Define Positive skew.

Define Positive skew.

• A. A distribution that is skewed to the right (tail to the right)
• B. A distribution that is skewed to the left (tail to the left)
• C. A symmetric distribution
• D. A distribution with no outliers

Answer: (A)

Positive skew means a distribution with a longer tail on the right side. Most scores cluster toward the lower end, while a few unusually high values stretch the tail to the right and pull the mean upward (the mean tends to be greater than the median, with the mode lowest). In practice, this shows up as a right-leaning histogram. It’s different from left-skew (tail on the left), a symmetric distribution (balanced tails), or a distribution with no particular tail pattern, which doesn’t define skewness. So the description that fits is a distribution skewed to the right, with a tail to the right.

Positive skew means a distribution with a longer tail on the right side. Most scores cluster toward the lower end, while a few unusually high values stretch the tail to the right and pull the mean upward (the mean tends to be greater than the median, with the mode lowest). In practice, this shows up as a right-leaning histogram. It’s different from left-skew (tail on the left), a symmetric distribution (balanced tails), or a distribution with no particular tail pattern, which doesn’t define skewness. So the description that fits is a distribution skewed to the right, with a tail to the right.