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PhD Course Requirements

The Statistics PhD program requires successful completion of 16 formal courses. Additional courses can be taken for audit or credit. The PhD Program Director will create a program of study with each student during one-on-one advising sessions.

Required Courses

BST 401       Probability Theory
BST 411       Statistical Inference I
BST 412       Statistical Inference II
BST 413       Bayesian Inference
BST 426       Linear Models
BST 430       Introduction to Statistical Computing
BST 432       High Dimensional Data Analysis (BCB concentration)
BST 434       Genomic Data Analysis (BCB concentration)
BST 461       Biostatistical Methods I
BST 462       Biostatistical Methods II
BST 479       Generalized Linear Models
BST 487       Seminar in Statistical Literature †
BST 513       Analysis of Longitudinal/Dependent Data
BST 514       Survival Analysis
IND 419       Introduction to Quantitative Biology (BCB concentration)

† 4 semesters

Strongly Recommended Courses

BST 402       Stochastic Processes
BST 432       High Dimensional Data Analysis (traditional program)
BST 465       Design of Clinical Trials
BST 516       Causal Inference
BST 531       Nonparametric Inference