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MSBST Master of Science in Biostatistics

Apply Department of Biostatistics

The 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.

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Why MS in Biostatistics at UK?

Traditional biostatistics programs train students to analyze biomedical data, with a heavy focus on data arising from clinical trials. Traditional epidemiology programs focus on the study of observational data and secondary data. Our symbiotic relationship between the departments of Biostatistics and Epidemiology provides the opportunity to train students to work as "team-scientists" to fill an emerging workforce gap in the intersection of these two fields. The MSBST teaches candidates traditional biostatistics methodology, prepares them to work alongside epidemiologists and other subject-matter experts, and provides the unique skills to work with epidemiological data such as healthcare data, case reports, and more. Furthermore, our educational opportunities will train students to work in the emerging field of health data science.

What We Value...

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Experiential Learning

Once entering the workforce, we expect our graduates to be well-prepared as the first line of defense in the battle against poor data analysis and misuse of data in a data-driven world.

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Balance of Theory & Application

We strive to provide students with an educational experience that will equip them with the background and intuition to learn and implement new methodologies.

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Software Training & Application

While we aim to provide students with the skills to code in some of today's most popular languages, we value the ability to grow and learn new computational languages such that students are positioned to adapt to using other languages in the future.

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Collaboration

We aim to prepare students to recognize and advocate for their role and, ultimately, to succeed as team scientists.

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