This problem set will give you practice in solving problems relating to probability learned in this module. Problems will be similar to those you will face on the quiz in Module Four and will include one or two real-world applications to prepare you to think like a biostatistician.

Check the videos in the module resource list to see which ones will help with this assignment.

To complete this assignment, review the Module Three Problem Set document.

SNHU logo

# IHP 525 Module Three Problem Set

1. A patient newly diagnosed with a serious ailment is told he has a 60% probability of surviving 5 or more years. Let us assume this statement is accurate. Explain the meaning of this statement to someone with no statistical background in terms he or she will understand.

2. Suppose a population has 26 members identified with the letters A through Z.

a) You select one individual at random from this population. What is the probability of selecting individual A?

b) Assume person A gets selected on an initial draw, you replace person A into the sampling frame, and then take a second random draw. What is the probability of drawing person A on the second draw?

c) Assume person A gets selected on the initial draw and you sample again without replacement. What is the probability of drawing person G on the second draw?

3. Let A represent cat ownership and B represent dog ownership. Suppose 35% of households in a population own cats, 30% own dogs, and 15% own both a cat and a dog. Suppose you know that a household owns a cat. What is the probability that it also owns a dog?

4. What is the complement of an event?

5. Suppose there were 4,065,014 births in a given year. Of those births, 2,081,287 were boys and 1,983,727 were girls.

a) If we randomly select two women from the population who then become pregnant, what is the probability both children will be boys?

b) If we randomly select two women from the population who then become pregnant, what is the probability that at least one child is a boy?

6. Explain the difference between mutually exclusive and independent events.