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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 computationTue, 11 Nov 2014 09:35:21 +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/Nov/11/t1415698603i7b17vyjovztmtq.htm/, Retrieved Fri, 17 May 2024 02:04:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=253522, Retrieved Fri, 17 May 2024 02:04:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Competence to learn] [2010-11-17 07:43:53] [b98453cac15ba1066b407e146608df68]
- RMPD    [Multiple Regression] [] [2014-11-11 09:35:21] [4cfc068a520cd237806cfcade835365e] [Current]
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Dataset

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

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'Herman Ole Andreas Wold' @ wold.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 & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&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]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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'Herman Ole Andreas Wold' @ wold.wessa.net






Multiple Linear Regression - Estimated Regression Equation
Sport1[t] = + 62.6643 -0.703375Depression[t] + 0.553319Happiness[t] + 0.182263Software[t] + 0.0816352Separate[t] + 0.152122Connected[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
Sport1[t] =  +  62.6643 -0.703375Depression[t] +  0.553319Happiness[t] +  0.182263Software[t] +  0.0816352Separate[t] +  0.152122Connected[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]Sport1[t] =  +  62.6643 -0.703375Depression[t] +  0.553319Happiness[t] +  0.182263Software[t] +  0.0816352Separate[t] +  0.152122Connected[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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
Sport1[t] = + 62.6643 -0.703375Depression[t] + 0.553319Happiness[t] + 0.182263Software[t] + 0.0816352Separate[t] + 0.152122Connected[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)62.66439.050176.9243.47446e-111.73723e-11
Depression-0.7033750.21536-3.2660.001238360.000619179
Happiness0.5533190.2990631.850.06543150.0327158
Software0.1822630.2689360.67770.4985570.249279
Separate0.08163520.1851260.4410.6596030.329801
Connected0.1521220.1798070.8460.398320.19916

\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) & 62.6643 & 9.05017 & 6.924 & 3.47446e-11 & 1.73723e-11 \tabularnewline
Depression & -0.703375 & 0.21536 & -3.266 & 0.00123836 & 0.000619179 \tabularnewline
Happiness & 0.553319 & 0.299063 & 1.85 & 0.0654315 & 0.0327158 \tabularnewline
Software & 0.182263 & 0.268936 & 0.6777 & 0.498557 & 0.249279 \tabularnewline
Separate & 0.0816352 & 0.185126 & 0.441 & 0.659603 & 0.329801 \tabularnewline
Connected & 0.152122 & 0.179807 & 0.846 & 0.39832 & 0.19916 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&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]62.6643[/C][C]9.05017[/C][C]6.924[/C][C]3.47446e-11[/C][C]1.73723e-11[/C][/ROW]
[ROW][C]Depression[/C][C]-0.703375[/C][C]0.21536[/C][C]-3.266[/C][C]0.00123836[/C][C]0.000619179[/C][/ROW]
[ROW][C]Happiness[/C][C]0.553319[/C][C]0.299063[/C][C]1.85[/C][C]0.0654315[/C][C]0.0327158[/C][/ROW]
[ROW][C]Software[/C][C]0.182263[/C][C]0.268936[/C][C]0.6777[/C][C]0.498557[/C][C]0.249279[/C][/ROW]
[ROW][C]Separate[/C][C]0.0816352[/C][C]0.185126[/C][C]0.441[/C][C]0.659603[/C][C]0.329801[/C][/ROW]
[ROW][C]Connected[/C][C]0.152122[/C][C]0.179807[/C][C]0.846[/C][C]0.39832[/C][C]0.19916[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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)62.66439.050176.9243.47446e-111.73723e-11
Depression-0.7033750.21536-3.2660.001238360.000619179
Happiness0.5533190.2990631.850.06543150.0327158
Software0.1822630.2689360.67770.4985570.249279
Separate0.08163520.1851260.4410.6596030.329801
Connected0.1521220.1798070.8460.398320.19916






Multiple Linear Regression - Regression Statistics
Multiple R0.360467
R-squared0.129936
Adjusted R-squared0.113075
F-TEST (value)7.706
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value9.00141e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.79023
Sum Squared Residuals24728.9

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.360467 \tabularnewline
R-squared & 0.129936 \tabularnewline
Adjusted R-squared & 0.113075 \tabularnewline
F-TEST (value) & 7.706 \tabularnewline
F-TEST (DF numerator) & 5 \tabularnewline
F-TEST (DF denominator) & 258 \tabularnewline
p-value & 9.00141e-07 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 9.79023 \tabularnewline
Sum Squared Residuals & 24728.9 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.360467[/C][/ROW]
[ROW][C]R-squared[/C][C]0.129936[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.113075[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]7.706[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]5[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]258[/C][/ROW]
[ROW][C]p-value[/C][C]9.00141e-07[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]9.79023[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]24728.9[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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 R0.360467
R-squared0.129936
Adjusted R-squared0.113075
F-TEST (value)7.706
F-TEST (DF numerator)5
F-TEST (DF denominator)258
p-value9.00141e-07
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation9.79023
Sum Squared Residuals24728.9






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15373.4965-20.4965
28375.43687.56316
36669.0583-3.05835
46769.3669-2.3669
57667.30858.69145
67873.69784.30219
75365.5871-12.5871
88073.33636.66371
97474.4511-0.451064
107672.19123.80882
117975.17093.82912
125477.9895-23.9895
136768.4718-1.47184
145472.7099-18.7099
158776.364710.6353
165870.3125-12.3125
177570.47484.52519
188875.403512.5965
196474.4168-10.4168
205772.0409-15.0409
216675.5087-9.50869
226868.3371-0.337139
235473.3745-19.3745
245670.274-14.274
258675.065810.9342
268072.53257.46751
277673.93652.06352
286970.4523-1.4523
297871.01796.98207
306769.2956-2.29562
318074.62065.37939
325467.4845-13.4845
337175.0188-4.01876
348473.606710.3933
357471.07522.9248
367174.7281-3.72806
376362.15920.84078
387172.881-1.88104
397673.80182.19822
406972.6645-3.66451
417474.6971-0.69713
427571.72343.27663
435477.0173-23.0173
445269.2977-17.2977
456973.116-4.11596
466870.2798-2.27979
476575.9675-10.9675
487573.02741.97257
497472.10351.89653
507572.70042.29961
517275.0053-3.00533
526769.7031-2.70306
536365.839-2.83903
546270.1005-8.10053
556369.9585-6.9585
567670.34445.65558
577473.2690.731012
586774.008-7.00795
597372.84260.157398
607068.6761.32405
615361.1486-8.14859
627772.16034.83972
638070.89139.10868
645270.1414-18.1414
655471.7102-17.7102
668071.17458.82549
676667.6787-1.67869
687369.63633.36372
696373.2055-10.2055
706971.6487-2.64871
716771.4444-4.44445
725470.7895-16.7895
738172.72788.27224
746975.6096-6.60964
758471.683712.3163
768065.962114.0379
777073.9452-3.94523
786967.60781.39225
797770.79746.20258
805473.5468-19.5468
817973.3735.62704
827175.1656-4.16559
837373.5865-0.586484
847272.1719-0.171929
857770.64026.35981
867572.42492.57506
876971.953-2.95299
885468.5178-14.5178
897060.96449.03562
907372.22180.778185
915470.1294-16.1294
927772.67864.32137
938269.200912.7991
948070.1139.88704
958074.47455.52552
966968.90520.094758
977872.16895.83108
988174.92486.07519
997673.55972.44031
1007676.3081-0.308106
1017368.54074.45928
1028574.307710.6923
1036670.1722-4.17222
1047969.91879.08127
1056865.16442.83564
1067674.60531.39475
1077171.318-0.317964
1085467.9853-13.9853
1094662.5622-16.5622
1108570.643214.3568
1117468.16165.83844
1128872.340115.6599
1133869.4269-31.4269
1147674.41021.58977
1158675.093910.9061
1165471.2183-17.2183
1176771.1625-4.1625
1186973.9625-4.96249
1199070.766719.2333
1205468.7989-14.7989
1217669.85286.14718
1228974.378514.6215
1237676.6194-0.619366
1247373.6034-0.603411
1257972.2646.73604
1269076.811413.1886
1277476.919-2.91895
1288175.03945.96055
1297271.84330.156716
1307171.5048-0.504768
1316662.45333.54674
1327774.49382.50623
1336568.9747-3.97465
1347473.44130.558659
1358571.092613.9074
1365460.2689-6.26889
1376370.5977-7.59774
1385466.7403-12.7403
1396472.7849-8.78488
1406970.6303-1.63028
1415473.0319-19.0319
1428470.894613.1054
1438672.125113.8749
1447771.12185.87818
1458973.853915.1461
1467672.51833.48167
1476070.2093-10.2093
1487571.15273.8473
1497363.8579.14304
1508573.317111.6829
1517969.67919.32093
1527175.1016-4.10163
1537270.46521.5348
1546964.29434.70567
1557866.205511.7945
1565470.1294-16.1294
1576969.5455-0.545453
1588175.03945.96055
1598473.316410.6836
1608466.071517.9285
1616968.17250.827482
1626659.36896.63112
1638168.859912.1401
1648268.476113.5239
1657265.71526.28476
1665460.1312-6.13123
1677871.23276.76727
1687467.646.35996
1698266.851615.1484
1707364.29838.70168
1715563.7538-8.75378
1727273.7609-1.7609
1737870.12057.87952
1745965.6283-6.62828
1757272.3228-0.322812
1767873.25714.74295
1776866.17071.8293
1786965.29643.70359
1796773.5527-6.55271
1807469.3454.65499
1815473.276-19.276
1826772.3939-5.39393
1837073.6155-3.6155
1848073.95716.04292
1858971.599917.4001
1867666.48729.5128
1877470.82033.17965
1888772.262814.7372
1895467.8312-13.8312
1906162.698-1.69797
1913869.6008-31.6008
1927574.61020.389836
1936968.52210.477932
1946267.8464-5.84642
1957270.41961.58035
1967071.7814-1.78138
1977966.389812.6102
1988770.087816.9122
1996263.081-1.08103
2007769.46827.53182
2016964.88664.11338
2026970.4462-1.44615
2037573.67681.32325
2045469.9818-15.9818
2057272.4806-0.480638
2067471.93612.06393
2078572.319912.6801
2085271.417-19.417
2097070.0031-0.00313084
2108472.765611.2344
2116465.74-1.74001
2128475.79638.20367
2138766.146620.8534
2147967.687711.3123
2156767.162-0.162042
2166569.9431-4.94309
2178574.215710.7843
2188372.501210.4988
2196161.4083-0.408282
2208271.964110.0359
2217670.51565.48435
2225873.619-15.619
2237266.05965.94043
2247273.6021-1.60214
2253862.6246-24.6246
2267873.3844.61604
2275474.5909-20.5909
2286370.2996-7.29957
2296660.41975.58034
2307069.27660.723368
2317170.6850.315
2326766.33490.665084
2335873.3707-15.3707
2347269.38272.61733
2357274.7941-2.79408
2367068.73321.26678
2377666.51799.48215
2385070.5812-20.5812
2397269.58972.4103
2407269.66372.33633
2418870.448117.5519
2425363.9131-10.9131
2435865.1421-7.14207
2446667.1619-1.16189
2458271.098610.9014
2466963.41015.58986
2476868.6723-0.672276
2484463.9622-19.9622
2495660.1927-4.19271
2505364.5177-11.5177
2517069.8840.115993
2527866.808211.1918
2537171.4658-0.46584
2547269.98622.01376
2556867.49180.508191
2566768.6245-1.62446
2577563.405211.5948
2586263.7696-1.76959
2596770.8224-3.82241
2608370.890612.1094
2616470.5315-6.53146
2626872.985-4.98498
2636261.36280.637177
2647270.63441.36555

