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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 computationTue, 20 Oct 2009 15:51:28 -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/2009/Oct/20/t12560755324onat1a8ec5qyx9.htm/, Retrieved Thu, 02 May 2024 21:00:38 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=49211, Retrieved Thu, 02 May 2024 21:00:38 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact132
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Bivariate Data Series] [Bivariate dataset] [2008-01-05 23:51:08] [74be16979710d4c4e7c6647856088456]
F RMPD  [Univariate Explorative Data Analysis] [Colombia Coffee] [2008-01-07 14:21:11] [74be16979710d4c4e7c6647856088456]
F RMPD    [Univariate Data Series] [] [2009-10-14 08:30:28] [74be16979710d4c4e7c6647856088456]
- RMPD      [Univariate Explorative Data Analysis] [Workshop3 - histo...] [2009-10-20 19:05:41] [df6326eec97a6ca984a853b142930499]
-   PD          [Univariate Explorative Data Analysis] [workshop 3 vraag ...] [2009-10-20 21:51:28] [0cc924834281808eda7297686c82928f] [Current]
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Dataseries X:
0.355911391
0.192295904
0.272267288
0.258689189
0.18567135
0.373877063
0.34691589
0.359880227
0.286165509
0.414310922
0.482794147
0.317571037
0.346366101
-0.13487635
-0.187377539
0.285965011
-0.081923433
0.165051707
-0.012919634
0.139960994
0.073744737
0.121091076
0.028232563
0.206453634
0.257216569
0.065350838
0.05924699
-0.052759239
0.047943153
0.029757832
0.10780113
0.084875467
-0.067866223
-0.050792543
-0.160144441
-0.169203507
0.148743398
-0.082307667
-0.127673304
-0.01080757
-0.315287757
0.042567136
0.005232124
-0.170879984
-0.044496029
-0.112199933
-0.150843154
-0.252805389
0.004218806
-0.105782565
-0.155260875
-0.063622103
-0.171783206
-0.045750814
-0.108936836
-0.101035287
-0.264863038
-0.106527791
-0.128082303
-0.208906985
-0.15472301
-0.107099467
-0.290272108
0.076359113
-0.233991104
-0.127904111
-0.137345117
-0.146830587
-0.153801771
-0.039895855
-0.332238711
-0.158714763
0.002967834
-0.001027051
-0.010295419
0.034237962
-0.159297351
-0.158707613
0.110832302
-0.003154811
-0.021356073
0.112124864
0.044872239
0.017477842
0.10245901
0.098946073
-0.206535883
-0.006024052
-0.219470394
0.057492629
0.132658623
0.014386318
0.277202467
-0.051526973
0.058962934
-0.099306341
0.197363426
-0.1163449
0.136960891
-0.084933941
-0.005866992
-0.031379518
0.098016068
0.009935834
0.049865297
0.194801823
0.067147354
-0.078575054
0.0080191
0.001027051
-0.015792757
0.025921638
-0.041486393
0.07401796
0.059698617
-0.019134923
-0.008463373
0.14716635
0.122507323
0.052540291




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135

\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 & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49211&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]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ 72.249.127.135[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49211&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49211&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 time2 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations120
minimum-0.332238711
Q1-0.10755880925
median0
mean0.0132077208416667
Q30.10379454
maximum0.482794147

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 120 \tabularnewline
minimum & -0.332238711 \tabularnewline
Q1 & -0.10755880925 \tabularnewline
median & 0 \tabularnewline
mean & 0.0132077208416667 \tabularnewline
Q3 & 0.10379454 \tabularnewline
maximum & 0.482794147 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=49211&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]120[/C][/ROW]
[ROW][C]minimum[/C][C]-0.332238711[/C][/ROW]
[ROW][C]Q1[/C][C]-0.10755880925[/C][/ROW]
[ROW][C]median[/C][C]0[/C][/ROW]
[ROW][C]mean[/C][C]0.0132077208416667[/C][/ROW]
[ROW][C]Q3[/C][C]0.10379454[/C][/ROW]
[ROW][C]maximum[/C][C]0.482794147[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=49211&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=49211&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
# observations120
minimum-0.332238711
Q1-0.10755880925
median0
mean0.0132077208416667
Q30.10379454
maximum0.482794147



Parameters (Session):
par1 = 500 ; par2 = 12 ;
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')