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Education / Graduate Education / PhD Programs / Statistics / Master of Arts in Statistics
 

Master of Arts in Statistics Program

Other Available Graduate Programs
PhD in Statistics (traditional program)
PhD in Statistics (bioinformatics concentration)
Master of Science in Biostatistics (Medical Statistics)

Program Overview

The Master of Arts (MA) degree in Statistics requires satisfactory completion of at least 32 credits and a final comprehensive written examination; no thesis is required. Of the 32 credits, at least 24 must be in departmental courses primarily at the 400 level or above.

A typical program of study includes three semesters of coursework. A balanced program is worked out with the student’s advisor. The final comprehensive examination is administered during the summer following completion of the first year of study.

Students must begin the MA program during the Fall semester.

Prerequisites

The requirements for entry into the MA program in Statistics are the same as those for entry into the Statistics PhD program. Entering MA students should have a strong background in mathematics, including three semesters of calculus (through multivariable calculus), a course in linear and/or matrix algebra, and a year of probability and mathematical statistics. A course in real analysis is encouraged; a course in statistical methods is also recommended.

Typical Program of Study

For students who enter the program during an even-numbered year:

Year 1: Fall (12 credits)

  • BST 401 Probability Theory (4 credits)
  • BST 411 Statistical Inference (4 credits)
  • BST 430 Introduction to Statistical Computing (4 credits)

Year 1: Spring (12 credits)

  • BST 426 Linear Models (4 credits)
  • BST 413 Bayesian Inference (4 credits)
  • BST 466 Categorical Data Analysis (4 credits)
  • Students may also consider taking BST 465 Design of Clinical Trials (4 credits)

Year 2: Fall (8 credits)

  • BST 432 High Dimensional Data Analysis (4 credits)
  • BST 479 Generalized Linear Models (4 credits)

For students who enter the program during an odd-numbered year:

Year 1: Fall (12 credits)

  • BST 401 Probability Theory (4 credits)
  • BST 411 Statistical Inference (4 credits)
  • BST 430 Introduction to Statistical Computing (4 credits)

Year 1: Spring (12 credits)

  • BST 426 Linear Models (4 credits)
  • BST 412 Large Sample Theory (4 credits)
  • BST 466 Categorical Data Analysis (4 credits)
  • Students may also consider taking BST 465 Design of Clinical Trials (4 credits) or BST 513 Analysis of Longitudinal and Dependent Data (4 credits)

Year 2: Fall (8 credits)

  • BST 432 High Dimensional Data Analysis (4 credits)
  • BST 514 Survival Analysis (4 credits)