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 53 & 73.4965 & -20.4965 \tabularnewline
2 & 83 & 75.4368 & 7.56316 \tabularnewline
3 & 66 & 69.0583 & -3.05835 \tabularnewline
4 & 67 & 69.3669 & -2.3669 \tabularnewline
5 & 76 & 67.3085 & 8.69145 \tabularnewline
6 & 78 & 73.6978 & 4.30219 \tabularnewline
7 & 53 & 65.5871 & -12.5871 \tabularnewline
8 & 80 & 73.3363 & 6.66371 \tabularnewline
9 & 74 & 74.4511 & -0.451064 \tabularnewline
10 & 76 & 72.1912 & 3.80882 \tabularnewline
11 & 79 & 75.1709 & 3.82912 \tabularnewline
12 & 54 & 77.9895 & -23.9895 \tabularnewline
13 & 67 & 68.4718 & -1.47184 \tabularnewline
14 & 54 & 72.7099 & -18.7099 \tabularnewline
15 & 87 & 76.3647 & 10.6353 \tabularnewline
16 & 58 & 70.3125 & -12.3125 \tabularnewline
17 & 75 & 70.4748 & 4.52519 \tabularnewline
18 & 88 & 75.4035 & 12.5965 \tabularnewline
19 & 64 & 74.4168 & -10.4168 \tabularnewline
20 & 57 & 72.0409 & -15.0409 \tabularnewline
21 & 66 & 75.5087 & -9.50869 \tabularnewline
22 & 68 & 68.3371 & -0.337139 \tabularnewline
23 & 54 & 73.3745 & -19.3745 \tabularnewline
24 & 56 & 70.274 & -14.274 \tabularnewline
25 & 86 & 75.0658 & 10.9342 \tabularnewline
26 & 80 & 72.5325 & 7.46751 \tabularnewline
27 & 76 & 73.9365 & 2.06352 \tabularnewline
28 & 69 & 70.4523 & -1.4523 \tabularnewline
29 & 78 & 71.0179 & 6.98207 \tabularnewline
30 & 67 & 69.2956 & -2.29562 \tabularnewline
31 & 80 & 74.6206 & 5.37939 \tabularnewline
32 & 54 & 67.4845 & -13.4845 \tabularnewline
33 & 71 & 75.0188 & -4.01876 \tabularnewline
34 & 84 & 73.6067 & 10.3933 \tabularnewline
35 & 74 & 71.0752 & 2.9248 \tabularnewline
36 & 71 & 74.7281 & -3.72806 \tabularnewline
37 & 63 & 62.1592 & 0.84078 \tabularnewline
38 & 71 & 72.881 & -1.88104 \tabularnewline
39 & 76 & 73.8018 & 2.19822 \tabularnewline
40 & 69 & 72.6645 & -3.66451 \tabularnewline
41 & 74 & 74.6971 & -0.69713 \tabularnewline
42 & 75 & 71.7234 & 3.27663 \tabularnewline
43 & 54 & 77.0173 & -23.0173 \tabularnewline
44 & 52 & 69.2977 & -17.2977 \tabularnewline
45 & 69 & 73.116 & -4.11596 \tabularnewline
46 & 68 & 70.2798 & -2.27979 \tabularnewline
47 & 65 & 75.9675 & -10.9675 \tabularnewline
48 & 75 & 73.0274 & 1.97257 \tabularnewline
49 & 74 & 72.1035 & 1.89653 \tabularnewline
50 & 75 & 72.7004 & 2.29961 \tabularnewline
51 & 72 & 75.0053 & -3.00533 \tabularnewline
52 & 67 & 69.7031 & -2.70306 \tabularnewline
53 & 63 & 65.839 & -2.83903 \tabularnewline
54 & 62 & 70.1005 & -8.10053 \tabularnewline
55 & 63 & 69.9585 & -6.9585 \tabularnewline
56 & 76 & 70.3444 & 5.65558 \tabularnewline
57 & 74 & 73.269 & 0.731012 \tabularnewline
58 & 67 & 74.008 & -7.00795 \tabularnewline
59 & 73 & 72.8426 & 0.157398 \tabularnewline
60 & 70 & 68.676 & 1.32405 \tabularnewline
61 & 53 & 61.1486 & -8.14859 \tabularnewline
62 & 77 & 72.1603 & 4.83972 \tabularnewline
63 & 80 & 70.8913 & 9.10868 \tabularnewline
64 & 52 & 70.1414 & -18.1414 \tabularnewline
65 & 54 & 71.7102 & -17.7102 \tabularnewline
66 & 80 & 71.1745 & 8.82549 \tabularnewline
67 & 66 & 67.6787 & -1.67869 \tabularnewline
68 & 73 & 69.6363 & 3.36372 \tabularnewline
69 & 63 & 73.2055 & -10.2055 \tabularnewline
70 & 69 & 71.6487 & -2.64871 \tabularnewline
71 & 67 & 71.4444 & -4.44445 \tabularnewline
72 & 54 & 70.7895 & -16.7895 \tabularnewline
73 & 81 & 72.7278 & 8.27224 \tabularnewline
74 & 69 & 75.6096 & -6.60964 \tabularnewline
75 & 84 & 71.6837 & 12.3163 \tabularnewline
76 & 80 & 65.9621 & 14.0379 \tabularnewline
77 & 70 & 73.9452 & -3.94523 \tabularnewline
78 & 69 & 67.6078 & 1.39225 \tabularnewline
79 & 77 & 70.7974 & 6.20258 \tabularnewline
80 & 54 & 73.5468 & -19.5468 \tabularnewline
81 & 79 & 73.373 & 5.62704 \tabularnewline
82 & 71 & 75.1656 & -4.16559 \tabularnewline
83 & 73 & 73.5865 & -0.586484 \tabularnewline
84 & 72 & 72.1719 & -0.171929 \tabularnewline
85 & 77 & 70.6402 & 6.35981 \tabularnewline
86 & 75 & 72.4249 & 2.57506 \tabularnewline
87 & 69 & 71.953 & -2.95299 \tabularnewline
88 & 54 & 68.5178 & -14.5178 \tabularnewline
89 & 70 & 60.9644 & 9.03562 \tabularnewline
90 & 73 & 72.2218 & 0.778185 \tabularnewline
91 & 54 & 70.1294 & -16.1294 \tabularnewline
92 & 77 & 72.6786 & 4.32137 \tabularnewline
93 & 82 & 69.2009 & 12.7991 \tabularnewline
94 & 80 & 70.113 & 9.88704 \tabularnewline
95 & 80 & 74.4745 & 5.52552 \tabularnewline
96 & 69 & 68.9052 & 0.094758 \tabularnewline
97 & 78 & 72.1689 & 5.83108 \tabularnewline
98 & 81 & 74.9248 & 6.07519 \tabularnewline
99 & 76 & 73.5597 & 2.44031 \tabularnewline
100 & 76 & 76.3081 & -0.308106 \tabularnewline
101 & 73 & 68.5407 & 4.45928 \tabularnewline
102 & 85 & 74.3077 & 10.6923 \tabularnewline
103 & 66 & 70.1722 & -4.17222 \tabularnewline
104 & 79 & 69.9187 & 9.08127 \tabularnewline
105 & 68 & 65.1644 & 2.83564 \tabularnewline
106 & 76 & 74.6053 & 1.39475 \tabularnewline
107 & 71 & 71.318 & -0.317964 \tabularnewline
108 & 54 & 67.9853 & -13.9853 \tabularnewline
109 & 46 & 62.5622 & -16.5622 \tabularnewline
110 & 85 & 70.6432 & 14.3568 \tabularnewline
111 & 74 & 68.1616 & 5.83844 \tabularnewline
112 & 88 & 72.3401 & 15.6599 \tabularnewline
113 & 38 & 69.4269 & -31.4269 \tabularnewline
114 & 76 & 74.4102 & 1.58977 \tabularnewline
115 & 86 & 75.0939 & 10.9061 \tabularnewline
116 & 54 & 71.2183 & -17.2183 \tabularnewline
117 & 67 & 71.1625 & -4.1625 \tabularnewline
118 & 69 & 73.9625 & -4.96249 \tabularnewline
119 & 90 & 70.7667 & 19.2333 \tabularnewline
120 & 54 & 68.7989 & -14.7989 \tabularnewline
121 & 76 & 69.8528 & 6.14718 \tabularnewline
122 & 89 & 74.3785 & 14.6215 \tabularnewline
123 & 76 & 76.6194 & -0.619366 \tabularnewline
124 & 73 & 73.6034 & -0.603411 \tabularnewline
125 & 79 & 72.264 & 6.73604 \tabularnewline
126 & 90 & 76.8114 & 13.1886 \tabularnewline
127 & 74 & 76.919 & -2.91895 \tabularnewline
128 & 81 & 75.0394 & 5.96055 \tabularnewline
129 & 72 & 71.8433 & 0.156716 \tabularnewline
130 & 71 & 71.5048 & -0.504768 \tabularnewline
131 & 66 & 62.4533 & 3.54674 \tabularnewline
132 & 77 & 74.4938 & 2.50623 \tabularnewline
133 & 65 & 68.9747 & -3.97465 \tabularnewline
134 & 74 & 73.4413 & 0.558659 \tabularnewline
135 & 85 & 71.0926 & 13.9074 \tabularnewline
136 & 54 & 60.2689 & -6.26889 \tabularnewline
137 & 63 & 70.5977 & -7.59774 \tabularnewline
138 & 54 & 66.7403 & -12.7403 \tabularnewline
139 & 64 & 72.7849 & -8.78488 \tabularnewline
140 & 69 & 70.6303 & -1.63028 \tabularnewline
141 & 54 & 73.0319 & -19.0319 \tabularnewline
142 & 84 & 70.8946 & 13.1054 \tabularnewline
143 & 86 & 72.1251 & 13.8749 \tabularnewline
144 & 77 & 71.1218 & 5.87818 \tabularnewline
145 & 89 & 73.8539 & 15.1461 \tabularnewline
146 & 76 & 72.5183 & 3.48167 \tabularnewline
147 & 60 & 70.2093 & -10.2093 \tabularnewline
148 & 75 & 71.1527 & 3.8473 \tabularnewline
149 & 73 & 63.857 & 9.14304 \tabularnewline
150 & 85 & 73.3171 & 11.6829 \tabularnewline
151 & 79 & 69.6791 & 9.32093 \tabularnewline
152 & 71 & 75.1016 & -4.10163 \tabularnewline
153 & 72 & 70.4652 & 1.5348 \tabularnewline
154 & 69 & 64.2943 & 4.70567 \tabularnewline
155 & 78 & 66.2055 & 11.7945 \tabularnewline
156 & 54 & 70.1294 & -16.1294 \tabularnewline
157 & 69 & 69.5455 & -0.545453 \tabularnewline
158 & 81 & 75.0394 & 5.96055 \tabularnewline
159 & 84 & 73.3164 & 10.6836 \tabularnewline
160 & 84 & 66.0715 & 17.9285 \tabularnewline
161 & 69 & 68.1725 & 0.827482 \tabularnewline
162 & 66 & 59.3689 & 6.63112 \tabularnewline
163 & 81 & 68.8599 & 12.1401 \tabularnewline
164 & 82 & 68.4761 & 13.5239 \tabularnewline
165 & 72 & 65.7152 & 6.28476 \tabularnewline
166 & 54 & 60.1312 & -6.13123 \tabularnewline
167 & 78 & 71.2327 & 6.76727 \tabularnewline
168 & 74 & 67.64 & 6.35996 \tabularnewline
169 & 82 & 66.8516 & 15.1484 \tabularnewline
170 & 73 & 64.2983 & 8.70168 \tabularnewline
171 & 55 & 63.7538 & -8.75378 \tabularnewline
172 & 72 & 73.7609 & -1.7609 \tabularnewline
173 & 78 & 70.1205 & 7.87952 \tabularnewline
174 & 59 & 65.6283 & -6.62828 \tabularnewline
175 & 72 & 72.3228 & -0.322812 \tabularnewline
176 & 78 & 73.2571 & 4.74295 \tabularnewline
177 & 68 & 66.1707 & 1.8293 \tabularnewline
178 & 69 & 65.2964 & 3.70359 \tabularnewline
179 & 67 & 73.5527 & -6.55271 \tabularnewline
180 & 74 & 69.345 & 4.65499 \tabularnewline
181 & 54 & 73.276 & -19.276 \tabularnewline
182 & 67 & 72.3939 & -5.39393 \tabularnewline
183 & 70 & 73.6155 & -3.6155 \tabularnewline
184 & 80 & 73.9571 & 6.04292 \tabularnewline
185 & 89 & 71.5999 & 17.4001 \tabularnewline
186 & 76 & 66.4872 & 9.5128 \tabularnewline
187 & 74 & 70.8203 & 3.17965 \tabularnewline
188 & 87 & 72.2628 & 14.7372 \tabularnewline
189 & 54 & 67.8312 & -13.8312 \tabularnewline
190 & 61 & 62.698 & -1.69797 \tabularnewline
191 & 38 & 69.6008 & -31.6008 \tabularnewline
192 & 75 & 74.6102 & 0.389836 \tabularnewline
193 & 69 & 68.5221 & 0.477932 \tabularnewline
194 & 62 & 67.8464 & -5.84642 \tabularnewline
195 & 72 & 70.4196 & 1.58035 \tabularnewline
196 & 70 & 71.7814 & -1.78138 \tabularnewline
197 & 79 & 66.3898 & 12.6102 \tabularnewline
198 & 87 & 70.0878 & 16.9122 \tabularnewline
199 & 62 & 63.081 & -1.08103 \tabularnewline
200 & 77 & 69.4682 & 7.53182 \tabularnewline
201 & 69 & 64.8866 & 4.11338 \tabularnewline
202 & 69 & 70.4462 & -1.44615 \tabularnewline
203 & 75 & 73.6768 & 1.32325 \tabularnewline
204 & 54 & 69.9818 & -15.9818 \tabularnewline
205 & 72 & 72.4806 & -0.480638 \tabularnewline
206 & 74 & 71.9361 & 2.06393 \tabularnewline
207 & 85 & 72.3199 & 12.6801 \tabularnewline
208 & 52 & 71.417 & -19.417 \tabularnewline
209 & 70 & 70.0031 & -0.00313084 \tabularnewline
210 & 84 & 72.7656 & 11.2344 \tabularnewline
211 & 64 & 65.74 & -1.74001 \tabularnewline
212 & 84 & 75.7963 & 8.20367 \tabularnewline
213 & 87 & 66.1466 & 20.8534 \tabularnewline
214 & 79 & 67.6877 & 11.3123 \tabularnewline
215 & 67 & 67.162 & -0.162042 \tabularnewline
216 & 65 & 69.9431 & -4.94309 \tabularnewline
217 & 85 & 74.2157 & 10.7843 \tabularnewline
218 & 83 & 72.5012 & 10.4988 \tabularnewline
219 & 61 & 61.4083 & -0.408282 \tabularnewline
220 & 82 & 71.9641 & 10.0359 \tabularnewline
221 & 76 & 70.5156 & 5.48435 \tabularnewline
222 & 58 & 73.619 & -15.619 \tabularnewline
223 & 72 & 66.0596 & 5.94043 \tabularnewline
224 & 72 & 73.6021 & -1.60214 \tabularnewline
225 & 38 & 62.6246 & -24.6246 \tabularnewline
226 & 78 & 73.384 & 4.61604 \tabularnewline
227 & 54 & 74.5909 & -20.5909 \tabularnewline
228 & 63 & 70.2996 & -7.29957 \tabularnewline
229 & 66 & 60.4197 & 5.58034 \tabularnewline
230 & 70 & 69.2766 & 0.723368 \tabularnewline
231 & 71 & 70.685 & 0.315 \tabularnewline
232 & 67 & 66.3349 & 0.665084 \tabularnewline
233 & 58 & 73.3707 & -15.3707 \tabularnewline
234 & 72 & 69.3827 & 2.61733 \tabularnewline
235 & 72 & 74.7941 & -2.79408 \tabularnewline
236 & 70 & 68.7332 & 1.26678 \tabularnewline
237 & 76 & 66.5179 & 9.48215 \tabularnewline
238 & 50 & 70.5812 & -20.5812 \tabularnewline
239 & 72 & 69.5897 & 2.4103 \tabularnewline
240 & 72 & 69.6637 & 2.33633 \tabularnewline
241 & 88 & 70.4481 & 17.5519 \tabularnewline
242 & 53 & 63.9131 & -10.9131 \tabularnewline
243 & 58 & 65.1421 & -7.14207 \tabularnewline
