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R Software Module

rwasp_multipleregression.wasp

Title produced by software

Multiple Regression

Date of computation

Tue, 09 Dec 2014 10:14:23 +0000

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Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/09/t1418120205dgim6inz3hcst8l.htm/, Retrieved Thu, 16 May 2024 18:27:59 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=264403, Retrieved Thu, 16 May 2024 18:27:59 +0000

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-       [Multiple Regression] [] [2014-12-09 10:14:23] [a4daf178ee9972867aacc2039fa7f163] [Current]

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0 1 26 18 12 20 0 21 149 7.5
0 1 57 23 20 19 1 22 139 6.0
0 1 37 22 14 18 0 22 148 6.5
0 1 67 22 25 24 1 18 158 1.0
0 1 43 19 15 20 1 23 128 1.0
0 1 52 25 20 20 1 12 224 5.5
0 1 52 28 21 24 0 20 159 8.5
0 1 43 16 15 21 1 22 105 6.5
0 1 84 28 28 28 1 21 159 4.5
0 1 67 21 11 10 1 19 167 2.0
0 1 49 22 22 22 1 22 165 5.0
0 1 70 24 22 19 1 15 159 0.5
0 1 52 24 27 27 1 20 119 5.0
0 1 58 26 24 23 0 19 176 5.0
0 1 68 28 23 24 0 18 54 2.5
0 0 62 24 24 24 0 15 91 5.0
0 1 43 20 21 25 1 20 163 5.5
0 1 56 26 20 24 0 21 124 3.5
0 0 56 21 19 21 1 21 137 3.0
0 1 74 28 25 28 0 15 121 4.0
0 1 65 27 16 28 1 16 153 0.5
0 1 63 23 24 22 1 23 148 6.5
0 1 58 24 21 26 0 21 221 4.5
0 1 57 24 22 26 1 18 188 7.5
0 1 63 22 25 21 1 25 149 5.5
0 1 53 21 23 26 1 9 244 4.0
0 0 57 25 20 23 1 30 148 7.5
0 0 51 20 21 20 0 20 92 7.0
0 1 64 21 22 24 1 23 150 4.0
0 1 53 26 25 25 0 16 153 5.5
0 1 29 23 23 24 0 16 94 2.5
0 1 54 21 19 20 0 19 156 5.5
0 1 58 27 21 24 1 25 132 3.5
0 1 43 25 19 25 1 18 161 2.5
0 1 51 23 25 23 1 23 105 4.5
0 1 53 25 16 21 1 21 97 4.5
0 1 54 23 24 23 0 10 151 4.5
0 0 56 19 24 21 1 14 131 6.0
0 1 61 22 18 18 1 22 166 2.5
0 1 47 24 28 24 0 26 157 5.0
0 1 39 19 15 18 1 23 111 0.0
0 1 48 21 17 21 1 23 145 5.0
0 1 50 27 18 23 1 24 162 6.5
0 1 35 25 26 25 1 24 163 5.0
0 0 30 25 18 22 1 18 59 6.0
0 1 68 23 22 22 0 23 187 4.5
0 1 49 17 19 23 1 15 109 5.5
0 0 61 28 17 24 1 19 90 1.0
0 1 67 25 26 25 0 16 105 7.5
0 0 47 20 21 22 1 25 83 6.0
0 0 56 25 26 24 1 23 116 5.0
0 0 50 21 21 21 1 17 42 1.0
0 1 43 24 12 24 1 19 148 5.0
0 0 67 28 20 25 1 21 155 6.5
0 1 62 20 20 23 1 18 125 7.0
0 1 57 19 24 27 1 27 116 4.5
0 0 41 24 24 27 0 21 128 0.0
0 1 54 21 22 23 1 13 138 8.5
0 0 45 24 21 18 0 8 49 3.5
0 0 48 23 20 20 1 29 96 7.5
0 1 61 18 23 23 1 28 164 3.5
0 1 56 27 19 24 0 23 162 6.0
0 1 41 25 24 26 0 21 99 1.5
0 1 43 20 21 20 1 19 202 9.0
0 1 53 21 16 23 0 19 186 3.5
0 0 44 23 17 22 1 20 66 3.5
0 1 66 27 23 23 0 18 183 4.0
0 1 58 24 20 17 1 19 214 6.5
0 1 46 27 19 20 1 17 188 7.5
0 0 37 24 18 22 0 19 104 6.0
0 1 51 23 18 18 0 25 177 5.0
0 1 51 24 21 19 0 19 126 5.5
0 0 56 21 20 19 0 22 76 3.5
0 0 66 23 17 16 1 23 99 7.5
0 1 37 27 25 26 0 14 139 6.5
0 1 59 24 15 14 1 28 78 NA
0 1 42 25 17 25 0 16 162 6.5
0 0 38 19 17 23 1 24 108 6.5
0 1 66 24 24 18 0 20 159 7.0
0 0 34 25 21 22 0 12 74 3.5
0 1 53 23 22 26 1 24 110 1.5
0 0 49 23 18 25 0 22 96 4.0
0 0 55 25 22 26 0 12 116 7.5
0 0 49 26 20 26 0 22 87 4.5
0 0 59 26 21 24 1 20 97 0.0
0 0 40 16 21 22 0 10 127 3.5
0 0 58 23 20 21 1 23 106 5.5
0 0 60 26 18 22 1 17 80 5.0
0 0 63 25 25 28 0 22 74 4.5
0 0 56 23 23 22 0 24 91 2.5
0 0 54 26 21 26 0 18 133 7.5
0 0 52 22 20 20 1 21 74 7.0
0 0 34 20 21 24 1 20 114 0.0
0 0 69 27 20 21 1 20 140 4.5
0 0 32 20 22 23 0 22 95 3.0
0 0 48 22 15 23 1 19 98 1.5
0 0 67 24 24 23 0 20 121 3.5
0 0 58 21 22 22 1 26 126 2.5
0 0 57 24 21 23 1 23 98 5.5
0 0 42 26 17 21 1 24 95 8.0
0 0 64 24 23 27 1 21 110 1.0
0 0 58 24 22 23 1 21 70 5.0
0 0 66 27 23 26 0 19 102 4.5
0 0 26 25 16 27 1 8 86 3.0
0 0 61 27 18 27 1 17 130 3.0
0 0 52 19 25 23 1 20 96 8.0
0 0 51 22 18 23 0 11 102 2.5
0 0 55 22 14 23 0 8 100 7.0
0 0 50 25 20 28 0 15 94 0.0
0 0 60 23 19 24 0 18 52 1.0
0 0 56 24 18 20 0 18 98 3.5
0 0 63 24 22 23 0 19 118 5.5
0 0 61 23 21 22 1 19 99 5.5
1 1 52 22 14 15 1 23 48 0.5
1 1 16 24 5 27 1 22 50 7.5
1 1 46 19 25 23 1 21 150 9
1 1 56 25 21 23 1 25 154 9.5
1 0 52 26 11 20 0 30 109 8.5
1 0 55 18 20 18 1 17 68 7
1 1 50 24 9 22 1 27 194 8
1 1 59 28 15 20 0 23 158 10
1 1 60 23 23 21 1 23 159 7
1 1 52 19 21 25 0 18 67 8.5
1 1 44 19 9 19 0 18 147 9
1 1 67 27 24 25 1 23 39 9.5
1 1 52 24 16 24 1 19 100 4
1 1 55 26 20 22 1 15 111 6
1 1 37 21 15 28 1 20 138 8
1 1 54 25 18 22 1 16 101 5.5
1 0 72 28 22 21 1 24 131 9.5
1 1 51 19 21 23 1 25 101 7.5
1 1 48 20 21 19 1 25 114 7
1 1 60 26 21 21 0 19 165 7.5
1 1 50 27 20 25 1 19 114 8
1 1 63 23 24 23 1 16 111 7
1 1 33 18 15 28 1 19 75 7
1 1 67 23 24 14 1 19 82 6
1 1 46 21 18 23 1 23 121 10
1 1 54 23 24 24 1 21 32 2.5
1 1 59 22 24 25 0 22 150 9
1 1 61 21 15 15 1 19 117 8
1 0 33 14 19 23 1 20 71 6
1 1 47 24 20 26 1 20 165 8.5
1 1 69 26 26 21 1 3 154 6
1 1 52 24 26 26 1 23 126 9
1 1 55 22 23 23 0 23 149 8
1 1 41 20 13 15 0 20 145 9
1 1 73 20 16 16 1 15 120 5.5
1 1 52 18 22 20 0 16 109 7
1 1 50 18 21 20 0 7 132 5.5
1 1 51 25 11 21 1 24 172 9
1 1 60 28 23 28 0 17 169 2
1 1 56 23 18 19 1 24 114 8.5
1 1 56 20 19 21 1 24 156 9
1 1 29 22 15 22 0 19 172 8.5
1 0 66 27 8 27 1 25 68 9
1 0 66 24 15 20 1 20 89 7.5
1 1 73 23 21 17 1 28 167 10
1 1 55 20 25 26 0 23 113 9
1 0 64 22 14 21 0 27 115 7.5
1 0 40 21 21 24 0 18 78 6
1 0 46 24 18 21 0 28 118 10.5
1 0 58 26 18 25 1 21 87 8.5
1 1 43 24 12 22 0 19 173 8
1 1 61 18 24 17 1 23 2 10
1 0 51 17 17 14 0 27 162 10.5
1 0 50 23 20 23 1 22 49 6.5
1 0 52 21 24 28 0 28 122 9.5
1 0 54 21 22 24 1 25 96 8.5
1 0 66 24 15 22 0 21 100 7.5
1 0 61 22 22 24 0 22 82 5
1 0 80 24 26 25 1 28 100 8
1 0 51 24 17 21 0 20 115 10
1 0 56 24 23 22 1 29 141 7
1 1 56 23 19 16 1 25 165 7.5
1 1 56 21 21 18 1 25 165 7.5
1 0 53 24 23 27 1 20 110 9.5
1 1 47 19 19 17 1 20 118 6
1 1 25 19 18 25 0 16 158 10
1 0 47 23 16 24 1 20 146 7
1 1 46 25 23 21 0 20 49 3
1 0 50 24 13 21 0 23 90 6
1 0 39 21 18 19 0 18 121 7
1 1 51 18 23 27 1 25 155 10
1 0 58 23 21 28 0 18 104 7
1 0 35 20 23 19 1 19 147 3.5
1 0 58 23 16 23 0 25 110 8
1 0 60 23 17 25 0 25 108 10
1 0 62 23 20 26 0 25 113 5.5
1 0 63 23 18 25 0 24 115 6
1 0 53 27 20 25 1 19 61 6.5
1 0 46 19 19 24 1 26 60 6.5
1 0 67 25 26 24 1 10 109 8.5
1 0 59 25 9 24 1 17 68 4
1 0 64 21 23 22 0 13 111 9.5
1 0 38 25 9 21 0 17 77 8
1 0 50 17 13 17 1 30 73 8.5
1 1 48 22 27 23 0 25 151 5.5
1 0 48 23 22 17 0 4 89 7
1 0 47 27 12 25 0 16 78 9
1 0 66 27 18 19 0 21 110 8
1 1 47 5 6 8 1 23 220 10
1 0 63 19 17 14 1 22 65 8
1 1 58 24 22 22 0 17 141 6
1 0 44 23 22 25 0 20 117 8
1 1 51 28 23 28 1 20 122 5
1 0 43 25 19 25 0 22 63 9
1 1 55 27 20 24 1 16 44 4.5
1 0 38 16 17 15 1 23 52 8.5
1 0 45 25 24 24 0 0 131 9.5
1 0 50 26 20 28 1 18 101 8.5
1 0 54 24 18 24 1 25 42 7.5
1 1 57 23 23 25 1 23 152 7.5
1 1 60 24 27 23 0 12 107 5
1 0 55 27 25 26 0 18 77 7
1 1 56 25 24 26 0 24 154 8
1 1 49 19 12 22 1 11 103 5.5
1 0 37 19 16 25 1 18 96 8.5
1 1 59 24 24 22 1 23 175 9.5
1 0 46 20 23 26 1 24 57 7
1 0 51 21 24 20 0 29 112 8
1 1 58 28 24 26 0 18 143 8.5
1 0 64 26 26 26 0 15 49 3.5
1 1 53 19 19 21 1 29 110 6.5
1 1 48 23 28 21 1 16 131 6.5
1 1 51 23 23 24 0 19 167 10.5
1 0 47 21 21 21 0 22 56 8.5
1 1 59 26 19 18 0 16 137 8
1 0 62 25 23 23 1 23 86 10
1 1 62 25 23 26 1 23 121 10
1 1 51 24 20 23 0 19 149 9.5
1 1 64 23 18 25 0 4 168 9
1 1 52 22 20 20 0 20 140 10
1 0 67 27 28 25 1 24 88 7.5
1 1 50 26 21 26 1 20 168 4.5
1 1 54 23 25 19 1 4 94 4.5
1 1 58 22 18 21 1 24 51 0.5
1 0 56 26 24 23 0 22 48 6.5
1 1 63 22 28 24 1 16 145 4.5
1 1 31 17 9 6 1 3 66 5.5
1 0 65 25 22 22 1 15 85 5
1 1 71 22 26 21 0 24 109 6
1 0 50 28 28 28 0 17 63 4
1 0 57 22 18 24 1 20 102 8
1 0 47 21 23 14 0 27 162 10.5
1 0 47 24 15 20 1 26 86 6.5
1 0 57 26 24 28 1 23 114 8
1 1 43 26 12 19 0 17 164 8.5
1 1 41 24 12 24 1 20 119 5.5
1 1 63 27 20 21 0 22 126 7
1 1 63 22 25 21 1 19 132 5
1 1 56 23 24 26 1 24 142 3.5
1 1 51 22 23 24 0 19 83 5
1 0 50 23 18 26 1 23 94 9
1 0 22 15 20 25 0 15 81 8.5
1 1 41 20 22 23 1 27 166 5
1 0 59 22 20 24 0 26 110 9.5
1 0 56 25 25 24 1 22 64 3
1 1 66 27 28 26 0 22 93 1.5
1 0 53 24 25 23 0 18 104 6
1 0 42 21 14 20 1 15 105 0.5
1 0 52 17 16 16 1 22 49 6.5
1 0 54 26 24 24 0 27 88 7.5
1 0 44 20 13 20 1 10 95 4.5
1 0 62 22 19 23 1 20 102 8
1 0 53 24 18 23 0 17 99 9
1 0 50 23 16 18 1 23 63 7.5
1 0 36 22 8 21 0 19 76 8.5
1 0 76 28 27 25 0 13 109 7
1 0 66 21 23 23 1 27 117 9.5
1 0 62 24 20 26 1 23 57 6.5
1 0 59 28 20 26 0 16 120 9.5
1 0 47 25 26 24 1 25 73 6
1 0 55 24 23 23 0 2 91 8
1 0 58 24 24 21 0 26 108 9.5
1 0 60 21 21 23 1 20 105 8
1 1 44 20 15 20 0 23 117 8
1 0 57 26 22 23 0 22 119 9
1 0 45 16 25 24 1 24 31 5

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 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=264403&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=264403&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=0

As an alternative you can also use a QR Code:

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

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	9 seconds
R Server	'Sir Maurice George Kendall' @ kendall.wessa.net

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 3.47851 + 2.92757jaarInd[t] -0.862207groepn[t] -0.00751167AMS.I[t] -0.0207303AMS.E1[t] -0.017222AMS.E2[t] -0.0317119AMS.E3[t] -0.487947gender[t] + 0.064768NUMERACYTOT[t] + 0.0198795LFM[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Ex[t] =  +  3.47851 +  2.92757jaarInd[t] -0.862207groepn[t] -0.00751167AMS.I[t] -0.0207303AMS.E1[t] -0.017222AMS.E2[t] -0.0317119AMS.E3[t] -0.487947gender[t] +  0.064768NUMERACYTOT[t] +  0.0198795LFM[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Ex[t] =  +  3.47851 +  2.92757jaarInd[t] -0.862207groepn[t] -0.00751167AMS.I[t] -0.0207303AMS.E1[t] -0.017222AMS.E2[t] -0.0317119AMS.E3[t] -0.487947gender[t] +  0.064768NUMERACYTOT[t] +  0.0198795LFM[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=1

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Estimated Regression Equation
Ex[t] = + 3.47851 + 2.92757jaarInd[t] -0.862207groepn[t] -0.00751167AMS.I[t] -0.0207303AMS.E1[t] -0.017222AMS.E2[t] -0.0317119AMS.E3[t] -0.487947gender[t] + 0.064768NUMERACYTOT[t] + 0.0198795LFM[t] + e[t]

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	3.47851	1.30764	2.66	0.0082816	0.0041408
jaarInd	2.92757	0.258201	11.34	1.33586e-24	6.67931e-25
groepn	-0.862207	0.29041	-2.969	0.00325879	0.00162939
AMS.I	-0.00751167	0.0141048	-0.5326	0.594779	0.29739
AMS.E1	-0.0207303	0.0482708	-0.4295	0.667935	0.333968
AMS.E2	-0.017222	0.0326956	-0.5267	0.598811	0.299406
AMS.E3	-0.0317119	0.0426971	-0.7427	0.458303	0.229152
gender	-0.487947	0.258055	-1.891	0.0597212	0.0298606
NUMERACYTOT	0.064768	0.024487	2.645	0.00865161	0.0043258
LFM	0.0198795	0.00371392	5.353	1.86279e-07	9.31397e-08

\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) & 3.47851 & 1.30764 & 2.66 & 0.0082816 & 0.0041408 \tabularnewline
jaarInd & 2.92757 & 0.258201 & 11.34 & 1.33586e-24 & 6.67931e-25 \tabularnewline
groepn & -0.862207 & 0.29041 & -2.969 & 0.00325879 & 0.00162939 \tabularnewline
AMS.I & -0.00751167 & 0.0141048 & -0.5326 & 0.594779 & 0.29739 \tabularnewline
AMS.E1 & -0.0207303 & 0.0482708 & -0.4295 & 0.667935 & 0.333968 \tabularnewline
AMS.E2 & -0.017222 & 0.0326956 & -0.5267 & 0.598811 & 0.299406 \tabularnewline
AMS.E3 & -0.0317119 & 0.0426971 & -0.7427 & 0.458303 & 0.229152 \tabularnewline
gender & -0.487947 & 0.258055 & -1.891 & 0.0597212 & 0.0298606 \tabularnewline
NUMERACYTOT & 0.064768 & 0.024487 & 2.645 & 0.00865161 & 0.0043258 \tabularnewline
LFM & 0.0198795 & 0.00371392 & 5.353 & 1.86279e-07 & 9.31397e-08 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&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]3.47851[/C][C]1.30764[/C][C]2.66[/C][C]0.0082816[/C][C]0.0041408[/C][/ROW]
[ROW][C]jaarInd[/C][C]2.92757[/C][C]0.258201[/C][C]11.34[/C][C]1.33586e-24[/C][C]6.67931e-25[/C][/ROW]
[ROW][C]groepn[/C][C]-0.862207[/C][C]0.29041[/C][C]-2.969[/C][C]0.00325879[/C][C]0.00162939[/C][/ROW]
[ROW][C]AMS.I[/C][C]-0.00751167[/C][C]0.0141048[/C][C]-0.5326[/C][C]0.594779[/C][C]0.29739[/C][/ROW]
[ROW][C]AMS.E1[/C][C]-0.0207303[/C][C]0.0482708[/C][C]-0.4295[/C][C]0.667935[/C][C]0.333968[/C][/ROW]
[ROW][C]AMS.E2[/C][C]-0.017222[/C][C]0.0326956[/C][C]-0.5267[/C][C]0.598811[/C][C]0.299406[/C][/ROW]
[ROW][C]AMS.E3[/C][C]-0.0317119[/C][C]0.0426971[/C][C]-0.7427[/C][C]0.458303[/C][C]0.229152[/C][/ROW]
[ROW][C]gender[/C][C]-0.487947[/C][C]0.258055[/C][C]-1.891[/C][C]0.0597212[/C][C]0.0298606[/C][/ROW]
[ROW][C]NUMERACYTOT[/C][C]0.064768[/C][C]0.024487[/C][C]2.645[/C][C]0.00865161[/C][C]0.0043258[/C][/ROW]
[ROW][C]LFM[/C][C]0.0198795[/C][C]0.00371392[/C][C]5.353[/C][C]1.86279e-07[/C][C]9.31397e-08[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=2

