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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 computationSat, 02 Nov 2013 17:13:17 -0400
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/02/t13834268453hzz1bntat7vuew.htm/, Retrieved Tue, 07 May 2024 06:43:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=221819, Retrieved Tue, 07 May 2024 06:43:41 +0000
QR Codes:

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

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [WORKSHOP 7 ] [2013-11-02 19:41:02] [69bf0eb8b9b38defaaf4848d8c317571]
-   PD    [Multiple Regression] [W7] [2013-11-02 21:13:17] [4c6743e926d608f4adf2160fecf92c6f] [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 time13 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 & 13 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&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]13 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=221819&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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 time13 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Learning[t] = + 4.08082 + 0.0291022Connected[t] + 0.0472371Separate[t] + 0.541624Software[t] + 0.0751756Happiness[t] -0.0307753Depression[t] + 0.0283578Sport1[t] -0.0360211Sport2[t] + 0.158478Month[t] + 0.233477M1[t] + 0.31278M2[t] + 0.536267M3[t] + 0.488297M4[t] -0.0692364M5[t] + 0.196586M6[t] + 0.417672M7[t] -0.31131M8[t] -0.0405797M9[t] -0.158836M10[t] -0.313449M11[t] -0.00648349t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Learning[t] =  +  4.08082 +  0.0291022Connected[t] +  0.0472371Separate[t] +  0.541624Software[t] +  0.0751756Happiness[t] -0.0307753Depression[t] +  0.0283578Sport1[t] -0.0360211Sport2[t] +  0.158478Month[t] +  0.233477M1[t] +  0.31278M2[t] +  0.536267M3[t] +  0.488297M4[t] -0.0692364M5[t] +  0.196586M6[t] +  0.417672M7[t] -0.31131M8[t] -0.0405797M9[t] -0.158836M10[t] -0.313449M11[t] -0.00648349t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Learning[t] =  +  4.08082 +  0.0291022Connected[t] +  0.0472371Separate[t] +  0.541624Software[t] +  0.0751756Happiness[t] -0.0307753Depression[t] +  0.0283578Sport1[t] -0.0360211Sport2[t] +  0.158478Month[t] +  0.233477M1[t] +  0.31278M2[t] +  0.536267M3[t] +  0.488297M4[t] -0.0692364M5[t] +  0.196586M6[t] +  0.417672M7[t] -0.31131M8[t] -0.0405797M9[t] -0.158836M10[t] -0.313449M11[t] -0.00648349t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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
Learning[t] = + 4.08082 + 0.0291022Connected[t] + 0.0472371Separate[t] + 0.541624Software[t] + 0.0751756Happiness[t] -0.0307753Depression[t] + 0.0283578Sport1[t] -0.0360211Sport2[t] + 0.158478Month[t] + 0.233477M1[t] + 0.31278M2[t] + 0.536267M3[t] + 0.488297M4[t] -0.0692364M5[t] + 0.196586M6[t] + 0.417672M7[t] -0.31131M8[t] -0.0405797M9[t] -0.158836M10[t] -0.313449M11[t] -0.00648349t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)4.080823.981191.0250.306370.153185
Connected0.02910220.03633470.80090.4239450.211973
Separate0.04723710.03614421.3070.1924810.0962404
Software0.5416240.05680759.5341.65074e-188.25369e-19
Happiness0.07517560.05918171.270.205210.102605
Depression-0.03077530.0441151-0.69760.4860860.243043
Sport10.02835780.03888180.72930.46650.23325
Sport2-0.03602110.0578006-0.62320.533740.26687
Month0.1584780.4153040.38160.7030940.351547
M10.2334770.5778870.4040.6865550.343278
M20.312780.575830.54320.5875030.293752
M30.5362670.5738190.93460.3509440.175472
M40.4882970.5714230.85450.3936550.196827
M5-0.06923640.578295-0.11970.90480.4524
M60.1965860.5826050.33740.7360870.368043
M70.4176720.5735540.72820.4671820.233591
M8-0.311310.57089-0.54530.5860430.293021
M9-0.04057970.570658-0.071110.9433680.471684
M10-0.1588360.574711-0.27640.7824940.391247
M11-0.3134490.57068-0.54930.5833350.291667
t-0.006483490.00440163-1.4730.1420520.0710259

\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) & 4.08082 & 3.98119 & 1.025 & 0.30637 & 0.153185 \tabularnewline
Connected & 0.0291022 & 0.0363347 & 0.8009 & 0.423945 & 0.211973 \tabularnewline
Separate & 0.0472371 & 0.0361442 & 1.307 & 0.192481 & 0.0962404 \tabularnewline
Software & 0.541624 & 0.0568075 & 9.534 & 1.65074e-18 & 8.25369e-19 \tabularnewline
Happiness & 0.0751756 & 0.0591817 & 1.27 & 0.20521 & 0.102605 \tabularnewline
Depression & -0.0307753 & 0.0441151 & -0.6976 & 0.486086 & 0.243043 \tabularnewline
Sport1 & 0.0283578 & 0.0388818 & 0.7293 & 0.4665 & 0.23325 \tabularnewline
Sport2 & -0.0360211 & 0.0578006 & -0.6232 & 0.53374 & 0.26687 \tabularnewline
Month & 0.158478 & 0.415304 & 0.3816 & 0.703094 & 0.351547 \tabularnewline
M1 & 0.233477 & 0.577887 & 0.404 & 0.686555 & 0.343278 \tabularnewline
M2 & 0.31278 & 0.57583 & 0.5432 & 0.587503 & 0.293752 \tabularnewline
M3 & 0.536267 & 0.573819 & 0.9346 & 0.350944 & 0.175472 \tabularnewline
M4 & 0.488297 & 0.571423 & 0.8545 & 0.393655 & 0.196827 \tabularnewline
M5 & -0.0692364 & 0.578295 & -0.1197 & 0.9048 & 0.4524 \tabularnewline
M6 & 0.196586 & 0.582605 & 0.3374 & 0.736087 & 0.368043 \tabularnewline
M7 & 0.417672 & 0.573554 & 0.7282 & 0.467182 & 0.233591 \tabularnewline
M8 & -0.31131 & 0.57089 & -0.5453 & 0.586043 & 0.293021 \tabularnewline
M9 & -0.0405797 & 0.570658 & -0.07111 & 0.943368 & 0.471684 \tabularnewline
M10 & -0.158836 & 0.574711 & -0.2764 & 0.782494 & 0.391247 \tabularnewline
M11 & -0.313449 & 0.57068 & -0.5493 & 0.583335 & 0.291667 \tabularnewline
t & -0.00648349 & 0.00440163 & -1.473 & 0.142052 & 0.0710259 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&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]4.08082[/C][C]3.98119[/C][C]1.025[/C][C]0.30637[/C][C]0.153185[/C][/ROW]
[ROW][C]Connected[/C][C]0.0291022[/C][C]0.0363347[/C][C]0.8009[/C][C]0.423945[/C][C]0.211973[/C][/ROW]
[ROW][C]Separate[/C][C]0.0472371[/C][C]0.0361442[/C][C]1.307[/C][C]0.192481[/C][C]0.0962404[/C][/ROW]
[ROW][C]Software[/C][C]0.541624[/C][C]0.0568075[/C][C]9.534[/C][C]1.65074e-18[/C][C]8.25369e-19[/C][/ROW]
[ROW][C]Happiness[/C][C]0.0751756[/C][C]0.0591817[/C][C]1.27[/C][C]0.20521[/C][C]0.102605[/C][/ROW]
[ROW][C]Depression[/C][C]-0.0307753[/C][C]0.0441151[/C][C]-0.6976[/C][C]0.486086[/C][C]0.243043[/C][/ROW]
[ROW][C]Sport1[/C][C]0.0283578[/C][C]0.0388818[/C][C]0.7293[/C][C]0.4665[/C][C]0.23325[/C][/ROW]
[ROW][C]Sport2[/C][C]-0.0360211[/C][C]0.0578006[/C][C]-0.6232[/C][C]0.53374[/C][C]0.26687[/C][/ROW]
[ROW][C]Month[/C][C]0.158478[/C][C]0.415304[/C][C]0.3816[/C][C]0.703094[/C][C]0.351547[/C][/ROW]
[ROW][C]M1[/C][C]0.233477[/C][C]0.577887[/C][C]0.404[/C][C]0.686555[/C][C]0.343278[/C][/ROW]
[ROW][C]M2[/C][C]0.31278[/C][C]0.57583[/C][C]0.5432[/C][C]0.587503[/C][C]0.293752[/C][/ROW]
[ROW][C]M3[/C][C]0.536267[/C][C]0.573819[/C][C]0.9346[/C][C]0.350944[/C][C]0.175472[/C][/ROW]
[ROW][C]M4[/C][C]0.488297[/C][C]0.571423[/C][C]0.8545[/C][C]0.393655[/C][C]0.196827[/C][/ROW]
[ROW][C]M5[/C][C]-0.0692364[/C][C]0.578295[/C][C]-0.1197[/C][C]0.9048[/C][C]0.4524[/C][/ROW]
[ROW][C]M6[/C][C]0.196586[/C][C]0.582605[/C][C]0.3374[/C][C]0.736087[/C][C]0.368043[/C][/ROW]
[ROW][C]M7[/C][C]0.417672[/C][C]0.573554[/C][C]0.7282[/C][C]0.467182[/C][C]0.233591[/C][/ROW]
[ROW][C]M8[/C][C]-0.31131[/C][C]0.57089[/C][C]-0.5453[/C][C]0.586043[/C][C]0.293021[/C][/ROW]
[ROW][C]M9[/C][C]-0.0405797[/C][C]0.570658[/C][C]-0.07111[/C][C]0.943368[/C][C]0.471684[/C][/ROW]
[ROW][C]M10[/C][C]-0.158836[/C][C]0.574711[/C][C]-0.2764[/C][C]0.782494[/C][C]0.391247[/C][/ROW]
[ROW][C]M11[/C][C]-0.313449[/C][C]0.57068[/C][C]-0.5493[/C][C]0.583335[/C][C]0.291667[/C][/ROW]
[ROW][C]t[/C][C]-0.00648349[/C][C]0.00440163[/C][C]-1.473[/C][C]0.142052[/C][C]0.0710259[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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)4.080823.981191.0250.306370.153185
Connected0.02910220.03633470.80090.4239450.211973
Separate0.04723710.03614421.3070.1924810.0962404
Software0.5416240.05680759.5341.65074e-188.25369e-19
Happiness0.07517560.05918171.270.205210.102605
Depression-0.03077530.0441151-0.69760.4860860.243043
Sport10.02835780.03888180.72930.46650.23325
Sport2-0.03602110.0578006-0.62320.533740.26687
Month0.1584780.4153040.38160.7030940.351547
M10.2334770.5778870.4040.6865550.343278
M20.312780.575830.54320.5875030.293752
M30.5362670.5738190.93460.3509440.175472
M40.4882970.5714230.85450.3936550.196827
M5-0.06923640.578295-0.11970.90480.4524
M60.1965860.5826050.33740.7360870.368043
M70.4176720.5735540.72820.4671820.233591
M8-0.311310.57089-0.54530.5860430.293021
M9-0.04057970.570658-0.071110.9433680.471684
M10-0.1588360.574711-0.27640.7824940.391247
M11-0.3134490.57068-0.54930.5833350.291667
t-0.006483490.00440163-1.4730.1420520.0710259






Multiple Linear Regression - Regression Statistics
Multiple R0.677609
R-squared0.459153
Adjusted R-squared0.414639
F-TEST (value)10.3148
F-TEST (DF numerator)20
F-TEST (DF denominator)243
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.87904
Sum Squared Residuals857.979

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.677609 \tabularnewline
R-squared & 0.459153 \tabularnewline
Adjusted R-squared & 0.414639 \tabularnewline
F-TEST (value) & 10.3148 \tabularnewline
F-TEST (DF numerator) & 20 \tabularnewline
F-TEST (DF denominator) & 243 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 1.87904 \tabularnewline
Sum Squared Residuals & 857.979 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.677609[/C][/ROW]
[ROW][C]R-squared[/C][C]0.459153[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.414639[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]10.3148[/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]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]1.87904[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]857.979[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&T=3

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

Multiple Linear Regression - Regression Statistics
Multiple R0.677609
R-squared0.459153
Adjusted R-squared0.414639
F-TEST (value)10.3148
F-TEST (DF numerator)20
F-TEST (DF denominator)243
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation1.87904
Sum Squared Residuals857.979






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11316.2553-3.25525
21615.94260.0573686
31917.42951.57053
41512.63612.36386
51416.2386-2.23858
61314.9723-1.97228
71915.52383.47618
81516.6342-1.63422
91415.9061-1.90607
101514.21960.78038
111614.55431.4457
121616.1073-0.107312
131615.59220.407799
141615.73160.268423
151718.3821-1.38206
161515.8509-0.850867
171514.43070.569332
182016.47723.5228
191815.77222.22779
201615.13090.869142
211615.23390.766102
221614.81111.18886
231916.04142.95856
241614.95491.04508
251716.22970.770291
261716.37250.627539
271615.45610.543875
281517.0674-2.06736
291615.55630.443707
301414.2156-0.215645
311516.0192-1.01924
321212.477-0.476963
331414.6447-0.644693
341615.59060.409391
351415.1108-1.1108
361012.9403-2.94027
371013.1985-3.19848
381415.9024-1.90235
391614.98351.01645
401614.84311.15694
411614.50491.49514
421415.7931-1.79306
432017.68712.31293
441413.73340.266611
451414.2525-0.252461
461115.194-4.19396
471416.0232-2.0232
481514.97920.0208119
491615.62540.374587
501415.7573-1.75733
511617.3736-1.37364
