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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 computationTue, 22 Nov 2011 14:05:53 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Nov/22/t1321988789i0p8enutpum661d.htm/, Retrieved Thu, 28 Mar 2024 17:40:18 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=146369, Retrieved Thu, 28 Mar 2024 17:40:18 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact56
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]
- R PD    [Univariate Explorative Data Analysis] [sequence nyrstar] [2011-11-22 19:05:53] [2adf2d2c11e011c12275478b9efd18e5] [Current]
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Dataseries X:
11,73
11,75
11,39
11,54
9,62
9,82
9,94
9,9
9,8
9,86
10,5
10,33
10,16
9,91
9,96
10,03
9,55
9,51
9,8
10,08
10,2
10,23
10,2
10,07
10,01
10,05
9,92
10,03
10,18
10,1
10,16
10,15
10,13
10,09
10,18
10,06
9,65
9,74
9,53
9,5
9
9,15
9,32
9,62
9,59
9,37
9,35
9,32
9,49
9,52
9,59
9,35
9,2
9,57
9,78
9,79
9,57
9,53
9,65
9,36
9,4
9,32
9,31
9,19
9,39
9,28
9,28
9,31
9,28
9,31
9,35
9,19
9,07
8,96
8,69
8,58
8,56
8,47
8,46
8,75
8,95
9,33
9,51
9,561
9,94
9,9
9,275
9,56
9,779
9,746
9,991
9,98
10,195
10,31
10,25
9,871
10,06
9,894
9,59
9,64
9,89
9,53
9,388
9,16
9,418
9,57
9,857
9,877
9,76
9,76
9,695
9,475
9,262
9,097
8,55
8,16
7,532
7,325
6,749
7,13
6,995
7,346
7,73
7,837
7,514
7,58
6,83
6,617
6,715
6,63
6,891
7,002
7,09
7,36
7,477
7,826
7,79
7,578
7,204
7,198
7,685
7,795
7,46
7,274
7,33
7,655
7,767
7,84
7,424
7,54
7,351
6,735
6,777
6,679
7,34
6,978
6,92
6,628
6,385
5,984
6,268
6,596
6,395
6,715
6,804
6,929
6,846
6,992
6,774
6,75
6,485
6,27
6,47
6,78
6,71
6,141
6,72
6,68
6,371
6,097
6,27
6,447
6,37
6,446
6,54
6,374
6,33
6,63
6,498
6,485
6,36




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'AstonUniversity' @ aston.wessa.net

\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 & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146369&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]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146369&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146369&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 time3 seconds
R Server'AstonUniversity' @ aston.wessa.net







Descriptive Statistics
# observations191
minimum5.984
Q17.11
median9.28
mean8.59396335078534
Q39.7795
maximum11.75

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 191 \tabularnewline
minimum & 5.984 \tabularnewline
Q1 & 7.11 \tabularnewline
median & 9.28 \tabularnewline
mean & 8.59396335078534 \tabularnewline
Q3 & 9.7795 \tabularnewline
maximum & 11.75 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=146369&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]191[/C][/ROW]
[ROW][C]minimum[/C][C]5.984[/C][/ROW]
[ROW][C]Q1[/C][C]7.11[/C][/ROW]
[ROW][C]median[/C][C]9.28[/C][/ROW]
[ROW][C]mean[/C][C]8.59396335078534[/C][/ROW]
[ROW][C]Q3[/C][C]9.7795[/C][/ROW]
[ROW][C]maximum[/C][C]11.75[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=146369&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=146369&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
# observations191
minimum5.984
Q17.11
median9.28
mean8.59396335078534
Q39.7795
maximum11.75



Parameters (Session):
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')