MS - Biostatistics Concentration

Biostatistics is one of the primary skills needed for the development and practice of public health – the methods of this discipline are appropriate for quantifying the possible effects of risk factors and health interventions on individuals and groups. The MS with a concentration in Biostatistics is a two-year program that provides training in clinical trials, epidemiologic methodology, implementation science, statistical genetics, and mathematical models for infectious diseases.

Biostatistics students may choose from three pathways:

• Biostatistics Standard Pathway
• Biostatistics Implementation and Prevention Science Methods Pathway
• Data Science Pathway

Applicants apply to the MS in Biostatistics and if admitted will have until the spring term of their first year to choose either the Standard Pathway or the Implementation and Prevention Science Methods Pathway.

Students wishing to choose the Data Science Pathway must choose at the start of the first-year Fall term. In contrast to the more general MPH degree, the MS degree emphasizes the mastery of biostatistical skills from the beginning of the plan of study. While graduates of this program may apply to the PhD degree program, the MS degree is itself quite marketable as a terminal degree. Part-time enrollment is permitted.

Please note that you may apply to both the MPH and the MS program simultaneously, but they do require separate applications.

The length of study for the MS in Biostatistics (all pathways) is two years. Full-time or part-time enrollment is permissible.

This program requires General GRE test scores. Please send them to institution code 3987 (there is no department code).

Students with strong quantitative skills from all undergraduate majors are welcome to apply. Students should have, at a minimum, previous college-level coursework in multivariable calculus (a.k.a., calculus 3) and linear algebra. Experience with introductory statistics and statistical programming language (e.g., R, SAS, python) is helpful, but not required.

Master of Science students in Biostatistics at the Yale School of Public Health enage with the field through summer internships and capstone or thesis projects. These immersive experiences provide robust opportunities for the real-world application of public health knowledge and skills and support your career goals. Many students report inspiring, life changing experiences from their time around the world and in local settings.

Opportunities for research abound at Yale. Although a master’s thesis is optional for MS students in biostatistics, many students use their summer internship to do research that culminates in a thesis. Capstone projects also provide experience to work with faculty labs and research teams to access data and formulate their analysis. In addition, many students work as research assistants at the Yale School of Public Health, Yale School of Medicine, Yale New Haven Hospital or the VA. Many of these projects culminate in peer review publications.

• Acumen
• Adaptive Biotechnologies
• Ainylam Pharmaceuticals
• Alibaba Group ---Management Executive Council
• American International Group,Inc.
• Analysis Group
• Bain and Company in Shanghai
• Bank of Communications - NY
• Bank of NY Mellon Corporation
• Bayer-Monsanto, Woodland, CA
• Boehringer Ingelheim
• Bristol-Myers Squibb
• CARDET in Cyprus
• CB Sciences
• Celegene
• Center for Outcomes Research and Evaluation - CORE - Yale New Haven Hospital
• Center for Perinatal, Pediatric and Environmental Epi at Yale
• Citadle, LLC
• closedloop.ai
• Digitas in Boston
• Dr. Emma Zang (Sociology)
• Dr. Forrest Crawford lab
• Dr. Heping Zhang lab
• Dr. Hongyu Zhao Lab
• Dr. Josh Warren
• Dr. Maria Ciarleglio
• Dr. Shi-Yi Wang
• Dr. Wei Wei
• Dr. Yize Zhao
• Ernst and Young
• Facebook, NY
• FDA
• Fulcrum Analytics
• Genetech
• GNS Healthcare,Inc.
• Goldenson Center for Actuarial Research- Uconn
• Goldman Sachs, NY
• Guotai Junan Securities Co., Ltd
• Health Services Advisory Group, Phoenix
• Mayo Clinic/Genetech - California
• McKinsey and Company
• Medical Consulting Corporation/China Merchants Securities/GF Securities
• Microsoft Research
• Mid-Atlantic Permante Med Group
• Millenuium/Takeda
• Mirae Asset Investment Management in Shanghai
• Netease - Hangzhou China
• NIH/Child Health and Human Dev
• Orient Securities
• People's Bank/Risk Mgmt
• Pfizer
• Pulse8, Inc. startup in MD
• Randstad
• Regeneron
• Remedy Partners - startup
• Rosenthal Collins group/Chicago
• Staff Strategic Holdings
• The Speree Institute
• Travelers Insurance
• United Nations/Data Science
• Univ. of Wisconsin/Madison
• VA Hospital - West Haven
• Verus Analytics LLC, NY
• WuXI NextCODE Genomics USA
• Yale Center for Analytical Sciences (YCAS)
• Yale Center for Asthma and Airway Diseases
• Yale - CORE
• Yale Dept. of Psychiatry and Genetics
• Yale Internal Medicine/Geriatrics/Red CAP
• Yale Internal Medicine/Pulmonary & Pulmonary, Critial Care & Sleep Medicine Ctr
• Yale New Haven Health
• Pulmonary, Critical Care and Sleep Medicine (PCCSM) Center at Yale
• Yale Program on Aging
• Yale Stress Center
• Yale School of Management
• Yale Dept Psychiatry
• Yale School of Medicine

• Longitudinal trajectories of nicotine product use in adolescents in the Population Assessment of Tobacco and Health study
• A Directionally-Varying Change Points Model for Quantifying the Impact of a Point Source
  
• A Bayesian Design for Trials with Multiple Indications under Multisource Exchangeability Assumptions
  
• Predicting Avoidable Medical Visits
• Treatment Effects Assessment in Multi-Regional Clinical Trials (MRCTs) Using Bayesian Methods
• Analysis of DNA methylation data to understand the relationship of appetite-related hormones and weight gain.
• A statistical framework to quantify genetic variability in De Novo mutations for complex diseases.
• Analysis of recurrence of myocardial infraction using GWAS information
• An algorithm for identifying naturalistic boundaries in robot-derived kinematic data and the efficacy of sub-setting in modeling Fugl-Meyer Assessments
• Recidivism of Women Living with HIV and at-risk for HIV on Probation: A Recurrent Events Survival Analysis
• Critical Window Variable Selection Modeling for Air Pollution and Birth Outcome
• Identifying Disease Heterogeneity from Gene Expression Data by Integrating Prior Pathway Information using Dirichlet Process
• Assessing non-coding genome annotations through enrichment analysis of 15 genome-wide association studies
• Longitudinal Associations of Gay and Bisexual Men's Stress and Mental Health
• Competing Risk Models for Assessing Mortality Among Men with Prostate Cancer