This workshop introduces zero-inflated poisson, zero-inflated negative binomial, and hurdle models for count data, which are two-part models used when more zeros are found in the data than expected with typical count distributions. We will discuss the formulations of the two parts of each model, the interpretation of model parameters, and how to run these models and analyze zero-inflated count data in R.