What is defined as a Type I error?

A Type I error occurs when a researcher incorrectly rejects the null hypothesis when it is true. Essentially, this error represents a false positive finding, where the results suggest that there is an effect or a difference when, in reality, none exists. In the context of hypothesis testing, the null hypothesis typically posits that there is no effect or no difference, and to commit a Type I error means that the evidence collected leads the researcher to falsely conclude that a significant effect is present. This is an important concept in statistical inference, as controlling the risk of Type I errors is crucial in research design and interpretation of results.