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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, 18 Dec 2011 09:28:16 -0500
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2011/Dec/18/t1324218553mi7p13e9dqjsfje.htm/, Retrieved Tue, 30 Apr 2024 01:29:58 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=156898, Retrieved Tue, 30 Apr 2024 01:29:58 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact119
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Multiple Regression] [Q1 The Seatbeltlaw] [2007-11-14 19:27:43] [8cd6641b921d30ebe00b648d1481bba0]
- RMPD  [Multiple Regression] [Seatbelt] [2009-11-12 13:54:52] [b98453cac15ba1066b407e146608df68]
-    D    [Multiple Regression] [WS7] [2009-11-18 17:01:04] [8b1aef4e7013bd33fbc2a5833375c5f5]
-   PD      [Multiple Regression] [WS7(2)] [2009-11-20 19:01:46] [7d268329e554b8694908ba13e6e6f258]
-   P         [Multiple Regression] [WS7(3)] [2009-11-21 10:22:47] [7d268329e554b8694908ba13e6e6f258]
-   PD          [Multiple Regression] [WS7(4)] [2009-11-21 10:55:20] [7d268329e554b8694908ba13e6e6f258]
- RMPD            [Univariate Data Series] [Niet-werkende wer...] [2009-11-25 19:16:52] [9717cb857c153ca3061376906953b329]
- RMP               [Univariate Explorative Data Analysis] [Univariate EDA] [2009-12-17 13:35:10] [9717cb857c153ca3061376906953b329]
-   PD                [Univariate Explorative Data Analysis] [Paper tijdreeks] [2011-12-16 15:35:08] [fbaf17a8836493f6de0f4e0e997711e1]
-   PD                  [Univariate Explorative Data Analysis] [Paper wijn] [2011-12-17 10:19:24] [fbaf17a8836493f6de0f4e0e997711e1]
- R PD                      [Univariate Explorative Data Analysis] [paper lag] [2011-12-18 14:28:16] [c897fb90cb9e1f725365d7e541ad7850] [Current]
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Dataseries X:
1.59637178246389e-05
-0.000528928079830371
-0.000379615335598625
0.00038524930093652
-0.00119668551397731
-0.00135467218692709
0.000629204239684938
-0.00125782493336941
-0.000715822604743877
-0.00145775397311118
0.00090586820257419
0.00081580291364592
0.000311413531980795
-0.00166616600916562
0.000335811392412256
0.000261623629287684
0.000112788631495469
-0.000465906882130304
-0.000402731982307803
-0.000529094285263005
0.0014484448842795
0.000173569797634477
0.000552904228538073
0.000540233381156932
0.000346921157112578
4.18534624111872e-05
0.000121673297196368
0.000152183353954878
0.000825672173592282
-0.000595892572118315
-0.0016596119546966
0.000881541979379421
-4.41549707230917e-05
0.000682300411395417
0.000854926176340672
-2.69238953622488e-05
0.000638044232975447
-0.000725889945687845
0.000425651240142468
0.00122388400385043
0.000372111611587248
-0.000932593775979713
0.00270510236012386
-7.86119270261397e-06
-0.000838903060403654
-0.00145322482097055
-0.000354536131935043
-0.000296075166764825
-0.000872298503414093
-0.000202893391347205
-0.000573032019690722
0.000283735480154173
-0.000962625097356925
-0.00257385715733466
0.000426805793820473
0.000486954349901254
0.000874136216786315
0.000529738734414838
0.000201257333054092
0.000968867197645315
-0.000157999749148343
-0.000391913356849448
0.0013234746686754
0.00157132368881926
0.000930560870053533
0.00139732391835725
0.000208947115718179
-0.00113966366994638
-0.000914229750354053
-0.000736236352959105
-0.000223780890036181
-0.000260017472186879
-0.000501037085654342
0.00102364951971444
-0.000354192095527308
0.000436463070874258
-0.00128264495060518
0.000491537956533721
-0.00058619492218505
-0.000736939522420208
0.00243816619015008
-0.00142180529586032
-0.00172730814501807
-0.00044083993783304
0.000219270293872929
0.000842857048790155
-0.00237840593168783
0.00014596557065336
0.00117948835793293
0.000329910805631347
0.000226648388377267
-0.00225979467020417
0.000328714382267304
-0.00163686721236423
-0.000191963911771234
-0.000411017424866446
0.000189438721984894
-0.00047832067303762
-1.33068681664467e-05
-0.00120487658809949
-0.000117105368110721
-8.66472262888335e-05
0.000499094461743711
0.00110098299004875
0.00190445867852853
-0.000253274519399314
-7.60427443683426e-05
-0.000257702457573011
-0.00135377245040492
-0.000262263188216794
0.000234369470566086
-0.000783049820634563
-0.000334352481417933
-0.000289677370045081
0.000304824512672808
0.000931577483137732
0.000448460660641138
-7.26094160660303e-05
0.000473142309587238
0.000559454250190315
-7.63680598443844e-05
0.0013155970723939
-0.0014088028705035
0.00080851663739419
0.00176584583722224
0.00114804274728237
-0.00137239739903595
-0.00142887150666404
0.000185555789291147
0.00033925084186637
-0.000111514181852716
0.000480812660515161
-0.000283313402830277
0.000531496360231672
-0.000143961813116484
-0.00121208620240699
-0.000973929770486086
-0.000115373815292925
0.0011199351601504
0.000216136666647929
0.000924239251654146
-0.000165416914692014
0.000151034288287409
-0.000305700504023248
-0.000346757256775254
0.00125379190755259
-0.00105801604376631
-6.71545817948968e-05
-0.00236496708859359
-9.75528703918148e-05
0.000570675622210595
0.000212357650356478
-0.00253695562425985
0.00209663613695227
-6.68604989478825e-05
0.000227606989053541
-0.000624544690875265
0.000266585831246069
-0.00130368062730513
-0.000599433785139688
-0.00101040388726545
0.000268183766744966
-0.00106087009948214
0.000237148554211627
0.000843003314494451
-0.00139130766025808
-0.000734060336315938
-0.000348323438856801
0.000252766813746514
0.000478905852301054
-0.000423978250784498
-0.000412298371434793
-0.000718029042657409
-0.000957329534311428
-0.00171363677882115
0.000244167682494328




