A team wants to quantify how far daily values usually fall from the average, using a single measure on the same unit scale as the dataset. Which measure meets this goal best?
One measure finds typical distances from the average by taking a square root of the average of squared distances, which preserves the original unit scale. This helps depict data spread in a way that is directly comparable to the original measurements. Range looks at extremes, which can distort typical spread. Variance is reported in squared units instead of the data's scale. Distribution is not a single number but a set of values that show how data are spread out.
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Why is standard deviation better than variance for measuring data spread on the same unit scale?
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How does standard deviation help in understanding the spread of data?
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What are the limitations of using standard deviation to measure data spread?