What does a positive skew indicate in a distribution of scores?

A positive skew indicates that the majority of scores in a distribution are concentrated at the lower end, with a tail extending towards the higher values. This means most individuals or observations have scores that are lower than the mean, which is pulled in the direction of the higher values due to a few scores that are exceptionally high. Hence, the distribution is not symmetrical; instead, it shows a long tail on the right side. Understanding this concept helps in identifying the tendency of data and making interpretations about the overall performance or outcomes being measured.

The other options do not accurately describe the characteristics of a positively skewed distribution. For instance, a statement indicating that the majority of scores are high would describe a negative skew, while saying that scores are evenly distributed or that no skew is present doesn't align with the definition of a positive skew.