Andre is running an A/B Test for two different versions of his ad campaign using LinkedIn’s experimentation tools. After the test, he sees a p-value of 0.03. What does this p-value indicate about his ad campaign?
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Correct answer: There is a 3% likelihood that the difference in performance is due to random chance..
Why this is the answer
LinkedIn A/B Testing uses statistical measurement to determine whether one campaign variation performed meaningfully better than another. A p-value shows the probability that the observed performance difference happened by random chance. A value of 0.03 means the result has a low chance of being random, which supports confidence in the observed difference. This helps advertisers make optimization decisions based on test evidence rather than surface-level performance variation.
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