Fill in the blank: Most tools require you have a confidence threshold of ————, in order to declare a winner in an A/B test.





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Explanation: The correct answer is ‘95%.’ In statistical hypothesis testing, particularly in A/B testing, a confidence level of 95% is commonly used to determine statistical significance. This confidence level indicates that there is a 95% probability that the observed difference in performance between the variations is not due to random chance but is instead a result of the actual difference in the variations. In other words, if the test reaches a confidence level of 95% or higher, it suggests that the observed results are reliable and meaningful, allowing marketers to confidently declare a winner and make informed decisions based on the test outcomes. This threshold provides a balance between being confident in the results while still allowing for a small margin of error, ensuring that conclusions drawn from the A/B test are robust and actionable.

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