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Statistical Modeling and Inference for Social Science [Paperback]

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  • Category: Books (Political Science)
  • Author:  Gailmard, Sean
  • Author:  Gailmard, Sean
  • ISBN-10:  1316622223
  • ISBN-10:  1316622223
  • ISBN-13:  9781316622223
  • ISBN-13:  9781316622223
  • Publisher:  Cambridge University Press
  • Publisher:  Cambridge University Press
  • Pages:  391
  • Pages:  391
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-May-2017
  • Pub Date:  01-May-2017
  • SKU:  1316622223-11-MPOD
  • SKU:  1316622223-11-MPOD
  • Item ID: 100262026
  • Seller: ShopSpell
  • Ships in: 2 business days
  • Transit time: Up to 5 business days
  • Delivery by: Jul 02 to Jul 04
  • Notes: Brand New Book. Order Now.
This textbook is an introduction to probability theory, statistical inference and statistical modeling for graduate students and practitioners beginning social science research.This book provides an introduction to probability theory, statistical inference, and statistical modeling for social science researchers and Ph.D. students. Focusing on the connection between statistical procedures and social science theory, Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables  the primary aim of social scientists.This book provides an introduction to probability theory, statistical inference, and statistical modeling for social science researchers and Ph.D. students. Focusing on the connection between statistical procedures and social science theory, Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables  the primary aim of social scientists.This book provides an introduction to probability theory, statistical inference, and statistical modeling for social science researchers and Ph.D. students. Focusing on the connection between statistical procedures and social science theory, Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables  the primary aim of social scientists. Gailmard explains how social scientists express and test substantive theoretical arguments in various models. Chapter exercises require application of concepts to actual data and extend students' grasp of core theoretical concepts. Students will complete the book with the ability to read and critique statistical applications in their fields of interest.1. Introduction; 2. Descriptive statistics: data and information; 3. Observable data and data-generating processes; 4. Probability theory: basic properties of data-generating processes; 5. Expectation and moments: summaries of data-generating processes; 6. Probability and lSH
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