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In this book, author Matheus , senior data scientist at , explains the largely untapped potential of causal inference for estimating impacts and effects. Managers, data scientists, and business analysts will learn classical causal inference methods like randomized control trials (A/B tests), linear regression, propensity score, synthetic controls, and difference-in-differences. Each method is accompanied by an application in the industry to serve as a grounding example. While we work to ensure that product information is correct, on occasion manufacturers may alter their ingredient lists. Actual product packaging and materials may contain more and/or different information than that shown on our web site. We recommend that you do not solely rely on the information presented and that you alw.
When you click on links to various merchants on this site and make a purchase, this can result in this site earning a commission. Affiliate programs and affiliations include, but are not limited to, the eBay Partner Network.