ELI5 mode
A Type I error happens in hypothesis testing when you incorrectly reject a true null hypothesis, essentially declaring something significant that isn't. This 'false positive' is controlled by setting an alpha level, like 0.05, and it's a sneaky pitfall in modern research that can lead to overhyped results in fields from medicine to AI.
AI-generated·