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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 computationMon, 26 Oct 2009 13:01:46 -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/26/t1256584217gcmgf3tta3p5g1p.htm/, Retrieved Thu, 02 May 2024 15:53:52 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50703, Retrieved Thu, 02 May 2024 15:53:52 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact211
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] [WS 4 Part 1.1] [2009-10-24 09:57:59] [83058a88a37d754675a5cd22dab372fc]
-    D      [Bivariate Explorative Data Analysis] [WS 4 Part 2.2] [2009-10-26 19:01:46] [eba9f01697e64705b70041e6f338cb22] [Current]
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Dataseries X:
4,633757643
4,578826211
4,713127327
4,470495283
4,572646994
4,737075257
4,703203926
4,643428898
4,621043535
4,549657476
4,563305982
4,651099118
4,632785353
4,585987367
4,73532087
4,393213824
4,561218298
4,729156166
4,662495253
4,689511334
4,627909673
4,59511985
4,6121458
4,74927053
4,6121458
4,699570861
4,741447804
4,447346101
4,610157727
4,743191484
4,757891273
4,726502471
4,624972813
4,663439094
4,656813419
4,777441407
4,664382046
4,694096395
4,763881877
4,527208645
4,646312129
4,722953222
4,80729437
4,730039168
4,605170186
4,70682384
4,725616339
4,698660529
4,764734756
4,692264893
4,75272775
4,564348191
4,603168183
4,76046307
4,751000634
4,599152114
4,54648119
4,510859507
4,534747722
4,635699391
Dataseries Y:
4,682223815
4,617197566
4,786908239
4,551347379
4,556609995
4,770345584
4,752382566
4,713486329
4,683611612
4,689235561
4,695467824
4,826952812
4,747624154
4,695833221
4,822215179
4,530985288
4,589244035
4,794798318
4,715995741
4,754451889
4,694736629
4,715368978
4,738739078
4,895448884
4,738564069
4,840163254
4,875197323
4,644390899
4,690246358
4,85577325
4,886129713
4,852342715
4,75660289
4,795211866
4,775672166
4,891100725
4,796203683
4,849057098
4,908528738
4,743888105
4,739176466
4,858648937
4,93375425
4,863217453
4,744584242
4,851874002
4,844423279
4,85787254
4,926601298
4,854916719
4,911919321
4,80557721
4,728095533
4,914124394
4,927253685
4,74701691
4,709079649
4,597440388
4,628789052
4,724463192




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50703&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]3 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=50703&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50703&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 time3 seconds
R Server'George Udny Yule' @ 72.249.76.132







Model: Y[t] = c + b X[t] + e[t]
c0.0667854859738619
b1.01075378324331

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0667854859738619 \tabularnewline
b & 1.01075378324331 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50703&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0667854859738619[/C][/ROW]
[ROW][C]b[/C][C]1.01075378324331[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50703&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50703&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]
c0.0667854859738619
b1.01075378324331







Descriptive Statistics about e[t]
# observations60
minimum-0.131995739595517
Q1-0.0316123752073992
median0.0093375789800198
mean3.1317631503149e-18
Q30.0268858446146886
maximum0.125359521933125

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.131995739595517 \tabularnewline
Q1 & -0.0316123752073992 \tabularnewline
median & 0.0093375789800198 \tabularnewline
mean & 3.1317631503149e-18 \tabularnewline
Q3 & 0.0268858446146886 \tabularnewline
maximum & 0.125359521933125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50703&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]-0.131995739595517[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0316123752073992[/C][/ROW]
[ROW][C]median[/C][C]0.0093375789800198[/C][/ROW]
[ROW][C]mean[/C][C]3.1317631503149e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0268858446146886[/C][/ROW]
[ROW][C]maximum[/C][C]0.125359521933125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50703&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50703&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-0.131995739595517
Q1-0.0316123752073992
median0.0093375789800198
mean3.1317631503149e-18
Q30.0268858446146886
maximum0.125359521933125



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')