521414.5036-0.503639
531214.8106-2.81059
541615.75170.248333
55911.7725-2.77255
561411.95622.04384
571615.61780.382218
581615.15950.840496
591514.66190.3381
601614.03561.96439
611211.66840.331628
621615.79990.200056
631616.8577-0.857683
641415.0734-1.07337
651615.040.960044
661716.15860.841439
671816.59511.40492
681814.14583.85419
691215.8469-3.84692
701615.45930.540656
711012.9987-2.99866
721414.9376-0.93764
731817.13580.864231
741817.45970.540328
751615.69970.300269
761713.90883.09116
771616.2769-0.276851
781614.5941.40597
791315.5679-2.5679
801614.73021.26978
811615.63270.367339
821615.48410.515929
831515.3038-0.303838
841514.83140.168648
851614.33191.66811
861414.477-0.476993
871615.83070.169313
881615.29670.703329
891514.32330.676665
901214.0471-2.04705
911717.0352-0.0351826
921615.46670.533265
931514.96260.0373852
941314.8261-1.82611
951614.42791.5721
961615.63190.368135
971613.89662.1034
981616.0328-0.03276
991414.9262-0.926157
1001617.3992-1.39918
1011614.48841.51165
1022017.49152.50849
1031514.47440.525617
1041614.6231.377
1051314.6627-1.66274
1061715.40471.59533
1071615.29310.706927
1081614.2571.74302
1091212.4561-0.456077
1101615.47790.522087
1111616.4048-0.404784
1121715.40671.59331
1131314.5839-1.58389
1141214.6682-2.66822
1151816.39191.60813
1161415.4574-1.45741
1171413.04580.954168
1181314.5325-1.53253
1191615.04840.951601
1201314.3367-1.3367
1211615.45310.546912
1221316.0028-3.00283
1231617.2026-1.20256
1241516.1414-1.14137
1251616.5573-0.557314
1261514.71090.28909
1271715.82431.17574
1281513.53761.46239
1291214.5083-2.50831
1301613.70952.29048
1311013.279-3.27898
1321613.40112.5989
1331214.2659-2.26593
1341415.6807-1.68071
1351515.4005-0.400486
1361312.46260.537434
1371514.2040.795973
1381113.5152-2.51518
1391213.3029-1.30286
1401112.9645-1.96449
1411612.74373.25632
1421513.39851.6015
1431716.28850.711451
1441613.96342.03662
1451013.3274-3.32737
1461815.57532.42471
1471315.256-2.25602
1481615.12290.877103
1491312.54010.459891
1501012.964-2.96397
1511516.1168-1.11682
1521613.49032.50972
1531611.73334.26674
1541411.89442.1056
1551011.9031-1.90309
1561716.19610.803916
1571311.83931.16065
1581513.96721.03281
1591614.87521.12479
1601213.105-1.10497
1611312.36010.639874
1621312.73640.263634
1631212.8739-0.873867
1641715.80851.19149
1651513.65231.34765
1661011.4993-1.49927
1671413.98370.016303
1681114.1567-3.15673
1691314.9543-1.95428
1701614.78361.21643
1711211.04730.952686
1721615.78250.217501
1731213.7221-1.72213
174911.5753-2.57528
1751215.2365-3.23651
1761514.24140.758602
1771212.1681-0.168124
1781212.504-0.503957
1791413.4510.548987
1801213.367-1.367
1811615.18830.811695
1821111.7657-0.765716
1831917.09021.90984
1841515.5207-0.520694
185814.4247-6.42474
1861614.90891.09115
1871714.81212.18788
1881212.0369-0.0369449
1891111.4841-0.48411
1901110.2790.721035
1911414.5118-0.511797
1921615.36070.639279
1931210.0311.96898
1941614.21911.78088
1951314.1088-1.10878
1961515.3458-0.345816
1971612.7853.21498
1981615.09340.906588
1991412.78741.21257
2001614.15961.84037
2011613.79512.20485
2021413.16160.838437
2031113.0763-2.07633
2041214.319-2.31901
2051512.90982.09017
2061514.65420.345778
2071614.85491.14511
2081615.28150.718455
2091113.3691-2.36909
2101514.03820.961817
2111214.449-2.44898
2121215.2466-3.2466
2131513.92891.07113
2141511.82233.17766
2151614.05091.94907
2161412.92961.07037
2171714.6992.30105
2181414.0445-0.0445054
2191312.33190.668149
2201515.4244-0.424449
2211314.3547-1.35474
2221414.1656-0.165598
2231514.45280.547206
2241212.6563-0.656333
2251312.6010.398992
226811.5315-3.53152
2271413.30130.69869
2281412.88151.11847
2291112.2481-1.24806
2301213.026-1.02604
2311311.66661.33335
2321013.4791-3.47905
2331611.22994.77008
2341815.67722.32282
2351314.0181-1.0181
2361112.7432-1.74316
237410.7236-6.72362
2381313.7511-0.751142
2391613.6752.32504
2401011.4678-1.46777
2411212.3061-0.306102
2421213.4925-1.49252
243109.340950.659047
2441311.3981.60197
2451513.23681.76323
2461211.91120.0887858
2471412.99461.00541
2481011.8865-1.88651
2491210.47461.52544
2501211.30690.693088
2511111.3518-0.351817
2521011.4266-1.42659
2531211.3880.612047
2541612.83463.16535
2551213.4812-1.48124
2561413.95030.0496874
2571613.96272.03735
2581411.53462.46536
2591314.2923-1.29235
26048.87378-4.87378
2611513.38131.6187
2621114.4603-3.46034
2631110.6640.335998
2641412.51861.48138

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 13 & 16.2553 & -3.25525 \tabularnewline
2 & 16 & 15.9426 & 0.0573686 \tabularnewline
3 & 19 & 17.4295 & 1.57053 \tabularnewline
4 & 15 & 12.6361 & 2.36386 \tabularnewline
5 & 14 & 16.2386 & -2.23858 \tabularnewline
6 & 13 & 14.9723 & -1.97228 \tabularnewline
7 & 19 & 15.5238 & 3.47618 \tabularnewline
8 & 15 & 16.6342 & -1.63422 \tabularnewline
9 & 14 & 15.9061 & -1.90607 \tabularnewline
10 & 15 & 14.2196 & 0.78038 \tabularnewline
11 & 16 & 14.5543 & 1.4457 \tabularnewline
12 & 16 & 16.1073 & -0.107312 \tabularnewline
13 & 16 & 15.5922 & 0.407799 \tabularnewline
14 & 16 & 15.7316 & 0.268423 \tabularnewline
15 & 17 & 18.3821 & -1.38206 \tabularnewline
16 & 15 & 15.8509 & -0.850867 \tabularnewline
17 & 15 & 14.4307 & 0.569332 \tabularnewline
18 & 20 & 16.4772 & 3.5228 \tabularnewline
19 & 18 & 15.7722 & 2.22779 \tabularnewline
20 & 16 & 15.1309 & 0.869142 \tabularnewline
21 & 16 & 15.2339 & 0.766102 \tabularnewline
22 & 16 & 14.8111 & 1.18886 \tabularnewline
23 & 19 & 16.0414 & 2.95856 \tabularnewline
24 & 16 & 14.9549 & 1.04508 \tabularnewline
25 & 17 & 16.2297 & 0.770291 \tabularnewline
26 & 17 & 16.3725 & 0.627539 \tabularnewline
27 & 16 & 15.4561 & 0.543875 \tabularnewline
28 & 15 & 17.0674 & -2.06736 \tabularnewline
29 & 16 & 15.5563 & 0.443707 \tabularnewline
30 & 14 & 14.2156 & -0.215645 \tabularnewline
31 & 15 & 16.0192 & -1.01924 \tabularnewline
32 & 12 & 12.477 & -0.476963 \tabularnewline
33 & 14 & 14.6447 & -0.644693 \tabularnewline
34 & 16 & 15.5906 & 0.409391 \tabularnewline
35 & 14 & 15.1108 & -1.1108 \tabularnewline
36 & 10 & 12.9403 & -2.94027 \tabularnewline
37 & 10 & 13.1985 & -3.19848 \tabularnewline
38 & 14 & 15.9024 & -1.90235 \tabularnewline
39 & 16 & 14.9835 & 1.01645 \tabularnewline
40 & 16 & 14.8431 & 1.15694 \tabularnewline
41 & 16 & 14.5049 & 1.49514 \tabularnewline
42 & 14 & 15.7931 & -1.79306 \tabularnewline
43 & 20 & 17.6871 & 2.31293 \tabularnewline
44 & 14 & 13.7334 & 0.266611 \tabularnewline
45 & 14 & 14.2525 & -0.252461 \tabularnewline
46 & 11 & 15.194 & -4.19396 \tabularnewline
47 & 14 & 16.0232 & -2.0232 \tabularnewline
48 & 15 & 14.9792 & 0.0208119 \tabularnewline
49 & 16 & 15.6254 & 0.374587 \tabularnewline
50 & 14 & 15.7573 & -1.75733 \tabularnewline
51 & 16 & 17.3736 & -1.37364 \tabularnewline
52 & 14 & 14.5036 & -0.503639 \tabularnewline
53 & 12 & 14.8106 & -2.81059 \tabularnewline
54 & 16 & 15.7517 & 0.248333 \tabularnewline
55 & 9 & 11.7725 & -2.77255 \tabularnewline
56 & 14 & 11.9562 & 2.04384 \tabularnewline
57 & 16 & 15.6178 & 0.382218 \tabularnewline
58 & 16 & 15.1595 & 0.840496 \tabularnewline
59 & 15 & 14.6619 & 0.3381 \tabularnewline
60 & 16 & 14.0356 & 1.96439 \tabularnewline
61 & 12 & 11.6684 & 0.331628 \tabularnewline
62 & 16 & 15.7999 & 0.200056 \tabularnewline
63 & 16 & 16.8577 & -0.857683 \tabularnewline
64 & 14 & 15.0734 & -1.07337 \tabularnewline
65 & 16 & 15.04 & 0.960044 \tabularnewline
66 & 17 & 16.1586 & 0.841439 \tabularnewline
67 & 18 & 16.5951 & 1.40492 \tabularnewline
68 & 18 & 14.1458 & 3.85419 \tabularnewline
69 & 12 & 15.8469 & -3.84692 \tabularnewline
70 & 16 & 15.4593 & 0.540656 \tabularnewline
71 & 10 & 12.9987 & -2.99866 \tabularnewline
72 & 14 & 14.9376 & -0.93764 \tabularnewline
73 & 18 & 17.1358 & 0.864231 \tabularnewline
74 & 18 & 17.4597 & 0.540328 \tabularnewline
75 & 16 & 15.6997 & 0.300269 \tabularnewline
76 & 17 & 13.9088 & 3.09116 \tabularnewline
77 & 16 & 16.2769 & -0.276851 \tabularnewline
78 & 16 & 14.594 & 1.40597 \tabularnewline
79 & 13 & 15.5679 & -2.5679 \tabularnewline
80 & 16 & 14.7302 & 1.26978 \tabularnewline
81 & 16 & 15.6327 & 0.367339 \tabularnewline
82 & 16 & 15.4841 & 0.515929 \tabularnewline
83 & 15 & 15.3038 & -0.303838 \tabularnewline
84 & 15 & 14.8314 & 0.168648 \tabularnewline
85 & 16 & 14.3319 & 1.66811 \tabularnewline
86 & 14 & 14.477 & -0.476993 \tabularnewline
87 & 16 & 15.8307 & 0.169313 \tabularnewline
88 & 16 & 15.2967 & 0.703329 \tabularnewline
89 & 15 & 14.3233 & 0.676665 \tabularnewline
90 & 12 & 14.0471 & -2.04705 \tabularnewline
91 & 17 & 17.0352 & -0.0351826 \tabularnewline
92 & 16 & 15.4667 & 0.533265 \tabularnewline
93 & 15 & 14.9626 & 0.0373852 \tabularnewline
94 & 13 & 14.8261 & -1.82611 \tabularnewline
95 & 16 & 14.4279 & 1.5721 \tabularnewline
96 & 16 & 15.6319 & 0.368135 \tabularnewline
97 & 16 & 13.8966 & 2.1034 \tabularnewline
98 & 16 & 16.0328 & -0.03276 \tabularnewline
99 & 14 & 14.9262 & -0.926157 \tabularnewline
100 & 16 & 17.3992 & -1.39918 \tabularnewline
101 & 16 & 14.4884 & 1.51165 \tabularnewline
102 & 20 & 17.4915 & 2.50849 \tabularnewline
103 & 15 & 14.4744 & 0.525617 \tabularnewline
104 & 16 & 14.623 & 1.377 \tabularnewline
105 & 13 & 14.6627 & -1.66274 \tabularnewline
106 & 17 & 15.4047 & 1.59533 \tabularnewline
107 & 16 & 15.2931 & 0.706927 \tabularnewline
108 & 16 & 14.257 & 1.74302 \tabularnewline
109 & 12 & 12.4561 & -0.456077 \tabularnewline
110 & 16 & 15.4779 & 0.522087 \tabularnewline
111 & 16 & 16.4048 & -0.404784 \tabularnewline
112 & 17 & 15.4067 & 1.59331 \tabularnewline
113 & 13 & 14.5839 & -1.58389 \tabularnewline
114 & 12 & 14.6682 & -2.66822 \tabularnewline
115 & 18 & 16.3919 & 1.60813 \tabularnewline
116 & 14 & 15.4574 & -1.45741 \tabularnewline
117 & 14 & 13.0458 & 0.954168 \tabularnewline
118 & 13 & 14.5325 & -1.53253 \tabularnewline
119 & 16 & 15.0484 & 0.951601 \tabularnewline
120 & 13 & 14.3367 & -1.3367 \tabularnewline
121 & 16 & 15.4531 & 0.546912 \tabularnewline
122 & 13 & 16.0028 & -3.00283 \tabularnewline
123 & 16 & 17.2026 & -1.20256 \tabularnewline
124 & 15 & 16.1414 & -1.14137 \tabularnewline
125 & 16 & 16.5573 & -0.557314 \tabularnewline
126 & 15 & 14.7109 & 0.28909 \tabularnewline
127 & 17 & 15.8243 & 1.17574 \tabularnewline
128 & 15 & 13.5376 & 1.46239 \tabularnewline
129 & 12 & 14.5083 & -2.50831 \tabularnewline
130 & 16 & 13.7095 & 2.29048 \tabularnewline
131 & 10 & 13.279 & -3.27898 \tabularnewline
132 & 16 & 13.4011 & 2.5989 \tabularnewline
133 & 12 & 14.2659 & -2.26593 \tabularnewline
134 & 14 & 15.6807 & -1.68071 \tabularnewline
135 & 15 & 15.4005 & -0.400486 \tabularnewline
136 & 13 & 12.4626 & 0.537434 \tabularnewline
137 & 15 & 14.204 & 0.795973 \tabularnewline
138 & 11 & 13.5152 & -2.51518 \tabularnewline
139 & 12 & 13.3029 & -1.30286 \tabularnewline
140 & 11 & 12.9645 & -1.96449 \tabularnewline
141 & 16 & 12.7437 & 3.25632 \tabularnewline
142 & 15 & 13.3985 & 1.6015 \tabularnewline
143 & 17 & 16.2885 & 0.711451 \tabularnewline
144 & 16 & 13.9634 & 2.03662 \tabularnewline
145 & 10 & 13.3274 & -3.32737 \tabularnewline
146 & 18 & 15.5753 & 2.42471 \tabularnewline
147 & 13 & 15.256 & -2.25602 \tabularnewline
148 & 16 & 15.1229 & 0.877103 \tabularnewline
149 & 13 & 12.5401 & 0.459891 \tabularnewline
150 & 10 & 12.964 & -2.96397 \tabularnewline
