Which statement about skewness is correct?

• A. Right-skewed distributions have longer right tails; left-skewed have longer left tails.
• B. The right tail is shorter for right-skewed distributions.
• C. Skewness measures only the central peak.
• D. A symmetric distribution has positive skewness.

Answer: (A)

Skewness describes how the distribution is asymmetric and where its longer tail lies. In a right-skewed (positive skew) distribution, the right tail is longer, and most data cluster on the left. In a left-skewed (negative skew) distribution, the left tail is longer, with most data on the right. This aligns with the statement being correct.

The idea that the right tail is shorter for a right-skewed distribution contradicts the definition, so that option isn’t correct. Skewness isn’t about the central peak alone; it’s about asymmetry and tails, so claiming it measures only the central peak misses the whole point. And a symmetric distribution has no skewness (zero), not positive skewness, so that option is also incorrect.