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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, 20 Nov 2012 17:22:15 -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/Nov/20/t1353450179hh8k7m6ormlcnii.htm/, Retrieved Mon, 29 Apr 2024 23:47:57 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=191312, Retrieved Mon, 29 Apr 2024 23:47:57 +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] [Workshop 7 - Time...] [2012-11-20 22:22:15] [8f5998680e1bcb718ece477961fd7528] [Current]
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Dataseries X:
476000
475000
470000
461000
455000
456000
517000
525000
523000
519000
509000
512000
519000
517000
510000
509000
501000
507000
569000
580000
578000
565000
547000
555000
562000
561000
555000
544000
537000
543000
594000
611000
613000
611000
594000
595000
591000
589000
584000
573000
567000
569000
621000
629000
628000
612000
595000
597000
593000
590000
580000
574000
573000
573000
620000
626000
620000
588000
566000
557000
561000
549000
532000
526000
511000
499000
555000
565000
542000
527000
510000
514000
517000
508000
493000
490000
469000
478000
528000
534000
518000
506000
502000
516000
528000
533000
536000
537000
524000
536000
587000
597000
581000
564000
558000
575000
580000
575000
563000
552000
537000
545000
601000
604000
586000
564000
549000
551000
556000
548000
540000
531000
521000
519000
572000
581000
563000
548000
539000
541000
562000
559000
546000
536000
528000
530000
582000
599000
584000
571000




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time6 seconds
R Server'George Udny Yule' @ yule.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 & 6 seconds \tabularnewline
R Server & 'George Udny Yule' @ yule.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191312&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]6 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ yule.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191312&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191312&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 time6 seconds
R Server'George Udny Yule' @ yule.wessa.net







Descriptive Statistics
# observations130
minimum455000
Q1523250
median551500
mean550453.846153846
Q3580000
maximum629000

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 130 \tabularnewline
minimum & 455000 \tabularnewline
Q1 & 523250 \tabularnewline
median & 551500 \tabularnewline
mean & 550453.846153846 \tabularnewline
Q3 & 580000 \tabularnewline
maximum & 629000 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=191312&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]130[/C][/ROW]
[ROW][C]minimum[/C][C]455000[/C][/ROW]
[ROW][C]Q1[/C][C]523250[/C][/ROW]
[ROW][C]median[/C][C]551500[/C][/ROW]
[ROW][C]mean[/C][C]550453.846153846[/C][/ROW]
[ROW][C]Q3[/C][C]580000[/C][/ROW]
[ROW][C]maximum[/C][C]629000[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=191312&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=191312&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
# observations130
minimum455000
Q1523250
median551500
mean550453.846153846
Q3580000
maximum629000



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')