Discrete Probability

Discrete Probability
Set theory; discrete probability; conditional probability; finite sample spaces; discrete random variables (pdf, cdf, moments).
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesSTAT 121; or STAT 151; or STAT 201; or Stat 301.
 TaughtFall, Winter, Summer
 ProgramsContaining STAT 240
Course Outcomes

Set Theory and Basic Set Operations

Apply fundamentals of set theory and basic set operations

Discrete Sample Space

Enumerate a discrete sample space with counting techniques

Bayes Theorem

Solve problems using axioms of probability, conditional probability, independence, and Bayes theorem

Random Variables

Solve problems with the pdf, cdf, moments of discrete univariate random variables

Discrete Distributions

Understand the assumptions and properties of the named discrete distributions (Bernoulli, binomial, Poisson, geometric)

Maximum Likelihood

Solve for the maximum likelihood estimator

Sampling Distribution

Derive the sampling distribution for the proportion for SRS with and without replacement

Solve Problems

Solve problems with the pdf, cdf, qf, moments of continuous distributions