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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 computationWed, 17 Dec 2014 14:08:47 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/17/t1418825347fkd127j11ipo15z.htm/, Retrieved Thu, 16 May 2024 14:38:02 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=270293, Retrieved Thu, 16 May 2024 14:38:02 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Notched Boxplots] [Academic Motivati...] [2010-10-12 12:51:42] [b98453cac15ba1066b407e146608df68]
- RMPD  [Notched Boxplots] [boxplot] [2014-12-02 12:25:06] [15866c21ed6246d5efde5ff3ba421193]
-   PD    [Notched Boxplots] [boxplot 3] [2014-12-02 12:41:06] [15866c21ed6246d5efde5ff3ba421193]
-    D      [Notched Boxplots] [nb] [2014-12-02 13:10:20] [15866c21ed6246d5efde5ff3ba421193]
-    D        [Notched Boxplots] [MANNEN EN VROUWEN] [2014-12-02 14:07:28] [15866c21ed6246d5efde5ff3ba421193]
- RMPD          [Back to Back Histogram] [baba] [2014-12-03 14:18:03] [15866c21ed6246d5efde5ff3ba421193]
- RMPD            [Notched Boxplots] [boxplot 5] [2014-12-07 12:32:26] [15866c21ed6246d5efde5ff3ba421193]
- RMPD                [Multiple Regression] [regressie] [2014-12-17 14:08:47] [69667246dd207ce9acb00bd9a43352d5] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
21	19	18	23	23	23	7
19	19	13	16	16	16	5
27	24	6	25	26	18	8
13	7	10	15	25	28	8
17	17	12	25	23	26	5
18	23	10	22	24	21	4
20	23	13	19	26	20	4
22	21	15	22	20	21	11
18	18	8	24	24	26	5
6	4	4	10	14	15	22
22	27	4	24	28	16	4
15	18	9	23	25	21	4
19	20	10	22	21	25	4
17	15	12	22	19	22	5
22	19	21	26	22	19	4
10	14	6	24	22	24	16
21	14	11	23	21	24	5
21	18	17	26	17	23	4
23	17	10	27	21	22	6
18	20	16	28	23	27	5
20	16	12	21	16	22	4
27	16	12	23	15	24	4
13	11	11	25	24	26	4
20	21	14	23	25	26	7
20	10	11	22	23	28	4
22	18	19	23	19	20	8
20	18	16	22	24	23	7
24	21	21	27	14	24	4
23	16	16	24	20	23	6
19	15	11	24	23	26	5
22	17	12	20	12	20	8
24	15	8	19	22	20	8
21	12	9	23	18	12	4
19	20	14	21	21	21	7
20	20	13	27	23	28	4
16	18	7	19	22	24	13
17	21	17	25	28	24	4
25	22	8	25	20	24	4
16	21	9	24	22	22	4
23	25	15	26	24	26	4
20	12	11	21	19	23	7
23	22	20	22	9	10	5
22	24	13	26	23	27	4
15	17	7	20	23	24	5
16	20	8	21	22	26	12
20	20	20	21	20	18	8
23	19	15	28	23	22	4
24	24	19	24	24	24	4
17	18	17	19	17	16	8
19	15	18	23	19	23	5
25	25	19	25	17	21	4
14	27	5	27	23	28	4
18	17	11	18	19	19	7
22	18	13	26	24	18	5
15	17	8	14	15	27	13
27	24	19	25	22	17	4
22	18	14	23	25	20	4
26	27	24	24	27	24	4
16	18	11	20	23	24	6
25	23	12	19	16	20	4
20	18	9	25	24	24	4
19	21	10	19	22	25	4
19	25	22	23	27	25	4
24	18	18	23	28	26	4
14	19	8	17	23	25	5
18	20	15	24	25	26	6
13	11	10	22	21	14	4
19	22	10	20	22	19	4
25	24	20	23	25	23	4
20	23	17	22	25	25	6
17	16	12	20	19	23	9
17	24	17	23	24	19	5
13	16	10	22	21	23	6
20	16	15	21	18	24	13
20	18	14	22	17	21	4
24	17	8	26	17	21	7
25	21	17	24	26	24	5
19	15	10	28	8	23	4
20	15	16	24	25	22	4
20	19	13	26	22	21	4
22	21	17	20	20	23	6
18	19	16	26	22	25	6
21	19	13	21	17	17	8
20	18	14	26	24	27	6
11	14	6	22	20	28	5
18	17	16	21	19	24	9
22	25	18	25	26	27	6
21	14	16	25	13	22	4
15	19	15	23	20	23	9
23	20	18	27	26	24	4
18	20	20	23	21	24	4
23	20	19	28	24	26	4
19	19	16	24	23	21	5
23	18	11	21	16	23	4
26	22	24	23	24	18	4
19	18	13	21	18	25	4
26	22	17	24	21	24	5
20	19	14	28	17	27	5
20	20	16	11	19	20	8
23	22	18	25	22	25	4
24	22	16	25	23	23	4
26	24	16	28	27	25	9
23	18	9	28	22	24	4
19	21	5	19	22	23	4
25	22	11	25	25	19	4
23	19	10	25	26	25	4
19	18	16	25	22	28	4
27	24	17	28	25	26	4
23	21	15	26	23	24	4
24	21	13	27	8	25	4
20	20	12	24	24	28	4
16	17	12	18	14	23	4
22	20	16	21	17	15	4
26	22	22	23	21	18	4
26	24	19	24	21	24	4
24	24	23	26	25	27	5
20	20	6	25	18	25	8
20	19	19	23	20	24	7
12	20	7	24	25	26	4
21	16	9	20	20	19	4
27	21	16	26	24	23	4
26	22	19	27	22	21	5
17	19	8	21	16	22	5
20	19	15	21	20	23	6
18	13	10	19	21	23	12
28	22	18	25	22	20	5
24	20	19	23	15	20	9
24	21	12	25	21	25	12
24	21	16	26	25	28	4
12	15	12	18	16	19	16
26	23	20	27	28	21	4
23	22	19	23	22	21	5
13	15	10	20	19	25	4
23	20	16	22	17	18	4
16	23	12	22	23	22	6
23	21	15	23	28	21	4
18	18	15	18	19	21	4
25	23	17	25	24	25	5
18	16	13	21	16	20	6
18	18	14	21	19	22	5
21	18	18	28	19	27	6
7	10	4	19	12	23	4
19	17	11	21	16	25	4
21	20	10	23	15	28	7
17	13	7	22	17	25	9
22	25	20	27	23	24	5
15	18	10	23	21	27	5
20	20	18	27	20	19	4
19	18	14	23	19	24	4
10	19	11	21	20	22	12
18	11	12	22	20	23	4
25	17	16	26	23	21	6
23	22	19	23	22	21	9
25	21	18	26	20	20	4
23	19	16	28	24	26	5
21	20	9	28	21	28	4
23	21	15	26	23	23	4
19	22	14	24	22	19	4
22	20	17	23	21	23	4
23	21	14	28	26	18	4
15	15	11	21	16	21	11
23	22	11	28	28	28	4
23	21	19	21	24	22	6
24	28	25	28	28	28	4
20	20	20	24	14	20	5
23	20	15	24	16	23	4
24	23	17	28	22	25	4
17	18	12	21	18	16	6
21	15	10	26	23	23	4
19	19	24	22	18	18	7
23	21	16	25	22	22	9
22	19	9	20	13	21	5
14	16	16	19	20	19	14
19	17	8	23	24	20	4
21	26	11	26	24	27	4
23	20	13	28	25	27	4
16	13	14	24	23	20	5
23	19	12	25	24	26	4
19	21	14	24	22	25	4
19	21	16	25	24	23	9
22	24	19	27	24	24	4
26	23	17	28	24	27	4
22	20	20	23	25	28	10
24	23	11	19	27	26	4
24	24	19	27	27	27	4
11	8	6	15	14	23	6
21	19	16	27	21	28	4
21	18	14	21	17	22	9
22	20	14	26	23	23	5
22	21	16	25	25	27	4
19	16	11	26	20	18	5
18	17	14	24	21	22	14
19	21	16	25	24	23	9
27	27	22	27	27	25	4
14	12	7	14	12	14	4
15	17	17	24	26	21	17
20	17	16	25	22	26	4
22	18	18	23	24	28	5
26	24	22	24	24	22	9
20	18	13	22	20	24	7
13	18	11	16	22	28	4
26	24	19	26	23	24	5
19	18	14	26	22	26	7
20	19	15	19	21	18	10
18	19	15	19	13	19	5
20	24	15	28	21	26	4
21	15	15	24	20	26	8
26	22	19	20	18	12	4
25	17	22	21	19	24	4
20	20	18	26	25	26	6
21	22	10	24	24	23	5

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 8 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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 time8 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net






Multiple Linear Regression - Estimated Regression Equation
I1[t] = + 8.14567 + 0.341352I2[t] + 0.260599I3[t] + 0.327694E1[t] -0.0419358E2[t] -0.153376E3[t] -0.21717A[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
I1[t] =  +  8.14567 +  0.341352I2[t] +  0.260599I3[t] +  0.327694E1[t] -0.0419358E2[t] -0.153376E3[t] -0.21717A[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]I1[t] =  +  8.14567 +  0.341352I2[t] +  0.260599I3[t] +  0.327694E1[t] -0.0419358E2[t] -0.153376E3[t] -0.21717A[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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
I1[t] = + 8.14567 + 0.341352I2[t] + 0.260599I3[t] + 0.327694E1[t] -0.0419358E2[t] -0.153376E3[t] -0.21717A[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)8.145671.985134.1035.88526e-052.94263e-05
I20.3413520.06554215.2084.64681e-072.32341e-07
I30.2605990.05010925.2014.81562e-072.40781e-07
E10.3276940.07380254.441.47169e-057.35845e-06
E2-0.04193580.0572144-0.7330.4644250.232212
E3-0.1533760.0615269-2.4930.01346840.0067342
A-0.217170.0737945-2.9430.003628110.00181405

\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) & 8.14567 & 1.98513 & 4.103 & 5.88526e-05 & 2.94263e-05 \tabularnewline
I2 & 0.341352 & 0.0655421 & 5.208 & 4.64681e-07 & 2.32341e-07 \tabularnewline
I3 & 0.260599 & 0.0501092 & 5.201 & 4.81562e-07 & 2.40781e-07 \tabularnewline
E1 & 0.327694 & 0.0738025 & 4.44 & 1.47169e-05 & 7.35845e-06 \tabularnewline
E2 & -0.0419358 & 0.0572144 & -0.733 & 0.464425 & 0.232212 \tabularnewline
E3 & -0.153376 & 0.0615269 & -2.493 & 0.0134684 & 0.0067342 \tabularnewline
A & -0.21717 & 0.0737945 & -2.943 & 0.00362811 & 0.00181405 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&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]8.14567[/C][C]1.98513[/C][C]4.103[/C][C]5.88526e-05[/C][C]2.94263e-05[/C][/ROW]
[ROW][C]I2[/C][C]0.341352[/C][C]0.0655421[/C][C]5.208[/C][C]4.64681e-07[/C][C]2.32341e-07[/C][/ROW]
[ROW][C]I3[/C][C]0.260599[/C][C]0.0501092[/C][C]5.201[/C][C]4.81562e-07[/C][C]2.40781e-07[/C][/ROW]
[ROW][C]E1[/C][C]0.327694[/C][C]0.0738025[/C][C]4.44[/C][C]1.47169e-05[/C][C]7.35845e-06[/C][/ROW]
[ROW][C]E2[/C][C]-0.0419358[/C][C]0.0572144[/C][C]-0.733[/C][C]0.464425[/C][C]0.232212[/C][/ROW]
[ROW][C]E3[/C][C]-0.153376[/C][C]0.0615269[/C][C]-2.493[/C][C]0.0134684[/C][C]0.0067342[/C][/ROW]
[ROW][C]A[/C][C]-0.21717[/C][C]0.0737945[/C][C]-2.943[/C][C]0.00362811[/C][C]0.00181405[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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)8.145671.985134.1035.88526e-052.94263e-05
I20.3413520.06554215.2084.64681e-072.32341e-07
I30.2605990.05010925.2014.81562e-072.40781e-07
E10.3276940.07380254.441.47169e-057.35845e-06
E2-0.04193580.0572144-0.7330.4644250.232212
E3-0.1533760.0615269-2.4930.01346840.0067342
A-0.217170.0737945-2.9430.003628110.00181405






Multiple Linear Regression - Regression Statistics
Multiple R0.72716
R-squared0.528762
Adjusted R-squared0.514902
F-TEST (value)38.1504
F-TEST (DF numerator)6
F-TEST (DF denominator)204
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76812
Sum Squared Residuals1563.15

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.72716 \tabularnewline
R-squared & 0.528762 \tabularnewline
Adjusted R-squared & 0.514902 \tabularnewline
F-TEST (value) & 38.1504 \tabularnewline
F-TEST (DF numerator) & 6 \tabularnewline
F-TEST (DF denominator) & 204 \tabularnewline
p-value & 0 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.76812 \tabularnewline
Sum Squared Residuals & 1563.15 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.72716[/C][/ROW]
