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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 18 Nov 2013 12:03:12 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Nov/18/t1384794218okkaovhq4peirec.htm/, Retrieved Sat, 27 Apr 2024 11:44:17 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=226172, Retrieved Sat, 27 Apr 2024 11:44:17 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [WS 7] [2013-11-18 17:03:12] [93c26c69267707c240373d21fead6bfa] [Current]
- R PD      [Multiple Regression] [regressie] [2013-11-20 12:55:33] [c6f8b1ebc3c8db7b9216fced5f615834]
- R P         [Multiple Regression] [multiple regres] [2013-11-20 13:00:18] [c6f8b1ebc3c8db7b9216fced5f615834]
- R P           [Multiple Regression] [multiple regression] [2013-11-20 13:07:29] [c6f8b1ebc3c8db7b9216fced5f615834]
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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 time20 seconds
R Server'Gertrude Mary Cox' @ cox.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 & 20 seconds \tabularnewline
R Server & 'Gertrude Mary Cox' @ cox.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&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]20 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gertrude Mary Cox' @ cox.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&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 time20 seconds
R Server'Gertrude Mary Cox' @ cox.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 12.6656 + 0.00332057Connected[t] + 0.0113272Separate[t] + 0.080466Learning[t] -0.0410455Software[t] -0.365596Depression[t] + 0.00760159Sport1[t] + 0.0277172Sport2[t] + 0.39136Month[t] -0.00816105t + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Happiness[t] =  +  12.6656 +  0.00332057Connected[t] +  0.0113272Separate[t] +  0.080466Learning[t] -0.0410455Software[t] -0.365596Depression[t] +  0.00760159Sport1[t] +  0.0277172Sport2[t] +  0.39136Month[t] -0.00816105t  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Happiness[t] =  +  12.6656 +  0.00332057Connected[t] +  0.0113272Separate[t] +  0.080466Learning[t] -0.0410455Software[t] -0.365596Depression[t] +  0.00760159Sport1[t] +  0.0277172Sport2[t] +  0.39136Month[t] -0.00816105t  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&T=1

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


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

Multiple Linear Regression - Estimated Regression Equation
Happiness[t] = + 12.6656 + 0.00332057Connected[t] + 0.0113272Separate[t] + 0.080466Learning[t] -0.0410455Software[t] -0.365596Depression[t] + 0.00760159Sport1[t] + 0.0277172Sport2[t] + 0.39136Month[t] -0.00816105t + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)12.66564.126063.070.00237540.0011877
Connected0.003320570.03741090.088760.9293430.464672
Separate0.01132720.03800530.2980.7659140.382957
Learning0.0804660.06738181.1940.2335220.116761
Software-0.04104550.0697082-0.58880.5565060.278253
Depression-0.3655960.0396045-9.2311.09082e-175.45411e-18
Sport10.007601590.04092130.18580.852780.42639
Sport20.02771720.06075090.45620.6486050.324303
Month0.391360.4396210.89020.3741890.187094
t-0.008161050.00465823-1.7520.08098650.0404932

\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) & 12.6656 & 4.12606 & 3.07 & 0.0023754 & 0.0011877 \tabularnewline
Connected & 0.00332057 & 0.0374109 & 0.08876 & 0.929343 & 0.464672 \tabularnewline
Separate & 0.0113272 & 0.0380053 & 0.298 & 0.765914 & 0.382957 \tabularnewline
Learning & 0.080466 & 0.0673818 & 1.194 & 0.233522 & 0.116761 \tabularnewline
Software & -0.0410455 & 0.0697082 & -0.5888 & 0.556506 & 0.278253 \tabularnewline
Depression & -0.365596 & 0.0396045 & -9.231 & 1.09082e-17 & 5.45411e-18 \tabularnewline
Sport1 & 0.00760159 & 0.0409213 & 0.1858 & 0.85278 & 0.42639 \tabularnewline
Sport2 & 0.0277172 & 0.0607509 & 0.4562 & 0.648605 & 0.324303 \tabularnewline
Month & 0.39136 & 0.439621 & 0.8902 & 0.374189 & 0.187094 \tabularnewline
t & -0.00816105 & 0.00465823 & -1.752 & 0.0809865 & 0.0404932 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&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]12.6656[/C][C]4.12606[/C][C]3.07[/C][C]0.0023754[/C][C]0.0011877[/C][/ROW]
[ROW][C]Connected[/C][C]0.00332057[/C][C]0.0374109[/C][C]0.08876[/C][C]0.929343[/C][C]0.464672[/C][/ROW]
[ROW][C]Separate[/C][C]0.0113272[/C][C]0.0380053[/C][C]0.298[/C][C]0.765914[/C][C]0.382957[/C][/ROW]
[ROW][C]Learning[/C][C]0.080466[/C][C]0.0673818[/C][C]1.194[/C][C]0.233522[/C][C]0.116761[/C][/ROW]
[ROW][C]Software[/C][C]-0.0410455[/C][C]0.0697082[/C][C]-0.5888[/C][C]0.556506[/C][C]0.278253[/C][/ROW]
[ROW][C]Depression[/C][C]-0.365596[/C][C]0.0396045[/C][C]-9.231[/C][C]1.09082e-17[/C][C]5.45411e-18[/C][/ROW]
[ROW][C]Sport1[/C][C]0.00760159[/C][C]0.0409213[/C][C]0.1858[/C][C]0.85278[/C][C]0.42639[/C][/ROW]
[ROW][C]Sport2[/C][C]0.0277172[/C][C]0.0607509[/C][C]0.4562[/C][C]0.648605[/C][C]0.324303[/C][/ROW]
[ROW][C]Month[/C][C]0.39136[/C][C]0.439621[/C][C]0.8902[/C][C]0.374189[/C][C]0.187094[/C][/ROW]
[ROW][C]t[/C][C]-0.00816105[/C][C]0.00465823[/C][C]-1.752[/C][C]0.0809865[/C][C]0.0404932[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&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)12.66564.126063.070.00237540.0011877
Connected0.003320570.03741090.088760.9293430.464672
Separate0.01132720.03800530.2980.7659140.382957
Learning0.0804660.06738181.1940.2335220.116761
Software-0.04104550.0697082-0.58880.5565060.278253
Depression-0.3655960.0396045-9.2311.09082e-175.45411e-18
Sport10.007601590.04092130.18580.852780.42639
Sport20.02771720.06075090.45620.6486050.324303
Month0.391360.4396210.89020.3741890.187094
t-0.008161050.00465823-1.7520.08098650.0404932






Multiple Linear Regression - Regression Statistics
Multiple R0.615819
R-squared0.379234
Adjusted R-squared0.357238
F-TEST (value)17.2413
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00322
Sum Squared Residuals1019.28

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.615819 \tabularnewline
R-squared & 0.379234 \tabularnewline
Adjusted R-squared & 0.357238 \tabularnewline
F-TEST (value) & 17.2413 \tabularnewline
F-TEST (DF numerator) & 9 \tabularnewline
F-TEST (DF denominator) & 254 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.00322 \tabularnewline
Sum Squared Residuals & 1019.28 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.615819[/C][/ROW]
[ROW][C]R-squared[/C][C]0.379234[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.357238[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]17.2413[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]9[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]254[/C][/ROW]
[ROW][C]p-value[/C][C]0[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.00322[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1019.28[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&T=3

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


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

Multiple Linear Regression - Regression Statistics
Multiple R0.615819
R-squared0.379234
Adjusted R-squared0.357238
F-TEST (value)17.2413
F-TEST (DF numerator)9
F-TEST (DF denominator)254
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.00322
Sum Squared Residuals1019.28






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11414.2025-0.202488
21815.52242.47756
31114.1201-3.12012
41214.8512-2.85124
51611.44724.5528
61814.72773.2723
71411.0332.96699
81415.2203-1.22033
91515.4182-0.41823
101514.62480.375178
111715.75511.24486
121915.78993.21009
131013.5888-3.58881
141613.67632.32368
151815.82082.17922
161413.57220.427834
171414.0267-0.0267326
181715.85851.14152
191415.5566-1.55659
201613.96672.03334
211815.49752.50254
221113.8754-2.87544
231414.4934-0.493372
241213.7255-1.72547
251715.42471.57533
26915.9291-6.92911
271615.10850.891474
281413.38050.61947
291513.95131.04865
301114.1219-3.12193
311615.77930.220684
321312.85730.142711
331715.18421.81577
341515.351-0.351023
351413.96280.0371754
361615.7260.274021
37910.9611-1.96112
381514.34950.650527
391715.39081.60921
401315.2611-2.26113
411515.735-0.735035
421613.63712.36288
431615.71960.280371
441213.171-1.17105
451514.64710.352882
461113.5972-2.59721
471515.3608-0.360763
481514.86990.130106
491713.41663.58339
501314.6983-1.69829
511615.13210.867914
521413.42530.574706
531111.6321-0.632148
541213.6723-1.67232
551214.1819-2.18188
561513.70971.29029
571614.08931.91072
581515.3739-0.373933
591215.0833-3.0833
601213.3166-1.31657
61810.763-2.76302
621314.4336-1.43355
631114.4473-3.4473
641412.97621.02385
651513.48881.51123
661015.355-5.35498
671112.8729-1.87288
681214.7308-2.73079
691513.85121.14883
701513.90851.09151
711413.98620.0138263
721613.04122.95875
731514.60530.394703
741515.4169-0.416906
751315.1836-2.18364
761212.4468-0.44677
771714.21792.78213
781312.77160.228395
791514.06740.932573
801315.1847-2.18475
811515.0844-0.0844208
821515.7369-0.736891
831614.47261.52742
841514.52030.4797
851414.3586-0.358552
861514.26710.732912
871414.4603-0.460319
881312.9560.0440465
89710.7316-3.73156
901714.02882.9712
911312.9120.0879561
921514.31150.68847
931413.42790.572063
941314.1426-1.14261
951615.10750.892501
961212.9358-0.935765
971415.0194-1.01938
981715.00691.99305
991515.1982-0.198152
1001715.17891.82105
1011213.0629-1.06289
1021614.97941.02063
1031114.5618-3.56183
1041513.17151.82852
105911.4781-2.47812
1061614.9711.02895
1071512.96082.03917
1081012.891-2.891
109109.393360.606638
1101513.93031.06974
1111113.161-2.16105
1121315.3241-2.32412
1131411.84152.15854
1141814.20533.79472
1151615.50760.492367
1161412.9951.00504
1171413.96470.0353442
1181415.1151-1.11509
1191413.66160.33841
1201212.5644-0.564366
1211413.48880.511247
1221514.85680.143243
1231515.7972-0.797204
1241514.4920.508017
1251314.5893-1.58929
1261716.12330.876726
1271715.17321.82681
1281914.95274.04726
1291513.54471.45531
1301314.5576-1.55764
131910.6172-1.61721
1321515.2174-0.217353
1331512.55622.44377
1341514.12330.876715
1351613.62352.37651
136119.40461.5954
1371413.25070.749309
1381111.9548-0.954802
1391514.15710.842943
1401313.7256-0.725559
1411514.54820.451802
1421613.71042.28956
1431414.3961-0.396111
1441514.07660.923375
1451614.53561.46442
1461614.20791.79211
1471113.217-2.21699
1481214.4473-2.44727
149911.4022-2.40216
1501614.16841.83164
1511312.2670.733014
1521615.18590.814108
1531214.3095-2.30948
154911.0106-2.01056
1551311.67711.32294
1561312.38160.618425
1571413.22110.778895
1581914.70794.29209
1591315.3547-2.3547
1601211.89110.10895
1611312.45360.546357
162109.587510.412493
1631413.47510.52489
1641611.62274.37729
1651012.1336-2.13364
166119.428111.57189
1671414.2923-0.292337
1681213.0254-1.02536
169912.8479-3.84788
170911.9975-2.99748
1711110.8580.142026
1721614.28021.71983
173914.1549-5.15495
1741311.57041.42961
1751613.46632.53372
1761315.3146-2.31457
177912.5192-3.51919
1781211.63370.366271
1791614.66971.33033
1801113.2514-2.25137
1811414.1193-0.119275
1821314.9355-1.93552
1831514.63110.368874
1841414.9547-0.954653
1851614.18161.81837
1861311.61251.38746
1871413.50160.498421
1881514.31070.689282
1891312.55980.44024
1901110.48110.51892
1911112.4009-1.40085
1921414.9116-0.911572
1931512.92272.07728
1941112.5168-1.5168
1951513.1321.86795
1961214.0033-2.00329
1971411.72962.27042
1981413.32470.675288
199811.1375-3.13755
2001313.6342-0.634232
201912.0935-3.0935
2021513.70371.29631
2031714.00632.99365
2041312.51640.483599
2051514.38850.611491
2061513.62261.37737
2071414.436-0.43597
2081612.36263.63742
2091312.86630.133731
2101614.17721.82275
211911.5884-2.58841
2121614.4341.56597
2131112.1131-1.11314
2141013.7708-3.77076
2151111.9264-0.926413
2161513.17781.82221
2171714.6882.31203
2181414.1073-0.107258
21989.83541-1.83541
2201513.39721.60281
2211113.6761-2.67609
2221613.32182.67815
2231011.8889-1.88891
2241514.68060.319379
22599.24792-0.247918
2261614.24961.75035
2271913.60315.39689
2281213.3958-1.39583
22989.36124-1.36124
2301113.1703-2.17029
2311413.68230.317706
232911.8908-2.89078
2331514.750.250013
2341312.05180.948226
2351614.64021.35977
2361112.5955-1.59555
2371211.32310.676858
2381312.54920.450848
2391013.9801-3.98005
2401113.3717-2.37168
2411214.5751-2.57513
242810.4213-2.42133
2431211.64060.359421
2441212.03-0.0299576
2451513.21571.78433
2461110.46970.530337
2471312.43940.560552
248148.593475.40653
249109.988270.0117308
2501211.20770.792345
2511512.58592.41407
2521311.58391.4161
2531313.8675-0.867549
2541313.3296-0.329625
2551211.46270.537345
2561212.2603-0.260293
257910.2879-1.28788
258911.1279-2.12787
2591512.12122.8788
2601014.6509-4.65095
2611413.17810.821873
2621513.03451.96552
26379.4718-2.4718
2641413.3840.616037

