Engineering materials including metals, polymers, ceramics, and composites. Emphasis on the relationship between the microstructure of materials and their mechanical behavior, including the fundamentals of design for performance.

Students choose a topic on their own under the guidance of a faculty adviser who will then grade the final written report

Major designs used in clinical investigations; alternative approaches to the analysis of gathered data. Prerequisite: BIOST&EP 640.

The analysis of time to event data focusing on applications of regression models to right censored data. Particular emphasis on the use and interpretation of the pro-portional hazards model. Prerequisite: PUBHLTH 640.

This is not available at this time

A discovery based capstone project provides an essential culminating learning experience in the UMASS Amherst M.S program in biostatistics. This course will guide students as they carry out an individual project in 7 steps: (1) formulate a research question, (2) conduct literature review, (3) select relevant data sources, (4) choose appropriate statistical/machine learning methodology, (5) create and implement their analytical plan including data ingestion, transformation, modeling, and interpretation, (6) write a research paper, and (7) effectively communicate their project and results.

The course introduces advanced central topics in biostatistics and health data science including survival analysis, design and analysis of clinical trials, models for correlated data, bayesian modeling, and causal inference. The course motivates statistical reasoning and methods through substantive research questions and features of data typically available in public health and biomedical research. Students will obtain hands-on experience in applying selected methods on real data using the statistical programming language R.