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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 computationSun, 03 Nov 2013 12:49:02 -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/03/t1383501030cnnmm99pkd22b2a.htm/, Retrieved Mon, 29 Apr 2024 10:58:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221976, Retrieved Mon, 29 Apr 2024 10:58:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsmultiple lineair regression
Estimated Impact71

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [WS7] [2013-11-03 17:49:02] [6b66da5303ca14f42aa66d23283a2413] [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 time14 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 14 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&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]14 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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 time14 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Connected[t] = + 23.9519 + 0.432094Separate[t] + 0.0904753Learning[t] -0.0896286Software[t] + 0.00230416Happiness[t] -0.0446149Depression[t] -0.0582569Sport1[t] + 0.1307Sport2[t] -0.540364Month[t] -0.0579873M1[t] + 0.924623M2[t] -0.939074M3[t] -0.531369M4[t] + 0.207999M5[t] -0.292459M6[t] + 1.52613M7[t] -0.460216M8[t] -0.131819M9[t] -2.10485M10[t] + 0.470861M11[t] -0.00112436t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Connected[t] =  +  23.9519 +  0.432094Separate[t] +  0.0904753Learning[t] -0.0896286Software[t] +  0.00230416Happiness[t] -0.0446149Depression[t] -0.0582569Sport1[t] +  0.1307Sport2[t] -0.540364Month[t] -0.0579873M1[t] +  0.924623M2[t] -0.939074M3[t] -0.531369M4[t] +  0.207999M5[t] -0.292459M6[t] +  1.52613M7[t] -0.460216M8[t] -0.131819M9[t] -2.10485M10[t] +  0.470861M11[t] -0.00112436t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Connected[t] =  +  23.9519 +  0.432094Separate[t] +  0.0904753Learning[t] -0.0896286Software[t] +  0.00230416Happiness[t] -0.0446149Depression[t] -0.0582569Sport1[t] +  0.1307Sport2[t] -0.540364Month[t] -0.0579873M1[t] +  0.924623M2[t] -0.939074M3[t] -0.531369M4[t] +  0.207999M5[t] -0.292459M6[t] +  1.52613M7[t] -0.460216M8[t] -0.131819M9[t] -2.10485M10[t] +  0.470861M11[t] -0.00112436t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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
Connected[t] = + 23.9519 + 0.432094Separate[t] + 0.0904753Learning[t] -0.0896286Software[t] + 0.00230416Happiness[t] -0.0446149Depression[t] -0.0582569Sport1[t] + 0.1307Sport2[t] -0.540364Month[t] -0.0579873M1[t] + 0.924623M2[t] -0.939074M3[t] -0.531369M4[t] + 0.207999M5[t] -0.292459M6[t] + 1.52613M7[t] -0.460216M8[t] -0.131819M9[t] -2.10485M10[t] + 0.470861M11[t] -0.00112436t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)23.95196.864953.4890.000575430.000287715
Separate0.4320940.0576347.4971.21568e-126.07838e-13
Learning0.09047530.112960.80090.4239450.211973
Software-0.08962860.117272-0.76430.4454420.222721
Happiness0.002304160.1046950.022010.9824590.49123
Depression-0.04461490.0778091-0.57340.5669120.283456
Sport1-0.05825690.0685297-0.85010.3961080.198054
Sport20.13070.101651.2860.1997420.0998711
Month-0.5403640.731664-0.73850.4608980.230449
M1-0.05798731.01927-0.056890.9546790.477339
M20.9246231.014190.91170.3628360.181418
M3-0.9390741.01178-0.92810.3542570.177129
M4-0.5313691.00847-0.52690.598740.29937
M50.2079991.019590.2040.8385230.419261
M6-0.2924591.02732-0.28470.7761310.388065
M71.526131.007651.5150.1311870.0655936
M8-0.4602161.00678-0.45710.6479950.323997
M9-0.1318191.00616-0.1310.8958740.447937
M10-2.104851.00446-2.0960.03716030.0185802
M110.4708611.00640.46790.6402980.320149
t-0.001124360.0077952-0.14420.8854320.442716

\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) & 23.9519 & 6.86495 & 3.489 & 0.00057543 & 0.000287715 \tabularnewline
Separate & 0.432094 & 0.057634 & 7.497 & 1.21568e-12 & 6.07838e-13 \tabularnewline
Learning & 0.0904753 & 0.11296 & 0.8009 & 0.423945 & 0.211973 \tabularnewline
Software & -0.0896286 & 0.117272 & -0.7643 & 0.445442 & 0.222721 \tabularnewline
Happiness & 0.00230416 & 0.104695 & 0.02201 & 0.982459 & 0.49123 \tabularnewline
Depression & -0.0446149 & 0.0778091 & -0.5734 & 0.566912 & 0.283456 \tabularnewline
Sport1 & -0.0582569 & 0.0685297 & -0.8501 & 0.396108 & 0.198054 \tabularnewline
Sport2 & 0.1307 & 0.10165 & 1.286 & 0.199742 & 0.0998711 \tabularnewline
Month & -0.540364 & 0.731664 & -0.7385 & 0.460898 & 0.230449 \tabularnewline
M1 & -0.0579873 & 1.01927 & -0.05689 & 0.954679 & 0.477339 \tabularnewline
M2 & 0.924623 & 1.01419 & 0.9117 & 0.362836 & 0.181418 \tabularnewline
M3 & -0.939074 & 1.01178 & -0.9281 & 0.354257 & 0.177129 \tabularnewline
M4 & -0.531369 & 1.00847 & -0.5269 & 0.59874 & 0.29937 \tabularnewline
M5 & 0.207999 & 1.01959 & 0.204 & 0.838523 & 0.419261 \tabularnewline
M6 & -0.292459 & 1.02732 & -0.2847 & 0.776131 & 0.388065 \tabularnewline
M7 & 1.52613 & 1.00765 & 1.515 & 0.131187 & 0.0655936 \tabularnewline
M8 & -0.460216 & 1.00678 & -0.4571 & 0.647995 & 0.323997 \tabularnewline
M9 & -0.131819 & 1.00616 & -0.131 & 0.895874 & 0.447937 \tabularnewline
M10 & -2.10485 & 1.00446 & -2.096 & 0.0371603 & 0.0185802 \tabularnewline
M11 & 0.470861 & 1.0064 & 0.4679 & 0.640298 & 0.320149 \tabularnewline
t & -0.00112436 & 0.0077952 & -0.1442 & 0.885432 & 0.442716 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&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]23.9519[/C][C]6.86495[/C][C]3.489[/C][C]0.00057543[/C][C]0.000287715[/C][/ROW]
[ROW][C]Separate[/C][C]0.432094[/C][C]0.057634[/C][C]7.497[/C][C]1.21568e-12[/C][C]6.07838e-13[/C][/ROW]
[ROW][C]Learning[/C][C]0.0904753[/C][C]0.11296[/C][C]0.8009[/C][C]0.423945[/C][C]0.211973[/C][/ROW]
[ROW][C]Software[/C][C]-0.0896286[/C][C]0.117272[/C][C]-0.7643[/C][C]0.445442[/C][C]0.222721[/C][/ROW]
[ROW][C]Happiness[/C][C]0.00230416[/C][C]0.104695[/C][C]0.02201[/C][C]0.982459[/C][C]0.49123[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0446149[/C][C]0.0778091[/C][C]-0.5734[/C][C]0.566912[/C][C]0.283456[/C][/ROW]
[ROW][C]Sport1[/C][C]-0.0582569[/C][C]0.0685297[/C][C]-0.8501[/C][C]0.396108[/C][C]0.198054[/C][/ROW]
[ROW][C]Sport2[/C][C]0.1307[/C][C]0.10165[/C][C]1.286[/C][C]0.199742[/C][C]0.0998711[/C][/ROW]
[ROW][C]Month[/C][C]-0.540364[/C][C]0.731664[/C][C]-0.7385[/C][C]0.460898[/C][C]0.230449[/C][/ROW]
[ROW][C]M1[/C][C]-0.0579873[/C][C]1.01927[/C][C]-0.05689[/C][C]0.954679[/C][C]0.477339[/C][/ROW]
[ROW][C]M2[/C][C]0.924623[/C][C]1.01419[/C][C]0.9117[/C][C]0.362836[/C][C]0.181418[/C][/ROW]
[ROW][C]M3[/C][C]-0.939074[/C][C]1.01178[/C][C]-0.9281[/C][C]0.354257[/C][C]0.177129[/C][/ROW]
[ROW][C]M4[/C][C]-0.531369[/C][C]1.00847[/C][C]-0.5269[/C][C]0.59874[/C][C]0.29937[/C][/ROW]
[ROW][C]M5[/C][C]0.207999[/C][C]1.01959[/C][C]0.204[/C][C]0.838523[/C][C]0.419261[/C][/ROW]
[ROW][C]M6[/C][C]-0.292459[/C][C]1.02732[/C][C]-0.2847[/C][C]0.776131[/C][C]0.388065[/C][/ROW]
[ROW][C]M7[/C][C]1.52613[/C][C]1.00765[/C][C]1.515[/C][C]0.131187[/C][C]0.0655936[/C][/ROW]
[ROW][C]M8[/C][C]-0.460216[/C][C]1.00678[/C][C]-0.4571[/C][C]0.647995[/C][C]0.323997[/C][/ROW]
[ROW][C]M9[/C][C]-0.131819[/C][C]1.00616[/C][C]-0.131[/C][C]0.895874[/C][C]0.447937[/C][/ROW]
[ROW][C]M10[/C][C]-2.10485[/C][C]1.00446[/C][C]-2.096[/C][C]0.0371603[/C][C]0.0185802[/C][/ROW]
[ROW][C]M11[/C][C]0.470861[/C][C]1.0064[/C][C]0.4679[/C][C]0.640298[/C][C]0.320149[/C][/ROW]
[ROW][C]t[/C][C]-0.00112436[/C][C]0.0077952[/C][C]-0.1442[/C][C]0.885432[/C][C]0.442716[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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)23.95196.864953.4890.000575430.000287715
Separate0.4320940.0576347.4971.21568e-126.07838e-13
Learning0.09047530.112960.80090.4239450.211973
Software-0.08962860.117272-0.76430.4454420.222721
Happiness0.002304160.1046950.022010.9824590.49123
Depression-0.04461490.0778091-0.57340.5669120.283456
Sport1-0.05825690.0685297-0.85010.3961080.198054
Sport20.13070.101651.2860.1997420.0998711
Month-0.5403640.731664-0.73850.4608980.230449
M1-0.05798731.01927-0.056890.9546790.477339
M20.9246231.014190.91170.3628360.181418
M3-0.9390741.01178-0.92810.3542570.177129
M4-0.5313691.00847-0.52690.598740.29937
M50.2079991.019590.2040.8385230.419261
M6-0.2924591.02732-0.28470.7761310.388065
M71.526131.007651.5150.1311870.0655936
M8-0.4602161.00678-0.45710.6479950.323997
M9-0.1318191.00616-0.1310.8958740.447937
M10-2.104851.00446-2.0960.03716030.0185802
M110.4708611.00640.46790.6402980.320149
t-0.001124360.0077952-0.14420.8854320.442716






Multiple Linear Regression - Regression Statistics
Multiple R0.544372
R-squared0.29634
Adjusted R-squared0.238426
F-TEST (value)5.11687
F-TEST (DF numerator)20
F-TEST (DF denominator)243
p-value1.38043e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.31312
Sum Squared Residuals2667.36

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.544372 \tabularnewline
R-squared & 0.29634 \tabularnewline
Adjusted R-squared & 0.238426 \tabularnewline
F-TEST (value) & 5.11687 \tabularnewline
F-TEST (DF numerator) & 20 \tabularnewline
F-TEST (DF denominator) & 243 \tabularnewline
p-value & 1.38043e-10 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 3.31312 \tabularnewline
Sum Squared Residuals & 2667.36 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.544372[/C][/ROW]
[ROW][C]R-squared[/C][C]0.29634[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.238426[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]5.11687[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]20[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]243[/C][/ROW]
[ROW][C]p-value[/C][C]1.38043e-10[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]3.31312[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]2667.36[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.544372
R-squared0.29634
Adjusted R-squared0.238426
F-TEST (value)5.11687
F-TEST (DF numerator)20
F-TEST (DF denominator)243
p-value1.38043e-10
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation3.31312
Sum Squared Residuals2667.36






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
14136.14144.85856
23935.68093.31915
33034.6893-4.68931
43134.579-3.57904
53436.0647-2.06466
63532.70512.29494
73935.44443.55564
83435.5624-1.56243
93635.42010.579946
103735.11261.88742
113834.88843.11156
123634.99251.00746
133835.45142.54856
143937.45831.54169
153335.768-2.76796
163233.814-1.81396
173634.48531.51469
183837.40910.590871
193938.8720.127963
203233.6465-1.64648
213234.7854-2.78543
223131.9161-0.916144
233937.17121.82878
243737.3516-0.351612
253934.62694.37315
264135.28555.71445
273634.53251.46746
283335.7098-2.70975
293334.6427-1.64266
303434.6849-0.684908
313135.6355-4.63555
322733.3161-6.31613
333733.76193.23807
343435.0132-1.01317
353433.30480.695219
363234.8792-2.87917
372932.7763-3.77626
383635.40380.596158
392933.2297-4.22969
403534.37620.623757
413734.83242.16757
423433.9930.00699075
433835.70572.29427
443533.63381.36615
453832.38875.61126
463732.6874.31303
473837.92630.0737171
483335.2839-2.28386
493636.4052-0.405206
503835.02662.97336
513235.8517-3.85167
523232.5645-0.564475
