Free Statistics

of Irreproducible Research!

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationMon, 15 Dec 2014 12:28:02 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/15/t1418647248ssxyk4k8m7527dm.htm/, Retrieved Thu, 31 Oct 2024 23:56:12 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=268261, Retrieved Thu, 31 Oct 2024 23:56:12 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact97
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [AMS.E] [2014-12-15 12:28:02] [21b927ddce509724d48ffb8407994bd0] [Current]
Feedback Forum

Post a new message
Dataseries X:
50 0
54 0
71 0
54 0
65 0
73 0
52 0
84 0
42 0
66 0
65 0
73 0
75 0
72 0
66 0
70 0
81 0
69 0
71 0
68 0
70 0
68 0
67 0
76 0
70 0
60 0
72 0
71 0
70 0
64 0
76 0
68 0
76 0
65 0
67 0
75 0
60 0
73 0
63 0
70 0
66 0
64 0
70 0
75 0
60 0
66 0
59 0
78 0
67 0
59 0
66 0
71 0
66 0
72 0
71 0
59 0
78 0
65 0
65 0
71 0
72 0
66 0
69 0
51 1
56 1
67 1
69 1
57 1
56 1
55 1
63 1
67 1
65 1
47 1
76 1
64 1
68 1
64 1
65 1
71 1
63 1
60 1
68 1
72 1
70 1
61 1
61 1
62 1
71 1
71 1
51 1
56 1
70 1
73 1
76 1
68 1
48 1
52 1
60 1
59 1
57 1
79 1
60 1
60 1
59 1
62 1
59 1
61 1
71 1
57 1
66 1
63 1
69 1
58 1
59 1
48 1
66 1
73 1
67 1
61 1
68 1
75 1
62 1
69 1
58 1
60 1
74 1
55 1
62 1
63 1
69 1
58 1
58 1
68 1
72 1
62 1
62 1
65 1
69 1
66 1
72 1
62 1
75 1
58 1
66 1
55 1
47 1
72 1
62 1
64 1
64 1
19 1
50 1
68 1
70 1
79 1
69 1
71 1
48 1
73 1
74 1
66 1
71 1
74 1
78 1
75 1
53 1
60 1
70 1
69 1
65 1
78 1
78 1
59 1
72 1
70 1
63 1
63 1
71 1
74 1
67 1
66 1
62 1
80 1
73 1
67 1
61 1
73 1
74 1
32 1
69 1
69 1
84 1
64 1
58 1
59 1
78 1
57 1
60 1
68 1
68 1
73 1
69 1
67 1
60 1
65 1
66 1
74 1
81 1
72 1
55 1
49 1
74 1
53 1
64 1
65 1
57 1
51 1
80 1
67 1
70 1
74 1
75 1
70 1
69 1
65 1
55 1
71 1
65 1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.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 & 6 seconds \tabularnewline
R Server & 'Sir Maurice George Kendall' @ kendall.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Maurice George Kendall' @ kendall.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=0

As an alternative you can also use a 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 time6 seconds
R Server'Sir Maurice George Kendall' @ kendall.wessa.net







Multiple Linear Regression - Estimated Regression Equation
AMS.E[t] = + 67.5714 -2.78227year.bin[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
AMS.E[t] =  +  67.5714 -2.78227year.bin[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]AMS.E[t] =  +  67.5714 -2.78227year.bin[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=1

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Estimated Regression Equation
AMS.E[t] = + 67.5714 -2.78227year.bin[t] + e[t]







Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)67.57141.0721563.028.2522e-1464.1261e-146
year.bin-2.782271.25927-2.2090.02814380.0140719

\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) & 67.5714 & 1.07215 & 63.02 & 8.2522e-146 & 4.1261e-146 \tabularnewline
year.bin & -2.78227 & 1.25927 & -2.209 & 0.0281438 & 0.0140719 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&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]67.5714[/C][C]1.07215[/C][C]63.02[/C][C]8.2522e-146[/C][C]4.1261e-146[/C][/ROW]
[ROW][C]year.bin[/C][C]-2.78227[/C][C]1.25927[/C][C]-2.209[/C][C]0.0281438[/C][C]0.0140719[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=2

As an alternative you can also use a 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)67.57141.0721563.028.2522e-1464.1261e-146
year.bin-2.782271.25927-2.2090.02814380.0140719







Multiple Linear Regression - Regression Statistics
Multiple R0.145093
R-squared0.0210521
Adjusted R-squared0.0167395
F-TEST (value)4.88159
F-TEST (DF numerator)1
F-TEST (DF denominator)227
p-value0.0281438
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8.50992
Sum Squared Residuals16439

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.145093 \tabularnewline
R-squared & 0.0210521 \tabularnewline
Adjusted R-squared & 0.0167395 \tabularnewline
F-TEST (value) & 4.88159 \tabularnewline
F-TEST (DF numerator) & 1 \tabularnewline
F-TEST (DF denominator) & 227 \tabularnewline
p-value & 0.0281438 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 8.50992 \tabularnewline
Sum Squared Residuals & 16439 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.145093[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0210521[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0167395[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.88159[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]1[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]227[/C][/ROW]
[ROW][C]p-value[/C][C]0.0281438[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]8.50992[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]16439[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=3

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Regression Statistics
Multiple R0.145093
R-squared0.0210521
Adjusted R-squared0.0167395
F-TEST (value)4.88159
F-TEST (DF numerator)1
F-TEST (DF denominator)227
p-value0.0281438
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation8.50992
Sum Squared Residuals16439







Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15067.5714-17.5714
25467.5714-13.5714
37167.57143.42857
45467.5714-13.5714
56567.5714-2.57143
67367.57145.42857
75267.5714-15.5714
88467.571416.4286
94267.5714-25.5714
106667.5714-1.57143
116567.5714-2.57143
127367.57145.42857
137567.57147.42857
147267.57144.42857
156667.5714-1.57143
167067.57142.42857
178167.571413.4286
186967.57141.42857
197167.57143.42857
206867.57140.428571
217067.57142.42857
226867.57140.428571
236767.5714-0.571429
247667.57148.42857
257067.57142.42857
266067.5714-7.57143
277267.57144.42857
287167.57143.42857
297067.57142.42857
306467.5714-3.57143
317667.57148.42857
326867.57140.428571
337667.57148.42857
346567.5714-2.57143
356767.5714-0.571429
367567.57147.42857
376067.5714-7.57143
387367.57145.42857
396367.5714-4.57143
407067.57142.42857
416667.5714-1.57143
426467.5714-3.57143
437067.57142.42857
447567.57147.42857
456067.5714-7.57143
466667.5714-1.57143
475967.5714-8.57143
487867.571410.4286
496767.5714-0.571429
505967.5714-8.57143
516667.5714-1.57143
527167.57143.42857
536667.5714-1.57143
547267.57144.42857
557167.57143.42857
565967.5714-8.57143
577867.571410.4286
586567.5714-2.57143
596567.5714-2.57143
607167.57143.42857
617267.57144.42857
626667.5714-1.57143
636967.57141.42857
645164.7892-13.7892
655664.7892-8.78916
666764.78922.21084
676964.78924.21084
685764.7892-7.78916
695664.7892-8.78916
705564.7892-9.78916
716364.7892-1.78916
726764.78922.21084
736564.78920.210843
744764.7892-17.7892
757664.789211.2108
766464.7892-0.789157
776864.78923.21084
786464.7892-0.789157
796564.78920.210843
807164.78926.21084
816364.7892-1.78916
826064.7892-4.78916
836864.78923.21084
847264.78927.21084
857064.78925.21084
866164.7892-3.78916
876164.7892-3.78916
886264.7892-2.78916
897164.78926.21084
907164.78926.21084
915164.7892-13.7892
925664.7892-8.78916
937064.78925.21084
947364.78928.21084
957664.789211.2108
966864.78923.21084
974864.7892-16.7892
985264.7892-12.7892
996064.7892-4.78916
1005964.7892-5.78916
1015764.7892-7.78916
1027964.789214.2108
1036064.7892-4.78916
1046064.7892-4.78916
1055964.7892-5.78916
1066264.7892-2.78916
1075964.7892-5.78916
1086164.7892-3.78916
1097164.78926.21084
1105764.7892-7.78916
1116664.78921.21084
1126364.7892-1.78916
1136964.78924.21084
1145864.7892-6.78916
1155964.7892-5.78916
1164864.7892-16.7892
1176664.78921.21084
1187364.78928.21084
1196764.78922.21084
1206164.7892-3.78916
1216864.78923.21084
1227564.789210.2108
1236264.7892-2.78916
1246964.78924.21084
1255864.7892-6.78916
1266064.7892-4.78916
1277464.78929.21084
1285564.7892-9.78916
1296264.7892-2.78916
1306364.7892-1.78916
1316964.78924.21084
1325864.7892-6.78916
1335864.7892-6.78916
1346864.78923.21084
1357264.78927.21084
1366264.7892-2.78916
1376264.7892-2.78916
1386564.78920.210843
1396964.78924.21084
1406664.78921.21084
1417264.78927.21084
1426264.7892-2.78916
1437564.789210.2108
1445864.7892-6.78916
1456664.78921.21084
1465564.7892-9.78916
1474764.7892-17.7892
1487264.78927.21084
1496264.7892-2.78916
1506464.7892-0.789157
1516464.7892-0.789157
1521964.7892-45.7892
1535064.7892-14.7892
1546864.78923.21084
1557064.78925.21084
1567964.789214.2108
1576964.78924.21084
1587164.78926.21084
1594864.7892-16.7892
1607364.78928.21084
1617464.78929.21084
1626664.78921.21084
1637164.78926.21084
1647464.78929.21084
1657864.789213.2108
1667564.789210.2108
1675364.7892-11.7892
1686064.7892-4.78916
1697064.78925.21084
1706964.78924.21084
1716564.78920.210843
1727864.789213.2108
1737864.789213.2108
1745964.7892-5.78916
1757264.78927.21084
1767064.78925.21084
1776364.7892-1.78916
1786364.7892-1.78916
1797164.78926.21084
1807464.78929.21084
1816764.78922.21084
1826664.78921.21084
1836264.7892-2.78916
1848064.789215.2108
1857364.78928.21084
1866764.78922.21084
1876164.7892-3.78916
1887364.78928.21084
1897464.78929.21084
1903264.7892-32.7892
1916964.78924.21084
1926964.78924.21084
1938464.789219.2108
1946464.7892-0.789157
1955864.7892-6.78916
1965964.7892-5.78916
1977864.789213.2108
1985764.7892-7.78916
1996064.7892-4.78916
2006864.78923.21084
2016864.78923.21084
2027364.78928.21084
2036964.78924.21084
2046764.78922.21084
2056064.7892-4.78916
2066564.78920.210843
2076664.78921.21084
2087464.78929.21084
2098164.789216.2108
2107264.78927.21084
2115564.7892-9.78916
2124964.7892-15.7892
2137464.78929.21084
2145364.7892-11.7892
2156464.7892-0.789157
2166564.78920.210843
2175764.7892-7.78916
2185164.7892-13.7892
2198064.789215.2108
2206764.78922.21084
2217064.78925.21084
2227464.78929.21084
2237564.789210.2108
2247064.78925.21084
2256964.78924.21084
2266564.78920.210843
2275564.7892-9.78916
2287164.78926.21084
2296564.78920.210843

