What is a Type I error?

A Type I error occurs when the null hypothesis is incorrectly rejected when it is actually true, which leads to a false positive result in statistical testing. This means that researchers conclude that there is an effect or a difference when, in reality, there is none.

The correct option indicates that a Type I error includes both rejecting the null hypothesis when it should not be rejected and the resultant false positive outcome. These concepts are crucial for understanding the implications of statistical testing in research; when conducting hypothesis testing, avoiding Type I errors is essential for maintaining the integrity of research conclusions. This error can lead to misguided theories, ineffective treatments, or policies based on inaccurate interpretations of data.

Recognizing that a Type I error involves both the misjudgment of the null hypothesis and resulting false positives in findings helps clarify the stakes involved in statistical analysis, particularly in psychological research contexts.