University of San Diego

What you'll study

The programme combines core statistical theory, applied biostatistical methods and computing, set within a liberal arts curriculum. Early study focuses on calculus, linear algebra and probability to build a rigorous mathematical base. Core statistics modules typically include mathematical statistics, statistical inference, and statistical modelling.

Applied and biostatistics-focused modules commonly cover regression and generalized linear models, survival analysis, categorical data analysis, longitudinal data analysis, experimental design and analysis of clinical trials. Students also study epidemiology principles and introductory topics in bioinformatics to understand the biological and public-health context of data.

Practical computing and data-handling form a substantial element: courses in statistical programming (R and Python), data visualisation, database fundamentals and use of statistical software such as SAS are standard. The degree often culminates in a capstone project, senior thesis or practicum that involves working with real biomedical datasets or partnering with a research group or external organisation.

• Calculus and linear algebra
• Probability theory and mathematical statistics
• Regression and generalized linear models
• Survival and longitudinal data analysis
• Design and analysis of experiments and clinical trials
• Statistical computing: R, Python and data management
• Epidemiology and introductory bioinformatics
• Capstone project or internship

Programme structure

The major is structured around required core courses, electives within the biostatistics concentration, and general education requirements. Students typically take progressively advanced statistics and mathematics courses across the programme, with options for research credits, independent study or industry internships in later years.

Entry requirements

Admission to the University of San Diego is selective and based on a holistic review of academic achievement, coursework, recommendations and personal statement. For this statistics major, applicants are expected to demonstrate strong preparation in mathematics—typically including high school calculus or equivalent—and a solid record in science and quantitative subjects.

Typical preparation includes:

• A high school diploma or recognised secondary qualification with courses in calculus and advanced mathematics (or equivalent college-level coursework)
• Competitive academic performance; successful applicants usually have above-average grades in quantitative subjects
• Letters of recommendation and a personal statement that highlight quantitative ability and interest in biological or health applications
• International applicants should present equivalent qualifications; evidence of proficiency in English is required if a student’s prior education was not in English

Standardised test submission policies may vary; check the university’s admissions guidance for current requirements. Students transferring from other institutions should present college transcripts with a record of calculus and introductory statistics courses. Placement testing in mathematics may be used to determine the appropriate starting mathematics course.

Career prospects

Graduates with a biostatistics concentration are prepared for quantitative roles in healthcare, biomedical research and the life sciences industry. Common entry-level positions include statistical programmer, data analyst, research analyst, clinical data manager and junior biostatistician at hospitals, university research units, contract research organisations (CROs), pharmaceutical and biotech companies, public health agencies and non-profit health organisations.

Many graduates pursue graduate study (master’s or PhD) in biostatistics, statistics, epidemiology or data science to qualify for senior biostatistician and research roles. Skills in statistical modelling, programming and data management are also transferable to roles in health informatics, regulatory affairs, market access analytics and broader data science positions.

Why study at University of San Diego

The University of San Diego offers a smaller-campus environment with opportunities for close faculty mentoring and undergraduate research. The mathematics and statistics curriculum emphasises both theoretical foundations and applied computing, and students can take advantage of interdisciplinary connections with biology, public health and data science programmes.

Located in the San Diego region, the university provides proximity to a strong life-sciences and biotech ecosystem, which supports internship and collaboration opportunities with hospitals, research institutes and industry partners. The programme’s focus on experiential learning—through capstone projects, labs and internships—helps students build a practical portfolio of applied biostatistics work that is valuable to employers and for graduate study.