151 & 15 & 16.1168 & -1.11682 \tabularnewline
152 & 16 & 13.4903 & 2.50972 \tabularnewline
153 & 16 & 11.7333 & 4.26674 \tabularnewline
154 & 14 & 11.8944 & 2.1056 \tabularnewline
155 & 10 & 11.9031 & -1.90309 \tabularnewline
156 & 17 & 16.1961 & 0.803916 \tabularnewline
157 & 13 & 11.8393 & 1.16065 \tabularnewline
158 & 15 & 13.9672 & 1.03281 \tabularnewline
159 & 16 & 14.8752 & 1.12479 \tabularnewline
160 & 12 & 13.105 & -1.10497 \tabularnewline
161 & 13 & 12.3601 & 0.639874 \tabularnewline
162 & 13 & 12.7364 & 0.263634 \tabularnewline
163 & 12 & 12.8739 & -0.873867 \tabularnewline
164 & 17 & 15.8085 & 1.19149 \tabularnewline
165 & 15 & 13.6523 & 1.34765 \tabularnewline
166 & 10 & 11.4993 & -1.49927 \tabularnewline
167 & 14 & 13.9837 & 0.016303 \tabularnewline
168 & 11 & 14.1567 & -3.15673 \tabularnewline
169 & 13 & 14.9543 & -1.95428 \tabularnewline
170 & 16 & 14.7836 & 1.21643 \tabularnewline
171 & 12 & 11.0473 & 0.952686 \tabularnewline
172 & 16 & 15.7825 & 0.217501 \tabularnewline
173 & 12 & 13.7221 & -1.72213 \tabularnewline
174 & 9 & 11.5753 & -2.57528 \tabularnewline
175 & 12 & 15.2365 & -3.23651 \tabularnewline
176 & 15 & 14.2414 & 0.758602 \tabularnewline
177 & 12 & 12.1681 & -0.168124 \tabularnewline
178 & 12 & 12.504 & -0.503957 \tabularnewline
179 & 14 & 13.451 & 0.548987 \tabularnewline
180 & 12 & 13.367 & -1.367 \tabularnewline
181 & 16 & 15.1883 & 0.811695 \tabularnewline
182 & 11 & 11.7657 & -0.765716 \tabularnewline
183 & 19 & 17.0902 & 1.90984 \tabularnewline
184 & 15 & 15.5207 & -0.520694 \tabularnewline
185 & 8 & 14.4247 & -6.42474 \tabularnewline
186 & 16 & 14.9089 & 1.09115 \tabularnewline
187 & 17 & 14.8121 & 2.18788 \tabularnewline
188 & 12 & 12.0369 & -0.0369449 \tabularnewline
189 & 11 & 11.4841 & -0.48411 \tabularnewline
190 & 11 & 10.279 & 0.721035 \tabularnewline
191 & 14 & 14.5118 & -0.511797 \tabularnewline
192 & 16 & 15.3607 & 0.639279 \tabularnewline
193 & 12 & 10.031 & 1.96898 \tabularnewline
194 & 16 & 14.2191 & 1.78088 \tabularnewline
195 & 13 & 14.1088 & -1.10878 \tabularnewline
196 & 15 & 15.3458 & -0.345816 \tabularnewline
197 & 16 & 12.785 & 3.21498 \tabularnewline
198 & 16 & 15.0934 & 0.906588 \tabularnewline
199 & 14 & 12.7874 & 1.21257 \tabularnewline
200 & 16 & 14.1596 & 1.84037 \tabularnewline
201 & 16 & 13.7951 & 2.20485 \tabularnewline
202 & 14 & 13.1616 & 0.838437 \tabularnewline
203 & 11 & 13.0763 & -2.07633 \tabularnewline
204 & 12 & 14.319 & -2.31901 \tabularnewline
205 & 15 & 12.9098 & 2.09017 \tabularnewline
206 & 15 & 14.6542 & 0.345778 \tabularnewline
207 & 16 & 14.8549 & 1.14511 \tabularnewline
208 & 16 & 15.2815 & 0.718455 \tabularnewline
209 & 11 & 13.3691 & -2.36909 \tabularnewline
210 & 15 & 14.0382 & 0.961817 \tabularnewline
211 & 12 & 14.449 & -2.44898 \tabularnewline
212 & 12 & 15.2466 & -3.2466 \tabularnewline
213 & 15 & 13.9289 & 1.07113 \tabularnewline
214 & 15 & 11.8223 & 3.17766 \tabularnewline
215 & 16 & 14.0509 & 1.94907 \tabularnewline
216 & 14 & 12.9296 & 1.07037 \tabularnewline
217 & 17 & 14.699 & 2.30105 \tabularnewline
218 & 14 & 14.0445 & -0.0445054 \tabularnewline
219 & 13 & 12.3319 & 0.668149 \tabularnewline
220 & 15 & 15.4244 & -0.424449 \tabularnewline
221 & 13 & 14.3547 & -1.35474 \tabularnewline
222 & 14 & 14.1656 & -0.165598 \tabularnewline
223 & 15 & 14.4528 & 0.547206 \tabularnewline
224 & 12 & 12.6563 & -0.656333 \tabularnewline
225 & 13 & 12.601 & 0.398992 \tabularnewline
226 & 8 & 11.5315 & -3.53152 \tabularnewline
227 & 14 & 13.3013 & 0.69869 \tabularnewline
228 & 14 & 12.8815 & 1.11847 \tabularnewline
229 & 11 & 12.2481 & -1.24806 \tabularnewline
230 & 12 & 13.026 & -1.02604 \tabularnewline
231 & 13 & 11.6666 & 1.33335 \tabularnewline
232 & 10 & 13.4791 & -3.47905 \tabularnewline
233 & 16 & 11.2299 & 4.77008 \tabularnewline
234 & 18 & 15.6772 & 2.32282 \tabularnewline
235 & 13 & 14.0181 & -1.0181 \tabularnewline
236 & 11 & 12.7432 & -1.74316 \tabularnewline
237 & 4 & 10.7236 & -6.72362 \tabularnewline
238 & 13 & 13.7511 & -0.751142 \tabularnewline
239 & 16 & 13.675 & 2.32504 \tabularnewline
240 & 10 & 11.4678 & -1.46777 \tabularnewline
241 & 12 & 12.3061 & -0.306102 \tabularnewline
242 & 12 & 13.4925 & -1.49252 \tabularnewline
243 & 10 & 9.34095 & 0.659047 \tabularnewline
244 & 13 & 11.398 & 1.60197 \tabularnewline
245 & 15 & 13.2368 & 1.76323 \tabularnewline
246 & 12 & 11.9112 & 0.0887858 \tabularnewline
247 & 14 & 12.9946 & 1.00541 \tabularnewline
248 & 10 & 11.8865 & -1.88651 \tabularnewline
249 & 12 & 10.4746 & 1.52544 \tabularnewline
250 & 12 & 11.3069 & 0.693088 \tabularnewline
251 & 11 & 11.3518 & -0.351817 \tabularnewline
252 & 10 & 11.4266 & -1.42659 \tabularnewline
253 & 12 & 11.388 & 0.612047 \tabularnewline
254 & 16 & 12.8346 & 3.16535 \tabularnewline
255 & 12 & 13.4812 & -1.48124 \tabularnewline
256 & 14 & 13.9503 & 0.0496874 \tabularnewline
257 & 16 & 13.9627 & 2.03735 \tabularnewline
258 & 14 & 11.5346 & 2.46536 \tabularnewline
259 & 13 & 14.2923 & -1.29235 \tabularnewline
260 & 4 & 8.87378 & -4.87378 \tabularnewline
261 & 15 & 13.3813 & 1.6187 \tabularnewline
262 & 11 & 14.4603 & -3.46034 \tabularnewline
263 & 11 & 10.664 & 0.335998 \tabularnewline
264 & 14 & 12.5186 & 1.48138 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&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]13[/C][C]16.2553[/C][C]-3.25525[/C][/ROW]
[ROW][C]2[/C][C]16[/C][C]15.9426[/C][C]0.0573686[/C][/ROW]
[ROW][C]3[/C][C]19[/C][C]17.4295[/C][C]1.57053[/C][/ROW]
[ROW][C]4[/C][C]15[/C][C]12.6361[/C][C]2.36386[/C][/ROW]
[ROW][C]5[/C][C]14[/C][C]16.2386[/C][C]-2.23858[/C][/ROW]
[ROW][C]6[/C][C]13[/C][C]14.9723[/C][C]-1.97228[/C][/ROW]
[ROW][C]7[/C][C]19[/C][C]15.5238[/C][C]3.47618[/C][/ROW]
[ROW][C]8[/C][C]15[/C][C]16.6342[/C][C]-1.63422[/C][/ROW]
[ROW][C]9[/C][C]14[/C][C]15.9061[/C][C]-1.90607[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.2196[/C][C]0.78038[/C][/ROW]
[ROW][C]11[/C][C]16[/C][C]14.5543[/C][C]1.4457[/C][/ROW]
[ROW][C]12[/C][C]16[/C][C]16.1073[/C][C]-0.107312[/C][/ROW]
[ROW][C]13[/C][C]16[/C][C]15.5922[/C][C]0.407799[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]15.7316[/C][C]0.268423[/C][/ROW]
[ROW][C]15[/C][C]17[/C][C]18.3821[/C][C]-1.38206[/C][/ROW]
[ROW][C]16[/C][C]15[/C][C]15.8509[/C][C]-0.850867[/C][/ROW]
[ROW][C]17[/C][C]15[/C][C]14.4307[/C][C]0.569332[/C][/ROW]
[ROW][C]18[/C][C]20[/C][C]16.4772[/C][C]3.5228[/C][/ROW]
[ROW][C]19[/C][C]18[/C][C]15.7722[/C][C]2.22779[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]15.1309[/C][C]0.869142[/C][/ROW]
[ROW][C]21[/C][C]16[/C][C]15.2339[/C][C]0.766102[/C][/ROW]
[ROW][C]22[/C][C]16[/C][C]14.8111[/C][C]1.18886[/C][/ROW]
[ROW][C]23[/C][C]19[/C][C]16.0414[/C][C]2.95856[/C][/ROW]
[ROW][C]24[/C][C]16[/C][C]14.9549[/C][C]1.04508[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]16.2297[/C][C]0.770291[/C][/ROW]
[ROW][C]26[/C][C]17[/C][C]16.3725[/C][C]0.627539[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.4561[/C][C]0.543875[/C][/ROW]
[ROW][C]28[/C][C]15[/C][C]17.0674[/C][C]-2.06736[/C][/ROW]
[ROW][C]29[/C][C]16[/C][C]15.5563[/C][C]0.443707[/C][/ROW]
[ROW][C]30[/C][C]14[/C][C]14.2156[/C][C]-0.215645[/C][/ROW]
[ROW][C]31[/C][C]15[/C][C]16.0192[/C][C]-1.01924[/C][/ROW]
[ROW][C]32[/C][C]12[/C][C]12.477[/C][C]-0.476963[/C][/ROW]
[ROW][C]33[/C][C]14[/C][C]14.6447[/C][C]-0.644693[/C][/ROW]
[ROW][C]34[/C][C]16[/C][C]15.5906[/C][C]0.409391[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]15.1108[/C][C]-1.1108[/C][/ROW]
[ROW][C]36[/C][C]10[/C][C]12.9403[/C][C]-2.94027[/C][/ROW]
[ROW][C]37[/C][C]10[/C][C]13.1985[/C][C]-3.19848[/C][/ROW]
[ROW][C]38[/C][C]14[/C][C]15.9024[/C][C]-1.90235[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]14.9835[/C][C]1.01645[/C][/ROW]
[ROW][C]40[/C][C]16[/C][C]14.8431[/C][C]1.15694[/C][/ROW]
[ROW][C]41[/C][C]16[/C][C]14.5049[/C][C]1.49514[/C][/ROW]
[ROW][C]42[/C][C]14[/C][C]15.7931[/C][C]-1.79306[/C][/ROW]
[ROW][C]43[/C][C]20[/C][C]17.6871[/C][C]2.31293[/C][/ROW]
[ROW][C]44[/C][C]14[/C][C]13.7334[/C][C]0.266611[/C][/ROW]
[ROW][C]45[/C][C]14[/C][C]14.2525[/C][C]-0.252461[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]15.194[/C][C]-4.19396[/C][/ROW]
[ROW][C]47[/C][C]14[/C][C]16.0232[/C][C]-2.0232[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.9792[/C][C]0.0208119[/C][/ROW]
[ROW][C]49[/C][C]16[/C][C]15.6254[/C][C]0.374587[/C][/ROW]
[ROW][C]50[/C][C]14[/C][C]15.7573[/C][C]-1.75733[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]17.3736[/C][C]-1.37364[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]14.5036[/C][C]-0.503639[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]14.8106[/C][C]-2.81059[/C][/ROW]
[ROW][C]54[/C][C]16[/C][C]15.7517[/C][C]0.248333[/C][/ROW]
[ROW][C]55[/C][C]9[/C][C]11.7725[/C][C]-2.77255[/C][/ROW]
[ROW][C]56[/C][C]14[/C][C]11.9562[/C][C]2.04384[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]15.6178[/C][C]0.382218[/C][/ROW]
[ROW][C]58[/C][C]16[/C][C]15.1595[/C][C]0.840496[/C][/ROW]
[ROW][C]59[/C][C]15[/C][C]14.6619[/C][C]0.3381[/C][/ROW]
[ROW][C]60[/C][C]16[/C][C]14.0356[/C][C]1.96439[/C][/ROW]
[ROW][C]61[/C][C]12[/C][C]11.6684[/C][C]0.331628[/C][/ROW]
[ROW][C]62[/C][C]16[/C][C]15.7999[/C][C]0.200056[/C][/ROW]
[ROW][C]63[/C][C]16[/C][C]16.8577[/C][C]-0.857683[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]15.0734[/C][C]-1.07337[/C][/ROW]
[ROW][C]65[/C][C]16[/C][C]15.04[/C][C]0.960044[/C][/ROW]
[ROW][C]66[/C][C]17[/C][C]16.1586[/C][C]0.841439[/C][/ROW]
[ROW][C]67[/C][C]18[/C][C]16.5951[/C][C]1.40492[/C][/ROW]
[ROW][C]68[/C][C]18[/C][C]14.1458[/C][C]3.85419[/C][/ROW]
[ROW][C]69[/C][C]12[/C][C]15.8469[/C][C]-3.84692[/C][/ROW]
[ROW][C]70[/C][C]16[/C][C]15.4593[/C][C]0.540656[/C][/ROW]
[ROW][C]71[/C][C]10[/C][C]12.9987[/C][C]-2.99866[/C][/ROW]
[ROW][C]72[/C][C]14[/C][C]14.9376[/C][C]-0.93764[/C][/ROW]
[ROW][C]73[/C][C]18[/C][C]17.1358[/C][C]0.864231[/C][/ROW]
[ROW][C]74[/C][C]18[/C][C]17.4597[/C][C]0.540328[/C][/ROW]
[ROW][C]75[/C][C]16[/C][C]15.6997[/C][C]0.300269[/C][/ROW]
[ROW][C]76[/C][C]17[/C][C]13.9088[/C][C]3.09116[/C][/ROW]
[ROW][C]77[/C][C]16[/C][C]16.2769[/C][C]-0.276851[/C][/ROW]
[ROW][C]78[/C][C]16[/C][C]14.594[/C][C]1.40597[/C][/ROW]
[ROW][C]79[/C][C]13[/C][C]15.5679[/C][C]-2.5679[/C][/ROW]
[ROW][C]80[/C][C]16[/C][C]14.7302[/C][C]1.26978[/C][/ROW]
[ROW][C]81[/C][C]16[/C][C]15.6327[/C][C]0.367339[/C][/ROW]
[ROW][C]82[/C][C]16[/C][C]15.4841[/C][C]0.515929[/C][/ROW]
[ROW][C]83[/C][C]15[/C][C]15.3038[/C][C]-0.303838[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.8314[/C][C]0.168648[/C][/ROW]
[ROW][C]85[/C][C]16[/C][C]14.3319[/C][C]1.66811[/C][/ROW]
[ROW][C]86[/C][C]14[/C][C]14.477[/C][C]-0.476993[/C][/ROW]
[ROW][C]87[/C][C]16[/C][C]15.8307[/C][C]0.169313[/C][/ROW]
[ROW][C]88[/C][C]16[/C][C]15.2967[/C][C]0.703329[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]14.3233[/C][C]0.676665[/C][/ROW]
[ROW][C]90[/C][C]12[/C][C]14.0471[/C][C]-2.04705[/C][/ROW]
[ROW][C]91[/C][C]17[/C][C]17.0352[/C][C]-0.0351826[/C][/ROW]
[ROW][C]92[/C][C]16[/C][C]15.4667[/C][C]0.533265[/C][/ROW]
[ROW][C]93[/C][C]15[/C][C]14.9626[/C][C]0.0373852[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.8261[/C][C]-1.82611[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]14.4279[/C][C]1.5721[/C][/ROW]
[ROW][C]96[/C][C]16[/C][C]15.6319[/C][C]0.368135[/C][/ROW]
