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 computationMon, 27 Oct 2008 04:05:38 -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/2008/Oct/27/t1225101993i7z3g6n7mzn4mjn.htm/, Retrieved Fri, 17 May 2024 07:05:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19173, Retrieved Fri, 17 May 2024 07:05:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact155
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Tukey lambda PPCC Plot] [Tukey lambda tot ...] [2008-10-24 09:02:28] [e1a46c1dcfccb0cb690f79a1a409b517]
F RMPD  [Univariate Explorative Data Analysis] [Univariate Explor...] [2008-10-24 12:02:31] [e1a46c1dcfccb0cb690f79a1a409b517]
-   PD    [Univariate Explorative Data Analysis] [UEDA - Vlaams gew...] [2008-10-26 09:55:38] [46c5a5fbda57fdfa1d4ef48658f82a0c]
F    D      [Univariate Explorative Data Analysis] [4plot investering...] [2008-10-26 10:33:39] [46c5a5fbda57fdfa1d4ef48658f82a0c]
-    D          [Univariate Explorative Data Analysis] [Investering - Tot...] [2008-10-27 10:05:38] [e7b118d7688fea522247297d6fc6c452] [Current]
Feedback Forum

Post a new message
Dataseries X:
0.656702899
0.616182573
0.841020608
0.830508475
0.775308642
0.918690602
0.784158416
1.023765996
0.774193548
1.456449835
0.416839917
0.718002081
0.560377358
0.715809893
0.562745098
0.774594078
0.541860465
0.449511401
0.666043031
0.603019538
0.707964602
1.581521739
0.407597536
0.535051546
0.699240987
0.690360273
0.619775739
0.583732057
0.623569794
0.434927697
0.606557377
0.523724261
0.606490872
0.834881321
0.392218717
0.459793814
0.432120674
0.524781341
0.508213552
0.552962298
0.400457666
0.368801653
0.449605609
0.444242974
0.399422522
0.713582677
0.445031712
0.459854015
0.430754537
0.489299611
0.416921509
0.414398595
0.456118665
0.42737722
0.338339223
0.43720491
0.261029412
0.766373412
0.371717172
0.50347567
0.370562771




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 5 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19173&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19173&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19173&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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Descriptive Statistics
# observations61
minimum0.261029412
Q10.434927697
median0.541860465
mean0.596325281737705
Q30.707964602
maximum1.581521739

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.261029412 \tabularnewline
Q1 & 0.434927697 \tabularnewline
median & 0.541860465 \tabularnewline
mean & 0.596325281737705 \tabularnewline
Q3 & 0.707964602 \tabularnewline
maximum & 1.581521739 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19173&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.261029412[/C][/ROW]
[ROW][C]Q1[/C][C]0.434927697[/C][/ROW]
[ROW][C]median[/C][C]0.541860465[/C][/ROW]
[ROW][C]mean[/C][C]0.596325281737705[/C][/ROW]
[ROW][C]Q3[/C][C]0.707964602[/C][/ROW]
[ROW][C]maximum[/C][C]1.581521739[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19173&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19173&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
# observations61
minimum0.261029412
Q10.434927697
median0.541860465
mean0.596325281737705
Q30.707964602
maximum1.581521739



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')