In a positively skewed distribution, where is the long tail, and where is most of the data centered?

In a positively skewed distribution, where is the long tail, and where is most of the data centered?

• A. The long tail is on the positive side and most data are centered to the left.
• B. The long tail is on the negative side and most data are centered to the right.
• C. The distribution is perfectly symmetrical.
• D. The mean is always equal to the mode.

Answer: (A)

In a positively skewed distribution, the tail stretches toward higher values while most of the data pile up toward the lower end. This means the long tail is on the positive side, and most data are centered to the left. That matches the statement that the long tail is on the positive side and most data are centered to the left. The other ideas don’t fit because a left tail would indicate negative skew, not positive. A perfectly symmetrical distribution has no skew, and in a skewed distribution the mean, median, and mode aren’t all equal—the mean is dragged toward the tail, so it’s not equal to the mode.

In a positively skewed distribution, the tail stretches toward higher values while most of the data pile up toward the lower end. This means the long tail is on the positive side, and most data are centered to the left. That matches the statement that the long tail is on the positive side and most data are centered to the left.

The other ideas don’t fit because a left tail would indicate negative skew, not positive. A perfectly symmetrical distribution has no skew, and in a skewed distribution the mean, median, and mode aren’t all equal—the mean is dragged toward the tail, so it’s not equal to the mode.