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time3 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\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' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156898&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' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156898&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156898&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' @ jenkins.wessa.net







Descriptive Statistics
# observations176
minimum-0.00257385715733466
Q1-0.000605711511573582
median-6.70075403713896e-05
mean-8.88334581471105e-05
Q30.000474583195265692
maximum0.00270510236012386

\begin{tabular}{lllllllll}
\hline
Descriptive Statistics \tabularnewline
# observations & 176 \tabularnewline
minimum & -0.00257385715733466 \tabularnewline
Q1 & -0.000605711511573582 \tabularnewline
median & -6.70075403713896e-05 \tabularnewline
mean & -8.88334581471105e-05 \tabularnewline
Q3 & 0.000474583195265692 \tabularnewline
maximum & 0.00270510236012386 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=156898&T=1

[TABLE]
[ROW][C]Descriptive Statistics[/C][/ROW]
[ROW][C]# observations[/C][C]176[/C][/ROW]
[ROW][C]minimum[/C][C]-0.00257385715733466[/C][/ROW]
[ROW][C]Q1[/C][C]-0.000605711511573582[/C][/ROW]
[ROW][C]median[/C][C]-6.70075403713896e-05[/C][/ROW]
[ROW][C]mean[/C][C]-8.88334581471105e-05[/C][/ROW]
[ROW][C]Q3[/C][C]0.000474583195265692[/C][/ROW]
[ROW][C]maximum[/C][C]0.00270510236012386[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=156898&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=156898&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-0.00257385715733466
Q1-0.000605711511573582
median-6.70075403713896e-05
mean-8.88334581471105e-05
Q30.000474583195265692
maximum0.00270510236012386



Parameters (Session):
par1 = FALSE ; par2 = -0.5 ; par3 = 0 ; par4 = 1 ; par5 = 1 ; par6 = 3 ; par7 = 1 ; par8 = 0 ; par9 = 1 ;
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')