Alpha (Alpha risk)

Alpha risk, also known as Type I error, is the probability of incorrectly rejecting a true null hypothesis in statistical testing. In simpler terms, it’s the chance of concluding that a treatment or effect is significant when, in fact, it isn’t—essentially a false positive. Researchers typically set alpha at 0.05, meaning there’s a 5% risk of making this error. Managing alpha risk is crucial to ensure that findings are reliable and not just due to random chance.