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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationFri, 15 Nov 2013 10:16:22 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/15/t13845286048e0eppva7xxtjkq.htm/, Retrieved Tue, 30 Apr 2024 19:47:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=225501, Retrieved Tue, 30 Apr 2024 19:47:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact49

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [] [2013-11-15 14:34:41] [a5062392f41e88f97a2275cae88db61b]
-   PD    [Multiple Regression] [] [2013-11-15 15:16:22] [8707ec56d577a36c6e8f91524bd637f5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
41 38 13 12 14 12 53 32 9
39 32 16 11 18 11 83 51 9
30 35 19 15 11 14 66 42 9
31 33 15 6 12 12 67 41 9
34 37 14 13 16 21 76 46 9
35 29 13 10 18 12 78 47 9
39 31 19 12 14 22 53 37 9
34 36 15 14 14 11 80 49 9
36 35 14 12 15 10 74 45 9
37 38 15 9 15 13 76 47 9
38 31 16 10 17 10 79 49 9
36 34 16 12 19 8 54 33 9
38 35 16 12 10 15 67 42 9
39 38 16 11 16 14 54 33 9
33 37 17 15 18 10 87 53 9
32 33 15 12 14 14 58 36 9
36 32 15 10 14 14 75 45 9
38 38 20 12 17 11 88 54 9
39 38 18 11 14 10 64 41 9
32 32 16 12 16 13 57 36 9
32 33 16 11 18 9.5 66 41 9
31 31 16 12 11 14 68 44 9
39 38 19 13 14 12 54 33 9
37 39 16 11 12 14 56 37 9
39 32 17 12 17 11 86 52 9
41 32 17 13 9 9 80 47 9
36 35 16 10 16 11 76 43 9
33 37 15 14 14 15 69 44 9
33 33 16 12 15 14 78 45 9
34 33 14 10 11 13 67 44 9
31 31 15 12 16 9 80 49 9
27 32 12 8 13 15 54 33 9
37 31 14 10 17 10 71 43 9
34 37 16 12 15 11 84 54 9
34 30 14 12 14 13 74 42 9
32 33 10 7 16 8 71 44 9
29 31 10 9 9 20 63 37 9
36 33 14 12 15 12 71 43 9
29 31 16 10 17 10 76 46 9
35 33 16 10 13 10 69 42 9
37 32 16 10 15 9 74 45 9
34 33 14 12 16 14 75 44 9
38 32 20 15 16 8 54 33 9
35 33 14 10 12 14 52 31 9
38 28 14 10 15 11 69 42 9
37 35 11 12 11 13 68 40 9
38 39 14 13 15 9 65 43 9
33 34 15 11 15 11 75 46 9
36 38 16 11 17 15 74 42 9
38 32 14 12 13 11 75 45 9
32 38 16 14 16 10 72 44 9
32 30 14 10 14 14 67 40 9
32 33 12 12 11 18 63 37 9
34 38 16 13 12 14 62 46 9
32 32 9 5 12 11 63 36 9
37 35 14 6 15 14.5 76 47 9
39 34 16 12 16 13 74 45 9
29 34 16 12 15 9 67 42 9
37 36 15 11 12 10 73 43 9
35 34 16 10 12 15 70 43 9
30 28 12 7 8 20 53 32 9
38 34 16 12 13 12 77 45 9
34 35 16 14 11 12 80 48 9
31 35 14 11 14 14 52 31 9
34 31 16 12 15 13 54 33 9
35 37 17 13 10 11 80 49 10
36 35 18 14 11 17 66 42 10
30 27 18 11 12 12 73 41 10
39 40 12 12 15 13 63 38 10
35 37 16 12 15 14 69 42 10
38 36 10 8 14 13 67 44 10
31 38 14 11 16 15 54 33 10
34 39 18 14 15 13 81 48 10
38 41 18 14 15 10 69 40 10
34 27 16 12 13 11 84 50 10
39 30 17 9 12 19 80 49 10
37 37 16 13 17 13 70 43 10
34 31 16 11 13 17 69 44 10
28 31 13 12 15 13 77 47 10
37 27 16 12 13 9 54 33 10
33 36 16 12 15 11 79 46 10
35 37 16 12 15 9 71 45 10
37 33 15 12 16 12 73 43 10
32 34 15 11 15 12 72 44 10
33 31 16 10 14 13 77 47 10
38 39 14 9 15 13 75 45 10
33 34 16 12 14 12 69 42 10
29 32 16 12 13 15 54 33 10
33 33 15 12 7 22 70 43 10
31 36 12 9 17 13 73 46 10
36 32 17 15 13 15 54 33 10
35 41 16 12 15 13 77 46 10
32 28 15 12 14 15 82 48 10
29 30 13 12 13 12.5 80 47 10
39 36 16 10 16 11 80 47 10
37 35 16 13 12 16 69 43 10
35 31 16 9 14 11 78 46 10
37 34 16 12 17 11 81 48 10
32 36 14 10 15 10 76 46 10
38 36 16 14 17 10 76 45 10
37 35 16 11 12 16 73 45 10
36 37 20 15 16 12 85 52 10
32 28 15 11 11 11 66 42 10
33 39 16 11 15 16 79 47 10
40 32 13 12 9 19 68 41 10
38 35 17 12 16 11 76 47 10
41 39 16 12 15 16 71 43 10
36 35 16 11 10 15 54 33 10
43 42 12 7 10 24 46 30 10
30 34 16 12 15 14 85 52 10
31 33 16 14 11 15 74 44 10
32 41 17 11 13 11 88 55 10
32 33 13 11 14 15 38 11 10
37 34 12 10 18 12 76 47 10
37 32 18 13 16 10 86 53 10
33 40 14 13 14 14 54 33 10
34 40 14 8 14 13 67 44 10
33 35 13 11 14 9 69 42 10
38 36 16 12 14 15 90 55 10
33 37 13 11 12 15 54 33 10
31 27 16 13 14 14 76 46 10
38 39 13 12 15 11 89 54 10
37 38 16 14 15 8 76 47 10
36 31 15 13 15 11 73 45 10
31 33 16 15 13 11 79 47 10
39 32 15 10 17 8 90 55 10
44 39 17 11 17 10 74 44 10
33 36 15 9 19 11 81 53 10
35 33 12 11 15 13 72 44 10
32 33 16 10 13 11 71 42 10
28 32 10 11 9 20 66 40 10
40 37 16 8 15 10 77 46 10
27 30 12 11 15 15 65 40 10
37 38 14 12 15 12 74 46 10
32 29 15 12 16 14 85 53 10
28 22 13 9 11 23 54 33 10
34 35 15 11 14 14 63 42 10
30 35 11 10 11 16 54 35 10
35 34 12 8 15 11 64 40 10
31 35 11 9 13 12 69 41 10
32 34 16 8 15 10 54 33 10
30 37 15 9 16 14 84 51 10
30 35 17 15 14 12 86 53 10
31 23 16 11 15 12 77 46 10
40 31 10 8 16 11 89 55 10
32 27 18 13 16 12 76 47 10
36 36 13 12 11 13 60 38 10
32 31 16 12 12 11 75 46 10
35 32 13 9 9 19 73 46 10
38 39 10 7 16 12 85 53 10
42 37 15 13 13 17 79 47 10
34 38 16 9 16 9 71 41 10
35 39 16 6 12 12 72 44 10
38 34 14 8 9 19 69 43 9
33 31 10 8 13 18 78 51 10
36 32 17 15 13 15 54 33 10
32 37 13 6 14 14 69 43 10
33 36 15 9 19 11 81 53 10
34 32 16 11 13 9 84 51 10
32 38 12 8 12 18 84 50 10
34 36 13 8 13 16 69 46 10
27 26 13 10 10 24 66 43 11
31 26 12 8 14 14 81 47 11
38 33 17 14 16 20 82 50 11
34 39 15 10 10 18 72 43 11
24 30 10 8 11 23 54 33 11
30 33 14 11 14 12 78 48 11
26 25 11 12 12 14 74 44 11
34 38 13 12 9 16 82 50 11
27 37 16 12 9 18 73 41 11
37 31 12 5 11 20 55 34 11
36 37 16 12 16 12 72 44 11
41 35 12 10 9 12 78 47 11
29 25 9 7 13 17 59 35 11
36 28 12 12 16 13 72 44 11
32 35 15 11 13 9 78 44 11
37 33 12 8 9 16 68 43 11
30 30 12 9 12 18 69 41 11
31 31 14 10 16 10 67 41 11
38 37 12 9 11 14 74 42 11
36 36 16 12 14 11 54 33 11
35 30 11 6 13 9 67 41 11
31 36 19 15 15 11 70 44 11
38 32 15 12 14 10 80 48 11
22 28 8 12 16 11 89 55 11
32 36 16 12 13 19 76 44 11
36 34 17 11 14 14 74 43 11
39 31 12 7 15 12 87 52 11
28 28 11 7 13 14 54 30 11
32 36 11 5 11 21 61 39 11
32 36 14 12 11 13 38 11 11
38 40 16 12 14 10 75 44 11
32 33 12 3 15 15 69 42 11
35 37 16 11 11 16 62 41 11
32 32 13 10 15 14 72 44 11
37 38 15 12 12 12 70 44 11
34 31 16 9 14 19 79 48 11
33 37 16 12 14 15 87 53 11
33 33 14 9 8 19 62 37 11
26 32 16 12 13 13 77 44 11
30 30 16 12 9 17 69 44 11
24 30 14 10 15 12 69 40 11
34 31 11 9 17 11 75 42 11
34 32 12 12 13 14 54 35 11
33 34 15 8 15 11 72 43 11
34 36 15 11 15 13 74 45 11
35 37 16 11 14 12 85 55 11
35 36 16 12 16 15 52 31 11
36 33 11 10 13 14 70 44 11
34 33 15 10 16 12 84 50 11
34 33 12 12 9 17 64 40 11
41 44 12 12 16 11 84 53 11
32 39 15 11 11 18 87 54 11
30 32 15 8 10 13 79 49 11
35 35 16 12 11 17 67 40 11
28 25 14 10 15 13 65 41 11
33 35 17 11 17 11 85 52 11
39 34 14 10 14 12 83 52 11
36 35 13 8 8 22 61 36 11
36 39 15 12 15 14 82 52 11
35 33 13 12 11 12 76 46 11
38 36 14 10 16 12 58 31 11
33 32 15 12 10 17 72 44 11
31 32 12 9 15 9 72 44 11
34 36 13 9 9 21 38 11 11
32 36 8 6 16 10 78 46 11
31 32 14 10 19 11 54 33 11
33 34 14 9 12 12 63 34 11
34 33 11 9 8 23 66 42 11
34 35 12 9 11 13 70 43 11
34 30 13 6 14 12 71 43 11
33 38 10 10 9 16 67 44 11
32 34 16 6 15 9 58 36 11
41 33 18 14 13 17 72 46 11
34 32 13 10 16 9 72 44 11
36 31 11 10 11 14 70 43 11
37 30 4 6 12 17 76 50 11
36 27 13 12 13 13 50 33 11
29 31 16 12 10 11 72 43 11
37 30 10 7 11 12 72 44 11
27 32 12 8 12 10 88 53 11
35 35 12 11 8 19 53 34 11
28 28 10 3 12 16 58 35 11
35 33 13 6 12 16 66 40 11
37 31 15 10 15 14 82 53 11
29 35 12 8 11 20 69 42 11
32 35 14 9 13 15 68 43 11
36 32 10 9 14 23 44 29 11
19 21 12 8 10 20 56 36 11
21 20 12 9 12 16 53 30 11
31 34 11 7 15 14 70 42 11
33 32 10 7 13 17 78 47 11
36 34 12 6 13 11 71 44 11
33 32 16 9 13 13 72 45 11
37 33 12 10 12 17 68 44 11
34 33 14 11 12 15 67 43 11
35 37 16 12 9 21 75 43 11
31 32 14 8 9 18 62 40 11
37 34 13 11 15 15 67 41 11
35 30 4 3 10 8 83 52 11
27 30 15 11 14 12 64 38 11
34 38 11 12 15 12 68 41 11
40 36 11 7 7 22 62 39 11
29 32 14 9 14 12 72 43 11

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time24 seconds
R Server'Gwilym Jenkins' @ jenkins.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 & 24 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&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]24 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=0

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


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

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time24 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.3933 + 0.0014584Connected[t] + 0.0101912Separate[t] + 0.0991405Learning[t] -0.0212946Software[t] -0.369643Depression[t] + 0.0159983Sport1[t] + 0.0127107Sport2[t] -0.32003Month[t] + 0.0743511M1[t] -0.070315M2[t] -0.240352M3[t] -0.0105674M4[t] + 0.125367M5[t] + 0.829632M6[t] + 0.141309M7[t] + 0.485995M8[t] + 0.0202259M9[t] -0.0119043M10[t] + 0.328975M11[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  18.3933 +  0.0014584Connected[t] +  0.0101912Separate[t] +  0.0991405Learning[t] -0.0212946Software[t] -0.369643Depression[t] +  0.0159983Sport1[t] +  0.0127107Sport2[t] -0.32003Month[t] +  0.0743511M1[t] -0.070315M2[t] -0.240352M3[t] -0.0105674M4[t] +  0.125367M5[t] +  0.829632M6[t] +  0.141309M7[t] +  0.485995M8[t] +  0.0202259M9[t] -0.0119043M10[t] +  0.328975M11[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  18.3933 +  0.0014584Connected[t] +  0.0101912Separate[t] +  0.0991405Learning[t] -0.0212946Software[t] -0.369643Depression[t] +  0.0159983Sport1[t] +  0.0127107Sport2[t] -0.32003Month[t] +  0.0743511M1[t] -0.070315M2[t] -0.240352M3[t] -0.0105674M4[t] +  0.125367M5[t] +  0.829632M6[t] +  0.141309M7[t] +  0.485995M8[t] +  0.0202259M9[t] -0.0119043M10[t] +  0.328975M11[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 18.3933 + 0.0014584Connected[t] + 0.0101912Separate[t] + 0.0991405Learning[t] -0.0212946Software[t] -0.369643Depression[t] + 0.0159983Sport1[t] + 0.0127107Sport2[t] -0.32003Month[t] + 0.0743511M1[t] -0.070315M2[t] -0.240352M3[t] -0.0105674M4[t] + 0.125367M5[t] + 0.829632M6[t] + 0.141309M7[t] + 0.485995M8[t] + 0.0202259M9[t] -0.0119043M10[t] + 0.328975M11[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.39332.733416.7291.20815e-106.04074e-11
Connected0.00145840.03942990.036990.9705260.485263
Separate0.01019120.03930490.25930.7956330.397816
Learning0.09914050.06892621.4380.1516140.075807
Software-0.02129460.0708961-0.30040.7641560.382078
Depression-0.3696430.0414528-8.9171.15197e-165.75983e-17
Sport10.01599830.04185570.38220.7026270.351313
Sport20.01271070.06220260.20430.8382550.419127
Month-0.320030.176714-1.8110.07137060.0356853
M10.07435110.6260690.11880.9055640.452782
M2-0.0703150.624406-0.11260.9104320.455216
M3-0.2403520.622767-0.38590.6998760.349938
M4-0.01056740.620183-0.017040.9864190.49321
M50.1253670.6264550.20010.8415520.420776
M60.8296320.6290421.3190.1884450.0942226
M70.1413090.6221850.22710.8205230.410261
M80.4859950.6180340.78640.4324220.216211
M90.02022590.6181610.032720.9739250.486963
M10-0.01190430.62297-0.019110.984770.492385
M110.3289750.6184780.53190.5952720.297636

