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Data Science · Glossary

A/B Testing

An experimental method that compares two versions of something to determine which performs better against a defined metric.

A/B testing is how most product and marketing decisions get validated with real data rather than opinion — showing version A to one group and version B to another, then comparing results.

Want to actually work with A/B Testing? This concept is covered hands-on in our Statistics for Data Science program — not just defined, but practiced.
View Statistics for Data Science
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