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Description of Statistical Computation

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 computationWed, 04 Nov 2009 11:27:40 -0700
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/Nov/04/t1257359332mtaluw6d7y893l6.htm/, Retrieved Mon, 29 Apr 2024 15:32:44 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53783, Retrieved Mon, 29 Apr 2024 15:32:44 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsWS5BEXZMLDG
Estimated Impact114

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [WS 5: partial cor...] [2009-11-03 20:50:00] [7c2a5b25a196bd646844b8f5223c9b3e]
- RMPD    [Bivariate Explorative Data Analysis] [WS 5: Bivariate E...] [2009-11-04 18:27:40] [3d2053c5f7c50d3c075d87ce0bd87294] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
26.90
27.80
28.70
30.50
31.80
31.40
34.80
32.20
33.00
32.40
30.50
28.60
30.00
28.20
27.60
24.90
23.80
24.30
23.60
24.20
28.10
30.10
31.10
32.00
32.40
34.00
35.10
37.10
37.30
38.10
39.50
38.30
37.30
38.70
37.50
38.70
37.90
36.60
35.50
37.60
38.60
40.30
39.00
36.80
36.50
34.10
34.20
31.90
33.70
33.50
33.80
29.90
32.30
30.50
28.50
29.00
23.80
17.90
9.90
3.00
4.20
0.40
0.00
2.40
4.20
8.20
9.00
13.60
14.00
Dataseries Y:
Download CSV
Histogram 
21.4
26.4
26.4
29.4
34.4
24.4
26.4
25.4
31.4
27.4
27.4
29.4
32.4
26.4
22.4
19.4
21.4
23.4
23.4
25.4
28.4
27.4
21.4
17.4
24.4
26.4
22.4
14.4
18.4
25.4
29.4
26.4
26.4
20.4
26.4
29.4
33.4
32.4
35.4
34.4
36.4
32.4
34.4
31.4
27.4
27.4
30.4
32.4
32.4
27.4
31.4
29.4
27.4
25.4
26.4
23.4
18.4
22.4
17.4
17.4
11.4
9.4
6.4
0
7.8
7.9
12
16.9
12.3

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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=53783&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=53783&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53783&T=0

As an alternative you can also use a QR Code:  
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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk






Model: Y[t] = c + b X[t] + e[t]
c8.17017481280851
b0.574541769904813

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 8.17017481280851 \tabularnewline
b & 0.574541769904813 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53783&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]8.17017481280851[/C][/ROW]
[ROW][C]b[/C][C]0.574541769904813[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53783&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53783&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Model: Y[t] = c + b X[t] + e[t]
c8.17017481280851
b0.574541769904813






Descriptive Statistics about e[t]
# observations69
minimum-15.0856744762771
Q1-2.22534842324795
median0.672126019266042
mean-1.27360757809623e-16
Q33.45469210779909
maximum7.95939690421845

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -15.0856744762771 \tabularnewline
Q1 & -2.22534842324795 \tabularnewline
median & 0.672126019266042 \tabularnewline
mean & -1.27360757809623e-16 \tabularnewline
Q3 & 3.45469210779909 \tabularnewline
maximum & 7.95939690421845 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53783&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]69[/C][/ROW]
[ROW][C]minimum[/C][C]-15.0856744762771[/C][/ROW]
[ROW][C]Q1[/C][C]-2.22534842324795[/C][/ROW]
[ROW][C]median[/C][C]0.672126019266042[/C][/ROW]
[ROW][C]mean[/C][C]-1.27360757809623e-16[/C][/ROW]
[ROW][C]Q3[/C][C]3.45469210779909[/C][/ROW]
[ROW][C]maximum[/C][C]7.95939690421845[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53783&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53783&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics about e[t]
# observations69
minimum-15.0856744762771
Q1-2.22534842324795
median0.672126019266042
mean-1.27360757809623e-16
Q33.45469210779909
maximum7.95939690421845


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 12 ;
Parameters (R input):
par1 = 0 ; par2 = 12 ;
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')