Applied Statistics, MS

Overview

The MS in Applied Statistics includes a combination of foundational and advanced statistical topics, such as probability, multivariate statistics, predictive models and nonparametric statistics, stochastic processes, stochastic calculus, computational probability and statistics. The program adds to theory a practical component that requires students to apply these techniques to concrete problems from financial markets, medical/health and biostatistics, cybersecurity, and other areas with societal impact. An important component of the program is the hands-on experience that students gain from industry practitioners with computational and statistical tools like R and Python which will move them to the front of the line with employers.

Requirements (30 credits)

Students may enroll in the general program or one of two concentrations: Financial Statistics or Biostatistics.

Core Courses

AIM 5001	Data Acquisition and Management	3
MAT 5002	Computational Statistics and Probability	3
STA 5003	Multivariate Analysis	3
STA 5004	Non-parametric Statistical Learning	3
STA 6500	Capstone in Applied Statistics	3

Electives

Complete electives below based on chosen concentration.

General Concentration: 15 credits of general electives.
Biostatistics Concentration: 9 credits of Biostatistics electives and 6 credits of general electives.
Financial Statistics Concentration:9 credits of Financial Statistics electives and 6 credits of general electives.

AIM 5004	Predictive Models	3
AIM 5005	Machine Learning	3
AIM 5009	Bayesian Methods	3
STA 5013	Bioinformatics	3
STA 6450	Internship in Applied Statistics	1 TO 3
STA 6900	Topics in Applied Statistics	1 TO 3
STA 6999	Independent Study in Applied Statistics	1 TO 3
	Biostatistics Electives:
STA 5010	Introduction to Biostatistics	3
STA 5011	Advanced Biostatistics	3
STA 5012	Statistics in Trials	3
	Financial Statistics Electives:
MAT 5360	Time Series Analysis	3
MAT 5640	Mathematics of Finance	3
STA 5020	Stochastic Processes	3
MAT 5350	Stochastic Calculus	3