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Summary
The Master of Science programs in Biostatistics provide rigorous training in the statistical, bioinformatics, and data science methods used in biomedical and health sciences.
The School offers three Master of Science programs in biostatistics—each designed for students with different levels of professional experience and educational goals. If you have questions, contact biostat_admissions@hsph.harvard.edu.
About
The Master of Science 42.5-credit program (SM-42.5) is designed for established professionals with master’s or doctoral degrees who are dedicated to improving the health of people everywhere through quantitative research. SM-42.5 students learn to critically evaluate scientific literature and apply scientific knowledge in real-world settings.
On Campus (Fall start) • Full-time (1 year)
Curriculum
- BST 220: Applied Regression Methods
- BST 222: Basics of Statistical Inference
- BST 221: Applied Data Structures and Algorithms
- BST 223: Applied Survival Analysis
- BST 226: Applied Longitudinal Analysis
- BST 227: Introduction to Statistical Genetics
- BST 228: Applied Bayesian Analysis
- BST 235: Advanced Regression and Statistical Learning
- BST 262: Computing for Big Data
- and many others – see handbook linked below
Competencies
The Master of Science program prepares students in five specific competencies:
- Designing research studies in medicine and public health (including recognizing study design and scientific/societal context, population selection and sample size justification, methods of data acquisition, curation and organization, data management methods, data analysis plans and protocol development);
- Analyzing and interpreting quantitative data for scientific inference and/or prediction studies (including data exploration, graphical and tabular displays, visuals, descriptive statistics, evaluation of modeling context and approaches, analysis methods, reproducibility, and choice of appropriate statistical software and programming languages);
- Using modern computational methods to effectively analyze complex medical and public health data (including linear, generalized linear, penalized, additive, time-to-event (survival), and correlated outcome regression methods and extensions, statistical and machine learning, and other data science methods, bioinformatics, statistical genetics, and more);
- Collaborating, presenting, and communicating effectively with research scientists in related disciplines;
- Using probabilistic and statistical reasoning, theory, and methods to effectively analyze non-standard problems arising in medicine and public health and assisting biostatistical researchers in the conduct of methodologic research. This competency is demonstrated through the completion of a Culminating Experience and corresponding report.
Our Community
The Department of Biostatistics hosts a variety of extracurricular seminars, working groups, and lectures focused on specific public health problems, creating opportunities to expand their knowledge while connecting with faculty and fellow students. It also participates in Data Adventure Day, when statistics students across Harvard help introduce high school students to the discipline. For those looking to expand their ability to present statistical analysis to others, the department offers workshops designed to help students hone their public speaking and writing skills.
The Harvard Chan School is committed to supporting our students both in and out of the classroom. The school offers a wide variety of academic support services, including research support through the Countway Library of Medicine and academic coaching and tutoring for students seeking additional help with either an overall transition to graduate school or specific subject matter.
Career Outcomes
A Master of Science 42.5-credit (SM-42.5) degree opens an extraordinary number of pathways to a meaningful career. Graduates of the SM-42.5 program are trained to pursue careers in a variety of industries:
- Biotech/pharma
- Health care organizations
- National and international government agencies
- Non-profit/NGO
- Public and private sector enterprises
- Research institutions
- University/research
Eligibility Criteria
The Master of Science 42.5-credit (SM-42.5) program is targeted towards significantly established research professionals. For most fields, applicants are required to have a doctoral degree and relevant work experience—contact admissions or the department for more detailed information.
Application Requirements
All applications must be submitted through SOPHAS – the centralized application for schools and programs of public health. In addition to the application, applicants must submit:
- Statement of purpose and objectives
- Official test scores
- Three letters of reference
- Resumé/curriculum vitae
- Post-secondary transcripts or mark sheets (World Education Services credential evaluation for applicants with degrees from outside of the United States.)
- English language proficiency (TOEFL/IELTS/Duolingo English Test), if applicable
Application Deadline: December 1
Applicants may apply to only one degree program for either full- or part-time status. Applications are reviewed in their entirety and decisions are released via email in late February/early March. Decisions are not released until all application components are received.
About
The 60-credit Master of Science program in Biostatistics advances students’ research skills in statistical, bioinformatics, and data science, especially as applied to the biomedical and health sciences.
As a student, you will learn:
- The biostatistical and bioinformatics methods used in planning research studies;
- How to conduct analyses and write reports;
- How to interpret numerical data in medicine and public health;
- How to collaborate and communicate effectively with scientists in related fields.
- The SM-60 program includes a thesis requirement.