[ROW][C]97[/C][C]16[/C][C]13.8966[/C][C]2.1034[/C][/ROW]
[ROW][C]98[/C][C]16[/C][C]16.0328[/C][C]-0.03276[/C][/ROW]
[ROW][C]99[/C][C]14[/C][C]14.9262[/C][C]-0.926157[/C][/ROW]
[ROW][C]100[/C][C]16[/C][C]17.3992[/C][C]-1.39918[/C][/ROW]
[ROW][C]101[/C][C]16[/C][C]14.4884[/C][C]1.51165[/C][/ROW]
[ROW][C]102[/C][C]20[/C][C]17.4915[/C][C]2.50849[/C][/ROW]
[ROW][C]103[/C][C]15[/C][C]14.4744[/C][C]0.525617[/C][/ROW]
[ROW][C]104[/C][C]16[/C][C]14.623[/C][C]1.377[/C][/ROW]
[ROW][C]105[/C][C]13[/C][C]14.6627[/C][C]-1.66274[/C][/ROW]
[ROW][C]106[/C][C]17[/C][C]15.4047[/C][C]1.59533[/C][/ROW]
[ROW][C]107[/C][C]16[/C][C]15.2931[/C][C]0.706927[/C][/ROW]
[ROW][C]108[/C][C]16[/C][C]14.257[/C][C]1.74302[/C][/ROW]
[ROW][C]109[/C][C]12[/C][C]12.4561[/C][C]-0.456077[/C][/ROW]
[ROW][C]110[/C][C]16[/C][C]15.4779[/C][C]0.522087[/C][/ROW]
[ROW][C]111[/C][C]16[/C][C]16.4048[/C][C]-0.404784[/C][/ROW]
[ROW][C]112[/C][C]17[/C][C]15.4067[/C][C]1.59331[/C][/ROW]
[ROW][C]113[/C][C]13[/C][C]14.5839[/C][C]-1.58389[/C][/ROW]
[ROW][C]114[/C][C]12[/C][C]14.6682[/C][C]-2.66822[/C][/ROW]
[ROW][C]115[/C][C]18[/C][C]16.3919[/C][C]1.60813[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]15.4574[/C][C]-1.45741[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.0458[/C][C]0.954168[/C][/ROW]
[ROW][C]118[/C][C]13[/C][C]14.5325[/C][C]-1.53253[/C][/ROW]
[ROW][C]119[/C][C]16[/C][C]15.0484[/C][C]0.951601[/C][/ROW]
[ROW][C]120[/C][C]13[/C][C]14.3367[/C][C]-1.3367[/C][/ROW]
[ROW][C]121[/C][C]16[/C][C]15.4531[/C][C]0.546912[/C][/ROW]
[ROW][C]122[/C][C]13[/C][C]16.0028[/C][C]-3.00283[/C][/ROW]
[ROW][C]123[/C][C]16[/C][C]17.2026[/C][C]-1.20256[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]16.1414[/C][C]-1.14137[/C][/ROW]
[ROW][C]125[/C][C]16[/C][C]16.5573[/C][C]-0.557314[/C][/ROW]
[ROW][C]126[/C][C]15[/C][C]14.7109[/C][C]0.28909[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.8243[/C][C]1.17574[/C][/ROW]
[ROW][C]128[/C][C]15[/C][C]13.5376[/C][C]1.46239[/C][/ROW]
[ROW][C]129[/C][C]12[/C][C]14.5083[/C][C]-2.50831[/C][/ROW]
[ROW][C]130[/C][C]16[/C][C]13.7095[/C][C]2.29048[/C][/ROW]
[ROW][C]131[/C][C]10[/C][C]13.279[/C][C]-3.27898[/C][/ROW]
[ROW][C]132[/C][C]16[/C][C]13.4011[/C][C]2.5989[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.2659[/C][C]-2.26593[/C][/ROW]
[ROW][C]134[/C][C]14[/C][C]15.6807[/C][C]-1.68071[/C][/ROW]
[ROW][C]135[/C][C]15[/C][C]15.4005[/C][C]-0.400486[/C][/ROW]
[ROW][C]136[/C][C]13[/C][C]12.4626[/C][C]0.537434[/C][/ROW]
[ROW][C]137[/C][C]15[/C][C]14.204[/C][C]0.795973[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]13.5152[/C][C]-2.51518[/C][/ROW]
[ROW][C]139[/C][C]12[/C][C]13.3029[/C][C]-1.30286[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]12.9645[/C][C]-1.96449[/C][/ROW]
[ROW][C]141[/C][C]16[/C][C]12.7437[/C][C]3.25632[/C][/ROW]
[ROW][C]142[/C][C]15[/C][C]13.3985[/C][C]1.6015[/C][/ROW]
[ROW][C]143[/C][C]17[/C][C]16.2885[/C][C]0.711451[/C][/ROW]
[ROW][C]144[/C][C]16[/C][C]13.9634[/C][C]2.03662[/C][/ROW]
[ROW][C]145[/C][C]10[/C][C]13.3274[/C][C]-3.32737[/C][/ROW]
[ROW][C]146[/C][C]18[/C][C]15.5753[/C][C]2.42471[/C][/ROW]
[ROW][C]147[/C][C]13[/C][C]15.256[/C][C]-2.25602[/C][/ROW]
[ROW][C]148[/C][C]16[/C][C]15.1229[/C][C]0.877103[/C][/ROW]
[ROW][C]149[/C][C]13[/C][C]12.5401[/C][C]0.459891[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]12.964[/C][C]-2.96397[/C][/ROW]
[ROW][C]151[/C][C]15[/C][C]16.1168[/C][C]-1.11682[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]13.4903[/C][C]2.50972[/C][/ROW]
[ROW][C]153[/C][C]16[/C][C]11.7333[/C][C]4.26674[/C][/ROW]
[ROW][C]154[/C][C]14[/C][C]11.8944[/C][C]2.1056[/C][/ROW]
[ROW][C]155[/C][C]10[/C][C]11.9031[/C][C]-1.90309[/C][/ROW]
[ROW][C]156[/C][C]17[/C][C]16.1961[/C][C]0.803916[/C][/ROW]
[ROW][C]157[/C][C]13[/C][C]11.8393[/C][C]1.16065[/C][/ROW]
[ROW][C]158[/C][C]15[/C][C]13.9672[/C][C]1.03281[/C][/ROW]
[ROW][C]159[/C][C]16[/C][C]14.8752[/C][C]1.12479[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]13.105[/C][C]-1.10497[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.3601[/C][C]0.639874[/C][/ROW]
[ROW][C]162[/C][C]13[/C][C]12.7364[/C][C]0.263634[/C][/ROW]
[ROW][C]163[/C][C]12[/C][C]12.8739[/C][C]-0.873867[/C][/ROW]
[ROW][C]164[/C][C]17[/C][C]15.8085[/C][C]1.19149[/C][/ROW]
[ROW][C]165[/C][C]15[/C][C]13.6523[/C][C]1.34765[/C][/ROW]
[ROW][C]166[/C][C]10[/C][C]11.4993[/C][C]-1.49927[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]13.9837[/C][C]0.016303[/C][/ROW]
[ROW][C]168[/C][C]11[/C][C]14.1567[/C][C]-3.15673[/C][/ROW]
[ROW][C]169[/C][C]13[/C][C]14.9543[/C][C]-1.95428[/C][/ROW]
[ROW][C]170[/C][C]16[/C][C]14.7836[/C][C]1.21643[/C][/ROW]
[ROW][C]171[/C][C]12[/C][C]11.0473[/C][C]0.952686[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]15.7825[/C][C]0.217501[/C][/ROW]
[ROW][C]173[/C][C]12[/C][C]13.7221[/C][C]-1.72213[/C][/ROW]
[ROW][C]174[/C][C]9[/C][C]11.5753[/C][C]-2.57528[/C][/ROW]
[ROW][C]175[/C][C]12[/C][C]15.2365[/C][C]-3.23651[/C][/ROW]
[ROW][C]176[/C][C]15[/C][C]14.2414[/C][C]0.758602[/C][/ROW]
[ROW][C]177[/C][C]12[/C][C]12.1681[/C][C]-0.168124[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]12.504[/C][C]-0.503957[/C][/ROW]
[ROW][C]179[/C][C]14[/C][C]13.451[/C][C]0.548987[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]13.367[/C][C]-1.367[/C][/ROW]
[ROW][C]181[/C][C]16[/C][C]15.1883[/C][C]0.811695[/C][/ROW]
[ROW][C]182[/C][C]11[/C][C]11.7657[/C][C]-0.765716[/C][/ROW]
[ROW][C]183[/C][C]19[/C][C]17.0902[/C][C]1.90984[/C][/ROW]
[ROW][C]184[/C][C]15[/C][C]15.5207[/C][C]-0.520694[/C][/ROW]
[ROW][C]185[/C][C]8[/C][C]14.4247[/C][C]-6.42474[/C][/ROW]
[ROW][C]186[/C][C]16[/C][C]14.9089[/C][C]1.09115[/C][/ROW]
[ROW][C]187[/C][C]17[/C][C]14.8121[/C][C]2.18788[/C][/ROW]
[ROW][C]188[/C][C]12[/C][C]12.0369[/C][C]-0.0369449[/C][/ROW]
[ROW][C]189[/C][C]11[/C][C]11.4841[/C][C]-0.48411[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.279[/C][C]0.721035[/C][/ROW]
[ROW][C]191[/C][C]14[/C][C]14.5118[/C][C]-0.511797[/C][/ROW]
[ROW][C]192[/C][C]16[/C][C]15.3607[/C][C]0.639279[/C][/ROW]
[ROW][C]193[/C][C]12[/C][C]10.031[/C][C]1.96898[/C][/ROW]
[ROW][C]194[/C][C]16[/C][C]14.2191[/C][C]1.78088[/C][/ROW]
[ROW][C]195[/C][C]13[/C][C]14.1088[/C][C]-1.10878[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]15.3458[/C][C]-0.345816[/C][/ROW]
[ROW][C]197[/C][C]16[/C][C]12.785[/C][C]3.21498[/C][/ROW]
[ROW][C]198[/C][C]16[/C][C]15.0934[/C][C]0.906588[/C][/ROW]
[ROW][C]199[/C][C]14[/C][C]12.7874[/C][C]1.21257[/C][/ROW]
[ROW][C]200[/C][C]16[/C][C]14.1596[/C][C]1.84037[/C][/ROW]
[ROW][C]201[/C][C]16[/C][C]13.7951[/C][C]2.20485[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]13.1616[/C][C]0.838437[/C][/ROW]
[ROW][C]203[/C][C]11[/C][C]13.0763[/C][C]-2.07633[/C][/ROW]
[ROW][C]204[/C][C]12[/C][C]14.319[/C][C]-2.31901[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]12.9098[/C][C]2.09017[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]14.6542[/C][C]0.345778[/C][/ROW]
[ROW][C]207[/C][C]16[/C][C]14.8549[/C][C]1.14511[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]15.2815[/C][C]0.718455[/C][/ROW]
[ROW][C]209[/C][C]11[/C][C]13.3691[/C][C]-2.36909[/C][/ROW]
[ROW][C]210[/C][C]15[/C][C]14.0382[/C][C]0.961817[/C][/ROW]
[ROW][C]211[/C][C]12[/C][C]14.449[/C][C]-2.44898[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]15.2466[/C][C]-3.2466[/C][/ROW]
[ROW][C]213[/C][C]15[/C][C]13.9289[/C][C]1.07113[/C][/ROW]
[ROW][C]214[/C][C]15[/C][C]11.8223[/C][C]3.17766[/C][/ROW]
[ROW][C]215[/C][C]16[/C][C]14.0509[/C][C]1.94907[/C][/ROW]
[ROW][C]216[/C][C]14[/C][C]12.9296[/C][C]1.07037[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.699[/C][C]2.30105[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.0445[/C][C]-0.0445054[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]12.3319[/C][C]0.668149[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]15.4244[/C][C]-0.424449[/C][/ROW]
[ROW][C]221[/C][C]13[/C][C]14.3547[/C][C]-1.35474[/C][/ROW]
[ROW][C]222[/C][C]14[/C][C]14.1656[/C][C]-0.165598[/C][/ROW]
[ROW][C]223[/C][C]15[/C][C]14.4528[/C][C]0.547206[/C][/ROW]
[ROW][C]224[/C][C]12[/C][C]12.6563[/C][C]-0.656333[/C][/ROW]
[ROW][C]225[/C][C]13[/C][C]12.601[/C][C]0.398992[/C][/ROW]
[ROW][C]226[/C][C]8[/C][C]11.5315[/C][C]-3.53152[/C][/ROW]
[ROW][C]227[/C][C]14[/C][C]13.3013[/C][C]0.69869[/C][/ROW]
[ROW][C]228[/C][C]14[/C][C]12.8815[/C][C]1.11847[/C][/ROW]
[ROW][C]229[/C][C]11[/C][C]12.2481[/C][C]-1.24806[/C][/ROW]
[ROW][C]230[/C][C]12[/C][C]13.026[/C][C]-1.02604[/C][/ROW]
[ROW][C]231[/C][C]13[/C][C]11.6666[/C][C]1.33335[/C][/ROW]
[ROW][C]232[/C][C]10[/C][C]13.4791[/C][C]-3.47905[/C][/ROW]
[ROW][C]233[/C][C]16[/C][C]11.2299[/C][C]4.77008[/C][/ROW]
[ROW][C]234[/C][C]18[/C][C]15.6772[/C][C]2.32282[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]14.0181[/C][C]-1.0181[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.7432[/C][C]-1.74316[/C][/ROW]
[ROW][C]237[/C][C]4[/C][C]10.7236[/C][C]-6.72362[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]13.7511[/C][C]-0.751142[/C][/ROW]
[ROW][C]239[/C][C]16[/C][C]13.675[/C][C]2.32504[/C][/ROW]
[ROW][C]240[/C][C]10[/C][C]11.4678[/C][C]-1.46777[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]12.3061[/C][C]-0.306102[/C][/ROW]
[ROW][C]242[/C][C]12[/C][C]13.4925[/C][C]-1.49252[/C][/ROW]
[ROW][C]243[/C][C]10[/C][C]9.34095[/C][C]0.659047[/C][/ROW]
[ROW][C]244[/C][C]13[/C][C]11.398[/C][C]1.60197[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.2368[/C][C]1.76323[/C][/ROW]
[ROW][C]246[/C][C]12[/C][C]11.9112[/C][C]0.0887858[/C][/ROW]
[ROW][C]247[/C][C]14[/C][C]12.9946[/C][C]1.00541[/C][/ROW]
[ROW][C]248[/C][C]10[/C][C]11.8865[/C][C]-1.88651[/C][/ROW]
[ROW][C]249[/C][C]12[/C][C]10.4746[/C][C]1.52544[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.3069[/C][C]0.693088[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]11.3518[/C][C]-0.351817[/C][/ROW]
[ROW][C]252[/C][C]10[/C][C]11.4266[/C][C]-1.42659[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]11.388[/C][C]0.612047[/C][/ROW]
[ROW][C]254[/C][C]16[/C][C]12.8346[/C][C]3.16535[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]13.4812[/C][C]-1.48124[/C][/ROW]
[ROW][C]256[/C][C]14[/C][C]13.9503[/C][C]0.0496874[/C][/ROW]
[ROW][C]257[/C][C]16[/C][C]13.9627[/C][C]2.03735[/C][/ROW]
[ROW][C]258[/C][C]14[/C][C]11.5346[/C][C]2.46536[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.2923[/C][C]-1.29235[/C][/ROW]
[ROW][C]260[/C][C]4[/C][C]8.87378[/C][C]-4.87378[/C][/ROW]
[ROW][C]261[/C][C]15[/C][C]13.3813[/C][C]1.6187[/C][/ROW]
[ROW][C]262[/C][C]11[/C][C]14.4603[/C][C]-3.46034[/C][/ROW]
[ROW][C]263[/C][C]11[/C][C]10.664[/C][C]0.335998[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]12.5186[/C][C]1.48138[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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
11316.2553-3.25525
21615.94260.0573686
31917.42951.57053
41512.63612.36386
51416.2386-2.23858
61314.9723-1.97228
71915.52383.47618
81516.6342-1.63422
91415.9061-1.90607
101514.21960.78038
111614.55431.4457
121616.1073-0.107312
131615.59220.407799
141615.73160.268423
151718.3821-1.38206
161515.8509-0.850867
171514.43070.569332
182016.47723.5228
191815.77222.22779
201615.13090.869142
211615.23390.766102
221614.81111.18886
231916.04142.95856
