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workshop 4

*The author of this computation has been verified*

R Software Module: rwasp_edabi.wasp (opens new window with default values)

Title produced by software: Bivariate Explorative Data Analysis

Date of computation: Tue, 27 Oct 2009 14:41:40 -0600

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp.htm/, Retrieved Wed, 22 May 2013 08:25:54 +0000

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

System-generated keywords (parent):

(pk = 0)

Estimated Impact

Dataseries X:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Dataseries Y:

» Textfile « » CSV « » Stem and Leaf « » Histogram « » Kernel Density « » Harrell-Davis Quantiles « » Central Tendency « » Variability «

Output produced by software:

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Model: Y[t] = c + b X[t] + e[t]
c	-4.17338339823217
b	1.79918412757276

Descriptive Statistics about e[t]
# observations	60
minimum	-0.0944638111131718
Q1	-0.030478088880649
median	0.00354842697323695
mean	4.84827541792574e-18
Q3	0.0365402682489640
maximum	0.0855361888868288

Charts produced by software:

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/1g9vr1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/1g9vr1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/2n9zz1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/2n9zz1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/3kyoy1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/3kyoy1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/4pi3p1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/4pi3p1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/5sxos1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/5sxos1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/6cott1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/6cott1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/7x8vv1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/7x8vv1256676096.ps (opens in new window)

Click here to open pdf file.

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/8jq6o1256676096.png (opens in new window)

http://www.freestatistics.org/blog/date/2009/Oct/27/t1256676448jea7uih6h30n3wp/8jq6o1256676096.ps (opens in new window)

Click here to open pdf file.

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')