\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) & 18.3933 & 2.73341 & 6.729 & 1.20815e-10 & 6.04074e-11 \tabularnewline
Connected & 0.0014584 & 0.0394299 & 0.03699 & 0.970526 & 0.485263 \tabularnewline
Separate & 0.0101912 & 0.0393049 & 0.2593 & 0.795633 & 0.397816 \tabularnewline
Learning & 0.0991405 & 0.0689262 & 1.438 & 0.151614 & 0.075807 \tabularnewline
Software & -0.0212946 & 0.0708961 & -0.3004 & 0.764156 & 0.382078 \tabularnewline
Depression & -0.369643 & 0.0414528 & -8.917 & 1.15197e-16 & 5.75983e-17 \tabularnewline
Sport1 & 0.0159983 & 0.0418557 & 0.3822 & 0.702627 & 0.351313 \tabularnewline
Sport2 & 0.0127107 & 0.0622026 & 0.2043 & 0.838255 & 0.419127 \tabularnewline
Month & -0.32003 & 0.176714 & -1.811 & 0.0713706 & 0.0356853 \tabularnewline
M1 & 0.0743511 & 0.626069 & 0.1188 & 0.905564 & 0.452782 \tabularnewline
M2 & -0.070315 & 0.624406 & -0.1126 & 0.910432 & 0.455216 \tabularnewline
M3 & -0.240352 & 0.622767 & -0.3859 & 0.699876 & 0.349938 \tabularnewline
M4 & -0.0105674 & 0.620183 & -0.01704 & 0.986419 & 0.49321 \tabularnewline
M5 & 0.125367 & 0.626455 & 0.2001 & 0.841552 & 0.420776 \tabularnewline
M6 & 0.829632 & 0.629042 & 1.319 & 0.188445 & 0.0942226 \tabularnewline
M7 & 0.141309 & 0.622185 & 0.2271 & 0.820523 & 0.410261 \tabularnewline
M8 & 0.485995 & 0.618034 & 0.7864 & 0.432422 & 0.216211 \tabularnewline
M9 & 0.0202259 & 0.618161 & 0.03272 & 0.973925 & 0.486963 \tabularnewline
M10 & -0.0119043 & 0.62297 & -0.01911 & 0.98477 & 0.492385 \tabularnewline
M11 & 0.328975 & 0.618478 & 0.5319 & 0.595272 & 0.297636 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&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]18.3933[/C][C]2.73341[/C][C]6.729[/C][C]1.20815e-10[/C][C]6.04074e-11[/C][/ROW]
[ROW][C]Connected[/C][C]0.0014584[/C][C]0.0394299[/C][C]0.03699[/C][C]0.970526[/C][C]0.485263[/C][/ROW]
[ROW][C]Separate[/C][C]0.0101912[/C][C]0.0393049[/C][C]0.2593[/C][C]0.795633[/C][C]0.397816[/C][/ROW]
[ROW][C]Learning[/C][C]0.0991405[/C][C]0.0689262[/C][C]1.438[/C][C]0.151614[/C][C]0.075807[/C][/ROW]
[ROW][C]Software[/C][C]-0.0212946[/C][C]0.0708961[/C][C]-0.3004[/C][C]0.764156[/C][C]0.382078[/C][/ROW]
[ROW][C]Depression[/C][C]-0.369643[/C][C]0.0414528[/C][C]-8.917[/C][C]1.15197e-16[/C][C]5.75983e-17[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0159983[/C][C]0.0418557[/C][C]0.3822[/C][C]0.702627[/C][C]0.351313[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0127107[/C][C]0.0622026[/C][C]0.2043[/C][C]0.838255[/C][C]0.419127[/C][/ROW]
[ROW][C]Month[/C][C]-0.32003[/C][C]0.176714[/C][C]-1.811[/C][C]0.0713706[/C][C]0.0356853[/C][/ROW]
[ROW][C]M1[/C][C]0.0743511[/C][C]0.626069[/C][C]0.1188[/C][C]0.905564[/C][C]0.452782[/C][/ROW]
[ROW][C]M2[/C][C]-0.070315[/C][C]0.624406[/C][C]-0.1126[/C][C]0.910432[/C][C]0.455216[/C][/ROW]
[ROW][C]M3[/C][C]-0.240352[/C][C]0.622767[/C][C]-0.3859[/C][C]0.699876[/C][C]0.349938[/C][/ROW]
[ROW][C]M4[/C][C]-0.0105674[/C][C]0.620183[/C][C]-0.01704[/C][C]0.986419[/C][C]0.49321[/C][/ROW]
[ROW][C]M5[/C][C]0.125367[/C][C]0.626455[/C][C]0.2001[/C][C]0.841552[/C][C]0.420776[/C][/ROW]
[ROW][C]M6[/C][C]0.829632[/C][C]0.629042[/C][C]1.319[/C][C]0.188445[/C][C]0.0942226[/C][/ROW]
[ROW][C]M7[/C][C]0.141309[/C][C]0.622185[/C][C]0.2271[/C][C]0.820523[/C][C]0.410261[/C][/ROW]
[ROW][C]M8[/C][C]0.485995[/C][C]0.618034[/C][C]0.7864[/C][C]0.432422[/C][C]0.216211[/C][/ROW]
[ROW][C]M9[/C][C]0.0202259[/C][C]0.618161[/C][C]0.03272[/C][C]0.973925[/C][C]0.486963[/C][/ROW]
[ROW][C]M10[/C][C]-0.0119043[/C][C]0.62297[/C][C]-0.01911[/C][C]0.98477[/C][C]0.492385[/C][/ROW]
[ROW][C]M11[/C][C]0.328975[/C][C]0.618478[/C][C]0.5319[/C][C]0.595272[/C][C]0.297636[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=2

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


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

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)18.39332.733416.7291.20815e-106.04074e-11
Connected0.00145840.03942990.036990.9705260.485263
Separate0.01019120.03930490.25930.7956330.397816
Learning0.09914050.06892621.4380.1516140.075807
Software-0.02129460.0708961-0.30040.7641560.382078
Depression-0.3696430.0414528-8.9171.15197e-165.75983e-17
Sport10.01599830.04185570.38220.7026270.351313
Sport20.01271070.06220260.20430.8382550.419127
Month-0.320030.176714-1.8110.07137060.0356853
M10.07435110.6260690.11880.9055640.452782
M2-0.0703150.624406-0.11260.9104320.455216
M3-0.2403520.622767-0.38590.6998760.349938
M4-0.01056740.620183-0.017040.9864190.49321
M50.1253670.6264550.20010.8415520.420776
M60.8296320.6290421.3190.1884450.0942226
M70.1413090.6221850.22710.8205230.410261
M80.4859950.6180340.78640.4324220.216211
M90.02022590.6181610.032720.9739250.486963
M10-0.01190430.62297-0.019110.984770.492385
M110.3289750.6184780.53190.5952720.297636






Multiple Linear Regression - Regression Statistics
Multiple R0.619428
R-squared0.383692
Adjusted R-squared0.3357
F-TEST (value)7.99503
F-TEST (DF numerator)19
F-TEST (DF denominator)244
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.03651
Sum Squared Residuals1011.96

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.619428 \tabularnewline
R-squared & 0.383692 \tabularnewline
Adjusted R-squared & 0.3357 \tabularnewline
F-TEST (value) & 7.99503 \tabularnewline
F-TEST (DF numerator) & 19 \tabularnewline
F-TEST (DF denominator) & 244 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.03651 \tabularnewline
Sum Squared Residuals & 1011.96 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.619428[/C][/ROW]
[ROW][C]R-squared[/C][C]0.383692[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.3357[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.99503[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]19[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]244[/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]2.03651[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1011.96[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.619428
R-squared0.383692
Adjusted R-squared0.3357
F-TEST (value)7.99503
F-TEST (DF numerator)19
F-TEST (DF denominator)244
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.03651
Sum Squared Residuals1011.96






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.88670.113345
21815.08772.91226
31113.6521-2.65209
41214.4006-2.40062
51611.21424.78576
61815.17472.82533
71410.84133.15868
81415.4411-1.44108
91515.1343-0.134295
101514.24570.75429
111715.77691.2231
121915.56893.43105
131013.3913-3.39128
141613.34722.65279
151815.43292.56707
161413.32750.672516
171413.8880.111982
181716.54080.459236
191415.4974-1.49736
201614.26661.73336
211815.33362.66635
221113.6651-2.66512
231414.7406-0.740619
241213.5076-1.50764
251715.3711.62905
26915.7877-6.78765
271614.75151.24848
281413.23510.764858
291513.99841.00162
301114.7294-3.72936
311615.82290.177063
321313.1226-0.122551
331715.06421.93584
341515.2226-0.222648
351414.2421-0.242109
361615.47630.523656
37910.8307-1.83067
381514.21070.789331
391715.10831.89168
401315.2044-2.20441
411515.8208-0.820834
421614.44511.55488
431616.0255-0.0254713
441213.6123-1.61233
451514.62070.379305
461113.5377-2.53773
471515.6657-0.665668
481514.8790.120997
491713.55223.44778
501314.6625-1.66245
511615.00940.990559
521413.43520.564814
531111.7801-0.780127
541214.4905-2.4905
551214.2123-2.21231
561514.12330.876686
571614.21781.78217
581515.4996-0.499568
591215.5337-3.53371
601213.4057-1.40566
61810.8189-2.81889
621314.5435-1.54347
631114.4213-3.42133
641413.1090.890982
651513.81261.18739
661015.6959-5.69591
671112.5357-1.5357
681214.8015-2.80148
691513.29741.70257
701513.40261.59736
711413.59110.40889
721612.51793.4821
731514.30140.698598
741514.99820.00178424
751314.5214-1.52141
761211.91820.0817596
771713.91993.08011
781313.1194-0.11936
791513.74831.25174
801315.2954-2.29539
811514.74140.258579
821515.321-0.320988
831614.42251.57748
841514.11450.885544
851414.0286-0.0286072
861513.73841.26164
871413.880.120009
881312.62030.379741
89710.4687-3.46866
901714.382.62004
911312.81760.182399
921514.48980.51022
931413.15410.845864
941313.8191-0.819133
951615.13020.869781
961212.6492-0.649212
971414.7954-0.795392
981714.69372.30625
991514.64530.354659
1001714.98432.01573
1011212.9066-0.906583
1021615.70070.299317
1031114.4428-3.44285
1041513.42361.57645
105911.2168-2.21676
1061614.77021.22975
1071513.07811.92192
1081012.6929-2.6929
109109.044510.955488
1101513.68941.31055
1111112.8208-1.82078
1121315.1389-2.13894
1131411.9592.04098
1141814.77743.22262
1151615.57520.424834
1161413.35430.645747
1171413.71390.286146
1181414.9514-0.951433
1191413.86930.130733
1201212.4115-0.41149
1211413.52270.477311
1221514.6530.347007
1231515.5381-0.538115
1241514.43490.565089
1251314.7619-1.7619
1261716.86160.138431
1271715.29381.70621
1281915.29293.70709
1291513.46181.5382
1301314.541-1.54102
131910.8175-1.81753
1321515.1644-0.16442
1331512.57162.42843
1341514.02920.970819
1351613.38492.61506
136119.326211.67379
1371413.34420.655761
1381112.6952-1.69516
1391514.21740.782584
1401314.1691-1.16908
1411514.60920.390796
1421613.71452.28553
1431414.9022-0.90218
1441514.20540.794553
1451614.51951.48049
1461614.32981.67024
1471113.0429-2.04286
1481214.5942-2.59422
149911.522-2.52204
1501614.91561.08436
1511312.56020.439762
1521615.84070.159339
1531214.3956-2.39563
154911.7479-2.74787
1551311.94961.0504
1561312.67630.323708
1571413.32760.672419
1581914.73664.2634
1591315.3457-2.34566
1601211.96150.0384992
1611312.62760.372421
162109.813830.186169
1631413.0620.937961
1641611.69254.30752
1651011.6592-1.65925
166118.804412.19559
1671414.158-0.157985
1681212.5688-0.568808
169912.4506-3.45056
170911.5852-2.58525
1711110.00490.995086
1721613.89812.10189
173913.8011-4.80111
1741311.84771.15229
1751613.19212.80794
1761315.4955-2.49553
177912.0229-3.02294
1781211.180.819979
1791614.63471.36531
1801112.8462-1.84621
1811413.91470.0853056
1821314.3884-1.38844
1831514.2220.777972
1841414.669-0.669047
1851613.91022.08978
1861312.19880.801223
1871413.41980.580151
1881514.38950.610527
1891312.23110.768919
190119.967791.03221
1911112.6903-1.69031
1921414.7295-0.729451
1931512.54922.45082
1941112.1815-1.18151
1951512.61742.38258
1961213.7786-1.77862
1971411.60922.3908
1981413.97940.0206226
199811.034-3.03399
2001314.0395-1.03948
201911.9526-2.95261
2021513.55341.44659
2031714.1342.86601
2041312.31660.683408
2051514.29110.708948
2061513.42251.57753
2071414.036-0.0359593
2081612.29233.70767
2091312.76890.231115
2101614.90631.09368
211911.5827-2.5827
2121614.75281.24724
2131112.0148-1.01483
2141013.629-3.629
2151112.2368-1.23676
2161513.09931.90074
2171714.7582.24199
2181413.93410.065859
21989.4616-1.4616
2201513.34171.65826
2211113.7838-2.78382
2221614.18611.81387
2231012.0473-2.0473
2241515.1127-0.112677
22599.39207-0.392074
2261614.07611.92391
2271913.96565.03443
2281213.4682-1.46824
22989.32004-1.32004
2301113.068-2.06804
2311413.39570.604291
232911.7931-2.79311
2331514.90870.091326
2341313.0377-0.0377353
2351614.85021.14979
2361113.0964-2.09642
2371211.08910.910852
2381312.6360.363983
2391014.5232-4.52323
2401113.3504-2.35043
2411214.7172-2.71722
242810.4227-2.42268
2431211.34480.655198
2441212.0608-0.0608291
2451513.45291.5471
2461111.3658-0.365774
2471312.70370.296259
248149.108074.89193
2491010.1149-0.114865
2501211.40850.591521
2511513.01391.98615
2521311.65091.34912
2531314.0373-1.03731
2541313.49-0.489984
2551211.36280.637161
2561212.4758-0.475812
257910.7411-1.74108
258912.1383-3.13828
2591512.51772.48231
2601015.0801-5.08008
2611413.56230.437656
2621513.30621.69378
26379.9241-2.9241
2641413.70040.299594