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Ordinary Least Squares
Variable	Parameter	S.D.	T-STATH0: parameter = 0	2-tail p-value	1-tail p-value
(Intercept)	3.47851	1.30764	2.66	0.0082816	0.0041408
jaarInd	2.92757	0.258201	11.34	1.33586e-24	6.67931e-25
groepn	-0.862207	0.29041	-2.969	0.00325879	0.00162939
AMS.I	-0.00751167	0.0141048	-0.5326	0.594779	0.29739
AMS.E1	-0.0207303	0.0482708	-0.4295	0.667935	0.333968
AMS.E2	-0.017222	0.0326956	-0.5267	0.598811	0.299406
AMS.E3	-0.0317119	0.0426971	-0.7427	0.458303	0.229152
gender	-0.487947	0.258055	-1.891	0.0597212	0.0298606
NUMERACYTOT	0.064768	0.024487	2.645	0.00865161	0.0043258
LFM	0.0198795	0.00371392	5.353	1.86279e-07	9.31397e-08

Multiple Linear Regression - Regression Statistics
Multiple R	0.618823
R-squared	0.382942
Adjusted R-squared	0.36222
F-TEST (value)	18.4799
F-TEST (DF numerator)	9
F-TEST (DF denominator)	268
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.02339
Sum Squared Residuals	1097.22

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.618823 \tabularnewline
R-squared & 0.382942 \tabularnewline
Adjusted R-squared & 0.36222 \tabularnewline
F-TEST (value) & 18.4799 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 268 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.02339 \tabularnewline
Sum Squared Residuals & 1097.22 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.618823[/C][/ROW]
[ROW][C]R-squared[/C][C]0.382942[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.36222[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]18.4799[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]268[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.02339[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1097.22[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=3

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Regression Statistics
Multiple R	0.618823
R-squared	0.382942
Adjusted R-squared	0.36222
F-TEST (value)	18.4799
F-TEST (DF numerator)	9
F-TEST (DF denominator)	268
p-value	0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation	2.02339
Sum Squared Residuals	1097.22

