What is a Type I error?

A Type I error occurs when a researcher incorrectly rejects a null hypothesis that is actually true. This means that the study concludes that there is an effect or a difference when, in reality, none exists. This situation is often referred to as a "false positive," where the evidence or data appears to support a significant finding that is not actually present.

In the context of hypothesis testing, the null hypothesis typically represents a statement of no effect or no difference. When a Type I error happens, it suggests that the researcher has detected a relationship or effect that is simply due to random chance rather than a true underlying effect in the population being studied. Understanding this concept is critical in research, as it emphasizes the importance of setting an appropriate significance level (alpha) to minimize the likelihood of making such an error.