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 13.8867 & 0.113345 \tabularnewline
2 & 18 & 15.0877 & 2.91226 \tabularnewline
3 & 11 & 13.6521 & -2.65209 \tabularnewline
4 & 12 & 14.4006 & -2.40062 \tabularnewline
5 & 16 & 11.2142 & 4.78576 \tabularnewline
6 & 18 & 15.1747 & 2.82533 \tabularnewline
7 & 14 & 10.8413 & 3.15868 \tabularnewline
8 & 14 & 15.4411 & -1.44108 \tabularnewline
9 & 15 & 15.1343 & -0.134295 \tabularnewline
10 & 15 & 14.2457 & 0.75429 \tabularnewline
11 & 17 & 15.7769 & 1.2231 \tabularnewline
12 & 19 & 15.5689 & 3.43105 \tabularnewline
13 & 10 & 13.3913 & -3.39128 \tabularnewline
14 & 16 & 13.3472 & 2.65279 \tabularnewline
15 & 18 & 15.4329 & 2.56707 \tabularnewline
16 & 14 & 13.3275 & 0.672516 \tabularnewline
17 & 14 & 13.888 & 0.111982 \tabularnewline
18 & 17 & 16.5408 & 0.459236 \tabularnewline
19 & 14 & 15.4974 & -1.49736 \tabularnewline
20 & 16 & 14.2666 & 1.73336 \tabularnewline
21 & 18 & 15.3336 & 2.66635 \tabularnewline
22 & 11 & 13.6651 & -2.66512 \tabularnewline
23 & 14 & 14.7406 & -0.740619 \tabularnewline
24 & 12 & 13.5076 & -1.50764 \tabularnewline
25 & 17 & 15.371 & 1.62905 \tabularnewline
26 & 9 & 15.7877 & -6.78765 \tabularnewline
27 & 16 & 14.7515 & 1.24848 \tabularnewline
28 & 14 & 13.2351 & 0.764858 \tabularnewline
29 & 15 & 13.9984 & 1.00162 \tabularnewline
30 & 11 & 14.7294 & -3.72936 \tabularnewline
31 & 16 & 15.8229 & 0.177063 \tabularnewline
32 & 13 & 13.1226 & -0.122551 \tabularnewline
33 & 17 & 15.0642 & 1.93584 \tabularnewline
34 & 15 & 15.2226 & -0.222648 \tabularnewline
35 & 14 & 14.2421 & -0.242109 \tabularnewline
36 & 16 & 15.4763 & 0.523656 \tabularnewline
37 & 9 & 10.8307 & -1.83067 \tabularnewline
38 & 15 & 14.2107 & 0.789331 \tabularnewline
39 & 17 & 15.1083 & 1.89168 \tabularnewline
40 & 13 & 15.2044 & -2.20441 \tabularnewline
41 & 15 & 15.8208 & -0.820834 \tabularnewline
42 & 16 & 14.4451 & 1.55488 \tabularnewline
43 & 16 & 16.0255 & -0.0254713 \tabularnewline
44 & 12 & 13.6123 & -1.61233 \tabularnewline
45 & 15 & 14.6207 & 0.379305 \tabularnewline
46 & 11 & 13.5377 & -2.53773 \tabularnewline
47 & 15 & 15.6657 & -0.665668 \tabularnewline
48 & 15 & 14.879 & 0.120997 \tabularnewline
49 & 17 & 13.5522 & 3.44778 \tabularnewline
50 & 13 & 14.6625 & -1.66245 \tabularnewline
51 & 16 & 15.0094 & 0.990559 \tabularnewline
52 & 14 & 13.4352 & 0.564814 \tabularnewline
53 & 11 & 11.7801 & -0.780127 \tabularnewline
54 & 12 & 14.4905 & -2.4905 \tabularnewline
55 & 12 & 14.2123 & -2.21231 \tabularnewline
56 & 15 & 14.1233 & 0.876686 \tabularnewline
57 & 16 & 14.2178 & 1.78217 \tabularnewline
58 & 15 & 15.4996 & -0.499568 \tabularnewline
59 & 12 & 15.5337 & -3.53371 \tabularnewline
60 & 12 & 13.4057 & -1.40566 \tabularnewline
61 & 8 & 10.8189 & -2.81889 \tabularnewline
62 & 13 & 14.5435 & -1.54347 \tabularnewline
63 & 11 & 14.4213 & -3.42133 \tabularnewline
64 & 14 & 13.109 & 0.890982 \tabularnewline
65 & 15 & 13.8126 & 1.18739 \tabularnewline
66 & 10 & 15.6959 & -5.69591 \tabularnewline
67 & 11 & 12.5357 & -1.5357 \tabularnewline
68 & 12 & 14.8015 & -2.80148 \tabularnewline
69 & 15 & 13.2974 & 1.70257 \tabularnewline
70 & 15 & 13.4026 & 1.59736 \tabularnewline
71 & 14 & 13.5911 & 0.40889 \tabularnewline
72 & 16 & 12.5179 & 3.4821 \tabularnewline
73 & 15 & 14.3014 & 0.698598 \tabularnewline
74 & 15 & 14.9982 & 0.00178424 \tabularnewline
75 & 13 & 14.5214 & -1.52141 \tabularnewline
76 & 12 & 11.9182 & 0.0817596 \tabularnewline
77 & 17 & 13.9199 & 3.08011 \tabularnewline
78 & 13 & 13.1194 & -0.11936 \tabularnewline
79 & 15 & 13.7483 & 1.25174 \tabularnewline
80 & 13 & 15.2954 & -2.29539 \tabularnewline
81 & 15 & 14.7414 & 0.258579 \tabularnewline
82 & 15 & 15.321 & -0.320988 \tabularnewline
83 & 16 & 14.4225 & 1.57748 \tabularnewline
84 & 15 & 14.1145 & 0.885544 \tabularnewline
85 & 14 & 14.0286 & -0.0286072 \tabularnewline
86 & 15 & 13.7384 & 1.26164 \tabularnewline
87 & 14 & 13.88 & 0.120009 \tabularnewline
88 & 13 & 12.6203 & 0.379741 \tabularnewline
89 & 7 & 10.4687 & -3.46866 \tabularnewline
90 & 17 & 14.38 & 2.62004 \tabularnewline
91 & 13 & 12.8176 & 0.182399 \tabularnewline
92 & 15 & 14.4898 & 0.51022 \tabularnewline
93 & 14 & 13.1541 & 0.845864 \tabularnewline
94 & 13 & 13.8191 & -0.819133 \tabularnewline
95 & 16 & 15.1302 & 0.869781 \tabularnewline
96 & 12 & 12.6492 & -0.649212 \tabularnewline
97 & 14 & 14.7954 & -0.795392 \tabularnewline
98 & 17 & 14.6937 & 2.30625 \tabularnewline
99 & 15 & 14.6453 & 0.354659 \tabularnewline
100 & 17 & 14.9843 & 2.01573 \tabularnewline
101 & 12 & 12.9066 & -0.906583 \tabularnewline
102 & 16 & 15.7007 & 0.299317 \tabularnewline
103 & 11 & 14.4428 & -3.44285 \tabularnewline
104 & 15 & 13.4236 & 1.57645 \tabularnewline
105 & 9 & 11.2168 & -2.21676 \tabularnewline
106 & 16 & 14.7702 & 1.22975 \tabularnewline
107 & 15 & 13.0781 & 1.92192 \tabularnewline
108 & 10 & 12.6929 & -2.6929 \tabularnewline
109 & 10 & 9.04451 & 0.955488 \tabularnewline
110 & 15 & 13.6894 & 1.31055 \tabularnewline
111 & 11 & 12.8208 & -1.82078 \tabularnewline
112 & 13 & 15.1389 & -2.13894 \tabularnewline
113 & 14 & 11.959 & 2.04098 \tabularnewline
114 & 18 & 14.7774 & 3.22262 \tabularnewline
115 & 16 & 15.5752 & 0.424834 \tabularnewline
116 & 14 & 13.3543 & 0.645747 \tabularnewline
117 & 14 & 13.7139 & 0.286146 \tabularnewline
118 & 14 & 14.9514 & -0.951433 \tabularnewline
119 & 14 & 13.8693 & 0.130733 \tabularnewline
120 & 12 & 12.4115 & -0.41149 \tabularnewline
121 & 14 & 13.5227 & 0.477311 \tabularnewline
122 & 15 & 14.653 & 0.347007 \tabularnewline
123 & 15 & 15.5381 & -0.538115 \tabularnewline
124 & 15 & 14.4349 & 0.565089 \tabularnewline
125 & 13 & 14.7619 & -1.7619 \tabularnewline
126 & 17 & 16.8616 & 0.138431 \tabularnewline
127 & 17 & 15.2938 & 1.70621 \tabularnewline
128 & 19 & 15.2929 & 3.70709 \tabularnewline
129 & 15 & 13.4618 & 1.5382 \tabularnewline
130 & 13 & 14.541 & -1.54102 \tabularnewline
131 & 9 & 10.8175 & -1.81753 \tabularnewline
132 & 15 & 15.1644 & -0.16442 \tabularnewline
133 & 15 & 12.5716 & 2.42843 \tabularnewline
134 & 15 & 14.0292 & 0.970819 \tabularnewline
135 & 16 & 13.3849 & 2.61506 \tabularnewline
136 & 11 & 9.32621 & 1.67379 \tabularnewline
137 & 14 & 13.3442 & 0.655761 \tabularnewline
138 & 11 & 12.6952 & -1.69516 \tabularnewline
139 & 15 & 14.2174 & 0.782584 \tabularnewline
140 & 13 & 14.1691 & -1.16908 \tabularnewline
141 & 15 & 14.6092 & 0.390796 \tabularnewline
142 & 16 & 13.7145 & 2.28553 \tabularnewline
143 & 14 & 14.9022 & -0.90218 \tabularnewline
144 & 15 & 14.2054 & 0.794553 \tabularnewline
145 & 16 & 14.5195 & 1.48049 \tabularnewline
146 & 16 & 14.3298 & 1.67024 \tabularnewline
147 & 11 & 13.0429 & -2.04286 \tabularnewline
148 & 12 & 14.5942 & -2.59422 \tabularnewline
149 & 9 & 11.522 & -2.52204 \tabularnewline
150 & 16 & 14.9156 & 1.08436 \tabularnewline
151 & 13 & 12.5602 & 0.439762 \tabularnewline
152 & 16 & 15.8407 & 0.159339 \tabularnewline
153 & 12 & 14.3956 & -2.39563 \tabularnewline
154 & 9 & 11.7479 & -2.74787 \tabularnewline
155 & 13 & 11.9496 & 1.0504 \tabularnewline
156 & 13 & 12.6763 & 0.323708 \tabularnewline
157 & 14 & 13.3276 & 0.672419 \tabularnewline
158 & 19 & 14.7366 & 4.2634 \tabularnewline
159 & 13 & 15.3457 & -2.34566 \tabularnewline
160 & 12 & 11.9615 & 0.0384992 \tabularnewline
161 & 13 & 12.6276 & 0.372421 \tabularnewline
162 & 10 & 9.81383 & 0.186169 \tabularnewline
163 & 14 & 13.062 & 0.937961 \tabularnewline
164 & 16 & 11.6925 & 4.30752 \tabularnewline
165 & 10 & 11.6592 & -1.65925 \tabularnewline
166 & 11 & 8.80441 & 2.19559 \tabularnewline
167 & 14 & 14.158 & -0.157985 \tabularnewline
168 & 12 & 12.5688 & -0.568808 \tabularnewline
169 & 9 & 12.4506 & -3.45056 \tabularnewline
170 & 9 & 11.5852 & -2.58525 \tabularnewline
171 & 11 & 10.0049 & 0.995086 \tabularnewline
172 & 16 & 13.8981 & 2.10189 \tabularnewline
173 & 9 & 13.8011 & -4.80111 \tabularnewline
174 & 13 & 11.8477 & 1.15229 \tabularnewline
175 & 16 & 13.1921 & 2.80794 \tabularnewline
176 & 13 & 15.4955 & -2.49553 \tabularnewline
177 & 9 & 12.0229 & -3.02294 \tabularnewline
178 & 12 & 11.18 & 0.819979 \tabularnewline
179 & 16 & 14.6347 & 1.36531 \tabularnewline
180 & 11 & 12.8462 & -1.84621 \tabularnewline
181 & 14 & 13.9147 & 0.0853056 \tabularnewline
182 & 13 & 14.3884 & -1.38844 \tabularnewline
183 & 15 & 14.222 & 0.777972 \tabularnewline
184 & 14 & 14.669 & -0.669047 \tabularnewline
185 & 16 & 13.9102 & 2.08978 \tabularnewline
186 & 13 & 12.1988 & 0.801223 \tabularnewline
187 & 14 & 13.4198 & 0.580151 \tabularnewline
188 & 15 & 14.3895 & 0.610527 \tabularnewline
189 & 13 & 12.2311 & 0.768919 \tabularnewline
190 & 11 & 9.96779 & 1.03221 \tabularnewline
191 & 11 & 12.6903 & -1.69031 \tabularnewline
192 & 14 & 14.7295 & -0.729451 \tabularnewline
193 & 15 & 12.5492 & 2.45082 \tabularnewline
194 & 11 & 12.1815 & -1.18151 \tabularnewline
195 & 15 & 12.6174 & 2.38258 \tabularnewline
196 & 12 & 13.7786 & -1.77862 \tabularnewline
197 & 14 & 11.6092 & 2.3908 \tabularnewline
198 & 14 & 13.9794 & 0.0206226 \tabularnewline
199 & 8 & 11.034 & -3.03399 \tabularnewline
200 & 13 & 14.0395 & -1.03948 \tabularnewline
201 & 9 & 11.9526 & -2.95261 \tabularnewline
202 & 15 & 13.5534 & 1.44659 \tabularnewline
203 & 17 & 14.134 & 2.86601 \tabularnewline
204 & 13 & 12.3166 & 0.683408 \tabularnewline
205 & 15 & 14.2911 & 0.708948 \tabularnewline
206 & 15 & 13.4225 & 1.57753 \tabularnewline
207 & 14 & 14.036 & -0.0359593 \tabularnewline
208 & 16 & 12.2923 & 3.70767 \tabularnewline
209 & 13 & 12.7689 & 0.231115 \tabularnewline
210 & 16 & 14.9063 & 1.09368 \tabularnewline
211 & 9 & 11.5827 & -2.5827 \tabularnewline
212 & 16 & 14.7528 & 1.24724 \tabularnewline
213 & 11 & 12.0148 & -1.01483 \tabularnewline
214 & 10 & 13.629 & -3.629 \tabularnewline
215 & 11 & 12.2368 & -1.23676 \tabularnewline
216 & 15 & 13.0993 & 1.90074 \tabularnewline
217 & 17 & 14.758 & 2.24199 \tabularnewline
218 & 14 & 13.9341 & 0.065859 \tabularnewline
219 & 8 & 9.4616 & -1.4616 \tabularnewline
220 & 15 & 13.3417 & 1.65826 \tabularnewline
221 & 11 & 13.7838 & -2.78382 \tabularnewline
222 & 16 & 14.1861 & 1.81387 \tabularnewline
223 & 10 & 12.0473 & -2.0473 \tabularnewline
224 & 15 & 15.1127 & -0.112677 \tabularnewline
225 & 9 & 9.39207 & -0.392074 \tabularnewline
226 & 16 & 14.0761 & 1.92391 \tabularnewline
227 & 19 & 13.9656 & 5.03443 \tabularnewline
228 & 12 & 13.4682 & -1.46824 \tabularnewline
229 & 8 & 9.32004 & -1.32004 \tabularnewline
230 & 11 & 13.068 & -2.06804 \tabularnewline
231 & 14 & 13.3957 & 0.604291 \tabularnewline
232 & 9 & 11.7931 & -2.79311 \tabularnewline
233 & 15 & 14.9087 & 0.091326 \tabularnewline
234 & 13 & 13.0377 & -0.0377353 \tabularnewline
235 & 16 & 14.8502 & 1.14979 \tabularnewline
236 & 11 & 13.0964 & -2.09642 \tabularnewline
237 & 12 & 11.0891 & 0.910852 \tabularnewline
238 & 13 & 12.636 & 0.363983 \tabularnewline
239 & 10 & 14.5232 & -4.52323 \tabularnewline
240 & 11 & 13.3504 & -2.35043 \tabularnewline
241 & 12 & 14.7172 & -2.71722 \tabularnewline
242 & 8 & 10.4227 & -2.42268 \tabularnewline
243 & 12 & 11.3448 & 0.655198 \tabularnewline
244 & 12 & 12.0608 & -0.0608291 \tabularnewline
245 & 15 & 13.4529 & 1.5471 \tabularnewline
246 & 11 & 11.3658 & -0.365774 \tabularnewline
247 & 13 & 12.7037 & 0.296259 \tabularnewline
248 & 14 & 9.10807 & 4.89193 \tabularnewline
249 & 10 & 10.1149 & -0.114865 \tabularnewline
250 & 12 & 11.4085 & 0.591521 \tabularnewline
251 & 15 & 13.0139 & 1.98615 \tabularnewline
252 & 13 & 11.6509 & 1.34912 \tabularnewline
253 & 13 & 14.0373 & -1.03731 \tabularnewline
254 & 13 & 13.49 & -0.489984 \tabularnewline
255 & 12 & 11.3628 & 0.637161 \tabularnewline
256 & 12 & 12.4758 & -0.475812 \tabularnewline
257 & 9 & 10.7411 & -1.74108 \tabularnewline
258 & 9 & 12.1383 & -3.13828 \tabularnewline
259 & 15 & 12.5177 & 2.48231 \tabularnewline
260 & 10 & 15.0801 & -5.08008 \tabularnewline
261 & 14 & 13.5623 & 0.437656 \tabularnewline
262 & 15 & 13.3062 & 1.69378 \tabularnewline
263 & 7 & 9.9241 & -2.9241 \tabularnewline
264 & 14 & 13.7004 & 0.299594 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&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]14[/C][C]13.8867[/C][C]0.113345[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.0877[/C][C]2.91226[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]13.6521[/C][C]-2.65209[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.4006[/C][C]-2.40062[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.2142[/C][C]4.78576[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]15.1747[/C][C]2.82533[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]10.8413[/C][C]3.15868[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.4411[/C][C]-1.44108[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.1343[/C][C]-0.134295[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.2457[/C][C]0.75429[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.7769[/C][C]1.2231[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.5689[/C][C]3.43105[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.3913[/C][C]-3.39128[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.3472[/C][C]2.65279[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.4329[/C][C]2.56707[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.3275[/C][C]0.672516[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]13.888[/C][C]0.111982[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]16.5408[/C][C]0.459236[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.4974[/C][C]-1.49736[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]14.2666[/C][C]1.73336[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.3336[/C][C]2.66635[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.6651[/C][C]-2.66512[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.7406[/C][C]-0.740619[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.5076[/C][C]-1.50764[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.371[/C][C]1.62905[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.7877[/C][C]-6.78765[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]14.7515[/C][C]1.24848[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.2351[/C][C]0.764858[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.9984[/C][C]1.00162[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.7294[/C][C]-3.72936[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.8229[/C][C]0.177063[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]13.1226[/C][C]-0.122551[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.0642[/C][C]1.93584[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.2226[/C][C]-0.222648[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]14.2421[/C][C]-0.242109[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.4763[/C][C]0.523656[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.8307[/C][C]-1.83067[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.2107[/C][C]0.789331[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.1083[/C][C]1.89168[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.2044[/C][C]-2.20441[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.8208[/C][C]-0.820834[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]14.4451[/C][C]1.55488[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]16.0255[/C][C]-0.0254713[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.6123[/C][C]-1.61233[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.6207[/C][C]0.379305[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.5377[/C][C]-2.53773[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.6657[/C][C]-0.665668[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.879[/C][C]0.120997[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.5522[/C][C]3.44778[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.6625[/C][C]-1.66245[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.0094[/C][C]0.990559[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4352[/C][C]0.564814[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.7801[/C][C]-0.780127[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]14.4905[/C][C]-2.4905[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.2123[/C][C]-2.21231[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]14.1233[/C][C]0.876686[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.2178[/C][C]1.78217[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.4996[/C][C]-0.499568[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.5337[/C][C]-3.53371[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.4057[/C][C]-1.40566[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.8189[/C][C]-2.81889[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.5435[/C][C]-1.54347[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4213[/C][C]-3.42133[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]13.109[/C][C]0.890982[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.8126[/C][C]1.18739[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.6959[/C][C]-5.69591[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.5357[/C][C]-1.5357[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.8015[/C][C]-2.80148[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.2974[/C][C]1.70257[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.4026[/C][C]1.59736[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.5911[/C][C]0.40889[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]12.5179[/C][C]3.4821[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.3014[/C][C]0.698598[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]14.9982[/C][C]0.00178424[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]14.5214[/C][C]-1.52141[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]11.9182[/C][C]0.0817596[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]13.9199[/C][C]3.08011[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]13.1194[/C][C]-0.11936[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]13.7483[/C][C]1.25174[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.2954[/C][C]-2.29539[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]14.7414[/C][C]0.258579[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.321[/C][C]-0.320988[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.4225[/C][C]1.57748[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.1145[/C][C]0.885544[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.0286[/C][C]-0.0286072[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]13.7384[/C][C]1.26164[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]13.88[/C][C]0.120009[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.6203[/C][C]0.379741[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.4687[/C][C]-3.46866[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]14.38[/C][C]2.62004[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.8176[/C][C]0.182399[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.4898[/C][C]0.51022[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.1541[/C][C]0.845864[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]13.8191[/C][C]-0.819133[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.1302[/C][C]0.869781[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.6492[/C][C]-0.649212[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]14.7954[/C][C]-0.795392[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]14.6937[/C][C]2.30625[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]14.6453[/C][C]0.354659[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]14.9843[/C][C]2.01573[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]12.9066[/C][C]-0.906583[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]15.7007[/C][C]0.299317[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.4428[/C][C]-3.44285[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.4236[/C][C]1.57645[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.2168[/C][C]-2.21676[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.7702[/C][C]1.22975[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]13.0781[/C][C]1.92192[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.6929[/C][C]-2.6929[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.04451[/C][C]0.955488[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.6894[/C][C]1.31055[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]12.8208[/C][C]-1.82078[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.1389[/C][C]-2.13894[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.959[/C][C]2.04098[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.7774[/C][C]3.22262[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5752[/C][C]0.424834[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]13.3543[/C][C]0.645747[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.7139[/C][C]0.286146[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]14.9514[/C][C]-0.951433[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.8693[/C][C]0.130733[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.4115[/C][C]-0.41149[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.5227[/C][C]0.477311[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.653[/C][C]0.347007[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.5381[/C][C]-0.538115[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.4349[/C][C]0.565089[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.7619[/C][C]-1.7619[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.8616[/C][C]0.138431[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.2938[/C][C]1.70621[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]15.2929[/C][C]3.70709[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.4618[/C][C]1.5382[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.541[/C][C]-1.54102[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.8175[/C][C]-1.81753[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.1644[/C][C]-0.16442[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.5716[/C][C]2.42843[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.0292[/C][C]0.970819[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.3849[/C][C]2.61506[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.32621[/C][C]1.67379[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.3442[/C][C]0.655761[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]12.6952[/C][C]-1.69516[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.2174[/C][C]0.782584[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]14.1691[/C][C]-1.16908[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.6092[/C][C]0.390796[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7145[/C][C]2.28553[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.9022[/C][C]-0.90218[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.2054[/C][C]0.794553[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5195[/C][C]1.48049[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.3298[/C][C]1.67024[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.0429[/C][C]-2.04286[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.5942[/C][C]-2.59422[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.522[/C][C]-2.52204[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.9156[/C][C]1.08436[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.5602[/C][C]0.439762[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.8407[/C][C]0.159339[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.3956[/C][C]-2.39563[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.7479[/C][C]-2.74787[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.9496[/C][C]1.0504[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.6763[/C][C]0.323708[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.3276[/C][C]0.672419[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.7366[/C][C]4.2634[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.3457[/C][C]-2.34566[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.9615[/C][C]0.0384992[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.6276[/C][C]0.372421[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.81383[/C][C]0.186169[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.062[/C][C]0.937961[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6925[/C][C]4.30752[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]11.6592[/C][C]-1.65925[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]8.80441[/C][C]2.19559[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.158[/C][C]-0.157985[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]12.5688[/C][C]-0.568808[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.4506[/C][C]-3.45056[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.5852[/C][C]-2.58525[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.0049[/C][C]0.995086[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]13.8981[/C][C]2.10189[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]13.8011[/C][C]-4.80111[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.8477[/C][C]1.15229[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.1921[/C][C]2.80794[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.4955[/C][C]-2.49553[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.0229[/C][C]-3.02294[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.18[/C][C]0.819979[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.6347[/C][C]1.36531[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]12.8462[/C][C]-1.84621[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]13.9147[/C][C]0.0853056[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.3884[/C][C]-1.38844[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.222[/C][C]0.777972[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.669[/C][C]-0.669047[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]13.9102[/C][C]2.08978[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]12.1988[/C][C]0.801223[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.4198[/C][C]0.580151[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.3895[/C][C]0.610527[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.2311[/C][C]0.768919[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]9.96779[/C][C]1.03221[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.6903[/C][C]-1.69031[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.7295[/C][C]-0.729451[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.5492[/C][C]2.45082[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.1815[/C][C]-1.18151[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]12.6174[/C][C]2.38258[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]13.7786[/C][C]-1.77862[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.6092[/C][C]2.3908[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.9794[/C][C]0.0206226[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.034[/C][C]-3.03399[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]14.0395[/C][C]-1.03948[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]11.9526[/C][C]-2.95261[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.5534[/C][C]1.44659[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.134[/C][C]2.86601[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.3166[/C][C]0.683408[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.2911[/C][C]0.708948[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.4225[/C][C]1.57753[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.036[/C][C]-0.0359593[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.2923[/C][C]3.70767[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.7689[/C][C]0.231115[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.9063[/C][C]1.09368[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.5827[/C][C]-2.5827[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.7528[/C][C]1.24724[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.0148[/C][C]-1.01483[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.629[/C][C]-3.629[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]12.2368[/C][C]-1.23676[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.0993[/C][C]1.90074[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.758[/C][C]2.24199[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]13.9341[/C][C]0.065859[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.4616[/C][C]-1.4616[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.3417[/C][C]1.65826[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.7838[/C][C]-2.78382[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]14.1861[/C][C]1.81387[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]12.0473[/C][C]-2.0473[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]15.1127[/C][C]-0.112677[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.39207[/C][C]-0.392074[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.0761[/C][C]1.92391[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.9656[/C][C]5.03443[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.4682[/C][C]-1.46824[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.32004[/C][C]-1.32004[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.068[/C][C]-2.06804[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.3957[/C][C]0.604291[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.7931[/C][C]-2.79311[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.9087[/C][C]0.091326[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]13.0377[/C][C]-0.0377353[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.8502[/C][C]1.14979[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]13.0964[/C][C]-2.09642[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.0891[/C][C]0.910852[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.636[/C][C]0.363983[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]14.5232[/C][C]-4.52323[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.3504[/C][C]-2.35043[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.7172[/C][C]-2.71722[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.4227[/C][C]-2.42268[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.3448[/C][C]0.655198[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.0608[/C][C]-0.0608291[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.4529[/C][C]1.5471[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]11.3658[/C][C]-0.365774[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.7037[/C][C]0.296259[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]9.10807[/C][C]4.89193[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]10.1149[/C][C]-0.114865[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.4085[/C][C]0.591521[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]13.0139[/C][C]1.98615[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.6509[/C][C]1.34912[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]14.0373[/C][C]-1.03731[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.49[/C][C]-0.489984[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.3628[/C][C]0.637161[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.4758[/C][C]-0.475812[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.7411[/C][C]-1.74108[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]12.1383[/C][C]-3.13828[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.5177[/C][C]2.48231[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]15.0801[/C][C]-5.08008[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.5623[/C][C]0.437656[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.3062[/C][C]1.69378[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.9241[/C][C]-2.9241[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.7004[/C][C]0.299594[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=4

