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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 computationFri, 01 Dec 2017 13:52:56 +0100
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2017/Dec/01/t15121331062gtcyohs4ut2iko.htm/, Retrieved Thu, 31 Oct 2024 23:03:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=308422, Retrieved Thu, 31 Oct 2024 23:03:33 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact141
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Univariate Explorative Data Analysis] [] [2017-12-01 12:52:56] [97f06f641c613c300eccf7f42763c030] [Current]
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Dataseries X:
17
19
18
17
17
19
19
12
15
16
16
14
15
16
14
18
15
18
19
15
17
9
18
17
15
13
17
14
15
14
17
14
13
19
15
14
11
16
13
15
17
15
12
15
15
8
16
12
13
16
16
8
14
15
16
16
17
18
9
19
14
14
15
19
12
17
16
17
15
11
8
16
20
20
13
11
15
15
14
16
15
15
16
19
20
14
16
14
11
16
16
15
16
12
13
11
20
11
14
16
15
13
15
13
17
18
14
13
12
17
6
9
15
15
17
19
20
10
9
15
16
16
9
10
9
17
17
19
10
12
9
11
17
9
14
19
17
13
11
14
7
17
16
12
10
10
8
18
15
18
14
16
11
16
17
20
14
16
17
11
13
11
8
9
9
12
15
18
10
15
16
18
15
17
17
14
17
13
16
12
17
10
9
15
14
16
17
18
14
17
14
15
14
10
9
12
13
14
18
15
14
10
9
17
12
16
11
13
12
15
15
10
16
11
14
17
16
16
11
16
13
7
13
14
14
9
15
16
11
20
14
9
16
13
15
15
15
15
14
15
13
12
17
8
17
10
9
9
15
14
12
16
19
6
11
16
12
12
8
11
8
12
16
18
16
15
20
10
15
14
14
8
19
17
18
10
15
16
12
13
10
14
15
20
9
12
13
16
12
14
15
19
16
16
14
14
14
13
18
15
15
15
13
14
15
14
19
16
16
12
10
11
13
14
11
11
16
9
16
19
13
15
14
15
11
14
15
17
16
13
15
14
15
14
12
12
15
17
13
5
7
10
15
9
9
15
14
11
18
20
20
16
15
14
13
18
14
12
9
19
13
12
14
6
14
11
11
14
12
19
13
14
17
12
16
15
15
15
16
15
12
13
14
17
14
14
14
15
11
11
16
12
12
19
18
16
16
13
11
10
14
14
14
16
10
16
7
16
15
17
11
11
10
13
14
13
13
12
10
15
6
15
15
11
14
14
16
12
15
20
12
9
13
15
19
11
11
17
15
14
15
11
12
15
16
16




Summary of computational transaction
Raw Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input view raw input (R code)  \tabularnewline
Raw Outputview raw output of R engine  \tabularnewline
Computing time3 seconds \tabularnewline
R ServerBig Analytics Cloud Computing Center \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308422&T=0

[TABLE]
[ROW]
Summary of computational transaction[/C][/ROW] [ROW]Raw Input[/C] view raw input (R code) [/C][/ROW] [ROW]Raw Output[/C]view raw output of R engine [/C][/ROW] [ROW]Computing time[/C]3 seconds[/C][/ROW] [ROW]R Server[/C]Big Analytics Cloud Computing Center[/C][/ROW] [/TABLE] Source: https://freestatistics.org/blog/index.php?pk=308422&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308422&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 Input view raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R ServerBig Analytics Cloud Computing Center







Descriptive Statistics
# observations446
minimum5
Q112
median14
mean14.0582959641256
Q316
maximum20

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 446 \tabularnewline
minimum & 5 \tabularnewline
Q1 & 12 \tabularnewline
median & 14 \tabularnewline
mean & 14.0582959641256 \tabularnewline
Q3 & 16 \tabularnewline
maximum & 20 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=308422&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]446[/C][/ROW]
[ROW][C]minimum[/C][C]5[/C][/ROW]
[ROW][C]Q1[/C][C]12[/C][/ROW]
[ROW][C]median[/C][C]14[/C][/ROW]
[ROW][C]mean[/C][C]14.0582959641256[/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=308422&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=308422&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
# observations446
minimum5
Q112
median14
mean14.0582959641256
Q316
maximum20



Parameters (Session):
par1 = 0 ; par2 = 0 ;
Parameters (R input):
par1 = 0 ; par2 = 0 ;
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)
print(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)
print(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')