FreeStatistics.org

Free Statistics

of Irreproducible Research!

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 08:31:37 -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/t1225031559wkcazp8v28ah3ku.htm/, Retrieved Sun, 19 May 2024 16:38:49 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18896, Retrieved Sun, 19 May 2024 16:38:49 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119

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] [Investigating Dis...] [2007-10-21 18:26:46] [b9964c45117f7aac638ab9056d451faa]
F   PD    [Univariate Explorative Data Analysis] [q4 kleding/tot pr...] [2008-10-26 14:31:37] [1aceffc2fa350402d9e8f8edd757a2e8] [Current]
Feedback Forum
2008-10-30 23:21:53 [Kenny Simons] [reply] 
Bij vraag 3 kom je wel tot de juiste oplossing, maar je zegt niet vanwaar je deze kan afleiden. Hiervoor moet je namelijk opnieuw zien naar het run sequence plot, hieraan zie je dat er duidelijk geen stijgende of constante spreiding is, maar wel een dalende.
2008-10-30 23:23:40 [Kenny Simons] [reply] 
Vraag 4 heb je juist beantwoord. Hiervoor moest je weer naar het run sequence plot kijken. Al is het hier wel moeilijk af te lezen. Maar er is wel degelijk seizoenaliteit vanwege de autocorrelatie. Dit hebben we ook besproken bij assumptie 1 van vraag 2
2008-11-03 19:30:28 [An De Koninck] [reply] 
Het is correct dat de grafiek een dalend verloop vertoont. Dit betekent dat op lange termijn de evolutie van kledingproductie niet gelijk loopt met die van de totale productie en niet dat ze geen invloed hebben op elkaar. De student denkt dat hier invloeden ten opzichte van elkaar met elkaar vergeleken worden, maar dit is niet het geval. Hier trekt de student dus een verkeerde conclusie.
2008-11-03 19:34:41 [An De Koninck] [reply] 
Q4: Het is correct dat er sprake is van seizoensgebondenheid, maar de student vertelt niet op welke grafiek hij dit afgelezen heeft.
Je moet hiervoor kijken naar de run sequenze plot. Tussen 30 en 40 en tussen 40 en 50 zijn er duidelijke bulten te zien. Op 40 en juist na 50 zijn er pieken te bespeuren. Dit wijst op seizoensgebondenheid.
Maar om dit te besluiten is het echter beter om de mean plot te gebruiken.

Post a new message

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 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=18896&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=18896&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18896&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
minimum0.683284457
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=18896&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=18896&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18896&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 = 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)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Lag plot, lowess, and regression line'))
lines(lowess(z))
abline(lm(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')