First edition published 2009. Includes bibliographical references (pages 219-220) and index.
Contents:
Matrices, linear Algebra, and vector Geometry: The basics -- Matrix decompositions and quadratic forms -- An introduction to Calculus -- Elementary Probability Theory -- Common probability distributions -- An introduction to Statistical Theory -- Putting the math to work: Linear Least-squares Regression.
Summary:
"A Mathematical Primer for Social Statistics, Second Edition is organized around bodies of mathematical knowledge central to learning and understanding advanced statistics: the basic "language" of linear algebra; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference. The volume concludes showing the application of mathematical concepts and operations to the familiar case, linear least-squares regression. The Second Edition gives much more attention to visualization. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods. Also included is a companion website with materials that will enable readers to use the R statistical computing environment to reproduce and expand on computations presented in the volume. The book will make an excellent text to accompany a math camp or a course designed to provide foundational mathematics needed to understand advanced statistics. It will also serve as a valuable reference for those who have completed their formal training but are still interested in learning new statistical methods"-- Provided by publisher.
Series:
Quantitative applications in the social sciences ; volume 159
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.