What defines a negatively skewed distribution?

A negatively skewed distribution is characterized by the tail of the distribution extending more towards the left side. This means that the bulk of the data is concentrated on the right of the mean, and there are fewer lower values pulling the tail to the left. In this scenario, the mean is typically less than the median, which illustrates the influence of the lower values on the overall data structure.

Negatively skewed distributions often appear in scenarios where extreme low values are present but most data points fall within a higher range. This distribution shape implies that while there are some low values, the majority of the observations lie at the higher end of the scale. Understanding this concept is crucial in fields such as sustainability accounting, where recognizing data distribution can inform decision-making and analysis of environmental impacts or resource management.