Introduction to probability and mathematical statistics ebook

The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics. It also emphasizes the important ideas in statistical modeling, such as sufficiency, exponential family distributions, and large sample properties. Mathematical Statistics: An Introduction to Likelihood Based Inference makes advanced topics accessible and understandable and covers many topics in more depth than typical mathematical statistics textbooks.

It includes numerous examples, case studies, a large number of exercises ranging from drill and skill to extremely difficult problems, and many of the important theorems of mathematical statistics along with their proofs. In addition to the connected chapters mentioned above, Mathematical Statistics covers likelihood-based estimation, with emphasis on multidimensional parameter spaces and range dependent support.

It also includes a chapter on confidence intervals, which contains examples of exact confidence intervals along with the standard large sample confidence intervals based on the MLE's and bootstrap confidence intervals. All Rights Reserved. This book is intended primarily for undergraduate statistics students. Preface Introduction Part I. Probability Theory Chapter 1. The Probability Space 1. Elementary Properties of Probability Spaces 2. Random Variables and Their Probability Distributions 3.

Typical Values 4. Limit Theorems 5. Some Important Distributions 6. Bain and Max Engelhardt focus on the mathematical development of the subject, with examples and exercises oriented toward applications.

An Introduction to Probability and Statistics. Authors: Vijay K. Rohatgi, A. Ehsanes Saleh. A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics.