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The Master of Science in Biostatistics (MSBST) is a 33-credit hour program consisting of 21 credits in core biostatistics courses and a capstone, which gives candidates the opportunity to learn consulting and collaboration practices through valuable experiential learning opportunities. The remaining 12 hours are a mix of customizable electives, which includes epidemiology courses and more. Courses are offered in the Fall and Spring semesters each year.

Learning Objectives and Core Courses

Learning Objectives

  • Demonstrate the ability to construct written or oral communication, which easily and accurately presents results and interpretations of a statistical analysis, to a collaborating health scientist or other vested audience
  • Develop a statistical analysis plan, which implements biostatistical methodology to address a biomedical research question while remaining aware of the limitations of the methodology
  • Analyze data and apply concepts from the intersection between biostatistics and epidemiology
  • Develop code for statistical software in order to college and analyze data sets using appropriate biostatistical methods

Core Courses

  • BST 635 - Databases and SAS Programming
  • BST 675 - Simulation Based Inference for Health Data Science
  • BST 681 - Linear Regression
  • BST 682 - Generalized Linear Models
  • BST 693 - Statistical Practice in Public Health
  • CPH 712 - Advanced Epidemiology
  • BST 699 - Advanced Biostatistics Practice

Electives

  • BST 535 - Introduction to R Programming
  • BST 631 - Design and Analysis of Health Surveys
  • BST 636 - Data Mining in Public Health
  • BST 655 - Introduction to Statistical Genetics
  • BST 661 - Survival Analysis
  • BST 762 - Longitudinal Data Analysis
  • BST 663 - Analysis of Categorical Data
  • BST 664 - Design and Analysis of Clinical Trials
  • BST 676 - Theory for Biostatistics Methods
  • BST 698 - Bayesian Modeling in Biostatistics
  • EPI 717 - Causal Inference

Vice Chair

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Amanda Ellis, PhD

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MSBST Brochure

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MSBST AET Page

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