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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 computationSun, 26 Oct 2008 11:27:53 -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/t1225042097q4jv4tv3oz24aoy.htm/, Retrieved Sun, 19 May 2024 14:32:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=18986, Retrieved Sun, 19 May 2024 14:32:37 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact168
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] [] [2008-10-26 17:27:53] [19ef54504342c1b076371d395a2ab19f] [Current]
F           [Univariate Explorative Data Analysis] [q7 - invest. distr.] [2008-10-27 20:34:48] [ffbe22449df335faef31f462015daa42]
-   P         [Univariate Explorative Data Analysis] [Q7 ] [2008-11-01 11:20:25] [4396f984ebeab43316cd6baa88a4fd40]
- R             [Univariate Explorative Data Analysis] [Q7] [2008-11-01 11:30:29] [4396f984ebeab43316cd6baa88a4fd40]
F           [Univariate Explorative Data Analysis] [q10 invest. distr.] [2008-10-27 20:40:16] [ffbe22449df335faef31f462015daa42]
-   P       [Univariate Explorative Data Analysis] [lag plot = 12 cor...] [2008-10-29 15:29:40] [e1a46c1dcfccb0cb690f79a1a409b517]
-   P       [Univariate Explorative Data Analysis] [Reproductie] [2008-11-02 17:53:22] [5e74953d94072114d25d7276793b561e]
Feedback Forum
2008-11-02 18:04:58 [Annelies Michiels] [reply
Allereerst moeten we hier ook de optie van de lag plots instellen:
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/02/t1225648459cor6xrwad9wn2q7.htm

Assumptie 1:
De autocorrelatie moet niet worden berekend door de run sequency plot maar door de lag plots.
Als we deze lag plots bekijken zien we dat we duidelijk te maken hebben met autocorrelatie. Als we de autocorrelation functie bekijken zien we duidelijk een terugkerend patroon.

Assumptie 2:
Als we het histogram, het density plot en de Q-Q plot bekijken zien we inderdaad dat het min of meer om een normaal verdeling gaat.

Assumptie 3:
Deze assumptie moet niet via de Q-Q plot worden onderzocht maar via de run sequency plot. Als we de run sequency plot bekijken, zien we dat de frequentie min of meer stabiel blijft. We kunnen dus zeggen dat de frequentie constant blijft.

Assumptie 4:
Deze assumptie kan wel worden onderzocht nl. via de run sequency plot.
Als we deze grafiek bekijken zien we dat de spreiding steeds groter en groter wordt.

Post a new message
Dataseries X:
22780
17351
21382
24561
17409
11514
31514
27071
29462
26105
22397
23843
21705
18089
20764
25316
17704
15548
28029
29383
36438
32034
22679
24319
18004
17537
20366
22782
19169
13807
29743
25591
29096
26482
22405
27044
17970
18730
19684
19785
18479
10698
31956
29506
34506
27165
26736
23691
18157
17328
18205
20995
17382
9367
31124
26551
30651
25859
25100
25778
20418
18688
20424
24776
19814
12738
31566
30111
30019
31934
25826
26835




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24

\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 & 4 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18986&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18986&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18986&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 time4 seconds
R Server'Sir Ronald Aylmer Fisher' @ 193.190.124.24







Descriptive Statistics
# observations72
minimum9367
Q118635.75
median23236.5
mean23305.2083333333
Q327094.5
maximum36438

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 72 \tabularnewline
minimum & 9367 \tabularnewline
Q1 & 18635.75 \tabularnewline
median & 23236.5 \tabularnewline
mean & 23305.2083333333 \tabularnewline
Q3 & 27094.5 \tabularnewline
maximum & 36438 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=18986&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]72[/C][/ROW]
[ROW][C]minimum[/C][C]9367[/C][/ROW]
[ROW][C]Q1[/C][C]18635.75[/C][/ROW]
[ROW][C]median[/C][C]23236.5[/C][/ROW]
[ROW][C]mean[/C][C]23305.2083333333[/C][/ROW]
[ROW][C]Q3[/C][C]27094.5[/C][/ROW]
[ROW][C]maximum[/C][C]36438[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=18986&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=18986&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
# observations72
minimum9367
Q118635.75
median23236.5
mean23305.2083333333
Q327094.5
maximum36438



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')