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 50 & 67.5714 & -17.5714 \tabularnewline
2 & 54 & 67.5714 & -13.5714 \tabularnewline
3 & 71 & 67.5714 & 3.42857 \tabularnewline
4 & 54 & 67.5714 & -13.5714 \tabularnewline
5 & 65 & 67.5714 & -2.57143 \tabularnewline
6 & 73 & 67.5714 & 5.42857 \tabularnewline
7 & 52 & 67.5714 & -15.5714 \tabularnewline
8 & 84 & 67.5714 & 16.4286 \tabularnewline
9 & 42 & 67.5714 & -25.5714 \tabularnewline
10 & 66 & 67.5714 & -1.57143 \tabularnewline
11 & 65 & 67.5714 & -2.57143 \tabularnewline
12 & 73 & 67.5714 & 5.42857 \tabularnewline
13 & 75 & 67.5714 & 7.42857 \tabularnewline
14 & 72 & 67.5714 & 4.42857 \tabularnewline
15 & 66 & 67.5714 & -1.57143 \tabularnewline
16 & 70 & 67.5714 & 2.42857 \tabularnewline
17 & 81 & 67.5714 & 13.4286 \tabularnewline
18 & 69 & 67.5714 & 1.42857 \tabularnewline
19 & 71 & 67.5714 & 3.42857 \tabularnewline
20 & 68 & 67.5714 & 0.428571 \tabularnewline
21 & 70 & 67.5714 & 2.42857 \tabularnewline
22 & 68 & 67.5714 & 0.428571 \tabularnewline
23 & 67 & 67.5714 & -0.571429 \tabularnewline
24 & 76 & 67.5714 & 8.42857 \tabularnewline
25 & 70 & 67.5714 & 2.42857 \tabularnewline
26 & 60 & 67.5714 & -7.57143 \tabularnewline
27 & 72 & 67.5714 & 4.42857 \tabularnewline
28 & 71 & 67.5714 & 3.42857 \tabularnewline
29 & 70 & 67.5714 & 2.42857 \tabularnewline
30 & 64 & 67.5714 & -3.57143 \tabularnewline
31 & 76 & 67.5714 & 8.42857 \tabularnewline
32 & 68 & 67.5714 & 0.428571 \tabularnewline
33 & 76 & 67.5714 & 8.42857 \tabularnewline
34 & 65 & 67.5714 & -2.57143 \tabularnewline
35 & 67 & 67.5714 & -0.571429 \tabularnewline
36 & 75 & 67.5714 & 7.42857 \tabularnewline
37 & 60 & 67.5714 & -7.57143 \tabularnewline
38 & 73 & 67.5714 & 5.42857 \tabularnewline
39 & 63 & 67.5714 & -4.57143 \tabularnewline
40 & 70 & 67.5714 & 2.42857 \tabularnewline
41 & 66 & 67.5714 & -1.57143 \tabularnewline
42 & 64 & 67.5714 & -3.57143 \tabularnewline
43 & 70 & 67.5714 & 2.42857 \tabularnewline
44 & 75 & 67.5714 & 7.42857 \tabularnewline
45 & 60 & 67.5714 & -7.57143 \tabularnewline
46 & 66 & 67.5714 & -1.57143 \tabularnewline
47 & 59 & 67.5714 & -8.57143 \tabularnewline
48 & 78 & 67.5714 & 10.4286 \tabularnewline
49 & 67 & 67.5714 & -0.571429 \tabularnewline
50 & 59 & 67.5714 & -8.57143 \tabularnewline
51 & 66 & 67.5714 & -1.57143 \tabularnewline
52 & 71 & 67.5714 & 3.42857 \tabularnewline
53 & 66 & 67.5714 & -1.57143 \tabularnewline
54 & 72 & 67.5714 & 4.42857 \tabularnewline
55 & 71 & 67.5714 & 3.42857 \tabularnewline
56 & 59 & 67.5714 & -8.57143 \tabularnewline
57 & 78 & 67.5714 & 10.4286 \tabularnewline
58 & 65 & 67.5714 & -2.57143 \tabularnewline
59 & 65 & 67.5714 & -2.57143 \tabularnewline
60 & 71 & 67.5714 & 3.42857 \tabularnewline
61 & 72 & 67.5714 & 4.42857 \tabularnewline
62 & 66 & 67.5714 & -1.57143 \tabularnewline
63 & 69 & 67.5714 & 1.42857 \tabularnewline
64 & 51 & 64.7892 & -13.7892 \tabularnewline
65 & 56 & 64.7892 & -8.78916 \tabularnewline
66 & 67 & 64.7892 & 2.21084 \tabularnewline
67 & 69 & 64.7892 & 4.21084 \tabularnewline
68 & 57 & 64.7892 & -7.78916 \tabularnewline
69 & 56 & 64.7892 & -8.78916 \tabularnewline
70 & 55 & 64.7892 & -9.78916 \tabularnewline
71 & 63 & 64.7892 & -1.78916 \tabularnewline
72 & 67 & 64.7892 & 2.21084 \tabularnewline
73 & 65 & 64.7892 & 0.210843 \tabularnewline
74 & 47 & 64.7892 & -17.7892 \tabularnewline
75 & 76 & 64.7892 & 11.2108 \tabularnewline
76 & 64 & 64.7892 & -0.789157 \tabularnewline
77 & 68 & 64.7892 & 3.21084 \tabularnewline
78 & 64 & 64.7892 & -0.789157 \tabularnewline
79 & 65 & 64.7892 & 0.210843 \tabularnewline
80 & 71 & 64.7892 & 6.21084 \tabularnewline
81 & 63 & 64.7892 & -1.78916 \tabularnewline
82 & 60 & 64.7892 & -4.78916 \tabularnewline
83 & 68 & 64.7892 & 3.21084 \tabularnewline
84 & 72 & 64.7892 & 7.21084 \tabularnewline
85 & 70 & 64.7892 & 5.21084 \tabularnewline
86 & 61 & 64.7892 & -3.78916 \tabularnewline
87 & 61 & 64.7892 & -3.78916 \tabularnewline
88 & 62 & 64.7892 & -2.78916 \tabularnewline
89 & 71 & 64.7892 & 6.21084 \tabularnewline
90 & 71 & 64.7892 & 6.21084 \tabularnewline
91 & 51 & 64.7892 & -13.7892 \tabularnewline
92 & 56 & 64.7892 & -8.78916 \tabularnewline
93 & 70 & 64.7892 & 5.21084 \tabularnewline
94 & 73 & 64.7892 & 8.21084 \tabularnewline
95 & 76 & 64.7892 & 11.2108 \tabularnewline
96 & 68 & 64.7892 & 3.21084 \tabularnewline
97 & 48 & 64.7892 & -16.7892 \tabularnewline
98 & 52 & 64.7892 & -12.7892 \tabularnewline
99 & 60 & 64.7892 & -4.78916 \tabularnewline
100 & 59 & 64.7892 & -5.78916 \tabularnewline
101 & 57 & 64.7892 & -7.78916 \tabularnewline
102 & 79 & 64.7892 & 14.2108 \tabularnewline
103 & 60 & 64.7892 & -4.78916 \tabularnewline
104 & 60 & 64.7892 & -4.78916 \tabularnewline
105 & 59 & 64.7892 & -5.78916 \tabularnewline
106 & 62 & 64.7892 & -2.78916 \tabularnewline
107 & 59 & 64.7892 & -5.78916 \tabularnewline
108 & 61 & 64.7892 & -3.78916 \tabularnewline
109 & 71 & 64.7892 & 6.21084 \tabularnewline
110 & 57 & 64.7892 & -7.78916 \tabularnewline
111 & 66 & 64.7892 & 1.21084 \tabularnewline
112 & 63 & 64.7892 & -1.78916 \tabularnewline
113 & 69 & 64.7892 & 4.21084 \tabularnewline
114 & 58 & 64.7892 & -6.78916 \tabularnewline
115 & 59 & 64.7892 & -5.78916 \tabularnewline
116 & 48 & 64.7892 & -16.7892 \tabularnewline
117 & 66 & 64.7892 & 1.21084 \tabularnewline
118 & 73 & 64.7892 & 8.21084 \tabularnewline
119 & 67 & 64.7892 & 2.21084 \tabularnewline
120 & 61 & 64.7892 & -3.78916 \tabularnewline
121 & 68 & 64.7892 & 3.21084 \tabularnewline
122 & 75 & 64.7892 & 10.2108 \tabularnewline
123 & 62 & 64.7892 & -2.78916 \tabularnewline
124 & 69 & 64.7892 & 4.21084 \tabularnewline
125 & 58 & 64.7892 & -6.78916 \tabularnewline
126 & 60 & 64.7892 & -4.78916 \tabularnewline
127 & 74 & 64.7892 & 9.21084 \tabularnewline
128 & 55 & 64.7892 & -9.78916 \tabularnewline
129 & 62 & 64.7892 & -2.78916 \tabularnewline
130 & 63 & 64.7892 & -1.78916 \tabularnewline
131 & 69 & 64.7892 & 4.21084 \tabularnewline
132 & 58 & 64.7892 & -6.78916 \tabularnewline
133 & 58 & 64.7892 & -6.78916 \tabularnewline
134 & 68 & 64.7892 & 3.21084 \tabularnewline
135 & 72 & 64.7892 & 7.21084 \tabularnewline
136 & 62 & 64.7892 & -2.78916 \tabularnewline
137 & 62 & 64.7892 & -2.78916 \tabularnewline
138 & 65 & 64.7892 & 0.210843 \tabularnewline
139 & 69 & 64.7892 & 4.21084 \tabularnewline
140 & 66 & 64.7892 & 1.21084 \tabularnewline
141 & 72 & 64.7892 & 7.21084 \tabularnewline
142 & 62 & 64.7892 & -2.78916 \tabularnewline
143 & 75 & 64.7892 & 10.2108 \tabularnewline
144 & 58 & 64.7892 & -6.78916 \tabularnewline
145 & 66 & 64.7892 & 1.21084 \tabularnewline
146 & 55 & 64.7892 & -9.78916 \tabularnewline
147 & 47 & 64.7892 & -17.7892 \tabularnewline
148 & 72 & 64.7892 & 7.21084 \tabularnewline
149 & 62 & 64.7892 & -2.78916 \tabularnewline
150 & 64 & 64.7892 & -0.789157 \tabularnewline
151 & 64 & 64.7892 & -0.789157 \tabularnewline
152 & 19 & 64.7892 & -45.7892 \tabularnewline
153 & 50 & 64.7892 & -14.7892 \tabularnewline
154 & 68 & 64.7892 & 3.21084 \tabularnewline
155 & 70 & 64.7892 & 5.21084 \tabularnewline
156 & 79 & 64.7892 & 14.2108 \tabularnewline
157 & 69 & 64.7892 & 4.21084 \tabularnewline
158 & 71 & 64.7892 & 6.21084 \tabularnewline
159 & 48 & 64.7892 & -16.7892 \tabularnewline
160 & 73 & 64.7892 & 8.21084 \tabularnewline
161 & 74 & 64.7892 & 9.21084 \tabularnewline
162 & 66 & 64.7892 & 1.21084 \tabularnewline
163 & 71 & 64.7892 & 6.21084 \tabularnewline
164 & 74 & 64.7892 & 9.21084 \tabularnewline
165 & 78 & 64.7892 & 13.2108 \tabularnewline
166 & 75 & 64.7892 & 10.2108 \tabularnewline
167 & 53 & 64.7892 & -11.7892 \tabularnewline
168 & 60 & 64.7892 & -4.78916 \tabularnewline
169 & 70 & 64.7892 & 5.21084 \tabularnewline
170 & 69 & 64.7892 & 4.21084 \tabularnewline
171 & 65 & 64.7892 & 0.210843 \tabularnewline
172 & 78 & 64.7892 & 13.2108 \tabularnewline
173 & 78 & 64.7892 & 13.2108 \tabularnewline
174 & 59 & 64.7892 & -5.78916 \tabularnewline
175 & 72 & 64.7892 & 7.21084 \tabularnewline
176 & 70 & 64.7892 & 5.21084 \tabularnewline
177 & 63 & 64.7892 & -1.78916 \tabularnewline
178 & 63 & 64.7892 & -1.78916 \tabularnewline
179 & 71 & 64.7892 & 6.21084 \tabularnewline
180 & 74 & 64.7892 & 9.21084 \tabularnewline
181 & 67 & 64.7892 & 2.21084 \tabularnewline
182 & 66 & 64.7892 & 1.21084 \tabularnewline
183 & 62 & 64.7892 & -2.78916 \tabularnewline
184 & 80 & 64.7892 & 15.2108 \tabularnewline
185 & 73 & 64.7892 & 8.21084 \tabularnewline
186 & 67 & 64.7892 & 2.21084 \tabularnewline
187 & 61 & 64.7892 & -3.78916 \tabularnewline
188 & 73 & 64.7892 & 8.21084 \tabularnewline
189 & 74 & 64.7892 & 9.21084 \tabularnewline
190 & 32 & 64.7892 & -32.7892 \tabularnewline
191 & 69 & 64.7892 & 4.21084 \tabularnewline
192 & 69 & 64.7892 & 4.21084 \tabularnewline
193 & 84 & 64.7892 & 19.2108 \tabularnewline
194 & 64 & 64.7892 & -0.789157 \tabularnewline
195 & 58 & 64.7892 & -6.78916 \tabularnewline
196 & 59 & 64.7892 & -5.78916 \tabularnewline
197 & 78 & 64.7892 & 13.2108 \tabularnewline
198 & 57 & 64.7892 & -7.78916 \tabularnewline
199 & 60 & 64.7892 & -4.78916 \tabularnewline
200 & 68 & 64.7892 & 3.21084 \tabularnewline
201 & 68 & 64.7892 & 3.21084 \tabularnewline
202 & 73 & 64.7892 & 8.21084 \tabularnewline
203 & 69 & 64.7892 & 4.21084 \tabularnewline
204 & 67 & 64.7892 & 2.21084 \tabularnewline
205 & 60 & 64.7892 & -4.78916 \tabularnewline
206 & 65 & 64.7892 & 0.210843 \tabularnewline
207 & 66 & 64.7892 & 1.21084 \tabularnewline
208 & 74 & 64.7892 & 9.21084 \tabularnewline
209 & 81 & 64.7892 & 16.2108 \tabularnewline
210 & 72 & 64.7892 & 7.21084 \tabularnewline
211 & 55 & 64.7892 & -9.78916 \tabularnewline
212 & 49 & 64.7892 & -15.7892 \tabularnewline
213 & 74 & 64.7892 & 9.21084 \tabularnewline
214 & 53 & 64.7892 & -11.7892 \tabularnewline
215 & 64 & 64.7892 & -0.789157 \tabularnewline
216 & 65 & 64.7892 & 0.210843 \tabularnewline
217 & 57 & 64.7892 & -7.78916 \tabularnewline
218 & 51 & 64.7892 & -13.7892 \tabularnewline
219 & 80 & 64.7892 & 15.2108 \tabularnewline
220 & 67 & 64.7892 & 2.21084 \tabularnewline
221 & 70 & 64.7892 & 5.21084 \tabularnewline
222 & 74 & 64.7892 & 9.21084 \tabularnewline
223 & 75 & 64.7892 & 10.2108 \tabularnewline
224 & 70 & 64.7892 & 5.21084 \tabularnewline
225 & 69 & 64.7892 & 4.21084 \tabularnewline
226 & 65 & 64.7892 & 0.210843 \tabularnewline
227 & 55 & 64.7892 & -9.78916 \tabularnewline
228 & 71 & 64.7892 & 6.21084 \tabularnewline
229 & 65 & 64.7892 & 0.210843 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&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]50[/C][C]67.5714[/C][C]-17.5714[/C][/ROW]
[ROW][C]2[/C][C]54[/C][C]67.5714[/C][C]-13.5714[/C][/ROW]
[ROW][C]3[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]4[/C][C]54[/C][C]67.5714[/C][C]-13.5714[/C][/ROW]
[ROW][C]5[/C][C]65[/C][C]67.5714[/C][C]-2.57143[/C][/ROW]
[ROW][C]6[/C][C]73[/C][C]67.5714[/C][C]5.42857[/C][/ROW]
[ROW][C]7[/C][C]52[/C][C]67.5714[/C][C]-15.5714[/C][/ROW]
[ROW][C]8[/C][C]84[/C][C]67.5714[/C][C]16.4286[/C][/ROW]
[ROW][C]9[/C][C]42[/C][C]67.5714[/C][C]-25.5714[/C][/ROW]
[ROW][C]10[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]11[/C][C]65[/C][C]67.5714[/C][C]-2.57143[/C][/ROW]
[ROW][C]12[/C][C]73[/C][C]67.5714[/C][C]5.42857[/C][/ROW]
[ROW][C]13[/C][C]75[/C][C]67.5714[/C][C]7.42857[/C][/ROW]
[ROW][C]14[/C][C]72[/C][C]67.5714[/C][C]4.42857[/C][/ROW]
[ROW][C]15[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]16[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]17[/C][C]81[/C][C]67.5714[/C][C]13.4286[/C][/ROW]
[ROW][C]18[/C][C]69[/C][C]67.5714[/C][C]1.42857[/C][/ROW]
[ROW][C]19[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]20[/C][C]68[/C][C]67.5714[/C][C]0.428571[/C][/ROW]
[ROW][C]21[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]22[/C][C]68[/C][C]67.5714[/C][C]0.428571[/C][/ROW]
[ROW][C]23[/C][C]67[/C][C]67.5714[/C][C]-0.571429[/C][/ROW]
[ROW][C]24[/C][C]76[/C][C]67.5714[/C][C]8.42857[/C][/ROW]
[ROW][C]25[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]26[/C][C]60[/C][C]67.5714[/C][C]-7.57143[/C][/ROW]
