We have all heard the maxim "correlation does not imply causation", but causation is often what environmental researchers seek to find. In this workshop we will explore tools to infer causal relationships in real-world data, using an example of environmental pollution and home values. The two-hour workshop will feature a presentation on necessary background material and then segue into an applied R-based example, with plenty of time for discussion and questions throughout. Registration is required.

Through this workshop, you will:

• Gain a basic understanding of some of the key tools for causal inference with observational data, including difference-in-differences, regression discontinuity, and instrumental variables. We will discuss the idea behind these different approaches, their strengths and weaknesses, and to what scenarios they can be applied.
• Work through an R-based example of the difference-in-difference approach
• Talk through ways in which these methods might be applied to your own research
• Meet other environmentally-interested faculty across campus who are seeking to "level up" their research skills and build community

This workshop is designed for faculty or research staff with basic R familiarity and provides both conceptual understanding and applied skills relevant across disciplines. Participants should bring their own laptops with a pre-installed copy of RStudio (https://posit.co/download/rstudio-desktop/).

Please note: This workshop is designed for faculty and research staff participants; graduate students may join if space permits.

RIEEE's EnviroData Collaborative (EDC) cultivates a vibrant, interdisciplinary community of Appalachian State faculty and research staff advancing environmental data science and modeling capacity through hands-on skill building, shared learning, and collaborative exchange.