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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 10:34:48 -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/t125804744277jf90attyhuhzv.htm/, Retrieved Fri, 03 May 2024 20:49:42 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=56289, Retrieved Fri, 03 May 2024 20:49:42 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

ws6bivariateeda2

Estimated Impact

140

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

-     [Box-Cox Normality Plot] [3/11/2009] [2009-11-02 22:22:24] [b98453cac15ba1066b407e146608df68]
- RMPD    [Bivariate Explorative Data Analysis] [] [2009-11-12 17:34:48] [2b548c9d2e9bba6e1eaf65bd4d551f41] [Current]

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Dataseries X:

Download CSV

Histogram

Boxplots

4,00
3,80
4,70
4,30
3,90
4,00
4,30
4,80
4,40
4,30
4,70
4,70
4,90
5,00
4,20
4,30
4,80
4,80
4,80
4,20
4,60
4,80
4,50
4,40
4,30
3,90
3,70
4,00
4,10
3,70
3,80
3,80
3,80
3,30
3,30
3,30
3,20
3,40
4,20
4,90
5,10
5,50
5,60
6,40
6,10
7,10
7,80
7,90
7,40
7,50
6,80
5,20
4,70
4,10
3,90
2,60
2,70
1,80
1,00
0,30

Dataseries Y:

Download CSV

Histogram

8.00
8.10
7.70
7.50
7.60
7.80
7.80
7.80
7.50
7.50
7.10
7.50
7.50
7.60
7.70
7.70
7.90
8.10
8.20
8.20
8.20
7.90
7.30
6.90
6.60
6.70
6.90
7.00
7.10
7.20
7.10
6.90
7.00
6.80
6.40
6.70
6.60
6.40
6.30
6.20
6.50
6.80
6.80
6.40
6.10
5.80
6.10
7.20
7.30
6.90
6.10
5.80
6.20
7.10
7.70
7.90
7.70
7.40
7.50
8.00

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	4 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=56289&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=56289&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56289&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	4 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24

Model: Y[t] = c + b X[t] + e[t]
c	7.89922550985638
b	-0.16325179727518

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 7.89922550985638 \tabularnewline
b & -0.16325179727518 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56289&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]7.89922550985638[/C][/ROW]
[ROW][C]b[/C][C]-0.16325179727518[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56289&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56289&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	7.89922550985638
b	-0.16325179727518

Descriptive Statistics about e[t]
# observations	60
minimum	-1.25031616402545
Q1	-0.534519763044559
median	-0.0635679613006293
mean	-2.7935598351352e-17
Q3	0.506326282950045
maximum	1.08438311706448

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.25031616402545 \tabularnewline
Q1 & -0.534519763044559 \tabularnewline
median & -0.0635679613006293 \tabularnewline
mean & -2.7935598351352e-17 \tabularnewline
Q3 & 0.506326282950045 \tabularnewline
maximum & 1.08438311706448 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=56289&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]-1.25031616402545[/C][/ROW]
[ROW][C]Q1[/C][C]-0.534519763044559[/C][/ROW]
[ROW][C]median[/C][C]-0.0635679613006293[/C][/ROW]
[ROW][C]mean[/C][C]-2.7935598351352e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.506326282950045[/C][/ROW]
[ROW][C]maximum[/C][C]1.08438311706448[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=56289&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=56289&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	60
minimum	-1.25031616402545
Q1	-0.534519763044559
median	-0.0635679613006293
mean	-2.7935598351352e-17
Q3	0.506326282950045
maximum	1.08438311706448

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 = 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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code