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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, 09 Nov 2009 13:15:56 -0700
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/Nov/09/t1257797803bp1y66ihvahelet.htm/, Retrieved Thu, 18 Apr 2024 03:18:41 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54998, Retrieved Thu, 18 Apr 2024 03:18:41 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact222
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [workshop 6] [2009-11-08 11:09:36] [3d8acb8ffdb376c5fec19e610f8198c2]
-   PD    [Bivariate Explorative Data Analysis] [workshop 6] [2009-11-09 20:15:56] [e81f30a5c3daacfe71a556c99a478849] [Current]
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Dataseries X:
6.9
6.8
6.7
6.6
6.5
6.5
7.0
7.5
7.6
7.6
7.6
7.8
8.0
8.0
8.0
7.9
7.9
8.0
8.5
9.2
9.4
9.5
9.5
9.6
9.7
9.7
9.6
9.5
9.4
9.3
9.6
10.2
10.2
10.1
9.9
9.8
9.8
9.7
9.5
9.3
9.1
9.0
9.5
10.0
10.2
10.1
10.0
9.9
10.0
9.9
9.7
9.5
9.2
9.0
9.3
9.8
9.8
9.6
9.4
9.3
9.2
9.2
9.0
8.8
8.7
8.7
9.1
9.7
9.8
9.6
9.4
9.4
9.5
9.4
9.3
9.2
9.0
8.9
9.2
9.8
9.9
9.6
9.2
9.1
9.1
9.0
8.9
8.7
8.5
8.3
8.5
8.7
8.4
8.1
7.8
7.7
7.5
7.2
6.8
6.7
6.4
6.3
6.8
7.3
7.1
7.0
6.8
6.6
6.3
6.1
6.1
6.3
6.3
6.0
6.2
6.4
6.8
7.5
7.5
7.6
7.6
7.4
7.3
7.1
6.9
6.8
7.5
7.6
7.8
8.0
8.1
8.2
8.3
8.2
8.0
7.9
7.6
7.6
8.3
8.4
8.4
8.4
8.4
8.6
8.9
8.8
8.3
7.5
7.2
7.4
8.8
9.3
9.3
8.7
8.2
8.3
8.5
8.6
8.5
8.2
8.1
7.9
8.6
8.7
8.7
8.5
8.4
8.5
8.7
8.7
8.6
8.5
8.3
8.0
8.2
8.1
8.1
8.0
7.9
7.9
Dataseries Y:
4.8
4.8
4.7
4.7
4.7
4.6
5.0
5.4
5.5
5.6
5.6
5.8
6.0
6.1
6.1
6.0
6.0
6.1
6.5
7.1
7.4
7.4
7.5
7.6
7.8
7.8
7.7
7.6
7.5
7.3
7.6
8.0
8.8
7.9
7.8
7.7
7.8
7.7
7.5
7.3
7.1
7.0
7.3
7.8
7.9
7.9
7.8
7.8
7.9
7.8
7.6
7.4
7.2
6.9
7.1
7.5
7.6
7.4
7.3
7.2
7.3
7.2
7.1
7.0
6.9
6.8
7.2
7.6
7.7
7.6
7.5
7.5
7.6
7.6
7.6
7.5
7.3
7.2
7.4
8.0
8.2
8.0
7.7
7.7
7.8
7.8
7.7
7.5
7.3
7.1
7.1
7.2
6.8
6.6
6.4
6.4
6.5
6.3
5.9
5.5
5.2
4.9
5.4
5.8
5.7
5.6
5.5
5.4
5.4
5.4
5.5
5.8
5.7
5.4
5.6
5.8
6.2
6.8
6.7
6.7
6.4
6.3
6.3
6.4
6.3
6.0
6.3
6.3
6.6
7.5
7.8
7.9
7.8
7.6
7.5
7.6
7.5
7.3
7.6
7.5
7.6
7.9
7.9
8.1
8.2
8.0
7.5
6.8
6.5
6.6
7.6
8.0
8.1
7.7
7.5
7.6
7.8
7.8
7.8
7.5
7.5
7.1
7.5
7.5
7.6
7.7
7.7
7.9
8.1
8.2
8.2
8.2
7.9
7.3
6.9
6.6
6.7
6.9
7.0
7.1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54998&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]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54998&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54998&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'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c1.07132667254828
b0.706358715806357

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.07132667254828 \tabularnewline
b & 0.706358715806357 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54998&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.07132667254828[/C][/ROW]
[ROW][C]b[/C][C]0.706358715806357[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54998&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54998&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]
c1.07132667254828
b0.706358715806357







Descriptive Statistics about e[t]
# observations180
minimum-1.14520181161219
Q1-0.336301055345743
median-0.116242591628188
mean2.19635266763952e-17
Q30.354190825734746
maximum1.12462424309768

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 180 \tabularnewline
minimum & -1.14520181161219 \tabularnewline
Q1 & -0.336301055345743 \tabularnewline
median & -0.116242591628188 \tabularnewline
mean & 2.19635266763952e-17 \tabularnewline
Q3 & 0.354190825734746 \tabularnewline
maximum & 1.12462424309768 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54998&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]180[/C][/ROW]
[ROW][C]minimum[/C][C]-1.14520181161219[/C][/ROW]
[ROW][C]Q1[/C][C]-0.336301055345743[/C][/ROW]
[ROW][C]median[/C][C]-0.116242591628188[/C][/ROW]
[ROW][C]mean[/C][C]2.19635266763952e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.354190825734746[/C][/ROW]
[ROW][C]maximum[/C][C]1.12462424309768[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54998&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54998&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]
# observations180
minimum-1.14520181161219
Q1-0.336301055345743
median-0.116242591628188
mean2.19635266763952e-17
Q30.354190825734746
maximum1.12462424309768



Parameters (Session):
par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;
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')