Canisius University

What you'll study

This programme builds a solid foundation in calculus and linear algebra before moving into core statistics and probability. Early courses cover calculus, discrete mathematics and introductory statistics; intermediate work includes probability theory, mathematical statistics and regression analysis. Advanced and applied modules focus on biostatistical topics such as survival analysis, longitudinal data analysis, design and analysis of clinical trials, epidemiologic methods and public health statistics.

• Core quantitative courses: calculus sequence, linear algebra, probability, mathematical statistics.
• Statistical methods: regression and generalized linear models, multivariate analysis, experimental design, nonparametric methods.
• Biostatistics and applied topics: survival analysis, longitudinal and repeated-measures analysis, clinical trials methodology, epidemiology, bioinformatics basics.
• Computing and data skills: statistical programming in R (and exposure to SAS or Python), data management, reproducible research and database querying.
• Supporting life-sciences courses: introductory biology, molecular biology or public health electives to provide domain knowledge for applied projects.
• Capstone and experiential learning: a senior capstone project or honours thesis applying statistical methods to a real dataset, plus internship options with local hospitals, public health departments or research labs.

Entry requirements

Applicants are expected to have a strong background in high-school mathematics, typically including algebra, geometry and precalculus; completion of calculus in high school is recommended. Admissions normally consider the overall academic record, with attention to quantitative coursework. Applicants without a calculus background may be admitted conditionally and required to take preparatory courses.

• Academic qualifications: a high-school diploma or equivalent with solid grades in mathematics; applicants may be asked for transcripts showing performance in math and science.
• Standardised tests and alternatives: Canisius considers standardised tests or other measures of preparedness where required; check the admissions office for current testing policies.
• International applicants: must present equivalent secondary-school qualifications and proof of English language proficiency where applicable.
• Recommendations and personal statement: letters of recommendation and a personal statement that highlight quantitative interests and motivation for studying biostatistics are helpful.

Career prospects

Graduates are prepared for quantitative roles in healthcare, pharmaceutical companies, public health agencies and academic research. Typical entry-level positions include biostatistician assistant, data analyst, clinical data coordinator, research technician and public health analyst. Many graduates go on to specialised graduate study in biostatistics, statistics, epidemiology or data science, or pursue careers in industry as statistical programmers and clinical trials specialists.

• Healthcare and hospitals: biostatistics support for clinical research and outcomes analysis.
• Pharmaceutical and medical-device industry: design and analysis of clinical trials, regulatory submissions.
• Public health agencies and NGOs: population health analysis, surveillance and policy evaluation.
• Academic and research institutions: research assistant roles and pathway to graduate study (MS/PhD).
• Data science and analytics roles across sectors that require strong statistical and programming skills.

Why study at Canisius University

Canisius offers the benefits of a Jesuit liberal-arts education with small class sizes and close faculty mentorship, which is especially valuable in a technical field like biostatistics. The university emphasises undergraduate research and hands-on learning, giving students opportunities to collaborate with faculty on applied projects and to complete a meaningful capstone. Canisius’s location in the Buffalo region provides access to medical and research organisations for internships and partnerships, and its strong pre-health advising helps students who plan to move into clinical research or graduate programmes. Students also gain ethical and communication training that complements quantitative skills and is important in healthcare-focused careers.