Which of the following is a potential outcome of an increased Type II error?

An increased Type II error refers to the failure to reject a false null hypothesis, which occurs when a real effect is present but is not detected by the statistical test. Consequently, the outcome of an increased Type II error is that researchers may conclude there is no significant effect when, in reality, one exists. This leads to missed opportunities for discovering valid relationships or effects in the data, which is precisely what option B describes.

Recognizing a real effect is critical for advancing knowledge in a given field, and failing to identify it can result in flawed conclusions and impede progress in research. Understanding Type II error is essential for researchers to ensure they are adequately powered to detect meaningful effects when they are present.