Stochastics
De Gruyter (Verlag)
978-3-11-029254-1 (ISBN)
- Lots of examples and applications
- Problem sets and selected solutions
- Suitable for a two semester course or self-study
This second revised and extended edition presents the fundamental ideas and results of both, probability theory and statistics, and comprises the material of a one-year course.
It is addressed to students with an interest in the mathematical side of stochastics. Stochastic concepts, models and methods are motivated by examples and developed and analysed systematically. Some measure theory is included, but this is done at an elementary level that is in accordance with the introductory character of the book.
A large number of problems offer applications and supplements to the text.
Prof. Dr. Hans-Otto Georgii, ist Emeritus des Mathematischen Instituts der Ludwig-Maximilians-Universität München.
»The textbook is based on a series of lectures taught by the author for many years at the Mathematical Institute of the University of Munich. The material of the book covers two one-semester courses in probability and mathematical statistics, respectively. All chapters are equipped with exercises of varying degrees of difficulty that help to clarify the concepts.The first part of the book is an introduction to probability theory. The material is presented using little of the measure-theoretical background but rather application-oriented examples that preserve its introductory character. Topics range from classical probability distributions to conditional distributions and limit theorems. A short introduction to Markov chains is also given.The second part of the book gives an introduction to mathematical statistics and describes main statistical procedures: parameter and interval estimation, hypothesis testing, linear regression and basics of the analysis of variance approach.The book can be used by undergraduate mathematics majors but also by science and engineering students who wish not only to apply probability and statistics but also to understand how the methods work.« Vladimir P. Kurenok, MathSciNet
| Erscheint lt. Verlag | 15.11.2012 |
|---|---|
| Reihe/Serie | De Gruyter Textbook |
| Zusatzinfo | 77 schw.-w. Abb., 22 schw.-w. Tab. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 170 x 240 mm |
| Gewicht | 716 g |
| Einbandart | Paperback |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik |
| Sozialwissenschaften ► Pädagogik | |
| Schlagworte | central limit theorem • confidence intervals • law of large numbers • markov chains • Maximum-Likelihood • Normal distribution • Probability Theory • Regression Analysis • Regression Analysis, Maximum-Likelihood • Statistics • Statistik; Handbuch/Lehrbuch • Statistik; Handbuch/Lehrbuch 116194 • stochastic • stochastics • Stochastics; Statistics; Probability Theory; Normal Distribution; Regression Analysis, Maximum-Likelihood; Law of Large Numbers; Central Limit Theorem; Markov Chains; Confidence Intervals • Stochastik; Handbuch/Lehrbuch • Wahrscheinlichkeitsrechnung; Handbuch/Lehrbuch |
| ISBN-10 | 3-11-029254-8 / 3110292548 |
| ISBN-13 | 978-3-11-029254-1 / 9783110292541 |
| Zustand | Neuware |
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