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


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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11413.88670.113345
21815.08772.91226
31113.6521-2.65209
41214.4006-2.40062
51611.21424.78576
61815.17472.82533
71410.84133.15868
81415.4411-1.44108
91515.1343-0.134295
101514.24570.75429
111715.77691.2231
121915.56893.43105
131013.3913-3.39128
141613.34722.65279
151815.43292.56707
161413.32750.672516
171413.8880.111982
181716.54080.459236
191415.4974-1.49736
201614.26661.73336
211815.33362.66635
221113.6651-2.66512
231414.7406-0.740619
241213.5076-1.50764
251715.3711.62905
26915.7877-6.78765
271614.75151.24848
281413.23510.764858
291513.99841.00162
301114.7294-3.72936
311615.82290.177063
321313.1226-0.122551
331715.06421.93584
341515.2226-0.222648
351414.2421-0.242109
361615.47630.523656
37910.8307-1.83067
381514.21070.789331
391715.10831.89168
401315.2044-2.20441
411515.8208-0.820834
421614.44511.55488
431616.0255-0.0254713
441213.6123-1.61233
451514.62070.379305
461113.5377-2.53773
471515.6657-0.665668
481514.8790.120997
491713.55223.44778
501314.6625-1.66245
511615.00940.990559
521413.43520.564814
531111.7801-0.780127
541214.4905-2.4905
551214.2123-2.21231
561514.12330.876686
571614.21781.78217
581515.4996-0.499568
591215.5337-3.53371
601213.4057-1.40566
61810.8189-2.81889
621314.5435-1.54347
631114.4213-3.42133
641413.1090.890982
651513.81261.18739
661015.6959-5.69591
671112.5357-1.5357
681214.8015-2.80148
691513.29741.70257
701513.40261.59736
711413.59110.40889
721612.51793.4821
731514.30140.698598
741514.99820.00178424
751314.5214-1.52141
761211.91820.0817596
771713.91993.08011
781313.1194-0.11936
791513.74831.25174
801315.2954-2.29539
811514.74140.258579
821515.321-0.320988
831614.42251.57748
841514.11450.885544
851414.0286-0.0286072
861513.73841.26164
871413.880.120009
881312.62030.379741
89710.4687-3.46866
901714.382.62004
911312.81760.182399
921514.48980.51022
931413.15410.845864
941313.8191-0.819133
951615.13020.869781
961212.6492-0.649212
971414.7954-0.795392
981714.69372.30625
991514.64530.354659
1001714.98432.01573
1011212.9066-0.906583
1021615.70070.299317
1031114.4428-3.44285
1041513.42361.57645
105911.2168-2.21676
1061614.77021.22975
1071513.07811.92192
1081012.6929-2.6929
109109.044510.955488
1101513.68941.31055
1111112.8208-1.82078
1121315.1389-2.13894
1131411.9592.04098
1141814.77743.22262
1151615.57520.424834
1161413.35430.645747
1171413.71390.286146
1181414.9514-0.951433
1191413.86930.130733
1201212.4115-0.41149
1211413.52270.477311
1221514.6530.347007
1231515.5381-0.538115
1241514.43490.565089
1251314.7619-1.7619
1261716.86160.138431
1271715.29381.70621
1281915.29293.70709
1291513.46181.5382
1301314.541-1.54102
131910.8175-1.81753
1321515.1644-0.16442
1331512.57162.42843
1341514.02920.970819
1351613.38492.61506
136119.326211.67379
1371413.34420.655761
1381112.6952-1.69516
1391514.21740.782584
1401314.1691-1.16908
1411514.60920.390796
1421613.71452.28553
1431414.9022-0.90218
1441514.20540.794553
1451614.51951.48049
1461614.32981.67024
1471113.0429-2.04286
1481214.5942-2.59422
149911.522-2.52204
1501614.91561.08436
1511312.56020.439762
1521615.84070.159339
1531214.3956-2.39563
154911.7479-2.74787
1551311.94961.0504
1561312.67630.323708
1571413.32760.672419
1581914.73664.2634
1591315.3457-2.34566
1601211.96150.0384992
1611312.62760.372421
162109.813830.186169
1631413.0620.937961
1641611.69254.30752
1651011.6592-1.65925
166118.804412.19559
1671414.158-0.157985
1681212.5688-0.568808
169912.4506-3.45056
170911.5852-2.58525
1711110.00490.995086
1721613.89812.10189
173913.8011-4.80111
1741311.84771.15229
1751613.19212.80794
1761315.4955-2.49553
177912.0229-3.02294
1781211.180.819979
1791614.63471.36531
1801112.8462-1.84621
1811413.91470.0853056
1821314.3884-1.38844
1831514.2220.777972
1841414.669-0.669047
1851613.91022.08978
1861312.19880.801223
1871413.41980.580151
1881514.38950.610527
1891312.23110.768919
190119.967791.03221
1911112.6903-1.69031
1921414.7295-0.729451
1931512.54922.45082
1941112.1815-1.18151
1951512.61742.38258
1961213.7786-1.77862
1971411.60922.3908
1981413.97940.0206226
199811.034-3.03399
2001314.0395-1.03948
201911.9526-2.95261
2021513.55341.44659
2031714.1342.86601
2041312.31660.683408
2051514.29110.708948
2061513.42251.57753
2071414.036-0.0359593
2081612.29233.70767
2091312.76890.231115
2101614.90631.09368
211911.5827-2.5827
2121614.75281.24724
2131112.0148-1.01483
2141013.629-3.629
2151112.2368-1.23676
2161513.09931.90074
2171714.7582.24199
2181413.93410.065859
21989.4616-1.4616
2201513.34171.65826
2211113.7838-2.78382
2221614.18611.81387
2231012.0473-2.0473
2241515.1127-0.112677
22599.39207-0.392074
2261614.07611.92391
2271913.96565.03443
2281213.4682-1.46824
22989.32004-1.32004
2301113.068-2.06804
2311413.39570.604291
232911.7931-2.79311
2331514.90870.091326
2341313.0377-0.0377353
2351614.85021.14979
2361113.0964-2.09642
2371211.08910.910852
2381312.6360.363983
2391014.5232-4.52323
2401113.3504-2.35043
2411214.7172-2.71722
242810.4227-2.42268
2431211.34480.655198
2441212.0608-0.0608291
2451513.45291.5471
2461111.3658-0.365774
2471312.70370.296259
248149.108074.89193
2491010.1149-0.114865
2501211.40850.591521
2511513.01391.98615
2521311.65091.34912
2531314.0373-1.03731
2541313.49-0.489984
2551211.36280.637161
2561212.4758-0.475812
257910.7411-1.74108
258912.1383-3.13828
2591512.51772.48231
2601015.0801-5.08008
2611413.56230.437656
2621513.30621.69378
26379.9241-2.9241
2641413.70040.299594






