Which of the following is a characteristic of resistant statistics?

The selected answer accurately highlights a key characteristic of resistant statistics, which is their ability to summarize data while minimizing the influence of extreme values or outliers. Resistant statistics, such as the median and interquartile range, are designed to provide a more accurate representation of a dataset when it contains unusual or extreme observations that could skew the results. This makes them particularly useful in real-world data analysis where outliers can heavily distort measures such as the mean and standard deviation.

In contrast, options that suggest including all data points or being highly affected by outliers do not align with the definition of resistant statistics. These measures specifically aim to produce a summary that reflects the central tendency and variability of the main body of data, independent of any extreme values. The implication that resistant statistics are only applicable to small datasets is also incorrect; they can be applied to datasets of any size, further affirming their utility in various analytical contexts.