[ROW][C]27[/C][C]72[/C][C]67.5714[/C][C]4.42857[/C][/ROW]
[ROW][C]28[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]29[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]30[/C][C]64[/C][C]67.5714[/C][C]-3.57143[/C][/ROW]
[ROW][C]31[/C][C]76[/C][C]67.5714[/C][C]8.42857[/C][/ROW]
[ROW][C]32[/C][C]68[/C][C]67.5714[/C][C]0.428571[/C][/ROW]
[ROW][C]33[/C][C]76[/C][C]67.5714[/C][C]8.42857[/C][/ROW]
[ROW][C]34[/C][C]65[/C][C]67.5714[/C][C]-2.57143[/C][/ROW]
[ROW][C]35[/C][C]67[/C][C]67.5714[/C][C]-0.571429[/C][/ROW]
[ROW][C]36[/C][C]75[/C][C]67.5714[/C][C]7.42857[/C][/ROW]
[ROW][C]37[/C][C]60[/C][C]67.5714[/C][C]-7.57143[/C][/ROW]
[ROW][C]38[/C][C]73[/C][C]67.5714[/C][C]5.42857[/C][/ROW]
[ROW][C]39[/C][C]63[/C][C]67.5714[/C][C]-4.57143[/C][/ROW]
[ROW][C]40[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]41[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]42[/C][C]64[/C][C]67.5714[/C][C]-3.57143[/C][/ROW]
[ROW][C]43[/C][C]70[/C][C]67.5714[/C][C]2.42857[/C][/ROW]
[ROW][C]44[/C][C]75[/C][C]67.5714[/C][C]7.42857[/C][/ROW]
[ROW][C]45[/C][C]60[/C][C]67.5714[/C][C]-7.57143[/C][/ROW]
[ROW][C]46[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]47[/C][C]59[/C][C]67.5714[/C][C]-8.57143[/C][/ROW]
[ROW][C]48[/C][C]78[/C][C]67.5714[/C][C]10.4286[/C][/ROW]
[ROW][C]49[/C][C]67[/C][C]67.5714[/C][C]-0.571429[/C][/ROW]
[ROW][C]50[/C][C]59[/C][C]67.5714[/C][C]-8.57143[/C][/ROW]
[ROW][C]51[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]52[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]53[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]54[/C][C]72[/C][C]67.5714[/C][C]4.42857[/C][/ROW]
[ROW][C]55[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]56[/C][C]59[/C][C]67.5714[/C][C]-8.57143[/C][/ROW]
[ROW][C]57[/C][C]78[/C][C]67.5714[/C][C]10.4286[/C][/ROW]
[ROW][C]58[/C][C]65[/C][C]67.5714[/C][C]-2.57143[/C][/ROW]
[ROW][C]59[/C][C]65[/C][C]67.5714[/C][C]-2.57143[/C][/ROW]
[ROW][C]60[/C][C]71[/C][C]67.5714[/C][C]3.42857[/C][/ROW]
[ROW][C]61[/C][C]72[/C][C]67.5714[/C][C]4.42857[/C][/ROW]
[ROW][C]62[/C][C]66[/C][C]67.5714[/C][C]-1.57143[/C][/ROW]
[ROW][C]63[/C][C]69[/C][C]67.5714[/C][C]1.42857[/C][/ROW]
[ROW][C]64[/C][C]51[/C][C]64.7892[/C][C]-13.7892[/C][/ROW]
[ROW][C]65[/C][C]56[/C][C]64.7892[/C][C]-8.78916[/C][/ROW]
[ROW][C]66[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]67[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]68[/C][C]57[/C][C]64.7892[/C][C]-7.78916[/C][/ROW]
[ROW][C]69[/C][C]56[/C][C]64.7892[/C][C]-8.78916[/C][/ROW]
[ROW][C]70[/C][C]55[/C][C]64.7892[/C][C]-9.78916[/C][/ROW]
[ROW][C]71[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]72[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]73[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]74[/C][C]47[/C][C]64.7892[/C][C]-17.7892[/C][/ROW]
[ROW][C]75[/C][C]76[/C][C]64.7892[/C][C]11.2108[/C][/ROW]
[ROW][C]76[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]77[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]78[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]79[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]80[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]81[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]82[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]83[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]84[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]85[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]86[/C][C]61[/C][C]64.7892[/C][C]-3.78916[/C][/ROW]
[ROW][C]87[/C][C]61[/C][C]64.7892[/C][C]-3.78916[/C][/ROW]
[ROW][C]88[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]89[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]90[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]91[/C][C]51[/C][C]64.7892[/C][C]-13.7892[/C][/ROW]
[ROW][C]92[/C][C]56[/C][C]64.7892[/C][C]-8.78916[/C][/ROW]
[ROW][C]93[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]94[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]95[/C][C]76[/C][C]64.7892[/C][C]11.2108[/C][/ROW]
[ROW][C]96[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]97[/C][C]48[/C][C]64.7892[/C][C]-16.7892[/C][/ROW]
[ROW][C]98[/C][C]52[/C][C]64.7892[/C][C]-12.7892[/C][/ROW]
[ROW][C]99[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]100[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]101[/C][C]57[/C][C]64.7892[/C][C]-7.78916[/C][/ROW]
[ROW][C]102[/C][C]79[/C][C]64.7892[/C][C]14.2108[/C][/ROW]
[ROW][C]103[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]104[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]105[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]106[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]107[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]108[/C][C]61[/C][C]64.7892[/C][C]-3.78916[/C][/ROW]
[ROW][C]109[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]110[/C][C]57[/C][C]64.7892[/C][C]-7.78916[/C][/ROW]
[ROW][C]111[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]112[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]113[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]114[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]115[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]116[/C][C]48[/C][C]64.7892[/C][C]-16.7892[/C][/ROW]
[ROW][C]117[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]118[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]119[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]120[/C][C]61[/C][C]64.7892[/C][C]-3.78916[/C][/ROW]
[ROW][C]121[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]122[/C][C]75[/C][C]64.7892[/C][C]10.2108[/C][/ROW]
[ROW][C]123[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]124[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]125[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]126[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]127[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]128[/C][C]55[/C][C]64.7892[/C][C]-9.78916[/C][/ROW]
[ROW][C]129[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]130[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]131[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]132[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]133[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]134[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]135[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]136[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]137[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]138[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]139[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]140[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]141[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]142[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]143[/C][C]75[/C][C]64.7892[/C][C]10.2108[/C][/ROW]
[ROW][C]144[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]145[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]146[/C][C]55[/C][C]64.7892[/C][C]-9.78916[/C][/ROW]
[ROW][C]147[/C][C]47[/C][C]64.7892[/C][C]-17.7892[/C][/ROW]
[ROW][C]148[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]149[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]150[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]151[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]152[/C][C]19[/C][C]64.7892[/C][C]-45.7892[/C][/ROW]
[ROW][C]153[/C][C]50[/C][C]64.7892[/C][C]-14.7892[/C][/ROW]
[ROW][C]154[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]155[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]156[/C][C]79[/C][C]64.7892[/C][C]14.2108[/C][/ROW]
[ROW][C]157[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]158[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]159[/C][C]48[/C][C]64.7892[/C][C]-16.7892[/C][/ROW]
[ROW][C]160[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]161[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]162[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]163[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]164[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]165[/C][C]78[/C][C]64.7892[/C][C]13.2108[/C][/ROW]
[ROW][C]166[/C][C]75[/C][C]64.7892[/C][C]10.2108[/C][/ROW]
[ROW][C]167[/C][C]53[/C][C]64.7892[/C][C]-11.7892[/C][/ROW]
[ROW][C]168[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]169[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]170[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]171[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]172[/C][C]78[/C][C]64.7892[/C][C]13.2108[/C][/ROW]
[ROW][C]173[/C][C]78[/C][C]64.7892[/C][C]13.2108[/C][/ROW]
[ROW][C]174[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]175[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]176[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]177[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]178[/C][C]63[/C][C]64.7892[/C][C]-1.78916[/C][/ROW]
[ROW][C]179[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]180[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]181[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]182[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]183[/C][C]62[/C][C]64.7892[/C][C]-2.78916[/C][/ROW]
[ROW][C]184[/C][C]80[/C][C]64.7892[/C][C]15.2108[/C][/ROW]
[ROW][C]185[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]186[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]187[/C][C]61[/C][C]64.7892[/C][C]-3.78916[/C][/ROW]
[ROW][C]188[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]189[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]190[/C][C]32[/C][C]64.7892[/C][C]-32.7892[/C][/ROW]
[ROW][C]191[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]192[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]193[/C][C]84[/C][C]64.7892[/C][C]19.2108[/C][/ROW]
[ROW][C]194[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]195[/C][C]58[/C][C]64.7892[/C][C]-6.78916[/C][/ROW]
[ROW][C]196[/C][C]59[/C][C]64.7892[/C][C]-5.78916[/C][/ROW]
[ROW][C]197[/C][C]78[/C][C]64.7892[/C][C]13.2108[/C][/ROW]
[ROW][C]198[/C][C]57[/C][C]64.7892[/C][C]-7.78916[/C][/ROW]
[ROW][C]199[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]200[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]201[/C][C]68[/C][C]64.7892[/C][C]3.21084[/C][/ROW]
[ROW][C]202[/C][C]73[/C][C]64.7892[/C][C]8.21084[/C][/ROW]
[ROW][C]203[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]204[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]205[/C][C]60[/C][C]64.7892[/C][C]-4.78916[/C][/ROW]
[ROW][C]206[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]207[/C][C]66[/C][C]64.7892[/C][C]1.21084[/C][/ROW]
[ROW][C]208[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]209[/C][C]81[/C][C]64.7892[/C][C]16.2108[/C][/ROW]
[ROW][C]210[/C][C]72[/C][C]64.7892[/C][C]7.21084[/C][/ROW]
[ROW][C]211[/C][C]55[/C][C]64.7892[/C][C]-9.78916[/C][/ROW]
[ROW][C]212[/C][C]49[/C][C]64.7892[/C][C]-15.7892[/C][/ROW]
[ROW][C]213[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]214[/C][C]53[/C][C]64.7892[/C][C]-11.7892[/C][/ROW]
[ROW][C]215[/C][C]64[/C][C]64.7892[/C][C]-0.789157[/C][/ROW]
[ROW][C]216[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]217[/C][C]57[/C][C]64.7892[/C][C]-7.78916[/C][/ROW]
[ROW][C]218[/C][C]51[/C][C]64.7892[/C][C]-13.7892[/C][/ROW]
[ROW][C]219[/C][C]80[/C][C]64.7892[/C][C]15.2108[/C][/ROW]
[ROW][C]220[/C][C]67[/C][C]64.7892[/C][C]2.21084[/C][/ROW]
[ROW][C]221[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]222[/C][C]74[/C][C]64.7892[/C][C]9.21084[/C][/ROW]
[ROW][C]223[/C][C]75[/C][C]64.7892[/C][C]10.2108[/C][/ROW]
[ROW][C]224[/C][C]70[/C][C]64.7892[/C][C]5.21084[/C][/ROW]
[ROW][C]225[/C][C]69[/C][C]64.7892[/C][C]4.21084[/C][/ROW]
[ROW][C]226[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[ROW][C]227[/C][C]55[/C][C]64.7892[/C][C]-9.78916[/C][/ROW]
[ROW][C]228[/C][C]71[/C][C]64.7892[/C][C]6.21084[/C][/ROW]
[ROW][C]229[/C][C]65[/C][C]64.7892[/C][C]0.210843[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=4