On Campus (Fall start) • Full-time (1.5 years) • Part-time (2+ years)
Learning Objectives
- BST 220: Applied Regression Methods
- BST 222: Basics of Statistical Inference
- BST 223: Applied Survival Analysis
- BST 226: Applied Longitudinal Analysis
- BST 221: Applied Data Structures and Algorithms
- BST 227: Introduction to Statistical Genetics
- BST 228: Applied Bayesian Analysis
- BST 260: Introduction to Data Science
- BST 267: Introduction to Social and Biological Networks
- BST 268: Functional Data Analysis in Digital Health
- EPI 511: Advanced Population and Medical Genetics
- GHP 525: Econometrics for Health Policy
- RDS 280: Decision Analysis for Health and Medical Practices
- and many others – see handbook linked below
Competencies
- Designing research studies in medicine and public health (including recognizing study design and scientific/societal context, population selection and sample size justification, methods of data acquisition, curation and organization, data management methods, data analysis plans and protocol development);
- Analyzing and interpreting quantitative data for scientific inference and/or prediction studies (including data exploration, graphical and tabular displays, visuals, descriptive statistics, evaluation of modeling context and approaches, analysis methods, reproducibility, and choice of appropriate statistical software and programming languages);
- Using modern computational methods to effectively analyze complex medical and public health data (including linear, generalized linear, penalized, additive, time-to-event (survival), and correlated outcome regression methods and extensions, statistical and machine learning, and other data science methods, bioinformatics, statistical genetics, and more);
- Collaborating, presenting, and communicating effectively with research scientists in related disciplines;
- Disseminating new statistical and/or applied knowledge in a research discipline through the preparation of a written report of original research, applied biostatistical analyses, comparison of different statistical methodologies, or some similar novel body of work in the biostatistics and allied fields, and the subsequent oral presentation of such results. This competency is demonstrated through the completion of a Biostatistics Master’s Thesis
Our Community
The Department of Biostatistics hosts a variety of extracurricular seminars, working groups, and lectures focused on specific public health problems, creating opportunities to expand their knowledge while connecting with faculty and fellow students. It also participates in Data Adventure Day, when statistics students across Harvard help introduce high school students to the discipline. For those looking to expand their ability to present statistical analysis to others, the department offers workshops designed to help students hone their public speaking and writing skills.
Harvard Chan School offers a wide variety of academic support services, including research support through the Countway Library of Medicine and academic coaching and tutoring for students seeking additional help with either an overall transition to graduate school or specific subject matter.
Beyond academics, the school is home to more than 40 official student organizations focusing on public health issues, cultural affinities, and extra-curricular interests. These groups and other offices throughout the school plan events on campus and around Boston.
Career Outcomes
A Master of Science 60-credit degree opens an extraordinary number of pathways to a meaningful career. Graduates of the SM-60 program are trained to pursue careers in a variety of industries:
- Biotech/pharma
- Health care organizations
- National and international government agencies
- Non-Profit/NGO
- Public and private sector enterprises
- Research institutions
- University/research
Eligibility Criteria
The Master of Science 60-credit program (SM-60) requires:
- Minimum prerequisite for entrance: Bachelor’s degree or non-U.S. equivalent;
- Excellent written and spoken English;
- An undergraduate degree (major or minor concentration) in mathematical sciences or allied fields (pure or applied mathematics, statistics, economics, data science, computer science, bioinformatics, etc.) with a strong interest in health science. Also, a natural science, social science, or other concentration with a minor in a mathematical science or successful completion of the necessary prerequisites listed below plus at least an intro statistics course;
- Successful completion of calculus through multivariable integration;
- Successful completion of one semester of linear algebra or matrix methods;
- Practical knowledge of computer scripting and programming, and experience with a statistical computing language such as R, Python, or SAS.
NOTE: Applicants must clearly list all required prerequisite courses from the bullet points above (calculus through multivariable integration, linear algebra) including dates taken, grades received, institution, and whether the course was online or in person, at the bottom of their Statement of Purpose, in order to be reviewed for admission.
Application Requirements
All applications must be submitted through SOPHAS – the centralized application service for public health programs. In addition to the application, applicants must submit:
- Statement of purpose and objectives
- Official test scores
- Three letters of reference
- Resumé/curriculum vitae
- Post-secondary transcripts or mark sheets (World Education Services credential evaluation for applicants with degrees from outside of the United States.)
- English language proficiency (TOEFL/IELTS/Duolingo English Test), if applicable
Application Deadline: December 1
Applicants may apply to only one degree program for either full- or part-time status. Applications are reviewed in their entirety and decisions are released via email in late February/early March. Decisions are not released until all application components are received.
About
The 80-credit Master of Science program in Biostatistics provides students with the skills they need to advance public health through rigorous quantitative research and data analysis.
As a student, you will learn:
- The basics of statistical theory;
- The biostatistical and bioinformatics methods used in planning research studies;
- How to conduct analyses and write reports;
- How to interpret numerical data in medicine and public health;
- How to collaborate and communicate effectively with scientists in related fields.
