Course code:
Probability is the branch of mathematics that deals with the likelihood of events occurring. It provides the theoretical foundation for making predictions about the behavior of random phenomena. Statistics uses this framework to analyze real-world data, make inferences, and draw conclusions. Probability theory can help us to make informed decisions whether it’s assessing risks, making choices based on potential outcomes, or understanding the likelihood of events. This course will introduce students to probability and random variables through real-world examples with an emphasis on developing probabilistic intuition through simulation. Topics covered include discrete and continuous random variables, probability spaces, densities and distributions, independence, joint and conditional distributions, expectation, and concepts including Bayes’ theorem, the central limit theorem and the law of large numbers.
This course will equip students with the tools and understanding to pursue more advanced studies in probability and related fields such as statistics and data science. Students’ learning will be assessed through weekly problem sets and take-home exams.
Prerequisites:
Calculus 1 or equivalent (e.g. AP Calculus, IB Calculus). Students unsure if they have the right background are warmly invited to contact the instructor.
Always visit the Registrar's Office for the official course catalog and schedules.
