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1. Could you gist your Python code?

2. You do not indicate whether you’ve run enough simulations to attain a high statistical significance (over the meta- result that each campaign statistical significance has been attained)

3. Correct me if I’m wrong, but I don’t think A/B testing should be run “until statistical significance has been attained” because it foils the purpose of a statistical test, that is, you should rather define before hand a number of iterations, wait until they have been completed, and then check whether it gives you statistical significance

4. The purpose of the epsilon-greedy algorithm is that it can be run for very long duration without knowing which statistical significance is best because it will adapt the most commonly seen version of your site to this particular version (ie it is made to be run almost indefinitely, and will -- in effect -- automatically remove the non-working versions after a while!




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