Which measure is most appropriate for summarizing variability in a dataset?

The standard deviation is the most appropriate measure for summarizing variability in a dataset because it quantifies the amount of dispersion or spread in the values. Specifically, the standard deviation indicates how much individual data points differ from the mean of the dataset. A low standard deviation means that the data points are generally close to the mean, while a high standard deviation indicates that the data points are spread out over a larger range of values.

The median, mode, and mean focus on central tendency rather than variability. The median provides the midpoint of a dataset, the mode identifies the most frequently occurring value, and the mean calculates the average score. While these measures are helpful for understanding the central value of the data, they do not provide insight into how much the data varies, which is crucial for a comprehensive understanding of any dataset's characteristics. Thus, when it comes to summarizing variability specifically, standard deviation is the preferred choice.