Covers contingency tables, measures of association, stratified analysis, logistic regression, generalized linear models, Poisson regression, log-linear models, matched data, marginal homogeneity, and methods for ordinal outcomes.
Two-course sequence providing a foundation in quantitative and research methods for evidence-based public health, with emphasis on study design, statistical reasoning, data analysis, and interpretation of findings.
Two-course sequence covering biostatistical reasoning and applied data analysis. Topics include descriptive statistics, probability, statistical inference, ANOVA and ANCOVA, linear and logistic regression, clinical trial design, nonparametric and categorical methods, factor and cluster analysis, and longitudinal and repeated-measures approaches.