533233.8943-1.89435
543437.2408-3.24083
553235.318-3.31802
563735.52071.4793
573934.98344.0166
582933.2011-4.2011
593736.36870.631342
603535.1643-0.164284
613031.74-1.73996
623835.89722.10285
633434.4979-0.49789
643134.3194-3.31938
653433.61240.387629
663535.8181-0.818071
673636.4075-0.407505
683030.919-0.919045
693936.38382.61617
703533.60391.39607
713835.98232.01768
723135.7025-4.70255
733436.643-2.64304
743838.276-0.27604
753430.74413.25587
763932.54956.45054
773735.9411.05905
783433.02730.972657
792834.5929-6.59287
803730.83246.1676
813335.2066-2.20658
823534.08910.910897
833734.33542.66461
843234.5718-2.57178
853333.4504-0.450383
863837.65470.345283
873333.5412-0.54124
882932.645-3.64503
893333.7737-0.773661
903135.2077-4.20773
913634.52081.47925
923537.0536-2.05357
933231.55170.448272
942930.3559-1.35585
953936.04752.95247
963734.76032.23971
973533.42681.57321
983735.52921.47078
993234.5968-2.59678
1003834.69973.3003
1013735.17031.8297
1023635.93980.0602105
1033233.6075-1.60752
1043336.1459-3.14586
1054032.79647.20363
1063833.17164.8284
1074136.92724.07281
1083634.53291.46709
1094337.16755.83251
1103035.667-5.66705
1113132.7323-1.73226
1123237.7601-5.76013
1133231.66560.334404
1143734.22982.77023
1153735.74331.25673
1163335.9178-2.9178
1173437.4182-3.41819
1183332.72470.275251
1193836.12131.87875
1203335.1168-2.11679
1213131.2956-0.295585
1223837.70480.295184
1233735.47631.52365
1243632.6373.36305
1253134.0579-3.05785
1263934.02974.97032
1274438.36835.63169
1283335.8114-2.81136
1293533.64121.35877
1303232.0001-7.52564e-05
1312833.1292-5.12922
1324036.23283.7672
1332732.21-5.21004
1343737.1333-0.13334
1353231.65730.342702
1362827.90610.0939443
1373435.3237-1.32365
1383034.0631-4.06307
1393536.0214-1.0214
1403134.0761-3.07611
1413234.4354-2.43538
1423034.0061-4.00614
1433035.5892-5.58923
1443129.81191.18813
1454033.45976.54032
1463232.6556-0.655575
1473634.01651.98348
1483232.7973-0.797343
1493533.71781.28218
1503836.6931.30702
1514236.89625.10378
1523435.8355-1.83552
1533537.0546-2.05455
1543832.82495.17507
1553333.7761-0.776098
1563632.92153.07846
1573235.9477-3.94772
1583337.1625-4.16246
1593433.11970.880283
1603235.4913-3.49131
1613435.8984-1.89843
1622729.7751-2.77512
1633131.7857-0.78568
1643832.80825.19176
1653435.6487-1.64871
1662429.0334-5.03343
1673034.0573-4.05734
1682629.3839-3.38393
1693435.345-1.345
1702735.4246-8.4246
1713731.28185.71819
1723634.70051.29947
1734134.41846.58163
1742928.91790.0820718
1753632.45933.5407
1763233.6795-1.67954
1773733.27043.72957
1783029.50840.491608
1793133.089-2.08905
1803834.65123.34878
1813634.38261.61737
1823533.23211.76787
1833134.0097-3.00973
1843832.57755.42254
1852231.3046-9.30459
1863233.9394-1.93936
1873635.28390.716064
1883932.41686.58318
1892830.3106-2.31056
1903232.424-0.424009
1913232.6798-0.67984
1923836.41551.58445
1933233.6439-1.6439
1943536.2219-1.2219
1953231.92280.0772074
1963735.12251.87754
1973432.88621.1138
1983335.0742-2.0742
1993334.4242-1.42416
2002632.2369-6.23692
2013031.9784-1.97838
2022429.7166-5.71663
2033432.50261.4974
2043432.44971.55027
2053334.0202-1.02018
2063435.6526-1.65262
2073535.0189-0.0188583
2083533.56011.43985
2093633.41722.58283
2103433.34220.65776
2113434.328-0.327955
2124137.91133.0887
2133236.0713-4.07126
2143031.3747-1.37466
2153534.32410.675886
2162829.9644-1.96438
2173334.7744-1.77441
2183935.2073.793
2193632.59353.40648
2203635.79180.208225
2213533.40191.59814
2223833.56594.43407
2233334.2128-1.21284
2243132.5913-1.59127
2253431.85582.14419
2263232.4493-0.449297
2273133.1412-2.1412
2283333.1687-0.16868
2293432.77691.2231
2303435.0638-1.06378
2313431.39112.60888
2323334.7983-1.79826
2333234.5143-2.51434
2344133.17457.82554
2353434.5684-0.568403
2363631.71914.2809
2373731.77335.22671
2383628.25297.74711
2392932.935-3.93495
2403732.02464.97544
2412733.2567-6.25668
2423534.41050.589503
2432830.0396-2.03957
2443532.79662.20339
2453733.35623.64376
2462933.5336-4.53359
2473235.859-3.85902
2483631.42714.57289
2491927.6124-8.61238
2502124.6901-3.69013
2513134.077-3.077
2523332.69930.300655
2533634.05841.94161
2543334.2519-1.25191
2553732.28924.71078
2563432.80391.19609
2573534.62120.378806
2583132.6358-1.63579
2593734.94522.05483
2603531.93843.06155
2612731.6518-4.65175
2623432.84421.1558
2634034.62635.3737
2642932.9206-3.92061

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 41 & 36.1414 & 4.85856 \tabularnewline
2 & 39 & 35.6809 & 3.31915 \tabularnewline
3 & 30 & 34.6893 & -4.68931 \tabularnewline
4 & 31 & 34.579 & -3.57904 \tabularnewline
5 & 34 & 36.0647 & -2.06466 \tabularnewline
6 & 35 & 32.7051 & 2.29494 \tabularnewline
7 & 39 & 35.4444 & 3.55564 \tabularnewline
8 & 34 & 35.5624 & -1.56243 \tabularnewline
9 & 36 & 35.4201 & 0.579946 \tabularnewline
10 & 37 & 35.1126 & 1.88742 \tabularnewline
11 & 38 & 34.8884 & 3.11156 \tabularnewline
12 & 36 & 34.9925 & 1.00746 \tabularnewline
13 & 38 & 35.4514 & 2.54856 \tabularnewline
14 & 39 & 37.4583 & 1.54169 \tabularnewline
15 & 33 & 35.768 & -2.76796 \tabularnewline
16 & 32 & 33.814 & -1.81396 \tabularnewline
17 & 36 & 34.4853 & 1.51469 \tabularnewline
18 & 38 & 37.4091 & 0.590871 \tabularnewline
19 & 39 & 38.872 & 0.127963 \tabularnewline
20 & 32 & 33.6465 & -1.64648 \tabularnewline
21 & 32 & 34.7854 & -2.78543 \tabularnewline
22 & 31 & 31.9161 & -0.916144 \tabularnewline
23 & 39 & 37.1712 & 1.82878 \tabularnewline
24 & 37 & 37.3516 & -0.351612 \tabularnewline
25 & 39 & 34.6269 & 4.37315 \tabularnewline
26 & 41 & 35.2855 & 5.71445 \tabularnewline
27 & 36 & 34.5325 & 1.46746 \tabularnewline
28 & 33 & 35.7098 & -2.70975 \tabularnewline
29 & 33 & 34.6427 & -1.64266 \tabularnewline
30 & 34 & 34.6849 & -0.684908 \tabularnewline
31 & 31 & 35.6355 & -4.63555 \tabularnewline
32 & 27 & 33.3161 & -6.31613 \tabularnewline
33 & 37 & 33.7619 & 3.23807 \tabularnewline
34 & 34 & 35.0132 & -1.01317 \tabularnewline
35 & 34 & 33.3048 & 0.695219 \tabularnewline
36 & 32 & 34.8792 & -2.87917 \tabularnewline
37 & 29 & 32.7763 & -3.77626 \tabularnewline
38 & 36 & 35.4038 & 0.596158 \tabularnewline
39 & 29 & 33.2297 & -4.22969 \tabularnewline
40 & 35 & 34.3762 & 0.623757 \tabularnewline
41 & 37 & 34.8324 & 2.16757 \tabularnewline
42 & 34 & 33.993 & 0.00699075 \tabularnewline
43 & 38 & 35.7057 & 2.29427 \tabularnewline
44 & 35 & 33.6338 & 1.36615 \tabularnewline
45 & 38 & 32.3887 & 5.61126 \tabularnewline
46 & 37 & 32.687 & 4.31303 \tabularnewline
47 & 38 & 37.9263 & 0.0737171 \tabularnewline
48 & 33 & 35.2839 & -2.28386 \tabularnewline
49 & 36 & 36.4052 & -0.405206 \tabularnewline
50 & 38 & 35.0266 & 2.97336 \tabularnewline
51 & 32 & 35.8517 & -3.85167 \tabularnewline
52 & 32 & 32.5645 & -0.564475 \tabularnewline
53 & 32 & 33.8943 & -1.89435 \tabularnewline
54 & 34 & 37.2408 & -3.24083 \tabularnewline
55 & 32 & 35.318 & -3.31802 \tabularnewline
56 & 37 & 35.5207 & 1.4793 \tabularnewline
57 & 39 & 34.9834 & 4.0166 \tabularnewline
58 & 29 & 33.2011 & -4.2011 \tabularnewline
59 & 37 & 36.3687 & 0.631342 \tabularnewline
60 & 35 & 35.1643 & -0.164284 \tabularnewline
61 & 30 & 31.74 & -1.73996 \tabularnewline
62 & 38 & 35.8972 & 2.10285 \tabularnewline
63 & 34 & 34.4979 & -0.49789 \tabularnewline
64 & 31 & 34.3194 & -3.31938 \tabularnewline
65 & 34 & 33.6124 & 0.387629 \tabularnewline
66 & 35 & 35.8181 & -0.818071 \tabularnewline
67 & 36 & 36.4075 & -0.407505 \tabularnewline
68 & 30 & 30.919 & -0.919045 \tabularnewline
69 & 39 & 36.3838 & 2.61617 \tabularnewline
70 & 35 & 33.6039 & 1.39607 \tabularnewline
71 & 38 & 35.9823 & 2.01768 \tabularnewline
72 & 31 & 35.7025 & -4.70255 \tabularnewline
73 & 34 & 36.643 & -2.64304 \tabularnewline
74 & 38 & 38.276 & -0.27604 \tabularnewline
75 & 34 & 30.7441 & 3.25587 \tabularnewline
76 & 39 & 32.5495 & 6.45054 \tabularnewline
77 & 37 & 35.941 & 1.05905 \tabularnewline
78 & 34 & 33.0273 & 0.972657 \tabularnewline
79 & 28 & 34.5929 & -6.59287 \tabularnewline
80 & 37 & 30.8324 & 6.1676 \tabularnewline
81 & 33 & 35.2066 & -2.20658 \tabularnewline
82 & 35 & 34.0891 & 0.910897 \tabularnewline
83 & 37 & 34.3354 & 2.66461 \tabularnewline
84 & 32 & 34.5718 & -2.57178 \tabularnewline
85 & 33 & 33.4504 & -0.450383 \tabularnewline
86 & 38 & 37.6547 & 0.345283 \tabularnewline
87 & 33 & 33.5412 & -0.54124 \tabularnewline
88 & 29 & 32.645 & -3.64503 \tabularnewline
89 & 33 & 33.7737 & -0.773661 \tabularnewline
90 & 31 & 35.2077 & -4.20773 \tabularnewline
91 & 36 & 34.5208 & 1.47925 \tabularnewline
92 & 35 & 37.0536 & -2.05357 \tabularnewline
93 & 32 & 31.5517 & 0.448272 \tabularnewline
94 & 29 & 30.3559 & -1.35585 \tabularnewline
95 & 39 & 36.0475 & 2.95247 \tabularnewline
96 & 37 & 34.7603 & 2.23971 \tabularnewline
97 & 35 & 33.4268 & 1.57321 \tabularnewline
98 & 37 & 35.5292 & 1.47078 \tabularnewline
99 & 32 & 34.5968 & -2.59678 \tabularnewline
100 & 38 & 34.6997 & 3.3003 \tabularnewline
101 & 37 & 35.1703 & 1.8297 \tabularnewline
102 & 36 & 35.9398 & 0.0602105 \tabularnewline
103 & 32 & 33.6075 & -1.60752 \tabularnewline
104 & 33 & 36.1459 & -3.14586 \tabularnewline
105 & 40 & 32.7964 & 7.20363 \tabularnewline
106 & 38 & 33.1716 & 4.8284 \tabularnewline
107 & 41 & 36.9272 & 4.07281 \tabularnewline
108 & 36 & 34.5329 & 1.46709 \tabularnewline
109 & 43 & 37.1675 & 5.83251 \tabularnewline
110 & 30 & 35.667 & -5.66705 \tabularnewline
111 & 31 & 32.7323 & -1.73226 \tabularnewline
112 & 32 & 37.7601 & -5.76013 \tabularnewline
113 & 32 & 31.6656 & 0.334404 \tabularnewline
114 & 37 & 34.2298 & 2.77023 \tabularnewline
115 & 37 & 35.7433 & 1.25673 \tabularnewline
116 & 33 & 35.9178 & -2.9178 \tabularnewline
117 & 34 & 37.4182 & -3.41819 \tabularnewline
118 & 33 & 32.7247 & 0.275251 \tabularnewline
119 & 38 & 36.1213 & 1.87875 \tabularnewline
120 & 33 & 35.1168 & -2.11679 \tabularnewline
121 & 31 & 31.2956 & -0.295585 \tabularnewline
122 & 38 & 37.7048 & 0.295184 \tabularnewline
123 & 37 & 35.4763 & 1.52365 \tabularnewline
124 & 36 & 32.637 & 3.36305 \tabularnewline
125 & 31 & 34.0579 & -3.05785 \tabularnewline
126 & 39 & 34.0297 & 4.97032 \tabularnewline
127 & 44 & 38.3683 & 5.63169 \tabularnewline
128 & 33 & 35.8114 & -2.81136 \tabularnewline
129 & 35 & 33.6412 & 1.35877 \tabularnewline
130 & 32 & 32.0001 & -7.52564e-05 \tabularnewline
131 & 28 & 33.1292 & -5.12922 \tabularnewline
132 & 40 & 36.2328 & 3.7672 \tabularnewline
133 & 27 & 32.21 & -5.21004 \tabularnewline
134 & 37 & 37.1333 & -0.13334 \tabularnewline
135 & 32 & 31.6573 & 0.342702 \tabularnewline
136 & 28 & 27.9061 & 0.0939443 \tabularnewline
137 & 34 & 35.3237 & -1.32365 \tabularnewline
138 & 30 & 34.0631 & -4.06307 \tabularnewline
139 & 35 & 36.0214 & -1.0214 \tabularnewline
140 & 31 & 34.0761 & -3.07611 \tabularnewline
141 & 32 & 34.4354 & -2.43538 \tabularnewline
142 & 30 & 34.0061 & -4.00614 \tabularnewline
143 & 30 & 35.5892 & -5.58923 \tabularnewline
144 & 31 & 29.8119 & 1.18813 \tabularnewline
145 & 40 & 33.4597 & 6.54032 \tabularnewline
146 & 32 & 32.6556 & -0.655575 \tabularnewline
147 & 36 & 34.0165 & 1.98348 \tabularnewline
148 & 32 & 32.7973 & -0.797343 \tabularnewline
149 & 35 & 33.7178 & 1.28218 \tabularnewline
150 & 38 & 36.693 & 1.30702 \tabularnewline
151 & 42 & 36.8962 & 5.10378 \tabularnewline
152 & 34 & 35.8355 & -1.83552 \tabularnewline
153 & 35 & 37.0546 & -2.05455 \tabularnewline
154 & 38 & 32.8249 & 5.17507 \tabularnewline
155 & 33 & 33.7761 & -0.776098 \tabularnewline
156 & 36 & 32.9215 & 3.07846 \tabularnewline
157 & 32 & 35.9477 & -3.94772 \tabularnewline
158 & 33 & 37.1625 & -4.16246 \tabularnewline
159 & 34 & 33.1197 & 0.880283 \tabularnewline
160 & 32 & 35.4913 & -3.49131 \tabularnewline
161 & 34 & 35.8984 & -1.89843 \tabularnewline
162 & 27 & 29.7751 & -2.77512 \tabularnewline
163 & 31 & 31.7857 & -0.78568 \tabularnewline
164 & 38 & 32.8082 & 5.19176 \tabularnewline
165 & 34 & 35.6487 & -1.64871 \tabularnewline
166 & 24 & 29.0334 & -5.03343 \tabularnewline
167 & 30 & 34.0573 & -4.05734 \tabularnewline
168 & 26 & 29.3839 & -3.38393 \tabularnewline
169 & 34 & 35.345 & -1.345 \tabularnewline
170 & 27 & 35.4246 & -8.4246 \tabularnewline
171 & 37 & 31.2818 & 5.71819 \tabularnewline
172 & 36 & 34.7005 & 1.29947 \tabularnewline
173 & 41 & 34.4184 & 6.58163 \tabularnewline
174 & 29 & 28.9179 & 0.0820718 \tabularnewline
175 & 36 & 32.4593 & 3.5407 \tabularnewline
176 & 32 & 33.6795 & -1.67954 \tabularnewline
177 & 37 & 33.2704 & 3.72957 \tabularnewline
178 & 30 & 29.5084 & 0.491608 \tabularnewline
179 & 31 & 33.089 & -2.08905 \tabularnewline
180 & 38 & 34.6512 & 3.34878 \tabularnewline
181 & 36 & 34.3826 & 1.61737 \tabularnewline
182 & 35 & 33.2321 & 1.76787 \tabularnewline
183 & 31 & 34.0097 & -3.00973 \tabularnewline
184 & 38 & 32.5775 & 5.42254 \tabularnewline
185 & 22 & 31.3046 & -9.30459 \tabularnewline
186 & 32 & 33.9394 & -1.93936 \tabularnewline
187 & 36 & 35.2839 & 0.716064 \tabularnewline
188 & 39 & 32.4168 & 6.58318 \tabularnewline
189 & 28 & 30.3106 & -2.31056 \tabularnewline
190 & 32 & 32.424 & -0.424009 \tabularnewline
191 & 32 & 32.6798 & -0.67984 \tabularnewline
192 & 38 & 36.4155 & 1.58445 \tabularnewline
193 & 32 & 33.6439 & -1.6439 \tabularnewline
194 & 35 & 36.2219 & -1.2219 \tabularnewline
195 & 32 & 31.9228 & 0.0772074 \tabularnewline
196 & 37 & 35.1225 & 1.87754 \tabularnewline
197 & 34 & 32.8862 & 1.1138 \tabularnewline
198 & 33 & 35.0742 & -2.0742 \tabularnewline
199 & 33 & 34.4242 & -1.42416 \tabularnewline
200 & 26 & 32.2369 & -6.23692 \tabularnewline
201 & 30 & 31.9784 & -1.97838 \tabularnewline
202 & 24 & 29.7166 & -5.71663 \tabularnewline
203 & 34 & 32.5026 & 1.4974 \tabularnewline
204 & 34 & 32.4497 & 1.55027 \tabularnewline
205 & 33 & 34.0202 & -1.02018 \tabularnewline
206 & 34 & 35.6526 & -1.65262 \tabularnewline
207 & 35 & 35.0189 & -0.0188583 \tabularnewline
208 & 35 & 33.5601 & 1.43985 \tabularnewline
209 & 36 & 33.4172 & 2.58283 \tabularnewline
210 & 34 & 33.3422 & 0.65776 \tabularnewline
211 & 34 & 34.328 & -0.327955 \tabularnewline
212 & 41 & 37.9113 & 3.0887 \tabularnewline
213 & 32 & 36.0713 & -4.07126 \tabularnewline
214 & 30 & 31.3747 & -1.37466 \tabularnewline
215 & 35 & 34.3241 & 0.675886 \tabularnewline
216 & 28 & 29.9644 & -1.96438 \tabularnewline
217 & 33 & 34.7744 & -1.77441 \tabularnewline
218 & 39 & 35.207 & 3.793 \tabularnewline
219 & 36 & 32.5935 & 3.40648 \tabularnewline
220 & 36 & 35.7918 & 0.208225 \tabularnewline
221 & 35 & 33.4019 & 1.59814 \tabularnewline
222 & 38 & 33.5659 & 4.43407 \tabularnewline
223 & 33 & 34.2128 & -1.21284 \tabularnewline
224 & 31 & 32.5913 & -1.59127 \tabularnewline
225 & 34 & 31.8558 & 2.14419 \tabularnewline
226 & 32 & 32.4493 & -0.449297 \tabularnewline
227 & 31 & 33.1412 & -2.1412 \tabularnewline
228 & 33 & 33.1687 & -0.16868 \tabularnewline
229 & 34 & 32.7769 & 1.2231 \tabularnewline
230 & 34 & 35.0638 & -1.06378 \tabularnewline
231 & 34 & 31.3911 & 2.60888 \tabularnewline
232 & 33 & 34.7983 & -1.79826 \tabularnewline
233 & 32 & 34.5143 & -2.51434 \tabularnewline
234 & 41 & 33.1745 & 7.82554 \tabularnewline
235 & 34 & 34.5684 & -0.568403 \tabularnewline
236 & 36 & 31.7191 & 4.2809 \tabularnewline
237 & 37 & 31.7733 & 5.22671 \tabularnewline
238 & 36 & 28.2529 & 7.74711 \tabularnewline
239 & 29 & 32.935 & -3.93495 \tabularnewline
240 & 37 & 32.0246 & 4.97544 \tabularnewline
241 & 27 & 33.2567 & -6.25668 \tabularnewline
242 & 35 & 34.4105 & 0.589503 \tabularnewline
243 & 28 & 30.0396 & -2.03957 \tabularnewline
244 & 35 & 32.7966 & 2.20339 \tabularnewline
245 & 37 & 33.3562 & 3.64376 \tabularnewline
246 & 29 & 33.5336 & -4.53359 \tabularnewline
247 & 32 & 35.859 & -3.85902 \tabularnewline
248 & 36 & 31.4271 & 4.57289 \tabularnewline
249 & 19 & 27.6124 & -8.61238 \tabularnewline
250 & 21 & 24.6901 & -3.69013 \tabularnewline
251 & 31 & 34.077 & -3.077 \tabularnewline
252 & 33 & 32.6993 & 0.300655 \tabularnewline
253 & 36 & 34.0584 & 1.94161 \tabularnewline
254 & 33 & 34.2519 & -1.25191 \tabularnewline
255 & 37 & 32.2892 & 4.71078 \tabularnewline
256 & 34 & 32.8039 & 1.19609 \tabularnewline
257 & 35 & 34.6212 & 0.378806 \tabularnewline
258 & 31 & 32.6358 & -1.63579 \tabularnewline
259 & 37 & 34.9452 & 2.05483 \tabularnewline
260 & 35 & 31.9384 & 3.06155 \tabularnewline
261 & 27 & 31.6518 & -4.65175 \tabularnewline
262 & 34 & 32.8442 & 1.1558 \tabularnewline
263 & 40 & 34.6263 & 5.3737 \tabularnewline
264 & 29 & 32.9206 & -3.92061 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&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]41[/C][C]36.1414[/C][C]4.85856[/C][/ROW]
[ROW][C]2[/C][C]39[/C][C]35.6809[/C][C]3.31915[/C][/ROW]
[ROW][C]3[/C][C]30[/C][C]34.6893[/C][C]-4.68931[/C][/ROW]
[ROW][C]4[/C][C]31[/C][C]34.579[/C][C]-3.57904[/C][/ROW]
[ROW][C]5[/C][C]34[/C][C]36.0647[/C][C]-2.06466[/C][/ROW]
[ROW][C]6[/C][C]35[/C][C]32.7051[/C][C]2.29494[/C][/ROW]
[ROW][C]7[/C][C]39[/C][C]35.4444[/C][C]3.55564[/C][/ROW]
[ROW][C]8[/C][C]34[/C][C]35.5624[/C][C]-1.56243[/C][/ROW]
[ROW][C]9[/C][C]36[/C][C]35.4201[/C][C]0.579946[/C][/ROW]
[ROW][C]10[/C][C]37[/C][C]35.1126[/C][C]1.88742[/C][/ROW]
[ROW][C]11[/C][C]38[/C][C]34.8884[/C][C]3.11156[/C][/ROW]
[ROW][C]12[/C][C]36[/C][C]34.9925[/C][C]1.00746[/C][/ROW]
[ROW][C]13[/C][C]38[/C][C]35.4514[/C][C]2.54856[/C][/ROW]
[ROW][C]14[/C][C]39[/C][C]37.4583[/C][C]1.54169[/C][/ROW]
[ROW][C]15[/C][C]33[/C][C]35.768[/C][C]-2.76796[/C][/ROW]
[ROW][C]16[/C][C]32[/C][C]33.814[/C][C]-1.81396[/C][/ROW]
[ROW][C]17[/C][C]36[/C][C]34.4853[/C][C]1.51469[/C][/ROW]
[ROW][C]18[/C][C]38[/C][C]37.4091[/C][C]0.590871[/C][/ROW]
[ROW][C]19[/C][C]39[/C][C]38.872[/C][C]0.127963[/C][/ROW]
[ROW][C]20[/C][C]32[/C][C]33.6465[/C][C]-1.64648[/C][/ROW]
[ROW][C]21[/C][C]32[/C][C]34.7854[/C][C]-2.78543[/C][/ROW]
[ROW][C]22[/C][C]31[/C][C]31.9161[/C][C]-0.916144[/C][/ROW]
[ROW][C]23[/C][C]39[/C][C]37.1712[/C][C]1.82878[/C][/ROW]
[ROW][C]24[/C][C]37[/C][C]37.3516[/C][C]-0.351612[/C][/ROW]
[ROW][C]25[/C][C]39[/C][C]34.6269[/C][C]4.37315[/C][/ROW]
[ROW][C]26[/C][C]41[/C][C]35.2855[/C][C]5.71445[/C][/ROW]
[ROW][C]27[/C][C]36[/C][C]34.5325[/C][C]1.46746[/C][/ROW]
[ROW][C]28[/C][C]33[/C][C]35.7098[/C][C]-2.70975[/C][/ROW]
[ROW][C]29[/C][C]33[/C][C]34.6427[/C][C]-1.64266[/C][/ROW]
[ROW][C]30[/C][C]34[/C][C]34.6849[/C][C]-0.684908[/C][/ROW]
[ROW][C]31[/C][C]31[/C][C]35.6355[/C][C]-4.63555[/C][/ROW]
[ROW][C]32[/C][C]27[/C][C]33.3161[/C][C]-6.31613[/C][/ROW]
[ROW][C]33[/C][C]37[/C][C]33.7619[/C][C]3.23807[/C][/ROW]
[ROW][C]34[/C][C]34[/C][C]35.0132[/C][C]-1.01317[/C][/ROW]
[ROW][C]35[/C][C]34[/C][C]33.3048[/C][C]0.695219[/C][/ROW]
[ROW][C]36[/C][C]32[/C][C]34.8792[/C][C]-2.87917[/C][/ROW]
[ROW][C]37[/C][C]29[/C][C]32.7763[/C][C]-3.77626[/C][/ROW]
[ROW][C]38[/C][C]36[/C][C]35.4038[/C][C]0.596158[/C][/ROW]
[ROW][C]39[/C][C]29[/C][C]33.2297[/C][C]-4.22969[/C][/ROW]
[ROW][C]40[/C][C]35[/C][C]34.3762[/C][C]0.623757[/C][/ROW]
[ROW][C]41[/C][C]37[/C][C]34.8324[/C][C]2.16757[/C][/ROW]
[ROW][C]42[/C][C]34[/C][C]33.993[/C][C]0.00699075[/C][/ROW]
[ROW][C]43[/C][C]38[/C][C]35.7057[/C][C]2.29427[/C][/ROW]
[ROW][C]44[/C][C]35[/C][C]33.6338[/C][C]1.36615[/C][/ROW]
[ROW][C]45[/C][C]38[/C][C]32.3887[/C][C]5.61126[/C][/ROW]
[ROW][C]46[/C][C]37[/C][C]32.687[/C][C]4.31303[/C][/ROW]
[ROW][C]47[/C][C]38[/C][C]37.9263[/C][C]0.0737171[/C][/ROW]
[ROW][C]48[/C][C]33[/C][C]35.2839[/C][C]-2.28386[/C][/ROW]
[ROW][C]49[/C][C]36[/C][C]36.4052[/C][C]-0.405206[/C][/ROW]
[ROW][C]50[/C][C]38[/C][C]35.0266[/C][C]2.97336[/C][/ROW]
[ROW][C]51[/C][C]32[/C][C]35.8517[/C][C]-3.85167[/C][/ROW]
[ROW][C]52[/C][C]32[/C][C]32.5645[/C][C]-0.564475[/C][/ROW]
[ROW][C]53[/C][C]32[/C][C]33.8943[/C][C]-1.89435[/C][/ROW]
[ROW][C]54[/C][C]34[/C][C]37.2408[/C][C]-3.24083[/C][/ROW]
[ROW][C]55[/C][C]32[/C][C]35.318[/C][C]-3.31802[/C][/ROW]
[ROW][C]56[/C][C]37[/C][C]35.5207[/C][C]1.4793[/C][/ROW]
[ROW][C]57[/C][C]39[/C][C]34.9834[/C][C]4.0166[/C][/ROW]
[ROW][C]58[/C][C]29[/C][C]33.2011[/C][C]-4.2011[/C][/ROW]
[ROW][C]59[/C][C]37[/C][C]36.3687[/C][C]0.631342[/C][/ROW]
[ROW][C]60[/C][C]35[/C][C]35.1643[/C][C]-0.164284[/C][/ROW]
[ROW][C]61[/C][C]30[/C][C]31.74[/C][C]-1.73996[/C][/ROW]
[ROW][C]62[/C][C]38[/C][C]35.8972[/C][C]2.10285[/C][/ROW]
[ROW][C]63[/C][C]34[/C][C]34.4979[/C][C]-0.49789[/C][/ROW]
[ROW][C]64[/C][C]31[/C][C]34.3194[/C][C]-3.31938[/C][/ROW]
[ROW][C]65[/C][C]34[/C][C]33.6124[/C][C]0.387629[/C][/ROW]
[ROW][C]66[/C][C]35[/C][C]35.8181[/C][C]-0.818071[/C][/ROW]
[ROW][C]67[/C][C]36[/C][C]36.4075[/C][C]-0.407505[/C][/ROW]
[ROW][C]68[/C][C]30[/C][C]30.919[/C][C]-0.919045[/C][/ROW]
[ROW][C]69[/C][C]39[/C][C]36.3838[/C][C]2.61617[/C][/ROW]
[ROW][C]70[/C][C]35[/C][C]33.6039[/C][C]1.39607[/C][/ROW]
[ROW][C]71[/C][C]38[/C][C]35.9823[/C][C]2.01768[/C][/ROW]
[ROW][C]72[/C][C]31[/C][C]35.7025[/C][C]-4.70255[/C][/ROW]
[ROW][C]73[/C][C]34[/C][C]36.643[/C][C]-2.64304[/C][/ROW]
[ROW][C]74[/C][C]38[/C][C]38.276[/C][C]-0.27604[/C][/ROW]
[ROW][C]75[/C][C]34[/C][C]30.7441[/C][C]3.25587[/C][/ROW]
[ROW][C]76[/C][C]39[/C][C]32.5495[/C][C]6.45054[/C][/ROW]
[ROW][C]77[/C][C]37[/C][C]35.941[/C][C]1.05905[/C][/ROW]
[ROW][C]78[/C][C]34[/C][C]33.0273[/C][C]0.972657[/C][/ROW]
[ROW][C]79[/C][C]28[/C][C]34.5929[/C][C]-6.59287[/C][/ROW]
[ROW][C]80[/C][C]37[/C][C]30.8324[/C][C]6.1676[/C][/ROW]
[ROW][C]81[/C][C]33[/C][C]35.2066[/C][C]-2.20658[/C][/ROW]
[ROW][C]82[/C][C]35[/C][C]34.0891[/C][C]0.910897[/C][/ROW]
[ROW][C]83[/C][C]37[/C][C]34.3354[/C][C]2.66461[/C][/ROW]
[ROW][C]84[/C][C]32[/C][C]34.5718[/C][C]-2.57178[/C][/ROW]
[ROW][C]85[/C][C]33[/C][C]33.4504[/C][C]-0.450383[/C][/ROW]
[ROW][C]86[/C][C]38[/C][C]37.6547[/C][C]0.345283[/C][/ROW]
[ROW][C]87[/C][C]33[/C][C]33.5412[/C][C]-0.54124[/C][/ROW]
[ROW][C]88[/C][C]29[/C][C]32.645[/C][C]-3.64503[/C][/ROW]
[ROW][C]89[/C][C]33[/C][C]33.7737[/C][C]-0.773661[/C][/ROW]
[ROW][C]90[/C][C]31[/C][C]35.2077[/C][C]-4.20773[/C][/ROW]
[ROW][C]91[/C][C]36[/C][C]34.5208[/C][C]1.47925[/C][/ROW]
[ROW][C]92[/C][C]35[/C][C]37.0536[/C][C]-2.05357[/C][/ROW]
[ROW][C]93[/C][C]32[/C][C]31.5517[/C][C]0.448272[/C][/ROW]
[ROW][C]94[/C][C]29[/C][C]30.3559[/C][C]-1.35585[/C][/ROW]
[ROW][C]95[/C][C]39[/C][C]36.0475[/C][C]2.95247[/C][/ROW]
[ROW][C]96[/C][C]37[/C][C]34.7603[/C][C]2.23971[/C][/ROW]
[ROW][C]97[/C][C]35[/C][C]33.4268[/C][C]1.57321[/C][/ROW]
[ROW][C]98[/C][C]37[/C][C]35.5292[/C][C]1.47078[/C][/ROW]
[ROW][C]99[/C][C]32[/C][C]34.5968[/C][C]-2.59678[/C][/ROW]
[ROW][C]100[/C][C]38[/C][C]34.6997[/C][C]3.3003[/C][/ROW]
