Why

Praise for Samantha Kleinberg’s Why

While cutting-edge computing tools make it easy to find patterns in data, the best insights come from understanding where those patterns come from, and this problem can’t be solved by computers alone. Kleinberg expertly guides readers on a tour of the key concepts and methods for identifying causal relationships, with a clear and practical approach that makes Why unlike any other book on the subject. Accessible yet comprehensive, Why is essential reading for scientific novices, seasoned experts, and anyone else looking to learn more from data.

Andrew Therriault, PhD, Director of Data Science, Democratic National Committee

Philosophy, economics, statistics, and logic all try to make sense of causality; Kleinberg manages to tie together these disparate approaches in a way that’s straightforward and practical. As more of our lives become “data driven,” clear thinking about inferring causality from observations will be needed for understanding policy, health, and the world around us.

Chris Wiggins, PhD, Chief Data Scientist at the New York Times and Associate Professor at Columbia University

While causality is a central feature of our lives, there is widespread debate and misunderstanding about it. Why lucidly explains causality without relying on prior knowledge or technical expertise. It is an accessible and enjoyable read, yet it gives logical rigor and depth of analysis to complex concepts.

David Lagnado, PhD,Senior Lecturer, University ...