Interdisciplinary fields are likely very familiar to students. Hot areas like Business Analytics (BA), Data Science (DS), and Financial Engineering are all cross-disciplinary. These programs not only offer great career prospects but also provide applicants with more options. Today, let's introduce—Biostatistics.
What Is Biostatistics?
Biostatistics is the science of designing, sampling, analyzing, organizing, and inferring from incomplete data to obtain scientifically reliable conclusions in biological experiments. Simply put, it uses statistical methods to study and analyze biological/medical data. It is an interdisciplinary field closely related to mathematics, statistics, bioinformatics, and computer science (especially data mining).
The Relationship and Differences Between Biostatistics and Statistics
Statistics is the summary and theoretical distillation of statistical practice, forming a systematic body of knowledge. It refers to the theories and methods for collecting, organizing, and analyzing statistical data. Statistics is a branch of applied mathematics that primarily uses probability theory to build mathematical models, collects data from observed systems, performs quantitative analysis and summarization, and makes inferences and predictions to inform decision-making.
Biostatistics applies the principles and methods of mathematical statistics to analyze and interpret various phenomena and data in the biological world, aiming to grasp its essence and patterns.
Statistics is typically housed in a Liberal Arts College, School of Science, or a separate school.
Biostatistics is generally under a School of Public Health or Medical College, and sometimes under an Agricultural College. Some universities that don’t have a separate biostatistics department may place it within a Liberal Arts College, but in such cases it is usually closely linked to the statistics or mathematics department.
Many people don’t understand the relationship and differences between biostatistics and statistics. Here is a simple introduction:
Biostatistics is a branch of statistics. Essentially, they are the same discipline—one is the field, the other a subfield.
Statistics departments lean more toward theoretical research, while biostatistics leans more toward practical application combined with biology.
The scope of statistical research is not limited to life sciences; it also includes industry, commerce, economics, and other fields. The scope of biostatistics research is focused on life sciences.
Statistics graduates have broader employment prospects, while biostatistics graduates have narrower ones, as the name implies. For industries like IT, market research, and finance, a more specialized field like biostatistics loses its “professional” advantage. Recruiters might see “biostatistics” and question whether your background is a good fit. Statistics has an edge in these broader industries. If you're unsure what to study, choose a field with broader options.
Statistics is harder to get into than biostatistics. The MPH in biostatistics is also slightly harder than the MS.
Research Directions
Research can be divided into two main directions: clinical statistics and statistical genetics.
Clinical Statistics
Clinical statistics is further divided into the following branches:
Survival Analysis
This mainly deals with individual lifespans in clinical trials. It is the study of survival phenomena and time-to-event data and their statistical properties. It has attracted attention from statisticians worldwide over the past two to three decades. Survival analysis primarily used Kaplan-Meier and Cox models, but new theories like frailty models, accelerated failure time models, and transformation models have emerged.
Longitudinal Data Analysis
This deals with data from repeated observations of the same individuals in clinical trials. Common models for describing longitudinal data include random effects models, marginal models, and so on.
Clinical Trial Design
This focuses on how to design randomized experiments so that as many patients as possible receive the new treatment (intention to treat) while maintaining statistical power. A relatively new theory in this area is alpha spending functions. Statistical genetics uses statistical methods to study issues in genetics and molecular biology, with methods like modeling and Monte Carlo simulation. Professors often work with gene expression data to study gene regulation and function. Overall, clinical statistics is more traditional, with theoretical derivations similar to mathematical statistics, emphasizing probabilistic model building and statistical inference. Statistical genetics, on the other hand, often deals with high-dimensional, high-noise data, so it places greater emphasis on computational algorithm design and implementation.
Statistical Genetics
A discipline that uses statistical methods, aided by computational tools, to study the heredity and variation of genomes in living organisms. The core question is genome heredity and variation—this is the essence and must not be deviated from. Everything serves the exploration of fundamental biological questions.
Degree Options
Master's degrees in this field include MPH, MS, MSPH, and ScM.
The MPH is a Master of Public Health, a professional degree (like JD, MD, or MBA). It often requires more work experience and is more applied; it generally has more credits (and higher tuition). Admission to an MS program is definitely harder than an MPH for students without a math background. On SOPHAS, MS programs usually also have an MPH option, but not vice versa. Some schools' MS programs do not use the SOPHAS system (e.g., Penn State, George Washington University).