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 14 & 14.2025 & -0.202488 \tabularnewline
2 & 18 & 15.5224 & 2.47756 \tabularnewline
3 & 11 & 14.1201 & -3.12012 \tabularnewline
4 & 12 & 14.8512 & -2.85124 \tabularnewline
5 & 16 & 11.4472 & 4.5528 \tabularnewline
6 & 18 & 14.7277 & 3.2723 \tabularnewline
7 & 14 & 11.033 & 2.96699 \tabularnewline
8 & 14 & 15.2203 & -1.22033 \tabularnewline
9 & 15 & 15.4182 & -0.41823 \tabularnewline
10 & 15 & 14.6248 & 0.375178 \tabularnewline
11 & 17 & 15.7551 & 1.24486 \tabularnewline
12 & 19 & 15.7899 & 3.21009 \tabularnewline
13 & 10 & 13.5888 & -3.58881 \tabularnewline
14 & 16 & 13.6763 & 2.32368 \tabularnewline
15 & 18 & 15.8208 & 2.17922 \tabularnewline
16 & 14 & 13.5722 & 0.427834 \tabularnewline
17 & 14 & 14.0267 & -0.0267326 \tabularnewline
18 & 17 & 15.8585 & 1.14152 \tabularnewline
19 & 14 & 15.5566 & -1.55659 \tabularnewline
20 & 16 & 13.9667 & 2.03334 \tabularnewline
21 & 18 & 15.4975 & 2.50254 \tabularnewline
22 & 11 & 13.8754 & -2.87544 \tabularnewline
23 & 14 & 14.4934 & -0.493372 \tabularnewline
24 & 12 & 13.7255 & -1.72547 \tabularnewline
25 & 17 & 15.4247 & 1.57533 \tabularnewline
26 & 9 & 15.9291 & -6.92911 \tabularnewline
27 & 16 & 15.1085 & 0.891474 \tabularnewline
28 & 14 & 13.3805 & 0.61947 \tabularnewline
29 & 15 & 13.9513 & 1.04865 \tabularnewline
30 & 11 & 14.1219 & -3.12193 \tabularnewline
31 & 16 & 15.7793 & 0.220684 \tabularnewline
32 & 13 & 12.8573 & 0.142711 \tabularnewline
33 & 17 & 15.1842 & 1.81577 \tabularnewline
34 & 15 & 15.351 & -0.351023 \tabularnewline
35 & 14 & 13.9628 & 0.0371754 \tabularnewline
36 & 16 & 15.726 & 0.274021 \tabularnewline
37 & 9 & 10.9611 & -1.96112 \tabularnewline
38 & 15 & 14.3495 & 0.650527 \tabularnewline
39 & 17 & 15.3908 & 1.60921 \tabularnewline
40 & 13 & 15.2611 & -2.26113 \tabularnewline
41 & 15 & 15.735 & -0.735035 \tabularnewline
42 & 16 & 13.6371 & 2.36288 \tabularnewline
43 & 16 & 15.7196 & 0.280371 \tabularnewline
44 & 12 & 13.171 & -1.17105 \tabularnewline
45 & 15 & 14.6471 & 0.352882 \tabularnewline
46 & 11 & 13.5972 & -2.59721 \tabularnewline
47 & 15 & 15.3608 & -0.360763 \tabularnewline
48 & 15 & 14.8699 & 0.130106 \tabularnewline
49 & 17 & 13.4166 & 3.58339 \tabularnewline
50 & 13 & 14.6983 & -1.69829 \tabularnewline
51 & 16 & 15.1321 & 0.867914 \tabularnewline
52 & 14 & 13.4253 & 0.574706 \tabularnewline
53 & 11 & 11.6321 & -0.632148 \tabularnewline
54 & 12 & 13.6723 & -1.67232 \tabularnewline
55 & 12 & 14.1819 & -2.18188 \tabularnewline
56 & 15 & 13.7097 & 1.29029 \tabularnewline
57 & 16 & 14.0893 & 1.91072 \tabularnewline
58 & 15 & 15.3739 & -0.373933 \tabularnewline
59 & 12 & 15.0833 & -3.0833 \tabularnewline
60 & 12 & 13.3166 & -1.31657 \tabularnewline
61 & 8 & 10.763 & -2.76302 \tabularnewline
62 & 13 & 14.4336 & -1.43355 \tabularnewline
63 & 11 & 14.4473 & -3.4473 \tabularnewline
64 & 14 & 12.9762 & 1.02385 \tabularnewline
65 & 15 & 13.4888 & 1.51123 \tabularnewline
66 & 10 & 15.355 & -5.35498 \tabularnewline
67 & 11 & 12.8729 & -1.87288 \tabularnewline
68 & 12 & 14.7308 & -2.73079 \tabularnewline
69 & 15 & 13.8512 & 1.14883 \tabularnewline
70 & 15 & 13.9085 & 1.09151 \tabularnewline
71 & 14 & 13.9862 & 0.0138263 \tabularnewline
72 & 16 & 13.0412 & 2.95875 \tabularnewline
73 & 15 & 14.6053 & 0.394703 \tabularnewline
74 & 15 & 15.4169 & -0.416906 \tabularnewline
75 & 13 & 15.1836 & -2.18364 \tabularnewline
76 & 12 & 12.4468 & -0.44677 \tabularnewline
77 & 17 & 14.2179 & 2.78213 \tabularnewline
78 & 13 & 12.7716 & 0.228395 \tabularnewline
79 & 15 & 14.0674 & 0.932573 \tabularnewline
80 & 13 & 15.1847 & -2.18475 \tabularnewline
81 & 15 & 15.0844 & -0.0844208 \tabularnewline
82 & 15 & 15.7369 & -0.736891 \tabularnewline
83 & 16 & 14.4726 & 1.52742 \tabularnewline
84 & 15 & 14.5203 & 0.4797 \tabularnewline
85 & 14 & 14.3586 & -0.358552 \tabularnewline
86 & 15 & 14.2671 & 0.732912 \tabularnewline
87 & 14 & 14.4603 & -0.460319 \tabularnewline
88 & 13 & 12.956 & 0.0440465 \tabularnewline
89 & 7 & 10.7316 & -3.73156 \tabularnewline
90 & 17 & 14.0288 & 2.9712 \tabularnewline
91 & 13 & 12.912 & 0.0879561 \tabularnewline
92 & 15 & 14.3115 & 0.68847 \tabularnewline
93 & 14 & 13.4279 & 0.572063 \tabularnewline
94 & 13 & 14.1426 & -1.14261 \tabularnewline
95 & 16 & 15.1075 & 0.892501 \tabularnewline
96 & 12 & 12.9358 & -0.935765 \tabularnewline
97 & 14 & 15.0194 & -1.01938 \tabularnewline
98 & 17 & 15.0069 & 1.99305 \tabularnewline
99 & 15 & 15.1982 & -0.198152 \tabularnewline
100 & 17 & 15.1789 & 1.82105 \tabularnewline
101 & 12 & 13.0629 & -1.06289 \tabularnewline
102 & 16 & 14.9794 & 1.02063 \tabularnewline
103 & 11 & 14.5618 & -3.56183 \tabularnewline
104 & 15 & 13.1715 & 1.82852 \tabularnewline
105 & 9 & 11.4781 & -2.47812 \tabularnewline
106 & 16 & 14.971 & 1.02895 \tabularnewline
107 & 15 & 12.9608 & 2.03917 \tabularnewline
108 & 10 & 12.891 & -2.891 \tabularnewline
109 & 10 & 9.39336 & 0.606638 \tabularnewline
110 & 15 & 13.9303 & 1.06974 \tabularnewline
111 & 11 & 13.161 & -2.16105 \tabularnewline
112 & 13 & 15.3241 & -2.32412 \tabularnewline
113 & 14 & 11.8415 & 2.15854 \tabularnewline
114 & 18 & 14.2053 & 3.79472 \tabularnewline
115 & 16 & 15.5076 & 0.492367 \tabularnewline
116 & 14 & 12.995 & 1.00504 \tabularnewline
117 & 14 & 13.9647 & 0.0353442 \tabularnewline
118 & 14 & 15.1151 & -1.11509 \tabularnewline
119 & 14 & 13.6616 & 0.33841 \tabularnewline
120 & 12 & 12.5644 & -0.564366 \tabularnewline
121 & 14 & 13.4888 & 0.511247 \tabularnewline
122 & 15 & 14.8568 & 0.143243 \tabularnewline
123 & 15 & 15.7972 & -0.797204 \tabularnewline
124 & 15 & 14.492 & 0.508017 \tabularnewline
125 & 13 & 14.5893 & -1.58929 \tabularnewline
126 & 17 & 16.1233 & 0.876726 \tabularnewline
127 & 17 & 15.1732 & 1.82681 \tabularnewline
128 & 19 & 14.9527 & 4.04726 \tabularnewline
129 & 15 & 13.5447 & 1.45531 \tabularnewline
130 & 13 & 14.5576 & -1.55764 \tabularnewline
131 & 9 & 10.6172 & -1.61721 \tabularnewline
132 & 15 & 15.2174 & -0.217353 \tabularnewline
133 & 15 & 12.5562 & 2.44377 \tabularnewline
134 & 15 & 14.1233 & 0.876715 \tabularnewline
135 & 16 & 13.6235 & 2.37651 \tabularnewline
136 & 11 & 9.4046 & 1.5954 \tabularnewline
137 & 14 & 13.2507 & 0.749309 \tabularnewline
138 & 11 & 11.9548 & -0.954802 \tabularnewline
139 & 15 & 14.1571 & 0.842943 \tabularnewline
140 & 13 & 13.7256 & -0.725559 \tabularnewline
141 & 15 & 14.5482 & 0.451802 \tabularnewline
142 & 16 & 13.7104 & 2.28956 \tabularnewline
143 & 14 & 14.3961 & -0.396111 \tabularnewline
144 & 15 & 14.0766 & 0.923375 \tabularnewline
145 & 16 & 14.5356 & 1.46442 \tabularnewline
146 & 16 & 14.2079 & 1.79211 \tabularnewline
147 & 11 & 13.217 & -2.21699 \tabularnewline
148 & 12 & 14.4473 & -2.44727 \tabularnewline
149 & 9 & 11.4022 & -2.40216 \tabularnewline
150 & 16 & 14.1684 & 1.83164 \tabularnewline
151 & 13 & 12.267 & 0.733014 \tabularnewline
152 & 16 & 15.1859 & 0.814108 \tabularnewline
153 & 12 & 14.3095 & -2.30948 \tabularnewline
154 & 9 & 11.0106 & -2.01056 \tabularnewline
155 & 13 & 11.6771 & 1.32294 \tabularnewline
156 & 13 & 12.3816 & 0.618425 \tabularnewline
157 & 14 & 13.2211 & 0.778895 \tabularnewline
158 & 19 & 14.7079 & 4.29209 \tabularnewline
159 & 13 & 15.3547 & -2.3547 \tabularnewline
160 & 12 & 11.8911 & 0.10895 \tabularnewline
161 & 13 & 12.4536 & 0.546357 \tabularnewline
162 & 10 & 9.58751 & 0.412493 \tabularnewline
163 & 14 & 13.4751 & 0.52489 \tabularnewline
164 & 16 & 11.6227 & 4.37729 \tabularnewline
165 & 10 & 12.1336 & -2.13364 \tabularnewline
166 & 11 & 9.42811 & 1.57189 \tabularnewline
167 & 14 & 14.2923 & -0.292337 \tabularnewline
168 & 12 & 13.0254 & -1.02536 \tabularnewline
169 & 9 & 12.8479 & -3.84788 \tabularnewline
170 & 9 & 11.9975 & -2.99748 \tabularnewline
171 & 11 & 10.858 & 0.142026 \tabularnewline
172 & 16 & 14.2802 & 1.71983 \tabularnewline
173 & 9 & 14.1549 & -5.15495 \tabularnewline
174 & 13 & 11.5704 & 1.42961 \tabularnewline
175 & 16 & 13.4663 & 2.53372 \tabularnewline
176 & 13 & 15.3146 & -2.31457 \tabularnewline
177 & 9 & 12.5192 & -3.51919 \tabularnewline
178 & 12 & 11.6337 & 0.366271 \tabularnewline
179 & 16 & 14.6697 & 1.33033 \tabularnewline
180 & 11 & 13.2514 & -2.25137 \tabularnewline
181 & 14 & 14.1193 & -0.119275 \tabularnewline
182 & 13 & 14.9355 & -1.93552 \tabularnewline
183 & 15 & 14.6311 & 0.368874 \tabularnewline
184 & 14 & 14.9547 & -0.954653 \tabularnewline
185 & 16 & 14.1816 & 1.81837 \tabularnewline
186 & 13 & 11.6125 & 1.38746 \tabularnewline
187 & 14 & 13.5016 & 0.498421 \tabularnewline
188 & 15 & 14.3107 & 0.689282 \tabularnewline
189 & 13 & 12.5598 & 0.44024 \tabularnewline
190 & 11 & 10.4811 & 0.51892 \tabularnewline
191 & 11 & 12.4009 & -1.40085 \tabularnewline
192 & 14 & 14.9116 & -0.911572 \tabularnewline
193 & 15 & 12.9227 & 2.07728 \tabularnewline
194 & 11 & 12.5168 & -1.5168 \tabularnewline
195 & 15 & 13.132 & 1.86795 \tabularnewline
196 & 12 & 14.0033 & -2.00329 \tabularnewline
197 & 14 & 11.7296 & 2.27042 \tabularnewline
198 & 14 & 13.3247 & 0.675288 \tabularnewline
199 & 8 & 11.1375 & -3.13755 \tabularnewline
200 & 13 & 13.6342 & -0.634232 \tabularnewline
201 & 9 & 12.0935 & -3.0935 \tabularnewline
202 & 15 & 13.7037 & 1.29631 \tabularnewline
203 & 17 & 14.0063 & 2.99365 \tabularnewline
204 & 13 & 12.5164 & 0.483599 \tabularnewline
205 & 15 & 14.3885 & 0.611491 \tabularnewline
206 & 15 & 13.6226 & 1.37737 \tabularnewline
207 & 14 & 14.436 & -0.43597 \tabularnewline
208 & 16 & 12.3626 & 3.63742 \tabularnewline
209 & 13 & 12.8663 & 0.133731 \tabularnewline
210 & 16 & 14.1772 & 1.82275 \tabularnewline
211 & 9 & 11.5884 & -2.58841 \tabularnewline
212 & 16 & 14.434 & 1.56597 \tabularnewline
213 & 11 & 12.1131 & -1.11314 \tabularnewline
214 & 10 & 13.7708 & -3.77076 \tabularnewline
215 & 11 & 11.9264 & -0.926413 \tabularnewline
216 & 15 & 13.1778 & 1.82221 \tabularnewline
217 & 17 & 14.688 & 2.31203 \tabularnewline
218 & 14 & 14.1073 & -0.107258 \tabularnewline
219 & 8 & 9.83541 & -1.83541 \tabularnewline
220 & 15 & 13.3972 & 1.60281 \tabularnewline
221 & 11 & 13.6761 & -2.67609 \tabularnewline
222 & 16 & 13.3218 & 2.67815 \tabularnewline
223 & 10 & 11.8889 & -1.88891 \tabularnewline
224 & 15 & 14.6806 & 0.319379 \tabularnewline
225 & 9 & 9.24792 & -0.247918 \tabularnewline
226 & 16 & 14.2496 & 1.75035 \tabularnewline
227 & 19 & 13.6031 & 5.39689 \tabularnewline
228 & 12 & 13.3958 & -1.39583 \tabularnewline
229 & 8 & 9.36124 & -1.36124 \tabularnewline
230 & 11 & 13.1703 & -2.17029 \tabularnewline
231 & 14 & 13.6823 & 0.317706 \tabularnewline
232 & 9 & 11.8908 & -2.89078 \tabularnewline
233 & 15 & 14.75 & 0.250013 \tabularnewline
234 & 13 & 12.0518 & 0.948226 \tabularnewline
235 & 16 & 14.6402 & 1.35977 \tabularnewline
236 & 11 & 12.5955 & -1.59555 \tabularnewline
237 & 12 & 11.3231 & 0.676858 \tabularnewline
238 & 13 & 12.5492 & 0.450848 \tabularnewline
239 & 10 & 13.9801 & -3.98005 \tabularnewline
240 & 11 & 13.3717 & -2.37168 \tabularnewline
241 & 12 & 14.5751 & -2.57513 \tabularnewline
242 & 8 & 10.4213 & -2.42133 \tabularnewline
243 & 12 & 11.6406 & 0.359421 \tabularnewline
244 & 12 & 12.03 & -0.0299576 \tabularnewline
245 & 15 & 13.2157 & 1.78433 \tabularnewline
246 & 11 & 10.4697 & 0.530337 \tabularnewline
247 & 13 & 12.4394 & 0.560552 \tabularnewline