[ROW][C]R-squared[/C][C]0.528762[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.514902[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]38.1504[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]6[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]204[/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]2.76812[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1563.15[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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 R0.72716
R-squared0.528762
Adjusted R-squared0.514902
F-TEST (value)38.1504
F-TEST (DF numerator)6
F-TEST (DF denominator)204
p-value0
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.76812
Sum Squared Residuals1563.15






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
12120.84670.153251
21919.0514-0.0514159
32720.50566.49439
41310.97632.02375
51719.23-2.23005
61820.716-2.71599
72020.5842-0.584213
82219.98382.01616
91818.1594-0.159372
1066.16494-0.164937
112221.77230.227666
121519.0344-4.03439
131919.2042-0.20424
141718.3455-1.34551
152223.9186-1.91858
161014.2745-4.27452
172117.68063.31937
182122.131-1.13101
192319.84443.15555
201822.1262-4.12621
212018.70211.29786
222719.09277.90728
231317.0966-4.09657
242019.94310.0569453
252015.50734.49268
262221.17670.823301
272019.61460.385432
282424.4976-0.497584
292319.97223.02783
301917.95911.04095
312218.32163.67838
322415.84958.15054
332118.66022.33978
341919.8809-0.880939
352021.0805-1.08051
361614.91361.08643
371722.2127-5.2127
382520.54414.45586
391620.3586-4.35857
402323.2456-0.245591
412016.14543.85456
422325.0796-2.07964
432222.2716-0.271599
441516.5953-1.59533
451616.4227-0.422676
462021.7294-1.72943
472322.50830.491691
482423.5980.402
491720.0421-3.0421
501920.0834-1.08342
512525.0207-0.0207262
521421.3852-7.38518
531817.48260.517374
542221.34480.65523
551513.02781.97224
562725.08321.9168
572220.49081.50923
582625.79920.200755
591617.7619-1.76191
602520.7434.25703
612019.27160.728411
621918.52060.479428
631924.1143-5.11427
642420.48713.5129
651416.4022-2.40218
661820.4072-2.40717
671317.8192-4.81921
681920.1099-1.10988
692523.64231.35765
702021.4504-1.45041
711717.0094-0.00941709
721723.2988-6.29882
731317.7112-4.71125
742017.13882.86121
752020.3452-0.345182
762419.09954.9005
772521.75173.2483
781920.3156-1.31556
792020.0089-0.00885077
802021.527-1.52703
812220.62871.37125
821821.261-3.26099
832119.84311.15693
842020.0078-0.00781124
851115.4784-4.47837
861818.5675-0.567485
872223.0281-1.02811
882120.49840.501577
891519.7564-4.75642
902322.87120.128796
911822.2913-4.2913
922323.2366-0.236617
931921.3943-2.39434
942318.97094.02913
952624.81091.18914
961919.1014-0.101447
972622.30273.69727
982021.5153-1.51527
992017.14532.85473
1002322.91290.0871139
1012422.65651.3435
1022622.76193.23805
1032320.33852.66146
1041917.52431.47567
1052521.88313.11686
1062319.63633.36371
1071920.5662-1.56615
1082724.03892.96111
1092322.22890.771129
1102422.5111.48897
1112019.79490.205109
1121617.9909-1.99091
1132222.1416-0.141649
1142624.41551.58453
1152623.72382.27619
1162424.5766-0.576551
1172018.40211.59795
1182021.0798-1.07978
1191218.7567-6.75671
1202117.8853.11496
1212722.60094.39909
1222624.22521.77479
1231718.4666-1.46663
1242019.75250.247461
1251814.40113.59891
1262823.46264.5374
1272421.812.19002
1282419.31254.68748
1292421.79212.20791
1301215.2318-3.2318
1312624.79271.20728
1322322.91440.0855676
1331316.926-3.92596
1342322.00920.990786
1351620.6914-4.69141
1362321.49621.50376
1371819.2111-1.21113
1382522.69262.3074
1391818.8352-0.835157
1401819.5631-1.56307
1412121.9153-0.915277
142713.9282-6.92822
1431918.32280.677232
1442118.67192.32809
1451715.11491.88513
1462225.0078-3.0078
1471518.3253-3.32531
1482023.8897-3.8897
1491920.1289-1.12888
1501017.5605-7.5605
1511817.0020.998041
1522521.14993.85015
1532322.04580.954247
1542523.751.25002
1552321.89631.1037
1562120.44970.550322
1572322.38220.617752
1581922.4631-3.46305
1592221.66290.337118
1602323.4181-0.418112
1611516.7334-1.73338
1622321.361.63997
1632321.46331.53673
1642427.0565-3.05653
1652023.3089-3.30889
1662321.67911.32094
1672423.97670.0232778
1681719.7869-2.7869
1692119.03111.96886
1701923.0592-4.05921
1712321.42461.57538
1722218.67873.32128
1731417.2098-3.20984
1741918.62780.372246
1752122.3912-1.39117
1762321.47771.52229
1771618.9784-2.9784
1782320.0882.91201
1791921.2014-2.20144
1801921.1874-2.18737
1812224.5811-2.58108
1822623.58612.4139
1832220.2071.79296
1842419.10084.89918
1852423.99510.00485344
1861111.9377-0.937721
1872121.6048-0.604827
1882118.77832.22174
1892221.56310.436873
1902221.61780.382225
1911920.3086-1.30861
1921818.1664-0.166402
1931921.1874-2.18737
1942726.10780.892247
1951415.1346-1.13463
1961518.2404-3.24039
1972020.5316-0.531551
1982220.13091.86908
1992623.60072.3993
2002018.84711.15286
2011316.3139-3.3139
2022624.07821.92185
2031920.0279-1.02789
2042018.95341.04658
2051820.2214-2.22138
2062023.6854-3.68543
2072118.47572.52425
2082623.69662.30335
2092521.21693.78307
2102021.8444-1.84435
2112120.50610.493892

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 21 & 20.8467 & 0.153251 \tabularnewline
2 & 19 & 19.0514 & -0.0514159 \tabularnewline
3 & 27 & 20.5056 & 6.49439 \tabularnewline
4 & 13 & 10.9763 & 2.02375 \tabularnewline
5 & 17 & 19.23 & -2.23005 \tabularnewline
6 & 18 & 20.716 & -2.71599 \tabularnewline
7 & 20 & 20.5842 & -0.584213 \tabularnewline
8 & 22 & 19.9838 & 2.01616 \tabularnewline
9 & 18 & 18.1594 & -0.159372 \tabularnewline
10 & 6 & 6.16494 & -0.164937 \tabularnewline
11 & 22 & 21.7723 & 0.227666 \tabularnewline
12 & 15 & 19.0344 & -4.03439 \tabularnewline
13 & 19 & 19.2042 & -0.20424 \tabularnewline
14 & 17 & 18.3455 & -1.34551 \tabularnewline
15 & 22 & 23.9186 & -1.91858 \tabularnewline
16 & 10 & 14.2745 & -4.27452 \tabularnewline
17 & 21 & 17.6806 & 3.31937 \tabularnewline
18 & 21 & 22.131 & -1.13101 \tabularnewline
19 & 23 & 19.8444 & 3.15555 \tabularnewline
20 & 18 & 22.1262 & -4.12621 \tabularnewline
21 & 20 & 18.7021 & 1.29786 \tabularnewline
22 & 27 & 19.0927 & 7.90728 \tabularnewline
23 & 13 & 17.0966 & -4.09657 \tabularnewline
24 & 20 & 19.9431 & 0.0569453 \tabularnewline
25 & 20 & 15.5073 & 4.49268 \tabularnewline
26 & 22 & 21.1767 & 0.823301 \tabularnewline
27 & 20 & 19.6146 & 0.385432 \tabularnewline
28 & 24 & 24.4976 & -0.497584 \tabularnewline
29 & 23 & 19.9722 & 3.02783 \tabularnewline
30 & 19 & 17.9591 & 1.04095 \tabularnewline
31 & 22 & 18.3216 & 3.67838 \tabularnewline
32 & 24 & 15.8495 & 8.15054 \tabularnewline
33 & 21 & 18.6602 & 2.33978 \tabularnewline
34 & 19 & 19.8809 & -0.880939 \tabularnewline
35 & 20 & 21.0805 & -1.08051 \tabularnewline
36 & 16 & 14.9136 & 1.08643 \tabularnewline
37 & 17 & 22.2127 & -5.2127 \tabularnewline
38 & 25 & 20.5441 & 4.45586 \tabularnewline
39 & 16 & 20.3586 & -4.35857 \tabularnewline
40 & 23 & 23.2456 & -0.245591 \tabularnewline
41 & 20 & 16.1454 & 3.85456 \tabularnewline
42 & 23 & 25.0796 & -2.07964 \tabularnewline
43 & 22 & 22.2716 & -0.271599 \tabularnewline
44 & 15 & 16.5953 & -1.59533 \tabularnewline
45 & 16 & 16.4227 & -0.422676 \tabularnewline
46 & 20 & 21.7294 & -1.72943 \tabularnewline
47 & 23 & 22.5083 & 0.491691 \tabularnewline
48 & 24 & 23.598 & 0.402 \tabularnewline
49 & 17 & 20.0421 & -3.0421 \tabularnewline
50 & 19 & 20.0834 & -1.08342 \tabularnewline
51 & 25 & 25.0207 & -0.0207262 \tabularnewline
52 & 14 & 21.3852 & -7.38518 \tabularnewline
53 & 18 & 17.4826 & 0.517374 \tabularnewline
54 & 22 & 21.3448 & 0.65523 \tabularnewline
55 & 15 & 13.0278 & 1.97224 \tabularnewline
56 & 27 & 25.0832 & 1.9168 \tabularnewline
57 & 22 & 20.4908 & 1.50923 \tabularnewline
58 & 26 & 25.7992 & 0.200755 \tabularnewline
59 & 16 & 17.7619 & -1.76191 \tabularnewline
60 & 25 & 20.743 & 4.25703 \tabularnewline
61 & 20 & 19.2716 & 0.728411 \tabularnewline
62 & 19 & 18.5206 & 0.479428 \tabularnewline
63 & 19 & 24.1143 & -5.11427 \tabularnewline
64 & 24 & 20.4871 & 3.5129 \tabularnewline
65 & 14 & 16.4022 & -2.40218 \tabularnewline
66 & 18 & 20.4072 & -2.40717 \tabularnewline
67 & 13 & 17.8192 & -4.81921 \tabularnewline
68 & 19 & 20.1099 & -1.10988 \tabularnewline
69 & 25 & 23.6423 & 1.35765 \tabularnewline
70 & 20 & 21.4504 & -1.45041 \tabularnewline
71 & 17 & 17.0094 & -0.00941709 \tabularnewline
72 & 17 & 23.2988 & -6.29882 \tabularnewline
73 & 13 & 17.7112 & -4.71125 \tabularnewline
74 & 20 & 17.1388 & 2.86121 \tabularnewline
75 & 20 & 20.3452 & -0.345182 \tabularnewline
76 & 24 & 19.0995 & 4.9005 \tabularnewline
77 & 25 & 21.7517 & 3.2483 \tabularnewline
78 & 19 & 20.3156 & -1.31556 \tabularnewline
79 & 20 & 20.0089 & -0.00885077 \tabularnewline
80 & 20 & 21.527 & -1.52703 \tabularnewline
81 & 22 & 20.6287 & 1.37125 \tabularnewline
82 & 18 & 21.261 & -3.26099 \tabularnewline
83 & 21 & 19.8431 & 1.15693 \tabularnewline
84 & 20 & 20.0078 & -0.00781124 \tabularnewline
85 & 11 & 15.4784 & -4.47837 \tabularnewline
86 & 18 & 18.5675 & -0.567485 \tabularnewline
87 & 22 & 23.0281 & -1.02811 \tabularnewline
88 & 21 & 20.4984 & 0.501577 \tabularnewline
89 & 15 & 19.7564 & -4.75642 \tabularnewline
90 & 23 & 22.8712 & 0.128796 \tabularnewline
91 & 18 & 22.2913 & -4.2913 \tabularnewline
92 & 23 & 23.2366 & -0.236617 \tabularnewline
93 & 19 & 21.3943 & -2.39434 \tabularnewline
94 & 23 & 18.9709 & 4.02913 \tabularnewline
95 & 26 & 24.8109 & 1.18914 \tabularnewline
96 & 19 & 19.1014 & -0.101447 \tabularnewline
97 & 26 & 22.3027 & 3.69727 \tabularnewline
98 & 20 & 21.5153 & -1.51527 \tabularnewline
99 & 20 & 17.1453 & 2.85473 \tabularnewline
100 & 23 & 22.9129 & 0.0871139 \tabularnewline
101 & 24 & 22.6565 & 1.3435 \tabularnewline
102 & 26 & 22.7619 & 3.23805 \tabularnewline
