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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 computationMon, 27 Oct 2008 12:28:35 -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/t1225132149tu52wly5fa68jeq.htm/, Retrieved Sun, 19 May 2024 13:56:26 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19376, Retrieved Sun, 19 May 2024 13:56:26 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact139

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 IA2] [2008-10-27 18:28:35] [b05bea52879de0a398b42c6968cc24b2] [Current]
Feedback Forum
2008-11-01 10:12:31 [Stéphanie Claes] [reply] 
De student maakt de juiste conclusie, er is duidelijk een dalende trend, dus het is geen constante. De kledingproductie wijkt af van de economische groei van totale productie.
2008-11-01 10:15:17 [Stéphanie Claes] [reply] 
Q4: We kijken naar de run sequence en daar zien we een grote piek gevolgd door een kleine, er is een zeker seizonaal patroon maar dat is moeilijk te zien. Er is seizonaliteit door autocorrelatie.
2008-11-02 19:53:51 [Bernard Femont] [reply] 
Indien de kledingproductie en de totale productie in gelijke mate evolueren, dan zou de grafiek geen dalend karakter hebben, maar horizontaal zijn (de deling kledingproductie/totale productie geeft dan een steeds wederkerende waarde) juiste interpretatie van de gegevens en juiste bespreking van output.
2008-11-02 19:56:15 [Bernard Femont] [reply] 
antw Q4:
Ja, want u ziet steeds een systematisch terugkomend patroon en dit patroon duidt op storingen die afhankelijk zijn van elkaar.
Dus een juiste interpretatie van de student

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0,989130
0,919087
0,925417
0,925612
1,066667
0,851109
1,030693
0,989031
0,913001
0,792723
0,978170
0,987513
0,909434
0,883608
0,827451
0,825215
1,023256
0,815418
1,026193
0,914742
0,807276
0,739130
0,989733
0,972165
0,853890
0,856865
0,775739
0,789474
0,931350
0,739711
0,885246
0,842435
0,818458
0,727554
0,923239
0,922680
0,883762
0,818270
0,771047
0,825853
0,924485
0,755165
0,874671
0,815956
0,799808
0,712598
0,832981
0,910323
0,869150
0,779183
0,750255
0,758560
0,920890
0,743992
0,816254
0,769594
0,784007
0,683284
0,850505
0,900695
0,868398

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 2 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19376&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19376&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19376&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 time2 seconds
R Server'George Udny Yule' @ 72.249.76.132






Descriptive Statistics
# observations61
minimum0.683284
Q10.792723
median0.85389
mean0.862100016393443
Q30.92268
maximum1.066667

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.683284 \tabularnewline
Q1 & 0.792723 \tabularnewline
median & 0.85389 \tabularnewline
mean & 0.862100016393443 \tabularnewline
Q3 & 0.92268 \tabularnewline
maximum & 1.066667 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19376&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.683284[/C][/ROW]
[ROW][C]Q1[/C][C]0.792723[/C][/ROW]
[ROW][C]median[/C][C]0.85389[/C][/ROW]
[ROW][C]mean[/C][C]0.862100016393443[/C][/ROW]
[ROW][C]Q3[/C][C]0.92268[/C][/ROW]
[ROW][C]maximum[/C][C]1.066667[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19376&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19376&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
minimum0.683284
Q10.792723
median0.85389
mean0.862100016393443
Q30.92268
maximum1.066667


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')