Research findings that display no significant difference when there is one can be attributed to which type of error?

A type II error occurs when a researcher fails to reject the null hypothesis when it is actually false. In other words, it represents a situation where the study concludes that there is no significant difference between groups or conditions when, in fact, such a difference does exist. This can happen due to insufficient sample size, low statistical power, or variability within the data that obscures the true effect. Therefore, the choice that indicates a lack of significant findings despite a genuine difference is indeed a type II error.

A type I error, on the other hand, refers to incorrectly rejecting the null hypothesis when it is true, leading to a false positive result. Type III errors pertain to correctly rejecting the null hypothesis for the wrong reason, while type IV errors are less commonly discussed in statistical literature and often refer to errors related to an inappropriate study design or analysis. These concepts do not directly address the scenario of failing to detect a true difference.