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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 computationMon, 27 Oct 2008 13:45:09 -0600
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2008/Oct/27/t1225136767l1tzkydkfn1ri7j.htm/, Retrieved Sun, 19 May 2024 16:36:46 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=19500, Retrieved Sun, 19 May 2024 16:36:46 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132

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] [Q3] [2008-10-25 13:03:36] [4300be8b33fd3dcdacd2aa9800ceba23]
F    D    [Univariate Explorative Data Analysis] [Q3] [2008-10-27 19:45:09] [541f63fa3157af9df10fc4d202b2a90b] [Current]
Feedback Forum
2008-11-01 20:47:33 [Tom Ardies] [reply] 
om de seizonaal gedrag te analyseren moet je reproduce aanklikken en de lags instellen op 12 of meer.
2008-11-04 07:19:12 [Nilay Erdogdu] [reply] 
lags instellen op 12 of op 36

zie links

link lag:12
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/04/t1225778184i2135t1qazndkpu.htm

link lag 36
http://www.freestatistics.org/blog/index.php?v=date/2008/Nov/04/t1225777919n8ct8dnmm6wev8r.htm


Post a new message

Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
0.99
0.92
0.93
0.93
1.07
0.85
1.03
0.99
0.91
0.79
0.98
0.99
0.91
0.88
0.83
0.83
1.02
0.82
1.03
0.91
0.81
0.74
0.99
0.97
0.85
0.86
0.78
0.79
0.93
0.74
0.89
0.84
0.82
0.73
0.92
0.92
0.88
0.82
0.77
0.83
0.92
0.76
0.87
0.82
0.80
0.71
0.83
0.91
0.87
0.78
0.75
0.76
0.92
0.74
0.82
0.77
0.78
0.68
0.85
0.90
0.87

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001

\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 & 4 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ 193.190.124.10:1001 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19500&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]4 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ 193.190.124.10:1001[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19500&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19500&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 time4 seconds
R Server'Herman Ole Andreas Wold' @ 193.190.124.10:1001






Descriptive Statistics
# observations61
minimum0.68
Q10.79
median0.85
mean0.862295081967213
Q30.92
maximum1.07

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & 0.68 \tabularnewline
Q1 & 0.79 \tabularnewline
median & 0.85 \tabularnewline
mean & 0.862295081967213 \tabularnewline
Q3 & 0.92 \tabularnewline
maximum & 1.07 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=19500&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]0.68[/C][/ROW]
[ROW][C]Q1[/C][C]0.79[/C][/ROW]
[ROW][C]median[/C][C]0.85[/C][/ROW]
[ROW][C]mean[/C][C]0.862295081967213[/C][/ROW]
[ROW][C]Q3[/C][C]0.92[/C][/ROW]
[ROW][C]maximum[/C][C]1.07[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=19500&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=19500&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
# observations61
minimum0.68
Q10.79
median0.85
mean0.862295081967213
Q30.92
maximum1.07


Figures (Output of Computation)

Input Parameters & R Code

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)
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')