The mean, often called the average, is the balancing point of a data set. Add up every value, then divide the total by how many values you had. Because every number contributes equally, one very large or very small value can drag the mean upward or downward.
The median is the middle value once the data are lined up from smallest to largest. If you have an odd number of values, the centre one is the median; if you have an even number, it is the halfway point between the two innermost values. Because it only cares about position, not size, extreme outliers hardly move the median at all.
Use it when your data are fairly symmetrical and free of extreme outliers – for instance, test scores in a single classroom or the average temperature over a month.
Choose it when the dataset is skewed or sprinkled with outliers, such as house prices in a city, income figures in an economy with a few billionaires, or daily website traffic that occasionally goes viral.
A school principal wants to know the typical height of students: the mean works well because heights seldom show wild extremes.
A journalist comparing typical salaries in Silicon Valley prefers the median, so that a handful of tech moguls do not inflate the picture.
A blogger tracking daily page views uses the median to stop one viral spike from masking an otherwise quiet month.
Mean
Add all the numbers (e.g. 10 + 12 + 8 + 15 = 45).
Count how many numbers there are (4).
Divide the sum by that count (45 ÷ 4 = 11.25).
Median
Write the numbers in order (8, 10, 12, 15).
If the list length is odd, pick the centre value. If even, average the two in the middle (10 + 12 = 22; 22 ÷ 2 = 11).
Both measures are simple, but knowing which one tells the truest story is what turns raw numbers into real insight.