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Data:
11.3116987179485 -1.00889071552047 -1.42606308906556 -1.20082430164484 -1.13303474573854 -1.58572156572882 -2.46418875530776 1.17590481771663 3.53466591323945 -3.58253526447356 -0.398631810933239 -15.6702267661356 -9.3194876182356 -1.66019387003109 1.55440755736015 -3.46367380095364 8.60218910821777 -1.46271056978173 -0.968271479589475 -7.75823957181171 -7.68256732327245 -7.66157998368169 -1.08314350787782 -4.80513835565023 -5.73130584492895 -2.17251944312579 6.14077786113126 5.32698317194513 12.2371530603986 4.75896085850928 8.80344990651213 -2.71575802762999 9.8445390593829 4.10059023344525 3.12014208591802 -0.0427160275510232 1.1774803365181 -6.44203321730345 5.44762391330005 -5.42152305415925 -0.097739392550011 22.0995692330761 -2.22119294502284 -3.95596241683825 6.84055573106752 3.63784064819242 -1.42135822955174 9.96276178085679 2.37465258229315 6.57990062625458 -17.9685138848948 -5.27602337281564 5.51460510459697 5.12460682087271 -17.0957752394993 -3.98516718373071 -0.0309461987523036 -3.74152523605596 9.38166111671853 0.280950320516922 0.026613573941745 -6.7159370859431 -17.1148636640841 -3.07930396511279 4.60102914911715 7.88124474931192 -6.05726672070853 3.62555894946672 -3.16779712625123 -2.6180851374146 10.5053362718456 3.71120020372666 1.51533411817161 -19.1463664304302 -17.3843660879422 -10.1223765564957 8.57341772548091 7.28700038621696 -0.724917385116555 5.99530215446396 0.746625734670829 -1.66776469797401 0.285058126660374 -0.415549716361284 6.09892544469881 -3.44044800395227 -11.7537905523661 -4.35810517835762 -4.26505703679572 7.44153442416825 1.71366438141206 -3.75236354196898 3.42833530062683 1.25270139254746 1.49932483833993 5.68164735911103 -1.86154176779678
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R Code
library(Hmisc) m <- mean(x) e <- median(x) bitmap(file='test1.png') op <- par(mfrow=c(2,1)) mydensity1 <- density(x,kernel='gaussian',na.rm=TRUE) plot(mydensity1,main='Density Plot - Gaussian Kernel',xlab='Median (0 -> full line) | Mean (0 -> dashed line)',ylab='density') abline(v=e,lty=1) abline(v=m,lty=5) grid() myseq <- seq(0.01, 0.99, 0.01) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) plot(myseq,hd,col=2,main='Harrell-Davis Quantiles',xlab='quantiles',ylab='Median (0 -> full) | Mean (0 -> dashed)') abline(h=m,lty=5) abline(h=e,lty=1) grid() par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Median versus Mean',2,TRUE) 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,'median',header=TRUE) a<-table.element(a,median(x)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab')
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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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