103 & 23 & 20.3385 & 2.66146 \tabularnewline
104 & 19 & 17.5243 & 1.47567 \tabularnewline
105 & 25 & 21.8831 & 3.11686 \tabularnewline
106 & 23 & 19.6363 & 3.36371 \tabularnewline
107 & 19 & 20.5662 & -1.56615 \tabularnewline
108 & 27 & 24.0389 & 2.96111 \tabularnewline
109 & 23 & 22.2289 & 0.771129 \tabularnewline
110 & 24 & 22.511 & 1.48897 \tabularnewline
111 & 20 & 19.7949 & 0.205109 \tabularnewline
112 & 16 & 17.9909 & -1.99091 \tabularnewline
113 & 22 & 22.1416 & -0.141649 \tabularnewline
114 & 26 & 24.4155 & 1.58453 \tabularnewline
115 & 26 & 23.7238 & 2.27619 \tabularnewline
116 & 24 & 24.5766 & -0.576551 \tabularnewline
117 & 20 & 18.4021 & 1.59795 \tabularnewline
118 & 20 & 21.0798 & -1.07978 \tabularnewline
119 & 12 & 18.7567 & -6.75671 \tabularnewline
120 & 21 & 17.885 & 3.11496 \tabularnewline
121 & 27 & 22.6009 & 4.39909 \tabularnewline
122 & 26 & 24.2252 & 1.77479 \tabularnewline
123 & 17 & 18.4666 & -1.46663 \tabularnewline
124 & 20 & 19.7525 & 0.247461 \tabularnewline
125 & 18 & 14.4011 & 3.59891 \tabularnewline
126 & 28 & 23.4626 & 4.5374 \tabularnewline
127 & 24 & 21.81 & 2.19002 \tabularnewline
128 & 24 & 19.3125 & 4.68748 \tabularnewline
129 & 24 & 21.7921 & 2.20791 \tabularnewline
130 & 12 & 15.2318 & -3.2318 \tabularnewline
131 & 26 & 24.7927 & 1.20728 \tabularnewline
132 & 23 & 22.9144 & 0.0855676 \tabularnewline
133 & 13 & 16.926 & -3.92596 \tabularnewline
134 & 23 & 22.0092 & 0.990786 \tabularnewline
135 & 16 & 20.6914 & -4.69141 \tabularnewline
136 & 23 & 21.4962 & 1.50376 \tabularnewline
137 & 18 & 19.2111 & -1.21113 \tabularnewline
138 & 25 & 22.6926 & 2.3074 \tabularnewline
139 & 18 & 18.8352 & -0.835157 \tabularnewline
140 & 18 & 19.5631 & -1.56307 \tabularnewline
141 & 21 & 21.9153 & -0.915277 \tabularnewline
142 & 7 & 13.9282 & -6.92822 \tabularnewline
143 & 19 & 18.3228 & 0.677232 \tabularnewline
144 & 21 & 18.6719 & 2.32809 \tabularnewline
145 & 17 & 15.1149 & 1.88513 \tabularnewline
146 & 22 & 25.0078 & -3.0078 \tabularnewline
147 & 15 & 18.3253 & -3.32531 \tabularnewline
148 & 20 & 23.8897 & -3.8897 \tabularnewline
149 & 19 & 20.1289 & -1.12888 \tabularnewline
150 & 10 & 17.5605 & -7.5605 \tabularnewline
151 & 18 & 17.002 & 0.998041 \tabularnewline
152 & 25 & 21.1499 & 3.85015 \tabularnewline
153 & 23 & 22.0458 & 0.954247 \tabularnewline
154 & 25 & 23.75 & 1.25002 \tabularnewline
155 & 23 & 21.8963 & 1.1037 \tabularnewline
156 & 21 & 20.4497 & 0.550322 \tabularnewline
157 & 23 & 22.3822 & 0.617752 \tabularnewline
158 & 19 & 22.4631 & -3.46305 \tabularnewline
159 & 22 & 21.6629 & 0.337118 \tabularnewline
160 & 23 & 23.4181 & -0.418112 \tabularnewline
161 & 15 & 16.7334 & -1.73338 \tabularnewline
162 & 23 & 21.36 & 1.63997 \tabularnewline
163 & 23 & 21.4633 & 1.53673 \tabularnewline
164 & 24 & 27.0565 & -3.05653 \tabularnewline
165 & 20 & 23.3089 & -3.30889 \tabularnewline
166 & 23 & 21.6791 & 1.32094 \tabularnewline
167 & 24 & 23.9767 & 0.0232778 \tabularnewline
168 & 17 & 19.7869 & -2.7869 \tabularnewline
169 & 21 & 19.0311 & 1.96886 \tabularnewline
170 & 19 & 23.0592 & -4.05921 \tabularnewline
171 & 23 & 21.4246 & 1.57538 \tabularnewline
172 & 22 & 18.6787 & 3.32128 \tabularnewline
173 & 14 & 17.2098 & -3.20984 \tabularnewline
174 & 19 & 18.6278 & 0.372246 \tabularnewline
175 & 21 & 22.3912 & -1.39117 \tabularnewline
176 & 23 & 21.4777 & 1.52229 \tabularnewline
177 & 16 & 18.9784 & -2.9784 \tabularnewline
178 & 23 & 20.088 & 2.91201 \tabularnewline
179 & 19 & 21.2014 & -2.20144 \tabularnewline
180 & 19 & 21.1874 & -2.18737 \tabularnewline
181 & 22 & 24.5811 & -2.58108 \tabularnewline
182 & 26 & 23.5861 & 2.4139 \tabularnewline
183 & 22 & 20.207 & 1.79296 \tabularnewline
184 & 24 & 19.1008 & 4.89918 \tabularnewline
185 & 24 & 23.9951 & 0.00485344 \tabularnewline
186 & 11 & 11.9377 & -0.937721 \tabularnewline
187 & 21 & 21.6048 & -0.604827 \tabularnewline
188 & 21 & 18.7783 & 2.22174 \tabularnewline
189 & 22 & 21.5631 & 0.436873 \tabularnewline
190 & 22 & 21.6178 & 0.382225 \tabularnewline
191 & 19 & 20.3086 & -1.30861 \tabularnewline
192 & 18 & 18.1664 & -0.166402 \tabularnewline
193 & 19 & 21.1874 & -2.18737 \tabularnewline
194 & 27 & 26.1078 & 0.892247 \tabularnewline
195 & 14 & 15.1346 & -1.13463 \tabularnewline
196 & 15 & 18.2404 & -3.24039 \tabularnewline
197 & 20 & 20.5316 & -0.531551 \tabularnewline
198 & 22 & 20.1309 & 1.86908 \tabularnewline
199 & 26 & 23.6007 & 2.3993 \tabularnewline
200 & 20 & 18.8471 & 1.15286 \tabularnewline
201 & 13 & 16.3139 & -3.3139 \tabularnewline
202 & 26 & 24.0782 & 1.92185 \tabularnewline
203 & 19 & 20.0279 & -1.02789 \tabularnewline
204 & 20 & 18.9534 & 1.04658 \tabularnewline
205 & 18 & 20.2214 & -2.22138 \tabularnewline
206 & 20 & 23.6854 & -3.68543 \tabularnewline
207 & 21 & 18.4757 & 2.52425 \tabularnewline
208 & 26 & 23.6966 & 2.30335 \tabularnewline
209 & 25 & 21.2169 & 3.78307 \tabularnewline
210 & 20 & 21.8444 & -1.84435 \tabularnewline
211 & 21 & 20.5061 & 0.493892 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&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]21[/C][C]20.8467[/C][C]0.153251[/C][/ROW]
[ROW][C]2[/C][C]19[/C][C]19.0514[/C][C]-0.0514159[/C][/ROW]
[ROW][C]3[/C][C]27[/C][C]20.5056[/C][C]6.49439[/C][/ROW]
[ROW][C]4[/C][C]13[/C][C]10.9763[/C][C]2.02375[/C][/ROW]
[ROW][C]5[/C][C]17[/C][C]19.23[/C][C]-2.23005[/C][/ROW]
[ROW][C]6[/C][C]18[/C][C]20.716[/C][C]-2.71599[/C][/ROW]
[ROW][C]7[/C][C]20[/C][C]20.5842[/C][C]-0.584213[/C][/ROW]
[ROW][C]8[/C][C]22[/C][C]19.9838[/C][C]2.01616[/C][/ROW]
[ROW][C]9[/C][C]18[/C][C]18.1594[/C][C]-0.159372[/C][/ROW]
[ROW][C]10[/C][C]6[/C][C]6.16494[/C][C]-0.164937[/C][/ROW]
[ROW][C]11[/C][C]22[/C][C]21.7723[/C][C]0.227666[/C][/ROW]
[ROW][C]12[/C][C]15[/C][C]19.0344[/C][C]-4.03439[/C][/ROW]
[ROW][C]13[/C][C]19[/C][C]19.2042[/C][C]-0.20424[/C][/ROW]
[ROW][C]14[/C][C]17[/C][C]18.3455[/C][C]-1.34551[/C][/ROW]
[ROW][C]15[/C][C]22[/C][C]23.9186[/C][C]-1.91858[/C][/ROW]
[ROW][C]16[/C][C]10[/C][C]14.2745[/C][C]-4.27452[/C][/ROW]
[ROW][C]17[/C][C]21[/C][C]17.6806[/C][C]3.31937[/C][/ROW]
[ROW][C]18[/C][C]21[/C][C]22.131[/C][C]-1.13101[/C][/ROW]
[ROW][C]19[/C][C]23[/C][C]19.8444[/C][C]3.15555[/C][/ROW]
[ROW][C]20[/C][C]18[/C][C]22.1262[/C][C]-4.12621[/C][/ROW]
[ROW][C]21[/C][C]20[/C][C]18.7021[/C][C]1.29786[/C][/ROW]
[ROW][C]22[/C][C]27[/C][C]19.0927[/C][C]7.90728[/C][/ROW]
[ROW][C]23[/C][C]13[/C][C]17.0966[/C][C]-4.09657[/C][/ROW]
[ROW][C]24[/C][C]20[/C][C]19.9431[/C][C]0.0569453[/C][/ROW]
[ROW][C]25[/C][C]20[/C][C]15.5073[/C][C]4.49268[/C][/ROW]
[ROW][C]26[/C][C]22[/C][C]21.1767[/C][C]0.823301[/C][/ROW]
[ROW][C]27[/C][C]20[/C][C]19.6146[/C][C]0.385432[/C][/ROW]
[ROW][C]28[/C][C]24[/C][C]24.4976[/C][C]-0.497584[/C][/ROW]
[ROW][C]29[/C][C]23[/C][C]19.9722[/C][C]3.02783[/C][/ROW]
[ROW][C]30[/C][C]19[/C][C]17.9591[/C][C]1.04095[/C][/ROW]
[ROW][C]31[/C][C]22[/C][C]18.3216[/C][C]3.67838[/C][/ROW]
[ROW][C]32[/C][C]24[/C][C]15.8495[/C][C]8.15054[/C][/ROW]
[ROW][C]33[/C][C]21[/C][C]18.6602[/C][C]2.33978[/C][/ROW]
[ROW][C]34[/C][C]19[/C][C]19.8809[/C][C]-0.880939[/C][/ROW]
[ROW][C]35[/C][C]20[/C][C]21.0805[/C][C]-1.08051[/C][/ROW]
[ROW][C]36[/C][C]16[/C][C]14.9136[/C][C]1.08643[/C][/ROW]
[ROW][C]37[/C][C]17[/C][C]22.2127[/C][C]-5.2127[/C][/ROW]
[ROW][C]38[/C][C]25[/C][C]20.5441[/C][C]4.45586[/C][/ROW]
[ROW][C]39[/C][C]16[/C][C]20.3586[/C][C]-4.35857[/C][/ROW]
[ROW][C]40[/C][C]23[/C][C]23.2456[/C][C]-0.245591[/C][/ROW]
[ROW][C]41[/C][C]20[/C][C]16.1454[/C][C]3.85456[/C][/ROW]
[ROW][C]42[/C][C]23[/C][C]25.0796[/C][C]-2.07964[/C][/ROW]
[ROW][C]43[/C][C]22[/C][C]22.2716[/C][C]-0.271599[/C][/ROW]
[ROW][C]44[/C][C]15[/C][C]16.5953[/C][C]-1.59533[/C][/ROW]
[ROW][C]45[/C][C]16[/C][C]16.4227[/C][C]-0.422676[/C][/ROW]
[ROW][C]46[/C][C]20[/C][C]21.7294[/C][C]-1.72943[/C][/ROW]
[ROW][C]47[/C][C]23[/C][C]22.5083[/C][C]0.491691[/C][/ROW]
[ROW][C]48[/C][C]24[/C][C]23.598[/C][C]0.402[/C][/ROW]
[ROW][C]49[/C][C]17[/C][C]20.0421[/C][C]-3.0421[/C][/ROW]
[ROW][C]50[/C][C]19[/C][C]20.0834[/C][C]-1.08342[/C][/ROW]
[ROW][C]51[/C][C]25[/C][C]25.0207[/C][C]-0.0207262[/C][/ROW]
[ROW][C]52[/C][C]14[/C][C]21.3852[/C][C]-7.38518[/C][/ROW]
[ROW][C]53[/C][C]18[/C][C]17.4826[/C][C]0.517374[/C][/ROW]
[ROW][C]54[/C][C]22[/C][C]21.3448[/C][C]0.65523[/C][/ROW]
[ROW][C]55[/C][C]15[/C][C]13.0278[/C][C]1.97224[/C][/ROW]
[ROW][C]56[/C][C]27[/C][C]25.0832[/C][C]1.9168[/C][/ROW]
[ROW][C]57[/C][C]22[/C][C]20.4908[/C][C]1.50923[/C][/ROW]
[ROW][C]58[/C][C]26[/C][C]25.7992[/C][C]0.200755[/C][/ROW]
[ROW][C]59[/C][C]16[/C][C]17.7619[/C][C]-1.76191[/C][/ROW]
[ROW][C]60[/C][C]25[/C][C]20.743[/C][C]4.25703[/C][/ROW]
[ROW][C]61[/C][C]20[/C][C]19.2716[/C][C]0.728411[/C][/ROW]
[ROW][C]62[/C][C]19[/C][C]18.5206[/C][C]0.479428[/C][/ROW]
[ROW][C]63[/C][C]19[/C][C]24.1143[/C][C]-5.11427[/C][/ROW]
[ROW][C]64[/C][C]24[/C][C]20.4871[/C][C]3.5129[/C][/ROW]
[ROW][C]65[/C][C]14[/C][C]16.4022[/C][C]-2.40218[/C][/ROW]
[ROW][C]66[/C][C]18[/C][C]20.4072[/C][C]-2.40717[/C][/ROW]
[ROW][C]67[/C][C]13[/C][C]17.8192[/C][C]-4.81921[/C][/ROW]
[ROW][C]68[/C][C]19[/C][C]20.1099[/C][C]-1.10988[/C][/ROW]
[ROW][C]69[/C][C]25[/C][C]23.6423[/C][C]1.35765[/C][/ROW]
[ROW][C]70[/C][C]20[/C][C]21.4504[/C][C]-1.45041[/C][/ROW]
[ROW][C]71[/C][C]17[/C][C]17.0094[/C][C]-0.00941709[/C][/ROW]
[ROW][C]72[/C][C]17[/C][C]23.2988[/C][C]-6.29882[/C][/ROW]
[ROW][C]73[/C][C]13[/C][C]17.7112[/C][C]-4.71125[/C][/ROW]
[ROW][C]74[/C][C]20[/C][C]17.1388[/C][C]2.86121[/C][/ROW]
[ROW][C]75[/C][C]20[/C][C]20.3452[/C][C]-0.345182[/C][/ROW]
