Curriculum & Concentrations
Campus MS Program

* All courses are 3 credit hours

Core Courses

The following five core courses are required for all M.S. students.

• PHC 6050c: Biostatistical Methods I
• PHC 6051: Biostatistical Methods II
• PHC 6063: Biostatistical Consulting
• PHC 6937: Introduction to Public Health
• PHC 6001: Principles of Epidemiology in Public Health

The courses “Biostatistical Methods I and II” make up the methods core of the program. Both courses cover the essentials of statistical methods for different types of data common in health studies.

The core course “Introduction to Public Health” provides a broad introduction to public health as well as an understanding about how public health workers contribute to achieving the goals of public health.

In addition, each student must take the course “Biostatistical Consulting”, which covers communication, management, organization, computational and biostatistical thinking skills necessary to consulting in biostatistics.

The course “Principles of Epidemiology in Public Health” provides students with an overview of epidemiology methods used in research studies that address disease patterns in community and clinic-based populations.

Concentration Core Courses

Biostatistics Methods and Practice Concentration

• PHC 6092: Introduction to Biostatistical Theory
• STA 6177: Applied Survival Analysis
• PHC 6020: Clinical Trial Analysis

The course “Introduction to Biostatistical Theory” provides students with the mathematical foundation necessary to use and understand biostatistical methods.

The course “Applied Survival Analysis” introduces the basic concepts and statistical methods used for analyzing survival data.

Health Data Science Concentration

• PHC 6099: Programming Basics for Biostatistics
• PHC 6791: Data Visualization in Health Sciences
• PHC 6097: Statistical Learning with Applications in Health Science

The core course “Programming Basics for Biostatistics” intends to develop students’ ability to perform statistical computing, and it covers programming topics (e.g., GitHub and building R packages), statistical and computational methods (e.g., optimization), and direct integration and dynamic reporting using R and Python.

In the core course “Data Visualization in Health Sciences”, students will learn the foundations of information visualization, and the course will sharpen their skills in communicating using health science data.

The core course “Statistical Learning with Applications in Health Sciences” covers a broad range of statistical/machine learning methods (e.g., deep learning) that are useful for health data analysis.

Electives

Students are also required to complete at least four additional biostatistics/statistics courses determined in conjunction with their supervisory committee. Special topics elective courses will be taught under the course number PHC 6937.

Capstone Experience

All MS in Biostatistics students are required to complete a capstone project to demonstrate mastery of the program. While every project will involve different goals and activities, each one presents multiple opportunities for students to expand on one or more of the MS core competencies. Students will typically begin working on their project at the beginning of the semester they wish to graduate, however, it may be started in the penultimate semester with the permission of their faculty advisor. The capstone project involves writing a paper and submitting it to your faculty advisor for feedback and approval. There are two options for the paper:

1. Read a paper from the statistical literature (e.g., the Journal of Statistics in Medicine) and submit a written report that summarizes the article and critiques the methodology used in the paper. Additionally, you will apply the methodology used in the paper to real or simulated data and include your process in the report. Any code used in the process should be attached as an appendix to your document. 
2. Complete a data analysis that uses one or more of the methods you learned about in the program to answer a research question. Submit a written report that summarizes the goals of the project, the data source, the methods used, the results of the analysis, and the conclusions of the project. 

The statistical methods you should be aiming to use/find should be at least on par with methods that you learned about in your MS program. Ideally, the method will be an extension of one of these methods in some way (e.g., a special case). If choosing option 1, your simulation should go beyond a simple reproduction of the paper. 

Comparison to M.S. in Statistics

The curriculum shares some components with the M.S. in Statistics (in particular, the theoretical core because the theoretical underpinnings of statistics and biostatistics are similar and therefore did not require new course development).

However, there is different emphasis in the methodology courses, with the core courses covering methodology for categorical data in Biostatistical Methods II and survival data and clinical trials.

In addition, there is a “subject matter” component in the M.S. in Biostatistics, consisting of the Public Health core courses as well as a consulting requirement.

These are key components in training for Biostatistics, but are not requirements in the M.S. in Statistics.

Learning Outcomes

All graduates of the program will be expected to be able to:

• Interpret and apply basic biostatistical methods using state-of-the art software in a way that meets the goals of a collaborating health scientist.
• Support successful collaborations with investigators in new quantitative fields.
• Interpret biostatistical analyses while remaining aware of limitations.
• Compete for positions in three primary settings: academic (either in a PhD program or as an academic research assistant), industry, and federal agencies that involve research and/or public health practice.

Overview

A minimum of 36 post-baccalaureate credit hours is required. Upon successful completion of the program, graduates will be awarded an M.S. degree in biostatistics. 

PLEASE NOTE: Students who enrolled and began attending traditional M.S. program prior to August 2022 will continue to follow the previous requirements for the program. These requirements can be found in the Departmental Graduate Handbook.