This workshop is intended for anyone who works with code they did not write themselves: generated by AI assistants, inherited from collaborators, or adapted from online examples. No previous experience with AI tools is required. This session will cover the following topics: checking your data and variable types before modeling; sanity-checking merges and sample sizes; catching “silent errors” code that runs without error but gives wrong results, and simple habits for testing unfamiliar code, etc. Examples use R, but the principles apply to any statistical software.

Hardware/software prerequisites: This is a virtual session. A Zoom link will be sent to registrants. Please make sure you have access to RStudio prior to the workshop. Information about R/RStudio installing the software can be found here.