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Regression and Other Stories (Analytical Methods for Social Research) by [Andrew Gelman, Jennifer Hill, Aki Vehtari]

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Regression and Other Stories (Analytical Methods for Social Research) 1st Edition, Kindle Edition

4.6 4.6 out of 5 stars 241 ratings

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Regression and Other Stories, Andrew Gelman, Analytical Methods for Social Research

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'Gelman, Hill and Vehtari provide an introductory regression book that hits an amazing trifecta: it motivates regression using real data examples, provides the necessary (but not superfluous) theory, and gives readers tools to implement these methods in their own work. The scope is ambitious - including introductions to causal inference and measurement - and the result is a book that I not only look forward to teaching from, but also keeping around as a reference for my own work.' Elizabeth Tipton, Northwestern University

'Regression and Other Stories is simply the best introduction to applied statistics out there. Filled with compelling real-world examples, intuitive explanations, and practical advice, the authors offer a delightfully modern perspective on the subject. It’s an essential resource for students and practitioners across the statistical and social sciences.' Sharad Goel, Department of Management Science and Engineering, Stanford University

'With modern software it is very easy to fit complex regression models, and even easier to get their interpretation completely wrong. This wonderful book, summarising the authors' years of experience, stays away from mathematical proofs, and instead focuses on the insights to be gained by careful plotting and modelling of data. In particular the chapters on causal modelling, and the challenges of working with selected samples, provide some desperately needed lessons.' David Spiegelhalter, University of Cambridge

'Gelman and Hill, have done it again, this time with Aki Vehtari. They have written a textbook that should be on every applied quantitative researcher’s bookshelf. Most importantly they explain how to do and interpret regression with real world, complicated examples. Practicing academics in addition to students will benefit from giving this book a close read.' Christopher Winship, Harvard University, Massachusetts

'Comprehensive and charming, this regression manual belongs on every regressor’s shelf.' Joshua Angrist, Massachusetts Institute of Technology
--This text refers to the hardcover edition.

Book Description

A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference. --This text refers to the hardcover edition.

Product details

  • ASIN ‏ : ‎ B08BKXPP5K
  • Publisher ‏ : ‎ Cambridge University Press; 1st edition (July 23 2020)
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 11959 KB
  • Simultaneous device usage ‏ : ‎ Up to 4 simultaneous devices, per publisher limits
  • Text-to-Speech ‏ : ‎ Not enabled
  • Enhanced typesetting ‏ : ‎ Not Enabled
  • X-Ray ‏ : ‎ Not Enabled
  • Word Wise ‏ : ‎ Not Enabled
  • Sticky notes ‏ : ‎ Not Enabled
  • Print length ‏ : ‎ 548 pages
  • Customer Reviews:
    4.6 4.6 out of 5 stars 241 ratings

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Customer reviews

4.6 out of 5 stars
4.6 out of 5
241 global ratings

Top review from Canada

Reviewed in Canada 🇨🇦 on August 15, 2020
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One person found this helpful

Top reviews from other countries

Graham Dean
2.0 out of 5 stars Made up data sets
Reviewed in the United Kingdom 🇬🇧 on June 29, 2021
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Laszlo Molnar
5.0 out of 5 stars Excellent reading
Reviewed in the United Kingdom 🇬🇧 on February 9, 2021
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5.0 out of 5 stars Wonderful book
Reviewed in India 🇮🇳 on July 24, 2020
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5.0 out of 5 stars Wonderful book
Reviewed in India 🇮🇳 on July 24, 2020
This is a wonderful book, one of the best on regression, recommended both for those looking for an introduction and for practitioners. Even those who have the earlier book by Gelman and Hill will find much to delight in. The authors show how you can use graphics with fitted regression models, and use simulation for understanding. The fun chapter titles on page xiii are a good guide. Appendix A tells you how to work with R. Appendix B offers invaluable tips, for example: “Forget about statistical significance”, “Do causal inference in a targeted way.” A website gives you all the data and code by example used in the book.
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3 people found this helpful
Georg Walther
2.0 out of 5 stars Kindle edition is not a great read on mobile devices
Reviewed in Germany 🇩🇪 on July 23, 2020
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2 people found this helpful
5.0 out of 5 stars Ottimo libro per un primo approccio alla regressione bayesiana
Reviewed in Italy 🇮🇹 on August 20, 2020
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