Why
A Guide to Finding and Using Causes
Nonfiction, Computers, Advanced Computing, Programming, Logic Design, Computer Science, Science & Nature, Mathematics, Statistics
| Author: | Samantha Kleinberg | ISBN: | 9781491949627 |
| Publisher: | O'Reilly Media | Publication: | November 16, 2015 |
| Imprint: | O'Reilly Media | Language: | English |
| Author: | Samantha Kleinberg |
| ISBN: | 9781491949627 |
| Publisher: | O'Reilly Media |
| Publication: | November 16, 2015 |
| Imprint: | O'Reilly Media |
| Language: | English |
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.
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.