[ROW][C]101[/C][C]37[/C][C]35.1703[/C][C]1.8297[/C][/ROW]
[ROW][C]102[/C][C]36[/C][C]35.9398[/C][C]0.0602105[/C][/ROW]
[ROW][C]103[/C][C]32[/C][C]33.6075[/C][C]-1.60752[/C][/ROW]
[ROW][C]104[/C][C]33[/C][C]36.1459[/C][C]-3.14586[/C][/ROW]
[ROW][C]105[/C][C]40[/C][C]32.7964[/C][C]7.20363[/C][/ROW]
[ROW][C]106[/C][C]38[/C][C]33.1716[/C][C]4.8284[/C][/ROW]
[ROW][C]107[/C][C]41[/C][C]36.9272[/C][C]4.07281[/C][/ROW]
[ROW][C]108[/C][C]36[/C][C]34.5329[/C][C]1.46709[/C][/ROW]
[ROW][C]109[/C][C]43[/C][C]37.1675[/C][C]5.83251[/C][/ROW]
[ROW][C]110[/C][C]30[/C][C]35.667[/C][C]-5.66705[/C][/ROW]
[ROW][C]111[/C][C]31[/C][C]32.7323[/C][C]-1.73226[/C][/ROW]
[ROW][C]112[/C][C]32[/C][C]37.7601[/C][C]-5.76013[/C][/ROW]
[ROW][C]113[/C][C]32[/C][C]31.6656[/C][C]0.334404[/C][/ROW]
[ROW][C]114[/C][C]37[/C][C]34.2298[/C][C]2.77023[/C][/ROW]
[ROW][C]115[/C][C]37[/C][C]35.7433[/C][C]1.25673[/C][/ROW]
[ROW][C]116[/C][C]33[/C][C]35.9178[/C][C]-2.9178[/C][/ROW]
[ROW][C]117[/C][C]34[/C][C]37.4182[/C][C]-3.41819[/C][/ROW]
[ROW][C]118[/C][C]33[/C][C]32.7247[/C][C]0.275251[/C][/ROW]
[ROW][C]119[/C][C]38[/C][C]36.1213[/C][C]1.87875[/C][/ROW]
[ROW][C]120[/C][C]33[/C][C]35.1168[/C][C]-2.11679[/C][/ROW]
[ROW][C]121[/C][C]31[/C][C]31.2956[/C][C]-0.295585[/C][/ROW]
[ROW][C]122[/C][C]38[/C][C]37.7048[/C][C]0.295184[/C][/ROW]
[ROW][C]123[/C][C]37[/C][C]35.4763[/C][C]1.52365[/C][/ROW]
[ROW][C]124[/C][C]36[/C][C]32.637[/C][C]3.36305[/C][/ROW]
[ROW][C]125[/C][C]31[/C][C]34.0579[/C][C]-3.05785[/C][/ROW]
[ROW][C]126[/C][C]39[/C][C]34.0297[/C][C]4.97032[/C][/ROW]
[ROW][C]127[/C][C]44[/C][C]38.3683[/C][C]5.63169[/C][/ROW]
[ROW][C]128[/C][C]33[/C][C]35.8114[/C][C]-2.81136[/C][/ROW]
[ROW][C]129[/C][C]35[/C][C]33.6412[/C][C]1.35877[/C][/ROW]
[ROW][C]130[/C][C]32[/C][C]32.0001[/C][C]-7.52564e-05[/C][/ROW]
[ROW][C]131[/C][C]28[/C][C]33.1292[/C][C]-5.12922[/C][/ROW]
[ROW][C]132[/C][C]40[/C][C]36.2328[/C][C]3.7672[/C][/ROW]
[ROW][C]133[/C][C]27[/C][C]32.21[/C][C]-5.21004[/C][/ROW]
[ROW][C]134[/C][C]37[/C][C]37.1333[/C][C]-0.13334[/C][/ROW]
[ROW][C]135[/C][C]32[/C][C]31.6573[/C][C]0.342702[/C][/ROW]
[ROW][C]136[/C][C]28[/C][C]27.9061[/C][C]0.0939443[/C][/ROW]
[ROW][C]137[/C][C]34[/C][C]35.3237[/C][C]-1.32365[/C][/ROW]
[ROW][C]138[/C][C]30[/C][C]34.0631[/C][C]-4.06307[/C][/ROW]
[ROW][C]139[/C][C]35[/C][C]36.0214[/C][C]-1.0214[/C][/ROW]
[ROW][C]140[/C][C]31[/C][C]34.0761[/C][C]-3.07611[/C][/ROW]
[ROW][C]141[/C][C]32[/C][C]34.4354[/C][C]-2.43538[/C][/ROW]
[ROW][C]142[/C][C]30[/C][C]34.0061[/C][C]-4.00614[/C][/ROW]
[ROW][C]143[/C][C]30[/C][C]35.5892[/C][C]-5.58923[/C][/ROW]
[ROW][C]144[/C][C]31[/C][C]29.8119[/C][C]1.18813[/C][/ROW]
[ROW][C]145[/C][C]40[/C][C]33.4597[/C][C]6.54032[/C][/ROW]
[ROW][C]146[/C][C]32[/C][C]32.6556[/C][C]-0.655575[/C][/ROW]
[ROW][C]147[/C][C]36[/C][C]34.0165[/C][C]1.98348[/C][/ROW]
[ROW][C]148[/C][C]32[/C][C]32.7973[/C][C]-0.797343[/C][/ROW]
[ROW][C]149[/C][C]35[/C][C]33.7178[/C][C]1.28218[/C][/ROW]
[ROW][C]150[/C][C]38[/C][C]36.693[/C][C]1.30702[/C][/ROW]
[ROW][C]151[/C][C]42[/C][C]36.8962[/C][C]5.10378[/C][/ROW]
[ROW][C]152[/C][C]34[/C][C]35.8355[/C][C]-1.83552[/C][/ROW]
[ROW][C]153[/C][C]35[/C][C]37.0546[/C][C]-2.05455[/C][/ROW]
[ROW][C]154[/C][C]38[/C][C]32.8249[/C][C]5.17507[/C][/ROW]
[ROW][C]155[/C][C]33[/C][C]33.7761[/C][C]-0.776098[/C][/ROW]
[ROW][C]156[/C][C]36[/C][C]32.9215[/C][C]3.07846[/C][/ROW]
[ROW][C]157[/C][C]32[/C][C]35.9477[/C][C]-3.94772[/C][/ROW]
[ROW][C]158[/C][C]33[/C][C]37.1625[/C][C]-4.16246[/C][/ROW]
[ROW][C]159[/C][C]34[/C][C]33.1197[/C][C]0.880283[/C][/ROW]
[ROW][C]160[/C][C]32[/C][C]35.4913[/C][C]-3.49131[/C][/ROW]
[ROW][C]161[/C][C]34[/C][C]35.8984[/C][C]-1.89843[/C][/ROW]
[ROW][C]162[/C][C]27[/C][C]29.7751[/C][C]-2.77512[/C][/ROW]
[ROW][C]163[/C][C]31[/C][C]31.7857[/C][C]-0.78568[/C][/ROW]
[ROW][C]164[/C][C]38[/C][C]32.8082[/C][C]5.19176[/C][/ROW]
[ROW][C]165[/C][C]34[/C][C]35.6487[/C][C]-1.64871[/C][/ROW]
[ROW][C]166[/C][C]24[/C][C]29.0334[/C][C]-5.03343[/C][/ROW]
[ROW][C]167[/C][C]30[/C][C]34.0573[/C][C]-4.05734[/C][/ROW]
[ROW][C]168[/C][C]26[/C][C]29.3839[/C][C]-3.38393[/C][/ROW]
[ROW][C]169[/C][C]34[/C][C]35.345[/C][C]-1.345[/C][/ROW]
[ROW][C]170[/C][C]27[/C][C]35.4246[/C][C]-8.4246[/C][/ROW]
[ROW][C]171[/C][C]37[/C][C]31.2818[/C][C]5.71819[/C][/ROW]
[ROW][C]172[/C][C]36[/C][C]34.7005[/C][C]1.29947[/C][/ROW]
[ROW][C]173[/C][C]41[/C][C]34.4184[/C][C]6.58163[/C][/ROW]
[ROW][C]174[/C][C]29[/C][C]28.9179[/C][C]0.0820718[/C][/ROW]
[ROW][C]175[/C][C]36[/C][C]32.4593[/C][C]3.5407[/C][/ROW]
[ROW][C]176[/C][C]32[/C][C]33.6795[/C][C]-1.67954[/C][/ROW]
[ROW][C]177[/C][C]37[/C][C]33.2704[/C][C]3.72957[/C][/ROW]
[ROW][C]178[/C][C]30[/C][C]29.5084[/C][C]0.491608[/C][/ROW]
[ROW][C]179[/C][C]31[/C][C]33.089[/C][C]-2.08905[/C][/ROW]
[ROW][C]180[/C][C]38[/C][C]34.6512[/C][C]3.34878[/C][/ROW]
[ROW][C]181[/C][C]36[/C][C]34.3826[/C][C]1.61737[/C][/ROW]
[ROW][C]182[/C][C]35[/C][C]33.2321[/C][C]1.76787[/C][/ROW]
[ROW][C]183[/C][C]31[/C][C]34.0097[/C][C]-3.00973[/C][/ROW]
[ROW][C]184[/C][C]38[/C][C]32.5775[/C][C]5.42254[/C][/ROW]
[ROW][C]185[/C][C]22[/C][C]31.3046[/C][C]-9.30459[/C][/ROW]
[ROW][C]186[/C][C]32[/C][C]33.9394[/C][C]-1.93936[/C][/ROW]
[ROW][C]187[/C][C]36[/C][C]35.2839[/C][C]0.716064[/C][/ROW]
[ROW][C]188[/C][C]39[/C][C]32.4168[/C][C]6.58318[/C][/ROW]
[ROW][C]189[/C][C]28[/C][C]30.3106[/C][C]-2.31056[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]32.424[/C][C]-0.424009[/C][/ROW]
[ROW][C]191[/C][C]32[/C][C]32.6798[/C][C]-0.67984[/C][/ROW]
[ROW][C]192[/C][C]38[/C][C]36.4155[/C][C]1.58445[/C][/ROW]
[ROW][C]193[/C][C]32[/C][C]33.6439[/C][C]-1.6439[/C][/ROW]
[ROW][C]194[/C][C]35[/C][C]36.2219[/C][C]-1.2219[/C][/ROW]
[ROW][C]195[/C][C]32[/C][C]31.9228[/C][C]0.0772074[/C][/ROW]
[ROW][C]196[/C][C]37[/C][C]35.1225[/C][C]1.87754[/C][/ROW]
[ROW][C]197[/C][C]34[/C][C]32.8862[/C][C]1.1138[/C][/ROW]
[ROW][C]198[/C][C]33[/C][C]35.0742[/C][C]-2.0742[/C][/ROW]
[ROW][C]199[/C][C]33[/C][C]34.4242[/C][C]-1.42416[/C][/ROW]
[ROW][C]200[/C][C]26[/C][C]32.2369[/C][C]-6.23692[/C][/ROW]
[ROW][C]201[/C][C]30[/C][C]31.9784[/C][C]-1.97838[/C][/ROW]
[ROW][C]202[/C][C]24[/C][C]29.7166[/C][C]-5.71663[/C][/ROW]
[ROW][C]203[/C][C]34[/C][C]32.5026[/C][C]1.4974[/C][/ROW]
[ROW][C]204[/C][C]34[/C][C]32.4497[/C][C]1.55027[/C][/ROW]
[ROW][C]205[/C][C]33[/C][C]34.0202[/C][C]-1.02018[/C][/ROW]
[ROW][C]206[/C][C]34[/C][C]35.6526[/C][C]-1.65262[/C][/ROW]
[ROW][C]207[/C][C]35[/C][C]35.0189[/C][C]-0.0188583[/C][/ROW]
[ROW][C]208[/C][C]35[/C][C]33.5601[/C][C]1.43985[/C][/ROW]
[ROW][C]209[/C][C]36[/C][C]33.4172[/C][C]2.58283[/C][/ROW]
[ROW][C]210[/C][C]34[/C][C]33.3422[/C][C]0.65776[/C][/ROW]
[ROW][C]211[/C][C]34[/C][C]34.328[/C][C]-0.327955[/C][/ROW]
[ROW][C]212[/C][C]41[/C][C]37.9113[/C][C]3.0887[/C][/ROW]
[ROW][C]213[/C][C]32[/C][C]36.0713[/C][C]-4.07126[/C][/ROW]
[ROW][C]214[/C][C]30[/C][C]31.3747[/C][C]-1.37466[/C][/ROW]
[ROW][C]215[/C][C]35[/C][C]34.3241[/C][C]0.675886[/C][/ROW]
[ROW][C]216[/C][C]28[/C][C]29.9644[/C][C]-1.96438[/C][/ROW]
[ROW][C]217[/C][C]33[/C][C]34.7744[/C][C]-1.77441[/C][/ROW]
[ROW][C]218[/C][C]39[/C][C]35.207[/C][C]3.793[/C][/ROW]
[ROW][C]219[/C][C]36[/C][C]32.5935[/C][C]3.40648[/C][/ROW]
[ROW][C]220[/C][C]36[/C][C]35.7918[/C][C]0.208225[/C][/ROW]
[ROW][C]221[/C][C]35[/C][C]33.4019[/C][C]1.59814[/C][/ROW]
[ROW][C]222[/C][C]38[/C][C]33.5659[/C][C]4.43407[/C][/ROW]
[ROW][C]223[/C][C]33[/C][C]34.2128[/C][C]-1.21284[/C][/ROW]
[ROW][C]224[/C][C]31[/C][C]32.5913[/C][C]-1.59127[/C][/ROW]
[ROW][C]225[/C][C]34[/C][C]31.8558[/C][C]2.14419[/C][/ROW]
[ROW][C]226[/C][C]32[/C][C]32.4493[/C][C]-0.449297[/C][/ROW]
[ROW][C]227[/C][C]31[/C][C]33.1412[/C][C]-2.1412[/C][/ROW]
[ROW][C]228[/C][C]33[/C][C]33.1687[/C][C]-0.16868[/C][/ROW]
[ROW][C]229[/C][C]34[/C][C]32.7769[/C][C]1.2231[/C][/ROW]
[ROW][C]230[/C][C]34[/C][C]35.0638[/C][C]-1.06378[/C][/ROW]
[ROW][C]231[/C][C]34[/C][C]31.3911[/C][C]2.60888[/C][/ROW]
[ROW][C]232[/C][C]33[/C][C]34.7983[/C][C]-1.79826[/C][/ROW]
[ROW][C]233[/C][C]32[/C][C]34.5143[/C][C]-2.51434[/C][/ROW]
[ROW][C]234[/C][C]41[/C][C]33.1745[/C][C]7.82554[/C][/ROW]
[ROW][C]235[/C][C]34[/C][C]34.5684[/C][C]-0.568403[/C][/ROW]
[ROW][C]236[/C][C]36[/C][C]31.7191[/C][C]4.2809[/C][/ROW]
[ROW][C]237[/C][C]37[/C][C]31.7733[/C][C]5.22671[/C][/ROW]
[ROW][C]238[/C][C]36[/C][C]28.2529[/C][C]7.74711[/C][/ROW]
[ROW][C]239[/C][C]29[/C][C]32.935[/C][C]-3.93495[/C][/ROW]
[ROW][C]240[/C][C]37[/C][C]32.0246[/C][C]4.97544[/C][/ROW]
[ROW][C]241[/C][C]27[/C][C]33.2567[/C][C]-6.25668[/C][/ROW]
[ROW][C]242[/C][C]35[/C][C]34.4105[/C][C]0.589503[/C][/ROW]
[ROW][C]243[/C][C]28[/C][C]30.0396[/C][C]-2.03957[/C][/ROW]
[ROW][C]244[/C][C]35[/C][C]32.7966[/C][C]2.20339[/C][/ROW]
[ROW][C]245[/C][C]37[/C][C]33.3562[/C][C]3.64376[/C][/ROW]
[ROW][C]246[/C][C]29[/C][C]33.5336[/C][C]-4.53359[/C][/ROW]
[ROW][C]247[/C][C]32[/C][C]35.859[/C][C]-3.85902[/C][/ROW]
[ROW][C]248[/C][C]36[/C][C]31.4271[/C][C]4.57289[/C][/ROW]
[ROW][C]249[/C][C]19[/C][C]27.6124[/C][C]-8.61238[/C][/ROW]
[ROW][C]250[/C][C]21[/C][C]24.6901[/C][C]-3.69013[/C][/ROW]
[ROW][C]251[/C][C]31[/C][C]34.077[/C][C]-3.077[/C][/ROW]
[ROW][C]252[/C][C]33[/C][C]32.6993[/C][C]0.300655[/C][/ROW]
[ROW][C]253[/C][C]36[/C][C]34.0584[/C][C]1.94161[/C][/ROW]
[ROW][C]254[/C][C]33[/C][C]34.2519[/C][C]-1.25191[/C][/ROW]
[ROW][C]255[/C][C]37[/C][C]32.2892[/C][C]4.71078[/C][/ROW]
[ROW][C]256[/C][C]34[/C][C]32.8039[/C][C]1.19609[/C][/ROW]
[ROW][C]257[/C][C]35[/C][C]34.6212[/C][C]0.378806[/C][/ROW]
[ROW][C]258[/C][C]31[/C][C]32.6358[/C][C]-1.63579[/C][/ROW]
[ROW][C]259[/C][C]37[/C][C]34.9452[/C][C]2.05483[/C][/ROW]
[ROW][C]260[/C][C]35[/C][C]31.9384[/C][C]3.06155[/C][/ROW]
[ROW][C]261[/C][C]27[/C][C]31.6518[/C][C]-4.65175[/C][/ROW]
[ROW][C]262[/C][C]34[/C][C]32.8442[/C][C]1.1558[/C][/ROW]
[ROW][C]263[/C][C]40[/C][C]34.6263[/C][C]5.3737[/C][/ROW]
[ROW][C]264[/C][C]29[/C][C]32.9206[/C][C]-3.92061[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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
14136.14144.85856
23935.68093.31915
33034.6893-4.68931
43134.579-3.57904
53436.0647-2.06466
63532.70512.29494
73935.44443.55564
83435.5624-1.56243
93635.42010.579946
103735.11261.88742
113834.88843.11156
123634.99251.00746
133835.45142.54856
143937.45831.54169
153335.768-2.76796
163233.814-1.81396
173634.48531.51469
183837.40910.590871
193938.8720.127963
203233.6465-1.64648
213234.7854-2.78543
223131.9161-0.916144
233937.17121.82878
243737.3516-0.351612
253934.62694.37315
264135.28555.71445
273634.53251.46746
283335.7098-2.70975
293334.6427-1.64266
303434.6849-0.684908
313135.6355-4.63555
322733.3161-6.31613
333733.76193.23807
343435.0132-1.01317
353433.30480.695219
363234.8792-2.87917
372932.7763-3.77626
383635.40380.596158
392933.2297-4.22969
403534.37620.623757
413734.83242.16757
423433.9930.00699075
433835.70572.29427
443533.63381.36615
453832.38875.61126
463732.6874.31303
473837.92630.0737171
483335.2839-2.28386
493636.4052-0.405206
503835.02662.97336
513235.8517-3.85167
523232.5645-0.564475
533233.8943-1.89435
543437.2408-3.24083
553235.318-3.31802
563735.52071.4793
573934.98344.0166
582933.2011-4.2011
593736.36870.631342
603535.1643-0.164284
613031.74-1.73996
623835.89722.10285
633434.4979-0.49789
643134.3194-3.31938
653433.61240.387629
