Probability and Statistics by Example

Erscheinungsjahr 2008
ISBN: 978-0-521-61234-0
Verlag: Cambridge University Press

Buch, Englisch, 504 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 851 g

Probability and Statistics are as much about intuition and problem solving as they are about theorem proving. Because of this, students can find it very difficult to make a successful transition from lectures to examinations to practice, since the problems involved can vary so much in nature. Since the subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science andengineering, the authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises with complete solutions, adapted to needs and skills of students. Following on from the success of Probability and Statistics by Example: Basic Probability and Statistics, the authors here concentrate on random processes, particularly Markov processes, emphasising modelsrather than general constructions. Basic mathematical facts are supplied as and when they are needed andhistorical information is sprinkled throughout.

Autoren/Hrsg.

Suhov, Yuri

Kelbert, Mark

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizinische Mathematik & Informatik

Inhaltsverzeichnis

Preface; Introduction: Andrei Markov and his time; 1. Discrete-time Markov chains; 2. Continuous-time Markov chains: basic theory; 3. Statistics of discrete-time Markov chains; Afterword: Pearson, Maxwell and other famous Cambridge Wranglers of the past: some lessons to be learned; Bibliography; Appendix; Index.

Über Autor(innen)

Kelbert, Mark
Mark Kelbert is a Reader in Statistics in the Department of Mathematics at the University of Swansea.

Suhov, Yuri
Yuri Suhov is a Professor of Applied Probability in the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge.