 & 0.0163521 & 0.991824 \tabularnewline
49 & 0.0097749 & 0.0195498 & 0.990225 \tabularnewline
50 & 0.00850917 & 0.0170183 & 0.991491 \tabularnewline
51 & 0.00628045 & 0.0125609 & 0.99372 \tabularnewline
52 & 0.0093142 & 0.0186284 & 0.990686 \tabularnewline
53 & 0.00757447 & 0.0151489 & 0.992426 \tabularnewline
54 & 0.00555881 & 0.0111176 & 0.994441 \tabularnewline
55 & 0.00635451 & 0.012709 & 0.993645 \tabularnewline
56 & 0.00484848 & 0.00969697 & 0.995152 \tabularnewline
57 & 0.0177754 & 0.0355509 & 0.982225 \tabularnewline
58 & 0.0282914 & 0.0565827 & 0.971709 \tabularnewline
59 & 0.021792 & 0.0435839 & 0.978208 \tabularnewline
60 & 0.017658 & 0.035316 & 0.982342 \tabularnewline
61 & 0.027299 & 0.0545979 & 0.972701 \tabularnewline
62 & 0.0269244 & 0.0538487 & 0.973076 \tabularnewline
63 & 0.0285216 & 0.0570433 & 0.971478 \tabularnewline
64 & 0.0348238 & 0.0696477 & 0.965176 \tabularnewline
65 & 0.0398654 & 0.0797308 & 0.960135 \tabularnewline
66 & 0.0335991 & 0.0671982 & 0.966401 \tabularnewline
67 & 0.0341585 & 0.068317 & 0.965841 \tabularnewline
68 & 0.0421172 & 0.0842345 & 0.957883 \tabularnewline
69 & 0.0576102 & 0.11522 & 0.94239 \tabularnewline
70 & 0.0496587 & 0.0993174 & 0.950341 \tabularnewline
71 & 0.0451816 & 0.0903631 & 0.954818 \tabularnewline
72 & 0.0396881 & 0.0793762 & 0.960312 \tabularnewline
73 & 0.0395878 & 0.0791757 & 0.960412 \tabularnewline
74 & 0.0405864 & 0.0811727 & 0.959414 \tabularnewline
75 & 0.0384599 & 0.0769197 & 0.96154 \tabularnewline
76 & 0.0347904 & 0.0695807 & 0.96521 \tabularnewline
77 & 0.0290973 & 0.0581945 & 0.970903 \tabularnewline
78 & 0.0285883 & 0.0571766 & 0.971412 \tabularnewline
79 & 0.0231528 & 0.0463056 & 0.976847 \tabularnewline
80 & 0.0316311 & 0.0632623 & 0.968369 \tabularnewline
81 & 0.0263514 & 0.0527028 & 0.973649 \tabularnewline
82 & 0.0250564 & 0.0501128 & 0.974944 \tabularnewline
83 & 0.0208179 & 0.0416357 & 0.979182 \tabularnewline
84 & 0.0843324 & 0.168665 & 0.915668 \tabularnewline
85 & 0.0782365 & 0.156473 & 0.921763 \tabularnewline
86 & 0.0707486 & 0.141497 & 0.929251 \tabularnewline
87 & 0.0599443 & 0.119889 & 0.940056 \tabularnewline
88 & 0.0514903 & 0.102981 & 0.94851 \tabularnewline
89 & 0.0538387 & 0.107677 & 0.946161 \tabularnewline
90 & 0.0505492 & 0.101098 & 0.949451 \tabularnewline
91 & 0.0485157 & 0.0970315 & 0.951484 \tabularnewline
92 & 0.118103 & 0.236206 & 0.881897 \tabularnewline
93 & 0.150043 & 0.300087 & 0.849957 \tabularnewline
94 & 0.152053 & 0.304105 & 0.847947 \tabularnewline
95 & 0.176621 & 0.353243 & 0.823379 \tabularnewline
96 & 0.187847 & 0.375695 & 0.812153 \tabularnewline
97 & 0.296957 & 0.593913 & 0.703043 \tabularnewline
98 & 0.277944 & 0.555887 & 0.722056 \tabularnewline
99 & 0.293424 & 0.586848 & 0.706576 \tabularnewline
100 & 0.376392 & 0.752785 & 0.623608 \tabularnewline
101 & 0.348531 & 0.697062 & 0.651469 \tabularnewline
102 & 0.345588 & 0.691176 & 0.654412 \tabularnewline
103 & 0.353415 & 0.70683 & 0.646585 \tabularnewline
104 & 0.414785 & 0.82957 & 0.585215 \tabularnewline
105 & 0.431617 & 0.863235 & 0.568383 \tabularnewline
106 & 0.469262 & 0.938523 & 0.530738 \tabularnewline
107 & 0.498208 & 0.996417 & 0.501792 \tabularnewline
108 & 0.726934 & 0.546132 & 0.273066 \tabularnewline
109 & 0.779896 & 0.440208 & 0.220104 \tabularnewline
110 & 0.8089 & 0.3822 & 0.1911 \tabularnewline
111 & 0.808752 & 0.382495 & 0.191248 \tabularnewline
112 & 0.804342 & 0.391315 & 0.195658 \tabularnewline
113 & 0.868205 & 0.26359 & 0.131795 \tabularnewline
114 & 0.879884 & 0.240231 & 0.120116 \tabularnewline
115 & 0.94913 & 0.101741 & 0.0508703 \tabularnewline
116 & 0.973165 & 0.0536694 & 0.0268347 \tabularnewline
117 & 0.974406 & 0.0511882 & 0.0255941 \tabularnewline
118 & 0.975189 & 0.0496216 & 0.0248108 \tabularnewline
119 & 0.979409 & 0.0411826 & 0.0205913 \tabularnewline
120 & 0.988514 & 0.0229716 & 0.0114858 \tabularnewline
121 & 0.990704 & 0.018593 & 0.00929649 \tabularnewline
122 & 0.993552 & 0.0128965 & 0.00644827 \tabularnewline
123 & 0.996918 & 0.00616385 & 0.00308193 \tabularnewline
124 & 0.99908 & 0.00184012 & 0.000920061 \tabularnewline
125 & 0.999034 & 0.00193296 & 0.000966479 \tabularnewline
126 & 0.998876 & 0.00224838 & 0.00112419 \tabularnewline
127 & 0.999111 & 0.00177813 & 0.000889067 \tabularnewline
128 & 0.998916 & 0.00216791 & 0.00108396 \tabularnewline
129 & 0.999375 & 0.00124975 & 0.000624874 \tabularnewline
130 & 0.999439 & 0.00112108 & 0.000560542 \tabularnewline
131 & 0.999459 & 0.00108176 & 0.000540879 \tabularnewline
132 & 0.999465 & 0.00106974 & 0.000534871 \tabularnewline
133 & 0.999447 & 0.00110653 & 0.000553266 \tabularnewline
134 & 0.999437 & 0.0011262 & 0.0005631 \tabularnewline
135 & 0.999268 & 0.00146462 & 0.000732309 \tabularnewline
136 & 0.999059 & 0.00188182 & 0.000940911 \tabularnewline
137 & 0.999533 & 0.000934489 & 0.000467245 \tabularnewline
138 & 0.999431 & 0.00113786 & 0.000568931 \tabularnewline
139 & 0.999546 & 0.000907293 & 0.000453646 \tabularnewline
140 & 0.999487 & 0.00102678 & 0.000513392 \tabularnewline
141 & 0.999341 & 0.00131739 & 0.000658694 \tabularnewline
142 & 0.999616 & 0.000767678 & 0.000383839 \tabularnewline
143 & 0.999612 & 0.000776304 & 0.000388152 \tabularnewline
144 & 0.999747 & 0.00050676 & 0.00025338 \tabularnewline
145 & 0.999725 & 0.00054977 & 0.000274885 \tabularnewline
146 & 0.99974 & 0.000519531 & 0.000259765 \tabularnewline
147 & 0.999661 & 0.00067747 & 0.000338735 \tabularnewline
148 & 0.999577 & 0.000845878 & 0.000422939 \tabularnewline
149 & 0.99953 & 0.00094048 & 0.00047024 \tabularnewline
150 & 0.999675 & 0.000650165 & 0.000325083 \tabularnewline
151 & 0.999918 & 0.00016442 & 8.22098e-05 \tabularnewline
152 & 0.999899 & 0.000202086 & 0.000101043 \tabularnewline
153 & 0.999939 & 0.000121019 & 6.05094e-05 \tabularnewline
154 & 0.999933 & 0.000133019 & 6.65097e-05 \tabularnewline
155 & 0.99994 & 0.000120322 & 6.01611e-05 \tabularnewline
156 & 0.999922 & 0.000155127 & 7.75634e-05 \tabularnewline
157 & 0.999918 & 0.00016353 & 8.17652e-05 \tabularnewline
158 & 0.999919 & 0.000161465 & 8.07326e-05 \tabularnewline
159 & 0.999907 & 0.00018597 & 9.29851e-05 \tabularnewline
160 & 0.99988 & 0.000239091 & 0.000119545 \tabularnewline
161 & 0.999898 & 0.000204728 & 0.000102364 \tabularnewline
162 & 0.999907 & 0.000186781 & 9.33904e-05 \tabularnewline
163 & 0.999889 & 0.000221179 & 0.000110589 \tabularnewline
164 & 0.999998 & 3.44081e-06 & 1.72041e-06 \tabularnewline
165 & 0.999999 & 2.95198e-06 & 1.47599e-06 \tabularnewline
166 & 0.999998 & 4.55857e-06 & 2.27928e-06 \tabularnewline
167 & 0.999998 & 4.20978e-06 & 2.10489e-06 \tabularnewline
168 & 0.999998 & 3.71878e-06 & 1.85939e-06 \tabularnewline
169 & 0.999997 & 5.28623e-06 & 2.64311e-06 \tabularnewline
170 & 0.999998 & 4.55833e-06 & 2.27917e-06 \tabularnewline
171 & 0.999997 & 5.50132e-06 & 2.75066e-06 \tabularnewline
172 & 0.999998 & 4.4058e-06 & 2.2029e-06 \tabularnewline
173 & 0.999998 & 4.32344e-06 & 2.16172e-06 \tabularnewline
174 & 0.999997 & 5.91365e-06 & 2.95683e-06 \tabularnewline
175 & 0.999996 & 8.10815e-06 & 4.05408e-06 \tabularnewline
176 & 0.999996 & 8.74484e-06 & 4.37242e-06 \tabularnewline
177 & 0.999994 & 1.26564e-05 & 6.32818e-06 \tabularnewline
178 & 0.999997 & 6.02504e-06 & 3.01252e-06 \tabularnewline
179 & 0.999997 & 6.3384e-06 & 3.1692e-06 \tabularnewline
180 & 0.999996 & 8.15986e-06 & 4.07993e-06 \tabularnewline
181 & 0.999996 & 8.79708e-06 & 4.39854e-06 \tabularnewline
182 & 0.999995 & 1.04593e-05 & 5.22965e-06 \tabularnewline
183 & 0.999995 & 9.12837e-06 & 4.56419e-06 \tabularnewline
184 & 0.999994 & 1.26503e-05 & 6.32513e-06 \tabularnewline
185 & 0.999997 & 6.65862e-06 & 3.32931e-06 \tabularnewline
186 & 0.999995 & 9.18579e-06 & 4.59289e-06 \tabularnewline
187 & 0.999998 & 4.44045e-06 & 2.22023e-06 \tabularnewline
188 & 0.999997 & 5.63566e-06 & 2.81783e-06 \tabularnewline
189 & 0.999996 & 7.81053e-06 & 3.90526e-06 \tabularnewline
190 & 0.999994 & 1.18701e-05 & 5.93505e-06 \tabularnewline
191 & 0.999991 & 1.71238e-05 & 8.5619e-06 \tabularnewline
192 & 0.999989 & 2.16529e-05 & 1.08265e-05 \tabularnewline
193 & 0.999989 & 2.10898e-05 & 1.05449e-05 \tabularnewline
194 & 0.999994 & 1.10069e-05 & 5.50347e-06 \tabularnewline
195 & 0.999992 & 1.57658e-05 & 7.88288e-06 \tabularnewline
196 & 0.999991 & 1.88497e-05 & 9.42486e-06 \tabularnewline
197 & 0.999987 & 2.64949e-05 & 1.32474e-05 \tabularnewline
198 & 0.999981 & 3.70296e-05 & 1.85148e-05 \tabularnewline
199 & 0.999982 & 3.6062e-05 & 1.8031e-05 \tabularnewline
200 & 0.999976 & 4.74426e-05 & 2.37213e-05 \tabularnewline
201 & 0.999974 & 5.10688e-05 & 2.55344e-05 \tabularnewline
202 & 0.99997 & 6.0297e-05 & 3.01485e-05 \tabularnewline
203 & 0.99996 & 8.03691e-05 & 4.01845e-05 \tabularnewline
204 & 0.999943 & 0.000114954 & 5.74769e-05 \tabularnewline
205 & 0.999912 & 0.000175551 & 8.77754e-05 \tabularnewline
206 & 0.999928 & 0.000143669 & 7.18345e-05 \tabularnewline
207 & 0.999894 & 0.000211846 & 0.000105923 \tabularnewline
208 & 0.999872 & 0.000255483 & 0.000127741 \tabularnewline
209 & 0.999861 & 0.000278436 & 0.000139218 \tabularnewline
210 & 0.999807 & 0.000385534 & 0.000192767 \tabularnewline
211 & 0.999719 & 0.000562886 & 0.000281443 \tabularnewline
212 & 0.999601 & 0.000797876 & 0.000398938 \tabularnewline
213 & 0.999551 & 0.00089892 & 0.00044946 \tabularnewline
214 & 0.999346 & 0.00130793 & 0.000653964 \tabularnewline
215 & 0.999126 & 0.00174719 & 0.000873594 \tabularnewline
216 & 0.998744 & 0.0025113 & 0.00125565 \tabularnewline
217 & 0.998448 & 0.00310426 & 0.00155213 \tabularnewline
218 & 0.998085 & 0.00382917 & 0.00191458 \tabularnewline
219 & 0.99725 & 0.00549955 & 0.00274978 \tabularnewline
220 & 0.996164 & 0.0076726 & 0.0038363 \tabularnewline
221 & 0.996632 & 0.00673672 & 0.00336836 \tabularnewline
222 & 0.997288 & 0.00542328 & 0.00271164 \tabularnewline
223 & 0.996517 & 0.00696566 & 0.00348283 \tabularnewline
224 & 0.997322 & 0.00535513 & 0.00267757 \tabularnewline
225 & 0.99725 & 0.00550065 & 0.00275032 \tabularnewline
226 & 0.998878 & 0.00224375 & 0.00112187 \tabularnewline
227 & 0.999368 & 0.00126498 & 0.000632492 \tabularnewline
228 & 0.99935 & 0.00130039 & 0.000650194 \tabularnewline
229 & 0.999253 & 0.00149344 & 0.000746719 \tabularnewline
230 & 0.999666 & 0.000668063 & 0.000334032 \tabularnewline
231 & 0.999871 & 0.000258048 & 0.000129024 \tabularnewline
232 & 0.999813 & 0.00037398 & 0.00018699 \tabularnewline
233 & 0.999687 & 0.00062591 & 0.000312955 \tabularnewline
234 & 0.999625 & 0.000750971 & 0.000375486 \tabularnewline
235 & 0.999384 & 0.00123225 & 0.000616127 \tabularnewline
236 & 0.999629 & 0.000742468 & 0.000371234 \tabularnewline
237 & 0.999594 & 0.000812465 & 0.000406232 \tabularnewline
238 & 0.999401 & 0.00119754 & 0.000598771 \tabularnewline
239 & 0.999313 & 0.0013732 & 0.000686598 \tabularnewline
240 & 0.998875 & 0.00225046 & 0.00112523 \tabularnewline
241 & 0.998143 & 0.00371478 & 0.00185739 \tabularnewline
242 & 0.99711 & 0.00577948 & 0.00288974 \tabularnewline
243 & 0.995821 & 0.00835704 & 0.00417852 \tabularnewline
244 & 0.993849 & 0.0123028 & 0.00615142 \tabularnewline
245 & 0.99038 & 0.019241 & 0.00962048 \tabularnewline
246 & 0.98664 & 0.0267193 & 0.0133597 \tabularnewline
247 & 0.980067 & 0.0398653 & 0.0199326 \tabularnewline
248 & 0.979294 & 0.0414116 & 0.0207058 \tabularnewline
249 & 0.972779 & 0.0544422 & 0.0272211 \tabularnewline
250 & 0.962416 & 0.0751686 & 0.0375843 \tabularnewline
251 & 0.945186 & 0.109628 & 0.0548138 \tabularnewline
252 & 0.922656 & 0.154688 & 0.0773442 \tabularnewline
253 & 0.892798 & 0.214403 & 0.107202 \tabularnewline
254 & 0.856514 & 0.286972 & 0.143486 \tabularnewline
255 & 0.827074 & 0.345853 & 0.172926 \tabularnewline
256 & 0.775457 & 0.449085 & 0.224543 \tabularnewline
257 & 0.76299 & 0.474021 & 0.23701 \tabularnewline
258 & 0.823843 & 0.352313 & 0.176157 \tabularnewline
259 & 0.83311 & 0.33378 & 0.16689 \tabularnewline
260 & 0.998881 & 0.00223876 & 0.00111938 \tabularnewline
261 & 0.997195 & 0.00561001 & 0.00280501 \tabularnewline
262 & 0.998391 & 0.00321714 & 0.00160857 \tabularnewline
263 & 0.999682 & 0.000636834 & 0.000318417 \tabularnewline
264 & 0.998884 & 0.00223291 & 0.00111645 \tabularnewline
265 & 0.997614 & 0.00477132 & 0.00238566 \tabularnewline
266 & 0.994807 & 0.0103854 & 0.00519268 \tabularnewline
267 & 0.99894 & 0.00212091 & 0.00106046 \tabularnewline
268 & 0.993519 & 0.012962 & 0.00648098 \tabularnewline
269 & 0.982139 & 0.0357223 & 0.0178611 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&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]10[/C][C]0.584996[/C][C]0.830009[/C][C]0.415004[/C][/ROW]
[ROW][C]11[/C][C]0.421062[/C][C]0.842124[/C][C]0.578938[/C][/ROW]
[ROW][C]12[/C][C]0.657032[/C][C]0.685937[/C][C]0.342968[/C][/ROW]
[ROW][C]13[/C][C]0.53625[/C][C]0.9275[/C][C]0.46375[/C][/ROW]
[ROW][C]14[/C][C]0.421273[/C][C]0.842547[/C][C]0.578727[/C][/ROW]
[ROW][C]15[/C][C]0.318983[/C][C]0.637966[/C][C]0.681017[/C][/ROW]
[ROW][C]16[/C][C]0.229228[/C][C]0.458457[/C][C]0.770772[/C][/ROW]
[ROW][C]17[/C][C]0.160565[/C][C]0.321131[/C][C]0.839435[/C][/ROW]
[ROW][C]18[/C][C]0.27426[/C][C]0.548521[/C][C]0.72574[/C][/ROW]
[ROW][C]19[/C][C]0.277602[/C][C]0.555204[/C][C]0.722398[/C][/ROW]
[ROW][C]20[/C][C]0.211608[/C][C]0.423216[/C][C]0.788392[/C][/ROW]
[ROW][C]21[/C][C]0.223151[/C][C]0.446301[/C][C]0.776849[/C][/ROW]
[ROW][C]22[/C][C]0.266524[/C][C]0.533048[/C][C]0.733476[/C][/ROW]
[ROW][C]23[/C][C]0.213303[/C][C]0.426606[/C][C]0.786697[/C][/ROW]
[ROW][C]24[/C][C]0.168429[/C][C]0.336858[/C][C]0.831571[/C][/ROW]
[ROW][C]25[/C][C]0.129951[/C][C]0.259902[/C][C]0.870049[/C][/ROW]
[ROW][C]26[/C][C]0.118923[/C][C]0.237847[/C][C]0.881077[/C][/ROW]
[ROW][C]27[/C][C]0.10299[/C][C]0.20598[/C][C]0.89701[/C][/ROW]
[ROW][C]28[/C][C]0.0844649[/C][C]0.16893[/C][C]0.915535[/C][/ROW]
[ROW][C]29[/C][C]0.0806577[/C][C]0.161315[/C][C]0.919342[/C][/ROW]
[ROW][C]30[/C][C]0.0680083[/C][C]0.136017[/C][C]0.931992[/C][/ROW]
[ROW][C]31[/C][C]0.0522443[/C][C]0.104489[/C][C]0.947756[/C][/ROW]
[ROW][C]32[/C][C]0.0399741[/C][C]0.0799482[/C][C]0.960026[/C][/ROW]
[ROW][C]33[/C][C]0.0324079[/C][C]0.0648158[/C][C]0.967592[/C][/ROW]
[ROW][C]34[/C][C]0.031239[/C][C]0.062478[/C][C]0.968761[/C][/ROW]
[ROW][C]35[/C][C]0.0235604[/C][C]0.0471209[/C][C]0.97644[/C][/ROW]
[ROW][C]36[/C][C]0.0171013[/C][C]0.0342026[/C][C]0.982899[/C][/ROW]
[ROW][C]37[/C][C]0.0164747[/C][C]0.0329494[/C][C]0.983525[/C][/ROW]
[ROW][C]38[/C][C]0.0119127[/C][C]0.0238253[/C][C]0.988087[/C][/ROW]
[ROW][C]39[/C][C]0.0114065[/C][C]0.0228129[/C][C]0.988594[/C][/ROW]
[ROW][C]40[/C][C]0.00822258[/C][C]0.0164452[/C][C]0.991777[/C][/ROW]
[ROW][C]41[/C][C]0.0147102[/C][C]0.0294204[/C][C]0.98529[/C][/ROW]
[ROW][C]42[/C][C]0.0108608[/C][C]0.0217215[/C][C]0.989139[/C][/ROW]
[ROW][C]43[/C][C]0.00877925[/C][C]0.0175585[/C][C]0.991221[/C][/ROW]
[ROW][C]44[/C][C]0.00715233[/C][C]0.0143047[/C][C]0.992848[/C][/ROW]
[ROW][C]45[/C][C]0.00516398[/C][C]0.010328[/C][C]0.994836[/C][/ROW]
[ROW][C]46[/C][C]0.00390597[/C][C]0.00781193[/C][C]0.996094[/C][/ROW]
[ROW][C]47[/C][C]0.00314421[/C][C]0.00628841[/C][C]0.996856[/C][/ROW]
[ROW][C]48[/C][C]0.00817603[/C][C]0.0163521[/C][C]0.991824[/C][/ROW]
[ROW][C]49[/C][C]0.0097749[/C][C]0.0195498[/C][C]0.990225[/C][/ROW]
[ROW][C]50[/C][C]0.00850917[/C][C]0.0170183[/C][C]0.991491[/C][/ROW]
[ROW][C]51[/C][C]0.00628045[/C][C]0.0125609[/C][C]0.99372[/C][/ROW]
[ROW][C]52[/C][C]0.0093142[/C][C]0.0186284[/C][C]0.990686[/C][/ROW]
[ROW][C]53[/C][C]0.00757447[/C][C]0.0151489[/C][C]0.992426[/C][/ROW]
[ROW][C]54[/C][C]0.00555881[/C][C]0.0111176[/C][C]0.994441[/C][/ROW]
[ROW][C]55[/C][C]0.00635451[/C][C]0.012709[/C][C]0.993645[/C][/ROW]
[ROW][C]56[/C][C]0.00484848[/C][C]0.00969697[/C][C]0.995152[/C][/ROW]
[ROW][C]57[/C][C]0.0177754[/C][C]0.0355509[/C][C]0.982225[/C][/ROW]
[ROW][C]58[/C][C]0.0282914[/C][C]0.0565827[/C][C]0.971709[/C][/ROW]
[ROW][C]59[/C][C]0.021792[/C][C]0.0435839[/C][C]0.978208[/C][/ROW]
[ROW][C]60[/C][C]0.017658[/C][C]0.035316[/C][C]0.982342[/C][/ROW]
[ROW][C]61[/C][C]0.027299[/C][C]0.0545979[/C][C]0.972701[/C][/ROW]
[ROW][C]62[/C][C]0.0269244[/C][C]0.0538487[/C][C]0.973076[/C][/ROW]
[ROW][C]63[/C][C]0.0285216[/C][C]0.0570433[/C][C]0.971478[/C][/ROW]
[ROW][C]64[/C][C]0.0348238[/C][C]0.0696477[/C][C]0.965176[/C][/ROW]
[ROW][C]65[/C][C]0.0398654[/C][C]0.0797308[/C][C]0.960135[/C][/ROW]
[ROW][C]66[/C][C]0.0335991[/C][C]0.0671982[/C][C]0.966401[/C][/ROW]
[ROW][C]67[/C][C]0.0341585[/C][C]0.068317[/C][C]0.965841[/C][/ROW]
[ROW][C]68[/C][C]0.0421172[/C][C]0.0842345[/C][C]0.957883[/C][/ROW]
[ROW][C]69[/C][C]0.0576102[/C][C]0.11522[/C][C]0.94239[/C][/ROW]
[ROW][C]70[/C][C]0.0496587[/C][C]0.0993174[/C][C]0.950341[/C][/ROW]
[ROW][C]71[/C][C]0.0451816[/C][C]0.0903631[/C][C]0.954818[/C][/ROW]
[ROW][C]72[/C][C]0.0396881[/C][C]0.0793762[/C][C]0.960312[/C][/ROW]
[ROW][C]73[/C][C]0.0395878[/C][C]0.0791757[/C][C]0.960412[/C][/ROW]
[ROW][C]74[/C][C]0.0405864[/C][C]0.0811727[/C][C]0.959414[/C][/ROW]
[ROW][C]75[/C][C]0.0384599[/C][C]0.0769197[/C][C]0.96154[/C][/ROW]
[ROW][C]76[/C][C]0.0347904[/C][C]0.0695807[/C][C]0.96521[/C][/ROW]
[ROW][C]77[/C][C]0.0290973[/C][C]0.0581945[/C][C]0.970903[/C][/ROW]
[ROW][C]78[/C][C]0.0285883[/C][C]0.0571766[/C][C]0.971412[/C][/ROW]
[ROW][C]79[/C][C]0.0231528[/C][C]0.0463056[/C][C]0.976847[/C][/ROW]
[ROW][C]80[/C][C]0.0316311[/C][C]0.0632623[/C][C]0.968369[/C][/ROW]
[ROW][C]81[/C][C]0.0263514[/C][C]0.0527028[/C][C]0.973649[/C][/ROW]
[ROW][C]82[/C][C]0.0250564[/C][C]0.0501128[/C][C]0.974944[/C][/ROW]
[ROW][C]83[/C][C]0.0208179[/C][C]0.0416357[/C][C]0.979182[/C][/ROW]
[ROW][C]84[/C][C]0.0843324[/C][C]0.168665[/C][C]0.915668[/C][/ROW]
[ROW][C]85[/C][C]0.0782365[/C][C]0.156473[/C][C]0.921763[/C][/ROW]
[ROW][C]86[/C][C]0.0707486[/C][C]0.141497[/C][C]0.929251[/C][/ROW]
[ROW][C]87[/C][C]0.0599443[/C][C]0.119889[/C][C]0.940056[/C][/ROW]
[ROW][C]88[/C][C]0.0514903[/C][C]0.102981[/C][C]0.94851[/C][/ROW]
[ROW][C]89[/C][C]0.0538387[/C][C]0.107677[/C][C]0.946161[/C][/ROW]
[ROW][C]90[/C][C]0.0505492[/C][C]0.101098[/C][C]0.949451[/C][/ROW]
[ROW][C]91[/C][C]0.0485157[/C][C]0.0970315[/C][C]0.951484[/C][/ROW]
[ROW][C]92[/C][C]0.118103[/C][C]0.236206[/C][C]0.881897[/C][/ROW]
[ROW][C]93[/C][C]0.150043[/C][C]0.300087[/C][C]0.849957[/C][/ROW]
[ROW][C]94[/C][C]0.152053[/C][C]0.304105[/C][C]0.847947[/C][/ROW]
[ROW][C]95[/C][C]0.176621[/C][C]0.353243[/C][C]0.823379[/C][/ROW]
[ROW][C]96[/C][C]0.187847[/C][C]0.375695[/C][C]0.812153[/C][/ROW]
[ROW][C]97[/C][C]0.296957[/C][C]0.593913[/C][C]0.703043[/C][/ROW]
[ROW][C]98[/C][C]0.277944[/C][C]0.555887[/C][C]0.722056[/C][/ROW]
[ROW][C]99[/C][C]0.293424[/C][C]0.586848[/C][C]0.706576[/C][/ROW]
[ROW][C]100[/C][C]0.376392[/C][C]0.752785[/C][C]0.623608[/C][/ROW]
[ROW][C]101[/C][C]0.348531[/C][C]0.697062[/C][C]0.651469[/C][/ROW]
[ROW][C]102[/C][C]0.345588[/C][C]0.691176[/C][C]0.654412[/C][/ROW]
[ROW][C]103[/C][C]0.353415[/C][C]0.70683[/C][C]0.646585[/C][/ROW]
[ROW][C]104[/C][C]0.414785[/C][C]0.82957[/C][C]0.585215[/C][/ROW]
[ROW][C]105[/C][C]0.431617[/C][C]0.863235[/C][C]0.568383[/C][/ROW]
[ROW][C]106[/C][C]0.469262[/C][C]0.938523[/C][C]0.530738[/C][/ROW]
[ROW][C]107[/C][C]0.498208[/C][C]0.996417[/C][C]0.501792[/C][/ROW]
[ROW][C]108[/C][C]0.726934[/C][C]0.546132[/C][C]0.273066[/C][/ROW]
[ROW][C]109[/C][C]0.779896[/C][C]0.440208[/C][C]0.220104[/C][/ROW]
[ROW][C]110[/C][C]0.8089[/C][C]0.3822[/C][C]0.1911[/C][/ROW]
[ROW][C]111[/C][C]0.808752[/C][C]0.382495[/C][C]0.191248[/C][/ROW]
[ROW][C]112[/C][C]0.804342[/C][C]0.391315[/C][C]0.195658[/C][/ROW]
[ROW][C]113[/C][C]0.868205[/C][C]0.26359[/C][C]0.131795[/C][/ROW]
[ROW][C]114[/C][C]0.879884[/C][C]0.240231[/C][C]0.120116[/C][/ROW]
[ROW][C]115[/C][C]0.94913[/C][C]0.101741[/C][C]0.0508703[/C][/ROW]
[ROW][C]116[/C][C]0.973165[/C][C]0.0536694[/C][C]0.0268347[/C][/ROW]
[ROW][C]117[/C][C]0.974406[/C][C]0.0511882[/C][C]0.0255941[/C][/ROW]
[ROW][C]118[/C][C]0.975189[/C][C]0.0496216[/C][C]0.0248108[/C][/ROW]
[ROW][C]119[/C][C]0.979409[/C][C]0.0411826[/C][C]0.0205913[/C][/ROW]
[ROW][C]120[/C][C]0.988514[/C][C]0.0229716[/C][C]0.0114858[/C][/ROW]
[ROW][C]121[/C][C]0.990704[/C][C]0.018593[/C][C]0.00929649[/C][/ROW]
[ROW][C]122[/C][C]0.993552[/C][C]0.0128965[/C][C]0.00644827[/C][/ROW]
[ROW][C]123[/C][C]0.996918[/C][C]0.00616385[/C][C]0.00308193[/C][/ROW]
[ROW][C]124[/C][C]0.99908[/C][C]0.00184012[/C][C]0.000920061[/C][/ROW]
[ROW][C]125[/C][C]0.999034[/C][C]0.00193296[/C][C]0.000966479[/C][/ROW]
[ROW][C]126[/C][C]0.998876[/C][C]0.00224838[/C][C]0.00112419[/C][/ROW]
[ROW][C]127[/C][C]0.999111[/C][C]0.00177813[/C][C]0.000889067[/C][/ROW]
[ROW][C]128[/C][C]0.998916[/C][C]0.00216791[/C][C]0.00108396[/C][/ROW]
[ROW][C]129[/C][C]0.999375[/C][C]0.00124975[/C][C]0.000624874[/C][/ROW]
[ROW][C]130[/C][C]0.999439[/C][C]0.00112108[/C][C]0.000560542[/C][/ROW]
[ROW][C]131[/C][C]0.999459[/C][C]0.00108176[/C][C]0.000540879[/C][/ROW]
[ROW][C]132[/C][C]0.999465[/C][C]0.00106974[/C][C]0.000534871[/C][/ROW]
[ROW][C]133[/C][C]0.999447[/C][C]0.00110653[/C][C]0.000553266[/C][/ROW]
[ROW][C]134[/C][C]0.999437[/C][C]0.0011262[/C][C]0.0005631[/C][/ROW]
[ROW][C]135[/C][C]0.999268[/C][C]0.00146462[/C][C]0.000732309[/C][/ROW]
[ROW][C]136[/C][C]0.999059[/C][C]0.00188182[/C][C]0.000940911[/C][/ROW]
[ROW][C]137[/C][C]0.999533[/C][C]0.000934489[/C][C]0.000467245[/C][/ROW]
[ROW][C]138[/C][C]0.999431[/C][C]0.00113786[/C][C]0.000568931[/C][/ROW]
[ROW][C]139[/C][C]0.999546[/C][C]0.000907293[/C][C]0.000453646[/C][/ROW]
[ROW][C]140[/C][C]0.999487[/C][C]0.00102678[/C][C]0.000513392[/C][/ROW]
[ROW][C]141[/C][C]0.999341[/C][C]0.00131739[/C][C]0.000658694[/C][/ROW]
[ROW][C]142[/C][C]0.999616[/C][C]0.000767678[/C][C]0.000383839[/C][/ROW]
[ROW][C]143[/C][C]0.999612[/C][C]0.000776304[/C][C]0.000388152[/C][/ROW]
[ROW][C]144[/C][C]0.999747[/C][C]0.00050676[/C][C]0.00025338[/C][/ROW]
[ROW][C]145[/C][C]0.999725[/C][C]0.00054977[/C][C]0.000274885[/C][/ROW]
[ROW][C]146[/C][C]0.99974[/C][C]0.000519531[/C][C]0.000259765[/C][/ROW]
[ROW][C]147[/C][C]0.999661[/C][C]0.00067747[/C][C]0.000338735[/C][/ROW]
[ROW][C]148[/C][C]0.999577[/C][C]0.000845878[/C][C]0.000422939[/C][/ROW]
[ROW][C]149[/C][C]0.99953[/C][C]0.00094048[/C][C]0.00047024[/C][/ROW]
[ROW][C]150[/C][C]0.999675[/C][C]0.000650165[/C][C]0.000325083[/C][/ROW]
[ROW][C]151[/C][C]0.999918[/C][C]0.00016442[/C][C]8.22098e-05[/C][/ROW]
[ROW][C]152[/C][C]0.999899[/C][C]0.000202086[/C][C]0.000101043[/C][/ROW]
[ROW][C]153[/C][C]0.999939[/C][C]0.000121019[/C][C]6.05094e-05[/C][/ROW]
[ROW][C]154[/C][C]0.999933[/C][C]0.000133019[/C][C]6.65097e-05[/C][/ROW]
[ROW][C]155[/C][C]0.99994[/C][C]0.000120322[/C][C]6.01611e-05[/C][/ROW]
[ROW][C]156[/C][C]0.999922[/C][C]0.000155127[/C][C]7.75634e-05[/C][/ROW]
[ROW][C]157[/C][C]0.999918[/C][C]0.00016353[/C][C]8.17652e-05[/C][/ROW]
[ROW][C]158[/C][C]0.999919[/C][C]0.000161465[/C][C]8.07326e-05[/C][/ROW]
[ROW][C]159[/C][C]0.999907[/C][C]0.00018597[/C][C]9.29851e-05[/C][/ROW]
[ROW][C]160[/C][C]0.99988[/C][C]0.000239091[/C][C]0.000119545[/C][/ROW]
[ROW][C]161[/C][C]0.999898[/C][C]0.000204728[/C][C]0.000102364[/C][/ROW]
[ROW][C]162[/C][C]0.999907[/C][C]0.000186781[/C][C]9.33904e-05[/C][/ROW]
[ROW][C]163[/C][C]0.999889[/C][C]0.000221179[/C][C]0.000110589[/C][/ROW]
[ROW][C]164[/C][C]0.999998[/C][C]3.44081e-06[/C][C]1.72041e-06[/C][/ROW]
[ROW][C]165[/C][C]0.999999[/C][C]2.95198e-06[/C][C]1.47599e-06[/C][/ROW]
[ROW][C]166[/C][C]0.999998[/C][C]4.55857e-06[/C][C]2.27928e-06[/C][/ROW]
[ROW][C]167[/C][C]0.999998[/C][C]4.20978e-06[/C][C]2.10489e-06[/C][/ROW]
[ROW][C]168[/C][C]0.999998[/C][C]3.71878e-06[/C][C]1.85939e-06[/C][/ROW]
[ROW][C]169[/C][C]0.999997[/C][C]5.28623e-06[/C][C]2.64311e-06[/C][/ROW]
[ROW][C]170[/C][C]0.999998[/C][C]4.55833e-06[/C][C]2.27917e-06[/C][/ROW]
[ROW][C]171[/C][C]0.999997[/C][C]5.50132e-06[/C][C]2.75066e-06[/C][/ROW]
[ROW][C]172[/C][C]0.999998[/C][C]4.4058e-06[/C][C]2.2029e-06[/C][/ROW]
[ROW][C]173[/C][C]0.999998[/C][C]4.32344e-06[/C][C]2.16172e-06[/C][/ROW]
[ROW][C]174[/C][C]0.999997[/C][C]5.91365e-06[/C][C]2.95683e-06[/C][/ROW]
[ROW][C]175[/C][C]0.999996[/C][C]8.10815e-06[/C][C]4.05408e-06[/C][/ROW]
[ROW][C]176[/C][C]0.999996[/C][C]8.74484e-06[/C][C]4.37242e-06[/C][/ROW]
[ROW][C]177[/C][C]0.999994[/C][C]1.26564e-05[/C][C]6.32818e-06[/C][/ROW]
[ROW][C]178[/C][C]0.999997[/C][C]6.02504e-06[/C][C]3.01252e-06[/C][/ROW]
[ROW][C]179[/C][C]0.999997[/C][C]6.3384e-06[/C][C]3.1692e-06[/C][/ROW]
[ROW][C]180[/C][C]0.999996[/C][C]8.15986e-06[/C][C]4.07993e-06[/C][/ROW]
[ROW][C]181[/C][C]0.999996[/C][C]8.79708e-06[/C][C]4.39854e-06[/C][/ROW]
[ROW][C]182[/C][C]0.999995[/C][C]1.04593e-05[/C][C]5.22965e-06[/C][/ROW]
[ROW][C]183[/C][C]0.999995[/C][C]9.12837e-06[/C][C]4.56419e-06[/C][/ROW]
[ROW][C]184[/C][C]0.999994[/C][C]1.26503e-05[/C][C]6.32513e-06[/C][/ROW]
[ROW][C]185[/C][C]0.999997[/C][C]6.65862e-06[/C][C]3.32931e-06[/C][/ROW]
[ROW][C]186[/C][C]0.999995[/C][C]9.18579e-06[/C][C]4.59289e-06[/C][/ROW]
[ROW][C]187[/C][C]0.999998[/C][C]4.44045e-06[/C][C]2.22023e-06[/C][/ROW]
[ROW][C]188[/C][C]0.999997[/C][C]5.63566e-06[/C][C]2.81783e-06[/C][/ROW]
[ROW][C]189[/C][C]0.999996[/C][C]7.81053e-06[/C][C]3.90526e-06[/C][/ROW]
[ROW][C]190[/C][C]0.999994[/C][C]1.18701e-05[/C][C]5.93505e-06[/C][/ROW]
[ROW][C]191[/C][C]0.999991[/C][C]1.71238e-05[/C][C]8.5619e-06[/C][/ROW]
[ROW][C]192[/C][C]0.999989[/C][C]2.16529e-05[/C][C]1.08265e-05[/C][/ROW]
[ROW][C]193[/C][C]0.999989[/C][C]2.10898e-05[/C][C]1.05449e-05[/C][/ROW]
[ROW][C]194[/C][C]0.999994[/C][C]1.10069e-05[/C][C]5.50347e-06[/C][/ROW]
[ROW][C]195[/C][C]0.999992[/C][C]1.57658e-05[/C][C]7.88288e-06[/C][/ROW]
[ROW][C]196[/C][C]0.999991[/C][C]1.88497e-05[/C][C]9.42486e-06[/C][/ROW]
[ROW][C]197[/C][C]0.999987[/C][C]2.64949e-05[/C][C]1.32474e-05[/C][/ROW]
[ROW][C]198[/C][C]0.999981[/C][C]3.70296e-05[/C][C]1.85148e-05[/C][/ROW]
[ROW][C]199[/C][C]0.999982[/C][C]3.6062e-05[/C][C]1.8031e-05[/C][/ROW]
[ROW][C]200[/C][C]0.999976[/C][C]4.74426e-05[/C][C]2.37213e-05[/C][/ROW]
[ROW][C]201[/C][C]0.999974[/C][C]5.10688e-05[/C][C]2.55344e-05[/C][/ROW]
[ROW][C]202[/C][C]0.99997[/C][C]6.0297e-05[/C][C]3.01485e-05[/C][/ROW]
[ROW][C]203[/C][C]0.99996[/C][C]8.03691e-05[/C][C]4.01845e-05[/C][/ROW]
[ROW][C]204[/C][C]0.999943[/C][C]0.000114954[/C][C]5.74769e-05[/C][/ROW]
[ROW][C]205[/C][C]0.999912[/C][C]0.000175551[/C][C]8.77754e-05[/C][/ROW]
[ROW][C]206[/C][C]0.999928[/C][C]0.000143669[/C][C]7.18345e-05[/C][/ROW]
[ROW][C]207[/C][C]0.999894[/C][C]0.000211846[/C][C]0.000105923[/C][/ROW]
[ROW][C]208[/C][C]0.999872[/C][C]0.000255483[/C][C]0.000127741[/C][/ROW]
[ROW][C]209[/C][C]0.999861[/C][C]0.000278436[/C][C]0.000139218[/C][/ROW]
[ROW][C]210[/C][C]0.999807[/C][C]0.000385534[/C][C]0.000192767[/C][/ROW]
[ROW][C]211[/C][C]0.999719[/C][C]0.000562886[/C][C]0.000281443[/C][/ROW]
[ROW][C]212[/C][C]0.999601[/C][C]0.000797876[/C][C]0.000398938[/C][/ROW]
[ROW][C]213[/C][C]0.999551[/C][C]0.00089892[/C][C]0.00044946[/C][/ROW]
[ROW][C]214[/C][C]0.999346[/C][C]0.00130793[/C][C]0.000653964[/C][/ROW]
[ROW][C]215[/C][C]0.999126[/C][C]0.00174719[/C][C]0.000873594[/C][/ROW]
[ROW][C]216[/C][C]0.998744[/C][C]0.0025113[/C][C]0.00125565[/C][/ROW]
[ROW][C]217[/C][C]0.998448[/C][C]0.00310426[/C][C]0.00155213[/C][/ROW]
[ROW][C]218[/C][C]0.998085[/C][C]0.00382917[/C][C]0.00191458[/C][/ROW]
[ROW][C]219[/C][C]0.99725[/C][C]0.00549955[/C][C]0.00274978[/C][/ROW]
[ROW][C]220[/C][C]0.996164[/C][C]0.0076726[/C][C]0.0038363[/C][/ROW]
[ROW][C]221[/C][C]0.996632[/C][C]0.00673672[/C][C]0.00336836[/C][/ROW]
[ROW][C]222[/C][C]0.997288[/C][C]0.00542328[/C][C]0.00271164[/C][/ROW]
[ROW][C]223[/C][C]0.996517[/C][C]0.00696566[/C][C]0.00348283[/C][/ROW]
[ROW][C]224[/C][C]0.997322[/C][C]0.00535513[/C][C]0.00267757[/C][/ROW]
[ROW][C]225[/C][C]0.99725[/C][C]0.00550065[/C][C]0.00275032[/C][/ROW]
[ROW][C]226[/C][C]0.998878[/C][C]0.00224375[/C][C]0.00112187[/C][/ROW]
[ROW][C]227[/C][C]0.999368[/C][C]0.00126498[/C][C]0.000632492[/C][/ROW]
[ROW][C]228[/C][C]0.99935[/C][C]0.00130039[/C][C]0.000650194[/C][/ROW]
[ROW][C]229[/C][C]0.999253[/C][C]0.00149344[/C][C]0.000746719[/C][/ROW]
[ROW][C]230[/C][C]0.999666[/C][C]0.000668063[/C][C]0.000334032[/C][/ROW]
[ROW][C]231[/C][C]0.999871[/C][C]0.000258048[/C][C]0.000129024[/C][/ROW]
[ROW][C]232[/C][C]0.999813[/C][C]0.00037398[/C][C]0.00018699[/C][/ROW]
[ROW][C]233[/C][C]0.999687[/C][C]0.00062591[/C][C]0.000312955[/C][/ROW]
[ROW][C]234[/C][C]0.999625[/C][C]0.000750971[/C][C]0.000375486[/C][/ROW]
[ROW][C]235[/C][C]0.999384[/C][C]0.00123225[/C][C]0.000616127[/C][/ROW]
[ROW][C]236[/C][C]0.999629[/C][C]0.000742468[/C][C]0.000371234[/C][/ROW]
[ROW][C]237[/C][C]0.999594[/C][C]0.000812465[/C][C]0.000406232[/C][/ROW]
[ROW][C]238[/C][C]0.999401[/C][C]0.00119754[/C][C]0.000598771[/C][/ROW]
[ROW][C]239[/C][C]0.999313[/C][C]0.0013732[/C][C]0.000686598[/C][/ROW]
[ROW][C]240[/C][C]0.998875[/C][C]0.00225046[/C][C]0.00112523[/C][/ROW]
[ROW][C]241[/C][C]0.998143[/C][C]0.00371478[/C][C]0.00185739[/C][/ROW]
[ROW][C]242[/C][C]0.99711[/C][C]0.00577948[/C][C]0.00288974[/C][/ROW]
[ROW][C]243[/C][C]0.995821[/C][C]0.00835704[/C][C]0.00417852[/C][/ROW]
[ROW][C]244[/C][C]0.993849[/C][C]0.0123028[/C][C]0.00615142[/C][/ROW]
[ROW][C]245[/C][C]0.99038[/C][C]0.019241[/C][C]0.00962048[/C][/ROW]
[ROW][C]246[/C][C]0.98664[/C][C]0.0267193[/C][C]0.0133597[/C][/ROW]
[ROW][C]247[/C][C]0.980067[/C][C]0.0398653[/C][C]0.0199326[/C][/ROW]
[ROW][C]248[/C][C]0.979294[/C][C]0.0414116[/C][C]0.0207058[/C][/ROW]
[ROW][C]249[/C][C]0.972779[/C][C]0.0544422[/C][C]0.0272211[/C][/ROW]
[ROW][C]250[/C][C]0.962416[/C][C]0.0751686[/C][C]0.0375843[/C][/ROW]
[ROW][C]251[/C][C]0.945186[/C][C]0.109628[/C][C]0.0548138[/C][/ROW]
[ROW][C]252[/C][C]0.922656[/C][C]0.154688[/C][C]0.0773442[/C][/ROW]
[ROW][C]253[/C][C]0.892798[/C][C]0.214403[/C][C]0.107202[/C][/ROW]
[ROW][C]254[/C][C]0.856514[/C][C]0.286972[/C][C]0.143486[/C][/ROW]
[ROW][C]255[/C][C]0.827074[/C][C]0.345853[/C][C]0.172926[/C][/ROW]
[ROW][C]256[/C][C]0.775457[/C][C]0.449085[/C][C]0.224543[/C][/ROW]
[ROW][C]257[/C][C]0.76299[/C][C]0.474021[/C][C]0.23701[/C][/ROW]
[ROW][C]258[/C][C]0.823843[/C][C]0.352313[/C][C]0.176157[/C][/ROW]
[ROW][C]259[/C][C]0.83311[/C][C]0.33378[/C][C]0.16689[/C][/ROW]
[ROW][C]260[/C][C]0.998881[/C][C]0.00223876[/C][C]0.00111938[/C][/ROW]
[ROW][C]261[/C][C]0.997195[/C][C]0.00561001[/C][C]0.00280501[/C][/ROW]
[ROW][C]262[/C][C]0.998391[/C][C]0.00321714[/C][C]0.00160857[/C][/ROW]
[ROW][C]263[/C][C]0.999682[/C][C]0.000636834[/C][C]0.000318417[/C][/ROW]
[ROW][C]264[/C][C]0.998884[/C][C]0.00223291[/C][C]0.00111645[/C][/ROW]
[ROW][C]265[/C][C]0.997614[/C][C]0.00477132[/C][C]0.00238566[/C][/ROW]
[ROW][C]266[/C][C]0.994807[/C][C]0.0103854[/C][C]0.00519268[/C][/ROW]
[ROW][C]267[/C][C]0.99894[/C][C]0.00212091[/C][C]0.00106046[/C][/ROW]
[ROW][C]268[/C][C]0.993519[/C][C]0.012962[/C][C]0.00648098[/C][/ROW]
[ROW][C]269[/C][C]0.982139[/C][C]0.0357223[/C][C]0.0178611[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&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
100.5849960.8300090.415004
110.4210620.8421240.578938
120.6570320.6859370.342968
130.536250.92750.46375
140.4212730.8425470.578727
150.3189830.6379660.681017
160.2292280.4584570.770772
170.1605650.3211310.839435
180.274260.5485210.72574
190.2776020.5552040.722398
200.2116080.4232160.788392
210.2231510.4463010.776849
220.2665240.5330480.733476
230.2133030.4266060.786697
240.1684290.3368580.831571
250.1299510.2599020.870049
260.1189230.2378470.881077
270.102990.205980.89701
280.08446490.168930.915535
290.08065770.1613150.919342
300.06800830.1360170.931992
310.05224430.1044890.947756
320.03997410.07994820.960026
330.03240790.06481580.967592
340.0312390.0624780.968761
350.02356040.04712090.97644
360.01710130.03420260.982899
370.01647470.03294940.983525
380.01191270.02382530.988087
390.01140650.02281290.988594
400.008222580.01644520.991777
410.01471020.02942040.98529
420.01086080.02172150.989139
430.008779250.01755850.991221
440.007152330.01430470.992848
450.005163980.0103280.994836
460.003905970.007811930.996094
470.003144210.006288410.996856
480.008176030.01635210.991824
490.00977490.01954980.990225
500.008509170.01701830.991491
510.006280450.01256090.99372
520.00931420.01862840.990686
530.007574470.01514890.992426
540.005558810.01111760.994441
550.006354510.0127090.993645
560.004848480.009696970.995152
570.01777540.03555090.982225
580.02829140.05658270.971709
590.0217920.04358390.978208
600.0176580.0353160.982342
610.0272990.05459790.972701
620.02692440.05384870.973076
630.02852160.05704330.971478
640.03482380.06964770.965176
650.03986540.07973080.960135
660.03359910.06719820.966401
670.03415850.0683170.965841
680.04211720.08423450.957883
690.05761020.115220.94239
700.04965870.09931740.950341
710.04518160.09036310.954818
720.03968810.07937620.960312
730.03958780.07917570.960412
740.04058640.08117270.959414
750.03845990.07691970.96154
760.03479040.06958070.96521
770.02909730.05819450.970903
780.02858830.05717660.971412
790.02315280.04630560.976847
800.03163110.06326230.968369
810.02635140.05270280.973649
820.02505640.05011280.974944
830.02081790.04163570.979182
840.08433240.1686650.915668
850.07823650.1564730.921763
860.07074860.1414970.929251
870.05994430.1198890.940056
880.05149030.1029810.94851
890.05383870.1076770.946161
900.05054920.1010980.949451
910.04851570.09703150.951484
920.1181030.2362060.881897
930.1500430.3000870.849957
940.1520530.3041050.847947
950.1766210.3532430.823379
960.1878470.3756950.812153
970.2969570.5939130.703043
980.2779440.5558870.722056
990.2934240.5868480.706576
1000.3763920.7527850.623608
1010.3485310.6970620.651469
1020.3455880.6911760.654412
1030.3534150.706830.646585
1040.4147850.829570.585215
1050.4316170.8632350.568383
1060.4692620.9385230.530738
1070.4982080.9964170.501792
1080.7269340.5461320.273066
1090.7798960.4402080.220104
1100.80890.38220.1911
1110.8087520.3824950.191248
1120.8043420.3913150.195658
1130.8682050.263590.131795
1140.8798840.2402310.120116
1150.949130.1017410.0508703
1160.9731650.05366940.0268347
1170.9744060.05118820.0255941
1180.9751890.04962160.0248108
1190.9794090.04118260.0205913
1200.9885140.02297160.0114858
1210.9907040.0185930.00929649
1220.9935520.01289650.00644827
1230.9969180.006163850.00308193
1240.999080.001840120.000920061
1250.9990340.001932960.000966479
1260.9988760.002248380.00112419
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1280.9989160.002167910.00108396
1290.9993750.001249750.000624874
1300.9994390.001121080.000560542
1310.9994590.001081760.000540879
1320.9994650.001069740.000534871
1330.9994470.001106530.000553266
1340.9994370.00112620.0005631
1350.9992680.001464620.000732309
1360.9990590.001881820.000940911
1370.9995330.0009344890.000467245
1380.9994310.001137860.000568931
1390.9995460.0009072930.000453646
1400.9994870.001026780.000513392
1410.9993410.001317390.000658694
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1430.9996120.0007763040.000388152
1440.9997470.000506760.00025338
1450.9997250.000549770.000274885
1460.999740.0005195310.000259765
