True or false: If neither variation in an A/B is statistically better, you pick the variation you like best and proceed to make the change.

True

False


Choose an option to see if it’s correct. Check the explanation below.

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Explanation: True or false: If neither variation in an A/B is statistically better, you pick the variation you like best and proceed to make the change.


Explanation: **False**. It's crucial to base decisions on statistical significance rather than personal preference when conducting A/B tests. A/B testing is a method used to compare two versions of a webpage, email, or other marketing asset to determine which one performs better. Statistical significance ensures that the observed differences in performance between variations are not due to random chance. If neither variation demonstrates statistical superiority over the other, it means there's insufficient evidence to conclude that one version outperforms the other. In such cases, it's essential to continue testing or explore alternative hypotheses to identify factors that may influence performance. Making decisions based solely on personal preference can lead to biased outcomes and ineffective optimization efforts, potentially missing opportunities for meaningful improvements. Therefore, it's essential to adhere to statistical principles and rely on data-driven insights to guide decision-making in A/B testing scenarios.
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