Stochastic Modeling and Mathematical Statistics

A Text for Statisticians and Quantitative Scientists
1. Auflage 2014
ISBN: 978-1-4665-6046-8
Verlag: CRC Press

Buch, Englisch, 622 Seiten, Format (B × H): 187 mm x 260 mm, Gewicht: 1215 g

Reihe: Chapman & Hall/CRC Texts in Statistical Science

Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability

Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is useful for statistics and mathematics majors as well as students in the quantitative sciences. The book’s conversational tone, which provides the mathematical justification behind widely used statistical methods in a reader-friendly manner, and the book’s many examples, tutorials, exercises and problems for solution, together constitute an effective resource that students can read and learn from and instructors can count on as a worthy complement to their lectures.

Using classroom-tested approaches that engage students in active learning, the text offers instructors the flexibility to control the mathematical level of their course. It contains the mathematical detail that is expected in a course for "majors" but is written in a way that emphasizes the intuitive content in statistical theory and the way theoretical results are used in practice. More than 1000 exercises and problems at varying levels of difficulty and with a broad range of topical focus give instructors many options in assigning homework and provide students with many problems on which to practice and from which to learn.

Autoren/Hrsg.

Samaniego, Francisco J

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

The Calculus of Probability. Discrete Probability Models. Continuous Probability Models. Multivariate Models. Limit Theorems and Related Topics. Statistical Estimation: Fixed Sample Size Theory. Statistical Estimation: Asymptotic Theory. Interval Estimation. The Bayesian Approach to Estimation. Hypothesis Testing. Estimation and Testing for Linear Models. Nonparametric Statistical Methods. Tables. Bibliography. Index.

Über Autor(innen)

F. J. Samaniego has served on the faculty of the University of California, Davis, for four decades, teaching upper division courses on probability and mathematical statistics numerous times. In 2002, he received the UCD Academic Senate Distinguished Teaching Award. He was the 2004 recipient of the Davis Prize for Undergraduate Teaching and Scholarly Achievement.