663535.8181-0.818071
673636.4075-0.407505
683030.919-0.919045
693936.38382.61617
703533.60391.39607
713835.98232.01768
723135.7025-4.70255
733436.643-2.64304
743838.276-0.27604
753430.74413.25587
763932.54956.45054
773735.9411.05905
783433.02730.972657
792834.5929-6.59287
803730.83246.1676
813335.2066-2.20658
823534.08910.910897
833734.33542.66461
843234.5718-2.57178
853333.4504-0.450383
863837.65470.345283
873333.5412-0.54124
882932.645-3.64503
893333.7737-0.773661
903135.2077-4.20773
913634.52081.47925
923537.0536-2.05357
933231.55170.448272
942930.3559-1.35585
953936.04752.95247
963734.76032.23971
973533.42681.57321
983735.52921.47078
993234.5968-2.59678
1003834.69973.3003
1013735.17031.8297
1023635.93980.0602105
1033233.6075-1.60752
1043336.1459-3.14586
1054032.79647.20363
1063833.17164.8284
1074136.92724.07281
1083634.53291.46709
1094337.16755.83251
1103035.667-5.66705
1113132.7323-1.73226
1123237.7601-5.76013
1133231.66560.334404
1143734.22982.77023
1153735.74331.25673
1163335.9178-2.9178
1173437.4182-3.41819
1183332.72470.275251
1193836.12131.87875
1203335.1168-2.11679
1213131.2956-0.295585
1223837.70480.295184
1233735.47631.52365
1243632.6373.36305
1253134.0579-3.05785
1263934.02974.97032
1274438.36835.63169
1283335.8114-2.81136
1293533.64121.35877
1303232.0001-7.52564e-05
1312833.1292-5.12922
1324036.23283.7672
1332732.21-5.21004
1343737.1333-0.13334
1353231.65730.342702
1362827.90610.0939443
1373435.3237-1.32365
1383034.0631-4.06307
1393536.0214-1.0214
1403134.0761-3.07611
1413234.4354-2.43538
1423034.0061-4.00614
1433035.5892-5.58923
1443129.81191.18813
1454033.45976.54032
1463232.6556-0.655575
1473634.01651.98348
1483232.7973-0.797343
1493533.71781.28218
1503836.6931.30702
1514236.89625.10378
1523435.8355-1.83552
1533537.0546-2.05455
1543832.82495.17507
1553333.7761-0.776098
1563632.92153.07846
1573235.9477-3.94772
1583337.1625-4.16246
1593433.11970.880283
1603235.4913-3.49131
1613435.8984-1.89843
1622729.7751-2.77512
1633131.7857-0.78568
1643832.80825.19176
1653435.6487-1.64871
1662429.0334-5.03343
1673034.0573-4.05734
1682629.3839-3.38393
1693435.345-1.345
1702735.4246-8.4246
1713731.28185.71819
1723634.70051.29947
1734134.41846.58163
1742928.91790.0820718
1753632.45933.5407
1763233.6795-1.67954
1773733.27043.72957
1783029.50840.491608
1793133.089-2.08905
1803834.65123.34878
1813634.38261.61737
1823533.23211.76787
1833134.0097-3.00973
1843832.57755.42254
1852231.3046-9.30459
1863233.9394-1.93936
1873635.28390.716064
1883932.41686.58318
1892830.3106-2.31056
1903232.424-0.424009
1913232.6798-0.67984
1923836.41551.58445
1933233.6439-1.6439
1943536.2219-1.2219
1953231.92280.0772074
1963735.12251.87754
1973432.88621.1138
1983335.0742-2.0742
1993334.4242-1.42416
2002632.2369-6.23692
2013031.9784-1.97838
2022429.7166-5.71663
2033432.50261.4974
2043432.44971.55027
2053334.0202-1.02018
2063435.6526-1.65262
2073535.0189-0.0188583
2083533.56011.43985
2093633.41722.58283
2103433.34220.65776
2113434.328-0.327955
2124137.91133.0887
2133236.0713-4.07126
2143031.3747-1.37466
2153534.32410.675886
2162829.9644-1.96438
2173334.7744-1.77441
2183935.2073.793
2193632.59353.40648
2203635.79180.208225
2213533.40191.59814
2223833.56594.43407
2233334.2128-1.21284
2243132.5913-1.59127
2253431.85582.14419
2263232.4493-0.449297
2273133.1412-2.1412
2283333.1687-0.16868
2293432.77691.2231
2303435.0638-1.06378
2313431.39112.60888
2323334.7983-1.79826
2333234.5143-2.51434
2344133.17457.82554
2353434.5684-0.568403
2363631.71914.2809
2373731.77335.22671
2383628.25297.74711
2392932.935-3.93495
2403732.02464.97544
2412733.2567-6.25668
2423534.41050.589503
2432830.0396-2.03957
2443532.79662.20339
2453733.35623.64376
2462933.5336-4.53359
2473235.859-3.85902
2483631.42714.57289
2491927.6124-8.61238
2502124.6901-3.69013
2513134.077-3.077
2523332.69930.300655
2533634.05841.94161
2543334.2519-1.25191
2553732.28924.71078
2563432.80391.19609
2573534.62120.378806
2583132.6358-1.63579
2593734.94522.05483
2603531.93843.06155
2612731.6518-4.65175
2623432.84421.1558
2634034.62635.3737
2642932.9206-3.92061






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
240.4140320.8280640.585968
250.2558850.5117690.744115
260.1682570.3365140.831743
270.09334890.1866980.906651
280.05691090.1138220.943089
290.04927360.09854720.950726
300.02540620.05081240.974594
310.1942350.3884690.805765
320.2424960.4849920.757504
330.2818730.5637470.718127
340.2140450.4280890.785955
350.1855340.3710680.814466
360.139940.2798790.86006
370.1959590.3919170.804041
380.1472890.2945780.852711
390.1132950.2265890.886705
400.1156860.2313720.884314
410.1017350.2034690.898265
420.07480050.1496010.925199
430.05408840.1081770.945912
440.07551710.1510340.924483
450.1217870.2435730.878213
460.1725840.3451670.827416
470.1405980.2811950.859402
480.1139620.2279240.886038
490.09960220.1992040.900398
500.08095710.1619140.919043
510.0642440.1284880.935756
520.05062430.1012490.949376
530.03814030.07628060.96186
540.02911780.05823550.970882
550.0222860.0445720.977714
560.0347930.0695860.965207
570.03208490.06416980.967915
580.05986850.1197370.940132
590.04614710.09229420.953853
600.03476110.06952210.965239
610.02983530.05967070.970165
620.02328330.04656650.976717
630.02151930.04303860.978481
640.01730180.03460360.982698
650.01277480.02554950.987225
660.009170960.01834190.990829
670.006794890.01358980.993205
680.005123810.01024760.994876
690.004802550.00960510.995197
700.003535410.007070830.996465
710.003401010.006802030.996599
720.004122280.008244550.995878
730.004780950.009561890.995219
740.004020690.008041380.995979
750.006408640.01281730.993591
760.01683330.03366660.983167
770.01335610.02671220.986644
780.009970310.01994060.99003
790.0197280.0394560.980272
800.03719410.07438820.962806
810.04372220.08744440.956278
820.03475150.06950290.965249
830.02923160.05846320.970768
840.02507350.0501470.974927
850.02161860.04323720.978381
860.01680070.03360140.983199
870.01314870.02629730.986851
880.01373920.02747840.986261
890.01053730.02107460.989463
900.01022510.02045030.989775
910.009008320.01801660.990992
920.007061770.01412350.992938
930.005932920.01186580.994067
940.004704290.009408570.995296
950.004093470.008186940.995907
960.004330260.008660520.99567
970.003375970.006751940.996624
980.002661620.005323240.997338
990.002152220.004304440.997848
1000.003184020.006368050.996816
1010.002618550.00523710.997381
1020.001905360.003810720.998095
1030.001450930.002901860.998549
1040.001205140.002410290.998795
1050.003905950.007811910.996094
1060.00543250.0108650.994567
1070.005958190.01191640.994042
1080.004753040.009506070.995247
1090.01070140.02140280.989299
1100.0249230.04984610.975077
1110.02062480.04124950.979375
1120.02662170.05324350.973378
1130.02190420.04380830.978096
1140.02510920.05021840.974891
1150.02215040.04430080.97785
1160.01978230.03956450.980218
1170.02175320.04350640.978247
1180.01726070.03452140.982739
1190.01536870.03073730.984631
1200.0134040.02680790.986596
1210.01183080.02366170.988169
1220.009570270.01914050.99043
1230.009802680.01960540.990197
1240.01121770.02243540.988782
1250.01058870.02117730.989411
1260.01680440.03360880.983196
1270.03193660.06387320.968063
1280.02877140.05754280.971229
1290.02497510.04995030.975025
1300.02155050.04310110.978449
1310.03029220.06058450.969708
1320.03285180.06570350.967148
1330.04387880.08775760.956121
1340.03590890.07181770.964091
1350.03021580.06043160.969784
1360.02424720.04849450.975753
1370.01998370.03996740.980016
1380.0231770.04635390.976823
1390.01915570.03831130.980844
1400.02014020.04028040.97986
1410.02297550.04595090.977025
1420.02470110.04940230.975299
1430.03703160.07406320.962968
1440.03150890.06301770.968491
1450.07456640.1491330.925434
1460.07031650.1406330.929684
1470.0716090.1432180.928391
1480.05953180.1190640.940468
1490.05162530.1032510.948375
1500.04550240.09100470.954498
1510.06701620.1340320.932984
1520.06165530.1233110.938345
1530.05692020.113840.94308
1540.09168420.1833680.908316
1550.07925360.1585070.920746
1560.08704020.174080.91296
1570.08454160.1690830.915458
1580.07992690.1598540.920073
1590.08099640.1619930.919004
1600.0692540.1385080.930746
1610.05720010.11440.9428
1620.05444520.108890.945555
1630.04568840.09137680.954312
1640.06824460.1364890.931755
1650.05923220.1184640.940768
1660.07816560.1563310.921834
1670.08020180.1604040.919798
1680.07503990.150080.92496
1690.06317470.1263490.936825
1700.14310.28620.8569
1710.1794770.3589550.820523
1720.1599590.3199180.840041
1730.2319380.4638760.768062
1740.2044070.4088140.795593
1750.2204870.4409730.779513
1760.2005220.4010430.799478
1770.2190940.4381880.780906
1780.1919930.3839860.808007
1790.1720150.3440290.827985
1800.1667370.3334750.833263
1810.1479040.2958080.852096
1820.1355370.2710750.864463
1830.1345810.2691630.865419
1840.202130.404260.79787
1850.4951510.9903010.504849
1860.4806580.9613160.519342
1870.4672420.9344840.532758
1880.6519350.696130.348065
1890.6220490.7559020.377951
1900.5804150.8391690.419585
1910.5416510.9166980.458349
1920.5069330.9861350.493067
1930.4683210.9366410.531679
1940.4310640.8621270.568936
1950.400310.800620.59969
1960.368420.736840.63158
1970.3388860.6777730.661114
1980.3196070.6392130.680393
1990.2816590.5633190.718341
2000.3491430.6982870.650857
2010.3164710.6329420.683529
2020.3762740.7525480.623726
2030.3400050.6800110.659995
2040.3095010.6190020.690499
2050.2720240.5440470.727976
2060.2445080.4890160.755492
2070.2173610.4347210.782639
2080.1845620.3691230.815438
2090.1605630.3211260.839437
2100.1313580.2627170.868642
2110.1106790.2213580.889321
2120.1018910.2037830.898109
2130.1003870.2007730.899613
2140.07934550.1586910.920655
2150.06142340.1228470.938577
2160.05140920.1028180.948591
2170.03918940.07837890.960811
2180.04386620.08773240.956134
2190.03468840.06937670.965312
2200.02555220.05110440.974448
2210.01902620.03805240.980974
2220.01828050.03656110.981719
2230.01293220.02586440.987068
2240.01345920.02691840.986541
2250.05160410.1032080.948396
2260.04328170.08656340.956718
2270.03195430.06390860.968046
2280.02642670.05285330.973573
2290.0177620.0355240.982238
2300.01126190.02252380.988738
2310.008016280.01603260.991984
2320.03401960.06803920.96598
2330.02944930.05889870.970551
2340.1326670.2653330.867333
2350.09127260.1825450.908727
2360.08802160.1760430.911978
2370.08334640.1666930.916654
2380.08925650.1785130.910744
2390.05071860.1014370.949281
2400.2029360.4058720.797064

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
24 & 0.414032 & 0.828064 & 0.585968 \tabularnewline
25 & 0.255885 & 0.511769 & 0.744115 \tabularnewline
26 & 0.168257 & 0.336514 & 0.831743 \tabularnewline
27 & 0.0933489 & 0.186698 & 0.906651 \tabularnewline
28 & 0.0569109 & 0.113822 & 0.943089 \tabularnewline
29 & 0.0492736 & 0.0985472 & 0.950726 \tabularnewline
30 & 0.0254062 & 0.0508124 & 0.974594 \tabularnewline
31 & 0.194235 & 0.388469 & 0.805765 \tabularnewline
32 & 0.242496 & 0.484992 & 0.757504 \tabularnewline
33 & 0.281873 & 0.563747 & 0.718127 \tabularnewline
34 & 0.214045 & 0.428089 & 0.785955 \tabularnewline
35 & 0.185534 & 0.371068 & 0.814466 \tabularnewline
36 & 0.13994 & 0.279879 & 0.86006 \tabularnewline
