CODEWITHSUNDEEP
r
user1629075
user1629075

Reputation: 119

Creating a histogram from iterations of a binomial distribution in R

Here are the instructions: Create 10,000 iterations (N = 10,000) of rbinom(50,1, 0.5) with n = 50 and your guess of p0 = 0.50 (hint: you will need to construct a for loop). Plot a histogram of the results of the sample. Then plot your pstar on the histogram. If pstar is not in the extreme region of the histogram, you would assume your guess is correct and vice versa. Finally calculate the probability that p0 < pstar (this is a p value).

I know how to create the for loop and the rbinom function, but am unsure on how transfer this information to plotting on a histogram, in addition to plotting a custom point (my guess value).

Upvotes: 0

Views: 2029

Answers (1)

Maurits Evers
Maurits Evers

Reputation: 50668

I'm not doing your homework for you, but this should get you started. You don't say what pstar is supposed to be, so I am assuming you are interested in the (distribution of the) maximum likelihood estimates for p.

You create 10,000 N=50 binomial samples (there is no need for a for loop):

sample <- lapply(seq(10^5), function(x) rbinom(50, 1, 0.5))

The ML estimates for p are then

phat <- sapply(sample, function(x) sum(x == 1) / length(x))

Inspect the distribution

require(ggplot)
ggplot(data.frame(phat = phat), aes(phat)) + geom_histogram(bins = 30)

and calculate the probability that p0 < phat.

Edit 1 If you insist, you can also use a for loop to generate your samples.

sample <- list();
for (i in 1:10^5) {
    sample[[i]] <- rbinom(50, 1, 0.5);
}

Upvotes: 1

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