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Quantitative Social Science:
An Introduction
Kosuke Imai

Book Description | Table of Contents
Chapter 1 [in PDF format] | Chapter 2 [PDF only]


"Kosuke Imai's book takes a very novel and interesting approach to a first quantitative methods course for the social sciences. Focusing on interesting questions from the beginning, he starts by introducing the potential outcome approach to causality, and proceeds to present the reader with a wide range of methods for an admirably broad range of settings, including textual, network, and spatial data. Integrated with the methodological discussions are examples with detailed R code. Readers who work through this book will be well equipped to use modern methods for data analysis in the social sciences. I highly recommend this book!"--Guido W. Imbens, coauthor of Causal Inference for Statistics, Social, and Biomedical Sciences

"This important new book seeks to democratize quantitative social science. In it, one of the world's foremost political methodologists shows how you can join the movement that has changed so much of the academic, commercial, government, and nonprofit worlds. It provides a seamless path from ignorance to insight in a few hundred clear and enlightening pages."--Gary King, Harvard University

"Imai's new textbook has the potential to totally transform how undergraduate statistics is taught. The focus is on data analysis first and statistics second. It is full of great and relevant empirical examples. Students will engage this book rather than dread it."--Christopher Winship, Harvard University

"This is the ideal book for a first class on data analysis. Not only does it provide students with a clear, accessible, and technically correct introduction to research design, computing with data, and statistical inference, but it does what truly great introductions to a topic all do--it generates excitement."--Kevin M. Quinn, University of California, Berkeley

"Finally, a statistics text has caught up with rapid developments in the social sciences in the last two decades, spanning everything from the rediscovery of design, randomization, and causality to Bayesian approaches. From the organization of the subject matter (e.g., causality, measurement, uncertainty) to the mode of presentation, Imai has produced a work that is both comprehensive and accessible, but reflects the vast breadth of topics and approaches today's social scientists are expected to know. The examples are extremely well chosen, a delight to read, and accompanied by R code. Social science finally has an introductory book that presents statistics as it is practiced at the research frontier today, not thirty years ago."--Simon Jackman, United States Studies Centre, University of Sydney

"Imai's new book on quantitative social science represents a groundbreaking and effective method for teaching statistics and quantitative methods to students in any number of fields--ranging from public health and medicine to education and political science. The motivating examples, clear and engaging exposition, and easy implementation for students will make it a resource they (and their instructors) turn to again and again."--Elizabeth Stuart, Johns Hopkins Bloomberg School of Public Health

"Imai's fantastic textbook provides a succinct but thorough introduction to quantitative methods and how they are applied to social science problems. The text is easy to read while also providing material that is generally pitched at a level appropriate for newcomers to the subject."--Justin Grimmer, Stanford University

"Imai's text is engaging and full of examples. It will be widely taught and will have a wide impact. Anyone who really masters the skills and concepts presented here will know statistics better than many professional political scientists."--Andrew Eggers, University of Oxford

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File created: 9/19/2017

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