given seed value = 151Distribution Information: X Bin(n = 10, p = 0.21)nBerTrial is n = 10pbty is p = 0.21i also attached page 4 for the hint!

What is an example of random sampling using the Binomial Distribution? Suppose we are interested in whether a person owns a dog. We decide to perform 5 trials, and each trial has a probability of success of 0.4. We define a random variable X to be the number of people who own dogs. We then have X ~ Bin(5, 0.4). If we go out on June 1 and talk to 5 people, the number of successes on this day will be the result of one random sample. If we go out June 6 and talk to 5 more people, the number of successes on this day will be the result of our second random sample. If we do this process on 50 days, we will have obtained the number of successes from 50 random samples. Task (C 7) Do something similar for your particular Binomial Distribution. Use parameters nBerTrial and pbty from Part 1. Do NOT change them to be something else. Obtain data from 53 random samples. You will use a particular R procedure to perform your sampling (hint: see page 4 of this project). Do this sampling with the given seed value. Save your result as sample_values. Note: You must run set . seed() right before you generate your random values from the specified Binomial Distribution. 21 A