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Education / Graduate Education / PhD Programs / Statistics / Master of Science in Biostatistics
 

Master of Science in Biostatistics

Other Available Graduate Programs
PhD in Statistics (traditional)
PhD in Statistics (bioinformatics concentration)
Master of Arts in Statistics

Program Overview

The Master of Science program in Biostatistics is primarily intended for students who wish to follow careers in health-related professions such as those in the pharmaceutical industry and biomedical or clinical research organizations.

The program consists of one core year (two semesters) of coursework as well as a capstone  project (BST 493), which is normally done in the summer after the core program. There are no thesis or language requirements. The degree requires 32 credit hours consisting of all the 400-level courses listed below; substitutions may be made with approval of the faculty program advisor.

The capstone project requirement is met by working with medical center investigators on an applied project. Students are required to write a formal report summarizing the findings from their research project. These findings are presented in a public lecture, which is followed by an oral qualifying examination.

Prerequisites

The program is open to students with a substantial background in statistics. For entry into the program, three semesters of calculus, a course in linear and/or matrix algebra (similar to MTH 165), a course in probability (see STT 201), a course in mathematical statistics (see STT 203), and a course in applied statistics (similar to STT 212) are required.

Typical Program of Study

A typical program for an entering student without previous advanced training is as follows:

Fall (12 credits)

  • Statistical Inference I (4 credits)
  • Biostatistical Methods I (4 credits)
  • Introduction to Statistical Computing (3 credits)
  • Introduction to SAS (1 credit)

Spring (12 credits)

  • Biostatistical Methods II (4 credits)
  • Design of Clinical Trials (4 credits)
  • One elective:
    • Bayesian Inference (4 credits)
    • Linear Models (4 credits)
    • Genomic Data Analysis (4 credits)

Summer (8 credits)

  • Capstone Project (8 credits)