What is a common outcome when a study experiences a skewed distribution of scores?

A skewed distribution of scores typically indicates that data points are not evenly spread across the range of possible values, which often results in the overrepresentation of certain outcomes. This happens because, in a skewed distribution, the majority of the scores cluster towards one end of the scale, leaving fewer scores at the opposite end. For example, if a dataset of test scores is skewed to the right (positively skewed), it means that there are many lower scores and only a few higher scores, leading to some outcomes being more frequent than others.

This skew can be significant in research, as it can affect statistical analyses and lead to biased interpretations if not recognized and accounted for. In contrast, a uniform distribution implies that all outcomes are evenly represented, while balanced outcomes suggest that different categories have similar representations, both of which are not typical characteristics of skewed distributions. A normal distribution, characterized by a symmetrical shape with most scores clustering around the mean, further contrasts with skewed distributions. Thus, the presence of a skewed distribution contributes to the overrepresentation of certain outcomes, making this the correct answer.