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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 computationSat, 25 Oct 2008 12:01:49 -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/25/t12249580321jrj7sv26fdq5cm.htm/, Retrieved Sun, 19 May 2024 15:57:21 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18784, Retrieved Sun, 19 May 2024 15:57:21 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact136

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F       [Univariate Explorative Data Analysis] [Q3 U EDA Clothin ...] [2008-10-25 18:01:49] [e11d930c9e2984715c66c796cf63ef19] [Current]
Feedback Forum
2008-10-30 21:41:41 [Kim De Vos] [reply] 
Men kan hier niet spreken van een constant want bij de Run Sequence plot merk je op dat er zich een dalende trend voordoet + alle validiteitsvoorwaarden van het model zijn niet voldaan.
2008-10-31 23:15:55 [Olivier Uyttendaele] [reply] 
Ik heb het model goed aangepast(juiste gegevens)en hier ook een correcte interpretatie aan gegeven volgens mij. Het is duidelijk dat er hier een verschil in niveau is.(dalende trend)
2008-10-31 23:23:47 [Olivier Uyttendaele] [reply] 
Q4 -> Er is inderdaad seizoenaliteit in de grafiek. Op het zicht is vrij moeilijk zichtbaar, maar er zit toch een zeker patroon in de reeks.
2008-11-03 21:21:30 [Bonifer Spillemaeckers] [reply] 
Er is hier inderdaad een dalende trend te bemerken. Dit wijst er op dat de totale productie en kledingproductie niet op een gelijke manier evolueren. De kledingproductie groeit dus niet zo snel als de totale productie

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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,989130435
0,919087137
0,925417076
0,925612053
1,066666667
0,851108765
1,030693069
0,989031079
0,913000978
0,792723264
0,978170478
0,987513007
0,909433962
0,883608147
0,82745098
0,8252149
1,023255814
0,815418024
1,026192703
0,914742451
0,807276303
0,739130435
0,98973306
0,972164948
0,853889943
0,856864654
0,775739042
0,789473684
0,931350114
0,73971079
0,885245902
0,842435094
0,818458418
0,72755418
0,923238696
0,922680412
0,883762201
0,818270165
0,771047228
0,825852783
0,924485126
0,755165289
0,874671341
0,815956482
0,799807507
0,712598425
0,832980973
0,910323253
0,869149952
0,779182879
0,750254842
0,75856014
0,920889988
0,743991641
0,816254417
0,769593957
0,784007353
0,683284457
0,850505051
0,900695134
0,868398268

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 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 & 4 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=18784&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]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18784&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18784&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Descriptive Statistics
# observations61
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.683284457 \tabularnewline
Q1 & 0.792723264 \tabularnewline
median & 0.853889943 \tabularnewline
mean & 0.86210009042623 \tabularnewline
Q3 & 0.922680412 \tabularnewline
maximum & 1.066666667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18784&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.683284457[/C][/ROW]
[ROW][C]Q1[/C][C]0.792723264[/C][/ROW]
[ROW][C]median[/C][C]0.853889943[/C][/ROW]
[ROW][C]mean[/C][C]0.86210009042623[/C][/ROW]
[ROW][C]Q3[/C][C]0.922680412[/C][/ROW]
[ROW][C]maximum[/C][C]1.066666667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18784&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18784&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
minimum0.683284457
Q10.792723264
median0.853889943
mean0.86210009042623
Q30.922680412
maximum1.066666667


Figures (Output of Computation)

Input Parameters & R Code

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