What does "negative skewed" indicate about the distribution of test scores?

A negative skewed distribution indicates that the tail on the left side of the distribution is longer or fatter than the right side. This results in most of the data points being concentrated on the higher end of the scale, which means that a majority of the scores are above the mean.

In such distributions, the relationships between the mean, median, and mode become significant. Specifically, in a negatively skewed distribution, the mean is typically pulled down more than the median due to the presence of lower scores. Therefore, the mean is lower than the median, reflecting the overall skew.

This characteristic helps in identifying the general placement of scores and understanding how performance is distributed around the average, which is crucial when interpreting test scores and performance metrics in various contexts. Understanding these distributions allows appraisers and evaluators to make informed assessments of performance data.