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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 04:26:21 -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/t1256812049p5ikhnnl4foj03w.htm/, Retrieved Sun, 28 Apr 2024 22:25:28 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51915, Retrieved Sun, 28 Apr 2024 22:25:28 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact170
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]
- RMPD  [Bivariate Explorative Data Analysis] [WS3Part1-EDA] [2009-10-27 11:32:51] [90f6d58d515a4caed6fb4b8be4e11eaa]
-    D    [Bivariate Explorative Data Analysis] [] [2009-10-27 19:38:29] [90f6d58d515a4caed6fb4b8be4e11eaa]
-    D      [Bivariate Explorative Data Analysis] [] [2009-10-28 14:45:34] [90f6d58d515a4caed6fb4b8be4e11eaa]
-    D          [Bivariate Explorative Data Analysis] [WS4.2.2] [2009-10-29 10:26:21] [d17577076e7e93abbeb88e2adc301f5b] [Current]
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Dataseries X:
2.2300144
2.163323026
2.104134154
2.116255515
2.140066163
2.151762203
2.140066163
2.104134154
2.091864062
2.066862759
2.151762203
2.163323026
2.163323026
2.140066163
2.128231706
2.140066163
2.163323026
2.163323026
2.151762203
2.140066163
2.116255515
2.079441542
2.104134154
2.091864062
2.091864062
2.079441542
2.066862759
2.066862759
2.079441542
2.079441542
2.066862759
2.079441542
2.041220329
1.974081026
2.014903021
1.987874348
1.945910149
1.945910149
1.945910149
1.974081026
1.987874348
1.960094784
1.916922612
1.85629799
1.808288771
1.871802177
2.041220329
2.066862759
2.014903021
1.931521412
1.887069649
1.931521412
2.041220329
2.079441542
2.079441542
2.041220329
1.987874348
2.00148
2.091864062
2.116255515
Dataseries Y:
4
3.8
4.7
4.3
3.9
4
4.3
4.8
4.4
4.3
4.7
4.7
4.9
5
4.2
4.3
4.8
4.8
4.8
4.2
4.6
4.8
4.5
4.4
4.3
3.9
3.7
4
4.1
3.7
3.8
3.8
3.8
3.3
3.3
3.3
3.2
3.4
4.2
4.9
5.1
5.5
5.6
6.4
6.1
7.1
7.8
7.9
7.4
7.5
6.8
5.2
4.7
4.1
3.9
2.6
2.7
1.8
1
0.3




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=51915&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=51915&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51915&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]
c14.4521309378648
b-4.86165796676387

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 14.4521309378648 \tabularnewline
b & -4.86165796676387 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51915&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]14.4521309378648[/C][/ROW]
[ROW][C]b[/C][C]-4.86165796676387[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51915&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51915&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]
c14.4521309378648
b-4.86165796676387







Descriptive Statistics about e[t]
# observations60
minimum-3.86362045365703
Q1-0.557885833926745
median0.127088095443773
mean1.15142270717961e-17
Q30.577247022053188
maximum3.49624886063515

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -3.86362045365703 \tabularnewline
Q1 & -0.557885833926745 \tabularnewline
median & 0.127088095443773 \tabularnewline
mean & 1.15142270717961e-17 \tabularnewline
Q3 & 0.577247022053188 \tabularnewline
maximum & 3.49624886063515 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51915&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]-3.86362045365703[/C][/ROW]
[ROW][C]Q1[/C][C]-0.557885833926745[/C][/ROW]
[ROW][C]median[/C][C]0.127088095443773[/C][/ROW]
[ROW][C]mean[/C][C]1.15142270717961e-17[/C][/ROW]
[ROW][C]Q3[/C][C]0.577247022053188[/C][/ROW]
[ROW][C]maximum[/C][C]3.49624886063515[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51915&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51915&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-3.86362045365703
Q1-0.557885833926745
median0.127088095443773
mean1.15142270717961e-17
Q30.577247022053188
maximum3.49624886063515



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')