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Data:
21 15 18 11 8 19 4 20 16 14 10 13 14 8 23 11 9 24 5 15 5 19 6 13 11 17 17 5 9 15 17 17 20 12 7 16 7 14 24 15 15 10 14 18 12 9 9 8 18 10 17 14 16 10 19 10 14 10 4 19 9 12 16 11 18 11 24 17 18 9 19 18 12 23 22 14 14 16 23 7 10 12 12 12 17 21 16 11 14 13 9 19 13 19 13 13 13 14 12 22 11 5 18 19 14 15 12 19 15 17 8 10 12 12 20 12 12 14 6 10 18 18 7 18 9 17 22 11 15 17 15 22 9 13 20 14 14 12 20 20 8 17 9 18 22 10 13 15 18 18 12 12 20 12 16 16 18 16 13 17 13 17


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Number of bins (leave empty to use default) (?)


Colour


Bins are closed on right side


Scale of data


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R Code
par1 <- as.numeric(par1) if (par3 == 'TRUE') par3 <- TRUE if (par3 == 'FALSE') par3 <- FALSE if (par4 == 'Unknown') par1 <- as.numeric(par1) if (par4 == 'Interval/Ratio') par1 <- as.numeric(par1) if (par4 == '3-point Likert') par1 <- c(1:3 - 0.5, 3.5) if (par4 == '4-point Likert') par1 <- c(1:4 - 0.5, 4.5) if (par4 == '5-point Likert') par1 <- c(1:5 - 0.5, 5.5) if (par4 == '6-point Likert') par1 <- c(1:6 - 0.5, 6.5) if (par4 == '7-point Likert') par1 <- c(1:7 - 0.5, 7.5) if (par4 == '8-point Likert') par1 <- c(1:8 - 0.5, 8.5) if (par4 == '9-point Likert') par1 <- c(1:9 - 0.5, 9.5) if (par4 == '10-point Likert') par1 <- c(1:10 - 0.5, 10.5) bitmap(file='test1.png') if(is.numeric(x[1])) { if (is.na(par1)) { myhist<-hist(x,col=par2,main=main,xlab=xlab,right=par3) } else { if (par1 < 0) par1 <- 3 if (par1 > 50) par1 <- 50 myhist<-hist(x,breaks=par1,col=par2,main=main,xlab=xlab,right=par3) } } else { plot(mytab <- table(x),col=par2,main='Frequency Plot',xlab=xlab,ylab='Absolute Frequency') } dev.off() if(is.numeric(x[1])) { myhist n <- length(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/histogram.htm','Frequency Table (Histogram)',''),6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Bins',header=TRUE) a<-table.element(a,'Midpoint',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.element(a,'Cumul. Rel. Freq.',header=TRUE) a<-table.element(a,'Density',header=TRUE) a<-table.row.end(a) crf <- 0 if (par3 == FALSE) mybracket <- '[' else mybracket <- ']' mynumrows <- (length(myhist$breaks)-1) for (i in 1:mynumrows) { a<-table.row.start(a) if (i == 1) dum <- paste('[',myhist$breaks[i],sep='') else dum <- paste(mybracket,myhist$breaks[i],sep='') dum <- paste(dum,myhist$breaks[i+1],sep=',') if (i==mynumrows) dum <- paste(dum,']',sep='') else dum <- paste(dum,mybracket,sep='') a<-table.element(a,dum,header=TRUE) a<-table.element(a,myhist$mids[i]) a<-table.element(a,myhist$counts[i]) rf <- myhist$counts[i]/n crf <- crf + rf a<-table.element(a,round(rf,6)) a<-table.element(a,round(crf,6)) a<-table.element(a,round(myhist$density[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') } else { mytab reltab <- mytab / sum(mytab) n <- length(mytab) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Frequency Table (Categorical Data)',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Category',header=TRUE) a<-table.element(a,'Abs. Frequency',header=TRUE) a<-table.element(a,'Rel. Frequency',header=TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,labels(mytab)$x[i],header=TRUE) a<-table.element(a,mytab[i]) a<-table.element(a,round(reltab[i],4)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') }

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	0 seconds
R Server	Big Analytics Cloud Computing Center