Free Statistics

of Irreproducible Research!

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 computationTue, 23 Nov 2010 10:55:06 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Nov/23/t1290509699gi3p4ahkbfpvxds.htm/, Retrieved Thu, 25 Apr 2024 09:28:24 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=98923, Retrieved Thu, 25 Apr 2024 09:28:24 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact178
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [time effect in su...] [2010-11-17 08:55:33] [b98453cac15ba1066b407e146608df68]
F    D    [Univariate Explorative Data Analysis] [ws 7 univariate EDA] [2010-11-23 10:55:06] [350231caf55a86a218fd48dc4d2e2f8b] [Current]
-    D      [Univariate Explorative Data Analysis] [Run sequence plot...] [2010-11-24 07:51:38] [d59201e34006b7e3f71c33fa566f42b3]
-             [Univariate Explorative Data Analysis] [] [2010-12-02 15:19:17] [8e0d27d3447b6ae48398467ddbde7cca]
Feedback Forum
2010-11-27 16:22:41 [48eb36e2c01435ad7e4ea7854a9d98fe] [reply
De student heeft de software hier op een correcte manier gebruikt en ook de interpretatie is correct. Men kan inderdaad geen duidelijke stijgende of dalende evolutie doorheen de tijd waarnemen.

Toch gaat de student in een volgende stap een maandvariabele toevoegen aan het model. Gezien de conclusies die hij of zij op basis van deze 'run sequence plot' zelf getrokken heeft, lijkt mij dit niet relevant.

Post a new message
Dataseries X:
13
12
15
12
10
12
15
9
12
11
11
11
15
7
11
11
10
14
10
6
11
15
11
12
14
15
9
13
13
16
13
12
14
11
9
16
12
10
13
16
14
15
5
8
11
16
17
9
9
13
10
6
12
8
14
12
11
16
8
15
7
16
14
16
9
14
11
13
15
5
15
13
11
11
12
12
12
12
14
6
7
14
14
10
13
12
9
12
16
10
14
10
16
15
12
10
8
8
11
13
16
16
14
11
4
14
9
14
8
8
11
12
11
14
15
16
16
11
14
14
12
14
8
13
16
12
16
12
11
4
16
15
10
13
15
12
14
7
19
12
12
13
15
8
12
10
8
10
15
16
13
16
9
14
14
12




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=98923&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=98923&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98923&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
# observations156
minimum4
Q110
median12
mean12.0448717948718
Q314
maximum19

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 156 \tabularnewline
minimum & 4 \tabularnewline
Q1 & 10 \tabularnewline
median & 12 \tabularnewline
mean & 12.0448717948718 \tabularnewline
Q3 & 14 \tabularnewline
maximum & 19 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=98923&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]156[/C][/ROW]
[ROW][C]minimum[/C][C]4[/C][/ROW]
[ROW][C]Q1[/C][C]10[/C][/ROW]
[ROW][C]median[/C][C]12[/C][/ROW]
[ROW][C]mean[/C][C]12.0448717948718[/C][/ROW]
[ROW][C]Q3[/C][C]14[/C][/ROW]
[ROW][C]maximum[/C][C]19[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=98923&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=98923&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
# observations156
minimum4
Q110
median12
mean12.0448717948718
Q314
maximum19



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')