Students also enjoy the opportunity to work with faculty on ongoing research projects and serve as teaching assistants for departmental courses.
On Campus (Fall start) • Full-time (2 years) • Part-time (3 years)
Curriculum
- BST 220: Applied Regression Methods
- BST 222: Basics of Statistical Inference
- BST 223: Applied Survival Analysis
- BST 226: Applied Longitudinal Analysis
- BST 221: Applied Data Structures and Algorithms
- BST 228: Applied Bayesian Analysis
- BST 260: Introduction to Data Science
- BST 273: Introduction to Programming
- BST 281: Genomic Data Manipulation
- GHP 525: Econometrics for Health Policy
- ID 271: Advanced Regression for Environmental Epidemiology
- SBS 263: Multilevel Statistical Methods: Concept and Application
- and many others – see handbook linked below
Competencies
The 80-credit Master of Science program prepares students in five specific competencies:
- Designing research studies in medicine and public health (including recognizing study design and scientific/societal context, population selection and sample size justification, methods of data acquisition, curation and organization, data management methods, data analysis plans and protocol development);
- Analyzing and interpreting quantitative data for scientific inference and/or prediction studies (including data exploration, graphical and tabular displays, visuals, descriptive statistics, evaluation of modeling context and approaches, analysis methods, reproducibility, and choice of appropriate statistical software and programming languages);
- Using modern computational methods to effectively analyze complex medical and public health data (including linear, generalized linear, penalized, additive, time-to-event (survival), and correlated outcome regression methods and extensions, statistical and machine learning, and other data science methods, bioinformatics, statistical genetics, and more);
- Collaborating, presenting, and communicating effectively with research scientists in related disciplines;
- Using probabilistic and statistical reasoning, theory, and methods to effectively analyze non-standard problems arising in medicine and public health and assisting biostatistical researchers in the conduct of methodologic research. This competency is demonstrated through the completion of a Culminating Experience and corresponding report.
Our Community
The Department of Biostatistics hosts a variety of extracurricular seminars, working groups, and lectures focused on specific public health problems, creating opportunities to expand their knowledge while connecting with faculty and fellow students. It also participates in Data Adventure Day, when statistics students across Harvard help introduce high school students to the discipline. For those looking to expand their ability to present statistical analysis to others, the department offers workshops designed to help students hone their public speaking and writing skills.
Harvard Chan School offers a wide variety of academic support services, including research support through the Countway Library of Medicine and academic coaching and tutoring for students seeking additional help with either an overall transition to graduate school or specific subject matter.
Beyond academics, the school is home to more than 40 official student organizations focusing on public health issues, cultural affinities, and extra-curricular interests. These groups and other offices throughout the school plan events on campus and around Boston.
Career Outcomes
Graduates of the SM-80 program are trained to pursue research careers in a variety of industries:
- Biotech/pharma
- Health care organizations
- National and international government agencies
- Non-profit/Non-governmental organization
- Public and private sector enterprises
- Research institutions
- University/research
Eligibility Criteria
The Master of Science 80-credit (SM-80) degree program requires a prior bachelor’s degree or non-US equivalent.
- Minimum prerequisite for entrance: Bachelor’s degree or non-U.S. equivalent;
- Excellent written and spoken English;
- An undergraduate degree (major or minor concentration) in mathematical sciences or allied fields (pure or applied mathematics, statistics, economics, data science, computer science, bioinformatics, etc.) with a strong interest in health science. Also, a natural science, social science, or other concentration with a minor in a mathematical science or successful completion of the necessary prerequisites listed below plus at least an intro statistics course;
- Successful completion of calculus through multivariable integration;
- Successful completion of one semester of linear algebra or matrix methods;
- Practical knowledge of computer scripting and programming, and experience with a statistical computing language such as R, Python, or SAS;
NOTE: Applicants must clearly list all required prerequisite courses from the bullet points above (calculus through multivariable integration, linear algebra) including dates taken, grades received, institution, and whether the course was online or in person, at the bottom of their Statement of Purpose, in order to be reviewed for admission.
Application Requirements
All applications must be submitted through SOPHAS – the centralized application service for public health programs. In addition to the application, applicants must submit:
- Statement of purpose and objectives
- Official test scores
- Three letters of reference
- Resumé/curriculum vitae
- Post-secondary transcripts or mark sheets (World Education Services credential evaluation for applicants with degrees from outside of the United States.)
- English language proficiency (TOEFL/IELTS/Duolingo English Test), if applicable
Application Deadline: December 1
Applicants may apply to only one degree program for either full- or part-time status. Applications are reviewed in their entirety and decisions are released via email in late February/early March. Decisions are not released until all application components are received.
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