This is the first version of the 2025–26 General Catalog. Please check back regularly for changes. The final edition and the historical PDF will be published during the fall semester.
Learning Outcomes
Students will:
- summarize current statistical methods and practices used in the health sciences;
- develop statistical designs for a health science investigation;
- write computer programs in SAS and R for the management and analysis of data sets;
- apply quantitative and reasoning skills to analyze data from public health studies; and
- communicate key statistical principles resulting from health science studies to lay audiences.
The Master of Science in biostatistics requires a minimum of 38 s.h. of graduate credit.
The program provides training in the design of experiments and in analysis of data related to biomedical or public health problems. It emphasizes mathematical, statistical, and computer methods for dealing with quantitative information and provides opportunities for students to gain statistical consulting experience with a variety of problems.
MS students are required to complete an in-depth preceptorship under the direction of a departmental faculty member and a final comprehensive-style examination.
The MS in biostatistics requires the following coursework.
Core Courses
All core courses must be taken on an A–F graded basis.
| Course # | Title | Hours |
|---|---|---|
| All of these: | ||
| BIOS:5510 | Biostatistical Computing (taken twice for 2 s.h. each; topics should be programming with R and programming with SAS) | 4 |
| BIOS:5710 & BIOS:5720 | Biostatistical Methods I and Biostatistical Methods II | 8 |
| BIOS:5730 | Biostatistical Methods in Categorical Data | 3 |
| BIOS:6610 | Statistical Methods in Clinical Trials | 3 |
| BIOS:7500 | Preceptorship in Biostatistics | 3 |
| EPID:4400 | Epidemiology I: Principles | 3 |
| One of these sequences: | ||
| STAT:4100 & STAT:4101 | Statistical Inference I and Statistical Inference II | 6 |
| STAT:5100 & STAT:5101 | Statistical Inference I and Statistical Inference II (required for students who intend to earn a PhD) | 6 |
Public Health Requirement
| Course # | Title | Hours |
|---|---|---|
| This course: | ||
| CPH:6100 | Essentials of Public Health | 2 |
Responsible Conduct of Research Training
| Course # | Title | Hours |
|---|---|---|
| This course: | ||
| BIOS:7270 | Scholarly Integrity in Biostatistics | 1 |
Electives
Students complete a minimum of 5 s.h. selected from the electives listed below. At least 3 s.h. must be in quantitative coursework in biostatistics (courses with prefix BIOS) or statistics (courses prefix STAT).
It is recommended that students consider a biology or public health course as the other elective, particularly if they have not had prior exposure to these areas. Electives must be approved by the advisor and the director of graduate studies; with their permission, courses not listed below may be completed as electives.
| Course # | Title | Hours |
|---|---|---|
| At least 3 s.h. from these: | ||
| BIOS:6210 | Applied Survival Analysis | 3 |
| BIOS:6310 | Introductory Longitudinal Data Analysis | 3 |
| BIOS:6420/EPID:6420 | Survey Design and Analysis | 3 |
| BIOS:6650/EPID:6655 | Causal Inference | 3 |
| BIOS:6720 | Statistical Machine Learning for Biomedical and Public Health Data | 3 |
| BIOS:6810 | Bayesian Methods and Design | 3 |
| BIOS:7110 | Likelihood Theory and Extensions | 4 |
| BIOS:7210 | Survival Data Analysis | 3 |
| BIOS:7230 | Advanced Clinical Trials | 3 |
| BIOS:7240 | High-Dimensional Data Analysis | 3 |
| BIOS:7250 | Theory of Linear and Generalized Linear Models | 4 |
| BIOS:7310 | Longitudinal Data Analysis | 3 |
| BIOS:7330 | Advanced Biostatistical Computing | 3 |
| BIOS:7410 | Analysis of Categorical Data | 3 |
| BIOS:7600 | Advanced Biostatistics Seminar (topics include statistical methods in bioinformatics, model selection, spatial modeling, statistical analysis of network data) | 1-3 |
| BIOS:7700 | Problems/Special Topics in Biostatistics | 1 |
| STAT:4520 | Bayesian Statistics | 3 |
| STAT:4540 | Statistical Learning | 3 |
| STAT:4580 | Data Visualization and Data Technologies | 3 |
| STAT:6560 | Applied Time Series Analysis | 3 |
| STAT:7400 | Computer Intensive Statistics | 3 |
| May complete one of these to reach the 5 s.h. minimum: | ||
| BIOL:4213 | Bioinformatics | 4 |
| BME:5335 | Computational Bioinformatics | 3 |
| CBH:4105 | Introduction to Health Promotion and Disease Prevention | 3 |
| CPH:5100 | Introduction to Public Health | 3 |
| CS:5110 | Introduction to Informatics | 3 |
| DATA:6200 | Predictive Analytics | 3 |
| GENE:7191 | Human Molecular Genetics | 3 |
| HHP:4390 | Understanding Human Disease | 3 |
| HMP:4000 | Introduction to the U.S. Health Care System | 3 |
| ISE:4172 | Big Data Analytics | 3 |
| OEH:4240 | Global Environmental Health | 3 |
| PATH:5270 | Pathogenesis of Major Human Diseases | 3 |
| PATH:8133 | Introduction to Human Pathology for Graduate Students | 2-4 |
Applicants to the MS program in biostatistics must apply through the Schools of Public Health Application Service (SOPHAS). After the SOPHAS application is verified, the applicant pays a supplemental Graduate College admission fee to University of Iowa Admissions. For detailed application information, visit Requirements and How to Apply to Biostatistics on the Department of Biostatistics website.
The biostatistics faculty considers several factors when evaluating applications for admission, including grade-point averages, letters of recommendation, intent and motivation for graduate study, and research interests.
All applicants must hold a bachelor's degree and have a cumulative grade-point average of at least 3.00.
All biostatistics applicants are required to have strong written and oral communication skills.
All applicants must be competent in at least one computer programming language. They must also have mathematical sciences training in methods and techniques of single variable and multivariable differential and integral calculus, and linear algebra. Previous coursework or experience in statistical methods or data analysis is preferred.
Applicants must meet the admission requirements of the Graduate College; see the Manual of Rules and Regulations on the Graduate College website.
Students may enter in the fall; the priority application deadline is Dec. 1.
Graduates find career opportunities in many areas, including pharmaceutics, health care, research companies and institutions, consulting firms, universities, and government agencies.
Sample Plan of Study
Sample plans represent one way to complete a program of study. Actual course selection and sequence will vary and should be discussed with an academic advisor. For additional sample plans, see MyUI.
Biostatistics, MS
This sample plan is currently being reviewed and will be added at a later date.