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.9829850.03402930.0170147
240.9766370.04672560.0233628
250.9566440.08671180.0433559
260.9999715.85258e-052.92629e-05
270.9999330.0001339366.69682e-05
280.9998790.0002419350.000120967
290.9997470.000505740.00025287
300.9998880.0002231120.000111556
310.9998080.0003831260.000191563
320.9996850.0006306010.000315301
330.9994460.001107580.000553792
340.9991810.00163780.000818899
350.9990680.001864020.000932011
360.9984210.003157280.00157864
370.9980010.003997680.00199884
380.9971110.005778720.00288936
390.9967230.006553240.00327662
400.995860.008280580.00414029
410.9940780.01184490.00592247
420.9916880.01662450.00831224
430.9878760.02424710.0121236
440.9862330.02753380.0137669
450.9824380.03512380.0175619
460.9818840.03623290.0181165
470.974950.05010020.0250501
480.9682220.06355630.0317782
490.9755730.04885370.0244268
500.9699850.0600310.0300155
510.9611690.07766120.0388306
520.9513560.09728770.0486438
530.9455070.1089860.0544931
540.93690.12620.0630998
550.9352350.129530.0647649
560.9186810.1626380.0813189
570.9047760.1904480.0952239
580.8907750.218450.109225
590.9205870.1588270.0794134
600.9319510.1360990.0680494
610.9347260.1305480.0652742
620.9279010.1441970.0720985
630.9579010.08419880.0420994
640.949960.1000810.0500405
650.9400760.1198470.0599237
660.9536280.09274330.0463716
670.9537860.09242890.0462145
680.9491570.1016860.050843
690.9573770.08524650.0426232
700.9704950.05901030.0295052
710.9714150.05717010.028585
720.9805180.03896480.0194824
730.9762570.04748520.0237426
740.9697080.0605840.030292
750.9635720.07285510.0364276
760.954250.09149980.0457499
770.9604460.07910890.0395545
780.952980.09404030.0470202
790.9478540.1042920.0521459
800.9461170.1077670.0538834
810.9387250.1225490.0612746
820.9265110.1469770.0734887
830.9223820.1552360.0776179
840.9080980.1838030.0919017
850.8916250.216750.108375
860.8766020.2467970.123398
870.854630.2907390.14537
880.8315340.3369320.168466
890.902780.194440.0972201
900.9165860.1668290.0834145
910.9006150.1987690.0993846
920.8820980.2358040.117902
930.8638880.2722250.136112
940.8437320.3125350.156268
950.821050.35790.17895
960.8017080.3965850.198292
970.7780170.4439660.221983
980.7843380.4313250.215662
990.7547870.4904250.245213
1000.7488570.5022870.251143
1010.7312320.5375370.268768
1020.6987670.6024650.301233
1030.7495370.5009260.250463
1040.7275040.5449920.272496
1050.747080.505840.25292
1060.7311090.5377820.268891
1070.7183410.5633190.281659
1080.7491130.5017740.250887
1090.7208430.5583140.279157
1100.6981550.603690.301845
1110.6880650.623870.311935
1120.7165980.5668030.283402
1130.7090820.5818360.290918
1140.7567750.4864490.243225
1150.7284250.543150.271575
1160.697220.6055590.30278
1170.6704350.659130.329565
1180.6428060.7143870.357194
1190.6071250.7857490.392875
1200.5739450.8521090.426055
1210.5487620.9024770.451238
1220.5155810.9688370.484419
1230.4802260.9604520.519774
1240.4481170.8962350.551883
1250.438810.8776210.56119
1260.4023410.8046820.597659
1270.3795260.7590530.620474
1280.4552820.9105630.544718
1290.4421940.8843870.557806
1300.4286020.8572030.571398
1310.4140320.8280650.585968
1320.382850.76570.61715
1330.4020330.8040670.597967
1340.3765330.7530660.623467
1350.4053890.8107790.594611
1360.3985270.7970540.601473
1370.3668280.7336560.633172
1380.3557460.7114920.644254
1390.3235760.6471520.676424
1400.3032790.6065570.696721
1410.2746470.5492930.725353
1420.2793660.5587320.720634
1430.2525840.5051680.747416
1440.2295590.4591190.770441
1450.2181540.4363080.781846
1460.2161730.4323450.783827
1470.2132080.4264160.786792
1480.2313010.4626020.768699
1490.2472810.4945620.752719
1500.2270880.4541750.772912
1510.2033380.4066770.796662
1520.1778630.3557260.822137
1530.1898520.3797050.810148
1540.2236660.4473330.776334
1550.1997950.3995890.800205
1560.1766310.3532620.823369
1570.1529250.305850.847075
1580.2441370.4882740.755863
1590.2589460.5178920.741054
1600.2300670.4601340.769933
1610.2015440.4030880.798456
1620.176610.353220.82339
1630.1558680.3117350.844132
1640.2445170.4890330.755483
1650.2368120.4736240.763188
1660.2325770.4651530.767423
1670.2040720.4081440.795928
1680.1810290.3620580.818971
1690.2267680.4535370.773232
1700.230640.461280.76936
1710.2046750.4093510.795325
1720.2010360.4020720.798964
1730.3432330.6864660.656767
1740.312630.625260.68737
1750.3366680.6733360.663332
1760.3470320.6940640.652968
1770.3775530.7551050.622447
1780.3440690.6881390.655931
1790.3197060.6394120.680294
1800.3057930.6115860.694207
1810.2735150.5470310.726485
1820.2487490.4974980.751251
1830.2190080.4380150.780992
1840.1919820.3839650.808018
1850.2022780.4045570.797722
1860.1824890.3649780.817511
1870.1592570.3185140.840743
1880.1386630.2773260.861337
1890.1186280.2372570.881372
1900.1015620.2031230.898438
1910.105030.210060.89497
1920.09069670.1813930.909303
1930.1013650.202730.898635
1940.08679820.1735960.913202
1950.08491440.1698290.915086
1960.08675490.173510.913245
1970.1169870.2339740.883013
1980.09787770.1957550.902122
1990.1055960.2111930.894404
2000.08769490.175390.912305
2010.1043370.2086740.895663
2020.09349780.1869960.906502
2030.1254040.2508070.874596
2040.1063160.2126320.893684
2050.08690320.1738060.913097
2060.08986890.1797380.910131
2070.07260420.1452080.927396
2080.08420290.1684060.915797
2090.06823120.1364620.931769
2100.06659680.1331940.933403
2110.07754060.1550810.922459
2120.06363630.1272730.936364
2130.05038010.100760.94962
2140.09358380.1871680.906416
2150.07907940.1581590.920921
2160.07457780.1491560.925422
2170.08328730.1665750.916713
2180.07808130.1561630.921919
2190.07497880.1499580.925021
2200.07914670.1582930.920853
2210.07221890.1444380.927781
2220.07991780.1598360.920082
2230.08614090.1722820.913859
2240.06562890.1312580.934371
2250.04948930.09897850.950511
2260.04574760.09149520.954252
2270.2294710.4589420.770529
2280.1953450.390690.804655
2290.1602960.3205920.839704
2300.124290.248580.87571
2310.08993040.1798610.91007
2320.08350880.1670180.916491
2330.05669840.1133970.943302
2340.05099560.1019910.949004
2350.03754420.07508840.962456
2360.02420030.04840060.9758
2370.01961440.03922880.980386
2380.01106480.02212960.988935
2390.01864820.03729650.981352
2400.01124490.02248970.988755
2410.005136780.01027360.994863