248 & 14 & 8.59347 & 5.40653 \tabularnewline
249 & 10 & 9.98827 & 0.0117308 \tabularnewline
250 & 12 & 11.2077 & 0.792345 \tabularnewline
251 & 15 & 12.5859 & 2.41407 \tabularnewline
252 & 13 & 11.5839 & 1.4161 \tabularnewline
253 & 13 & 13.8675 & -0.867549 \tabularnewline
254 & 13 & 13.3296 & -0.329625 \tabularnewline
255 & 12 & 11.4627 & 0.537345 \tabularnewline
256 & 12 & 12.2603 & -0.260293 \tabularnewline
257 & 9 & 10.2879 & -1.28788 \tabularnewline
258 & 9 & 11.1279 & -2.12787 \tabularnewline
259 & 15 & 12.1212 & 2.8788 \tabularnewline
260 & 10 & 14.6509 & -4.65095 \tabularnewline
261 & 14 & 13.1781 & 0.821873 \tabularnewline
262 & 15 & 13.0345 & 1.96552 \tabularnewline
263 & 7 & 9.4718 & -2.4718 \tabularnewline
264 & 14 & 13.384 & 0.616037 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]14[/C][C]14.2025[/C][C]-0.202488[/C][/ROW]
[ROW][C]2[/C][C]18[/C][C]15.5224[/C][C]2.47756[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]14.1201[/C][C]-3.12012[/C][/ROW]
[ROW][C]4[/C][C]12[/C][C]14.8512[/C][C]-2.85124[/C][/ROW]
[ROW][C]5[/C][C]16[/C][C]11.4472[/C][C]4.5528[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]14.7277[/C][C]3.2723[/C][/ROW]
[ROW][C]7[/C][C]14[/C][C]11.033[/C][C]2.96699[/C][/ROW]
[ROW][C]8[/C][C]14[/C][C]15.2203[/C][C]-1.22033[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]15.4182[/C][C]-0.41823[/C][/ROW]
[ROW][C]10[/C][C]15[/C][C]14.6248[/C][C]0.375178[/C][/ROW]
[ROW][C]11[/C][C]17[/C][C]15.7551[/C][C]1.24486[/C][/ROW]
[ROW][C]12[/C][C]19[/C][C]15.7899[/C][C]3.21009[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]13.5888[/C][C]-3.58881[/C][/ROW]
[ROW][C]14[/C][C]16[/C][C]13.6763[/C][C]2.32368[/C][/ROW]
[ROW][C]15[/C][C]18[/C][C]15.8208[/C][C]2.17922[/C][/ROW]
[ROW][C]16[/C][C]14[/C][C]13.5722[/C][C]0.427834[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]14.0267[/C][C]-0.0267326[/C][/ROW]
[ROW][C]18[/C][C]17[/C][C]15.8585[/C][C]1.14152[/C][/ROW]
[ROW][C]19[/C][C]14[/C][C]15.5566[/C][C]-1.55659[/C][/ROW]
[ROW][C]20[/C][C]16[/C][C]13.9667[/C][C]2.03334[/C][/ROW]
[ROW][C]21[/C][C]18[/C][C]15.4975[/C][C]2.50254[/C][/ROW]
[ROW][C]22[/C][C]11[/C][C]13.8754[/C][C]-2.87544[/C][/ROW]
[ROW][C]23[/C][C]14[/C][C]14.4934[/C][C]-0.493372[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]13.7255[/C][C]-1.72547[/C][/ROW]
[ROW][C]25[/C][C]17[/C][C]15.4247[/C][C]1.57533[/C][/ROW]
[ROW][C]26[/C][C]9[/C][C]15.9291[/C][C]-6.92911[/C][/ROW]
[ROW][C]27[/C][C]16[/C][C]15.1085[/C][C]0.891474[/C][/ROW]
[ROW][C]28[/C][C]14[/C][C]13.3805[/C][C]0.61947[/C][/ROW]
[ROW][C]29[/C][C]15[/C][C]13.9513[/C][C]1.04865[/C][/ROW]
[ROW][C]30[/C][C]11[/C][C]14.1219[/C][C]-3.12193[/C][/ROW]
[ROW][C]31[/C][C]16[/C][C]15.7793[/C][C]0.220684[/C][/ROW]
[ROW][C]32[/C][C]13[/C][C]12.8573[/C][C]0.142711[/C][/ROW]
[ROW][C]33[/C][C]17[/C][C]15.1842[/C][C]1.81577[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]15.351[/C][C]-0.351023[/C][/ROW]
[ROW][C]35[/C][C]14[/C][C]13.9628[/C][C]0.0371754[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]15.726[/C][C]0.274021[/C][/ROW]
[ROW][C]37[/C][C]9[/C][C]10.9611[/C][C]-1.96112[/C][/ROW]
[ROW][C]38[/C][C]15[/C][C]14.3495[/C][C]0.650527[/C][/ROW]
[ROW][C]39[/C][C]17[/C][C]15.3908[/C][C]1.60921[/C][/ROW]
[ROW][C]40[/C][C]13[/C][C]15.2611[/C][C]-2.26113[/C][/ROW]
[ROW][C]41[/C][C]15[/C][C]15.735[/C][C]-0.735035[/C][/ROW]
[ROW][C]42[/C][C]16[/C][C]13.6371[/C][C]2.36288[/C][/ROW]
[ROW][C]43[/C][C]16[/C][C]15.7196[/C][C]0.280371[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]13.171[/C][C]-1.17105[/C][/ROW]
[ROW][C]45[/C][C]15[/C][C]14.6471[/C][C]0.352882[/C][/ROW]
[ROW][C]46[/C][C]11[/C][C]13.5972[/C][C]-2.59721[/C][/ROW]
[ROW][C]47[/C][C]15[/C][C]15.3608[/C][C]-0.360763[/C][/ROW]
[ROW][C]48[/C][C]15[/C][C]14.8699[/C][C]0.130106[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]13.4166[/C][C]3.58339[/C][/ROW]
[ROW][C]50[/C][C]13[/C][C]14.6983[/C][C]-1.69829[/C][/ROW]
[ROW][C]51[/C][C]16[/C][C]15.1321[/C][C]0.867914[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]13.4253[/C][C]0.574706[/C][/ROW]
[ROW][C]53[/C][C]11[/C][C]11.6321[/C][C]-0.632148[/C][/ROW]
[ROW][C]54[/C][C]12[/C][C]13.6723[/C][C]-1.67232[/C][/ROW]
[ROW][C]55[/C][C]12[/C][C]14.1819[/C][C]-2.18188[/C][/ROW]
[ROW][C]56[/C][C]15[/C][C]13.7097[/C][C]1.29029[/C][/ROW]
[ROW][C]57[/C][C]16[/C][C]14.0893[/C][C]1.91072[/C][/ROW]
[ROW][C]58[/C][C]15[/C][C]15.3739[/C][C]-0.373933[/C][/ROW]
[ROW][C]59[/C][C]12[/C][C]15.0833[/C][C]-3.0833[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]13.3166[/C][C]-1.31657[/C][/ROW]
[ROW][C]61[/C][C]8[/C][C]10.763[/C][C]-2.76302[/C][/ROW]
[ROW][C]62[/C][C]13[/C][C]14.4336[/C][C]-1.43355[/C][/ROW]
[ROW][C]63[/C][C]11[/C][C]14.4473[/C][C]-3.4473[/C][/ROW]
[ROW][C]64[/C][C]14[/C][C]12.9762[/C][C]1.02385[/C][/ROW]
[ROW][C]65[/C][C]15[/C][C]13.4888[/C][C]1.51123[/C][/ROW]
[ROW][C]66[/C][C]10[/C][C]15.355[/C][C]-5.35498[/C][/ROW]
[ROW][C]67[/C][C]11[/C][C]12.8729[/C][C]-1.87288[/C][/ROW]
[ROW][C]68[/C][C]12[/C][C]14.7308[/C][C]-2.73079[/C][/ROW]
[ROW][C]69[/C][C]15[/C][C]13.8512[/C][C]1.14883[/C][/ROW]
[ROW][C]70[/C][C]15[/C][C]13.9085[/C][C]1.09151[/C][/ROW]
[ROW][C]71[/C][C]14[/C][C]13.9862[/C][C]0.0138263[/C][/ROW]
[ROW][C]72[/C][C]16[/C][C]13.0412[/C][C]2.95875[/C][/ROW]
[ROW][C]73[/C][C]15[/C][C]14.6053[/C][C]0.394703[/C][/ROW]
[ROW][C]74[/C][C]15[/C][C]15.4169[/C][C]-0.416906[/C][/ROW]
[ROW][C]75[/C][C]13[/C][C]15.1836[/C][C]-2.18364[/C][/ROW]
[ROW][C]76[/C][C]12[/C][C]12.4468[/C][C]-0.44677[/C][/ROW]
[ROW][C]77[/C][C]17[/C][C]14.2179[/C][C]2.78213[/C][/ROW]
[ROW][C]78[/C][C]13[/C][C]12.7716[/C][C]0.228395[/C][/ROW]
[ROW][C]79[/C][C]15[/C][C]14.0674[/C][C]0.932573[/C][/ROW]
[ROW][C]80[/C][C]13[/C][C]15.1847[/C][C]-2.18475[/C][/ROW]
[ROW][C]81[/C][C]15[/C][C]15.0844[/C][C]-0.0844208[/C][/ROW]
[ROW][C]82[/C][C]15[/C][C]15.7369[/C][C]-0.736891[/C][/ROW]
[ROW][C]83[/C][C]16[/C][C]14.4726[/C][C]1.52742[/C][/ROW]
[ROW][C]84[/C][C]15[/C][C]14.5203[/C][C]0.4797[/C][/ROW]
[ROW][C]85[/C][C]14[/C][C]14.3586[/C][C]-0.358552[/C][/ROW]
[ROW][C]86[/C][C]15[/C][C]14.2671[/C][C]0.732912[/C][/ROW]
[ROW][C]87[/C][C]14[/C][C]14.4603[/C][C]-0.460319[/C][/ROW]
[ROW][C]88[/C][C]13[/C][C]12.956[/C][C]0.0440465[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]10.7316[/C][C]-3.73156[/C][/ROW]
[ROW][C]90[/C][C]17[/C][C]14.0288[/C][C]2.9712[/C][/ROW]
[ROW][C]91[/C][C]13[/C][C]12.912[/C][C]0.0879561[/C][/ROW]
[ROW][C]92[/C][C]15[/C][C]14.3115[/C][C]0.68847[/C][/ROW]
[ROW][C]93[/C][C]14[/C][C]13.4279[/C][C]0.572063[/C][/ROW]
[ROW][C]94[/C][C]13[/C][C]14.1426[/C][C]-1.14261[/C][/ROW]
[ROW][C]95[/C][C]16[/C][C]15.1075[/C][C]0.892501[/C][/ROW]
[ROW][C]96[/C][C]12[/C][C]12.9358[/C][C]-0.935765[/C][/ROW]
[ROW][C]97[/C][C]14[/C][C]15.0194[/C][C]-1.01938[/C][/ROW]
[ROW][C]98[/C][C]17[/C][C]15.0069[/C][C]1.99305[/C][/ROW]
[ROW][C]99[/C][C]15[/C][C]15.1982[/C][C]-0.198152[/C][/ROW]
[ROW][C]100[/C][C]17[/C][C]15.1789[/C][C]1.82105[/C][/ROW]
[ROW][C]101[/C][C]12[/C][C]13.0629[/C][C]-1.06289[/C][/ROW]
[ROW][C]102[/C][C]16[/C][C]14.9794[/C][C]1.02063[/C][/ROW]
[ROW][C]103[/C][C]11[/C][C]14.5618[/C][C]-3.56183[/C][/ROW]
[ROW][C]104[/C][C]15[/C][C]13.1715[/C][C]1.82852[/C][/ROW]
[ROW][C]105[/C][C]9[/C][C]11.4781[/C][C]-2.47812[/C][/ROW]
[ROW][C]106[/C][C]16[/C][C]14.971[/C][C]1.02895[/C][/ROW]
[ROW][C]107[/C][C]15[/C][C]12.9608[/C][C]2.03917[/C][/ROW]
[ROW][C]108[/C][C]10[/C][C]12.891[/C][C]-2.891[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]9.39336[/C][C]0.606638[/C][/ROW]
[ROW][C]110[/C][C]15[/C][C]13.9303[/C][C]1.06974[/C][/ROW]
[ROW][C]111[/C][C]11[/C][C]13.161[/C][C]-2.16105[/C][/ROW]
[ROW][C]112[/C][C]13[/C][C]15.3241[/C][C]-2.32412[/C][/ROW]
[ROW][C]113[/C][C]14[/C][C]11.8415[/C][C]2.15854[/C][/ROW]
[ROW][C]114[/C][C]18[/C][C]14.2053[/C][C]3.79472[/C][/ROW]
[ROW][C]115[/C][C]16[/C][C]15.5076[/C][C]0.492367[/C][/ROW]
[ROW][C]116[/C][C]14[/C][C]12.995[/C][C]1.00504[/C][/ROW]
[ROW][C]117[/C][C]14[/C][C]13.9647[/C][C]0.0353442[/C][/ROW]
[ROW][C]118[/C][C]14[/C][C]15.1151[/C][C]-1.11509[/C][/ROW]
[ROW][C]119[/C][C]14[/C][C]13.6616[/C][C]0.33841[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]12.5644[/C][C]-0.564366[/C][/ROW]
[ROW][C]121[/C][C]14[/C][C]13.4888[/C][C]0.511247[/C][/ROW]
[ROW][C]122[/C][C]15[/C][C]14.8568[/C][C]0.143243[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.7972[/C][C]-0.797204[/C][/ROW]
[ROW][C]124[/C][C]15[/C][C]14.492[/C][C]0.508017[/C][/ROW]
[ROW][C]125[/C][C]13[/C][C]14.5893[/C][C]-1.58929[/C][/ROW]
[ROW][C]126[/C][C]17[/C][C]16.1233[/C][C]0.876726[/C][/ROW]
[ROW][C]127[/C][C]17[/C][C]15.1732[/C][C]1.82681[/C][/ROW]
[ROW][C]128[/C][C]19[/C][C]14.9527[/C][C]4.04726[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]13.5447[/C][C]1.45531[/C][/ROW]
[ROW][C]130[/C][C]13[/C][C]14.5576[/C][C]-1.55764[/C][/ROW]
[ROW][C]131[/C][C]9[/C][C]10.6172[/C][C]-1.61721[/C][/ROW]
[ROW][C]132[/C][C]15[/C][C]15.2174[/C][C]-0.217353[/C][/ROW]
[ROW][C]133[/C][C]15[/C][C]12.5562[/C][C]2.44377[/C][/ROW]
[ROW][C]134[/C][C]15[/C][C]14.1233[/C][C]0.876715[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]13.6235[/C][C]2.37651[/C][/ROW]
[ROW][C]136[/C][C]11[/C][C]9.4046[/C][C]1.5954[/C][/ROW]
[ROW][C]137[/C][C]14[/C][C]13.2507[/C][C]0.749309[/C][/ROW]
[ROW][C]138[/C][C]11[/C][C]11.9548[/C][C]-0.954802[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.1571[/C][C]0.842943[/C][/ROW]
[ROW][C]140[/C][C]13[/C][C]13.7256[/C][C]-0.725559[/C][/ROW]
[ROW][C]141[/C][C]15[/C][C]14.5482[/C][C]0.451802[/C][/ROW]
[ROW][C]142[/C][C]16[/C][C]13.7104[/C][C]2.28956[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]14.3961[/C][C]-0.396111[/C][/ROW]
[ROW][C]144[/C][C]15[/C][C]14.0766[/C][C]0.923375[/C][/ROW]
[ROW][C]145[/C][C]16[/C][C]14.5356[/C][C]1.46442[/C][/ROW]
[ROW][C]146[/C][C]16[/C][C]14.2079[/C][C]1.79211[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]13.217[/C][C]-2.21699[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]14.4473[/C][C]-2.44727[/C][/ROW]
[ROW][C]149[/C][C]9[/C][C]11.4022[/C][C]-2.40216[/C][/ROW]
[ROW][C]150[/C][C]16[/C][C]14.1684[/C][C]1.83164[/C][/ROW]
[ROW][C]151[/C][C]13[/C][C]12.267[/C][C]0.733014[/C][/ROW]
[ROW][C]152[/C][C]16[/C][C]15.1859[/C][C]0.814108[/C][/ROW]
[ROW][C]153[/C][C]12[/C][C]14.3095[/C][C]-2.30948[/C][/ROW]
[ROW][C]154[/C][C]9[/C][C]11.0106[/C][C]-2.01056[/C][/ROW]
[ROW][C]155[/C][C]13[/C][C]11.6771[/C][C]1.32294[/C][/ROW]
[ROW][C]156[/C][C]13[/C][C]12.3816[/C][C]0.618425[/C][/ROW]
[ROW][C]157[/C][C]14[/C][C]13.2211[/C][C]0.778895[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]14.7079[/C][C]4.29209[/C][/ROW]
[ROW][C]159[/C][C]13[/C][C]15.3547[/C][C]-2.3547[/C][/ROW]
[ROW][C]160[/C][C]12[/C][C]11.8911[/C][C]0.10895[/C][/ROW]
[ROW][C]161[/C][C]13[/C][C]12.4536[/C][C]0.546357[/C][/ROW]
[ROW][C]162[/C][C]10[/C][C]9.58751[/C][C]0.412493[/C][/ROW]
[ROW][C]163[/C][C]14[/C][C]13.4751[/C][C]0.52489[/C][/ROW]
[ROW][C]164[/C][C]16[/C][C]11.6227[/C][C]4.37729[/C][/ROW]
[ROW][C]165[/C][C]10[/C][C]12.1336[/C][C]-2.13364[/C][/ROW]
[ROW][C]166[/C][C]11[/C][C]9.42811[/C][C]1.57189[/C][/ROW]
[ROW][C]167[/C][C]14[/C][C]14.2923[/C][C]-0.292337[/C][/ROW]
[ROW][C]168[/C][C]12[/C][C]13.0254[/C][C]-1.02536[/C][/ROW]
