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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 computationSun, 25 Oct 2009 18:08:55 -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/26/t12565157923qetoxcjcz0fwi8.htm/, Retrieved Thu, 02 May 2024 19:45:20 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50441, Retrieved Thu, 02 May 2024 19:45:20 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact200
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Harrell-Davis Quantiles] [WS3, part 1-3] [2009-10-20 14:26:04] [ed603017d2bee8fbd82b6d5ec04e12c3]
-   P   [Harrell-Davis Quantiles] [WS3 part 1 -3] [2009-10-20 14:31:26] [ed603017d2bee8fbd82b6d5ec04e12c3]
- RMPD    [Univariate Explorative Data Analysis] [WS part 2y(t)- co...] [2009-10-20 15:38:58] [ed603017d2bee8fbd82b6d5ec04e12c3]
-    D        [Univariate Explorative Data Analysis] [WS 3 deel III.4] [2009-10-26 00:08:55] [71c065898bd1c08eef04509b4bcee039] [Current]
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Dataseries X:
0,730769231
0,720720721
0,743119266
0,77
0,815217391
0,826086957
0,821052632
0,8125
0,821052632
0,824175824
0,842696629
0,788888889
0,742574257
0,72815534
0,745098039
0,802083333
0,836956522
0,849462366
0,861702128
0,872340426
0,891304348
0,911111111
0,877777778
0,811111111
0,704081633
0,66
0,683673469
0,741935484
0,777777778
0,788888889
0,791208791
0,78021978
0,758241758
0,760869565
0,772727273
0,771084337
0,797619048
0,814814815
0,831168831
0,797468354
0,784810127
0,8125
0,860759494
0,894736842
0,901408451
0,897058824
0,892307692
0,884057971
0,87804878
0,83908046
0,831325301
0,772151899
0,773333333
0,794871795
0,855421687
0,916666667
0,963414634
1
1,027777778
1,02739726




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50441&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]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50441&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50441&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'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations60
minimum0.66
Q10.7725834295
median0.8136574075
mean0.82141442885
Q30.8643617025
maximum1.027777778

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 0.66 \tabularnewline
Q1 & 0.7725834295 \tabularnewline
median & 0.8136574075 \tabularnewline
mean & 0.82141442885 \tabularnewline
Q3 & 0.8643617025 \tabularnewline
maximum & 1.027777778 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50441&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]0.66[/C][/ROW]
[ROW][C]Q1[/C][C]0.7725834295[/C][/ROW]
[ROW][C]median[/C][C]0.8136574075[/C][/ROW]
[ROW][C]mean[/C][C]0.82141442885[/C][/ROW]
[ROW][C]Q3[/C][C]0.8643617025[/C][/ROW]
[ROW][C]maximum[/C][C]1.027777778[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50441&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50441&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
minimum0.66
Q10.7725834295
median0.8136574075
mean0.82141442885
Q30.8643617025
maximum1.027777778



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')