Sponsored by the Department of Applied Mathematics & Statistics
*NOTE: Innovation and Design II does not count as a technical course in Probability and Statistics.
One upper-division undergraduate course in probability and one in mathematical statistics (equivalent to 550.420 Introduction to Probability and 550.430 Introduction to Statistics).
Any five (5) of the following courses, approved by the faculty advisor:
553.613 Applied Statistics and Data Analysis I
553.614 Applied Statistics and Data Analysis II
553.620 Introduction to Probability
553.626 Introduction to Stochastic Processes
553.627 Stochastic Processes and Applications to Finance I
553.628 Stochastic Processes and Applications to Finance II
553.629 Introduction to Research in Discrete Probability
553.630 Introduction to Statistics
553.632 Bayesian Statistics
553.633 Monte Carlo Methods
553.636 Introduction to Data Science
553.639 Time Series Analysis
553.688 Computing for Mathematics
553.692 Mathematical Biology
553.693 Mathematical Image Analysis
553.720 Probability Theory I
553.721 Probability Theory II
553.722 Introduction to Stochastic Calculus
553.723 Markov Chains
553.727 Large Deviation Theory
553.729 Topics in Probability: Random Graphs and Percolation
553.730 Statistical Theory I
553.731 Statistical Theory II
553.732 Bayesian Statistics
553.733 Advanced Topics in Bayesian Statistics
553.734 Introduction to Nonparametric Estimation
553.735 Topics in Statistical Pattern Recognition
553.736 System Identification and Likelihood Methods
553.737 Distribution-free Statistics and Resampling Methods
553.738 High-Dimensional Approximation, Probability and Statistical Learning
553.739 Statistical Pattern Recognition Theory & Methods
553.740 Machine Learning I
553.741 Machine Learning II
553.742 Statistical Inference on Graphs
AS.110.653 Stochastic Differential Equations: An Introduction with Applications
Substitutions for required courses can be made at the advisor’s discretion.
- An overall GPA of 3.0 must be maintained in courses used to meet the program’s technical requirements. At most two course grades of C or C+ are allowed to be used, and the rest of the course grades must be B- or better.
- Students must satisfy the department’s graduate student computing requirement.
- With advisor’s approval, one non-departmental course containing appropriate mathematical or statistical content can be counted to satisfy the five course requirement.
Courses not on this list can be used at the advisor’s discretion.