244 & 66 & 67.1619 & -1.16189 \tabularnewline
245 & 82 & 71.0986 & 10.9014 \tabularnewline
246 & 69 & 63.4101 & 5.58986 \tabularnewline
247 & 68 & 68.6723 & -0.672276 \tabularnewline
248 & 44 & 63.9622 & -19.9622 \tabularnewline
249 & 56 & 60.1927 & -4.19271 \tabularnewline
250 & 53 & 64.5177 & -11.5177 \tabularnewline
251 & 70 & 69.884 & 0.115993 \tabularnewline
252 & 78 & 66.8082 & 11.1918 \tabularnewline
253 & 71 & 71.4658 & -0.46584 \tabularnewline
254 & 72 & 69.9862 & 2.01376 \tabularnewline
255 & 68 & 67.4918 & 0.508191 \tabularnewline
256 & 67 & 68.6245 & -1.62446 \tabularnewline
257 & 75 & 63.4052 & 11.5948 \tabularnewline
258 & 62 & 63.7696 & -1.76959 \tabularnewline
259 & 67 & 70.8224 & -3.82241 \tabularnewline
260 & 83 & 70.8906 & 12.1094 \tabularnewline
261 & 64 & 70.5315 & -6.53146 \tabularnewline
262 & 68 & 72.985 & -4.98498 \tabularnewline
263 & 62 & 61.3628 & 0.637177 \tabularnewline
264 & 72 & 70.6344 & 1.36555 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&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]53[/C][C]73.4965[/C][C]-20.4965[/C][/ROW]
[ROW][C]2[/C][C]83[/C][C]75.4368[/C][C]7.56316[/C][/ROW]
[ROW][C]3[/C][C]66[/C][C]69.0583[/C][C]-3.05835[/C][/ROW]
[ROW][C]4[/C][C]67[/C][C]69.3669[/C][C]-2.3669[/C][/ROW]
[ROW][C]5[/C][C]76[/C][C]67.3085[/C][C]8.69145[/C][/ROW]
[ROW][C]6[/C][C]78[/C][C]73.6978[/C][C]4.30219[/C][/ROW]
[ROW][C]7[/C][C]53[/C][C]65.5871[/C][C]-12.5871[/C][/ROW]
[ROW][C]8[/C][C]80[/C][C]73.3363[/C][C]6.66371[/C][/ROW]
[ROW][C]9[/C][C]74[/C][C]74.4511[/C][C]-0.451064[/C][/ROW]
[ROW][C]10[/C][C]76[/C][C]72.1912[/C][C]3.80882[/C][/ROW]
[ROW][C]11[/C][C]79[/C][C]75.1709[/C][C]3.82912[/C][/ROW]
[ROW][C]12[/C][C]54[/C][C]77.9895[/C][C]-23.9895[/C][/ROW]
[ROW][C]13[/C][C]67[/C][C]68.4718[/C][C]-1.47184[/C][/ROW]
[ROW][C]14[/C][C]54[/C][C]72.7099[/C][C]-18.7099[/C][/ROW]
[ROW][C]15[/C][C]87[/C][C]76.3647[/C][C]10.6353[/C][/ROW]
[ROW][C]16[/C][C]58[/C][C]70.3125[/C][C]-12.3125[/C][/ROW]
[ROW][C]17[/C][C]75[/C][C]70.4748[/C][C]4.52519[/C][/ROW]
[ROW][C]18[/C][C]88[/C][C]75.4035[/C][C]12.5965[/C][/ROW]
[ROW][C]19[/C][C]64[/C][C]74.4168[/C][C]-10.4168[/C][/ROW]
[ROW][C]20[/C][C]57[/C][C]72.0409[/C][C]-15.0409[/C][/ROW]
[ROW][C]21[/C][C]66[/C][C]75.5087[/C][C]-9.50869[/C][/ROW]
[ROW][C]22[/C][C]68[/C][C]68.3371[/C][C]-0.337139[/C][/ROW]
[ROW][C]23[/C][C]54[/C][C]73.3745[/C][C]-19.3745[/C][/ROW]
[ROW][C]24[/C][C]56[/C][C]70.274[/C][C]-14.274[/C][/ROW]
[ROW][C]25[/C][C]86[/C][C]75.0658[/C][C]10.9342[/C][/ROW]
[ROW][C]26[/C][C]80[/C][C]72.5325[/C][C]7.46751[/C][/ROW]
[ROW][C]27[/C][C]76[/C][C]73.9365[/C][C]2.06352[/C][/ROW]
[ROW][C]28[/C][C]69[/C][C]70.4523[/C][C]-1.4523[/C][/ROW]
[ROW][C]29[/C][C]78[/C][C]71.0179[/C][C]6.98207[/C][/ROW]
[ROW][C]30[/C][C]67[/C][C]69.2956[/C][C]-2.29562[/C][/ROW]
[ROW][C]31[/C][C]80[/C][C]74.6206[/C][C]5.37939[/C][/ROW]
[ROW][C]32[/C][C]54[/C][C]67.4845[/C][C]-13.4845[/C][/ROW]
[ROW][C]33[/C][C]71[/C][C]75.0188[/C][C]-4.01876[/C][/ROW]
[ROW][C]34[/C][C]84[/C][C]73.6067[/C][C]10.3933[/C][/ROW]
[ROW][C]35[/C][C]74[/C][C]71.0752[/C][C]2.9248[/C][/ROW]
[ROW][C]36[/C][C]71[/C][C]74.7281[/C][C]-3.72806[/C][/ROW]
[ROW][C]37[/C][C]63[/C][C]62.1592[/C][C]0.84078[/C][/ROW]
[ROW][C]38[/C][C]71[/C][C]72.881[/C][C]-1.88104[/C][/ROW]
[ROW][C]39[/C][C]76[/C][C]73.8018[/C][C]2.19822[/C][/ROW]
[ROW][C]40[/C][C]69[/C][C]72.6645[/C][C]-3.66451[/C][/ROW]
[ROW][C]41[/C][C]74[/C][C]74.6971[/C][C]-0.69713[/C][/ROW]
[ROW][C]42[/C][C]75[/C][C]71.7234[/C][C]3.27663[/C][/ROW]
[ROW][C]43[/C][C]54[/C][C]77.0173[/C][C]-23.0173[/C][/ROW]
[ROW][C]44[/C][C]52[/C][C]69.2977[/C][C]-17.2977[/C][/ROW]
[ROW][C]45[/C][C]69[/C][C]73.116[/C][C]-4.11596[/C][/ROW]
[ROW][C]46[/C][C]68[/C][C]70.2798[/C][C]-2.27979[/C][/ROW]
[ROW][C]47[/C][C]65[/C][C]75.9675[/C][C]-10.9675[/C][/ROW]
[ROW][C]48[/C][C]75[/C][C]73.0274[/C][C]1.97257[/C][/ROW]
[ROW][C]49[/C][C]74[/C][C]72.1035[/C][C]1.89653[/C][/ROW]
[ROW][C]50[/C][C]75[/C][C]72.7004[/C][C]2.29961[/C][/ROW]
[ROW][C]51[/C][C]72[/C][C]75.0053[/C][C]-3.00533[/C][/ROW]
[ROW][C]52[/C][C]67[/C][C]69.7031[/C][C]-2.70306[/C][/ROW]
[ROW][C]53[/C][C]63[/C][C]65.839[/C][C]-2.83903[/C][/ROW]
[ROW][C]54[/C][C]62[/C][C]70.1005[/C][C]-8.10053[/C][/ROW]
[ROW][C]55[/C][C]63[/C][C]69.9585[/C][C]-6.9585[/C][/ROW]
[ROW][C]56[/C][C]76[/C][C]70.3444[/C][C]5.65558[/C][/ROW]
[ROW][C]57[/C][C]74[/C][C]73.269[/C][C]0.731012[/C][/ROW]
[ROW][C]58[/C][C]67[/C][C]74.008[/C][C]-7.00795[/C][/ROW]
[ROW][C]59[/C][C]73[/C][C]72.8426[/C][C]0.157398[/C][/ROW]
[ROW][C]60[/C][C]70[/C][C]68.676[/C][C]1.32405[/C][/ROW]
[ROW][C]61[/C][C]53[/C][C]61.1486[/C][C]-8.14859[/C][/ROW]
[ROW][C]62[/C][C]77[/C][C]72.1603[/C][C]4.83972[/C][/ROW]
[ROW][C]63[/C][C]80[/C][C]70.8913[/C][C]9.10868[/C][/ROW]
[ROW][C]64[/C][C]52[/C][C]70.1414[/C][C]-18.1414[/C][/ROW]
[ROW][C]65[/C][C]54[/C][C]71.7102[/C][C]-17.7102[/C][/ROW]
[ROW][C]66[/C][C]80[/C][C]71.1745[/C][C]8.82549[/C][/ROW]
[ROW][C]67[/C][C]66[/C][C]67.6787[/C][C]-1.67869[/C][/ROW]
[ROW][C]68[/C][C]73[/C][C]69.6363[/C][C]3.36372[/C][/ROW]
[ROW][C]69[/C][C]63[/C][C]73.2055[/C][C]-10.2055[/C][/ROW]
[ROW][C]70[/C][C]69[/C][C]71.6487[/C][C]-2.64871[/C][/ROW]
[ROW][C]71[/C][C]67[/C][C]71.4444[/C][C]-4.44445[/C][/ROW]
[ROW][C]72[/C][C]54[/C][C]70.7895[/C][C]-16.7895[/C][/ROW]
[ROW][C]73[/C][C]81[/C][C]72.7278[/C][C]8.27224[/C][/ROW]
[ROW][C]74[/C][C]69[/C][C]75.6096[/C][C]-6.60964[/C][/ROW]
[ROW][C]75[/C][C]84[/C][C]71.6837[/C][C]12.3163[/C][/ROW]
[ROW][C]76[/C][C]80[/C][C]65.9621[/C][C]14.0379[/C][/ROW]
[ROW][C]77[/C][C]70[/C][C]73.9452[/C][C]-3.94523[/C][/ROW]
[ROW][C]78[/C][C]69[/C][C]67.6078[/C][C]1.39225[/C][/ROW]
[ROW][C]79[/C][C]77[/C][C]70.7974[/C][C]6.20258[/C][/ROW]
[ROW][C]80[/C][C]54[/C][C]73.5468[/C][C]-19.5468[/C][/ROW]
[ROW][C]81[/C][C]79[/C][C]73.373[/C][C]5.62704[/C][/ROW]
[ROW][C]82[/C][C]71[/C][C]75.1656[/C][C]-4.16559[/C][/ROW]
[ROW][C]83[/C][C]73[/C][C]73.5865[/C][C]-0.586484[/C][/ROW]
[ROW][C]84[/C][C]72[/C][C]72.1719[/C][C]-0.171929[/C][/ROW]
[ROW][C]85[/C][C]77[/C][C]70.6402[/C][C]6.35981[/C][/ROW]
[ROW][C]86[/C][C]75[/C][C]72.4249[/C][C]2.57506[/C][/ROW]
[ROW][C]87[/C][C]69[/C][C]71.953[/C][C]-2.95299[/C][/ROW]
[ROW][C]88[/C][C]54[/C][C]68.5178[/C][C]-14.5178[/C][/ROW]
[ROW][C]89[/C][C]70[/C][C]60.9644[/C][C]9.03562[/C][/ROW]
[ROW][C]90[/C][C]73[/C][C]72.2218[/C][C]0.778185[/C][/ROW]
[ROW][C]91[/C][C]54[/C][C]70.1294[/C][C]-16.1294[/C][/ROW]
[ROW][C]92[/C][C]77[/C][C]72.6786[/C][C]4.32137[/C][/ROW]
[ROW][C]93[/C][C]82[/C][C]69.2009[/C][C]12.7991[/C][/ROW]
[ROW][C]94[/C][C]80[/C][C]70.113[/C][C]9.88704[/C][/ROW]
[ROW][C]95[/C][C]80[/C][C]74.4745[/C][C]5.52552[/C][/ROW]
[ROW][C]96[/C][C]69[/C][C]68.9052[/C][C]0.094758[/C][/ROW]
[ROW][C]97[/C][C]78[/C][C]72.1689[/C][C]5.83108[/C][/ROW]
[ROW][C]98[/C][C]81[/C][C]74.9248[/C][C]6.07519[/C][/ROW]
[ROW][C]99[/C][C]76[/C][C]73.5597[/C][C]2.44031[/C][/ROW]
[ROW][C]100[/C][C]76[/C][C]76.3081[/C][C]-0.308106[/C][/ROW]
[ROW][C]101[/C][C]73[/C][C]68.5407[/C][C]4.45928[/C][/ROW]
[ROW][C]102[/C][C]85[/C][C]74.3077[/C][C]10.6923[/C][/ROW]
[ROW][C]103[/C][C]66[/C][C]70.1722[/C][C]-4.17222[/C][/ROW]
[ROW][C]104[/C][C]79[/C][C]69.9187[/C][C]9.08127[/C][/ROW]
[ROW][C]105[/C][C]68[/C][C]65.1644[/C][C]2.83564[/C][/ROW]
[ROW][C]106[/C][C]76[/C][C]74.6053[/C][C]1.39475[/C][/ROW]
[ROW][C]107[/C][C]71[/C][C]71.318[/C][C]-0.317964[/C][/ROW]
[ROW][C]108[/C][C]54[/C][C]67.9853[/C][C]-13.9853[/C][/ROW]
[ROW][C]109[/C][C]46[/C][C]62.5622[/C][C]-16.5622[/C][/ROW]
[ROW][C]110[/C][C]85[/C][C]70.6432[/C][C]14.3568[/C][/ROW]
[ROW][C]111[/C][C]74[/C][C]68.1616[/C][C]5.83844[/C][/ROW]
[ROW][C]112[/C][C]88[/C][C]72.3401[/C][C]15.6599[/C][/ROW]
[ROW][C]113[/C][C]38[/C][C]69.4269[/C][C]-31.4269[/C][/ROW]
[ROW][C]114[/C][C]76[/C][C]74.4102[/C][C]1.58977[/C][/ROW]
[ROW][C]115[/C][C]86[/C][C]75.0939[/C][C]10.9061[/C][/ROW]
[ROW][C]116[/C][C]54[/C][C]71.2183[/C][C]-17.2183[/C][/ROW]
[ROW][C]117[/C][C]67[/C][C]71.1625[/C][C]-4.1625[/C][/ROW]
[ROW][C]118[/C][C]69[/C][C]73.9625[/C][C]-4.96249[/C][/ROW]
[ROW][C]119[/C][C]90[/C][C]70.7667[/C][C]19.2333[/C][/ROW]
[ROW][C]120[/C][C]54[/C][C]68.7989[/C][C]-14.7989[/C][/ROW]
[ROW][C]121[/C][C]76[/C][C]69.8528[/C][C]6.14718[/C][/ROW]
[ROW][C]122[/C][C]89[/C][C]74.3785[/C][C]14.6215[/C][/ROW]
[ROW][C]123[/C][C]76[/C][C]76.6194[/C][C]-0.619366[/C][/ROW]
[ROW][C]124[/C][C]73[/C][C]73.6034[/C][C]-0.603411[/C][/ROW]
[ROW][C]125[/C][C]79[/C][C]72.264[/C][C]6.73604[/C][/ROW]
[ROW][C]126[/C][C]90[/C][C]76.8114[/C][C]13.1886[/C][/ROW]
[ROW][C]127[/C][C]74[/C][C]76.919[/C][C]-2.91895[/C][/ROW]
[ROW][C]128[/C][C]81[/C][C]75.0394[/C][C]5.96055[/C][/ROW]
[ROW][C]129[/C][C]72[/C][C]71.8433[/C][C]0.156716[/C][/ROW]
[ROW][C]130[/C][C]71[/C][C]71.5048[/C][C]-0.504768[/C][/ROW]
[ROW][C]131[/C][C]66[/C][C]62.4533[/C][C]3.54674[/C][/ROW]
[ROW][C]132[/C][C]77[/C][C]74.4938[/C][C]2.50623[/C][/ROW]
[ROW][C]133[/C][C]65[/C][C]68.9747[/C][C]-3.97465[/C][/ROW]
[ROW][C]134[/C][C]74[/C][C]73.4413[/C][C]0.558659[/C][/ROW]
[ROW][C]135[/C][C]85[/C][C]71.0926[/C][C]13.9074[/C][/ROW]
[ROW][C]136[/C][C]54[/C][C]60.2689[/C][C]-6.26889[/C][/ROW]
[ROW][C]137[/C][C]63[/C][C]70.5977[/C][C]-7.59774[/C][/ROW]
[ROW][C]138[/C][C]54[/C][C]66.7403[/C][C]-12.7403[/C][/ROW]
[ROW][C]139[/C][C]64[/C][C]72.7849[/C][C]-8.78488[/C][/ROW]
[ROW][C]140[/C][C]69[/C][C]70.6303[/C][C]-1.63028[/C][/ROW]
[ROW][C]141[/C][C]54[/C][C]73.0319[/C][C]-19.0319[/C][/ROW]
[ROW][C]142[/C][C]84[/C][C]70.8946[/C][C]13.1054[/C][/ROW]
[ROW][C]143[/C][C]86[/C][C]72.1251[/C][C]13.8749[/C][/ROW]
[ROW][C]144[/C][C]77[/C][C]71.1218[/C][C]5.87818[/C][/ROW]
[ROW][C]145[/C][C]89[/C][C]73.8539[/C][C]15.1461[/C][/ROW]
[ROW][C]146[/C][C]76[/C][C]72.5183[/C][C]3.48167[/C][/ROW]
[ROW][C]147[/C][C]60[/C][C]70.2093[/C][C]-10.2093[/C][/ROW]
[ROW][C]148[/C][C]75[/C][C]71.1527[/C][C]3.8473[/C][/ROW]
[ROW][C]149[/C][C]73[/C][C]63.857[/C][C]9.14304[/C][/ROW]
[ROW][C]150[/C][C]85[/C][C]73.3171[/C][C]11.6829[/C][/ROW]
[ROW][C]151[/C][C]79[/C][C]69.6791[/C][C]9.32093[/C][/ROW]
[ROW][C]152[/C][C]71[/C][C]75.1016[/C][C]-4.10163[/C][/ROW]
[ROW][C]153[/C][C]72[/C][C]70.4652[/C][C]1.5348[/C][/ROW]
[ROW][C]154[/C][C]69[/C][C]64.2943[/C][C]4.70567[/C][/ROW]
[ROW][C]155[/C][C]78[/C][C]66.2055[/C][C]11.7945[/C][/ROW]
[ROW][C]156[/C][C]54[/C][C]70.1294[/C][C]-16.1294[/C][/ROW]
[ROW][C]157[/C][C]69[/C][C]69.5455[/C][C]-0.545453[/C][/ROW]
[ROW][C]158[/C][C]81[/C][C]75.0394[/C][C]5.96055[/C][/ROW]
[ROW][C]159[/C][C]84[/C][C]73.3164[/C][C]10.6836[/C][/ROW]
[ROW][C]160[/C][C]84[/C][C]66.0715[/C][C]17.9285[/C][/ROW]
[ROW][C]161[/C][C]69[/C][C]68.1725[/C][C]0.827482[/C][/ROW]
[ROW][C]162[/C][C]66[/C][C]59.3689[/C][C]6.63112[/C][/ROW]
[ROW][C]163[/C][C]81[/C][C]68.8599[/C][C]12.1401[/C][/ROW]
[ROW][C]164[/C][C]82[/C][C]68.4761[/C][C]13.5239[/C][/ROW]
[ROW][C]165[/C][C]72[/C][C]65.7152[/C][C]6.28476[/C][/ROW]
[ROW][C]166[/C][C]54[/C][C]60.1312[/C][C]-6.13123[/C][/ROW]
[ROW][C]167[/C][C]78[/C][C]71.2327[/C][C]6.76727[/C][/ROW]
[ROW][C]168[/C][C]74[/C][C]67.64[/C][C]6.35996[/C][/ROW]
[ROW][C]169[/C][C]82[/C][C]66.8516[/C][C]15.1484[/C][/ROW]
[ROW][C]170[/C][C]73[/C][C]64.2983[/C][C]8.70168[/C][/ROW]
[ROW][C]171[/C][C]55[/C][C]63.7538[/C][C]-8.75378[/C][/ROW]
[ROW][C]172[/C][C]72[/C][C]73.7609[/C][C]-1.7609[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]70.1205[/C][C]7.87952[/C][/ROW]
[ROW][C]174[/C][C]59[/C][C]65.6283[/C][C]-6.62828[/C][/ROW]
[ROW][C]175[/C][C]72[/C][C]72.3228[/C][C]-0.322812[/C][/ROW]
[ROW][C]176[/C][C]78[/C][C]73.2571[/C][C]4.74295[/C][/ROW]
[ROW][C]177[/C][C]68[/C][C]66.1707[/C][C]1.8293[/C][/ROW]
[ROW][C]178[/C][C]69[/C][C]65.2964[/C][C]3.70359[/C][/ROW]
[ROW][C]179[/C][C]67[/C][C]73.5527[/C][C]-6.55271[/C][/ROW]
[ROW][C]180[/C][C]74[/C][C]69.345[/C][C]4.65499[/C][/ROW]
[ROW][C]181[/C][C]54[/C][C]73.276[/C][C]-19.276[/C][/ROW]
[ROW][C]182[/C][C]67[/C][C]72.3939[/C][C]-5.39393[/C][/ROW]
[ROW][C]183[/C][C]70[/C][C]73.6155[/C][C]-3.6155[/C][/ROW]
[ROW][C]184[/C][C]80[/C][C]73.9571[/C][C]6.04292[/C][/ROW]
[ROW][C]185[/C][C]89[/C][C]71.5999[/C][C]17.4001[/C][/ROW]
[ROW][C]186[/C][C]76[/C][C]66.4872[/C][C]9.5128[/C][/ROW]
[ROW][C]187[/C][C]74[/C][C]70.8203[/C][C]3.17965[/C][/ROW]
[ROW][C]188[/C][C]87[/C][C]72.2628[/C][C]14.7372[/C][/ROW]
[ROW][C]189[/C][C]54[/C][C]67.8312[/C][C]-13.8312[/C][/ROW]
[ROW][C]190[/C][C]61[/C][C]62.698[/C][C]-1.69797[/C][/ROW]
[ROW][C]191[/C][C]38[/C][C]69.6008[/C][C]-31.6008[/C][/ROW]
[ROW][C]192[/C][C]75[/C][C]74.6102[/C][C]0.389836[/C][/ROW]
[ROW][C]193[/C][C]69[/C][C]68.5221[/C][C]0.477932[/C][/ROW]
[ROW][C]194[/C][C]62[/C][C]67.8464[/C][C]-5.84642[/C][/ROW]
[ROW][C]195[/C][C]72[/C][C]70.4196[/C][C]1.58035[/C][/ROW]
[ROW][C]196[/C][C]70[/C][C]71.7814[/C][C]-1.78138[/C][/ROW]
[ROW][C]197[/C][C]79[/C][C]66.3898[/C][C]12.6102[/C][/ROW]
[ROW][C]198[/C][C]87[/C][C]70.0878[/C][C]16.9122[/C][/ROW]
[ROW][C]199[/C][C]62[/C][C]63.081[/C][C]-1.08103[/C][/ROW]
[ROW][C]200[/C][C]77[/C][C]69.4682[/C][C]7.53182[/C][/ROW]
[ROW][C]201[/C][C]69[/C][C]64.8866[/C][C]4.11338[/C][/ROW]
[ROW][C]202[/C][C]69[/C][C]70.4462[/C][C]-1.44615[/C][/ROW]
[ROW][C]203[/C][C]75[/C][C]73.6768[/C][C]1.32325[/C][/ROW]
[ROW][C]204[/C][C]54[/C][C]69.9818[/C][C]-15.9818[/C][/ROW]
[ROW][C]205[/C][C]72[/C][C]72.4806[/C][C]-0.480638[/C][/ROW]
[ROW][C]206[/C][C]74[/C][C]71.9361[/C][C]2.06393[/C][/ROW]
[ROW][C]207[/C][C]85[/C][C]72.3199[/C][C]12.6801[/C][/ROW]
[ROW][C]208[/C][C]52[/C][C]71.417[/C][C]-19.417[/C][/ROW]
[ROW][C]209[/C][C]70[/C][C]70.0031[/C][C]-0.00313084[/C][/ROW]
[ROW][C]210[/C][C]84[/C][C]72.7656[/C][C]11.2344[/C][/ROW]
[ROW][C]211[/C][C]64[/C][C]65.74[/C][C]-1.74001[/C][/ROW]
[ROW][C]212[/C][C]84[/C][C]75.7963[/C][C]8.20367[/C][/ROW]
[ROW][C]213[/C][C]87[/C][C]66.1466[/C][C]20.8534[/C][/ROW]
[ROW][C]214[/C][C]79[/C][C]67.6877[/C][C]11.3123[/C][/ROW]
[ROW][C]215[/C][C]67[/C][C]67.162[/C][C]-0.162042[/C][/ROW]
[ROW][C]216[/C][C]65[/C][C]69.9431[/C][C]-4.94309[/C][/ROW]
[ROW][C]217[/C][C]85[/C][C]74.2157[/C][C]10.7843[/C][/ROW]
[ROW][C]218[/C][C]83[/C][C]72.5012[/C][C]10.4988[/C][/ROW]
[ROW][C]219[/C][C]61[/C][C]61.4083[/C][C]-0.408282[/C][/ROW]
[ROW][C]220[/C][C]82[/C][C]71.9641[/C][C]10.0359[/C][/ROW]
[ROW][C]221[/C][C]76[/C][C]70.5156[/C][C]5.48435[/C][/ROW]
[ROW][C]222[/C][C]58[/C][C]73.619[/C][C]-15.619[/C][/ROW]
[ROW][C]223[/C][C]72[/C][C]66.0596[/C][C]5.94043[/C][/ROW]
[ROW][C]224[/C][C]72[/C][C]73.6021[/C][C]-1.60214[/C][/ROW]
[ROW][C]225[/C][C]38[/C][C]62.6246[/C][C]-24.6246[/C][/ROW]
[ROW][C]226[/C][C]78[/C][C]73.384[/C][C]4.61604[/C][/ROW]
[ROW][C]227[/C][C]54[/C][C]74.5909[/C][C]-20.5909[/C][/ROW]
[ROW][C]228[/C][C]63[/C][C]70.2996[/C][C]-7.29957[/C][/ROW]
[ROW][C]229[/C][C]66[/C][C]60.4197[/C][C]5.58034[/C][/ROW]
[ROW][C]230[/C][C]70[/C][C]69.2766[/C][C]0.723368[/C][/ROW]
[ROW][C]231[/C][C]71[/C][C]70.685[/C][C]0.315[/C][/ROW]
[ROW][C]232[/C][C]67[/C][C]66.3349[/C][C]0.665084[/C][/ROW]
[ROW][C]233[/C][C]58[/C][C]73.3707[/C][C]-15.3707[/C][/ROW]
[ROW][C]234[/C][C]72[/C][C]69.3827[/C][C]2.61733[/C][/ROW]
[ROW][C]235[/C][C]72[/C][C]74.7941[/C][C]-2.79408[/C][/ROW]
[ROW][C]236[/C][C]70[/C][C]68.7332[/C][C]1.26678[/C][/ROW]
[ROW][C]237[/C][C]76[/C][C]66.5179[/C][C]9.48215[/C][/ROW]
[ROW][C]238[/C][C]50[/C][C]70.5812[/C][C]-20.5812[/C][/ROW]
[ROW][C]239[/C][C]72[/C][C]69.5897[/C][C]2.4103[/C][/ROW]
[ROW][C]240[/C][C]72[/C][C]69.6637[/C][C]2.33633[/C][/ROW]
[ROW][C]241[/C][C]88[/C][C]70.4481[/C][C]17.5519[/C][/ROW]
[ROW][C]242[/C][C]53[/C][C]63.9131[/C][C]-10.9131[/C][/ROW]
[ROW][C]243[/C][C]58[/C][C]65.1421[/C][C]-7.14207[/C][/ROW]
[ROW][C]244[/C][C]66[/C][C]67.1619[/C][C]-1.16189[/C][/ROW]
[ROW][C]245[/C][C]82[/C][C]71.0986[/C][C]10.9014[/C][/ROW]
[ROW][C]246[/C][C]69[/C][C]63.4101[/C][C]5.58986[/C][/ROW]
[ROW][C]247[/C][C]68[/C][C]68.6723[/C][C]-0.672276[/C][/ROW]
[ROW][C]248[/C][C]44[/C][C]63.9622[/C][C]-19.9622[/C][/ROW]
[ROW][C]249[/C][C]56[/C][C]60.1927[/C][C]-4.19271[/C][/ROW]
[ROW][C]250[/C][C]53[/C][C]64.5177[/C][C]-11.5177[/C][/ROW]
[ROW][C]251[/C][C]70[/C][C]69.884[/C][C]0.115993[/C][/ROW]
[ROW][C]252[/C][C]78[/C][C]66.8082[/C][C]11.1918[/C][/ROW]
[ROW][C]253[/C][C]71[/C][C]71.4658[/C][C]-0.46584[/C][/ROW]
[ROW][C]254[/C][C]72[/C][C]69.9862[/C][C]2.01376[/C][/ROW]
[ROW][C]255[/C][C]68[/C][C]67.4918[/C][C]0.508191[/C][/ROW]
[ROW][C]256[/C][C]67[/C][C]68.6245[/C][C]-1.62446[/C][/ROW]
[ROW][C]257[/C][C]75[/C][C]63.4052[/C][C]11.5948[/C][/ROW]
[ROW][C]258[/C][C]62[/C][C]63.7696[/C][C]-1.76959[/C][/ROW]
[ROW][C]259[/C][C]67[/C][C]70.8224[/C][C]-3.82241[/C][/ROW]
[ROW][C]260[/C][C]83[/C][C]70.8906[/C][C]12.1094[/C][/ROW]
[ROW][C]261[/C][C]64[/C][C]70.5315[/C][C]-6.53146[/C][/ROW]
[ROW][C]262[/C][C]68[/C][C]72.985[/C][C]-4.98498[/C][/ROW]
[ROW][C]263[/C][C]62[/C][C]61.3628[/C][C]0.637177[/C][/ROW]
[ROW][C]264[/C][C]72[/C][C]70.6344[/C][C]1.36555[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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
15373.4965-20.4965
28375.43687.56316
36669.0583-3.05835
46769.3669-2.3669
57667.30858.69145
67873.69784.30219
75365.5871-12.5871
88073.33636.66371
97474.4511-0.451064
107672.19123.80882
117975.17093.82912
125477.9895-23.9895
136768.4718-1.47184
145472.7099-18.7099
158776.364710.6353
165870.3125-12.3125
177570.47484.52519
188875.403512.5965
196474.4168-10.4168
205772.0409-15.0409
216675.5087-9.50869
226868.3371-0.337139
235473.3745-19.3745
245670.274-14.274
258675.065810.9342
268072.53257.46751
277673.93652.06352
286970.4523-1.4523
297871.01796.98207
306769.2956-2.29562
318074.62065.37939
325467.4845-13.4845
337175.0188-4.01876
348473.606710.3933
357471.07522.9248
367174.7281-3.72806
376362.15920.84078
387172.881-1.88104
397673.80182.19822
406972.6645-3.66451
417474.6971-0.69713
427571.72343.27663
435477.0173-23.0173
445269.2977-17.2977
456973.116-4.11596
466870.2798-2.27979
476575.9675-10.9675
487573.02741.97257
497472.10351.89653
507572.70042.29961
517275.0053-3.00533
526769.7031-2.70306
536365.839-2.83903
546270.1005-8.10053
556369.9585-6.9585
567670.34445.65558
577473.2690.731012
586774.008-7.00795
597372.84260.157398
607068.6761.32405
615361.1486-8.14859
627772.16034.83972
638070.89139.10868
645270.1414-18.1414
655471.7102-17.7102
668071.17458.82549
676667.6787-1.67869
687369.63633.36372
696373.2055-10.2055
706971.6487-2.64871
716771.4444-4.44445
725470.7895-16.7895
738172.72788.27224
746975.6096-6.60964
758471.683712.3163
768065.962114.0379
777073.9452-3.94523
786967.60781.39225
797770.79746.20258
805473.5468-19.5468
817973.3735.62704
827175.1656-4.16559
837373.5865-0.586484
847272.1719-0.171929
857770.64026.35981
867572.42492.57506
876971.953-2.95299
885468.5178-14.5178
897060.96449.03562
907372.22180.778185
915470.1294-16.1294
927772.67864.32137
938269.200912.7991
948070.1139.88704
958074.47455.52552
966968.90520.094758
977872.16895.83108
988174.92486.07519
997673.55972.44031
1007676.3081-0.308106
1017368.54074.45928
1028574.307710.6923
1036670.1722-4.17222
1047969.91879.08127
1056865.16442.83564
1067674.60531.39475
1077171.318-0.317964
1085467.9853-13.9853
1094662.5622-16.5622
1108570.643214.3568
1117468.16165.83844
1128872.340115.6599
1133869.4269-31.4269
1147674.41021.58977
1158675.093910.9061
1165471.2183-17.2183
1176771.1625-4.1625
1186973.9625-4.96249
1199070.766719.2333
1205468.7989-14.7989
1217669.85286.14718
1228974.378514.6215
1237676.6194-0.619366
1247373.6034-0.603411
1257972.2646.73604
1269076.811413.1886
1277476.919-2.91895
1288175.03945.96055
1297271.84330.156716
1307171.5048-0.504768
1316662.45333.54674
1327774.49382.50623
1336568.9747-3.97465
1347473.44130.558659
1358571.092613.9074
1365460.2689-6.26889
1376370.5977-7.59774
1385466.7403-12.7403
1396472.7849-8.78488
1406970.6303-1.63028
1415473.0319-19.0319
1428470.894613.1054
1438672.125113.8749
1447771.12185.87818
1458973.853915.1461
1467672.51833.48167
1476070.2093-10.2093
1487571.15273.8473
1497363.8579.14304
1508573.317111.6829
1517969.67919.32093
1527175.1016-4.10163
1537270.46521.5348
1546964.29434.70567
1557866.205511.7945
1565470.1294-16.1294
1576969.5455-0.545453
1588175.03945.96055
1598473.316410.6836
1608466.071517.9285
1616968.17250.827482
1626659.36896.63112
1638168.859912.1401
1648268.476113.5239
1657265.71526.28476
1665460.1312-6.13123
1677871.23276.76727
1687467.646.35996
1698266.851615.1484
1707364.29838.70168
1715563.7538-8.75378
1727273.7609-1.7609
1737870.12057.87952
1745965.6283-6.62828
1757272.3228-0.322812
1767873.25714.74295
1776866.17071.8293
1786965.29643.70359
1796773.5527-6.55271
1807469.3454.65499
1815473.276-19.276
1826772.3939-5.39393
1837073.6155-3.6155
1848073.95716.04292
1858971.599917.4001
1867666.48729.5128
1877470.82033.17965
1888772.262814.7372
1895467.8312-13.8312
1906162.698-1.69797
1913869.6008-31.6008
1927574.61020.389836
1936968.52210.477932
1946267.8464-5.84642
1957270.41961.58035
1967071.7814-1.78138
1977966.389812.6102
1988770.087816.9122
1996263.081-1.08103
2007769.46827.53182
2016964.88664.11338
2026970.4462-1.44615
2037573.67681.32325
2045469.9818-15.9818
2057272.4806-0.480638
2067471.93612.06393
2078572.319912.6801
2085271.417-19.417
2097070.0031-0.00313084
2108472.765611.2344
2116465.74-1.74001
2128475.79638.20367
2138766.146620.8534
2147967.687711.3123
2156767.162-0.162042
2166569.9431-4.94309
2178574.215710.7843
2188372.501210.4988
2196161.4083-0.408282
2208271.964110.0359
2217670.51565.48435
2225873.619-15.619
2237266.05965.94043
2247273.6021-1.60214
2253862.6246-24.6246
2267873.3844.61604
2275474.5909-20.5909
2286370.2996-7.29957
2296660.41975.58034
2307069.27660.723368
2317170.6850.315
2326766.33490.665084
2335873.3707-15.3707
2347269.38272.61733
2357274.7941-2.79408
2367068.73321.26678
2377666.51799.48215
2385070.5812-20.5812
2397269.58972.4103
2407269.66372.33633
2418870.448117.5519
2425363.9131-10.9131
2435865.1421-7.14207
2446667.1619-1.16189
2458271.098610.9014
2466963.41015.58986
2476868.6723-0.672276
2484463.9622-19.9622
2495660.1927-4.19271
2505364.5177-11.5177
2517069.8840.115993
2527866.808211.1918
2537171.4658-0.46584
2547269.98622.01376
2556867.49180.508191
2566768.6245-1.62446
2577563.405211.5948
2586263.7696-1.76959
2596770.8224-3.82241
2608370.890612.1094
2616470.5315-6.53146
2626872.985-4.98498
2636261.36280.637177
2647270.63441.36555






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
90.2682170.5364340.731783
100.1834920.3669840.816508
110.1061020.2122050.893898
120.9261580.1476840.073842
130.8998580.2002840.100142
140.9072230.1855540.0927768
150.8988070.2023860.101193
160.9241810.1516390.0758194
170.9062160.1875680.0937842
180.9380980.1238040.0619021
190.9163810.1672380.083619
200.9459290.1081430.0540714
210.9413890.1172230.0586113
220.9195350.160930.080465
230.9350840.1298320.064916
240.9266880.1466240.0733118
250.9420780.1158450.0579224
260.9428710.1142570.0571287
270.9289090.1421830.0710914
280.9072330.1855340.0927671
290.8957580.2084840.104242
300.866640.266720.13336
310.8359750.328050.164025
320.8360270.3279450.163973
330.8043720.3912560.195628
340.8312420.3375160.168758
350.7956750.4086510.204325
360.7557420.4885170.244258
370.7227440.5545110.277256
380.6771580.6456840.322842
390.6294360.7411280.370564
400.5809650.838070.419035
410.5297380.9405240.470262
420.4858070.9716150.514193
430.7188760.5622470.281124
440.7633510.4732970.236649
450.7274520.5450960.272548
460.6887330.6225340.311267
470.668840.6623190.33116
480.6311980.7376030.368802
490.5978350.8043290.402165
500.5647150.870570.435285
510.5198190.9603620.480181
520.4758360.9516710.524164
530.4310070.8620150.568993
540.3984280.7968570.601572
550.3617990.7235980.638201
560.3590270.7180540.640973
570.3215360.6430730.678464
580.2955120.5910230.704488
590.2681260.5362520.731874
600.2391020.4782030.760898
610.2209970.4419940.779003
620.2093620.4187250.790638
630.225630.451260.77437
640.2890080.5780150.710992
650.3677240.7354480.632276
660.3833750.766750.616625
670.344740.689480.65526
680.3136160.6272320.686384
690.2999870.5999740.700013
700.266410.532820.73359
710.2359790.4719590.764021
720.2700610.5401220.729939
730.2806470.5612940.719353
740.2565080.5130150.743492
750.2700920.5401840.729908
760.3194570.6389140.680543
770.2881830.5763670.711817
780.2561910.5123830.743809
790.2407060.4814130.759294
800.3663620.7327250.633638
810.3529320.7058640.647068
820.3215520.6431050.678448
830.2883060.5766120.711694
840.257440.5148790.74256
850.2440350.488070.755965
860.2265130.4530260.773487
870.2003380.4006760.799662
880.2309540.4619070.769046
890.2300030.4600070.769997
900.2059570.4119140.794043
910.2589970.5179950.741003
920.2434320.4868640.756568
930.2663930.5327860.733607
940.2687350.537470.731265
950.2558290.5116580.744171
960.2274030.4548060.772597
970.212220.424440.78778
980.1991990.3983990.800801
990.1785880.3571760.821412
1000.1568450.313690.843155
1010.1417870.2835730.858213
1020.1499780.2999570.850022
1030.133010.2660190.86699
1040.1340840.2681690.865916
1050.1166640.2333290.883336
1060.1006530.2013060.899347
1070.08566830.1713370.914332
1080.09926370.1985270.900736
1090.1215240.2430490.878476
1100.1440250.2880490.855975
1110.1304670.2609350.869533
1120.1747280.3494570.825272
1130.466160.932320.53384
1140.4328680.8657350.567132
1150.4380320.8760640.561968
1160.5121810.9756370.487819
1170.4824370.9648730.517563
1180.4559810.9119620.544019
1190.5604490.8791010.439551
1200.6017180.7965650.398282
1210.5770060.8459880.422994
1220.6219120.7561770.378088
1230.5891690.8216630.410831
1240.5547280.8905430.445272
1250.532050.93590.46795
1260.558660.882680.44134
1270.5286190.9427630.471381
1280.5059130.9881740.494087
1290.4704960.9409920.529504
1300.435580.871160.56442
1310.4077490.8154990.592251
1320.3784130.7568270.621587
1330.3510330.7020660.648967
1340.319710.6394210.68029
1350.3465980.6931960.653402
1360.3254270.6508540.674573
1370.313270.626540.68673
1380.3318650.6637290.668135
1390.3241160.6482330.675884
1400.2946760.5893530.705324
1410.3828770.7657540.617123
1420.4127330.8254670.587267
1430.4383340.8766670.561666
1440.4172450.8344910.582755
1450.4714370.9428740.528563
1460.4421760.8843510.557824
1470.447920.895840.55208
1480.4181310.8362620.581869
1490.4214950.8429910.578505
1500.4386780.8773570.561322
1510.4343730.8687460.565627
1520.4085160.8170310.591484
1530.3809530.7619060.619047
1540.3576190.7152390.642381
1550.3765760.7531520.623424
1560.4371520.8743030.562848
1570.4034390.8068780.596561
1580.3790850.758170.620915
1590.3832420.7664850.616758
1600.4604350.920870.539565
1610.4246470.8492950.575353
1620.4097250.819450.590275
1630.4374970.8749950.562503
1640.4877530.9755060.512247
1650.4637090.9274170.536291
1660.4393890.8787780.560611
1670.4184040.8368090.581596
1680.4038810.8077620.596119
1690.4424480.8848960.557552
1700.4280460.8560910.571954
1710.4164280.8328570.583572
1720.3815740.7631480.618426
1730.3659210.7318430.634079
1740.3418250.6836490.658175
1750.310860.6217210.68914
1760.2835570.5671140.716443
1770.2532470.5064930.746753
1780.2298380.4596770.770162
1790.2122890.4245780.787711
1800.1897160.3794320.810284
1810.2753170.5506330.724683
1820.2551980.5103960.744802
1830.2305710.4611420.769429
1840.2125960.4251920.787404
1850.2946620.5893250.705338
1860.2986330.5972660.701367
1870.2696560.5393120.730344
1880.3135580.6271150.686442
1890.3376090.6752180.662391
1900.3054970.6109930.694503
1910.7165930.5668140.283407
1920.6875860.6248290.312414
1930.6504620.6990760.349538
1940.6398250.7203510.360175
1950.6047470.7905050.395253
1960.5801720.8396570.419828
1970.6685570.6628860.331443
1980.7370160.5259680.262984
1990.7044860.5910280.295514
2000.6876250.6247510.312375
2010.6568140.6863730.343186
2020.6171690.7656620.382831
2030.5870390.8259220.412961
2040.6432820.7134360.356718
2050.6020650.795870.397935
2060.5607430.8785140.439257
2070.5722530.8554940.427747
2080.6652240.6695520.334776
2090.6228520.7542950.377148
2100.6593610.6812770.340639
2110.622080.755840.37792
2120.5892290.8215430.410771
2130.7173640.5652730.282636
2140.7109280.5781440.289072
2150.668490.663020.33151
2160.6276870.7446260.372313
2170.6778130.6443730.322187
2180.6930790.6138420.306921
2190.6489060.7021880.351094
2200.6936090.6127820.306391
2210.6580020.6839950.341998
2220.6869020.6261950.313098
2230.6689230.6621540.331077
2240.6197670.7604670.380233
2250.8802090.2395820.119791
2260.8608150.278370.139185
2270.8881550.223690.111845
2280.886510.2269790.11349
2290.8661310.2677380.133869
2300.8341770.3316460.165823
2310.7946520.4106970.205348
2320.7616090.4767820.238391
2330.889470.2210590.11053
2340.8989860.2020280.101014
2350.8688610.2622770.131139
2360.8340260.3319470.165974
2370.8691320.2617360.130868
2380.9095140.1809720.0904858
2390.8798650.2402690.120135
2400.8397910.3204180.160209
2410.8783080.2433830.121692
2420.9318640.1362730.0681365
2430.9134230.1731540.0865772
2440.8800140.2399720.119986
2450.9686270.06274560.0313728
2460.9497620.1004760.0502379
2470.9213060.1573870.0786937
2480.9609070.07818590.0390929
2490.9321730.1356530.0678266
2500.9135550.1728910.0864455
2510.8597750.280450.140225
2520.9345630.1308740.0654372
2530.8730950.2538110.126905
2540.7806570.4386860.219343
2550.631010.737980.36899

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
9 & 0.268217 & 0.536434 & 0.731783 \tabularnewline
10 & 0.183492 & 0.366984 & 0.816508 \tabularnewline
11 & 0.106102 & 0.212205 & 0.893898 \tabularnewline
12 & 0.926158 & 0.147684 & 0.073842 \tabularnewline
13 & 0.899858 & 0.200284 & 0.100142 \tabularnewline
14 & 0.907223 & 0.185554 & 0.0927768 \tabularnewline
15 & 0.898807 & 0.202386 & 0.101193 \tabularnewline
16 & 0.924181 & 0.151639 & 0.0758194 \tabularnewline
17 & 0.906216 & 0.187568 & 0.0937842 \tabularnewline
18 & 0.938098 & 0.123804 & 0.0619021 \tabularnewline
19 & 0.916381 & 0.167238 & 0.083619 \tabularnewline
20 & 0.945929 & 0.108143 & 0.0540714 \tabularnewline
21 & 0.941389 & 0.117223 & 0.0586113 \tabularnewline
22 & 0.919535 & 0.16093 & 0.080465 \tabularnewline
23 & 0.935084 & 0.129832 & 0.064916 \tabularnewline
24 & 0.926688 & 0.146624 & 0.0733118 \tabularnewline
25 & 0.942078 & 0.115845 & 0.0579224 \tabularnewline
26 & 0.942871 & 0.114257 & 0.0571287 \tabularnewline
27 & 0.928909 & 0.142183 & 0.0710914 \tabularnewline
28 & 0.907233 & 0.185534 & 0.0927671 \tabularnewline
29 & 0.895758 & 0.208484 & 0.104242 \tabularnewline
30 & 0.86664 & 0.26672 & 0.13336 \tabularnewline
31 & 0.835975 & 0.32805 & 0.164025 \tabularnewline
32 & 0.836027 & 0.327945 & 0.163973 \tabularnewline
33 & 0.804372 & 0.391256 & 0.195628 \tabularnewline
34 & 0.831242 & 0.337516 & 0.168758 \tabularnewline
35 & 0.795675 & 0.408651 & 0.204325 \tabularnewline
36 & 0.755742 & 0.488517 & 0.244258 \tabularnewline
37 & 0.722744 & 0.554511 & 0.277256 \tabularnewline
38 & 0.677158 & 0.645684 & 0.322842 \tabularnewline
39 & 0.629436 & 0.741128 & 0.370564 \tabularnewline
40 & 0.580965 & 0.83807 & 0.419035 \tabularnewline
41 & 0.529738 & 0.940524 & 0.470262 \tabularnewline
42 & 0.485807 & 0.971615 & 0.514193 \tabularnewline
43 & 0.718876 & 0.562247 & 0.281124 \tabularnewline
44 & 0.763351 & 0.473297 & 0.236649 \tabularnewline
45 & 0.727452 & 0.545096 & 0.272548 \tabularnewline
46 & 0.688733 & 0.622534 & 0.311267 \tabularnewline
47 & 0.66884 & 0.662319 & 0.33116 \tabularnewline
48 & 0.631198 & 0.737603 & 0.368802 \tabularnewline
49 & 0.597835 & 0.804329 & 0.402165 \tabularnewline
50 & 0.564715 & 0.87057 & 0.435285 \tabularnewline
51 & 0.519819 & 0.960362 & 0.480181 \tabularnewline
52 & 0.475836 & 0.951671 & 0.524164 \tabularnewline
53 & 0.431007 & 0.862015 & 0.568993 \tabularnewline
54 & 0.398428 & 0.796857 & 0.601572 \tabularnewline
55 & 0.361799 & 0.723598 & 0.638201 \tabularnewline
56 & 0.359027 & 0.718054 & 0.640973 \tabularnewline
57 & 0.321536 & 0.643073 & 0.678464 \tabularnewline
58 & 0.295512 & 0.591023 & 0.704488 \tabularnewline
59 & 0.268126 & 0.536252 & 0.731874 \tabularnewline
60 & 0.239102 & 0.478203 & 0.760898 \tabularnewline
61 & 0.220997 & 0.441994 & 0.779003 \tabularnewline
62 & 0.209362 & 0.418725 & 0.790638 \tabularnewline
63 & 0.22563 & 0.45126 & 0.77437 \tabularnewline
64 & 0.289008 & 0.578015 & 0.710992 \tabularnewline
65 & 0.367724 & 0.735448 & 0.632276 \tabularnewline
66 & 0.383375 & 0.76675 & 0.616625 \tabularnewline
67 & 0.34474 & 0.68948 & 0.65526 \tabularnewline
68 & 0.313616 & 0.627232 & 0.686384 \tabularnewline
69 & 0.299987 & 0.599974 & 0.700013 \tabularnewline
70 & 0.26641 & 0.53282 & 0.73359 \tabularnewline
71 & 0.235979 & 0.471959 & 0.764021 \tabularnewline
72 & 0.270061 & 0.540122 & 0.729939 \tabularnewline
73 & 0.280647 & 0.561294 & 0.719353 \tabularnewline
74 & 0.256508 & 0.513015 & 0.743492 \tabularnewline
75 & 0.270092 & 0.540184 & 0.729908 \tabularnewline
76 & 0.319457 & 0.638914 & 0.680543 \tabularnewline
77 & 0.288183 & 0.576367 & 0.711817 \tabularnewline
78 & 0.256191 & 0.512383 & 0.743809 \tabularnewline
79 & 0.240706 & 0.481413 & 0.759294 \tabularnewline
80 & 0.366362 & 0.732725 & 0.633638 \tabularnewline
81 & 0.352932 & 0.705864 & 0.647068 \tabularnewline
82 & 0.321552 & 0.643105 & 0.678448 \tabularnewline
83 & 0.288306 & 0.576612 & 0.711694 \tabularnewline
84 & 0.25744 & 0.514879 & 0.74256 \tabularnewline
85 & 0.244035 & 0.48807 & 0.755965 \tabularnewline
86 & 0.226513 & 0.453026 & 0.773487 \tabularnewline
87 & 0.200338 & 0.400676 & 0.799662 \tabularnewline
88 & 0.230954 & 0.461907 & 0.769046 \tabularnewline
89 & 0.230003 & 0.460007 & 0.769997 \tabularnewline
90 & 0.205957 & 0.411914 & 0.794043 \tabularnewline
91 & 0.258997 & 0.517995 & 0.741003 \tabularnewline
92 & 0.243432 & 0.486864 & 0.756568 \tabularnewline
93 & 0.266393 & 0.532786 & 0.733607 \tabularnewline
94 & 0.268735 & 0.53747 & 0.731265 \tabularnewline
95 & 0.255829 & 0.511658 & 0.744171 \tabularnewline
96 & 0.227403 & 0.454806 & 0.772597 \tabularnewline
97 & 0.21222 & 0.42444 & 0.78778 \tabularnewline
98 & 0.199199 & 0.398399 & 0.800801 \tabularnewline
99 & 0.178588 & 0.357176 & 0.821412 \tabularnewline
100 & 0.156845 & 0.31369 & 0.843155 \tabularnewline
101 & 0.141787 & 0.283573 & 0.858213 \tabularnewline
102 & 0.149978 & 0.299957 & 0.850022 \tabularnewline
103 & 0.13301 & 0.266019 & 0.86699 \tabularnewline
104 & 0.134084 & 0.268169 & 0.865916 \tabularnewline
105 & 0.116664 & 0.233329 & 0.883336 \tabularnewline
106 & 0.100653 & 0.201306 & 0.899347 \tabularnewline
107 & 0.0856683 & 0.171337 & 0.914332 \tabularnewline
108 & 0.0992637 & 0.198527 & 0.900736 \tabularnewline
109 & 0.121524 & 0.243049 & 0.878476 \tabularnewline
110 & 0.144025 & 0.288049 & 0.855975 \tabularnewline
111 & 0.130467 & 0.260935 & 0.869533 \tabularnewline
112 & 0.174728 & 0.349457 & 0.825272 \tabularnewline
113 & 0.46616 & 0.93232 & 0.53384 \tabularnewline
114 & 0.432868 & 0.865735 & 0.567132 \tabularnewline
115 & 0.438032 & 0.876064 & 0.561968 \tabularnewline
116 & 0.512181 & 0.975637 & 0.487819 \tabularnewline
117 & 0.482437 & 0.964873 & 0.517563 \tabularnewline
118 & 0.455981 & 0.911962 & 0.544019 \tabularnewline
119 & 0.560449 & 0.879101 & 0.439551 \tabularnewline
120 & 0.601718 & 0.796565 & 0.398282 \tabularnewline
121 & 0.577006 & 0.845988 & 0.422994 \tabularnewline
122 & 0.621912 & 0.756177 & 0.378088 \tabularnewline
123 & 0.589169 & 0.821663 & 0.410831 \tabularnewline
124 & 0.554728 & 0.890543 & 0.445272 \tabularnewline
125 & 0.53205 & 0.9359 & 0.46795 \tabularnewline
126 & 0.55866 & 0.88268 & 0.44134 \tabularnewline
127 & 0.528619 & 0.942763 & 0.471381 \tabularnewline
128 & 0.505913 & 0.988174 & 0.494087 \tabularnewline
129 & 0.470496 & 0.940992 & 0.529504 \tabularnewline
130 & 0.43558 & 0.87116 & 0.56442 \tabularnewline
131 & 0.407749 & 0.815499 & 0.592251 \tabularnewline
132 & 0.378413 & 0.756827 & 0.621587 \tabularnewline
133 & 0.351033 & 0.702066 & 0.648967 \tabularnewline
134 & 0.31971 & 0.639421 & 0.68029 \tabularnewline
135 & 0.346598 & 0.693196 & 0.653402 \tabularnewline
136 & 0.325427 & 0.650854 & 0.674573 \tabularnewline
137 & 0.31327 & 0.62654 & 0.68673 \tabularnewline
138 & 0.331865 & 0.663729 & 0.668135 \tabularnewline
139 & 0.324116 & 0.648233 & 0.675884 \tabularnewline
140 & 0.294676 & 0.589353 & 0.705324 \tabularnewline
141 & 0.382877 & 0.765754 & 0.617123 \tabularnewline
142 & 0.412733 & 0.825467 & 0.587267 \tabularnewline
143 & 0.438334 & 0.876667 & 0.561666 \tabularnewline
144 & 0.417245 & 0.834491 & 0.582755 \tabularnewline
145 & 0.471437 & 0.942874 & 0.528563 \tabularnewline
146 & 0.442176 & 0.884351 & 0.557824 \tabularnewline
147 & 0.44792 & 0.89584 & 0.55208 \tabularnewline
148 & 0.418131 & 0.836262 & 0.581869 \tabularnewline
149 & 0.421495 & 0.842991 & 0.578505 \tabularnewline
150 & 0.438678 & 0.877357 & 0.561322 \tabularnewline
151 & 0.434373 & 0.868746 & 0.565627 \tabularnewline
152 & 0.408516 & 0.817031 & 0.591484 \tabularnewline
153 & 0.380953 & 0.761906 & 0.619047 \tabularnewline
154 & 0.357619 & 0.715239 & 0.642381 \tabularnewline
155 & 0.376576 & 0.753152 & 0.623424 \tabularnewline
156 & 0.437152 & 0.874303 & 0.562848 \tabularnewline
157 & 0.403439 & 0.806878 & 0.596561 \tabularnewline
158 & 0.379085 & 0.75817 & 0.620915 \tabularnewline
159 & 0.383242 & 0.766485 & 0.616758 \tabularnewline
160 & 0.460435 & 0.92087 & 0.539565 \tabularnewline
161 & 0.424647 & 0.849295 & 0.575353 \tabularnewline
162 & 0.409725 & 0.81945 & 0.590275 \tabularnewline
163 & 0.437497 & 0.874995 & 0.562503 \tabularnewline
164 & 0.487753 & 0.975506 & 0.512247 \tabularnewline
165 & 0.463709 & 0.927417 & 0.536291 \tabularnewline
166 & 0.439389 & 0.878778 & 0.560611 \tabularnewline
167 & 0.418404 & 0.836809 & 0.581596 \tabularnewline
168 & 0.403881 & 0.807762 & 0.596119 \tabularnewline
169 & 0.442448 & 0.884896 & 0.557552 \tabularnewline
170 & 0.428046 & 0.856091 & 0.571954 \tabularnewline
171 & 0.416428 & 0.832857 & 0.583572 \tabularnewline
172 & 0.381574 & 0.763148 & 0.618426 \tabularnewline
173 & 0.365921 & 0.731843 & 0.634079 \tabularnewline
174 & 0.341825 & 0.683649 & 0.658175 \tabularnewline
175 & 0.31086 & 0.621721 & 0.68914 \tabularnewline
176 & 0.283557 & 0.567114 & 0.716443 \tabularnewline
177 & 0.253247 & 0.506493 & 0.746753 \tabularnewline
178 & 0.229838 & 0.459677 & 0.770162 \tabularnewline
179 & 0.212289 & 0.424578 & 0.787711 \tabularnewline
180 & 0.189716 & 0.379432 & 0.810284 \tabularnewline
181 & 0.275317 & 0.550633 & 0.724683 \tabularnewline
182 & 0.255198 & 0.510396 & 0.744802 \tabularnewline
183 & 0.230571 & 0.461142 & 0.769429 \tabularnewline
184 & 0.212596 & 0.425192 & 0.787404 \tabularnewline
185 & 0.294662 & 0.589325 & 0.705338 \tabularnewline
186 & 0.298633 & 0.597266 & 0.701367 \tabularnewline
187 & 0.269656 & 0.539312 & 0.730344 \tabularnewline
188 & 0.313558 & 0.627115 & 0.686442 \tabularnewline
189 & 0.337609 & 0.675218 & 0.662391 \tabularnewline
190 & 0.305497 & 0.610993 & 0.694503 \tabularnewline
191 & 0.716593 & 0.566814 & 0.283407 \tabularnewline
192 & 0.687586 & 0.624829 & 0.312414 \tabularnewline
193 & 0.650462 & 0.699076 & 0.349538 \tabularnewline
194 & 0.639825 & 0.720351 & 0.360175 \tabularnewline
195 & 0.604747 & 0.790505 & 0.395253 \tabularnewline
196 & 0.580172 & 0.839657 & 0.419828 \tabularnewline
197 & 0.668557 & 0.662886 & 0.331443 \tabularnewline
198 & 0.737016 & 0.525968 & 0.262984 \tabularnewline
199 & 0.704486 & 0.591028 & 0.295514 \tabularnewline
200 & 0.687625 & 0.624751 & 0.312375 \tabularnewline
201 & 0.656814 & 0.686373 & 0.343186 \tabularnewline
202 & 0.617169 & 0.765662 & 0.382831 \tabularnewline
203 & 0.587039 & 0.825922 & 0.412961 \tabularnewline
204 & 0.643282 & 0.713436 & 0.356718 \tabularnewline
205 & 0.602065 & 0.79587 & 0.397935 \tabularnewline
206 & 0.560743 & 0.878514 & 0.439257 \tabularnewline
207 & 0.572253 & 0.855494 & 0.427747 \tabularnewline
208 & 0.665224 & 0.669552 & 0.334776 \tabularnewline
209 & 0.622852 & 0.754295 & 0.377148 \tabularnewline
210 & 0.659361 & 0.681277 & 0.340639 \tabularnewline
211 & 0.62208 & 0.75584 & 0.37792 \tabularnewline
212 & 0.589229 & 0.821543 & 0.410771 \tabularnewline
213 & 0.717364 & 0.565273 & 0.282636 \tabularnewline
214 & 0.710928 & 0.578144 & 0.289072 \tabularnewline
215 & 0.66849 & 0.66302 & 0.33151 \tabularnewline
216 & 0.627687 & 0.744626 & 0.372313 \tabularnewline
217 & 0.677813 & 0.644373 & 0.322187 \tabularnewline
218 & 0.693079 & 0.613842 & 0.306921 \tabularnewline
219 & 0.648906 & 0.702188 & 0.351094 \tabularnewline
220 & 0.693609 & 0.612782 & 0.306391 \tabularnewline
221 & 0.658002 & 0.683995 & 0.341998 \tabularnewline
222 & 0.686902 & 0.626195 & 0.313098 \tabularnewline
223 & 0.668923 & 0.662154 & 0.331077 \tabularnewline
224 & 0.619767 & 0.760467 & 0.380233 \tabularnewline
225 & 0.880209 & 0.239582 & 0.119791 \tabularnewline
226 & 0.860815 & 0.27837 & 0.139185 \tabularnewline
227 & 0.888155 & 0.22369 & 0.111845 \tabularnewline
228 & 0.88651 & 0.226979 & 0.11349 \tabularnewline
229 & 0.866131 & 0.267738 & 0.133869 \tabularnewline
230 & 0.834177 & 0.331646 & 0.165823 \tabularnewline
231 & 0.794652 & 0.410697 & 0.205348 \tabularnewline
232 & 0.761609 & 0.476782 & 0.238391 \tabularnewline
233 & 0.88947 & 0.221059 & 0.11053 \tabularnewline
234 & 0.898986 & 0.202028 & 0.101014 \tabularnewline
235 & 0.868861 & 0.262277 & 0.131139 \tabularnewline
236 & 0.834026 & 0.331947 & 0.165974 \tabularnewline
237 & 0.869132 & 0.261736 & 0.130868 \tabularnewline
238 & 0.909514 & 0.180972 & 0.0904858 \tabularnewline
239 & 0.879865 & 0.240269 & 0.120135 \tabularnewline
240 & 0.839791 & 0.320418 & 0.160209 \tabularnewline
241 & 0.878308 & 0.243383 & 0.121692 \tabularnewline
242 & 0.931864 & 0.136273 & 0.0681365 \tabularnewline
243 & 0.913423 & 0.173154 & 0.0865772 \tabularnewline
244 & 0.880014 & 0.239972 & 0.119986 \tabularnewline
245 & 0.968627 & 0.0627456 & 0.0313728 \tabularnewline
246 & 0.949762 & 0.100476 & 0.0502379 \tabularnewline
247 & 0.921306 & 0.157387 & 0.0786937 \tabularnewline
248 & 0.960907 & 0.0781859 & 0.0390929 \tabularnewline
249 & 0.932173 & 0.135653 & 0.0678266 \tabularnewline
250 & 0.913555 & 0.172891 & 0.0864455 \tabularnewline
251 & 0.859775 & 0.28045 & 0.140225 \tabularnewline
252 & 0.934563 & 0.130874 & 0.0654372 \tabularnewline
253 & 0.873095 & 0.253811 & 0.126905 \tabularnewline
254 & 0.780657 & 0.438686 & 0.219343 \tabularnewline
255 & 0.63101 & 0.73798 & 0.36899 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&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]9[/C][C]0.268217[/C][C]0.536434[/C][C]0.731783[/C][/ROW]
[ROW][C]10[/C][C]0.183492[/C][C]0.366984[/C][C]0.816508[/C][/ROW]
[ROW][C]11[/C][C]0.106102[/C][C]0.212205[/C][C]0.893898[/C][/ROW]
[ROW][C]12[/C][C]0.926158[/C][C]0.147684[/C][C]0.073842[/C][/ROW]
[ROW][C]13[/C][C]0.899858[/C][C]0.200284[/C][C]0.100142[/C][/ROW]
[ROW][C]14[/C][C]0.907223[/C][C]0.185554[/C][C]0.0927768[/C][/ROW]
[ROW][C]15[/C][C]0.898807[/C][C]0.202386[/C][C]0.101193[/C][/ROW]
[ROW][C]16[/C][C]0.924181[/C][C]0.151639[/C][C]0.0758194[/C][/ROW]
[ROW][C]17[/C][C]0.906216[/C][C]0.187568[/C][C]0.0937842[/C][/ROW]
[ROW][C]18[/C][C]0.938098[/C][C]0.123804[/C][C]0.0619021[/C][/ROW]
[ROW][C]19[/C][C]0.916381[/C][C]0.167238[/C][C]0.083619[/C][/ROW]
[ROW][C]20[/C][C]0.945929[/C][C]0.108143[/C][C]0.0540714[/C][/ROW]
[ROW][C]21[/C][C]0.941389[/C][C]0.117223[/C][C]0.0586113[/C][/ROW]
[ROW][C]22[/C][C]0.919535[/C][C]0.16093[/C][C]0.080465[/C][/ROW]
[ROW][C]23[/C][C]0.935084[/C][C]0.129832[/C][C]0.064916[/C][/ROW]
[ROW][C]24[/C][C]0.926688[/C][C]0.146624[/C][C]0.0733118[/C][/ROW]
[ROW][C]25[/C][C]0.942078[/C][C]0.115845[/C][C]0.0579224[/C][/ROW]
[ROW][C]26[/C][C]0.942871[/C][C]0.114257[/C][C]0.0571287[/C][/ROW]
[ROW][C]27[/C][C]0.928909[/C][C]0.142183[/C][C]0.0710914[/C][/ROW]
[ROW][C]28[/C][C]0.907233[/C][C]0.185534[/C][C]0.0927671[/C][/ROW]
[ROW][C]29[/C][C]0.895758[/C][C]0.208484[/C][C]0.104242[/C][/ROW]
[ROW][C]30[/C][C]0.86664[/C][C]0.26672[/C][C]0.13336[/C][/ROW]
[ROW][C]31[/C][C]0.835975[/C][C]0.32805[/C][C]0.164025[/C][/ROW]
[ROW][C]32[/C][C]0.836027[/C][C]0.327945[/C][C]0.163973[/C][/ROW]
[ROW][C]33[/C][C]0.804372[/C][C]0.391256[/C][C]0.195628[/C][/ROW]
[ROW][C]34[/C][C]0.831242[/C][C]0.337516[/C][C]0.168758[/C][/ROW]
[ROW][C]35[/C][C]0.795675[/C][C]0.408651[/C][C]0.204325[/C][/ROW]
[ROW][C]36[/C][C]0.755742[/C][C]0.488517[/C][C]0.244258[/C][/ROW]
[ROW][C]37[/C][C]0.722744[/C][C]0.554511[/C][C]0.277256[/C][/ROW]
[ROW][C]38[/C][C]0.677158[/C][C]0.645684[/C][C]0.322842[/C][/ROW]
[ROW][C]39[/C][C]0.629436[/C][C]0.741128[/C][C]0.370564[/C][/ROW]
[ROW][C]40[/C][C]0.580965[/C][C]0.83807[/C][C]0.419035[/C][/ROW]
[ROW][C]41[/C][C]0.529738[/C][C]0.940524[/C][C]0.470262[/C][/ROW]
[ROW][C]42[/C][C]0.485807[/C][C]0.971615[/C][C]0.514193[/C][/ROW]
[ROW][C]43[/C][C]0.718876[/C][C]0.562247[/C][C]0.281124[/C][/ROW]
[ROW][C]44[/C][C]0.763351[/C][C]0.473297[/C][C]0.236649[/C][/ROW]
[ROW][C]45[/C][C]0.727452[/C][C]0.545096[/C][C]0.272548[/C][/ROW]
[ROW][C]46[/C][C]0.688733[/C][C]0.622534[/C][C]0.311267[/C][/ROW]
[ROW][C]47[/C][C]0.66884[/C][C]0.662319[/C][C]0.33116[/C][/ROW]
[ROW][C]48[/C][C]0.631198[/C][C]0.737603[/C][C]0.368802[/C][/ROW]
[ROW][C]49[/C][C]0.597835[/C][C]0.804329[/C][C]0.402165[/C][/ROW]
[ROW][C]50[/C][C]0.564715[/C][C]0.87057[/C][C]0.435285[/C][/ROW]
[ROW][C]51[/C][C]0.519819[/C][C]0.960362[/C][C]0.480181[/C][/ROW]
[ROW][C]52[/C][C]0.475836[/C][C]0.951671[/C][C]0.524164[/C][/ROW]
[ROW][C]53[/C][C]0.431007[/C][C]0.862015[/C][C]0.568993[/C][/ROW]
[ROW][C]54[/C][C]0.398428[/C][C]0.796857[/C][C]0.601572[/C][/ROW]
[ROW][C]55[/C][C]0.361799[/C][C]0.723598[/C][C]0.638201[/C][/ROW]
[ROW][C]56[/C][C]0.359027[/C][C]0.718054[/C][C]0.640973[/C][/ROW]
[ROW][C]57[/C][C]0.321536[/C][C]0.643073[/C][C]0.678464[/C][/ROW]
[ROW][C]58[/C][C]0.295512[/C][C]0.591023[/C][C]0.704488[/C][/ROW]
[ROW][C]59[/C][C]0.268126[/C][C]0.536252[/C][C]0.731874[/C][/ROW]
[ROW][C]60[/C][C]0.239102[/C][C]0.478203[/C][C]0.760898[/C][/ROW]
[ROW][C]61[/C][C]0.220997[/C][C]0.441994[/C][C]0.779003[/C][/ROW]
[ROW][C]62[/C][C]0.209362[/C][C]0.418725[/C][C]0.790638[/C][/ROW]
[ROW][C]63[/C][C]0.22563[/C][C]0.45126[/C][C]0.77437[/C][/ROW]
[ROW][C]64[/C][C]0.289008[/C][C]0.578015[/C][C]0.710992[/C][/ROW]
[ROW][C]65[/C][C]0.367724[/C][C]0.735448[/C][C]0.632276[/C][/ROW]
[ROW][C]66[/C][C]0.383375[/C][C]0.76675[/C][C]0.616625[/C][/ROW]
[ROW][C]67[/C][C]0.34474[/C][C]0.68948[/C][C]0.65526[/C][/ROW]
[ROW][C]68[/C][C]0.313616[/C][C]0.627232[/C][C]0.686384[/C][/ROW]
[ROW][C]69[/C][C]0.299987[/C][C]0.599974[/C][C]0.700013[/C][/ROW]
[ROW][C]70[/C][C]0.26641[/C][C]0.53282[/C][C]0.73359[/C][/ROW]
[ROW][C]71[/C][C]0.235979[/C][C]0.471959[/C][C]0.764021[/C][/ROW]
[ROW][C]72[/C][C]0.270061[/C][C]0.540122[/C][C]0.729939[/C][/ROW]
[ROW][C]73[/C][C]0.280647[/C][C]0.561294[/C][C]0.719353[/C][/ROW]
[ROW][C]74[/C][C]0.256508[/C][C]0.513015[/C][C]0.743492[/C][/ROW]
[ROW][C]75[/C][C]0.270092[/C][C]0.540184[/C][C]0.729908[/C][/ROW]
[ROW][C]76[/C][C]0.319457[/C][C]0.638914[/C][C]0.680543[/C][/ROW]
[ROW][C]77[/C][C]0.288183[/C][C]0.576367[/C][C]0.711817[/C][/ROW]
[ROW][C]78[/C][C]0.256191[/C][C]0.512383[/C][C]0.743809[/C][/ROW]
[ROW][C]79[/C][C]0.240706[/C][C]0.481413[/C][C]0.759294[/C][/ROW]
[ROW][C]80[/C][C]0.366362[/C][C]0.732725[/C][C]0.633638[/C][/ROW]
[ROW][C]81[/C][C]0.352932[/C][C]0.705864[/C][C]0.647068[/C][/ROW]
[ROW][C]82[/C][C]0.321552[/C][C]0.643105[/C][C]0.678448[/C][/ROW]
[ROW][C]83[/C][C]0.288306[/C][C]0.576612[/C][C]0.711694[/C][/ROW]
[ROW][C]84[/C][C]0.25744[/C][C]0.514879[/C][C]0.74256[/C][/ROW]
[ROW][C]85[/C][C]0.244035[/C][C]0.48807[/C][C]0.755965[/C][/ROW]
[ROW][C]86[/C][C]0.226513[/C][C]0.453026[/C][C]0.773487[/C][/ROW]
[ROW][C]87[/C][C]0.200338[/C][C]0.400676[/C][C]0.799662[/C][/ROW]
[ROW][C]88[/C][C]0.230954[/C][C]0.461907[/C][C]0.769046[/C][/ROW]
[ROW][C]89[/C][C]0.230003[/C][C]0.460007[/C][C]0.769997[/C][/ROW]
[ROW][C]90[/C][C]0.205957[/C][C]0.411914[/C][C]0.794043[/C][/ROW]
[ROW][C]91[/C][C]0.258997[/C][C]0.517995[/C][C]0.741003[/C][/ROW]
[ROW][C]92[/C][C]0.243432[/C][C]0.486864[/C][C]0.756568[/C][/ROW]
[ROW][C]93[/C][C]0.266393[/C][C]0.532786[/C][C]0.733607[/C][/ROW]
[ROW][C]94[/C][C]0.268735[/C][C]0.53747[/C][C]0.731265[/C][/ROW]
[ROW][C]95[/C][C]0.255829[/C][C]0.511658[/C][C]0.744171[/C][/ROW]
[ROW][C]96[/C][C]0.227403[/C][C]0.454806[/C][C]0.772597[/C][/ROW]
[ROW][C]97[/C][C]0.21222[/C][C]0.42444[/C][C]0.78778[/C][/ROW]
[ROW][C]98[/C][C]0.199199[/C][C]0.398399[/C][C]0.800801[/C][/ROW]
[ROW][C]99[/C][C]0.178588[/C][C]0.357176[/C][C]0.821412[/C][/ROW]
[ROW][C]100[/C][C]0.156845[/C][C]0.31369[/C][C]0.843155[/C][/ROW]
[ROW][C]101[/C][C]0.141787[/C][C]0.283573[/C][C]0.858213[/C][/ROW]
[ROW][C]102[/C][C]0.149978[/C][C]0.299957[/C][C]0.850022[/C][/ROW]
[ROW][C]103[/C][C]0.13301[/C][C]0.266019[/C][C]0.86699[/C][/ROW]
[ROW][C]104[/C][C]0.134084[/C][C]0.268169[/C][C]0.865916[/C][/ROW]
[ROW][C]105[/C][C]0.116664[/C][C]0.233329[/C][C]0.883336[/C][/ROW]
[ROW][C]106[/C][C]0.100653[/C][C]0.201306[/C][C]0.899347[/C][/ROW]
[ROW][C]107[/C][C]0.0856683[/C][C]0.171337[/C][C]0.914332[/C][/ROW]
[ROW][C]108[/C][C]0.0992637[/C][C]0.198527[/C][C]0.900736[/C][/ROW]
[ROW][C]109[/C][C]0.121524[/C][C]0.243049[/C][C]0.878476[/C][/ROW]
[ROW][C]110[/C][C]0.144025[/C][C]0.288049[/C][C]0.855975[/C][/ROW]
[ROW][C]111[/C][C]0.130467[/C][C]0.260935[/C][C]0.869533[/C][/ROW]
[ROW][C]112[/C][C]0.174728[/C][C]0.349457[/C][C]0.825272[/C][/ROW]
[ROW][C]113[/C][C]0.46616[/C][C]0.93232[/C][C]0.53384[/C][/ROW]
[ROW][C]114[/C][C]0.432868[/C][C]0.865735[/C][C]0.567132[/C][/ROW]
[ROW][C]115[/C][C]0.438032[/C][C]0.876064[/C][C]0.561968[/C][/ROW]
[ROW][C]116[/C][C]0.512181[/C][C]0.975637[/C][C]0.487819[/C][/ROW]
[ROW][C]117[/C][C]0.482437[/C][C]0.964873[/C][C]0.517563[/C][/ROW]
[ROW][C]118[/C][C]0.455981[/C][C]0.911962[/C][C]0.544019[/C][/ROW]
[ROW][C]119[/C][C]0.560449[/C][C]0.879101[/C][C]0.439551[/C][/ROW]
[ROW][C]120[/C][C]0.601718[/C][C]0.796565[/C][C]0.398282[/C][/ROW]
[ROW][C]121[/C][C]0.577006[/C][C]0.845988[/C][C]0.422994[/C][/ROW]
[ROW][C]122[/C][C]0.621912[/C][C]0.756177[/C][C]0.378088[/C][/ROW]
[ROW][C]123[/C][C]0.589169[/C][C]0.821663[/C][C]0.410831[/C][/ROW]
[ROW][C]124[/C][C]0.554728[/C][C]0.890543[/C][C]0.445272[/C][/ROW]
[ROW][C]125[/C][C]0.53205[/C][C]0.9359[/C][C]0.46795[/C][/ROW]
[ROW][C]126[/C][C]0.55866[/C][C]0.88268[/C][C]0.44134[/C][/ROW]
[ROW][C]127[/C][C]0.528619[/C][C]0.942763[/C][C]0.471381[/C][/ROW]
[ROW][C]128[/C][C]0.505913[/C][C]0.988174[/C][C]0.494087[/C][/ROW]
[ROW][C]129[/C][C]0.470496[/C][C]0.940992[/C][C]0.529504[/C][/ROW]
[ROW][C]130[/C][C]0.43558[/C][C]0.87116[/C][C]0.56442[/C][/ROW]
[ROW][C]131[/C][C]0.407749[/C][C]0.815499[/C][C]0.592251[/C][/ROW]
[ROW][C]132[/C][C]0.378413[/C][C]0.756827[/C][C]0.621587[/C][/ROW]
[ROW][C]133[/C][C]0.351033[/C][C]0.702066[/C][C]0.648967[/C][/ROW]
[ROW][C]134[/C][C]0.31971[/C][C]0.639421[/C][C]0.68029[/C][/ROW]
[ROW][C]135[/C][C]0.346598[/C][C]0.693196[/C][C]0.653402[/C][/ROW]
[ROW][C]136[/C][C]0.325427[/C][C]0.650854[/C][C]0.674573[/C][/ROW]
[ROW][C]137[/C][C]0.31327[/C][C]0.62654[/C][C]0.68673[/C][/ROW]
[ROW][C]138[/C][C]0.331865[/C][C]0.663729[/C][C]0.668135[/C][/ROW]
[ROW][C]139[/C][C]0.324116[/C][C]0.648233[/C][C]0.675884[/C][/ROW]
[ROW][C]140[/C][C]0.294676[/C][C]0.589353[/C][C]0.705324[/C][/ROW]
[ROW][C]141[/C][C]0.382877[/C][C]0.765754[/C][C]0.617123[/C][/ROW]
[ROW][C]142[/C][C]0.412733[/C][C]0.825467[/C][C]0.587267[/C][/ROW]
[ROW][C]143[/C][C]0.438334[/C][C]0.876667[/C][C]0.561666[/C][/ROW]
[ROW][C]144[/C][C]0.417245[/C][C]0.834491[/C][C]0.582755[/C][/ROW]
[ROW][C]145[/C][C]0.471437[/C][C]0.942874[/C][C]0.528563[/C][/ROW]
[ROW][C]146[/C][C]0.442176[/C][C]0.884351[/C][C]0.557824[/C][/ROW]
[ROW][C]147[/C][C]0.44792[/C][C]0.89584[/C][C]0.55208[/C][/ROW]
[ROW][C]148[/C][C]0.418131[/C][C]0.836262[/C][C]0.581869[/C][/ROW]
[ROW][C]149[/C][C]0.421495[/C][C]0.842991[/C][C]0.578505[/C][/ROW]
[ROW][C]150[/C][C]0.438678[/C][C]0.877357[/C][C]0.561322[/C][/ROW]
[ROW][C]151[/C][C]0.434373[/C][C]0.868746[/C][C]0.565627[/C][/ROW]
[ROW][C]152[/C][C]0.408516[/C][C]0.817031[/C][C]0.591484[/C][/ROW]
[ROW][C]153[/C][C]0.380953[/C][C]0.761906[/C][C]0.619047[/C][/ROW]
[ROW][C]154[/C][C]0.357619[/C][C]0.715239[/C][C]0.642381[/C][/ROW]
[ROW][C]155[/C][C]0.376576[/C][C]0.753152[/C][C]0.623424[/C][/ROW]
[ROW][C]156[/C][C]0.437152[/C][C]0.874303[/C][C]0.562848[/C][/ROW]
[ROW][C]157[/C][C]0.403439[/C][C]0.806878[/C][C]0.596561[/C][/ROW]
[ROW][C]158[/C][C]0.379085[/C][C]0.75817[/C][C]0.620915[/C][/ROW]
[ROW][C]159[/C][C]0.383242[/C][C]0.766485[/C][C]0.616758[/C][/ROW]
[ROW][C]160[/C][C]0.460435[/C][C]0.92087[/C][C]0.539565[/C][/ROW]
[ROW][C]161[/C][C]0.424647[/C][C]0.849295[/C][C]0.575353[/C][/ROW]
[ROW][C]162[/C][C]0.409725[/C][C]0.81945[/C][C]0.590275[/C][/ROW]
[ROW][C]163[/C][C]0.437497[/C][C]0.874995[/C][C]0.562503[/C][/ROW]
[ROW][C]164[/C][C]0.487753[/C][C]0.975506[/C][C]0.512247[/C][/ROW]
[ROW][C]165[/C][C]0.463709[/C][C]0.927417[/C][C]0.536291[/C][/ROW]
[ROW][C]166[/C][C]0.439389[/C][C]0.878778[/C][C]0.560611[/C][/ROW]
[ROW][C]167[/C][C]0.418404[/C][C]0.836809[/C][C]0.581596[/C][/ROW]
[ROW][C]168[/C][C]0.403881[/C][C]0.807762[/C][C]0.596119[/C][/ROW]
[ROW][C]169[/C][C]0.442448[/C][C]0.884896[/C][C]0.557552[/C][/ROW]
[ROW][C]170[/C][C]0.428046[/C][C]0.856091[/C][C]0.571954[/C][/ROW]
[ROW][C]171[/C][C]0.416428[/C][C]0.832857[/C][C]0.583572[/C][/ROW]
[ROW][C]172[/C][C]0.381574[/C][C]0.763148[/C][C]0.618426[/C][/ROW]
[ROW][C]173[/C][C]0.365921[/C][C]0.731843[/C][C]0.634079[/C][/ROW]
[ROW][C]174[/C][C]0.341825[/C][C]0.683649[/C][C]0.658175[/C][/ROW]
[ROW][C]175[/C][C]0.31086[/C][C]0.621721[/C][C]0.68914[/C][/ROW]
[ROW][C]176[/C][C]0.283557[/C][C]0.567114[/C][C]0.716443[/C][/ROW]
[ROW][C]177[/C][C]0.253247[/C][C]0.506493[/C][C]0.746753[/C][/ROW]
[ROW][C]178[/C][C]0.229838[/C][C]0.459677[/C][C]0.770162[/C][/ROW]
[ROW][C]179[/C][C]0.212289[/C][C]0.424578[/C][C]0.787711[/C][/ROW]
[ROW][C]180[/C][C]0.189716[/C][C]0.379432[/C][C]0.810284[/C][/ROW]
[ROW][C]181[/C][C]0.275317[/C][C]0.550633[/C][C]0.724683[/C][/ROW]
[ROW][C]182[/C][C]0.255198[/C][C]0.510396[/C][C]0.744802[/C][/ROW]
[ROW][C]183[/C][C]0.230571[/C][C]0.461142[/C][C]0.769429[/C][/ROW]
[ROW][C]184[/C][C]0.212596[/C][C]0.425192[/C][C]0.787404[/C][/ROW]
[ROW][C]185[/C][C]0.294662[/C][C]0.589325[/C][C]0.705338[/C][/ROW]
[ROW][C]186[/C][C]0.298633[/C][C]0.597266[/C][C]0.701367[/C][/ROW]
[ROW][C]187[/C][C]0.269656[/C][C]0.539312[/C][C]0.730344[/C][/ROW]
[ROW][C]188[/C][C]0.313558[/C][C]0.627115[/C][C]0.686442[/C][/ROW]
[ROW][C]189[/C][C]0.337609[/C][C]0.675218[/C][C]0.662391[/C][/ROW]
[ROW][C]190[/C][C]0.305497[/C][C]0.610993[/C][C]0.694503[/C][/ROW]
[ROW][C]191[/C][C]0.716593[/C][C]0.566814[/C][C]0.283407[/C][/ROW]
[ROW][C]192[/C][C]0.687586[/C][C]0.624829[/C][C]0.312414[/C][/ROW]
[ROW][C]193[/C][C]0.650462[/C][C]0.699076[/C][C]0.349538[/C][/ROW]
[ROW][C]194[/C][C]0.639825[/C][C]0.720351[/C][C]0.360175[/C][/ROW]
[ROW][C]195[/C][C]0.604747[/C][C]0.790505[/C][C]0.395253[/C][/ROW]
[ROW][C]196[/C][C]0.580172[/C][C]0.839657[/C][C]0.419828[/C][/ROW]
[ROW][C]197[/C][C]0.668557[/C][C]0.662886[/C][C]0.331443[/C][/ROW]
[ROW][C]198[/C][C]0.737016[/C][C]0.525968[/C][C]0.262984[/C][/ROW]
[ROW][C]199[/C][C]0.704486[/C][C]0.591028[/C][C]0.295514[/C][/ROW]
[ROW][C]200[/C][C]0.687625[/C][C]0.624751[/C][C]0.312375[/C][/ROW]
[ROW][C]201[/C][C]0.656814[/C][C]0.686373[/C][C]0.343186[/C][/ROW]
[ROW][C]202[/C][C]0.617169[/C][C]0.765662[/C][C]0.382831[/C][/ROW]
[ROW][C]203[/C][C]0.587039[/C][C]0.825922[/C][C]0.412961[/C][/ROW]
[ROW][C]204[/C][C]0.643282[/C][C]0.713436[/C][C]0.356718[/C][/ROW]
[ROW][C]205[/C][C]0.602065[/C][C]0.79587[/C][C]0.397935[/C][/ROW]
[ROW][C]206[/C][C]0.560743[/C][C]0.878514[/C][C]0.439257[/C][/ROW]
[ROW][C]207[/C][C]0.572253[/C][C]0.855494[/C][C]0.427747[/C][/ROW]
[ROW][C]208[/C][C]0.665224[/C][C]0.669552[/C][C]0.334776[/C][/ROW]
[ROW][C]209[/C][C]0.622852[/C][C]0.754295[/C][C]0.377148[/C][/ROW]
[ROW][C]210[/C][C]0.659361[/C][C]0.681277[/C][C]0.340639[/C][/ROW]
[ROW][C]211[/C][C]0.62208[/C][C]0.75584[/C][C]0.37792[/C][/ROW]
[ROW][C]212[/C][C]0.589229[/C][C]0.821543[/C][C]0.410771[/C][/ROW]
[ROW][C]213[/C][C]0.717364[/C][C]0.565273[/C][C]0.282636[/C][/ROW]
[ROW][C]214[/C][C]0.710928[/C][C]0.578144[/C][C]0.289072[/C][/ROW]
[ROW][C]215[/C][C]0.66849[/C][C]0.66302[/C][C]0.33151[/C][/ROW]
[ROW][C]216[/C][C]0.627687[/C][C]0.744626[/C][C]0.372313[/C][/ROW]
[ROW][C]217[/C][C]0.677813[/C][C]0.644373[/C][C]0.322187[/C][/ROW]
[ROW][C]218[/C][C]0.693079[/C][C]0.613842[/C][C]0.306921[/C][/ROW]
[ROW][C]219[/C][C]0.648906[/C][C]0.702188[/C][C]0.351094[/C][/ROW]
[ROW][C]220[/C][C]0.693609[/C][C]0.612782[/C][C]0.306391[/C][/ROW]
[ROW][C]221[/C][C]0.658002[/C][C]0.683995[/C][C]0.341998[/C][/ROW]
[ROW][C]222[/C][C]0.686902[/C][C]0.626195[/C][C]0.313098[/C][/ROW]
[ROW][C]223[/C][C]0.668923[/C][C]0.662154[/C][C]0.331077[/C][/ROW]
[ROW][C]224[/C][C]0.619767[/C][C]0.760467[/C][C]0.380233[/C][/ROW]
[ROW][C]225[/C][C]0.880209[/C][C]0.239582[/C][C]0.119791[/C][/ROW]
[ROW][C]226[/C][C]0.860815[/C][C]0.27837[/C][C]0.139185[/C][/ROW]
[ROW][C]227[/C][C]0.888155[/C][C]0.22369[/C][C]0.111845[/C][/ROW]
[ROW][C]228[/C][C]0.88651[/C][C]0.226979[/C][C]0.11349[/C][/ROW]
[ROW][C]229[/C][C]0.866131[/C][C]0.267738[/C][C]0.133869[/C][/ROW]
[ROW][C]230[/C][C]0.834177[/C][C]0.331646[/C][C]0.165823[/C][/ROW]
[ROW][C]231[/C][C]0.794652[/C][C]0.410697[/C][C]0.205348[/C][/ROW]
[ROW][C]232[/C][C]0.761609[/C][C]0.476782[/C][C]0.238391[/C][/ROW]
[ROW][C]233[/C][C]0.88947[/C][C]0.221059[/C][C]0.11053[/C][/ROW]
[ROW][C]234[/C][C]0.898986[/C][C]0.202028[/C][C]0.101014[/C][/ROW]
[ROW][C]235[/C][C]0.868861[/C][C]0.262277[/C][C]0.131139[/C][/ROW]
[ROW][C]236[/C][C]0.834026[/C][C]0.331947[/C][C]0.165974[/C][/ROW]
[ROW][C]237[/C][C]0.869132[/C][C]0.261736[/C][C]0.130868[/C][/ROW]
[ROW][C]238[/C][C]0.909514[/C][C]0.180972[/C][C]0.0904858[/C][/ROW]
[ROW][C]239[/C][C]0.879865[/C][C]0.240269[/C][C]0.120135[/C][/ROW]
[ROW][C]240[/C][C]0.839791[/C][C]0.320418[/C][C]0.160209[/C][/ROW]
[ROW][C]241[/C][C]0.878308[/C][C]0.243383[/C][C]0.121692[/C][/ROW]
[ROW][C]242[/C][C]0.931864[/C][C]0.136273[/C][C]0.0681365[/C][/ROW]
[ROW][C]243[/C][C]0.913423[/C][C]0.173154[/C][C]0.0865772[/C][/ROW]
[ROW][C]244[/C][C]0.880014[/C][C]0.239972[/C][C]0.119986[/C][/ROW]
[ROW][C]245[/C][C]0.968627[/C][C]0.0627456[/C][C]0.0313728[/C][/ROW]
[ROW][C]246[/C][C]0.949762[/C][C]0.100476[/C][C]0.0502379[/C][/ROW]
[ROW][C]247[/C][C]0.921306[/C][C]0.157387[/C][C]0.0786937[/C][/ROW]
[ROW][C]248[/C][C]0.960907[/C][C]0.0781859[/C][C]0.0390929[/C][/ROW]
[ROW][C]249[/C][C]0.932173[/C][C]0.135653[/C][C]0.0678266[/C][/ROW]
[ROW][C]250[/C][C]0.913555[/C][C]0.172891[/C][C]0.0864455[/C][/ROW]
[ROW][C]251[/C][C]0.859775[/C][C]0.28045[/C][C]0.140225[/C][/ROW]
[ROW][C]252[/C][C]0.934563[/C][C]0.130874[/C][C]0.0654372[/C][/ROW]
[ROW][C]253[/C][C]0.873095[/C][C]0.253811[/C][C]0.126905[/C][/ROW]
[ROW][C]254[/C][C]0.780657[/C][C]0.438686[/C][C]0.219343[/C][/ROW]
[ROW][C]255[/C][C]0.63101[/C][C]0.73798[/C][C]0.36899[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&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
90.2682170.5364340.731783
100.1834920.3669840.816508
110.1061020.2122050.893898
120.9261580.1476840.073842
130.8998580.2002840.100142
140.9072230.1855540.0927768
150.8988070.2023860.101193
160.9241810.1516390.0758194
170.9062160.1875680.0937842
180.9380980.1238040.0619021
190.9163810.1672380.083619
200.9459290.1081430.0540714
210.9413890.1172230.0586113
220.9195350.160930.080465
230.9350840.1298320.064916
240.9266880.1466240.0733118
250.9420780.1158450.0579224
260.9428710.1142570.0571287
270.9289090.1421830.0710914
280.9072330.1855340.0927671
290.8957580.2084840.104242
300.866640.266720.13336
310.8359750.328050.164025
320.8360270.3279450.163973
330.8043720.3912560.195628
340.8312420.3375160.168758
350.7956750.4086510.204325
360.7557420.4885170.244258
370.7227440.5545110.277256
380.6771580.6456840.322842
390.6294360.7411280.370564
400.5809650.838070.419035
410.5297380.9405240.470262
420.4858070.9716150.514193
430.7188760.5622470.281124
440.7633510.4732970.236649
450.7274520.5450960.272548
460.6887330.6225340.311267
470.668840.6623190.33116
480.6311980.7376030.368802
490.5978350.8043290.402165
500.5647150.870570.435285
510.5198190.9603620.480181
520.4758360.9516710.524164
530.4310070.8620150.568993
540.3984280.7968570.601572
550.3617990.7235980.638201
560.3590270.7180540.640973
570.3215360.6430730.678464
580.2955120.5910230.704488
590.2681260.5362520.731874
600.2391020.4782030.760898
610.2209970.4419940.779003
620.2093620.4187250.790638
630.225630.451260.77437
640.2890080.5780150.710992
650.3677240.7354480.632276
660.3833750.766750.616625
670.344740.689480.65526
680.3136160.6272320.686384
690.2999870.5999740.700013
700.266410.532820.73359
710.2359790.4719590.764021
720.2700610.5401220.729939
730.2806470.5612940.719353
740.2565080.5130150.743492
750.2700920.5401840.729908
760.3194570.6389140.680543
770.2881830.5763670.711817
780.2561910.5123830.743809
790.2407060.4814130.759294
800.3663620.7327250.633638
810.3529320.7058640.647068
820.3215520.6431050.678448
830.2883060.5766120.711694
840.257440.5148790.74256
850.2440350.488070.755965
860.2265130.4530260.773487
870.2003380.4006760.799662
880.2309540.4619070.769046
890.2300030.4600070.769997
900.2059570.4119140.794043
910.2589970.5179950.741003
920.2434320.4868640.756568
930.2663930.5327860.733607
940.2687350.537470.731265
950.2558290.5116580.744171
960.2274030.4548060.772597
970.212220.424440.78778
980.1991990.3983990.800801
990.1785880.3571760.821412
1000.1568450.313690.843155
1010.1417870.2835730.858213
1020.1499780.2999570.850022
1030.133010.2660190.86699
1040.1340840.2681690.865916
1050.1166640.2333290.883336
1060.1006530.2013060.899347
1070.08566830.1713370.914332
1080.09926370.1985270.900736
1090.1215240.2430490.878476
1100.1440250.2880490.855975
1110.1304670.2609350.869533
1120.1747280.3494570.825272
1130.466160.932320.53384
1140.4328680.8657350.567132
1150.4380320.8760640.561968
1160.5121810.9756370.487819
1170.4824370.9648730.517563
1180.4559810.9119620.544019
1190.5604490.8791010.439551
1200.6017180.7965650.398282
1210.5770060.8459880.422994
1220.6219120.7561770.378088
1230.5891690.8216630.410831
1240.5547280.8905430.445272
1250.532050.93590.46795
1260.558660.882680.44134
1270.5286190.9427630.471381
1280.5059130.9881740.494087
1290.4704960.9409920.529504
1300.435580.871160.56442
1310.4077490.8154990.592251
1320.3784130.7568270.621587
1330.3510330.7020660.648967
1340.319710.6394210.68029
1350.3465980.6931960.653402
1360.3254270.6508540.674573
1370.313270.626540.68673
1380.3318650.6637290.668135
1390.3241160.6482330.675884
1400.2946760.5893530.705324
1410.3828770.7657540.617123
1420.4127330.8254670.587267
1430.4383340.8766670.561666
1440.4172450.8344910.582755
1450.4714370.9428740.528563
1460.4421760.8843510.557824
1470.447920.895840.55208
1480.4181310.8362620.581869
1490.4214950.8429910.578505
1500.4386780.8773570.561322
1510.4343730.8687460.565627
1520.4085160.8170310.591484
1530.3809530.7619060.619047
1540.3576190.7152390.642381
1550.3765760.7531520.623424
1560.4371520.8743030.562848
1570.4034390.8068780.596561
1580.3790850.758170.620915
1590.3832420.7664850.616758
1600.4604350.920870.539565
1610.4246470.8492950.575353
1620.4097250.819450.590275
1630.4374970.8749950.562503
1640.4877530.9755060.512247
1650.4637090.9274170.536291
1660.4393890.8787780.560611
1670.4184040.8368090.581596
1680.4038810.8077620.596119
1690.4424480.8848960.557552
1700.4280460.8560910.571954
1710.4164280.8328570.583572
1720.3815740.7631480.618426
1730.3659210.7318430.634079
1740.3418250.6836490.658175
1750.310860.6217210.68914
1760.2835570.5671140.716443
1770.2532470.5064930.746753
1780.2298380.4596770.770162
1790.2122890.4245780.787711
1800.1897160.3794320.810284
1810.2753170.5506330.724683
1820.2551980.5103960.744802
1830.2305710.4611420.769429
1840.2125960.4251920.787404
1850.2946620.5893250.705338
1860.2986330.5972660.701367
1870.2696560.5393120.730344
1880.3135580.6271150.686442
1890.3376090.6752180.662391
1900.3054970.6109930.694503
1910.7165930.5668140.283407
1920.6875860.6248290.312414
1930.6504620.6990760.349538
1940.6398250.7203510.360175
1950.6047470.7905050.395253
1960.5801720.8396570.419828
1970.6685570.6628860.331443
1980.7370160.5259680.262984
1990.7044860.5910280.295514
2000.6876250.6247510.312375
2010.6568140.6863730.343186
2020.6171690.7656620.382831
2030.5870390.8259220.412961
2040.6432820.7134360.356718
2050.6020650.795870.397935
2060.5607430.8785140.439257
2070.5722530.8554940.427747
2080.6652240.6695520.334776
2090.6228520.7542950.377148
2100.6593610.6812770.340639
2110.622080.755840.37792
2120.5892290.8215430.410771
2130.7173640.5652730.282636
2140.7109280.5781440.289072
2150.668490.663020.33151
2160.6276870.7446260.372313
2170.6778130.6443730.322187
2180.6930790.6138420.306921
2190.6489060.7021880.351094
2200.6936090.6127820.306391
2210.6580020.6839950.341998
2220.6869020.6261950.313098
2230.6689230.6621540.331077
2240.6197670.7604670.380233
2250.8802090.2395820.119791
2260.8608150.278370.139185
2270.8881550.223690.111845
2280.886510.2269790.11349
2290.8661310.2677380.133869
2300.8341770.3316460.165823
2310.7946520.4106970.205348
2320.7616090.4767820.238391
2330.889470.2210590.11053
2340.8989860.2020280.101014
2350.8688610.2622770.131139
2360.8340260.3319470.165974
2370.8691320.2617360.130868
2380.9095140.1809720.0904858
2390.8798650.2402690.120135
2400.8397910.3204180.160209
2410.8783080.2433830.121692
2420.9318640.1362730.0681365
2430.9134230.1731540.0865772
2440.8800140.2399720.119986
2450.9686270.06274560.0313728
2460.9497620.1004760.0502379
2470.9213060.1573870.0786937
2480.9609070.07818590.0390929
2490.9321730.1356530.0678266
2500.9135550.1728910.0864455
2510.8597750.280450.140225
2520.9345630.1308740.0654372
2530.8730950.2538110.126905
2540.7806570.4386860.219343
2550.631010.737980.36899






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level20.00809717OK

\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 & 0 & 0 & OK \tabularnewline
10% type I error level & 2 & 0.00809717 & OK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=253522&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]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]2[/C][C]0.00809717[/C][C]OK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=253522&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=253522&T=6

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level00OK
10% type I error level20.00809717OK


Figures (Output of Computation)

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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
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')
}