This book is an introduction to statistical field theory, which is an important subject within theoretical physics and a field that has seen substantial progress in recent years. The book covers fundamental topics in great detail and includes areas like conformal field theory, quantum integrability, S-matrices, braiding groups, Bethe ansatz, renormalization groups, Majorana fer...(展开全部)

This book provides a thorough introduction to the fascinating world of phase transitions as well as many related topics, including random walks, combinatorial problems, quantum field theory and S-matrix. Fundamental concepts of phase transitions, such as order parameters, spontaneous symmetry breaking, scaling transformations, conformal symmetry, and anomalous dimensions, have ...(展开全部)

This text explores two-dimensional lattice models in statistical mechanics and illustrates methods for their solution. Comprehensive but concise, it indicates the routes between equations without superfluous details. Author R. J. Baxter is a fellow of the Royal Society of London and the Australian Academy of Science, as well as Emeritus Professor of the Mathematical Sciences In...(展开全部)

This text explores the solution of two-dimensional lattice models. Topics include basic statistical mechanics, Ising models, the mean field model, the spherical model, ice-type models, corner transfer matrices, hard hexagonal models, and elliptic functions. The author has updated the 1989 version with a new chapter, "Subsequent Developments," for the 2007 edition.

Acclaimed by "American Scientist" as "a classic text on field theoretic methods in statistical physics," this comprehensive introduction to the many-body theory and its ramifications was written by three internationally known Russian physicists. It constitutes an invaluable guide to physicists, mathematicians, and others involved in statistical and solid state physics.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, a...(展开全部)

Perfected over three editions and more than forty years, this field- and classroom-tested reference: * Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. * Treats all the basic and important topics in multivariate statistics. * Adds two new chapters, along with a number of new sections. * Provides the most methodi...(展开全部)

This lively and engaging textbook provides the knowledge required to read empirical papers in the social and health sciences, as well as the techniques needed to build statistical models. The author explains the basic ideas of association and regression, and describes the current models that link these ideas to causality. He focuses on applications of linear models, including g...(展开全部)

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedma...(展开全部)