What does positive skewness indicate about data distribution?

Positive skewness indicates that the tail of the data distribution extends to the right. In a positively skewed distribution, most of the data points cluster toward the lower end of the range, while a few extreme values stretch the tail toward higher values. This results in a longer right tail, which reflects the presence of outliers or a significant number of high-value observations.

Understanding positive skewness is crucial in interpreting data, as it influences statistical measures, such as the mean and median. In a positively skewed distribution, the mean is generally greater than the median, highlighting the effect of the higher values on the average. This characteristic helps researchers and analysts recognize that data is not symmetrically distributed and may require specific statistical methods or transformations for analysis.