241614.95491.04508
251716.22970.770291
261716.37250.627539
271615.45610.543875
281517.0674-2.06736
291615.55630.443707
301414.2156-0.215645
311516.0192-1.01924
321212.477-0.476963
331414.6447-0.644693
341615.59060.409391
351415.1108-1.1108
361012.9403-2.94027
371013.1985-3.19848
381415.9024-1.90235
391614.98351.01645
401614.84311.15694
411614.50491.49514
421415.7931-1.79306
432017.68712.31293
441413.73340.266611
451414.2525-0.252461
461115.194-4.19396
471416.0232-2.0232
481514.97920.0208119
491615.62540.374587
501415.7573-1.75733
511617.3736-1.37364
521414.5036-0.503639
531214.8106-2.81059
541615.75170.248333
55911.7725-2.77255
561411.95622.04384
571615.61780.382218
581615.15950.840496
591514.66190.3381
601614.03561.96439
611211.66840.331628
621615.79990.200056
631616.8577-0.857683
641415.0734-1.07337
651615.040.960044
661716.15860.841439
671816.59511.40492
681814.14583.85419
691215.8469-3.84692
701615.45930.540656
711012.9987-2.99866
721414.9376-0.93764
731817.13580.864231
741817.45970.540328
751615.69970.300269
761713.90883.09116
771616.2769-0.276851
781614.5941.40597
791315.5679-2.5679
801614.73021.26978
811615.63270.367339
821615.48410.515929
831515.3038-0.303838
841514.83140.168648
851614.33191.66811
861414.477-0.476993
871615.83070.169313
881615.29670.703329
891514.32330.676665
901214.0471-2.04705
911717.0352-0.0351826
921615.46670.533265
931514.96260.0373852
941314.8261-1.82611
951614.42791.5721
961615.63190.368135
971613.89662.1034
981616.0328-0.03276
991414.9262-0.926157
1001617.3992-1.39918
1011614.48841.51165
1022017.49152.50849
1031514.47440.525617
1041614.6231.377
1051314.6627-1.66274
1061715.40471.59533
1071615.29310.706927
1081614.2571.74302
1091212.4561-0.456077
1101615.47790.522087
1111616.4048-0.404784
1121715.40671.59331
1131314.5839-1.58389
1141214.6682-2.66822
1151816.39191.60813
1161415.4574-1.45741
1171413.04580.954168
1181314.5325-1.53253
1191615.04840.951601
1201314.3367-1.3367
1211615.45310.546912
1221316.0028-3.00283
1231617.2026-1.20256
1241516.1414-1.14137
1251616.5573-0.557314
1261514.71090.28909
1271715.82431.17574
1281513.53761.46239
1291214.5083-2.50831
1301613.70952.29048
1311013.279-3.27898
1321613.40112.5989
1331214.2659-2.26593
1341415.6807-1.68071
1351515.4005-0.400486
1361312.46260.537434
1371514.2040.795973
1381113.5152-2.51518
1391213.3029-1.30286
1401112.9645-1.96449
1411612.74373.25632
1421513.39851.6015
1431716.28850.711451
1441613.96342.03662
1451013.3274-3.32737
1461815.57532.42471
1471315.256-2.25602
1481615.12290.877103
1491312.54010.459891
1501012.964-2.96397
1511516.1168-1.11682
1521613.49032.50972
1531611.73334.26674
1541411.89442.1056
1551011.9031-1.90309
1561716.19610.803916
1571311.83931.16065
1581513.96721.03281
1591614.87521.12479
1601213.105-1.10497
1611312.36010.639874
1621312.73640.263634
1631212.8739-0.873867
1641715.80851.19149
1651513.65231.34765
1661011.4993-1.49927
1671413.98370.016303
1681114.1567-3.15673
1691314.9543-1.95428
1701614.78361.21643
1711211.04730.952686
1721615.78250.217501
1731213.7221-1.72213
174911.5753-2.57528
1751215.2365-3.23651
1761514.24140.758602
1771212.1681-0.168124
1781212.504-0.503957
1791413.4510.548987
1801213.367-1.367
1811615.18830.811695
1821111.7657-0.765716
1831917.09021.90984
1841515.5207-0.520694
185814.4247-6.42474
1861614.90891.09115
1871714.81212.18788
1881212.0369-0.0369449
1891111.4841-0.48411
1901110.2790.721035
1911414.5118-0.511797
1921615.36070.639279
1931210.0311.96898
1941614.21911.78088
1951314.1088-1.10878
1961515.3458-0.345816
1971612.7853.21498
1981615.09340.906588
1991412.78741.21257
2001614.15961.84037
2011613.79512.20485
2021413.16160.838437
2031113.0763-2.07633
2041214.319-2.31901
2051512.90982.09017
2061514.65420.345778
2071614.85491.14511
2081615.28150.718455
2091113.3691-2.36909
2101514.03820.961817
2111214.449-2.44898
2121215.2466-3.2466
2131513.92891.07113
2141511.82233.17766
2151614.05091.94907
2161412.92961.07037
2171714.6992.30105
2181414.0445-0.0445054
2191312.33190.668149
2201515.4244-0.424449
2211314.3547-1.35474
2221414.1656-0.165598
2231514.45280.547206
2241212.6563-0.656333
2251312.6010.398992
226811.5315-3.53152
2271413.30130.69869
2281412.88151.11847
2291112.2481-1.24806
2301213.026-1.02604
2311311.66661.33335
2321013.4791-3.47905
2331611.22994.77008
2341815.67722.32282
2351314.0181-1.0181
2361112.7432-1.74316
237410.7236-6.72362
2381313.7511-0.751142
2391613.6752.32504
2401011.4678-1.46777
2411212.3061-0.306102
2421213.4925-1.49252
243109.340950.659047
2441311.3981.60197
2451513.23681.76323
2461211.91120.0887858
2471412.99461.00541
2481011.8865-1.88651
2491210.47461.52544
2501211.30690.693088
2511111.3518-0.351817
2521011.4266-1.42659
2531211.3880.612047
2541612.83463.16535
2551213.4812-1.48124
2561413.95030.0496874
2571613.96272.03735
2581411.53462.46536
2591314.2923-1.29235
26048.87378-4.87378
2611513.38131.6187
2621114.4603-3.46034
2631110.6640.335998
2641412.51861.48138






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
240.8709410.2581180.129059
250.8454740.3090530.154526
260.7563830.4872340.243617
270.6500130.6999740.349987
280.6935710.6128570.306429
290.6036870.7926260.396313
300.7465810.5068380.253419
310.803790.3924210.19621
320.7522980.4954050.247702
330.7012880.5974240.298712
340.6347720.7304560.365228
350.5815990.8368010.418401
360.6646430.6707150.335357
370.6109450.7781110.389055
380.5681070.8637850.431893
390.507690.984620.49231
400.4422460.8844930.557754
410.3814730.7629450.618527
420.3252840.6505690.674716
430.2913890.5827780.708611
440.2417870.4835740.758213
450.2008910.4017820.799109
460.3464440.6928880.653556
470.5085440.9829130.491456
480.5025370.9949260.497463
490.5822420.8355160.417758
500.5457180.9085630.454282
510.5091130.9817730.490887
520.4544870.9089740.545513
530.4451110.8902230.554889
540.3921470.7842930.607853
550.4556330.9112660.544367
560.4189140.8378280.581086
570.3776330.7552660.622367
580.4045630.8091270.595437
590.367570.735140.63243
600.400330.800660.59967
610.3825220.7650440.617478
620.3562020.7124050.643798
630.322640.6452790.67736
640.2847330.5694660.715267
650.2543070.5086150.745693
660.2180590.4361180.781941
670.1944810.3889610.805519
680.2360080.4720160.763992
690.3791190.7582370.620881
700.3363810.6727620.663619
710.4935790.9871570.506421
720.4534770.9069540.546523
730.4526570.9053140.547343
740.4344180.8688350.565582
750.4067890.8135780.593211
760.4106970.8213950.589303
770.3731320.7462650.626868
780.3436240.6872480.656376
790.3739440.7478870.626056
800.3622670.7245330.637733
810.3577630.7155260.642237
820.3198260.6396520.680174
830.2830530.5661060.716947
840.2482430.4964850.751757
850.2381470.4762930.761853
860.2074630.4149270.792537
870.1787020.3574050.821298
880.1568830.3137660.843117
890.1357990.2715980.864201
900.1325310.2650610.867469
910.1142830.2285670.885717
920.09612660.1922530.903873
930.08062540.1612510.919375
940.07650520.153010.923495
950.07224760.1444950.927752
960.06010080.1202020.939899
970.05984210.1196840.940158
980.04864290.09728580.951357
990.04166370.08332740.958336
1000.04401730.08803460.955983
1010.03869960.07739920.9613
1020.04492430.08984860.955076
1030.03768280.07536570.962317
1040.03292850.06585710.967071
1050.03234980.06469970.96765
1060.02855080.05710160.971449
1070.02330010.04660010.9767
1080.02274640.04549280.977254
1090.01864270.03728530.981357
1100.0157110.03142190.984289
1110.01232720.02465440.987673
1120.01099430.02198850.989006
1130.01060750.02121510.989392
1140.01629450.0325890.983705
1150.01441490.02882980.985585
1160.0131210.02624190.986879
1170.01248840.02497670.987512
1180.01107310.02214610.988927
1190.009095050.01819010.990905
1200.007745610.01549120.992254
1210.006024130.01204830.993976
1220.009799950.01959990.9902
1230.008888160.01777630.991112
1240.008474910.01694980.991525
1250.006748830.01349770.993251
1260.00520550.0104110.994795
1270.004258570.008517140.995741
1280.003671280.007342570.996329
1290.004327590.008655170.995672
1300.005778420.01155680.994222
1310.007854250.01570850.992146
1320.009030930.01806190.990969
1330.009899740.01979950.9901
1340.009661560.01932310.990338
1350.007804980.015610.992195
1360.006230220.01246040.99377
1370.004914990.009829980.995085
1380.005599030.01119810.994401
1390.004914510.009829020.995085
1400.00538810.01077620.994612
1410.01392930.02785850.986071
1420.01393910.02787820.986061
1430.01220490.02440990.987795
1440.01221370.02442750.987786
1450.02594330.05188660.974057
1460.02936960.05873930.97063
1470.03726280.07452560.962737
1480.0309770.06195410.969023
1490.02487730.04975460.975123
1500.03798480.07596970.962015
1510.03424180.06848350.965758
1520.03750110.07500210.962499
1530.08317910.1663580.916821
1540.08635810.1727160.913642
1550.08615560.1723110.913844
1560.07388690.1477740.926113
1570.06679280.1335860.933207
1580.05765670.1153130.942343
1590.04977530.09955060.950225
1600.04355730.08711460.956443
1610.03532010.07064010.96468
1620.02868930.05737870.971311
1630.02432510.04865030.975675
1640.02383090.04766190.976169
1650.02178510.04357020.978215
1660.01909150.0381830.980909
1670.01496360.02992730.985036
1680.02197670.04395340.978023
1690.02494250.04988510.975057
1700.02392210.04784420.976078
1710.01979830.03959650.980202
1720.01569420.03138840.984306
1730.01569190.03138380.984308
1740.02150720.04301440.978493
1750.03088350.06176690.969117
1760.02715310.05430620.972847
1770.02204270.04408530.977957
1780.01739440.03478880.982606
1790.01391870.02783750.986081
1800.01183040.02366090.98817
1810.009531070.01906210.990469
1820.007674790.01534960.992325
1830.007176640.01435330.992823
1840.005527470.01105490.994473
1850.21060.4212010.7894
1860.2027210.4054420.797279
1870.214190.428380.78581
1880.2199910.4399820.780009
1890.1940910.3881820.805909
1900.1780860.3561710.821914
1910.1876630.3753250.812337
1920.1704070.3408140.829593
1930.1663640.3327280.833636
1940.1569050.3138090.843095
1950.1630010.3260020.836999
1960.1377930.2755860.862207
1970.1537160.3074320.846284
1980.1338970.2677940.866103
1990.1262230.2524450.873777
2000.114440.2288790.88556
2010.1304060.2608110.869594
2020.1093230.2186460.890677
2030.1399870.2799740.860013
2040.1456860.2913730.854314
2050.1393510.2787010.860649
2060.1149620.2299250.885038
2070.09668770.1933750.903312
2080.0778770.1557540.922123
2090.1213230.2426470.878677
2100.1015780.2031570.898422
2110.1149520.2299030.885048
2120.1136240.2272480.886376
2130.1397390.2794780.860261
2140.503870.992260.49613
2150.5021030.9957950.497897
2160.4487910.8975810.551209
2170.4768530.9537060.523147
2180.4454760.8909520.554524
2190.4439620.8879250.556038
2200.4471560.8943110.552844
2210.6049490.7901010.395051
2220.6888480.6223040.311152
2230.675770.648460.32423
2240.6670150.665970.332985
2250.6293060.7413890.370694
2260.6754610.6490780.324539
2270.7113090.5773820.288691
2280.6435530.7128950.356447
2290.5814990.8370030.418501
2300.5053920.9892160.494608
2310.4977550.9955090.502245
2320.4606770.9213530.539323
2330.4166620.8333240.583338
2340.3905250.781050.609475
2350.3222830.6445660.677717
2360.3426430.6852860.657357
2370.3643380.7286770.635662
2380.2829030.5658060.717097
2390.3086870.6173740.691313
2400.2313960.4627930.768604

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