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.52912	1.97088
2	6	4.46457	1.53543
3	6.5	5.43744	1.06256
4	1	4.28415	-3.28415
5	1	4.55314	-3.55314
6	5.5	5.47103	0.028973
7	8.5	4.97869	3.52131
8	6.5	4.06163	2.43837
9	4.5	4.06774	0.432262
10	2	5.23364	-3.23364
11	5	4.93268	0.067324
12	0.5	4.25595	-3.75595
13	5	3.58002	1.41998
14	5	5.22831	-0.228311
15	2.5	2.60718	-0.107181
16	5	4.12139	0.878606
17	5.5	4.772	0.728002
18	3.5	4.37631	-0.876314
19	3	5.22502	-2.22502
20	4	3.53844	0.46156
21	0.5	3.99474	-3.49474
22	6.5	4.49916	2.00084
23	4.5	6.25041	-1.75041
24	7.5	4.90243	2.59757
25	5.5	4.68379	0.816209
26	4	5.50778	-1.50778
27	7.5	5.85552	1.64448
28	7	4.80918	2.19082
29	4	4.54388	-0.543883
30	5.5	4.53369	0.966308
31	2.5	3.66943	-1.16943
32	5.5	5.14567	0.354334
33	3.5	4.2535	-0.753499
34	2.5	4.5335	-2.0335
35	4.5	3.68554	0.814456
36	4.5	3.55891	0.941089
37	4.5	4.24065	0.25935
38	6	4.60771	1.39229
39	2.5	5.05815	-2.55815
40	5	5.32747	-0.327466
41	0	4.30866	-4.30866
42	5	4.74592	0.254081
43	6.5	4.92859	1.57141
44	5	4.9014	0.0985982
45	6	3.57801	2.42199
46	4.5	5.75929	-1.25929
47	5.5	3.48966	2.01034
48	1	3.91778	-2.91778
49	7.5	3.47782	4.02218
50	6	4.43278	1.56722
51	5	4.63847	0.361527
52	1	3.08802	-2.08802
53	5	4.51283	0.487173
54	6.5	5.21104	1.28896
55	7	3.82497	3.17503
56	4.5	4.09152	0.408484
57	0	5.30815	-5.30815
58	8.5	3.76448	4.73552
59	3.5	3.20272	0.297284
60	7.5	4.96123	2.53877
61	3.5	5.24525	-1.74525
62	6	5.25776	0.742238
63	1.5	3.88042	-2.38042
64	9	5.64109	3.35891
65	3.5	5.70609	-2.20609
66	3.5	3.80022	-0.300218
67	4	5.2391	-1.2391
68	6.5	5.7964	0.703596
69	7.5	5.10004	2.39996
70	6	4.99345	1.00655
71	5	6.01346	-1.01346
72	5.5	4.50689	0.993106
73	3.5	4.61129	-1.11129
74	7.5	4.67556	2.82444
75	6.5	4.19359	2.30641
76	NA	NA	1.54626
77	6.5	4.99051	1.50949
78	6.5	4.59505	1.90495
79	7	7.39383	-0.393825
80	3.5	5.79122	-2.29122
81	1.5	2.36417	-0.864169
82	4	0.926948	3.07305
83	7.5	7.55691	-0.0569074
84	4.5	8.6093	-4.1093
85	0	1.4594	-1.4594
86	3.5	2.66458	0.835417
87	5.5	4.18463	1.31537
88	5	4.56451	0.435493
89	4.5	6.85075	-2.35075
90	2.5	0.157511	2.34249
91	7.5	4.49642	3.00358
92	7	11.7594	-4.75943
93	0	0.480632	-0.480632
94	4.5	6.52871	-2.02871
95	3	5.86501	-2.86501
96	1.5	3.03577	-1.53577
97	3.5	6.23178	-2.73178
98	2.5	1.41168	1.08832
99	5.5	2.12034	3.37966
100	8	11.3068	-3.30683
101	1	-0.299211	1.29921
102	5	4.9607	0.0392991
103	4.5	4.873	-0.373004
104	3	4.4918	-1.4918
105	3	-0.750058	3.75006
106	8	9.84013	-1.84013
107	2.5	-0.355092	2.85509
108	7	11.1925	-4.19248
109	0	2.66226	-2.66226
110	1	2.2301	-1.2301
111	3.5	2.97586	0.524144
112	5.5	4.19489	1.30511
113	5.5	10.9363	-5.43634
114	0.5	-1.08525	1.58525
115	7.5	5.99864	1.50136
116	9	7.20662	1.79338
117	9.5	9.76271	-0.262707
118	8.5	8.16945	0.330549
119	7	7.93551	-0.935508
120	8	6.25829	1.74171
121	10	10.7169	-0.716872
122	7	4.60268	2.39732
123	8.5	7.65006	0.849935
124	9	4.55176	4.44824
125	9.5	11.8497	-2.34969
126	4	4.23984	-0.239835
127	6	5.23512	0.764879
128	8	8.66849	-0.668494
129	5.5	3.91065	1.58935
130	9.5	8.81494	0.685055
131	7.5	7.70203	-0.20203
132	7	7.53728	-0.537277
133	7.5	5.98024	1.51976
134	8	7.2061	0.7939
135	7	6.01018	0.989816
136	7	7.07926	-0.0792601
137	6	3.13076	2.86924
138	10	12.4954	-2.49536
139	2.5	1.34531	1.15469
140	9	7.98486	1.01514
141	8	9.03023	-1.03023
142	6	5.11187	0.888127
143	8.5	8.64065	-0.140653
144	6	3.88999	2.11001
145	9	9.00089	-0.000888765
146	8	7.29961	0.700394
147	9	10.1671	-1.16708
148	5.5	5.47015	0.0298521
149	7	8.37671	-1.37671
150	5.5	4.77288	0.727119
151	9	14.6894	-5.68937
152	2	0.566644	1.43336
153	8.5	7.38313	1.11687
154	9	9.06384	-0.0638361
155	8.5	6.33965	2.16035
156	9	8.5969	0.4031
157	7.5	5.76339	1.73661
158	10	8.19711	1.80289
159	9	10.0971	-1.09708
160	7.5	8.76395	-1.26395
161	6	4.24635	1.75365
162	10.5	8.93032	1.56968
163	8.5	8.98876	-0.488758
164	8	2.80156	5.19844
165	10	9.40304	0.596962
166	10.5	10.3909	0.109072
167	6.5	5.51767	0.982326
168	9.5	8.46483	1.03517
169	8.5	8.80487	-0.304865
170	7.5	9.90684	-2.40684
171	5	4.38055	0.619447
172	8	6.14823	1.85177
173	10	11.5875	-1.58746
174	7	7.72318	-0.723178
175	7.5	8.16677	-0.666771
176	7.5	5.25226	2.24774
177	9.5	10.5838	-1.08382
178	6	4.03666	1.96334
179	10	11.2494	-1.24941
180	7	9.88748	-2.88748
181	3	4.92195	-1.92195
182	6	7.33651	-1.33651
183	7	4.74787	2.25213
184	10	10.4773	-0.4773
185	7	11.8949	-4.89486
186	3.5	3.79462	-0.294622
187	8	6.15919	1.84081
188	10	12.6602	-2.66019
189	5.5	7.69382	-2.19382
190	6	5.7663	0.233702
191	6.5	6.96715	-0.467152
192	6.5	4.50228	1.99772
193	8.5	10.9935	-2.49346
194	4	1.94483	2.05517
195	9.5	8.91321	0.586794
196	8	7.32139	0.678614
197	8.5	11.1539	-2.65388
198	5.5	5.17908	0.320919
199	7	5.08074	1.91926
200	9	8.98494	0.015061
201	8	8.10534	-0.105344
202	10	9.03134	0.968658
203	8	9.43818	-1.43818
204	6	6.04835	-0.0483456
205	8	9.529	-1.529
206	5	3.12211	1.87789
207	9	9.38852	-0.388525
208	4.5	3.05595	1.44405
209	8.5	5.97959	2.52041
210	9.5	7.94484	1.55516
211	8.5	7.39803	1.10197
212	7.5	7.4734	0.0265972
213	7.5	8.8056	-1.3056
214	5	4.8747	0.125296
215	7	6.98299	0.017006
216	8	8.64969	-0.649685
217	5.5	4.25223	1.24777
218	8.5	6.97279	1.52721
219	9.5	9.12494	0.375064
220	7	7.64485	-0.644854
221	8	6.7985	1.2015
222	8.5	11.0597	-2.55968
223	3.5	4.33578	-0.835776
224	6.5	6.7109	-0.210901
225	6.5	4.07725	2.42275
226	10.5	9.12823	1.37177
227	8.5	7.92344	0.576561
228	8	5.00797	2.99203
229	10	6.74641	3.25359
230	10	8.28207	1.71793
231	9.5	7.58236	1.91764
232	9	6.79701	2.20299
233	10	9.38394	0.616056
234	7.5	10.5903	-3.09029
235	4.5	5.26816	-0.768164
236	4.5	9.75652	-5.25652
237	0.5	0.682847	-0.182847
238	6.5	8.80213	-2.30213
239	4.5	4.63173	-0.131728
240	5.5	6.99635	-1.49635
241	5	6.16205	-1.16205
242	6	8.43336	-2.43336
243	4	3.28589	0.714115
244	8	7.24683	0.753168
245	10.5	11.5686	-1.06859
246	6.5	5.90564	0.594358
247	8	7.73398	0.266018
248	8.5	9.94369	-1.44369
249	5.5	5.93024	-0.430238
250	7	8.88481	-1.88481
251	5	8.79795	-3.79795
252	3.5	4.92811	-1.42811
253	5	3.28958	1.71042
254	9	7.87439	1.12561
255	8.5	11.7738	-3.27381
256	5	3.77201	1.22799
257	9.5	12.9848	-3.48477
258	3	7.95535	-4.95535
259	1.5	3.0838	-1.5838
260	6	12.8508	-6.85082
261	0.5	0.791158	-0.291158
262	6.5	6.78518	-0.285177
263	7.5	9.85112	-2.35112
264	4.5	3.76282	0.737183
265	8	6.54019	1.45981
266	9	8.46146	0.538544
267	7.5	6.6173	0.882701
268	8.5	8.5058	-0.00579932
269	7	5.43618	1.56382
270	9.5	9.40873	0.0912737
271	6.5	4.63532	1.86468
272	9.5	10.4084	-0.90837
273	6	4.3085	1.6915
274	8	6.72455	1.27545
275	9.5	8.82376	0.676235
276	8	7.72175	0.278254
277	8	7.12122	0.878778
278	9	10.2275	-1.22748
279	5	NA	NA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 7.5 & 5.52912 & 1.97088 \tabularnewline
2 & 6 & 4.46457 & 1.53543 \tabularnewline
3 & 6.5 & 5.43744 & 1.06256 \tabularnewline
4 & 1 & 4.28415 & -3.28415 \tabularnewline
5 & 1 & 4.55314 & -3.55314 \tabularnewline
6 & 5.5 & 5.47103 & 0.028973 \tabularnewline
7 & 8.5 & 4.97869 & 3.52131 \tabularnewline
8 & 6.5 & 4.06163 & 2.43837 \tabularnewline
9 & 4.5 & 4.06774 & 0.432262 \tabularnewline
10 & 2 & 5.23364 & -3.23364 \tabularnewline
11 & 5 & 4.93268 & 0.067324 \tabularnewline
12 & 0.5 & 4.25595 & -3.75595 \tabularnewline
13 & 5 & 3.58002 & 1.41998 \tabularnewline
14 & 5 & 5.22831 & -0.228311 \tabularnewline
15 & 2.5 & 2.60718 & -0.107181 \tabularnewline
16 & 5 & 4.12139 & 0.878606 \tabularnewline
17 & 5.5 & 4.772 & 0.728002 \tabularnewline
18 & 3.5 & 4.37631 & -0.876314 \tabularnewline
19 & 3 & 5.22502 & -2.22502 \tabularnewline
20 & 4 & 3.53844 & 0.46156 \tabularnewline
21 & 0.5 & 3.99474 & -3.49474 \tabularnewline
22 & 6.5 & 4.49916 & 2.00084 \tabularnewline
23 & 4.5 & 6.25041 & -1.75041 \tabularnewline
24 & 7.5 & 4.90243 & 2.59757 \tabularnewline
25 & 5.5 & 4.68379 & 0.816209 \tabularnewline
26 & 4 & 5.50778 & -1.50778 \tabularnewline
27 & 7.5 & 5.85552 & 1.64448 \tabularnewline
28 & 7 & 4.80918 & 2.19082 \tabularnewline
29 & 4 & 4.54388 & -0.543883 \tabularnewline
30 & 5.5 & 4.53369 & 0.966308 \tabularnewline
31 & 2.5 & 3.66943 & -1.16943 \tabularnewline
32 & 5.5 & 5.14567 & 0.354334 \tabularnewline
33 & 3.5 & 4.2535 & -0.753499 \tabularnewline
34 & 2.5 & 4.5335 & -2.0335 \tabularnewline
35 & 4.5 & 3.68554 & 0.814456 \tabularnewline
36 & 4.5 & 3.55891 & 0.941089 \tabularnewline
37 & 4.5 & 4.24065 & 0.25935 \tabularnewline
38 & 6 & 4.60771 & 1.39229 \tabularnewline
39 & 2.5 & 5.05815 & -2.55815 \tabularnewline
40 & 5 & 5.32747 & -0.327466 \tabularnewline
41 & 0 & 4.30866 & -4.30866 \tabularnewline
42 & 5 & 4.74592 & 0.254081 \tabularnewline
43 & 6.5 & 4.92859 & 1.57141 \tabularnewline
44 & 5 & 4.9014 & 0.0985982 \tabularnewline
45 & 6 & 3.57801 & 2.42199 \tabularnewline
46 & 4.5 & 5.75929 & -1.25929 \tabularnewline
47 & 5.5 & 3.48966 & 2.01034 \tabularnewline
48 & 1 & 3.91778 & -2.91778 \tabularnewline
49 & 7.5 & 3.47782 & 4.02218 \tabularnewline
50 & 6 & 4.43278 & 1.56722 \tabularnewline
51 & 5 & 4.63847 & 0.361527 \tabularnewline
52 & 1 & 3.08802 & -2.08802 \tabularnewline
53 & 5 & 4.51283 & 0.487173 \tabularnewline
54 & 6.5 & 5.21104 & 1.28896 \tabularnewline
55 & 7 & 3.82497 & 3.17503 \tabularnewline
56 & 4.5 & 4.09152 & 0.408484 \tabularnewline
57 & 0 & 5.30815 & -5.30815 \tabularnewline
58 & 8.5 & 3.76448 & 4.73552 \tabularnewline
59 & 3.5 & 3.20272 & 0.297284 \tabularnewline
60 & 7.5 & 4.96123 & 2.53877 \tabularnewline
61 & 3.5 & 5.24525 & -1.74525 \tabularnewline
62 & 6 & 5.25776 & 0.742238 \tabularnewline
63 & 1.5 & 3.88042 & -2.38042 \tabularnewline
64 & 9 & 5.64109 & 3.35891 \tabularnewline
65 & 3.5 & 5.70609 & -2.20609 \tabularnewline
66 & 3.5 & 3.80022 & -0.300218 \tabularnewline
67 & 4 & 5.2391 & -1.2391 \tabularnewline
68 & 6.5 & 5.7964 & 0.703596 \tabularnewline
69 & 7.5 & 5.10004 & 2.39996 \tabularnewline
70 & 6 & 4.99345 & 1.00655 \tabularnewline
71 & 5 & 6.01346 & -1.01346 \tabularnewline
72 & 5.5 & 4.50689 & 0.993106 \tabularnewline
73 & 3.5 & 4.61129 & -1.11129 \tabularnewline
74 & 7.5 & 4.67556 & 2.82444 \tabularnewline
75 & 6.5 & 4.19359 & 2.30641 \tabularnewline
76 & NA & NA & 1.54626 \tabularnewline
77 & 6.5 & 4.99051 & 1.50949 \tabularnewline
78 & 6.5 & 4.59505 & 1.90495 \tabularnewline
79 & 7 & 7.39383 & -0.393825 \tabularnewline
80 & 3.5 & 5.79122 & -2.29122 \tabularnewline
81 & 1.5 & 2.36417 & -0.864169 \tabularnewline
82 & 4 & 0.926948 & 3.07305 \tabularnewline
83 & 7.5 & 7.55691 & -0.0569074 \tabularnewline
84 & 4.5 & 8.6093 & -4.1093 \tabularnewline
85 & 0 & 1.4594 & -1.4594 \tabularnewline
86 & 3.5 & 2.66458 & 0.835417 \tabularnewline
87 & 5.5 & 4.18463 & 1.31537 \tabularnewline
88 & 5 & 4.56451 & 0.435493 \tabularnewline
89 & 4.5 & 6.85075 & -2.35075 \tabularnewline
90 & 2.5 & 0.157511 & 2.34249 \tabularnewline
91 & 7.5 & 4.49642 & 3.00358 \tabularnewline
92 & 7 & 11.7594 & -4.75943 \tabularnewline
93 & 0 & 0.480632 & -0.480632 \tabularnewline
94 & 4.5 & 6.52871 & -2.02871 \tabularnewline
95 & 3 & 5.86501 & -2.86501 \tabularnewline
96 & 1.5 & 3.03577 & -1.53577 \tabularnewline
97 & 3.5 & 6.23178 & -2.73178 \tabularnewline
98 & 2.5 & 1.41168 & 1.08832 \tabularnewline
99 & 5.5 & 2.12034 & 3.37966 \tabularnewline
100 & 8 & 11.3068 & -3.30683 \tabularnewline
101 & 1 & -0.299211 & 1.29921 \tabularnewline
102 & 5 & 4.9607 & 0.0392991 \tabularnewline
103 & 4.5 & 4.873 & -0.373004 \tabularnewline
104 & 3 & 4.4918 & -1.4918 \tabularnewline
105 & 3 & -0.750058 & 3.75006 \tabularnewline
106 & 8 & 9.84013 & -1.84013 \tabularnewline
107 & 2.5 & -0.355092 & 2.85509 \tabularnewline
108 & 7 & 11.1925 & -4.19248 \tabularnewline
109 & 0 & 2.66226 & -2.66226 \tabularnewline
110 & 1 & 2.2301 & -1.2301 \tabularnewline
111 & 3.5 & 2.97586 & 0.524144 \tabularnewline
112 & 5.5 & 4.19489 & 1.30511 \tabularnewline
113 & 5.5 & 10.9363 & -5.43634 \tabularnewline
114 & 0.5 & -1.08525 & 1.58525 \tabularnewline
115 & 7.5 & 5.99864 & 1.50136 \tabularnewline
116 & 9 & 7.20662 & 1.79338 \tabularnewline
117 & 9.5 & 9.76271 & -0.262707 \tabularnewline
118 & 8.5 & 8.16945 & 0.330549 \tabularnewline
119 & 7 & 7.93551 & -0.935508 \tabularnewline
120 & 8 & 6.25829 & 1.74171 \tabularnewline
121 & 10 & 10.7169 & -0.716872 \tabularnewline
122 & 7 & 4.60268 & 2.39732 \tabularnewline
123 & 8.5 & 7.65006 & 0.849935 \tabularnewline
124 & 9 & 4.55176 & 4.44824 \tabularnewline
125 & 9.5 & 11.8497 & -2.34969 \tabularnewline
126 & 4 & 4.23984 & -0.239835 \tabularnewline
127 & 6 & 5.23512 & 0.764879 \tabularnewline
128 & 8 & 8.66849 & -0.668494 \tabularnewline
129 & 5.5 & 3.91065 & 1.58935 \tabularnewline
130 & 9.5 & 8.81494 & 0.685055 \tabularnewline
131 & 7.5 & 7.70203 & -0.20203 \tabularnewline
132 & 7 & 7.53728 & -0.537277 \tabularnewline
133 & 7.5 & 5.98024 & 1.51976 \tabularnewline
134 & 8 & 7.2061 & 0.7939 \tabularnewline
135 & 7 & 6.01018 & 0.989816 \tabularnewline
136 & 7 & 7.07926 & -0.0792601 \tabularnewline
137 & 6 & 3.13076 & 2.86924 \tabularnewline
138 & 10 & 12.4954 & -2.49536 \tabularnewline
139 & 2.5 & 1.34531 & 1.15469 \tabularnewline
140 & 9 & 7.98486 & 1.01514 \tabularnewline
141 & 8 & 9.03023 & -1.03023 \tabularnewline
142 & 6 & 5.11187 & 0.888127 \tabularnewline
143 & 8.5 & 8.64065 & -0.140653 \tabularnewline
144 & 6 & 3.88999 & 2.11001 \tabularnewline
145 & 9 & 9.00089 & -0.000888765 \tabularnewline
146 & 8 & 7.29961 & 0.700394 \tabularnewline
147 & 9 & 10.1671 & -1.16708 \tabularnewline
148 & 5.5 & 5.47015 & 0.0298521 \tabularnewline
149 & 7 & 8.37671 & -1.37671 \tabularnewline
150 & 5.5 & 4.77288 & 0.727119 \tabularnewline
151 & 9 & 14.6894 & -5.68937 \tabularnewline
152 & 2 & 0.566644 & 1.43336 \tabularnewline
153 & 8.5 & 7.38313 & 1.11687 \tabularnewline
154 & 9 & 9.06384 & -0.0638361 \tabularnewline
155 & 8.5 & 6.33965 & 2.16035 \tabularnewline
156 & 9 & 8.5969 & 0.4031 \tabularnewline
157 & 7.5 & 5.76339 & 1.73661 \tabularnewline
158 & 10 & 8.19711 & 1.80289 \tabularnewline
159 & 9 & 10.0971 & -1.09708 \tabularnewline
160 & 7.5 & 8.76395 & -1.26395 \tabularnewline
161 & 6 & 4.24635 & 1.75365 \tabularnewline
162 & 10.5 & 8.93032 & 1.56968 \tabularnewline
163 & 8.5 & 8.98876 & -0.488758 \tabularnewline
164 & 8 & 2.80156 & 5.19844 \tabularnewline
165 & 10 & 9.40304 & 0.596962 \tabularnewline
166 & 10.5 & 10.3909 & 0.109072 \tabularnewline
167 & 6.5 & 5.51767 & 0.982326 \tabularnewline
168 & 9.5 & 8.46483 & 1.03517 \tabularnewline
169 & 8.5 & 8.80487 & -0.304865 \tabularnewline
170 & 7.5 & 9.90684 & -2.40684 \tabularnewline
171 & 5 & 4.38055 & 0.619447 \tabularnewline
172 & 8 & 6.14823 & 1.85177 \tabularnewline
173 & 10 & 11.5875 & -1.58746 \tabularnewline
174 & 7 & 7.72318 & -0.723178 \tabularnewline
175 & 7.5 & 8.16677 & -0.666771 \tabularnewline
176 & 7.5 & 5.25226 & 2.24774 \tabularnewline
177 & 9.5 & 10.5838 & -1.08382 \tabularnewline
178 & 6 & 4.03666 & 1.96334 \tabularnewline
179 & 10 & 11.2494 & -1.24941 \tabularnewline
180 & 7 & 9.88748 & -2.88748 \tabularnewline
181 & 3 & 4.92195 & -1.92195 \tabularnewline
182 & 6 & 7.33651 & -1.33651 \tabularnewline
183 & 7 & 4.74787 & 2.25213 \tabularnewline
184 & 10 & 10.4773 & -0.4773 \tabularnewline
185 & 7 & 11.8949 & -4.89486 \tabularnewline
186 & 3.5 & 3.79462 & -0.294622 \tabularnewline
187 & 8 & 6.15919 & 1.84081 \tabularnewline
188 & 10 & 12.6602 & -2.66019 \tabularnewline
189 & 5.5 & 7.69382 & -2.19382 \tabularnewline
190 & 6 & 5.7663 & 0.233702 \tabularnewline
191 & 6.5 & 6.96715 & -0.467152 \tabularnewline
192 & 6.5 & 4.50228 & 1.99772 \tabularnewline
193 & 8.5 & 10.9935 & -2.49346 \tabularnewline
194 & 4 & 1.94483 & 2.05517 \tabularnewline
195 & 9.5 & 8.91321 & 0.586794 \tabularnewline
196 & 8 & 7.32139 & 0.678614 \tabularnewline
197 & 8.5 & 11.1539 & -2.65388 \tabularnewline
198 & 5.5 & 5.17908 & 0.320919 \tabularnewline
199 & 7 & 5.08074 & 1.91926 \tabularnewline
200 & 9 & 8.98494 & 0.015061 \tabularnewline
201 & 8 & 8.10534 & -0.105344 \tabularnewline
202 & 10 & 9.03134 & 0.968658 \tabularnewline
203 & 8 & 9.43818 & -1.43818 \tabularnewline
204 & 6 & 6.04835 & -0.0483456 \tabularnewline
205 & 8 & 9.529 & -1.529 \tabularnewline
206 & 5 & 3.12211 & 1.87789 \tabularnewline
207 & 9 & 9.38852 & -0.388525 \tabularnewline
208 & 4.5 & 3.05595 & 1.44405 \tabularnewline
209 & 8.5 & 5.97959 & 2.52041 \tabularnewline
210 & 9.5 & 7.94484 & 1.55516 \tabularnewline
211 & 8.5 & 7.39803 & 1.10197 \tabularnewline
212 & 7.5 & 7.4734 & 0.0265972 \tabularnewline
213 & 7.5 & 8.8056 & -1.3056 \tabularnewline
214 & 5 & 4.8747 & 0.125296 \tabularnewline
215 & 7 & 6.98299 & 0.017006 \tabularnewline
216 & 8 & 8.64969 & -0.649685 \tabularnewline
217 & 5.5 & 4.25223 & 1.24777 \tabularnewline
218 & 8.5 & 6.97279 & 1.52721 \tabularnewline
219 & 9.5 & 9.12494 & 0.375064 \tabularnewline
220 & 7 & 7.64485 & -0.644854 \tabularnewline
221 & 8 & 6.7985 & 1.2015 \tabularnewline
222 & 8.5 & 11.0597 & -2.55968 \tabularnewline
223 & 3.5 & 4.33578 & -0.835776 \tabularnewline
224 & 6.5 & 6.7109 & -0.210901 \tabularnewline
225 & 6.5 & 4.07725 & 2.42275 \tabularnewline
226 & 10.5 & 9.12823 & 1.37177 \tabularnewline
227 & 8.5 & 7.92344 & 0.576561 \tabularnewline
228 & 8 & 5.00797 & 2.99203 \tabularnewline
229 & 10 & 6.74641 & 3.25359 \tabularnewline
230 & 10 & 8.28207 & 1.71793 \tabularnewline
231 & 9.5 & 7.58236 & 1.91764 \tabularnewline
232 & 9 & 6.79701 & 2.20299 \tabularnewline
233 & 10 & 9.38394 & 0.616056 \tabularnewline
234 & 7.5 & 10.5903 & -3.09029 \tabularnewline
235 & 4.5 & 5.26816 & -0.768164 \tabularnewline
236 & 4.5 & 9.75652 & -5.25652 \tabularnewline
237 & 0.5 & 0.682847 & -0.182847 \tabularnewline
238 & 6.5 & 8.80213 & -2.30213 \tabularnewline
239 & 4.5 & 4.63173 & -0.131728 \tabularnewline
240 & 5.5 & 6.99635 & -1.49635 \tabularnewline
241 & 5 & 6.16205 & -1.16205 \tabularnewline
242 & 6 & 8.43336 & -2.43336 \tabularnewline
243 & 4 & 3.28589 & 0.714115 \tabularnewline
244 & 8 & 7.24683 & 0.753168 \tabularnewline
245 & 10.5 & 11.5686 & -1.06859 \tabularnewline
246 & 6.5 & 5.90564 & 0.594358 \tabularnewline
247 & 8 & 7.73398 & 0.266018 \tabularnewline
248 & 8.5 & 9.94369 & -1.44369 \tabularnewline
249 & 5.5 & 5.93024 & -0.430238 \tabularnewline
250 & 7 & 8.88481 & -1.88481 \tabularnewline
251 & 5 & 8.79795 & -3.79795 \tabularnewline
