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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16. Regression Discontinuity, Matching, and Uplift in R
Chapter 15 covered A/B testing and predictive modeling. This chapter covers R implementation for the last subsection of the book on causal inference methods—that is, the implementation in R of difference-in-difference (DID) modeling, regression discontinuity (RD), statistical matching, and uplift modeling, discussed in Chapters 10–13. We’ll work with the Lalonde data set, which contains data from an experimental jobs program described in Chapter 13, for statistical matching and uplift modeling.
By the end of the chapter, you will be able to:
Estimate a difference-in-difference model.
Remove the effects of seasonality.
Calculate the effect size in a regression discontinuity or interrupted ...
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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.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.