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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, 24 Dec 2010 09:39:16 +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/24/t1293183482uvgaxdi1i2yxhta.htm/, Retrieved Tue, 30 Apr 2024 01:25:54 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=114664, Retrieved Tue, 30 Apr 2024 01:25:54 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact145
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Univariate Explorative Data Analysis] [univariate EDA na...] [2010-12-24 09:39:16] [27f38de572a508a633f0ad2411de6a3e] [Current]
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Dataseries X:
0.217499822516866
-9.78478953094158
-4.69092289728636
10.8303737739891
17.4025635868567
-18.695949344517
-1.45165150662704
24.2055636204555
-7.85142459641661
-9.4984274601968
15.4524605741829
-4.57316796503045
-35.3790647494429
-1.71841266886546
16.4887231604473
12.3672525241091
-30.5270631334762
14.0831320895415
12.2671755298376
7.6573009730872
-10.2588701804503
4.98218909929218
18.2374731745486
-18.1217207388952
19.2509327179740
20.7168346335646
27.0084172311441
-13.1935985382014
3.91871968362315
23.2274665865825
39.0004011190054
23.2030259046977
50.985499051697
26.9190549927636
5.61997889463015
-49.70729388275
-6.42398274476005
-41.6977425555609
-7.92694134412627
5.34208987982118
27.7759340629904
-6.52456657092852
3.12509229100933
-4.61574932357839
11.4276121576526
18.3833489895730
-42.4568062507692
7.51193809087255
-16.7513836179227
8.95264961600874
8.81854600123269
-18.5966360042492
11.7598212958319
-7.41354314708516
17.5247266754596
17.9797835233522
-36.4653940696526
4.31529911509816
8.75602862255269
7.65533116235876
-1.38678324054813




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' @ 193.190.124.24

\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' @ 193.190.124.24 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114664&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' @ 193.190.124.24[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114664&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114664&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' @ 193.190.124.24







Descriptive Statistics
# observations61
minimum-49.70729388275
Q1-7.85142459641661
median5.34208987982118
mean2.42062875682102
Q316.4887231604473
maximum50.985499051697

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 61 \tabularnewline
minimum & -49.70729388275 \tabularnewline
Q1 & -7.85142459641661 \tabularnewline
median & 5.34208987982118 \tabularnewline
mean & 2.42062875682102 \tabularnewline
Q3 & 16.4887231604473 \tabularnewline
maximum & 50.985499051697 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=114664&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]61[/C][/ROW]
[ROW][C]minimum[/C][C]-49.70729388275[/C][/ROW]
[ROW][C]Q1[/C][C]-7.85142459641661[/C][/ROW]
[ROW][C]median[/C][C]5.34208987982118[/C][/ROW]
[ROW][C]mean[/C][C]2.42062875682102[/C][/ROW]
[ROW][C]Q3[/C][C]16.4887231604473[/C][/ROW]
[ROW][C]maximum[/C][C]50.985499051697[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=114664&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=114664&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
# observations61
minimum-49.70729388275
Q1-7.85142459641661
median5.34208987982118
mean2.42062875682102
Q316.4887231604473
maximum50.985499051697



Parameters (Session):
par1 = 0 ; par2 = 12 ;
Parameters (R input):
par1 = 0 ; par2 = 12 ;
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')