Courses

All courses carry 3 credits unless otherwise specified.

540 Introductory Biostatistics  Introductory course. Statistical concepts and interpretation of numeric data summaries along with basic analysis methods, using examples from medical and public health studies.

591L Reproductive Epidemiology Introduction to areas of active research in the field of reproductive health focusing on their public health significance, descriptive epidemiology etiology and prevention.  Addresses both methodologic and substantive challenges to reproductive and perinatal research.

597D Introduction to Statistical Computing in R  Introductory course. Foundational training in the modern tools of statistical computing and reproducible research using R. Manipulate, summarize, analyze, and visualize data using R. Credit, 1.

597E Intermediate Statistical Computing  Prepare students with necessary computing skills for a career as a statistician or data analyst/scientist. Students will learn to use various tools to extract data from different sources (structured or unstructured), and transform them into forms that are ready for analysis and modeling. Students will also be able to build web based tools to deliver data products using R Shiny. Credit, 1.

597F Advanced Statistical Computing   Prepare students with advanced computing skills for a career as a statistician or data analyst/scientist. By the end of this course, you should be able have mastery over the fundamentals of the R programming language, including concepts such as functional programming and meta programming.

630 Principles of Epidemiology  Introductory course. An epidemiological perspective on health. General approaches for describing patterns of disease in groups of people, and elucidating various processes involved in creating differing levels of health in human groups. Lecture and lab examples of a wide range of contemporary health problems.

631 Scientific Writing for Thesis, Dissertation and Grant Proposals in Epidemiology  Provides students with the necessary analytic techniques, technical resources, and writing expertise to design and write thesis proposal and final thesis manuscripts in the field of epidemiology. Students prepare a written proposal and a class presentation, and critique another presentations. Prerequisite: EPI 630.

632 Applied Epidemiology   Intermediate level course. Application of epidemiologic methods to study the etiology, control, and impact on society of selected diseases. Prerequisite: EPI 630.

633 Communicable Disease Epidemiology   Review of selected infectious diseases; emphasis on current theories of distribution, transmission, and control.

634 Nutritional Epidemiology   Epidemiologic study design problems and issues; major methods of dietary assessment; non-dietary nutritional assessments; and the relative strength of evidence in support of diet-disease relationships. Prerequisite: PUBHLTH 630.

635 Social Epidemiology   Links between life styles and risks to which individuals in populations are vulnerable. Models linking social stress and physiological responses, psychosocial mediators, and social support systems as they promote or reduce susceptibility to disease.

636 Epidemiological Assessment   Methods for epidemiological assessment of the efficacy and safety of medical technologies, including drugs, devices, and medical and surgical procedures.

639 Cancer Epidemiology   Background in the principles of oncology and a review of epidemiological strategies used in cancer research. The major cancer risk factors and the key strategies of prevention.

640 Intermediate Biostatistics   Intermediate course. Basic statistical literacy and skills in the analysis of biological and health data.  Use of the computer (Stata and R) and the analysis of data sets included. Prerequisite: BIOSTATS 540.

650 Biostatistics Methods 2: Applied Regression Modeling   Intermediate course. Theory and application of linear regression and generalized linear regression models.  Examples and exercises from scientific, medical, and public health reserach.  Prerequisitie:  BIOSTATS 540.

690EW Epidemiology of Women's Health   Overview of current issues in women's health throughout the life cycle.  Exploring how epidemiologic methods are used to evaluate factors influencing reproductive health, cancer, cardiovascular disease and other common disorders.  Sstudents learn basic quantitative methods, study design concepts, and critical thinking skills.

690JQ Biostatistics Methods 3: Modern Applied Statistical Learning   Advanced Course. Statistical modeling approaches including: penalized regression, methods for classification, statistical methods for biomarker discovery, robust regression, and flexible regression methods. Prerequisite: BIOSTATS 540

690MS Applied Stochastic Models in Population Geonomics   Introduction to stochastic models used in Population Genomics to study the evolutionary forces that shape genetic variation. These models will be introduced in a neutral setting, and extend to incorporate biological phenomena like natural selection, recombination, and changes in population size and structure.  Students will learn how to use these models for simulation, as will as applying them to modern genomic datasets to infer biological relevant parameters.

690T Applied Statistical Genetics  Statistical concepts and R tools relevant to the analysis of genetic data arising from population-based association studies. Multiple comparison procedures, classification algorithms for high dimensional data, methods for haplotype estimation and unobservable phase.

