Number of weekly car accidents at an intersection, number of published articles by faculty, number of falls in a hospital per week. These are examples of count data. Statistical modeling of count data sometimes requires special handling. For starters, counts are discrete and they can’t be negative. Counts can also have odd or highly skewed distributions. For these reasons we need special methods to model count data. In this workshop we cover various types of count models and how to assess, interpret and visualize them. Knowledge of basic linear modeling and familiarity with R would be helpful but are not required.