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Author's title

Author*The author of this computation has been verified*
R Software Module--
Title produced by softwareUnivariate Explorative Data Analysis
Date of computationSat, 03 Nov 2012 09:54:08 -0400
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/03/t135195089878i9yon92fbf4ji.htm/, Retrieved Sun, 03 Jul 2022 14:16:37 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=185723, Retrieved Sun, 03 Jul 2022 14:16:37 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact93
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     [Univariate Explorative Data Analysis] [Run sequence Plot...] [2011-11-22 17:49:24] [59e9c089bdd600b584669dddc48fbcc3]
-  M        [Univariate Explorative Data Analysis] [] [2012-11-03 13:54:08] [f3ca428ef12de0510f6752588dd725b0] [Current]
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Dataseries X:
13
16
19
15
14
13
19
15
14
15
16
16
16
16
17
15
15
20
18
16
16
16
19
16
17
17
16
15
16
14
15
12
14
16
14
10
10
14
16
16
16
14
20
14
14
11
14
15
16
14
16
14
12
16
9
14
16
16
15
16
12
16
16
14
16
17
18
18
12
16
10
14
18
18
16
17
16
16
13
16
16
16
15
15
16
14
16
16
15
12
17
16
15
13
16
16
16
16
14
16
16
20
15
16
13
17
16
16
12
16
16
17
13
12
18
14
14
13
16
13
16
13
16
15
16
15
17
15
12
16
10
16
12
14
15
13
15
11
12
11
16
15
17
16
10
18
13
16
13
10
15
16
16
14
10
17
13
15
16
12
13
13
12
17
15
10
14
11
13
16
12
16
12
9
12
15
12
12
14
12
16
11
19
15
8
16
17
12
11
11
14
16
12
16
13
15
16
16
14
16
16
14
11
12
15
15
16
16
11
15
12
12
15
15
16
14
17
14
13
15
13
14
15
12
13
8
14
14
11
12
13
10
16
18
13
11
4
13
16
10
12
12
10
13
15
12
14
10
12
12
11
10
12
16
12
14
16
14
13
4
15
11
11
14




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.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 & 5 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185723&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]5 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185723&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185723&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 time5 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net







Descriptive Statistics
# observations264
minimum4
Q113
median15
mean14.2727272727273
Q316
maximum20

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 264 \tabularnewline
minimum & 4 \tabularnewline
Q1 & 13 \tabularnewline
median & 15 \tabularnewline
mean & 14.2727272727273 \tabularnewline
Q3 & 16 \tabularnewline
maximum & 20 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=185723&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]264[/C][/ROW]
[ROW][C]minimum[/C][C]4[/C][/ROW]
[ROW][C]Q1[/C][C]13[/C][/ROW]
[ROW][C]median[/C][C]15[/C][/ROW]
[ROW][C]mean[/C][C]14.2727272727273[/C][/ROW]
[ROW][C]Q3[/C][C]16[/C][/ROW]
[ROW][C]maximum[/C][C]20[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=185723&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=185723&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
# observations264
minimum4
Q113
median15
mean14.2727272727273
Q316
maximum20



Parameters (Session):
par1 = 0 ; par2 = 36 ;
Parameters (R input):
par1 = 0 ; par2 = 36 ; par3 = ; par4 = ; par5 = ; par6 = ; par7 = ; par8 = ; par9 = ; par10 = ; par11 = ; par12 = ; par13 = ; par14 = ; par15 = ; par16 = ; par17 = ; par18 = ; par19 = ; par20 = ;
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')