[ROW][C]169[/C][C]9[/C][C]12.8479[/C][C]-3.84788[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]11.9975[/C][C]-2.99748[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]10.858[/C][C]0.142026[/C][/ROW]
[ROW][C]172[/C][C]16[/C][C]14.2802[/C][C]1.71983[/C][/ROW]
[ROW][C]173[/C][C]9[/C][C]14.1549[/C][C]-5.15495[/C][/ROW]
[ROW][C]174[/C][C]13[/C][C]11.5704[/C][C]1.42961[/C][/ROW]
[ROW][C]175[/C][C]16[/C][C]13.4663[/C][C]2.53372[/C][/ROW]
[ROW][C]176[/C][C]13[/C][C]15.3146[/C][C]-2.31457[/C][/ROW]
[ROW][C]177[/C][C]9[/C][C]12.5192[/C][C]-3.51919[/C][/ROW]
[ROW][C]178[/C][C]12[/C][C]11.6337[/C][C]0.366271[/C][/ROW]
[ROW][C]179[/C][C]16[/C][C]14.6697[/C][C]1.33033[/C][/ROW]
[ROW][C]180[/C][C]11[/C][C]13.2514[/C][C]-2.25137[/C][/ROW]
[ROW][C]181[/C][C]14[/C][C]14.1193[/C][C]-0.119275[/C][/ROW]
[ROW][C]182[/C][C]13[/C][C]14.9355[/C][C]-1.93552[/C][/ROW]
[ROW][C]183[/C][C]15[/C][C]14.6311[/C][C]0.368874[/C][/ROW]
[ROW][C]184[/C][C]14[/C][C]14.9547[/C][C]-0.954653[/C][/ROW]
[ROW][C]185[/C][C]16[/C][C]14.1816[/C][C]1.81837[/C][/ROW]
[ROW][C]186[/C][C]13[/C][C]11.6125[/C][C]1.38746[/C][/ROW]
[ROW][C]187[/C][C]14[/C][C]13.5016[/C][C]0.498421[/C][/ROW]
[ROW][C]188[/C][C]15[/C][C]14.3107[/C][C]0.689282[/C][/ROW]
[ROW][C]189[/C][C]13[/C][C]12.5598[/C][C]0.44024[/C][/ROW]
[ROW][C]190[/C][C]11[/C][C]10.4811[/C][C]0.51892[/C][/ROW]
[ROW][C]191[/C][C]11[/C][C]12.4009[/C][C]-1.40085[/C][/ROW]
[ROW][C]192[/C][C]14[/C][C]14.9116[/C][C]-0.911572[/C][/ROW]
[ROW][C]193[/C][C]15[/C][C]12.9227[/C][C]2.07728[/C][/ROW]
[ROW][C]194[/C][C]11[/C][C]12.5168[/C][C]-1.5168[/C][/ROW]
[ROW][C]195[/C][C]15[/C][C]13.132[/C][C]1.86795[/C][/ROW]
[ROW][C]196[/C][C]12[/C][C]14.0033[/C][C]-2.00329[/C][/ROW]
[ROW][C]197[/C][C]14[/C][C]11.7296[/C][C]2.27042[/C][/ROW]
[ROW][C]198[/C][C]14[/C][C]13.3247[/C][C]0.675288[/C][/ROW]
[ROW][C]199[/C][C]8[/C][C]11.1375[/C][C]-3.13755[/C][/ROW]
[ROW][C]200[/C][C]13[/C][C]13.6342[/C][C]-0.634232[/C][/ROW]
[ROW][C]201[/C][C]9[/C][C]12.0935[/C][C]-3.0935[/C][/ROW]
[ROW][C]202[/C][C]15[/C][C]13.7037[/C][C]1.29631[/C][/ROW]
[ROW][C]203[/C][C]17[/C][C]14.0063[/C][C]2.99365[/C][/ROW]
[ROW][C]204[/C][C]13[/C][C]12.5164[/C][C]0.483599[/C][/ROW]
[ROW][C]205[/C][C]15[/C][C]14.3885[/C][C]0.611491[/C][/ROW]
[ROW][C]206[/C][C]15[/C][C]13.6226[/C][C]1.37737[/C][/ROW]
[ROW][C]207[/C][C]14[/C][C]14.436[/C][C]-0.43597[/C][/ROW]
[ROW][C]208[/C][C]16[/C][C]12.3626[/C][C]3.63742[/C][/ROW]
[ROW][C]209[/C][C]13[/C][C]12.8663[/C][C]0.133731[/C][/ROW]
[ROW][C]210[/C][C]16[/C][C]14.1772[/C][C]1.82275[/C][/ROW]
[ROW][C]211[/C][C]9[/C][C]11.5884[/C][C]-2.58841[/C][/ROW]
[ROW][C]212[/C][C]16[/C][C]14.434[/C][C]1.56597[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.1131[/C][C]-1.11314[/C][/ROW]
[ROW][C]214[/C][C]10[/C][C]13.7708[/C][C]-3.77076[/C][/ROW]
[ROW][C]215[/C][C]11[/C][C]11.9264[/C][C]-0.926413[/C][/ROW]
[ROW][C]216[/C][C]15[/C][C]13.1778[/C][C]1.82221[/C][/ROW]
[ROW][C]217[/C][C]17[/C][C]14.688[/C][C]2.31203[/C][/ROW]
[ROW][C]218[/C][C]14[/C][C]14.1073[/C][C]-0.107258[/C][/ROW]
[ROW][C]219[/C][C]8[/C][C]9.83541[/C][C]-1.83541[/C][/ROW]
[ROW][C]220[/C][C]15[/C][C]13.3972[/C][C]1.60281[/C][/ROW]
[ROW][C]221[/C][C]11[/C][C]13.6761[/C][C]-2.67609[/C][/ROW]
[ROW][C]222[/C][C]16[/C][C]13.3218[/C][C]2.67815[/C][/ROW]
[ROW][C]223[/C][C]10[/C][C]11.8889[/C][C]-1.88891[/C][/ROW]
[ROW][C]224[/C][C]15[/C][C]14.6806[/C][C]0.319379[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]9.24792[/C][C]-0.247918[/C][/ROW]
[ROW][C]226[/C][C]16[/C][C]14.2496[/C][C]1.75035[/C][/ROW]
[ROW][C]227[/C][C]19[/C][C]13.6031[/C][C]5.39689[/C][/ROW]
[ROW][C]228[/C][C]12[/C][C]13.3958[/C][C]-1.39583[/C][/ROW]
[ROW][C]229[/C][C]8[/C][C]9.36124[/C][C]-1.36124[/C][/ROW]
[ROW][C]230[/C][C]11[/C][C]13.1703[/C][C]-2.17029[/C][/ROW]
[ROW][C]231[/C][C]14[/C][C]13.6823[/C][C]0.317706[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]11.8908[/C][C]-2.89078[/C][/ROW]
[ROW][C]233[/C][C]15[/C][C]14.75[/C][C]0.250013[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]12.0518[/C][C]0.948226[/C][/ROW]
[ROW][C]235[/C][C]16[/C][C]14.6402[/C][C]1.35977[/C][/ROW]
[ROW][C]236[/C][C]11[/C][C]12.5955[/C][C]-1.59555[/C][/ROW]
[ROW][C]237[/C][C]12[/C][C]11.3231[/C][C]0.676858[/C][/ROW]
[ROW][C]238[/C][C]13[/C][C]12.5492[/C][C]0.450848[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]13.9801[/C][C]-3.98005[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]13.3717[/C][C]-2.37168[/C][/ROW]
[ROW][C]241[/C][C]12[/C][C]14.5751[/C][C]-2.57513[/C][/ROW]
[ROW][C]242[/C][C]8[/C][C]10.4213[/C][C]-2.42133[/C][/ROW]
[ROW][C]243[/C][C]12[/C][C]11.6406[/C][C]0.359421[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]12.03[/C][C]-0.0299576[/C][/ROW]
[ROW][C]245[/C][C]15[/C][C]13.2157[/C][C]1.78433[/C][/ROW]
[ROW][C]246[/C][C]11[/C][C]10.4697[/C][C]0.530337[/C][/ROW]
[ROW][C]247[/C][C]13[/C][C]12.4394[/C][C]0.560552[/C][/ROW]
[ROW][C]248[/C][C]14[/C][C]8.59347[/C][C]5.40653[/C][/ROW]
[ROW][C]249[/C][C]10[/C][C]9.98827[/C][C]0.0117308[/C][/ROW]
[ROW][C]250[/C][C]12[/C][C]11.2077[/C][C]0.792345[/C][/ROW]
[ROW][C]251[/C][C]15[/C][C]12.5859[/C][C]2.41407[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.5839[/C][C]1.4161[/C][/ROW]
[ROW][C]253[/C][C]13[/C][C]13.8675[/C][C]-0.867549[/C][/ROW]
[ROW][C]254[/C][C]13[/C][C]13.3296[/C][C]-0.329625[/C][/ROW]
[ROW][C]255[/C][C]12[/C][C]11.4627[/C][C]0.537345[/C][/ROW]
[ROW][C]256[/C][C]12[/C][C]12.2603[/C][C]-0.260293[/C][/ROW]
[ROW][C]257[/C][C]9[/C][C]10.2879[/C][C]-1.28788[/C][/ROW]
[ROW][C]258[/C][C]9[/C][C]11.1279[/C][C]-2.12787[/C][/ROW]
[ROW][C]259[/C][C]15[/C][C]12.1212[/C][C]2.8788[/C][/ROW]
[ROW][C]260[/C][C]10[/C][C]14.6509[/C][C]-4.65095[/C][/ROW]
[ROW][C]261[/C][C]14[/C][C]13.1781[/C][C]0.821873[/C][/ROW]
[ROW][C]262[/C][C]15[/C][C]13.0345[/C][C]1.96552[/C][/ROW]
[ROW][C]263[/C][C]7[/C][C]9.4718[/C][C]-2.4718[/C][/ROW]
[ROW][C]264[/C][C]14[/C][C]13.384[/C][C]0.616037[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&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
11414.2025-0.202488
21815.52242.47756
31114.1201-3.12012
41214.8512-2.85124
51611.44724.5528
61814.72773.2723
71411.0332.96699
81415.2203-1.22033
91515.4182-0.41823
101514.62480.375178
111715.75511.24486
121915.78993.21009
131013.5888-3.58881
141613.67632.32368
151815.82082.17922
161413.57220.427834
171414.0267-0.0267326
181715.85851.14152
191415.5566-1.55659
201613.96672.03334
211815.49752.50254
221113.8754-2.87544
231414.4934-0.493372
241213.7255-1.72547
251715.42471.57533
26915.9291-6.92911
271615.10850.891474
281413.38050.61947
291513.95131.04865
301114.1219-3.12193
311615.77930.220684
321312.85730.142711
331715.18421.81577
341515.351-0.351023
351413.96280.0371754
361615.7260.274021
37910.9611-1.96112
381514.34950.650527
391715.39081.60921
401315.2611-2.26113
411515.735-0.735035
421613.63712.36288
431615.71960.280371
441213.171-1.17105
451514.64710.352882
461113.5972-2.59721
471515.3608-0.360763
481514.86990.130106
491713.41663.58339
501314.6983-1.69829
511615.13210.867914
521413.42530.574706
531111.6321-0.632148
541213.6723-1.67232
551214.1819-2.18188
561513.70971.29029
571614.08931.91072
581515.3739-0.373933
591215.0833-3.0833
601213.3166-1.31657
61810.763-2.76302
621314.4336-1.43355
631114.4473-3.4473
641412.97621.02385
651513.48881.51123
661015.355-5.35498
671112.8729-1.87288
681214.7308-2.73079
691513.85121.14883
701513.90851.09151
711413.98620.0138263
721613.04122.95875
731514.60530.394703
741515.4169-0.416906
751315.1836-2.18364
761212.4468-0.44677
771714.21792.78213
781312.77160.228395
791514.06740.932573
801315.1847-2.18475
811515.0844-0.0844208
821515.7369-0.736891
831614.47261.52742
841514.52030.4797
851414.3586-0.358552
861514.26710.732912
871414.4603-0.460319
881312.9560.0440465
89710.7316-3.73156
901714.02882.9712
911312.9120.0879561
921514.31150.68847
931413.42790.572063
941314.1426-1.14261
951615.10750.892501
961212.9358-0.935765
971415.0194-1.01938
981715.00691.99305
991515.1982-0.198152
1001715.17891.82105
1011213.0629-1.06289
1021614.97941.02063
1031114.5618-3.56183
1041513.17151.82852
105911.4781-2.47812
1061614.9711.02895
1071512.96082.03917
1081012.891-2.891
109109.393360.606638
1101513.93031.06974
1111113.161-2.16105
1121315.3241-2.32412
1131411.84152.15854
1141814.20533.79472
1151615.50760.492367
1161412.9951.00504
1171413.96470.0353442
1181415.1151-1.11509
1191413.66160.33841
1201212.5644-0.564366
1211413.48880.511247
1221514.85680.143243
1231515.7972-0.797204
1241514.4920.508017
1251314.5893-1.58929
1261716.12330.876726
1271715.17321.82681
1281914.95274.04726
1291513.54471.45531
1301314.5576-1.55764
131910.6172-1.61721
1321515.2174-0.217353
1331512.55622.44377
1341514.12330.876715
1351613.62352.37651
136119.40461.5954
1371413.25070.749309
1381111.9548-0.954802
1391514.15710.842943
1401313.7256-0.725559
1411514.54820.451802
1421613.71042.28956
1431414.3961-0.396111
1441514.07660.923375
1451614.53561.46442
1461614.20791.79211
1471113.217-2.21699
1481214.4473-2.44727
149911.4022-2.40216
1501614.16841.83164
1511312.2670.733014
1521615.18590.814108
1531214.3095-2.30948
154911.0106-2.01056
1551311.67711.32294
1561312.38160.618425
1571413.22110.778895
1581914.70794.29209
1591315.3547-2.3547
1601211.89110.10895
1611312.45360.546357
162109.587510.412493
1631413.47510.52489
1641611.62274.37729
1651012.1336-2.13364
166119.428111.57189
1671414.2923-0.292337
1681213.0254-1.02536
169912.8479-3.84788
170911.9975-2.99748
1711110.8580.142026
1721614.28021.71983
173914.1549-5.15495
1741311.57041.42961
1751613.46632.53372
1761315.3146-2.31457
177912.5192-3.51919
1781211.63370.366271
1791614.66971.33033
1801113.2514-2.25137
1811414.1193-0.119275
1821314.9355-1.93552
1831514.63110.368874
1841414.9547-0.954653
1851614.18161.81837
1861311.61251.38746
1871413.50160.498421
1881514.31070.689282
1891312.55980.44024
1901110.48110.51892
1911112.4009-1.40085
1921414.9116-0.911572
1931512.92272.07728
1941112.5168-1.5168
1951513.1321.86795
1961214.0033-2.00329
1971411.72962.27042
1981413.32470.675288
199811.1375-3.13755
2001313.6342-0.634232
201912.0935-3.0935
2021513.70371.29631
2031714.00632.99365
2041312.51640.483599
2051514.38850.611491
2061513.62261.37737
2071414.436-0.43597
2081612.36263.63742
2091312.86630.133731
2101614.17721.82275
211911.5884-2.58841
2121614.4341.56597
2131112.1131-1.11314
2141013.7708-3.77076
2151111.9264-0.926413
2161513.17781.82221
2171714.6882.31203
2181414.1073-0.107258
21989.83541-1.83541
2201513.39721.60281
2211113.6761-2.67609
2221613.32182.67815
2231011.8889-1.88891
2241514.68060.319379
22599.24792-0.247918
2261614.24961.75035
2271913.60315.39689
2281213.3958-1.39583
22989.36124-1.36124
2301113.1703-2.17029
2311413.68230.317706
232911.8908-2.89078
2331514.750.250013
2341312.05180.948226
2351614.64021.35977
2361112.5955-1.59555
2371211.32310.676858
2381312.54920.450848
2391013.9801-3.98005
2401113.3717-2.37168
2411214.5751-2.57513
242810.4213-2.42133
2431211.64060.359421
2441212.03-0.0299576
2451513.21571.78433
2461110.46970.530337
2471312.43940.560552
248148.593475.40653
249109.988270.0117308
2501211.20770.792345
2511512.58592.41407
2521311.58391.4161
2531313.8675-0.867549
2541313.3296-0.329625
2551211.46270.537345
2561212.2603-0.260293
257910.2879-1.28788
258911.1279-2.12787
2591512.12122.8788
2601014.6509-4.65095
2611413.17810.821873
2621513.03451.96552
26379.4718-2.4718
2641413.3840.616037






