If a curve tails off toward the high end of the scale, it is said to be skewed to which direction?

When a curve tails off toward the high end of the scale, it indicates that there are fewer occurrences of higher values, causing the distribution to lean toward lower values. This type of distribution is characterized as being skewed to the right.

In a right-skewed distribution, the majority of data points are clustered around the lower end, while the tail on the right side extends further out. In visual terms, the peak of the curve is on the left side, and as you move to the right, the number of occurrences decreases, hence the tailing off. This enhances the understanding that the mean of the data will be greater than the median in this type of skewness, due to the influence of the values on the right.

The other options relate to different types of skewness: a left-skewed (or negatively skewed) distribution has a tail on the left side, indicating a concentration of higher values; the terms "positive" and "negative" are sometimes used interchangeably with right and left skewed distributions, but without the context of the direction mentioned in the question, they can lead to confusion. Therefore, the clear association of tailing off toward the high end aligns with being skewed to the right.