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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 13:51:38 -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/t12577999754mv6uzwf2k4y1u2.htm/, Retrieved Fri, 29 Mar 2024 11:34:07 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55047, Retrieved Fri, 29 Mar 2024 11:34:07 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS5 bivariate EDA X en Z
Estimated Impact223
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [WS5 trivariate] [2009-11-09 12:59:13] [c620fe7250af73a91c51407172a85dab]
- RMP   [Partial Correlation] [WS5 partiële corr...] [2009-11-09 19:36:40] [c620fe7250af73a91c51407172a85dab]
- RMPD      [Bivariate Explorative Data Analysis] [WS5 bivariate EDA...] [2009-11-09 20:51:38] [b4ff140915b3f24d4faed3d78f95eba4] [Current]
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Dataseries X:
8
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
7.1
7.2
7.1
6.9
7
6.8
6.4
6.7
6.6
6.4
6.3
6.2
6.5
6.8
6.8
6.4
6.1
5.8
6.1
7.2
7.3
6.9
6.1
5.8
6.2
7.1
7.7
7.9
7.7
7.4
7.5
8
Dataseries Y:
4.2
4
4.9
4.6
4.3
4.3
4.6
5.1
4.8
4.5
4.9
5.1
5.1
5.2
4.5
4.6
4.9
4.6
4.4
3.7
4
4.2
3.9
3.6
3.6
3.2
3.2
3.5
3.6
3.7
3.8
3.8
3.8
3.3
3.3
3.4
3.1
3.5
4.2
4.9
5.1
5.5
5.6
6.4
6.2
7.2
7.8
7.9
7.4
7.5
6.7
5.1
4.6
4.3
3.9
2.6
2.6
1.6
0.9
0.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55047&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]2 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=55047&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55047&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c9.6137183196087
b-0.724432022255455

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 9.6137183196087 \tabularnewline
b & -0.724432022255455 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55047&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]9.6137183196087[/C][/ROW]
[ROW][C]b[/C][C]-0.724432022255455[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55047&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55047&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]
c9.6137183196087
b-0.724432022255455







Descriptive Statistics about e[t]
# observations60
minimum-3.51826214156507
Q1-0.906472562707747
median0.224635442856117
mean-2.02167565096130e-17
Q30.856737858434935
maximum3.50219224063057

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -3.51826214156507 \tabularnewline
Q1 & -0.906472562707747 \tabularnewline
median & 0.224635442856117 \tabularnewline
mean & -2.02167565096130e-17 \tabularnewline
Q3 & 0.856737858434935 \tabularnewline
maximum & 3.50219224063057 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55047&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]-3.51826214156507[/C][/ROW]
[ROW][C]Q1[/C][C]-0.906472562707747[/C][/ROW]
[ROW][C]median[/C][C]0.224635442856117[/C][/ROW]
[ROW][C]mean[/C][C]-2.02167565096130e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.856737858434935[/C][/ROW]
[ROW][C]maximum[/C][C]3.50219224063057[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55047&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55047&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-3.51826214156507
Q1-0.906472562707747
median0.224635442856117
mean-2.02167565096130e-17
Q30.856737858434935
maximum3.50219224063057



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')