252 & 3.5 & 4.92811 & -1.42811 \tabularnewline
253 & 5 & 3.28958 & 1.71042 \tabularnewline
254 & 9 & 7.87439 & 1.12561 \tabularnewline
255 & 8.5 & 11.7738 & -3.27381 \tabularnewline
256 & 5 & 3.77201 & 1.22799 \tabularnewline
257 & 9.5 & 12.9848 & -3.48477 \tabularnewline
258 & 3 & 7.95535 & -4.95535 \tabularnewline
259 & 1.5 & 3.0838 & -1.5838 \tabularnewline
260 & 6 & 12.8508 & -6.85082 \tabularnewline
261 & 0.5 & 0.791158 & -0.291158 \tabularnewline
262 & 6.5 & 6.78518 & -0.285177 \tabularnewline
263 & 7.5 & 9.85112 & -2.35112 \tabularnewline
264 & 4.5 & 3.76282 & 0.737183 \tabularnewline
265 & 8 & 6.54019 & 1.45981 \tabularnewline
266 & 9 & 8.46146 & 0.538544 \tabularnewline
267 & 7.5 & 6.6173 & 0.882701 \tabularnewline
268 & 8.5 & 8.5058 & -0.00579932 \tabularnewline
269 & 7 & 5.43618 & 1.56382 \tabularnewline
270 & 9.5 & 9.40873 & 0.0912737 \tabularnewline
271 & 6.5 & 4.63532 & 1.86468 \tabularnewline
272 & 9.5 & 10.4084 & -0.90837 \tabularnewline
273 & 6 & 4.3085 & 1.6915 \tabularnewline
274 & 8 & 6.72455 & 1.27545 \tabularnewline
275 & 9.5 & 8.82376 & 0.676235 \tabularnewline
276 & 8 & 7.72175 & 0.278254 \tabularnewline
277 & 8 & 7.12122 & 0.878778 \tabularnewline
278 & 9 & 10.2275 & -1.22748 \tabularnewline
279 & 5 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]7.5[/C][C]5.52912[/C][C]1.97088[/C][/ROW]
[ROW][C]2[/C][C]6[/C][C]4.46457[/C][C]1.53543[/C][/ROW]
[ROW][C]3[/C][C]6.5[/C][C]5.43744[/C][C]1.06256[/C][/ROW]
[ROW][C]4[/C][C]1[/C][C]4.28415[/C][C]-3.28415[/C][/ROW]
[ROW][C]5[/C][C]1[/C][C]4.55314[/C][C]-3.55314[/C][/ROW]
[ROW][C]6[/C][C]5.5[/C][C]5.47103[/C][C]0.028973[/C][/ROW]
[ROW][C]7[/C][C]8.5[/C][C]4.97869[/C][C]3.52131[/C][/ROW]
[ROW][C]8[/C][C]6.5[/C][C]4.06163[/C][C]2.43837[/C][/ROW]
[ROW][C]9[/C][C]4.5[/C][C]4.06774[/C][C]0.432262[/C][/ROW]
[ROW][C]10[/C][C]2[/C][C]5.23364[/C][C]-3.23364[/C][/ROW]
[ROW][C]11[/C][C]5[/C][C]4.93268[/C][C]0.067324[/C][/ROW]
[ROW][C]12[/C][C]0.5[/C][C]4.25595[/C][C]-3.75595[/C][/ROW]
[ROW][C]13[/C][C]5[/C][C]3.58002[/C][C]1.41998[/C][/ROW]
[ROW][C]14[/C][C]5[/C][C]5.22831[/C][C]-0.228311[/C][/ROW]
[ROW][C]15[/C][C]2.5[/C][C]2.60718[/C][C]-0.107181[/C][/ROW]
[ROW][C]16[/C][C]5[/C][C]4.12139[/C][C]0.878606[/C][/ROW]
[ROW][C]17[/C][C]5.5[/C][C]4.772[/C][C]0.728002[/C][/ROW]
[ROW][C]18[/C][C]3.5[/C][C]4.37631[/C][C]-0.876314[/C][/ROW]
[ROW][C]19[/C][C]3[/C][C]5.22502[/C][C]-2.22502[/C][/ROW]
[ROW][C]20[/C][C]4[/C][C]3.53844[/C][C]0.46156[/C][/ROW]
[ROW][C]21[/C][C]0.5[/C][C]3.99474[/C][C]-3.49474[/C][/ROW]
[ROW][C]22[/C][C]6.5[/C][C]4.49916[/C][C]2.00084[/C][/ROW]
[ROW][C]23[/C][C]4.5[/C][C]6.25041[/C][C]-1.75041[/C][/ROW]
[ROW][C]24[/C][C]7.5[/C][C]4.90243[/C][C]2.59757[/C][/ROW]
[ROW][C]25[/C][C]5.5[/C][C]4.68379[/C][C]0.816209[/C][/ROW]
[ROW][C]26[/C][C]4[/C][C]5.50778[/C][C]-1.50778[/C][/ROW]
[ROW][C]27[/C][C]7.5[/C][C]5.85552[/C][C]1.64448[/C][/ROW]
[ROW][C]28[/C][C]7[/C][C]4.80918[/C][C]2.19082[/C][/ROW]
[ROW][C]29[/C][C]4[/C][C]4.54388[/C][C]-0.543883[/C][/ROW]
[ROW][C]30[/C][C]5.5[/C][C]4.53369[/C][C]0.966308[/C][/ROW]
[ROW][C]31[/C][C]2.5[/C][C]3.66943[/C][C]-1.16943[/C][/ROW]
[ROW][C]32[/C][C]5.5[/C][C]5.14567[/C][C]0.354334[/C][/ROW]
[ROW][C]33[/C][C]3.5[/C][C]4.2535[/C][C]-0.753499[/C][/ROW]
[ROW][C]34[/C][C]2.5[/C][C]4.5335[/C][C]-2.0335[/C][/ROW]
[ROW][C]35[/C][C]4.5[/C][C]3.68554[/C][C]0.814456[/C][/ROW]
[ROW][C]36[/C][C]4.5[/C][C]3.55891[/C][C]0.941089[/C][/ROW]
[ROW][C]37[/C][C]4.5[/C][C]4.24065[/C][C]0.25935[/C][/ROW]
[ROW][C]38[/C][C]6[/C][C]4.60771[/C][C]1.39229[/C][/ROW]
[ROW][C]39[/C][C]2.5[/C][C]5.05815[/C][C]-2.55815[/C][/ROW]
[ROW][C]40[/C][C]5[/C][C]5.32747[/C][C]-0.327466[/C][/ROW]
[ROW][C]41[/C][C]0[/C][C]4.30866[/C][C]-4.30866[/C][/ROW]
[ROW][C]42[/C][C]5[/C][C]4.74592[/C][C]0.254081[/C][/ROW]
[ROW][C]43[/C][C]6.5[/C][C]4.92859[/C][C]1.57141[/C][/ROW]
[ROW][C]44[/C][C]5[/C][C]4.9014[/C][C]0.0985982[/C][/ROW]
[ROW][C]45[/C][C]6[/C][C]3.57801[/C][C]2.42199[/C][/ROW]
[ROW][C]46[/C][C]4.5[/C][C]5.75929[/C][C]-1.25929[/C][/ROW]
[ROW][C]47[/C][C]5.5[/C][C]3.48966[/C][C]2.01034[/C][/ROW]
[ROW][C]48[/C][C]1[/C][C]3.91778[/C][C]-2.91778[/C][/ROW]
[ROW][C]49[/C][C]7.5[/C][C]3.47782[/C][C]4.02218[/C][/ROW]
[ROW][C]50[/C][C]6[/C][C]4.43278[/C][C]1.56722[/C][/ROW]
[ROW][C]51[/C][C]5[/C][C]4.63847[/C][C]0.361527[/C][/ROW]
[ROW][C]52[/C][C]1[/C][C]3.08802[/C][C]-2.08802[/C][/ROW]
[ROW][C]53[/C][C]5[/C][C]4.51283[/C][C]0.487173[/C][/ROW]
[ROW][C]54[/C][C]6.5[/C][C]5.21104[/C][C]1.28896[/C][/ROW]
[ROW][C]55[/C][C]7[/C][C]3.82497[/C][C]3.17503[/C][/ROW]
[ROW][C]56[/C][C]4.5[/C][C]4.09152[/C][C]0.408484[/C][/ROW]
[ROW][C]57[/C][C]0[/C][C]5.30815[/C][C]-5.30815[/C][/ROW]
[ROW][C]58[/C][C]8.5[/C][C]3.76448[/C][C]4.73552[/C][/ROW]
[ROW][C]59[/C][C]3.5[/C][C]3.20272[/C][C]0.297284[/C][/ROW]
[ROW][C]60[/C][C]7.5[/C][C]4.96123[/C][C]2.53877[/C][/ROW]
[ROW][C]61[/C][C]3.5[/C][C]5.24525[/C][C]-1.74525[/C][/ROW]
[ROW][C]62[/C][C]6[/C][C]5.25776[/C][C]0.742238[/C][/ROW]
[ROW][C]63[/C][C]1.5[/C][C]3.88042[/C][C]-2.38042[/C][/ROW]
[ROW][C]64[/C][C]9[/C][C]5.64109[/C][C]3.35891[/C][/ROW]
[ROW][C]65[/C][C]3.5[/C][C]5.70609[/C][C]-2.20609[/C][/ROW]
[ROW][C]66[/C][C]3.5[/C][C]3.80022[/C][C]-0.300218[/C][/ROW]
[ROW][C]67[/C][C]4[/C][C]5.2391[/C][C]-1.2391[/C][/ROW]
[ROW][C]68[/C][C]6.5[/C][C]5.7964[/C][C]0.703596[/C][/ROW]
[ROW][C]69[/C][C]7.5[/C][C]5.10004[/C][C]2.39996[/C][/ROW]
[ROW][C]70[/C][C]6[/C][C]4.99345[/C][C]1.00655[/C][/ROW]
[ROW][C]71[/C][C]5[/C][C]6.01346[/C][C]-1.01346[/C][/ROW]
[ROW][C]72[/C][C]5.5[/C][C]4.50689[/C][C]0.993106[/C][/ROW]
[ROW][C]73[/C][C]3.5[/C][C]4.61129[/C][C]-1.11129[/C][/ROW]
[ROW][C]74[/C][C]7.5[/C][C]4.67556[/C][C]2.82444[/C][/ROW]
[ROW][C]75[/C][C]6.5[/C][C]4.19359[/C][C]2.30641[/C][/ROW]
[ROW][C]76[/C][C]NA[/C][C]NA[/C][C]1.54626[/C][/ROW]
[ROW][C]77[/C][C]6.5[/C][C]4.99051[/C][C]1.50949[/C][/ROW]
[ROW][C]78[/C][C]6.5[/C][C]4.59505[/C][C]1.90495[/C][/ROW]
[ROW][C]79[/C][C]7[/C][C]7.39383[/C][C]-0.393825[/C][/ROW]
[ROW][C]80[/C][C]3.5[/C][C]5.79122[/C][C]-2.29122[/C][/ROW]
[ROW][C]81[/C][C]1.5[/C][C]2.36417[/C][C]-0.864169[/C][/ROW]
[ROW][C]82[/C][C]4[/C][C]0.926948[/C][C]3.07305[/C][/ROW]
[ROW][C]83[/C][C]7.5[/C][C]7.55691[/C][C]-0.0569074[/C][/ROW]
[ROW][C]84[/C][C]4.5[/C][C]8.6093[/C][C]-4.1093[/C][/ROW]
[ROW][C]85[/C][C]0[/C][C]1.4594[/C][C]-1.4594[/C][/ROW]
[ROW][C]86[/C][C]3.5[/C][C]2.66458[/C][C]0.835417[/C][/ROW]
[ROW][C]87[/C][C]5.5[/C][C]4.18463[/C][C]1.31537[/C][/ROW]
[ROW][C]88[/C][C]5[/C][C]4.56451[/C][C]0.435493[/C][/ROW]
[ROW][C]89[/C][C]4.5[/C][C]6.85075[/C][C]-2.35075[/C][/ROW]
[ROW][C]90[/C][C]2.5[/C][C]0.157511[/C][C]2.34249[/C][/ROW]
[ROW][C]91[/C][C]7.5[/C][C]4.49642[/C][C]3.00358[/C][/ROW]
[ROW][C]92[/C][C]7[/C][C]11.7594[/C][C]-4.75943[/C][/ROW]
[ROW][C]93[/C][C]0[/C][C]0.480632[/C][C]-0.480632[/C][/ROW]
[ROW][C]94[/C][C]4.5[/C][C]6.52871[/C][C]-2.02871[/C][/ROW]
[ROW][C]95[/C][C]3[/C][C]5.86501[/C][C]-2.86501[/C][/ROW]
[ROW][C]96[/C][C]1.5[/C][C]3.03577[/C][C]-1.53577[/C][/ROW]
[ROW][C]97[/C][C]3.5[/C][C]6.23178[/C][C]-2.73178[/C][/ROW]
[ROW][C]98[/C][C]2.5[/C][C]1.41168[/C][C]1.08832[/C][/ROW]
[ROW][C]99[/C][C]5.5[/C][C]2.12034[/C][C]3.37966[/C][/ROW]
[ROW][C]100[/C][C]8[/C][C]11.3068[/C][C]-3.30683[/C][/ROW]
[ROW][C]101[/C][C]1[/C][C]-0.299211[/C][C]1.29921[/C][/ROW]
[ROW][C]102[/C][C]5[/C][C]4.9607[/C][C]0.0392991[/C][/ROW]
[ROW][C]103[/C][C]4.5[/C][C]4.873[/C][C]-0.373004[/C][/ROW]
[ROW][C]104[/C][C]3[/C][C]4.4918[/C][C]-1.4918[/C][/ROW]
[ROW][C]105[/C][C]3[/C][C]-0.750058[/C][C]3.75006[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]9.84013[/C][C]-1.84013[/C][/ROW]
[ROW][C]107[/C][C]2.5[/C][C]-0.355092[/C][C]2.85509[/C][/ROW]
[ROW][C]108[/C][C]7[/C][C]11.1925[/C][C]-4.19248[/C][/ROW]
[ROW][C]109[/C][C]0[/C][C]2.66226[/C][C]-2.66226[/C][/ROW]
[ROW][C]110[/C][C]1[/C][C]2.2301[/C][C]-1.2301[/C][/ROW]
[ROW][C]111[/C][C]3.5[/C][C]2.97586[/C][C]0.524144[/C][/ROW]
[ROW][C]112[/C][C]5.5[/C][C]4.19489[/C][C]1.30511[/C][/ROW]
[ROW][C]113[/C][C]5.5[/C][C]10.9363[/C][C]-5.43634[/C][/ROW]
[ROW][C]114[/C][C]0.5[/C][C]-1.08525[/C][C]1.58525[/C][/ROW]
[ROW][C]115[/C][C]7.5[/C][C]5.99864[/C][C]1.50136[/C][/ROW]
[ROW][C]116[/C][C]9[/C][C]7.20662[/C][C]1.79338[/C][/ROW]
[ROW][C]117[/C][C]9.5[/C][C]9.76271[/C][C]-0.262707[/C][/ROW]
[ROW][C]118[/C][C]8.5[/C][C]8.16945[/C][C]0.330549[/C][/ROW]
[ROW][C]119[/C][C]7[/C][C]7.93551[/C][C]-0.935508[/C][/ROW]
[ROW][C]120[/C][C]8[/C][C]6.25829[/C][C]1.74171[/C][/ROW]
[ROW][C]121[/C][C]10[/C][C]10.7169[/C][C]-0.716872[/C][/ROW]
[ROW][C]122[/C][C]7[/C][C]4.60268[/C][C]2.39732[/C][/ROW]
[ROW][C]123[/C][C]8.5[/C][C]7.65006[/C][C]0.849935[/C][/ROW]
[ROW][C]124[/C][C]9[/C][C]4.55176[/C][C]4.44824[/C][/ROW]
[ROW][C]125[/C][C]9.5[/C][C]11.8497[/C][C]-2.34969[/C][/ROW]
[ROW][C]126[/C][C]4[/C][C]4.23984[/C][C]-0.239835[/C][/ROW]
[ROW][C]127[/C][C]6[/C][C]5.23512[/C][C]0.764879[/C][/ROW]
[ROW][C]128[/C][C]8[/C][C]8.66849[/C][C]-0.668494[/C][/ROW]
[ROW][C]129[/C][C]5.5[/C][C]3.91065[/C][C]1.58935[/C][/ROW]
[ROW][C]130[/C][C]9.5[/C][C]8.81494[/C][C]0.685055[/C][/ROW]
[ROW][C]131[/C][C]7.5[/C][C]7.70203[/C][C]-0.20203[/C][/ROW]
[ROW][C]132[/C][C]7[/C][C]7.53728[/C][C]-0.537277[/C][/ROW]
[ROW][C]133[/C][C]7.5[/C][C]5.98024[/C][C]1.51976[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]7.2061[/C][C]0.7939[/C][/ROW]
[ROW][C]135[/C][C]7[/C][C]6.01018[/C][C]0.989816[/C][/ROW]
[ROW][C]136[/C][C]7[/C][C]7.07926[/C][C]-0.0792601[/C][/ROW]
[ROW][C]137[/C][C]6[/C][C]3.13076[/C][C]2.86924[/C][/ROW]
[ROW][C]138[/C][C]10[/C][C]12.4954[/C][C]-2.49536[/C][/ROW]
[ROW][C]139[/C][C]2.5[/C][C]1.34531[/C][C]1.15469[/C][/ROW]
[ROW][C]140[/C][C]9[/C][C]7.98486[/C][C]1.01514[/C][/ROW]
[ROW][C]141[/C][C]8[/C][C]9.03023[/C][C]-1.03023[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]5.11187[/C][C]0.888127[/C][/ROW]
[ROW][C]143[/C][C]8.5[/C][C]8.64065[/C][C]-0.140653[/C][/ROW]
[ROW][C]144[/C][C]6[/C][C]3.88999[/C][C]2.11001[/C][/ROW]
[ROW][C]145[/C][C]9[/C][C]9.00089[/C][C]-0.000888765[/C][/ROW]
[ROW][C]146[/C][C]8[/C][C]7.29961[/C][C]0.700394[/C][/ROW]
[ROW][C]147[/C][C]9[/C][C]10.1671[/C][C]-1.16708[/C][/ROW]
[ROW][C]148[/C][C]5.5[/C][C]5.47015[/C][C]0.0298521[/C][/ROW]
[ROW][C]149[/C][C]7[/C][C]8.37671[/C][C]-1.37671[/C][/ROW]
[ROW][C]150[/C][C]5.5[/C][C]4.77288[/C][C]0.727119[/C][/ROW]
[ROW][C]151[/C][C]9[/C][C]14.6894[/C][C]-5.68937[/C][/ROW]
[ROW][C]152[/C][C]2[/C][C]0.566644[/C][C]1.43336[/C][/ROW]
[ROW][C]153[/C][C]8.5[/C][C]7.38313[/C][C]1.11687[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]9.06384[/C][C]-0.0638361[/C][/ROW]
[ROW][C]155[/C][C]8.5[/C][C]6.33965[/C][C]2.16035[/C][/ROW]
[ROW][C]156[/C][C]9[/C][C]8.5969[/C][C]0.4031[/C][/ROW]
[ROW][C]157[/C][C]7.5[/C][C]5.76339[/C][C]1.73661[/C][/ROW]
[ROW][C]158[/C][C]10[/C][C]8.19711[/C][C]1.80289[/C][/ROW]
[ROW][C]159[/C][C]9[/C][C]10.0971[/C][C]-1.09708[/C][/ROW]
[ROW][C]160[/C][C]7.5[/C][C]8.76395[/C][C]-1.26395[/C][/ROW]
[ROW][C]161[/C][C]6[/C][C]4.24635[/C][C]1.75365[/C][/ROW]
[ROW][C]162[/C][C]10.5[/C][C]8.93032[/C][C]1.56968[/C][/ROW]
[ROW][C]163[/C][C]8.5[/C][C]8.98876[/C][C]-0.488758[/C][/ROW]
[ROW][C]164[/C][C]8[/C][C]2.80156[/C][C]5.19844[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]9.40304[/C][C]0.596962[/C][/ROW]
[ROW][C]166[/C][C]10.5[/C][C]10.3909[/C][C]0.109072[/C][/ROW]
[ROW][C]167[/C][C]6.5[/C][C]5.51767[/C][C]0.982326[/C][/ROW]
[ROW][C]168[/C][C]9.5[/C][C]8.46483[/C][C]1.03517[/C][/ROW]
[ROW][C]169[/C][C]8.5[/C][C]8.80487[/C][C]-0.304865[/C][/ROW]
[ROW][C]170[/C][C]7.5[/C][C]9.90684[/C][C]-2.40684[/C][/ROW]
[ROW][C]171[/C][C]5[/C][C]4.38055[/C][C]0.619447[/C][/ROW]
[ROW][C]172[/C][C]8[/C][C]6.14823[/C][C]1.85177[/C][/ROW]
[ROW][C]173[/C][C]10[/C][C]11.5875[/C][C]-1.58746[/C][/ROW]
[ROW][C]174[/C][C]7[/C][C]7.72318[/C][C]-0.723178[/C][/ROW]
[ROW][C]175[/C][C]7.5[/C][C]8.16677[/C][C]-0.666771[/C][/ROW]
[ROW][C]176[/C][C]7.5[/C][C]5.25226[/C][C]2.24774[/C][/ROW]
[ROW][C]177[/C][C]9.5[/C][C]10.5838[/C][C]-1.08382[/C][/ROW]
[ROW][C]178[/C][C]6[/C][C]4.03666[/C][C]1.96334[/C][/ROW]
[ROW][C]179[/C][C]10[/C][C]11.2494[/C][C]-1.24941[/C][/ROW]
[ROW][C]180[/C][C]7[/C][C]9.88748[/C][C]-2.88748[/C][/ROW]
[ROW][C]181[/C][C]3[/C][C]4.92195[/C][C]-1.92195[/C][/ROW]
[ROW][C]182[/C][C]6[/C][C]7.33651[/C][C]-1.33651[/C][/ROW]
[ROW][C]183[/C][C]7[/C][C]4.74787[/C][C]2.25213[/C][/ROW]
[ROW][C]184[/C][C]10[/C][C]10.4773[/C][C]-0.4773[/C][/ROW]
[ROW][C]185[/C][C]7[/C][C]11.8949[/C][C]-4.89486[/C][/ROW]
[ROW][C]186[/C][C]3.5[/C][C]3.79462[/C][C]-0.294622[/C][/ROW]
[ROW][C]187[/C][C]8[/C][C]6.15919[/C][C]1.84081[/C][/ROW]
[ROW][C]188[/C][C]10[/C][C]12.6602[/C][C]-2.66019[/C][/ROW]
[ROW][C]189[/C][C]5.5[/C][C]7.69382[/C][C]-2.19382[/C][/ROW]
[ROW][C]190[/C][C]6[/C][C]5.7663[/C][C]0.233702[/C][/ROW]
[ROW][C]191[/C][C]6.5[/C][C]6.96715[/C][C]-0.467152[/C][/ROW]
[ROW][C]192[/C][C]6.5[/C][C]4.50228[/C][C]1.99772[/C][/ROW]
[ROW][C]193[/C][C]8.5[/C][C]10.9935[/C][C]-2.49346[/C][/ROW]
[ROW][C]194[/C][C]4[/C][C]1.94483[/C][C]2.05517[/C][/ROW]
[ROW][C]195[/C][C]9.5[/C][C]8.91321[/C][C]0.586794[/C][/ROW]
[ROW][C]196[/C][C]8[/C][C]7.32139[/C][C]0.678614[/C][/ROW]
[ROW][C]197[/C][C]8.5[/C][C]11.1539[/C][C]-2.65388[/C][/ROW]
[ROW][C]198[/C][C]5.5[/C][C]5.17908[/C][C]0.320919[/C][/ROW]
[ROW][C]199[/C][C]7[/C][C]5.08074[/C][C]1.91926[/C][/ROW]
[ROW][C]200[/C][C]9[/C][C]8.98494[/C][C]0.015061[/C][/ROW]
[ROW][C]201[/C][C]8[/C][C]8.10534[/C][C]-0.105344[/C][/ROW]
[ROW][C]202[/C][C]10[/C][C]9.03134[/C][C]0.968658[/C][/ROW]
[ROW][C]203[/C][C]8[/C][C]9.43818[/C][C]-1.43818[/C][/ROW]
[ROW][C]204[/C][C]6[/C][C]6.04835[/C][C]-0.0483456[/C][/ROW]
[ROW][C]205[/C][C]8[/C][C]9.529[/C][C]-1.529[/C][/ROW]
[ROW][C]206[/C][C]5[/C][C]3.12211[/C][C]1.87789[/C][/ROW]
[ROW][C]207[/C][C]9[/C][C]9.38852[/C][C]-0.388525[/C][/ROW]
[ROW][C]208[/C][C]4.5[/C][C]3.05595[/C][C]1.44405[/C][/ROW]
[ROW][C]209[/C][C]8.5[/C][C]5.97959[/C][C]2.52041[/C][/ROW]
[ROW][C]210[/C][C]9.5[/C][C]7.94484[/C][C]1.55516[/C][/ROW]
[ROW][C]211[/C][C]8.5[/C][C]7.39803[/C][C]1.10197[/C][/ROW]
[ROW][C]212[/C][C]7.5[/C][C]7.4734[/C][C]0.0265972[/C][/ROW]
[ROW][C]213[/C][C]7.5[/C][C]8.8056[/C][C]-1.3056[/C][/ROW]
[ROW][C]214[/C][C]5[/C][C]4.8747[/C][C]0.125296[/C][/ROW]
[ROW][C]215[/C][C]7[/C][C]6.98299[/C][C]0.017006[/C][/ROW]
[ROW][C]216[/C][C]8[/C][C]8.64969[/C][C]-0.649685[/C][/ROW]
[ROW][C]217[/C][C]5.5[/C][C]4.25223[/C][C]1.24777[/C][/ROW]
[ROW][C]218[/C][C]8.5[/C][C]6.97279[/C][C]1.52721[/C][/ROW]
[ROW][C]219[/C][C]9.5[/C][C]9.12494[/C][C]0.375064[/C][/ROW]
[ROW][C]220[/C][C]7[/C][C]7.64485[/C][C]-0.644854[/C][/ROW]
[ROW][C]221[/C][C]8[/C][C]6.7985[/C][C]1.2015[/C][/ROW]
[ROW][C]222[/C][C]8.5[/C][C]11.0597[/C][C]-2.55968[/C][/ROW]
[ROW][C]223[/C][C]3.5[/C][C]4.33578[/C][C]-0.835776[/C][/ROW]
[ROW][C]224[/C][C]6.5[/C][C]6.7109[/C][C]-0.210901[/C][/ROW]
[ROW][C]225[/C][C]6.5[/C][C]4.07725[/C][C]2.42275[/C][/ROW]
[ROW][C]226[/C][C]10.5[/C][C]9.12823[/C][C]1.37177[/C][/ROW]
[ROW][C]227[/C][C]8.5[/C][C]7.92344[/C][C]0.576561[/C][/ROW]
[ROW][C]228[/C][C]8[/C][C]5.00797[/C][C]2.99203[/C][/ROW]
[ROW][C]229[/C][C]10[/C][C]6.74641[/C][C]3.25359[/C][/ROW]
[ROW][C]230[/C][C]10[/C][C]8.28207[/C][C]1.71793[/C][/ROW]
[ROW][C]231[/C][C]9.5[/C][C]7.58236[/C][C]1.91764[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]6.79701[/C][C]2.20299[/C][/ROW]
[ROW][C]233[/C][C]10[/C][C]9.38394[/C][C]0.616056[/C][/ROW]
[ROW][C]234[/C][C]7.5[/C][C]10.5903[/C][C]-3.09029[/C][/ROW]
[ROW][C]235[/C][C]4.5[/C][C]5.26816[/C][C]-0.768164[/C][/ROW]
[ROW][C]236[/C][C]4.5[/C][C]9.75652[/C][C]-5.25652[/C][/ROW]
[ROW][C]237[/C][C]0.5[/C][C]0.682847[/C][C]-0.182847[/C][/ROW]
[ROW][C]238[/C][C]6.5[/C][C]8.80213[/C][C]-2.30213[/C][/ROW]
[ROW][C]239[/C][C]4.5[/C][C]4.63173[/C][C]-0.131728[/C][/ROW]
[ROW][C]240[/C][C]5.5[/C][C]6.99635[/C][C]-1.49635[/C][/ROW]
[ROW][C]241[/C][C]5[/C][C]6.16205[/C][C]-1.16205[/C][/ROW]
[ROW][C]242[/C][C]6[/C][C]8.43336[/C][C]-2.43336[/C][/ROW]
[ROW][C]243[/C][C]4[/C][C]3.28589[/C][C]0.714115[/C][/ROW]
[ROW][C]244[/C][C]8[/C][C]7.24683[/C][C]0.753168[/C][/ROW]
[ROW][C]245[/C][C]10.5[/C][C]11.5686[/C][C]-1.06859[/C][/ROW]
[ROW][C]246[/C][C]6.5[/C][C]5.90564[/C][C]0.594358[/C][/ROW]
[ROW][C]247[/C][C]8[/C][C]7.73398[/C][C]0.266018[/C][/ROW]
[ROW][C]248[/C][C]8.5[/C][C]9.94369[/C][C]-1.44369[/C][/ROW]
[ROW][C]249[/C][C]5.5[/C][C]5.93024[/C][C]-0.430238[/C][/ROW]
[ROW][C]250[/C][C]7[/C][C]8.88481[/C][C]-1.88481[/C][/ROW]
[ROW][C]251[/C][C]5[/C][C]8.79795[/C][C]-3.79795[/C][/ROW]
[ROW][C]252[/C][C]3.5[/C][C]4.92811[/C][C]-1.42811[/C][/ROW]
[ROW][C]253[/C][C]5[/C][C]3.28958[/C][C]1.71042[/C][/ROW]
[ROW][C]254[/C][C]9[/C][C]7.87439[/C][C]1.12561[/C][/ROW]
[ROW][C]255[/C][C]8.5[/C][C]11.7738[/C][C]-3.27381[/C][/ROW]
[ROW][C]256[/C][C]5[/C][C]3.77201[/C][C]1.22799[/C][/ROW]
[ROW][C]257[/C][C]9.5[/C][C]12.9848[/C][C]-3.48477[/C][/ROW]
[ROW][C]258[/C][C]3[/C][C]7.95535[/C][C]-4.95535[/C][/ROW]
[ROW][C]259[/C][C]1.5[/C][C]3.0838[/C][C]-1.5838[/C][/ROW]
[ROW][C]260[/C][C]6[/C][C]12.8508[/C][C]-6.85082[/C][/ROW]
[ROW][C]261[/C][C]0.5[/C][C]0.791158[/C][C]-0.291158[/C][/ROW]
[ROW][C]262[/C][C]6.5[/C][C]6.78518[/C][C]-0.285177[/C][/ROW]
[ROW][C]263[/C][C]7.5[/C][C]9.85112[/C][C]-2.35112[/C][/ROW]
[ROW][C]264[/C][C]4.5[/C][C]3.76282[/C][C]0.737183[/C][/ROW]
[ROW][C]265[/C][C]8[/C][C]6.54019[/C][C]1.45981[/C][/ROW]
[ROW][C]266[/C][C]9[/C][C]8.46146[/C][C]0.538544[/C][/ROW]
[ROW][C]267[/C][C]7.5[/C][C]6.6173[/C][C]0.882701[/C][/ROW]
[ROW][C]268[/C][C]8.5[/C][C]8.5058[/C][C]-0.00579932[/C][/ROW]
[ROW][C]269[/C][C]7[/C][C]5.43618[/C][C]1.56382[/C][/ROW]
[ROW][C]270[/C][C]9.5[/C][C]9.40873[/C][C]0.0912737[/C][/ROW]
[ROW][C]271[/C][C]6.5[/C][C]4.63532[/C][C]1.86468[/C][/ROW]
[ROW][C]272[/C][C]9.5[/C][C]10.4084[/C][C]-0.90837[/C][/ROW]
[ROW][C]273[/C][C]6[/C][C]4.3085[/C][C]1.6915[/C][/ROW]
[ROW][C]274[/C][C]8[/C][C]6.72455[/C][C]1.27545[/C][/ROW]
[ROW][C]275[/C][C]9.5[/C][C]8.82376[/C][C]0.676235[/C][/ROW]
[ROW][C]276[/C][C]8[/C][C]7.72175[/C][C]0.278254[/C][/ROW]
[ROW][C]277[/C][C]8[/C][C]7.12122[/C][C]0.878778[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]10.2275[/C][C]-1.22748[/C][/ROW]
[ROW][C]279[/C][C]5[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=4

