#Problem 2
#Part 2
B=1000
sample_med_vars=numeric()
CIs = character()
n_values = c(10,100,1000)
for (i in 1:3) {
sample_meds=replicate(B, median(rnorm(n_values[i],1, 1)))
sample_med_vars[i] = var(sample_meds)
CIs[i] = paste(mean(sample_meds)-1.96*sd(sample_meds),
mean(sample_meds)+1.96*sd(sample_meds))
}
sample_med_vars #0.132826885 0.015370697 0.001603544
CIs (“0.265111943430679 1.69377252141066”) #n=10
(“0.757126210069845 1.24312238725003”) #n=100
(“0.922210181934582 1.07918375732663”) #n=1000
#Part 3
theoretical_vars=numeric()
n_values=c(10,100,1000)
for (i in 1:3){
var_samplemed= (pi*(1)^2)/(2*n_values[i])
