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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 computationThu, 29 Oct 2009 09:48:25 -0600
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/Oct/29/t1256831670j5wzsa7f0pnu1xe.htm/, Retrieved Sun, 28 Apr 2024 21:38:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=52012, Retrieved Sun, 28 Apr 2024 21:38:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Partial Correlation] [Workshop 5 correl...] [2009-10-29 15:05:45] [eaf42bcf5162b5692bb3c7f9d4636222]
- RMPD    [Bivariate Explorative Data Analysis] [workshop 5 bivari...] [2009-10-29 15:48:25] [78d370e6d5f4594e9982a5085e7604c6] [Current]
-  M D      [Bivariate Explorative Data Analysis] [WS5 bivariate EDA] [2009-11-02 20:57:59] [37a8d600db9abe09a2528d150ccff095]
-    D        [Bivariate Explorative Data Analysis] [WS5 E't(y) E't(x)] [2009-11-03 20:51:33] [37a8d600db9abe09a2528d150ccff095]
-  M D      [Bivariate Explorative Data Analysis] [WS5 bivariate EDA...] [2009-11-02 21:05:06] [37a8d600db9abe09a2528d150ccff095]
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Dataseries X:
2,86
2,55
2,27
2,26
2,57
3,07
2,76
2,51
2,87
3,14
3,11
3,16
2,47
2,57
2,89
2,63
2,38
1,69
1,96
2,19
1,87
1,6
1,63
1,22
1,21
1,49
1,64
1,66
1,77
1,82
1,78
1,28
1,29
1,37
1,12
1,51
2,24
2,94
3,09
3,46
3,64
4,39
4,15
5,21
5,8
5,91
5,39
5,46
4,72
3,14
2,63
2,32
1,93
0,62
0,6
-0,37
-1,1
-1,68
-0,78
-1,19
Dataseries Y:
8,9
8,6
8,3
8,3
8,3
8,4
8,5
8,4
8,6
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,5
8,6
8,4
8,1
8
8
8
8
7,9
7,8
7,8
7,9
8,1
8
7,6
7,3
7
6,8
7
7,1
7,2
7,1
6,9
6,7
6,7
6,6
6,9
7,3
7,5
7,3
7,1
6,9
7,1
7,5
7,7
7,8
7,8
7,7
7,7
7,8
7,9




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=52012&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=52012&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52012&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]
c8.11484176961421
b-0.118901912011341

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 8.11484176961421 \tabularnewline
b & -0.118901912011341 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52012&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]8.11484176961421[/C][/ROW]
[ROW][C]b[/C][C]-0.118901912011341[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52012&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52012&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]
c8.11484176961421
b-0.118901912011341







Descriptive Statistics about e[t]
# observations60
minimum-1.04850148670881
Q1-0.520507070427064
median0.0129165888427412
mean-6.7450024153944e-17
Q30.625042837868667
maximum1.12521769873817

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.04850148670881 \tabularnewline
Q1 & -0.520507070427064 \tabularnewline
median & 0.0129165888427412 \tabularnewline
mean & -6.7450024153944e-17 \tabularnewline
Q3 & 0.625042837868667 \tabularnewline
maximum & 1.12521769873817 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=52012&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]-1.04850148670881[/C][/ROW]
[ROW][C]Q1[/C][C]-0.520507070427064[/C][/ROW]
[ROW][C]median[/C][C]0.0129165888427412[/C][/ROW]
[ROW][C]mean[/C][C]-6.7450024153944e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.625042837868667[/C][/ROW]
[ROW][C]maximum[/C][C]1.12521769873817[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=52012&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=52012&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]
# observations60
minimum-1.04850148670881
Q1-0.520507070427064
median0.0129165888427412
mean-6.7450024153944e-17
Q30.625042837868667
maximum1.12521769873817



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')