37 & 0.195959 & 0.391917 & 0.804041 \tabularnewline
38 & 0.147289 & 0.294578 & 0.852711 \tabularnewline
39 & 0.113295 & 0.226589 & 0.886705 \tabularnewline
40 & 0.115686 & 0.231372 & 0.884314 \tabularnewline
41 & 0.101735 & 0.203469 & 0.898265 \tabularnewline
42 & 0.0748005 & 0.149601 & 0.925199 \tabularnewline
43 & 0.0540884 & 0.108177 & 0.945912 \tabularnewline
44 & 0.0755171 & 0.151034 & 0.924483 \tabularnewline
45 & 0.121787 & 0.243573 & 0.878213 \tabularnewline
46 & 0.172584 & 0.345167 & 0.827416 \tabularnewline
47 & 0.140598 & 0.281195 & 0.859402 \tabularnewline
48 & 0.113962 & 0.227924 & 0.886038 \tabularnewline
49 & 0.0996022 & 0.199204 & 0.900398 \tabularnewline
50 & 0.0809571 & 0.161914 & 0.919043 \tabularnewline
51 & 0.064244 & 0.128488 & 0.935756 \tabularnewline
52 & 0.0506243 & 0.101249 & 0.949376 \tabularnewline
53 & 0.0381403 & 0.0762806 & 0.96186 \tabularnewline
54 & 0.0291178 & 0.0582355 & 0.970882 \tabularnewline
55 & 0.022286 & 0.044572 & 0.977714 \tabularnewline
56 & 0.034793 & 0.069586 & 0.965207 \tabularnewline
57 & 0.0320849 & 0.0641698 & 0.967915 \tabularnewline
58 & 0.0598685 & 0.119737 & 0.940132 \tabularnewline
59 & 0.0461471 & 0.0922942 & 0.953853 \tabularnewline
60 & 0.0347611 & 0.0695221 & 0.965239 \tabularnewline
61 & 0.0298353 & 0.0596707 & 0.970165 \tabularnewline
62 & 0.0232833 & 0.0465665 & 0.976717 \tabularnewline
63 & 0.0215193 & 0.0430386 & 0.978481 \tabularnewline
64 & 0.0173018 & 0.0346036 & 0.982698 \tabularnewline
65 & 0.0127748 & 0.0255495 & 0.987225 \tabularnewline
66 & 0.00917096 & 0.0183419 & 0.990829 \tabularnewline
67 & 0.00679489 & 0.0135898 & 0.993205 \tabularnewline
68 & 0.00512381 & 0.0102476 & 0.994876 \tabularnewline
69 & 0.00480255 & 0.0096051 & 0.995197 \tabularnewline
70 & 0.00353541 & 0.00707083 & 0.996465 \tabularnewline
71 & 0.00340101 & 0.00680203 & 0.996599 \tabularnewline
72 & 0.00412228 & 0.00824455 & 0.995878 \tabularnewline
73 & 0.00478095 & 0.00956189 & 0.995219 \tabularnewline
74 & 0.00402069 & 0.00804138 & 0.995979 \tabularnewline
75 & 0.00640864 & 0.0128173 & 0.993591 \tabularnewline
76 & 0.0168333 & 0.0336666 & 0.983167 \tabularnewline
77 & 0.0133561 & 0.0267122 & 0.986644 \tabularnewline
78 & 0.00997031 & 0.0199406 & 0.99003 \tabularnewline
79 & 0.019728 & 0.039456 & 0.980272 \tabularnewline
80 & 0.0371941 & 0.0743882 & 0.962806 \tabularnewline
81 & 0.0437222 & 0.0874444 & 0.956278 \tabularnewline
82 & 0.0347515 & 0.0695029 & 0.965249 \tabularnewline
83 & 0.0292316 & 0.0584632 & 0.970768 \tabularnewline
84 & 0.0250735 & 0.050147 & 0.974927 \tabularnewline
85 & 0.0216186 & 0.0432372 & 0.978381 \tabularnewline
86 & 0.0168007 & 0.0336014 & 0.983199 \tabularnewline
87 & 0.0131487 & 0.0262973 & 0.986851 \tabularnewline
88 & 0.0137392 & 0.0274784 & 0.986261 \tabularnewline
89 & 0.0105373 & 0.0210746 & 0.989463 \tabularnewline
90 & 0.0102251 & 0.0204503 & 0.989775 \tabularnewline
91 & 0.00900832 & 0.0180166 & 0.990992 \tabularnewline
92 & 0.00706177 & 0.0141235 & 0.992938 \tabularnewline
93 & 0.00593292 & 0.0118658 & 0.994067 \tabularnewline
94 & 0.00470429 & 0.00940857 & 0.995296 \tabularnewline
95 & 0.00409347 & 0.00818694 & 0.995907 \tabularnewline
96 & 0.00433026 & 0.00866052 & 0.99567 \tabularnewline
97 & 0.00337597 & 0.00675194 & 0.996624 \tabularnewline
98 & 0.00266162 & 0.00532324 & 0.997338 \tabularnewline
99 & 0.00215222 & 0.00430444 & 0.997848 \tabularnewline
100 & 0.00318402 & 0.00636805 & 0.996816 \tabularnewline
101 & 0.00261855 & 0.0052371 & 0.997381 \tabularnewline
102 & 0.00190536 & 0.00381072 & 0.998095 \tabularnewline
103 & 0.00145093 & 0.00290186 & 0.998549 \tabularnewline
104 & 0.00120514 & 0.00241029 & 0.998795 \tabularnewline
105 & 0.00390595 & 0.00781191 & 0.996094 \tabularnewline
106 & 0.0054325 & 0.010865 & 0.994567 \tabularnewline
107 & 0.00595819 & 0.0119164 & 0.994042 \tabularnewline
108 & 0.00475304 & 0.00950607 & 0.995247 \tabularnewline
109 & 0.0107014 & 0.0214028 & 0.989299 \tabularnewline
110 & 0.024923 & 0.0498461 & 0.975077 \tabularnewline
111 & 0.0206248 & 0.0412495 & 0.979375 \tabularnewline
112 & 0.0266217 & 0.0532435 & 0.973378 \tabularnewline
113 & 0.0219042 & 0.0438083 & 0.978096 \tabularnewline
114 & 0.0251092 & 0.0502184 & 0.974891 \tabularnewline
115 & 0.0221504 & 0.0443008 & 0.97785 \tabularnewline
116 & 0.0197823 & 0.0395645 & 0.980218 \tabularnewline
117 & 0.0217532 & 0.0435064 & 0.978247 \tabularnewline
118 & 0.0172607 & 0.0345214 & 0.982739 \tabularnewline
119 & 0.0153687 & 0.0307373 & 0.984631 \tabularnewline
120 & 0.013404 & 0.0268079 & 0.986596 \tabularnewline
121 & 0.0118308 & 0.0236617 & 0.988169 \tabularnewline
122 & 0.00957027 & 0.0191405 & 0.99043 \tabularnewline
123 & 0.00980268 & 0.0196054 & 0.990197 \tabularnewline
124 & 0.0112177 & 0.0224354 & 0.988782 \tabularnewline
125 & 0.0105887 & 0.0211773 & 0.989411 \tabularnewline
126 & 0.0168044 & 0.0336088 & 0.983196 \tabularnewline
127 & 0.0319366 & 0.0638732 & 0.968063 \tabularnewline
128 & 0.0287714 & 0.0575428 & 0.971229 \tabularnewline
129 & 0.0249751 & 0.0499503 & 0.975025 \tabularnewline
130 & 0.0215505 & 0.0431011 & 0.978449 \tabularnewline
131 & 0.0302922 & 0.0605845 & 0.969708 \tabularnewline
132 & 0.0328518 & 0.0657035 & 0.967148 \tabularnewline
133 & 0.0438788 & 0.0877576 & 0.956121 \tabularnewline
134 & 0.0359089 & 0.0718177 & 0.964091 \tabularnewline
135 & 0.0302158 & 0.0604316 & 0.969784 \tabularnewline
136 & 0.0242472 & 0.0484945 & 0.975753 \tabularnewline
137 & 0.0199837 & 0.0399674 & 0.980016 \tabularnewline
138 & 0.023177 & 0.0463539 & 0.976823 \tabularnewline
139 & 0.0191557 & 0.0383113 & 0.980844 \tabularnewline
140 & 0.0201402 & 0.0402804 & 0.97986 \tabularnewline
141 & 0.0229755 & 0.0459509 & 0.977025 \tabularnewline
142 & 0.0247011 & 0.0494023 & 0.975299 \tabularnewline
143 & 0.0370316 & 0.0740632 & 0.962968 \tabularnewline
144 & 0.0315089 & 0.0630177 & 0.968491 \tabularnewline
145 & 0.0745664 & 0.149133 & 0.925434 \tabularnewline
146 & 0.0703165 & 0.140633 & 0.929684 \tabularnewline
147 & 0.071609 & 0.143218 & 0.928391 \tabularnewline
148 & 0.0595318 & 0.119064 & 0.940468 \tabularnewline
149 & 0.0516253 & 0.103251 & 0.948375 \tabularnewline
150 & 0.0455024 & 0.0910047 & 0.954498 \tabularnewline
151 & 0.0670162 & 0.134032 & 0.932984 \tabularnewline
152 & 0.0616553 & 0.123311 & 0.938345 \tabularnewline
153 & 0.0569202 & 0.11384 & 0.94308 \tabularnewline
154 & 0.0916842 & 0.183368 & 0.908316 \tabularnewline
155 & 0.0792536 & 0.158507 & 0.920746 \tabularnewline
156 & 0.0870402 & 0.17408 & 0.91296 \tabularnewline
157 & 0.0845416 & 0.169083 & 0.915458 \tabularnewline
158 & 0.0799269 & 0.159854 & 0.920073 \tabularnewline
159 & 0.0809964 & 0.161993 & 0.919004 \tabularnewline
160 & 0.069254 & 0.138508 & 0.930746 \tabularnewline
161 & 0.0572001 & 0.1144 & 0.9428 \tabularnewline
162 & 0.0544452 & 0.10889 & 0.945555 \tabularnewline
163 & 0.0456884 & 0.0913768 & 0.954312 \tabularnewline
164 & 0.0682446 & 0.136489 & 0.931755 \tabularnewline
165 & 0.0592322 & 0.118464 & 0.940768 \tabularnewline
166 & 0.0781656 & 0.156331 & 0.921834 \tabularnewline
167 & 0.0802018 & 0.160404 & 0.919798 \tabularnewline
168 & 0.0750399 & 0.15008 & 0.92496 \tabularnewline
169 & 0.0631747 & 0.126349 & 0.936825 \tabularnewline
170 & 0.1431 & 0.2862 & 0.8569 \tabularnewline
171 & 0.179477 & 0.358955 & 0.820523 \tabularnewline
172 & 0.159959 & 0.319918 & 0.840041 \tabularnewline
173 & 0.231938 & 0.463876 & 0.768062 \tabularnewline
174 & 0.204407 & 0.408814 & 0.795593 \tabularnewline
175 & 0.220487 & 0.440973 & 0.779513 \tabularnewline
176 & 0.200522 & 0.401043 & 0.799478 \tabularnewline
177 & 0.219094 & 0.438188 & 0.780906 \tabularnewline
178 & 0.191993 & 0.383986 & 0.808007 \tabularnewline
179 & 0.172015 & 0.344029 & 0.827985 \tabularnewline
180 & 0.166737 & 0.333475 & 0.833263 \tabularnewline
181 & 0.147904 & 0.295808 & 0.852096 \tabularnewline
182 & 0.135537 & 0.271075 & 0.864463 \tabularnewline
183 & 0.134581 & 0.269163 & 0.865419 \tabularnewline
184 & 0.20213 & 0.40426 & 0.79787 \tabularnewline
185 & 0.495151 & 0.990301 & 0.504849 \tabularnewline
186 & 0.480658 & 0.961316 & 0.519342 \tabularnewline
187 & 0.467242 & 0.934484 & 0.532758 \tabularnewline
188 & 0.651935 & 0.69613 & 0.348065 \tabularnewline
189 & 0.622049 & 0.755902 & 0.377951 \tabularnewline
190 & 0.580415 & 0.839169 & 0.419585 \tabularnewline
191 & 0.541651 & 0.916698 & 0.458349 \tabularnewline
192 & 0.506933 & 0.986135 & 0.493067 \tabularnewline
193 & 0.468321 & 0.936641 & 0.531679 \tabularnewline
194 & 0.431064 & 0.862127 & 0.568936 \tabularnewline
195 & 0.40031 & 0.80062 & 0.59969 \tabularnewline
196 & 0.36842 & 0.73684 & 0.63158 \tabularnewline
197 & 0.338886 & 0.677773 & 0.661114 \tabularnewline
198 & 0.319607 & 0.639213 & 0.680393 \tabularnewline
199 & 0.281659 & 0.563319 & 0.718341 \tabularnewline
200 & 0.349143 & 0.698287 & 0.650857 \tabularnewline
201 & 0.316471 & 0.632942 & 0.683529 \tabularnewline
202 & 0.376274 & 0.752548 & 0.623726 \tabularnewline
203 & 0.340005 & 0.680011 & 0.659995 \tabularnewline
204 & 0.309501 & 0.619002 & 0.690499 \tabularnewline
205 & 0.272024 & 0.544047 & 0.727976 \tabularnewline
206 & 0.244508 & 0.489016 & 0.755492 \tabularnewline
207 & 0.217361 & 0.434721 & 0.782639 \tabularnewline
208 & 0.184562 & 0.369123 & 0.815438 \tabularnewline
209 & 0.160563 & 0.321126 & 0.839437 \tabularnewline
210 & 0.131358 & 0.262717 & 0.868642 \tabularnewline
211 & 0.110679 & 0.221358 & 0.889321 \tabularnewline
212 & 0.101891 & 0.203783 & 0.898109 \tabularnewline
213 & 0.100387 & 0.200773 & 0.899613 \tabularnewline
214 & 0.0793455 & 0.158691 & 0.920655 \tabularnewline
215 & 0.0614234 & 0.122847 & 0.938577 \tabularnewline
216 & 0.0514092 & 0.102818 & 0.948591 \tabularnewline
217 & 0.0391894 & 0.0783789 & 0.960811 \tabularnewline
218 & 0.0438662 & 0.0877324 & 0.956134 \tabularnewline
219 & 0.0346884 & 0.0693767 & 0.965312 \tabularnewline
220 & 0.0255522 & 0.0511044 & 0.974448 \tabularnewline
221 & 0.0190262 & 0.0380524 & 0.980974 \tabularnewline
222 & 0.0182805 & 0.0365611 & 0.981719 \tabularnewline
223 & 0.0129322 & 0.0258644 & 0.987068 \tabularnewline
224 & 0.0134592 & 0.0269184 & 0.986541 \tabularnewline
225 & 0.0516041 & 0.103208 & 0.948396 \tabularnewline
226 & 0.0432817 & 0.0865634 & 0.956718 \tabularnewline
227 & 0.0319543 & 0.0639086 & 0.968046 \tabularnewline
228 & 0.0264267 & 0.0528533 & 0.973573 \tabularnewline
229 & 0.017762 & 0.035524 & 0.982238 \tabularnewline
230 & 0.0112619 & 0.0225238 & 0.988738 \tabularnewline
231 & 0.00801628 & 0.0160326 & 0.991984 \tabularnewline
232 & 0.0340196 & 0.0680392 & 0.96598 \tabularnewline
233 & 0.0294493 & 0.0588987 & 0.970551 \tabularnewline
234 & 0.132667 & 0.265333 & 0.867333 \tabularnewline
235 & 0.0912726 & 0.182545 & 0.908727 \tabularnewline
236 & 0.0880216 & 0.176043 & 0.911978 \tabularnewline
237 & 0.0833464 & 0.166693 & 0.916654 \tabularnewline
238 & 0.0892565 & 0.178513 & 0.910744 \tabularnewline
239 & 0.0507186 & 0.101437 & 0.949281 \tabularnewline
240 & 0.202936 & 0.405872 & 0.797064 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&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]24[/C][C]0.414032[/C][C]0.828064[/C][C]0.585968[/C][/ROW]
