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Probability and Mathematical Statistics: Theory, Applications, and Practice in R

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by Mary C. Meyer


2019 / xii + 707 pages / Hardcover / 978-1-611975-77-2 / List Price $109.00 / SIAM Member Price $76.30 / Order Code: OT162

Keywords: likelihood-based inference, hypothesis testing, point estimation, interval estimation, probability distributions

This book develops the theory of probability and mathematical statistics with the goal of analyzing real-world data. Throughout the text, the R package is used to compute probabilities, check analytically computed answers, simulate probability distributions, illustrate answers with appropriate graphics, and help students develop intuition surrounding probability and statistics. Examples, demonstrations, and exercises in the R programming language serve to reinforce ideas and facilitate understanding and confidence. 

The book’s Chapter Highlights provide a summary of key concepts, while the examples utilizing R within the chapters are instructive and practical. Exercises that focus on real-world applications without sacrificing mathematical rigor are included, along with more than 200 figures that help clarify both concepts and applications. In addition, the book features two helpful appendices: annotated solutions to 700 exercises and a Review of Useful Math

Written for use in applied masters classes, Probability and Mathematical Statistics: Theory, Applications, and Practice in R is also suitable for advanced undergraduates and for self-study by applied mathematicians and statisticians and qualitatively inclined engineers and scientists

About the Author
Mary C. Meyer
is a statistics professor at Colorado State University, where her main area of research is estimation and inference in statistical models with inequality constraints. This includes nonparametric function estimation using constrained regression splines, density and hazard function estimation with shape constraints, and models with order restrictions.


ISBN 9781611975772

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