October 2020
Beginner to intermediate
448 pages
15h 6m
English
book
Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights
by Joanne Rodrigues
Content preview from Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights
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15. A/B Testing, Predictive Modeling, and Population Projection in R
In the last chapter, we learned how to set up our R environment and R data objects, and how to sample from distributions. This chapter covers R implementation of A/B testing, predictive modeling, and population projection, as described in Chapters 6–9. By the end of this chapter, you should be able to:
Run an A/B test in R.
Analyze the results of an A/B test in R.
Build simple clustering and predictive models in R.
Cross-validate those models in R.
Project populations from your web product.
Understand and plot the long run dynamics of populations.
In this section, we’ll go through the technical aspects of defining, building, and analyzing an A/B test. First, we’ll build an ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.