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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 computationMon, 02 Nov 2009 08:34:41 -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/02/t1257176118wvhopvzozqbut6k.htm/, Retrieved Fri, 03 May 2024 17:09:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52719, Retrieved Fri, 03 May 2024 17:09:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
-   PD  [Bivariate Data Series] [] [2009-10-25 17:21:06] [badc6a9acdc45286bea7f74742e15a21]
- RMPD    [Bivariate Explorative Data Analysis] [] [2009-10-25 17:24:36] [badc6a9acdc45286bea7f74742e15a21]
-  M D        [Bivariate Explorative Data Analysis] [] [2009-11-02 15:34:41] [0545e25c765ce26b196961216dc11e13] [Current]
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Dataseries X:
-0,73
-0,78
-0,83
-0,94
-0,95
-0,94
-0,97
-1,15
-1,13
-1,06
-1,02
-0,97
-1,03
-0,89
-0,66
-0,56
-0,56
-0,76
-0,64
-0,58
-0,47
-0,55
-0,72
-0,58
-0,74
-0,75
-0,75
-0,60
-0,77
-0,42
-0,45
-0,10
-0,05
0,02
0,19
0,39
0,59
0,57
0,64
0,75
0,84
1,00
1,06
0,97
1,07
1,15
1,20
1,18
1,20
1,06
1,16
1,05
1,22
1,12
1,45
1,55
1,45
1,35
1,04
0,61
0,52
0,38
0,15
-0,15
-0,40
-0,44
-0,58
-0,61
-0,64
Dataseries Y:
-0,93
-1,19
-1,46
-0,91
-0,23
-0,61
-0,55
-0,91
-1,08
-0,07
-0,42
-0,76
-0,74
-0,24
0,58
0,31
0,21
0,34
0,51
0,79
1,04
0,13
0,00
0,39
0,12
0,10
-0,77
-0,23
-0,27
-0,27
-0,57
-0,44
-0,86
-1,21
-0,78
-0,60
-0,86
-0,80
-0,91
-0,90
-1,26
-1,25
-1,31
-1,54
-1,20
-0,29
0,48
0,66
1,08
0,98
1,93
1,47
2,71
3,27
3,57
3,13
3,08
2,63
1,37
1,19
1,08
1,12
-0,02
0,15
-0,79
-1,53
-2,43
-1,47
-1,80




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52719&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52719&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52719&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Model: Y[t] = c + b X[t] + e[t]
c-0.000691620643412288
b0.772182439544911

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.000691620643412288 \tabularnewline
b & 0.772182439544911 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52719&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.000691620643412288[/C][/ROW]
[ROW][C]b[/C][C]0.772182439544911[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52719&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52719&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-0.000691620643412288
b0.772182439544911







Descriptive Statistics about e[t]
# observations69
minimum-2.28832534571515
Q1-0.820699257379342
median0.116543113815628
mean-1.5408241309265e-17
Q30.692106625906646
maximum2.45102708330329

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 69 \tabularnewline
minimum & -2.28832534571515 \tabularnewline
Q1 & -0.820699257379342 \tabularnewline
median & 0.116543113815628 \tabularnewline
mean & -1.5408241309265e-17 \tabularnewline
Q3 & 0.692106625906646 \tabularnewline
maximum & 2.45102708330329 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52719&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]-2.28832534571515[/C][/ROW]
[ROW][C]Q1[/C][C]-0.820699257379342[/C][/ROW]
[ROW][C]median[/C][C]0.116543113815628[/C][/ROW]
[ROW][C]mean[/C][C]-1.5408241309265e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.692106625906646[/C][/ROW]
[ROW][C]maximum[/C][C]2.45102708330329[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52719&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52719&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]
# observations69
minimum-2.28832534571515
Q1-0.820699257379342
median0.116543113815628
mean-1.5408241309265e-17
Q30.692106625906646
maximum2.45102708330329



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')