Minor
About Statistics (Minor Only) at CSUSB
The Statistics minor at Cal State San Bernardino offers students a rigorous and applied curriculum in both theoretical and practical aspects of statistics.
This minor focuses on the analysis, interpretation, and communication of data—skills that are essential in today’s data-driven world. The program combines mathematical foundations with computational and applied coursework designed to prepare students for quantitative reasoning roles in diverse fields.
The minor is suitable for students in mathematics, computer science and engineering, physics, chemistry, biology, health sciences, psychology, data science, and related majors who have completed foundational coursework in calculus and statistics. Through this sequence of courses, students gain experience in probability, statistical modeling, computational techniques, and elective applications of statistics to real-world problems.
Careers in Statistics (Minor Only)
The Statistics minor equips students with analytical and quantitative skills that are highly valued across industries where data interpretation, modeling, and evidence-based decision-making are central. Graduates can pursue roles such as:
- Data analyst or quantitative specialist
- Statistical consultant or research analyst
- Biostatistician or health analytics professional
- Machine learning support and computational modeling roles
- Market research analyst or business intelligence specialist
- Quality control and operations research
- Policy analysis and social science research
The ability to frame, conduct, and communicate statistical analysis effectively strengthens career readiness in science, business, public policy, technology, health fields, and graduate study.
Meet Professor Madeleine Jetter, Ph.D.
Opportunities for Students
Students in the Statistics minor engage in coursework and applied experiences that build quantitative reasoning and practical data skills:
- Foundational lower-division coursework including Calculus I and Calculus II, Statistics with Applications, Applied Linear Algebra, and Multivariable Calculus that establish mathematical underpinnings.
- Upper-division core courses such as Probability Theory, Computational Statistics, and Linear Statistical Models that deepen theoretical and applied understanding.
- Elective options allowing students to tailor their studies with courses in areas such as Statistical Methods for Machine Learning, Mathematical Statistics, Big Data Analytics, Biostatistics for Health Science, Advanced Psychological Statistics, or Biostatistics and Experimental Design.
- Development of programming and computational skills to support data analysis across platforms and research contexts.
- Faculty mentorship from experienced mathematicians and statisticians to guide students in analytical thinking and career planning.
- Cross-disciplinary collaborations in courses or applied projects with peers in science, engineering, social sciences, and data science.
These experiences help students build a strong foundation in statistical reasoning and prepare them to meet the analytic challenges of a wide range of careers and advanced academic pursuits.