Book DetailAuthor/Editor(s): Shelemyahu Zacks
Publication Date: February 18, 2014
Size: 2.75 MB
Book DescriptionProvides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises
With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory and application and presents numerous problem-solving examples that illustrate the related notations and proven results.
Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features:
- Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving
- More than 430 unique exercises with select solutions
- Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis
Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers.
More importantly, the book is very well written, including everything needed to understand the topic.
--J.M. Wilinsky, Amazon Customer Reviews
I think this book would be very useful for those taking graduate level courses in mathematical statistics but also may be useful for the adventurous undergraduate.
--Patrick Regan, Amazon Customer Reviews
For practitioners , engineers, actuaries, data scientists, etc, this is an excellent book that you'll enjoy.
--William G. Ryan, Amazon Customer Reviews