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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 computationFri, 19 Dec 2008 02:28:10 -0700
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/Dec/19/t12296789564uiax7z70r2avih.htm/, Retrieved Wed, 15 May 2024 01:29:14 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=35000, Retrieved Wed, 15 May 2024 01:29:14 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact220

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
F     [Univariate Explorative Data Analysis] [Investigation Dis...] [2007-10-21 17:06:37] [b9964c45117f7aac638ab9056d451faa]
F    D  [Univariate Explorative Data Analysis] [] [2008-10-23 10:15:43] [2a30350413961f11db13c46be07a5f73]
-   PD    [Univariate Explorative Data Analysis] [investigating dis...] [2008-11-04 05:50:48] [090686c1af2bb318059a6f656863a319]
-   P       [Univariate Explorative Data Analysis] [investigating dis...] [2008-11-04 05:55:10] [090686c1af2bb318059a6f656863a319]
-    D        [Univariate Explorative Data Analysis] [paper 2.3 werkloo...] [2008-12-19 09:24:48] [090686c1af2bb318059a6f656863a319]
-   P             [Univariate Explorative Data Analysis] [paper 2.3 werkloo...] [2008-12-19 09:28:10] [c577d4c76516de948d1234ed72fcf120] [Current]
-   PD              [Univariate Explorative Data Analysis] [paper 2.3 aantal ...] [2008-12-19 09:31:18] [090686c1af2bb318059a6f656863a319]
-   P                 [Univariate Explorative Data Analysis] [paper 2.3 aantal ...] [2008-12-19 09:35:48] [090686c1af2bb318059a6f656863a319]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
493.000
481.000
462.000
457.000
442.000
439.000
488.000
521.000
501.000
485.000
464.000
460.000
467.000
460.000
448.000
443.000
436.000
431.000
484.000
510.000
513.000
503.000
471.000
471.000
476.000
475.000
470.000
461.000
455.000
456.000
517.000
525.000
523.000
519.000
509.000
512.000
519.000
517.000
510.000
509.000
501.000
507.000
569.000
580.000
578.000
565.000
547.000
555.000
562.000
561.000
555.000
544.000
537.000
543.000
594.000
611.000
613.000
611.000
594.000
595.000

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=35000&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=35000&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35000&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
# observations60
minimum431
Q1469.25
median509
mean510.083333333333
Q3544.75
maximum613

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 60 \tabularnewline
minimum & 431 \tabularnewline
Q1 & 469.25 \tabularnewline
median & 509 \tabularnewline
mean & 510.083333333333 \tabularnewline
Q3 & 544.75 \tabularnewline
maximum & 613 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=35000&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]60[/C][/ROW]
[ROW][C]minimum[/C][C]431[/C][/ROW]
[ROW][C]Q1[/C][C]469.25[/C][/ROW]
[ROW][C]median[/C][C]509[/C][/ROW]
[ROW][C]mean[/C][C]510.083333333333[/C][/ROW]
[ROW][C]Q3[/C][C]544.75[/C][/ROW]
[ROW][C]maximum[/C][C]613[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=35000&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=35000&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
# observations60
minimum431
Q1469.25
median509
mean510.083333333333
Q3544.75
maximum613


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)
grid()
dev.off()
if (par2 > 0)
{
bitmap(file='lagplot.png')
dum <- cbind(lag(x,k=1),x)
dum
dum1 <- dum[2:length(x),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Lag plot, lowess, and regression line'))
lines(lowess(z))
abline(lm(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')