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Author's title

Author*Unverified author*
R Software Modulerwasp_univariatedataseries.wasp
Title produced by softwareUnivariate Data Series
Date of computationMon, 13 Feb 2012 07:00:09 -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/2012/Feb/13/t1329135527s9sb3lqdb7pa0bx.htm/, Retrieved Thu, 02 May 2024 21:05:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=162194, Retrieved Thu, 02 May 2024 21:05:14 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywordsKDG2011W2MO
Estimated Impact110
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Univariate Data Series] [Studio 100] [2012-02-13 12:00:09] [aa59cfa385e119596867d158cdccc7ef] [Current]
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Dataseries X:
25
25
25
25
29
30
30
29
35
30
30
30
29
30
30
26
30
30
30
35
30
30
30
50
25
29
30
25
30
30
25
42
29
15
29
30
25
20
10
30
29
30
50
25
30
30
25
50
29
30
30
30
30
30
30
29
35
40
29
26
23
25
30
30
30
30
20
29
25
25
28
30
30
25
30
31
30
29
45
30
30
35
30
30
25
50
40
20
35
22
30
25
30
30
29
50
45
30
26
30
29
35
20
29
25
30
45
35
30
30
40
20
26
29
20
25
30
30
25
30
23
25
30
30
40
30
40
35
40
30
25
33
30
30
30
35
33
35
30
40
29
25
27
30
30
35
20
30
30
25
25
30
30
30
40
40
30
40
20
50
20
30
30
30
30
25
30
30
30
30
30
30
23
30
25
50
20
23
25
29
26
40
30
30
35
20
29
25
30
30
30
50
30
35
30
30
30
35
30
35
15
30
20
35
40
30
30
40
29
30
20
35
50
30
30
40
30
50
18
15
30
23
29
30
35
30
23
30
25
26
25
30
20
25
30
29
40
30
30
30
40
37
20
25
30
32
35
32
30
30
35
30
25
30
24
30
35
30
30
30
30
30
25
30
25
35
30
30
30
30
30
30
35
32
30
20
20
30
35
30
40
29
26
40
25
35
30
23
30
27
35
30
20
30
25
50
30
30
29
35
29
25
30
45
30
25
29
25
40
30
30
40
30
30
29
35
35
30
30
27
30
30
29
50
30
30
20
25
25
30
27
29
50
50
30
30
40
20
30
30
30
25
30
30
30
30
40
25
35
30
30
35
20
20
50
35
29
50
40
30
45
30
40
30
29
25
40
35
25
21
30
30
30
30
15
30
30
30
30
30
25
30
30
30
30
25
25
40
30
33
40
26
30
37
25
29
30
25
29
30
30
30
30
30
22
25
30
40
30
29
25
30
30
29
30
30
30
35
30
35
30
12
15
25
30
30
30
25
20
30
35
35
29
40
30
40
30
25
30
20
29
28
30
25
30
50
30
30
29
30
35
20
30
30
30
30
30
40
30
30
35
25
30
50
30
30
30
30
25
30
30
30
25
30
30
30
25
30
30
26
30
30
30
30
25
20
30
35
30
20
20
25
30
30
30
30
29
35
25
30
30
35
35
30
20
30
30
30
25
30
30
26
30
25
30
50
30
20
29
30
30
30
30
30
40
30
35
27
30
25
29
25
30
25
30
29
25
20
30
25
32
30
29
30
30
30
30
25
25
30
30
60
20
30
35
25
30
25
30
40
25
30
29
29
30
29
26
18
30
40
30
30
30
30
30
29
30
30
30
35
30
30
30
20
29
20
30
30
25
30
40
30
30
25
40
30
30
29
25
30
35
30
20
30
20
25
30
40
25
47
20
20
30
30
25
30
25
40
29
40
29
30
30
30
35
30
20
30
24
30
40
30
30
15
35
18
30
25
30
30
30
15
20
30
25
30
20
30
30
30
25
40
50
30
30
35
30
30
15
30
25
30
30
26
30
25
25
30
30
30
50
30
25
30
25
30
26
25
34
30
25
30
35
30
40
30
30
29
30
29
30
50
30
15
30
25
50
30
30
35
35
25
23
30
30
30
35
25
15
30
29
30
15
30
40
29
30
25
25
50
30
1
30
30
30
35
30
30
35
30
20
20
20
30
35
30
25
29
35
40
30
35
29
30
30
30
29
30
30
30
30
30
30
30
35
30
30
30
25
50
30
30
30
25
25
35
30
35
30
29
30
35
30
30
35
25
25
29
35
50
30
30
29
30
30
30
20
30
30
20
30
25
20
30
50
20
40
40
30
29
35
25
20
20
21
29
35
30
28
30
30
35
26
30
25
25
30
30
30
25
35
30
35
35
30
29
30
26
30
27
30
30
50
25
30
30
30
40
30
32
25
35
30
30
20
30
40
30
26
30
40
30
30
26
35
35
26
50
30
30
25
30
40
25
30
25
30
15
40
30
25
30
30
30
30
30
25
25
30
20
18
25
30
29
13
27
30
30
30
30
25
30
35
29
30
29
30
30
25
45
29
30
30
25
25
29
30
30
30
29
30
23
35
35
10
32
29
45
30
29
30
15
50
35
25
25
30
30
30
30
30
40
29
25
30
25
30
25
25
30
35
30
25
20
30
30
30
15
30
35
50
35
30
30
25
30
30
15
30
25
30
30
25
29
30
30
40
25
30
30
25
35
29
30
25
30
30
25
30
30
30
25
35
25
29
25
30
30
50
30
30

