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Data X:
1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 0 1 0 0 1 1 0 1 1 1 1 1 0 1 0 1 0 1 0 1 0 1 0 1 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 0 1 0 1 1 1 1 1 0 0 1 1 1 1 0 0 1 0 1 1 1 1 0 1 1 1 0 1 0 1 0 1 1 1 1 1 0 0 1 0 1 0 1 0 1 0 1 0 1 0 1 1 0 1 0 0 1 1 0 1 1 1 1 1 0 1 0 1 0 1 1 1 1 1 0 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 1 0 1 1 1 1 0 0 1 0 1 1 0 1 1 1 0 1 0 1 1 1 0 1 0 1 1 1 0 0 1 1 0 1 0 1 1 1 0 1 0 1 0 0 1 1 0 0 1 1 0 0 1 1 1 1 0 0 1 1 0 0 1 0 1 0 1 0 1 1 0 0 1 0 1 0 1 0 1 0 1 0 1 1 0 0 1 0 1 0 1 0 1 1 1 0 1 0 1 0 1 1 0 1 0 1 0 0 1 0 1 1 1 1 1 0 1 1 1 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 1 0 0 0 1 0 1 0 0 1 0 1
Names of X columns:
groupB spssC
Sample Range:
(leave blank to include all observations)
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To:
Color
020020 20pearsongrey11grey1 1pearsongrey
grey
white
blue
red
black
brown
yellow
Omit all rows with missing values?
grey05no22Do not include Seasonal DummiesDo not include Seasonal DummiesDo not include Seasonal Dummiesnono
no
yes
Chart options
Title:
Label y-axis:
Label x-axis:
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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Big Analytics Cloud Computing Center
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