As an alternative you can also use a QR Code:  

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

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
15067.5714-17.5714
25467.5714-13.5714
37167.57143.42857
45467.5714-13.5714
56567.5714-2.57143
67367.57145.42857
75267.5714-15.5714
88467.571416.4286
94267.5714-25.5714
106667.5714-1.57143
116567.5714-2.57143
127367.57145.42857
137567.57147.42857
147267.57144.42857
156667.5714-1.57143
167067.57142.42857
178167.571413.4286
186967.57141.42857
197167.57143.42857
206867.57140.428571
217067.57142.42857
226867.57140.428571
236767.5714-0.571429
247667.57148.42857
257067.57142.42857
266067.5714-7.57143
277267.57144.42857
287167.57143.42857
297067.57142.42857
306467.5714-3.57143
317667.57148.42857
326867.57140.428571
337667.57148.42857
346567.5714-2.57143
356767.5714-0.571429
367567.57147.42857
376067.5714-7.57143
387367.57145.42857
396367.5714-4.57143
407067.57142.42857
416667.5714-1.57143
426467.5714-3.57143
437067.57142.42857
447567.57147.42857
456067.5714-7.57143
466667.5714-1.57143
475967.5714-8.57143
487867.571410.4286
496767.5714-0.571429
505967.5714-8.57143
516667.5714-1.57143
527167.57143.42857
536667.5714-1.57143
547267.57144.42857
557167.57143.42857
565967.5714-8.57143
577867.571410.4286
586567.5714-2.57143
596567.5714-2.57143
607167.57143.42857
617267.57144.42857
626667.5714-1.57143
636967.57141.42857
645164.7892-13.7892
655664.7892-8.78916
666764.78922.21084
676964.78924.21084
685764.7892-7.78916
695664.7892-8.78916
705564.7892-9.78916
716364.7892-1.78916
726764.78922.21084
736564.78920.210843
744764.7892-17.7892
757664.789211.2108
766464.7892-0.789157
776864.78923.21084
786464.7892-0.789157
796564.78920.210843
807164.78926.21084
816364.7892-1.78916
826064.7892-4.78916
836864.78923.21084
847264.78927.21084
857064.78925.21084
866164.7892-3.78916
876164.7892-3.78916
886264.7892-2.78916
897164.78926.21084
907164.78926.21084
915164.7892-13.7892
925664.7892-8.78916
937064.78925.21084
947364.78928.21084
957664.789211.2108
966864.78923.21084
974864.7892-16.7892
985264.7892-12.7892
996064.7892-4.78916
1005964.7892-5.78916
1015764.7892-7.78916
1027964.789214.2108
1036064.7892-4.78916
1046064.7892-4.78916
1055964.7892-5.78916
1066264.7892-2.78916
1075964.7892-5.78916
1086164.7892-3.78916
1097164.78926.21084
1105764.7892-7.78916
1116664.78921.21084
1126364.7892-1.78916
1136964.78924.21084
1145864.7892-6.78916
1155964.7892-5.78916
1164864.7892-16.7892
1176664.78921.21084
1187364.78928.21084
1196764.78922.21084
1206164.7892-3.78916
1216864.78923.21084
1227564.789210.2108
1236264.7892-2.78916
1246964.78924.21084
1255864.7892-6.78916
1266064.7892-4.78916
1277464.78929.21084
1285564.7892-9.78916
1296264.7892-2.78916
1306364.7892-1.78916
1316964.78924.21084
1325864.7892-6.78916
1335864.7892-6.78916
1346864.78923.21084
1357264.78927.21084
1366264.7892-2.78916
1376264.7892-2.78916
1386564.78920.210843
1396964.78924.21084
1406664.78921.21084
1417264.78927.21084
1426264.7892-2.78916
1437564.789210.2108
1445864.7892-6.78916
1456664.78921.21084
1465564.7892-9.78916
1474764.7892-17.7892
1487264.78927.21084
1496264.7892-2.78916
1506464.7892-0.789157
1516464.7892-0.789157
1521964.7892-45.7892
1535064.7892-14.7892
1546864.78923.21084
1557064.78925.21084
1567964.789214.2108
1576964.78924.21084
1587164.78926.21084
1594864.7892-16.7892
1607364.78928.21084
1617464.78929.21084
1626664.78921.21084
1637164.78926.21084
1647464.78929.21084
1657864.789213.2108
1667564.789210.2108
1675364.7892-11.7892
1686064.7892-4.78916
1697064.78925.21084
1706964.78924.21084
1716564.78920.210843
1727864.789213.2108
1737864.789213.2108
1745964.7892-5.78916
1757264.78927.21084
1767064.78925.21084
1776364.7892-1.78916
1786364.7892-1.78916
1797164.78926.21084
1807464.78929.21084
1816764.78922.21084
1826664.78921.21084
1836264.7892-2.78916
1848064.789215.2108
1857364.78928.21084
1866764.78922.21084
1876164.7892-3.78916
1887364.78928.21084
1897464.78929.21084
1903264.7892-32.7892
1916964.78924.21084
1926964.78924.21084
1938464.789219.2108
1946464.7892-0.789157
1955864.7892-6.78916
1965964.7892-5.78916
1977864.789213.2108
1985764.7892-7.78916
1996064.7892-4.78916
2006864.78923.21084
2016864.78923.21084
2027364.78928.21084
2036964.78924.21084
2046764.78922.21084
2056064.7892-4.78916
2066564.78920.210843
2076664.78921.21084
2087464.78929.21084
2098164.789216.2108
2107264.78927.21084
2115564.7892-9.78916
2124964.7892-15.7892
2137464.78929.21084
2145364.7892-11.7892
2156464.7892-0.789157
2166564.78920.210843
2175764.7892-7.78916
2185164.7892-13.7892
2198064.789215.2108
2206764.78922.21084
2217064.78925.21084
2227464.78929.21084
2237564.789210.2108
2247064.78925.21084
2256964.78924.21084
2266564.78920.210843
2275564.7892-9.78916
2287164.78926.21084
2296564.78920.210843







Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.7747570.4504860.225243
60.845870.3082590.15413
70.8308990.3382020.169101
80.9792050.04158970.0207949
90.9962660.007467850.00373393
100.9937390.01252270.00626134
110.9894570.02108510.0105425
120.9898480.02030470.0101523
130.9913530.01729320.00864658
140.9894240.02115270.0105764
150.983240.03351940.0167597
160.9771180.04576310.0228816
170.9882590.02348220.0117411
180.9826880.03462430.0173121
190.9766140.04677170.0233858
200.9663830.06723470.0336174
210.9546960.09060820.0453041
220.937950.1241010.0620504
230.9165440.1669120.0834558
240.9164580.1670840.0835418
250.8937480.2125050.106252
260.8817440.2365110.118256
270.8605740.2788510.139426
280.8328730.3342540.167127
290.7986150.4027710.201385
300.7620810.4758380.237919
310.7609430.4781140.239057
320.7162780.5674440.283722
330.7134610.5730790.286539
340.6698750.660250.330125
350.6202180.7595630.379782
360.6066420.7867160.393358
370.5945570.8108870.405443
380.5639730.8720540.436027
390.5272570.9454860.472743
400.4805510.9611030.519449
410.4320020.8640030.567998
420.3914950.782990.608505
430.348460.696920.65154
440.338250.67650.66175
450.3296550.6593110.670345
460.2882140.5764270.711786
470.2894270.5788540.710573
480.312590.6251810.68741
490.2720010.5440020.727999
500.2736310.5472620.726369
510.2374530.4749070.762547
520.2086790.4173580.791321
530.1782190.3564370.821781
540.1574780.3149570.842522
550.1356250.2712510.864375
560.1383120.2766230.861688
570.1526170.3052340.847383
580.1301130.2602260.869887
590.1104040.2208090.889596
600.09367660.1873530.906323
610.08094270.1618850.919057
620.06623510.132470.933765
630.0535180.1070360.946482
640.04890660.09781330.951093
650.042670.085340.95733
660.0474770.09495410.952523
670.04880090.09760170.951199
680.04205620.08411250.957944
690.03685730.07371470.963143
700.0330370.0660740.966963
710.02729510.05459030.972705
720.02501260.05002510.974987
730.0207630.04152610.979237
740.03479570.06959150.965204
750.05748360.1149670.942516
760.04767630.09535260.952324
770.04310370.08620750.956896
780.03505450.07010910.964945
790.02860580.05721160.971394
800.02859610.05719220.971404
810.02267570.04535150.977324
820.01848740.03697490.981513
830.01579250.03158490.984208
840.01624760.03249530.983752
850.01468830.02937650.985312
860.01171920.02343840.988281
870.009281710.01856340.990718
880.007168790.01433760.992831
890.006771910.01354380.993228
900.006308970.01261790.993691
910.009481860.01896370.990518
920.009223260.01844650.990777
930.008285330.01657070.991715
940.008814030.01762810.991186
950.0116460.0232920.988354
960.009476330.01895270.990524
970.01916370.03832740.980836
980.02465550.0493110.975344
990.02066010.04132030.97934
1000.01774230.03548460.982258
1010.01644380.03288760.983556
1020.02800240.05600490.971998
1030.02362490.04724970.976375
1040.01983290.03966590.980167
1050.01707340.03414690.982927
1060.01364050.0272810.98636
1070.01164480.02328970.988355
1080.009360280.01872060.99064
1090.008777510.0175550.991222
1100.008138320.01627660.991862
1110.006388320.01277660.993612
1120.004911260.009822510.995089
1130.004137940.008275870.995862
1140.003630530.007261060.996369
1150.00303690.006073810.996963
1160.006401140.01280230.993599
1170.005011250.01002250.994989
1180.005290090.01058020.99471
1190.004184360.008368730.995816
1200.003298880.006597770.996701
1210.002650610.005301210.997349
1220.003239670.006479340.99676
1230.002486430.004972860.997514
1240.002043750.004087490.997956
1250.001797090.003594180.998203
1260.001440070.002880140.99856
1270.001605710.003211420.998394
1280.001729280.003458550.998271
1290.001309430.002618870.998691
1300.0009691010.00193820.999031
1310.0007797990.00155960.99922
1320.0006822580.001364520.999318
1330.0005966340.001193270.999403
1340.0004574250.0009148510.999543
1350.0004313270.0008626540.999569
1360.0003167430.0006334870.999683
1370.0002311170.0004622330.999769
1380.0001626070.0003252150.999837
1390.0001258030.0002516070.999874
1408.80314e-050.0001760630.999912
1418.11525e-050.0001623050.999919
1425.75202e-050.000115040.999942
1436.9919e-050.0001398380.99993
1446.03187e-050.0001206370.99994
1454.13012e-058.26024e-050.999959
1464.64886e-059.29773e-050.999954
1470.0001649940.0003299880.999835
1480.0001498550.0002997110.99985
1490.0001079810.0002159630.999892
1507.44458e-050.0001488920.999926
1515.08883e-050.0001017770.999949
1520.1213270.2426540.878673
1530.1756090.3512180.824391
1540.1544220.3088440.845578
1550.1390210.2780420.860979
1560.1759470.3518940.824053
1570.155990.311980.84401
1580.1428560.2857120.857144
1590.2332570.4665130.766743
1600.2259810.4519610.774019
1610.2250780.4501560.774922
1620.1965430.3930850.803457
1630.1800220.3600440.819978
1640.1786640.3573290.821336
1650.2088620.4177240.791138
1660.2145510.4291030.785449
1670.2536220.5072440.746378
1680.2366080.4732160.763392
1690.2128130.4256260.787187
1700.1875230.3750460.812477
1710.1608860.3217730.839114
1720.1880310.3760620.811969
1730.2187180.4374350.781282
1740.2067020.4134040.793298
1750.1920050.3840110.807995
1760.1701090.3402180.829891
1770.1462510.2925020.853749
1780.1247340.2494680.875266
1790.1105410.2210820.889459
1800.1080780.2161550.891922
1810.0889460.1778920.911054
1820.07205040.1441010.92795
1830.0600130.1200260.939987
1840.0850920.1701840.914908
1850.07973650.1594730.920264
1860.06409830.1281970.935902
1870.05372850.1074570.946272
1880.04980170.09960350.950198
1890.04864330.09728660.951357
1900.515040.9699190.48496
1910.470160.9403210.52984
1920.4253950.8507910.574605
1930.6113780.7772430.388622
1940.5609940.8780130.439006
1950.5520440.8959110.447956
1960.533960.9320810.46604
1970.5915110.8169780.408489
1980.5972460.8055080.402754
1990.5702990.8594030.429701
2000.5153480.9693050.484652
2010.4595390.9190770.540461
2020.4398390.8796780.560161
2030.3886810.7773620.611319
2040.3323090.6646170.667691
2050.3012170.6024340.698783
2060.2490580.4981160.750942
2070.2009460.4018920.799054
2080.1924910.3849820.807509
2090.2998690.5997380.700131
2100.2783760.5567530.721624
2110.2927080.5854160.707292
2120.4759860.9519720.524014
2130.4677770.9355530.532223
2140.5765940.8468120.423406
2150.4996990.9993980.500301
2160.4162110.8324230.583789
2170.4484350.896870.551565
2180.7640740.4718510.235926
2190.8610760.2778470.138924
2200.7860430.4279150.213957
2210.6903040.6193930.309696
2220.6489140.7021710.351086
2230.6721690.6556620.327831
2240.5586410.8827170.441359

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
5 & 0.774757 & 0.450486 & 0.225243 \tabularnewline
6 & 0.84587 & 0.308259 & 0.15413 \tabularnewline
7 & 0.830899 & 0.338202 & 0.169101 \tabularnewline
8 & 0.979205 & 0.0415897 & 0.0207949 \tabularnewline
9 & 0.996266 & 0.00746785 & 0.00373393 \tabularnewline
10 & 0.993739 & 0.0125227 & 0.00626134 \tabularnewline
11 & 0.989457 & 0.0210851 & 0.0105425 \tabularnewline
12 & 0.989848 & 0.0203047 & 0.0101523 \tabularnewline
13 & 0.991353 & 0.0172932 & 0.00864658 \tabularnewline
14 & 0.989424 & 0.0211527 & 0.0105764 \tabularnewline
15 & 0.98324 & 0.0335194 & 0.0167597 \tabularnewline
16 & 0.977118 & 0.0457631 & 0.0228816 \tabularnewline
17 & 0.988259 & 0.0234822 & 0.0117411 \tabularnewline
18 & 0.982688 & 0.0346243 & 0.0173121 \tabularnewline
19 & 0.976614 & 0.0467717 & 0.0233858 \tabularnewline
20 & 0.966383 & 0.0672347 & 0.0336174 \tabularnewline
21 & 0.954696 & 0.0906082 & 0.0453041 \tabularnewline
22 & 0.93795 & 0.124101 & 0.0620504 \tabularnewline
23 & 0.916544 & 0.166912 & 0.0834558 \tabularnewline
24 & 0.916458 & 0.167084 & 0.0835418 \tabularnewline
25 & 0.893748 & 0.212505 & 0.106252 \tabularnewline
26 & 0.881744 & 0.236511 & 0.118256 \tabularnewline
27 & 0.860574 & 0.278851 & 0.139426 \tabularnewline
28 & 0.832873 & 0.334254 & 0.167127 \tabularnewline
29 & 0.798615 & 0.402771 & 0.201385 \tabularnewline
30 & 0.762081 & 0.475838 & 0.237919 \tabularnewline
31 & 0.760943 & 0.478114 & 0.239057 \tabularnewline
32 & 0.716278 & 0.567444 & 0.283722 \tabularnewline
33 & 0.713461 & 0.573079 & 0.286539 \tabularnewline
34 & 0.669875 & 0.66025 & 0.330125 \tabularnewline
35 & 0.620218 & 0.759563 & 0.379782 \tabularnewline
36 & 0.606642 & 0.786716 & 0.393358 \tabularnewline
37 & 0.594557 & 0.810887 & 0.405443 \tabularnewline
38 & 0.563973 & 0.872054 & 0.436027 \tabularnewline
39 & 0.527257 & 0.945486 & 0.472743 \tabularnewline
40 & 0.480551 & 0.961103 & 0.519449 \tabularnewline
41 & 0.432002 & 0.864003 & 0.567998 \tabularnewline
42 & 0.391495 & 0.78299 & 0.608505 \tabularnewline
43 & 0.34846 & 0.69692 & 0.65154 \tabularnewline
44 & 0.33825 & 0.6765 & 0.66175 \tabularnewline
45 & 0.329655 & 0.659311 & 0.670345 \tabularnewline
46 & 0.288214 & 0.576427 & 0.711786 \tabularnewline
47 & 0.289427 & 0.578854 & 0.710573 \tabularnewline
48 & 0.31259 & 0.625181 & 0.68741 \tabularnewline
49 & 0.272001 & 0.544002 & 0.727999 \tabularnewline
50 & 0.273631 & 0.547262 & 0.726369 \tabularnewline
51 & 0.237453 & 0.474907 & 0.762547 \tabularnewline
52 & 0.208679 & 0.417358 & 0.791321 \tabularnewline
53 & 0.178219 & 0.356437 & 0.821781 \tabularnewline
54 & 0.157478 & 0.314957 & 0.842522 \tabularnewline
55 & 0.135625 & 0.271251 & 0.864375 \tabularnewline
56 & 0.138312 & 0.276623 & 0.861688 \tabularnewline
57 & 0.152617 & 0.305234 & 0.847383 \tabularnewline
58 & 0.130113 & 0.260226 & 0.869887 \tabularnewline
59 & 0.110404 & 0.220809 & 0.889596 \tabularnewline
60 & 0.0936766 & 0.187353 & 0.906323 \tabularnewline
61 & 0.0809427 & 0.161885 & 0.919057 \tabularnewline
62 & 0.0662351 & 0.13247 & 0.933765 \tabularnewline
63 & 0.053518 & 0.107036 & 0.946482 \tabularnewline
64 & 0.0489066 & 0.0978133 & 0.951093 \tabularnewline
65 & 0.04267 & 0.08534 & 0.95733 \tabularnewline
66 & 0.047477 & 0.0949541 & 0.952523 \tabularnewline
67 & 0.0488009 & 0.0976017 & 0.951199 \tabularnewline
68 & 0.0420562 & 0.0841125 & 0.957944 \tabularnewline
69 & 0.0368573 & 0.0737147 & 0.963143 \tabularnewline
70 & 0.033037 & 0.066074 & 0.966963 \tabularnewline
71 & 0.0272951 & 0.0545903 & 0.972705 \tabularnewline
72 & 0.0250126 & 0.0500251 & 0.974987 \tabularnewline
73 & 0.020763 & 0.0415261 & 0.979237 \tabularnewline
74 & 0.0347957 & 0.0695915 & 0.965204 \tabularnewline
75 & 0.0574836 & 0.114967 & 0.942516 \tabularnewline
76 & 0.0476763 & 0.0953526 & 0.952324 \tabularnewline
77 & 0.0431037 & 0.0862075 & 0.956896 \tabularnewline
78 & 0.0350545 & 0.0701091 & 0.964945 \tabularnewline
79 & 0.0286058 & 0.0572116 & 0.971394 \tabularnewline
80 & 0.0285961 & 0.0571922 & 0.971404 \tabularnewline
81 & 0.0226757 & 0.0453515 & 0.977324 \tabularnewline
82 & 0.0184874 & 0.0369749 & 0.981513 \tabularnewline
83 & 0.0157925 & 0.0315849 & 0.984208 \tabularnewline
84 & 0.0162476 & 0.0324953 & 0.983752 \tabularnewline
85 & 0.0146883 & 0.0293765 & 0.985312 \tabularnewline
86 & 0.0117192 & 0.0234384 & 0.988281 \tabularnewline
87 & 0.00928171 & 0.0185634 & 0.990718 \tabularnewline
88 & 0.00716879 & 0.0143376 & 0.992831 \tabularnewline
89 & 0.00677191 & 0.0135438 & 0.993228 \tabularnewline
90 & 0.00630897 & 0.0126179 & 0.993691 \tabularnewline
91 & 0.00948186 & 0.0189637 & 0.990518 \tabularnewline
92 & 0.00922326 & 0.0184465 & 0.990777 \tabularnewline
93 & 0.00828533 & 0.0165707 & 0.991715 \tabularnewline
94 & 0.00881403 & 0.0176281 & 0.991186 \tabularnewline
95 & 0.011646 & 0.023292 & 0.988354 \tabularnewline
96 & 0.00947633 & 0.0189527 & 0.990524 \tabularnewline
97 & 0.0191637 & 0.0383274 & 0.980836 \tabularnewline
98 & 0.0246555 & 0.049311 & 0.975344 \tabularnewline
99 & 0.0206601 & 0.0413203 & 0.97934 \tabularnewline
100 & 0.0177423 & 0.0354846 & 0.982258 \tabularnewline
101 & 0.0164438 & 0.0328876 & 0.983556 \tabularnewline
102 & 0.0280024 & 0.0560049 & 0.971998 \tabularnewline
103 & 0.0236249 & 0.0472497 & 0.976375 \tabularnewline
104 & 0.0198329 & 0.0396659 & 0.980167 \tabularnewline
105 & 0.0170734 & 0.0341469 & 0.982927 \tabularnewline
106 & 0.0136405 & 0.027281 & 0.98636 \tabularnewline
107 & 0.0116448 & 0.0232897 & 0.988355 \tabularnewline
108 & 0.00936028 & 0.0187206 & 0.99064 \tabularnewline
109 & 0.00877751 & 0.017555 & 0.991222 \tabularnewline
110 & 0.00813832 & 0.0162766 & 0.991862 \tabularnewline
111 & 0.00638832 & 0.0127766 & 0.993612 \tabularnewline
112 & 0.00491126 & 0.00982251 & 0.995089 \tabularnewline
113 & 0.00413794 & 0.00827587 & 0.995862 \tabularnewline
114 & 0.00363053 & 0.00726106 & 0.996369 \tabularnewline
115 & 0.0030369 & 0.00607381 & 0.996963 \tabularnewline
116 & 0.00640114 & 0.0128023 & 0.993599 \tabularnewline
117 & 0.00501125 & 0.0100225 & 0.994989 \tabularnewline
118 & 0.00529009 & 0.0105802 & 0.99471 \tabularnewline
119 & 0.00418436 & 0.00836873 & 0.995816 \tabularnewline
120 & 0.00329888 & 0.00659777 & 0.996701 \tabularnewline
121 & 0.00265061 & 0.00530121 & 0.997349 \tabularnewline
122 & 0.00323967 & 0.00647934 & 0.99676 \tabularnewline
123 & 0.00248643 & 0.00497286 & 0.997514 \tabularnewline
124 & 0.00204375 & 0.00408749 & 0.997956 \tabularnewline
125 & 0.00179709 & 0.00359418 & 0.998203 \tabularnewline
126 & 0.00144007 & 0.00288014 & 0.99856 \tabularnewline
127 & 0.00160571 & 0.00321142 & 0.998394 \tabularnewline
128 & 0.00172928 & 0.00345855 & 0.998271 \tabularnewline
129 & 0.00130943 & 0.00261887 & 0.998691 \tabularnewline
130 & 0.000969101 & 0.0019382 & 0.999031 \tabularnewline
131 & 0.000779799 & 0.0015596 & 0.99922 \tabularnewline
132 & 0.000682258 & 0.00136452 & 0.999318 \tabularnewline
133 & 0.000596634 & 0.00119327 & 0.999403 \tabularnewline
134 & 0.000457425 & 0.000914851 & 0.999543 \tabularnewline
135 & 0.000431327 & 0.000862654 & 0.999569 \tabularnewline
136 & 0.000316743 & 0.000633487 & 0.999683 \tabularnewline
137 & 0.000231117 & 0.000462233 & 0.999769 \tabularnewline
138 & 0.000162607 & 0.000325215 & 0.999837 \tabularnewline
139 & 0.000125803 & 0.000251607 & 0.999874 \tabularnewline
140 & 8.80314e-05 & 0.000176063 & 0.999912 \tabularnewline
141 & 8.11525e-05 & 0.000162305 & 0.999919 \tabularnewline
142 & 5.75202e-05 & 0.00011504 & 0.999942 \tabularnewline
143 & 6.9919e-05 & 0.000139838 & 0.99993 \tabularnewline
144 & 6.03187e-05 & 0.000120637 & 0.99994 \tabularnewline
145 & 4.13012e-05 & 8.26024e-05 & 0.999959 \tabularnewline
146 & 4.64886e-05 & 9.29773e-05 & 0.999954 \tabularnewline
147 & 0.000164994 & 0.000329988 & 0.999835 \tabularnewline
148 & 0.000149855 & 0.000299711 & 0.99985 \tabularnewline
149 & 0.000107981 & 0.000215963 & 0.999892 \tabularnewline
150 & 7.44458e-05 & 0.000148892 & 0.999926 \tabularnewline
151 & 5.08883e-05 & 0.000101777 & 0.999949 \tabularnewline
152 & 0.121327 & 0.242654 & 0.878673 \tabularnewline
153 & 0.175609 & 0.351218 & 0.824391 \tabularnewline
154 & 0.154422 & 0.308844 & 0.845578 \tabularnewline
155 & 0.139021 & 0.278042 & 0.860979 \tabularnewline
156 & 0.175947 & 0.351894 & 0.824053 \tabularnewline
157 & 0.15599 & 0.31198 & 0.84401 \tabularnewline
158 & 0.142856 & 0.285712 & 0.857144 \tabularnewline
159 & 0.233257 & 0.466513 & 0.766743 \tabularnewline
160 & 0.225981 & 0.451961 & 0.774019 \tabularnewline
161 & 0.225078 & 0.450156 & 0.774922 \tabularnewline
162 & 0.196543 & 0.393085 & 0.803457 \tabularnewline
163 & 0.180022 & 0.360044 & 0.819978 \tabularnewline
164 & 0.178664 & 0.357329 & 0.821336 \tabularnewline
165 & 0.208862 & 0.417724 & 0.791138 \tabularnewline
166 & 0.214551 & 0.429103 & 0.785449 \tabularnewline
167 & 0.253622 & 0.507244 & 0.746378 \tabularnewline
168 & 0.236608 & 0.473216 & 0.763392 \tabularnewline
169 & 0.212813 & 0.425626 & 0.787187 \tabularnewline
170 & 0.187523 & 0.375046 & 0.812477 \tabularnewline
171 & 0.160886 & 0.321773 & 0.839114 \tabularnewline
172 & 0.188031 & 0.376062 & 0.811969 \tabularnewline
173 & 0.218718 & 0.437435 & 0.781282 \tabularnewline
174 & 0.206702 & 0.413404 & 0.793298 \tabularnewline
175 & 0.192005 & 0.384011 & 0.807995 \tabularnewline
176 & 0.170109 & 0.340218 & 0.829891 \tabularnewline
177 & 0.146251 & 0.292502 & 0.853749 \tabularnewline
178 & 0.124734 & 0.249468 & 0.875266 \tabularnewline
179 & 0.110541 & 0.221082 & 0.889459 \tabularnewline
180 & 0.108078 & 0.216155 & 0.891922 \tabularnewline
181 & 0.088946 & 0.177892 & 0.911054 \tabularnewline
182 & 0.0720504 & 0.144101 & 0.92795 \tabularnewline
183 & 0.060013 & 0.120026 & 0.939987 \tabularnewline
184 & 0.085092 & 0.170184 & 0.914908 \tabularnewline
185 & 0.0797365 & 0.159473 & 0.920264 \tabularnewline
186 & 0.0640983 & 0.128197 & 0.935902 \tabularnewline
187 & 0.0537285 & 0.107457 & 0.946272 \tabularnewline
188 & 0.0498017 & 0.0996035 & 0.950198 \tabularnewline
189 & 0.0486433 & 0.0972866 & 0.951357 \tabularnewline
190 & 0.51504 & 0.969919 & 0.48496 \tabularnewline
191 & 0.47016 & 0.940321 & 0.52984 \tabularnewline
192 & 0.425395 & 0.850791 & 0.574605 \tabularnewline
193 & 0.611378 & 0.777243 & 0.388622 \tabularnewline
194 & 0.560994 & 0.878013 & 0.439006 \tabularnewline
195 & 0.552044 & 0.895911 & 0.447956 \tabularnewline
196 & 0.53396 & 0.932081 & 0.46604 \tabularnewline
197 & 0.591511 & 0.816978 & 0.408489 \tabularnewline
198 & 0.597246 & 0.805508 & 0.402754 \tabularnewline
199 & 0.570299 & 0.859403 & 0.429701 \tabularnewline
200 & 0.515348 & 0.969305 & 0.484652 \tabularnewline
201 & 0.459539 & 0.919077 & 0.540461 \tabularnewline
202 & 0.439839 & 0.879678 & 0.560161 \tabularnewline
203 & 0.388681 & 0.777362 & 0.611319 \tabularnewline
204 & 0.332309 & 0.664617 & 0.667691 \tabularnewline
205 & 0.301217 & 0.602434 & 0.698783 \tabularnewline
206 & 0.249058 & 0.498116 & 0.750942 \tabularnewline
207 & 0.200946 & 0.401892 & 0.799054 \tabularnewline
208 & 0.192491 & 0.384982 & 0.807509 \tabularnewline
209 & 0.299869 & 0.599738 & 0.700131 \tabularnewline
210 & 0.278376 & 0.556753 & 0.721624 \tabularnewline
211 & 0.292708 & 0.585416 & 0.707292 \tabularnewline
212 & 0.475986 & 0.951972 & 0.524014 \tabularnewline
213 & 0.467777 & 0.935553 & 0.532223 \tabularnewline
214 & 0.576594 & 0.846812 & 0.423406 \tabularnewline
215 & 0.499699 & 0.999398 & 0.500301 \tabularnewline
216 & 0.416211 & 0.832423 & 0.583789 \tabularnewline
217 & 0.448435 & 0.89687 & 0.551565 \tabularnewline
218 & 0.764074 & 0.471851 & 0.235926 \tabularnewline
219 & 0.861076 & 0.277847 & 0.138924 \tabularnewline
220 & 0.786043 & 0.427915 & 0.213957 \tabularnewline
221 & 0.690304 & 0.619393 & 0.309696 \tabularnewline
222 & 0.648914 & 0.702171 & 0.351086 \tabularnewline
223 & 0.672169 & 0.655662 & 0.327831 \tabularnewline
224 & 0.558641 & 0.882717 & 0.441359 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&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]5[/C][C]0.774757[/C][C]0.450486[/C][C]0.225243[/C][/ROW]
[ROW][C]6[/C][C]0.84587[/C][C]0.308259[/C][C]0.15413[/C][/ROW]
[ROW][C]7[/C][C]0.830899[/C][C]0.338202[/C][C]0.169101[/C][/ROW]
[ROW][C]8[/C][C]0.979205[/C][C]0.0415897[/C][C]0.0207949[/C][/ROW]
[ROW][C]9[/C][C]0.996266[/C][C]0.00746785[/C][C]0.00373393[/C][/ROW]
[ROW][C]10[/C][C]0.993739[/C][C]0.0125227[/C][C]0.00626134[/C][/ROW]
[ROW][C]11[/C][C]0.989457[/C][C]0.0210851[/C][C]0.0105425[/C][/ROW]
[ROW][C]12[/C][C]0.989848[/C][C]0.0203047[/C][C]0.0101523[/C][/ROW]
[ROW][C]13[/C][C]0.991353[/C][C]0.0172932[/C][C]0.00864658[/C][/ROW]
[ROW][C]14[/C][C]0.989424[/C][C]0.0211527[/C][C]0.0105764[/C][/ROW]
[ROW][C]15[/C][C]0.98324[/C][C]0.0335194[/C][C]0.0167597[/C][/ROW]
[ROW][C]16[/C][C]0.977118[/C][C]0.0457631[/C][C]0.0228816[/C][/ROW]
[ROW][C]17[/C][C]0.988259[/C][C]0.0234822[/C][C]0.0117411[/C][/ROW]
[ROW][C]18[/C][C]0.982688[/C][C]0.0346243[/C][C]0.0173121[/C][/ROW]
[ROW][C]19[/C][C]0.976614[/C][C]0.0467717[/C][C]0.0233858[/C][/ROW]
[ROW][C]20[/C][C]0.966383[/C][C]0.0672347[/C][C]0.0336174[/C][/ROW]
[ROW][C]21[/C][C]0.954696[/C][C]0.0906082[/C][C]0.0453041[/C][/ROW]
[ROW][C]22[/C][C]0.93795[/C][C]0.124101[/C][C]0.0620504[/C][/ROW]
[ROW][C]23[/C][C]0.916544[/C][C]0.166912[/C][C]0.0834558[/C][/ROW]
[ROW][C]24[/C][C]0.916458[/C][C]0.167084[/C][C]0.0835418[/C][/ROW]
[ROW][C]25[/C][C]0.893748[/C][C]0.212505[/C][C]0.106252[/C][/ROW]
[ROW][C]26[/C][C]0.881744[/C][C]0.236511[/C][C]0.118256[/C][/ROW]
[ROW][C]27[/C][C]0.860574[/C][C]0.278851[/C][C]0.139426[/C][/ROW]
[ROW][C]28[/C][C]0.832873[/C][C]0.334254[/C][C]0.167127[/C][/ROW]
[ROW][C]29[/C][C]0.798615[/C][C]0.402771[/C][C]0.201385[/C][/ROW]
[ROW][C]30[/C][C]0.762081[/C][C]0.475838[/C][C]0.237919[/C][/ROW]
[ROW][C]31[/C][C]0.760943[/C][C]0.478114[/C][C]0.239057[/C][/ROW]
[ROW][C]32[/C][C]0.716278[/C][C]0.567444[/C][C]0.283722[/C][/ROW]
[ROW][C]33[/C][C]0.713461[/C][C]0.573079[/C][C]0.286539[/C][/ROW]
[ROW][C]34[/C][C]0.669875[/C][C]0.66025[/C][C]0.330125[/C][/ROW]
[ROW][C]35[/C][C]0.620218[/C][C]0.759563[/C][C]0.379782[/C][/ROW]
[ROW][C]36[/C][C]0.606642[/C][C]0.786716[/C][C]0.393358[/C][/ROW]
[ROW][C]37[/C][C]0.594557[/C][C]0.810887[/C][C]0.405443[/C][/ROW]
[ROW][C]38[/C][C]0.563973[/C][C]0.872054[/C][C]0.436027[/C][/ROW]
[ROW][C]39[/C][C]0.527257[/C][C]0.945486[/C][C]0.472743[/C][/ROW]
[ROW][C]40[/C][C]0.480551[/C][C]0.961103[/C][C]0.519449[/C][/ROW]
[ROW][C]41[/C][C]0.432002[/C][C]0.864003[/C][C]0.567998[/C][/ROW]
[ROW][C]42[/C][C]0.391495[/C][C]0.78299[/C][C]0.608505[/C][/ROW]
[ROW][C]43[/C][C]0.34846[/C][C]0.69692[/C][C]0.65154[/C][/ROW]
[ROW][C]44[/C][C]0.33825[/C][C]0.6765[/C][C]0.66175[/C][/ROW]
[ROW][C]45[/C][C]0.329655[/C][C]0.659311[/C][C]0.670345[/C][/ROW]
[ROW][C]46[/C][C]0.288214[/C][C]0.576427[/C][C]0.711786[/C][/ROW]
[ROW][C]47[/C][C]0.289427[/C][C]0.578854[/C][C]0.710573[/C][/ROW]
[ROW][C]48[/C][C]0.31259[/C][C]0.625181[/C][C]0.68741[/C][/ROW]
[ROW][C]49[/C][C]0.272001[/C][C]0.544002[/C][C]0.727999[/C][/ROW]
[ROW][C]50[/C][C]0.273631[/C][C]0.547262[/C][C]0.726369[/C][/ROW]
[ROW][C]51[/C][C]0.237453[/C][C]0.474907[/C][C]0.762547[/C][/ROW]
[ROW][C]52[/C][C]0.208679[/C][C]0.417358[/C][C]0.791321[/C][/ROW]
[ROW][C]53[/C][C]0.178219[/C][C]0.356437[/C][C]0.821781[/C][/ROW]
[ROW][C]54[/C][C]0.157478[/C][C]0.314957[/C][C]0.842522[/C][/ROW]
[ROW][C]55[/C][C]0.135625[/C][C]0.271251[/C][C]0.864375[/C][/ROW]
[ROW][C]56[/C][C]0.138312[/C][C]0.276623[/C][C]0.861688[/C][/ROW]
[ROW][C]57[/C][C]0.152617[/C][C]0.305234[/C][C]0.847383[/C][/ROW]
[ROW][C]58[/C][C]0.130113[/C][C]0.260226[/C][C]0.869887[/C][/ROW]
[ROW][C]59[/C][C]0.110404[/C][C]0.220809[/C][C]0.889596[/C][/ROW]
[ROW][C]60[/C][C]0.0936766[/C][C]0.187353[/C][C]0.906323[/C][/ROW]
[ROW][C]61[/C][C]0.0809427[/C][C]0.161885[/C][C]0.919057[/C][/ROW]
[ROW][C]62[/C][C]0.0662351[/C][C]0.13247[/C][C]0.933765[/C][/ROW]
[ROW][C]63[/C][C]0.053518[/C][C]0.107036[/C][C]0.946482[/C][/ROW]
[ROW][C]64[/C][C]0.0489066[/C][C]0.0978133[/C][C]0.951093[/C][/ROW]
[ROW][C]65[/C][C]0.04267[/C][C]0.08534[/C][C]0.95733[/C][/ROW]
[ROW][C]66[/C][C]0.047477[/C][C]0.0949541[/C][C]0.952523[/C][/ROW]
[ROW][C]67[/C][C]0.0488009[/C][C]0.0976017[/C][C]0.951199[/C][/ROW]
[ROW][C]68[/C][C]0.0420562[/C][C]0.0841125[/C][C]0.957944[/C][/ROW]
[ROW][C]69[/C][C]0.0368573[/C][C]0.0737147[/C][C]0.963143[/C][/ROW]
[ROW][C]70[/C][C]0.033037[/C][C]0.066074[/C][C]0.966963[/C][/ROW]
[ROW][C]71[/C][C]0.0272951[/C][C]0.0545903[/C][C]0.972705[/C][/ROW]
[ROW][C]72[/C][C]0.0250126[/C][C]0.0500251[/C][C]0.974987[/C][/ROW]
[ROW][C]73[/C][C]0.020763[/C][C]0.0415261[/C][C]0.979237[/C][/ROW]
[ROW][C]74[/C][C]0.0347957[/C][C]0.0695915[/C][C]0.965204[/C][/ROW]
[ROW][C]75[/C][C]0.0574836[/C][C]0.114967[/C][C]0.942516[/C][/ROW]
[ROW][C]76[/C][C]0.0476763[/C][C]0.0953526[/C][C]0.952324[/C][/ROW]
[ROW][C]77[/C][C]0.0431037[/C][C]0.0862075[/C][C]0.956896[/C][/ROW]
[ROW][C]78[/C][C]0.0350545[/C][C]0.0701091[/C][C]0.964945[/C][/ROW]
[ROW][C]79[/C][C]0.0286058[/C][C]0.0572116[/C][C]0.971394[/C][/ROW]
[ROW][C]80[/C][C]0.0285961[/C][C]0.0571922[/C][C]0.971404[/C][/ROW]
[ROW][C]81[/C][C]0.0226757[/C][C]0.0453515[/C][C]0.977324[/C][/ROW]
[ROW][C]82[/C][C]0.0184874[/C][C]0.0369749[/C][C]0.981513[/C][/ROW]
[ROW][C]83[/C][C]0.0157925[/C][C]0.0315849[/C][C]0.984208[/C][/ROW]
[ROW][C]84[/C][C]0.0162476[/C][C]0.0324953[/C][C]0.983752[/C][/ROW]
[ROW][C]85[/C][C]0.0146883[/C][C]0.0293765[/C][C]0.985312[/C][/ROW]
[ROW][C]86[/C][C]0.0117192[/C][C]0.0234384[/C][C]0.988281[/C][/ROW]
[ROW][C]87[/C][C]0.00928171[/C][C]0.0185634[/C][C]0.990718[/C][/ROW]
[ROW][C]88[/C][C]0.00716879[/C][C]0.0143376[/C][C]0.992831[/C][/ROW]
[ROW][C]89[/C][C]0.00677191[/C][C]0.0135438[/C][C]0.993228[/C][/ROW]
[ROW][C]90[/C][C]0.00630897[/C][C]0.0126179[/C][C]0.993691[/C][/ROW]
[ROW][C]91[/C][C]0.00948186[/C][C]0.0189637[/C][C]0.990518[/C][/ROW]
[ROW][C]92[/C][C]0.00922326[/C][C]0.0184465[/C][C]0.990777[/C][/ROW]
[ROW][C]93[/C][C]0.00828533[/C][C]0.0165707[/C][C]0.991715[/C][/ROW]
[ROW][C]94[/C][C]0.00881403[/C][C]0.0176281[/C][C]0.991186[/C][/ROW]
