Probability

Exercise 1. A geneticist is studying two genes. Each gene can be either dominant or recessive. A collection of 100 individuals is categorized and found to have 58 individuals with both genes dominant, 6 individuals with both genes recessive and a total of 70 Gene 2 dominant individuals.

  1. Create a 2-way table (like the one below) to organize the counts of individuals within each of the 4 combinations of dominant and recessive for the two genes.
X Gene 2 Dominant Gene 2 Recessive Total
Gene 1 Dominant 58 24 82
Gene 1 Recessive 12 6 18
Total 70 30 100
  1. What is the probability that a randomly sampled individual from this group has Gene 1 dominant?
  1. What is the probability that a randomly sampled individual from this group has Gene 1 or Gene 2 dominant?
  1. What is the probability that in a random sample of 3 individuals from this group (without replacement), at least one of the three has both recessive genes?
  1. What is the probability that a randomly sampled individual from this group has Gene 2 dominant, given we know they have Gene 1 dominant?
  1. The genes are said to be in linkage equilibrium if the event that Gene 1 is dominant is independent of the event that Gene 2 is dominant. Are these genes in linkage equilibrium in this group of 100 individuals?
  1. Now suppose in a different group of 100 individuals, 6 individuals have both genes recessive and a total of 70 Gene 2 dominant individuals. How many individuals would have both genes dominant if the event: Gene 1 is dominant is independent of the event: Gene 2 is dominant in this group of 100 individuals? Make sure to show how you calculated your answer.
X Gene 2 Dominant Gene 2 Recessive Total
Gene 1 Dominant 49 24 73
Gene 1 Recessive 21 6 27
Total 70 30 100

Exercise 2. Prevention after acute myocardial infarction (AMI) is primarily managed through medications. A large cohort study of post-AMI patients >65 years old found only 74% of patients filled all their discharge prescriptions within 120 days after discharge.

A physician at UW has 4 post-AMI patients >65 yo and will use \(\pi = 0.74\) for the probability for each of his patients individually filling all of their discharge prescriptions within 120 days. Define a random variable F, the count of the patients out of four who fill all their discharge prescriptions within 120 days. Assume that the filling of prescription behavior is independent between the 4 patients and that \(\pi=0.74\).

  1. Determine the probability function for F (write out the pmf) using probability theory.
dbinom(0,4,0.74)
## [1] 0.00456976
dbinom(1,4,0.74)
## [1] 0.05202496
dbinom(2,4,0.74)
## [1] 0.2221066
dbinom(3,4,0.74)
## [1] 0.421433
dbinom(4,4,0.74)
## [1] 0.2998658
dbinom(15,20,0.74)
## [1] 0.2012734
dbinom(15:20,20,0.74,)
## [1] 0.201273359 0.179017171 0.119884802 0.056868432 0.017037506 0.002424568
0.201273359+0.179017171+0.119884802+0.056868432+0.017037506+0.002424568
## [1] 0.5765058
  1. Compute the probability that F > 0. What does this value mean in the context of the scenerio?
  1. What is the expected value for F, \(\mu_F\)? What does that value mean in the context of the scenerio?
  1. What is the standard deviation for F, \(\sigma_F\)?
  1. Suppose this physician now has 20 post-AMI patients >65 years and wants to use a binomial model (\(n = 20, \pi=0.74\)) to describe the number of those 20 patients who will get all discharge prescriptions filled within 120 days.
  1. What the the probability that exactly 15 of those 20 patients get all discharge prescriptions filled within 120 days? (You can use R).
  1. What the the probability that 15 or more of those 20 patients get all discharge prescriptions filled within 120 days? (You can use R).
  1. Which histogram given below correctly shows the pdf for the binomial model described in (e)?

Exercise 3. For each of the following questions, say whether the random variable is reasonably approximated by a binomial random variable or not, and explain your answer. Comment on the reasonableness of each of things that must be true for a variable to be a binomial random variable (ex: identify \(n\) the number of trials, \(\pi\) the probability of success, etc).

  1. A fair die is rolled until a 1 appears, and X denotes the number of rolls.
  1. Twenty of the different Badger basketball players each attempt 1 free throw and X is the total number of successful attempts.
  1. A die is rolled 50 times. Let X be the face that lands up.
  1. In a bag of 10 batteries, I know 2 are old. Let X be the number of old batteries I choose when taking a sample of 4 to put into my calculator.
  1. It is reported that 20% of Madison homeowners have installed a home security system. Let X be the number of homes without home security systems installed in a random sample of 100 houses in the Madison city limits.