Applied probability is a broad research area that is of interest to scientists in diverse disciplines in science and technology, including: anthropology, biology, communication theory, economics, epidemiology, finance, geography, linguistics, medicine, meteorology, operations research, psychology, quality control, sociology, and statistics. Recent Advances in Applied Probability is a collection of survey articles that bring together the work of leading researchers in applied probability to present current research advances in this important area. This volume will be of interest to graduate students and researchers whose research is closely connected to probability modelling and their applications. It is suitable for one semester graduate level research seminar in applied probability.

Probability theory is a branch of statistics, a science that employs mathematical methods of collection, organization, and interpretation of data, with applications in practically all scientific areas. This book provides a comprehensive overview of probability theory. It discusses some fundamental aspects of pure and applied probability theory and explores its use in solving a large array of problems. Topics addressed include complex probability, the stability of algorithms in statistical modeling, the non-homogeneous Hofmann process, and more.

This unique volume presents chapters written on the areas of life-testing and reliability by many well-known researchers who have contributed significantly to these two areas over the years. Chapters cover a wide range of topics such as inference under censoring and truncation, reliability growth models, designs to improve quality, prediction techniques, Bayesian analysis of reliability, multivariate methods, accelerated testing, and more. The book is written in an easy-to-follow style, first presenting the necessary theoretical details and then illustrating the methods with a numerical examples wherever possible. Many tables and graphs that are essential for the use of some of the new methodologies are presented throughout the volume. Numerous examples provide the reader with a clear understanding of the methods presented as well as with insight into the applications of these results.

This is one of two volumes that sets forth invited papers presented at the International Indian Statistical Association Conference. This volume emphasizes advancements in methodology and applications of probability and statistics. The chapters, representing the ideas of vanguard researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing, robust inference, regression and design and sample size methodology. The text also fully describes the applications of these new ideas to industry, ecology, biology, health, economics and management. Researchers and graduate students in mathematical analysis, as well as probability and statistics professionals in industry, will learn much from this volume.