Correlation vs. Causation: Why Getting It Wrong Can Derail Good Decisions

In this solo episode of Evidence in the Wild, I explore one of the most common pitfalls in interpreting data, confusing correlation with causation. Whether it's linking ice cream consumption to shark attacks, or assuming a program "works" based on surface-level trends, failing to account for confounding variables can lead to deeply flawed conclusions.
I share a vivid education example from a well-known randomized control trial of charter schools and explain how rigorous methods help us move from hunches to evidence. We’ll also touch on how these issues show up in everyday conversations, policymaking, and the research-to-practice gap.
Read the full study referenced in this episode: https://www.aeaweb.org/articles?id=10.1257/app.5.4.1