Page 73 - FINAL CFA SLIDES DECEMBER 2018 DAY 3

LOS 10.e: Define a Discrete Uniform Session Unit 3:
Random Variable, a Bernoulli random 10. Common Probability Distributions
variable, and a binomial random variable..

LOS 10.f: Calculate and interpret probabilities given the discrete uniform and the binomial DF

The binomial probability function (bpf) defines the probability of x successes in n trials, p.218:

p(x) = P(X = x) = (number of ways to choose x from n)px(1 – p)n–x

Example: p.218: Assuming a binomial distribution, compute the p. of drawing 3 Black Beans from a bowl
of Black and White beans if the p. of selecting a Black bean = 60%. You will draw 5 Beans from the bowl.

Note that the definition of success is critical to any binomial problem.

C. Success = having a fax machine. [6! / 4!(6 – 4)!](0.6)4(0.4)6 – 4 = 15(0.1296)(0.16) = 0.311.

A. Success = staying for five years. [6! / 2!(6 – 2)!](0.10)2(0.90)6 – 2 = 15(0.01)(0.656) = 0.0984.