University of Iowa

What you'll study

The programme builds a foundation in probability, statistical inference and modelling, then layers on specialised methods and computing for biological and clinical applications. Core topics include introductory and mathematical statistics, regression and applied linear models, experimental design and statistical computing (R and/or SAS).

• Foundations: calculus, linear algebra, probability and mathematical statistics to support rigorous understanding of methods.
• Core statistical methods: applied regression, generalized linear models, multivariate analysis and model selection.
• Biostatistics-focused modules: clinical trials methodology, survival and time-to-event analysis, longitudinal and clustered data analysis, epidemiologic methods, and statistical genetics/genomics introductions.
• Computing and data skills: statistical programming, reproducible research, data management, and applied data visualisation, often using R and tools for handling biological datasets.
• Applied experience: consulting practicum, internships, or a capstone/senior project collaborating with faculty in public health, medicine or biological sciences.

Entry requirements

Applicants should demonstrate strong preparation in mathematics, typically including high school calculus or equivalent. Successful candidates usually have a background in algebra, geometry and introductory statistics; further preparation in calculus, linear algebra or computer programming is advantageous. Admission is to the university and the department; decisions consider academic performance, coursework rigor and other application materials. International applicants must meet the university’s English proficiency requirements.

Career prospects

Graduates are prepared for roles that apply statistical methods to health and biology, or for further training in graduate programmes. Typical career paths include:

• Biostatistician or statistical analyst in pharmaceutical companies, contract research organisations (CROs) and biotechnology firms.
• Data analyst or epidemiology analyst in public‑health agencies, hospitals and health systems.
• Clinical trial statistician supporting design, monitoring and analysis of clinical studies.
• Research support roles in academic medical centres and research institutes, or technical roles in genomics and bioinformatics teams.
• Progression to graduate study (MSc/PhD) in biostatistics, statistics, epidemiology or related quantitative disciplines.

Why study at University of Iowa

The University of Iowa offers a supportive environment that connects statistical training with active biomedical research and clinical practice. Departmental strengths include dedicated faculty who work closely with the College of Public Health, the university hospital and biological science departments, providing frequent opportunities for undergraduate research, practicum placements and interdisciplinary collaboration. Students benefit from access to computing resources, statistical consulting experiences and career services that build pathways into industry, public health and graduate study.