College of Public Health students graduating

Courses

Course Number Course Title Description Credit Hours
BST 330 Statistical Thinking for Population Health

This course provides students with an introduction to statistical concepts that are important for solving real-world public health problems. This course will present statistical principles and associated scientific reasoning underlying public health practice and health policy decision-making.

3
BST 639 Computing Tools for the Biomedical Sciences

This course is an introduction to statistical and epidemiologic software technologies commonly used for the collection, management, and analysis of data. Prereq: STA 580 or consent of instructor and basic computer literacy. (Same as CPH 639.) 

3
BST 655 Introduction to Statistical Genetics

BST 655 presents an introduction to the statistical methodologies used today to investigate genetic susceptibility to complex diseases. The course focuses on linkage and association analysis with applications to real-world data. Commonly used (and freely available) software will be presented and used throughout. Because the field is constantly evolving, a focus of the material for this course will be recent statistical human genetics literature. Prereq: STA 580 or equivalent. (Same as STA 655.) 

3
BST 675 Biometrics I

This course, the first of a two-semester sequence in biometrics, introduces probability, discrete random variables, continuous random variables, joint distributions, and sampling distributions. Prereq: STA 580 and MA 114 or equivalent. 

4
BST 676 Biometrics II

This course, the second of a two-semester sequence in biometrics, introduces techniques for constructing and evaluating point estimators, hypothesis testing procedures, and interval estimators. Prereq: BST 675. 

4
BST 701 Bayesian Modeling in Biostatistics

This course provides an introduction to Bayesian ideas and data analysis applied to the biosciences. The course illustrates current approaches to Bayesian modeling and computation in biostatistics. Prereq: BST 760 and BST 676 or equivalent. 

3
BST 713 Clinical Trials

Design and analysis of Phase I-III clinical trials, interim monitoring of trials, sample size, power, crossover trials, bioequivalency, mixed models, and meta analysis. Coreq: STA 603. (Same as STA 653.) 

3
BST 740 Spatial Statistics

Course will cover risks and rates, types of spatial data, visualizing spatial data, analysis of spatial point patterns, spatial clustering of health events based on case control studies, and based on regional counts, linking spatial exposure data to health events through regression modeling, Bayesian spatial analysis. Prereq: BST 760 

3
BST 760 Advanced Regression

This course provides an introduction to theoretical methods and applications of linear and generalized linear models. Regression methods for normally distributed outcomes will provide a discussion of experimental design, design matrices, and modes of parametric inference for the linear model. Students will learn to apply these concepts in sophisticated data analysis where they will implement tools for model building and selection, variable selection, and handling categorical predictors, confounders and interactions. Additionally, students will learn polynomial regression and flexible alternatives such as weighted least squares and robust, ridge and nonparametric regression. Regression models for non-normal outcomes (focusing on binomial and count data) will be covered in detail, providing students with foundational tools for understanding and implementing generalized linear models that are commonly used to analyze epidemiologic and public health data from various study designs including but not limited to cohort, case-control, and clinical trials. Prereq: BST 675 and STA 580; coreq: BST 676. 

3
BST 761 Time to Event Analysis

Analysis of time to event data encountered in Public Health and Medicine. Survival distributions and hazard functions. Time to event analysis using Kaplan-Meier method and life-table method. Accelerated failure time model, logit model for discrete data, complimentary log-log model, and proportional hazards model. Tests for goodness-of-fit, graphical methods, and residual and influence statistics. Time- dependent covariates, non-proportional hazards, left truncation, and late entry into the risk set. Sample size and power, competing risks, and time to event analysis with missing data. Prereq: STA 580 or equivalent. 

3
BST 762 Longitudinal Data Analysis

This course presents statistical techniques for analyzing longitudinal studies and repeated measures experiments that occur frequently in public health, clinical trials, and outcomes research. This course will cover linear mixed models, generalized linear mixed models and an introduction to nonlinear models as they apply to the analysis of correlated data. Prereq: BST 676 and BST 760 OR STA 603 and STA 607. (Same as STA 632.) 