[ROW][C]95[/C][C]0.011646[/C][C]0.023292[/C][C]0.988354[/C][/ROW]
[ROW][C]96[/C][C]0.00947633[/C][C]0.0189527[/C][C]0.990524[/C][/ROW]
[ROW][C]97[/C][C]0.0191637[/C][C]0.0383274[/C][C]0.980836[/C][/ROW]
[ROW][C]98[/C][C]0.0246555[/C][C]0.049311[/C][C]0.975344[/C][/ROW]
[ROW][C]99[/C][C]0.0206601[/C][C]0.0413203[/C][C]0.97934[/C][/ROW]
[ROW][C]100[/C][C]0.0177423[/C][C]0.0354846[/C][C]0.982258[/C][/ROW]
[ROW][C]101[/C][C]0.0164438[/C][C]0.0328876[/C][C]0.983556[/C][/ROW]
[ROW][C]102[/C][C]0.0280024[/C][C]0.0560049[/C][C]0.971998[/C][/ROW]
[ROW][C]103[/C][C]0.0236249[/C][C]0.0472497[/C][C]0.976375[/C][/ROW]
[ROW][C]104[/C][C]0.0198329[/C][C]0.0396659[/C][C]0.980167[/C][/ROW]
[ROW][C]105[/C][C]0.0170734[/C][C]0.0341469[/C][C]0.982927[/C][/ROW]
[ROW][C]106[/C][C]0.0136405[/C][C]0.027281[/C][C]0.98636[/C][/ROW]
[ROW][C]107[/C][C]0.0116448[/C][C]0.0232897[/C][C]0.988355[/C][/ROW]
[ROW][C]108[/C][C]0.00936028[/C][C]0.0187206[/C][C]0.99064[/C][/ROW]
[ROW][C]109[/C][C]0.00877751[/C][C]0.017555[/C][C]0.991222[/C][/ROW]
[ROW][C]110[/C][C]0.00813832[/C][C]0.0162766[/C][C]0.991862[/C][/ROW]
[ROW][C]111[/C][C]0.00638832[/C][C]0.0127766[/C][C]0.993612[/C][/ROW]
[ROW][C]112[/C][C]0.00491126[/C][C]0.00982251[/C][C]0.995089[/C][/ROW]
[ROW][C]113[/C][C]0.00413794[/C][C]0.00827587[/C][C]0.995862[/C][/ROW]
[ROW][C]114[/C][C]0.00363053[/C][C]0.00726106[/C][C]0.996369[/C][/ROW]
[ROW][C]115[/C][C]0.0030369[/C][C]0.00607381[/C][C]0.996963[/C][/ROW]
[ROW][C]116[/C][C]0.00640114[/C][C]0.0128023[/C][C]0.993599[/C][/ROW]
[ROW][C]117[/C][C]0.00501125[/C][C]0.0100225[/C][C]0.994989[/C][/ROW]
[ROW][C]118[/C][C]0.00529009[/C][C]0.0105802[/C][C]0.99471[/C][/ROW]
[ROW][C]119[/C][C]0.00418436[/C][C]0.00836873[/C][C]0.995816[/C][/ROW]
[ROW][C]120[/C][C]0.00329888[/C][C]0.00659777[/C][C]0.996701[/C][/ROW]
[ROW][C]121[/C][C]0.00265061[/C][C]0.00530121[/C][C]0.997349[/C][/ROW]
[ROW][C]122[/C][C]0.00323967[/C][C]0.00647934[/C][C]0.99676[/C][/ROW]
[ROW][C]123[/C][C]0.00248643[/C][C]0.00497286[/C][C]0.997514[/C][/ROW]
[ROW][C]124[/C][C]0.00204375[/C][C]0.00408749[/C][C]0.997956[/C][/ROW]
[ROW][C]125[/C][C]0.00179709[/C][C]0.00359418[/C][C]0.998203[/C][/ROW]
[ROW][C]126[/C][C]0.00144007[/C][C]0.00288014[/C][C]0.99856[/C][/ROW]
[ROW][C]127[/C][C]0.00160571[/C][C]0.00321142[/C][C]0.998394[/C][/ROW]
[ROW][C]128[/C][C]0.00172928[/C][C]0.00345855[/C][C]0.998271[/C][/ROW]
[ROW][C]129[/C][C]0.00130943[/C][C]0.00261887[/C][C]0.998691[/C][/ROW]
[ROW][C]130[/C][C]0.000969101[/C][C]0.0019382[/C][C]0.999031[/C][/ROW]
[ROW][C]131[/C][C]0.000779799[/C][C]0.0015596[/C][C]0.99922[/C][/ROW]
[ROW][C]132[/C][C]0.000682258[/C][C]0.00136452[/C][C]0.999318[/C][/ROW]
[ROW][C]133[/C][C]0.000596634[/C][C]0.00119327[/C][C]0.999403[/C][/ROW]
[ROW][C]134[/C][C]0.000457425[/C][C]0.000914851[/C][C]0.999543[/C][/ROW]
[ROW][C]135[/C][C]0.000431327[/C][C]0.000862654[/C][C]0.999569[/C][/ROW]
[ROW][C]136[/C][C]0.000316743[/C][C]0.000633487[/C][C]0.999683[/C][/ROW]
[ROW][C]137[/C][C]0.000231117[/C][C]0.000462233[/C][C]0.999769[/C][/ROW]
[ROW][C]138[/C][C]0.000162607[/C][C]0.000325215[/C][C]0.999837[/C][/ROW]
[ROW][C]139[/C][C]0.000125803[/C][C]0.000251607[/C][C]0.999874[/C][/ROW]
[ROW][C]140[/C][C]8.80314e-05[/C][C]0.000176063[/C][C]0.999912[/C][/ROW]
[ROW][C]141[/C][C]8.11525e-05[/C][C]0.000162305[/C][C]0.999919[/C][/ROW]
[ROW][C]142[/C][C]5.75202e-05[/C][C]0.00011504[/C][C]0.999942[/C][/ROW]
[ROW][C]143[/C][C]6.9919e-05[/C][C]0.000139838[/C][C]0.99993[/C][/ROW]
[ROW][C]144[/C][C]6.03187e-05[/C][C]0.000120637[/C][C]0.99994[/C][/ROW]
[ROW][C]145[/C][C]4.13012e-05[/C][C]8.26024e-05[/C][C]0.999959[/C][/ROW]
[ROW][C]146[/C][C]4.64886e-05[/C][C]9.29773e-05[/C][C]0.999954[/C][/ROW]
[ROW][C]147[/C][C]0.000164994[/C][C]0.000329988[/C][C]0.999835[/C][/ROW]
[ROW][C]148[/C][C]0.000149855[/C][C]0.000299711[/C][C]0.99985[/C][/ROW]
[ROW][C]149[/C][C]0.000107981[/C][C]0.000215963[/C][C]0.999892[/C][/ROW]
[ROW][C]150[/C][C]7.44458e-05[/C][C]0.000148892[/C][C]0.999926[/C][/ROW]
[ROW][C]151[/C][C]5.08883e-05[/C][C]0.000101777[/C][C]0.999949[/C][/ROW]
[ROW][C]152[/C][C]0.121327[/C][C]0.242654[/C][C]0.878673[/C][/ROW]
[ROW][C]153[/C][C]0.175609[/C][C]0.351218[/C][C]0.824391[/C][/ROW]
[ROW][C]154[/C][C]0.154422[/C][C]0.308844[/C][C]0.845578[/C][/ROW]
[ROW][C]155[/C][C]0.139021[/C][C]0.278042[/C][C]0.860979[/C][/ROW]
[ROW][C]156[/C][C]0.175947[/C][C]0.351894[/C][C]0.824053[/C][/ROW]
[ROW][C]157[/C][C]0.15599[/C][C]0.31198[/C][C]0.84401[/C][/ROW]
[ROW][C]158[/C][C]0.142856[/C][C]0.285712[/C][C]0.857144[/C][/ROW]
[ROW][C]159[/C][C]0.233257[/C][C]0.466513[/C][C]0.766743[/C][/ROW]
[ROW][C]160[/C][C]0.225981[/C][C]0.451961[/C][C]0.774019[/C][/ROW]
[ROW][C]161[/C][C]0.225078[/C][C]0.450156[/C][C]0.774922[/C][/ROW]
[ROW][C]162[/C][C]0.196543[/C][C]0.393085[/C][C]0.803457[/C][/ROW]
[ROW][C]163[/C][C]0.180022[/C][C]0.360044[/C][C]0.819978[/C][/ROW]
[ROW][C]164[/C][C]0.178664[/C][C]0.357329[/C][C]0.821336[/C][/ROW]
[ROW][C]165[/C][C]0.208862[/C][C]0.417724[/C][C]0.791138[/C][/ROW]
[ROW][C]166[/C][C]0.214551[/C][C]0.429103[/C][C]0.785449[/C][/ROW]
[ROW][C]167[/C][C]0.253622[/C][C]0.507244[/C][C]0.746378[/C][/ROW]
[ROW][C]168[/C][C]0.236608[/C][C]0.473216[/C][C]0.763392[/C][/ROW]
[ROW][C]169[/C][C]0.212813[/C][C]0.425626[/C][C]0.787187[/C][/ROW]
[ROW][C]170[/C][C]0.187523[/C][C]0.375046[/C][C]0.812477[/C][/ROW]
[ROW][C]171[/C][C]0.160886[/C][C]0.321773[/C][C]0.839114[/C][/ROW]
[ROW][C]172[/C][C]0.188031[/C][C]0.376062[/C][C]0.811969[/C][/ROW]
[ROW][C]173[/C][C]0.218718[/C][C]0.437435[/C][C]0.781282[/C][/ROW]
[ROW][C]174[/C][C]0.206702[/C][C]0.413404[/C][C]0.793298[/C][/ROW]
[ROW][C]175[/C][C]0.192005[/C][C]0.384011[/C][C]0.807995[/C][/ROW]
[ROW][C]176[/C][C]0.170109[/C][C]0.340218[/C][C]0.829891[/C][/ROW]
[ROW][C]177[/C][C]0.146251[/C][C]0.292502[/C][C]0.853749[/C][/ROW]
[ROW][C]178[/C][C]0.124734[/C][C]0.249468[/C][C]0.875266[/C][/ROW]
[ROW][C]179[/C][C]0.110541[/C][C]0.221082[/C][C]0.889459[/C][/ROW]
[ROW][C]180[/C][C]0.108078[/C][C]0.216155[/C][C]0.891922[/C][/ROW]
[ROW][C]181[/C][C]0.088946[/C][C]0.177892[/C][C]0.911054[/C][/ROW]
[ROW][C]182[/C][C]0.0720504[/C][C]0.144101[/C][C]0.92795[/C][/ROW]
[ROW][C]183[/C][C]0.060013[/C][C]0.120026[/C][C]0.939987[/C][/ROW]
[ROW][C]184[/C][C]0.085092[/C][C]0.170184[/C][C]0.914908[/C][/ROW]
[ROW][C]185[/C][C]0.0797365[/C][C]0.159473[/C][C]0.920264[/C][/ROW]
[ROW][C]186[/C][C]0.0640983[/C][C]0.128197[/C][C]0.935902[/C][/ROW]
[ROW][C]187[/C][C]0.0537285[/C][C]0.107457[/C][C]0.946272[/C][/ROW]
[ROW][C]188[/C][C]0.0498017[/C][C]0.0996035[/C][C]0.950198[/C][/ROW]
[ROW][C]189[/C][C]0.0486433[/C][C]0.0972866[/C][C]0.951357[/C][/ROW]
[ROW][C]190[/C][C]0.51504[/C][C]0.969919[/C][C]0.48496[/C][/ROW]
[ROW][C]191[/C][C]0.47016[/C][C]0.940321[/C][C]0.52984[/C][/ROW]
[ROW][C]192[/C][C]0.425395[/C][C]0.850791[/C][C]0.574605[/C][/ROW]
[ROW][C]193[/C][C]0.611378[/C][C]0.777243[/C][C]0.388622[/C][/ROW]
[ROW][C]194[/C][C]0.560994[/C][C]0.878013[/C][C]0.439006[/C][/ROW]
[ROW][C]195[/C][C]0.552044[/C][C]0.895911[/C][C]0.447956[/C][/ROW]
[ROW][C]196[/C][C]0.53396[/C][C]0.932081[/C][C]0.46604[/C][/ROW]
[ROW][C]197[/C][C]0.591511[/C][C]0.816978[/C][C]0.408489[/C][/ROW]
[ROW][C]198[/C][C]0.597246[/C][C]0.805508[/C][C]0.402754[/C][/ROW]
[ROW][C]199[/C][C]0.570299[/C][C]0.859403[/C][C]0.429701[/C][/ROW]
[ROW][C]200[/C][C]0.515348[/C][C]0.969305[/C][C]0.484652[/C][/ROW]
[ROW][C]201[/C][C]0.459539[/C][C]0.919077[/C][C]0.540461[/C][/ROW]
[ROW][C]202[/C][C]0.439839[/C][C]0.879678[/C][C]0.560161[/C][/ROW]
[ROW][C]203[/C][C]0.388681[/C][C]0.777362[/C][C]0.611319[/C][/ROW]
[ROW][C]204[/C][C]0.332309[/C][C]0.664617[/C][C]0.667691[/C][/ROW]
[ROW][C]205[/C][C]0.301217[/C][C]0.602434[/C][C]0.698783[/C][/ROW]
[ROW][C]206[/C][C]0.249058[/C][C]0.498116[/C][C]0.750942[/C][/ROW]
[ROW][C]207[/C][C]0.200946[/C][C]0.401892[/C][C]0.799054[/C][/ROW]
[ROW][C]208[/C][C]0.192491[/C][C]0.384982[/C][C]0.807509[/C][/ROW]
[ROW][C]209[/C][C]0.299869[/C][C]0.599738[/C][C]0.700131[/C][/ROW]
[ROW][C]210[/C][C]0.278376[/C][C]0.556753[/C][C]0.721624[/C][/ROW]
[ROW][C]211[/C][C]0.292708[/C][C]0.585416[/C][C]0.707292[/C][/ROW]
[ROW][C]212[/C][C]0.475986[/C][C]0.951972[/C][C]0.524014[/C][/ROW]
[ROW][C]213[/C][C]0.467777[/C][C]0.935553[/C][C]0.532223[/C][/ROW]
[ROW][C]214[/C][C]0.576594[/C][C]0.846812[/C][C]0.423406[/C][/ROW]
[ROW][C]215[/C][C]0.499699[/C][C]0.999398[/C][C]0.500301[/C][/ROW]
[ROW][C]216[/C][C]0.416211[/C][C]0.832423[/C][C]0.583789[/C][/ROW]
[ROW][C]217[/C][C]0.448435[/C][C]0.89687[/C][C]0.551565[/C][/ROW]
[ROW][C]218[/C][C]0.764074[/C][C]0.471851[/C][C]0.235926[/C][/ROW]
[ROW][C]219[/C][C]0.861076[/C][C]0.277847[/C][C]0.138924[/C][/ROW]
[ROW][C]220[/C][C]0.786043[/C][C]0.427915[/C][C]0.213957[/C][/ROW]
[ROW][C]221[/C][C]0.690304[/C][C]0.619393[/C][C]0.309696[/C][/ROW]
[ROW][C]222[/C][C]0.648914[/C][C]0.702171[/C][C]0.351086[/C][/ROW]
[ROW][C]223[/C][C]0.672169[/C][C]0.655662[/C][C]0.327831[/C][/ROW]
[ROW][C]224[/C][C]0.558641[/C][C]0.882717[/C][C]0.441359[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=5

