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Description of Statistical Computation

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, 26 Oct 2008 08:28:17 -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/26/t1225031564t96tr7udq2lpvw6.htm/, Retrieved Sun, 19 May 2024 14:57:43 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18897, Retrieved Sun, 19 May 2024 14:57:43 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168

Tree of Dependent Computations

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 prijs kledi...] [2008-10-26 10:30:49] [46c5a5fbda57fdfa1d4ef48658f82a0c]
F    D        [Univariate Explorative Data Analysis] [taak 2/1] [2008-10-26 11:52:50] [29647dffafb5b58c12a48dbf6cba2b57]
F    D            [Univariate Explorative Data Analysis] [taak 2/2] [2008-10-26 14:28:17] [dbfa7caa6871c163dec68ca05d48bb00] [Current]
Feedback Forum
2008-11-02 14:55:07 [Evelyn Ongena] [reply] 
Als we kijken naar de lag plot, zien we dat de punten redelijk dicht bij de rechte liggen, wat zou wijzen op autocorrelatie. Om de derde voorwaarde te beoordelen moet er naar de run sequence plot gekeken worden en niet naar de mean en median. Ook hier is een lichte wijziging van de r code nodig om de 4de voorwaarde na te gaan : x<-x-gevonden gemiddelde
2008-11-03 08:12:25 [Thomas Baken] [reply] 
Er is inderdaad geen autocorrelatie, er liggen punten hoger dan de strikt genomen limiet, eveneens is er geen normaal verdeling, de histogram en density plot wijken zeer sterk af naar rechts en zijn bijgevolg niet normaal. Om te zeggen dat, omdat de mean en mediaan dicht bij elkaar liggen dit als gevolg heeft dat de determinerende component constant is, is niet juist. Hiervoor moeten we kijken naar het run sequence plot of deze vast is en flucueert... Ze fluctueert zeer sterk en is niet vast, bijgevolg kunnen we niet spreken van een constant component. Tenslotte kunnen we spreken over een fixed variation van het random component.

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
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

Tables (Output of Computation)





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=18897&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=18897&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18897&T=0

As an alternative you can also use a QR Code:  
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
# 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=18897&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=18897&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18897&T=1

As an alternative you can also use a QR Code:  
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


Figures (Output of Computation)

Input Parameters & R Code

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')