The MPH in Quantitative Methods provides the professional training that is common to all MPH subtracks 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 Quantitative Methods 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
An undergraduate degree is required. No specific major is required. Previous coursework or experience in statistical methods or data analysis is preferred. The cumulative grade point average should be a minimum of a 3.0 on a 4.0 scale. The applicant’s training should include basic course work in computer science and mathematics. The level of training required in each of these areas is described below.
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.
Persons with deficiencies in any of the above areas may apply for admission with the understanding that they will gain such experience through self-study in the first semester of enrollment.
MPH Core Courses (18 s.h.)
The following course work is required for all MPH students. Students must earn ≥ B- (2.67) on each core course and must earn a ≥ B (3.0) cumulative grade point average on all core courses. When necessary, a student may repeat courses to achieve this standard.
|CPH:5100||Intro to Public Health||3 s.h.|
|BIOS:4120||Intro to Biostatistics OR Biostatistical Methods I||3 s.h.|
|CBH:4105||Intro to Health Promotion and Disease Prevention||3 s.h.|
|EPID:4400||Epidemiology I: Principles||3 s.h.|
|HMP:4000||Intro to the US Healthcare System||3 s.h.|
|OEH:4240||Global Environmental Health||3 s.h.|
Required Biostatistics Courses (10 s.h.)
|BIOS:5120||Regression Modeling and ANOVA in the Health Sciences||3 s.h.|
|BIOS:6110||Applied Categorical Data Analysis||3 s.h.|
|BIOS:5510||Biostatistical Computing (Programming with R)||2 s.h.|
|BIOS:5510||Biostatistical Computing (Programming with SAS)*||2 s.h.|
*This course is waived if previously taken BIOS:5310 Research Data Management
Electives (students select 11-13 s.h. in consultation with advisor)
Electives may be chosen from the following list or may include any related course approved by the student’s advisor.
|BIOS:6310||Introductory Longitudinal Data Analysis||3 s.h.|
|BIOS:6610||Statistical Methods in Clinical Trials||3 s.h.|
|BIOS:6210||Applied Survival & Cohort Data Analysis||3 s.h.|
|BIOS:7600||Advanced Biostatistics Seminar||1-3 s.h.|
|BIOS:6810||Bayesian Methods and Design||3 s.h.|
|STAT:3100||Intro to Mathematical Statistics I||3 s.h.|
|STAT:3101||Intro to Mathematical Statistics II||3 s.h.|
|STAT:4100||Mathematical Statistics I||3 s.h.|
|STAT:4101||Mathematical Statistics II||3 s.h.|
|STAT:5100||Statistical Inference I||3 s.h.|
|STAT:5101||Statistical Inference II||3 s.h.|
|STAT:4200||Statistical Methods and Computing||3 s.h.|
|STAT:4520||Bayesian Statistics||3 s.h.|
|STAT:4540||Statistical Learning||3 s.h.|
|STAT:6560||Applied Time Series Analysis||3 s.h.|
|STAT:3210||Experimental Design & Analysis||3 s.h.|
|STAT:6540||Applied Multivariate Analysis||3 s.h.|
|IE:4172||Big Data Analysis||3 s.h.|
As specified by the Graduate College, a maximum of 6 s.h. may be transferred from another graduate or professional degree.
Practicum Requirement (3 s.h.)
The experience from this course, including a final written report and a poster presentation, constitutes the final examination for the MPH.
|CPH:7000||MPH Practicum Experience||3 s.h.|
Pre-Requisite to MPH Practicum:
Students must complete all of their MPH core courses and the majority of other MPH coursework prior to registering for the Practicum.
Summary of Hour Requirements
|MPH Core||18-19 s.h.|
|Required courses||10 s.h.|
* Advanced Biostatistics Sequence Substitution: A student with sufficient mathematical background can substitute: Biostatistics Methods I, Biostatistics Methods II, and Biostatistics Methods in Categorical Data (11 s.h.) in place of Introduction to Biostatistics, Regression Modeling and ANOVA in the Health Sciences, and Applied Categorical Data Analysis (9 s.h.). This advanced sequence has the additional prerequisites of undergraduate multivariable calculus and linear algebra. The advanced sequence requires 2 s.h. fewer elective credits.