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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, 22 Dec 2009 13:29:18 -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/2009/Dec/22/t1261513851veyhg0wegdwem4u.htm/, Retrieved Sat, 04 May 2024 18:25:33 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=70480, Retrieved Sat, 04 May 2024 18:25:33 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact108
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Univariate Explorative Data Analysis] [workshop 3] [2009-11-06 10:21:50] [3d8acb8ffdb376c5fec19e610f8198c2]
- R  D    [Univariate Explorative Data Analysis] [paper] [2009-12-22 20:29:18] [e81f30a5c3daacfe71a556c99a478849] [Current]
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Dataseries X:
-0.0554261742134966
-0.0103723682328288
-0.09774824332988
0.0682838841648196
-0.0598771056498073
-0.0115369164551084
0.0737440480162446
0.0652896783949673
0.0212699541543462
-0.00207374705171083
0.110078189837195
-0.0146254989919655
0.114698886599707
0.122494579401249
-0.093917668042089
0.317437918041701
0.0233064257137833
0.0907672748631918
0.137726863879236
0.0413595313391135
0.0478723668655492
0.0876104346350919
0.0384005884923821
0.0522380787977494
0.0585774158784047
-0.0318052895741221
-0.181701157975095
0.312417016566173
-0.161245884995846
-0.0498906070653545
0.0164895011305049
-0.106532442482812
-0.0111252289051036
-0.0112051724184589
-0.0621266808603795
-0.0194747117256815
-0.005215993087672
0.00868532947685446
0.0189643082939415
0.132126779126779
0.114222267764316
-0.0512424762283885
0.111763287181735
-0.0727789247238114
0.099056920984902
-0.0133229962434981
-0.0540901157284234
0.0131003534096119
-0.105083618822970
-0.0532746009105622
-0.152603426068890
0.169880388606489
-0.134937086209412
-0.156403695781353
0.0220625418036537
-0.122447540039379
-0.147301939947001
0.124893101691225
-0.0981932532160595
-0.0338473507167997
0.120285012723111
0.0619113501360601
-0.127397173085151
0.295513148096302
-0.00395731088007977
-0.134137032646724
0.0800913155281188
0.0420046126531497
0.061555085014176
-0.0129403767474939
0.0972860535162994
0.0877108066588468
-0.0356206200854371
0.0505485461316185
-0.131893718779630
0.343673596883514
-0.00930805173243436
-0.244200397859937
-0.054917088296814
0.0337991899193833
-0.0441366211382616
-0.0401696208416182
0.0586113053187203
-0.0362167322426645
0.0214944435265415
-0.0394242009278998
-0.219189486789616
-0.038750207606925
-0.305953588706861
-0.160680743573754
-0.129309183705573
-0.175325132712971
-0.285383831304565
-0.182559850590123
-0.224103473978491
0.0611619478196247
-0.253257239400946
-0.0667794801013696
-0.0203659156623685
0.0390230291850474
-0.362690960075248
0.0333119163149927
-0.0749260168888494
-0.310091538794336
-0.313174314082963
-0.0446943832910636
0.0884651538474875
0.148008967470383
-0.0581099037570537
-0.265335985463967
-0.142815914648150
-0.0634276688751165
0.301971033848160
0.509200438595075
-0.226853203690718
0.132746336473417
0.113478705894465
-0.0714550273266129
0.107207329251342
-0.070724916726179
-0.0351999533754058
0.0397456022551489
0.211380404750537
-0.349347916179288
0.270214046482663
0.281727228579061
0.0814427167227327
0.0585457504519322
0.131338788505694
0.0584680902381685
0.0145094042468520
0.131142061479022
-0.118748120650334
0.161971940232045
0.217140021180596
-0.36075238703227
0.112369257289203
0.177091978202189
0.0560949481137286
0.141966781350567
0.238943521016553
-0.0169617673898806
-0.217034348244890
-0.386510308927318
0.119169209082527
0.239427960434481
0.619747125797162
-0.229810610454884
0.0509120935252796
-0.212011167464921
-0.0887441758042202
0.216923527514844
-0.0205975632055718
0.047788699609204
0.031052755829211
-0.0774958020653822
0.210654616027303
-0.0984341615804984
0.232160736649630
-0.318032671100063
0.0466865439469646
-0.0217807544657625
0.0373144926595483
0.0649938009681715
0.108204156147779
0.0766226157267711
0.109937091688754
0.145533105760753
0.0217820395557200
-0.119359221276209
-0.131759892290998
-0.318234299422278
0.118288319679319
-0.0502150450132071
-0.0419800466493269
-0.0104536303122343




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 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 & 3 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ 72.249.127.135 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70480&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]3 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=70480&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70480&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 time3 seconds
R Server'Gwilym Jenkins' @ 72.249.127.135







Descriptive Statistics
# observations176
minimum-0.386510308927318
Q1-0.0803078955000917
median-0.0030155289658953
mean1.58441362933677e-18
Q30.0890406841014136
maximum0.619747125797162

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 176 \tabularnewline
minimum & -0.386510308927318 \tabularnewline
Q1 & -0.0803078955000917 \tabularnewline
median & -0.0030155289658953 \tabularnewline
mean & 1.58441362933677e-18 \tabularnewline
Q3 & 0.0890406841014136 \tabularnewline
maximum & 0.619747125797162 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=70480&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]176[/C][/ROW]
[ROW][C]minimum[/C][C]-0.386510308927318[/C][/ROW]
[ROW][C]Q1[/C][C]-0.0803078955000917[/C][/ROW]
[ROW][C]median[/C][C]-0.0030155289658953[/C][/ROW]
[ROW][C]mean[/C][C]1.58441362933677e-18[/C][/ROW]
[ROW][C]Q3[/C][C]0.0890406841014136[/C][/ROW]
[ROW][C]maximum[/C][C]0.619747125797162[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=70480&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=70480&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
# observations176
minimum-0.386510308927318
Q1-0.0803078955000917
median-0.0030155289658953
mean1.58441362933677e-18
Q30.0890406841014136
maximum0.619747125797162



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')