As an alternative you can also use a QR Code:

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or Index	Actuals	InterpolationForecast	ResidualsPrediction Error
1	7.5	5.52912	1.97088
2	6	4.46457	1.53543
3	6.5	5.43744	1.06256
4	1	4.28415	-3.28415
5	1	4.55314	-3.55314
6	5.5	5.47103	0.028973
7	8.5	4.97869	3.52131
8	6.5	4.06163	2.43837
9	4.5	4.06774	0.432262
10	2	5.23364	-3.23364
11	5	4.93268	0.067324
12	0.5	4.25595	-3.75595
13	5	3.58002	1.41998
14	5	5.22831	-0.228311
15	2.5	2.60718	-0.107181
16	5	4.12139	0.878606
17	5.5	4.772	0.728002
18	3.5	4.37631	-0.876314
19	3	5.22502	-2.22502
20	4	3.53844	0.46156
21	0.5	3.99474	-3.49474
22	6.5	4.49916	2.00084
23	4.5	6.25041	-1.75041
24	7.5	4.90243	2.59757
25	5.5	4.68379	0.816209
26	4	5.50778	-1.50778
27	7.5	5.85552	1.64448
28	7	4.80918	2.19082
29	4	4.54388	-0.543883
30	5.5	4.53369	0.966308
31	2.5	3.66943	-1.16943
32	5.5	5.14567	0.354334
33	3.5	4.2535	-0.753499
34	2.5	4.5335	-2.0335
35	4.5	3.68554	0.814456
36	4.5	3.55891	0.941089
37	4.5	4.24065	0.25935
38	6	4.60771	1.39229
39	2.5	5.05815	-2.55815
40	5	5.32747	-0.327466
41	0	4.30866	-4.30866
42	5	4.74592	0.254081
43	6.5	4.92859	1.57141
44	5	4.9014	0.0985982
45	6	3.57801	2.42199
46	4.5	5.75929	-1.25929
47	5.5	3.48966	2.01034
48	1	3.91778	-2.91778
49	7.5	3.47782	4.02218
50	6	4.43278	1.56722
51	5	4.63847	0.361527
52	1	3.08802	-2.08802
53	5	4.51283	0.487173
54	6.5	5.21104	1.28896
55	7	3.82497	3.17503
56	4.5	4.09152	0.408484
57	0	5.30815	-5.30815
58	8.5	3.76448	4.73552
59	3.5	3.20272	0.297284
60	7.5	4.96123	2.53877
61	3.5	5.24525	-1.74525
62	6	5.25776	0.742238
63	1.5	3.88042	-2.38042
64	9	5.64109	3.35891
65	3.5	5.70609	-2.20609
66	3.5	3.80022	-0.300218
67	4	5.2391	-1.2391
68	6.5	5.7964	0.703596
69	7.5	5.10004	2.39996
70	6	4.99345	1.00655
71	5	6.01346	-1.01346
72	5.5	4.50689	0.993106
73	3.5	4.61129	-1.11129
74	7.5	4.67556	2.82444
75	6.5	4.19359	2.30641
76	NA	NA	1.54626
77	6.5	4.99051	1.50949
78	6.5	4.59505	1.90495
79	7	7.39383	-0.393825
80	3.5	5.79122	-2.29122
81	1.5	2.36417	-0.864169
82	4	0.926948	3.07305
83	7.5	7.55691	-0.0569074
84	4.5	8.6093	-4.1093
85	0	1.4594	-1.4594
86	3.5	2.66458	0.835417
87	5.5	4.18463	1.31537
88	5	4.56451	0.435493
89	4.5	6.85075	-2.35075
90	2.5	0.157511	2.34249
91	7.5	4.49642	3.00358
92	7	11.7594	-4.75943
93	0	0.480632	-0.480632
94	4.5	6.52871	-2.02871
95	3	5.86501	-2.86501
96	1.5	3.03577	-1.53577
97	3.5	6.23178	-2.73178
98	2.5	1.41168	1.08832
99	5.5	2.12034	3.37966
100	8	11.3068	-3.30683
101	1	-0.299211	1.29921
102	5	4.9607	0.0392991
103	4.5	4.873	-0.373004
104	3	4.4918	-1.4918
105	3	-0.750058	3.75006
106	8	9.84013	-1.84013
107	2.5	-0.355092	2.85509
108	7	11.1925	-4.19248
109	0	2.66226	-2.66226
110	1	2.2301	-1.2301
111	3.5	2.97586	0.524144
112	5.5	4.19489	1.30511
113	5.5	10.9363	-5.43634
114	0.5	-1.08525	1.58525
115	7.5	5.99864	1.50136
116	9	7.20662	1.79338
117	9.5	9.76271	-0.262707
118	8.5	8.16945	0.330549
119	7	7.93551	-0.935508
120	8	6.25829	1.74171
121	10	10.7169	-0.716872
122	7	4.60268	2.39732
123	8.5	7.65006	0.849935
124	9	4.55176	4.44824
125	9.5	11.8497	-2.34969
126	4	4.23984	-0.239835
127	6	5.23512	0.764879
128	8	8.66849	-0.668494
129	5.5	3.91065	1.58935
130	9.5	8.81494	0.685055
131	7.5	7.70203	-0.20203
132	7	7.53728	-0.537277
133	7.5	5.98024	1.51976
134	8	7.2061	0.7939
135	7	6.01018	0.989816
136	7	7.07926	-0.0792601
137	6	3.13076	2.86924
138	10	12.4954	-2.49536
139	2.5	1.34531	1.15469
140	9	7.98486	1.01514
141	8	9.03023	-1.03023
142	6	5.11187	0.888127
143	8.5	8.64065	-0.140653
144	6	3.88999	2.11001
145	9	9.00089	-0.000888765
146	8	7.29961	0.700394
147	9	10.1671	-1.16708
148	5.5	5.47015	0.0298521
149	7	8.37671	-1.37671
150	5.5	4.77288	0.727119
151	9	14.6894	-5.68937
152	2	0.566644	1.43336
153	8.5	7.38313	1.11687
154	9	9.06384	-0.0638361
155	8.5	6.33965	2.16035
156	9	8.5969	0.4031
157	7.5	5.76339	1.73661
158	10	8.19711	1.80289
159	9	10.0971	-1.09708
160	7.5	8.76395	-1.26395
161	6	4.24635	1.75365
162	10.5	8.93032	1.56968
163	8.5	8.98876	-0.488758
164	8	2.80156	5.19844
165	10	9.40304	0.596962
166	10.5	10.3909	0.109072
167	6.5	5.51767	0.982326
168	9.5	8.46483	1.03517
169	8.5	8.80487	-0.304865
170	7.5	9.90684	-2.40684
171	5	4.38055	0.619447
172	8	6.14823	1.85177
173	10	11.5875	-1.58746
174	7	7.72318	-0.723178
175	7.5	8.16677	-0.666771
176	7.5	5.25226	2.24774
177	9.5	10.5838	-1.08382
178	6	4.03666	1.96334
179	10	11.2494	-1.24941
180	7	9.88748	-2.88748
181	3	4.92195	-1.92195
182	6	7.33651	-1.33651
183	7	4.74787	2.25213
184	10	10.4773	-0.4773
185	7	11.8949	-4.89486
186	3.5	3.79462	-0.294622
187	8	6.15919	1.84081
188	10	12.6602	-2.66019
189	5.5	7.69382	-2.19382
190	6	5.7663	0.233702
191	6.5	6.96715	-0.467152
192	6.5	4.50228	1.99772
193	8.5	10.9935	-2.49346
194	4	1.94483	2.05517
195	9.5	8.91321	0.586794
196	8	7.32139	0.678614
197	8.5	11.1539	-2.65388
198	5.5	5.17908	0.320919
199	7	5.08074	1.91926
200	9	8.98494	0.015061
201	8	8.10534	-0.105344
202	10	9.03134	0.968658
203	8	9.43818	-1.43818
204	6	6.04835	-0.0483456
205	8	9.529	-1.529
206	5	3.12211	1.87789
207	9	9.38852	-0.388525
208	4.5	3.05595	1.44405
209	8.5	5.97959	2.52041
210	9.5	7.94484	1.55516
211	8.5	7.39803	1.10197
212	7.5	7.4734	0.0265972
213	7.5	8.8056	-1.3056
214	5	4.8747	0.125296
215	7	6.98299	0.017006
216	8	8.64969	-0.649685
217	5.5	4.25223	1.24777
218	8.5	6.97279	1.52721
219	9.5	9.12494	0.375064
220	7	7.64485	-0.644854
221	8	6.7985	1.2015
222	8.5	11.0597	-2.55968
223	3.5	4.33578	-0.835776
224	6.5	6.7109	-0.210901
225	6.5	4.07725	2.42275
226	10.5	9.12823	1.37177
227	8.5	7.92344	0.576561
228	8	5.00797	2.99203
229	10	6.74641	3.25359
230	10	8.28207	1.71793
231	9.5	7.58236	1.91764
232	9	6.79701	2.20299
233	10	9.38394	0.616056
234	7.5	10.5903	-3.09029
235	4.5	5.26816	-0.768164
236	4.5	9.75652	-5.25652
237	0.5	0.682847	-0.182847
238	6.5	8.80213	-2.30213
239	4.5	4.63173	-0.131728
240	5.5	6.99635	-1.49635
241	5	6.16205	-1.16205
242	6	8.43336	-2.43336
243	4	3.28589	0.714115
244	8	7.24683	0.753168
245	10.5	11.5686	-1.06859
246	6.5	5.90564	0.594358
247	8	7.73398	0.266018
248	8.5	9.94369	-1.44369
249	5.5	5.93024	-0.430238
250	7	8.88481	-1.88481
251	5	8.79795	-3.79795
252	3.5	4.92811	-1.42811
253	5	3.28958	1.71042
254	9	7.87439	1.12561
255	8.5	11.7738	-3.27381
256	5	3.77201	1.22799
257	9.5	12.9848	-3.48477
258	3	7.95535	-4.95535
259	1.5	3.0838	-1.5838
260	6	12.8508	-6.85082
261	0.5	0.791158	-0.291158
262	6.5	6.78518	-0.285177
263	7.5	9.85112	-2.35112
264	4.5	3.76282	0.737183
265	8	6.54019	1.45981
266	9	8.46146	0.538544
267	7.5	6.6173	0.882701
268	8.5	8.5058	-0.00579932
269	7	5.43618	1.56382
270	9.5	9.40873	0.0912737
271	6.5	4.63532	1.86468
272	9.5	10.4084	-0.90837
273	6	4.3085	1.6915
274	8	6.72455	1.27545
275	9.5	8.82376	0.676235
276	8	7.72175	0.278254
277	8	7.12122	0.878778
278	9	10.2275	-1.22748
279	5	NA	NA

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
13	0.958502	0.0829953	0.0414977
14	0.91675	0.1665	0.0832499
15	0.872574	0.254852	0.127426
16	0.800151	0.399698	0.199849
17	0.713627	0.572745	0.286373
18	0.723204	0.553592	0.276796
19	0.733553	0.532893	0.266447
20	0.65275	0.694501	0.34725
21	0.655855	0.688289	0.344145
22	0.649496	0.701007	0.350504
23	0.611189	0.777622	0.388811
24	0.703029	0.593941	0.296971
25	0.635701	0.728598	0.364299
26	0.567218	0.865564	0.432782
27	0.504981	0.990038	0.495019
28	0.469107	0.938213	0.530893
29	0.401823	0.803645	0.598177
30	0.344079	0.688158	0.655921
31	0.510678	0.978643	0.489322
32	0.449454	0.898908	0.550546
33	0.412104	0.824209	0.587896
34	0.393445	0.78689	0.606555
35	0.336619	0.673237	0.663381
36	0.331721	0.663443	0.668279
37	0.285701	0.571402	0.714299
38	0.266475	0.532951	0.733525
39	0.259701	0.519402	0.740299
40	0.296404	0.592808	0.703596
41	0.455668	0.911335	0.544332
42	0.410786	0.821573	0.589214
43	0.395753	0.791506	0.604247
44	0.363046	0.726092	0.636954
45	0.3366	0.673201	0.6634
46	0.302974	0.605948	0.697026
47	0.333133	0.666265	0.666867
48	0.386633	0.773266	0.613367
49	0.489246	0.978492	0.510754
50	0.446482	0.892964	0.553518
51	0.403493	0.806985	0.596507
52	0.436091	0.872181	0.563909
53	0.40936	0.81872	0.59064
54	0.395065	0.790131	0.604935
55	0.486189	0.972377	0.513811
56	0.447827	0.895655	0.552173
57	0.791334	0.417332	0.208666
58	0.889706	0.220588	0.110294
59	0.86778	0.264441	0.13222
60	0.878548	0.242903	0.121452
61	0.874096	0.251809	0.125904
62	0.855388	0.289223	0.144612
63	0.88184	0.23632	0.11816
64	0.911544	0.176911	0.0884557
65	0.905831	0.188337	0.0941686
66	0.887547	0.224906	0.112453
67	0.871049	0.257901	0.128951
68	0.852621	0.294757	0.147379
69	0.858116	0.283768	0.141884
70	0.840305	0.319391	0.159695
71	0.817288	0.365425	0.182712
72	0.794305	0.411389	0.205695
73	0.770215	0.459571	0.229785
74	0.803369	0.393263	0.196631
75	0.800487	0.399025	0.199513
76	0.794455	0.41109	0.205545
77	0.782187	0.435626	0.217813
78	0.779653	0.440695	0.220347
79	0.758775	0.48245	0.241225
80	0.766104	0.467792	0.233896
81	0.736506	0.526989	0.263494
82	0.775903	0.448194	0.224097
83	0.746384	0.507233	0.253616
84	0.824726	0.350549	0.175274
85	0.815737	0.368526	0.184263
86	0.795534	0.408932	0.204466
87	0.782147	0.435706	0.217853
88	0.756055	0.487891	0.243945
89	0.76095	0.4781	0.23905
90	0.778472	0.443056	0.221528
91	0.810839	0.378322	0.189161
92	0.898438	0.203124	0.101562
93	0.881412	0.237176	0.118588
94	0.877489	0.245022	0.122511
95	0.885029	0.229941	0.114971
96	0.873925	0.252149	0.126075
97	0.880797	0.238406	0.119203
98	0.868659	0.262682	0.131341
99	0.902136	0.195729	0.0978644
100	0.917729	0.164542	0.0822712
101	0.909938	0.180125	0.0900623
102	0.894656	0.210688	0.105344
103	0.878573	0.242854	0.121427
104	0.8646	0.2708	0.1354
105	0.9116	0.176799	0.0883997
106	0.902591	0.194819	0.0974094
107	0.929847	0.140305	0.0701527
108	0.950725	0.0985508	0.0492754
109	0.953805	0.0923908	0.0461954
110	0.948651	0.102698	0.051349
111	0.940356	0.119287	0.0596436
112	0.931627	0.136745	0.0683727
113	0.952999	0.0940015	0.0470007
114	0.97536	0.0492798	0.0246399
115	0.976393	0.0472142	0.0236071
116	0.976661	0.0466776	0.0233388
117	0.972108	0.0557836	0.0278918
118	0.966044	0.0679117	0.0339558
119	0.959887	0.0802251	0.0401126
120	0.95794	0.0841198	0.0420599
121	0.951242	0.0975152	0.0487576
122	0.953784	0.0924325	0.0462163
123	0.946604	0.106791	0.0533956
124	0.970156	0.0596881	0.029844
125	0.973748	0.052503	0.0262515
126	0.969156	0.0616881	0.030844
127	0.963481	0.0730387	0.0365193
128	0.957839	0.0843224	0.0421612
129	0.953392	0.0932168	0.0466084
130	0.945024	0.109951	0.0549757
131	0.935832	0.128336	0.0641682
132	0.925982	0.148036	0.0740178
133	0.920627	0.158747	0.0793733
134	0.908892	0.182216	0.0911079
135	0.89791	0.20418	0.10209
136	0.884692	0.230617	0.115308
137	0.901586	0.196828	0.0984141
138	0.912501	0.174998	0.0874992
139	0.901774	0.196453	0.0982263
140	0.88966	0.220681	0.11034
141	0.8779	0.244199	0.1221
142	0.8642	0.271599	0.1358
143	0.847359	0.305283	0.152641
144	0.853078	0.293844	0.146922
145	0.832565	0.334871	0.167435
146	0.812767	0.374465	0.187233
147	0.797471	0.405057	0.202529
148	0.77188	0.456241	0.22812
149	0.760056	0.479888	0.239944
150	0.738567	0.522867	0.261433
151	0.894572	0.210855	0.105428
152	0.889387	0.221227	0.110613
153	0.878488	0.243024	0.121512
154	0.860346	0.279308	0.139654
155	0.86588	0.268241	0.13412
156	0.846238	0.307525	0.153762
157	0.844196	0.311608	0.155804
158	0.839021	0.321959	0.160979
159	0.827089	0.345823	0.172911
160	0.815265	0.369471	0.184735
161	0.809944	0.380112	0.190056
162	0.801311	0.397379	0.198689
163	0.775825	0.448351	0.224175
164	0.923647	0.152707	0.0763534
165	0.910285	0.179431	0.0897155
166	0.896782	0.206437	0.103218
167	0.881546	0.236909	0.118454
168	0.868471	0.263058	0.131529
169	0.851107	0.297786	0.148893
170	0.867712	0.264576	0.132288
171	0.84909	0.301819	0.15091
172	0.841192	0.317616	0.158808
173	0.834155	0.33169	0.165845
174	0.814446	0.371107	0.185554
175	0.792058	0.415884	0.207942
176	0.797929	0.404143	0.202071
177	0.777322	0.445357	0.222678
178	0.779583	0.440834	0.220417
179	0.76659	0.466821	0.23341
180	0.780293	0.439415	0.219707
181	0.784971	0.430059	0.215029
182	0.775409	0.449182	0.224591
183	0.802883	0.394234	0.197117
184	0.782185	0.435629	0.217815
185	0.904581	0.190838	0.0954188
186	0.890305	0.219389	0.109695
187	0.882874	0.234252	0.117126
188	0.909	0.182001	0.0910003
189	0.927959	0.144083	0.0720415
190	0.914968	0.170063	0.0850317
191	0.899244	0.201512	0.100756
192	0.897123	0.205754	0.102877
193	0.917773	0.164455	0.0822273
194	0.910839	0.178322	0.0891612
195	0.896093	0.207815	0.103907
196	0.878901	0.242198	0.121099
197	0.885559	0.228881	0.114441
198	0.865292	0.269415	0.134708
199	0.852455	0.29509	0.147545
200	0.833932	0.332137	0.166068
201	0.821981	0.356038	0.178019
202	0.7998	0.4004	0.2002
203	0.786813	0.426374	0.213187
204	0.760954	0.478092	0.239046
205	0.735602	0.528796	0.264398
206	0.73022	0.539561	0.26978
207	0.731133	0.537734	0.268867
208	0.732518	0.534964	0.267482
209	0.726206	0.547588	0.273794
210	0.717149	0.565703	0.282851
211	0.71982	0.560359	0.28018
212	0.685882	0.628236	0.314118
213	0.654511	0.690977	0.345489
214	0.614867	0.770265	0.385133
215	0.572306	0.855389	0.427694
216	0.530273	0.939453	0.469727
217	0.505921	0.988158	0.494079
218	0.500044	0.999911	0.499956
219	0.48272	0.96544	0.51728
220	0.458088	0.916177	0.541912
221	0.440966	0.881932	0.559034
222	0.460436	0.920873	0.539564
223	0.419422	0.838845	0.580578
224	0.416766	0.833532	0.583234
225	0.440032	0.880065	0.559968
226	0.413127	0.826253	0.586873
227	0.37099	0.74198	0.62901
228	0.471837	0.943674	0.528163
229	0.744801	0.510398	0.255199
230	0.756346	0.487308	0.243654
231	0.730141	0.539718	0.269859
232	0.773775	0.452449	0.226225
233	0.777162	0.445677	0.222838
234	0.753831	0.492339	0.246169
235	0.78199	0.436021	0.21801
236	0.846076	0.307847	0.153924
237	0.811049	0.377903	0.188951
238	0.781254	0.437492	0.218746
239	0.85564	0.28872	0.14436
240	0.822362	0.355277	0.177638
241	0.78554	0.42892	0.21446
242	0.758414	0.483172	0.241586
243	0.711621	0.576758	0.288379
244	0.659983	0.680034	0.340017
245	0.603895	0.79221	0.396105
246	0.568722	0.862556	0.431278
247	0.547781	0.904437	0.452219
248	0.528691	0.942618	0.471309
249	0.485746	0.971491	0.514254
250	0.481208	0.962415	0.518792
251	0.432674	0.865349	0.567326
252	0.377198	0.754396	0.622802
253	0.3808	0.7616	0.6192
254	0.325498	0.650997	0.674502
255	0.297722	0.595445	0.702278
256	0.266743	0.533487	0.733257
257	0.232549	0.465098	0.767451
258	0.460831	0.921662	0.539169
259	0.421665	0.84333	0.578335
260	0.951825	0.09635	0.048175
261	0.912057	0.175886	0.0879429
262	0.887093	0.225814	0.112907
263	0.984947	0.030107	0.0150535
264	0.961575	0.0768498	0.0384249
265	0.896536	0.206928	0.103464
266	0.751774	0.496452	0.248226

