How does the presence of outliers affect the range of a data set as discussed in the chapter?

The presence of outliers significantly affects the range of a data set by increasing it. A single outlier can cause the range to expand dramatically, which can lead to misleading interpretations of the data's variability.

Outliers can have a substantial impact on the range of a data set because the range is calculated by subtracting the lowest score from the highest score. When an outlier is present, particularly a high outlier, it increases the highest score, thus expanding the range. This can lead to a misrepresentation of the data's variability, as the range may suggest a broader spread of data than actually exists. For example, in a data set with systolic pressures of 125, 130, 122, 128, and 160 mmHg, the presence of the outlier 160 increases the range to 38 mmHg, compared to a much smaller range without the outlier. This can falsely imply that the data varies more widely around the mean than it actually does.