24 & 0.870941 & 0.258118 & 0.129059 \tabularnewline
25 & 0.845474 & 0.309053 & 0.154526 \tabularnewline
26 & 0.756383 & 0.487234 & 0.243617 \tabularnewline
27 & 0.650013 & 0.699974 & 0.349987 \tabularnewline
28 & 0.693571 & 0.612857 & 0.306429 \tabularnewline
29 & 0.603687 & 0.792626 & 0.396313 \tabularnewline
30 & 0.746581 & 0.506838 & 0.253419 \tabularnewline
31 & 0.80379 & 0.392421 & 0.19621 \tabularnewline
32 & 0.752298 & 0.495405 & 0.247702 \tabularnewline
33 & 0.701288 & 0.597424 & 0.298712 \tabularnewline
34 & 0.634772 & 0.730456 & 0.365228 \tabularnewline
35 & 0.581599 & 0.836801 & 0.418401 \tabularnewline
36 & 0.664643 & 0.670715 & 0.335357 \tabularnewline
37 & 0.610945 & 0.778111 & 0.389055 \tabularnewline
38 & 0.568107 & 0.863785 & 0.431893 \tabularnewline
39 & 0.50769 & 0.98462 & 0.49231 \tabularnewline
40 & 0.442246 & 0.884493 & 0.557754 \tabularnewline
41 & 0.381473 & 0.762945 & 0.618527 \tabularnewline
42 & 0.325284 & 0.650569 & 0.674716 \tabularnewline
43 & 0.291389 & 0.582778 & 0.708611 \tabularnewline
44 & 0.241787 & 0.483574 & 0.758213 \tabularnewline
45 & 0.200891 & 0.401782 & 0.799109 \tabularnewline
46 & 0.346444 & 0.692888 & 0.653556 \tabularnewline
47 & 0.508544 & 0.982913 & 0.491456 \tabularnewline
48 & 0.502537 & 0.994926 & 0.497463 \tabularnewline
49 & 0.582242 & 0.835516 & 0.417758 \tabularnewline
50 & 0.545718 & 0.908563 & 0.454282 \tabularnewline
51 & 0.509113 & 0.981773 & 0.490887 \tabularnewline
52 & 0.454487 & 0.908974 & 0.545513 \tabularnewline
53 & 0.445111 & 0.890223 & 0.554889 \tabularnewline
54 & 0.392147 & 0.784293 & 0.607853 \tabularnewline
55 & 0.455633 & 0.911266 & 0.544367 \tabularnewline
56 & 0.418914 & 0.837828 & 0.581086 \tabularnewline
57 & 0.377633 & 0.755266 & 0.622367 \tabularnewline
58 & 0.404563 & 0.809127 & 0.595437 \tabularnewline
59 & 0.36757 & 0.73514 & 0.63243 \tabularnewline
60 & 0.40033 & 0.80066 & 0.59967 \tabularnewline
61 & 0.382522 & 0.765044 & 0.617478 \tabularnewline
62 & 0.356202 & 0.712405 & 0.643798 \tabularnewline
63 & 0.32264 & 0.645279 & 0.67736 \tabularnewline
64 & 0.284733 & 0.569466 & 0.715267 \tabularnewline
65 & 0.254307 & 0.508615 & 0.745693 \tabularnewline
66 & 0.218059 & 0.436118 & 0.781941 \tabularnewline
67 & 0.194481 & 0.388961 & 0.805519 \tabularnewline
68 & 0.236008 & 0.472016 & 0.763992 \tabularnewline
69 & 0.379119 & 0.758237 & 0.620881 \tabularnewline
70 & 0.336381 & 0.672762 & 0.663619 \tabularnewline
71 & 0.493579 & 0.987157 & 0.506421 \tabularnewline
72 & 0.453477 & 0.906954 & 0.546523 \tabularnewline
73 & 0.452657 & 0.905314 & 0.547343 \tabularnewline
74 & 0.434418 & 0.868835 & 0.565582 \tabularnewline
75 & 0.406789 & 0.813578 & 0.593211 \tabularnewline
76 & 0.410697 & 0.821395 & 0.589303 \tabularnewline
77 & 0.373132 & 0.746265 & 0.626868 \tabularnewline
78 & 0.343624 & 0.687248 & 0.656376 \tabularnewline
79 & 0.373944 & 0.747887 & 0.626056 \tabularnewline
80 & 0.362267 & 0.724533 & 0.637733 \tabularnewline
81 & 0.357763 & 0.715526 & 0.642237 \tabularnewline
82 & 0.319826 & 0.639652 & 0.680174 \tabularnewline
83 & 0.283053 & 0.566106 & 0.716947 \tabularnewline
84 & 0.248243 & 0.496485 & 0.751757 \tabularnewline
85 & 0.238147 & 0.476293 & 0.761853 \tabularnewline
86 & 0.207463 & 0.414927 & 0.792537 \tabularnewline
87 & 0.178702 & 0.357405 & 0.821298 \tabularnewline
88 & 0.156883 & 0.313766 & 0.843117 \tabularnewline
89 & 0.135799 & 0.271598 & 0.864201 \tabularnewline
90 & 0.132531 & 0.265061 & 0.867469 \tabularnewline
91 & 0.114283 & 0.228567 & 0.885717 \tabularnewline
92 & 0.0961266 & 0.192253 & 0.903873 \tabularnewline
93 & 0.0806254 & 0.161251 & 0.919375 \tabularnewline
94 & 0.0765052 & 0.15301 & 0.923495 \tabularnewline
95 & 0.0722476 & 0.144495 & 0.927752 \tabularnewline
96 & 0.0601008 & 0.120202 & 0.939899 \tabularnewline
97 & 0.0598421 & 0.119684 & 0.940158 \tabularnewline
98 & 0.0486429 & 0.0972858 & 0.951357 \tabularnewline
99 & 0.0416637 & 0.0833274 & 0.958336 \tabularnewline
100 & 0.0440173 & 0.0880346 & 0.955983 \tabularnewline
101 & 0.0386996 & 0.0773992 & 0.9613 \tabularnewline
102 & 0.0449243 & 0.0898486 & 0.955076 \tabularnewline
103 & 0.0376828 & 0.0753657 & 0.962317 \tabularnewline
104 & 0.0329285 & 0.0658571 & 0.967071 \tabularnewline
105 & 0.0323498 & 0.0646997 & 0.96765 \tabularnewline
106 & 0.0285508 & 0.0571016 & 0.971449 \tabularnewline
107 & 0.0233001 & 0.0466001 & 0.9767 \tabularnewline
108 & 0.0227464 & 0.0454928 & 0.977254 \tabularnewline
109 & 0.0186427 & 0.0372853 & 0.981357 \tabularnewline
110 & 0.015711 & 0.0314219 & 0.984289 \tabularnewline
111 & 0.0123272 & 0.0246544 & 0.987673 \tabularnewline
112 & 0.0109943 & 0.0219885 & 0.989006 \tabularnewline
113 & 0.0106075 & 0.0212151 & 0.989392 \tabularnewline
114 & 0.0162945 & 0.032589 & 0.983705 \tabularnewline
115 & 0.0144149 & 0.0288298 & 0.985585 \tabularnewline
116 & 0.013121 & 0.0262419 & 0.986879 \tabularnewline
117 & 0.0124884 & 0.0249767 & 0.987512 \tabularnewline
118 & 0.0110731 & 0.0221461 & 0.988927 \tabularnewline
119 & 0.00909505 & 0.0181901 & 0.990905 \tabularnewline
120 & 0.00774561 & 0.0154912 & 0.992254 \tabularnewline
121 & 0.00602413 & 0.0120483 & 0.993976 \tabularnewline
122 & 0.00979995 & 0.0195999 & 0.9902 \tabularnewline
123 & 0.00888816 & 0.0177763 & 0.991112 \tabularnewline
124 & 0.00847491 & 0.0169498 & 0.991525 \tabularnewline
125 & 0.00674883 & 0.0134977 & 0.993251 \tabularnewline
126 & 0.0052055 & 0.010411 & 0.994795 \tabularnewline
127 & 0.00425857 & 0.00851714 & 0.995741 \tabularnewline
128 & 0.00367128 & 0.00734257 & 0.996329 \tabularnewline
129 & 0.00432759 & 0.00865517 & 0.995672 \tabularnewline
130 & 0.00577842 & 0.0115568 & 0.994222 \tabularnewline
131 & 0.00785425 & 0.0157085 & 0.992146 \tabularnewline
132 & 0.00903093 & 0.0180619 & 0.990969 \tabularnewline
133 & 0.00989974 & 0.0197995 & 0.9901 \tabularnewline
134 & 0.00966156 & 0.0193231 & 0.990338 \tabularnewline
135 & 0.00780498 & 0.01561 & 0.992195 \tabularnewline
136 & 0.00623022 & 0.0124604 & 0.99377 \tabularnewline
137 & 0.00491499 & 0.00982998 & 0.995085 \tabularnewline
138 & 0.00559903 & 0.0111981 & 0.994401 \tabularnewline
139 & 0.00491451 & 0.00982902 & 0.995085 \tabularnewline
140 & 0.0053881 & 0.0107762 & 0.994612 \tabularnewline
141 & 0.0139293 & 0.0278585 & 0.986071 \tabularnewline
142 & 0.0139391 & 0.0278782 & 0.986061 \tabularnewline
143 & 0.0122049 & 0.0244099 & 0.987795 \tabularnewline
144 & 0.0122137 & 0.0244275 & 0.987786 \tabularnewline
145 & 0.0259433 & 0.0518866 & 0.974057 \tabularnewline
146 & 0.0293696 & 0.0587393 & 0.97063 \tabularnewline
147 & 0.0372628 & 0.0745256 & 0.962737 \tabularnewline
148 & 0.030977 & 0.0619541 & 0.969023 \tabularnewline
149 & 0.0248773 & 0.0497546 & 0.975123 \tabularnewline
150 & 0.0379848 & 0.0759697 & 0.962015 \tabularnewline
151 & 0.0342418 & 0.0684835 & 0.965758 \tabularnewline
152 & 0.0375011 & 0.0750021 & 0.962499 \tabularnewline
153 & 0.0831791 & 0.166358 & 0.916821 \tabularnewline
154 & 0.0863581 & 0.172716 & 0.913642 \tabularnewline
155 & 0.0861556 & 0.172311 & 0.913844 \tabularnewline
156 & 0.0738869 & 0.147774 & 0.926113 \tabularnewline
157 & 0.0667928 & 0.133586 & 0.933207 \tabularnewline
158 & 0.0576567 & 0.115313 & 0.942343 \tabularnewline
159 & 0.0497753 & 0.0995506 & 0.950225 \tabularnewline
160 & 0.0435573 & 0.0871146 & 0.956443 \tabularnewline
161 & 0.0353201 & 0.0706401 & 0.96468 \tabularnewline
162 & 0.0286893 & 0.0573787 & 0.971311 \tabularnewline
163 & 0.0243251 & 0.0486503 & 0.975675 \tabularnewline
164 & 0.0238309 & 0.0476619 & 0.976169 \tabularnewline
165 & 0.0217851 & 0.0435702 & 0.978215 \tabularnewline
166 & 0.0190915 & 0.038183 & 0.980909 \tabularnewline
167 & 0.0149636 & 0.0299273 & 0.985036 \tabularnewline
168 & 0.0219767 & 0.0439534 & 0.978023 \tabularnewline
169 & 0.0249425 & 0.0498851 & 0.975057 \tabularnewline
170 & 0.0239221 & 0.0478442 & 0.976078 \tabularnewline
171 & 0.0197983 & 0.0395965 & 0.980202 \tabularnewline
172 & 0.0156942 & 0.0313884 & 0.984306 \tabularnewline
173 & 0.0156919 & 0.0313838 & 0.984308 \tabularnewline
174 & 0.0215072 & 0.0430144 & 0.978493 \tabularnewline
175 & 0.0308835 & 0.0617669 & 0.969117 \tabularnewline
176 & 0.0271531 & 0.0543062 & 0.972847 \tabularnewline
177 & 0.0220427 & 0.0440853 & 0.977957 \tabularnewline
178 & 0.0173944 & 0.0347888 & 0.982606 \tabularnewline
179 & 0.0139187 & 0.0278375 & 0.986081 \tabularnewline
180 & 0.0118304 & 0.0236609 & 0.98817 \tabularnewline
181 & 0.00953107 & 0.0190621 & 0.990469 \tabularnewline
182 & 0.00767479 & 0.0153496 & 0.992325 \tabularnewline
183 & 0.00717664 & 0.0143533 & 0.992823 \tabularnewline
184 & 0.00552747 & 0.0110549 & 0.994473 \tabularnewline
185 & 0.2106 & 0.421201 & 0.7894 \tabularnewline
186 & 0.202721 & 0.405442 & 0.797279 \tabularnewline
187 & 0.21419 & 0.42838 & 0.78581 \tabularnewline
188 & 0.219991 & 0.439982 & 0.780009 \tabularnewline
189 & 0.194091 & 0.388182 & 0.805909 \tabularnewline
190 & 0.178086 & 0.356171 & 0.821914 \tabularnewline
191 & 0.187663 & 0.375325 & 0.812337 \tabularnewline
192 & 0.170407 & 0.340814 & 0.829593 \tabularnewline
193 & 0.166364 & 0.332728 & 0.833636 \tabularnewline
194 & 0.156905 & 0.313809 & 0.843095 \tabularnewline
195 & 0.163001 & 0.326002 & 0.836999 \tabularnewline
196 & 0.137793 & 0.275586 & 0.862207 \tabularnewline
197 & 0.153716 & 0.307432 & 0.846284 \tabularnewline
198 & 0.133897 & 0.267794 & 0.866103 \tabularnewline
199 & 0.126223 & 0.252445 & 0.873777 \tabularnewline
200 & 0.11444 & 0.228879 & 0.88556 \tabularnewline
201 & 0.130406 & 0.260811 & 0.869594 \tabularnewline
202 & 0.109323 & 0.218646 & 0.890677 \tabularnewline
203 & 0.139987 & 0.279974 & 0.860013 \tabularnewline
204 & 0.145686 & 0.291373 & 0.854314 \tabularnewline
205 & 0.139351 & 0.278701 & 0.860649 \tabularnewline
206 & 0.114962 & 0.229925 & 0.885038 \tabularnewline
207 & 0.0966877 & 0.193375 & 0.903312 \tabularnewline
208 & 0.077877 & 0.155754 & 0.922123 \tabularnewline
209 & 0.121323 & 0.242647 & 0.878677 \tabularnewline
210 & 0.101578 & 0.203157 & 0.898422 \tabularnewline
211 & 0.114952 & 0.229903 & 0.885048 \tabularnewline
212 & 0.113624 & 0.227248 & 0.886376 \tabularnewline
213 & 0.139739 & 0.279478 & 0.860261 \tabularnewline
214 & 0.50387 & 0.99226 & 0.49613 \tabularnewline
215 & 0.502103 & 0.995795 & 0.497897 \tabularnewline
216 & 0.448791 & 0.897581 & 0.551209 \tabularnewline
217 & 0.476853 & 0.953706 & 0.523147 \tabularnewline
218 & 0.445476 & 0.890952 & 0.554524 \tabularnewline
219 & 0.443962 & 0.887925 & 0.556038 \tabularnewline
220 & 0.447156 & 0.894311 & 0.552844 \tabularnewline
221 & 0.604949 & 0.790101 & 0.395051 \tabularnewline
222 & 0.688848 & 0.622304 & 0.311152 \tabularnewline
223 & 0.67577 & 0.64846 & 0.32423 \tabularnewline
224 & 0.667015 & 0.66597 & 0.332985 \tabularnewline
225 & 0.629306 & 0.741389 & 0.370694 \tabularnewline
226 & 0.675461 & 0.649078 & 0.324539 \tabularnewline
227 & 0.711309 & 0.577382 & 0.288691 \tabularnewline
228 & 0.643553 & 0.712895 & 0.356447 \tabularnewline
229 & 0.581499 & 0.837003 & 0.418501 \tabularnewline
230 & 0.505392 & 0.989216 & 0.494608 \tabularnewline
231 & 0.497755 & 0.995509 & 0.502245 \tabularnewline
232 & 0.460677 & 0.921353 & 0.539323 \tabularnewline