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.958502 & 0.0829953 & 0.0414977 \tabularnewline
14 & 0.91675 & 0.1665 & 0.0832499 \tabularnewline
15 & 0.872574 & 0.254852 & 0.127426 \tabularnewline
16 & 0.800151 & 0.399698 & 0.199849 \tabularnewline
17 & 0.713627 & 0.572745 & 0.286373 \tabularnewline
18 & 0.723204 & 0.553592 & 0.276796 \tabularnewline
19 & 0.733553 & 0.532893 & 0.266447 \tabularnewline
20 & 0.65275 & 0.694501 & 0.34725 \tabularnewline
21 & 0.655855 & 0.688289 & 0.344145 \tabularnewline
22 & 0.649496 & 0.701007 & 0.350504 \tabularnewline
23 & 0.611189 & 0.777622 & 0.388811 \tabularnewline
24 & 0.703029 & 0.593941 & 0.296971 \tabularnewline
25 & 0.635701 & 0.728598 & 0.364299 \tabularnewline
26 & 0.567218 & 0.865564 & 0.432782 \tabularnewline
27 & 0.504981 & 0.990038 & 0.495019 \tabularnewline
28 & 0.469107 & 0.938213 & 0.530893 \tabularnewline
29 & 0.401823 & 0.803645 & 0.598177 \tabularnewline
30 & 0.344079 & 0.688158 & 0.655921 \tabularnewline
31 & 0.510678 & 0.978643 & 0.489322 \tabularnewline
32 & 0.449454 & 0.898908 & 0.550546 \tabularnewline
33 & 0.412104 & 0.824209 & 0.587896 \tabularnewline
34 & 0.393445 & 0.78689 & 0.606555 \tabularnewline
35 & 0.336619 & 0.673237 & 0.663381 \tabularnewline
36 & 0.331721 & 0.663443 & 0.668279 \tabularnewline
37 & 0.285701 & 0.571402 & 0.714299 \tabularnewline
38 & 0.266475 & 0.532951 & 0.733525 \tabularnewline
39 & 0.259701 & 0.519402 & 0.740299 \tabularnewline
40 & 0.296404 & 0.592808 & 0.703596 \tabularnewline
41 & 0.455668 & 0.911335 & 0.544332 \tabularnewline
42 & 0.410786 & 0.821573 & 0.589214 \tabularnewline
43 & 0.395753 & 0.791506 & 0.604247 \tabularnewline
44 & 0.363046 & 0.726092 & 0.636954 \tabularnewline
45 & 0.3366 & 0.673201 & 0.6634 \tabularnewline
46 & 0.302974 & 0.605948 & 0.697026 \tabularnewline
47 & 0.333133 & 0.666265 & 0.666867 \tabularnewline
48 & 0.386633 & 0.773266 & 0.613367 \tabularnewline
49 & 0.489246 & 0.978492 & 0.510754 \tabularnewline
50 & 0.446482 & 0.892964 & 0.553518 \tabularnewline
51 & 0.403493 & 0.806985 & 0.596507 \tabularnewline
52 & 0.436091 & 0.872181 & 0.563909 \tabularnewline
53 & 0.40936 & 0.81872 & 0.59064 \tabularnewline
54 & 0.395065 & 0.790131 & 0.604935 \tabularnewline
55 & 0.486189 & 0.972377 & 0.513811 \tabularnewline
56 & 0.447827 & 0.895655 & 0.552173 \tabularnewline
57 & 0.791334 & 0.417332 & 0.208666 \tabularnewline
58 & 0.889706 & 0.220588 & 0.110294 \tabularnewline
59 & 0.86778 & 0.264441 & 0.13222 \tabularnewline
60 & 0.878548 & 0.242903 & 0.121452 \tabularnewline
61 & 0.874096 & 0.251809 & 0.125904 \tabularnewline
62 & 0.855388 & 0.289223 & 0.144612 \tabularnewline
63 & 0.88184 & 0.23632 & 0.11816 \tabularnewline
64 & 0.911544 & 0.176911 & 0.0884557 \tabularnewline
65 & 0.905831 & 0.188337 & 0.0941686 \tabularnewline
66 & 0.887547 & 0.224906 & 0.112453 \tabularnewline
67 & 0.871049 & 0.257901 & 0.128951 \tabularnewline
68 & 0.852621 & 0.294757 & 0.147379 \tabularnewline
69 & 0.858116 & 0.283768 & 0.141884 \tabularnewline
70 & 0.840305 & 0.319391 & 0.159695 \tabularnewline
71 & 0.817288 & 0.365425 & 0.182712 \tabularnewline
72 & 0.794305 & 0.411389 & 0.205695 \tabularnewline
73 & 0.770215 & 0.459571 & 0.229785 \tabularnewline
74 & 0.803369 & 0.393263 & 0.196631 \tabularnewline
75 & 0.800487 & 0.399025 & 0.199513 \tabularnewline
76 & 0.794455 & 0.41109 & 0.205545 \tabularnewline
77 & 0.782187 & 0.435626 & 0.217813 \tabularnewline
78 & 0.779653 & 0.440695 & 0.220347 \tabularnewline
79 & 0.758775 & 0.48245 & 0.241225 \tabularnewline
80 & 0.766104 & 0.467792 & 0.233896 \tabularnewline
81 & 0.736506 & 0.526989 & 0.263494 \tabularnewline
82 & 0.775903 & 0.448194 & 0.224097 \tabularnewline
83 & 0.746384 & 0.507233 & 0.253616 \tabularnewline
84 & 0.824726 & 0.350549 & 0.175274 \tabularnewline
85 & 0.815737 & 0.368526 & 0.184263 \tabularnewline
86 & 0.795534 & 0.408932 & 0.204466 \tabularnewline
87 & 0.782147 & 0.435706 & 0.217853 \tabularnewline
88 & 0.756055 & 0.487891 & 0.243945 \tabularnewline
89 & 0.76095 & 0.4781 & 0.23905 \tabularnewline
90 & 0.778472 & 0.443056 & 0.221528 \tabularnewline
91 & 0.810839 & 0.378322 & 0.189161 \tabularnewline
92 & 0.898438 & 0.203124 & 0.101562 \tabularnewline
93 & 0.881412 & 0.237176 & 0.118588 \tabularnewline
94 & 0.877489 & 0.245022 & 0.122511 \tabularnewline
95 & 0.885029 & 0.229941 & 0.114971 \tabularnewline
96 & 0.873925 & 0.252149 & 0.126075 \tabularnewline
97 & 0.880797 & 0.238406 & 0.119203 \tabularnewline
98 & 0.868659 & 0.262682 & 0.131341 \tabularnewline
99 & 0.902136 & 0.195729 & 0.0978644 \tabularnewline
100 & 0.917729 & 0.164542 & 0.0822712 \tabularnewline
101 & 0.909938 & 0.180125 & 0.0900623 \tabularnewline
102 & 0.894656 & 0.210688 & 0.105344 \tabularnewline
103 & 0.878573 & 0.242854 & 0.121427 \tabularnewline
104 & 0.8646 & 0.2708 & 0.1354 \tabularnewline
105 & 0.9116 & 0.176799 & 0.0883997 \tabularnewline
106 & 0.902591 & 0.194819 & 0.0974094 \tabularnewline
107 & 0.929847 & 0.140305 & 0.0701527 \tabularnewline
108 & 0.950725 & 0.0985508 & 0.0492754 \tabularnewline
109 & 0.953805 & 0.0923908 & 0.0461954 \tabularnewline
110 & 0.948651 & 0.102698 & 0.051349 \tabularnewline
111 & 0.940356 & 0.119287 & 0.0596436 \tabularnewline
112 & 0.931627 & 0.136745 & 0.0683727 \tabularnewline
113 & 0.952999 & 0.0940015 & 0.0470007 \tabularnewline
114 & 0.97536 & 0.0492798 & 0.0246399 \tabularnewline
115 & 0.976393 & 0.0472142 & 0.0236071 \tabularnewline
116 & 0.976661 & 0.0466776 & 0.0233388 \tabularnewline
117 & 0.972108 & 0.0557836 & 0.0278918 \tabularnewline
118 & 0.966044 & 0.0679117 & 0.0339558 \tabularnewline
119 & 0.959887 & 0.0802251 & 0.0401126 \tabularnewline
120 & 0.95794 & 0.0841198 & 0.0420599 \tabularnewline
121 & 0.951242 & 0.0975152 & 0.0487576 \tabularnewline
122 & 0.953784 & 0.0924325 & 0.0462163 \tabularnewline
123 & 0.946604 & 0.106791 & 0.0533956 \tabularnewline
124 & 0.970156 & 0.0596881 & 0.029844 \tabularnewline
125 & 0.973748 & 0.052503 & 0.0262515 \tabularnewline
126 & 0.969156 & 0.0616881 & 0.030844 \tabularnewline
127 & 0.963481 & 0.0730387 & 0.0365193 \tabularnewline
128 & 0.957839 & 0.0843224 & 0.0421612 \tabularnewline
129 & 0.953392 & 0.0932168 & 0.0466084 \tabularnewline
130 & 0.945024 & 0.109951 & 0.0549757 \tabularnewline
131 & 0.935832 & 0.128336 & 0.0641682 \tabularnewline
132 & 0.925982 & 0.148036 & 0.0740178 \tabularnewline
133 & 0.920627 & 0.158747 & 0.0793733 \tabularnewline
134 & 0.908892 & 0.182216 & 0.0911079 \tabularnewline
135 & 0.89791 & 0.20418 & 0.10209 \tabularnewline
136 & 0.884692 & 0.230617 & 0.115308 \tabularnewline
137 & 0.901586 & 0.196828 & 0.0984141 \tabularnewline
138 & 0.912501 & 0.174998 & 0.0874992 \tabularnewline
139 & 0.901774 & 0.196453 & 0.0982263 \tabularnewline
140 & 0.88966 & 0.220681 & 0.11034 \tabularnewline
141 & 0.8779 & 0.244199 & 0.1221 \tabularnewline
142 & 0.8642 & 0.271599 & 0.1358 \tabularnewline
143 & 0.847359 & 0.305283 & 0.152641 \tabularnewline
144 & 0.853078 & 0.293844 & 0.146922 \tabularnewline
145 & 0.832565 & 0.334871 & 0.167435 \tabularnewline
146 & 0.812767 & 0.374465 & 0.187233 \tabularnewline
147 & 0.797471 & 0.405057 & 0.202529 \tabularnewline
148 & 0.77188 & 0.456241 & 0.22812 \tabularnewline
149 & 0.760056 & 0.479888 & 0.239944 \tabularnewline
150 & 0.738567 & 0.522867 & 0.261433 \tabularnewline
151 & 0.894572 & 0.210855 & 0.105428 \tabularnewline
152 & 0.889387 & 0.221227 & 0.110613 \tabularnewline
153 & 0.878488 & 0.243024 & 0.121512 \tabularnewline
154 & 0.860346 & 0.279308 & 0.139654 \tabularnewline
155 & 0.86588 & 0.268241 & 0.13412 \tabularnewline
156 & 0.846238 & 0.307525 & 0.153762 \tabularnewline
157 & 0.844196 & 0.311608 & 0.155804 \tabularnewline
158 & 0.839021 & 0.321959 & 0.160979 \tabularnewline
159 & 0.827089 & 0.345823 & 0.172911 \tabularnewline
160 & 0.815265 & 0.369471 & 0.184735 \tabularnewline
161 & 0.809944 & 0.380112 & 0.190056 \tabularnewline
162 & 0.801311 & 0.397379 & 0.198689 \tabularnewline
163 & 0.775825 & 0.448351 & 0.224175 \tabularnewline
164 & 0.923647 & 0.152707 & 0.0763534 \tabularnewline
165 & 0.910285 & 0.179431 & 0.0897155 \tabularnewline
166 & 0.896782 & 0.206437 & 0.103218 \tabularnewline
167 & 0.881546 & 0.236909 & 0.118454 \tabularnewline
168 & 0.868471 & 0.263058 & 0.131529 \tabularnewline
169 & 0.851107 & 0.297786 & 0.148893 \tabularnewline
170 & 0.867712 & 0.264576 & 0.132288 \tabularnewline
171 & 0.84909 & 0.301819 & 0.15091 \tabularnewline
172 & 0.841192 & 0.317616 & 0.158808 \tabularnewline
173 & 0.834155 & 0.33169 & 0.165845 \tabularnewline
174 & 0.814446 & 0.371107 & 0.185554 \tabularnewline
175 & 0.792058 & 0.415884 & 0.207942 \tabularnewline
176 & 0.797929 & 0.404143 & 0.202071 \tabularnewline
177 & 0.777322 & 0.445357 & 0.222678 \tabularnewline
178 & 0.779583 & 0.440834 & 0.220417 \tabularnewline
179 & 0.76659 & 0.466821 & 0.23341 \tabularnewline
180 & 0.780293 & 0.439415 & 0.219707 \tabularnewline
181 & 0.784971 & 0.430059 & 0.215029 \tabularnewline
182 & 0.775409 & 0.449182 & 0.224591 \tabularnewline
183 & 0.802883 & 0.394234 & 0.197117 \tabularnewline
184 & 0.782185 & 0.435629 & 0.217815 \tabularnewline
185 & 0.904581 & 0.190838 & 0.0954188 \tabularnewline
186 & 0.890305 & 0.219389 & 0.109695 \tabularnewline
187 & 0.882874 & 0.234252 & 0.117126 \tabularnewline
188 & 0.909 & 0.182001 & 0.0910003 \tabularnewline
189 & 0.927959 & 0.144083 & 0.0720415 \tabularnewline
190 & 0.914968 & 0.170063 & 0.0850317 \tabularnewline
191 & 0.899244 & 0.201512 & 0.100756 \tabularnewline
192 & 0.897123 & 0.205754 & 0.102877 \tabularnewline
193 & 0.917773 & 0.164455 & 0.0822273 \tabularnewline
194 & 0.910839 & 0.178322 & 0.0891612 \tabularnewline
195 & 0.896093 & 0.207815 & 0.103907 \tabularnewline
196 & 0.878901 & 0.242198 & 0.121099 \tabularnewline
197 & 0.885559 & 0.228881 & 0.114441 \tabularnewline
198 & 0.865292 & 0.269415 & 0.134708 \tabularnewline
199 & 0.852455 & 0.29509 & 0.147545 \tabularnewline
200 & 0.833932 & 0.332137 & 0.166068 \tabularnewline
201 & 0.821981 & 0.356038 & 0.178019 \tabularnewline
202 & 0.7998 & 0.4004 & 0.2002 \tabularnewline
203 & 0.786813 & 0.426374 & 0.213187 \tabularnewline
204 & 0.760954 & 0.478092 & 0.239046 \tabularnewline
205 & 0.735602 & 0.528796 & 0.264398 \tabularnewline
206 & 0.73022 & 0.539561 & 0.26978 \tabularnewline
207 & 0.731133 & 0.537734 & 0.268867 \tabularnewline
208 & 0.732518 & 0.534964 & 0.267482 \tabularnewline
209 & 0.726206 & 0.547588 & 0.273794 \tabularnewline
210 & 0.717149 & 0.565703 & 0.282851 \tabularnewline
211 & 0.71982 & 0.560359 & 0.28018 \tabularnewline
212 & 0.685882 & 0.628236 & 0.314118 \tabularnewline
213 & 0.654511 & 0.690977 & 0.345489 \tabularnewline
214 & 0.614867 & 0.770265 & 0.385133 \tabularnewline
215 & 0.572306 & 0.855389 & 0.427694 \tabularnewline
216 & 0.530273 & 0.939453 & 0.469727 \tabularnewline
217 & 0.505921 & 0.988158 & 0.494079 \tabularnewline
218 & 0.500044 & 0.999911 & 0.499956 \tabularnewline
219 & 0.48272 & 0.96544 & 0.51728 \tabularnewline
220 & 0.458088 & 0.916177 & 0.541912 \tabularnewline
221 & 0.440966 & 0.881932 & 0.559034 \tabularnewline
222 & 0.460436 & 0.920873 & 0.539564 \tabularnewline
223 & 0.419422 & 0.838845 & 0.580578 \tabularnewline
224 & 0.416766 & 0.833532 & 0.583234 \tabularnewline
225 & 0.440032 & 0.880065 & 0.559968 \tabularnewline
226 & 0.413127 & 0.826253 & 0.586873 \tabularnewline
227 & 0.37099 & 0.74198 & 0.62901 \tabularnewline
228 & 0.471837 & 0.943674 & 0.528163 \tabularnewline
229 & 0.744801 & 0.510398 & 0.255199 \tabularnewline
230 & 0.756346 & 0.487308 & 0.243654 \tabularnewline
231 & 0.730141 & 0.539718 & 0.269859 \tabularnewline
232 & 0.773775 & 0.452449 & 0.226225 \tabularnewline
233 & 0.777162 & 0.445677 & 0.222838 \tabularnewline
234 & 0.753831 & 0.492339 & 0.246169 \tabularnewline
235 & 0.78199 & 0.436021 & 0.21801 \tabularnewline
236 & 0.846076 & 0.307847 & 0.153924 \tabularnewline
237 & 0.811049 & 0.377903 & 0.188951 \tabularnewline
238 & 0.781254 & 0.437492 & 0.218746 \tabularnewline
239 & 0.85564 & 0.28872 & 0.14436 \tabularnewline
240 & 0.822362 & 0.355277 & 0.177638 \tabularnewline
241 & 0.78554 & 0.42892 & 0.21446 \tabularnewline
242 & 0.758414 & 0.483172 & 0.241586 \tabularnewline
243 & 0.711621 & 0.576758 & 0.288379 \tabularnewline
244 & 0.659983 & 0.680034 & 0.340017 \tabularnewline
245 & 0.603895 & 0.79221 & 0.396105 \tabularnewline
246 & 0.568722 & 0.862556 & 0.431278 \tabularnewline
247 & 0.547781 & 0.904437 & 0.452219 \tabularnewline
248 & 0.528691 & 0.942618 & 0.471309 \tabularnewline
249 & 0.485746 & 0.971491 & 0.514254 \tabularnewline
250 & 0.481208 & 0.962415 & 0.518792 \tabularnewline
251 & 0.432674 & 0.865349 & 0.567326 \tabularnewline
252 & 0.377198 & 0.754396 & 0.622802 \tabularnewline
253 & 0.3808 & 0.7616 & 0.6192 \tabularnewline
254 & 0.325498 & 0.650997 & 0.674502 \tabularnewline
255 & 0.297722 & 0.595445 & 0.702278 \tabularnewline
256 & 0.266743 & 0.533487 & 0.733257 \tabularnewline
257 & 0.232549 & 0.465098 & 0.767451 \tabularnewline
258 & 0.460831 & 0.921662 & 0.539169 \tabularnewline
259 & 0.421665 & 0.84333 & 0.578335 \tabularnewline
260 & 0.951825 & 0.09635 & 0.048175 \tabularnewline
261 & 0.912057 & 0.175886 & 0.0879429 \tabularnewline
262 & 0.887093 & 0.225814 & 0.112907 \tabularnewline
263 & 0.984947 & 0.030107 & 0.0150535 \tabularnewline
264 & 0.961575 & 0.0768498 & 0.0384249 \tabularnewline
265 & 0.896536 & 0.206928 & 0.103464 \tabularnewline
266 & 0.751774 & 0.496452 & 0.248226 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]13[/C][C]0.958502[/C][C]0.0829953[/C][C]0.0414977[/C][/ROW]
[ROW][C]14[/C][C]0.91675[/C][C]0.1665[/C][C]0.0832499[/C][/ROW]
[ROW][C]15[/C][C]0.872574[/C][C]0.254852[/C][C]0.127426[/C][/ROW]
[ROW][C]16[/C][C]0.800151[/C][C]0.399698[/C][C]0.199849[/C][/ROW]
[ROW][C]17[/C][C]0.713627[/C][C]0.572745[/C][C]0.286373[/C][/ROW]
[ROW][C]18[/C][C]0.723204[/C][C]0.553592[/C][C]0.276796[/C][/ROW]
[ROW][C]19[/C][C]0.733553[/C][C]0.532893[/C][C]0.266447[/C][/ROW]
[ROW][C]20[/C][C]0.65275[/C][C]0.694501[/C][C]0.34725[/C][/ROW]
[ROW][C]21[/C][C]0.655855[/C][C]0.688289[/C][C]0.344145[/C][/ROW]
[ROW][C]22[/C][C]0.649496[/C][C]0.701007[/C][C]0.350504[/C][/ROW]
[ROW][C]23[/C][C]0.611189[/C][C]0.777622[/C][C]0.388811[/C][/ROW]
[ROW][C]24[/C][C]0.703029[/C][C]0.593941[/C][C]0.296971[/C][/ROW]
[ROW][C]25[/C][C]0.635701[/C][C]0.728598[/C][C]0.364299[/C][/ROW]
[ROW][C]26[/C][C]0.567218[/C][C]0.865564[/C][C]0.432782[/C][/ROW]
[ROW][C]27[/C][C]0.504981[/C][C]0.990038[/C][C]0.495019[/C][/ROW]
[ROW][C]28[/C][C]0.469107[/C][C]0.938213[/C][C]0.530893[/C][/ROW]
[ROW][C]29[/C][C]0.401823[/C][C]0.803645[/C][C]0.598177[/C][/ROW]
[ROW][C]30[/C][C]0.344079[/C][C]0.688158[/C][C]0.655921[/C][/ROW]
[ROW][C]31[/C][C]0.510678[/C][C]0.978643[/C][C]0.489322[/C][/ROW]
[ROW][C]32[/C][C]0.449454[/C][C]0.898908[/C][C]0.550546[/C][/ROW]
[ROW][C]33[/C][C]0.412104[/C][C]0.824209[/C][C]0.587896[/C][/ROW]
[ROW][C]34[/C][C]0.393445[/C][C]0.78689[/C][C]0.606555[/C][/ROW]
[ROW][C]35[/C][C]0.336619[/C][C]0.673237[/C][C]0.663381[/C][/ROW]
[ROW][C]36[/C][C]0.331721[/C][C]0.663443[/C][C]0.668279[/C][/ROW]
[ROW][C]37[/C][C]0.285701[/C][C]0.571402[/C][C]0.714299[/C][/ROW]
[ROW][C]38[/C][C]0.266475[/C][C]0.532951[/C][C]0.733525[/C][/ROW]
[ROW][C]39[/C][C]0.259701[/C][C]0.519402[/C][C]0.740299[/C][/ROW]
