The Master of Science in Biostatistics provides students with a strong foundation in statistical methods, data analysis, and computational techniques applied to biological and medical research. The program emphasizes probability theory, statistical modeling, and bioinformatics applications, preparing students to address complex challenges in healthcare, genetics, and epidemiology. Students develop expertise in statistical modeling, data analysis, and computational tools, equipping them to analyze large datasets, interpret biological data, and contribute to evidence-based research. Through applied projects, laboratory exercises, and research collaborations, learners gain practical experience in designing studies, conducting statistical analyses, and implementing bioinformatics solutions.
Over the two-year program, students engage in intensive coursework, applied research, and collaborative learning that strengthens both technical and analytical competencies. The curriculum covers biostatistical theory, statistical computing, epidemiology, and research methodology, providing a solid foundation for professional practice. By integrating theoretical knowledge with practical application, students develop competencies in data interpretation, statistical programming, and research design. This approach prepares graduates to contribute effectively to academic institutions, healthcare organizations, pharmaceutical companies, and research centers while fostering analytical thinking, problem-solving skills, and expertise in biostatistics and bioinformatics.
Key information
Key Facts
- Program Title: Biostatistics
- Degree Type: Master of Science
- Duration: 2 years
- Mode of Study: Full-time, On Campus
- Application Deadline: 15 December 2025
- Location: Yale University, United States
- Field of Study: Bioinformatics & Biostatistics
- Language of Instruction: English
Program Structure
Semester 1 – Foundations in Biostatistics
• Introduction to Biostatistics
• Probability and Statistical Theory
• Research Methods in Life Sciences
• Statistical Computing and Software
Semester 2 – Applied Biostatistical Methods
• Regression Analysis and Modeling
• Epidemiology and Study Design
• Data Management and Cleaning
• Elective Modules in Biostatistics or Bioinformatics
Semester 3 – Advanced Techniques & Applied Research
• Survival Analysis and Longitudinal Data
• Advanced Statistical Computing
• Applied Research Projects
• Seminar: Case Studies in Biostatistics
Semester 4 – Capstone & Professional Practice
• Independent Research / Thesis
• Data Analysis and Interpretation
• Portfolio Development and Presentation
• Professional Development and Networking
Career Opportunities
Graduates of this program are prepared for analytical and research-focused careers in healthcare, academia, and industry. Career opportunities include positions in biostatistics departments, pharmaceutical companies, public health organizations, research institutions, and healthcare analytics firms. Graduates may also pursue roles in clinical trial analysis, bioinformatics, epidemiological research, and data-driven decision-making. The program equips students with strong analytical, computational, and research skills, enabling them to manage complex datasets, develop statistical models, and provide evidence-based insights. With expertise in biostatistics and bioinformatics, graduates are well-prepared to influence research outcomes, optimize health interventions, and contribute meaningfully to scientific discovery.
Why Choose This Program
This program is ideal for students seeking an applied and research-intensive education in biostatistics, offering a curriculum that emphasizes statistical modeling and computational analysis. Its four-semester structure provides opportunities for applied research, programming projects, and case studies, allowing learners to integrate theoretical knowledge with practical problem-solving skills. Through mentorship, collaborative projects, and capstone experiences, students acquire the expertise, analytical skills, and professional confidence necessary to design studies, analyze biological data, and implement computational solutions effectively. Graduates leave prepared to lead in data-driven research, advise on statistical methodologies, and make significant contributions to the fields of biostatistics and bioinformatics.
Contact Information
For further information, please contact the admissions office at:
Phone: +1 203 432 2300
Email: admissions@yale.edu
Address: University of Yale, New Haven, CT 06520, United States
