"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"--