Suppose an institution (say a large firm?) implements random drug testing among a large population (let's say 10,000 people). It is known that 8% of the population uses one of the drugs being screened. Suppose the test gives a true positive 95% of the time, and a true negative 90% of the time. (a) First, use a tree diagram like the one shown in class to estimate the number of true/false positivesegatives. (b) Using the info from this diagram, what is the probability that a randomly selected person is a user given a positive test result? (c) Now, using the formula for Baye's rule, calculate the true probability (given only this evidence) that a randomly selected person has used one of the drugs being screened for given a positive test result? Note that this problem involves different rates of true/false positives