M.S. in Applied Statistics Curriculum Explore Applied Stats Course Descriptions and Degree Requirements Request More Info Apply Now Attend an Info Session Contact Us Artificial Intelligence Biotechnology Computer Science Cybersecurity Data Analytics and Visualization Digital Marketing and Media Mathematics Nursing Occupational Therapy Physician Assistant Physics Speech-Language Pathology Curriculum Overview The 30-credit M.S. in Applied Statistics turns rigorous statistical theory into market-ready expertise, preparing graduates to solve high-stakes problems in finance, medicine, technology, and AI. Core courses build mastery in Computational Statistics and Probability, Multivariate Analysis, Non-Parametric Statistical Learning, and Data Acquisition and Management — developing the analytical depth that separates statisticians who understand their models from those who simply run them. View Degree Requirements | Download Course Descriptions About the Coursework Students choose from three tracks: a General Track with electives in Machine Learning, Bayesian Methods, and Time Series Analysis; a Financial Statistics Track in Stochastic Calculus and Mathematics of Finance; and a Biostatistics Track covering Clinical Trial Design, Bioinformatics, and Survival Analysis. The program culminates in a capstone integrating industry collaboration, original research, or startup development. Full-time and part-time options are available. Full-Time & Part-Time Options How You'll Learn At the Katz School, you learn the way real innovators work — identifying problems, then designing, building, testing, and improving solutions across a multi-semester project. In the Applied Statistics program, that means working alongside faculty who are active researchers, applying statistical modeling, machine learning, and computational methods to real datasets in finance, healthcare, and technology. You graduate with the theoretical mastery and computational fluency to make an immediate impact in today's data-driven economy. Read More
