Gine E., Grimmett G.R., Saloff-Coste L. Lectures on Probability Theory and Statistics

3rd Edition. Wiley series in probability and mathematical statistics. John Wiley & Sons, Inc., 2003, - 721 pages. This book has been designed primarily as a text for a two-semester course in multivariate statistics. The book will also serve as an introduction to many topics in this area to statisticians who are not students and will be used as a reference by other statisticians. For several years the book in the form of dittoed notes has bee...

Springer, 2009. - 237 pages. This volume contains lectures given at the Saint-Flour Summer School of Probability Theory during the period 10th 26th July, 1995. These lectures are at a postgraduate research level. They are works of reference in their domain.

Wiley series in probability and statistics. Wiley & Sons, Ltd, 2000. - 611 pages. This volume, first published in hardback in 1994, presents an overview of the foundations and key theoretical concepts of Bayesian Statistics. The world of Bayesian Statistics has been changing shape and growing in size rapidly and unpredictably - most notably in relation to developments in computational methods and the subsequent opening up of new application h...

Thompson, 2006. - 848 pages. Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without emphasizing contemporary statistical practice. "Modern Mathematical Statistics with Applications" strikes a balance between mathematical foundations and statistical practice. Accomplished authors Jay Devore and Ken Berk first engage students with real-life problems and scenarios an...

John Wiley & Sons, 1963. - 695 pages. Probability theory can be understood as a mathematical model for the intuitive notion of uncertainty. Without probability theory all the stochastic models in Physics, Biology, and Economics would either not have been developed or would not be rigorous. Also, probability is used in many branches of pure mathematics, even in branches one does not expect this, like in convex geometry.

This classic book is intended to be the first introduction to probability and statistics written with an emphasis on the analytic approach to the problems discussed. Topics include the axiomatic setup of probability theory, polynomial distribution, finite Markov chains, distribution functions and convolution, the laws of large numbers (weak and strong), characteristic functions, the central limit theorem, infinitely divisible distributions, and M...

McGraw-Hill, 1998, 376 pages. The purpose of this book is to present a modern introduction to probability and statistics using background of calculus. For convenience the book is divided into two parts. The first deals with probability (and by itself can be used to provide an introduction to the subject), while the second deals with statistics. The book is designed to be used either as a textbook for formal course in probability and statistics or...

Duxbury Press, 1995. - 838 pages. This author's modern approach is intended primarily for honors undergraduates or undergraduates with a good math background taking a mathematical statistics or statistical inference course. The author takes a finite-dimensional functional modeling viewpoint (in contrast to the conventional parametric approach) to strengthen the connection between statistical theory and statistical methodology. The writing of...

Cambridge University Press, 2008. - 504 Pages. Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative manage...

Springer, 2008. - 315 pages. This volume contains lectures given at the 31st Probability Summer School in Saint-Flour (July 8-25, 2001). Simon Tavar?’s lectures serve as an introduction to the coalescent, and to inference for ancestral processes in population genetics. The stochastic computation methods described include rejection methods, importance sampling, Markov chain Monte Carlo, and approximate Bayesian methods. Ofer Zeitouni’s course on...