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
23 & 0.982985 & 0.0340293 & 0.0170147 \tabularnewline
24 & 0.976637 & 0.0467256 & 0.0233628 \tabularnewline
25 & 0.956644 & 0.0867118 & 0.0433559 \tabularnewline
26 & 0.999971 & 5.85258e-05 & 2.92629e-05 \tabularnewline
27 & 0.999933 & 0.000133936 & 6.69682e-05 \tabularnewline
28 & 0.999879 & 0.000241935 & 0.000120967 \tabularnewline
29 & 0.999747 & 0.00050574 & 0.00025287 \tabularnewline
30 & 0.999888 & 0.000223112 & 0.000111556 \tabularnewline
31 & 0.999808 & 0.000383126 & 0.000191563 \tabularnewline
32 & 0.999685 & 0.000630601 & 0.000315301 \tabularnewline
33 & 0.999446 & 0.00110758 & 0.000553792 \tabularnewline
34 & 0.999181 & 0.0016378 & 0.000818899 \tabularnewline
35 & 0.999068 & 0.00186402 & 0.000932011 \tabularnewline
36 & 0.998421 & 0.00315728 & 0.00157864 \tabularnewline
37 & 0.998001 & 0.00399768 & 0.00199884 \tabularnewline
38 & 0.997111 & 0.00577872 & 0.00288936 \tabularnewline
39 & 0.996723 & 0.00655324 & 0.00327662 \tabularnewline
40 & 0.99586 & 0.00828058 & 0.00414029 \tabularnewline
41 & 0.994078 & 0.0118449 & 0.00592247 \tabularnewline
42 & 0.991688 & 0.0166245 & 0.00831224 \tabularnewline
43 & 0.987876 & 0.0242471 & 0.0121236 \tabularnewline
44 & 0.986233 & 0.0275338 & 0.0137669 \tabularnewline
45 & 0.982438 & 0.0351238 & 0.0175619 \tabularnewline
46 & 0.981884 & 0.0362329 & 0.0181165 \tabularnewline
47 & 0.97495 & 0.0501002 & 0.0250501 \tabularnewline
48 & 0.968222 & 0.0635563 & 0.0317782 \tabularnewline
49 & 0.975573 & 0.0488537 & 0.0244268 \tabularnewline
50 & 0.969985 & 0.060031 & 0.0300155 \tabularnewline
51 & 0.961169 & 0.0776612 & 0.0388306 \tabularnewline
52 & 0.951356 & 0.0972877 & 0.0486438 \tabularnewline
53 & 0.945507 & 0.108986 & 0.0544931 \tabularnewline
54 & 0.9369 & 0.1262 & 0.0630998 \tabularnewline
55 & 0.935235 & 0.12953 & 0.0647649 \tabularnewline
56 & 0.918681 & 0.162638 & 0.0813189 \tabularnewline
57 & 0.904776 & 0.190448 & 0.0952239 \tabularnewline
58 & 0.890775 & 0.21845 & 0.109225 \tabularnewline
59 & 0.920587 & 0.158827 & 0.0794134 \tabularnewline
60 & 0.931951 & 0.136099 & 0.0680494 \tabularnewline
61 & 0.934726 & 0.130548 & 0.0652742 \tabularnewline
62 & 0.927901 & 0.144197 & 0.0720985 \tabularnewline
63 & 0.957901 & 0.0841988 & 0.0420994 \tabularnewline
64 & 0.94996 & 0.100081 & 0.0500405 \tabularnewline
65 & 0.940076 & 0.119847 & 0.0599237 \tabularnewline
66 & 0.953628 & 0.0927433 & 0.0463716 \tabularnewline
67 & 0.953786 & 0.0924289 & 0.0462145 \tabularnewline
68 & 0.949157 & 0.101686 & 0.050843 \tabularnewline
69 & 0.957377 & 0.0852465 & 0.0426232 \tabularnewline
70 & 0.970495 & 0.0590103 & 0.0295052 \tabularnewline
71 & 0.971415 & 0.0571701 & 0.028585 \tabularnewline
72 & 0.980518 & 0.0389648 & 0.0194824 \tabularnewline
73 & 0.976257 & 0.0474852 & 0.0237426 \tabularnewline
74 & 0.969708 & 0.060584 & 0.030292 \tabularnewline
75 & 0.963572 & 0.0728551 & 0.0364276 \tabularnewline
76 & 0.95425 & 0.0914998 & 0.0457499 \tabularnewline
77 & 0.960446 & 0.0791089 & 0.0395545 \tabularnewline
78 & 0.95298 & 0.0940403 & 0.0470202 \tabularnewline
79 & 0.947854 & 0.104292 & 0.0521459 \tabularnewline
80 & 0.946117 & 0.107767 & 0.0538834 \tabularnewline
81 & 0.938725 & 0.122549 & 0.0612746 \tabularnewline
82 & 0.926511 & 0.146977 & 0.0734887 \tabularnewline
83 & 0.922382 & 0.155236 & 0.0776179 \tabularnewline
84 & 0.908098 & 0.183803 & 0.0919017 \tabularnewline
85 & 0.891625 & 0.21675 & 0.108375 \tabularnewline
86 & 0.876602 & 0.246797 & 0.123398 \tabularnewline
87 & 0.85463 & 0.290739 & 0.14537 \tabularnewline
88 & 0.831534 & 0.336932 & 0.168466 \tabularnewline
89 & 0.90278 & 0.19444 & 0.0972201 \tabularnewline
90 & 0.916586 & 0.166829 & 0.0834145 \tabularnewline
91 & 0.900615 & 0.198769 & 0.0993846 \tabularnewline
92 & 0.882098 & 0.235804 & 0.117902 \tabularnewline
93 & 0.863888 & 0.272225 & 0.136112 \tabularnewline
94 & 0.843732 & 0.312535 & 0.156268 \tabularnewline
95 & 0.82105 & 0.3579 & 0.17895 \tabularnewline
96 & 0.801708 & 0.396585 & 0.198292 \tabularnewline
97 & 0.778017 & 0.443966 & 0.221983 \tabularnewline
98 & 0.784338 & 0.431325 & 0.215662 \tabularnewline
99 & 0.754787 & 0.490425 & 0.245213 \tabularnewline
100 & 0.748857 & 0.502287 & 0.251143 \tabularnewline
101 & 0.731232 & 0.537537 & 0.268768 \tabularnewline
102 & 0.698767 & 0.602465 & 0.301233 \tabularnewline
103 & 0.749537 & 0.500926 & 0.250463 \tabularnewline
104 & 0.727504 & 0.544992 & 0.272496 \tabularnewline
105 & 0.74708 & 0.50584 & 0.25292 \tabularnewline
106 & 0.731109 & 0.537782 & 0.268891 \tabularnewline
107 & 0.718341 & 0.563319 & 0.281659 \tabularnewline
108 & 0.749113 & 0.501774 & 0.250887 \tabularnewline
109 & 0.720843 & 0.558314 & 0.279157 \tabularnewline
110 & 0.698155 & 0.60369 & 0.301845 \tabularnewline
111 & 0.688065 & 0.62387 & 0.311935 \tabularnewline
112 & 0.716598 & 0.566803 & 0.283402 \tabularnewline
113 & 0.709082 & 0.581836 & 0.290918 \tabularnewline
114 & 0.756775 & 0.486449 & 0.243225 \tabularnewline
115 & 0.728425 & 0.54315 & 0.271575 \tabularnewline
116 & 0.69722 & 0.605559 & 0.30278 \tabularnewline
117 & 0.670435 & 0.65913 & 0.329565 \tabularnewline
118 & 0.642806 & 0.714387 & 0.357194 \tabularnewline
119 & 0.607125 & 0.785749 & 0.392875 \tabularnewline
120 & 0.573945 & 0.852109 & 0.426055 \tabularnewline
121 & 0.548762 & 0.902477 & 0.451238 \tabularnewline
122 & 0.515581 & 0.968837 & 0.484419 \tabularnewline
123 & 0.480226 & 0.960452 & 0.519774 \tabularnewline
124 & 0.448117 & 0.896235 & 0.551883 \tabularnewline
125 & 0.43881 & 0.877621 & 0.56119 \tabularnewline
126 & 0.402341 & 0.804682 & 0.597659 \tabularnewline
127 & 0.379526 & 0.759053 & 0.620474 \tabularnewline
128 & 0.455282 & 0.910563 & 0.544718 \tabularnewline
129 & 0.442194 & 0.884387 & 0.557806 \tabularnewline
130 & 0.428602 & 0.857203 & 0.571398 \tabularnewline
131 & 0.414032 & 0.828065 & 0.585968 \tabularnewline
132 & 0.38285 & 0.7657 & 0.61715 \tabularnewline
133 & 0.402033 & 0.804067 & 0.597967 \tabularnewline
134 & 0.376533 & 0.753066 & 0.623467 \tabularnewline
135 & 0.405389 & 0.810779 & 0.594611 \tabularnewline
136 & 0.398527 & 0.797054 & 0.601473 \tabularnewline
137 & 0.366828 & 0.733656 & 0.633172 \tabularnewline
138 & 0.355746 & 0.711492 & 0.644254 \tabularnewline
139 & 0.323576 & 0.647152 & 0.676424 \tabularnewline
140 & 0.303279 & 0.606557 & 0.696721 \tabularnewline
141 & 0.274647 & 0.549293 & 0.725353 \tabularnewline
142 & 0.279366 & 0.558732 & 0.720634 \tabularnewline
143 & 0.252584 & 0.505168 & 0.747416 \tabularnewline
144 & 0.229559 & 0.459119 & 0.770441 \tabularnewline
145 & 0.218154 & 0.436308 & 0.781846 \tabularnewline
146 & 0.216173 & 0.432345 & 0.783827 \tabularnewline
147 & 0.213208 & 0.426416 & 0.786792 \tabularnewline
148 & 0.231301 & 0.462602 & 0.768699 \tabularnewline
149 & 0.247281 & 0.494562 & 0.752719 \tabularnewline
150 & 0.227088 & 0.454175 & 0.772912 \tabularnewline
151 & 0.203338 & 0.406677 & 0.796662 \tabularnewline
152 & 0.177863 & 0.355726 & 0.822137 \tabularnewline
153 & 0.189852 & 0.379705 & 0.810148 \tabularnewline
154 & 0.223666 & 0.447333 & 0.776334 \tabularnewline
155 & 0.199795 & 0.399589 & 0.800205 \tabularnewline
156 & 0.176631 & 0.353262 & 0.823369 \tabularnewline
157 & 0.152925 & 0.30585 & 0.847075 \tabularnewline
158 & 0.244137 & 0.488274 & 0.755863 \tabularnewline
159 & 0.258946 & 0.517892 & 0.741054 \tabularnewline
160 & 0.230067 & 0.460134 & 0.769933 \tabularnewline
161 & 0.201544 & 0.403088 & 0.798456 \tabularnewline
162 & 0.17661 & 0.35322 & 0.82339 \tabularnewline
163 & 0.155868 & 0.311735 & 0.844132 \tabularnewline
164 & 0.244517 & 0.489033 & 0.755483 \tabularnewline
165 & 0.236812 & 0.473624 & 0.763188 \tabularnewline
166 & 0.232577 & 0.465153 & 0.767423 \tabularnewline
167 & 0.204072 & 0.408144 & 0.795928 \tabularnewline
168 & 0.181029 & 0.362058 & 0.818971 \tabularnewline
169 & 0.226768 & 0.453537 & 0.773232 \tabularnewline
170 & 0.23064 & 0.46128 & 0.76936 \tabularnewline
171 & 0.204675 & 0.409351 & 0.795325 \tabularnewline
172 & 0.201036 & 0.402072 & 0.798964 \tabularnewline
173 & 0.343233 & 0.686466 & 0.656767 \tabularnewline
174 & 0.31263 & 0.62526 & 0.68737 \tabularnewline
175 & 0.336668 & 0.673336 & 0.663332 \tabularnewline
176 & 0.347032 & 0.694064 & 0.652968 \tabularnewline
177 & 0.377553 & 0.755105 & 0.622447 \tabularnewline
178 & 0.344069 & 0.688139 & 0.655931 \tabularnewline
179 & 0.319706 & 0.639412 & 0.680294 \tabularnewline
180 & 0.305793 & 0.611586 & 0.694207 \tabularnewline
181 & 0.273515 & 0.547031 & 0.726485 \tabularnewline
182 & 0.248749 & 0.497498 & 0.751251 \tabularnewline
183 & 0.219008 & 0.438015 & 0.780992 \tabularnewline
184 & 0.191982 & 0.383965 & 0.808018 \tabularnewline
185 & 0.202278 & 0.404557 & 0.797722 \tabularnewline
186 & 0.182489 & 0.364978 & 0.817511 \tabularnewline
187 & 0.159257 & 0.318514 & 0.840743 \tabularnewline
188 & 0.138663 & 0.277326 & 0.861337 \tabularnewline
189 & 0.118628 & 0.237257 & 0.881372 \tabularnewline
190 & 0.101562 & 0.203123 & 0.898438 \tabularnewline
191 & 0.10503 & 0.21006 & 0.89497 \tabularnewline
192 & 0.0906967 & 0.181393 & 0.909303 \tabularnewline
193 & 0.101365 & 0.20273 & 0.898635 \tabularnewline
194 & 0.0867982 & 0.173596 & 0.913202 \tabularnewline
195 & 0.0849144 & 0.169829 & 0.915086 \tabularnewline
196 & 0.0867549 & 0.17351 & 0.913245 \tabularnewline
197 & 0.116987 & 0.233974 & 0.883013 \tabularnewline
198 & 0.0978777 & 0.195755 & 0.902122 \tabularnewline
199 & 0.105596 & 0.211193 & 0.894404 \tabularnewline
200 & 0.0876949 & 0.17539 & 0.912305 \tabularnewline
201 & 0.104337 & 0.208674 & 0.895663 \tabularnewline
202 & 0.0934978 & 0.186996 & 0.906502 \tabularnewline
203 & 0.125404 & 0.250807 & 0.874596 \tabularnewline
204 & 0.106316 & 0.212632 & 0.893684 \tabularnewline
205 & 0.0869032 & 0.173806 & 0.913097 \tabularnewline
206 & 0.0898689 & 0.179738 & 0.910131 \tabularnewline
207 & 0.0726042 & 0.145208 & 0.927396 \tabularnewline
208 & 0.0842029 & 0.168406 & 0.915797 \tabularnewline
209 & 0.0682312 & 0.136462 & 0.931769 \tabularnewline
210 & 0.0665968 & 0.133194 & 0.933403 \tabularnewline
211 & 0.0775406 & 0.155081 & 0.922459 \tabularnewline
212 & 0.0636363 & 0.127273 & 0.936364 \tabularnewline
213 & 0.0503801 & 0.10076 & 0.94962 \tabularnewline
214 & 0.0935838 & 0.187168 & 0.906416 \tabularnewline
215 & 0.0790794 & 0.158159 & 0.920921 \tabularnewline
216 & 0.0745778 & 0.149156 & 0.925422 \tabularnewline
217 & 0.0832873 & 0.166575 & 0.916713 \tabularnewline
218 & 0.0780813 & 0.156163 & 0.921919 \tabularnewline
219 & 0.0749788 & 0.149958 & 0.925021 \tabularnewline
220 & 0.0791467 & 0.158293 & 0.920853 \tabularnewline
221 & 0.0722189 & 0.144438 & 0.927781 \tabularnewline
222 & 0.0799178 & 0.159836 & 0.920082 \tabularnewline
223 & 0.0861409 & 0.172282 & 0.913859 \tabularnewline
224 & 0.0656289 & 0.131258 & 0.934371 \tabularnewline
225 & 0.0494893 & 0.0989785 & 0.950511 \tabularnewline
226 & 0.0457476 & 0.0914952 & 0.954252 \tabularnewline
227 & 0.229471 & 0.458942 & 0.770529 \tabularnewline
228 & 0.195345 & 0.39069 & 0.804655 \tabularnewline
229 & 0.160296 & 0.320592 & 0.839704 \tabularnewline
230 & 0.12429 & 0.24858 & 0.87571 \tabularnewline
231 & 0.0899304 & 0.179861 & 0.91007 \tabularnewline
232 & 0.0835088 & 0.167018 & 0.916491 \tabularnewline
233 & 0.0566984 & 0.113397 & 0.943302 \tabularnewline
234 & 0.0509956 & 0.101991 & 0.949004 \tabularnewline
235 & 0.0375442 & 0.0750884 & 0.962456 \tabularnewline
236 & 0.0242003 & 0.0484006 & 0.9758 \tabularnewline
237 & 0.0196144 & 0.0392288 & 0.980386 \tabularnewline
238 & 0.0110648 & 0.0221296 & 0.988935 \tabularnewline
239 & 0.0186482 & 0.0372965 & 0.981352 \tabularnewline
240 & 0.0112449 & 0.0224897 & 0.988755 \tabularnewline
241 & 0.00513678 & 0.0102736 & 0.994863 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&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]23[/C][C]0.982985[/C][C]0.0340293[/C][C]0.0170147[/C][/ROW]
[ROW][C]24[/C][C]0.976637[/C][C]0.0467256[/C][C]0.0233628[/C][/ROW]
[ROW][C]25[/C][C]0.956644[/C][C]0.0867118[/C][C]0.0433559[/C][/ROW]
[ROW][C]26[/C][C]0.999971[/C][C]5.85258e-05[/C][C]2.92629e-05[/C][/ROW]
[ROW][C]27[/C][C]0.999933[/C][C]0.000133936[/C][C]6.69682e-05[/C][/ROW]
[ROW][C]28[/C][C]0.999879[/C][C]0.000241935[/C][C]0.000120967[/C][/ROW]
[ROW][C]29[/C][C]0.999747[/C][C]0.00050574[/C][C]0.00025287[/C][/ROW]
[ROW][C]30[/C][C]0.999888[/C][C]0.000223112[/C][C]0.000111556[/C][/ROW]
[ROW][C]31[/C][C]0.999808[/C][C]0.000383126[/C][C]0.000191563[/C][/ROW]
[ROW][C]32[/C][C]0.999685[/C][C]0.000630601[/C][C]0.000315301[/C][/ROW]
[ROW][C]33[/C][C]0.999446[/C][C]0.00110758[/C][C]0.000553792[/C][/ROW]
[ROW][C]34[/C][C]0.999181[/C][C]0.0016378[/C][C]0.000818899[/C][/ROW]
[ROW][C]35[/C][C]0.999068[/C][C]0.00186402[/C][C]0.000932011[/C][/ROW]
[ROW][C]36[/C][C]0.998421[/C][C]0.00315728[/C][C]0.00157864[/C][/ROW]
[ROW][C]37[/C][C]0.998001[/C][C]0.00399768[/C][C]0.00199884[/C][/ROW]
[ROW][C]38[/C][C]0.997111[/C][C]0.00577872[/C][C]0.00288936[/C][/ROW]
[ROW][C]39[/C][C]0.996723[/C][C]0.00655324[/C][C]0.00327662[/C][/ROW]
[ROW][C]40[/C][C]0.99586[/C][C]0.00828058[/C][C]0.00414029[/C][/ROW]
[ROW][C]41[/C][C]0.994078[/C][C]0.0118449[/C][C]0.00592247[/C][/ROW]
[ROW][C]42[/C][C]0.991688[/C][C]0.0166245[/C][C]0.00831224[/C][/ROW]
[ROW][C]43[/C][C]0.987876[/C][C]0.0242471[/C][C]0.0121236[/C][/ROW]