691F Data Management and Statistical Computing   Introductory course. Basic data management principles and practice. Design of data collection forms, data processing/cleaning, sampling from databases, data security and generation of descriptive summary reports.

691P Seminar - Physical Activity  Epidemiologic methods in studies of physical activity. Seminar will cover measurement of physical activity and inactivity; establishing validity and reliability of physical activity; design of present-day epidemiologic studies of physical activity and health; and physical activity surveillance.

696D Independent Study in Public Health  Special investigational or research problems for M.P.H. candidates or advanced students. Scope of the work can be varied to meet specified conditions. Credit, 3-6.

697G Bayesian Computation in Biostatistics   Theory and application of Bayesian methods for analysis of biomedical datasets. Bayesian thinking, estimation of single and multi-parameter models and Bayesian computation using Markov Chain Monte Carlo (MCMC) methods.

698 Practicum  Opportunity for supervised field observation to gain practice experience in selected public health agencies.

699 Master’s Thesis   Independent research leading to a thesis on a public health subject. Results should be suitable for publication. Credit, 3-6.

700 Analysis of Epidemiologic Data   Students will develop fundamental skills in data analysis and interpretation.  A major emphasis will be to gain practical experience in analyzing data using statistical software.

737 Intermediate Methods in Epidemiology   A methodologic core course. Details of concepts and quantitative techniques used in modern epidemiology. Prerequisites: EPI 630 and 632.

740 Mixed Models and Longitudinal Data Analysis   Advanced course. Mixed model methods and longitudinal data analysis applications in statistics.

741 The Design and Analysis of Experiments in the Health and Pharmaceutical Sciences   Fundamental concepts in experimental design, with specific application to medical, public health, and pharmaceutical research. Extensive use of computer programs; many illustrative examples. Prerequisite: PUBHLTH 640.

743 Analysis of Categorical Data in the Health Sciences   An overview of statistical methods for analyzing data where the outcome variable is categorical or discrete. The course will emphasize the theoretical underpinnings of the methods as well as an applied understanding of the computation and interpretation, both of which are necessary to succeed with real data analysis.  We will cover inference for binomial and multinomial variable with contingency tables, generalized linear  models, logistic regression for binary responses, logit models for multiple response categories, log-linear models, some statistical machine learning approaches, inference for matched-pairs, and correlated/clustered data. Examples will be taken from public health and biomedical research.  Prerequisite: BIOSTATS 540, STAT, 515, STAT 516, BIOSTATS 650/525, or equivalent coursework.

744 Computer Analysis of Health Sciences Data  Applications of the linear regression model. Emphasis on use and interpretation of statistical software output. Prerequisite: BIOSTATS 640.

745 Sampling Methods for the Health Sciences   Application of widely used sampling methods to situations commonly occurring in public health research. Alternative sampling strategies compared; emphasis on design of sample surveys. Types of samples stressed: simple random sample, stratified sample, systematic sample, and cluster sample. Also the combined ratio estimate, and large-scale, ongoing sample surveys such as the Health Examination Survey of the National Center for Health Statistics. Prerequisite: BIOSTATS 540.

746 Nonparametric Methods in Public Health Research   Application of nonparametric methods to commonly occurring problems in public health research. Data from one, two, and multisample problems from environmental health, epidemiology, health administration, and health education. Prerequisite: BIOSTATS 540.

748 Applied Survival Analysis   Introduction to statistical techniques used for the analysis of time-to-event data. Types of censoring mechanisms, graphical and numerical description of survival data, methods for comparison of survival between groups, Cox and AFT models to explain and predict survival as a function of baseline and time-varying covariates.

749 Statistical Methods for Clinical Trials  Statistical techniques in the design, analysis and interpretation of clinical trials. Types of clinical research, study design, treatment allocation, randomization and stratification, quality control, sample size requirements, patient consent, introduction to survival analysis and interpretation.

796 Independent Study

797 Special Problems

891 Research Seminar

892A Doctoral Seminar in Epidemiology Credit, 1.

892BW Advanced Epidemiological Methods Seminar   A PhD level seminar class that will explore complex and contemporary methodological concepts used in epidemiological research, as described in the published epi methods literature. Credit, 1.

892D Doctoral Seminar in Biostatistics. Credit, 1

899 Doctoral Dissertation. Credit, 18.