The most important questions in human health do not fit within a single discipline

That's where BIOSTATISTICS and HEALTH DATA SCIENCE 
unite scientific insight, complex data, and quantitative rigor to produce trustworthy evidence.

Hello Kyle,

Your academic coursework has prepared you to approach problems from multiple directions. You can understand the science behind a question, represent it quantitatively, and use data and computation to investigate it.

That interdisciplinary perspective is at the heart of biostatistics and health data science -- fields that apply mathematical and statistical reasoning to biological, clinical, and public health questions, turning scientific observations into rigorous evidence about health and disease.

At Michigan Biostatistics, graduate study can help you deepen and unite those interdisciplinary strengths, preparing you to approach consequential health questions from multiple directions.

Biostatistics goes beyond finding patterns. It asks whether the right data was collected, whether the analysis addresses the scientific question, how uncertainty should be measured, and whether the conclusions will hold beyond the original study.

Biostatisticians develop models, design studies, quantify uncertainty, and evaluate the evidence behind decisions in medicine and public health. They work with data ranging from electronic health records and medical images to clinical trials, genetics, and population studies.

That work might include:

Predicting patient outcomes using high-dimensional health data

Evaluating whether a vaccine works across diverse populations

Quantifying uncertainty in a large genetic study

Measuring differences in treatment response

Developing new statistical methods for complex biomedical data

Validating emerging biomedical technologies for scientific and clinical use

At the University of Michigan, you can pursue this work through three distinct graduate pathways:

• MS in Biostatistics, combining rigorous statistical training with applied health research
• MS in Health Data Science, with its strong computational and machine-learning focus
• PhD in Biostatistics, preparing students to develop new methods and lead original research.

You have already learned to cross disciplinary boundaries. In biostatistics, that is not an extra advantage—it is the foundation of the work.