Skip to main content
Sign In

Department of Biostatistics & Informatics Academics


Master of Public Health - Applied Biostatistics

The Master of Public Health in Applied Biostatistics (MPH-AB) program is designed for students wanting a broad education in the field of public health, augmented with specialization in biostatistics and informatics.  In addition to coursework in four other core areas of public health, students are exposed to a variety of commonly used statistical methods as well as their application in public health and medical research.  Coursework, a practicum, and a capstone project provide experience with design, collection, management, analysis, interpretation and presentation of health data.

The Applied Biostatistics concentration in the MPH program (MPH/AB) targets students interested in a broader exposure to areas of public health, with specialization in biostatistics and analysis.  The concentration is flexiable and requires 15-24 credits of biostatistics courses, but does not require the statistical theory sequence BIOS 6631/32. Students in the MPH/AB are strongly encouraged to take the more advanced applied sequence BIOS 6611/12, which requires a semester of calculus, rather than the introductory MPH applied sequence BIOS 6601/02.  The MPH/AB does not prepare students for PhD work in Biostatistics.

Graduates look forward to rewarding careers in local, state and federal agencies, health and medical centers, pharmaceutical companies and research institutions, working in areas such as heart and lung disease, cancer, dental health, genetics, and infectious diseases, among others. This degree targets public health workers and researchers wishing to strengthen their analytic skills, and is particularly useful in combination with a previous research degree or experience.  Students with strong skills, training and interest in mathematics and a desire to work primarily as biostatisticians in health care and biological settings should consider the MS in Biostatistics program.

NOTE: Students considering an MPH in Applied Biostatistics are strongly encouraged to take the more advanced sequence Biostatistical Methods BIOS 6611 or BIOS 6612, which requires a semester of calculus, rather than the introductory sequence Applied Biostatistics BIOS 6601 or BIOS 6602.

MPH Applied Biostatistics Curriculum


MPH Applied Biostatistics Curriculum Checksheet


Required MPH Core Courses (17 credits)
​BIOS 6601/6611 Applied Biostatistics I ​3 credits
EPID 6630 Epidemiology ​3 credits
EHOH 6614 Environmental & Occupational Health ​3 credits
CBHS 6610 Social & Behavioral Factors & Health ​3 credits
HSMP 6601 Health Systems Management Policy ​3 credits
PUBH 6600 Foundations in Public Health 2 credits
Required Concentration Courses (12 credits)
BIOS 6602/6612 Applied Biostatistics II ​3 credits
​BIOS 6623 Advanced Data Analysis ​3 credits
​BIOS 6680 SAS Database Design and Management ​3 credits
Minimum of 3 credits from the following:
​BIOS 6621 Statistical Consulting I 1 credit
BIOS 6622 Statistical Consulting II ​1 credit
BIOS 6629 Applied Survival & Longitudinal Analysis 3 credits
​BIOS 6648 Design of Clinical Trials ​3 credits
BIOS 6655 Statistical Methods in Genetic Association 3 credits
EPID 6631 Analytical Epidemiology ​3 credits
BIOS 6631 Statistical Theory I 3 credits
EPID 6626 ​Research Methods in Epidemiology ​3 credits
Electives (9 credits)
​PUBH 6606 Practicum 2 credits​
PUBH 6955​ Capstone Project 2 credits​
TOTAL​   ​42 credits


Concentration Competencies

Identifier MPH Applied Biostatistics Concentration (CN) Competencies
Select and apply appropriate biostatistical methods to support research and evaluation in the core areas of public health research and practice, including: epidemiology, environmental and occupational health, community and behavioral health, and public health systems management, policy and outcomes research.
Translate a study’s scientific question or aims into testable statistical hypotheses and propose and apply appropriate statistical methods to test those hypotheses.
Test and interpret models for continuous outcome data (normal linear model), categorical outcome data (logistic and Poisson regression), and time-to-event data (Cox regression).
Apply the concepts of bias, error, confounding, effect modification, sampling, and generalizability and how they relate to interpretation of study results.
Carry out appropriate sample size and power calculations in basic situations to ensure that a study is sufficiently powered to achieve the scientific aims or address a specific research hypothesis.
Use computer software for data entry and data base management and for summarizing, analyzing and displaying research results.
Apply basic ethical issues involved in collection, management, use and dissemination of biomedical and public health data.
Critically review and interpret basic statistical methods presented in public health and medical literature to identify strengths, weaknesses, and potential biases in these studies.
Apply scientific and statistical principles and methods to design basic public health and biomedical studies.
Use the principles of hypothesis testing and estimation of population parameters to draw inferences from quantitative data and communicate verbally and in writing those inferences and their statistical and scientific interpretation to non-statistical scientists.
Address a biomedical, public health or statistical research question with a basic statistical analysis (e.g. linear or logistic regression).

Colorado School of Public Health

13001 E. 17th Place
Mail Stop B119
Aurora, CO 80045


© The Regents of the University of Colorado, a body corporate. All rights reserved.

Accredited by the Higher Learning Commission. All trademarks are registered property of the University. Used by permission only.