"When the facts change, I change my mind. What do you do, sir?" - John Maynard Keynes (maybe)

A/B testing as the name suggests, is a method of statistically testing two different versions of a design pattern to determine difference of effectiviness. Simply put, an A/B test is a way to compare two versions of a single variable by testing a subject's response to one version against the other, and determining which of the two is more effective.

I work in the biopharma industry and A/B tests come up all the time. Our aim lies in calculating the effectiveness of a certain drug A versus drug B. So we would test the drug A on some percentage of a patient group and the drug B on the rest of the patient group. After sufficient trials are performed, the in-house statisticians (my SAS people!) measure the efficacy to ascertain which drug gave better results.

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