Probability

Course #OA3101

Est.imated Completion Time: 3 months

Overview

Probability axioms, counting techniques, conditional probability. Discrete and continuous probability distributions: binomial, hypergeometric, negative binomial, Poisson, normal, exponential, gamma, and others. Joint probability distributions, conditional distributions and conditional expectation, linear functions. Random samples, probability plots. CO-REQUISITES: MA1118 and MA3042.

Corequisites

MA1118
MA3042

Learning Outcomes

After successfully completing this course, students will be able to:

· Identify the components that comprise a probability model, and the quantities that would need to be estimated in order to draw quantitative conclusions from the model.

· Use counting techniques to solve probability problems involving equally likely outcomes.

· Compute conditional probabilities using their definition and using Bayes’ Rule.

· Identify commonly used discrete probability distributions, articulate their underlying assumptions, and use them to compute probabilities.

· Identify commonly used continuous probability distributions, articulate their underlying assumptions, and use them to compute probabilities.

· Compute probabilities using joint probability distributions.

Offerings database access

Asset Publisher

Application Deadlines

08 Jul 2024

Fall Quarter applications due