Use data and quantitative thinking to solve real-world health challenges

That's where BIOSTATISTICS and HEALTH DATA SCIENCE 
turn complex data into health impact.

Hello Kyle,

Your academic coursework gives you a powerful combination: the computational ability to work with complex datasets and the mathematical foundation to understand the methods behind the results.

At Michigan Biostatistics, graduate study can prepare you to maximize that combination so you can build sophisticated analytical tools and understand whether the evidence they produce deserves to be trusted.

Biostatistics lets you apply both strengths to questions where rigor is essential. Computation and theory reinforce one another. Programming makes sophisticated analysis possible; statistical reasoning determines whether the resulting conclusions deserve to be trusted.

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.

Their work spans nearly every form of modern health data. They analyze electronic health records to uncover patterns in care and outcomes, study genomic data to identify factors associated with disease, use medical images to improve detection and diagnosis of cancer, and integrate information across clinical studies and entire populations. They also adapt machine-learning methods for healthcare—evaluating whether algorithms are accurate, reproducible, interpretable, fair, and appropriate for the decisions they may influence.

That work might include:

Predicting patient outcomes using high-dimensional health data

Building reproducible tools for large biomedical datasets

Adapting machine-learning methods for healthcare applications

Quantifying uncertainty in a large genetic study

Developing new statistical methods for complex biomedical data

Detecting and addressing bias in health algorithms

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 want to build tools—and understand the evidence those tools produce—biostatistics may be the field you have been preparing for.