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

Required courses
BIOS:5510Biostatistical Computing4 s.h.
BIOS:5710Biostatistical Methods I4 s.h.
BIOS:5720Biostatistical Methods II4 s.h.
BIOS:5730Biostatistical Methods in Categorical Data3 s.h.
BIOS:6610Statistical Methods in Clinical Trials3 s.h.
BIOS:7500Preceptorship in Biostatistics*3 s.h.
Mathematical Statistics I & II
Statistical Inference I & II
6 s.h.
EPID:4400Epidemiology I: Principles3 s.h.
CPH:6100Essentials of Public Health2 s.h.
BIOS:7270Scholarly Integrity in Biostatistics1 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.

BIOS:6210Applied Survival Analysis(Spring)3 s.h.
BIOS:6310Introductory Longitudinal Data Analysis(Fall)3 s.h.
BIOS:6420Survey Design and Analysis(Spring even)3 s.h.
BIOS:6650Causal Inference(Spring)3 s.h.
BIOS:6720Machine Learning for Biomedical Data(Spring even)3 s.h.
BIOS:6810Bayesian Methods & Design(Fall even)3 s.h.
BIOS:7110Likelihood Theory and Extensions(Fall)4 s.h.
BIOS:7210Survival Data Analysis(Fall odd)3 s.h.
BIOS:7230Advanced Clinical Trials(Fall even)3 s.h.
BIOS:7240High-Dimensional Data Analysis(Spring odd)3 s.h.
BIOS:7250Theory of Linear/Generalized Linear Models(Spring)4 s.h.
BIOS:7310Longitudinal Data Analysis(Spring odd)3 s.h.
BIOS:7330Advanced Biostatistical Computing(Fall 0dd)3 s.h.
BIOS:7410Analysis of Categorical Data(Spring even)3 s.h.
BIOS:7600Advanced Biostatistics Seminar(arr)1-3 s.h.
BIOS:7700Problems/Special Topics in Biostatistics(arr)1 s.h.
BME:5335Computational Bioinformatics(Spring)3 s.h.
DATA:6200Predictive Analytics(Spring)3 s.h.
STAT:4520Bayesian Statistics(Fall)3 s.h.
STAT:4580Data Visualization and Data Technologies(Spring)3 s.h.
STAT:6560Applied Time Series Analysis(Spring)3 s.h.
STAT:7400Computer Intensive Statistics(Spring)3 s.h.
CS:5110Introduction to Informatics(Fall)3 s.h.
ISE:4172Big Data Analysis(Fall)3 s.h.

Possible Public Health or Biology Electives

NumberCourse SemesterHours
BIOL:4213Bioinformatics(Fall)4 s.h.
CBH:4105Introduction to Health Promotion & Disease Prevention(Spring)3 s.h.
CPH:5100Introduction to Public Health(Fall)3 s.h.
GENE:7191Human Molecular Genetics(Spring)3 s.h.
HMP:4000Introduction to U.S. Health Care System(Spring)3 s.h.
OEH:4240Global Environmental Health(Fall)3 s.h.
PATH:5270Pathogenesis of Major Human Diseases(Spring)3 s.h.
PATH:8133Introduction to Human Pathology(Fall)2-3 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.