Courses

It depends on your background and interests. If in doubt, please discuss this with your academic advisors and the Statistics advisors. By far the most common places to start are Stat 100, 102, or 104 (which are introductions to applied statistics, each...

Statistics is guided by a few fundamental principles but has applications in a great variety of different fields. To best serve the needs of students with a wide range of backgrounds and interests, the department has several versions of its introductory...

They are complementary, with very little overlap. Stat 100, 102, and 104 are each an introduction to statistical principles and concepts, as described above. Stat 110 is an introduction to probability. The emphasis of Stat 110 is on random variables and...

Stat 108 and 109a are the two main examples. Stat 108 is an introduction to programming with a statistical focus using R, while Stat 109a is an introduction to data science using Python to perform copmutation (this is the same course as CS 109a). There...

Stat 111, 123, 170, and 171 have Stat 110 as their main or only prerequisite. There are also various courses in other departments, especially Applied Mathematics, Computer Science, and Economics, that rely heavily on the ideas from Stat 110.

They are complementary courses on the science of learning from data, with very different emphases: Stat 111 focuses the theory of statistical inference, while Stat 139 focuses on applications. Stat 111 is an introduction to both Bayesian and frequentist...

They are complementary courses on mathematical finance. Stat 123 focuses on derivatives, with an emphasis on interest rate derivatives and issues about trading them in real markets. Stat 170 focuses on the pricing of assets, portfolio analysis, and...