stat

n <- 16;
data <- c(1.80, 1.86, 1.76, 1.69, 1.65, 2.12, 1.66, 1.79, 1.90, 2.06, 2.19, 1.64, 1.57, 2.10, 2.24, 1.91)

alpha = 0.05;

l <- mean(data) - sd(data)/sqrt(length(data)) * qt(1- alpha/2, length(data) - 1)
u <- mean(data) + sd(data)/sqrt(length(data)) * qt(1- alpha/2, length(data) - 1)
rm
t.test(data)$conf.int
sample(data, n, replace = T)

B<-1000
meanB<-numeric(B)
for(i in 1:B) {
  meanB[i]<-mean(sample(data, n, replace = T))
}


q<-quantile(meanB, c(0.025, 0.975))