The salaries of a small business are graphed with many outliers in the upper range. How is this histogram described?

When examining how a histogram is described, the presence of many outliers in the upper range directly influences the distribution's shape. In this scenario, the presence of outliers above the main cluster of data points indicates that the tail of the histogram is extended to the right. This asymmetrical distribution, where most of the data values are concentrated on the left and the right tail is longer or fatter, is characteristic of a right-skewed distribution.

In contrast, a left-skewed distribution would indicate that the lower values have a longer tail. A normal distribution would imply symmetry around the mean, with no significant outliers present. A bimodal distribution would have two distinct peaks, which is not suggested by the presence of many outliers in the upper range.

Thus, the correct description of the histogram with many outliers in the upper range is that it is right skewed, demonstrating how outliers can significantly affect the overall shape and interpretation of the data distribution.