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Write a program to carry out the following experiment. A coin is tossed 100 times and the number of heads that turn up is recorded. This experiment is then repeated 1000 times. Have your program plot a bar graph for the proportion of the 1000 experiments in which the number of heads is n, for each n in the interval [35, 65]. Does the bar graph look as though it can be fit with a normal curve?

n <- 1000
coinFace <- c("heads", "tails")
heads <- rep(0, n)
for(i in 1:n){
  trials <- sample(coinFace, size = 100, replace = TRUE)
  heads[i] <- length(which(trials == "heads" ))
}

x = rep(0, 31)
y = rep(0, 31)

for(i in 35:65){
  x[i - 34] = i
  y[i - 34] = length(which(heads == i))
}

results <- data.frame(n = x, heads = y)

ggplot(data=results, aes(x=n, y=heads)) +
  geom_bar(stat="identity", fill="steelblue") +
  labs( title="1000 Simulations of 100 Coin Tosses", x= "Heads", y = "No. of times coin face is ") +
  theme_minimal()