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MPH in Biostatistics
The MPH in Biostatistics provides the professional training that is common to all MPH Programs of Study in the College of Public Health (the Core MPH requirements) as well as substantive and meaningful training in Biostatistics. This degree is designed to train public health professionals who can provide leadership in the analysis of public health data and the design of studies for public health investigations. Individuals with an interest in public health and with quantitative ability, but without advanced mathematics training, may find this an interesting career track.
Graduates of the MPH in Biostatistics will be able to:
- Demonstrate a broad knowledge and understanding of statistical techniques used in public health studies and investigations.
- Serve as an advocate for good statistical design in public health investigations.
- Apply appropriate statistical methods for inference about public health-related questions, and describe the results to public health professionals and educated lay audiences.
- Interpret the results of statistical analyses in public health-related publications for public health professionals and educated lay audiences.
- Promote the use of sound statistical methods to answer open questions in public health practice.
- Function as a collaborator on public health projects, taking a leadership role in the design and implementation of projects.
- Assume responsibility for the design and implementation of analyses in investigations of public health questions.
- Manage the data for public health-related projects such as large community surveys, laboratory investigations, and multi-center clinical trials.
- Demonstrate effective written and oral communication skills when communicating quantitative information and statistical inferences to different audiences of public health professionals.
Examples of careers include:
- Biostatistician
- Data Scientist
- Data Analyst
- SAS Programmer
- Informatics Analyst
Prerequisites
- Although no specific major is required, previous coursework or experience in statistical methods or data analysis is preferred.
- Familiarity with the mathematics of single variable calculus and matrix algebra are required. These requirements can be satisfied by a one-semester college course in calculus equivalent to AP Calculus AB and a high school algebra course involving matrices.
- Knowledge of elementary computer programming is required. Programming in any commonly used modern programming language (e.g., Python, Java, C++) is acceptable.
A typical student completes the MPH in two years. The following are two sample plans of study based on a full-time student starting in the Fall. Please work with your advisor to choose a plan that works best for you.
Course No. | Course name | Hours |
---|---|---|
Fall 1 | 12 s.h. | |
BIOS:4120 | Intro to Biostatistics | 3 s.h. |
EPID:4400 | Epidemiology I | 3 s.h. |
OEH:4240 | Global Environmental Health | 3 s.h. |
CPH:5100 | Introduction to Public Health | 3 s.h. |
Spring 1 | 14 s.h. | |
BIOS:4510 | Data Science Foundations in R | 2 s.h. |
BIOS:5120 | Regression & ANOVA in Health Sciences | 3 s.h. |
CBH:4105 | Intro to Health Promotion and Disease Prevention | 3 s.h. |
HMP:4000 | Intro to the US Healthcare System | 3 s.h. |
BIOS: ### | BIOS Elective* | 3 s.h. |
Fall 2 | 11-12 s.h. | |
BIOS:5130 | Applied Categorical Data Analysis | 3 s.h. |
BIOS:#### | BIOS Elective* or BIOS:6310 Introductory Longitudinal Data Analysis | 3 s.h. |
BIOS: ### | BIOS Elective* | 3 s.h. |
BIOS: ### | BIOS Elective* | 2-3 s.h. |
CPH:5203 | Interprofessional Education & Practice for MPH Students | 0 s.h. |
Spring 2 | 5-6 s.h. | |
BIOS: ### | BIOS Elective* or BIOS:6210 Applied Survival Analysis | 2-3 s.h. |
CPH:7800 | MPH Practicum | 3 s.h. |
MPH degree total | 42 s.h. |
Area | Hours |
---|---|
MPH Core | 18 s.h. |
BIOS Electives | 13 s.h. |
BIOS Required | 8 s.h. |
Interprofessional Education & Practice | 0 s.h. |
MPH Practicum | 3 s.h. |
Total | 42 s.h. |
Course No. | Course name | Hours |
---|---|---|
Fall 1 | 14 s.h. | |
BIOS:5710 | Biostatistical Methods I | 4 s.h. |
BIOS:5510 | Biostatistical Computing (R & SAS) | 4 s.h. |
OEH:4240 | Global Environmental Health | 3 s.h. |
EPID:4400 | Epidemiology I: Principles | 3 s.h. |
Spring 1 | 13 s.h. | |
BIOS:5720 | Biostatistical Methods II | 4 s.h. |
BIOS:5730 | Biostatistical Methods Categorical Data | 3 s.h. |
CBH:4105 | Intro to Health Promotion and Disease Prevention | 3 s.h. |
HMP:4000 | Intro to the US Healthcare System | 3 s.h. |
Fall 2 | 12 s.h. | |
CPH:5100 | Intro to Public Health | 3 s.h. |
BIOS: 6310 | Introductory Longitudinal Data Analysis | 3 s.h. |
BIOS: ### | BIOS Elective* | 3 s.h. |
BIOS: ### | BIOS Elective* | 3 s.h. |
CPH:5203 | Interprofessional Education & Practice for MPH Students | 0 s.h. |
Spring 2 | 3 s.h. | |
CPH:7800 | MPH Practicum | 3 s.h. |
MPH degree total | 42 s.h. |
Area | Hours |
---|---|
MPH Core | 19 s.h. |
BIOS Required | 11 s.h. |
BIOS Electives | 9 s.h. |
Interprofessional Education & Practice | 0 s.h. |
MPH Practicum | 3 s.h. |
Total | 42 s.h. |
Course No. | Course name | Hours |
---|---|---|
BIOL:4213 | Bioinformatics | 3 s.h. |
BIOS:6210 | Applied Survival Analysis | 3 s.h. |
BIOS:6310 | Introductory Longitudinal Data Analysis | 3 s.h. |
BIOS:6420 | Survey Design and Analysis | 3 s.h. |
BIOS:6610 | Statistical Methods in Clinical Trials | 3 s.h. |
BIOS:6650 | Casual Inference | 3 s.h. |
BIOS:6720 | Machine Learning for Biomedical Data | 3 s.h. |
BIOS:6810 | Bayesian Methods and Design | 3 s.h. |
BIOS:7270 | Scholarly Integrity in Biostatistics | 1 s.h. |
BIOS:7600 | Advanced Biostatistics Seminar | 1-3 s.h. |
CS:4470 | Health Data Analytics | 3 s.h. |
CS:4740 | Large Data Analysis | 3 s.h. |
CS:5110 | Introduction to Informatics | 3 s.h. |
EPID:5200 | Principles of Public Health Informatics | 3 s.h. |
EPID:6920 | Applied Administrative Data Analysis | 2 s.h. |
ISE:4172 | Big Dara Analytics | 3 s.h. |
STAT:3100 | Intro to Mathematical Statistics I | 3 s.h. |
STAT:3101 | Intro to Mathematical Statistics II | 3 s.h. |
STAT:3210 | Experimental Design & Analysis | 3 s.h. |
STAT:4100 | Mathematical Statistics I | 3 s.h. |
STAT:4101 | Mathematical Statistics II | 3 s.h. |
STAT:4520 | Bayesian Statistics | 3 s.h. |
STAT:4540 | Statistical Learning | 3 s.h. |
STAT:4580 | Data Visualization and Data Technologies | 3 s.h. |
Work with your advisor to select electives. |