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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 computationTue, 20 Oct 2009 13:14:26 -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/20/t12560661577z5agzgw0hrqzim.htm/, Retrieved Fri, 03 May 2024 03:42:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49032, Retrieved Fri, 03 May 2024 03:42:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsworkshop 3 deel 2.1 eda
Estimated Impact117
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]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMP       [Histogram] [workshop 3 deel 1...] [2009-10-19 19:20:29] [309ee52d0058ff0a6f7eec15e07b2d9f]
- RMPD          [Univariate Explorative Data Analysis] [workshop 3 deel 2...] [2009-10-20 19:14:26] [6198946fb53eb5eb18db46bb758f7fde] [Current]
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Dataseries X:
-0.034795
-0.035595
-0.040445
-0.047915
-0.536795
-0.060695
-0.061025
-0.042875
-0.046685
-0.045665
-0.051215
-0.049475
-0.053005
-0.057995
-0.053865
-0.055525
-0.041365
-0.025545
-0.030895
-0.033265
-0.039005
-0.039655
-0.032505
-0.027425
-0.012485
0.000175
0.012955
0.019425
0.043625
0.032645
0.030855
0.029595
0.027335
0.028035
0.023185
0.032365
0.022555
0.007305
0.001645
-0.004275
0.001975
-0.005315
-0.003835
-0.000175
0.011705
0.021845
0.029025
0.025405
0.029075
0.020085
0.022735
0.013335
0.014395
-0.000645
0.017965
0.015675
0.008005
0.011775
0.009735
0.009625
0.016385
0.013375
0.019755
0.025035
0.013705
0.017065
0.018225
0.007095
0.005515
0.002945
0.004375
0.003265
-0.006185
-0.001595
0.010615
0.009745
0.011765
0.006025
0.004805
0.008065
0.019275
0.026545
0.039365
0.051045
0.077655




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49032&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]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49032&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49032&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'George Udny Yule' @ 72.249.76.132







Descriptive Statistics
# observations85
minimum-0.536795
Q1-0.030895
median0.007305
mean-0.00696511764705882
Q30.019425
maximum0.077655

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 85 \tabularnewline
minimum & -0.536795 \tabularnewline
Q1 & -0.030895 \tabularnewline
median & 0.007305 \tabularnewline
mean & -0.00696511764705882 \tabularnewline
Q3 & 0.019425 \tabularnewline
maximum & 0.077655 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49032&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]85[/C][/ROW]
[ROW][C]minimum[/C][C]-0.536795[/C][/ROW]
[ROW][C]Q1[/C][C]-0.030895[/C][/ROW]
[ROW][C]median[/C][C]0.007305[/C][/ROW]
[ROW][C]mean[/C][C]-0.00696511764705882[/C][/ROW]
[ROW][C]Q3[/C][C]0.019425[/C][/ROW]
[ROW][C]maximum[/C][C]0.077655[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49032&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49032&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
# observations85
minimum-0.536795
Q1-0.030895
median0.007305
mean-0.00696511764705882
Q30.019425
maximum0.077655



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')