[ROW][C]40[/C][C]0.296404[/C][C]0.592808[/C][C]0.703596[/C][/ROW]
[ROW][C]41[/C][C]0.455668[/C][C]0.911335[/C][C]0.544332[/C][/ROW]
[ROW][C]42[/C][C]0.410786[/C][C]0.821573[/C][C]0.589214[/C][/ROW]
[ROW][C]43[/C][C]0.395753[/C][C]0.791506[/C][C]0.604247[/C][/ROW]
[ROW][C]44[/C][C]0.363046[/C][C]0.726092[/C][C]0.636954[/C][/ROW]
[ROW][C]45[/C][C]0.3366[/C][C]0.673201[/C][C]0.6634[/C][/ROW]
[ROW][C]46[/C][C]0.302974[/C][C]0.605948[/C][C]0.697026[/C][/ROW]
[ROW][C]47[/C][C]0.333133[/C][C]0.666265[/C][C]0.666867[/C][/ROW]
[ROW][C]48[/C][C]0.386633[/C][C]0.773266[/C][C]0.613367[/C][/ROW]
[ROW][C]49[/C][C]0.489246[/C][C]0.978492[/C][C]0.510754[/C][/ROW]
[ROW][C]50[/C][C]0.446482[/C][C]0.892964[/C][C]0.553518[/C][/ROW]
[ROW][C]51[/C][C]0.403493[/C][C]0.806985[/C][C]0.596507[/C][/ROW]
[ROW][C]52[/C][C]0.436091[/C][C]0.872181[/C][C]0.563909[/C][/ROW]
[ROW][C]53[/C][C]0.40936[/C][C]0.81872[/C][C]0.59064[/C][/ROW]
[ROW][C]54[/C][C]0.395065[/C][C]0.790131[/C][C]0.604935[/C][/ROW]
[ROW][C]55[/C][C]0.486189[/C][C]0.972377[/C][C]0.513811[/C][/ROW]
[ROW][C]56[/C][C]0.447827[/C][C]0.895655[/C][C]0.552173[/C][/ROW]
[ROW][C]57[/C][C]0.791334[/C][C]0.417332[/C][C]0.208666[/C][/ROW]
[ROW][C]58[/C][C]0.889706[/C][C]0.220588[/C][C]0.110294[/C][/ROW]
[ROW][C]59[/C][C]0.86778[/C][C]0.264441[/C][C]0.13222[/C][/ROW]
[ROW][C]60[/C][C]0.878548[/C][C]0.242903[/C][C]0.121452[/C][/ROW]
[ROW][C]61[/C][C]0.874096[/C][C]0.251809[/C][C]0.125904[/C][/ROW]
[ROW][C]62[/C][C]0.855388[/C][C]0.289223[/C][C]0.144612[/C][/ROW]
[ROW][C]63[/C][C]0.88184[/C][C]0.23632[/C][C]0.11816[/C][/ROW]
[ROW][C]64[/C][C]0.911544[/C][C]0.176911[/C][C]0.0884557[/C][/ROW]
[ROW][C]65[/C][C]0.905831[/C][C]0.188337[/C][C]0.0941686[/C][/ROW]
[ROW][C]66[/C][C]0.887547[/C][C]0.224906[/C][C]0.112453[/C][/ROW]
[ROW][C]67[/C][C]0.871049[/C][C]0.257901[/C][C]0.128951[/C][/ROW]
[ROW][C]68[/C][C]0.852621[/C][C]0.294757[/C][C]0.147379[/C][/ROW]
[ROW][C]69[/C][C]0.858116[/C][C]0.283768[/C][C]0.141884[/C][/ROW]
[ROW][C]70[/C][C]0.840305[/C][C]0.319391[/C][C]0.159695[/C][/ROW]
[ROW][C]71[/C][C]0.817288[/C][C]0.365425[/C][C]0.182712[/C][/ROW]
[ROW][C]72[/C][C]0.794305[/C][C]0.411389[/C][C]0.205695[/C][/ROW]
[ROW][C]73[/C][C]0.770215[/C][C]0.459571[/C][C]0.229785[/C][/ROW]
[ROW][C]74[/C][C]0.803369[/C][C]0.393263[/C][C]0.196631[/C][/ROW]
[ROW][C]75[/C][C]0.800487[/C][C]0.399025[/C][C]0.199513[/C][/ROW]
[ROW][C]76[/C][C]0.794455[/C][C]0.41109[/C][C]0.205545[/C][/ROW]
[ROW][C]77[/C][C]0.782187[/C][C]0.435626[/C][C]0.217813[/C][/ROW]
[ROW][C]78[/C][C]0.779653[/C][C]0.440695[/C][C]0.220347[/C][/ROW]
[ROW][C]79[/C][C]0.758775[/C][C]0.48245[/C][C]0.241225[/C][/ROW]
[ROW][C]80[/C][C]0.766104[/C][C]0.467792[/C][C]0.233896[/C][/ROW]
[ROW][C]81[/C][C]0.736506[/C][C]0.526989[/C][C]0.263494[/C][/ROW]
[ROW][C]82[/C][C]0.775903[/C][C]0.448194[/C][C]0.224097[/C][/ROW]
[ROW][C]83[/C][C]0.746384[/C][C]0.507233[/C][C]0.253616[/C][/ROW]
[ROW][C]84[/C][C]0.824726[/C][C]0.350549[/C][C]0.175274[/C][/ROW]
[ROW][C]85[/C][C]0.815737[/C][C]0.368526[/C][C]0.184263[/C][/ROW]
[ROW][C]86[/C][C]0.795534[/C][C]0.408932[/C][C]0.204466[/C][/ROW]
[ROW][C]87[/C][C]0.782147[/C][C]0.435706[/C][C]0.217853[/C][/ROW]
[ROW][C]88[/C][C]0.756055[/C][C]0.487891[/C][C]0.243945[/C][/ROW]
[ROW][C]89[/C][C]0.76095[/C][C]0.4781[/C][C]0.23905[/C][/ROW]
[ROW][C]90[/C][C]0.778472[/C][C]0.443056[/C][C]0.221528[/C][/ROW]
[ROW][C]91[/C][C]0.810839[/C][C]0.378322[/C][C]0.189161[/C][/ROW]
[ROW][C]92[/C][C]0.898438[/C][C]0.203124[/C][C]0.101562[/C][/ROW]
[ROW][C]93[/C][C]0.881412[/C][C]0.237176[/C][C]0.118588[/C][/ROW]
[ROW][C]94[/C][C]0.877489[/C][C]0.245022[/C][C]0.122511[/C][/ROW]
[ROW][C]95[/C][C]0.885029[/C][C]0.229941[/C][C]0.114971[/C][/ROW]
[ROW][C]96[/C][C]0.873925[/C][C]0.252149[/C][C]0.126075[/C][/ROW]
[ROW][C]97[/C][C]0.880797[/C][C]0.238406[/C][C]0.119203[/C][/ROW]
[ROW][C]98[/C][C]0.868659[/C][C]0.262682[/C][C]0.131341[/C][/ROW]
[ROW][C]99[/C][C]0.902136[/C][C]0.195729[/C][C]0.0978644[/C][/ROW]
[ROW][C]100[/C][C]0.917729[/C][C]0.164542[/C][C]0.0822712[/C][/ROW]
[ROW][C]101[/C][C]0.909938[/C][C]0.180125[/C][C]0.0900623[/C][/ROW]
[ROW][C]102[/C][C]0.894656[/C][C]0.210688[/C][C]0.105344[/C][/ROW]
[ROW][C]103[/C][C]0.878573[/C][C]0.242854[/C][C]0.121427[/C][/ROW]
[ROW][C]104[/C][C]0.8646[/C][C]0.2708[/C][C]0.1354[/C][/ROW]
[ROW][C]105[/C][C]0.9116[/C][C]0.176799[/C][C]0.0883997[/C][/ROW]
[ROW][C]106[/C][C]0.902591[/C][C]0.194819[/C][C]0.0974094[/C][/ROW]
[ROW][C]107[/C][C]0.929847[/C][C]0.140305[/C][C]0.0701527[/C][/ROW]
[ROW][C]108[/C][C]0.950725[/C][C]0.0985508[/C][C]0.0492754[/C][/ROW]
[ROW][C]109[/C][C]0.953805[/C][C]0.0923908[/C][C]0.0461954[/C][/ROW]
[ROW][C]110[/C][C]0.948651[/C][C]0.102698[/C][C]0.051349[/C][/ROW]
[ROW][C]111[/C][C]0.940356[/C][C]0.119287[/C][C]0.0596436[/C][/ROW]
[ROW][C]112[/C][C]0.931627[/C][C]0.136745[/C][C]0.0683727[/C][/ROW]
[ROW][C]113[/C][C]0.952999[/C][C]0.0940015[/C][C]0.0470007[/C][/ROW]
[ROW][C]114[/C][C]0.97536[/C][C]0.0492798[/C][C]0.0246399[/C][/ROW]
[ROW][C]115[/C][C]0.976393[/C][C]0.0472142[/C][C]0.0236071[/C][/ROW]
[ROW][C]116[/C][C]0.976661[/C][C]0.0466776[/C][C]0.0233388[/C][/ROW]
[ROW][C]117[/C][C]0.972108[/C][C]0.0557836[/C][C]0.0278918[/C][/ROW]
[ROW][C]118[/C][C]0.966044[/C][C]0.0679117[/C][C]0.0339558[/C][/ROW]
[ROW][C]119[/C][C]0.959887[/C][C]0.0802251[/C][C]0.0401126[/C][/ROW]
[ROW][C]120[/C][C]0.95794[/C][C]0.0841198[/C][C]0.0420599[/C][/ROW]
[ROW][C]121[/C][C]0.951242[/C][C]0.0975152[/C][C]0.0487576[/C][/ROW]
[ROW][C]122[/C][C]0.953784[/C][C]0.0924325[/C][C]0.0462163[/C][/ROW]
[ROW][C]123[/C][C]0.946604[/C][C]0.106791[/C][C]0.0533956[/C][/ROW]
[ROW][C]124[/C][C]0.970156[/C][C]0.0596881[/C][C]0.029844[/C][/ROW]
[ROW][C]125[/C][C]0.973748[/C][C]0.052503[/C][C]0.0262515[/C][/ROW]
[ROW][C]126[/C][C]0.969156[/C][C]0.0616881[/C][C]0.030844[/C][/ROW]
[ROW][C]127[/C][C]0.963481[/C][C]0.0730387[/C][C]0.0365193[/C][/ROW]
[ROW][C]128[/C][C]0.957839[/C][C]0.0843224[/C][C]0.0421612[/C][/ROW]
[ROW][C]129[/C][C]0.953392[/C][C]0.0932168[/C][C]0.0466084[/C][/ROW]
[ROW][C]130[/C][C]0.945024[/C][C]0.109951[/C][C]0.0549757[/C][/ROW]
[ROW][C]131[/C][C]0.935832[/C][C]0.128336[/C][C]0.0641682[/C][/ROW]
[ROW][C]132[/C][C]0.925982[/C][C]0.148036[/C][C]0.0740178[/C][/ROW]
[ROW][C]133[/C][C]0.920627[/C][C]0.158747[/C][C]0.0793733[/C][/ROW]
[ROW][C]134[/C][C]0.908892[/C][C]0.182216[/C][C]0.0911079[/C][/ROW]
[ROW][C]135[/C][C]0.89791[/C][C]0.20418[/C][C]0.10209[/C][/ROW]
[ROW][C]136[/C][C]0.884692[/C][C]0.230617[/C][C]0.115308[/C][/ROW]
[ROW][C]137[/C][C]0.901586[/C][C]0.196828[/C][C]0.0984141[/C][/ROW]
[ROW][C]138[/C][C]0.912501[/C][C]0.174998[/C][C]0.0874992[/C][/ROW]
[ROW][C]139[/C][C]0.901774[/C][C]0.196453[/C][C]0.0982263[/C][/ROW]
[ROW][C]140[/C][C]0.88966[/C][C]0.220681[/C][C]0.11034[/C][/ROW]
[ROW][C]141[/C][C]0.8779[/C][C]0.244199[/C][C]0.1221[/C][/ROW]
[ROW][C]142[/C][C]0.8642[/C][C]0.271599[/C][C]0.1358[/C][/ROW]
[ROW][C]143[/C][C]0.847359[/C][C]0.305283[/C][C]0.152641[/C][/ROW]
[ROW][C]144[/C][C]0.853078[/C][C]0.293844[/C][C]0.146922[/C][/ROW]
[ROW][C]145[/C][C]0.832565[/C][C]0.334871[/C][C]0.167435[/C][/ROW]
[ROW][C]146[/C][C]0.812767[/C][C]0.374465[/C][C]0.187233[/C][/ROW]
[ROW][C]147[/C][C]0.797471[/C][C]0.405057[/C][C]0.202529[/C][/ROW]
[ROW][C]148[/C][C]0.77188[/C][C]0.456241[/C][C]0.22812[/C][/ROW]
[ROW][C]149[/C][C]0.760056[/C][C]0.479888[/C][C]0.239944[/C][/ROW]
[ROW][C]150[/C][C]0.738567[/C][C]0.522867[/C][C]0.261433[/C][/ROW]
[ROW][C]151[/C][C]0.894572[/C][C]0.210855[/C][C]0.105428[/C][/ROW]
[ROW][C]152[/C][C]0.889387[/C][C]0.221227[/C][C]0.110613[/C][/ROW]
[ROW][C]153[/C][C]0.878488[/C][C]0.243024[/C][C]0.121512[/C][/ROW]
[ROW][C]154[/C][C]0.860346[/C][C]0.279308[/C][C]0.139654[/C][/ROW]
[ROW][C]155[/C][C]0.86588[/C][C]0.268241[/C][C]0.13412[/C][/ROW]
[ROW][C]156[/C][C]0.846238[/C][C]0.307525[/C][C]0.153762[/C][/ROW]
[ROW][C]157[/C][C]0.844196[/C][C]0.311608[/C][C]0.155804[/C][/ROW]
[ROW][C]158[/C][C]0.839021[/C][C]0.321959[/C][C]0.160979[/C][/ROW]
[ROW][C]159[/C][C]0.827089[/C][C]0.345823[/C][C]0.172911[/C][/ROW]
[ROW][C]160[/C][C]0.815265[/C][C]0.369471[/C][C]0.184735[/C][/ROW]
[ROW][C]161[/C][C]0.809944[/C][C]0.380112[/C][C]0.190056[/C][/ROW]
[ROW][C]162[/C][C]0.801311[/C][C]0.397379[/C][C]0.198689[/C][/ROW]
[ROW][C]163[/C][C]0.775825[/C][C]0.448351[/C][C]0.224175[/C][/ROW]
[ROW][C]164[/C][C]0.923647[/C][C]0.152707[/C][C]0.0763534[/C][/ROW]
[ROW][C]165[/C][C]0.910285[/C][C]0.179431[/C][C]0.0897155[/C][/ROW]
[ROW][C]166[/C][C]0.896782[/C][C]0.206437[/C][C]0.103218[/C][/ROW]
[ROW][C]167[/C][C]0.881546[/C][C]0.236909[/C][C]0.118454[/C][/ROW]
[ROW][C]168[/C][C]0.868471[/C][C]0.263058[/C][C]0.131529[/C][/ROW]
[ROW][C]169[/C][C]0.851107[/C][C]0.297786[/C][C]0.148893[/C][/ROW]
[ROW][C]170[/C][C]0.867712[/C][C]0.264576[/C][C]0.132288[/C][/ROW]
[ROW][C]171[/C][C]0.84909[/C][C]0.301819[/C][C]0.15091[/C][/ROW]
[ROW][C]172[/C][C]0.841192[/C][C]0.317616[/C][C]0.158808[/C][/ROW]
[ROW][C]173[/C][C]0.834155[/C][C]0.33169[/C][C]0.165845[/C][/ROW]
[ROW][C]174[/C][C]0.814446[/C][C]0.371107[/C][C]0.185554[/C][/ROW]
[ROW][C]175[/C][C]0.792058[/C][C]0.415884[/C][C]0.207942[/C][/ROW]
[ROW][C]176[/C][C]0.797929[/C][C]0.404143[/C][C]0.202071[/C][/ROW]
[ROW][C]177[/C][C]0.777322[/C][C]0.445357[/C][C]0.222678[/C][/ROW]
[ROW][C]178[/C][C]0.779583[/C][C]0.440834[/C][C]0.220417[/C][/ROW]
[ROW][C]179[/C][C]0.76659[/C][C]0.466821[/C][C]0.23341[/C][/ROW]
[ROW][C]180[/C][C]0.780293[/C][C]0.439415[/C][C]0.219707[/C][/ROW]
[ROW][C]181[/C][C]0.784971[/C][C]0.430059[/C][C]0.215029[/C][/ROW]
[ROW][C]182[/C][C]0.775409[/C][C]0.449182[/C][C]0.224591[/C][/ROW]
[ROW][C]183[/C][C]0.802883[/C][C]0.394234[/C][C]0.197117[/C][/ROW]
[ROW][C]184[/C][C]0.782185[/C][C]0.435629[/C][C]0.217815[/C][/ROW]
[ROW][C]185[/C][C]0.904581[/C][C]0.190838[/C][C]0.0954188[/C][/ROW]
[ROW][C]186[/C][C]0.890305[/C][C]0.219389[/C][C]0.109695[/C][/ROW]
[ROW][C]187[/C][C]0.882874[/C][C]0.234252[/C][C]0.117126[/C][/ROW]
[ROW][C]188[/C][C]0.909[/C][C]0.182001[/C][C]0.0910003[/C][/ROW]
[ROW][C]189[/C][C]0.927959[/C][C]0.144083[/C][C]0.0720415[/C][/ROW]
[ROW][C]190[/C][C]0.914968[/C][C]0.170063[/C][C]0.0850317[/C][/ROW]
[ROW][C]191[/C][C]0.899244[/C][C]0.201512[/C][C]0.100756[/C][/ROW]
[ROW][C]192[/C][C]0.897123[/C][C]0.205754[/C][C]0.102877[/C][/ROW]
[ROW][C]193[/C][C]0.917773[/C][C]0.164455[/C][C]0.0822273[/C][/ROW]
[ROW][C]194[/C][C]0.910839[/C][C]0.178322[/C][C]0.0891612[/C][/ROW]
[ROW][C]195[/C][C]0.896093[/C][C]0.207815[/C][C]0.103907[/C][/ROW]
[ROW][C]196[/C][C]0.878901[/C][C]0.242198[/C][C]0.121099[/C][/ROW]
[ROW][C]197[/C][C]0.885559[/C][C]0.228881[/C][C]0.114441[/C][/ROW]
[ROW][C]198[/C][C]0.865292[/C][C]0.269415[/C][C]0.134708[/C][/ROW]
[ROW][C]199[/C][C]0.852455[/C][C]0.29509[/C][C]0.147545[/C][/ROW]
[ROW][C]200[/C][C]0.833932[/C][C]0.332137[/C][C]0.166068[/C][/ROW]
[ROW][C]201[/C][C]0.821981[/C][C]0.356038[/C][C]0.178019[/C][/ROW]
[ROW][C]202[/C][C]0.7998[/C][C]0.4004[/C][C]0.2002[/C][/ROW]
[ROW][C]203[/C][C]0.786813[/C][C]0.426374[/C][C]0.213187[/C][/ROW]
[ROW][C]204[/C][C]0.760954[/C][C]0.478092[/C][C]0.239046[/C][/ROW]
[ROW][C]205[/C][C]0.735602[/C][C]0.528796[/C][C]0.264398[/C][/ROW]
[ROW][C]206[/C][C]0.73022[/C][C]0.539561[/C][C]0.26978[/C][/ROW]
[ROW][C]207[/C][C]0.731133[/C][C]0.537734[/C][C]0.268867[/C][/ROW]
[ROW][C]208[/C][C]0.732518[/C][C]0.534964[/C][C]0.267482[/C][/ROW]
[ROW][C]209[/C][C]0.726206[/C][C]0.547588[/C][C]0.273794[/C][/ROW]
[ROW][C]210[/C][C]0.717149[/C][C]0.565703[/C][C]0.282851[/C][/ROW]
[ROW][C]211[/C][C]0.71982[/C][C]0.560359[/C][C]0.28018[/C][/ROW]
[ROW][C]212[/C][C]0.685882[/C][C]0.628236[/C][C]0.314118[/C][/ROW]
[ROW][C]213[/C][C]0.654511[/C][C]0.690977[/C][C]0.345489[/C][/ROW]
[ROW][C]214[/C][C]0.614867[/C][C]0.770265[/C][C]0.385133[/C][/ROW]
[ROW][C]215[/C][C]0.572306[/C][C]0.855389[/C][C]0.427694[/C][/ROW]
[ROW][C]216[/C][C]0.530273[/C][C]0.939453[/C][C]0.469727[/C][/ROW]
[ROW][C]217[/C][C]0.505921[/C][C]0.988158[/C][C]0.494079[/C][/ROW]
[ROW][C]218[/C][C]0.500044[/C][C]0.999911[/C][C]0.499956[/C][/ROW]
[ROW][C]219[/C][C]0.48272[/C][C]0.96544[/C][C]0.51728[/C][/ROW]
[ROW][C]220[/C][C]0.458088[/C][C]0.916177[/C][C]0.541912[/C][/ROW]
[ROW][C]221[/C][C]0.440966[/C][C]0.881932[/C][C]0.559034[/C][/ROW]
[ROW][C]222[/C][C]0.460436[/C][C]0.920873[/C][C]0.539564[/C][/ROW]
[ROW][C]223[/C][C]0.419422[/C][C]0.838845[/C][C]0.580578[/C][/ROW]
[ROW][C]224[/C][C]0.416766[/C][C]0.833532[/C][C]0.583234[/C][/ROW]
[ROW][C]225[/C][C]0.440032[/C][C]0.880065[/C][C]0.559968[/C][/ROW]
[ROW][C]226[/C][C]0.413127[/C][C]0.826253[/C][C]0.586873[/C][/ROW]
[ROW][C]227[/C][C]0.37099[/C][C]0.74198[/C][C]0.62901[/C][/ROW]
[ROW][C]228[/C][C]0.471837[/C][C]0.943674[/C][C]0.528163[/C][/ROW]
[ROW][C]229[/C][C]0.744801[/C][C]0.510398[/C][C]0.255199[/C][/ROW]
[ROW][C]230[/C][C]0.756346[/C][C]0.487308[/C][C]0.243654[/C][/ROW]
[ROW][C]231[/C][C]0.730141[/C][C]0.539718[/C][C]0.269859[/C][/ROW]
[ROW][C]232[/C][C]0.773775[/C][C]0.452449[/C][C]0.226225[/C][/ROW]
[ROW][C]233[/C][C]0.777162[/C][C]0.445677[/C][C]0.222838[/C][/ROW]
[ROW][C]234[/C][C]0.753831[/C][C]0.492339[/C][C]0.246169[/C][/ROW]
[ROW][C]235[/C][C]0.78199[/C][C]0.436021[/C][C]0.21801[/C][/ROW]
[ROW][C]236[/C][C]0.846076[/C][C]0.307847[/C][C]0.153924[/C][/ROW]
[ROW][C]237[/C][C]0.811049[/C][C]0.377903[/C][C]0.188951[/C][/ROW]
[ROW][C]238[/C][C]0.781254[/C][C]0.437492[/C][C]0.218746[/C][/ROW]
[ROW][C]239[/C][C]0.85564[/C][C]0.28872[/C][C]0.14436[/C][/ROW]
[ROW][C]240[/C][C]0.822362[/C][C]0.355277[/C][C]0.177638[/C][/ROW]
[ROW][C]241[/C][C]0.78554[/C][C]0.42892[/C][C]0.21446[/C][/ROW]
[ROW][C]242[/C][C]0.758414[/C][C]0.483172[/C][C]0.241586[/C][/ROW]
[ROW][C]243[/C][C]0.711621[/C][C]0.576758[/C][C]0.288379[/C][/ROW]
[ROW][C]244[/C][C]0.659983[/C][C]0.680034[/C][C]0.340017[/C][/ROW]
[ROW][C]245[/C][C]0.603895[/C][C]0.79221[/C][C]0.396105[/C][/ROW]
[ROW][C]246[/C][C]0.568722[/C][C]0.862556[/C][C]0.431278[/C][/ROW]
[ROW][C]247[/C][C]0.547781[/C][C]0.904437[/C][C]0.452219[/C][/ROW]
[ROW][C]248[/C][C]0.528691[/C][C]0.942618[/C][C]0.471309[/C][/ROW]
[ROW][C]249[/C][C]0.485746[/C][C]0.971491[/C][C]0.514254[/C][/ROW]
[ROW][C]250[/C][C]0.481208[/C][C]0.962415[/C][C]0.518792[/C][/ROW]
[ROW][C]251[/C][C]0.432674[/C][C]0.865349[/C][C]0.567326[/C][/ROW]
[ROW][C]252[/C][C]0.377198[/C][C]0.754396[/C][C]0.622802[/C][/ROW]
[ROW][C]253[/C][C]0.3808[/C][C]0.7616[/C][C]0.6192[/C][/ROW]
[ROW][C]254[/C][C]0.325498[/C][C]0.650997[/C][C]0.674502[/C][/ROW]
[ROW][C]255[/C][C]0.297722[/C][C]0.595445[/C][C]0.702278[/C][/ROW]
[ROW][C]256[/C][C]0.266743[/C][C]0.533487[/C][C]0.733257[/C][/ROW]
[ROW][C]257[/C][C]0.232549[/C][C]0.465098[/C][C]0.767451[/C][/ROW]
[ROW][C]258[/C][C]0.460831[/C][C]0.921662[/C][C]0.539169[/C][/ROW]
[ROW][C]259[/C][C]0.421665[/C][C]0.84333[/C][C]0.578335[/C][/ROW]
[ROW][C]260[/C][C]0.951825[/C][C]0.09635[/C][C]0.048175[/C][/ROW]
[ROW][C]261[/C][C]0.912057[/C][C]0.175886[/C][C]0.0879429[/C][/ROW]
[ROW][C]262[/C][C]0.887093[/C][C]0.225814[/C][C]0.112907[/C][/ROW]
[ROW][C]263[/C][C]0.984947[/C][C]0.030107[/C][C]0.0150535[/C][/ROW]
[ROW][C]264[/C][C]0.961575[/C][C]0.0768498[/C][C]0.0384249[/C][/ROW]
[ROW][C]265[/C][C]0.896536[/C][C]0.206928[/C][C]0.103464[/C][/ROW]
[ROW][C]266[/C][C]0.751774[/C][C]0.496452[/C][C]0.248226[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=5

