File:Comparison_standard_deviations.svg · Wikimedia Commons · See Wikimedia Commons
thumb|400px|right|Example of samples from two populations with the same mean but different variances. The red population has mean and variance (), while the blue population has mean and variance ().
Variance measures how spread out data points are from their average—a small variance means numbers cluster close together, while a large variance means they're scattered far apart. It matters because two groups can have the same average but tell very different stories; for example, one group's values might be tightly bunched while another's are wildly scattered, which affects how predictable or stable that group is.
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