Courses For the Non-Major
Undergraduate non-majors interested in an introduction to the basic principles and techniques of probability and statistics should consider W1001 (for students in non-quantitative fields), W1111 (for students in quantitative fields who are not looking for a calculus-based course), or W1211 (for students who have had some experience with calculus). Introduction to Applied Statistics W2110 takes W1001, W1111, or W1211 as a prerequisite and provides practical experience in data analysis. G6191 is an intensive course in statistical methods for student researchers in fields outside of statistics.
The core courses W4105 and W4107 are calculus-based introductions to probability and statistics, respectively, and are designed for students planning to continue with more advanced theory and methods courses. W4109 combines W4105 and W4107 in a single semester and is recommended only for students in the MA program who plan to finish their degree in two semesters. W4150 combines much of the material in W4105 and W4107 in a single semester, but is not as comprehensive as W4109; students whose schedule permits should take W4105 and W4107 in place of W4150 (W4150 does not count to fulfill MA course requirements). W4105 takes advanced calculus as a prerequisite, and W4107 takes advanced calculus and linear algebra as a prerequisite; less prepared students and undergraduates who are completing the prerequisites may substitute W3105 and W3107 for W4105 and W4107.
Several more advanced theory and methods courses take one or more of the foundation courses as prerequisites. Among these are W4315 (Linear Regression), W4437 (Time Series Analysis), W4543 (Survival Analysis), W4330 (Multilevel Models), W4325 (Generalized Linear Models), W4335 (Sample Surveys), W4415 (Nonparametric Methods), W4606 (Elementary Stochastic Processes), W6501 (Stochastic Processes and Applications), G6505 (Stochastic Methods in Finance), W4290 (Statistical Methods in Finance), and G6503 (Statistical Inference and Time-Series Modeling). Statistics W4201 is a survey course in applied statistical methods, that provides intensive practical experience. W4840 is a course in financial mathematics suitable for students in the Actuarial Science program.
Core Doctoral Courses
The core graduate sequence in probability theory, G6105/G6106, and the core graduate sequence in the theory of statistics, G6107/G6108, are designed for students of advanced mathematical maturity interested in research careers in probability theory or statistcis. The core graduate sequence in data analysis, G6101/G6102/G6103, is designed to develop advanced data analytic skills.
Doctoral Seminar Courses
A variety of topics courses and seminars are available. The content varies according to the interests of the instructor and the students. The focus ranges from exploring mathematical techniques useful to researchers in probability and statistics, to surveys of statistical methods used in particular application areas, to developing advanced data analytic skills. These courses have 8000 numbers. In recent semesters, seminar topics have included stochastic differential equations and applications, semi-parametric inference, management of extreme financial events, analysis of neural spike-train data, large data sets in genetics and classification, causal inference, and statistical methods in fMRI research.
Working Groups and Reading Courses
These courses are a formal mechanism to bring together faculty and students from Statistics and other Departments to discuss common interests. In some cases, course credit is available for participation in the groups. These courses have 7000 numbers. Current working groups topics include statistics in sports, biostatistics, risk management, quantitative research in political science, Bayesian statistics, statistical methods in genetic epidemiology, and stochastic analysis.