Discover a rigorous, collaborative field where independent thinking can improve human health.

The frontiers of health research demand people who are willing to question assumptions, work across disciplines, and develop better ways to study complex problems. Biostatistics offers the intellectual challenge of creating rigorous methods while applying them where the answers can change lives.

But intellectual rigor means going beyond a technically correct answer:


  • Are we asking the most meaningful question?
  • Does the study design support the conclusion we want to draw?
  • Have we examined the assumptions and uncertainty behind the result?
  • Could bias or incomplete evidence affect who benefits?
  • Can we create a stronger method, explanation, or path forward?

That's where BIOSTATISTICS and HEALTH DATA SCIENCE 
turn intellectual curiosity into rigorous discovery - and discovery into impact.

Hello Kyle,


Your honors experience has likely asked you to do more than complete coursework. You may have pursued an independent project, worked closely with faculty, explored connections across disciplines, or learned to remain with a difficult question when the answer was not immediately clear.


Those habits of mind translate exceptionally well to 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 those capabilities by developing stronger methods, collaborating across disciplines, and applying rigorous thinking to questions that affect patients and communities.


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 take on questions that are both technically demanding and deeply consequential by developing models, designing studies, quantifying uncertainty, and evaluating 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:

Adapting machine-learning methods for healthcare applications

Quantifying uncertainty in a large genetic study

Developing new statistical methods for complex biomedical data

Designing an efficient and informative clinical trial

Detecting and addressing bias in health algorithms

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.


If you are looking for graduate study that will challenge your thinking, expand your capabilities, and prepare you to contribute to research with lasting impact, biostatistics and health data science deserve your consideration.

Interested in learning more about biostatistics?
 
 
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