(Taken from the UC Berkeley Course Guide)
This is an introductory course in probability designed to develop a good understanding of uncertain phenomena and the mathematical tools used to model and analyze it. Applications will be given in such areas as reliability theory, risk theory, inventory theory, financial models, and computer science, among others. To complement the theory, the course also covers the basics of stochastic simulation. This course is a probability course and cannot be used to fulfill any engineering unit or elective requirements.
Students should have a solid knowledge of calculus, including multiple variable integration, such as Mathematics 1A-1B or 16A-16B, as well as programming experience in Matlab or Python
Students will receive no credit for 172 after taking Statistics 134 or Stat 140. Fall only
Students will learn how to model random phenomena and learn about a variety of areas where it is important to estimate the likelihood of uncertain events. Students will also learn how to use computer simulation to replicate and analyze these events.
3 hours of lecture and 1 hour of discussion per week.