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Case: Suppose there was an A/B test where the goal is to increase customer time spent on a website, and the goal is to test whether a new font helps. You randomly assign the next 200 visitors to your site to the two different options.
Question 1: Describe how you can use a regression model to determine whether the font has a significant effect on time spent on the website. Be sure to describe what your "x" and "y" variables are here and what p-value you would look at to do the test.
Question 2: You know that the age of a customer is highly related to the amount of time spent on the website (young customers spend a lot of time on there!). Thus you are worried that if by chance a lot of young people were randomly assigned to the new font, then perhaps you could be fooled into thinking the effect you were seeing in part (a) was due to the difference in font when in fact it was just due to one font happening to get more of the young people than the other. Describe how you can use a regression model to conduct the A/B test while accounting for this problem with age. You do have access to the age of your customers. As in the previous part, describe what your "x" and "y" are and what p-value you would look at to do the A/B test to determine whether the new font leads to more time on the site
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