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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 01:50:28 -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/t1225093891s5egqvu1up43go2.htm/, Retrieved Sun, 19 May 2024 01:44:42 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19091, Retrieved Sun, 19 May 2024 01:44:42 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact210
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] [Taak 3 Q7] [2008-10-27 07:50:28] [dbfa7caa6871c163dec68ca05d48bb00] [Current]
Feedback Forum
2008-11-02 14:59:13 [Evelyn Ongena] [reply
Het was hier niet nodig om de ene tijdreeks door de andere te delen, de vraag was nl. 'Your Time Series = constant + random component'
2008-11-03 08:16:07 [Thomas Baken] [reply
De studente heeft het model 'Ontwikkeling van de prijzen in België / Financiële situatie van de gezinnen = constant + random component' toegepast, wat niet de vraag was. Hiervoor is het jammer want volgens mij wist de studente wel hoe ze het moest aanpakken.
2008-11-03 08:22:28 [Thomas Baken] [reply
Ook het ontdekken van de seizoenaliteit is nu onmogelijk aangezien de studente heeft gebruikt gemaakt van bovenstaande model. Als we echter toch een kijkje nemen naar de grafiek, bemerken we geen seizoenaliteit.
2008-11-03 10:37:14 [Jens Peeters] [reply
Het was inderdaad niet de bedoeling om de 2 tijdreeksen door elkaar te delen.

Post a new message
Dataseries X:
0,30952381
0,384615385
0,25
0,289473684
0,40625
0,407407407
0,578947368
0,37037037
0,407407407
0,428571429
0,47826087
0,4
0,375
0,541666667
0,375
0,368421053
0,302325581
0,386363636
0,285714286
0,29787234
0,347826087
0,301886792
0,276595745
0,277777778
0,291666667
0,295454545
0,355555556
0,285714286
0,306122449
0,326923077
0,275862069
0,274509804
0,307692308
0,46875
0,40625
0,315789474
0,444444444
0,378378378
0,30952381
0,311111111
0,352941176
0,32
0,306122449
0,352941176
0,301886792
0,296296296
0,25
0,240740741
0,25
0,225806452
0,253968254
0,327272727
0,26984127
0,3125
0,25
0,236111111
0,257575758
0,257575758
0,258064516
0,25
0,277777778
0,25
0,25
0,243243243
0,233333333
0,25
0,225806452
0,333333333
0,25
0,4
1
0,571428571
0,571428571




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 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 & 5 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=19091&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]5 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=19091&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19091&T=0

As an alternative you can also use a 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 time5 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001







Descriptive Statistics
# observations73
minimum0.225806452
Q10.258064516
median0.306122449
mean0.337356457945205
Q30.375
maximum1

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 73 \tabularnewline
minimum & 0.225806452 \tabularnewline
Q1 & 0.258064516 \tabularnewline
median & 0.306122449 \tabularnewline
mean & 0.337356457945205 \tabularnewline
Q3 & 0.375 \tabularnewline
maximum & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19091&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]73[/C][/ROW]
[ROW][C]minimum[/C][C]0.225806452[/C][/ROW]
[ROW][C]Q1[/C][C]0.258064516[/C][/ROW]
[ROW][C]median[/C][C]0.306122449[/C][/ROW]
[ROW][C]mean[/C][C]0.337356457945205[/C][/ROW]
[ROW][C]Q3[/C][C]0.375[/C][/ROW]
[ROW][C]maximum[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19091&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19091&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Descriptive Statistics
# observations73
minimum0.225806452
Q10.258064516
median0.306122449
mean0.337356457945205
Q30.375
maximum1



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')