The Model Thinker

What You Need to Know to Make Data Work for You

By: Scott E. Page

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Hardcover | 8 May 2019 | Edition Number 1

At a Glance

Hardcover
400 Pages

Dimensions(cm)
3.7 x 16.2 x 24.1

Hardcover

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Data, data, data: It's all one ever hears about these days. Science is all about big data. Our bosses call out for analytics, whatever those might be. And everyone wants to predict what will happen next. Can we accurately predict if a company's stock will rise, whether or not a disease will spread, or who will become the next President of the United States? As anyone who has ever opened up a spreadsheet groaning with weeks, months, or years of data knows, numbers aren't enough: we have to know how to make them talk.

Enter Scott Page and The Model Thinker. A leading professor of quantitative social science at the University of Michigan, he has taken his expertise as both a teacher and researcher and distilled it into the one book anyone will need to master data and turn it to professional use. This is no armchair exercise in imagined understanding, like The Signal and the Noise or The Black Swan or a legion of books on networks, the purposes of which are to make us look good in meetings (or in our own minds) than they are to enable us to do something useful. The Model Thinker is the guide to turning data into understanding. Underneath it all is what Page calls the "many-model paradigm", where the key isn't to just find one related set of statistical tools and work with them over and over, but to test our understanding of things by modeling them from several perspectives. The result is both a deep, quantitative acquaintance with tools ranging from Markov chains to game theory to Taleb-style long-tail statistics to network analysis and complexity theory, and a profound trip through the thought-process of a world-class data modeler. All the major tools of modeling--which readers will have heard of in everything from Wired to The Economist to The New York Times--will finally yield their secrets.

As The Theoretical Minimum showed, readers in quantitative fields aren't just looking for entertainment. They want to change their understanding of, and ability to act, in the real world. Businesspeople, students, and scientists alike will find much to learn from The Model Thinker.

Industry Reviews

Choice award for outstanding academic title
"A tremendously significant book embracing a creative, innovative approach for thinking about the complex mechanisms of social and natural phenomena"--S-T. Kim, North Carolina A&T State University, Choice
A hands-on reference for the working data scientist, "The Model Thinker" challenges us to consider that the historical methods we have used for data analysis are no longer adequate given the complexity of today's world....What has given this book a place in my permanent library is its deep dives into dozens of models. Equations and the diagrams are here, but so are applications."--Carol Wells, Inside Big Data: Your Source for Machine Learning
Scott Page's The Model Thinker is a deeper dive into the theory of mental models and the math behind them. Page is a professor at the University of Michigan, and his book explores mental models in a wonderful way.--Tomasz Tunguz
"Page explains the value of applying several models to a single problem, and then provides a conceptual toolkit for doing so. His book is a labor of love."--Art Friedman, co-author of Quantum Mechanics
"The clarity of Scott's thinking has been awing me since our days together as doctoral students at Kellogg. Beautifully written, this book teaches us how to stay logical, coherent and effective at work and at life more broadly--amidst a world awash in ever more data, distraction and complexity."--Sally Blount, former dean of the Kellogg School of Management at Northwestern University
"This book offers a remarkably comprehensive and insightful introduction to mathematical models in the social sciences, written by one who is a master of the field and a brilliant teacher."--Roger Myerson, Winner of the Nobel Memorial Prize in Economic Sciences (2007) and Glen A. Lloyd Distinguished Service Professor of Economics at the University of Chicago
"With the exception of physics, science--and particularly the social sciences--currently resides in a liminal period characterized by hints of universal principles and the tantalizing possibility of robust prediction. In this accessible and pragmatic book, Page persuasively shows us how in these transition periods we can use the wisdom of crowds to improve our decision-making. The twist is that the 'crowd' is not made of individuals but of well-chosen models each of which offers a different window on the world."--Jessica Flack, professor at the Santa Fe Institute and director of the Collective Computation Group
"An original and thought-provoking book, and a challenging one for a one-model thinker like myself. Brace yourself for an entirely new perspective."--Daron Acemoglu, professor of economics at MIT and co-author of Why Nations Fail

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