Bio-Mathematical and Statistical Analysis Graduate Certificate
Technological advances have revolutionized the study of biological systems, enabling the acquisition and interrogation of datasets of unprecedented depth and complexity. The Bio-Mathematical and Statistical Analysis Graduate Certificate trains students for the research and development workforce of the future with a solid foundation in the theory, application, and data analyses needed to match the technological advances.
Program Overview
The Biomathematical and Statistical Analysis Graduate Certificate teaches advanced computational math, statistics, and data science to analyze data in biological life sciences.
Our program promotes bold inquiry, preparing students for careers in biotechnology, public health, environmental consulting, government agencies, and research laboratories, where they analyze and interpret biological data to support scientific decision-making. The certificate also provides valuable preparation for advanced graduate study and careers involving data science, bioinformatics, epidemiology, ecological modeling, and quantitative biological research.
You will learn to use computer and data modeling, as well as information technology and AI to collect and analyze data at the intersection of biology, statistics, and data science. With course offerings in ecology and evolutionary biology, life sciences, and statistics, students gain interdisciplinary knowledge on topics such as phylogenetic methods, biometry, and computational ecology.
This program is ideal for currently enrolled students or professionals already working in health, life sciences, or related fields wishing to enhance their credentials.
Why Study Bio-Mathematical and Statistical Analysis?
At the University of Tennessee, Knoxville, a graduate certificate in biomathematical and statistical analysis means you’ll never be sitting on the sidelines.
Our certificate program will prepare students for a variety of careers and provide expertise and certification in a critically important area of biological science. Designed as an add-on or stand-alone certificate, our program welcomes already enrolled students or those seeking to enhance their professional credentials.
Plus, you’ll work alongside faculty mentors that are dedicated to seeing you succeed and achieve your career goals. Whatever your interests, our certificate program equips you with skills and mentorship to hit the ground running.
What Can You Do with a Graduate Certificate in Bio-Mathematical and Statistical Analysis After Graduation?
In the Bio-Mathematical and Statistical Analysis graduate program at UT, students will learn the theoretical basis of mathematical and statistical techniques used to investigate biological systems, apply this knowledge to data, and analyze and interpret this data with the techniques they’ve learned. This program and its hands-on nature will help students to be better equipped for careers in research or research-related fields in academia, government, and private sectors.
A certificate in bio-math and statistics provides credentials to verify expertise in this important area that will enhance skills and employability in many careers, including: biostatistics, data analysis, public health, ecology and conservation data management, population modeling, environmental health analysis as well as field research programs, quantitative ecology, conservation analysis and more.
Employment at places such as government agencies, environmental agencies, conservation organizations, universities, research institutes, and biotechnology firms are enhanced with this certificate.
Featured Courses
EEB 560 Biometry
Statistical applications in biological research using R package, case studies, and your own data in a hands-on exploration of data analysis and interpretation.
MICR 435 Quantitative Analysis of Biological Data
Students will learn the basics of scientific methods, science philosophy and experimental design in biology; there is an emphasis on interpretation of quantitative experimental data. Students will utilize source programming languages for the analysis and visualization of experimental data.
EEB 587 Phylogenetic Methods
Topics include likelihood, Bayesian, and parsimony methods of tree inference, gene tree species, tree and network methods, dating trees, correlating characters, discrete and continuous character models and diversification.
EEB 610 Advanced Topics in Mathematical, Theoretical and Computational Ecology
Students will receive exposure and in-depth training in contemporary topics and approaches important to advanced research in mathematical, theoretical, and computational ecology.
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