233 & 0.416662 & 0.833324 & 0.583338 \tabularnewline
234 & 0.390525 & 0.78105 & 0.609475 \tabularnewline
235 & 0.322283 & 0.644566 & 0.677717 \tabularnewline
236 & 0.342643 & 0.685286 & 0.657357 \tabularnewline
237 & 0.364338 & 0.728677 & 0.635662 \tabularnewline
238 & 0.282903 & 0.565806 & 0.717097 \tabularnewline
239 & 0.308687 & 0.617374 & 0.691313 \tabularnewline
240 & 0.231396 & 0.462793 & 0.768604 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&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]0.870941[/C][C]0.258118[/C][C]0.129059[/C][/ROW]
[ROW][C]25[/C][C]0.845474[/C][C]0.309053[/C][C]0.154526[/C][/ROW]
[ROW][C]26[/C][C]0.756383[/C][C]0.487234[/C][C]0.243617[/C][/ROW]
[ROW][C]27[/C][C]0.650013[/C][C]0.699974[/C][C]0.349987[/C][/ROW]
[ROW][C]28[/C][C]0.693571[/C][C]0.612857[/C][C]0.306429[/C][/ROW]
[ROW][C]29[/C][C]0.603687[/C][C]0.792626[/C][C]0.396313[/C][/ROW]
[ROW][C]30[/C][C]0.746581[/C][C]0.506838[/C][C]0.253419[/C][/ROW]
[ROW][C]31[/C][C]0.80379[/C][C]0.392421[/C][C]0.19621[/C][/ROW]
[ROW][C]32[/C][C]0.752298[/C][C]0.495405[/C][C]0.247702[/C][/ROW]
[ROW][C]33[/C][C]0.701288[/C][C]0.597424[/C][C]0.298712[/C][/ROW]
[ROW][C]34[/C][C]0.634772[/C][C]0.730456[/C][C]0.365228[/C][/ROW]
[ROW][C]35[/C][C]0.581599[/C][C]0.836801[/C][C]0.418401[/C][/ROW]
[ROW][C]36[/C][C]0.664643[/C][C]0.670715[/C][C]0.335357[/C][/ROW]
[ROW][C]37[/C][C]0.610945[/C][C]0.778111[/C][C]0.389055[/C][/ROW]
[ROW][C]38[/C][C]0.568107[/C][C]0.863785[/C][C]0.431893[/C][/ROW]
[ROW][C]39[/C][C]0.50769[/C][C]0.98462[/C][C]0.49231[/C][/ROW]
[ROW][C]40[/C][C]0.442246[/C][C]0.884493[/C][C]0.557754[/C][/ROW]
[ROW][C]41[/C][C]0.381473[/C][C]0.762945[/C][C]0.618527[/C][/ROW]
[ROW][C]42[/C][C]0.325284[/C][C]0.650569[/C][C]0.674716[/C][/ROW]
[ROW][C]43[/C][C]0.291389[/C][C]0.582778[/C][C]0.708611[/C][/ROW]
[ROW][C]44[/C][C]0.241787[/C][C]0.483574[/C][C]0.758213[/C][/ROW]
[ROW][C]45[/C][C]0.200891[/C][C]0.401782[/C][C]0.799109[/C][/ROW]
[ROW][C]46[/C][C]0.346444[/C][C]0.692888[/C][C]0.653556[/C][/ROW]
[ROW][C]47[/C][C]0.508544[/C][C]0.982913[/C][C]0.491456[/C][/ROW]
[ROW][C]48[/C][C]0.502537[/C][C]0.994926[/C][C]0.497463[/C][/ROW]
[ROW][C]49[/C][C]0.582242[/C][C]0.835516[/C][C]0.417758[/C][/ROW]
[ROW][C]50[/C][C]0.545718[/C][C]0.908563[/C][C]0.454282[/C][/ROW]
[ROW][C]51[/C][C]0.509113[/C][C]0.981773[/C][C]0.490887[/C][/ROW]
[ROW][C]52[/C][C]0.454487[/C][C]0.908974[/C][C]0.545513[/C][/ROW]
[ROW][C]53[/C][C]0.445111[/C][C]0.890223[/C][C]0.554889[/C][/ROW]
[ROW][C]54[/C][C]0.392147[/C][C]0.784293[/C][C]0.607853[/C][/ROW]
[ROW][C]55[/C][C]0.455633[/C][C]0.911266[/C][C]0.544367[/C][/ROW]
[ROW][C]56[/C][C]0.418914[/C][C]0.837828[/C][C]0.581086[/C][/ROW]
[ROW][C]57[/C][C]0.377633[/C][C]0.755266[/C][C]0.622367[/C][/ROW]
[ROW][C]58[/C][C]0.404563[/C][C]0.809127[/C][C]0.595437[/C][/ROW]
[ROW][C]59[/C][C]0.36757[/C][C]0.73514[/C][C]0.63243[/C][/ROW]
[ROW][C]60[/C][C]0.40033[/C][C]0.80066[/C][C]0.59967[/C][/ROW]
[ROW][C]61[/C][C]0.382522[/C][C]0.765044[/C][C]0.617478[/C][/ROW]
[ROW][C]62[/C][C]0.356202[/C][C]0.712405[/C][C]0.643798[/C][/ROW]
[ROW][C]63[/C][C]0.32264[/C][C]0.645279[/C][C]0.67736[/C][/ROW]
[ROW][C]64[/C][C]0.284733[/C][C]0.569466[/C][C]0.715267[/C][/ROW]
[ROW][C]65[/C][C]0.254307[/C][C]0.508615[/C][C]0.745693[/C][/ROW]
[ROW][C]66[/C][C]0.218059[/C][C]0.436118[/C][C]0.781941[/C][/ROW]
[ROW][C]67[/C][C]0.194481[/C][C]0.388961[/C][C]0.805519[/C][/ROW]
[ROW][C]68[/C][C]0.236008[/C][C]0.472016[/C][C]0.763992[/C][/ROW]
[ROW][C]69[/C][C]0.379119[/C][C]0.758237[/C][C]0.620881[/C][/ROW]
[ROW][C]70[/C][C]0.336381[/C][C]0.672762[/C][C]0.663619[/C][/ROW]
[ROW][C]71[/C][C]0.493579[/C][C]0.987157[/C][C]0.506421[/C][/ROW]
[ROW][C]72[/C][C]0.453477[/C][C]0.906954[/C][C]0.546523[/C][/ROW]
[ROW][C]73[/C][C]0.452657[/C][C]0.905314[/C][C]0.547343[/C][/ROW]
[ROW][C]74[/C][C]0.434418[/C][C]0.868835[/C][C]0.565582[/C][/ROW]
[ROW][C]75[/C][C]0.406789[/C][C]0.813578[/C][C]0.593211[/C][/ROW]
[ROW][C]76[/C][C]0.410697[/C][C]0.821395[/C][C]0.589303[/C][/ROW]
[ROW][C]77[/C][C]0.373132[/C][C]0.746265[/C][C]0.626868[/C][/ROW]
[ROW][C]78[/C][C]0.343624[/C][C]0.687248[/C][C]0.656376[/C][/ROW]
[ROW][C]79[/C][C]0.373944[/C][C]0.747887[/C][C]0.626056[/C][/ROW]
[ROW][C]80[/C][C]0.362267[/C][C]0.724533[/C][C]0.637733[/C][/ROW]
[ROW][C]81[/C][C]0.357763[/C][C]0.715526[/C][C]0.642237[/C][/ROW]
[ROW][C]82[/C][C]0.319826[/C][C]0.639652[/C][C]0.680174[/C][/ROW]
[ROW][C]83[/C][C]0.283053[/C][C]0.566106[/C][C]0.716947[/C][/ROW]
[ROW][C]84[/C][C]0.248243[/C][C]0.496485[/C][C]0.751757[/C][/ROW]
[ROW][C]85[/C][C]0.238147[/C][C]0.476293[/C][C]0.761853[/C][/ROW]
[ROW][C]86[/C][C]0.207463[/C][C]0.414927[/C][C]0.792537[/C][/ROW]
[ROW][C]87[/C][C]0.178702[/C][C]0.357405[/C][C]0.821298[/C][/ROW]
[ROW][C]88[/C][C]0.156883[/C][C]0.313766[/C][C]0.843117[/C][/ROW]
[ROW][C]89[/C][C]0.135799[/C][C]0.271598[/C][C]0.864201[/C][/ROW]
[ROW][C]90[/C][C]0.132531[/C][C]0.265061[/C][C]0.867469[/C][/ROW]
[ROW][C]91[/C][C]0.114283[/C][C]0.228567[/C][C]0.885717[/C][/ROW]
[ROW][C]92[/C][C]0.0961266[/C][C]0.192253[/C][C]0.903873[/C][/ROW]
[ROW][C]93[/C][C]0.0806254[/C][C]0.161251[/C][C]0.919375[/C][/ROW]
[ROW][C]94[/C][C]0.0765052[/C][C]0.15301[/C][C]0.923495[/C][/ROW]
[ROW][C]95[/C][C]0.0722476[/C][C]0.144495[/C][C]0.927752[/C][/ROW]
[ROW][C]96[/C][C]0.0601008[/C][C]0.120202[/C][C]0.939899[/C][/ROW]
[ROW][C]97[/C][C]0.0598421[/C][C]0.119684[/C][C]0.940158[/C][/ROW]
[ROW][C]98[/C][C]0.0486429[/C][C]0.0972858[/C][C]0.951357[/C][/ROW]
[ROW][C]99[/C][C]0.0416637[/C][C]0.0833274[/C][C]0.958336[/C][/ROW]
[ROW][C]100[/C][C]0.0440173[/C][C]0.0880346[/C][C]0.955983[/C][/ROW]
[ROW][C]101[/C][C]0.0386996[/C][C]0.0773992[/C][C]0.9613[/C][/ROW]
[ROW][C]102[/C][C]0.0449243[/C][C]0.0898486[/C][C]0.955076[/C][/ROW]
[ROW][C]103[/C][C]0.0376828[/C][C]0.0753657[/C][C]0.962317[/C][/ROW]
[ROW][C]104[/C][C]0.0329285[/C][C]0.0658571[/C][C]0.967071[/C][/ROW]
[ROW][C]105[/C][C]0.0323498[/C][C]0.0646997[/C][C]0.96765[/C][/ROW]
[ROW][C]106[/C][C]0.0285508[/C][C]0.0571016[/C][C]0.971449[/C][/ROW]
[ROW][C]107[/C][C]0.0233001[/C][C]0.0466001[/C][C]0.9767[/C][/ROW]
[ROW][C]108[/C][C]0.0227464[/C][C]0.0454928[/C][C]0.977254[/C][/ROW]
[ROW][C]109[/C][C]0.0186427[/C][C]0.0372853[/C][C]0.981357[/C][/ROW]
[ROW][C]110[/C][C]0.015711[/C][C]0.0314219[/C][C]0.984289[/C][/ROW]
[ROW][C]111[/C][C]0.0123272[/C][C]0.0246544[/C][C]0.987673[/C][/ROW]
[ROW][C]112[/C][C]0.0109943[/C][C]0.0219885[/C][C]0.989006[/C][/ROW]
[ROW][C]113[/C][C]0.0106075[/C][C]0.0212151[/C][C]0.989392[/C][/ROW]
[ROW][C]114[/C][C]0.0162945[/C][C]0.032589[/C][C]0.983705[/C][/ROW]
[ROW][C]115[/C][C]0.0144149[/C][C]0.0288298[/C][C]0.985585[/C][/ROW]
[ROW][C]116[/C][C]0.013121[/C][C]0.0262419[/C][C]0.986879[/C][/ROW]
[ROW][C]117[/C][C]0.0124884[/C][C]0.0249767[/C][C]0.987512[/C][/ROW]
[ROW][C]118[/C][C]0.0110731[/C][C]0.0221461[/C][C]0.988927[/C][/ROW]
[ROW][C]119[/C][C]0.00909505[/C][C]0.0181901[/C][C]0.990905[/C][/ROW]
[ROW][C]120[/C][C]0.00774561[/C][C]0.0154912[/C][C]0.992254[/C][/ROW]
[ROW][C]121[/C][C]0.00602413[/C][C]0.0120483[/C][C]0.993976[/C][/ROW]
[ROW][C]122[/C][C]0.00979995[/C][C]0.0195999[/C][C]0.9902[/C][/ROW]
[ROW][C]123[/C][C]0.00888816[/C][C]0.0177763[/C][C]0.991112[/C][/ROW]
[ROW][C]124[/C][C]0.00847491[/C][C]0.0169498[/C][C]0.991525[/C][/ROW]
[ROW][C]125[/C][C]0.00674883[/C][C]0.0134977[/C][C]0.993251[/C][/ROW]
[ROW][C]126[/C][C]0.0052055[/C][C]0.010411[/C][C]0.994795[/C][/ROW]
[ROW][C]127[/C][C]0.00425857[/C][C]0.00851714[/C][C]0.995741[/C][/ROW]
[ROW][C]128[/C][C]0.00367128[/C][C]0.00734257[/C][C]0.996329[/C][/ROW]
[ROW][C]129[/C][C]0.00432759[/C][C]0.00865517[/C][C]0.995672[/C][/ROW]
[ROW][C]130[/C][C]0.00577842[/C][C]0.0115568[/C][C]0.994222[/C][/ROW]
[ROW][C]131[/C][C]0.00785425[/C][C]0.0157085[/C][C]0.992146[/C][/ROW]
[ROW][C]132[/C][C]0.00903093[/C][C]0.0180619[/C][C]0.990969[/C][/ROW]
[ROW][C]133[/C][C]0.00989974[/C][C]0.0197995[/C][C]0.9901[/C][/ROW]
[ROW][C]134[/C][C]0.00966156[/C][C]0.0193231[/C][C]0.990338[/C][/ROW]
[ROW][C]135[/C][C]0.00780498[/C][C]0.01561[/C][C]0.992195[/C][/ROW]
[ROW][C]136[/C][C]0.00623022[/C][C]0.0124604[/C][C]0.99377[/C][/ROW]
[ROW][C]137[/C][C]0.00491499[/C][C]0.00982998[/C][C]0.995085[/C][/ROW]
[ROW][C]138[/C][C]0.00559903[/C][C]0.0111981[/C][C]0.994401[/C][/ROW]
[ROW][C]139[/C][C]0.00491451[/C][C]0.00982902[/C][C]0.995085[/C][/ROW]
[ROW][C]140[/C][C]0.0053881[/C][C]0.0107762[/C][C]0.994612[/C][/ROW]
[ROW][C]141[/C][C]0.0139293[/C][C]0.0278585[/C][C]0.986071[/C][/ROW]
[ROW][C]142[/C][C]0.0139391[/C][C]0.0278782[/C][C]0.986061[/C][/ROW]
[ROW][C]143[/C][C]0.0122049[/C][C]0.0244099[/C][C]0.987795[/C][/ROW]
[ROW][C]144[/C][C]0.0122137[/C][C]0.0244275[/C][C]0.987786[/C][/ROW]
[ROW][C]145[/C][C]0.0259433[/C][C]0.0518866[/C][C]0.974057[/C][/ROW]
[ROW][C]146[/C][C]0.0293696[/C][C]0.0587393[/C][C]0.97063[/C][/ROW]
[ROW][C]147[/C][C]0.0372628[/C][C]0.0745256[/C][C]0.962737[/C][/ROW]
[ROW][C]148[/C][C]0.030977[/C][C]0.0619541[/C][C]0.969023[/C][/ROW]
[ROW][C]149[/C][C]0.0248773[/C][C]0.0497546[/C][C]0.975123[/C][/ROW]
[ROW][C]150[/C][C]0.0379848[/C][C]0.0759697[/C][C]0.962015[/C][/ROW]
[ROW][C]151[/C][C]0.0342418[/C][C]0.0684835[/C][C]0.965758[/C][/ROW]
[ROW][C]152[/C][C]0.0375011[/C][C]0.0750021[/C][C]0.962499[/C][/ROW]
[ROW][C]153[/C][C]0.0831791[/C][C]0.166358[/C][C]0.916821[/C][/ROW]
[ROW][C]154[/C][C]0.0863581[/C][C]0.172716[/C][C]0.913642[/C][/ROW]
[ROW][C]155[/C][C]0.0861556[/C][C]0.172311[/C][C]0.913844[/C][/ROW]
[ROW][C]156[/C][C]0.0738869[/C][C]0.147774[/C][C]0.926113[/C][/ROW]
[ROW][C]157[/C][C]0.0667928[/C][C]0.133586[/C][C]0.933207[/C][/ROW]
[ROW][C]158[/C][C]0.0576567[/C][C]0.115313[/C][C]0.942343[/C][/ROW]
[ROW][C]159[/C][C]0.0497753[/C][C]0.0995506[/C][C]0.950225[/C][/ROW]
[ROW][C]160[/C][C]0.0435573[/C][C]0.0871146[/C][C]0.956443[/C][/ROW]
[ROW][C]161[/C][C]0.0353201[/C][C]0.0706401[/C][C]0.96468[/C][/ROW]
[ROW][C]162[/C][C]0.0286893[/C][C]0.0573787[/C][C]0.971311[/C][/ROW]
[ROW][C]163[/C][C]0.0243251[/C][C]0.0486503[/C][C]0.975675[/C][/ROW]
[ROW][C]164[/C][C]0.0238309[/C][C]0.0476619[/C][C]0.976169[/C][/ROW]
[ROW][C]165[/C][C]0.0217851[/C][C]0.0435702[/C][C]0.978215[/C][/ROW]
[ROW][C]166[/C][C]0.0190915[/C][C]0.038183[/C][C]0.980909[/C][/ROW]
[ROW][C]167[/C][C]0.0149636[/C][C]0.0299273[/C][C]0.985036[/C][/ROW]
[ROW][C]168[/C][C]0.0219767[/C][C]0.0439534[/C][C]0.978023[/C][/ROW]
[ROW][C]169[/C][C]0.0249425[/C][C]0.0498851[/C][C]0.975057[/C][/ROW]
[ROW][C]170[/C][C]0.0239221[/C][C]0.0478442[/C][C]0.976078[/C][/ROW]
[ROW][C]171[/C][C]0.0197983[/C][C]0.0395965[/C][C]0.980202[/C][/ROW]
[ROW][C]172[/C][C]0.0156942[/C][C]0.0313884[/C][C]0.984306[/C][/ROW]
[ROW][C]173[/C][C]0.0156919[/C][C]0.0313838[/C][C]0.984308[/C][/ROW]
[ROW][C]174[/C][C]0.0215072[/C][C]0.0430144[/C][C]0.978493[/C][/ROW]
[ROW][C]175[/C][C]0.0308835[/C][C]0.0617669[/C][C]0.969117[/C][/ROW]
[ROW][C]176[/C][C]0.0271531[/C][C]0.0543062[/C][C]0.972847[/C][/ROW]
[ROW][C]177[/C][C]0.0220427[/C][C]0.0440853[/C][C]0.977957[/C][/ROW]
[ROW][C]178[/C][C]0.0173944[/C][C]0.0347888[/C][C]0.982606[/C][/ROW]
[ROW][C]179[/C][C]0.0139187[/C][C]0.0278375[/C][C]0.986081[/C][/ROW]
[ROW][C]180[/C][C]0.0118304[/C][C]0.0236609[/C][C]0.98817[/C][/ROW]
[ROW][C]181[/C][C]0.00953107[/C][C]0.0190621[/C][C]0.990469[/C][/ROW]
