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 computationMon, 27 Oct 2008 15:31:04 -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/t1225143217nwiwx7npjtty2vy.htm/, Retrieved Sun, 19 May 2024 00:26:35 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19642, Retrieved Sun, 19 May 2024 00:26:35 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141

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] [Q7] [2008-10-27 21:31:04] [5e2b1e7aa808f9f0d23fd35605d4968f] [Current]
-   P     [Univariate Explorative Data Analysis] [Q7 correctie] [2008-11-01 18:11:19] [547636b63517c1c2916a747d66b36ebf]
-   P     [Univariate Explorative Data Analysis] [Q7 - verbetering] [2008-11-02 14:54:25] [299afd6311e4c20059ea2f05c8dd029d]
- RM        [Harrell-Davis Quantiles] [Q9] [2008-11-02 15:18:12] [299afd6311e4c20059ea2f05c8dd029d]
- R           [Harrell-Davis Quantiles] [Q9 - wijziging R-...] [2008-11-02 15:27:37] [299afd6311e4c20059ea2f05c8dd029d]
Feedback Forum
2008-11-01 18:28:53 [Olivier Uyttendaele] [reply] 
Hier werk je in tegenstelling tot Q2 wel met assumpties. Echter moet je bij eht reproduceren nog de lags aanpassen om een lag Plot e.d. te bekomen.
Aangepast blog: http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/01/t1225563247715rwjwi9a1t5o9.htm

Assumptie 1: Via het Lag Plot en/of Autocorrelation
de waarden liggen redelijk verspreid bij het Lag Plot, toch is er een kleine centralisatie rond de rechten. Bij de grafiek autocorrelatie zien we toch een matige positieve autocorrelatie.

Assumptie 2:
Heb je de correcte grafieken voor gebruikt.
Inderdaad is een vrij normale verdeling merkbaar. We merken iets meer waarden op aan de rechterkant, we krijgen dus een right skewed histogram.

assumptie 3:
Hiervoor gebruik je het Run sequence plot om te kijken of het niveau gelijk blijft. Het QQ plot dient meer om randomness en correlatie te onderzoeken.
Je kan een duidelijk stijgende trend merken bij het niveau in deze grafiek.

Assumptie 4:
Hiervoor weer het Run Sequence Plot, (eventueel met de aanpassing om het gemiddelde(constante) uit de reeks te halen)
De spreiding lijkt mij op het eerste zicht gelijk te blijven.
Fluctuatie en niveau hebben hier geen uitstaans mee.

Assumptie 3 en in mindere mate assumptie 1 dienen verworpen te worden.

Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12192.5
11268.8
9097.4
12639.8
13040.1
11687.3
11191.7
11391.9
11793.1
13933.2
12778.1
11810.3
13698.4
11956.6
10723.8
13938.9
13979.8
13807.4
12973.9
12509.8
12934.1
14908.3
13772.1
13012.6
14049.9
11816.5
11593.2
14466.2
13615.9
14733.9
13880.7
13527.5
13584.0
16170.2
13260.6
14741.9
15486.5
13154.5
12621.2
15031.6
15452.4
15428.0
13105.9
14716.8
14180.0
16202.2
14392.4
15140.6
15960.1
14351.3
13230.2
15202.1
17157.3
16159.1
13405.7
17224.7
17338.4
17370.6
18817.8
16593.2
17979.5

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=19642&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=19642&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19642&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
# observations52
minimum10723.8
Q112963.95
median13789.75
mean13824.7019230769
Q314783.5
maximum17224.7

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 52 \tabularnewline
minimum & 10723.8 \tabularnewline
Q1 & 12963.95 \tabularnewline
median & 13789.75 \tabularnewline
mean & 13824.7019230769 \tabularnewline
Q3 & 14783.5 \tabularnewline
maximum & 17224.7 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19642&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]52[/C][/ROW]
[ROW][C]minimum[/C][C]10723.8[/C][/ROW]
[ROW][C]Q1[/C][C]12963.95[/C][/ROW]
[ROW][C]median[/C][C]13789.75[/C][/ROW]
[ROW][C]mean[/C][C]13824.7019230769[/C][/ROW]
[ROW][C]Q3[/C][C]14783.5[/C][/ROW]
[ROW][C]maximum[/C][C]17224.7[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19642&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19642&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
# observations52
minimum10723.8
Q112963.95
median13789.75
mean13824.7019230769
Q314783.5
maximum17224.7


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')