Causal Inference in Python
-
- Taschenbuch
- eBook ausgewählt
-
Form:Einzelkauf Download
-
Sprache:Englisch
-
eBook Format:ePUB
- PDF Fr. 65.90
- ePUB Fr. 65.90 ausgewählt
Fr. 65.90
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Ja
Family Sharing
Ja
Text-to-Speech
Ja
Erscheinungsdatum
14.07.2023
Verlag
O'Reilly MediaSeitenzahl
408 (Printausgabe)
Dateigröße
9670 KB
Sprache
Englisch
EAN
9781098140212
How many buyers will an additional dollar of online marketing bring in? Which customers will only buy when given a discount coupon? How do you establish an optimal pricing strategy? The best way to determine how the levers at our disposal affect the business metrics we want to drive is through causal inference.
In this book, author Matheus Facure, senior data scientist at Nubank, 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.
With this book, you will:
- Learn how to use basic concepts of causal inference
- Frame a business problem as a causal inference problem
- Understand how bias gets in the way of causal inference
- Learn how causal effects can differ from person to person
- Use repeated observations of the same customers across time to adjust for biases
- Understand how causal effects differ across geographic locations
- Examine noncompliance bias and effect dilution
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.