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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 computationSun, 25 Oct 2009 07:13:23 -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/25/t1256476461g7n3rgnz0a5g1db.htm/, Retrieved Mon, 29 Apr 2024 08:03:09 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=50310, Retrieved Mon, 29 Apr 2024 08:03:09 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact180
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]
- RMPD  [Univariate Explorative Data Analysis] [SHW_WS4_Q3] [2009-10-23 09:32:44] [8b1aef4e7013bd33fbc2a5833375c5f5]
-           [Univariate Explorative Data Analysis] [] [2009-10-25 13:13:23] [2a6f24d4847085573f343c759dfbabef] [Current]
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Dataseries X:
0.651124187
0.677462043
0.487584459
0.35573232
0.467396208
0.5847797
0.638410776
0.562504993
0.226959834
0.096608848
0.346780629
0.32212801
0.124353661
0.116113081
0.298476107
0.320797584
0.320938168
0.272939992
0.242238517
0.029850007
0.144567637
0.073595478
0.105558217
0.179094701
0.347499306
0.323095391
0.379457113
0.373362194
0.295091587
0.173059076
0.25395154
0.466386248
0.343237476
0.307402512
0.235057345
0.300157187
0.190740285
0.223666633
0.144958306
0.188004361
0.248384872
0.323674763
0.305392718
0.200707615
0.209268012
0.060984282
-0.002231387
-0.069789538
-0.059028506
-0.091004634
-0.135694478
-0.152499926
-0.366844839
-0.450497399
-0.515235087
-0.442133219
-0.514521352
-0.490012558
-0.303601016
-0.310362096
-0.01578921
-0.056493576
0.020719536
0.026208378
-0.044823852
-0.098827417
-0.034225275
-0.034225275
-0.008453333
0.213738024
0.172428731
0.242113198
0.15114142
-0.002440472
-0.306723255
-0.453671587
-0.227233275
-0.130523048
-0.047519648
-0.068848603
-0.201545891
-0.421545609
-0.333128768
-0.5438376
-1.551038145
-0.983778668
-0.662441384
-0.269523484
-0.060934863
-0.217716491
-0.651830893
-1.502188008
-0.879597713
-0.831909014
-1.225813299
-1.208658248
-0.732318801
-0.700744426
-0.473166048
-0.522039199
-0.853039535
-0.979494757
-1.108876863
-0.772168602
-0.503727917
-0.414905721
-0.25200225
-0.014582013
-0.095054366
-0.009089297
0.138738084
0.036439646
0.09359806
0.33509075
0.349531434
0.381745218
0.536301301
0.413095585
0.456051135
0.237104602
0.113336816
0.136326454
0.062846398
0.352464439
0.471155508
0.402330127
0.302224828
0.309743661
0.143310479
0.182417007
0.084235603
0.107550334
0.393103741
0.295544151
0.310972647
-0.077335332
-0.385262055
-0.798163939
-0.423084824
-0.43872323
-0.438448813
-0.414863511
-0.573976594
-0.354421361
-0.478284249
-0.114965004
-0.103481844
-0.276699126
-0.62908592
-0.185555629
-0.269043576
-0.085442224
-0.079763405
-0.21001755
-0.04659717
-0.113020436
-0.203010969
-0.435472926
-0.5442069
-0.013832988
0.293298418
0.149790454
0.214316775
0.150318618
0.043147573
0.386091161
0.2715729
0.155364229
0.151210935
0.279908767
0.457889092
0.352014075
0.257325144
0.391406149
0.481729908
0.472232849
0.488285072
0.242085404
0.281978442
0.399431551
0.305312483
0.205735682
-0.136076382
0.012342482
0.123502113
-0.034258798
-0.190092633
-0.171264219
-0.460842425
-0.468821782
-0.260515601
-0.164445256
-0.152273865
-0.087961961
-0.060005142
-0.082178379
-0.411831932
-0.403900354
-0.343582591
-0.545014941
-0.246134632
0.148529096
0.420561811
0.470669144
0.583865257
0.635121216
0.823492271
0.76770808
0.995614642
1.102989155
1.121969728
1.030205654
1.043444445
0.897900099
0.49074351
0.313599762
0.188325762
0.004373587
-1.130992438
-1.163640132




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=50310&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=50310&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50310&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
# observations220
minimum-1.551038145
Q1-0.26264759475
median0.06191534
mean-1.36363648296936e-11
Q30.30533254175
maximum1.121969728

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 220 \tabularnewline
minimum & -1.551038145 \tabularnewline
Q1 & -0.26264759475 \tabularnewline
median & 0.06191534 \tabularnewline
mean & -1.36363648296936e-11 \tabularnewline
Q3 & 0.30533254175 \tabularnewline
maximum & 1.121969728 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=50310&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]220[/C][/ROW]
[ROW][C]minimum[/C][C]-1.551038145[/C][/ROW]
[ROW][C]Q1[/C][C]-0.26264759475[/C][/ROW]
[ROW][C]median[/C][C]0.06191534[/C][/ROW]
[ROW][C]mean[/C][C]-1.36363648296936e-11[/C][/ROW]
[ROW][C]Q3[/C][C]0.30533254175[/C][/ROW]
[ROW][C]maximum[/C][C]1.121969728[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=50310&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=50310&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
# observations220
minimum-1.551038145
Q1-0.26264759475
median0.06191534
mean-1.36363648296936e-11
Q30.30533254175
maximum1.121969728



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')