Median

Imagine lining up students by height in gym class. If you pick the student standing right in the center—not the shortest, not the tallest—that student's height is the median.

We usually think of the average (the mean, where you add all numbers and divide by the count) to represent a group. But the average has a major flaw: a single gigantic number can skew the entire result.

For example, imagine eight people with ordinary incomes gathered in a room, and a billionaire walks in. The average income of those nine people instantly surges into millions of dollars, even though nothing changed in the lives of the original eight. But if you sort all nine people by income and pick the income of the 5th person right in the middle, that value barely moves. Because the middle position only shifts over by one spot, one billionaire cannot pull the entire number off balance.

If you have an odd number of data points, finding the center is straightforward. If you have 5 numbers, the 3rd number is automatically the median.

However, when a dataset has an even number of values, there is no single middle spot. If 6 numbers are lined up, the center falls right between the 3rd and 4th numbers. In this case, there is a simple rule to follow.

You calculate the median by taking the average of the two middle numbers. For instance, if test scores are 10, 20, 30, 40, 50, and 60, you add the two middle values (30 and 40) and divide by 2, giving you 35. This ensures that even with an even number of data points, everyone arrives at the same single representative value.

In statistics, numbers that stray unusually far from the rest are called outliers. Many real-world datasets—such as home prices, household income, and website visit durations—are skewed by a small handful of extreme numbers.

When data is symmetrically distributed in a normal distribution (a balanced bell curve), the mean and median are virtually identical. But whenever inequality is high or extreme values exist, the mean fails to reflect reality accurately.

This is why news reports on housing or household wealth rely on median income or median home prices. Because it marks the exact 50th percentile of a population, it delivers a number much closer to what typical people actually experience.