Biostatistics, MS

The University of Kentucky’s new Master of Science in Biostatistics (MSBST) program trains students in methodological skills that are foundational in biostatistics. The MSBST meets the needs of candidates who seek careers in healthcare, government health agencies, biomedical research, and pharmaceutical industries which all require advanced knowledge in analyzing health science data. Students will benefit from experiential learning opportunities and formal training in applying descriptive and inferential statistics specific to biomedical research, clinical and translational studies, and public health research aimed at improving population health.

Admission Requirements

We welcome your application to the Master of Science in Biostatistics (MSBST) program, and are available to answer any questions or assist you through the application process. Applicants are encouraged to apply early, opportunities are available for those students who do not have all of the prerequisite courses.

Students applying to the Master of Science in Biostatistics program must submit a primary application (for the College of Public Health) and a supplemental application (for the University of Kentucky). Applicants should submit their primary application by using the Schools of Public Health Application Service (SOPHAS) (https://sophas.org). The admissions committee will review the SOPHAS application before the applicant completes the supplemental application for the University of Kentucky Graduate School.

Ideal candidates for the MSBST program are those with a moderate mathematics background or STEM education, along with a commitment to public health and biomedical science. Working professionals in the health-related workforce seeking additional advanced training in the design, analysis, and communication of biomedical data are also encouraged to learn more.

Degree Requirements

The Master of Science in Biostatistics (MSBST) is a 33-credit hour program consisting of 21 credits in core biostatistics courses and a capstone, which gives candidates the opportunity to learn consulting and collaboration practices through valuable experiential learning opportunities. The remaining 12 hours are a mix of customizable electives, which includes epidemiology courses and more. Courses are offered in the Fall and Spring semesters each year.

Core Courses:

BST 635 - DATABASES AND SAS PROGRAMMING

BST 675 - SIMULATION BASED INFERENCE FOR HEALTH DATA SCIENCE

BST 681 - LINEAR REGRESSION

BST 682 - GENERALIZED LINEAR MODELS

BST 693 - STATISTICAL PRACTICE IN PUBLIC HEALTH

CPH 712 - ADVANCED EPIDEMIOLOGY

BST 699 - ADVANCED BIOSTATISTICS PRACTICE

Electives:

BST 535 - INTRODUCTION TO R PROGRAMMING

BST 631 - DESIGN AND ANALYSIS OF HEALTH SURVEYS

BST 636 - ANALYTIC METHODS FOR MINING HEALTHCARE DATA