In a negatively skewed distribution, where is the long tail, and where is most data concentrated?

In a negatively skewed distribution, where is the long tail, and where is most data concentrated?

• A. The long tail is on the positive side and most data are centered on the left.
• B. The long tail is on the negative side and most data are concentrated on the right.
• C. The data are uniformly distributed.
• D. The median is always greater than the mean.

Answer: (B)

Negatively skewed means the long tail stretches to the left (lower values), while the bulk of the data clusters toward the right (higher values). So the tail is on the negative side and most data are concentrated on the right. This is why that description is the best match for a negatively skewed distribution. The other statements don’t fit: a tail on the right would be positive skew, a uniform distribution has no tail or concentration pattern, and in negative skew the mean is pulled toward the tail and is typically less than the median (not always the median greater than the mean).

Negatively skewed means the long tail stretches to the left (lower values), while the bulk of the data clusters toward the right (higher values). So the tail is on the negative side and most data are concentrated on the right. This is why that description is the best match for a negatively skewed distribution. The other statements don’t fit: a tail on the right would be positive skew, a uniform distribution has no tail or concentration pattern, and in negative skew the mean is pulled toward the tail and is typically less than the median (not always the median greater than the mean).