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Education / Graduate Education / PhD Programs / Statistics / About the Program / Master of Arts in Statistics
 

Program for the Degree of Master of Arts in Statistics

Other Available Graduate Programs
PhD in Statistics
PhD in Statistics (bioinformatics concentration)
MS in Medical Statistics

The requirements for entry into the MA program in statistics are the same as those for entry into the PhD program. Entering MA students should have a strong background in mathematics, including advanced calculus or mathematical analysis, a course in linear and/or matrix algebra, and a year of probability and mathematical statistics. The MA degree 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.

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)
Program of study 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)