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Description of Statistical Computation

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 computationWed, 01 Dec 2010 15:00:34 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2010/Dec/01/t1291215533guzw2bonxoy6pgu.htm/, Retrieved Sun, 11 May 2025 07:48:04 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=104045, Retrieved Sun, 11 May 2025 07:48:04 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact262

Tree of Dependent Computations

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]
-    D  [Univariate Explorative Data Analysis] [Run sequency plot...] [2010-11-20 14:46:56] [95e8426e0df851c9330605aa1e892ab5]
-           [Univariate Explorative Data Analysis] [] [2010-12-01 15:00:34] [6d73806852b9f5b8ac8b27fc8f7b83c4] [Current]
-             [Univariate Explorative Data Analysis] [] [2010-12-03 17:26:41] [5e7b9ab9ddedd2d2f5ce6c303ba3ebe3]
-   PD        [Univariate Explorative Data Analysis] [run sequence plot...] [2011-11-24 10:08:43] [ca5872d1d4d784184b94263c274137e3]
- RMPD        [Multiple Regression] [tre] [2011-11-24 10:14:29] [ca5872d1d4d784184b94263c274137e3]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
11
7
17
10
12
12
11
11
12
13
14
16
11
10
11
15
9
11
17
17
11
18
14
10
11
15
15
13
16
13
9
18
18
12
17
9
9
12
18
12
18
14
15
16
10
11
14
9
12
17
5
12
12
6
24
12
12
14
7
13
12
13
14
8
11
9
11
13
10
11
12
9
15
18
15
12
13
14
10
13
13
11
13
16
8
16
11
9
16
12
14
8
9
15
11
21
14
18
12
13
15
12
19
15
11
11
10
13
15
12
12
16
9
18
8
13
17
9
15
8
7
12
14
6
8
17
10
11
14
11
13
12
11
9
12
20
12
13
12
12
9
15
24
7
17
11
17
11
12
14
11
16
21
14
20
13
11
15
19

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time26 seconds
R Server'George Udny Yule' @ 72.249.76.132

\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 & 26 seconds \tabularnewline
R Server & 'George Udny Yule' @ 72.249.76.132 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104045&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]26 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'George Udny Yule' @ 72.249.76.132[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104045&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104045&T=0

As an alternative you can also use a QR Code:  
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 time26 seconds
R Server'George Udny Yule' @ 72.249.76.132






Descriptive Statistics
# observations159
minimum5
Q111
median12
mean12.8553459119497
Q315
maximum24

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 159 \tabularnewline
minimum & 5 \tabularnewline
Q1 & 11 \tabularnewline
median & 12 \tabularnewline
mean & 12.8553459119497 \tabularnewline
Q3 & 15 \tabularnewline
maximum & 24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=104045&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]159[/C][/ROW]
[ROW][C]minimum[/C][C]5[/C][/ROW]
[ROW][C]Q1[/C][C]11[/C][/ROW]
[ROW][C]median[/C][C]12[/C][/ROW]
[ROW][C]mean[/C][C]12.8553459119497[/C][/ROW]
[ROW][C]Q3[/C][C]15[/C][/ROW]
[ROW][C]maximum[/C][C]24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=104045&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=104045&T=1

As an alternative you can also use a QR Code:  
QR Code


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

Descriptive Statistics
# observations159
minimum5
Q111
median12
mean12.8553459119497
Q315
maximum24


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
par1 = 0 ; par2 = 36 ;
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')