University of Southern Indiana

What you'll study

The programme provides a foundation in probability and mathematical statistics, statistical computing and applied methods tailored to biological and health sciences. Study begins with core courses in calculus, linear algebra and introductory statistics, then progresses to intermediate and advanced topics with an emphasis on biostatistical applications.

• Core statistics and mathematics: probability theory, mathematical statistics, regression and multivariate analysis, time series and applied statistical modelling.
• Biostatistics and applied modules: introductory biostatistics, design and analysis of clinical trials, survival analysis, categorical data analysis, longitudinal data methods and epidemiologic methods.
• Computational skills: statistical computing using R and/or SAS, data management, reproducible research, and courses that include hands‑on data analysis projects.
• Supporting life sciences: fundamental biology courses such as cell biology, genetics, and an introduction to public health or epidemiology to provide context for biostatistical problems.
• Capstone and experiential learning: a senior capstone or practicum in which students complete a substantial analysis project, often completed in partnership with faculty research, a healthcare provider or an industry internship.
• Electives and professional preparation: electives in machine learning, data visualisation, clinical research methods, and preparation for professional roles or graduate study.

Entry requirements

Applicants are normally required to hold a high school diploma (or equivalent) with a strong background in mathematics. Successful candidates typically have completed courses in algebra, precalculus or calculus, and at least one laboratory science such as biology.

• Academic background: strong performance in mathematics and science courses; coursework in calculus is highly recommended before or during degree entry.
• Admissions materials: official transcripts; personal statement outlining quantitative interests and experience; letters of recommendation may strengthen an application.
• Standardised tests: test scores (SAT/ACT) may be submitted where relevant; consult the university’s admissions guidance for current testing policies.
• Transfer students: transfer credit for introductory mathematics and science courses is typically considered; applicants transferring from community colleges should provide course descriptions and transcripts for evaluation.
• Preparation suggestions: prospective students are advised to build programming experience (R, Python) and seek laboratory or data-focused extracurriculars to strengthen their readiness for biostatistics coursework.

Career prospects

Graduates are prepared for roles that apply statistical methods to health-related data in industry, government and research settings or for further study in graduate programmes. The degree equips students with analysis, computing and communication skills employers seek in quantitative health roles.

• Biostatistician or statistical analyst in pharmaceutical companies, contract research organisations (CROs) and biotech.
• Data analyst or data scientist in hospitals, public health departments and health technology firms.
• Clinical trials analyst, outcomes researcher or regulatory data specialist.
• Research assistant or study coordinator in academic medical centres and public health research units.
• Further training options: graduate study (master’s or PhD) in biostatistics, statistics, epidemiology, public health or related fields for advanced research and leadership roles.

Why study at University of Southern Indiana

The University of Southern Indiana offers a student-centred environment with small class sizes and direct access to faculty who are active in applied research and community partnerships. The campus emphasises hands-on learning through lab courses, statistical consulting opportunities and internships with regional healthcare providers and industry partners.

• Applied focus: curriculum designed to connect statistical theory with real biomedical data through projects and practicum experiences.
• Computing and resources: access to statistical software and computing labs, plus faculty support for learning programming tools commonly used in biostatistics.
• Local partnerships: opportunities for internships and collaborative projects with hospitals, public health departments and regional research organisations in the Evansville area.
• Preparation for next steps: advising and course options that prepare students for certification, graduate study and careers in industry, government and academia.