Stochastik
About this book
Due to the extremely positive reception of this textbook, it is now being published in its 5th edition. The book provides an introduction to the key ideas and elements of probability theory and statistics. Stochastic concepts, models, and methods are highlighted through typical application examples, then analyzed theoretically and systematically explored.
- Zahlreiche Beispiele und Anwendungen
- Übungsaufgaben und ausgewählte Lösungsskizzen
- Begleittext für einführende Vorlesungen in Wahrscheinlichkeitstheorie und/oder Statistik
- Auch zum Selbststudium geeignet
Author / Editor information
Hans-Otto Georgii, LMU München.
Reviews
Review for the 3rd edition by Vladimir P. Kurenok (MathSciNet)
"The 3rd edition of the book has been further extended and improved. 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."
Topics
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Frontmatter
i -
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Vorwort
v -
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Inhaltsverzeichnis
vii -
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Zufall und Mathematik
1 - Teil I. Wahrscheinlichkeitstheorie
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Kapitel 1. Mathematische Beschreibung von Zufallssituationen
7 -
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Kapitel 2. Stochastische Standardmodelle
29 -
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Kapitel 3. BedingteWahrscheinlichkeiten und Unabhängigkeit
57 -
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Kapitel 4. Erwartungswert und Varianz
101 -
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Kapitel 5. Gesetz der großen Zahl und zentraler Grenzwertsatz
129 -
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Kapitel 6. Markov-Ketten
167 - Teil II. Statistik
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Kapitel 7. Parameterschätzung
211 -
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Kapitel 8. Konfidenzbereiche
250 -
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Kapitel 9. Rund um die Normalverteilung
271 -
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Kapitel 10. Testen von Hypothesen
286 -
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Kapitel 11. Asymptotische Tests und Rangtests
316 -
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Kapitel 12. Regressions- und Varianzanalyse
353 -
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Lösungsskizzen
385 -
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Verteilungstabellen
416 -
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Literatur
422 -
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Symbolverzeichnis
426 -
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Index
429
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