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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 11:03:27 -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/t1256749452cjhw8thjv1dqw7p.htm/, Retrieved Mon, 06 May 2024 09:58:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51580, Retrieved Mon, 06 May 2024 09:58:41 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact100
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 bivariate EDA...] [2009-10-28 15:49:46] [37a8d600db9abe09a2528d150ccff095]
-   PD      [Bivariate Explorative Data Analysis] [Workshop 4] [2009-10-28 17:03:27] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
3,496507561
3,663561646
3,80666249
3,828641396
3,80666249
3,80666249
3,891820298
3,912023005
3,988984047
4,077537444
4,060443011
4,025351691
3,871201011
3,912023005
3,951243719
3,970291914
4,007333185
3,761200116
3,737669618
3,63758616
3,713572067
3,713572067
3,663561646
3,526360525
3,295836866
2,708050201
2,63905733
3,433987204
3,713572067
3,761200116
3,828641396
3,737669618
3,80666249
3,80666249
3,688879454
3,555348061
3,583518938
3,63758616
3,663561646
3,465735903
3,17805383
3,044522438
2,48490665
3,36729583
3,583518938
3,433987204
3,33220451
3,401197382
3,63758616
3,295836866
3,688879454
3,688879454
3,784189634
3,850147602
3,80666249
3,737669618
3,63758616
3,828641396
3,610917913
3,713572067
3,688879454
3,496507561
3,526360525
3,583518938
3,583518938
3,63758616
3,737669618
3,555348061
3,218875825
3,17805383
3,091042453
3,295836866
2,833213344
3,401197382
3,401197382
3,526360525
3,610917913
3,583518938
3,496507561
3,496507561
3,496507561
3,610917913
3,688879454
3,555348061
3,610917913
3,761200116
3,737669618
3,496507561
3,663561646
3,688879454
3,610917913
3,784189634
3,737669618
3,761200116
3,688879454
3,401197382
3,401197382
3,433987204
2,890371758
3,17805383
3,091042453
3,258096538
3,33220451
3,135494216
2,833213344
2,48490665
2,197224577
2,944438979
3,044522438
2,890371758
2,890371758
2,708050201
3,17805383
2,890371758
2,944438979
3,401197382
3,496507561
3,555348061
3,583518938
3,850147602
3,828641396
Dataseries Y:
4,127134385
4,158883083
4,127134385
4,158883083
4,158883083
4,234106505
4,234106505
4,17438727
4,025351691
4,060443011
3,970291914
4,127134385
4,007333185
4,094344562
4,077537444
4,060443011
3,970291914
4,043051268
4,043051268
3,970291914
3,988984047
3,970291914
4,043051268
4,043051268
4,007333185
3,891820298
3,912023005
3,891820298
3,988984047
4,060443011
4,060443011
3,951243719
4,025351691
3,951243719
4,077537444
3,970291914
3,951243719
3,970291914
3,931825633
3,912023005
4,025351691
3,951243719
3,828641396
3,871201011
3,828641396
3,871201011
3,871201011
3,891820298
3,970291914
3,871201011
3,931825633
3,871201011
3,912023005
4,007333185
3,951243719
3,970291914
3,951243719
4,007333185
3,970291914
3,970291914
4,025351691
3,988984047
3,951243719
4,007333185
3,988984047
4,077537444
4,025351691
4,025351691
3,931825633
3,970291914
3,951243719
3,931825633
3,828641396
3,891820298
3,828641396
4,007333185
4,043051268
3,970291914
3,951243719
3,970291914
3,912023005
3,988984047
3,970291914
3,912023005
3,931825633
3,951243719
3,850147602
3,931825633
3,891820298
3,970291914
3,951243719
3,80666249
3,970291914
3,931825633
3,871201011
3,871201011
3,871201011
3,871201011
3,688879454
3,761200116
3,688879454
3,663561646
3,663561646
3,583518938
3,713572067
3,663561646
3,688879454
3,663561646
3,828641396
3,688879454
3,610917913
3,610917913
3,784189634
3,713572067
3,688879454
3,583518938
3,63758616
3,761200116
3,737669618
3,80666249
3,828641396




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51580&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]'RServer@AstonUniversity' @ vre.aston.ac.uk[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51580&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51580&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'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c3.04032594608837
b0.252273496219803

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 3.04032594608837 \tabularnewline
b & 0.252273496219803 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51580&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]3.04032594608837[/C][/ROW]
[ROW][C]b[/C][C]0.252273496219803[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51580&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51580&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]
c3.04032594608837
b0.252273496219803







Descriptive Statistics about e[t]
# observations121
minimum-0.314838962979153
Q1-0.0494022823694529
median-0.000640549082349676
mean1.44933637520273e-19
Q30.0629803876524928
maximum0.233460503630547

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 121 \tabularnewline
minimum & -0.314838962979153 \tabularnewline
Q1 & -0.0494022823694529 \tabularnewline
median & -0.000640549082349676 \tabularnewline
mean & 1.44933637520273e-19 \tabularnewline
Q3 & 0.0629803876524928 \tabularnewline
maximum & 0.233460503630547 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51580&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]121[/C][/ROW]
[ROW][C]minimum[/C][C]-0.314838962979153[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0494022823694529[/C][/ROW]
[ROW][C]median[/C][C]-0.000640549082349676[/C][/ROW]
[ROW][C]mean[/C][C]1.44933637520273e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0629803876524928[/C][/ROW]
[ROW][C]maximum[/C][C]0.233460503630547[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51580&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51580&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]
# observations121
minimum-0.314838962979153
Q1-0.0494022823694529
median-0.000640549082349676
mean1.44933637520273e-19
Q30.0629803876524928
maximum0.233460503630547



Parameters (Session):
par1 = 0 ; par2 = 1 ;
Parameters (R input):
par1 = 0 ; par2 = 1 ;
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')