MS, MSPH (Master of Science in Public Health), and ScM (Master of Science) are all science master's degrees. Different schools may use different abbreviations. They belong to the STEM-designated degree list, benefiting from STEM OPT extension. These degrees demand a stronger math background, are more theoretical, and make it easier to transfer to a PhD program or directly apply for a PhD. MS programs also distinguish between thesis and capstone tracks: the former resembles a research master's requiring a thesis (usually 24–36 months), while the latter is typically 18–24 months.
Below is information from Emory University's website: (The credit difference is not absolute; some schools' MPH may require more credits than MS. Overall, the MPH is professionally oriented—similar to a professional master’s in China—while the MS is academically oriented, akin to an academic master’s. Non-math majors may find MPH admission easier.)
What is the difference between an MPH and an MSPH in BIOS?
The MSPH degree is a research/academic-based degree that requires 48 credit hours and has a stronger emphasis on research.
An MPH degree is a professional/practice-based degree that requires 42 credit hours and is more focused on the applied practice of public health.
Doctoral degrees in this field include the PhD and DrPH (Doctor of Public Health).
PhDs are usually fully funded (known as an "Offer"). PhD funding is not free money; a significant portion comes through Teaching Assistantships (TA) and Research Assistantships (RA).
Program Placement
Biostatistics programs may be named: biostatistics, bio-systems, bioinformatics, etc.
They are often housed in departments of mathematics, computer science, biology, schools of medicine, or public health. Programs in math or CS departments emphasize mathematical methods more. Those in biology or medical schools share some similarities, but medical school-based programs are harder to get into. Those under public health departments may study different subjects.
Curriculum
Data Analysis Workshop
Statistics for Laboratory Scientists
Data Management
The SAS Statistical Package
Biostatistics in Medical Product Regulation
Analysis of Biological Sequences
Survival Analysis
Design of Clinical Experiment
Methods in Biostatistics
Spatial Analysis and GIS
Advanced Methods in Biostatistics
Statistical Computing
Prerequisites
Each school has slightly different prerequisites for Master's programs. It is strongly recommended to check the official program websites—they are listed very clearly.
UW Biostatistics prerequisite:
approximately three semesters or four quarters of calculus, which must include multivariate calculus
one course in linear algebra
one course in probability theory (calculus based)
Georgetown University Biostatistics prerequisite:
Algebra, Multivariable Calculus, and a college-level statistics course.
Alternative combinations of coursework and/or experience will be considered on a case-by-case basis.
Introduction to Biostatistics Programs
Harvard University
Harvard’s biostatistics department is housed under the School of Public Health (SPH), located on the Harvard Medical Campus. The Harvard School of Public Health established its biostatistics department in 1922, shortly after the school itself was founded. The department has about 70 students, 60 faculty members, and 55 researchers. Degrees offered: Doctor of Philosophy degree and Master of Science degree.
Harvard’s biostatistics department focuses on computational biology and bioinformatics. The Harvard School of Public Health, Harvard Medical School, Brigham and Women’s Hospital, Children’s Hospital, and the Dana Farber Cancer Institute (DFCI, a world-leading cancer research center) are all clustered together, with many faculty holding appointments at multiple institutions.
The Johns Hopkins University
Johns Hopkins’ biostatistics program is under the School of Public Health (SPH). Degrees offered: PhD, ScM (Master of Science), MHS (Master of Health Science). Johns Hopkins' biostatistics department is famously described as “one of the oldest and best biostatistics departments in the world.” Founded in 1918, it was the world’s first biostatistics department, and it has high requirements in both mathematics and biology.
The biostatistics program sits within the Bloomberg School of Public Health, which is ranked #1 in the nation. Graduates find employment in academia, government, and industry. Statistics show 70% of graduates enter academia; of the previous cohort of 20 PhD graduates, 16 landed faculty positions at prestigious universities including Harvard, Brown, Berkeley, the University of Chicago, and Washington University.
Starting salaries are highly competitive: academia and government: $90,000; industry: $110,000.
University of Michigan, Ann Arbor
Michigan’s biostatistics department is also under the School of Public Health (SPH). Research areas include bioinformatics, brain imaging, cancer, clinical trials, endocrinology, epidemiology, genetics, and more. Degrees offered: Master of Science (M.S.), Master of Public Health (M.P.H.), Doctor of Philosophy (Ph.D.).
Columbia University
Columbia’s biostatistics department is, again, under the School of Public Health (SPH). The “three pillars” of biostatistics—methodological research, collaboration, and teaching—are well integrated, with an emphasis on evidence. Degrees offered: MPH/MS and DrPH.
