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Controlled experiments such as A/B tests are used heavily by companies.

However, many people are repelled by A/B testing due to the presence of intimidating statistical jargon including terms such as confidence, power, p-value, t-test, effect size, and so on.

In this article, I will show you that you dont need a Master in Statistics to understand A/B testing quite the opposite. In fact, simulations can replace most of those statistical artifacts that were necessary 100 years ago.

Not only this: I will also show you that the feasibility of an experiment can be measured using something that, unlike confidence and power, is understandable by anyone in the company: dollars.

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Forget Statistical Tests: A/B Testing Is All About Simulations - Towards Data Science