[ROW][C]25[/C][C]0.255885[/C][C]0.511769[/C][C]0.744115[/C][/ROW]
[ROW][C]26[/C][C]0.168257[/C][C]0.336514[/C][C]0.831743[/C][/ROW]
[ROW][C]27[/C][C]0.0933489[/C][C]0.186698[/C][C]0.906651[/C][/ROW]
[ROW][C]28[/C][C]0.0569109[/C][C]0.113822[/C][C]0.943089[/C][/ROW]
[ROW][C]29[/C][C]0.0492736[/C][C]0.0985472[/C][C]0.950726[/C][/ROW]
[ROW][C]30[/C][C]0.0254062[/C][C]0.0508124[/C][C]0.974594[/C][/ROW]
[ROW][C]31[/C][C]0.194235[/C][C]0.388469[/C][C]0.805765[/C][/ROW]
[ROW][C]32[/C][C]0.242496[/C][C]0.484992[/C][C]0.757504[/C][/ROW]
[ROW][C]33[/C][C]0.281873[/C][C]0.563747[/C][C]0.718127[/C][/ROW]
[ROW][C]34[/C][C]0.214045[/C][C]0.428089[/C][C]0.785955[/C][/ROW]
[ROW][C]35[/C][C]0.185534[/C][C]0.371068[/C][C]0.814466[/C][/ROW]
[ROW][C]36[/C][C]0.13994[/C][C]0.279879[/C][C]0.86006[/C][/ROW]
[ROW][C]37[/C][C]0.195959[/C][C]0.391917[/C][C]0.804041[/C][/ROW]
[ROW][C]38[/C][C]0.147289[/C][C]0.294578[/C][C]0.852711[/C][/ROW]
[ROW][C]39[/C][C]0.113295[/C][C]0.226589[/C][C]0.886705[/C][/ROW]
[ROW][C]40[/C][C]0.115686[/C][C]0.231372[/C][C]0.884314[/C][/ROW]
[ROW][C]41[/C][C]0.101735[/C][C]0.203469[/C][C]0.898265[/C][/ROW]
[ROW][C]42[/C][C]0.0748005[/C][C]0.149601[/C][C]0.925199[/C][/ROW]
[ROW][C]43[/C][C]0.0540884[/C][C]0.108177[/C][C]0.945912[/C][/ROW]
[ROW][C]44[/C][C]0.0755171[/C][C]0.151034[/C][C]0.924483[/C][/ROW]
[ROW][C]45[/C][C]0.121787[/C][C]0.243573[/C][C]0.878213[/C][/ROW]
[ROW][C]46[/C][C]0.172584[/C][C]0.345167[/C][C]0.827416[/C][/ROW]
[ROW][C]47[/C][C]0.140598[/C][C]0.281195[/C][C]0.859402[/C][/ROW]
[ROW][C]48[/C][C]0.113962[/C][C]0.227924[/C][C]0.886038[/C][/ROW]
[ROW][C]49[/C][C]0.0996022[/C][C]0.199204[/C][C]0.900398[/C][/ROW]
[ROW][C]50[/C][C]0.0809571[/C][C]0.161914[/C][C]0.919043[/C][/ROW]
[ROW][C]51[/C][C]0.064244[/C][C]0.128488[/C][C]0.935756[/C][/ROW]
[ROW][C]52[/C][C]0.0506243[/C][C]0.101249[/C][C]0.949376[/C][/ROW]
[ROW][C]53[/C][C]0.0381403[/C][C]0.0762806[/C][C]0.96186[/C][/ROW]
[ROW][C]54[/C][C]0.0291178[/C][C]0.0582355[/C][C]0.970882[/C][/ROW]
[ROW][C]55[/C][C]0.022286[/C][C]0.044572[/C][C]0.977714[/C][/ROW]
[ROW][C]56[/C][C]0.034793[/C][C]0.069586[/C][C]0.965207[/C][/ROW]
[ROW][C]57[/C][C]0.0320849[/C][C]0.0641698[/C][C]0.967915[/C][/ROW]
[ROW][C]58[/C][C]0.0598685[/C][C]0.119737[/C][C]0.940132[/C][/ROW]
[ROW][C]59[/C][C]0.0461471[/C][C]0.0922942[/C][C]0.953853[/C][/ROW]
[ROW][C]60[/C][C]0.0347611[/C][C]0.0695221[/C][C]0.965239[/C][/ROW]
[ROW][C]61[/C][C]0.0298353[/C][C]0.0596707[/C][C]0.970165[/C][/ROW]
[ROW][C]62[/C][C]0.0232833[/C][C]0.0465665[/C][C]0.976717[/C][/ROW]
[ROW][C]63[/C][C]0.0215193[/C][C]0.0430386[/C][C]0.978481[/C][/ROW]
[ROW][C]64[/C][C]0.0173018[/C][C]0.0346036[/C][C]0.982698[/C][/ROW]
[ROW][C]65[/C][C]0.0127748[/C][C]0.0255495[/C][C]0.987225[/C][/ROW]
[ROW][C]66[/C][C]0.00917096[/C][C]0.0183419[/C][C]0.990829[/C][/ROW]
[ROW][C]67[/C][C]0.00679489[/C][C]0.0135898[/C][C]0.993205[/C][/ROW]
[ROW][C]68[/C][C]0.00512381[/C][C]0.0102476[/C][C]0.994876[/C][/ROW]
[ROW][C]69[/C][C]0.00480255[/C][C]0.0096051[/C][C]0.995197[/C][/ROW]
[ROW][C]70[/C][C]0.00353541[/C][C]0.00707083[/C][C]0.996465[/C][/ROW]
[ROW][C]71[/C][C]0.00340101[/C][C]0.00680203[/C][C]0.996599[/C][/ROW]
[ROW][C]72[/C][C]0.00412228[/C][C]0.00824455[/C][C]0.995878[/C][/ROW]
[ROW][C]73[/C][C]0.00478095[/C][C]0.00956189[/C][C]0.995219[/C][/ROW]
[ROW][C]74[/C][C]0.00402069[/C][C]0.00804138[/C][C]0.995979[/C][/ROW]
[ROW][C]75[/C][C]0.00640864[/C][C]0.0128173[/C][C]0.993591[/C][/ROW]
[ROW][C]76[/C][C]0.0168333[/C][C]0.0336666[/C][C]0.983167[/C][/ROW]
[ROW][C]77[/C][C]0.0133561[/C][C]0.0267122[/C][C]0.986644[/C][/ROW]
[ROW][C]78[/C][C]0.00997031[/C][C]0.0199406[/C][C]0.99003[/C][/ROW]
[ROW][C]79[/C][C]0.019728[/C][C]0.039456[/C][C]0.980272[/C][/ROW]
[ROW][C]80[/C][C]0.0371941[/C][C]0.0743882[/C][C]0.962806[/C][/ROW]
[ROW][C]81[/C][C]0.0437222[/C][C]0.0874444[/C][C]0.956278[/C][/ROW]
[ROW][C]82[/C][C]0.0347515[/C][C]0.0695029[/C][C]0.965249[/C][/ROW]
[ROW][C]83[/C][C]0.0292316[/C][C]0.0584632[/C][C]0.970768[/C][/ROW]
[ROW][C]84[/C][C]0.0250735[/C][C]0.050147[/C][C]0.974927[/C][/ROW]
[ROW][C]85[/C][C]0.0216186[/C][C]0.0432372[/C][C]0.978381[/C][/ROW]
[ROW][C]86[/C][C]0.0168007[/C][C]0.0336014[/C][C]0.983199[/C][/ROW]
[ROW][C]87[/C][C]0.0131487[/C][C]0.0262973[/C][C]0.986851[/C][/ROW]
[ROW][C]88[/C][C]0.0137392[/C][C]0.0274784[/C][C]0.986261[/C][/ROW]
[ROW][C]89[/C][C]0.0105373[/C][C]0.0210746[/C][C]0.989463[/C][/ROW]
[ROW][C]90[/C][C]0.0102251[/C][C]0.0204503[/C][C]0.989775[/C][/ROW]
[ROW][C]91[/C][C]0.00900832[/C][C]0.0180166[/C][C]0.990992[/C][/ROW]
[ROW][C]92[/C][C]0.00706177[/C][C]0.0141235[/C][C]0.992938[/C][/ROW]
[ROW][C]93[/C][C]0.00593292[/C][C]0.0118658[/C][C]0.994067[/C][/ROW]
[ROW][C]94[/C][C]0.00470429[/C][C]0.00940857[/C][C]0.995296[/C][/ROW]
[ROW][C]95[/C][C]0.00409347[/C][C]0.00818694[/C][C]0.995907[/C][/ROW]
[ROW][C]96[/C][C]0.00433026[/C][C]0.00866052[/C][C]0.99567[/C][/ROW]
[ROW][C]97[/C][C]0.00337597[/C][C]0.00675194[/C][C]0.996624[/C][/ROW]
[ROW][C]98[/C][C]0.00266162[/C][C]0.00532324[/C][C]0.997338[/C][/ROW]
[ROW][C]99[/C][C]0.00215222[/C][C]0.00430444[/C][C]0.997848[/C][/ROW]
[ROW][C]100[/C][C]0.00318402[/C][C]0.00636805[/C][C]0.996816[/C][/ROW]
[ROW][C]101[/C][C]0.00261855[/C][C]0.0052371[/C][C]0.997381[/C][/ROW]
[ROW][C]102[/C][C]0.00190536[/C][C]0.00381072[/C][C]0.998095[/C][/ROW]
[ROW][C]103[/C][C]0.00145093[/C][C]0.00290186[/C][C]0.998549[/C][/ROW]
[ROW][C]104[/C][C]0.00120514[/C][C]0.00241029[/C][C]0.998795[/C][/ROW]
[ROW][C]105[/C][C]0.00390595[/C][C]0.00781191[/C][C]0.996094[/C][/ROW]
[ROW][C]106[/C][C]0.0054325[/C][C]0.010865[/C][C]0.994567[/C][/ROW]
[ROW][C]107[/C][C]0.00595819[/C][C]0.0119164[/C][C]0.994042[/C][/ROW]
[ROW][C]108[/C][C]0.00475304[/C][C]0.00950607[/C][C]0.995247[/C][/ROW]
[ROW][C]109[/C][C]0.0107014[/C][C]0.0214028[/C][C]0.989299[/C][/ROW]
[ROW][C]110[/C][C]0.024923[/C][C]0.0498461[/C][C]0.975077[/C][/ROW]
[ROW][C]111[/C][C]0.0206248[/C][C]0.0412495[/C][C]0.979375[/C][/ROW]
[ROW][C]112[/C][C]0.0266217[/C][C]0.0532435[/C][C]0.973378[/C][/ROW]
[ROW][C]113[/C][C]0.0219042[/C][C]0.0438083[/C][C]0.978096[/C][/ROW]
[ROW][C]114[/C][C]0.0251092[/C][C]0.0502184[/C][C]0.974891[/C][/ROW]
[ROW][C]115[/C][C]0.0221504[/C][C]0.0443008[/C][C]0.97785[/C][/ROW]
[ROW][C]116[/C][C]0.0197823[/C][C]0.0395645[/C][C]0.980218[/C][/ROW]
[ROW][C]117[/C][C]0.0217532[/C][C]0.0435064[/C][C]0.978247[/C][/ROW]
[ROW][C]118[/C][C]0.0172607[/C][C]0.0345214[/C][C]0.982739[/C][/ROW]
[ROW][C]119[/C][C]0.0153687[/C][C]0.0307373[/C][C]0.984631[/C][/ROW]
[ROW][C]120[/C][C]0.013404[/C][C]0.0268079[/C][C]0.986596[/C][/ROW]
[ROW][C]121[/C][C]0.0118308[/C][C]0.0236617[/C][C]0.988169[/C][/ROW]
[ROW][C]122[/C][C]0.00957027[/C][C]0.0191405[/C][C]0.99043[/C][/ROW]
[ROW][C]123[/C][C]0.00980268[/C][C]0.0196054[/C][C]0.990197[/C][/ROW]
[ROW][C]124[/C][C]0.0112177[/C][C]0.0224354[/C][C]0.988782[/C][/ROW]
[ROW][C]125[/C][C]0.0105887[/C][C]0.0211773[/C][C]0.989411[/C][/ROW]
[ROW][C]126[/C][C]0.0168044[/C][C]0.0336088[/C][C]0.983196[/C][/ROW]
[ROW][C]127[/C][C]0.0319366[/C][C]0.0638732[/C][C]0.968063[/C][/ROW]
[ROW][C]128[/C][C]0.0287714[/C][C]0.0575428[/C][C]0.971229[/C][/ROW]
[ROW][C]129[/C][C]0.0249751[/C][C]0.0499503[/C][C]0.975025[/C][/ROW]
[ROW][C]130[/C][C]0.0215505[/C][C]0.0431011[/C][C]0.978449[/C][/ROW]
[ROW][C]131[/C][C]0.0302922[/C][C]0.0605845[/C][C]0.969708[/C][/ROW]
[ROW][C]132[/C][C]0.0328518[/C][C]0.0657035[/C][C]0.967148[/C][/ROW]
[ROW][C]133[/C][C]0.0438788[/C][C]0.0877576[/C][C]0.956121[/C][/ROW]
[ROW][C]134[/C][C]0.0359089[/C][C]0.0718177[/C][C]0.964091[/C][/ROW]
[ROW][C]135[/C][C]0.0302158[/C][C]0.0604316[/C][C]0.969784[/C][/ROW]
[ROW][C]136[/C][C]0.0242472[/C][C]0.0484945[/C][C]0.975753[/C][/ROW]
[ROW][C]137[/C][C]0.0199837[/C][C]0.0399674[/C][C]0.980016[/C][/ROW]
[ROW][C]138[/C][C]0.023177[/C][C]0.0463539[/C][C]0.976823[/C][/ROW]
[ROW][C]139[/C][C]0.0191557[/C][C]0.0383113[/C][C]0.980844[/C][/ROW]
[ROW][C]140[/C][C]0.0201402[/C][C]0.0402804[/C][C]0.97986[/C][/ROW]
[ROW][C]141[/C][C]0.0229755[/C][C]0.0459509[/C][C]0.977025[/C][/ROW]
[ROW][C]142[/C][C]0.0247011[/C][C]0.0494023[/C][C]0.975299[/C][/ROW]
[ROW][C]143[/C][C]0.0370316[/C][C]0.0740632[/C][C]0.962968[/C][/ROW]
[ROW][C]144[/C][C]0.0315089[/C][C]0.0630177[/C][C]0.968491[/C][/ROW]
[ROW][C]145[/C][C]0.0745664[/C][C]0.149133[/C][C]0.925434[/C][/ROW]
[ROW][C]146[/C][C]0.0703165[/C][C]0.140633[/C][C]0.929684[/C][/ROW]
[ROW][C]147[/C][C]0.071609[/C][C]0.143218[/C][C]0.928391[/C][/ROW]
[ROW][C]148[/C][C]0.0595318[/C][C]0.119064[/C][C]0.940468[/C][/ROW]
[ROW][C]149[/C][C]0.0516253[/C][C]0.103251[/C][C]0.948375[/C][/ROW]
[ROW][C]150[/C][C]0.0455024[/C][C]0.0910047[/C][C]0.954498[/C][/ROW]
[ROW][C]151[/C][C]0.0670162[/C][C]0.134032[/C][C]0.932984[/C][/ROW]
[ROW][C]152[/C][C]0.0616553[/C][C]0.123311[/C][C]0.938345[/C][/ROW]
[ROW][C]153[/C][C]0.0569202[/C][C]0.11384[/C][C]0.94308[/C][/ROW]
[ROW][C]154[/C][C]0.0916842[/C][C]0.183368[/C][C]0.908316[/C][/ROW]
[ROW][C]155[/C][C]0.0792536[/C][C]0.158507[/C][C]0.920746[/C][/ROW]
[ROW][C]156[/C][C]0.0870402[/C][C]0.17408[/C][C]0.91296[/C][/ROW]
[ROW][C]157[/C][C]0.0845416[/C][C]0.169083[/C][C]0.915458[/C][/ROW]
[ROW][C]158[/C][C]0.0799269[/C][C]0.159854[/C][C]0.920073[/C][/ROW]
[ROW][C]159[/C][C]0.0809964[/C][C]0.161993[/C][C]0.919004[/C][/ROW]
[ROW][C]160[/C][C]0.069254[/C][C]0.138508[/C][C]0.930746[/C][/ROW]
[ROW][C]161[/C][C]0.0572001[/C][C]0.1144[/C][C]0.9428[/C][/ROW]
[ROW][C]162[/C][C]0.0544452[/C][C]0.10889[/C][C]0.945555[/C][/ROW]
[ROW][C]163[/C][C]0.0456884[/C][C]0.0913768[/C][C]0.954312[/C][/ROW]
[ROW][C]164[/C][C]0.0682446[/C][C]0.136489[/C][C]0.931755[/C][/ROW]
[ROW][C]165[/C][C]0.0592322[/C][C]0.118464[/C][C]0.940768[/C][/ROW]
[ROW][C]166[/C][C]0.0781656[/C][C]0.156331[/C][C]0.921834[/C][/ROW]
[ROW][C]167[/C][C]0.0802018[/C][C]0.160404[/C][C]0.919798[/C][/ROW]
[ROW][C]168[/C][C]0.0750399[/C][C]0.15008[/C][C]0.92496[/C][/ROW]
[ROW][C]169[/C][C]0.0631747[/C][C]0.126349[/C][C]0.936825[/C][/ROW]
[ROW][C]170[/C][C]0.1431[/C][C]0.2862[/C][C]0.8569[/C][/ROW]
[ROW][C]171[/C][C]0.179477[/C][C]0.358955[/C][C]0.820523[/C][/ROW]
[ROW][C]172[/C][C]0.159959[/C][C]0.319918[/C][C]0.840041[/C][/ROW]
[ROW][C]173[/C][C]0.231938[/C][C]0.463876[/C][C]0.768062[/C][/ROW]
[ROW][C]174[/C][C]0.204407[/C][C]0.408814[/C][C]0.795593[/C][/ROW]
[ROW][C]175[/C][C]0.220487[/C][C]0.440973[/C][C]0.779513[/C][/ROW]
[ROW][C]176[/C][C]0.200522[/C][C]0.401043[/C][C]0.799478[/C][/ROW]
[ROW][C]177[/C][C]0.219094[/C][C]0.438188[/C][C]0.780906[/C][/ROW]
[ROW][C]178[/C][C]0.191993[/C][C]0.383986[/C][C]0.808007[/C][/ROW]
[ROW][C]179[/C][C]0.172015[/C][C]0.344029[/C][C]0.827985[/C][/ROW]
[ROW][C]180[/C][C]0.166737[/C][C]0.333475[/C][C]0.833263[/C][/ROW]
[ROW][C]181[/C][C]0.147904[/C][C]0.295808[/C][C]0.852096[/C][/ROW]
[ROW][C]182[/C][C]0.135537[/C][C]0.271075[/C][C]0.864463[/C][/ROW]
[ROW][C]183[/C][C]0.134581[/C][C]0.269163[/C][C]0.865419[/C][/ROW]
[ROW][C]184[/C][C]0.20213[/C][C]0.40426[/C][C]0.79787[/C][/ROW]
[ROW][C]185[/C][C]0.495151[/C][C]0.990301[/C][C]0.504849[/C][/ROW]
[ROW][C]186[/C][C]0.480658[/C][C]0.961316[/C][C]0.519342[/C][/ROW]
