Library Services | Technical University of Kenya

Your cart is empty.
Normal view MARC view ISBD view

Probability: A Graduate Course [electronic resource] : A Graduate Course / by Allan Gut.

By: Gut, Allan [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Springer Texts in Statistics: 75Publisher: New York, NY : Springer New York : Imprint: Springer, 2013Edition: 2nd ed. 2013.Description: XXV, 600 p. 13 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781461447085.Subject(s): Mathematics | Distribution (Probability theory) | Statistics | Mathematical statistics | Mathematics | Probability Theory and Stochastic Processes | Statistical Theory and Methods | Statistics, generalDDC classification: 519.2 Online resources: Click here to access online
Contents:
Preface to the First Edition -- Preface to the Second Edition -- Outline of Contents -- Notation and Symbols -- Introductory Measure Theory -- Random Variables -- Inequalities -- Characteristic Functions -- Convergence -- The Law of Large Numbers -- The Central Limit Theorem -- The Law of the Iterated Logarithm -- Limited Theorems -- Martingales -- Some Useful Mathematics -- References -- Index.
In: Springer eBooksSummary: Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate companion of statistics. The book starts with the basic tools, and goes on to cover a number of subjects in detail, including chapters on inequalities, characteristic functions and convergence. This is followed by a thorough treatment of the three main subjects in probability theory: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and extensions, the book concludes with an extensive chapter on martingales. The new edition is comprehensively updated, including some new material as well as around a dozen new references.
Tags from this library: No tags from this library for this title. Log in to add tags.
No physical items for this record

Preface to the First Edition -- Preface to the Second Edition -- Outline of Contents -- Notation and Symbols -- Introductory Measure Theory -- Random Variables -- Inequalities -- Characteristic Functions -- Convergence -- The Law of Large Numbers -- The Central Limit Theorem -- The Law of the Iterated Logarithm -- Limited Theorems -- Martingales -- Some Useful Mathematics -- References -- Index.

Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate companion of statistics. The book starts with the basic tools, and goes on to cover a number of subjects in detail, including chapters on inequalities, characteristic functions and convergence. This is followed by a thorough treatment of the three main subjects in probability theory: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and extensions, the book concludes with an extensive chapter on martingales. The new edition is comprehensively updated, including some new material as well as around a dozen new references.

There are no comments for this item.

Log in to your account to post a comment.

2017 | The Technical University of Kenya Library | +254(020) 2219929, 3341639, 3343672 | library@tukenya.ac.ke | Haile Selassie Avenue