ICS 471: Probability, Statistics, and Queuing

Description: A hands-on introduction to probability, statistical inference, regression, Markov chains, queuing theory. Use of an interactive statistical graphics environment such as R.

Objectives

• Students understand basic probability theory
• Students understand basic statistical inference
• Students can model problems using probability and statistical tools

Course Learning Outcomes: See course objectives.

Program Learning Outcomes

• a. Students can apply knowledge of computing and mathematics appropriate to the discipline
• j. An ability to use and apply current technical concepts and practices in the core information technologies. [BA IT only]

Prerequisites: 241 and 311, or consent.

Textbook(s): An Introduction to Stochastic Modeling (3rd edition). Howard M. Taylor and Samuel Karlin. Academic Press. isbn 0-12-684887-4.

Grading

• Homeworks Assignments (50%)
• Midterm Exam (25%)
• Final Exam (25%)

Schedule: Week 1: Introduction and Math refresher Week 2-3: Probability theory Week 4-5: Basic statistics Week 6-7: Bayesian reasoning Week 8-10: Linear regression, regularization, ridge regression, LASSO Week 11: Beyond linear regression models Week 12-14: Advanced statistics Week 15: Final class project