What is the difference between mean, median, and mode?

The mean is what most people call the average: add all the values and divide by how many there are. The median is the middle value when the data are sorted, with half above and half below, and for an even count it is the average of the two central values. The mode is the value that occurs most often, and a dataset can have several modes or none.

The choice between them is where statistics gets consequential rather than academic. The mean is sensitive to outliers, so a handful of extreme values drags it far from where most of the data sit, while the median is resistant. This is precisely why income, wealth, and home price statistics are reported as medians: put a few billionaires in a room of ordinary earners and the mean income becomes enormous while describing no one present, whereas the median still describes a typical person. Reporting that switches between the two is a reliable place to look for spin, since mean and median tell very different stories about skewed distributions like housing costs, salaries, and healthcare charges. Mode is most useful for categorical data, the most common response, the best-selling size, where averaging makes no sense. A good rule: symmetric data, mean is fine; skewed data, use the median and be suspicious of anyone who does not.