If a study finds a statistically significant difference where none exists, what type of error is this called?

A statistically significant finding where none exists is known as a Type I error or an alpha error. This occurs when the null hypothesis is rejected despite it being true. In hypothesis testing, the null hypothesis typically posits that there is no effect or no difference between groups. When researchers incorrectly reject this null hypothesis, they conclude that an effect exists when, in reality, it does not. This type of error is particularly critical in research and clinical settings because it can lead to false conclusions and potentially harmful decisions based on the incorrect assumption that an intervention or variable has a significant effect.

The concept of alpha error is directly tied to the significance level set before conducting the test (commonly 0.05), which represents the probability of making a Type I error.