分享遇到的两个很好的ab testing的题目和suggested answers！

感觉很经典的两道题目！
1、Testing Price Increase
Let’s say that you work at a B2B SAAS company that’s interested in testing the pricing of different levels of subscriptions.
Your project manager comes to you and asks you to run a two-week-long A/B test to test an increase in pricing.
How would you approach designing this test? How would you determine whether the increase in pricing is a good business decision?
Let’s tackle one overarching question first - should we run an A/B test when testing pricing?

answers：A/B testing pricing generally has more downsides than upsides. One major downside is that if two users go to a pricing page and one of them sees a product for \$50$50/month and the other sees one for \$25$25/month, you’re risking an incentive for your users to opt-out of your A/B test into another bucket, creating real statistical anomalies.
But an even larger issue on A/B testing pricing is on understanding success? If you’re testing a discount rate on a subscription product - you want to know two things:
1.        Does the customer convert at a higher rate for the discount?

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would be a greedy version of running the test given that if the red button won and then the bottom of the page variant won, we wouldn’t have known if the interaction effect of blue + bottom of the page may have changed the outcome.
Let’s make sure to add into the solution to note the general design of the AB test as well to not get caught up in the specifics of the multivariate testing. We need to calculate the sample size we would need by multiplying the number of users per day that would be bucketed in each variant by the number of days that it would take to reach significance. We also need to note that we would randomly bucket each user into each variant in order to not bias the results.


求rice看面积哇，谢谢各位大佬！

补充内容 (2022-11-06 13:04 +8:00):
sorry，面经

谢谢分享，第二题不是应该用 ANOVA 来分析吗？

谢谢分享！

谢谢楼主分享！！

谢谢楼主分享

谢谢分享

感谢分享

xie xie fen xiang

谢谢分享