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Author's title

Author*Unverified author*
R Software Modulerwasp_edabi.wasp
Title produced by softwareBivariate Explorative Data Analysis
Date of computationMon, 09 Nov 2009 03:23:33 -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/09/t1257762324n25eoynwhfopp77.htm/, Retrieved Tue, 16 Apr 2024 11:49:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=54708, Retrieved Tue, 16 Apr 2024 11:49:18 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact164
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Bivariate Explorative Data Analysis] [WS5 Et en Et'] [2009-11-09 10:23:33] [5d37783481a916b2505b66314b556267] [Current]
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Dataseries X:
2.164990976
1.994990976
1.910193625
1.951494287
1.921494287
2.011899584
1.974500909
1.954500909
1.984500909
1.974500909
1.994500909
1.984500909
1.984500909
1.894500909
1.874500909
1.774500909
1.884500909
1.904500909
1.934500909
1.934500909
1.934500909
1.934500909
1.974500909
1.994500909
1.984500909
1.954500909
1.944500909
1.954500909
1.944500909
1.934500909
1.924500909
1.934500909
1.944500909
1.964500909
2.054500909
2.101038128
2.107997598
2.147997598
2.072794949
2.191494287
2.221494287
2.225852433
2.264990976
2.186308593
2.258487666
2.248065414
2.331984355
2.316342501
2.285481044
2.355481044
2.311579057
2.298977733
2.388977733
2.365075747
2.342474422
2.532474422
2.772474422
2.832474422
2.772474422
2.912474422
2.742474422
2.502474422
2.562474422
2.812474422
2.912474422
2.882474422
2.963792039
2.745971112
2.765971112
3.192491376
1.688555482
1.531984355
Dataseries Y:
3.967916254
3.967916254
3.968505941
3.968653363
3.968653363
3.969832737
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.97012758
3.969508409
3.969390472
3.969390472
3.968800785
3.968653363
3.968653363
3.968240582
3.967916254
3.967385536
3.967179145
3.966677911
3.966442036
3.966029256
3.965704928
3.965704928
3.965262662
3.964967819
3.964967819
3.964525554
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.96423071
3.963699992
3.963493601
3.963493601
3.22355257
2.964466585
2.966442036




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 seconds \tabularnewline
R Server & 'RServer@AstonUniversity' @ vre.aston.ac.uk \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54708&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]4 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=54708&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54708&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 time4 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c3.83133247762845
b0.0446625743387028

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & 3.83133247762845 \tabularnewline
b & 0.0446625743387028 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54708&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]3.83133247762845[/C][/ROW]
[ROW][C]b[/C][C]0.0446625743387028[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54708&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54708&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]
c3.83133247762845
b0.0446625743387028







Descriptive Statistics about e[t]
# observations72
minimum-0.942281127368302
Q10.0274063901978550
median0.0441237773681819
mean-1.14594146286315e-18
Q30.0515020602282728
maximum0.0595413236092394

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 72 \tabularnewline
minimum & -0.942281127368302 \tabularnewline
Q1 & 0.0274063901978550 \tabularnewline
median & 0.0441237773681819 \tabularnewline
mean & -1.14594146286315e-18 \tabularnewline
Q3 & 0.0515020602282728 \tabularnewline
maximum & 0.0595413236092394 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=54708&T=2

[TABLE]
[ROW][C]Descriptive Statistics about e[t][/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]-0.942281127368302[/C][/ROW]
[ROW][C]Q1[/C][C]0.0274063901978550[/C][/ROW]
[ROW][C]median[/C][C]0.0441237773681819[/C][/ROW]
[ROW][C]mean[/C][C]-1.14594146286315e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0515020602282728[/C][/ROW]
[ROW][C]maximum[/C][C]0.0595413236092394[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=54708&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=54708&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]
# observations72
minimum-0.942281127368302
Q10.0274063901978550
median0.0441237773681819
mean-1.14594146286315e-18
Q30.0515020602282728
maximum0.0595413236092394



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')