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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, 21 Oct 2009 10:32:20 -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/21/t1256142779zkg35fxo410aone.htm/, Retrieved Thu, 02 May 2024 04:17:50 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49491, Retrieved Thu, 02 May 2024 04:17:50 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsSHW WS 3 - Vraag 2 (3)
Estimated Impact177
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]
- RMPD      [Univariate Explorative Data Analysis] [WS 3 - Vraag 1 (1)] [2009-10-21 15:37:29] [b103a1dc147def8132c7f643ad8c8f84]
- RMP         [Central Tendency] [WS 3 - Vraag 1 (2)] [2009-10-21 15:45:10] [b103a1dc147def8132c7f643ad8c8f84]
- RMPD          [Univariate Explorative Data Analysis] [WS 3 - Vraag 2 (1)] [2009-10-21 16:02:49] [b103a1dc147def8132c7f643ad8c8f84]
-    D              [Univariate Explorative Data Analysis] [WS 3 - Vraag 2 (3)] [2009-10-21 16:32:20] [a45cc820faa25ce30779915639528ec2] [Current]
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Dataseries X:
-0.07
-0.10
0.03
-0.09
-0.06
-0.05
0.01
-0.02
-0.04
-0.03
-0.05
-0.06
-0.01
-0.08
0.05
-0.06
-0.06
-0.04
0.02
-0.01
0.00
-0.03
-0.04
-0.03
-0.01
-0.06
0.05
-0.05
-0.04
0.00
0.07
0.04
0.01
0.03
0.00
-0.03
-0.03
-0.06
0.05
-0.04
-0.02
-0.02
0.03
-0.01
-0.02
-0.04
-0.02
0.00
-0.03
-0.01
0.02
-0.02
0.00
0.03
0.10
0.07
0.00
0.05
0.03
0.02
0.03
0.03
0.12
0.05
0.05
0.11
0.11
0.09
0.03
0.04
0.00
0.00
0.02




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=49491&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=49491&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49491&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
# observations73
minimum-0.1
Q1-0.04
median0
mean-0.000684931506849315
Q30.03
maximum0.12

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 73 \tabularnewline
minimum & -0.1 \tabularnewline
Q1 & -0.04 \tabularnewline
median & 0 \tabularnewline
mean & -0.000684931506849315 \tabularnewline
Q3 & 0.03 \tabularnewline
maximum & 0.12 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49491&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]73[/C][/ROW]
[ROW][C]minimum[/C][C]-0.1[/C][/ROW]
[ROW][C]Q1[/C][C]-0.04[/C][/ROW]
[ROW][C]median[/C][C]0[/C][/ROW]
[ROW][C]mean[/C][C]-0.000684931506849315[/C][/ROW]
[ROW][C]Q3[/C][C]0.03[/C][/ROW]
[ROW][C]maximum[/C][C]0.12[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49491&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49491&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
# observations73
minimum-0.1
Q1-0.04
median0
mean-0.000684931506849315
Q30.03
maximum0.12



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')