University of Northern Colorado

What you'll study

This undergraduate programme builds a foundation in calculus and linear algebra before progressing to core statistical theory and applied methods with a focus on biological and health applications. Typical modules include:

• Calculus and Linear Algebra — single-variable and multivariable calculus and matrix methods that underpin statistical models.
• Probability and Mathematical Statistics — probability theory, distributions, estimation and hypothesis testing.
• Statistical Modelling — linear and generalized linear models, analysis of variance and categorical data methods.
• Regression and Time-to-Event Methods — multiple regression, logistic regression and introductory survival analysis.
• Experimental Design and Clinical Trials — design principles, randomisation, power and analysis relevant to laboratory and clinical studies.
• Statistical Computing — intensive training in R and other statistical software, reproducible research, data management and simulation techniques.
• Bioinformatics and Epidemiology Electives — introductory genomics data analysis, population health methods and disease surveillance.
• Capstone / Research Project — an applied project or thesis in collaboration with faculty, often involving real biomedical or public-health data.

Students also take supporting coursework from biology, public health or psychology to ensure strong domain knowledge for applied biostatistical work. Practical elements such as internships, lab collaborations and consulting experiences are commonly integrated into the programme.

Entry requirements

Applicants should hold a recognised secondary-school diploma or equivalent. Typical academic expectations include strong performance in mathematics (algebra and precalculus; calculus recommended), and science subjects. Admissions normally consider overall GPA and the strength of the mathematical preparation. Standardised test requirements vary and applicants should check current university admissions policy; mature and transfer applicants are welcome with appropriate college-level mathematics coursework.

Recommended preparation before entry:

• High school calculus or equivalent college-level calculus.
• Courses demonstrating quantitative reasoning and good computing familiarity.
• For transfer students, college credit in calculus and an introductory statistics course will ease progression through core modules.

Career prospects

Graduates are equipped for entry-level roles where statistical analysis of biological, clinical or public-health data is required. Common job titles include:

• Biostatistician or statistical analyst in healthcare, pharmaceuticals, medical devices and contract research organisations.
• Clinical trials data analyst and clinical data coordinator.
• Public health analyst or epidemiology data specialist in government and non-profit organisations.
• Data scientist or data analyst roles within healthcare IT, insurance and health analytics companies.

Many graduates also pursue further study — master’s programmes in biostatistics, statistics, epidemiology or data science, or doctoral research — to move into senior research roles, academia or biostatistics leadership positions in industry and regulatory agencies.

Why study at University of Northern Colorado

The University of Northern Colorado offers a supportive undergraduate environment with relatively small class sizes and direct access to faculty in mathematics and applied health fields. The programme emphasises hands-on computing skills and applied projects, enabling students to work with real datasets and to develop portfolios attractive to employers.

Interdisciplinary links with biology, public health and nursing create opportunities for collaborative research and internships with regional healthcare organisations. Students benefit from faculty mentorship, research assistantships and career services that help place graduates into industry, government and graduate programmes.