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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 computationFri, 30 Oct 2009 05:58:59 -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/30/t1256904023p4znsg0jyp40ug6.htm/, Retrieved Sun, 28 Apr 2024 22:51:36 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52081, Retrieved Sun, 28 Apr 2024 22:51:36 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact85
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [workshop 4,2,2] [2009-10-30 11:58:59] [2210215221105fab636491031ce54076] [Current]
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Dataseries X:
2,091864062
2,079441542
2,014903021
2,00148
2,041220329
2,066862759
2,041220329
1,960094784
1,824549292
1,757857918
1,808288771
1,931521412
1,987874348
1,974081026
1,808288771
1,757857918
1,808288771
1,840549633
1,916922612
1,916922612
1,871802177
1,824549292
1,840549633
1,85629799
1,887069649
2,028148247
1,85629799
1,916922612
1,945910149
1,931521412
1,960094784
1,974081026
1,960094784
1,945910149
1,931521412
1,902107526
1,887069649
1,931521412
1,987874348
2,066862759
2,104134154
2,104134154
2,104134154
2,091864062
2,066862759
2,041220329
2,041220329
2,028148247
2,014903021
2,014903021
1,960094784
2,014903021
2,014903021
2,054123734
2,054123734
2,054123734
2,028148247
2,014903021
2,041220329
2,091864062
2,079441542
Dataseries Y:
2,406945108
2,388762789
2,302585093
2,219203484
2,219203484
2,251291799
2,261763098
2,251291799
2,208274414
2,186051277
2,197224577
2,312535424
2,332143895
2,32238772
2,261763098
2,219203484
2,2300144
2,240709689
2,240709689
2,219203484
2,197224577
2,197224577
2,197224577
2,282382386
2,302585093
2,282382386
2,2300144
2,197224577
2,197224577
2,208274414
2,208274414
2,208274414
2,219203484
2,174751721
2,116255515
2,128231706
2,091864062
2,041220329
2,066862759
2,066862759
2,079441542
2,066862759
2,028148247
1,960094784
1,916922612
1,871802177
1,931521412
2,104134154
2,163323026
2,116255515
2,066862759
2,014903021
2,054123734
2,116255515
2,128231706
2,104134154
2,041220329
1,974081026
1,987874348
2,091864062
2,140066163




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52081&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]4 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=52081&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52081&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c3.00525157708987
b-0.428422499474173

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 3.00525157708987 \tabularnewline
b & -0.428422499474173 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52081&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]3.00525157708987[/C][/ROW]
[ROW][C]b[/C][C]-0.428422499474173[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52081&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52081&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]
c3.00525157708987
b-0.428422499474173







Descriptive Statistics about e[t]
# observations61
minimum-0.258944684762192
Q1-0.0621142105323104
median-0.00610483289832725
mean7.27393014901136e-19
Q30.0537006134777034
maximum0.297895160912372

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -0.258944684762192 \tabularnewline
Q1 & -0.0621142105323104 \tabularnewline
median & -0.00610483289832725 \tabularnewline
mean & 7.27393014901136e-19 \tabularnewline
Q3 & 0.0537006134777034 \tabularnewline
maximum & 0.297895160912372 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52081&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-0.258944684762192[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0621142105323104[/C][/ROW]
[ROW][C]median[/C][C]-0.00610483289832725[/C][/ROW]
[ROW][C]mean[/C][C]7.27393014901136e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0537006134777034[/C][/ROW]
[ROW][C]maximum[/C][C]0.297895160912372[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52081&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52081&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]
# observations61
minimum-0.258944684762192
Q1-0.0621142105323104
median-0.00610483289832725
mean7.27393014901136e-19
Q30.0537006134777034
maximum0.297895160912372



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')