Repository of Reproducible Computations

Free Statistics

of Irreproducible Research!

Author's title

Author

*The author of this computation has been verified*

R Software Module

rwasp_edauni.wasp

Title produced by software

Univariate Explorative Data Analysis

Date of computation

Mon, 27 Oct 2008 10:45:31 -0600

Cite this page as follows

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225126011kg5jaqxzvc8odgc.htm/, Retrieved Sun, 19 May 2024 13:19:08 +0000

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19251, Retrieved Sun, 19 May 2024 13:19:08 +0000

QR Codes:

Paste this QR Code to cite your computation.

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords

Estimated Impact

204

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...] [2007-10-22 19:45:25] [b9964c45117f7aac638ab9056d451faa]
F    D    [Univariate Explorative Data Analysis] [Q7 tijdreeks werk...] [2008-10-27 16:45:31] [35348cd8592af0baf5f138bd59921307] [Current]
F           [Univariate Explorative Data Analysis] [Q7 tijdreeks werk...] [2008-10-27 20:40:29] [c993f605b206b366f754f7f8c1fcc291] 
-   P       [Univariate Explorative Data Analysis] [Q7 assumpties eig...] [2008-11-03 18:47:18] [7d3039e6253bb5fb3b26df1537d500b4] 
- RMP       [Central Tendency] [Q8 central tendency] [2008-11-03 18:54:47] [c993f605b206b366f754f7f8c1fcc291] 
F RMPD      [Mean Plot] [Task 5 mean plot ...] [2008-11-03 19:06:21] [7d3039e6253bb5fb3b26df1537d500b4] 
-   P       [Univariate Explorative Data Analysis] [Autocorrelation p...] [2008-11-03 23:21:35] [aa5573c1db401b164e448aef050955a1] 

Feedback Forum

2008-11-03 18:55:31 [Stéphanie Claes] [reply] 
De lags hadden ingesteld moeten worden. 
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/03/t1225738073d4x22zj6nsnjxv3.htm => lags ingesteld 
 
1.Bij de eerste assumptie moeten we naar de lag plot gaan kijken en dan zien we dat de punten toch redelijk dicht tegen de lijn liggen dus dit zou kunnen duiden op seizonaliteit. 
 
2.Dit is correct geïnterpreteerd 
 
3.Hiervoor moet gekeken worden naar de run sequence en dan zien we dat het eindigt met een daling, dit zou kunnen betekenen dat het niveau op lange termijn niet constant blijft. 
 
4.Als we kijken naar de spreiding bij de run sequence dan zien we dat die niet overal even breed is. 
2008-11-03 19:06:17 [Kevin Engels] [reply] 
Q7: net als bij task 1 gebruikte ik de foute plots om de assumpties te testen. Voor asumptie 3 zie je dat het gemiddelde tussen de betrouwbaarheidsintervallen zit en min of meer constant blijft. 
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/03/t1225738939em1r01lgxza88fq.htm 
 
Q8 is correct opgelost. 
Bij Q9 gebruikte ik de juiste methode.  
Bij Q10 is er inderdaag geen seizoensgebondenheid terug te vinden als we de run sequence plot bekijken. Ook op de lag plot is hier niks van te merken.
2008-11-04 00:48:01 [Steven Symons] [reply] 
ASS 1: de lags moeten worden ingesteld op 36, anders kan je geen uitspraken doen over eventuele seizonaliteit. Als we dit doen zien we dat de punten dicht tegen de lijn komen te liggen wat duidt op seizonaliteit. 
 

Post a new message

Dataseries X:

Download CSV

Histogram

Boxplots

0.939759036
0.926829268
0.9375
0.962025316
0.986842105
0.960526316
0.926829268
0.903614458
0.904761905
0.94047619
0.94047619
0.941860465
0.921348315
0.909090909
0.903614458
0.906666667
0.902777778
0.88
0.863636364
0.860215054
0.860215054
0.885057471
0.914634146
0.915662651
0.905882353
0.918604651
0.906976744
0.914634146
0.925925926
0.8875
0.872093023
0.862068966
0.863636364
0.905882353
0.916666667
0.929411765
0.931034483
0.942528736
0.953488372
0.952941176
0.951807229
0.901234568
0.841463415
0.814814815
0.827160494
0.873417722
0.886075949
0.898734177
0.9
0.8875
0.873417722
0.875
0.883116883
0.888888889
0.893333333
0.917808219
0.914285714
0.9
0.885714286
0.902777778
0.931506849
0.957746479
0.955882353
0.954545455
0.951612903
0.951612903
0.941176471
0.927536232

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 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=19251&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=19251&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19251&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 Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	3 seconds
R Server	'Gwilym Jenkins' @ 72.249.127.135

Descriptive Statistics
# observations	68
minimum	0.814814815
Q1	0.88714398725
median	0.9080338265
mean	0.90988038157353
Q3	0.938064759
maximum	0.986842105

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 68 \tabularnewline
minimum & 0.814814815 \tabularnewline
Q1 & 0.88714398725 \tabularnewline
median & 0.9080338265 \tabularnewline
mean & 0.90988038157353 \tabularnewline
Q3 & 0.938064759 \tabularnewline
maximum & 0.986842105 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19251&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]68[/C][/ROW]
[ROW][C]minimum[/C][C]0.814814815[/C][/ROW]
[ROW][C]Q1[/C][C]0.88714398725[/C][/ROW]
[ROW][C]median[/C][C]0.9080338265[/C][/ROW]
[ROW][C]mean[/C][C]0.90988038157353[/C][/ROW]
[ROW][C]Q3[/C][C]0.938064759[/C][/ROW]
[ROW][C]maximum[/C][C]0.986842105[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19251&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19251&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
# observations	68
minimum	0.814814815
Q1	0.88714398725
median	0.9080338265
mean	0.90988038157353
Q3	0.938064759
maximum	0.986842105

Figure 1

PNG link

Postscript link

PDF link

Figure 2

PNG link

Postscript link

PDF link

Figure 3

PNG link

Postscript link

PDF link

Figure 4

PNG link

Postscript link

PDF link

Figure 5

PNG link

Postscript link

PDF link

Figure 6

PNG link

Postscript link

PDF link

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)
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')

Free Statistics

Description of Statistical Computation

Tree of Dependent Computations

Dataset

Tables (Output of Computation)

Figures (Output of Computation)

Input Parameters & R Code