Buch, Englisch, 444 Seiten, Format (B × H): 154 mm x 230 mm, Gewicht: 670 g
From Basic Principles to Advanced Models
Buch, Englisch, 444 Seiten, Format (B × H): 154 mm x 230 mm, Gewicht: 670 g
Reihe: Chapman & Hall/CRC Texts in Statistical Science
ISBN: 978-0-367-74912-5
Verlag: Taylor & Francis Ltd
Features:
•Complete introduction to mathematical probability, random variables, and distribution theory.
•Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes.
•Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference.
•Detailed introduction to Bayesian statistics and associated topics.
•Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC).
This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.
Zielgruppe
Undergraduate
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
1. Introduction
2. Probability
3. Random Variables and Univariate Distributions
4. Multivariate Distributions
5. Conditional Distributions
6. Statistical Models
7. Sample Moments and Quantiles
8. Estimation, Testing, and Prediction
9. Likelihood-based Inference
10. Inferential Theory
11. Bayesian Inference
12. Simulation Methods