Автор: Florent Buisson
Издательство: O’Reilly Media, Inc.
Год: 2021-01-21
Страниц: 252
Язык: английский
Формат: epub, rtf
Размер: 10.1 MB
Most of the data that companies collect is related to customer behaviors, such as clicks on a website or purchases in a supermarket. But data science algorithms and predictive analytics tools aren't that specific, so customer data is treated the same way as, for example, astronomical or genomic data. This practical guide introduces powerful methods for behavioral data analysis that you're probably not aware of.
Advanced experimental design will help you get the most out of your A/B tests, while causal diagrams will allow you to tease out causality from correlation even when you can't run experiments. Written in an accessible style for data scientists, business analysts, and behavioral scientists, this practical book provides complete examples and exercises in R and Python to help you gain more insight from your immediately.
In the 1 chapter, I’ll walk you through a simple example of a linear regression gone awry because of a hidden joint cause. Such variables, which we’ll call "confounders" are the main obstacle to measuring what drives behavior. I’ll then introduce a new tool, causal diagrams, which allow us to identify and cancel confounders and that we’ll use again and again in the rest of the book.
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