Free Statistics

of Irreproducible Research!

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, 03 Nov 2009 14:32:19 -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/Nov/03/t12572841217si0dwxj21blytd.htm/, Retrieved Wed, 01 May 2024 14:15:10 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=53434, Retrieved Wed, 01 May 2024 14:15:10 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact142
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]
- RMPD  [Bivariate Explorative Data Analysis] [WS 4 - Deel 2 - V...] [2009-10-26 08:18:42] [b103a1dc147def8132c7f643ad8c8f84]
- RMPD      [Univariate Explorative Data Analysis] [RWS4 univar EDA e...] [2009-11-03 21:32:19] [b08f24ccf7d7e0757793cda532be96b3] [Current]
Feedback Forum

Post a new message
Dataseries X:
-0.964240779
-1.239025656
0.775302887
-1.414671024
-0.839886147
-0.532721875
0.373581905
-0.007506753
-0.351633217
-0.515531515
-0.720974805
-0.757936998
-0.215531515
-1.089455901
0.936619712
-1.009227734
-1.015531515
-0.584012611
0.460113853
0.004240318
0.066417634
-0.591176883
-0.709227734
-0.47140505
-0.159657979
-0.914671024
0.960974344
-0.997480663
-0.702923953
-0.091176883
1.178164705
0.809683608
0.190772266
0.382747504
0.12859495
-0.610088225
-0.735303348
-0.996620173
0.991632757
-0.816392006
-0.541607128
-0.547910909
0.522291169
-0.178569321
-0.359657979
-1.036163838
-0.359657979
-0.135303348
-0.898341154
-0.322695786
0.297076047
-0.535303348
-0.286594084
0.407962626
1.784468485
1.295355065
-0.323556277
0.763836162
0.362975671
0.170139942
0.206241645
0.300798355
2.159253363
0.775583232
0.907102136
1.990772266
1.879025195
1.604240318
0.679025195
0.697076047
0.166417634
0.091632757
0.259253363




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=53434&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=53434&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53434&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-1.414671024
Q1-0.610088225
median-0.135303348
mean-1.36986245988597e-11
Q30.460113853
maximum2.159253363

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 73 \tabularnewline
minimum & -1.414671024 \tabularnewline
Q1 & -0.610088225 \tabularnewline
median & -0.135303348 \tabularnewline
mean & -1.36986245988597e-11 \tabularnewline
Q3 & 0.460113853 \tabularnewline
maximum & 2.159253363 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=53434&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]73[/C][/ROW]
[ROW][C]minimum[/C][C]-1.414671024[/C][/ROW]
[ROW][C]Q1[/C][C]-0.610088225[/C][/ROW]
[ROW][C]median[/C][C]-0.135303348[/C][/ROW]
[ROW][C]mean[/C][C]-1.36986245988597e-11[/C][/ROW]
[ROW][C]Q3[/C][C]0.460113853[/C][/ROW]
[ROW][C]maximum[/C][C]2.159253363[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=53434&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=53434&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-1.414671024
Q1-0.610088225
median-0.135303348
mean-1.36986245988597e-11
Q30.460113853
maximum2.159253363



Parameters (Session):
par1 = 0 ; par2 = 12 ;
Parameters (R input):
par1 = 0 ; par2 = 12 ;
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')