As an alternative you can also use a QR Code:  

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

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
50.7747570.4504860.225243
60.845870.3082590.15413
70.8308990.3382020.169101
80.9792050.04158970.0207949
90.9962660.007467850.00373393
100.9937390.01252270.00626134
110.9894570.02108510.0105425
120.9898480.02030470.0101523
130.9913530.01729320.00864658
140.9894240.02115270.0105764
150.983240.03351940.0167597
160.9771180.04576310.0228816
170.9882590.02348220.0117411
180.9826880.03462430.0173121
190.9766140.04677170.0233858
200.9663830.06723470.0336174
210.9546960.09060820.0453041
220.937950.1241010.0620504
230.9165440.1669120.0834558
240.9164580.1670840.0835418
250.8937480.2125050.106252
260.8817440.2365110.118256
270.8605740.2788510.139426
280.8328730.3342540.167127
290.7986150.4027710.201385
300.7620810.4758380.237919
310.7609430.4781140.239057
320.7162780.5674440.283722
330.7134610.5730790.286539
340.6698750.660250.330125
350.6202180.7595630.379782
360.6066420.7867160.393358
370.5945570.8108870.405443
380.5639730.8720540.436027
390.5272570.9454860.472743
400.4805510.9611030.519449
410.4320020.8640030.567998
420.3914950.782990.608505
430.348460.696920.65154
440.338250.67650.66175
450.3296550.6593110.670345
460.2882140.5764270.711786
470.2894270.5788540.710573
480.312590.6251810.68741
490.2720010.5440020.727999
500.2736310.5472620.726369
510.2374530.4749070.762547
520.2086790.4173580.791321
530.1782190.3564370.821781
540.1574780.3149570.842522
550.1356250.2712510.864375
560.1383120.2766230.861688
570.1526170.3052340.847383
580.1301130.2602260.869887
590.1104040.2208090.889596
600.09367660.1873530.906323
610.08094270.1618850.919057
620.06623510.132470.933765
630.0535180.1070360.946482
640.04890660.09781330.951093
650.042670.085340.95733
660.0474770.09495410.952523
670.04880090.09760170.951199
680.04205620.08411250.957944
690.03685730.07371470.963143
700.0330370.0660740.966963
710.02729510.05459030.972705
720.02501260.05002510.974987
730.0207630.04152610.979237
740.03479570.06959150.965204
750.05748360.1149670.942516
760.04767630.09535260.952324
770.04310370.08620750.956896
780.03505450.07010910.964945
790.02860580.05721160.971394
800.02859610.05719220.971404
810.02267570.04535150.977324
820.01848740.03697490.981513
830.01579250.03158490.984208
840.01624760.03249530.983752
850.01468830.02937650.985312
860.01171920.02343840.988281
870.009281710.01856340.990718
880.007168790.01433760.992831
890.006771910.01354380.993228
900.006308970.01261790.993691
910.009481860.01896370.990518
920.009223260.01844650.990777
930.008285330.01657070.991715
940.008814030.01762810.991186
950.0116460.0232920.988354
960.009476330.01895270.990524
970.01916370.03832740.980836
980.02465550.0493110.975344
990.02066010.04132030.97934
1000.01774230.03548460.982258
1010.01644380.03288760.983556
1020.02800240.05600490.971998
1030.02362490.04724970.976375
1040.01983290.03966590.980167
1050.01707340.03414690.982927
1060.01364050.0272810.98636
1070.01164480.02328970.988355
1080.009360280.01872060.99064
1090.008777510.0175550.991222
1100.008138320.01627660.991862
1110.006388320.01277660.993612
1120.004911260.009822510.995089
1130.004137940.008275870.995862
1140.003630530.007261060.996369
1150.00303690.006073810.996963
1160.006401140.01280230.993599
1170.005011250.01002250.994989
1180.005290090.01058020.99471
1190.004184360.008368730.995816
1200.003298880.006597770.996701
1210.002650610.005301210.997349
1220.003239670.006479340.99676
1230.002486430.004972860.997514
1240.002043750.004087490.997956
1250.001797090.003594180.998203
1260.001440070.002880140.99856
1270.001605710.003211420.998394
1280.001729280.003458550.998271
1290.001309430.002618870.998691
1300.0009691010.00193820.999031
1310.0007797990.00155960.99922
1320.0006822580.001364520.999318
1330.0005966340.001193270.999403
1340.0004574250.0009148510.999543
1350.0004313270.0008626540.999569
1360.0003167430.0006334870.999683
1370.0002311170.0004622330.999769
1380.0001626070.0003252150.999837
1390.0001258030.0002516070.999874
1408.80314e-050.0001760630.999912
1418.11525e-050.0001623050.999919
1425.75202e-050.000115040.999942
1436.9919e-050.0001398380.99993
1446.03187e-050.0001206370.99994
1454.13012e-058.26024e-050.999959
1464.64886e-059.29773e-050.999954
1470.0001649940.0003299880.999835
1480.0001498550.0002997110.99985
1490.0001079810.0002159630.999892
1507.44458e-050.0001488920.999926
1515.08883e-050.0001017770.999949
1520.1213270.2426540.878673
1530.1756090.3512180.824391
1540.1544220.3088440.845578
1550.1390210.2780420.860979
1560.1759470.3518940.824053
1570.155990.311980.84401
1580.1428560.2857120.857144
1590.2332570.4665130.766743
1600.2259810.4519610.774019
1610.2250780.4501560.774922
1620.1965430.3930850.803457
1630.1800220.3600440.819978
1640.1786640.3573290.821336
1650.2088620.4177240.791138
1660.2145510.4291030.785449
1670.2536220.5072440.746378
1680.2366080.4732160.763392
1690.2128130.4256260.787187
1700.1875230.3750460.812477
1710.1608860.3217730.839114
1720.1880310.3760620.811969
1730.2187180.4374350.781282
1740.2067020.4134040.793298
1750.1920050.3840110.807995
1760.1701090.3402180.829891
1770.1462510.2925020.853749
1780.1247340.2494680.875266
1790.1105410.2210820.889459
1800.1080780.2161550.891922
1810.0889460.1778920.911054
1820.07205040.1441010.92795
1830.0600130.1200260.939987
1840.0850920.1701840.914908
1850.07973650.1594730.920264
1860.06409830.1281970.935902
1870.05372850.1074570.946272
1880.04980170.09960350.950198
1890.04864330.09728660.951357
1900.515040.9699190.48496
1910.470160.9403210.52984
1920.4253950.8507910.574605
1930.6113780.7772430.388622
1940.5609940.8780130.439006
1950.5520440.8959110.447956
1960.533960.9320810.46604
1970.5915110.8169780.408489
1980.5972460.8055080.402754
1990.5702990.8594030.429701
2000.5153480.9693050.484652
2010.4595390.9190770.540461
2020.4398390.8796780.560161
2030.3886810.7773620.611319
2040.3323090.6646170.667691
2050.3012170.6024340.698783
2060.2490580.4981160.750942
2070.2009460.4018920.799054
2080.1924910.3849820.807509
2090.2998690.5997380.700131
2100.2783760.5567530.721624
2110.2927080.5854160.707292
2120.4759860.9519720.524014
2130.4677770.9355530.532223
2140.5765940.8468120.423406
2150.4996990.9993980.500301
2160.4162110.8324230.583789
2170.4484350.896870.551565
2180.7640740.4718510.235926
2190.8610760.2778470.138924
2200.7860430.4279150.213957
2210.6903040.6193930.309696
2220.6489140.7021710.351086
2230.6721690.6556620.327831
2240.5586410.8827170.441359







Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.172727NOK
5% type I error level830.377273NOK
10% type I error level1030.468182NOK

\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 & 38 & 0.172727 & NOK \tabularnewline
5% type I error level & 83 & 0.377273 & NOK \tabularnewline
10% type I error level & 103 & 0.468182 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=268261&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]38[/C][C]0.172727[/C][C]NOK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]83[/C][C]0.377273[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]103[/C][C]0.468182[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=268261&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=268261&T=6

As an alternative you can also use a QR Code:  

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

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level380.172727NOK
5% type I error level830.377273NOK
10% type I error level1030.468182NOK



Parameters (Session):
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')
}