Abstract: Many graduate students in the basic sciences are afraid of data exploration and cleaning, which can greatly impact their downstream analysis results. By using a synthetic dataset, some simple `dplyr` commands, and a `shiny` dashboard, we teach graduate students how to explore their data and how to handle issues that can arise (missing values, differences in units). For this talk, we'll run through a simple EDA example (combining two weight loss datasets) with a general data explorer in `shiny` that can be easily customized to teach specific EDA concepts.
