Essentials of Probability Theory for Statisticians

The book Essentials of Probability Theory for Statisticians does not try to compete with probability textbooks like Billingsley (2012) or Chung (2001), but targets a particular audience: graduate students in statistics who need to quickly learn the essentials of probability theory to make rigorous arguments in statistics. The book does not try to give a full introduction to measure theory but instead focuses on the essentials that are needed by statisticians. . . . I think that this textbook fills an important niche: It provides a concise summary of the essentials of probability theory that are needed by statisticians and at the same time relates these concepts to important applications in statistics. Hence, the reader learns to appreciate the interplay between probability and statistics. The book is well written and uses engaging language and plenty of examples and illustrations. Overall, I enjoyed teaching from this book and plan to use it again for future graduate-level teaching in statistics. --Journal of the American Statistical Association This book has tremendous potential for usage in statistics and biostatistics departments where the Ph.D. students would not necessarily have taken a measure theory course but would need a rigorous treatment of probability for their dissertation research and publications in statistical and biostatistics journals ... The authors are commended for providing this valuable book for students in statistics and biostatistics. The illustrative biostatistics examples (throughout chapter 10 but especially in chapter 11) provide motivating rewards for students. --Robert Taylor, Clemson University .. . a very good textbook choice for our courses on advanced probability theory (I, II) at the graduate level. --Jie Yang, University of Illinois at Chicago Many successful graduate students in statistics lack the mathematical prerequisites necessary for Billingsley's book and find such a course too hard ... The strong points of this book are a good selection of topics, good choices for proofs to include and omit, and interesting examples. Some of the examples motivate the need for mathematical theory while others illustrate the relation of the theory to statistical practice. When there is a need for it, the presentation of the material includes side explanations that should help a student with a less solid math background. --Wlodek Byrc, University of Cincinnati I think the authors have done a great job at writing this book. The material is presented carefully and the examples and exercises are appropriate and extremely helpful ... The strongest point of this book is the large collection of statistical applications presented along with each topic. These examples are used to motivate the need for fundamental probabilistic results. The authors have also included a great set of exercises at the end of each section. Another good idea is the summary presented at the end of each chapter. ... I would be happy to adopt this book as a required text for the course that I teach; its content is appropriate and at the right level. --Radu Herbei, Ohio State University . . . I would say Proschan and Shaw have written a useful textbook for introductory graduate or advanced undergraduate use, and one that should help statisticians see why probability is useful. --Thomas Lumley, University of Auckland