COURSE CURRICULUM

The Statistics program includes a range of foundational and advanced courses designed to build strong mathematical, computational, and analytical skills. Students begin with Fundamentals of Programming, which introduces coding concepts and computational thinking used for data analysis and statistical computing. Elementary Linear Algebra provides essential knowledge of vectors, matrices, and linear systems, which are widely used in statistical modelling. The Calculus I–IV sequence develops a deep understanding of mathematical concepts such as limits, derivatives, integrals, and multivariable functions, forming the backbone for advanced statistical theory. Survey Design and Analysis teaches students how to collect reliable data, design questionnaires, and analyze survey results effectively for real-world applications. Mathematical Probability introduces the principles of randomness, probability distributions, and uncertainty, which are critical for statistical inference. Mathematical Statistics builds on probability theory to focus on estimation, hypothesis testing, and statistical decision-making. Design and Analysis of Experiments explores how to structure experiments, control variables, and interpret results in scientific and applied research settings. Together, these courses provide a strong combination of theory and practical application, preparing students to analyze data across various fields such as economics, psychology, geography, and public policy. The program equips students with quantitative reasoning, problem-solving abilities, and technical expertise needed for careers in data science, research, and analytics.