Define Negative skew.

Define Negative skew.

• A. A distribution that is skewed to the left (tail to the left)
• B. A distribution that is skewed to the right (tail to the right)
• C. A symmetric distribution
• D. A distribution with a sharp peak

Answer: (A)

Negative skew describes a distribution in which the left tail is longer or fatter than the right tail. Most observations cluster toward the higher end, while a few low scores pull the tail to the left. Because those few low values pull the average downward, the mean is typically smaller than the median, and the median is smaller than the mode. This contrasts with a distribution skewed to the right (tail to the right, mean higher than the median), a symmetric distribution (no skew), or a distribution with a sharp peak (leptokurtic, not defined by skew).

Negative skew describes a distribution in which the left tail is longer or fatter than the right tail. Most observations cluster toward the higher end, while a few low scores pull the tail to the left. Because those few low values pull the average downward, the mean is typically smaller than the median, and the median is smaller than the mode. This contrasts with a distribution skewed to the right (tail to the right, mean higher than the median), a symmetric distribution (no skew), or a distribution with a sharp peak (leptokurtic, not defined by skew).