Statistics: Biostatistics, M.S.

Program Overview

This Master's program in Statistics provides a comprehensive foundation in statistical theory and methods. Students complete core courses in mathematical statistics, statistical inference, regression, and analysis of variance, along with electives in specialized areas such as clinical trials, epidemiology, and machine learning. The program culminates in a competency test and a statistical consulting project, preparing graduates for careers as practicing statisticians.

Program Outline

Outline:

• Required Courses:
• STAT 609 Mathematical Statistics I or STAT/MATH 709 Mathematical Statistics
• STAT 610 Introduction to Statistical Inference or STAT/MATH 710 Mathematical Statistics
• STAT 849 Theory and Application of Regression and Analysis of Variance I
• STAT 850 Theory and Application of Regression and Analysis of Variance II
• STAT 998 Statistical Consulting
• 6 credits of Statistics courses at the 600 level or higher, including 6 elective credits in STAT/B M I 641 Statistical Methods for Clinical Trials and STAT/B M I 642 Statistical Methods for Epidemiology or STAT/B M I 741 Survival Analysis Theory and Methods or STAT/B M I 877 Statistical Methods for Molecular Biology
• Optional Courses (with permission of the Director of Graduate Studies):
• Up to 6 credits from Statistics Courses Numbered 6: STAT 303 R for Statistics I, STAT 304 R for Statistics II, STAT 305 R for Statistics III, STAT 349 Introduction to Time Series, STAT 351 Introductory Nonparametric Statistics, STAT 411 An Introduction to Sample Survey Theory and Methods, STAT 421 Applied Categorical Data Analysis, STAT 433 Data Science with R, STAT 443 Classification and Regression Trees, STAT 451 Introduction to Machine Learning and Statistical Pattern Classification, STAT 453 Introduction to Deep Learning and Generative Models, STAT 456 Applied Multivariate Analysis, STAT 461 Financial Statistics, STAT/COMP SCI 471 Introduction to Computational Statistics, STAT/COMP SCI/MATH 475 Introduction to Combinatorics, STAT 479 Special Topics in Statistics, STAT/COMP SCI/ISY E/MATH 525 Linear Optimization, STAT 575 Statistical Methods for Spatial Data
• Up to 6 credits of graduate courses outside of STAT in consultation with advisor
• Up to 6 credits of STAT 699 in consultation with advisor

Assessment:

• Students must pass a competency test containing both a written and an oral component, demonstrating that they have the potential to be a practicing statistician.

Teaching:

• Mode of Instruction:
Face-to-Face
• Faculty:
• Cecile Ane, Professor
• Joshua Cape, Assistant Professor
• Richard Chappell, Professor
• Peter Chien, Professor
• Jessi Cisewski-Kehe, Assistant Professor
• Deshpande, Sameer, Assistant Professor
• Nicolas Garcia Trillos, Assistant Professor
• Yinqiu He, Assistant Professor
• Hyunseung Kang, Associate Professor
• Sunduz Keles, Professor
• Bret Larget, Professor
• Keith Levin, Assistant Professor
• Wei-Yin Loh, Professor
• Michael Newton, Professor
• Vivak Patel, Assistant Professor
• Alejandra Quintos, Assistant Professor
• Garvesh Raskutti, Associate Professor
• Karl Rohe, Professor
• Kris Sankaran, Assistant Professor
• Jun Shao, Professor
• Miaoyan Wang, Assistant Professor
• Yahzen Wang, Professor
• Brian Yandell, Professor
• Chunming Zhang, Professor
• Yiqiao Zhong, Assistant Professor
• Jun Zhu, Professor