[ROW][C]44[/C][C]0.986233[/C][C]0.0275338[/C][C]0.0137669[/C][/ROW]
[ROW][C]45[/C][C]0.982438[/C][C]0.0351238[/C][C]0.0175619[/C][/ROW]
[ROW][C]46[/C][C]0.981884[/C][C]0.0362329[/C][C]0.0181165[/C][/ROW]
[ROW][C]47[/C][C]0.97495[/C][C]0.0501002[/C][C]0.0250501[/C][/ROW]
[ROW][C]48[/C][C]0.968222[/C][C]0.0635563[/C][C]0.0317782[/C][/ROW]
[ROW][C]49[/C][C]0.975573[/C][C]0.0488537[/C][C]0.0244268[/C][/ROW]
[ROW][C]50[/C][C]0.969985[/C][C]0.060031[/C][C]0.0300155[/C][/ROW]
[ROW][C]51[/C][C]0.961169[/C][C]0.0776612[/C][C]0.0388306[/C][/ROW]
[ROW][C]52[/C][C]0.951356[/C][C]0.0972877[/C][C]0.0486438[/C][/ROW]
[ROW][C]53[/C][C]0.945507[/C][C]0.108986[/C][C]0.0544931[/C][/ROW]
[ROW][C]54[/C][C]0.9369[/C][C]0.1262[/C][C]0.0630998[/C][/ROW]
[ROW][C]55[/C][C]0.935235[/C][C]0.12953[/C][C]0.0647649[/C][/ROW]
[ROW][C]56[/C][C]0.918681[/C][C]0.162638[/C][C]0.0813189[/C][/ROW]
[ROW][C]57[/C][C]0.904776[/C][C]0.190448[/C][C]0.0952239[/C][/ROW]
[ROW][C]58[/C][C]0.890775[/C][C]0.21845[/C][C]0.109225[/C][/ROW]
[ROW][C]59[/C][C]0.920587[/C][C]0.158827[/C][C]0.0794134[/C][/ROW]
[ROW][C]60[/C][C]0.931951[/C][C]0.136099[/C][C]0.0680494[/C][/ROW]
[ROW][C]61[/C][C]0.934726[/C][C]0.130548[/C][C]0.0652742[/C][/ROW]
[ROW][C]62[/C][C]0.927901[/C][C]0.144197[/C][C]0.0720985[/C][/ROW]
[ROW][C]63[/C][C]0.957901[/C][C]0.0841988[/C][C]0.0420994[/C][/ROW]
[ROW][C]64[/C][C]0.94996[/C][C]0.100081[/C][C]0.0500405[/C][/ROW]
[ROW][C]65[/C][C]0.940076[/C][C]0.119847[/C][C]0.0599237[/C][/ROW]
[ROW][C]66[/C][C]0.953628[/C][C]0.0927433[/C][C]0.0463716[/C][/ROW]
[ROW][C]67[/C][C]0.953786[/C][C]0.0924289[/C][C]0.0462145[/C][/ROW]
[ROW][C]68[/C][C]0.949157[/C][C]0.101686[/C][C]0.050843[/C][/ROW]
[ROW][C]69[/C][C]0.957377[/C][C]0.0852465[/C][C]0.0426232[/C][/ROW]
[ROW][C]70[/C][C]0.970495[/C][C]0.0590103[/C][C]0.0295052[/C][/ROW]
[ROW][C]71[/C][C]0.971415[/C][C]0.0571701[/C][C]0.028585[/C][/ROW]
[ROW][C]72[/C][C]0.980518[/C][C]0.0389648[/C][C]0.0194824[/C][/ROW]
[ROW][C]73[/C][C]0.976257[/C][C]0.0474852[/C][C]0.0237426[/C][/ROW]
[ROW][C]74[/C][C]0.969708[/C][C]0.060584[/C][C]0.030292[/C][/ROW]
[ROW][C]75[/C][C]0.963572[/C][C]0.0728551[/C][C]0.0364276[/C][/ROW]
[ROW][C]76[/C][C]0.95425[/C][C]0.0914998[/C][C]0.0457499[/C][/ROW]
[ROW][C]77[/C][C]0.960446[/C][C]0.0791089[/C][C]0.0395545[/C][/ROW]
[ROW][C]78[/C][C]0.95298[/C][C]0.0940403[/C][C]0.0470202[/C][/ROW]
[ROW][C]79[/C][C]0.947854[/C][C]0.104292[/C][C]0.0521459[/C][/ROW]
[ROW][C]80[/C][C]0.946117[/C][C]0.107767[/C][C]0.0538834[/C][/ROW]
[ROW][C]81[/C][C]0.938725[/C][C]0.122549[/C][C]0.0612746[/C][/ROW]
[ROW][C]82[/C][C]0.926511[/C][C]0.146977[/C][C]0.0734887[/C][/ROW]
[ROW][C]83[/C][C]0.922382[/C][C]0.155236[/C][C]0.0776179[/C][/ROW]
[ROW][C]84[/C][C]0.908098[/C][C]0.183803[/C][C]0.0919017[/C][/ROW]
[ROW][C]85[/C][C]0.891625[/C][C]0.21675[/C][C]0.108375[/C][/ROW]
[ROW][C]86[/C][C]0.876602[/C][C]0.246797[/C][C]0.123398[/C][/ROW]
[ROW][C]87[/C][C]0.85463[/C][C]0.290739[/C][C]0.14537[/C][/ROW]
[ROW][C]88[/C][C]0.831534[/C][C]0.336932[/C][C]0.168466[/C][/ROW]
[ROW][C]89[/C][C]0.90278[/C][C]0.19444[/C][C]0.0972201[/C][/ROW]
[ROW][C]90[/C][C]0.916586[/C][C]0.166829[/C][C]0.0834145[/C][/ROW]
[ROW][C]91[/C][C]0.900615[/C][C]0.198769[/C][C]0.0993846[/C][/ROW]
[ROW][C]92[/C][C]0.882098[/C][C]0.235804[/C][C]0.117902[/C][/ROW]
[ROW][C]93[/C][C]0.863888[/C][C]0.272225[/C][C]0.136112[/C][/ROW]
[ROW][C]94[/C][C]0.843732[/C][C]0.312535[/C][C]0.156268[/C][/ROW]
[ROW][C]95[/C][C]0.82105[/C][C]0.3579[/C][C]0.17895[/C][/ROW]
[ROW][C]96[/C][C]0.801708[/C][C]0.396585[/C][C]0.198292[/C][/ROW]
[ROW][C]97[/C][C]0.778017[/C][C]0.443966[/C][C]0.221983[/C][/ROW]
[ROW][C]98[/C][C]0.784338[/C][C]0.431325[/C][C]0.215662[/C][/ROW]
[ROW][C]99[/C][C]0.754787[/C][C]0.490425[/C][C]0.245213[/C][/ROW]
[ROW][C]100[/C][C]0.748857[/C][C]0.502287[/C][C]0.251143[/C][/ROW]
[ROW][C]101[/C][C]0.731232[/C][C]0.537537[/C][C]0.268768[/C][/ROW]
[ROW][C]102[/C][C]0.698767[/C][C]0.602465[/C][C]0.301233[/C][/ROW]
[ROW][C]103[/C][C]0.749537[/C][C]0.500926[/C][C]0.250463[/C][/ROW]
[ROW][C]104[/C][C]0.727504[/C][C]0.544992[/C][C]0.272496[/C][/ROW]
[ROW][C]105[/C][C]0.74708[/C][C]0.50584[/C][C]0.25292[/C][/ROW]
[ROW][C]106[/C][C]0.731109[/C][C]0.537782[/C][C]0.268891[/C][/ROW]
[ROW][C]107[/C][C]0.718341[/C][C]0.563319[/C][C]0.281659[/C][/ROW]
[ROW][C]108[/C][C]0.749113[/C][C]0.501774[/C][C]0.250887[/C][/ROW]
[ROW][C]109[/C][C]0.720843[/C][C]0.558314[/C][C]0.279157[/C][/ROW]
[ROW][C]110[/C][C]0.698155[/C][C]0.60369[/C][C]0.301845[/C][/ROW]
[ROW][C]111[/C][C]0.688065[/C][C]0.62387[/C][C]0.311935[/C][/ROW]
[ROW][C]112[/C][C]0.716598[/C][C]0.566803[/C][C]0.283402[/C][/ROW]
[ROW][C]113[/C][C]0.709082[/C][C]0.581836[/C][C]0.290918[/C][/ROW]
[ROW][C]114[/C][C]0.756775[/C][C]0.486449[/C][C]0.243225[/C][/ROW]
[ROW][C]115[/C][C]0.728425[/C][C]0.54315[/C][C]0.271575[/C][/ROW]
[ROW][C]116[/C][C]0.69722[/C][C]0.605559[/C][C]0.30278[/C][/ROW]
[ROW][C]117[/C][C]0.670435[/C][C]0.65913[/C][C]0.329565[/C][/ROW]
[ROW][C]118[/C][C]0.642806[/C][C]0.714387[/C][C]0.357194[/C][/ROW]
[ROW][C]119[/C][C]0.607125[/C][C]0.785749[/C][C]0.392875[/C][/ROW]
[ROW][C]120[/C][C]0.573945[/C][C]0.852109[/C][C]0.426055[/C][/ROW]
[ROW][C]121[/C][C]0.548762[/C][C]0.902477[/C][C]0.451238[/C][/ROW]
[ROW][C]122[/C][C]0.515581[/C][C]0.968837[/C][C]0.484419[/C][/ROW]
[ROW][C]123[/C][C]0.480226[/C][C]0.960452[/C][C]0.519774[/C][/ROW]
[ROW][C]124[/C][C]0.448117[/C][C]0.896235[/C][C]0.551883[/C][/ROW]
[ROW][C]125[/C][C]0.43881[/C][C]0.877621[/C][C]0.56119[/C][/ROW]
[ROW][C]126[/C][C]0.402341[/C][C]0.804682[/C][C]0.597659[/C][/ROW]
[ROW][C]127[/C][C]0.379526[/C][C]0.759053[/C][C]0.620474[/C][/ROW]
[ROW][C]128[/C][C]0.455282[/C][C]0.910563[/C][C]0.544718[/C][/ROW]
[ROW][C]129[/C][C]0.442194[/C][C]0.884387[/C][C]0.557806[/C][/ROW]
[ROW][C]130[/C][C]0.428602[/C][C]0.857203[/C][C]0.571398[/C][/ROW]
[ROW][C]131[/C][C]0.414032[/C][C]0.828065[/C][C]0.585968[/C][/ROW]
[ROW][C]132[/C][C]0.38285[/C][C]0.7657[/C][C]0.61715[/C][/ROW]
[ROW][C]133[/C][C]0.402033[/C][C]0.804067[/C][C]0.597967[/C][/ROW]
[ROW][C]134[/C][C]0.376533[/C][C]0.753066[/C][C]0.623467[/C][/ROW]
[ROW][C]135[/C][C]0.405389[/C][C]0.810779[/C][C]0.594611[/C][/ROW]
[ROW][C]136[/C][C]0.398527[/C][C]0.797054[/C][C]0.601473[/C][/ROW]
[ROW][C]137[/C][C]0.366828[/C][C]0.733656[/C][C]0.633172[/C][/ROW]
[ROW][C]138[/C][C]0.355746[/C][C]0.711492[/C][C]0.644254[/C][/ROW]
[ROW][C]139[/C][C]0.323576[/C][C]0.647152[/C][C]0.676424[/C][/ROW]
[ROW][C]140[/C][C]0.303279[/C][C]0.606557[/C][C]0.696721[/C][/ROW]
[ROW][C]141[/C][C]0.274647[/C][C]0.549293[/C][C]0.725353[/C][/ROW]
[ROW][C]142[/C][C]0.279366[/C][C]0.558732[/C][C]0.720634[/C][/ROW]
[ROW][C]143[/C][C]0.252584[/C][C]0.505168[/C][C]0.747416[/C][/ROW]
[ROW][C]144[/C][C]0.229559[/C][C]0.459119[/C][C]0.770441[/C][/ROW]
[ROW][C]145[/C][C]0.218154[/C][C]0.436308[/C][C]0.781846[/C][/ROW]
[ROW][C]146[/C][C]0.216173[/C][C]0.432345[/C][C]0.783827[/C][/ROW]
[ROW][C]147[/C][C]0.213208[/C][C]0.426416[/C][C]0.786792[/C][/ROW]
[ROW][C]148[/C][C]0.231301[/C][C]0.462602[/C][C]0.768699[/C][/ROW]
[ROW][C]149[/C][C]0.247281[/C][C]0.494562[/C][C]0.752719[/C][/ROW]
[ROW][C]150[/C][C]0.227088[/C][C]0.454175[/C][C]0.772912[/C][/ROW]
[ROW][C]151[/C][C]0.203338[/C][C]0.406677[/C][C]0.796662[/C][/ROW]
[ROW][C]152[/C][C]0.177863[/C][C]0.355726[/C][C]0.822137[/C][/ROW]
[ROW][C]153[/C][C]0.189852[/C][C]0.379705[/C][C]0.810148[/C][/ROW]
[ROW][C]154[/C][C]0.223666[/C][C]0.447333[/C][C]0.776334[/C][/ROW]
[ROW][C]155[/C][C]0.199795[/C][C]0.399589[/C][C]0.800205[/C][/ROW]
[ROW][C]156[/C][C]0.176631[/C][C]0.353262[/C][C]0.823369[/C][/ROW]
[ROW][C]157[/C][C]0.152925[/C][C]0.30585[/C][C]0.847075[/C][/ROW]
[ROW][C]158[/C][C]0.244137[/C][C]0.488274[/C][C]0.755863[/C][/ROW]
[ROW][C]159[/C][C]0.258946[/C][C]0.517892[/C][C]0.741054[/C][/ROW]
[ROW][C]160[/C][C]0.230067[/C][C]0.460134[/C][C]0.769933[/C][/ROW]
[ROW][C]161[/C][C]0.201544[/C][C]0.403088[/C][C]0.798456[/C][/ROW]
[ROW][C]162[/C][C]0.17661[/C][C]0.35322[/C][C]0.82339[/C][/ROW]
[ROW][C]163[/C][C]0.155868[/C][C]0.311735[/C][C]0.844132[/C][/ROW]
[ROW][C]164[/C][C]0.244517[/C][C]0.489033[/C][C]0.755483[/C][/ROW]
[ROW][C]165[/C][C]0.236812[/C][C]0.473624[/C][C]0.763188[/C][/ROW]
[ROW][C]166[/C][C]0.232577[/C][C]0.465153[/C][C]0.767423[/C][/ROW]
[ROW][C]167[/C][C]0.204072[/C][C]0.408144[/C][C]0.795928[/C][/ROW]
[ROW][C]168[/C][C]0.181029[/C][C]0.362058[/C][C]0.818971[/C][/ROW]
[ROW][C]169[/C][C]0.226768[/C][C]0.453537[/C][C]0.773232[/C][/ROW]
[ROW][C]170[/C][C]0.23064[/C][C]0.46128[/C][C]0.76936[/C][/ROW]
[ROW][C]171[/C][C]0.204675[/C][C]0.409351[/C][C]0.795325[/C][/ROW]
[ROW][C]172[/C][C]0.201036[/C][C]0.402072[/C][C]0.798964[/C][/ROW]
[ROW][C]173[/C][C]0.343233[/C][C]0.686466[/C][C]0.656767[/C][/ROW]
[ROW][C]174[/C][C]0.31263[/C][C]0.62526[/C][C]0.68737[/C][/ROW]
[ROW][C]175[/C][C]0.336668[/C][C]0.673336[/C][C]0.663332[/C][/ROW]
[ROW][C]176[/C][C]0.347032[/C][C]0.694064[/C][C]0.652968[/C][/ROW]
[ROW][C]177[/C][C]0.377553[/C][C]0.755105[/C][C]0.622447[/C][/ROW]
[ROW][C]178[/C][C]0.344069[/C][C]0.688139[/C][C]0.655931[/C][/ROW]
[ROW][C]179[/C][C]0.319706[/C][C]0.639412[/C][C]0.680294[/C][/ROW]
[ROW][C]180[/C][C]0.305793[/C][C]0.611586[/C][C]0.694207[/C][/ROW]
[ROW][C]181[/C][C]0.273515[/C][C]0.547031[/C][C]0.726485[/C][/ROW]
[ROW][C]182[/C][C]0.248749[/C][C]0.497498[/C][C]0.751251[/C][/ROW]
[ROW][C]183[/C][C]0.219008[/C][C]0.438015[/C][C]0.780992[/C][/ROW]
[ROW][C]184[/C][C]0.191982[/C][C]0.383965[/C][C]0.808018[/C][/ROW]
[ROW][C]185[/C][C]0.202278[/C][C]0.404557[/C][C]0.797722[/C][/ROW]
[ROW][C]186[/C][C]0.182489[/C][C]0.364978[/C][C]0.817511[/C][/ROW]
[ROW][C]187[/C][C]0.159257[/C][C]0.318514[/C][C]0.840743[/C][/ROW]
[ROW][C]188[/C][C]0.138663[/C][C]0.277326[/C][C]0.861337[/C][/ROW]
[ROW][C]189[/C][C]0.118628[/C][C]0.237257[/C][C]0.881372[/C][/ROW]
[ROW][C]190[/C][C]0.101562[/C][C]0.203123[/C][C]0.898438[/C][/ROW]
[ROW][C]191[/C][C]0.10503[/C][C]0.21006[/C][C]0.89497[/C][/ROW]
[ROW][C]192[/C][C]0.0906967[/C][C]0.181393[/C][C]0.909303[/C][/ROW]
[ROW][C]193[/C][C]0.101365[/C][C]0.20273[/C][C]0.898635[/C][/ROW]
[ROW][C]194[/C][C]0.0867982[/C][C]0.173596[/C][C]0.913202[/C][/ROW]
[ROW][C]195[/C][C]0.0849144[/C][C]0.169829[/C][C]0.915086[/C][/ROW]
[ROW][C]196[/C][C]0.0867549[/C][C]0.17351[/C][C]0.913245[/C][/ROW]
[ROW][C]197[/C][C]0.116987[/C][C]0.233974[/C][C]0.883013[/C][/ROW]
[ROW][C]198[/C][C]0.0978777[/C][C]0.195755[/C][C]0.902122[/C][/ROW]
[ROW][C]199[/C][C]0.105596[/C][C]0.211193[/C][C]0.894404[/C][/ROW]
[ROW][C]200[/C][C]0.0876949[/C][C]0.17539[/C][C]0.912305[/C][/ROW]
[ROW][C]201[/C][C]0.104337[/C][C]0.208674[/C][C]0.895663[/C][/ROW]
[ROW][C]202[/C][C]0.0934978[/C][C]0.186996[/C][C]0.906502[/C][/ROW]
[ROW][C]203[/C][C]0.125404[/C][C]0.250807[/C][C]0.874596[/C][/ROW]
[ROW][C]204[/C][C]0.106316[/C][C]0.212632[/C][C]0.893684[/C][/ROW]
[ROW][C]205[/C][C]0.0869032[/C][C]0.173806[/C][C]0.913097[/C][/ROW]
[ROW][C]206[/C][C]0.0898689[/C][C]0.179738[/C][C]0.910131[/C][/ROW]
[ROW][C]207[/C][C]0.0726042[/C][C]0.145208[/C][C]0.927396[/C][/ROW]
[ROW][C]208[/C][C]0.0842029[/C][C]0.168406[/C][C]0.915797[/C][/ROW]
[ROW][C]209[/C][C]0.0682312[/C][C]0.136462[/C][C]0.931769[/C][/ROW]
[ROW][C]210[/C][C]0.0665968[/C][C]0.133194[/C][C]0.933403[/C][/ROW]
[ROW][C]211[/C][C]0.0775406[/C][C]0.155081[/C][C]0.922459[/C][/ROW]
[ROW][C]212[/C][C]0.0636363[/C][C]0.127273[/C][C]0.936364[/C][/ROW]
[ROW][C]213[/C][C]0.0503801[/C][C]0.10076[/C][C]0.94962[/C][/ROW]
[ROW][C]214[/C][C]0.0935838[/C][C]0.187168[/C][C]0.906416[/C][/ROW]
[ROW][C]215[/C][C]0.0790794[/C][C]0.158159[/C][C]0.920921[/C][/ROW]
[ROW][C]216[/C][C]0.0745778[/C][C]0.149156[/C][C]0.925422[/C][/ROW]
[ROW][C]217[/C][C]0.0832873[/C][C]0.166575[/C][C]0.916713[/C][/ROW]
[ROW][C]218[/C][C]0.0780813[/C][C]0.156163[/C][C]0.921919[/C][/ROW]
[ROW][C]219[/C][C]0.0749788[/C][C]0.149958[/C][C]0.925021[/C][/ROW]
[ROW][C]220[/C][C]0.0791467[/C][C]0.158293[/C][C]0.920853[/C][/ROW]
[ROW][C]221[/C][C]0.0722189[/C][C]0.144438[/C][C]0.927781[/C][/ROW]
[ROW][C]222[/C][C]0.0799178[/C][C]0.159836[/C][C]0.920082[/C][/ROW]
[ROW][C]223[/C][C]0.0861409[/C][C]0.172282[/C][C]0.913859[/C][/ROW]
[ROW][C]224[/C][C]0.0656289[/C][C]0.131258[/C][C]0.934371[/C][/ROW]
[ROW][C]225[/C][C]0.0494893[/C][C]0.0989785[/C][C]0.950511[/C][/ROW]
[ROW][C]226[/C][C]0.0457476[/C][C]0.0914952[/C][C]0.954252[/C][/ROW]
[ROW][C]227[/C][C]0.229471[/C][C]0.458942[/C][C]0.770529[/C][/ROW]
[ROW][C]228[/C][C]0.195345[/C][C]0.39069[/C][C]0.804655[/C][/ROW]
[ROW][C]229[/C][C]0.160296[/C][C]0.320592[/C][C]0.839704[/C][/ROW]
[ROW][C]230[/C][C]0.12429[/C][C]0.24858[/C][C]0.87571[/C][/ROW]
[ROW][C]231[/C][C]0.0899304[/C][C]0.179861[/C][C]0.91007[/C][/ROW]
[ROW][C]232[/C][C]0.0835088[/C][C]0.167018[/C][C]0.916491[/C][/ROW]
[ROW][C]233[/C][C]0.0566984[/C][C]0.113397[/C][C]0.943302[/C][/ROW]
[ROW][C]234[/C][C]0.0509956[/C][C]0.101991[/C][C]0.949004[/C][/ROW]
[ROW][C]235[/C][C]0.0375442[/C][C]0.0750884[/C][C]0.962456[/C][/ROW]
[ROW][C]236[/C][C]0.0242003[/C][C]0.0484006[/C][C]0.9758[/C][/ROW]
[ROW][C]237[/C][C]0.0196144[/C][C]0.0392288[/C][C]0.980386[/C][/ROW]
[ROW][C]238[/C][C]0.0110648[/C][C]0.0221296[/C][C]0.988935[/C][/ROW]
[ROW][C]239[/C][C]0.0186482[/C][C]0.0372965[/C][C]0.981352[/C][/ROW]
[ROW][C]240[/C][C]0.0112449[/C][C]0.0224897[/C][C]0.988755[/C][/ROW]
[ROW][C]241[/C][C]0.00513678[/C][C]0.0102736[/C][C]0.994863[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=5

