Introduction
Please note that this is a preliminary course description. The final version will be published in June 2026.
The language and tools of mathematics are used extensively to analyze problems in business, economics and finance. The mathematical sophistication required of a graduate student goes beyond that usually taught in undergraduate courses. This course will teach the beginning graduate student more advanced mathematical models, theories, and methods. It will also provide an introduction to probability and the fundamental ideas of statistical inference. The course is taught in the first semester of the master program and is split into two parts. The topics in the first part include linear algebra and vector calculus, calculus in several variables, optimization in several variables with and without constraints. The topics in the second part include: an introduction to probability (random variables, expectations, conditioning and independence) and an introduction to statistical inference (statistical models, estimators, tests, evaluation criteria, confidence intervals, p-values).