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Research, past history, and even gut feelings can give us strong indications of what is likely to happen, but there's no better way to find out than to run a real, live test.
A/B testing is a simple way to put a hypothesis to work, and generate real results and insights from your actual users. In this class, we will learn what is required to run a clean experiment (control vs variable, sample size, significance analysis, etc) that can create significant and actionable results.
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