A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

Eric Newborn is used to dealing with people whose lives are in crisis. When his wife dies, he finds that grief renders him helpless. He retreats, with his female dog, Ralph, to his isolated home on Martha's Vineyard. Five years later, on a wild, storm-wracked night, a car crashes at the end of Eric's lane and a woman turns up at his door, seeking help. Sam is a fan who has tracked him down, convinced that Eric will sort out the co-incidences that have both destroyed and coloured her life. As Eric and Sam spin around one another like constellations in a greater universe, they set out to search for answers to their questions, and to find some meaning in the signs that we all see.

The inspirational bestseller that ignited a movement and asked us to find our WHY Discover the book that is captivating millions on TikTok and that served as the basis for one of the most popular TED Talks of all time—with more than 56 million views and counting. Over a decade ago, Simon Sinek started a movement that inspired millions to demand purpose at work, to ask what was the WHY of their organization. Since then, millions have been touched by the power of his ideas, and these ideas remain as relevant and timely as ever. START WITH WHY asks (and answers) the questions: why are some people and organizations more innovative, more influential, and more profitable than others? Why do some command greater loyalty from customers and employees alike? Even among the successful, why are so few able to repeat their success over and over? People like Martin Luther King Jr., Steve Jobs, and the Wright Brothers had little in common, but they all started with WHY. They realized that people won't truly buy into a product, service, movement, or idea until they understand the WHY behind it. START WITH WHY shows that the leaders who have had the greatest influence in the world all think, act and communicate the same way—and it's the opposite of what everyone else does. Sinek calls this powerful idea The Golden Circle, and it provides a framework upon which organizations can be built, movements can be led, and people can be inspired. And it all starts with WHY.

Why do Jews eat gefilte fish? Why is a glass broken at the end of a Jewish wedding ceremony? Why must the chapter of curses in the Torah be read quickly in a low voice? Why are shrimp and lobster not kosher? Why do Jews fast on Yom Kippur? Why are some Matzot square while others are round? If you've ever asked or been asked any of these questions, The Jewish Book of Why has all the answers. In this complete, concise, fascinating, and thoroughly informative guide to Jewish life and tradition, Rabbi Alfred J. Kolatch clearly explains both the significance and the origin of nearly every symbol, custom, and practice known to Jewish culture-from Afikomon to Yarmulkes, and from Passover to Purim. Kolatch also dispels many of the prevalent misconceptions and misunderstandings that surround Jewish observance and provides a full and unfettered look at the biblical, historical, and sometimes superstitious reasons and rituals that helped develop Jewish law and custom and make Judaism not just a religion, but a way of life. L'chaim!

"An illustrated, popular science reader for any age."--

EVER WONDERED WHY PEOPLE REALLY DO WHAT THEY DO? (AND WHAT WE COULD ACCOMPLISH IF WE ONLY KNEW?) We need a clear-eyed look at what’s happening in society right now. Social systems are being undermined, or failing, before our eyes. The trust that we once had in organizations, corporations, journalism, education, science, medicine, government—and even one another—is compromised. People are feeling isolated and alone. How do we move forward as a society? How can we connect with and understand one another? How do we find productive ways to communicate, meeting those we are trying to reach where they are and speaking to what’s important to them? And how do we have robust and productive dialogue that (re)builds meaningful, supportive, and resilient relationships and institutions? Bob Raleigh suggests that any approach must start by understanding the why. The Search for Why compellingly demonstrates that we need a better model and follows Raleigh on his career journey to find one. In this book, Raleigh draws on his decades of experience in market research and public-communication strategy, the possibilities of our contemporary era of big data, and groundbreaking research from psychology, cognitive and behavioral sciences, anthropology, sociology, and philosophy, all of which have informed the Model of Why approach that he proposes. For anyone looking to persuade people, heal divisions, or build better relationships, The Search for Why is a crucial step in the right direction.

CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.