30
30
30
20
25
25
35
25
30
25
50
20
45
25
35
30
40
35
30
30
30
30
23
30
25
30
15




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.

\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 & 1 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
R Framework error message & 
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
\tabularnewline \hline \end{tabular} %Source: https://freestatistics.org/blog/index.php?pk=162194&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]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[ROW][C]R Framework error message[/C][C]
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.
[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=162194&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=162194&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 time1 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net
R Framework error message
Warning: there are blank lines in the 'Data' field.
Please, use NA for missing data - blank lines are simply
 deleted and are NOT treated as missing values.







Univariate Dataseries
Name of dataseriesMaximumprijs STUDIO100 2006
SourceBlackboard
DescriptionMaximumprijs STUDIO100 2006
Number of observations1018

\begin{tabular}{lllllllll}
\hline
Univariate Dataseries \tabularnewline
Name of dataseries & Maximumprijs STUDIO100 2006 \tabularnewline
Source & Blackboard \tabularnewline
Description & Maximumprijs STUDIO100 2006 \tabularnewline
Number of observations & 1018 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=162194&T=1

[TABLE]
[ROW][C]Univariate Dataseries[/C][/ROW]
[ROW][C]Name of dataseries[/C][C]Maximumprijs STUDIO100 2006[/C][/ROW]
[ROW][C]Source[/C][C]Blackboard[/C][/ROW]
[ROW][C]Description[/C][C]Maximumprijs STUDIO100 2006[/C][/ROW]
[ROW][C]Number of observations[/C][C]1018[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=162194&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=162194&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Univariate Dataseries
Name of dataseriesMaximumprijs STUDIO100 2006
SourceBlackboard
DescriptionMaximumprijs STUDIO100 2006
Number of observations1018



Parameters (Session):
par1 = Maximumprijs STUDIO100 2006 ; par2 = Blackboard ; par3 = Maximumprijs STUDIO100 2006 ; par4 = No season ;
Parameters (R input):
par1 = Maximumprijs STUDIO100 2006 ; par2 = Blackboard ; par3 = Maximumprijs STUDIO100 2006 ; par4 = No season ;
R code (references can be found in the software module):
if (par4 != 'No season') {
par4 <- as.numeric(par4)
if (par4 < 4) par4 <- 12
}
summary(x)
n <- length(x)
bitmap(file='test1.png')
if (par4=='No season') {
plot(x,col=2,type='b',main=main,xlab=xlab,ylab=ylab,xaxt='n')
axis(1,at=seq(1,n,10))
}
if (par4!='No season') {
plot(x,col=2,type='b',main=main,xlab=xlab,ylab=ylab,xaxt='n')
axis(1,at=seq(1,n,par4))
grid(nx=0,ny=NULL,col='black')
abline(v=seq(1,n,par4),col='black',lty='dotted')
}
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Univariate Dataseries',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Name of dataseries',header=TRUE)
a<-table.element(a,par1)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Source',header=TRUE)
a<-table.element(a,par2)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,par3)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of observations',header=TRUE)
a<-table.element(a,length(x))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')