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Biostatistics is an innovative field that involves the design, analysis, and interpretation of data for studies in public health and medicine. Biostatistics experts play a crucial role in drawing insightful conclusions about disease and health risks by applying, adjusting, and developing mathematical and statistical methods to address factors that impact health.

Our students benefit from collaboration as statisticians with the renowned University of Pittsburgh School of Medicine and UPMC, Pennsylvania’s largest academic medical center, and have access to real-world research opportunities and extensive University computing facilities. Through rigorous courses, students will

• gain a comprehensive understanding of statistical methods in the context of public health and medical problems;
• work with faculty on developing new and innovative methodologies and analytical techniques;
• have the opportunity through both research and service to apply these methods to current and pressing concerns in medicine and public health.

Contact Information

Admissions

In addition to the School-level Admission Requirements , admission to all Biostatistics degree programs requires two semesters (six credits) of college-level calculus. Calculus courses taken in the Advanced Placement Program can be considered towards this requirement.

Applying for Admission to Pitt Public Health  

Early Admission

University of Pittsburgh undergraduates may apply for early admission to the Biostatistics MS Program. Students must have completed the number of undergraduate credits required by their school before they can become a Biostatistics MS student.

Accelerated Bachelor’s/Master’s Program   

Accelerated Bachelor’s/Master’s Program Admission Requirements  

Financial Aid

The department awards tuition and stipend to full-time PhD students. The department awards financial aid to applicable MS students at the time of admission and a limited number of awards for the enrolled students.

Tuition and Billing  

Tuition & Financial Aid  

Advanced Standing and Credit Transfer

Acceptance of a maximum of 12 credits taken as a non-degree student at Pitt Public Health is at the discretion of the department and program.

Students enrolled at Pitt Public Health may take credits in another school or institution, providing that their department has approved application of those credits to the degree requirements. In all cases, any combination of advanced standing credits and credits taken from another school or institution during enrollment at Pitt Public Health may not exceed the limits established by the University or the Regulations Governing Graduate Study at the University of Pittsburgh .

Students with previous graduate experience in Biostatistics or a related field may apply to transfer credits for graduate-level coursework successfully completed with a grade of B or better.  PhD students may apply to transfer up to 24 credits and MS students up to 6 credits. The course credits to be transferred must be reviewed and approved by the student’s academic advisor. Students who receive transfer credits for a public health core course must complete a Core Course Exemption Form in addition to the credit transfer paperwork to exempt out of those classes. Students who receive transfer credits for BIOST 2179  must complete a Course Exemption Form in addition to the credit transfer paperwork to exempt out of the course. All transfer credit and course exemption paperwork must be completed by the end of a student’s first term of study.

Programs

• Biostatistics, PhD

• Biostatistics, MS
• Biostatistics, MS - Health Data Science (HDS) Concentration
• Biostatistics, MS - Statistical and Computational Genomics (SCG) Concentration

Courses

• BIOST 2000 - TEACHING PRACTICUM
• BIOST 2011 - PRINCIPLES OF STATISTICAL REASONING
• BIOST 2016 - SAMPLING DESIGN AND ANALYSIS
• BIOST 2021 - SPECIAL STUDIES
• BIOST 2022 - CAPSTONE PREPARATION
• BIOST 2025 - BIOSTATISTICS SEMINAR
• BIOST 2040 - ELEMENTS OF STOCHASTIC PROCESSES
• BIOST 2041 - INTRODUCTION TO STATISTICAL METHODS
• BIOST 2058 - SCIENTIFIC COMMUNICATION SKILLS
• BIOST 2059 - CONSTRAINED STATISTICAL INFERENCE WITH APPLICATIONS
• BIOST 2067 - APPLIED META-ANALYSIS
• BIOST 2068 - INTRODUCTION TO CASUAL INFERENCE
• BIOST 2069 - STATISTICAL METHODS FOR OMICS DATA
• BIOST 2080 - ADVANCED STATISTICAL LEARNING
• BIOST 2081 - MATHEMATICAL METHODS FOR STATISTICS
• BIOST 2099 - CAPSTONE
• BIOST 2131 - FOUNDATIONS OF STATISTICAL THEORY
• BIOST 2137 - FOUNDATIONS OF STATISTICAL THEORY
• BIOST 2141 - BIOSTATISTICAL METHODS
• BIOST 2142 - APPLIED REGRESSION ANALYSIS
• BIOST 2143 - LONGITUDINAL AND CLUSTERED DATA ANALYSIS
• BIOST 2145 - INTRODUCTION TO HEALTH DATA SCIENCE
• BIOST 2150 - APPLIED SURVIVAL ANALYSIS: METHODS AND PRACTICE
• BIOST 2151 - BAYESIAN DATA SCIENCE
• BIOST 2154 - STATISTICAL METHODS FOR OMICS DATA
• BIOST 2155 - INTRODUCTORY STATISTICAL LEARNING FOR HEALTH SCIENCES
• BIOST 2162 - CLINICAL TRIALS: METHODS AND PRACTICE
• BIOST 2165 - STATISTICAL EVALUATION OF BIOMARKERS AND CLASSIFICATION TOOLS
• BIOST 2168 - INTRODUCTION TO CAUSAL INFERENCE
• BIOST 2173 - SAS FOR DATA MANAGEMENT AND ANALYSIS
• BIOST 2174 - ADVANCED R COMPUTING
• BIOST 2179 - BIOSTATISTICS CONSULTING PRACTICUM
• BIOST 3000 - DOCTORAL TEACHING PRACTICUM
• BIOST 3010 - RESEARCH AND DISSERTATION PHD
• BIOST 3011 - INTRODUCTION TO STATISTICAL INFERENCE 1
• BIOST 3012 - INTRODUCTION TO STATISTICAL INFERENCE 2
• BIOST 3021 - ADVANCED STATISTICAL INFERENCE 1
• BIOST 3022 - ADVANCED STATISTICAL INFERENCE 2
• BIOST 3025 - LINEAR MODELS
• BIOST 3042 - MIXED MODELS
• BIOST 3050 - SURVIVAL ANALYSIS
• BIOST 3065 - ANALYSIS OF DATA WITH MISSING VALUES

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