Probability and Mathematical Statistics
Theory, Applications, and Practice in R
Seiten
2019
Society for Industrial & Applied Mathematics,U.S. (Verlag)
978-1-61197-577-2 (ISBN)
Society for Industrial & Applied Mathematics,U.S. (Verlag)
978-1-61197-577-2 (ISBN)
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Develops the theory of probability and mathematical statistics with the goal of analysing real-world data. Throughout, 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 statistics.
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.
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.
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.
| Erscheinungsdatum | 01.07.2019 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Gewicht | 1650 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Statistik | |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| ISBN-10 | 1-61197-577-8 / 1611975778 |
| ISBN-13 | 978-1-61197-577-2 / 9781611975772 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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