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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

Mon, 09 Nov 2009 14:12:34 -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/09/t1257801232ulcswssnsq6l418.htm/, Retrieved Sat, 20 Apr 2024 08:32:24 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=55057, Retrieved Sat, 20 Apr 2024 08:32:24 +0000

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Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

WS5 bivariate EDA van Yt

Estimated Impact

210

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 parti�le corr...] [2009-11-09 19:36:40] [c620fe7250af73a91c51407172a85dab]
- RMPD      [Bivariate Explorative Data Analysis] [WS5 bivariate EDA...] [2009-11-09 21:12:34] [b4ff140915b3f24d4faed3d78f95eba4] [Current]

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Dataseries X:

Download CSV

Histogram

Boxplots

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

Dataseries Y:

Download CSV

Histogram

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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	8 seconds
R Server	'George Udny Yule' @ 72.249.76.132

\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 & 8 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55057&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]8 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55057&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55057&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	8 seconds
R Server	'George Udny Yule' @ 72.249.76.132

Model: Y[t] = c + b X[t] + e[t]
c	6.33304042675829
b	-0.218990517738272

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 6.33304042675829 \tabularnewline
b & -0.218990517738272 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55057&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]6.33304042675829[/C][/ROW]
[ROW][C]b[/C][C]-0.218990517738272[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55057&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55057&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	6.33304042675829
b	-0.218990517738272

Descriptive Statistics about e[t]
# observations	60
minimum	-4.25921723307829
Q1	-0.623802426509646
median	0.0506628541720822
mean	4.65556412865276e-17
Q3	0.641894728811836
maximum	3.36268181869554

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -4.25921723307829 \tabularnewline
Q1 & -0.623802426509646 \tabularnewline
median & 0.0506628541720822 \tabularnewline
mean & 4.65556412865276e-17 \tabularnewline
Q3 & 0.641894728811836 \tabularnewline
maximum & 3.36268181869554 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=55057&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]-4.25921723307829[/C][/ROW]
[ROW][C]Q1[/C][C]-0.623802426509646[/C][/ROW]
[ROW][C]median[/C][C]0.0506628541720822[/C][/ROW]
[ROW][C]mean[/C][C]4.65556412865276e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.641894728811836[/C][/ROW]
[ROW][C]maximum[/C][C]3.36268181869554[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=55057&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=55057&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	-4.25921723307829
Q1	-0.623802426509646
median	0.0506628541720822
mean	4.65556412865276e-17
Q3	0.641894728811836
maximum	3.36268181869554

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