University of California, Berkeley
Berkeley does not have an independent biostatistics department; the program is housed within the Statistics Department, which is part of the School of Public Health. Degrees offered: MA and PhD. The program suits students with backgrounds in mathematics or statistics who are interested in biological sciences. Each year, Berkeley’s biostatistics program receives about 90–100 applications, with an acceptance rate of only 15–20%. The MA degree requires a minimum GPA of 3.0.
Emory University
Emory’s Department of Biostatistics and Bioinformatics is under the School of Public Health (SPH). It was established in the 1960s, originally within the School of Medicine. Degrees offered: MSPH and MPH (through the Rollins School of Public Health), MS/PhD (under the Graduate School of Arts and Sciences), and a BA/MSPH degree.
University of North Carolina at Chapel Hill
UNC’s biostatistics department is similarly under its School of Public Health (SPH). Biostatistics is one of the university’s strongest programs and one of the best biostatistics departments in the world. UNC’s biostatistics department was founded in 1949.
Degrees offered:
1. Bachelor of Science in Public Health (BSPH), minimum GPA 3.0
2. Master of Public Health (MPH)
3. Master of Science (MS)
4. Doctor of Public Health (DrPH)
5. Doctor of Philosophy (PhD)
University of Washington
UW’s biostatistics department is under the School of Public Health (SPH), founded in 1970. The department has 78 faculty members, including one member of the National Academy of Sciences, two members of the Institute of Medicine, and 20 Fellows of the American Statistical Association—an impressive faculty lineup.
Additionally, the department collaborates with the Fred Hutchinson Cancer Research Center, Children’s Hospital Research Institute, Group Health Cooperative, and the Veterans Administration. According to statistics, 488 alumni hold leadership positions worldwide in academia, government, and industry. Degrees offered: Master of Science, Master of Public Health, and Doctor of Philosophy.
Application Requirements
01 Suitable background:
Any quantitative major can be considered. Besides math majors, the department includes graduates from economics, bioinformatics, and engineering. Other majors may also be considered if they have a strong quantitative foundation, such as statistics, applied mathematics, computer science, or biology.
02 Language test scores:
TOEFL is recommended. Statistics programs generally do not have very high TOEFL requirements; a score between 90 and 100 usually meets most schools' requirements. However, applicants targeting top programs should still aim for 100 or above.
03 GPA
GPA is not an absolute determining factor in biostatistics applications, but it should still be decent. Generally, a GPA of 3.6 or above is competitive. If your GPA falls below that, you can compensate with research experience and publications. If you still have time, try to raise your GPA as much as possible. For applicants switching from another field, a low GPA combined with a less relevant background can be a disadvantage; in that case, achieving high grades in relevant coursework can help offset this.
04 Research
Research is very important in biostatistics applications. For PhD applications, research experience and strong recommendation letters are top priorities for admissions committees. For master’s applications, a holistic review of research, recommendation letters, and GPA is conducted (with GPA perhaps carrying slightly more weight).
05 Application documents (CV & PS)
Essays play a role in the application process. Your CV should highlight any biostatistics-related courses you have taken and emphasize how you have addressed any gaps in your undergraduate curriculum. For example, if your undergraduate coursework lacks computer science, highlight the training and use of programming languages and statistical software in your research experience. Descriptions of your research should be clear and easy to understand so that readers can quickly grasp what you did. Your personal statement (PS) should convey genuine motivation; avoid relying entirely on templates. Demonstrate originality and a thorough understanding of the program’s focus.
06 Reach out to potential advisors
Regarding reaching out to potential advisors: although many schools use a committee-based admissions system where individual advisors do not have absolute decision-making power, a successful connection with a faculty member who strongly recommends you can positively influence the committee's decision. Success in reaching out depends largely on demonstrating an understanding of the advisor’s research direction and showcasing relevant research experience.
Career Prospects
Graduates of U.S. biostatistics programs, whether at the master’s or doctoral level, enjoy excellent job prospects. In addition to faculty positions, PhD graduates find many opportunities in industry, especially in pharmaceutical companies or biotech firms where biostatisticians are in high demand. Some graduates also enter finance and insurance industries.
For statistics and biostatistics graduates, the main career paths are in pharmaceutical/biotech fields and finance/insurance/banking. However, data is increasingly generated across all domains—from traditional finance and pharma to emerging areas like social networks, data-driven marketing, and the web. Wherever there is data, there is a need for statistical analysis. The typical model is that core tasks are handled by a small number of statisticians, with large volumes of specific work delegated to bachelor’s and master’s level programmers.
Employment Directions:
1. Pharmaceutical companies or biotech firms are in high demand.
2. Finance and insurance industries.
3. Hospitals or research institutions.
