Enter a list of numbers to instantly get mean, median, mode and range.
Mean = sum ÷ count. Median = middle value when sorted. Mode = most frequent value(s). Range = max − min.
Mean, median and mode are all "averages" in the loose everyday sense, but they measure genuinely different things and can diverge sharply on the same data set — which is precisely why relying on just one of them can be misleading. The mean (sum of all values divided by count) is pulled hard by outliers: a neighborhood of nine houses worth $300,000 each and one mansion worth $3,000,000 has a mean home value over $570,000, a number that doesn't represent a single actual house in that neighborhood. The median (the middle value when data is sorted) is unaffected by that same outlier — it would still show $300,000, arguably the more representative "typical" value for that neighborhood.
This is exactly why income and home-price statistics are so often reported as medians rather than means — income and wealth distributions have a long right tail (a relatively small number of very high earners), and the mean gets dragged upward by that tail in a way that overstates what a "typical" person actually earns, while the median stays anchored to the actual middle of the distribution. Mode (the most frequently occurring value) serves a different purpose entirely — it's the only one of the three that works for non-numeric, categorical data (like the most common shoe size sold, or the most frequent survey response), and a data set can have one mode, multiple modes, or no mode at all, unlike mean and median which always produce exactly one value.
Mean is the sum of all values divided by the count. Median is the middle value when data is sorted from smallest to largest. Mode is the most frequently occurring value. All three are called 'averages,' but they can produce very different numbers on the same data set, especially when outliers are present.
Because the mean incorporates every value's magnitude directly into the calculation, so one extreme value pulls the total (and therefore the average) noticeably in its direction. The median only cares about which value sits in the middle position once sorted, so an extreme outlier at either end doesn't change which value is in the middle.
Because income distributions have a long right tail — a relatively small number of very high earners — and the mean gets pulled upward by that tail, overstating what a 'typical' person actually earns. The median stays anchored to the actual middle of the distribution, making it a more representative figure for typical income.
Yes — unlike mean and median, which always produce exactly one value, a data set can be bimodal (two values tied for most frequent), multimodal (more than two), or have no mode at all if every value appears with equal frequency. Mode is also the only one of the three measures that works meaningfully on non-numeric, categorical data.