Why: A Guide to Finding and Using Causes

Kleinberg, Samantha

ISBN 10: 1491949643 / ISBN 13: 9781491949641

Published by O'Reilly Media, 2015

About this Item

Book is in good condition. Minimal signs of wear. It May have markings or highlights, but kept to only a few pages. May not come with supplemental materials if applicable. Seller Inventory # LFM.4K0S

Bibliographic Details

Title: Why: A Guide to Finding and Using Causes

Publisher: O'Reilly Media

Publication Date: 2015

Binding: Soft cover

Condition: good

About this title

Synopsis:

Can drinking coffee help people live longer? What makes a stock’s price go up? Why did you get the flu? Causal questions like these arise on a regular basis, but most people likely have not thought deeply about how to answer them.

This book helps you think about causality in a structured way: What is a cause, what are causes good for, and what is compelling evidence of causality? Author Samantha Kleinberg shows you how to develop a set of tools for thinking more critically about causes. You’ll learn how to question claims, identify causes, make decisions based on causal information, and verify causes through further tests.

Whether it’s figuring out what data you need, or understanding that the way you collect and prepare data affects the conclusions you can draw from it, Why will help you sharpen your causal inference skills.

About the Author:

Samantha Kleinberg is an Assistant Professor of Computer Science at Stevens Institute of Technology, where she works on developing methods for understanding how systems work when they can only be observed - and not experimented on. Currently, these methods are being used to understand causes of secondary complications in stroke patients (funded by an NIH/NLM R01 grant) and to predict changes in glucose in people with diabetes. She introduced courses on causal inference and health informatics at Stevens, and enjoys helping students cope with the challenges of real-world data. She received her PhD in computer science and B.A. in computer science and physics all from New York University, and previously held an NSF/CRA Computing Innovation Fellowship at Columbia University.