3
BST 763 Analysis of Categorical Data

Multinomial and product-multinomial models; large-sample theory of estimation and testing, Pearson chi-square and modified chi- square statistics, Pearson-Fisher Theorem, Wald Statistics and generalized least squares technique; applications to problems of symmetry, association and hypotheses of no interaction in multi-dimensional contingency tables. Prereq: STA 603 and STA 606. (Same as STA 665.) 

3
BST 764 Applied Statistical Modeleing for Medicine and Public Health

This course introduces some useful statistical models not typically encountered in the core courses of a master’s or doctoral biostatistics curriculum. These include finite mixture models, nonparametric regression models, covariance-based models, and stochastic models. Prereq: BST 675 and BST 760. 

3
BST 765 Missing Data Methodology for Public Health

This course surveys methods for analyzing data with missing observations. This includes methods for data missing completely at random including hot deck cold deck, mean substitution, and single imputation; methods for data missing at random including multiple imputation and weighted estimating equations and methods for data missing not at random including pattern mixture models, selection models, and shared random effects models. Prereq: BST 676 and BST 762. 

3
BST 766 Analysis of Temporal Data in Public Health

This course surveys methods for analyzing public health data collected over time. Methods covered include smoothing time series data, the modeling of stationary time series for Gaussian, dichotomous, and case count responses, methods for detecting the clustering of disease over time, and methods for the surveillance of infectious diseases in real time. Prereq: BST 675 and BST 760. 

3
CPH 535 Databases and SAS Programming

Students will learn how to construct and maintain databases with applications to public health. They will also learn how to program in SAS, the leading statistical analysis system. SAS skills include report writing, MACRO writing, and Programming using SAS Intranet. Lecture, two hours; laboratory, two hours per week. Prerequisites: STA 291 or equivalent.

3
CPH 630 Biostatistics II

Students will learn statistical methods used in public health studies. This includes receiver operator curves, multiple regression logistic regression, confounding and stratification, the Mantel-Haenzel procedure, and the Cox proportional hazardous model. Lecture, two hours; laboratory, two hours per week. Prereq: STA 580 or equivalent. (Same as STA 681.)

3
CPH 631 Design and Analysis of Health Surveys

Students will learn design and analysis issues associated with well-known national health surveys, including reliability and validity of measurements, instrument validation, sampling designs, weighing of responses, and multiple imputations. Students will learn how to use statistical software to analyze data from complex survey designs. Lecture, two hours; laboratory, two hours per week. Prereq: STA 580 or equivalent.

3
CPH 636 Data Mining in Public Health

This course concerns statistical techniques for and practical issues associated with the exploration of large public health data sets, the development of models from such data sets, and the effective communication of one’s findings. Prereq: STA 570 or 580 and CPH 535, or consent of instructor.

3
CPH 664 Design and Analysis of Clinical Trials

This course will introduce the fundamental concepts used in the design of Phase IIV clinical trials and statistical methodology associated with trial data analysis. Prereq: STA 570 or permission of instructor

3
CPH 930 Advanced Topics in Biostatistics

Addresses advance topics in biostatistics for the public health professional. Content emphasizes biostatistical concepts over methodology to prepare students for generalist public health positions. Course topics will address public health problem solving using study design, vital statistics, data, large health surveys, and an overview of multivariate statistics including multiple regression, logistic regression, longitudinal data, survival analysis, and recursive partitioning. Prerequisites: STA 570/580 or equivalent and one semester of calculus.

3
CPH 931 Professional Seminar in Biostatistics

Professional Seminar in Biostatistics is an advanced course in one of the five content areas of public health. All students enrolling will have completed the prerequisite introductory course at the masters’ degree level, and the advanced course at the doctoral level. The Professional Seminar in Biostatistics is designed as the opportunity to link academic work in biostatistics with application in public health practice, and to prepare the student for a leadership role in public health. This will be accomplished through readings, case studies and exercises, and individual research relevant to the discipline and the profession of public health.

3
STA 580 Biostatistics I

Descriptive statistics, hypothesis testing, paired and unpaired tests, ANOVA, contingency tables, log rank test, and regression with biostatistics applications. Prereq: MA 109 or equivalent.

3