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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationWed, 28 Oct 2009 19:11:13 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Oct/29/t1256778746569smfj4hl530xa.htm/, Retrieved Mon, 29 Apr 2024 05:00:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51907, Retrieved Mon, 29 Apr 2024 05:00:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [] [2009-10-28 22:00:50] [30e733e0d80e1684893fcdfadcb286e7]
-         [Bivariate Explorative Data Analysis] [] [2009-10-29 01:11:13] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
3760265041
3374215744
2983672129
2861715025
2685726976
2552068324
2405902500
2219446321
2048829696
1967543449
3009839044
3349052641
3489264900
3166650529
2791748569
2673096804
2445005809
2397571225
2201674084
2139617536
2043040000
1977669841
2821628161
3026760256
3208202881
2688111409
2303040100
2092513536
2152032100
1976780521
1729062724
1665700969
1451305216
1257482521
1969140625
2139525025
2080272100
1881390625
1613387889
1650634384
1647548100
1558117729
1349460225
1342049956
1076233636
1082870649
1687237776
1785400516
1867536225
1690525456
1629979129
1766184676
1909777401
1945339236
1998090000
1980784036
1728813241
1803700900
2566030336
2793862449
Dataseries Y:
82140706404
80112773764
76555695969
77236747225
76799928384
76786072609
75645351369
72981022500
71363779600
70221290049
82517733081
84789286596
85439290000
83051170596
79229301529
79894414336
78506436100
78628646464
76638170896
75743846656
75269019904
73609658721
83985199204
84521607076
85439290000
77565592036
72806070276
70682071321
72379293156
69788958976
65126019204
64187742609
60544047249
55399978384
66851205136
68117346049
64853243569
62821913449
59254270084
61060881025
61772628681
60044111521
56206926400
56209297225
50874606916
51455931921
61471268356
61669278889
60993686961
60073029604
60645465169
65415735225
69864533761
72010112409
74554118116
75055725369
71518804900
73980192049
85679144100
87545566161




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk

\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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51907&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51907&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51907&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c41442632909.0114
b13.608896292005

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 41442632909.0114 \tabularnewline
b & 13.608896292005 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51907&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]41442632909.0114[/C][/ROW]
[ROW][C]b[/C][C]13.608896292005[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51907&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51907&T=1

As an alternative you can also use a QR Code:  

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

Model: Y[t] = c + b X[t] + e[t]
c41442632909.0114
b13.608896292005







Descriptive Statistics about e[t]
# observations60
minimum-10474983478.4323
Q1-3151902442.95898
median-20559141.2320008
mean3.34251672029495e-07
Q32163397747.38817
maximum9315670466.2259

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -10474983478.4323 \tabularnewline
Q1 & -3151902442.95898 \tabularnewline
median & -20559141.2320008 \tabularnewline
mean & 3.34251672029495e-07 \tabularnewline
Q3 & 2163397747.38817 \tabularnewline
maximum & 9315670466.2259 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51907&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-10474983478.4323[/C][/ROW]
[ROW][C]Q1[/C][C]-3151902442.95898[/C][/ROW]
[ROW][C]median[/C][C]-20559141.2320008[/C][/ROW]
[ROW][C]mean[/C][C]3.34251672029495e-07[/C][/ROW]
[ROW][C]Q3[/C][C]2163397747.38817[/C][/ROW]
[ROW][C]maximum[/C][C]9315670466.2259[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51907&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51907&T=2

As an alternative you can also use a QR Code:  

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

Descriptive Statistics about e[t]
# observations60
minimum-10474983478.4323
Q1-3151902442.95898
median-20559141.2320008
mean3.34251672029495e-07
Q32163397747.38817
maximum9315670466.2259



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
par2 <- as.numeric(par2)
x <- as.ts(x)
y <- as.ts(y)
mylm <- lm(y~x)
cbind(mylm$resid)
library(lattice)
bitmap(file='pic1.png')
plot(y,type='l',main='Run Sequence Plot of Y[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1a.png')
plot(x,type='l',main='Run Sequence Plot of X[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic1b.png')
plot(x,y,main='Scatter Plot',xlab='X[t]',ylab='Y[t]')
grid()
dev.off()
bitmap(file='pic1c.png')
plot(mylm$resid,type='l',main='Run Sequence Plot of e[t]',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(mylm$resid,main='Histogram of e[t]')
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~mylm$resid,col='black',main=paste('Density Plot of e[t] bw = ',par1),bw=par1)
} else {
densityplot(~mylm$resid,col='black',main='Density Plot of e[t]')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(mylm$resid,main='QQ plot of e[t]')
qqline(mylm$resid)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='pic5.png')
acf(mylm$resid,lag.max=par2,main='Residual Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Model: Y[t] = c + b X[t] + e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'c',1,TRUE)
a<-table.element(a,mylm$coeff[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'b',1,TRUE)
a<-table.element(a,mylm$coeff[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics about e[t]',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(mylm$resid))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(mylm$resid,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(mylm$resid))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')