Mean

Mean (specifically the arithmetic mean) is the sum of a set of values divided by their count. For the dataset [4, 8, 6, 5, 3, 7]: sum 33, count 6, mean 5.5. It’s the most common form of “average” in everyday speech and the default returned by AVG(), numpy.mean, statistics.mean, and every other library function called “mean.”

Important properties: it’s sensitive to outliers (one extreme value pulls it dramatically), it has the same units as the underlying data, and it’s a property of a set — not of any individual element. The mean of [1, 1, 1, 100] is 25.75; only one of the four values is even close.

Other “means” exist for specific contexts: the geometric mean (nth root of the product, used for compounding rates), the harmonic mean (reciprocal of the mean of reciprocals, used for averaging rates), the weighted mean (some values count more than others). When someone says “mean” without qualification, they mean the arithmetic mean.

Use the statistics calculator for any of these or for the median, mode, variance, and standard deviation in a single pass.