R code help

5. Matching the sample and theoretical densities.

Finally, let's see how well your random sample matches the theoretical density. A histogram of your sample (with green bars and density scaling)

n<-100000 count<-0 x<-rnorm(n,16.1,0.5) for(i in 1:n){ if(x[i]>=16 && x[i]<=16.5) count=count+1 } count/n simNorm<-quantile(x,0.10) hist(simNorm, probability=TRUE, col="green")

Now add the normal pdf on top. Range is plus/minus 4 stadnard deviations around mean.

xValues<- seq(16.1 - 4*.5, 16.1 + 4*.5, length.out=250) pdf<- dnorm(xValues, mean=16.1, sd=.5) lines(xValues, pdf, col="grey",lwd=2 ) # grey line twice the width

Comment on how well your sample histogram tracks the density curve. Where does it do well? What does it miss?