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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 computationThu, 29 Oct 2009 02:14:45 -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/29/t12568041669cbd5c6cnlsit4u.htm/, Retrieved Mon, 29 Apr 2024 02:11:39 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51911, Retrieved Mon, 29 Apr 2024 02:11:39 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS4 Deel II Bivar...] [2009-10-29 08:14:45] [762da55b2e2304daaed24a7cc507d14d] [Current]
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Dataseries X:
1,92
2,06
2,05
2,02
2,04
2,00
2,03
2,11
2,05
2,01
2,11
1,94
1,94
2,07
2,01
2,04
2,05
2,01
2,05
2,13
2,02
2,11
2,14
1,96
1,96
2,09
2,09
2,09
2,08
2,07
2,08
2,15
2,09
2,11
2,18
2,04
2,00
2,12
2,13
2,11
2,11
2,08
2,13
2,16
2,17
2,13
2,19
2,09
2,02
2,15
2,14
2,05
2,07
1,97
2,01
2,05
2,00
1,94
2,06
1,90
Dataseries Y:
 
2.04	   
2.11	   
2.08	   
2.08	   
2.11	   
2.04	   
2.02	   
2.08	   
2.05	   
2.04	   
2.08	   
1.99	   
2.03	   
2.10	   
2.07	   
2.08	   
2.07	   
2.05	   
2.05	   
2.12	   
2.04	   
2.07	   
2.09	   
2.01	   
2.05	   
2.11	   
2.11	   
2.10	   
2.08	   
2.06	   
2.06	   
2.11	   
2.05	   
2.07	   
2.10	   
2.05	   
2.06	   
2.08	   
2.12	   
2.10	   
2.08	   
2.07	   
2.07	   
2.08	   
2.11	   
2.05	   
2.10	   
2.06	   
2.02	   
2.12	   
2.11	   
2.05	   
2.10	   
2.03	   
2.03	   
2.08	   
2.04	   
2.03	   
2.07	   
2.02	




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51911&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51911&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51911&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Model: Y[t] = c + b X[t] + e[t]
c1.35617548041480
b0.345726642748317

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.35617548041480 \tabularnewline
b & 0.345726642748317 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51911&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.35617548041480[/C][/ROW]
[ROW][C]b[/C][C]0.345726642748317[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51911&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51911&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]
c1.35617548041480
b0.345726642748317







Descriptive Statistics about e[t]
# observations60
minimum-0.0425732294687179
Q1-0.0149150980488525
median-0.00547279697252669
mean-8.39974339360515e-20
Q30.0153637514129848
maximum0.0485421683786307

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.0425732294687179 \tabularnewline
Q1 & -0.0149150980488525 \tabularnewline
median & -0.00547279697252669 \tabularnewline
mean & -8.39974339360515e-20 \tabularnewline
Q3 & 0.0153637514129848 \tabularnewline
maximum & 0.0485421683786307 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51911&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]-0.0425732294687179[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0149150980488525[/C][/ROW]
[ROW][C]median[/C][C]-0.00547279697252669[/C][/ROW]
[ROW][C]mean[/C][C]-8.39974339360515e-20[/C][/ROW]
[ROW][C]Q3[/C][C]0.0153637514129848[/C][/ROW]
[ROW][C]maximum[/C][C]0.0485421683786307[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51911&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51911&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-0.0425732294687179
Q1-0.0149150980488525
median-0.00547279697252669
mean-8.39974339360515e-20
Q30.0153637514129848
maximum0.0485421683786307



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')