[ROW][C]187[/C][C]0.467242[/C][C]0.934484[/C][C]0.532758[/C][/ROW]
[ROW][C]188[/C][C]0.651935[/C][C]0.69613[/C][C]0.348065[/C][/ROW]
[ROW][C]189[/C][C]0.622049[/C][C]0.755902[/C][C]0.377951[/C][/ROW]
[ROW][C]190[/C][C]0.580415[/C][C]0.839169[/C][C]0.419585[/C][/ROW]
[ROW][C]191[/C][C]0.541651[/C][C]0.916698[/C][C]0.458349[/C][/ROW]
[ROW][C]192[/C][C]0.506933[/C][C]0.986135[/C][C]0.493067[/C][/ROW]
[ROW][C]193[/C][C]0.468321[/C][C]0.936641[/C][C]0.531679[/C][/ROW]
[ROW][C]194[/C][C]0.431064[/C][C]0.862127[/C][C]0.568936[/C][/ROW]
[ROW][C]195[/C][C]0.40031[/C][C]0.80062[/C][C]0.59969[/C][/ROW]
[ROW][C]196[/C][C]0.36842[/C][C]0.73684[/C][C]0.63158[/C][/ROW]
[ROW][C]197[/C][C]0.338886[/C][C]0.677773[/C][C]0.661114[/C][/ROW]
[ROW][C]198[/C][C]0.319607[/C][C]0.639213[/C][C]0.680393[/C][/ROW]
[ROW][C]199[/C][C]0.281659[/C][C]0.563319[/C][C]0.718341[/C][/ROW]
[ROW][C]200[/C][C]0.349143[/C][C]0.698287[/C][C]0.650857[/C][/ROW]
[ROW][C]201[/C][C]0.316471[/C][C]0.632942[/C][C]0.683529[/C][/ROW]
[ROW][C]202[/C][C]0.376274[/C][C]0.752548[/C][C]0.623726[/C][/ROW]
[ROW][C]203[/C][C]0.340005[/C][C]0.680011[/C][C]0.659995[/C][/ROW]
[ROW][C]204[/C][C]0.309501[/C][C]0.619002[/C][C]0.690499[/C][/ROW]
[ROW][C]205[/C][C]0.272024[/C][C]0.544047[/C][C]0.727976[/C][/ROW]
[ROW][C]206[/C][C]0.244508[/C][C]0.489016[/C][C]0.755492[/C][/ROW]
[ROW][C]207[/C][C]0.217361[/C][C]0.434721[/C][C]0.782639[/C][/ROW]
[ROW][C]208[/C][C]0.184562[/C][C]0.369123[/C][C]0.815438[/C][/ROW]
[ROW][C]209[/C][C]0.160563[/C][C]0.321126[/C][C]0.839437[/C][/ROW]
[ROW][C]210[/C][C]0.131358[/C][C]0.262717[/C][C]0.868642[/C][/ROW]
[ROW][C]211[/C][C]0.110679[/C][C]0.221358[/C][C]0.889321[/C][/ROW]
[ROW][C]212[/C][C]0.101891[/C][C]0.203783[/C][C]0.898109[/C][/ROW]
[ROW][C]213[/C][C]0.100387[/C][C]0.200773[/C][C]0.899613[/C][/ROW]
[ROW][C]214[/C][C]0.0793455[/C][C]0.158691[/C][C]0.920655[/C][/ROW]
[ROW][C]215[/C][C]0.0614234[/C][C]0.122847[/C][C]0.938577[/C][/ROW]
[ROW][C]216[/C][C]0.0514092[/C][C]0.102818[/C][C]0.948591[/C][/ROW]
[ROW][C]217[/C][C]0.0391894[/C][C]0.0783789[/C][C]0.960811[/C][/ROW]
[ROW][C]218[/C][C]0.0438662[/C][C]0.0877324[/C][C]0.956134[/C][/ROW]
[ROW][C]219[/C][C]0.0346884[/C][C]0.0693767[/C][C]0.965312[/C][/ROW]
[ROW][C]220[/C][C]0.0255522[/C][C]0.0511044[/C][C]0.974448[/C][/ROW]
[ROW][C]221[/C][C]0.0190262[/C][C]0.0380524[/C][C]0.980974[/C][/ROW]
[ROW][C]222[/C][C]0.0182805[/C][C]0.0365611[/C][C]0.981719[/C][/ROW]
[ROW][C]223[/C][C]0.0129322[/C][C]0.0258644[/C][C]0.987068[/C][/ROW]
[ROW][C]224[/C][C]0.0134592[/C][C]0.0269184[/C][C]0.986541[/C][/ROW]
[ROW][C]225[/C][C]0.0516041[/C][C]0.103208[/C][C]0.948396[/C][/ROW]
[ROW][C]226[/C][C]0.0432817[/C][C]0.0865634[/C][C]0.956718[/C][/ROW]
[ROW][C]227[/C][C]0.0319543[/C][C]0.0639086[/C][C]0.968046[/C][/ROW]
[ROW][C]228[/C][C]0.0264267[/C][C]0.0528533[/C][C]0.973573[/C][/ROW]
[ROW][C]229[/C][C]0.017762[/C][C]0.035524[/C][C]0.982238[/C][/ROW]
[ROW][C]230[/C][C]0.0112619[/C][C]0.0225238[/C][C]0.988738[/C][/ROW]
[ROW][C]231[/C][C]0.00801628[/C][C]0.0160326[/C][C]0.991984[/C][/ROW]
[ROW][C]232[/C][C]0.0340196[/C][C]0.0680392[/C][C]0.96598[/C][/ROW]
[ROW][C]233[/C][C]0.0294493[/C][C]0.0588987[/C][C]0.970551[/C][/ROW]
[ROW][C]234[/C][C]0.132667[/C][C]0.265333[/C][C]0.867333[/C][/ROW]
[ROW][C]235[/C][C]0.0912726[/C][C]0.182545[/C][C]0.908727[/C][/ROW]
[ROW][C]236[/C][C]0.0880216[/C][C]0.176043[/C][C]0.911978[/C][/ROW]
[ROW][C]237[/C][C]0.0833464[/C][C]0.166693[/C][C]0.916654[/C][/ROW]
[ROW][C]238[/C][C]0.0892565[/C][C]0.178513[/C][C]0.910744[/C][/ROW]
[ROW][C]239[/C][C]0.0507186[/C][C]0.101437[/C][C]0.949281[/C][/ROW]
[ROW][C]240[/C][C]0.202936[/C][C]0.405872[/C][C]0.797064[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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
240.4140320.8280640.585968
250.2558850.5117690.744115
260.1682570.3365140.831743
270.09334890.1866980.906651
280.05691090.1138220.943089
290.04927360.09854720.950726
300.02540620.05081240.974594
310.1942350.3884690.805765
320.2424960.4849920.757504
330.2818730.5637470.718127
340.2140450.4280890.785955
350.1855340.3710680.814466
360.139940.2798790.86006
370.1959590.3919170.804041
380.1472890.2945780.852711
390.1132950.2265890.886705
400.1156860.2313720.884314
410.1017350.2034690.898265
420.07480050.1496010.925199
430.05408840.1081770.945912
440.07551710.1510340.924483
450.1217870.2435730.878213
460.1725840.3451670.827416
470.1405980.2811950.859402
480.1139620.2279240.886038
490.09960220.1992040.900398
500.08095710.1619140.919043
510.0642440.1284880.935756
520.05062430.1012490.949376
530.03814030.07628060.96186
540.02911780.05823550.970882
550.0222860.0445720.977714
560.0347930.0695860.965207
570.03208490.06416980.967915
580.05986850.1197370.940132
590.04614710.09229420.953853
600.03476110.06952210.965239
610.02983530.05967070.970165
620.02328330.04656650.976717
630.02151930.04303860.978481
640.01730180.03460360.982698
650.01277480.02554950.987225
660.009170960.01834190.990829
670.006794890.01358980.993205
680.005123810.01024760.994876
690.004802550.00960510.995197
700.003535410.007070830.996465
710.003401010.006802030.996599
720.004122280.008244550.995878
730.004780950.009561890.995219
740.004020690.008041380.995979
750.006408640.01281730.993591
760.01683330.03366660.983167
770.01335610.02671220.986644
780.009970310.01994060.99003
790.0197280.0394560.980272
800.03719410.07438820.962806
810.04372220.08744440.956278
820.03475150.06950290.965249
830.02923160.05846320.970768
840.02507350.0501470.974927
850.02161860.04323720.978381
860.01680070.03360140.983199
870.01314870.02629730.986851
880.01373920.02747840.986261
890.01053730.02107460.989463
900.01022510.02045030.989775
910.009008320.01801660.990992
920.007061770.01412350.992938
930.005932920.01186580.994067
940.004704290.009408570.995296
950.004093470.008186940.995907
960.004330260.008660520.99567
970.003375970.006751940.996624
980.002661620.005323240.997338
990.002152220.004304440.997848
1000.003184020.006368050.996816
1010.002618550.00523710.997381
1020.001905360.003810720.998095
1030.001450930.002901860.998549
1040.001205140.002410290.998795
1050.003905950.007811910.996094
1060.00543250.0108650.994567
1070.005958190.01191640.994042
1080.004753040.009506070.995247
1090.01070140.02140280.989299
1100.0249230.04984610.975077
1110.02062480.04124950.979375
1120.02662170.05324350.973378
1130.02190420.04380830.978096
1140.02510920.05021840.974891
1150.02215040.04430080.97785
1160.01978230.03956450.980218
1170.02175320.04350640.978247
1180.01726070.03452140.982739
1190.01536870.03073730.984631
1200.0134040.02680790.986596
1210.01183080.02366170.988169
1220.009570270.01914050.99043
1230.009802680.01960540.990197
1240.01121770.02243540.988782
1250.01058870.02117730.989411
1260.01680440.03360880.983196
1270.03193660.06387320.968063
1280.02877140.05754280.971229
1290.02497510.04995030.975025
1300.02155050.04310110.978449
1310.03029220.06058450.969708
1320.03285180.06570350.967148
1330.04387880.08775760.956121
1340.03590890.07181770.964091
1350.03021580.06043160.969784
1360.02424720.04849450.975753
1370.01998370.03996740.980016
1380.0231770.04635390.976823
1390.01915570.03831130.980844
1400.02014020.04028040.97986
1410.02297550.04595090.977025
1420.02470110.04940230.975299
1430.03703160.07406320.962968
1440.03150890.06301770.968491
1450.07456640.1491330.925434
1460.07031650.1406330.929684
1470.0716090.1432180.928391
1480.05953180.1190640.940468
1490.05162530.1032510.948375
1500.04550240.09100470.954498
1510.06701620.1340320.932984
1520.06165530.1233110.938345
1530.05692020.113840.94308
1540.09168420.1833680.908316
1550.07925360.1585070.920746
1560.08704020.174080.91296
1570.08454160.1690830.915458
1580.07992690.1598540.920073
1590.08099640.1619930.919004
1600.0692540.1385080.930746
1610.05720010.11440.9428
1620.05444520.108890.945555
1630.04568840.09137680.954312
1640.06824460.1364890.931755
1650.05923220.1184640.940768
1660.07816560.1563310.921834
1670.08020180.1604040.919798
1680.07503990.150080.92496
1690.06317470.1263490.936825
1700.14310.28620.8569
1710.1794770.3589550.820523
1720.1599590.3199180.840041
1730.2319380.4638760.768062
1740.2044070.4088140.795593
1750.2204870.4409730.779513
1760.2005220.4010430.799478
1770.2190940.4381880.780906
1780.1919930.3839860.808007
1790.1720150.3440290.827985
1800.1667370.3334750.833263
1810.1479040.2958080.852096
1820.1355370.2710750.864463
1830.1345810.2691630.865419
1840.202130.404260.79787
1850.4951510.9903010.504849
1860.4806580.9613160.519342
1870.4672420.9344840.532758
1880.6519350.696130.348065
1890.6220490.7559020.377951
1900.5804150.8391690.419585
1910.5416510.9166980.458349
1920.5069330.9861350.493067
1930.4683210.9366410.531679
1940.4310640.8621270.568936
1950.400310.800620.59969
1960.368420.736840.63158
1970.3388860.6777730.661114
1980.3196070.6392130.680393
1990.2816590.5633190.718341
2000.3491430.6982870.650857
2010.3164710.6329420.683529
2020.3762740.7525480.623726
2030.3400050.6800110.659995
2040.3095010.6190020.690499
2050.2720240.5440470.727976
2060.2445080.4890160.755492
2070.2173610.4347210.782639
2080.1845620.3691230.815438
2090.1605630.3211260.839437
2100.1313580.2627170.868642
2110.1106790.2213580.889321
2120.1018910.2037830.898109
2130.1003870.2007730.899613
2140.07934550.1586910.920655
2150.06142340.1228470.938577
2160.05140920.1028180.948591
2170.03918940.07837890.960811
2180.04386620.08773240.956134
2190.03468840.06937670.965312
2200.02555220.05110440.974448
2210.01902620.03805240.980974
2220.01828050.03656110.981719
2230.01293220.02586440.987068
2240.01345920.02691840.986541
2250.05160410.1032080.948396
2260.04328170.08656340.956718
2270.03195430.06390860.968046
2280.02642670.05285330.973573
2290.0177620.0355240.982238
2300.01126190.02252380.988738
2310.008016280.01603260.991984
2320.03401960.06803920.96598
2330.02944930.05889870.970551
2340.1326670.2653330.867333
2350.09127260.1825450.908727
2360.08802160.1760430.911978
2370.08334640.1666930.916654
2380.08925650.1785130.910744
2390.05071860.1014370.949281
2400.2029360.4058720.797064






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level190.0875576NOK
5% type I error level750.345622NOK
10% type I error level1110.511521NOK

\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 & 19 & 0.0875576 & NOK \tabularnewline
5% type I error level & 75 & 0.345622 & NOK \tabularnewline
10% type I error level & 111 & 0.511521 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221976&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]19[/C][C]0.0875576[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]75[/C][C]0.345622[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]111[/C][C]0.511521[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221976&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221976&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 level190.0875576NOK
5% type I error level750.345622NOK
10% type I error level1110.511521NOK


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 = 1 ; par2 = Include Monthly Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Include Monthly Dummies ; par3 = 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')
}