Graduate Biostatistics (BST)

The minimum prerequisite for 50000-69999 level courses is graduate standing. The minimum prerequisite for courses 70000 and higher is doctoral standing. Additional prerequisites may apply and are listed in this catalog.

50196 Individual Investigation in Biostatistics (1-3)
Individual graduate investigation or research in areas related to biostatistics. Repeat registration permitted for a maximum of 6 credit hours. IP permissible. Prerequisite: special approval

52019 Biostatistics in Public Health (3)
Provides students with an understanding of basic statistical methods in public health research, as well as the skills to perform and interpret basic statistical procedures. Students learn how to use statistical analysis software to analyze real data from public health-related studies. They then learn how to interpret the analysis and present the results to public health professionals and educated lay audiences.

63012/83012 Survival Analysis in Public Health (3)
Introductory course in survival analysis for graduate student in public health. Covers survival functions, hazard rates, types of censoring and truncation. Methods of focus include life tables, Kaplan-Meier plots, log-rank tests, Cox regression models and parametric survival models. Inference for recurrent event and competing risks models are also covered.

63013/83013 Experimental Designs in Public Health Research (3)
Introduces students to experimental research methods, in public health settings. The course first introduces a number of quasi-experimental and experimental study designs, then identifies a number of statistical methods that can be used to draw correct causal inferences from the study. Students are expected to develop two research proposals, first using quasi-experimental then an experimental design and develop a statistical analysis plan for each study. Prerequisite: BST 52019.

63014/83014 Applied Regression Analysis of Public Health Data (3)
Focuses on developing student proficiency in building and evaluating various regression models for public health studies. Topics covered include exploratory and descriptive methods, simple and multiple linear regression models, predictor selection, binary and multinomial logistic regression models, survival analysis, repeated measures and generalized linear models. Prerequisite: BST 52019

63015 Categorical Data Analysis of Public Health Data (3)
Provides an applied introduction to the most important methods for analyzing categorical data in public health. Topics covered include contingency tables, logistic regression, generalized linear models, modeling
matched pairs and clustered responses. Prerequisites: BST 52019 and EPI 52017.

73010 Qualitative Methods for Public Health Research (3)
Surveys major methods of qualitative research and explores issues and applications in public health, including integrating qualitative and quantitative methods. Approaches examined include: Ethnography; grounded theory; phenomenology; focus groups; narrative analysis; and Photovoice. Community-Based Participatory Research is explored as an approach for conducting qualitative research in Public Health.

73011 Multivariate Analysis in Public Health (3)
Multivariate statistical methods are designed to evaluate more than one variable at a time. An application-oriented introduction to essential multivariate statistical methods used in public health. Topics covered include matrix theory, data screening and preliminary analyses, multivariate normal distributions, multivariate versions of the general linear model (MANOVA, multivariate multiple regression, MANCOVA), discrimination and classification, canonical correlation analysis, and methods of analyzing covariance and correlation structures (principal components and factor analysis). Also introduces and explores methods of handling missing data. Prerequisite: BST 52019.