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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 11:38:37 -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/t1225042760vep1y74y3lbjqg3.htm/, Retrieved Sun, 19 May 2024 13:01:19 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18989, Retrieved Sun, 19 May 2024 13:01:19 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact173

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Maximum-likelihood Fitting - Exponential Distribution] [Taak 4 Deel 2 Mod...] [2008-10-23 11:18:07] [819b576fab25b35cfda70f80599828ec]
F RMPD    [Univariate Explorative Data Analysis] [Investigating Dis...] [2008-10-26 17:38:37] [e08fee3874f3333d6b7a377a061b860d] [Current]
Feedback Forum
2008-11-02 11:04:00 [Kevin Neelen] [reply] 
Dit is een tweede model dat we uitgeprobeerd hebben.
Hierbij kunnen we bemerken dat de kledingproductie sneller groeit in vergelijking met de investeringen in kleding en dus niet gelijk loopt met de algemene groei in de kledinginvesteringen. Dit uit zich in het run sequence plot door een stijgende trend in de grafiek.
2008-11-02 14:13:12 [Stijn Van de Velde] [reply] 
Goede grafiek + goede uitleg.
  2008-11-02 20:25:19 [Yara Van Overstraeten] [reply] 
Mooie grafiek en correcte conclusie.
2008-11-03 08:38:43 [Siem Van Opstal] [reply] 
correcte conclusie

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
1,506206897
1,491582492
1,100350058
1,114512472
1,375796178
0,926436782
1,314393939
0,966071429
1,179292929
0,544284633
2,346633416
1,375362319
1,622895623
1,234417344
1,470383275
1,065351418
1,888412017
1,814009662
1,540730337
1,516936672
1,140277778
0,467353952
2,428211587
1,816955684
1,221166893
1,241184767
1,251644737
1,352459016
1,493577982
1,700767263
1,459459459
1,608547009
1,349498328
0,87144623
2,353887399
2,006726457
2,045174538
1,559259259
1,517171717
1,493506494
2,308571429
2,047619048
1,945419103
1,836734694
2,002409639
0,99862069
1,871733967
1,979591837
2,017738359
1,592445328
1,799511002
1,830508475
2,01897019
1,740831296
2,412532637
1,760259179
3,003521127
0,891581633
2,288043478
1,788954635
2,343457944

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=18989&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=18989&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18989&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
minimum0.467353952
Q11.251644737
median1.559259259
mean1.61067855952459
Q31.945419103
maximum3.003521127

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.467353952 \tabularnewline
Q1 & 1.251644737 \tabularnewline
median & 1.559259259 \tabularnewline
mean & 1.61067855952459 \tabularnewline
Q3 & 1.945419103 \tabularnewline
maximum & 3.003521127 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18989&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.467353952[/C][/ROW]
[ROW][C]Q1[/C][C]1.251644737[/C][/ROW]
[ROW][C]median[/C][C]1.559259259[/C][/ROW]
[ROW][C]mean[/C][C]1.61067855952459[/C][/ROW]
[ROW][C]Q3[/C][C]1.945419103[/C][/ROW]
[ROW][C]maximum[/C][C]3.003521127[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18989&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18989&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
minimum0.467353952
Q11.251644737
median1.559259259
mean1.61067855952459
Q31.945419103
maximum3.003521127


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)
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')