MS in Biostatistics

Degree Description and Learner Objectives

The M.S. program trains students in the planning and data analysis of biomedical and public health studies, and is designed to take two years to complete. The degree requirements and electives include biostatistics courses, statistics courses, and health-related courses. Program graduates successfully compete for positions in research institutions, pharmaceutical companies, government agencies, and universities.

Upon completion of the M.S. in Biostatistics, the student should be prepared to function as a statistician or statistical consultant. Therefore the student must have an extensive understanding of statistical theory and practice and should be proficient in the application of statistical methods to one or more areas in the health sciences. At the completion of the M.S. degree in Biostatistics the graduate should be able to:

  1. Demonstrate a broad knowledge and understanding of current statistical theory, methods, and practices in the health sciences
  2. Effectively collaborate on a research team
  3. Develop statistical designs and implement analyses for health science investigations
  4. Develop computer programs for the management and analysis of data sets
  5. Prepare reports and publications resulting from health science studies
  6. Effectively communicate key statistical principles to a non-statistical audience


A bachelor’s degree in mathematical, biological, or physical sciences is recommended.

The applicant’s training should include three semesters of calculus, a course in linear algebra, and the ability to program in at least one computer language. Applicants will be asked to provide, as part of the application, transcript verification or a brief statement indicating whether and how the calculus and linear algebra prerequisites have been met, either through coursework at the University of Iowa (MATH:1850, MATH:1860, MATH:2850, MATH:2700) or through comparable regularly-scheduled coursework or independent study at other institutions.

Course Requirements

Number Course Hours
Required courses
BIOS:5510 Biostatistical Computing 4 s.h.
BIOS:5710 Biostatistical Methods I 4 s.h.
BIOS:5720 Biostatistical Methods II 4 s.h.
BIOS:5730 Biostatistical Methods in Categorical Data 3 s.h.
BIOS:6610 Statistical Methods in Clinical Trials 3 s.h.
BIOS:7500 Preceptorship in Biostatistics* 3 s.h.
Mathematical Statistics I & II
Statistical Inference I & II
6 s.h.
EPID:4400 Epidemiology I: Principles 3 s.h.
CPH:6100 Essentials of Public Health 2 s.h.
BIOS:7270 Scholarly Integrity in Biostatistics 1 s.h.

*Preceptorship may be taken for only 1 s.h. if the student has sufficient experience in biostatistical collaborations, as determined by the student’s advisor and the Director of Graduate Studies.


Complete 5-6 s.h. of elective courses, of which at least 3 s.h. must be in quantitative coursework (i.e., Statistics or Biostatistics).  It is recommended that students consider a Biology/Public Health course as the other elective – particularly for those who have not had prior exposure to these areas.  Electives must be approved by the advisor and the Director of Graduate Studies.

Number Course Semester Hours
BIOS:6210 Applied Survival Analysis (Spring) 3 s.h.
BIOS:6310 Introductory Longitudinal Data Analysis (Fall) 3 s.h.
BIOS:6420 Survey Design and Analysis (Spring even) 3 s.h.
BIOS:6650 Causal Inference (arr) 3 s.h.
BIOS:6720 Machine Learning for Biomedical Data (Spring even) 3 s.h.
BIOS:6810 Bayesian Methods & Design (Fall even) 3 s.h.
BIOS:7110 Likelihood Theory and Extensions (Fall) 4 s.h.
BIOS:7210 Survival Data Analysis (Spring odd) 3 s.h.
BIOS:7230 Advanced Clinical Trials (Fall even) 3 s.h.
BIOS:7240 High-Dimensional Data Analysis (Spring odd) 3 s.h.
BIOS:7250 Theory of Linear/Generalized Linear Models (Spring) 4 s.h.
BIOS:7310 Longitudinal Data Analysis (Spring odd) 3 s.h.
BIOS:7330 Advanced Biostatistical Computing (Fall 0dd) 3 s.h.
BIOS:7410 Analysis of Categorical Data (Spring arr) 3 s.h.
BIOS:7600 Advanced Biostatistics Seminar (arr) 1-3 s.h.
BIOS:7700 Problems/Special Topics in Biostatistics (arr) 1 s.h.
STAT:4520 Bayesian Statistics (Fall) 3 s.h.
STAT:6560 Applied Time Series Analysis (Spring) 3 s.h.
STAT:7400 Computer Intensive Statistics (Spring) 3 s.h.
CS:5110 Introduction to Informatics (Fall) 3 s.h.
ISE:4172 Big Data Analysis (Fall) 3 s.h.

Possible Public Health or Biology Electives

Number Course Hours
BIOL:4213 Bioinformatics (Fall) 4 s.h.
CBH:4105 Introduction to Health Promotion & Disease Prevention (Spring) 3 s.h.
CPH:5100 Introduction to Public Health (Fall) 3 s.h.
ECE:5220 Computational Genomics (Spring) 3 s.h.
GENE:7191 Human Molecular Genetics (Spring) 3 s.h.
HMP:4000 Introduction to U.S. Health Care System (Spring) 3 s.h.
OEH:4240 Global Environmental Health (Fall) 3 s.h.
PATH:5270 Pathogenesis of Major Human Diseases (Spring) 3 s.h.
PATH:8133 Introduction to Human Pathology (Fall) 3 s.h.

The student must complete at least 38 semester hours of coursework. The student may choose to take additional graduate-level courses in consultation with her/his advisor.

Master’s Examination

The master’s core examination is a written in-class exam focusing on the required biostatistics and statistics coursework. This exam is offered twice per year.