 Lots of examples of real life problems
 Problem sets with solution hints

Suitable for a two semester course or selfstudy
Aims and Scope
This textbook, now in its second revised and extended edition, presents the fundamental ideas and results of both probability theory and statistics. It comprises the material of a oneyear course, which is addressed to students of mathematics and to scientists with an interest in the mathematical side of stochastics.
The stochastic concepts, models and methods are motivated by examples and then 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, now in part with solutions, offer applications and supplements to the text.
Supplementary Information
 ix, 407 pages
 Language:
 English
 Type of Publication:
 Textbook
 Keywords:
 Stochastics; Statistics; Probability Theory; Normal Distribution; Regression Analysis, MaximumLikelihood; Law of Large Numbers; Central Limit Theorem; Markov Chains; Confidence Intervals
 Subjects
 Mathematics > Probability Theory and Statistics
 Natural Sciences > Textbooks, Reference Books Natural Sciences
 Social Sciences, Economics > Economics and Social Sciences, General
 Mathematics > Probability Theory and Statistics
 Natural Sciences > Textbooks, Reference Books Natural Sciences
 Social Sciences, Economics > Economics and Social Sciences, General
MARC record
MARC record for eBook"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 onesemester 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 measuretheoretical background but rather applicationoriented 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