Which type of error occurs when the null hypothesis is rejected when it is actually true?

The answer is indeed the identification of a Type I error. This type of error occurs when a researcher concludes that there is a significant effect or difference when, in reality, there is none; that is, they reject the null hypothesis even though it is true.

In hypothesis testing, the null hypothesis typically posits that there is no effect or no difference. When researchers perform tests and find results that lead them to reject this null hypothesis incorrectly, they are making a Type I error. This is akin to a "false positive," where one mistakenly believes they have found evidence for something that simply isn’t there, leading to potentially misleading conclusions in research.

Understanding Type I errors is crucial because it emphasizes the importance of setting appropriate significance levels (like alpha = 0.05) in research to control the likelihood of making such errors, ultimately ensuring that findings are reliable and valid.