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
130.9920920.01581630.00790817
140.9819720.03605650.0180282
150.9775870.04482590.022413
160.9584250.08314940.0415747
170.9808760.03824740.0191237
180.9670680.0658640.032932
190.9471640.1056720.052836
200.9383650.123270.061635
210.9434820.1130350.0565176
220.9523320.09533580.0476679
230.954680.09064060.0453203
240.9355080.1289850.0644923
250.9203040.1593920.0796959
260.9993760.001248050.000624024
270.9990410.001918510.000959255
280.9984830.00303410.00151705
290.9976140.004772680.00238634
300.9974810.005037520.00251876
310.9964760.007047610.0035238
320.9945950.01080960.00540479
330.9946170.01076640.0053832
340.9925410.01491840.00745922
350.9896340.0207320.010366
360.9858280.02834460.0141723
370.9879680.02406370.0120318
380.9842270.03154640.0157732
390.9836090.03278120.0163906
400.9811280.03774390.018872
410.9744270.05114620.0255731
420.9756280.04874320.0243716
430.9691930.06161380.0308069
440.9609810.07803790.0390189
450.9500940.09981240.0499062
460.9511650.09766910.0488345
470.9423140.1153720.0576859
480.9286940.1426120.0713062
490.9506710.09865880.0493294
500.9435340.1129320.0564658
510.933240.133520.0667599
520.9182710.1634580.0817292
530.9020980.1958040.0979021
540.8846320.2307360.115368
550.8747970.2504050.125203
560.8640550.2718910.135945
570.8599330.2801340.140067
580.8340340.3319310.165966
590.8586430.2827140.141357
600.8426750.3146490.157325
610.8515830.2968340.148417
620.8362390.3275210.163761
630.8710010.2579990.128999
640.8648540.2702920.135146
650.8655020.2689960.134498
660.8835770.2328460.116423
670.8862640.2274730.113736
680.8766370.2467270.123363
690.9148920.1702150.0851077
700.9221170.1557670.0778835
710.9154320.1691350.0845676
720.9399910.1200170.0600085
730.9285450.1429090.0714545
740.913960.172080.0860399
750.9055690.1888620.0944311
760.8886070.2227850.111393
770.9123830.1752350.0876174
780.8984120.2031770.101588
790.8894690.2210620.110531
800.8830280.2339450.116972
810.8627570.2744850.137243
820.8419260.3161480.158074
830.8370880.3258250.162912
840.8163460.3673080.183654
850.7907570.4184870.209243
860.7649860.4700280.235014
870.7353190.5293630.264681
880.7038880.5922250.296112
890.7746810.4506380.225319
900.8121940.3756110.187806
910.7887520.4224970.211248
920.7626010.4747980.237399
930.7403460.5193080.259654
940.715820.5683590.28418
950.6908050.618390.309195
960.6619030.6761930.338097
970.6338910.7322190.366109
980.6404680.7190640.359532
990.604970.790060.39503
1000.6011340.7977320.398866
1010.5729990.8540020.427001
1020.5490.9020.451
1030.6007720.7984560.399228
1040.5887510.8224980.411249
1050.6018680.7962640.398132
1060.5814420.8371160.418558
1070.5765560.8468870.423444
1080.6137370.7725270.386263
1090.5790650.841870.420935
1100.5565440.8869120.443456
1110.5577910.8844170.442209
1120.5725780.8548430.427422
1130.5594930.8810140.440507
1140.6656020.6687960.334398
1150.6414180.7171640.358582
1160.6147520.7704970.385248
1170.5795660.8408680.420434
1180.5533320.8933360.446668
1190.5182390.9635220.481761
1200.4845350.969070.515465
1210.4639680.9279360.536032
1220.4287290.8574570.571271
1230.3988620.7977240.601138
1240.3730860.7461710.626914
1250.3594990.7189970.640501
1260.3355720.6711430.664428
1270.323130.6462590.67687
1280.4362150.872430.563785
1290.4193550.838710.580645
1300.4061950.8123890.593805
1310.3916510.7833010.608349
1320.3592170.7184350.640783
1330.3840530.7681070.615947
1340.3550090.7100170.644991
1350.3719110.7438230.628089
1360.364730.7294610.63527
1370.3353140.6706270.664686
1380.3112570.6225130.688743
1390.2837310.5674620.716269
1400.2591110.5182220.740889
1410.2319290.4638580.768071
1420.2372210.4744420.762779
1430.2110580.4221160.788942
1440.1918910.3837810.808109
1450.1790540.3581080.820946
1460.1736940.3473880.826306
1470.1811160.3622320.818884
1480.1963350.392670.803665
1490.2131550.4263090.786845
1500.2084820.4169650.791518
1510.1866760.3733520.813324
1520.1666110.3332210.833389
1530.1766950.353390.823305
1540.1887190.3774390.811281
1550.1703270.3406550.829673
1560.1541770.3083530.845823
1570.1341820.2683640.865818
1580.2065190.4130390.793481
1590.2235150.4470290.776485
1600.1979070.3958140.802093
1610.1734170.3468330.826583
1620.1510120.3020250.848988
1630.1312290.2624570.868771
1640.2194950.438990.780505
1650.2216910.4433830.778309
1660.2119570.4239150.788043
1670.186960.373920.81304
1680.1689280.3378560.831072
1690.2262450.452490.773755
1700.2533550.5067090.746645
1710.2249830.4499660.775017
1720.2176750.435350.782325
1730.3829350.7658710.617065
1740.3625560.7251110.637444
1750.3794080.7588160.620592
1760.3890010.7780030.610999
1770.4582140.9164280.541786
1780.421190.8423790.57881
1790.3963340.7926670.603666
1800.4005870.8011730.599413
1810.3660830.7321670.633917
1820.3724960.7449930.627504
1830.3367610.6735230.663239
1840.3144610.6289230.685539
1850.3129970.6259930.687003
1860.3007830.6015670.699217
1870.2679460.5358920.732054
1880.2389510.4779020.761049
1890.2097770.4195530.790223
1900.1848830.3697660.815117
1910.1915570.3831140.808443
1920.1762190.3524390.823781
1930.1818650.363730.818135
1940.1724250.344850.827575
1950.1684760.3369530.831524
1960.179790.3595810.82021
1970.2144670.4289350.785533
1980.197060.3941190.80294
1990.2287790.4575580.771221
2000.1990390.3980790.800961
2010.2381270.4762550.761873
2020.2149770.4299530.785023
2030.2618470.5236940.738153
2040.2333220.4666430.766678
2050.2022390.4044790.797761
2060.1828190.3656390.817181
2070.1553230.3106460.844677
2080.174410.3488210.82559
2090.1468540.2937080.853146
2100.1611270.3222530.838873
2110.1820490.3640980.817951
2120.1683660.3367320.831634
2130.1438540.2877070.856146
2140.1846810.3693620.815319
2150.1624170.3248350.837583
2160.1488620.2977230.851138
2170.1747250.349450.825275
2180.1487330.2974650.851267
2190.1355460.2710920.864454
2200.1428110.2856220.857189
2210.144020.2880390.85598
2220.1478570.2957140.852143
2230.1321370.2642740.867863
2240.1071940.2143870.892806
2250.09519160.1903830.904808
2260.1179870.2359730.882013
2270.3097430.6194860.690257
2280.2720110.5440230.727989
2290.2363020.4726040.763698
2300.2134260.4268530.786574
2310.1801750.360350.819825
2320.2028850.4057710.797115
2330.1657470.3314940.834253
2340.1344490.2688980.865551
2350.1392080.2784150.860792
2360.1148340.2296680.885166
2370.09518070.1903610.904819
2380.06970210.1394040.930298
2390.1448460.2896910.855154
2400.1608330.3216660.839167
2410.1607030.3214050.839297
2420.7636310.4727380.236369
2430.6895430.6209140.310457
2440.6374340.7251310.362566
2450.5887640.8224720.411236
2460.5032110.9935790.496789
2470.4758810.9517610.524119
2480.4582830.9165660.541717
2490.3388450.677690.661155
2500.3592750.718550.640725
2510.2440760.4881520.755924

