Which term best describes the consequence of a Type I error?

A Type I error occurs when a researcher concludes that there is an effect or a relationship when none actually exists. This is commonly referred to as a "false positive." In this context, it means that the researcher mistakenly identifies an effect, leading them to reject the null hypothesis when it is actually true.

For example, if a medical test indicates that a patient has a disease when they do not, the test has produced a Type I error. The consequence is significant because it can lead to unnecessary anxiety, further invasive testing, and inappropriate treatment for the patient. Understanding the concept of Type I errors is crucial for interpreting research findings and understanding the validity of conclusions drawn from statistical tests.