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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 computationMon, 14 Dec 2009 10:14:02 -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/Dec/14/t126081087781ibr1szbl1yfaf.htm/, Retrieved Sun, 05 May 2024 10:26:11 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=67589, Retrieved Sun, 05 May 2024 10:26:11 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Data Series] [data set] [2008-12-01 19:54:57] [b98453cac15ba1066b407e146608df68]
- RMP   [ARIMA Backward Selection] [] [2009-11-27 14:53:14] [b98453cac15ba1066b407e146608df68]
-   PD    [ARIMA Backward Selection] [WS9] [2009-12-03 23:50:09] [37a8d600db9abe09a2528d150ccff095]
- RMPD      [Harrell-Davis Quantiles] [] [2009-12-04 21:24:16] [74be16979710d4c4e7c6647856088456]
- RMP         [Univariate Explorative Data Analysis] [] [2009-12-04 21:35:31] [74be16979710d4c4e7c6647856088456]
-    D          [Univariate Explorative Data Analysis] [] [2009-12-11 20:05:01] [74be16979710d4c4e7c6647856088456]
-    D              [Univariate Explorative Data Analysis] [] [2009-12-14 17:14:02] [d41d8cd98f00b204e9800998ecf8427e] [Current]
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Dataseries X:
0.102099945804887
0.737601051471779
0.0106618293088252
0.52239377142817
1.07142787304473
-0.914061367174038
-0.428462409725616
-0.0654398048209609
1.19700131954875
-0.415035627082705
0.790229966140711
-1.20057857422849
1.10379820587161
-0.273135171804026
-0.267822467388643
1.34265393731741
-1.54293043754615
-0.0119730328107786
0.222952413225187
-0.345660667035868
0.264305650805457
1.72740775878021
1.58805033299532
0.377632331984582
0.0174696730264222
-0.844095886303813
0.141125552395322
0.849526022031545
0.652168611346395
-0.919947768004273
0.433795873152471
-1.43446391109305
-0.649941295444581
0.290571683853168
-0.430213956986155
0.231554627911427
1.29492092986709
-0.39281211697063
-0.587917646775748
-0.806911791305758
-0.392543947667208
-1.0340885974776
-0.75641012970889
-0.301789001672712
-0.547361456817899




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=67589&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=67589&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67589&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







Descriptive Statistics
# observations45
minimum-1.54293043754615
Q1-0.547361456817899
median-0.0119730328107786
mean0.00901671767701947
Q30.52239377142817
maximum1.72740775878021

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 45 \tabularnewline
minimum & -1.54293043754615 \tabularnewline
Q1 & -0.547361456817899 \tabularnewline
median & -0.0119730328107786 \tabularnewline
mean & 0.00901671767701947 \tabularnewline
Q3 & 0.52239377142817 \tabularnewline
maximum & 1.72740775878021 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=67589&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]45[/C][/ROW]
[ROW][C]minimum[/C][C]-1.54293043754615[/C][/ROW]
[ROW][C]Q1[/C][C]-0.547361456817899[/C][/ROW]
[ROW][C]median[/C][C]-0.0119730328107786[/C][/ROW]
[ROW][C]mean[/C][C]0.00901671767701947[/C][/ROW]
[ROW][C]Q3[/C][C]0.52239377142817[/C][/ROW]
[ROW][C]maximum[/C][C]1.72740775878021[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=67589&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=67589&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
# observations45
minimum-1.54293043754615
Q1-0.547361456817899
median-0.0119730328107786
mean0.00901671767701947
Q30.52239377142817
maximum1.72740775878021



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')