[ROW][C]76[/C][C]24[/C][C]19.0995[/C][C]4.9005[/C][/ROW]
[ROW][C]77[/C][C]25[/C][C]21.7517[/C][C]3.2483[/C][/ROW]
[ROW][C]78[/C][C]19[/C][C]20.3156[/C][C]-1.31556[/C][/ROW]
[ROW][C]79[/C][C]20[/C][C]20.0089[/C][C]-0.00885077[/C][/ROW]
[ROW][C]80[/C][C]20[/C][C]21.527[/C][C]-1.52703[/C][/ROW]
[ROW][C]81[/C][C]22[/C][C]20.6287[/C][C]1.37125[/C][/ROW]
[ROW][C]82[/C][C]18[/C][C]21.261[/C][C]-3.26099[/C][/ROW]
[ROW][C]83[/C][C]21[/C][C]19.8431[/C][C]1.15693[/C][/ROW]
[ROW][C]84[/C][C]20[/C][C]20.0078[/C][C]-0.00781124[/C][/ROW]
[ROW][C]85[/C][C]11[/C][C]15.4784[/C][C]-4.47837[/C][/ROW]
[ROW][C]86[/C][C]18[/C][C]18.5675[/C][C]-0.567485[/C][/ROW]
[ROW][C]87[/C][C]22[/C][C]23.0281[/C][C]-1.02811[/C][/ROW]
[ROW][C]88[/C][C]21[/C][C]20.4984[/C][C]0.501577[/C][/ROW]
[ROW][C]89[/C][C]15[/C][C]19.7564[/C][C]-4.75642[/C][/ROW]
[ROW][C]90[/C][C]23[/C][C]22.8712[/C][C]0.128796[/C][/ROW]
[ROW][C]91[/C][C]18[/C][C]22.2913[/C][C]-4.2913[/C][/ROW]
[ROW][C]92[/C][C]23[/C][C]23.2366[/C][C]-0.236617[/C][/ROW]
[ROW][C]93[/C][C]19[/C][C]21.3943[/C][C]-2.39434[/C][/ROW]
[ROW][C]94[/C][C]23[/C][C]18.9709[/C][C]4.02913[/C][/ROW]
[ROW][C]95[/C][C]26[/C][C]24.8109[/C][C]1.18914[/C][/ROW]
[ROW][C]96[/C][C]19[/C][C]19.1014[/C][C]-0.101447[/C][/ROW]
[ROW][C]97[/C][C]26[/C][C]22.3027[/C][C]3.69727[/C][/ROW]
[ROW][C]98[/C][C]20[/C][C]21.5153[/C][C]-1.51527[/C][/ROW]
[ROW][C]99[/C][C]20[/C][C]17.1453[/C][C]2.85473[/C][/ROW]
[ROW][C]100[/C][C]23[/C][C]22.9129[/C][C]0.0871139[/C][/ROW]
[ROW][C]101[/C][C]24[/C][C]22.6565[/C][C]1.3435[/C][/ROW]
[ROW][C]102[/C][C]26[/C][C]22.7619[/C][C]3.23805[/C][/ROW]
[ROW][C]103[/C][C]23[/C][C]20.3385[/C][C]2.66146[/C][/ROW]
[ROW][C]104[/C][C]19[/C][C]17.5243[/C][C]1.47567[/C][/ROW]
[ROW][C]105[/C][C]25[/C][C]21.8831[/C][C]3.11686[/C][/ROW]
[ROW][C]106[/C][C]23[/C][C]19.6363[/C][C]3.36371[/C][/ROW]
[ROW][C]107[/C][C]19[/C][C]20.5662[/C][C]-1.56615[/C][/ROW]
[ROW][C]108[/C][C]27[/C][C]24.0389[/C][C]2.96111[/C][/ROW]
[ROW][C]109[/C][C]23[/C][C]22.2289[/C][C]0.771129[/C][/ROW]
[ROW][C]110[/C][C]24[/C][C]22.511[/C][C]1.48897[/C][/ROW]
[ROW][C]111[/C][C]20[/C][C]19.7949[/C][C]0.205109[/C][/ROW]
[ROW][C]112[/C][C]16[/C][C]17.9909[/C][C]-1.99091[/C][/ROW]
[ROW][C]113[/C][C]22[/C][C]22.1416[/C][C]-0.141649[/C][/ROW]
[ROW][C]114[/C][C]26[/C][C]24.4155[/C][C]1.58453[/C][/ROW]
[ROW][C]115[/C][C]26[/C][C]23.7238[/C][C]2.27619[/C][/ROW]
[ROW][C]116[/C][C]24[/C][C]24.5766[/C][C]-0.576551[/C][/ROW]
[ROW][C]117[/C][C]20[/C][C]18.4021[/C][C]1.59795[/C][/ROW]
[ROW][C]118[/C][C]20[/C][C]21.0798[/C][C]-1.07978[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]18.7567[/C][C]-6.75671[/C][/ROW]
[ROW][C]120[/C][C]21[/C][C]17.885[/C][C]3.11496[/C][/ROW]
[ROW][C]121[/C][C]27[/C][C]22.6009[/C][C]4.39909[/C][/ROW]
[ROW][C]122[/C][C]26[/C][C]24.2252[/C][C]1.77479[/C][/ROW]
[ROW][C]123[/C][C]17[/C][C]18.4666[/C][C]-1.46663[/C][/ROW]
[ROW][C]124[/C][C]20[/C][C]19.7525[/C][C]0.247461[/C][/ROW]
[ROW][C]125[/C][C]18[/C][C]14.4011[/C][C]3.59891[/C][/ROW]
[ROW][C]126[/C][C]28[/C][C]23.4626[/C][C]4.5374[/C][/ROW]
[ROW][C]127[/C][C]24[/C][C]21.81[/C][C]2.19002[/C][/ROW]
[ROW][C]128[/C][C]24[/C][C]19.3125[/C][C]4.68748[/C][/ROW]
[ROW][C]129[/C][C]24[/C][C]21.7921[/C][C]2.20791[/C][/ROW]
[ROW][C]130[/C][C]12[/C][C]15.2318[/C][C]-3.2318[/C][/ROW]
[ROW][C]131[/C][C]26[/C][C]24.7927[/C][C]1.20728[/C][/ROW]
[ROW][C]132[/C][C]23[/C][C]22.9144[/C][C]0.0855676[/C][/ROW]
[ROW][C]133[/C][C]13[/C][C]16.926[/C][C]-3.92596[/C][/ROW]
[ROW][C]134[/C][C]23[/C][C]22.0092[/C][C]0.990786[/C][/ROW]
[ROW][C]135[/C][C]16[/C][C]20.6914[/C][C]-4.69141[/C][/ROW]
[ROW][C]136[/C][C]23[/C][C]21.4962[/C][C]1.50376[/C][/ROW]
[ROW][C]137[/C][C]18[/C][C]19.2111[/C][C]-1.21113[/C][/ROW]
[ROW][C]138[/C][C]25[/C][C]22.6926[/C][C]2.3074[/C][/ROW]
[ROW][C]139[/C][C]18[/C][C]18.8352[/C][C]-0.835157[/C][/ROW]
[ROW][C]140[/C][C]18[/C][C]19.5631[/C][C]-1.56307[/C][/ROW]
[ROW][C]141[/C][C]21[/C][C]21.9153[/C][C]-0.915277[/C][/ROW]
[ROW][C]142[/C][C]7[/C][C]13.9282[/C][C]-6.92822[/C][/ROW]
[ROW][C]143[/C][C]19[/C][C]18.3228[/C][C]0.677232[/C][/ROW]
[ROW][C]144[/C][C]21[/C][C]18.6719[/C][C]2.32809[/C][/ROW]
[ROW][C]145[/C][C]17[/C][C]15.1149[/C][C]1.88513[/C][/ROW]
[ROW][C]146[/C][C]22[/C][C]25.0078[/C][C]-3.0078[/C][/ROW]
[ROW][C]147[/C][C]15[/C][C]18.3253[/C][C]-3.32531[/C][/ROW]
[ROW][C]148[/C][C]20[/C][C]23.8897[/C][C]-3.8897[/C][/ROW]
[ROW][C]149[/C][C]19[/C][C]20.1289[/C][C]-1.12888[/C][/ROW]
[ROW][C]150[/C][C]10[/C][C]17.5605[/C][C]-7.5605[/C][/ROW]
[ROW][C]151[/C][C]18[/C][C]17.002[/C][C]0.998041[/C][/ROW]
[ROW][C]152[/C][C]25[/C][C]21.1499[/C][C]3.85015[/C][/ROW]
[ROW][C]153[/C][C]23[/C][C]22.0458[/C][C]0.954247[/C][/ROW]
[ROW][C]154[/C][C]25[/C][C]23.75[/C][C]1.25002[/C][/ROW]
[ROW][C]155[/C][C]23[/C][C]21.8963[/C][C]1.1037[/C][/ROW]
[ROW][C]156[/C][C]21[/C][C]20.4497[/C][C]0.550322[/C][/ROW]
[ROW][C]157[/C][C]23[/C][C]22.3822[/C][C]0.617752[/C][/ROW]
[ROW][C]158[/C][C]19[/C][C]22.4631[/C][C]-3.46305[/C][/ROW]
[ROW][C]159[/C][C]22[/C][C]21.6629[/C][C]0.337118[/C][/ROW]
[ROW][C]160[/C][C]23[/C][C]23.4181[/C][C]-0.418112[/C][/ROW]
[ROW][C]161[/C][C]15[/C][C]16.7334[/C][C]-1.73338[/C][/ROW]
[ROW][C]162[/C][C]23[/C][C]21.36[/C][C]1.63997[/C][/ROW]
[ROW][C]163[/C][C]23[/C][C]21.4633[/C][C]1.53673[/C][/ROW]
[ROW][C]164[/C][C]24[/C][C]27.0565[/C][C]-3.05653[/C][/ROW]
[ROW][C]165[/C][C]20[/C][C]23.3089[/C][C]-3.30889[/C][/ROW]
[ROW][C]166[/C][C]23[/C][C]21.6791[/C][C]1.32094[/C][/ROW]
[ROW][C]167[/C][C]24[/C][C]23.9767[/C][C]0.0232778[/C][/ROW]
[ROW][C]168[/C][C]17[/C][C]19.7869[/C][C]-2.7869[/C][/ROW]
[ROW][C]169[/C][C]21[/C][C]19.0311[/C][C]1.96886[/C][/ROW]
[ROW][C]170[/C][C]19[/C][C]23.0592[/C][C]-4.05921[/C][/ROW]
[ROW][C]171[/C][C]23[/C][C]21.4246[/C][C]1.57538[/C][/ROW]
[ROW][C]172[/C][C]22[/C][C]18.6787[/C][C]3.32128[/C][/ROW]
[ROW][C]173[/C][C]14[/C][C]17.2098[/C][C]-3.20984[/C][/ROW]
[ROW][C]174[/C][C]19[/C][C]18.6278[/C][C]0.372246[/C][/ROW]
[ROW][C]175[/C][C]21[/C][C]22.3912[/C][C]-1.39117[/C][/ROW]
[ROW][C]176[/C][C]23[/C][C]21.4777[/C][C]1.52229[/C][/ROW]
[ROW][C]177[/C][C]16[/C][C]18.9784[/C][C]-2.9784[/C][/ROW]
[ROW][C]178[/C][C]23[/C][C]20.088[/C][C]2.91201[/C][/ROW]
[ROW][C]179[/C][C]19[/C][C]21.2014[/C][C]-2.20144[/C][/ROW]
[ROW][C]180[/C][C]19[/C][C]21.1874[/C][C]-2.18737[/C][/ROW]
[ROW][C]181[/C][C]22[/C][C]24.5811[/C][C]-2.58108[/C][/ROW]
[ROW][C]182[/C][C]26[/C][C]23.5861[/C][C]2.4139[/C][/ROW]
[ROW][C]183[/C][C]22[/C][C]20.207[/C][C]1.79296[/C][/ROW]
[ROW][C]184[/C][C]24[/C][C]19.1008[/C][C]4.89918[/C][/ROW]
[ROW][C]185[/C][C]24[/C][C]23.9951[/C][C]0.00485344[/C][/ROW]
[ROW][C]186[/C][C]11[/C][C]11.9377[/C][C]-0.937721[/C][/ROW]
[ROW][C]187[/C][C]21[/C][C]21.6048[/C][C]-0.604827[/C][/ROW]
[ROW][C]188[/C][C]21[/C][C]18.7783[/C][C]2.22174[/C][/ROW]
[ROW][C]189[/C][C]22[/C][C]21.5631[/C][C]0.436873[/C][/ROW]
[ROW][C]190[/C][C]22[/C][C]21.6178[/C][C]0.382225[/C][/ROW]
[ROW][C]191[/C][C]19[/C][C]20.3086[/C][C]-1.30861[/C][/ROW]
[ROW][C]192[/C][C]18[/C][C]18.1664[/C][C]-0.166402[/C][/ROW]
[ROW][C]193[/C][C]19[/C][C]21.1874[/C][C]-2.18737[/C][/ROW]
[ROW][C]194[/C][C]27[/C][C]26.1078[/C][C]0.892247[/C][/ROW]
[ROW][C]195[/C][C]14[/C][C]15.1346[/C][C]-1.13463[/C][/ROW]
[ROW][C]196[/C][C]15[/C][C]18.2404[/C][C]-3.24039[/C][/ROW]
[ROW][C]197[/C][C]20[/C][C]20.5316[/C][C]-0.531551[/C][/ROW]
[ROW][C]198[/C][C]22[/C][C]20.1309[/C][C]1.86908[/C][/ROW]
[ROW][C]199[/C][C]26[/C][C]23.6007[/C][C]2.3993[/C][/ROW]
[ROW][C]200[/C][C]20[/C][C]18.8471[/C][C]1.15286[/C][/ROW]
[ROW][C]201[/C][C]13[/C][C]16.3139[/C][C]-3.3139[/C][/ROW]
[ROW][C]202[/C][C]26[/C][C]24.0782[/C][C]1.92185[/C][/ROW]
[ROW][C]203[/C][C]19[/C][C]20.0279[/C][C]-1.02789[/C][/ROW]
[ROW][C]204[/C][C]20[/C][C]18.9534[/C][C]1.04658[/C][/ROW]
[ROW][C]205[/C][C]18[/C][C]20.2214[/C][C]-2.22138[/C][/ROW]
[ROW][C]206[/C][C]20[/C][C]23.6854[/C][C]-3.68543[/C][/ROW]
[ROW][C]207[/C][C]21[/C][C]18.4757[/C][C]2.52425[/C][/ROW]
[ROW][C]208[/C][C]26[/C][C]23.6966[/C][C]2.30335[/C][/ROW]
[ROW][C]209[/C][C]25[/C][C]21.2169[/C][C]3.78307[/C][/ROW]
[ROW][C]210[/C][C]20[/C][C]21.8444[/C][C]-1.84435[/C][/ROW]
[ROW][C]211[/C][C]21[/C][C]20.5061[/C][C]0.493892[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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
12120.84670.153251
21919.0514-0.0514159
32720.50566.49439
41310.97632.02375
51719.23-2.23005
61820.716-2.71599
72020.5842-0.584213
82219.98382.01616
91818.1594-0.159372
1066.16494-0.164937
112221.77230.227666
121519.0344-4.03439
131919.2042-0.20424
141718.3455-1.34551
152223.9186-1.91858
161014.2745-4.27452
172117.68063.31937
182122.131-1.13101
192319.84443.15555
201822.1262-4.12621
212018.70211.29786
222719.09277.90728
231317.0966-4.09657
242019.94310.0569453
252015.50734.49268
262221.17670.823301
272019.61460.385432
282424.4976-0.497584
292319.97223.02783
301917.95911.04095
312218.32163.67838
322415.84958.15054
332118.66022.33978
341919.8809-0.880939
352021.0805-1.08051
361614.91361.08643
371722.2127-5.2127
382520.54414.45586
391620.3586-4.35857
402323.2456-0.245591
412016.14543.85456
422325.0796-2.07964
432222.2716-0.271599
441516.5953-1.59533
451616.4227-0.422676
462021.7294-1.72943
472322.50830.491691
482423.5980.402
491720.0421-3.0421
501920.0834-1.08342
512525.0207-0.0207262
521421.3852-7.38518
531817.48260.517374
542221.34480.65523
551513.02781.97224
562725.08321.9168
572220.49081.50923
582625.79920.200755
591617.7619-1.76191
602520.7434.25703
612019.27160.728411
621918.52060.479428
631924.1143-5.11427
642420.48713.5129
651416.4022-2.40218
661820.4072-2.40717
671317.8192-4.81921
681920.1099-1.10988
692523.64231.35765
702021.4504-1.45041
711717.0094-0.00941709
721723.2988-6.29882
731317.7112-4.71125
742017.13882.86121
752020.3452-0.345182
762419.09954.9005
772521.75173.2483
781920.3156-1.31556
792020.0089-0.00885077
802021.527-1.52703
812220.62871.37125
821821.261-3.26099
832119.84311.15693
842020.0078-0.00781124
851115.4784-4.47837
861818.5675-0.567485
872223.0281-1.02811
882120.49840.501577
891519.7564-4.75642
902322.87120.128796
911822.2913-4.2913
922323.2366-0.236617
931921.3943-2.39434
942318.97094.02913
952624.81091.18914
961919.1014-0.101447
972622.30273.69727
982021.5153-1.51527
992017.14532.85473
1002322.91290.0871139
1012422.65651.3435
1022622.76193.23805
1032320.33852.66146
1041917.52431.47567
1052521.88313.11686
1062319.63633.36371
1071920.5662-1.56615
1082724.03892.96111
1092322.22890.771129
1102422.5111.48897
1112019.79490.205109
1121617.9909-1.99091
1132222.1416-0.141649
1142624.41551.58453
1152623.72382.27619
1162424.5766-0.576551
1172018.40211.59795
1182021.0798-1.07978
1191218.7567-6.75671
1202117.8853.11496
1212722.60094.39909
1222624.22521.77479
1231718.4666-1.46663
1242019.75250.247461
1251814.40113.59891
1262823.46264.5374
1272421.812.19002
1282419.31254.68748
1292421.79212.20791
1301215.2318-3.2318
1312624.79271.20728
1322322.91440.0855676
1331316.926-3.92596
1342322.00920.990786
1351620.6914-4.69141
1362321.49621.50376
1371819.2111-1.21113
1382522.69262.3074
1391818.8352-0.835157
1401819.5631-1.56307
1412121.9153-0.915277
142713.9282-6.92822
1431918.32280.677232
1442118.67192.32809
1451715.11491.88513
1462225.0078-3.0078
1471518.3253-3.32531
1482023.8897-3.8897
1491920.1289-1.12888
1501017.5605-7.5605
1511817.0020.998041
1522521.14993.85015
1532322.04580.954247
1542523.751.25002
1552321.89631.1037
1562120.44970.550322
1572322.38220.617752
1581922.4631-3.46305
1592221.66290.337118
1602323.4181-0.418112
1611516.7334-1.73338
1622321.361.63997
1632321.46331.53673
1642427.0565-3.05653
1652023.3089-3.30889
1662321.67911.32094
1672423.97670.0232778
1681719.7869-2.7869
1692119.03111.96886
1701923.0592-4.05921
1712321.42461.57538
1722218.67873.32128
1731417.2098-3.20984
1741918.62780.372246
1752122.3912-1.39117
1762321.47771.52229
1771618.9784-2.9784
1782320.0882.91201
1791921.2014-2.20144
1801921.1874-2.18737
1812224.5811-2.58108
1822623.58612.4139
1832220.2071.79296
1842419.10084.89918
1852423.99510.00485344
1861111.9377-0.937721
1872121.6048-0.604827
1882118.77832.22174
1892221.56310.436873
1902221.61780.382225
1911920.3086-1.30861
1921818.1664-0.166402
1931921.1874-2.18737
1942726.10780.892247
1951415.1346-1.13463
1961518.2404-3.24039
1972020.5316-0.531551
1982220.13091.86908
1992623.60072.3993
2002018.84711.15286
2011316.3139-3.3139
2022624.07821.92185
2031920.0279-1.02789
2042018.95341.04658
2051820.2214-2.22138
2062023.6854-3.68543
2072118.47572.52425
2082623.69662.30335
2092521.21693.78307
2102021.8444-1.84435
2112120.50610.493892






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
100.8295920.3408160.170408
110.7813850.4372310.218615
120.7775850.4448310.222415
130.6755380.6489230.324462
140.5977590.8044820.402241
150.494980.9899590.50502
160.6944370.6111270.305563
170.8142240.3715520.185776
180.7512660.4974680.248734
190.785030.429940.21497
200.7906940.4186130.209306
210.7446240.5107520.255376
220.9259490.1481020.0740511
230.9274990.1450020.0725011
240.9030670.1938670.0969334
250.9397080.1205840.0602922
260.9246780.1506430.0753217
270.9044470.1911060.0955528
280.880380.239240.11962
290.8843320.2313360.115668
300.8545270.2909470.145473
310.8329870.3340260.167013
320.9579040.08419220.0420961
330.9463720.1072550.0536275
340.9322430.1355130.0677567
350.9142060.1715870.0857936
360.892250.21550.10775
370.9064910.1870170.0935086
380.9073910.1852180.0926089
390.9500330.0999350.0499675
400.9356710.1286590.0643293
410.9366410.1267190.0633593
420.9405990.1188020.0594009
430.9242070.1515860.0757932
440.9249110.1501780.0750892
450.9073410.1853180.0926591
460.8871430.2257140.112857
470.8665740.2668530.133426
480.8497420.3005150.150258
490.8511050.2977910.148895
500.8245370.3509260.175463
510.7923290.4153430.207671
520.9455070.1089850.0544925
530.9321580.1356840.0678418
540.9175280.1649430.0824717
550.9039480.1921040.0960519
560.9021870.1956270.0978135
570.8884830.2230340.111517
580.8780470.2439060.121953
590.865340.2693210.13466
600.8783840.2432320.121616
610.8556680.2886630.144332
620.8294380.3411240.170562
630.8610190.2779610.138981
640.8893440.2213120.110656
650.8904840.2190310.109516
660.8793810.2412380.120619
670.9305460.1389080.0694542
680.9183080.1633840.081692
690.9099490.1801030.0900514
700.8947830.2104340.105217
710.8747960.2504070.125204
720.9354710.1290590.0645294
730.9581590.08368270.0418413
740.9600350.07992970.0399649
750.9509860.09802760.0490138
760.9669190.0661610.0330805
770.9725970.05480530.0274027
780.9711340.05773260.0288663
790.9636540.07269130.0363457
800.9571570.08568630.0428431
810.9493410.1013180.0506589
820.9511520.09769680.0488484
830.941770.1164610.0582305
840.9290270.1419460.0709732
850.9507840.09843110.0492156
860.9400570.1198850.0599426
870.929510.1409810.0704903
880.9165910.1668170.0834086
890.9403230.1193540.0596771
900.9286540.1426920.0713459
910.9447320.1105360.0552681
920.9334020.1331950.0665977
930.9292950.141410.070705
940.9418820.1162370.0581185
950.9331550.1336890.0668446
960.9192180.1615630.0807815
970.9317780.1364440.0682218
980.920770.1584590.0792296
990.9211130.1577740.0788872
1000.9057490.1885020.094251
1010.8931230.2137530.106877
1020.9063260.1873470.0936737
1030.9052480.1895050.0947525
1040.8920690.2158620.107931
1050.8974710.2050580.102529
1060.9067510.1864980.0932491
1070.8954280.2091440.104572
1080.8990520.2018960.100948
1090.8816390.2367220.118361
1100.868410.263180.13159
1110.8456930.3086130.154307
1120.8346590.3306830.165341
1130.8087390.3825220.191261
1140.7893080.4213840.210692
1150.779730.440540.22027
1160.7526730.4946540.247327
1170.7394470.5211060.260553
1180.711160.577680.28884
1190.8567310.2865380.143269
1200.8656090.2687810.134391
1210.8964410.2071190.103559
1220.8859310.2281380.114069
1230.8696160.2607670.130384
1240.8467270.3065450.153273
1250.8710820.2578360.128918
1260.9080350.183930.0919649
1270.9096580.1806840.0903422
1280.9500810.09983750.0499187
1290.9447740.1104520.055226
1300.9440950.111810.0559052
1310.9328030.1343930.0671967
1320.917890.1642190.0821097
1330.9346240.1307520.0653758
1340.9254860.1490270.0745136
1350.9491580.1016830.0508416
1360.939150.12170.06085
1370.9282510.1434970.0717487
1380.9230470.1539070.0769534
1390.9071530.1856940.092847
1400.8931450.213710.106855
1410.8729410.2541170.127059
1420.9578790.0842430.0421215
1430.9474020.1051950.0525977
1440.9487630.1024750.0512374
1450.947320.1053610.0526803
1460.9486620.1026770.0513385
1470.9565230.08695360.0434768
1480.9650270.06994510.0349725
1490.9575690.08486280.0424314
1500.9918060.01638770.00819385
1510.9889660.02206810.011034
1520.9935280.01294450.00647224
1530.9918320.01633680.0081684
1540.9904070.01918590.00959293
1550.9876820.02463610.012318
1560.9832720.03345610.0167281
1570.977910.04418010.02209
1580.9819220.03615620.0180781
1590.9755910.04881770.0244089
1600.9674420.06511660.0325583
1610.9591130.08177460.0408873
1620.9490110.1019770.0509885
1630.9385230.1229550.0614774
1640.9512310.09753840.0487692
1650.9535360.09292820.0464641
1660.9428790.1142410.0571207
1670.9256740.1486530.0743263
1680.9218340.1563320.0781662
1690.9198380.1603230.0801617
1700.9493790.1012430.0506213
1710.9425950.114810.0574048
1720.9605970.07880520.0394026
1730.9633590.07328120.0366406
1740.9524640.09507230.0475362
1750.9384990.1230010.0615007
1760.9339110.1321780.0660892
1770.93950.1209990.0604996
1780.9520160.09596760.0479838
1790.9460310.1079390.0539695
1800.9386780.1226430.0613216
1810.9509090.09818270.0490913
1820.9509320.09813580.0490679
1830.9329410.1341170.0670587
1840.9841780.03164360.0158218
1850.975050.04990090.0249504
1860.9616660.07666730.0383336
1870.9437350.112530.056265
1880.9539890.09202180.0460109
1890.9342430.1315140.0657568
1900.9035850.192830.0964149
1910.867460.265080.13254
1920.8395210.3209580.160479
1930.798940.4021190.20106
1940.7308550.5382890.269145
1950.6482210.7035590.351779
1960.8232640.3534730.176736
1970.76870.4626010.2313
1980.6706910.6586190.329309
1990.5573510.8852980.442649
2000.4685570.9371150.531443
2010.3827810.7655620.617219

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
10 & 0.829592 & 0.340816 & 0.170408 \tabularnewline
11 & 0.781385 & 0.437231 & 0.218615 \tabularnewline
12 & 0.777585 & 0.444831 & 0.222415 \tabularnewline
13 & 0.675538 & 0.648923 & 0.324462 \tabularnewline
14 & 0.597759 & 0.804482 & 0.402241 \tabularnewline
15 & 0.49498 & 0.989959 & 0.50502 \tabularnewline
16 & 0.694437 & 0.611127 & 0.305563 \tabularnewline
17 & 0.814224 & 0.371552 & 0.185776 \tabularnewline
18 & 0.751266 & 0.497468 & 0.248734 \tabularnewline
19 & 0.78503 & 0.42994 & 0.21497 \tabularnewline
20 & 0.790694 & 0.418613 & 0.209306 \tabularnewline
21 & 0.744624 & 0.510752 & 0.255376 \tabularnewline
22 & 0.925949 & 0.148102 & 0.0740511 \tabularnewline
23 & 0.927499 & 0.145002 & 0.0725011 \tabularnewline
24 & 0.903067 & 0.193867 & 0.0969334 \tabularnewline
25 & 0.939708 & 0.120584 & 0.0602922 \tabularnewline
26 & 0.924678 & 0.150643 & 0.0753217 \tabularnewline
27 & 0.904447 & 0.191106 & 0.0955528 \tabularnewline
28 & 0.88038 & 0.23924 & 0.11962 \tabularnewline
29 & 0.884332 & 0.231336 & 0.115668 \tabularnewline
30 & 0.854527 & 0.290947 & 0.145473 \tabularnewline
31 & 0.832987 & 0.334026 & 0.167013 \tabularnewline
32 & 0.957904 & 0.0841922 & 0.0420961 \tabularnewline
33 & 0.946372 & 0.107255 & 0.0536275 \tabularnewline
34 & 0.932243 & 0.135513 & 0.0677567 \tabularnewline
35 & 0.914206 & 0.171587 & 0.0857936 \tabularnewline
36 & 0.89225 & 0.2155 & 0.10775 \tabularnewline
37 & 0.906491 & 0.187017 & 0.0935086 \tabularnewline
38 & 0.907391 & 0.185218 & 0.0926089 \tabularnewline
39 & 0.950033 & 0.099935 & 0.0499675 \tabularnewline
40 & 0.935671 & 0.128659 & 0.0643293 \tabularnewline
41 & 0.936641 & 0.126719 & 0.0633593 \tabularnewline
42 & 0.940599 & 0.118802 & 0.0594009 \tabularnewline
43 & 0.924207 & 0.151586 & 0.0757932 \tabularnewline
44 & 0.924911 & 0.150178 & 0.0750892 \tabularnewline
45 & 0.907341 & 0.185318 & 0.0926591 \tabularnewline
46 & 0.887143 & 0.225714 & 0.112857 \tabularnewline
47 & 0.866574 & 0.266853 & 0.133426 \tabularnewline
48 & 0.849742 & 0.300515 & 0.150258 \tabularnewline
49 & 0.851105 & 0.297791 & 0.148895 \tabularnewline
50 & 0.824537 & 0.350926 & 0.175463 \tabularnewline
51 & 0.792329 & 0.415343 & 0.207671 \tabularnewline
52 & 0.945507 & 0.108985 & 0.0544925 \tabularnewline
53 & 0.932158 & 0.135684 & 0.0678418 \tabularnewline
54 & 0.917528 & 0.164943 & 0.0824717 \tabularnewline
55 & 0.903948 & 0.192104 & 0.0960519 \tabularnewline
56 & 0.902187 & 0.195627 & 0.0978135 \tabularnewline
57 & 0.888483 & 0.223034 & 0.111517 \tabularnewline
58 & 0.878047 & 0.243906 & 0.121953 \tabularnewline
59 & 0.86534 & 0.269321 & 0.13466 \tabularnewline
60 & 0.878384 & 0.243232 & 0.121616 \tabularnewline
61 & 0.855668 & 0.288663 & 0.144332 \tabularnewline
62 & 0.829438 & 0.341124 & 0.170562 \tabularnewline
63 & 0.861019 & 0.277961 & 0.138981 \tabularnewline
64 & 0.889344 & 0.221312 & 0.110656 \tabularnewline
65 & 0.890484 & 0.219031 & 0.109516 \tabularnewline
66 & 0.879381 & 0.241238 & 0.120619 \tabularnewline
67 & 0.930546 & 0.138908 & 0.0694542 \tabularnewline
68 & 0.918308 & 0.163384 & 0.081692 \tabularnewline
69 & 0.909949 & 0.180103 & 0.0900514 \tabularnewline
70 & 0.894783 & 0.210434 & 0.105217 \tabularnewline
71 & 0.874796 & 0.250407 & 0.125204 \tabularnewline
72 & 0.935471 & 0.129059 & 0.0645294 \tabularnewline
73 & 0.958159 & 0.0836827 & 0.0418413 \tabularnewline
74 & 0.960035 & 0.0799297 & 0.0399649 \tabularnewline
75 & 0.950986 & 0.0980276 & 0.0490138 \tabularnewline
76 & 0.966919 & 0.066161 & 0.0330805 \tabularnewline
77 & 0.972597 & 0.0548053 & 0.0274027 \tabularnewline
78 & 0.971134 & 0.0577326 & 0.0288663 \tabularnewline
79 & 0.963654 & 0.0726913 & 0.0363457 \tabularnewline
80 & 0.957157 & 0.0856863 & 0.0428431 \tabularnewline
81 & 0.949341 & 0.101318 & 0.0506589 \tabularnewline
82 & 0.951152 & 0.0976968 & 0.0488484 \tabularnewline
83 & 0.94177 & 0.116461 & 0.0582305 \tabularnewline
84 & 0.929027 & 0.141946 & 0.0709732 \tabularnewline
85 & 0.950784 & 0.0984311 & 0.0492156 \tabularnewline
86 & 0.940057 & 0.119885 & 0.0599426 \tabularnewline
87 & 0.92951 & 0.140981 & 0.0704903 \tabularnewline
88 & 0.916591 & 0.166817 & 0.0834086 \tabularnewline
89 & 0.940323 & 0.119354 & 0.0596771 \tabularnewline
90 & 0.928654 & 0.142692 & 0.0713459 \tabularnewline
91 & 0.944732 & 0.110536 & 0.0552681 \tabularnewline
92 & 0.933402 & 0.133195 & 0.0665977 \tabularnewline
93 & 0.929295 & 0.14141 & 0.070705 \tabularnewline
94 & 0.941882 & 0.116237 & 0.0581185 \tabularnewline
95 & 0.933155 & 0.133689 & 0.0668446 \tabularnewline
96 & 0.919218 & 0.161563 & 0.0807815 \tabularnewline
97 & 0.931778 & 0.136444 & 0.0682218 \tabularnewline
98 & 0.92077 & 0.158459 & 0.0792296 \tabularnewline
99 & 0.921113 & 0.157774 & 0.0788872 \tabularnewline
100 & 0.905749 & 0.188502 & 0.094251 \tabularnewline
101 & 0.893123 & 0.213753 & 0.106877 \tabularnewline
102 & 0.906326 & 0.187347 & 0.0936737 \tabularnewline
103 & 0.905248 & 0.189505 & 0.0947525 \tabularnewline
104 & 0.892069 & 0.215862 & 0.107931 \tabularnewline
105 & 0.897471 & 0.205058 & 0.102529 \tabularnewline
106 & 0.906751 & 0.186498 & 0.0932491 \tabularnewline
107 & 0.895428 & 0.209144 & 0.104572 \tabularnewline
108 & 0.899052 & 0.201896 & 0.100948 \tabularnewline
109 & 0.881639 & 0.236722 & 0.118361 \tabularnewline
110 & 0.86841 & 0.26318 & 0.13159 \tabularnewline
111 & 0.845693 & 0.308613 & 0.154307 \tabularnewline
112 & 0.834659 & 0.330683 & 0.165341 \tabularnewline
113 & 0.808739 & 0.382522 & 0.191261 \tabularnewline
114 & 0.789308 & 0.421384 & 0.210692 \tabularnewline
115 & 0.77973 & 0.44054 & 0.22027 \tabularnewline
116 & 0.752673 & 0.494654 & 0.247327 \tabularnewline
117 & 0.739447 & 0.521106 & 0.260553 \tabularnewline
118 & 0.71116 & 0.57768 & 0.28884 \tabularnewline
119 & 0.856731 & 0.286538 & 0.143269 \tabularnewline
120 & 0.865609 & 0.268781 & 0.134391 \tabularnewline
121 & 0.896441 & 0.207119 & 0.103559 \tabularnewline
122 & 0.885931 & 0.228138 & 0.114069 \tabularnewline
123 & 0.869616 & 0.260767 & 0.130384 \tabularnewline
124 & 0.846727 & 0.306545 & 0.153273 \tabularnewline
125 & 0.871082 & 0.257836 & 0.128918 \tabularnewline
126 & 0.908035 & 0.18393 & 0.0919649 \tabularnewline
127 & 0.909658 & 0.180684 & 0.0903422 \tabularnewline
128 & 0.950081 & 0.0998375 & 0.0499187 \tabularnewline
129 & 0.944774 & 0.110452 & 0.055226 \tabularnewline
130 & 0.944095 & 0.11181 & 0.0559052 \tabularnewline
131 & 0.932803 & 0.134393 & 0.0671967 \tabularnewline
132 & 0.91789 & 0.164219 & 0.0821097 \tabularnewline
133 & 0.934624 & 0.130752 & 0.0653758 \tabularnewline
134 & 0.925486 & 0.149027 & 0.0745136 \tabularnewline
135 & 0.949158 & 0.101683 & 0.0508416 \tabularnewline
136 & 0.93915 & 0.1217 & 0.06085 \tabularnewline
137 & 0.928251 & 0.143497 & 0.0717487 \tabularnewline
138 & 0.923047 & 0.153907 & 0.0769534 \tabularnewline
139 & 0.907153 & 0.185694 & 0.092847 \tabularnewline
140 & 0.893145 & 0.21371 & 0.106855 \tabularnewline
141 & 0.872941 & 0.254117 & 0.127059 \tabularnewline
142 & 0.957879 & 0.084243 & 0.0421215 \tabularnewline
143 & 0.947402 & 0.105195 & 0.0525977 \tabularnewline
144 & 0.948763 & 0.102475 & 0.0512374 \tabularnewline
145 & 0.94732 & 0.105361 & 0.0526803 \tabularnewline
146 & 0.948662 & 0.102677 & 0.0513385 \tabularnewline
147 & 0.956523 & 0.0869536 & 0.0434768 \tabularnewline
148 & 0.965027 & 0.0699451 & 0.0349725 \tabularnewline
149 & 0.957569 & 0.0848628 & 0.0424314 \tabularnewline
150 & 0.991806 & 0.0163877 & 0.00819385 \tabularnewline
151 & 0.988966 & 0.0220681 & 0.011034 \tabularnewline
152 & 0.993528 & 0.0129445 & 0.00647224 \tabularnewline
153 & 0.991832 & 0.0163368 & 0.0081684 \tabularnewline
154 & 0.990407 & 0.0191859 & 0.00959293 \tabularnewline
155 & 0.987682 & 0.0246361 & 0.012318 \tabularnewline
156 & 0.983272 & 0.0334561 & 0.0167281 \tabularnewline
157 & 0.97791 & 0.0441801 & 0.02209 \tabularnewline
158 & 0.981922 & 0.0361562 & 0.0180781 \tabularnewline
159 & 0.975591 & 0.0488177 & 0.0244089 \tabularnewline
160 & 0.967442 & 0.0651166 & 0.0325583 \tabularnewline
161 & 0.959113 & 0.0817746 & 0.0408873 \tabularnewline
162 & 0.949011 & 0.101977 & 0.0509885 \tabularnewline
163 & 0.938523 & 0.122955 & 0.0614774 \tabularnewline
164 & 0.951231 & 0.0975384 & 0.0487692 \tabularnewline
165 & 0.953536 & 0.0929282 & 0.0464641 \tabularnewline
166 & 0.942879 & 0.114241 & 0.0571207 \tabularnewline
167 & 0.925674 & 0.148653 & 0.0743263 \tabularnewline
168 & 0.921834 & 0.156332 & 0.0781662 \tabularnewline
169 & 0.919838 & 0.160323 & 0.0801617 \tabularnewline
170 & 0.949379 & 0.101243 & 0.0506213 \tabularnewline
171 & 0.942595 & 0.11481 & 0.0574048 \tabularnewline
172 & 0.960597 & 0.0788052 & 0.0394026 \tabularnewline
173 & 0.963359 & 0.0732812 & 0.0366406 \tabularnewline
174 & 0.952464 & 0.0950723 & 0.0475362 \tabularnewline
175 & 0.938499 & 0.123001 & 0.0615007 \tabularnewline
176 & 0.933911 & 0.132178 & 0.0660892 \tabularnewline
177 & 0.9395 & 0.120999 & 0.0604996 \tabularnewline
178 & 0.952016 & 0.0959676 & 0.0479838 \tabularnewline
179 & 0.946031 & 0.107939 & 0.0539695 \tabularnewline
180 & 0.938678 & 0.122643 & 0.0613216 \tabularnewline
181 & 0.950909 & 0.0981827 & 0.0490913 \tabularnewline
182 & 0.950932 & 0.0981358 & 0.0490679 \tabularnewline
183 & 0.932941 & 0.134117 & 0.0670587 \tabularnewline
184 & 0.984178 & 0.0316436 & 0.0158218 \tabularnewline
185 & 0.97505 & 0.0499009 & 0.0249504 \tabularnewline
186 & 0.961666 & 0.0766673 & 0.0383336 \tabularnewline
187 & 0.943735 & 0.11253 & 0.056265 \tabularnewline
188 & 0.953989 & 0.0920218 & 0.0460109 \tabularnewline
189 & 0.934243 & 0.131514 & 0.0657568 \tabularnewline
190 & 0.903585 & 0.19283 & 0.0964149 \tabularnewline
191 & 0.86746 & 0.26508 & 0.13254 \tabularnewline
192 & 0.839521 & 0.320958 & 0.160479 \tabularnewline
193 & 0.79894 & 0.402119 & 0.20106 \tabularnewline
194 & 0.730855 & 0.538289 & 0.269145 \tabularnewline
195 & 0.648221 & 0.703559 & 0.351779 \tabularnewline
196 & 0.823264 & 0.353473 & 0.176736 \tabularnewline
197 & 0.7687 & 0.462601 & 0.2313 \tabularnewline
198 & 0.670691 & 0.658619 & 0.329309 \tabularnewline
199 & 0.557351 & 0.885298 & 0.442649 \tabularnewline
200 & 0.468557 & 0.937115 & 0.531443 \tabularnewline
201 & 0.382781 & 0.765562 & 0.617219 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&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]10[/C][C]0.829592[/C][C]0.340816[/C][C]0.170408[/C][/ROW]
[ROW][C]11[/C][C]0.781385[/C][C]0.437231[/C][C]0.218615[/C][/ROW]
[ROW][C]12[/C][C]0.777585[/C][C]0.444831[/C][C]0.222415[/C][/ROW]
[ROW][C]13[/C][C]0.675538[/C][C]0.648923[/C][C]0.324462[/C][/ROW]
[ROW][C]14[/C][C]0.597759[/C][C]0.804482[/C][C]0.402241[/C][/ROW]
[ROW][C]15[/C][C]0.49498[/C][C]0.989959[/C][C]0.50502[/C][/ROW]
[ROW][C]16[/C][C]0.694437[/C][C]0.611127[/C][C]0.305563[/C][/ROW]
[ROW][C]17[/C][C]0.814224[/C][C]0.371552[/C][C]0.185776[/C][/ROW]
[ROW][C]18[/C][C]0.751266[/C][C]0.497468[/C][C]0.248734[/C][/ROW]
[ROW][C]19[/C][C]0.78503[/C][C]0.42994[/C][C]0.21497[/C][/ROW]
[ROW][C]20[/C][C]0.790694[/C][C]0.418613[/C][C]0.209306[/C][/ROW]
[ROW][C]21[/C][C]0.744624[/C][C]0.510752[/C][C]0.255376[/C][/ROW]
[ROW][C]22[/C][C]0.925949[/C][C]0.148102[/C][C]0.0740511[/C][/ROW]
[ROW][C]23[/C][C]0.927499[/C][C]0.145002[/C][C]0.0725011[/C][/ROW]
[ROW][C]24[/C][C]0.903067[/C][C]0.193867[/C][C]0.0969334[/C][/ROW]
[ROW][C]25[/C][C]0.939708[/C][C]0.120584[/C][C]0.0602922[/C][/ROW]
[ROW][C]26[/C][C]0.924678[/C][C]0.150643[/C][C]0.0753217[/C][/ROW]
[ROW][C]27[/C][C]0.904447[/C][C]0.191106[/C][C]0.0955528[/C][/ROW]
[ROW][C]28[/C][C]0.88038[/C][C]0.23924[/C][C]0.11962[/C][/ROW]
[ROW][C]29[/C][C]0.884332[/C][C]0.231336[/C][C]0.115668[/C][/ROW]
[ROW][C]30[/C][C]0.854527[/C][C]0.290947[/C][C]0.145473[/C][/ROW]
[ROW][C]31[/C][C]0.832987[/C][C]0.334026[/C][C]0.167013[/C][/ROW]
[ROW][C]32[/C][C]0.957904[/C][C]0.0841922[/C][C]0.0420961[/C][/ROW]
[ROW][C]33[/C][C]0.946372[/C][C]0.107255[/C][C]0.0536275[/C][/ROW]
[ROW][C]34[/C][C]0.932243[/C][C]0.135513[/C][C]0.0677567[/C][/ROW]
[ROW][C]35[/C][C]0.914206[/C][C]0.171587[/C][C]0.0857936[/C][/ROW]
[ROW][C]36[/C][C]0.89225[/C][C]0.2155[/C][C]0.10775[/C][/ROW]
[ROW][C]37[/C][C]0.906491[/C][C]0.187017[/C][C]0.0935086[/C][/ROW]
[ROW][C]38[/C][C]0.907391[/C][C]0.185218[/C][C]0.0926089[/C][/ROW]
[ROW][C]39[/C][C]0.950033[/C][C]0.099935[/C][C]0.0499675[/C][/ROW]
[ROW][C]40[/C][C]0.935671[/C][C]0.128659[/C][C]0.0643293[/C][/ROW]
[ROW][C]41[/C][C]0.936641[/C][C]0.126719[/C][C]0.0633593[/C][/ROW]
[ROW][C]42[/C][C]0.940599[/C][C]0.118802[/C][C]0.0594009[/C][/ROW]
[ROW][C]43[/C][C]0.924207[/C][C]0.151586[/C][C]0.0757932[/C][/ROW]
[ROW][C]44[/C][C]0.924911[/C][C]0.150178[/C][C]0.0750892[/C][/ROW]
[ROW][C]45[/C][C]0.907341[/C][C]0.185318[/C][C]0.0926591[/C][/ROW]
[ROW][C]46[/C][C]0.887143[/C][C]0.225714[/C][C]0.112857[/C][/ROW]
[ROW][C]47[/C][C]0.866574[/C][C]0.266853[/C][C]0.133426[/C][/ROW]
[ROW][C]48[/C][C]0.849742[/C][C]0.300515[/C][C]0.150258[/C][/ROW]
[ROW][C]49[/C][C]0.851105[/C][C]0.297791[/C][C]0.148895[/C][/ROW]
[ROW][C]50[/C][C]0.824537[/C][C]0.350926[/C][C]0.175463[/C][/ROW]
[ROW][C]51[/C][C]0.792329[/C][C]0.415343[/C][C]0.207671[/C][/ROW]
[ROW][C]52[/C][C]0.945507[/C][C]0.108985[/C][C]0.0544925[/C][/ROW]
[ROW][C]53[/C][C]0.932158[/C][C]0.135684[/C][C]0.0678418[/C][/ROW]
[ROW][C]54[/C][C]0.917528[/C][C]0.164943[/C][C]0.0824717[/C][/ROW]
[ROW][C]55[/C][C]0.903948[/C][C]0.192104[/C][C]0.0960519[/C][/ROW]
[ROW][C]56[/C][C]0.902187[/C][C]0.195627[/C][C]0.0978135[/C][/ROW]
[ROW][C]57[/C][C]0.888483[/C][C]0.223034[/C][C]0.111517[/C][/ROW]
[ROW][C]58[/C][C]0.878047[/C][C]0.243906[/C][C]0.121953[/C][/ROW]
[ROW][C]59[/C][C]0.86534[/C][C]0.269321[/C][C]0.13466[/C][/ROW]
[ROW][C]60[/C][C]0.878384[/C][C]0.243232[/C][C]0.121616[/C][/ROW]
[ROW][C]61[/C][C]0.855668[/C][C]0.288663[/C][C]0.144332[/C][/ROW]
[ROW][C]62[/C][C]0.829438[/C][C]0.341124[/C][C]0.170562[/C][/ROW]
[ROW][C]63[/C][C]0.861019[/C][C]0.277961[/C][C]0.138981[/C][/ROW]
[ROW][C]64[/C][C]0.889344[/C][C]0.221312[/C][C]0.110656[/C][/ROW]
[ROW][C]65[/C][C]0.890484[/C][C]0.219031[/C][C]0.109516[/C][/ROW]
[ROW][C]66[/C][C]0.879381[/C][C]0.241238[/C][C]0.120619[/C][/ROW]
[ROW][C]67[/C][C]0.930546[/C][C]0.138908[/C][C]0.0694542[/C][/ROW]
[ROW][C]68[/C][C]0.918308[/C][C]0.163384[/C][C]0.081692[/C][/ROW]
[ROW][C]69[/C][C]0.909949[/C][C]0.180103[/C][C]0.0900514[/C][/ROW]
[ROW][C]70[/C][C]0.894783[/C][C]0.210434[/C][C]0.105217[/C][/ROW]
[ROW][C]71[/C][C]0.874796[/C][C]0.250407[/C][C]0.125204[/C][/ROW]
[ROW][C]72[/C][C]0.935471[/C][C]0.129059[/C][C]0.0645294[/C][/ROW]
[ROW][C]73[/C][C]0.958159[/C][C]0.0836827[/C][C]0.0418413[/C][/ROW]
[ROW][C]74[/C][C]0.960035[/C][C]0.0799297[/C][C]0.0399649[/C][/ROW]
[ROW][C]75[/C][C]0.950986[/C][C]0.0980276[/C][C]0.0490138[/C][/ROW]
[ROW][C]76[/C][C]0.966919[/C][C]0.066161[/C][C]0.0330805[/C][/ROW]
[ROW][C]77[/C][C]0.972597[/C][C]0.0548053[/C][C]0.0274027[/C][/ROW]
[ROW][C]78[/C][C]0.971134[/C][C]0.0577326[/C][C]0.0288663[/C][/ROW]
[ROW][C]79[/C][C]0.963654[/C][C]0.0726913[/C][C]0.0363457[/C][/ROW]
[ROW][C]80[/C][C]0.957157[/C][C]0.0856863[/C][C]0.0428431[/C][/ROW]
[ROW][C]81[/C][C]0.949341[/C][C]0.101318[/C][C]0.0506589[/C][/ROW]
[ROW][C]82[/C][C]0.951152[/C][C]0.0976968[/C][C]0.0488484[/C][/ROW]
[ROW][C]83[/C][C]0.94177[/C][C]0.116461[/C][C]0.0582305[/C][/ROW]
[ROW][C]84[/C][C]0.929027[/C][C]0.141946[/C][C]0.0709732[/C][/ROW]
[ROW][C]85[/C][C]0.950784[/C][C]0.0984311[/C][C]0.0492156[/C][/ROW]
[ROW][C]86[/C][C]0.940057[/C][C]0.119885[/C][C]0.0599426[/C][/ROW]
[ROW][C]87[/C][C]0.92951[/C][C]0.140981[/C][C]0.0704903[/C][/ROW]
[ROW][C]88[/C][C]0.916591[/C][C]0.166817[/C][C]0.0834086[/C][/ROW]
[ROW][C]89[/C][C]0.940323[/C][C]0.119354[/C][C]0.0596771[/C][/ROW]
[ROW][C]90[/C][C]0.928654[/C][C]0.142692[/C][C]0.0713459[/C][/ROW]
[ROW][C]91[/C][C]0.944732[/C][C]0.110536[/C][C]0.0552681[/C][/ROW]
[ROW][C]92[/C][C]0.933402[/C][C]0.133195[/C][C]0.0665977[/C][/ROW]
[ROW][C]93[/C][C]0.929295[/C][C]0.14141[/C][C]0.070705[/C][/ROW]
[ROW][C]94[/C][C]0.941882[/C][C]0.116237[/C][C]0.0581185[/C][/ROW]
[ROW][C]95[/C][C]0.933155[/C][C]0.133689[/C][C]0.0668446[/C][/ROW]
[ROW][C]96[/C][C]0.919218[/C][C]0.161563[/C][C]0.0807815[/C][/ROW]
[ROW][C]97[/C][C]0.931778[/C][C]0.136444[/C][C]0.0682218[/C][/ROW]
[ROW][C]98[/C][C]0.92077[/C][C]0.158459[/C][C]0.0792296[/C][/ROW]
[ROW][C]99[/C][C]0.921113[/C][C]0.157774[/C][C]0.0788872[/C][/ROW]
[ROW][C]100[/C][C]0.905749[/C][C]0.188502[/C][C]0.094251[/C][/ROW]
[ROW][C]101[/C][C]0.893123[/C][C]0.213753[/C][C]0.106877[/C][/ROW]
[ROW][C]102[/C][C]0.906326[/C][C]0.187347[/C][C]0.0936737[/C][/ROW]
[ROW][C]103[/C][C]0.905248[/C][C]0.189505[/C][C]0.0947525[/C][/ROW]
[ROW][C]104[/C][C]0.892069[/C][C]0.215862[/C][C]0.107931[/C][/ROW]
[ROW][C]105[/C][C]0.897471[/C][C]0.205058[/C][C]0.102529[/C][/ROW]
[ROW][C]106[/C][C]0.906751[/C][C]0.186498[/C][C]0.0932491[/C][/ROW]
[ROW][C]107[/C][C]0.895428[/C][C]0.209144[/C][C]0.104572[/C][/ROW]
[ROW][C]108[/C][C]0.899052[/C][C]0.201896[/C][C]0.100948[/C][/ROW]
[ROW][C]109[/C][C]0.881639[/C][C]0.236722[/C][C]0.118361[/C][/ROW]
[ROW][C]110[/C][C]0.86841[/C][C]0.26318[/C][C]0.13159[/C][/ROW]
[ROW][C]111[/C][C]0.845693[/C][C]0.308613[/C][C]0.154307[/C][/ROW]
[ROW][C]112[/C][C]0.834659[/C][C]0.330683[/C][C]0.165341[/C][/ROW]
[ROW][C]113[/C][C]0.808739[/C][C]0.382522[/C][C]0.191261[/C][/ROW]
[ROW][C]114[/C][C]0.789308[/C][C]0.421384[/C][C]0.210692[/C][/ROW]
[ROW][C]115[/C][C]0.77973[/C][C]0.44054[/C][C]0.22027[/C][/ROW]
[ROW][C]116[/C][C]0.752673[/C][C]0.494654[/C][C]0.247327[/C][/ROW]
[ROW][C]117[/C][C]0.739447[/C][C]0.521106[/C][C]0.260553[/C][/ROW]
[ROW][C]118[/C][C]0.71116[/C][C]0.57768[/C][C]0.28884[/C][/ROW]
[ROW][C]119[/C][C]0.856731[/C][C]0.286538[/C][C]0.143269[/C][/ROW]
[ROW][C]120[/C][C]0.865609[/C][C]0.268781[/C][C]0.134391[/C][/ROW]
[ROW][C]121[/C][C]0.896441[/C][C]0.207119[/C][C]0.103559[/C][/ROW]
[ROW][C]122[/C][C]0.885931[/C][C]0.228138[/C][C]0.114069[/C][/ROW]
[ROW][C]123[/C][C]0.869616[/C][C]0.260767[/C][C]0.130384[/C][/ROW]
[ROW][C]124[/C][C]0.846727[/C][C]0.306545[/C][C]0.153273[/C][/ROW]
[ROW][C]125[/C][C]0.871082[/C][C]0.257836[/C][C]0.128918[/C][/ROW]
[ROW][C]126[/C][C]0.908035[/C][C]0.18393[/C][C]0.0919649[/C][/ROW]
[ROW][C]127[/C][C]0.909658[/C][C]0.180684[/C][C]0.0903422[/C][/ROW]
[ROW][C]128[/C][C]0.950081[/C][C]0.0998375[/C][C]0.0499187[/C][/ROW]
[ROW][C]129[/C][C]0.944774[/C][C]0.110452[/C][C]0.055226[/C][/ROW]
[ROW][C]130[/C][C]0.944095[/C][C]0.11181[/C][C]0.0559052[/C][/ROW]
[ROW][C]131[/C][C]0.932803[/C][C]0.134393[/C][C]0.0671967[/C][/ROW]
[ROW][C]132[/C][C]0.91789[/C][C]0.164219[/C][C]0.0821097[/C][/ROW]
[ROW][C]133[/C][C]0.934624[/C][C]0.130752[/C][C]0.0653758[/C][/ROW]
[ROW][C]134[/C][C]0.925486[/C][C]0.149027[/C][C]0.0745136[/C][/ROW]
[ROW][C]135[/C][C]0.949158[/C][C]0.101683[/C][C]0.0508416[/C][/ROW]
[ROW][C]136[/C][C]0.93915[/C][C]0.1217[/C][C]0.06085[/C][/ROW]
[ROW][C]137[/C][C]0.928251[/C][C]0.143497[/C][C]0.0717487[/C][/ROW]
[ROW][C]138[/C][C]0.923047[/C][C]0.153907[/C][C]0.0769534[/C][/ROW]
[ROW][C]139[/C][C]0.907153[/C][C]0.185694[/C][C]0.092847[/C][/ROW]
[ROW][C]140[/C][C]0.893145[/C][C]0.21371[/C][C]0.106855[/C][/ROW]
[ROW][C]141[/C][C]0.872941[/C][C]0.254117[/C][C]0.127059[/C][/ROW]
[ROW][C]142[/C][C]0.957879[/C][C]0.084243[/C][C]0.0421215[/C][/ROW]
[ROW][C]143[/C][C]0.947402[/C][C]0.105195[/C][C]0.0525977[/C][/ROW]
[ROW][C]144[/C][C]0.948763[/C][C]0.102475[/C][C]0.0512374[/C][/ROW]
[ROW][C]145[/C][C]0.94732[/C][C]0.105361[/C][C]0.0526803[/C][/ROW]
[ROW][C]146[/C][C]0.948662[/C][C]0.102677[/C][C]0.0513385[/C][/ROW]
[ROW][C]147[/C][C]0.956523[/C][C]0.0869536[/C][C]0.0434768[/C][/ROW]
[ROW][C]148[/C][C]0.965027[/C][C]0.0699451[/C][C]0.0349725[/C][/ROW]
[ROW][C]149[/C][C]0.957569[/C][C]0.0848628[/C][C]0.0424314[/C][/ROW]
[ROW][C]150[/C][C]0.991806[/C][C]0.0163877[/C][C]0.00819385[/C][/ROW]
[ROW][C]151[/C][C]0.988966[/C][C]0.0220681[/C][C]0.011034[/C][/ROW]
[ROW][C]152[/C][C]0.993528[/C][C]0.0129445[/C][C]0.00647224[/C][/ROW]
[ROW][C]153[/C][C]0.991832[/C][C]0.0163368[/C][C]0.0081684[/C][/ROW]
[ROW][C]154[/C][C]0.990407[/C][C]0.0191859[/C][C]0.00959293[/C][/ROW]
[ROW][C]155[/C][C]0.987682[/C][C]0.0246361[/C][C]0.012318[/C][/ROW]
[ROW][C]156[/C][C]0.983272[/C][C]0.0334561[/C][C]0.0167281[/C][/ROW]
[ROW][C]157[/C][C]0.97791[/C][C]0.0441801[/C][C]0.02209[/C][/ROW]
[ROW][C]158[/C][C]0.981922[/C][C]0.0361562[/C][C]0.0180781[/C][/ROW]
[ROW][C]159[/C][C]0.975591[/C][C]0.0488177[/C][C]0.0244089[/C][/ROW]
[ROW][C]160[/C][C]0.967442[/C][C]0.0651166[/C][C]0.0325583[/C][/ROW]
[ROW][C]161[/C][C]0.959113[/C][C]0.0817746[/C][C]0.0408873[/C][/ROW]
[ROW][C]162[/C][C]0.949011[/C][C]0.101977[/C][C]0.0509885[/C][/ROW]
[ROW][C]163[/C][C]0.938523[/C][C]0.122955[/C][C]0.0614774[/C][/ROW]
[ROW][C]164[/C][C]0.951231[/C][C]0.0975384[/C][C]0.0487692[/C][/ROW]
[ROW][C]165[/C][C]0.953536[/C][C]0.0929282[/C][C]0.0464641[/C][/ROW]
[ROW][C]166[/C][C]0.942879[/C][C]0.114241[/C][C]0.0571207[/C][/ROW]
[ROW][C]167[/C][C]0.925674[/C][C]0.148653[/C][C]0.0743263[/C][/ROW]
[ROW][C]168[/C][C]0.921834[/C][C]0.156332[/C][C]0.0781662[/C][/ROW]
[ROW][C]169[/C][C]0.919838[/C][C]0.160323[/C][C]0.0801617[/C][/ROW]
[ROW][C]170[/C][C]0.949379[/C][C]0.101243[/C][C]0.0506213[/C][/ROW]
[ROW][C]171[/C][C]0.942595[/C][C]0.11481[/C][C]0.0574048[/C][/ROW]
[ROW][C]172[/C][C]0.960597[/C][C]0.0788052[/C][C]0.0394026[/C][/ROW]
[ROW][C]173[/C][C]0.963359[/C][C]0.0732812[/C][C]0.0366406[/C][/ROW]
[ROW][C]174[/C][C]0.952464[/C][C]0.0950723[/C][C]0.0475362[/C][/ROW]
[ROW][C]175[/C][C]0.938499[/C][C]0.123001[/C][C]0.0615007[/C][/ROW]
[ROW][C]176[/C][C]0.933911[/C][C]0.132178[/C][C]0.0660892[/C][/ROW]
[ROW][C]177[/C][C]0.9395[/C][C]0.120999[/C][C]0.0604996[/C][/ROW]
[ROW][C]178[/C][C]0.952016[/C][C]0.0959676[/C][C]0.0479838[/C][/ROW]
[ROW][C]179[/C][C]0.946031[/C][C]0.107939[/C][C]0.0539695[/C][/ROW]
[ROW][C]180[/C][C]0.938678[/C][C]0.122643[/C][C]0.0613216[/C][/ROW]
[ROW][C]181[/C][C]0.950909[/C][C]0.0981827[/C][C]0.0490913[/C][/ROW]
[ROW][C]182[/C][C]0.950932[/C][C]0.0981358[/C][C]0.0490679[/C][/ROW]
[ROW][C]183[/C][C]0.932941[/C][C]0.134117[/C][C]0.0670587[/C][/ROW]
[ROW][C]184[/C][C]0.984178[/C][C]0.0316436[/C][C]0.0158218[/C][/ROW]
[ROW][C]185[/C][C]0.97505[/C][C]0.0499009[/C][C]0.0249504[/C][/ROW]
[ROW][C]186[/C][C]0.961666[/C][C]0.0766673[/C][C]0.0383336[/C][/ROW]
[ROW][C]187[/C][C]0.943735[/C][C]0.11253[/C][C]0.056265[/C][/ROW]
[ROW][C]188[/C][C]0.953989[/C][C]0.0920218[/C][C]0.0460109[/C][/ROW]
[ROW][C]189[/C][C]0.934243[/C][C]0.131514[/C][C]0.0657568[/C][/ROW]
[ROW][C]190[/C][C]0.903585[/C][C]0.19283[/C][C]0.0964149[/C][/ROW]
[ROW][C]191[/C][C]0.86746[/C][C]0.26508[/C][C]0.13254[/C][/ROW]
[ROW][C]192[/C][C]0.839521[/C][C]0.320958[/C][C]0.160479[/C][/ROW]
[ROW][C]193[/C][C]0.79894[/C][C]0.402119[/C][C]0.20106[/C][/ROW]
[ROW][C]194[/C][C]0.730855[/C][C]0.538289[/C][C]0.269145[/C][/ROW]
[ROW][C]195[/C][C]0.648221[/C][C]0.703559[/C][C]0.351779[/C][/ROW]
[ROW][C]196[/C][C]0.823264[/C][C]0.353473[/C][C]0.176736[/C][/ROW]
[ROW][C]197[/C][C]0.7687[/C][C]0.462601[/C][C]0.2313[/C][/ROW]
[ROW][C]198[/C][C]0.670691[/C][C]0.658619[/C][C]0.329309[/C][/ROW]
[ROW][C]199[/C][C]0.557351[/C][C]0.885298[/C][C]0.442649[/C][/ROW]
[ROW][C]200[/C][C]0.468557[/C][C]0.937115[/C][C]0.531443[/C][/ROW]
[ROW][C]201[/C][C]0.382781[/C][C]0.765562[/C][C]0.617219[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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
100.8295920.3408160.170408
110.7813850.4372310.218615
120.7775850.4448310.222415
130.6755380.6489230.324462
140.5977590.8044820.402241
150.494980.9899590.50502
160.6944370.6111270.305563
170.8142240.3715520.185776
180.7512660.4974680.248734
190.785030.429940.21497
200.7906940.4186130.209306
210.7446240.5107520.255376
220.9259490.1481020.0740511
230.9274990.1450020.0725011
240.9030670.1938670.0969334
250.9397080.1205840.0602922
260.9246780.1506430.0753217
270.9044470.1911060.0955528
280.880380.239240.11962
290.8843320.2313360.115668
300.8545270.2909470.145473
310.8329870.3340260.167013
320.9579040.08419220.0420961
330.9463720.1072550.0536275
340.9322430.1355130.0677567
350.9142060.1715870.0857936
360.892250.21550.10775
370.9064910.1870170.0935086
380.9073910.1852180.0926089
390.9500330.0999350.0499675
400.9356710.1286590.0643293
410.9366410.1267190.0633593
420.9405990.1188020.0594009
430.9242070.1515860.0757932
440.9249110.1501780.0750892
450.9073410.1853180.0926591
460.8871430.2257140.112857
470.8665740.2668530.133426
480.8497420.3005150.150258
490.8511050.2977910.148895
500.8245370.3509260.175463
510.7923290.4153430.207671
520.9455070.1089850.0544925
530.9321580.1356840.0678418
540.9175280.1649430.0824717
550.9039480.1921040.0960519
560.9021870.1956270.0978135
570.8884830.2230340.111517
580.8780470.2439060.121953
590.865340.2693210.13466
600.8783840.2432320.121616
610.8556680.2886630.144332
620.8294380.3411240.170562
630.8610190.2779610.138981
640.8893440.2213120.110656
650.8904840.2190310.109516
660.8793810.2412380.120619
670.9305460.1389080.0694542
680.9183080.1633840.081692
690.9099490.1801030.0900514
700.8947830.2104340.105217
710.8747960.2504070.125204
720.9354710.1290590.0645294
730.9581590.08368270.0418413
740.9600350.07992970.0399649
750.9509860.09802760.0490138
760.9669190.0661610.0330805
770.9725970.05480530.0274027
780.9711340.05773260.0288663
790.9636540.07269130.0363457
800.9571570.08568630.0428431
810.9493410.1013180.0506589
820.9511520.09769680.0488484
830.941770.1164610.0582305
840.9290270.1419460.0709732
850.9507840.09843110.0492156
860.9400570.1198850.0599426
870.929510.1409810.0704903
880.9165910.1668170.0834086
890.9403230.1193540.0596771
900.9286540.1426920.0713459
910.9447320.1105360.0552681
920.9334020.1331950.0665977
930.9292950.141410.070705
940.9418820.1162370.0581185
950.9331550.1336890.0668446
960.9192180.1615630.0807815
970.9317780.1364440.0682218
980.920770.1584590.0792296
990.9211130.1577740.0788872
1000.9057490.1885020.094251
1010.8931230.2137530.106877
1020.9063260.1873470.0936737
1030.9052480.1895050.0947525
1040.8920690.2158620.107931
1050.8974710.2050580.102529
1060.9067510.1864980.0932491
1070.8954280.2091440.104572
1080.8990520.2018960.100948
1090.8816390.2367220.118361
1100.868410.263180.13159
1110.8456930.3086130.154307
1120.8346590.3306830.165341
1130.8087390.3825220.191261
1140.7893080.4213840.210692
1150.779730.440540.22027
1160.7526730.4946540.247327
1170.7394470.5211060.260553
1180.711160.577680.28884
1190.8567310.2865380.143269
1200.8656090.2687810.134391
1210.8964410.2071190.103559
1220.8859310.2281380.114069
1230.8696160.2607670.130384
1240.8467270.3065450.153273
1250.8710820.2578360.128918
1260.9080350.183930.0919649
1270.9096580.1806840.0903422
1280.9500810.09983750.0499187
1290.9447740.1104520.055226
1300.9440950.111810.0559052
1310.9328030.1343930.0671967
1320.917890.1642190.0821097
1330.9346240.1307520.0653758
1340.9254860.1490270.0745136
1350.9491580.1016830.0508416
1360.939150.12170.06085
1370.9282510.1434970.0717487
1380.9230470.1539070.0769534
1390.9071530.1856940.092847
1400.8931450.213710.106855
1410.8729410.2541170.127059
1420.9578790.0842430.0421215
1430.9474020.1051950.0525977
1440.9487630.1024750.0512374
1450.947320.1053610.0526803
1460.9486620.1026770.0513385
1470.9565230.08695360.0434768
1480.9650270.06994510.0349725
1490.9575690.08486280.0424314
1500.9918060.01638770.00819385
1510.9889660.02206810.011034
1520.9935280.01294450.00647224
1530.9918320.01633680.0081684
1540.9904070.01918590.00959293
1550.9876820.02463610.012318
1560.9832720.03345610.0167281
1570.977910.04418010.02209
1580.9819220.03615620.0180781
1590.9755910.04881770.0244089
1600.9674420.06511660.0325583
1610.9591130.08177460.0408873
1620.9490110.1019770.0509885
1630.9385230.1229550.0614774
1640.9512310.09753840.0487692
1650.9535360.09292820.0464641
1660.9428790.1142410.0571207
1670.9256740.1486530.0743263
1680.9218340.1563320.0781662
1690.9198380.1603230.0801617
1700.9493790.1012430.0506213
1710.9425950.114810.0574048
1720.9605970.07880520.0394026
1730.9633590.07328120.0366406
1740.9524640.09507230.0475362
1750.9384990.1230010.0615007
1760.9339110.1321780.0660892
1770.93950.1209990.0604996
1780.9520160.09596760.0479838
1790.9460310.1079390.0539695
1800.9386780.1226430.0613216
1810.9509090.09818270.0490913
1820.9509320.09813580.0490679
1830.9329410.1341170.0670587
1840.9841780.03164360.0158218
1850.975050.04990090.0249504
1860.9616660.07666730.0383336
1870.9437350.112530.056265
1880.9539890.09202180.0460109
1890.9342430.1315140.0657568
1900.9035850.192830.0964149
1910.867460.265080.13254
1920.8395210.3209580.160479
1930.798940.4021190.20106
1940.7308550.5382890.269145
1950.6482210.7035590.351779
1960.8232640.3534730.176736
1970.76870.4626010.2313
1980.6706910.6586190.329309
1990.5573510.8852980.442649
2000.4685570.9371150.531443
2010.3827810.7655620.617219






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level120.0625NOK
10% type I error level410.213542NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 12 & 0.0625 & NOK \tabularnewline
10% type I error level & 41 & 0.213542 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=270293&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]12[/C][C]0.0625[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]41[/C][C]0.213542[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=270293&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=270293&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 level00OK
5% type I error level120.0625NOK
10% type I error level410.213542NOK


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 = blue ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}