In skewed distributions, what does a negatively skewed curve indicate?

In a negatively skewed distribution, the curve displays a longer tail on the left side, which indicates that the majority of the data points, or scores, are concentrated towards the higher end of the scale. This means that there are fewer low scores influencing the average, raising the mean relative to the median.

A negatively skewed curve signifies that while most scores are higher, there are some lower scores pulling the tail out to the left. This clustering of higher scores can often result in the median being higher than the mean, which is a characteristic of this type of distribution. Understanding the shape of a negatively skewed distribution helps in interpreting the central tendency of the data and how scores relate to one another.