Essential Mathematics for Political and Social Research / Edition 1

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Overview

More than ever before, modern social scientists require a basic level of mathematical literacy, yet many students receive only limited mathematical training prior to beginning their research careers. This textbook addresses this dilemma by offering a comprehensive, unified introduction to the essential mathematics of social science. Throughout the book the presentation builds from first principles and eschews unnecessary complexity. Most importantly, the discussion is thoroughly and consistently anchored in real social science applications, with more than 80 research-based illustrations woven into the text and featured in end-of-chapter exercises. Students and researchers alike will find this first-of-its-kind volume to be an invaluable resource.
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Editorial Reviews

From the Publisher
"Ultimately, math is a language, and Jeff Gill's new book is a comprehensive guide to its grammar, syntax, and vocabulary. The book covers essential topics for advanced social science research and will be an excellent teaching, reference, and self-study tool." --Scott Desposato, University of California, San Diego

"The body of topics that Gill covers is both appropriate and desirable for any primer in mathematics. The use of substantive examples is really outstanding, and makes this a uniquely attractive commodity for political science faculty who would be teaching a mathematical research/methods class over the course of a semester." --Alan Wiseman, Ohio State University

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Product Details

  • ISBN-13: 9780521684033
  • Publisher: Cambridge University Press
  • Publication date: 4/30/2006
  • Series: Analytical Methods for Social Research Series
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 476
  • Sales rank: 453,762
  • Product dimensions: 5.98 (w) x 8.98 (h) x 1.06 (d)

Meet the Author

Jeff Gill is an associate professor of Political Science at the University of California, Davis. His current research is focused on projects such as Bayesian hierarchical models, MCMC theory, budgetary behavior in the House of Representatives, Congress, generalized linear model theory, and simulation techniques. He recently completed a book entitled Numerical Issues in Statistical Computing for the Social Scientist (with Altman and McDonald).
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Table of Contents

1 The basics 1
2 Analytic geometry 51
3 Linear algebra : vectors, matrices, and operations 82
4 Linear algebra continued : matrix structure 132
5 Elementary scalar calculus 178
6 Additional topics in scalar and vector calculus 235
7 Probability theory 284
8 Random variables 330
9 Markov chains 392
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