1470.9996610.000677470.000338735
1480.9995770.0008458780.000422939
1490.999530.000940480.00047024
1500.9996750.0006501650.000325083
1510.9999180.000164428.22098e-05
1520.9998990.0002020860.000101043
1530.9999390.0001210196.05094e-05
1540.9999330.0001330196.65097e-05
1550.999940.0001203226.01611e-05
1560.9999220.0001551277.75634e-05
1570.9999180.000163538.17652e-05
1580.9999190.0001614658.07326e-05
1590.9999070.000185979.29851e-05
1600.999880.0002390910.000119545
1610.9998980.0002047280.000102364
1620.9999070.0001867819.33904e-05
1630.9998890.0002211790.000110589
1640.9999983.44081e-061.72041e-06
1650.9999992.95198e-061.47599e-06
1660.9999984.55857e-062.27928e-06
1670.9999984.20978e-062.10489e-06
1680.9999983.71878e-061.85939e-06
1690.9999975.28623e-062.64311e-06
1700.9999984.55833e-062.27917e-06
1710.9999975.50132e-062.75066e-06
1720.9999984.4058e-062.2029e-06
1730.9999984.32344e-062.16172e-06
1740.9999975.91365e-062.95683e-06
1750.9999968.10815e-064.05408e-06
1760.9999968.74484e-064.37242e-06
1770.9999941.26564e-056.32818e-06
1780.9999976.02504e-063.01252e-06
1790.9999976.3384e-063.1692e-06
1800.9999968.15986e-064.07993e-06
1810.9999968.79708e-064.39854e-06
1820.9999951.04593e-055.22965e-06
1830.9999959.12837e-064.56419e-06
1840.9999941.26503e-056.32513e-06
1850.9999976.65862e-063.32931e-06
1860.9999959.18579e-064.59289e-06
1870.9999984.44045e-062.22023e-06
1880.9999975.63566e-062.81783e-06
1890.9999967.81053e-063.90526e-06
1900.9999941.18701e-055.93505e-06
1910.9999911.71238e-058.5619e-06
1920.9999892.16529e-051.08265e-05
1930.9999892.10898e-051.05449e-05
1940.9999941.10069e-055.50347e-06
1950.9999921.57658e-057.88288e-06
1960.9999911.88497e-059.42486e-06
1970.9999872.64949e-051.32474e-05
1980.9999813.70296e-051.85148e-05
1990.9999823.6062e-051.8031e-05
2000.9999764.74426e-052.37213e-05
2010.9999745.10688e-052.55344e-05
2020.999976.0297e-053.01485e-05
2030.999968.03691e-054.01845e-05
2040.9999430.0001149545.74769e-05
2050.9999120.0001755518.77754e-05
2060.9999280.0001436697.18345e-05
2070.9998940.0002118460.000105923
2080.9998720.0002554830.000127741
2090.9998610.0002784360.000139218
2100.9998070.0003855340.000192767
2110.9997190.0005628860.000281443
2120.9996010.0007978760.000398938
2130.9995510.000898920.00044946
2140.9993460.001307930.000653964
2150.9991260.001747190.000873594
2160.9987440.00251130.00125565
2170.9984480.003104260.00155213
2180.9980850.003829170.00191458
2190.997250.005499550.00274978
2200.9961640.00767260.0038363
2210.9966320.006736720.00336836
2220.9972880.005423280.00271164
2230.9965170.006965660.00348283
2240.9973220.005355130.00267757
2250.997250.005500650.00275032
2260.9988780.002243750.00112187
2270.9993680.001264980.000632492
2280.999350.001300390.000650194
2290.9992530.001493440.000746719
2300.9996660.0006680630.000334032
2310.9998710.0002580480.000129024
2320.9998130.000373980.00018699
2330.9996870.000625910.000312955
2340.9996250.0007509710.000375486
2350.9993840.001232250.000616127
2360.9996290.0007424680.000371234
2370.9995940.0008124650.000406232
2380.9994010.001197540.000598771
2390.9993130.00137320.000686598
2400.9988750.002250460.00112523
2410.9981430.003714780.00185739
2420.997110.005779480.00288974
2430.9958210.008357040.00417852
2440.9938490.01230280.00615142
2450.990380.0192410.00962048
2460.986640.02671930.0133597
2470.9800670.03986530.0199326
2480.9792940.04141160.0207058
2490.9727790.05444220.0272211
2500.9624160.07516860.0375843
2510.9451860.1096280.0548138
2520.9226560.1546880.0773442
2530.8927980.2144030.107202
2540.8565140.2869720.143486
2550.8270740.3458530.172926
2560.7754570.4490850.224543
2570.762990.4740210.23701
2580.8238430.3523130.176157
2590.833110.333780.16689
2600.9988810.002238760.00111938
2610.9971950.005610010.00280501
2620.9983910.003217140.00160857
2630.9996820.0006368340.000318417
2640.9988840.002232910.00111645
2650.9976140.004771320.00238566
2660.9948070.01038540.00519268
2670.998940.002120910.00106046
2680.9935190.0129620.00648098
2690.9821390.03572230.0178611






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1310.503846NOK
5% type I error level1680.646154NOK
10% type I error level1970.757692NOK

\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 & 131 & 0.503846 & NOK \tabularnewline
5% type I error level & 168 & 0.646154 & NOK \tabularnewline
10% type I error level & 197 & 0.757692 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264060&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]131[/C][C]0.503846[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]168[/C][C]0.646154[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]197[/C][C]0.757692[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264060&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264060&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level1310.503846NOK
5% type I error level1680.646154NOK
10% type I error level1970.757692NOK


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')
}