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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 computationThu, 11 Nov 2010 13:16:21 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/11/t12894812821n2dbh5n59u2553.htm/, Retrieved Thu, 18 Apr 2024 22:36:05 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=93293, Retrieved Thu, 18 Apr 2024 22:36:05 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact214
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]
-  MPD      [Univariate Explorative Data Analysis] [Mini tutorial 2] [2010-11-11 13:16:21] [380f6bceef280be3d93cc6fafd18141e] [Current]
-    D        [Univariate Explorative Data Analysis] [ws6 mini tutorial...] [2010-11-15 17:46:29] [e4076051fbfb461c886b1e223cd7862f]
-    D        [Univariate Explorative Data Analysis] [ws6.mini hypothese 2] [2010-11-15 18:19:49] [e4076051fbfb461c886b1e223cd7862f]
-    D          [Univariate Explorative Data Analysis] [] [2010-11-16 13:16:37] [8d09066a9d3795298da6860e7d4a4400]
-                 [Univariate Explorative Data Analysis] [] [2010-11-17 06:00:13] [6e5489189f7de5cfbcc25dd35ae15009]
-    D          [Univariate Explorative Data Analysis] [] [2010-11-16 13:26:20] [8d09066a9d3795298da6860e7d4a4400]
-                 [Univariate Explorative Data Analysis] [] [2010-11-17 06:01:04] [6e5489189f7de5cfbcc25dd35ae15009]
- RM          [Univariate Explorative Data Analysis] [mini tuorial] [2011-11-15 15:20:34] [d31984dff2665bea309b726bae3d5241]
- R  D        [Univariate Explorative Data Analysis] [] [2011-11-15 17:03:59] [ad2d4c5ace9fa07b356a7b5098237581]
- R  D        [Univariate Explorative Data Analysis] [Graph Mini-Tutorial] [2011-11-15 22:12:51] [f722e8e78b9e5c5ebaa2263f273aa636]
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Dataseries X:
5,11
3,53
4,52
3,72
5,99
3,15
3,17
3,50
3,39
4,15
4,50
3,31
3,09
5,31
4,24
5,06
4,72
4,58
5,30
5,11
4,05
4,62
4,66
4,66
2,76
5,10
4,97
2,87
5,14
4,98
4,55
5,45
4,36
4,78
4,74
5,44
5,78
2,92
4,22
3,93
3,01
3,22
5,12
3,04
5,82
3,11
3,87
3,75
4,82
2,83




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93293&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]3 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=93293&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93293&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations50
minimum2.76
Q13.4175
median4.51
mean4.2804
Q35.04
maximum5.99

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 50 \tabularnewline
minimum & 2.76 \tabularnewline
Q1 & 3.4175 \tabularnewline
median & 4.51 \tabularnewline
mean & 4.2804 \tabularnewline
Q3 & 5.04 \tabularnewline
maximum & 5.99 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=93293&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]50[/C][/ROW]
[ROW][C]minimum[/C][C]2.76[/C][/ROW]
[ROW][C]Q1[/C][C]3.4175[/C][/ROW]
[ROW][C]median[/C][C]4.51[/C][/ROW]
[ROW][C]mean[/C][C]4.2804[/C][/ROW]
[ROW][C]Q3[/C][C]5.04[/C][/ROW]
[ROW][C]maximum[/C][C]5.99[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=93293&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=93293&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
# observations50
minimum2.76
Q13.4175
median4.51
mean4.2804
Q35.04
maximum5.99



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)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Lag plot, lowess, and regression line'))
lines(lowess(z))
abline(lm(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')