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
13 & 0.992092 & 0.0158163 & 0.00790817 \tabularnewline
14 & 0.981972 & 0.0360565 & 0.0180282 \tabularnewline
15 & 0.977587 & 0.0448259 & 0.022413 \tabularnewline
16 & 0.958425 & 0.0831494 & 0.0415747 \tabularnewline
17 & 0.980876 & 0.0382474 & 0.0191237 \tabularnewline
18 & 0.967068 & 0.065864 & 0.032932 \tabularnewline
19 & 0.947164 & 0.105672 & 0.052836 \tabularnewline
20 & 0.938365 & 0.12327 & 0.061635 \tabularnewline
21 & 0.943482 & 0.113035 & 0.0565176 \tabularnewline
22 & 0.952332 & 0.0953358 & 0.0476679 \tabularnewline
23 & 0.95468 & 0.0906406 & 0.0453203 \tabularnewline
24 & 0.935508 & 0.128985 & 0.0644923 \tabularnewline
25 & 0.920304 & 0.159392 & 0.0796959 \tabularnewline
26 & 0.999376 & 0.00124805 & 0.000624024 \tabularnewline
27 & 0.999041 & 0.00191851 & 0.000959255 \tabularnewline
28 & 0.998483 & 0.0030341 & 0.00151705 \tabularnewline
29 & 0.997614 & 0.00477268 & 0.00238634 \tabularnewline
30 & 0.997481 & 0.00503752 & 0.00251876 \tabularnewline
31 & 0.996476 & 0.00704761 & 0.0035238 \tabularnewline
32 & 0.994595 & 0.0108096 & 0.00540479 \tabularnewline
33 & 0.994617 & 0.0107664 & 0.0053832 \tabularnewline
34 & 0.992541 & 0.0149184 & 0.00745922 \tabularnewline
35 & 0.989634 & 0.020732 & 0.010366 \tabularnewline
36 & 0.985828 & 0.0283446 & 0.0141723 \tabularnewline
37 & 0.987968 & 0.0240637 & 0.0120318 \tabularnewline
38 & 0.984227 & 0.0315464 & 0.0157732 \tabularnewline
39 & 0.983609 & 0.0327812 & 0.0163906 \tabularnewline
40 & 0.981128 & 0.0377439 & 0.018872 \tabularnewline
41 & 0.974427 & 0.0511462 & 0.0255731 \tabularnewline
42 & 0.975628 & 0.0487432 & 0.0243716 \tabularnewline
43 & 0.969193 & 0.0616138 & 0.0308069 \tabularnewline
44 & 0.960981 & 0.0780379 & 0.0390189 \tabularnewline
45 & 0.950094 & 0.0998124 & 0.0499062 \tabularnewline
46 & 0.951165 & 0.0976691 & 0.0488345 \tabularnewline
47 & 0.942314 & 0.115372 & 0.0576859 \tabularnewline
48 & 0.928694 & 0.142612 & 0.0713062 \tabularnewline
49 & 0.950671 & 0.0986588 & 0.0493294 \tabularnewline
50 & 0.943534 & 0.112932 & 0.0564658 \tabularnewline
51 & 0.93324 & 0.13352 & 0.0667599 \tabularnewline
52 & 0.918271 & 0.163458 & 0.0817292 \tabularnewline
53 & 0.902098 & 0.195804 & 0.0979021 \tabularnewline
54 & 0.884632 & 0.230736 & 0.115368 \tabularnewline
55 & 0.874797 & 0.250405 & 0.125203 \tabularnewline
56 & 0.864055 & 0.271891 & 0.135945 \tabularnewline
57 & 0.859933 & 0.280134 & 0.140067 \tabularnewline
58 & 0.834034 & 0.331931 & 0.165966 \tabularnewline
59 & 0.858643 & 0.282714 & 0.141357 \tabularnewline
60 & 0.842675 & 0.314649 & 0.157325 \tabularnewline
61 & 0.851583 & 0.296834 & 0.148417 \tabularnewline
62 & 0.836239 & 0.327521 & 0.163761 \tabularnewline
63 & 0.871001 & 0.257999 & 0.128999 \tabularnewline
64 & 0.864854 & 0.270292 & 0.135146 \tabularnewline
65 & 0.865502 & 0.268996 & 0.134498 \tabularnewline
66 & 0.883577 & 0.232846 & 0.116423 \tabularnewline
67 & 0.886264 & 0.227473 & 0.113736 \tabularnewline
68 & 0.876637 & 0.246727 & 0.123363 \tabularnewline
69 & 0.914892 & 0.170215 & 0.0851077 \tabularnewline
70 & 0.922117 & 0.155767 & 0.0778835 \tabularnewline
71 & 0.915432 & 0.169135 & 0.0845676 \tabularnewline
72 & 0.939991 & 0.120017 & 0.0600085 \tabularnewline
73 & 0.928545 & 0.142909 & 0.0714545 \tabularnewline
74 & 0.91396 & 0.17208 & 0.0860399 \tabularnewline
75 & 0.905569 & 0.188862 & 0.0944311 \tabularnewline
76 & 0.888607 & 0.222785 & 0.111393 \tabularnewline
77 & 0.912383 & 0.175235 & 0.0876174 \tabularnewline
78 & 0.898412 & 0.203177 & 0.101588 \tabularnewline
79 & 0.889469 & 0.221062 & 0.110531 \tabularnewline
80 & 0.883028 & 0.233945 & 0.116972 \tabularnewline
81 & 0.862757 & 0.274485 & 0.137243 \tabularnewline
82 & 0.841926 & 0.316148 & 0.158074 \tabularnewline
83 & 0.837088 & 0.325825 & 0.162912 \tabularnewline
84 & 0.816346 & 0.367308 & 0.183654 \tabularnewline
85 & 0.790757 & 0.418487 & 0.209243 \tabularnewline
86 & 0.764986 & 0.470028 & 0.235014 \tabularnewline
87 & 0.735319 & 0.529363 & 0.264681 \tabularnewline
88 & 0.703888 & 0.592225 & 0.296112 \tabularnewline
89 & 0.774681 & 0.450638 & 0.225319 \tabularnewline
90 & 0.812194 & 0.375611 & 0.187806 \tabularnewline
91 & 0.788752 & 0.422497 & 0.211248 \tabularnewline
92 & 0.762601 & 0.474798 & 0.237399 \tabularnewline
93 & 0.740346 & 0.519308 & 0.259654 \tabularnewline
94 & 0.71582 & 0.568359 & 0.28418 \tabularnewline
95 & 0.690805 & 0.61839 & 0.309195 \tabularnewline
96 & 0.661903 & 0.676193 & 0.338097 \tabularnewline
97 & 0.633891 & 0.732219 & 0.366109 \tabularnewline
98 & 0.640468 & 0.719064 & 0.359532 \tabularnewline
99 & 0.60497 & 0.79006 & 0.39503 \tabularnewline
100 & 0.601134 & 0.797732 & 0.398866 \tabularnewline
101 & 0.572999 & 0.854002 & 0.427001 \tabularnewline
102 & 0.549 & 0.902 & 0.451 \tabularnewline
103 & 0.600772 & 0.798456 & 0.399228 \tabularnewline
104 & 0.588751 & 0.822498 & 0.411249 \tabularnewline
105 & 0.601868 & 0.796264 & 0.398132 \tabularnewline
106 & 0.581442 & 0.837116 & 0.418558 \tabularnewline
107 & 0.576556 & 0.846887 & 0.423444 \tabularnewline
108 & 0.613737 & 0.772527 & 0.386263 \tabularnewline
109 & 0.579065 & 0.84187 & 0.420935 \tabularnewline
110 & 0.556544 & 0.886912 & 0.443456 \tabularnewline
111 & 0.557791 & 0.884417 & 0.442209 \tabularnewline
112 & 0.572578 & 0.854843 & 0.427422 \tabularnewline
113 & 0.559493 & 0.881014 & 0.440507 \tabularnewline
114 & 0.665602 & 0.668796 & 0.334398 \tabularnewline
115 & 0.641418 & 0.717164 & 0.358582 \tabularnewline
116 & 0.614752 & 0.770497 & 0.385248 \tabularnewline
117 & 0.579566 & 0.840868 & 0.420434 \tabularnewline
118 & 0.553332 & 0.893336 & 0.446668 \tabularnewline
119 & 0.518239 & 0.963522 & 0.481761 \tabularnewline
120 & 0.484535 & 0.96907 & 0.515465 \tabularnewline
121 & 0.463968 & 0.927936 & 0.536032 \tabularnewline
122 & 0.428729 & 0.857457 & 0.571271 \tabularnewline
123 & 0.398862 & 0.797724 & 0.601138 \tabularnewline
124 & 0.373086 & 0.746171 & 0.626914 \tabularnewline
125 & 0.359499 & 0.718997 & 0.640501 \tabularnewline
126 & 0.335572 & 0.671143 & 0.664428 \tabularnewline
127 & 0.32313 & 0.646259 & 0.67687 \tabularnewline
128 & 0.436215 & 0.87243 & 0.563785 \tabularnewline
129 & 0.419355 & 0.83871 & 0.580645 \tabularnewline
130 & 0.406195 & 0.812389 & 0.593805 \tabularnewline
131 & 0.391651 & 0.783301 & 0.608349 \tabularnewline
132 & 0.359217 & 0.718435 & 0.640783 \tabularnewline
133 & 0.384053 & 0.768107 & 0.615947 \tabularnewline
134 & 0.355009 & 0.710017 & 0.644991 \tabularnewline
135 & 0.371911 & 0.743823 & 0.628089 \tabularnewline
136 & 0.36473 & 0.729461 & 0.63527 \tabularnewline
137 & 0.335314 & 0.670627 & 0.664686 \tabularnewline
138 & 0.311257 & 0.622513 & 0.688743 \tabularnewline
139 & 0.283731 & 0.567462 & 0.716269 \tabularnewline
140 & 0.259111 & 0.518222 & 0.740889 \tabularnewline
141 & 0.231929 & 0.463858 & 0.768071 \tabularnewline
142 & 0.237221 & 0.474442 & 0.762779 \tabularnewline
143 & 0.211058 & 0.422116 & 0.788942 \tabularnewline
144 & 0.191891 & 0.383781 & 0.808109 \tabularnewline
145 & 0.179054 & 0.358108 & 0.820946 \tabularnewline
146 & 0.173694 & 0.347388 & 0.826306 \tabularnewline
147 & 0.181116 & 0.362232 & 0.818884 \tabularnewline
148 & 0.196335 & 0.39267 & 0.803665 \tabularnewline
149 & 0.213155 & 0.426309 & 0.786845 \tabularnewline
150 & 0.208482 & 0.416965 & 0.791518 \tabularnewline
151 & 0.186676 & 0.373352 & 0.813324 \tabularnewline
152 & 0.166611 & 0.333221 & 0.833389 \tabularnewline
153 & 0.176695 & 0.35339 & 0.823305 \tabularnewline
154 & 0.188719 & 0.377439 & 0.811281 \tabularnewline
155 & 0.170327 & 0.340655 & 0.829673 \tabularnewline
156 & 0.154177 & 0.308353 & 0.845823 \tabularnewline
157 & 0.134182 & 0.268364 & 0.865818 \tabularnewline
158 & 0.206519 & 0.413039 & 0.793481 \tabularnewline
159 & 0.223515 & 0.447029 & 0.776485 \tabularnewline
160 & 0.197907 & 0.395814 & 0.802093 \tabularnewline
161 & 0.173417 & 0.346833 & 0.826583 \tabularnewline
162 & 0.151012 & 0.302025 & 0.848988 \tabularnewline
163 & 0.131229 & 0.262457 & 0.868771 \tabularnewline
164 & 0.219495 & 0.43899 & 0.780505 \tabularnewline
165 & 0.221691 & 0.443383 & 0.778309 \tabularnewline
166 & 0.211957 & 0.423915 & 0.788043 \tabularnewline
167 & 0.18696 & 0.37392 & 0.81304 \tabularnewline
168 & 0.168928 & 0.337856 & 0.831072 \tabularnewline
169 & 0.226245 & 0.45249 & 0.773755 \tabularnewline
170 & 0.253355 & 0.506709 & 0.746645 \tabularnewline
171 & 0.224983 & 0.449966 & 0.775017 \tabularnewline
172 & 0.217675 & 0.43535 & 0.782325 \tabularnewline
173 & 0.382935 & 0.765871 & 0.617065 \tabularnewline
174 & 0.362556 & 0.725111 & 0.637444 \tabularnewline
175 & 0.379408 & 0.758816 & 0.620592 \tabularnewline
176 & 0.389001 & 0.778003 & 0.610999 \tabularnewline
177 & 0.458214 & 0.916428 & 0.541786 \tabularnewline
178 & 0.42119 & 0.842379 & 0.57881 \tabularnewline
179 & 0.396334 & 0.792667 & 0.603666 \tabularnewline
180 & 0.400587 & 0.801173 & 0.599413 \tabularnewline
181 & 0.366083 & 0.732167 & 0.633917 \tabularnewline
182 & 0.372496 & 0.744993 & 0.627504 \tabularnewline
183 & 0.336761 & 0.673523 & 0.663239 \tabularnewline
184 & 0.314461 & 0.628923 & 0.685539 \tabularnewline
185 & 0.312997 & 0.625993 & 0.687003 \tabularnewline
186 & 0.300783 & 0.601567 & 0.699217 \tabularnewline
187 & 0.267946 & 0.535892 & 0.732054 \tabularnewline
188 & 0.238951 & 0.477902 & 0.761049 \tabularnewline
189 & 0.209777 & 0.419553 & 0.790223 \tabularnewline
190 & 0.184883 & 0.369766 & 0.815117 \tabularnewline
191 & 0.191557 & 0.383114 & 0.808443 \tabularnewline
192 & 0.176219 & 0.352439 & 0.823781 \tabularnewline
193 & 0.181865 & 0.36373 & 0.818135 \tabularnewline
194 & 0.172425 & 0.34485 & 0.827575 \tabularnewline
195 & 0.168476 & 0.336953 & 0.831524 \tabularnewline
196 & 0.17979 & 0.359581 & 0.82021 \tabularnewline
197 & 0.214467 & 0.428935 & 0.785533 \tabularnewline
198 & 0.19706 & 0.394119 & 0.80294 \tabularnewline
199 & 0.228779 & 0.457558 & 0.771221 \tabularnewline
200 & 0.199039 & 0.398079 & 0.800961 \tabularnewline
201 & 0.238127 & 0.476255 & 0.761873 \tabularnewline
202 & 0.214977 & 0.429953 & 0.785023 \tabularnewline
203 & 0.261847 & 0.523694 & 0.738153 \tabularnewline
204 & 0.233322 & 0.466643 & 0.766678 \tabularnewline
205 & 0.202239 & 0.404479 & 0.797761 \tabularnewline
206 & 0.182819 & 0.365639 & 0.817181 \tabularnewline
207 & 0.155323 & 0.310646 & 0.844677 \tabularnewline
208 & 0.17441 & 0.348821 & 0.82559 \tabularnewline
209 & 0.146854 & 0.293708 & 0.853146 \tabularnewline
210 & 0.161127 & 0.322253 & 0.838873 \tabularnewline
211 & 0.182049 & 0.364098 & 0.817951 \tabularnewline
212 & 0.168366 & 0.336732 & 0.831634 \tabularnewline
213 & 0.143854 & 0.287707 & 0.856146 \tabularnewline
214 & 0.184681 & 0.369362 & 0.815319 \tabularnewline
215 & 0.162417 & 0.324835 & 0.837583 \tabularnewline
216 & 0.148862 & 0.297723 & 0.851138 \tabularnewline
217 & 0.174725 & 0.34945 & 0.825275 \tabularnewline
218 & 0.148733 & 0.297465 & 0.851267 \tabularnewline
219 & 0.135546 & 0.271092 & 0.864454 \tabularnewline
220 & 0.142811 & 0.285622 & 0.857189 \tabularnewline
221 & 0.14402 & 0.288039 & 0.85598 \tabularnewline
222 & 0.147857 & 0.295714 & 0.852143 \tabularnewline
223 & 0.132137 & 0.264274 & 0.867863 \tabularnewline
224 & 0.107194 & 0.214387 & 0.892806 \tabularnewline
225 & 0.0951916 & 0.190383 & 0.904808 \tabularnewline
226 & 0.117987 & 0.235973 & 0.882013 \tabularnewline
227 & 0.309743 & 0.619486 & 0.690257 \tabularnewline
228 & 0.272011 & 0.544023 & 0.727989 \tabularnewline
229 & 0.236302 & 0.472604 & 0.763698 \tabularnewline
230 & 0.213426 & 0.426853 & 0.786574 \tabularnewline
231 & 0.180175 & 0.36035 & 0.819825 \tabularnewline
232 & 0.202885 & 0.405771 & 0.797115 \tabularnewline
233 & 0.165747 & 0.331494 & 0.834253 \tabularnewline
234 & 0.134449 & 0.268898 & 0.865551 \tabularnewline
235 & 0.139208 & 0.278415 & 0.860792 \tabularnewline
236 & 0.114834 & 0.229668 & 0.885166 \tabularnewline
237 & 0.0951807 & 0.190361 & 0.904819 \tabularnewline
238 & 0.0697021 & 0.139404 & 0.930298 \tabularnewline
239 & 0.144846 & 0.289691 & 0.855154 \tabularnewline
240 & 0.160833 & 0.321666 & 0.839167 \tabularnewline
241 & 0.160703 & 0.321405 & 0.839297 \tabularnewline
242 & 0.763631 & 0.472738 & 0.236369 \tabularnewline
