Which statistic best describes dispersion of a dataset around the center for a numerical dataset?

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Dispersion around the center for numerical data is best described by the standard deviation. It measures how far, on average, each data point lies from the mean by averaging the squared deviations and then taking the square root, so the result is in the same units as the data. This uses every value in the dataset, giving a precise sense of typical variability and aligning with many statistical methods and distributions. The median and mode describe where data tend to sit (central tendency) rather than how spread out they are, so they don’t quantify dispersion. The range shows only the extreme spread from minimum to maximum and can be heavily influenced by outliers, missing the nuance of how values cluster around the center. In short, standard deviation provides a fuller, unit-consistent measure of dispersion for numerical datasets.