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Data X:
22 13 24 16 26 17 21 NA 26 NA 25 16 21 NA 24 NA 27 NA 28 17 23 17 25 15 24 16 24 14 24 16 25 17 25 NA 25 NA 25 NA 24 16 26 NA 26 16 25 NA 26 NA 23 NA 24 16 24 15 25 16 25 16 24 13 28 15 27 17 NA NA 23 13 23 17 24 NA 24 14 22 14 25 18 25 NA 28 17 22 13 28 16 25 15 24 15 24 NA 23 15 25 13 26 17 25 NA 27 NA 26 11 23 14 25 13 21 NA 22 17 24 16 25 NA 27 17 24 16 26 16 21 16 27 15 22 12 23 17 24 14 25 14 24 16 23 NA 28 NA NA NA 24 NA 26 NA 22 15 25 16 25 14 24 15 24 17 26 NA 21 10 25 NA 25 17 26 NA 25 20 26 17 27 18 25 NA 20 14 24 NA 26 17 25 NA 25 17 24 NA 26 16 25 18 28 18 27 16 26 NA 26 15 26 13 NA NA 28 NA NA NA 21 NA 25 NA 25 16 24 NA 24 NA 24 NA 23 12 23 NA 24 16 24 16 25 NA 28 16 23 14 24 15 23 14 24 NA 25 15 24 NA 23 15 23 16 25 NA 21 NA 22 NA 19 11 24 NA 25 18 21 NA 22 11 23 NA 27 18 26 15 29 19 28 17 24 NA 25 14 25 NA 22 13 25 17 26 14 26 19 24 14 25 NA 19 NA 25 16 23 16 25 15 25 12 26 NA 27 17 24 NA 22 NA 25 18 24 15 23 18 27 15 24 NA 24 NA 21 NA 25 16 25 NA 23 16
Names of X columns:
SKEOUSUM TVDCSUM
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white
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Omit all rows with missing values?
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yes
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R Code
if(par2=='yes') { z <- na.omit(as.data.frame(t(y))) } else { z <- as.data.frame(t(y)) } bitmap(file='test1.png') (r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,col=par1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot statistics',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower whisker',1,TRUE) a<-table.element(a,'lower hinge',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper hinge',1,TRUE) a<-table.element(a,'upper whisker',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,i]) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot Notches',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower bound',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper bound',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) a<-table.element(a,r$conf[1,i]) a<-table.element(a,r$stats[3,i]) a<-table.element(a,r$conf[2,i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
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