newf.1<-function(n, mu=0, stdev=1, nsamps=500){
ns<-nsamps
simdat<-numeric(n)
nsvar<-numeric(ns)
ss1<-numeric(ns)
for(i in 1:ns){
simdat<-rnorm(n, mean=mu, sd=stdev)
nsvar[i]<-var(simdat)}
ss1<-(n-1)*nsvar/(stdev^2)
return(ss1)}





newf.2<-function(n, mu=0, stdev=1, nsamps=500){
ns<-nsamps
simdat<-numeric(n)
xbar<-numeric(ns)
med<-numeric(ns)
for(i in 1:ns){
simdat<-rnorm(n, mean=mu, sd=stdev)
xbar[i]<-mean(simdat)
med[i]<-median(simdat)}
ss2<-data.frame(xbar, med)
return(ss2)}




newf.3<-function(n, lambda=10, nsamps=500){
ns<-nsamps
simdat<-numeric(n)
xbar<-numeric(ns)
med<-numeric(ns)
xvar<-numeric(ns)
for(i in 1:ns){
simdat<-rpois(n, lambda=lambda)
xbar[i]<-mean(simdat)
med[i]<-median(simdat)
xvar[i]<-var(simdat)}
ss3<-data.frame(xbar, med, xvar)
return(ss3)}



newf.4<-function(n, p, nsamps=500){
ns<-nsamps
simdat<-numeric(n)
ss4<-numeric(ns)
for(i in 1:ns){
simdat<-rbinom(n=n, size=1, prob=p)
ss4[i]<-sum(simdat)/n}
return(ss4)}