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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 10:06:34 -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/28/t125674611315e0htwrgqnm66q.htm/, Retrieved Mon, 06 May 2024 09:09:13 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51489, Retrieved Mon, 06 May 2024 09:09:13 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact83
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
- RMPD  [Bivariate Explorative Data Analysis] [ws4 part2 ex2] [2009-10-27 18:06:47] [95cead3ebb75668735f848316249436a]
-    D      [Bivariate Explorative Data Analysis] [Ws 4 part 2 ex 2] [2009-10-28 16:06:34] [ba02bcb7e07025bbb7f8a074d38ad767] [Current]
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Dataseries X:
2,797281335
2,879198457
3,104586678
3,126760536
2,90690106
3,109060959
3,173878459
3,058707073
3,135494216
3,063390922
3,054001182
3,039749159
2,884800713
3,0301337
3,100092289
2,985681938
2,87356464
2,975529566
3,034952987
2,985681938
2,923161581
3,044522438
2,923161581
2,939161922
2,850706502
2,995732274
2,990719732
2,970414466
2,785011242
2,867898902
2,985681938
2,965273066
2,844909384
3,04927304
2,879198457
2,862200881
2,890371758
2,949688335
2,87356464
2,954910279
2,714694744
2,791165108
2,923161581
2,844909384
2,879198457
2,949688335
2,809402695
2,772588722
2,815408719
2,856470206
2,884800713
2,879198457
2,63188884
2,766319109
2,884800713
2,734367509
2,797281335
2,884800713
2,727852828
2,681021529
2,701361213
2,708050201
2,815408719
2,791165108
2,459588842
2,714694744
2,740840024
2,708050201
2,734367509
2,772588722
2,687847494
2,694627181
Dataseries Y:
2,890371758
2,975529566
3,148453361
3,165475048
3,010620886
3,126760536
3,19047635
3,068052935
3,157000421
3,100092289
3,039749159
3,100092289
2,970414466
3,04927304
3,091042453
2,954910279
2,879198457
2,954910279
2,990719732
2,975529566
2,895911938
3,015534901
2,895911938
2,923161581
2,867898902
2,965273066
2,960105096
2,923161581
2,827313622
2,797281335
2,944438979
2,928523524
2,839078464
3,068052935
2,879198457
2,895911938
2,944438979
2,939161922
2,821378886
2,895911938
2,753660712
2,714694744
2,90690106
2,803360381
2,827313622
2,912350665
2,797281335
2,753660712
2,827313622
2,809402695
2,815408719
2,809402695
2,667228207
2,674148649
2,862200881
2,660259537
2,734367509
2,844909384
2,681021529
2,653241965
2,701361213
2,646174797
2,747270914
2,681021529
2,4765384
2,602689685
2,653241965
2,617395833
2,667228207
2,727852828
2,660259537
2,674148649




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 5 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51489&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51489&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51489&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 time5 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c-0.27844894205909
b1.09081543711929

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.27844894205909 \tabularnewline
b & 1.09081543711929 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51489&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.27844894205909[/C][/ROW]
[ROW][C]b[/C][C]1.09081543711929[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51489&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51489&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]
c-0.27844894205909
b1.09081543711929







Descriptive Statistics about e[t]
# observations72
minimum-0.0851755162960413
Q1-0.0341302306329241
median-0.00913622898531611
mean1.73472347597681e-18
Q30.0225837067195115
maximum0.118177277632661

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -0.0851755162960413 \tabularnewline
Q1 & -0.0341302306329241 \tabularnewline
median & -0.00913622898531611 \tabularnewline
mean & 1.73472347597681e-18 \tabularnewline
Q3 & 0.0225837067195115 \tabularnewline
maximum & 0.118177277632661 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51489&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-0.0851755162960413[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0341302306329241[/C][/ROW]
[ROW][C]median[/C][C]-0.00913622898531611[/C][/ROW]
[ROW][C]mean[/C][C]1.73472347597681e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0225837067195115[/C][/ROW]
[ROW][C]maximum[/C][C]0.118177277632661[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51489&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51489&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]
# observations72
minimum-0.0851755162960413
Q1-0.0341302306329241
median-0.00913622898531611
mean1.73472347597681e-18
Q30.0225837067195115
maximum0.118177277632661



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ;
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')