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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 computationSun, 25 Oct 2009 11:45:33 -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/25/t1256492783neifrcro1vxjmje.htm/, Retrieved Mon, 29 Apr 2024 11:43:16 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50349, Retrieved Mon, 29 Apr 2024 11:43:16 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact176
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]
-   PD  [Bivariate Data Series] [] [2009-10-25 17:21:06] [badc6a9acdc45286bea7f74742e15a21]
-   PD    [Bivariate Data Series] [] [2009-10-25 17:43:31] [badc6a9acdc45286bea7f74742e15a21]
- RM D        [Bivariate Explorative Data Analysis] [] [2009-10-25 17:45:33] [0545e25c765ce26b196961216dc11e13] [Current]
- RM            [Pearson Correlation] [] [2009-10-25 17:47:50] [badc6a9acdc45286bea7f74742e15a21]
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Dataseries X:
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.693147181
0.792992516
0.810930216
0.810930216
0.896088025
0.916290732
0.916290732
0.970778917
1.011600912
1.075002423
1.098612289
1.153731588
1.178654996
1.220829921
1.252762968
1.252762968
1.294727168
1.32175584
1.32175584
1.360976553
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.386294361
1.430311247
1.446918983
1.446918983
1.378766095
1.229640551
1.011600912
0.837247525
0.693147181
0.506817602
0.270027137
0.086177696
0
0
0
0
Dataseries Y:
1.4
1.2
1
1.7
2.4
2
2.1
2
1.8
2.7
2.3
1.9
2
2.3
2.8
2.4
2.3
2.7
2.7
2.9
3
2.2
2.3
2.8
2.8
2.8
2.2
2.6
2.8
2.5
2.4
2.3
1.9
1.7
2
2.1
1.7
1.8
1.8
1.8
1.3
1.3
1.3
1.2
1.4
2.2
2.9
3.1
3.5
3.6
4.4
4.1
5.1
5.8
5.9
5.4
5.5
4.8
3.2
2.7
2.1
1.9
0.6
0.7
-0.2
-1
-1.7
-0.7
-1




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time15 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 & 15 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50349&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]15 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=50349&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50349&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 time15 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c0.0135575986611310
b2.46275319501904

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 0.0135575986611310 \tabularnewline
b & 2.46275319501904 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50349&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]0.0135575986611310[/C][/ROW]
[ROW][C]b[/C][C]2.46275319501904[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50349&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50349&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]
c0.0135575986611310
b2.46275319501904







Descriptive Statistics about e[t]
# observations69
minimum-2.22765846545076
Q1-0.720608033287324
median0.158141205638643
mean-2.37644545748852e-17
Q30.679391966712676
maximum2.37234153454924

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -2.22765846545076 \tabularnewline
Q1 & -0.720608033287324 \tabularnewline
median & 0.158141205638643 \tabularnewline
mean & -2.37644545748852e-17 \tabularnewline
Q3 & 0.679391966712676 \tabularnewline
maximum & 2.37234153454924 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50349&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]69[/C][/ROW]
[ROW][C]minimum[/C][C]-2.22765846545076[/C][/ROW]
[ROW][C]Q1[/C][C]-0.720608033287324[/C][/ROW]
[ROW][C]median[/C][C]0.158141205638643[/C][/ROW]
[ROW][C]mean[/C][C]-2.37644545748852e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.679391966712676[/C][/ROW]
[ROW][C]maximum[/C][C]2.37234153454924[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50349&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50349&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]
# observations69
minimum-2.22765846545076
Q1-0.720608033287324
median0.158141205638643
mean-2.37644545748852e-17
Q30.679391966712676
maximum2.37234153454924



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')