The MS in Biostatistics is an academic degree program for students with a background in math and a strong interest in public health. The program emphasizes statistical theory and methods so that students are prepared to be effective statistical collaborators in interdisciplinary studies; and lead the design and execution of studies.
Careers
Recent graduates hold the following positions:
- Opioid compliance specialist, Georgia Dept. of Public Health
- Actuarial analyst, Highmark Health
- Biostatistician, Ichan School of Medicine at Mt. Sinai
- Statistician, Mayo Clinic
- Business analyst, PNC Financial Services
- Biostatistician, University of Pittsburgh Dept. of Critical Care Medicine
- Biostatistician, University of Pittsburgh Dept. of Orthopedic Surgery
- Data analyst, University of Pittsburgh School of Pharmacy
- Statistician, University of Pittsburgh School of Social Work
- Biostatistician, Cleveland Clinic
- Data-analyst, DeFiner
Recent Thesis Titles
Browse titles in D-Scholarship, the institutional repository for research output at the University of Pittsburgh
MS Competencies
Graduates will be able to:
- Identify appropriate problem definitions, study designs and data collection methods to address public health problems
- Utilize fundamental theoretical concepts and relationships to effectively apply and interpret common statistical inference techniques
- Use common biostatistical inference techniques and regression models to analyze data and interpret the results for public health practice
- Recognize strengths and weaknesses of approaches, including alternative designs, data sources and analytic methods
- Communicate the meaning, potential and results of biostatistical analyses to potential collaborators with varying degrees of statistical knowledge
- Effectively use SAS software for advanced data management and in-depth statistical analysis
- Appropriately utilize generalized linear models to analyze clustered and longitudinal data (binary/continuous/count) applicable to health sciences
- Derive and interpret fundamental quantities and statistics from various survival analysis models; perform the analysis and interpret the results from nonparametric, parametric, and semiparametric survival models
- Apply advanced methods or theories in at least three major areas of classical biostatistics
Requirements
40 credits, including:
- Coursework in fundamentals of statistical theory and applications
- A statistical consulting practicum
- Coursework in epidemiology and public health
- Faculty-guided thesis project or Capstone course to prepare an appropriate MS thesis
Program Information
MS Two-year Schedule (PDF, 2023-24)
MS Eighteen-month Schedule (PDF, 2023-24)
MS Degree Requirements Worksheet (PDF, 2023-24)
Student Handbook (PDF, 2023-24)