As an alternative you can also use a QR Code:

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

Goldfeld-Quandt test for Heteroskedasticity
p-values	Alternative Hypothesis
breakpoint index	greater	2-sided	less
13	0.958502	0.0829953	0.0414977
14	0.91675	0.1665	0.0832499
15	0.872574	0.254852	0.127426
16	0.800151	0.399698	0.199849
17	0.713627	0.572745	0.286373
18	0.723204	0.553592	0.276796
19	0.733553	0.532893	0.266447
20	0.65275	0.694501	0.34725
21	0.655855	0.688289	0.344145
22	0.649496	0.701007	0.350504
23	0.611189	0.777622	0.388811
24	0.703029	0.593941	0.296971
25	0.635701	0.728598	0.364299
26	0.567218	0.865564	0.432782
27	0.504981	0.990038	0.495019
28	0.469107	0.938213	0.530893
29	0.401823	0.803645	0.598177
30	0.344079	0.688158	0.655921
31	0.510678	0.978643	0.489322
32	0.449454	0.898908	0.550546
33	0.412104	0.824209	0.587896
34	0.393445	0.78689	0.606555
35	0.336619	0.673237	0.663381
36	0.331721	0.663443	0.668279
37	0.285701	0.571402	0.714299
38	0.266475	0.532951	0.733525
39	0.259701	0.519402	0.740299
40	0.296404	0.592808	0.703596
41	0.455668	0.911335	0.544332
42	0.410786	0.821573	0.589214
43	0.395753	0.791506	0.604247
44	0.363046	0.726092	0.636954
45	0.3366	0.673201	0.6634
46	0.302974	0.605948	0.697026
47	0.333133	0.666265	0.666867
48	0.386633	0.773266	0.613367
49	0.489246	0.978492	0.510754
50	0.446482	0.892964	0.553518
51	0.403493	0.806985	0.596507
52	0.436091	0.872181	0.563909
53	0.40936	0.81872	0.59064
54	0.395065	0.790131	0.604935
55	0.486189	0.972377	0.513811
56	0.447827	0.895655	0.552173
57	0.791334	0.417332	0.208666
58	0.889706	0.220588	0.110294
59	0.86778	0.264441	0.13222
60	0.878548	0.242903	0.121452
61	0.874096	0.251809	0.125904
62	0.855388	0.289223	0.144612
63	0.88184	0.23632	0.11816
64	0.911544	0.176911	0.0884557
65	0.905831	0.188337	0.0941686
66	0.887547	0.224906	0.112453
67	0.871049	0.257901	0.128951
68	0.852621	0.294757	0.147379
69	0.858116	0.283768	0.141884
70	0.840305	0.319391	0.159695
71	0.817288	0.365425	0.182712
72	0.794305	0.411389	0.205695
73	0.770215	0.459571	0.229785
74	0.803369	0.393263	0.196631
75	0.800487	0.399025	0.199513
76	0.794455	0.41109	0.205545
77	0.782187	0.435626	0.217813
78	0.779653	0.440695	0.220347
79	0.758775	0.48245	0.241225
80	0.766104	0.467792	0.233896
81	0.736506	0.526989	0.263494
82	0.775903	0.448194	0.224097
83	0.746384	0.507233	0.253616
84	0.824726	0.350549	0.175274
85	0.815737	0.368526	0.184263
86	0.795534	0.408932	0.204466
87	0.782147	0.435706	0.217853
88	0.756055	0.487891	0.243945
89	0.76095	0.4781	0.23905
90	0.778472	0.443056	0.221528
91	0.810839	0.378322	0.189161
92	0.898438	0.203124	0.101562
93	0.881412	0.237176	0.118588
94	0.877489	0.245022	0.122511
95	0.885029	0.229941	0.114971
96	0.873925	0.252149	0.126075
97	0.880797	0.238406	0.119203
98	0.868659	0.262682	0.131341
99	0.902136	0.195729	0.0978644
100	0.917729	0.164542	0.0822712
101	0.909938	0.180125	0.0900623
102	0.894656	0.210688	0.105344
103	0.878573	0.242854	0.121427
104	0.8646	0.2708	0.1354
105	0.9116	0.176799	0.0883997
106	0.902591	0.194819	0.0974094
107	0.929847	0.140305	0.0701527
108	0.950725	0.0985508	0.0492754
109	0.953805	0.0923908	0.0461954
110	0.948651	0.102698	0.051349
111	0.940356	0.119287	0.0596436
112	0.931627	0.136745	0.0683727
113	0.952999	0.0940015	0.0470007
114	0.97536	0.0492798	0.0246399
115	0.976393	0.0472142	0.0236071
116	0.976661	0.0466776	0.0233388
117	0.972108	0.0557836	0.0278918
118	0.966044	0.0679117	0.0339558
119	0.959887	0.0802251	0.0401126
120	0.95794	0.0841198	0.0420599
121	0.951242	0.0975152	0.0487576
122	0.953784	0.0924325	0.0462163
123	0.946604	0.106791	0.0533956
124	0.970156	0.0596881	0.029844
125	0.973748	0.052503	0.0262515
126	0.969156	0.0616881	0.030844
127	0.963481	0.0730387	0.0365193
128	0.957839	0.0843224	0.0421612
129	0.953392	0.0932168	0.0466084
130	0.945024	0.109951	0.0549757
131	0.935832	0.128336	0.0641682
132	0.925982	0.148036	0.0740178
133	0.920627	0.158747	0.0793733
134	0.908892	0.182216	0.0911079
135	0.89791	0.20418	0.10209
136	0.884692	0.230617	0.115308
137	0.901586	0.196828	0.0984141
138	0.912501	0.174998	0.0874992
139	0.901774	0.196453	0.0982263
140	0.88966	0.220681	0.11034
141	0.8779	0.244199	0.1221
142	0.8642	0.271599	0.1358
143	0.847359	0.305283	0.152641
144	0.853078	0.293844	0.146922
145	0.832565	0.334871	0.167435
146	0.812767	0.374465	0.187233
147	0.797471	0.405057	0.202529
148	0.77188	0.456241	0.22812
149	0.760056	0.479888	0.239944
150	0.738567	0.522867	0.261433
151	0.894572	0.210855	0.105428
152	0.889387	0.221227	0.110613
153	0.878488	0.243024	0.121512
154	0.860346	0.279308	0.139654
155	0.86588	0.268241	0.13412
156	0.846238	0.307525	0.153762
157	0.844196	0.311608	0.155804
158	0.839021	0.321959	0.160979
159	0.827089	0.345823	0.172911
160	0.815265	0.369471	0.184735
161	0.809944	0.380112	0.190056
162	0.801311	0.397379	0.198689
163	0.775825	0.448351	0.224175
164	0.923647	0.152707	0.0763534
165	0.910285	0.179431	0.0897155
166	0.896782	0.206437	0.103218
167	0.881546	0.236909	0.118454
168	0.868471	0.263058	0.131529
169	0.851107	0.297786	0.148893
170	0.867712	0.264576	0.132288
171	0.84909	0.301819	0.15091
172	0.841192	0.317616	0.158808
173	0.834155	0.33169	0.165845
174	0.814446	0.371107	0.185554
175	0.792058	0.415884	0.207942
176	0.797929	0.404143	0.202071
177	0.777322	0.445357	0.222678
178	0.779583	0.440834	0.220417
179	0.76659	0.466821	0.23341
180	0.780293	0.439415	0.219707
181	0.784971	0.430059	0.215029
182	0.775409	0.449182	0.224591
183	0.802883	0.394234	0.197117
184	0.782185	0.435629	0.217815
185	0.904581	0.190838	0.0954188
186	0.890305	0.219389	0.109695
187	0.882874	0.234252	0.117126
188	0.909	0.182001	0.0910003
189	0.927959	0.144083	0.0720415
190	0.914968	0.170063	0.0850317
191	0.899244	0.201512	0.100756
192	0.897123	0.205754	0.102877
193	0.917773	0.164455	0.0822273
194	0.910839	0.178322	0.0891612
195	0.896093	0.207815	0.103907
196	0.878901	0.242198	0.121099
197	0.885559	0.228881	0.114441
198	0.865292	0.269415	0.134708
199	0.852455	0.29509	0.147545
200	0.833932	0.332137	0.166068
201	0.821981	0.356038	0.178019
202	0.7998	0.4004	0.2002
203	0.786813	0.426374	0.213187
204	0.760954	0.478092	0.239046
205	0.735602	0.528796	0.264398
206	0.73022	0.539561	0.26978
207	0.731133	0.537734	0.268867
208	0.732518	0.534964	0.267482
209	0.726206	0.547588	0.273794
210	0.717149	0.565703	0.282851
211	0.71982	0.560359	0.28018
212	0.685882	0.628236	0.314118
213	0.654511	0.690977	0.345489
214	0.614867	0.770265	0.385133
215	0.572306	0.855389	0.427694
216	0.530273	0.939453	0.469727
217	0.505921	0.988158	0.494079
218	0.500044	0.999911	0.499956
219	0.48272	0.96544	0.51728
220	0.458088	0.916177	0.541912
221	0.440966	0.881932	0.559034
222	0.460436	0.920873	0.539564
223	0.419422	0.838845	0.580578
224	0.416766	0.833532	0.583234
225	0.440032	0.880065	0.559968
226	0.413127	0.826253	0.586873
227	0.37099	0.74198	0.62901
228	0.471837	0.943674	0.528163
229	0.744801	0.510398	0.255199
230	0.756346	0.487308	0.243654
231	0.730141	0.539718	0.269859
232	0.773775	0.452449	0.226225
233	0.777162	0.445677	0.222838
234	0.753831	0.492339	0.246169
235	0.78199	0.436021	0.21801
236	0.846076	0.307847	0.153924
237	0.811049	0.377903	0.188951
238	0.781254	0.437492	0.218746
239	0.85564	0.28872	0.14436
240	0.822362	0.355277	0.177638
241	0.78554	0.42892	0.21446
242	0.758414	0.483172	0.241586
243	0.711621	0.576758	0.288379
244	0.659983	0.680034	0.340017
245	0.603895	0.79221	0.396105
246	0.568722	0.862556	0.431278
247	0.547781	0.904437	0.452219
248	0.528691	0.942618	0.471309
249	0.485746	0.971491	0.514254
250	0.481208	0.962415	0.518792
251	0.432674	0.865349	0.567326
252	0.377198	0.754396	0.622802
253	0.3808	0.7616	0.6192
254	0.325498	0.650997	0.674502
255	0.297722	0.595445	0.702278
256	0.266743	0.533487	0.733257
257	0.232549	0.465098	0.767451
258	0.460831	0.921662	0.539169
259	0.421665	0.84333	0.578335
260	0.951825	0.09635	0.048175
261	0.912057	0.175886	0.0879429
262	0.887093	0.225814	0.112907
263	0.984947	0.030107	0.0150535
264	0.961575	0.0768498	0.0384249
265	0.896536	0.206928	0.103464
266	0.751774	0.496452	0.248226

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	4	0.015748	OK
10% type I error level	22	0.0866142	OK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 4 & 0.015748 & OK \tabularnewline
10% type I error level & 22 & 0.0866142 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=264403&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]4[/C][C]0.015748[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]22[/C][C]0.0866142[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=264403&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=264403&T=6

As an alternative you can also use a QR Code:

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description	# significant tests	% significant tests	OK/NOK
1% type I error level	0	0	OK
5% type I error level	4	0.015748	OK
10% type I error level	22	0.0866142	OK

Figure 1

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Figure 2

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Figure 3

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Figure 4

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Figure 5

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Figure 6

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Figure 7

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Figure 8

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Figure 9

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Figure 10

PNG link

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Parameters (Session):

par1 = 10 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;

Parameters (R input):

par1 = 10 ; 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')
}

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code