20.10. A/B testing. A/B testing is a user experience research methodology where two variants of a page are shown to users at random. A company wants to evaluate whether users will spend more time, on average, on Page A or Page B using an A/B test. Two user experience designers at the company, Lucie and Müge, are tasked with conducting the analysis of the data collected. They agree on how the null hypothesis should be set: on average, users spend the same amount of time on Page A and Page B. Lucie believes that Page B will provide a better experience for users and hence wants to use a one-tailed test, Müge believes that a two-tailed test would be a better choice. Which designer do you agree with, and why?
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Sonic Selection would like to conduct A/B testing to improve the average revenue per site visitor. In order to reach their target, which is an average increase of $200.00 in revenue per site visitor, a new landing page is designed and then compared to the original website landing page. As the data analyst at Sonic Selection, you have been tasked with conducting an analysis as to whether the new website design achieves an increase in revenue per site visitor. 2.1 State your null and alternative hypotheses for the A/B testing research project, in the spaces provided. Null Hypothesis (H0) Start writing here: There is no increase in the revenue achieves by the original website landing page and the new website design landing page. Alternative hypothesis (HA)
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