Welcome to the Biostatistics Concentration!
Biostatistics uses data analysis to determine the cause of disease and injuries, as well as to identify health trends within communities. Students entering into a biostatistics program should possess a broad knowledge of biology and a solid understanding of mathematics, statistical methods, and measures.
The Biostatistics Concentration is designed primarily for students with a previous graduate degree, particularly in the health sciences, who want to obtain a solid background in quantitative and analytical methods for public health research. The coursework exposes students to methodology typically used to analyze different types of public health data and gives them opportunities to apply these methodologies themselves.
Graduates of the MPH program with a concentration in Biostatistics return to their careers with an improved understanding of quantitative methods for public health research. This increased knowledge will both facilitate their own research programs and enhance their ability to critically read the literature in their field.
Faculty in the Department of Epidemiology and Biostatistics, Division of Biostatistics, teach courses and advise students in the biostatistics concentration. The curriculum is designed to enable students to develop competence in very specific biostatistical skills. In addition to 16 credits that constitute the public health core courses, the biostatistics concentration requires 15 credits of courses in biostatistics. Two of these courses address mathematical methods of statistics which are essential for undertaking the advanced biostatistics courses that are available as electives. Students are also required to develop basic skills in regression analysis, survival analysis, and epidemiology methods. Each biostatistics MPH student has an opportunity to take public health electives and completes his/her program of study with an analytical project.
Click below to view full curricula for the 48-credit and accelerated 42-credit MPH programs.
- Standard 48-credit MPH Curriculum, Biostatistics Concentration
- Accelerated 42-credit MPH Curriculum, Biostatistics Concentration
Click here to review
the competencies expected of graduates of the Biostatistics concentration
and the courses that contribute to them.
Click below for descriptions of the biostatistics concentration core courses.
- PHC 6053 Regression Methods for the Health and Life Sciences
- PHC 6000 Epidemiology Research Methods I
- PHC 6937 Bias in Observational Research
- PHC 6937 Biostatistical Computing using R
- PHC 6937 Special Topics: SAS for Public Health Data
- PHC 6937 Special Topics: SAS for Public Health Analysis
- PHC 6937 Special Topics: SAS Applications
- PHC 6937 Special Topics: Survival Analysis
PHC 6053 – Regression
Methods for the Health and Life Sciences (3) Prereq: STA 6166
or equivalent.
This course introduces graduate students in fields other than statistics
to a wide range of modern regression methods. Emphasis is on modeling driven
by actual data from studies in a variety of areas, primarily from health,
biology, and ecology. The primary topics are multiple linear regression,
logistic regression, and Poisson regression. A main goal is to determine
what approach to use among the linear and nonlinear models, and how to determine
if the fit is adequate. By the end of the course, students will achieve
competence in carrying out the analyses in standard statistical software,
primarily the SAS language. Full syllabus
PHC 6000—Epidemiology
Research Methods I (3) Prereq: PHC 6001, and STA 6166 or PHC
6050 or approval of department.
This course extends the concepts and methods of epidemiology from PHC 6001
(Principles of Epidemiology). Research design and analytic reasoning are
emphasized throughout the class. The course provides an understanding of
the methods of epidemiological study designs and their analyses including
issues of bias, confounding, and effect modification. The goal of this class
is to provide a strong background in analytic reasoning and research design,
study execution, analysis, and research interpretation. Full syllabus
PHC 6937 - Bias in Observational Research
The purpose of this course is to provide a foundation for identifying and addressing sources of bias in statistical analysis of observational research. Sources of bias to be considered include confounding, misclassification, measurement error, selection bias, ecologic bias, bias due to censored or missing data, overmatching, recall bias, and tacit assumptions of homogeneity. Statistical methods for remediation of bias will be examined in theory and in practice. Students will use the statistical programming language SAS to analyze observational data with and without bias adjustments. Full syllabus
PHC 6937 - Biostatistical Computing Using R (1) Prereq: PHC 6053 or equivalent
This is a one credit course which covers using R to process public health data. Students will learn how to input, store, modify, display, and analyze data using R. Students will develop basic R programming skills including working with vectors, lists, arrays, and matrices, writing functions and using R to simulate data. Full syllabus
PHC 6937 - SAS for Public Health Data (1) Prereq: PHC 6052 or equivalent.
This is a one credit course which covers using SAS to process public health data. Students will learn how to input, store, and modify data using SAS. Students must have prior experience with basic data entry and analysis in SAS and also have access to a laptop with SAS version 9.2 for in-class use. Full syllabus
PHC 6937 - SAS for Public Health Analysis (1) Coereq: PHC 6937: SAS for Public Health - Data (or equivalent), Prereq: PHC 6052 or equivalent.
This is a one credit course which covers using SAS to analyze public health data. Students will learn how to use common SAS procedures to conduct common statistical analyses. Although we results will be discussed, this course does NOT teach statistical methods. Students must have prior experience with basic data entry and analysis in SAS and also have access to a laptop with SAS version 9.2 for in-class use. Full syllabus
PHC 6937 - Special Topics: SAS Applications (1) Prereq: PHC 6937 SAS for Public Health Data and PHC 6937 SAS for Public Health Analysis and consent of instructor
This is a one credit course providing students an environment for discussion of data
management and analysis in their research using SAS. During the course, each student will apply their SAS knowledge to a specific data analysis research project. Students will use many resources for SAS documentation, resulting in skills that promote independent understanding of the application of SAS for analyzing data in current and future research. Students must have prior experience with basic data entry and analysis in SAS and also have access to a laptop with SAS version 9.2 for in-class use. Full syllabus
PHC 6937—Special Topics: Survival Analysis
(3) Prereq: STA 6127, STA 6167 or equivalent, knowledge of
multiple regression, SAS programming experience.
This course discusses “time to event” data, where the event
can be response to treatment, relapse of disease, or death. Often we wish
to quantify the relationship between the time to event and prognostic factors
such as mode of therapy, age of patient, and severity of disease. This course
will cover inference for a single population, methods for comparison of
two or more populations, and methods for doing regression analysis. Procedures
will include the Kaplan-Meier estimator, the log-rank test, and Cox proportional
hazards regression. All these procedures handle the common case of censored
data, where the information on some individuals is incomplete in the sense
that the event had not yet occurred at the termination date of the study. Full syllabus