243 & 0.689543 & 0.620914 & 0.310457 \tabularnewline
244 & 0.637434 & 0.725131 & 0.362566 \tabularnewline
245 & 0.588764 & 0.822472 & 0.411236 \tabularnewline
246 & 0.503211 & 0.993579 & 0.496789 \tabularnewline
247 & 0.475881 & 0.951761 & 0.524119 \tabularnewline
248 & 0.458283 & 0.916566 & 0.541717 \tabularnewline
249 & 0.338845 & 0.67769 & 0.661155 \tabularnewline
250 & 0.359275 & 0.71855 & 0.640725 \tabularnewline
251 & 0.244076 & 0.488152 & 0.755924 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]13[/C][C]0.992092[/C][C]0.0158163[/C][C]0.00790817[/C][/ROW]
[ROW][C]14[/C][C]0.981972[/C][C]0.0360565[/C][C]0.0180282[/C][/ROW]
[ROW][C]15[/C][C]0.977587[/C][C]0.0448259[/C][C]0.022413[/C][/ROW]
[ROW][C]16[/C][C]0.958425[/C][C]0.0831494[/C][C]0.0415747[/C][/ROW]
[ROW][C]17[/C][C]0.980876[/C][C]0.0382474[/C][C]0.0191237[/C][/ROW]
[ROW][C]18[/C][C]0.967068[/C][C]0.065864[/C][C]0.032932[/C][/ROW]
[ROW][C]19[/C][C]0.947164[/C][C]0.105672[/C][C]0.052836[/C][/ROW]
[ROW][C]20[/C][C]0.938365[/C][C]0.12327[/C][C]0.061635[/C][/ROW]
[ROW][C]21[/C][C]0.943482[/C][C]0.113035[/C][C]0.0565176[/C][/ROW]
[ROW][C]22[/C][C]0.952332[/C][C]0.0953358[/C][C]0.0476679[/C][/ROW]
[ROW][C]23[/C][C]0.95468[/C][C]0.0906406[/C][C]0.0453203[/C][/ROW]
[ROW][C]24[/C][C]0.935508[/C][C]0.128985[/C][C]0.0644923[/C][/ROW]
[ROW][C]25[/C][C]0.920304[/C][C]0.159392[/C][C]0.0796959[/C][/ROW]
[ROW][C]26[/C][C]0.999376[/C][C]0.00124805[/C][C]0.000624024[/C][/ROW]
[ROW][C]27[/C][C]0.999041[/C][C]0.00191851[/C][C]0.000959255[/C][/ROW]
[ROW][C]28[/C][C]0.998483[/C][C]0.0030341[/C][C]0.00151705[/C][/ROW]
[ROW][C]29[/C][C]0.997614[/C][C]0.00477268[/C][C]0.00238634[/C][/ROW]
[ROW][C]30[/C][C]0.997481[/C][C]0.00503752[/C][C]0.00251876[/C][/ROW]
[ROW][C]31[/C][C]0.996476[/C][C]0.00704761[/C][C]0.0035238[/C][/ROW]
[ROW][C]32[/C][C]0.994595[/C][C]0.0108096[/C][C]0.00540479[/C][/ROW]
[ROW][C]33[/C][C]0.994617[/C][C]0.0107664[/C][C]0.0053832[/C][/ROW]
[ROW][C]34[/C][C]0.992541[/C][C]0.0149184[/C][C]0.00745922[/C][/ROW]
[ROW][C]35[/C][C]0.989634[/C][C]0.020732[/C][C]0.010366[/C][/ROW]
[ROW][C]36[/C][C]0.985828[/C][C]0.0283446[/C][C]0.0141723[/C][/ROW]
[ROW][C]37[/C][C]0.987968[/C][C]0.0240637[/C][C]0.0120318[/C][/ROW]
[ROW][C]38[/C][C]0.984227[/C][C]0.0315464[/C][C]0.0157732[/C][/ROW]
[ROW][C]39[/C][C]0.983609[/C][C]0.0327812[/C][C]0.0163906[/C][/ROW]
[ROW][C]40[/C][C]0.981128[/C][C]0.0377439[/C][C]0.018872[/C][/ROW]
[ROW][C]41[/C][C]0.974427[/C][C]0.0511462[/C][C]0.0255731[/C][/ROW]
[ROW][C]42[/C][C]0.975628[/C][C]0.0487432[/C][C]0.0243716[/C][/ROW]
[ROW][C]43[/C][C]0.969193[/C][C]0.0616138[/C][C]0.0308069[/C][/ROW]
[ROW][C]44[/C][C]0.960981[/C][C]0.0780379[/C][C]0.0390189[/C][/ROW]
[ROW][C]45[/C][C]0.950094[/C][C]0.0998124[/C][C]0.0499062[/C][/ROW]
[ROW][C]46[/C][C]0.951165[/C][C]0.0976691[/C][C]0.0488345[/C][/ROW]
[ROW][C]47[/C][C]0.942314[/C][C]0.115372[/C][C]0.0576859[/C][/ROW]
[ROW][C]48[/C][C]0.928694[/C][C]0.142612[/C][C]0.0713062[/C][/ROW]
[ROW][C]49[/C][C]0.950671[/C][C]0.0986588[/C][C]0.0493294[/C][/ROW]
[ROW][C]50[/C][C]0.943534[/C][C]0.112932[/C][C]0.0564658[/C][/ROW]
[ROW][C]51[/C][C]0.93324[/C][C]0.13352[/C][C]0.0667599[/C][/ROW]
[ROW][C]52[/C][C]0.918271[/C][C]0.163458[/C][C]0.0817292[/C][/ROW]
[ROW][C]53[/C][C]0.902098[/C][C]0.195804[/C][C]0.0979021[/C][/ROW]
[ROW][C]54[/C][C]0.884632[/C][C]0.230736[/C][C]0.115368[/C][/ROW]
[ROW][C]55[/C][C]0.874797[/C][C]0.250405[/C][C]0.125203[/C][/ROW]
[ROW][C]56[/C][C]0.864055[/C][C]0.271891[/C][C]0.135945[/C][/ROW]
[ROW][C]57[/C][C]0.859933[/C][C]0.280134[/C][C]0.140067[/C][/ROW]
[ROW][C]58[/C][C]0.834034[/C][C]0.331931[/C][C]0.165966[/C][/ROW]
[ROW][C]59[/C][C]0.858643[/C][C]0.282714[/C][C]0.141357[/C][/ROW]
[ROW][C]60[/C][C]0.842675[/C][C]0.314649[/C][C]0.157325[/C][/ROW]
[ROW][C]61[/C][C]0.851583[/C][C]0.296834[/C][C]0.148417[/C][/ROW]
[ROW][C]62[/C][C]0.836239[/C][C]0.327521[/C][C]0.163761[/C][/ROW]
[ROW][C]63[/C][C]0.871001[/C][C]0.257999[/C][C]0.128999[/C][/ROW]
[ROW][C]64[/C][C]0.864854[/C][C]0.270292[/C][C]0.135146[/C][/ROW]
[ROW][C]65[/C][C]0.865502[/C][C]0.268996[/C][C]0.134498[/C][/ROW]
[ROW][C]66[/C][C]0.883577[/C][C]0.232846[/C][C]0.116423[/C][/ROW]
[ROW][C]67[/C][C]0.886264[/C][C]0.227473[/C][C]0.113736[/C][/ROW]
[ROW][C]68[/C][C]0.876637[/C][C]0.246727[/C][C]0.123363[/C][/ROW]
[ROW][C]69[/C][C]0.914892[/C][C]0.170215[/C][C]0.0851077[/C][/ROW]
[ROW][C]70[/C][C]0.922117[/C][C]0.155767[/C][C]0.0778835[/C][/ROW]
[ROW][C]71[/C][C]0.915432[/C][C]0.169135[/C][C]0.0845676[/C][/ROW]
[ROW][C]72[/C][C]0.939991[/C][C]0.120017[/C][C]0.0600085[/C][/ROW]
[ROW][C]73[/C][C]0.928545[/C][C]0.142909[/C][C]0.0714545[/C][/ROW]
[ROW][C]74[/C][C]0.91396[/C][C]0.17208[/C][C]0.0860399[/C][/ROW]
[ROW][C]75[/C][C]0.905569[/C][C]0.188862[/C][C]0.0944311[/C][/ROW]
[ROW][C]76[/C][C]0.888607[/C][C]0.222785[/C][C]0.111393[/C][/ROW]
[ROW][C]77[/C][C]0.912383[/C][C]0.175235[/C][C]0.0876174[/C][/ROW]
[ROW][C]78[/C][C]0.898412[/C][C]0.203177[/C][C]0.101588[/C][/ROW]
[ROW][C]79[/C][C]0.889469[/C][C]0.221062[/C][C]0.110531[/C][/ROW]
[ROW][C]80[/C][C]0.883028[/C][C]0.233945[/C][C]0.116972[/C][/ROW]
[ROW][C]81[/C][C]0.862757[/C][C]0.274485[/C][C]0.137243[/C][/ROW]
[ROW][C]82[/C][C]0.841926[/C][C]0.316148[/C][C]0.158074[/C][/ROW]
[ROW][C]83[/C][C]0.837088[/C][C]0.325825[/C][C]0.162912[/C][/ROW]
[ROW][C]84[/C][C]0.816346[/C][C]0.367308[/C][C]0.183654[/C][/ROW]
[ROW][C]85[/C][C]0.790757[/C][C]0.418487[/C][C]0.209243[/C][/ROW]
[ROW][C]86[/C][C]0.764986[/C][C]0.470028[/C][C]0.235014[/C][/ROW]
[ROW][C]87[/C][C]0.735319[/C][C]0.529363[/C][C]0.264681[/C][/ROW]
[ROW][C]88[/C][C]0.703888[/C][C]0.592225[/C][C]0.296112[/C][/ROW]
[ROW][C]89[/C][C]0.774681[/C][C]0.450638[/C][C]0.225319[/C][/ROW]
[ROW][C]90[/C][C]0.812194[/C][C]0.375611[/C][C]0.187806[/C][/ROW]
[ROW][C]91[/C][C]0.788752[/C][C]0.422497[/C][C]0.211248[/C][/ROW]
[ROW][C]92[/C][C]0.762601[/C][C]0.474798[/C][C]0.237399[/C][/ROW]
[ROW][C]93[/C][C]0.740346[/C][C]0.519308[/C][C]0.259654[/C][/ROW]
[ROW][C]94[/C][C]0.71582[/C][C]0.568359[/C][C]0.28418[/C][/ROW]
[ROW][C]95[/C][C]0.690805[/C][C]0.61839[/C][C]0.309195[/C][/ROW]
[ROW][C]96[/C][C]0.661903[/C][C]0.676193[/C][C]0.338097[/C][/ROW]
[ROW][C]97[/C][C]0.633891[/C][C]0.732219[/C][C]0.366109[/C][/ROW]
[ROW][C]98[/C][C]0.640468[/C][C]0.719064[/C][C]0.359532[/C][/ROW]
[ROW][C]99[/C][C]0.60497[/C][C]0.79006[/C][C]0.39503[/C][/ROW]
[ROW][C]100[/C][C]0.601134[/C][C]0.797732[/C][C]0.398866[/C][/ROW]
[ROW][C]101[/C][C]0.572999[/C][C]0.854002[/C][C]0.427001[/C][/ROW]
[ROW][C]102[/C][C]0.549[/C][C]0.902[/C][C]0.451[/C][/ROW]
[ROW][C]103[/C][C]0.600772[/C][C]0.798456[/C][C]0.399228[/C][/ROW]
[ROW][C]104[/C][C]0.588751[/C][C]0.822498[/C][C]0.411249[/C][/ROW]
[ROW][C]105[/C][C]0.601868[/C][C]0.796264[/C][C]0.398132[/C][/ROW]
[ROW][C]106[/C][C]0.581442[/C][C]0.837116[/C][C]0.418558[/C][/ROW]
[ROW][C]107[/C][C]0.576556[/C][C]0.846887[/C][C]0.423444[/C][/ROW]
[ROW][C]108[/C][C]0.613737[/C][C]0.772527[/C][C]0.386263[/C][/ROW]
[ROW][C]109[/C][C]0.579065[/C][C]0.84187[/C][C]0.420935[/C][/ROW]
[ROW][C]110[/C][C]0.556544[/C][C]0.886912[/C][C]0.443456[/C][/ROW]
[ROW][C]111[/C][C]0.557791[/C][C]0.884417[/C][C]0.442209[/C][/ROW]
[ROW][C]112[/C][C]0.572578[/C][C]0.854843[/C][C]0.427422[/C][/ROW]
[ROW][C]113[/C][C]0.559493[/C][C]0.881014[/C][C]0.440507[/C][/ROW]
[ROW][C]114[/C][C]0.665602[/C][C]0.668796[/C][C]0.334398[/C][/ROW]
[ROW][C]115[/C][C]0.641418[/C][C]0.717164[/C][C]0.358582[/C][/ROW]
[ROW][C]116[/C][C]0.614752[/C][C]0.770497[/C][C]0.385248[/C][/ROW]
[ROW][C]117[/C][C]0.579566[/C][C]0.840868[/C][C]0.420434[/C][/ROW]
[ROW][C]118[/C][C]0.553332[/C][C]0.893336[/C][C]0.446668[/C][/ROW]
[ROW][C]119[/C][C]0.518239[/C][C]0.963522[/C][C]0.481761[/C][/ROW]
[ROW][C]120[/C][C]0.484535[/C][C]0.96907[/C][C]0.515465[/C][/ROW]
[ROW][C]121[/C][C]0.463968[/C][C]0.927936[/C][C]0.536032[/C][/ROW]
[ROW][C]122[/C][C]0.428729[/C][C]0.857457[/C][C]0.571271[/C][/ROW]
[ROW][C]123[/C][C]0.398862[/C][C]0.797724[/C][C]0.601138[/C][/ROW]
[ROW][C]124[/C][C]0.373086[/C][C]0.746171[/C][C]0.626914[/C][/ROW]
[ROW][C]125[/C][C]0.359499[/C][C]0.718997[/C][C]0.640501[/C][/ROW]
[ROW][C]126[/C][C]0.335572[/C][C]0.671143[/C][C]0.664428[/C][/ROW]
[ROW][C]127[/C][C]0.32313[/C][C]0.646259[/C][C]0.67687[/C][/ROW]
[ROW][C]128[/C][C]0.436215[/C][C]0.87243[/C][C]0.563785[/C][/ROW]
[ROW][C]129[/C][C]0.419355[/C][C]0.83871[/C][C]0.580645[/C][/ROW]
[ROW][C]130[/C][C]0.406195[/C][C]0.812389[/C][C]0.593805[/C][/ROW]
[ROW][C]131[/C][C]0.391651[/C][C]0.783301[/C][C]0.608349[/C][/ROW]
[ROW][C]132[/C][C]0.359217[/C][C]0.718435[/C][C]0.640783[/C][/ROW]
[ROW][C]133[/C][C]0.384053[/C][C]0.768107[/C][C]0.615947[/C][/ROW]
[ROW][C]134[/C][C]0.355009[/C][C]0.710017[/C][C]0.644991[/C][/ROW]
[ROW][C]135[/C][C]0.371911[/C][C]0.743823[/C][C]0.628089[/C][/ROW]
[ROW][C]136[/C][C]0.36473[/C][C]0.729461[/C][C]0.63527[/C][/ROW]
[ROW][C]137[/C][C]0.335314[/C][C]0.670627[/C][C]0.664686[/C][/ROW]
[ROW][C]138[/C][C]0.311257[/C][C]0.622513[/C][C]0.688743[/C][/ROW]
[ROW][C]139[/C][C]0.283731[/C][C]0.567462[/C][C]0.716269[/C][/ROW]
[ROW][C]140[/C][C]0.259111[/C][C]0.518222[/C][C]0.740889[/C][/ROW]
[ROW][C]141[/C][C]0.231929[/C][C]0.463858[/C][C]0.768071[/C][/ROW]
[ROW][C]142[/C][C]0.237221[/C][C]0.474442[/C][C]0.762779[/C][/ROW]
[ROW][C]143[/C][C]0.211058[/C][C]0.422116[/C][C]0.788942[/C][/ROW]
[ROW][C]144[/C][C]0.191891[/C][C]0.383781[/C][C]0.808109[/C][/ROW]
[ROW][C]145[/C][C]0.179054[/C][C]0.358108[/C][C]0.820946[/C][/ROW]
[ROW][C]146[/C][C]0.173694[/C][C]0.347388[/C][C]0.826306[/C][/ROW]
[ROW][C]147[/C][C]0.181116[/C][C]0.362232[/C][C]0.818884[/C][/ROW]
[ROW][C]148[/C][C]0.196335[/C][C]0.39267[/C][C]0.803665[/C][/ROW]
[ROW][C]149[/C][C]0.213155[/C][C]0.426309[/C][C]0.786845[/C][/ROW]
[ROW][C]150[/C][C]0.208482[/C][C]0.416965[/C][C]0.791518[/C][/ROW]
[ROW][C]151[/C][C]0.186676[/C][C]0.373352[/C][C]0.813324[/C][/ROW]
[ROW][C]152[/C][C]0.166611[/C][C]0.333221[/C][C]0.833389[/C][/ROW]
[ROW][C]153[/C][C]0.176695[/C][C]0.35339[/C][C]0.823305[/C][/ROW]
[ROW][C]154[/C][C]0.188719[/C][C]0.377439[/C][C]0.811281[/C][/ROW]
[ROW][C]155[/C][C]0.170327[/C][C]0.340655[/C][C]0.829673[/C][/ROW]
[ROW][C]156[/C][C]0.154177[/C][C]0.308353[/C][C]0.845823[/C][/ROW]
[ROW][C]157[/C][C]0.134182[/C][C]0.268364[/C][C]0.865818[/C][/ROW]
[ROW][C]158[/C][C]0.206519[/C][C]0.413039[/C][C]0.793481[/C][/ROW]
[ROW][C]159[/C][C]0.223515[/C][C]0.447029[/C][C]0.776485[/C][/ROW]
[ROW][C]160[/C][C]0.197907[/C][C]0.395814[/C][C]0.802093[/C][/ROW]
[ROW][C]161[/C][C]0.173417[/C][C]0.346833[/C][C]0.826583[/C][/ROW]
[ROW][C]162[/C][C]0.151012[/C][C]0.302025[/C][C]0.848988[/C][/ROW]
[ROW][C]163[/C][C]0.131229[/C][C]0.262457[/C][C]0.868771[/C][/ROW]
[ROW][C]164[/C][C]0.219495[/C][C]0.43899[/C][C]0.780505[/C][/ROW]
[ROW][C]165[/C][C]0.221691[/C][C]0.443383[/C][C]0.778309[/C][/ROW]
[ROW][C]166[/C][C]0.211957[/C][C]0.423915[/C][C]0.788043[/C][/ROW]
[ROW][C]167[/C][C]0.18696[/C][C]0.37392[/C][C]0.81304[/C][/ROW]
[ROW][C]168[/C][C]0.168928[/C][C]0.337856[/C][C]0.831072[/C][/ROW]
[ROW][C]169[/C][C]0.226245[/C][C]0.45249[/C][C]0.773755[/C][/ROW]
[ROW][C]170[/C][C]0.253355[/C][C]0.506709[/C][C]0.746645[/C][/ROW]
[ROW][C]171[/C][C]0.224983[/C][C]0.449966[/C][C]0.775017[/C][/ROW]
[ROW][C]172[/C][C]0.217675[/C][C]0.43535[/C][C]0.782325[/C][/ROW]
[ROW][C]173[/C][C]0.382935[/C][C]0.765871[/C][C]0.617065[/C][/ROW]
[ROW][C]174[/C][C]0.362556[/C][C]0.725111[/C][C]0.637444[/C][/ROW]
[ROW][C]175[/C][C]0.379408[/C][C]0.758816[/C][C]0.620592[/C][/ROW]
[ROW][C]176[/C][C]0.389001[/C][C]0.778003[/C][C]0.610999[/C][/ROW]
[ROW][C]177[/C][C]0.458214[/C][C]0.916428[/C][C]0.541786[/C][/ROW]
[ROW][C]178[/C][C]0.42119[/C][C]0.842379[/C][C]0.57881[/C][/ROW]
[ROW][C]179[/C][C]0.396334[/C][C]0.792667[/C][C]0.603666[/C][/ROW]
[ROW][C]180[/C][C]0.400587[/C][C]0.801173[/C][C]0.599413[/C][/ROW]
[ROW][C]181[/C][C]0.366083[/C][C]0.732167[/C][C]0.633917[/C][/ROW]
[ROW][C]182[/C][C]0.372496[/C][C]0.744993[/C][C]0.627504[/C][/ROW]
[ROW][C]183[/C][C]0.336761[/C][C]0.673523[/C][C]0.663239[/C][/ROW]
[ROW][C]184[/C][C]0.314461[/C][C]0.628923[/C][C]0.685539[/C][/ROW]
[ROW][C]185[/C][C]0.312997[/C][C]0.625993[/C][C]0.687003[/C][/ROW]
[ROW][C]186[/C][C]0.300783[/C][C]0.601567[/C][C]0.699217[/C][/ROW]
[ROW][C]187[/C][C]0.267946[/C][C]0.535892[/C][C]0.732054[/C][/ROW]
