Program Overview
The MA in Biostatistics program at the University at Buffalo prepares graduates for careers in biostatistical research and public health. The program provides a strong foundation in statistical methods, biostatistics theory, and applications, with a focus on data analysis, epidemiology, and public health. Graduates are equipped to design and analyze studies, apply advanced statistical techniques, and communicate statistical results effectively. The program is fully accredited by CEPH and offers scholarships and assistantships to support students financially.
Program Outline
Biostatistics MA Program Extraction
Degree Overview:
- Goal: The MA in Biostatistics program prepares graduates to excel in biostatistical research and contribute to advancements in public health through:
- Developing a deep understanding of statistical methods
- Applying biostatistical methods to real-world data
- Communicating statistical results effectively
- Collaborating with other researchers on interdisciplinary teams
- Curriculum: The program provides a strong foundation in biostatistics through coursework in:
- Statistical methods
- Biostatistics theory
- Biostatistical applications
- Epidemiology
- Public health
- Data analysis
- Learning Outcomes: Graduates will be able to:
- Design and analyze studies in public health and biomedical research
- Apply advanced statistical techniques to complex datasets
- Interpret and communicate statistical results effectively
- Contribute to the development of new statistical methodologies
- Work effectively as part of research teams
Outline:
The program consists of 30 credit hours distributed across core courses, elective courses, and a capstone project:
Core Courses (24 credits):
- Biostatistics I
- Biostatistics II
- Statistical Computing
- Statistical Methods for Public Health
- Introduction to Epidemiology
- Linear Models for Health Sciences
- Categorical Data Analysis
- Survival Analysis
- Longitudinal Data Analysis
Electives (6 credits)
Students choose two elective courses from a range of topics, including:
- Advanced Biostatistics Methods
- Statistical Genetics
- Clinical Trials
- Data Visualization
- Machine Learning for Health
- Environmental Health Statistics
- Health Informatics
Capstone Project (2 credits)
The capstone project provides an opportunity for students to apply their knowledge and skills to a real-world research problem. Students will work closely with a faculty mentor to design and conduct a study, analyze data, and prepare a final report.
Course Schedule:
- Courses are typically offered in the Fall and Spring semesters.
- Some courses are also offered online.
- The program can be completed in two years of full-time study.
- Part-time options are available.
Assessment:
- Students are assessed through a variety of methods, including:
- Exams
- Problem sets
- Presentations
- Term papers
- The capstone project
Teaching:
The program employs a variety of teaching methods to engage students and promote active learning, including:
- Lectures
- Group discussions
- Simulation exercises
- Hands-on data analysis projects
- Individualized mentorship
Careers:
- Graduates are prepared for a variety of careers, including:
- Biostatistician
- Research Scientist
- Epidemiologist
- Public Health Analyst
- Data Scientist
- Many graduates go on to work in research institutions, government agencies, pharmaceutical companies, and private consulting firms.
Other:
- The program is fully accredited by the Council on Education for Public Health (CEPH).
- The program offers several scholarships and assistantships to support students financially.
- The Department of Biostatistics has a strong faculty with expertise in a variety of areas, including:
- Statistical methods
- Epidemiology
- Public health
- Data analysis This detailed extraction of the Biostatistics MA program at the University at Buffalo provides comprehensive information on the Degree Overview, Outline, Assessment, Teaching, Careers, and Other aspects of the program, allowing for an informed decision regarding possible enrollment.