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


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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
230.9829850.03402930.0170147
240.9766370.04672560.0233628
250.9566440.08671180.0433559
260.9999715.85258e-052.92629e-05
270.9999330.0001339366.69682e-05
280.9998790.0002419350.000120967
290.9997470.000505740.00025287
300.9998880.0002231120.000111556
310.9998080.0003831260.000191563
320.9996850.0006306010.000315301
330.9994460.001107580.000553792
340.9991810.00163780.000818899
350.9990680.001864020.000932011
360.9984210.003157280.00157864
370.9980010.003997680.00199884
380.9971110.005778720.00288936
390.9967230.006553240.00327662
400.995860.008280580.00414029
410.9940780.01184490.00592247
420.9916880.01662450.00831224
430.9878760.02424710.0121236
440.9862330.02753380.0137669
450.9824380.03512380.0175619
460.9818840.03623290.0181165
470.974950.05010020.0250501
480.9682220.06355630.0317782
490.9755730.04885370.0244268
500.9699850.0600310.0300155
510.9611690.07766120.0388306
520.9513560.09728770.0486438
530.9455070.1089860.0544931
540.93690.12620.0630998
550.9352350.129530.0647649
560.9186810.1626380.0813189
570.9047760.1904480.0952239
580.8907750.218450.109225
590.9205870.1588270.0794134
600.9319510.1360990.0680494
610.9347260.1305480.0652742
620.9279010.1441970.0720985
630.9579010.08419880.0420994
640.949960.1000810.0500405
650.9400760.1198470.0599237
660.9536280.09274330.0463716
670.9537860.09242890.0462145
680.9491570.1016860.050843
690.9573770.08524650.0426232
700.9704950.05901030.0295052
710.9714150.05717010.028585
720.9805180.03896480.0194824
730.9762570.04748520.0237426
740.9697080.0605840.030292
750.9635720.07285510.0364276
760.954250.09149980.0457499
770.9604460.07910890.0395545
780.952980.09404030.0470202
790.9478540.1042920.0521459
800.9461170.1077670.0538834
810.9387250.1225490.0612746
820.9265110.1469770.0734887
830.9223820.1552360.0776179
840.9080980.1838030.0919017
850.8916250.216750.108375
860.8766020.2467970.123398
870.854630.2907390.14537
880.8315340.3369320.168466
890.902780.194440.0972201
900.9165860.1668290.0834145
910.9006150.1987690.0993846
920.8820980.2358040.117902
930.8638880.2722250.136112
940.8437320.3125350.156268
950.821050.35790.17895
960.8017080.3965850.198292
970.7780170.4439660.221983
980.7843380.4313250.215662
990.7547870.4904250.245213
1000.7488570.5022870.251143
1010.7312320.5375370.268768
1020.6987670.6024650.301233
1030.7495370.5009260.250463
1040.7275040.5449920.272496
1050.747080.505840.25292
1060.7311090.5377820.268891
1070.7183410.5633190.281659
1080.7491130.5017740.250887
1090.7208430.5583140.279157
1100.6981550.603690.301845
1110.6880650.623870.311935
1120.7165980.5668030.283402
1130.7090820.5818360.290918
1140.7567750.4864490.243225
1150.7284250.543150.271575
1160.697220.6055590.30278
1170.6704350.659130.329565
1180.6428060.7143870.357194
1190.6071250.7857490.392875
1200.5739450.8521090.426055
1210.5487620.9024770.451238
1220.5155810.9688370.484419
1230.4802260.9604520.519774
1240.4481170.8962350.551883
1250.438810.8776210.56119
1260.4023410.8046820.597659
1270.3795260.7590530.620474
1280.4552820.9105630.544718
1290.4421940.8843870.557806
1300.4286020.8572030.571398
1310.4140320.8280650.585968
1320.382850.76570.61715
1330.4020330.8040670.597967
1340.3765330.7530660.623467
1350.4053890.8107790.594611
1360.3985270.7970540.601473
1370.3668280.7336560.633172
1380.3557460.7114920.644254
1390.3235760.6471520.676424
1400.3032790.6065570.696721
1410.2746470.5492930.725353
1420.2793660.5587320.720634
1430.2525840.5051680.747416
1440.2295590.4591190.770441
1450.2181540.4363080.781846
1460.2161730.4323450.783827
1470.2132080.4264160.786792
1480.2313010.4626020.768699
1490.2472810.4945620.752719
1500.2270880.4541750.772912
1510.2033380.4066770.796662
1520.1778630.3557260.822137
1530.1898520.3797050.810148
1540.2236660.4473330.776334
1550.1997950.3995890.800205
1560.1766310.3532620.823369
1570.1529250.305850.847075
1580.2441370.4882740.755863
1590.2589460.5178920.741054
1600.2300670.4601340.769933
1610.2015440.4030880.798456
1620.176610.353220.82339
1630.1558680.3117350.844132
1640.2445170.4890330.755483
1650.2368120.4736240.763188
1660.2325770.4651530.767423
1670.2040720.4081440.795928
1680.1810290.3620580.818971
1690.2267680.4535370.773232
1700.230640.461280.76936
1710.2046750.4093510.795325
1720.2010360.4020720.798964
1730.3432330.6864660.656767
1740.312630.625260.68737
1750.3366680.6733360.663332
1760.3470320.6940640.652968
1770.3775530.7551050.622447
1780.3440690.6881390.655931
1790.3197060.6394120.680294
1800.3057930.6115860.694207
1810.2735150.5470310.726485
1820.2487490.4974980.751251
1830.2190080.4380150.780992
1840.1919820.3839650.808018
1850.2022780.4045570.797722
1860.1824890.3649780.817511
1870.1592570.3185140.840743
1880.1386630.2773260.861337
1890.1186280.2372570.881372
1900.1015620.2031230.898438
1910.105030.210060.89497
1920.09069670.1813930.909303
1930.1013650.202730.898635
1940.08679820.1735960.913202
1950.08491440.1698290.915086
1960.08675490.173510.913245
1970.1169870.2339740.883013
1980.09787770.1957550.902122
1990.1055960.2111930.894404
2000.08769490.175390.912305
2010.1043370.2086740.895663
2020.09349780.1869960.906502
2030.1254040.2508070.874596
2040.1063160.2126320.893684
2050.08690320.1738060.913097
2060.08986890.1797380.910131
2070.07260420.1452080.927396
2080.08420290.1684060.915797
2090.06823120.1364620.931769
2100.06659680.1331940.933403
2110.07754060.1550810.922459
2120.06363630.1272730.936364
2130.05038010.100760.94962
2140.09358380.1871680.906416
2150.07907940.1581590.920921
2160.07457780.1491560.925422
2170.08328730.1665750.916713
2180.07808130.1561630.921919
2190.07497880.1499580.925021
2200.07914670.1582930.920853
2210.07221890.1444380.927781
2220.07991780.1598360.920082
2230.08614090.1722820.913859
2240.06562890.1312580.934371
2250.04948930.09897850.950511
2260.04574760.09149520.954252
2270.2294710.4589420.770529
2280.1953450.390690.804655
2290.1602960.3205920.839704
2300.124290.248580.87571
2310.08993040.1798610.91007
2320.08350880.1670180.916491
2330.05669840.1133970.943302
2340.05099560.1019910.949004
2350.03754420.07508840.962456
2360.02420030.04840060.9758
2370.01961440.03922880.980386
2380.01106480.02212960.988935
2390.01864820.03729650.981352
2400.01124490.02248970.988755
2410.005136780.01027360.994863






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level150.0684932NOK
5% type I error level320.146119NOK
10% type I error level520.237443NOK

\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 & 15 & 0.0684932 & NOK \tabularnewline
5% type I error level & 32 & 0.146119 & NOK \tabularnewline
10% type I error level & 52 & 0.237443 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=225501&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]15[/C][C]0.0684932[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]32[/C][C]0.146119[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]52[/C][C]0.237443[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=225501&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=225501&T=6

As an alternative you can also use a QR Code:  
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 testsOK/NOK
1% type I error level150.0684932NOK
5% type I error level320.146119NOK
10% type I error level520.237443NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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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
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Input Parameters & R Code

Parameters (Session):
par1 = 5 ; par2 = Include Monthly Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Include Monthly 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')
}