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Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_edauni.wasp
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationWed, 04 Nov 2009 09:38:24 -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/04/t12573527574o0lrukj1wwl01h.htm/, Retrieved Mon, 29 Apr 2024 14:58:34 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53704, Retrieved Mon, 29 Apr 2024 14:58:34 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact171
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Trivariate Scatterplots] [] [2009-11-03 19:22:33] [134dc66689e3d457a82860db6471d419]
- RMPD  [Univariate Explorative Data Analysis] [] [2009-11-03 20:12:41] [134dc66689e3d457a82860db6471d419]
-    D      [Univariate Explorative Data Analysis] [ws5 univariate et'] [2009-11-04 16:38:24] [95523ebdb89b97dbf680ec91e0b4bca2] [Current]
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Dataseries X:
-0.498266979
-0.552520681
-0.594845723
-0.630273959
-0.688175462
-0.703212376
-0.710889178
-0.676844995
-0.69798699
-0.735743484
-0.791733117
-0.80337441
-0.814112549
-0.85438497
-0.930730738
-0.78210675
-0.867747957
-0.929267937
-0.66610184
-0.6107104
-0.47527261
-0.302386644
-0.396607807
-0.209846123
-0.308618239
-0.094527375
-0.147977623
0.012281793
-0.022161185
0.063263031
0.17586059
0.113877304
0.158190456
0.442533736
0.653848122
0.598738184
0.517372293
0.710934441
0.704190115
0.863819507
0.936253566
0.963571017
0.856119247
0.8892896
1.063287339
1.339963038
1.581500375
1.631167936
2.079530709
2.187070449
1.775989985
1.001018386
0.056392232
0.139036613
-0.474954221
-0.83496297
-0.821814468
-0.845994341
-0.976529299
-1.06441666




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=53704&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=53704&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53704&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







Descriptive Statistics
# observations60
minimum-1.06441666
Q1-0.7051315765
median-0.2561163835
mean6.66666760063111e-11
Q30.66643362025
maximum2.187070449

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & -1.06441666 \tabularnewline
Q1 & -0.7051315765 \tabularnewline
median & -0.2561163835 \tabularnewline
mean & 6.66666760063111e-11 \tabularnewline
Q3 & 0.66643362025 \tabularnewline
maximum & 2.187070449 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53704&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]-1.06441666[/C][/ROW]
[ROW][C]Q1[/C][C]-0.7051315765[/C][/ROW]
[ROW][C]median[/C][C]-0.2561163835[/C][/ROW]
[ROW][C]mean[/C][C]6.66666760063111e-11[/C][/ROW]
[ROW][C]Q3[/C][C]0.66643362025[/C][/ROW]
[ROW][C]maximum[/C][C]2.187070449[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53704&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53704&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics
# observations60
minimum-1.06441666
Q1-0.7051315765
median-0.2561163835
mean6.66666760063111e-11
Q30.66643362025
maximum2.187070449



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)
library(lattice)
bitmap(file='pic1.png')
plot(x,type='l',main='Run Sequence Plot',xlab='time or index',ylab='value')
grid()
dev.off()
bitmap(file='pic2.png')
hist(x)
grid()
dev.off()
bitmap(file='pic3.png')
if (par1 > 0)
{
densityplot(~x,col='black',main=paste('Density Plot bw = ',par1),bw=par1)
} else {
densityplot(~x,col='black',main='Density Plot')
}
dev.off()
bitmap(file='pic4.png')
qqnorm(x)
qqline(x)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot1.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main='Lag plot (k=1), lowess, and regression line')
lines(lowess(z))
abline(lm(z))
dev.off()
if (par2 > 1) {
bitmap(file='lagplotpar2.png')
dum <- cbind(lag(x,k=par2),x)
dum
dum1 <- dum[(par2+1):length(x),]
dum1
z <- as.data.frame(dum1)
z
mylagtitle <- 'Lag plot (k='
mylagtitle <- paste(mylagtitle,par2,sep='')
mylagtitle <- paste(mylagtitle,'), and lowess',sep='')
plot(z,main=mylagtitle)
lines(lowess(z))
dev.off()
}
bitmap(file='pic5.png')
acf(x,lag.max=par2,main='Autocorrelation Function')
grid()
dev.off()
}
summary(x)
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Descriptive Statistics',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'# observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'minimum',header=TRUE)
a<-table.element(a,min(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q1',header=TRUE)
a<-table.element(a,quantile(x,0.25))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'median',header=TRUE)
a<-table.element(a,median(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,mean(x))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Q3',header=TRUE)
a<-table.element(a,quantile(x,0.75))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'maximum',header=TRUE)
a<-table.element(a,max(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')