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Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_edabi.wasp

Title produced by software

Bivariate Explorative Data Analysis

Date of computation

Thu, 12 Nov 2009 07:25:08 -0700

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2009/Nov/12/t12580359875oikd4gwo29frv4.htm/, Retrieved Fri, 03 May 2024 20:35:52 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56027, Retrieved Fri, 03 May 2024 20:35:52 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

126

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)

-     [Bivariate Explorative Data Analysis] [3/11/2009] [2009-11-02 22:01:32] [b98453cac15ba1066b407e146608df68]
-   PD  [Bivariate Explorative Data Analysis] [regression model] [2009-11-12 14:22:18] [976efdaed7598845c859b86bc2e467ce]
-    D      [Bivariate Explorative Data Analysis] [regression model ...] [2009-11-12 14:25:08] [d45d8d97b86162be82506c3c0ea6e4a6] [Current]

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Dataseries X:

Download CSV

Histogram

Boxplots

1
-0.8
-2.9
-0.7
-0.7
1.5
3
3.2
3.1
3.9
1
1.3
0.8
1.2
2.9
3.9
4.5
4.5
3.3
2
1.5
1
2.1
3
4
5.1
4.5
4.2
3.3
2.7
1.8
1.4
0.5
-0.4
0.8
0.7
1.9
2
1.1
0.9
0.4
0.7
2.1
2.8
3.9
3.5
2
2
1.5
2.5
3.1
2.7
2.8
2.5
3
3.2
2.8
2.4
2
1.8
1.1
-1.5
-3.7
-4.2
-3.5

Dataseries Y:

Download CSV

Histogram

1.6
1.7
1.6
1.4
2.1
1.9
1.7
1.8
2
2.5
2.1
2.1
2.3
2.4
2.4
2.3
1.7
2
2.3
2
2
1.3
1.7
1.9
1.7
1.6
1.7
1.8
1.9
1.9
1.9
2
2.1
1.9
1.9
1.3
1.3
1.4
1.2
1.3
1.8
2.2
2.6
2.8
3.1
3.9
3.7
4.6
5.1
5.2
4.9
5.1
4.8
3.9
3.5
3.3
2.8
1.6
1.5
0.7
-0.1
-0.7
-0.2
-0.6
-0.6

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 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 & 5 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56027&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]5 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=56027&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56027&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	5 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk

Model: Y[t] = c + b X[t] + e[t]
c	1.56991911398706
b	0.320660154305625

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 1.56991911398706 \tabularnewline
b & 0.320660154305625 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56027&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]1.56991911398706[/C][/ROW]
[ROW][C]b[/C][C]0.320660154305625[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56027&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56027&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]
c	1.56991911398706
b	0.320660154305625

Descriptive Statistics about e[t]
# observations	65
minimum	-2.02264528372325
Q1	-0.72809762319562
median	-0.211239422598308
mean	1.33923988352094e-17
Q3	0.405618777999005
maximum	3.04909065455450

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 65 \tabularnewline
minimum & -2.02264528372325 \tabularnewline
Q1 & -0.72809762319562 \tabularnewline
median & -0.211239422598308 \tabularnewline
mean & 1.33923988352094e-17 \tabularnewline
Q3 & 0.405618777999005 \tabularnewline
maximum & 3.04909065455450 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56027&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]65[/C][/ROW]
[ROW][C]minimum[/C][C]-2.02264528372325[/C][/ROW]
[ROW][C]Q1[/C][C]-0.72809762319562[/C][/ROW]
[ROW][C]median[/C][C]-0.211239422598308[/C][/ROW]
[ROW][C]mean[/C][C]1.33923988352094e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.405618777999005[/C][/ROW]
[ROW][C]maximum[/C][C]3.04909065455450[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56027&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56027&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]
# observations	65
minimum	-2.02264528372325
Q1	-0.72809762319562
median	-0.211239422598308
mean	1.33923988352094e-17
Q3	0.405618777999005
maximum	3.04909065455450

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

Figure 7

PNG link

Postscript link

PDF link

Figure 8

PNG link

Postscript link

PDF link

Parameters (Session):

par1 = 50 ; par2 = 50 ; par3 = 0 ; par4 = 0 ; par5 = 0 ; par6 = Y ; par7 = Y ;

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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code