A Modern Introduction to Probability and Statistics PDF Download

Author: F.M. Dekking
Publisher: Springer Science & Business Media
ISBN: 1846281687
Category : Mathematics
Languages : en
Pages : 488

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Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Author: F.M. Dekking
Publisher: Springer Science & Business Media
ISBN: 1852338962
Category : Mathematics
Languages : en
Pages : 485

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Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Author: F.M. Dekking
Publisher: Springer
ISBN: 9781849969529
Category : Mathematics
Languages : en
Pages : 488

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Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Author: Walter A. Rosenkrantz
Publisher: CRC Press
ISBN: 158488813X
Category : Mathematics
Languages : en
Pages : 680

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Book Description
Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create

Author: John Tabak
Publisher: Infobase Publishing
ISBN: 0816068739
Category : Electronic books
Languages : en
Pages : 241

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Book Description
Presents a survey of the history and evolution of the branch of mathematics that focuses on probability and statistics, including useful applications and notable mathematicians in this area.

Author: David F. Anderson
Publisher: Cambridge University Press
ISBN: 110824498X
Category : Mathematics
Languages : en
Pages : 447

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Book Description
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Author: Geoffrey Grimmett
Publisher: OUP Oxford
ISBN: 0191019933
Category : Mathematics
Languages : en
Pages : 288

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Book Description
Probability is an area of mathematics of tremendous contemporary importance across all aspects of human endeavour. This book is a compact account of the basic features of probability and random processes at the level of first and second year mathematics undergraduates and Masters' students in cognate fields. It is suitable for a first course in probability, plus a follow-up course in random processes including Markov chains. A special feature is the authors' attention to rigorous mathematics: not everything is rigorous, but the need for rigour is explained at difficult junctures. The text is enriched by simple exercises, together with problems (with very brief hints) many of which are taken from final examinations at Cambridge and Oxford. The first eight chapters form a course in basic probability, being an account of events, random variables, and distributions - discrete and continuous random variables are treated separately - together with simple versions of the law of large numbers and the central limit theorem. There is an account of moment generating functions and their applications. The following three chapters are about branching processes, random walks, and continuous-time random processes such as the Poisson process. The final chapter is a fairly extensive account of Markov chains in discrete time. This second edition develops the success of the first edition through an updated presentation, the extensive new chapter on Markov chains, and a number of new sections to ensure comprehensive coverage of the syllabi at major universities.

Author: John E. Freund
Publisher: Courier Corporation
ISBN: 0486158438
Category : Mathematics
Languages : en
Pages : 247

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Book Description
Featured topics include permutations and factorials, probabilities and odds, frequency interpretation, mathematical expectation, decision making, postulates of probability, rule of elimination, much more. Exercises with some solutions. Summary. 1973 edition.

Author: Bert E. Fristedt
Publisher: Springer Science & Business Media
ISBN: 1489928375
Category : Mathematics
Languages : en
Pages : 775

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Book Description
Students and teachers of mathematics and related fields will find this book a comprehensive and modern approach to probability theory, providing the background and techniques to go from the beginning graduate level to the point of specialization in research areas of current interest. The book is designed for a two- or three-semester course, assuming only courses in undergraduate real analysis or rigorous advanced calculus, and some elementary linear algebra. A variety of applications—Bayesian statistics, financial mathematics, information theory, tomography, and signal processing—appear as threads to both enhance the understanding of the relevant mathematics and motivate students whose main interests are outside of pure areas.

Author: Bruce Hansen
Publisher: Princeton University Press
ISBN: 0691236143
Category : Business & Economics
Languages : en
Pages : 417

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Book Description
A comprehensive and up-to-date introduction to the mathematics that all economics students need to know Probability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics. Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics. This incisive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of the mathematics that every economist needs to know. Covers probability and statistics with mathematical rigor while emphasizing intuitive explanations that are accessible to economics students of all backgrounds Discusses random variables, parametric and multivariate distributions, sampling, the law of large numbers, central limit theory, maximum likelihood estimation, numerical optimization, hypothesis testing, and more Features hundreds of exercises that enable students to learn by doing Includes an in-depth appendix summarizing important mathematical results as well as a wealth of real-world examples Can serve as a core textbook for a first-semester PhD course in econometrics and as a companion book to Bruce E. Hansen’s Econometrics Also an invaluable reference for researchers and practitioners