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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 05:37:24 -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/t1256903727le68ywdlkrx48b1.htm/, Retrieved Mon, 29 Apr 2024 05:01:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52080, Retrieved Mon, 29 Apr 2024 05:01:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact107
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [workshop 4,2,1] [2009-10-30 11:37:24] [2210215221105fab636491031ce54076] [Current]
-    D    [Bivariate Explorative Data Analysis] [workshop 4,2,3] [2009-10-30 13:22:16] [35f0fff14d789f48983afb62e692bd0d]
- RMPD    [Trivariate Scatterplots] [workshop 5,1] [2009-10-30 14:16:01] [35f0fff14d789f48983afb62e692bd0d]
- RMPD    [Partial Correlation] [workshop 5,2] [2009-10-30 14:17:43] [35f0fff14d789f48983afb62e692bd0d]
- RMPD      [Bivariate Explorative Data Analysis] [workshop 5,3] [2009-11-04 20:21:14] [35f0fff14d789f48983afb62e692bd0d]
- RMPD      [Bivariate Explorative Data Analysis] [workshop 5,4] [2009-11-04 20:30:38] [35f0fff14d789f48983afb62e692bd0d]
- RMPD      [Bivariate Explorative Data Analysis] [workshop 5,5] [2009-11-04 20:39:02] [35f0fff14d789f48983afb62e692bd0d]
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Dataseries X:
8,1
8
7,5
7,4
7,7
7,9
7,7
7,1
6,2
5,8
6,1
6,9
7,3
7,2
6,1
5,8
6,1
6,3
6,8
6,8
6,5
6,2
6,3
6,4
6,6
7,6
6,4
6,8
7
6,9
7,1
7,2
7,1
7
6,9
6,7
6,6
6,9
7,3
7,9
8,2
8,2
8,2
8,1
7,9
7,7
7,7
7,6
7,5
7,5
7,1
7,5
7,5
7,8
7,8
7,8
7,6
7,5
7,7
8,1
8
Dataseries Y:
11,1
10,9
10
9,2
9,2
9,5
9,6
9,5
9,1
8,9
9
10,1
10,3
10,2
9,6
9,2
9,3
9,4
9,4
9,2
9
9
9
9,8
10
9,8
9,3
9
9
9,1
9,1
9,1
9,2
8,8
8,3
8,4
8,1
7,7
7,9
7,9
8
7,9
7,6
7,1
6,8
6,5
6,9
8,2
8,7
8,3
7,9
7,5
7,8
8,3
8,4
8,2
7,7
7,2
7,3
8,1
8,5




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=52080&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=52080&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52080&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]
c12.2631537861046
b-0.489417989417989

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 12.2631537861046 \tabularnewline
b & -0.489417989417989 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52080&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]12.2631537861046[/C][/ROW]
[ROW][C]b[/C][C]-0.489417989417989[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52080&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52080&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]
c12.2631537861046
b-0.489417989417989







Descriptive Statistics about e[t]
# observations61
minimum-1.99463526758609
Q1-0.584053257004076
median-0.0819368548876744
mean4.01288107365434e-17
Q30.411713938763118
maximum2.80113192818111

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 61 \tabularnewline
minimum & -1.99463526758609 \tabularnewline
Q1 & -0.584053257004076 \tabularnewline
median & -0.0819368548876744 \tabularnewline
mean & 4.01288107365434e-17 \tabularnewline
Q3 & 0.411713938763118 \tabularnewline
maximum & 2.80113192818111 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52080&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]-1.99463526758609[/C][/ROW]
[ROW][C]Q1[/C][C]-0.584053257004076[/C][/ROW]
[ROW][C]median[/C][C]-0.0819368548876744[/C][/ROW]
[ROW][C]mean[/C][C]4.01288107365434e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.411713938763118[/C][/ROW]
[ROW][C]maximum[/C][C]2.80113192818111[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52080&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52080&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-1.99463526758609
Q1-0.584053257004076
median-0.0819368548876744
mean4.01288107365434e-17
Q30.411713938763118
maximum2.80113192818111



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')