[ROW][C]182[/C][C]0.00767479[/C][C]0.0153496[/C][C]0.992325[/C][/ROW]
[ROW][C]183[/C][C]0.00717664[/C][C]0.0143533[/C][C]0.992823[/C][/ROW]
[ROW][C]184[/C][C]0.00552747[/C][C]0.0110549[/C][C]0.994473[/C][/ROW]
[ROW][C]185[/C][C]0.2106[/C][C]0.421201[/C][C]0.7894[/C][/ROW]
[ROW][C]186[/C][C]0.202721[/C][C]0.405442[/C][C]0.797279[/C][/ROW]
[ROW][C]187[/C][C]0.21419[/C][C]0.42838[/C][C]0.78581[/C][/ROW]
[ROW][C]188[/C][C]0.219991[/C][C]0.439982[/C][C]0.780009[/C][/ROW]
[ROW][C]189[/C][C]0.194091[/C][C]0.388182[/C][C]0.805909[/C][/ROW]
[ROW][C]190[/C][C]0.178086[/C][C]0.356171[/C][C]0.821914[/C][/ROW]
[ROW][C]191[/C][C]0.187663[/C][C]0.375325[/C][C]0.812337[/C][/ROW]
[ROW][C]192[/C][C]0.170407[/C][C]0.340814[/C][C]0.829593[/C][/ROW]
[ROW][C]193[/C][C]0.166364[/C][C]0.332728[/C][C]0.833636[/C][/ROW]
[ROW][C]194[/C][C]0.156905[/C][C]0.313809[/C][C]0.843095[/C][/ROW]
[ROW][C]195[/C][C]0.163001[/C][C]0.326002[/C][C]0.836999[/C][/ROW]
[ROW][C]196[/C][C]0.137793[/C][C]0.275586[/C][C]0.862207[/C][/ROW]
[ROW][C]197[/C][C]0.153716[/C][C]0.307432[/C][C]0.846284[/C][/ROW]
[ROW][C]198[/C][C]0.133897[/C][C]0.267794[/C][C]0.866103[/C][/ROW]
[ROW][C]199[/C][C]0.126223[/C][C]0.252445[/C][C]0.873777[/C][/ROW]
[ROW][C]200[/C][C]0.11444[/C][C]0.228879[/C][C]0.88556[/C][/ROW]
[ROW][C]201[/C][C]0.130406[/C][C]0.260811[/C][C]0.869594[/C][/ROW]
[ROW][C]202[/C][C]0.109323[/C][C]0.218646[/C][C]0.890677[/C][/ROW]
[ROW][C]203[/C][C]0.139987[/C][C]0.279974[/C][C]0.860013[/C][/ROW]
[ROW][C]204[/C][C]0.145686[/C][C]0.291373[/C][C]0.854314[/C][/ROW]
[ROW][C]205[/C][C]0.139351[/C][C]0.278701[/C][C]0.860649[/C][/ROW]
[ROW][C]206[/C][C]0.114962[/C][C]0.229925[/C][C]0.885038[/C][/ROW]
[ROW][C]207[/C][C]0.0966877[/C][C]0.193375[/C][C]0.903312[/C][/ROW]
[ROW][C]208[/C][C]0.077877[/C][C]0.155754[/C][C]0.922123[/C][/ROW]
[ROW][C]209[/C][C]0.121323[/C][C]0.242647[/C][C]0.878677[/C][/ROW]
[ROW][C]210[/C][C]0.101578[/C][C]0.203157[/C][C]0.898422[/C][/ROW]
[ROW][C]211[/C][C]0.114952[/C][C]0.229903[/C][C]0.885048[/C][/ROW]
[ROW][C]212[/C][C]0.113624[/C][C]0.227248[/C][C]0.886376[/C][/ROW]
[ROW][C]213[/C][C]0.139739[/C][C]0.279478[/C][C]0.860261[/C][/ROW]
[ROW][C]214[/C][C]0.50387[/C][C]0.99226[/C][C]0.49613[/C][/ROW]
[ROW][C]215[/C][C]0.502103[/C][C]0.995795[/C][C]0.497897[/C][/ROW]
[ROW][C]216[/C][C]0.448791[/C][C]0.897581[/C][C]0.551209[/C][/ROW]
[ROW][C]217[/C][C]0.476853[/C][C]0.953706[/C][C]0.523147[/C][/ROW]
[ROW][C]218[/C][C]0.445476[/C][C]0.890952[/C][C]0.554524[/C][/ROW]
[ROW][C]219[/C][C]0.443962[/C][C]0.887925[/C][C]0.556038[/C][/ROW]
[ROW][C]220[/C][C]0.447156[/C][C]0.894311[/C][C]0.552844[/C][/ROW]
[ROW][C]221[/C][C]0.604949[/C][C]0.790101[/C][C]0.395051[/C][/ROW]
[ROW][C]222[/C][C]0.688848[/C][C]0.622304[/C][C]0.311152[/C][/ROW]
[ROW][C]223[/C][C]0.67577[/C][C]0.64846[/C][C]0.32423[/C][/ROW]
[ROW][C]224[/C][C]0.667015[/C][C]0.66597[/C][C]0.332985[/C][/ROW]
[ROW][C]225[/C][C]0.629306[/C][C]0.741389[/C][C]0.370694[/C][/ROW]
[ROW][C]226[/C][C]0.675461[/C][C]0.649078[/C][C]0.324539[/C][/ROW]
[ROW][C]227[/C][C]0.711309[/C][C]0.577382[/C][C]0.288691[/C][/ROW]
[ROW][C]228[/C][C]0.643553[/C][C]0.712895[/C][C]0.356447[/C][/ROW]
[ROW][C]229[/C][C]0.581499[/C][C]0.837003[/C][C]0.418501[/C][/ROW]
[ROW][C]230[/C][C]0.505392[/C][C]0.989216[/C][C]0.494608[/C][/ROW]
[ROW][C]231[/C][C]0.497755[/C][C]0.995509[/C][C]0.502245[/C][/ROW]
[ROW][C]232[/C][C]0.460677[/C][C]0.921353[/C][C]0.539323[/C][/ROW]
[ROW][C]233[/C][C]0.416662[/C][C]0.833324[/C][C]0.583338[/C][/ROW]
[ROW][C]234[/C][C]0.390525[/C][C]0.78105[/C][C]0.609475[/C][/ROW]
[ROW][C]235[/C][C]0.322283[/C][C]0.644566[/C][C]0.677717[/C][/ROW]
[ROW][C]236[/C][C]0.342643[/C][C]0.685286[/C][C]0.657357[/C][/ROW]
[ROW][C]237[/C][C]0.364338[/C][C]0.728677[/C][C]0.635662[/C][/ROW]
[ROW][C]238[/C][C]0.282903[/C][C]0.565806[/C][C]0.717097[/C][/ROW]
[ROW][C]239[/C][C]0.308687[/C][C]0.617374[/C][C]0.691313[/C][/ROW]
[ROW][C]240[/C][C]0.231396[/C][C]0.462793[/C][C]0.768604[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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
240.8709410.2581180.129059
250.8454740.3090530.154526
260.7563830.4872340.243617
270.6500130.6999740.349987
280.6935710.6128570.306429
290.6036870.7926260.396313
300.7465810.5068380.253419
310.803790.3924210.19621
320.7522980.4954050.247702
330.7012880.5974240.298712
340.6347720.7304560.365228
350.5815990.8368010.418401
360.6646430.6707150.335357
370.6109450.7781110.389055
380.5681070.8637850.431893
390.507690.984620.49231
400.4422460.8844930.557754
410.3814730.7629450.618527
420.3252840.6505690.674716
430.2913890.5827780.708611
440.2417870.4835740.758213
450.2008910.4017820.799109
460.3464440.6928880.653556
470.5085440.9829130.491456
480.5025370.9949260.497463
490.5822420.8355160.417758
500.5457180.9085630.454282
510.5091130.9817730.490887
520.4544870.9089740.545513
530.4451110.8902230.554889
540.3921470.7842930.607853
550.4556330.9112660.544367
560.4189140.8378280.581086
570.3776330.7552660.622367
580.4045630.8091270.595437
590.367570.735140.63243
600.400330.800660.59967
610.3825220.7650440.617478
620.3562020.7124050.643798
630.322640.6452790.67736
640.2847330.5694660.715267
650.2543070.5086150.745693
660.2180590.4361180.781941
670.1944810.3889610.805519
680.2360080.4720160.763992
690.3791190.7582370.620881
700.3363810.6727620.663619
710.4935790.9871570.506421
720.4534770.9069540.546523
730.4526570.9053140.547343
740.4344180.8688350.565582
750.4067890.8135780.593211
760.4106970.8213950.589303
770.3731320.7462650.626868
780.3436240.6872480.656376
790.3739440.7478870.626056
800.3622670.7245330.637733
810.3577630.7155260.642237
820.3198260.6396520.680174
830.2830530.5661060.716947
840.2482430.4964850.751757
850.2381470.4762930.761853
860.2074630.4149270.792537
870.1787020.3574050.821298
880.1568830.3137660.843117
890.1357990.2715980.864201
900.1325310.2650610.867469
910.1142830.2285670.885717
920.09612660.1922530.903873
930.08062540.1612510.919375
940.07650520.153010.923495
950.07224760.1444950.927752
960.06010080.1202020.939899
970.05984210.1196840.940158
980.04864290.09728580.951357
990.04166370.08332740.958336
1000.04401730.08803460.955983
1010.03869960.07739920.9613
1020.04492430.08984860.955076
1030.03768280.07536570.962317
1040.03292850.06585710.967071
1050.03234980.06469970.96765
1060.02855080.05710160.971449
1070.02330010.04660010.9767
1080.02274640.04549280.977254
1090.01864270.03728530.981357
1100.0157110.03142190.984289
1110.01232720.02465440.987673
1120.01099430.02198850.989006
1130.01060750.02121510.989392
1140.01629450.0325890.983705
1150.01441490.02882980.985585
1160.0131210.02624190.986879
1170.01248840.02497670.987512
1180.01107310.02214610.988927
1190.009095050.01819010.990905
1200.007745610.01549120.992254
1210.006024130.01204830.993976
1220.009799950.01959990.9902
1230.008888160.01777630.991112
1240.008474910.01694980.991525
1250.006748830.01349770.993251
1260.00520550.0104110.994795
1270.004258570.008517140.995741
1280.003671280.007342570.996329
1290.004327590.008655170.995672
1300.005778420.01155680.994222
1310.007854250.01570850.992146
1320.009030930.01806190.990969
1330.009899740.01979950.9901
1340.009661560.01932310.990338
1350.007804980.015610.992195
1360.006230220.01246040.99377
1370.004914990.009829980.995085
1380.005599030.01119810.994401
1390.004914510.009829020.995085
1400.00538810.01077620.994612
1410.01392930.02785850.986071
1420.01393910.02787820.986061
1430.01220490.02440990.987795
1440.01221370.02442750.987786
1450.02594330.05188660.974057
1460.02936960.05873930.97063
1470.03726280.07452560.962737
1480.0309770.06195410.969023
1490.02487730.04975460.975123
1500.03798480.07596970.962015
1510.03424180.06848350.965758
1520.03750110.07500210.962499
1530.08317910.1663580.916821
1540.08635810.1727160.913642
1550.08615560.1723110.913844
1560.07388690.1477740.926113
1570.06679280.1335860.933207
1580.05765670.1153130.942343
1590.04977530.09955060.950225
1600.04355730.08711460.956443
1610.03532010.07064010.96468
1620.02868930.05737870.971311
1630.02432510.04865030.975675
1640.02383090.04766190.976169
1650.02178510.04357020.978215
1660.01909150.0381830.980909
1670.01496360.02992730.985036
1680.02197670.04395340.978023
1690.02494250.04988510.975057
1700.02392210.04784420.976078
1710.01979830.03959650.980202
1720.01569420.03138840.984306
1730.01569190.03138380.984308
1740.02150720.04301440.978493
1750.03088350.06176690.969117
1760.02715310.05430620.972847
1770.02204270.04408530.977957
1780.01739440.03478880.982606
1790.01391870.02783750.986081
1800.01183040.02366090.98817
1810.009531070.01906210.990469
1820.007674790.01534960.992325
1830.007176640.01435330.992823
1840.005527470.01105490.994473
1850.21060.4212010.7894
1860.2027210.4054420.797279
1870.214190.428380.78581
1880.2199910.4399820.780009
1890.1940910.3881820.805909
1900.1780860.3561710.821914
1910.1876630.3753250.812337
1920.1704070.3408140.829593
1930.1663640.3327280.833636
1940.1569050.3138090.843095
1950.1630010.3260020.836999
1960.1377930.2755860.862207
1970.1537160.3074320.846284
1980.1338970.2677940.866103
1990.1262230.2524450.873777
2000.114440.2288790.88556
2010.1304060.2608110.869594
2020.1093230.2186460.890677
2030.1399870.2799740.860013
2040.1456860.2913730.854314
2050.1393510.2787010.860649
2060.1149620.2299250.885038
2070.09668770.1933750.903312
2080.0778770.1557540.922123
2090.1213230.2426470.878677
2100.1015780.2031570.898422
2110.1149520.2299030.885048
2120.1136240.2272480.886376
2130.1397390.2794780.860261
2140.503870.992260.49613
2150.5021030.9957950.497897
2160.4487910.8975810.551209
2170.4768530.9537060.523147
2180.4454760.8909520.554524
2190.4439620.8879250.556038
2200.4471560.8943110.552844
2210.6049490.7901010.395051
2220.6888480.6223040.311152
2230.675770.648460.32423
2240.6670150.665970.332985
2250.6293060.7413890.370694
2260.6754610.6490780.324539
2270.7113090.5773820.288691
2280.6435530.7128950.356447
2290.5814990.8370030.418501
2300.5053920.9892160.494608
2310.4977550.9955090.502245
2320.4606770.9213530.539323
2330.4166620.8333240.583338
2340.3905250.781050.609475
2350.3222830.6445660.677717
2360.3426430.6852860.657357
2370.3643380.7286770.635662
2380.2829030.5658060.717097
2390.3086870.6173740.691313
2400.2313960.4627930.768604






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level50.0230415NOK
5% type I error level590.271889NOK
10% type I error level810.373272NOK

\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 & 5 & 0.0230415 & NOK \tabularnewline
5% type I error level & 59 & 0.271889 & NOK \tabularnewline
10% type I error level & 81 & 0.373272 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=221819&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]5[/C][C]0.0230415[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]59[/C][C]0.271889[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]81[/C][C]0.373272[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=221819&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=221819&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 level50.0230415NOK
5% type I error level590.271889NOK
10% type I error level810.373272NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = 3 ; 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')
}