The course objective is to focus on a logistic regression approach for analyzing contingency table data, where the cell entries represent counts that are cross-tabulated using categorical variables. It lays the groundwork for logistic regression models for binomial responses and goes on to introduce more complex data structures, e.g. those with more categorical variables or continuous covariates. Students get a broad view of the generalized linear model framework and are also exposed to several model variations. This course is laser-focused on logistic regression modeling and how to interpret these models, rather than the theory behind them.