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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 computationWed, 28 Oct 2009 15:52:50 -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/28/t12567668168eyuh303e4jtg0r.htm/, Retrieved Mon, 06 May 2024 02:57:53 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=51870, Retrieved Mon, 06 May 2024 02:57:53 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact99
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Explorative Data Analysis] [] [2009-10-28 21:40:42] [9f35ad889e41dd0c9322ca60d75b9f47]
-    D    [Bivariate Explorative Data Analysis] [] [2009-10-28 21:52:50] [48076ccf082563ab8a2c81e57fdb5364] [Current]
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Dataseries X:
9.280220849
9.542438772
9.54536871
9.532959959
9.470694926
9.434267616
9.467622514
9.609673384
9.530400086
9.473673398
9.550370557
9.377252139
9.358173998
9.579570173
9.518993506
9.59790624
9.538254665
9.51247993
9.516647909
9.690925321
9.492552512
9.598449058
9.647723956
9.484519184
9.443133219
9.617909931
9.64551961
9.643939319
9.480817789
9.596744977
9.5595878
9.692902314
9.574455568
9.625135156
9.677847137
9.571595809
9.490257374
9.629188855
9.744257327
9.685188498
9.499136823
9.705182945
9.714691079
9.715892113
9.773447202
9.688411372
9.824677002
9.705195138
9.549117094
9.747365765
9.75017319
9.538189825
9.422414887
9.448057215
9.442150262
9.516625824
9.460811111
9.421176497
9.544452683
9.481458517
Dataseries Y:
9.250992752
9.431626199
9.424209044
9.414643553
9.466524037
9.349867504
9.404425796
9.54103883
9.445949899
9.395499566
9.487949381
9.294800999
9.332664194
9.521047814
9.434842999
9.545461697
9.56631407
9.505618521
9.515299827
9.693772188
9.470394277
9.552503527
9.563459
9.410288989
9.439943018
9.556083784
9.561757518
9.573489314
9.483629359
9.526223529
9.519434071
9.640810239
9.495992886
9.574372188
9.609780701
9.54862525
9.468943727
9.57110793
9.686164529
9.643005516
9.595990453
9.678642555
9.695318817
9.718747073
9.748948464
9.656493066
9.79834368
9.688814277
9.576627966
9.728503014
9.72807408
9.556324371
9.442007494
9.393036858
9.407172802
9.4931104
9.417297629
9.375905657
9.537721409
9.414879937




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=51870&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=51870&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51870&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 time5 seconds
R Server'RServer@AstonUniversity' @ vre.aston.ac.uk







Model: Y[t] = c + b X[t] + e[t]
c-0.0406119385089266
b1.00005050356125

\begin{tabular}{lllllllll}
\hline
Model: Y[t] = c + b X[t] + e[t] \tabularnewline
c & -0.0406119385089266 \tabularnewline
b & 1.00005050356125 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51870&T=1

[TABLE]
[ROW][C]Model: Y[t] = c + b X[t] + e[t][/C][/ROW]
[ROW][C]c[/C][C]-0.0406119385089266[/C][/ROW]
[ROW][C]b[/C][C]1.00005050356125[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51870&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51870&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-0.0406119385089266
b1.00005050356125







Descriptive Statistics about e[t]
# observations60
minimum-0.0810298026044202
Q1-0.0280844319824455
median-0.00271976407309312
mean-4.68155109947452e-19
Q30.0208760152159448
maximum0.136985828270517

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics about e[t] \tabularnewline
# observations & 60 \tabularnewline
minimum & -0.0810298026044202 \tabularnewline
Q1 & -0.0280844319824455 \tabularnewline
median & -0.00271976407309312 \tabularnewline
mean & -4.68155109947452e-19 \tabularnewline
Q3 & 0.0208760152159448 \tabularnewline
maximum & 0.136985828270517 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=51870&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]-0.0810298026044202[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0280844319824455[/C][/ROW]
[ROW][C]median[/C][C]-0.00271976407309312[/C][/ROW]
[ROW][C]mean[/C][C]-4.68155109947452e-19[/C][/ROW]
[ROW][C]Q3[/C][C]0.0208760152159448[/C][/ROW]
[ROW][C]maximum[/C][C]0.136985828270517[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=51870&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=51870&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-0.0810298026044202
Q1-0.0280844319824455
median-0.00271976407309312
mean-4.68155109947452e-19
Q30.0208760152159448
maximum0.136985828270517



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')