*Sponsored by the **Department of Applied Mathematics & Statistics*

*NOTE: Innovation and Design II does not count as a technical course in Probability and Statistics.

To learn more about the admissions criteria for AMS-sponsored tracks, please visit the AMS website.

#### Admissions Requirements

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).

#### Curricular Requirements

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. *

#### Additional Requirements

- 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.*