[ROW][C]188[/C][C]0.238951[/C][C]0.477902[/C][C]0.761049[/C][/ROW]
[ROW][C]189[/C][C]0.209777[/C][C]0.419553[/C][C]0.790223[/C][/ROW]
[ROW][C]190[/C][C]0.184883[/C][C]0.369766[/C][C]0.815117[/C][/ROW]
[ROW][C]191[/C][C]0.191557[/C][C]0.383114[/C][C]0.808443[/C][/ROW]
[ROW][C]192[/C][C]0.176219[/C][C]0.352439[/C][C]0.823781[/C][/ROW]
[ROW][C]193[/C][C]0.181865[/C][C]0.36373[/C][C]0.818135[/C][/ROW]
[ROW][C]194[/C][C]0.172425[/C][C]0.34485[/C][C]0.827575[/C][/ROW]
[ROW][C]195[/C][C]0.168476[/C][C]0.336953[/C][C]0.831524[/C][/ROW]
[ROW][C]196[/C][C]0.17979[/C][C]0.359581[/C][C]0.82021[/C][/ROW]
[ROW][C]197[/C][C]0.214467[/C][C]0.428935[/C][C]0.785533[/C][/ROW]
[ROW][C]198[/C][C]0.19706[/C][C]0.394119[/C][C]0.80294[/C][/ROW]
[ROW][C]199[/C][C]0.228779[/C][C]0.457558[/C][C]0.771221[/C][/ROW]
[ROW][C]200[/C][C]0.199039[/C][C]0.398079[/C][C]0.800961[/C][/ROW]
[ROW][C]201[/C][C]0.238127[/C][C]0.476255[/C][C]0.761873[/C][/ROW]
[ROW][C]202[/C][C]0.214977[/C][C]0.429953[/C][C]0.785023[/C][/ROW]
[ROW][C]203[/C][C]0.261847[/C][C]0.523694[/C][C]0.738153[/C][/ROW]
[ROW][C]204[/C][C]0.233322[/C][C]0.466643[/C][C]0.766678[/C][/ROW]
[ROW][C]205[/C][C]0.202239[/C][C]0.404479[/C][C]0.797761[/C][/ROW]
[ROW][C]206[/C][C]0.182819[/C][C]0.365639[/C][C]0.817181[/C][/ROW]
[ROW][C]207[/C][C]0.155323[/C][C]0.310646[/C][C]0.844677[/C][/ROW]
[ROW][C]208[/C][C]0.17441[/C][C]0.348821[/C][C]0.82559[/C][/ROW]
[ROW][C]209[/C][C]0.146854[/C][C]0.293708[/C][C]0.853146[/C][/ROW]
[ROW][C]210[/C][C]0.161127[/C][C]0.322253[/C][C]0.838873[/C][/ROW]
[ROW][C]211[/C][C]0.182049[/C][C]0.364098[/C][C]0.817951[/C][/ROW]
[ROW][C]212[/C][C]0.168366[/C][C]0.336732[/C][C]0.831634[/C][/ROW]
[ROW][C]213[/C][C]0.143854[/C][C]0.287707[/C][C]0.856146[/C][/ROW]
[ROW][C]214[/C][C]0.184681[/C][C]0.369362[/C][C]0.815319[/C][/ROW]
[ROW][C]215[/C][C]0.162417[/C][C]0.324835[/C][C]0.837583[/C][/ROW]
[ROW][C]216[/C][C]0.148862[/C][C]0.297723[/C][C]0.851138[/C][/ROW]
[ROW][C]217[/C][C]0.174725[/C][C]0.34945[/C][C]0.825275[/C][/ROW]
[ROW][C]218[/C][C]0.148733[/C][C]0.297465[/C][C]0.851267[/C][/ROW]
[ROW][C]219[/C][C]0.135546[/C][C]0.271092[/C][C]0.864454[/C][/ROW]
[ROW][C]220[/C][C]0.142811[/C][C]0.285622[/C][C]0.857189[/C][/ROW]
[ROW][C]221[/C][C]0.14402[/C][C]0.288039[/C][C]0.85598[/C][/ROW]
[ROW][C]222[/C][C]0.147857[/C][C]0.295714[/C][C]0.852143[/C][/ROW]
[ROW][C]223[/C][C]0.132137[/C][C]0.264274[/C][C]0.867863[/C][/ROW]
[ROW][C]224[/C][C]0.107194[/C][C]0.214387[/C][C]0.892806[/C][/ROW]
[ROW][C]225[/C][C]0.0951916[/C][C]0.190383[/C][C]0.904808[/C][/ROW]
[ROW][C]226[/C][C]0.117987[/C][C]0.235973[/C][C]0.882013[/C][/ROW]
[ROW][C]227[/C][C]0.309743[/C][C]0.619486[/C][C]0.690257[/C][/ROW]
[ROW][C]228[/C][C]0.272011[/C][C]0.544023[/C][C]0.727989[/C][/ROW]
[ROW][C]229[/C][C]0.236302[/C][C]0.472604[/C][C]0.763698[/C][/ROW]
[ROW][C]230[/C][C]0.213426[/C][C]0.426853[/C][C]0.786574[/C][/ROW]
[ROW][C]231[/C][C]0.180175[/C][C]0.36035[/C][C]0.819825[/C][/ROW]
[ROW][C]232[/C][C]0.202885[/C][C]0.405771[/C][C]0.797115[/C][/ROW]
[ROW][C]233[/C][C]0.165747[/C][C]0.331494[/C][C]0.834253[/C][/ROW]
[ROW][C]234[/C][C]0.134449[/C][C]0.268898[/C][C]0.865551[/C][/ROW]
[ROW][C]235[/C][C]0.139208[/C][C]0.278415[/C][C]0.860792[/C][/ROW]
[ROW][C]236[/C][C]0.114834[/C][C]0.229668[/C][C]0.885166[/C][/ROW]
[ROW][C]237[/C][C]0.0951807[/C][C]0.190361[/C][C]0.904819[/C][/ROW]
[ROW][C]238[/C][C]0.0697021[/C][C]0.139404[/C][C]0.930298[/C][/ROW]
[ROW][C]239[/C][C]0.144846[/C][C]0.289691[/C][C]0.855154[/C][/ROW]
[ROW][C]240[/C][C]0.160833[/C][C]0.321666[/C][C]0.839167[/C][/ROW]
[ROW][C]241[/C][C]0.160703[/C][C]0.321405[/C][C]0.839297[/C][/ROW]
[ROW][C]242[/C][C]0.763631[/C][C]0.472738[/C][C]0.236369[/C][/ROW]
[ROW][C]243[/C][C]0.689543[/C][C]0.620914[/C][C]0.310457[/C][/ROW]
[ROW][C]244[/C][C]0.637434[/C][C]0.725131[/C][C]0.362566[/C][/ROW]
[ROW][C]245[/C][C]0.588764[/C][C]0.822472[/C][C]0.411236[/C][/ROW]
[ROW][C]246[/C][C]0.503211[/C][C]0.993579[/C][C]0.496789[/C][/ROW]
[ROW][C]247[/C][C]0.475881[/C][C]0.951761[/C][C]0.524119[/C][/ROW]
[ROW][C]248[/C][C]0.458283[/C][C]0.916566[/C][C]0.541717[/C][/ROW]
[ROW][C]249[/C][C]0.338845[/C][C]0.67769[/C][C]0.661155[/C][/ROW]
[ROW][C]250[/C][C]0.359275[/C][C]0.71855[/C][C]0.640725[/C][/ROW]
[ROW][C]251[/C][C]0.244076[/C][C]0.488152[/C][C]0.755924[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&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
130.9920920.01581630.00790817
140.9819720.03605650.0180282
150.9775870.04482590.022413
160.9584250.08314940.0415747
170.9808760.03824740.0191237
180.9670680.0658640.032932
190.9471640.1056720.052836
200.9383650.123270.061635
210.9434820.1130350.0565176
220.9523320.09533580.0476679
230.954680.09064060.0453203
240.9355080.1289850.0644923
250.9203040.1593920.0796959
260.9993760.001248050.000624024
270.9990410.001918510.000959255
280.9984830.00303410.00151705
290.9976140.004772680.00238634
300.9974810.005037520.00251876
310.9964760.007047610.0035238
320.9945950.01080960.00540479
330.9946170.01076640.0053832
340.9925410.01491840.00745922
350.9896340.0207320.010366
360.9858280.02834460.0141723
370.9879680.02406370.0120318
380.9842270.03154640.0157732
390.9836090.03278120.0163906
400.9811280.03774390.018872
410.9744270.05114620.0255731
420.9756280.04874320.0243716
430.9691930.06161380.0308069
440.9609810.07803790.0390189
450.9500940.09981240.0499062
460.9511650.09766910.0488345
470.9423140.1153720.0576859
480.9286940.1426120.0713062
490.9506710.09865880.0493294
500.9435340.1129320.0564658
510.933240.133520.0667599
520.9182710.1634580.0817292
530.9020980.1958040.0979021
540.8846320.2307360.115368
550.8747970.2504050.125203
560.8640550.2718910.135945
570.8599330.2801340.140067
580.8340340.3319310.165966
590.8586430.2827140.141357
600.8426750.3146490.157325
610.8515830.2968340.148417
620.8362390.3275210.163761
630.8710010.2579990.128999
640.8648540.2702920.135146
650.8655020.2689960.134498
660.8835770.2328460.116423
670.8862640.2274730.113736
680.8766370.2467270.123363
690.9148920.1702150.0851077
700.9221170.1557670.0778835
710.9154320.1691350.0845676
720.9399910.1200170.0600085
730.9285450.1429090.0714545
740.913960.172080.0860399
750.9055690.1888620.0944311
760.8886070.2227850.111393
770.9123830.1752350.0876174
780.8984120.2031770.101588
790.8894690.2210620.110531
800.8830280.2339450.116972
810.8627570.2744850.137243
820.8419260.3161480.158074
830.8370880.3258250.162912
840.8163460.3673080.183654
850.7907570.4184870.209243
860.7649860.4700280.235014
870.7353190.5293630.264681
880.7038880.5922250.296112
890.7746810.4506380.225319
900.8121940.3756110.187806
910.7887520.4224970.211248
920.7626010.4747980.237399
930.7403460.5193080.259654
940.715820.5683590.28418
950.6908050.618390.309195
960.6619030.6761930.338097
970.6338910.7322190.366109
980.6404680.7190640.359532
990.604970.790060.39503
1000.6011340.7977320.398866
1010.5729990.8540020.427001
1020.5490.9020.451
1030.6007720.7984560.399228
1040.5887510.8224980.411249
1050.6018680.7962640.398132
1060.5814420.8371160.418558
1070.5765560.8468870.423444
1080.6137370.7725270.386263
1090.5790650.841870.420935
1100.5565440.8869120.443456
1110.5577910.8844170.442209
1120.5725780.8548430.427422
1130.5594930.8810140.440507
1140.6656020.6687960.334398
1150.6414180.7171640.358582
1160.6147520.7704970.385248
1170.5795660.8408680.420434
1180.5533320.8933360.446668
1190.5182390.9635220.481761
1200.4845350.969070.515465
1210.4639680.9279360.536032
1220.4287290.8574570.571271
1230.3988620.7977240.601138
1240.3730860.7461710.626914
1250.3594990.7189970.640501
1260.3355720.6711430.664428
1270.323130.6462590.67687
1280.4362150.872430.563785
1290.4193550.838710.580645
1300.4061950.8123890.593805
1310.3916510.7833010.608349
1320.3592170.7184350.640783
1330.3840530.7681070.615947
1340.3550090.7100170.644991
1350.3719110.7438230.628089
1360.364730.7294610.63527
1370.3353140.6706270.664686
1380.3112570.6225130.688743
1390.2837310.5674620.716269
1400.2591110.5182220.740889
1410.2319290.4638580.768071
1420.2372210.4744420.762779
1430.2110580.4221160.788942
1440.1918910.3837810.808109
1450.1790540.3581080.820946
1460.1736940.3473880.826306
1470.1811160.3622320.818884
1480.1963350.392670.803665
1490.2131550.4263090.786845
1500.2084820.4169650.791518
1510.1866760.3733520.813324
1520.1666110.3332210.833389
1530.1766950.353390.823305
1540.1887190.3774390.811281
1550.1703270.3406550.829673
1560.1541770.3083530.845823
1570.1341820.2683640.865818
1580.2065190.4130390.793481
1590.2235150.4470290.776485
1600.1979070.3958140.802093
1610.1734170.3468330.826583
1620.1510120.3020250.848988
1630.1312290.2624570.868771
1640.2194950.438990.780505
1650.2216910.4433830.778309
1660.2119570.4239150.788043
1670.186960.373920.81304
1680.1689280.3378560.831072
1690.2262450.452490.773755
1700.2533550.5067090.746645
1710.2249830.4499660.775017
1720.2176750.435350.782325
1730.3829350.7658710.617065
1740.3625560.7251110.637444
1750.3794080.7588160.620592
1760.3890010.7780030.610999
1770.4582140.9164280.541786
1780.421190.8423790.57881
1790.3963340.7926670.603666
1800.4005870.8011730.599413
1810.3660830.7321670.633917
1820.3724960.7449930.627504
1830.3367610.6735230.663239
1840.3144610.6289230.685539
1850.3129970.6259930.687003
1860.3007830.6015670.699217
1870.2679460.5358920.732054
1880.2389510.4779020.761049
1890.2097770.4195530.790223
1900.1848830.3697660.815117
1910.1915570.3831140.808443
1920.1762190.3524390.823781
1930.1818650.363730.818135
1940.1724250.344850.827575
1950.1684760.3369530.831524
1960.179790.3595810.82021
1970.2144670.4289350.785533
1980.197060.3941190.80294
1990.2287790.4575580.771221
2000.1990390.3980790.800961
2010.2381270.4762550.761873
2020.2149770.4299530.785023
2030.2618470.5236940.738153
2040.2333220.4666430.766678
2050.2022390.4044790.797761
2060.1828190.3656390.817181
2070.1553230.3106460.844677
2080.174410.3488210.82559
2090.1468540.2937080.853146
2100.1611270.3222530.838873
2110.1820490.3640980.817951
2120.1683660.3367320.831634
2130.1438540.2877070.856146
2140.1846810.3693620.815319
2150.1624170.3248350.837583
2160.1488620.2977230.851138
2170.1747250.349450.825275
2180.1487330.2974650.851267
2190.1355460.2710920.864454
2200.1428110.2856220.857189
2210.144020.2880390.85598
2220.1478570.2957140.852143
2230.1321370.2642740.867863
2240.1071940.2143870.892806
2250.09519160.1903830.904808
2260.1179870.2359730.882013
2270.3097430.6194860.690257
2280.2720110.5440230.727989
2290.2363020.4726040.763698
2300.2134260.4268530.786574
2310.1801750.360350.819825
2320.2028850.4057710.797115
2330.1657470.3314940.834253
2340.1344490.2688980.865551
2350.1392080.2784150.860792
2360.1148340.2296680.885166
2370.09518070.1903610.904819
2380.06970210.1394040.930298
2390.1448460.2896910.855154
2400.1608330.3216660.839167
2410.1607030.3214050.839297
2420.7636310.4727380.236369
2430.6895430.6209140.310457
2440.6374340.7251310.362566
2450.5887640.8224720.411236
2460.5032110.9935790.496789
2470.4758810.9517610.524119
2480.4582830.9165660.541717
2490.3388450.677690.661155
2500.3592750.718550.640725
2510.2440760.4881520.755924






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level60.0251046NOK
5% type I error level200.083682NOK
10% type I error level300.125523NOK

\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 & 6 & 0.0251046 & NOK \tabularnewline
5% type I error level & 20 & 0.083682 & NOK \tabularnewline
10% type I error level & 30 & 0.125523 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=226172&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]6[/C][C]0.0251046[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]20[/C][C]0.083682[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]30[/C][C]0.125523[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=226172&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=226172&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 level60.0251046NOK
5% type I error level200.083682NOK
10% type I error level300.125523NOK


Figures (Output of Computation)

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

Parameters (Session):
par1 = 5 ; par2 = Do not include Seasonal Dummies ; par3 = Linear Trend ;
Parameters (R input):
par1 = 5 ; par2 = Do not include Seasonal 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')
}