What is represented by negative skewness in a dataset?

Negative skewness in a dataset indicates that the tail on the left side of the distribution is longer or fatter than the right side. In other words, the bulk of the data points are clustered on the right, with fewer points trailing off towards the left. This results in a leftward extension of the tail.

When you visualize this, you'll notice that most values are situated towards the higher end of the scale, with fewer lower-end values dragging the mean down in comparison to the median. Therefore, the indication of negative skewness is primarily about the shape of the distribution, emphasizing that the left tail is more pronounced.

This characteristic helps in understanding the overall distribution and can influence various statistical analyses, such as assumptions of normality or decisions in choosing the appropriate measures of central tendency.