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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). 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.

Join us at a future information session!

Admissions Requirements

  • SOPHAS ( application submitted by June 1, 2024 (domestic applicants) and April 1, 2024 (international applicants)

  • Official transcripts from all previously attended institutions

  • Three letters of recommendation

  • Professional CV/Resume

  • Personal Statement

  • Prerequisite courses Calculus I, Calculus II, and Intro to Biostatistics or Statistics*

  • International transcripts (International Students ONLY - must be evaluated by WES)

  • Official TOEFL or IELTS score for international students

*Applicants who have not completed prerequisite coursework (Calculus I & II, and Intro to Biostatistics, Statistics, or similar) should apply by March 1, 2024. Opportunities to complete prerequisite coursework will be provided in the summer term prior to the fall start.

Students who are admitted to the MS-Biostatistics program will be required to complete a secondary UK Graduate School application to accept admission to the program.

  • The Department of Biostatistics understands that not all interested students will have completed the prerequisite coursework as a part of their academic studies. To help students meet these requirements, the department offers the prerequisite courses during the summer as online, asynchronous courses. Interested students are highly encouraged to contact the Director of Graduate Studies for the program for more information.

  • Interested students without these classes need to apply by March 1 to be able to enroll in the pre-requisite coursework.

Commitment to Diversity and First-Generation Students

We are committed to increase diversity in the field of biostatistics and our goal is to give all qualified students the opportunity to apply and be considered. The MSBST program has been designed to those needing to expand existing quantitative skills and training before effectively moving into the workforce and with health-related training who may lack an in-depth quantitative background. The potential lack of concentrated quantitative skills is a recognized challenge for under-represented and first-generation students in STEM fields. As we continue to work on developing pathways for these students, our admissions process will give all candidates the opportunity to demonstrate their abilities to be competitive for consideration in the MSBST program.

Full-Time Sample Schedule (2 Years)

Year 1 Fall Year 1 Spring Years 2 Fall Years 2 Spring
BST 681 BST 635 BST 693 BST 699
BST 675 BST 682 Elective Elective
Elective (BST 535 recommended) CPH 712 Elective  

Part-Time Sample Schedule (3 Years)

Year 1 Fall Year 1 Spring Year 2 Fall Year 2 Spring Year 3 Fall Year 3 Spring
BST 681 BST 635 BST 675 BST 682 BST 693 BST 699
Elective (BST 535 recommended) CPH 712 Elective Elective Elective  

Vice Chair

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Amanda Ellis, PhD

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MSBST Brochure

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See the MSBST on UK's Academic Exploration Tool.

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