Introductory statistical inference mukhopadhyay nitis
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Author by : George G. SapnaOnline offers Free shipment all across India for orders above Rs199 and Global Shipment at the most economical cost. It also features worked examples of statistical principles as well as exercises with hints. In many universities, graduate students from Economics, Actuarial Sciences, Finance, and several other departments do no t have enough time to take a two-semester sequence For them, this book is ideal. The text provides a unique, insightful approach to the subject, describing statistics as the study of random variables rather than the study of data.

Introductory Statistical Inference studies multivariate random variables, exponential families of distributions, and standard probability inequalities. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology. Abstract: Develops the concepts and intricacies of statistical inference. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology. Probability and distributions -- 2. The validity of the approximation to the distribution of the estimator by a resampling technique is also examined visually.

The likelihood function is used for pure likelihood inference throughout the book. Moments and generating functions -- 3. The importance of special features in reliability data is stressed throughout. In many universities, graduate students from Economics, Actuarial Sciences, Finance, and several other departments do no t have enough time to take a two-semester sequenceFor them, this book is ideal. Includes fully updated and revised material from the successful second edition Recent changes in emphasis, principle and methodology are carefully explained and evaluated Discusses all recent major developments Particular attention is given to the nature and importance of basic concepts probability, utility, likelihood etc Includes extensive references and bibliography Written by a well-known and respected author, the essence of this successful book remains unchanged providing the reader with a thorough explanation of the many approaches to inference and decision making.

Probability and distributions -- 2. The author provides a historical context for statistics and statistical discoveries and answers to a majority of the end-of-chapter exercises. Dey, University of Connecticut Book Description Introductory Statistical Inference develops the concepts and intricacies of statistical inference. Beginning with a review of the basic concepts and methods in probability theory, moments, and moment generating functions, the author moves to more intricate topics. The text also provides in-depth coverage of Lehmann-Scheffé theorems, focuses on tests of hypotheses, describes Bayesian methods and the Bayes' estimator, and develops large-sample inference. This book is fundamental reading for graduate-levelstudents in statistics as well as anyone with an interest in thefoundations of statistics and the principles underlying statisticalinference, including students in mathematics and the philosophy ofscience. The author provides a historical context for statistics and statistical discoveries and answers to a majority of the end-of-chapter exercises.

Statistical inference differs from other possible modes of inferences in that it always gives measures of uncertainties of the statements made. Coverage highlights sampling distributions, Basu's theorem, Rao-Blackwellization and the Cramequality. With a review of probability concepts, this book discusses topics such as sufficiency, ancillarity, point estimation, minimum variance estimation, confidence intervals, multiple comparisons, and large-sample inference. M78 2006 Literary form non fiction Nature of contents bibliography Series statement Statistics, textbooks and monographs Series volume v. An appendix contains unique coverage of the interpretation of probability, and coverage of probability and mathematical concepts.

The book concludes with sections on Bayesian computation and inference. Sufficiency, completeness, and ancillarity -- 7. Key features include the following. This gracefully organized text reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, figures, tables, and computer simulations to develop and illustrate concepts. The book begins with fascinating highlights from the history ofstatistical inference. Simple Alternative One-Sided Composite Alternative Simple Null vs.

Drills and boxed summaries emphasize and reinforce important ideas and special techniques. Introductory Statistical Inference studies multivariate random variables, exponential families of distributions, and standard probability inequalities. Designed primarily for a one-semester, first-year graduate course in probability and statistical inference, this text serves readers from varied backgrounds, ranging from engineering, economics, agriculture, and bioscience to finance, financial mathematics, operations and information management, and psychology. Readers gain a deeper understanding of the evolution andunderlying logic of each mode as well as each mode's strengths andweaknesses. Coverage highlights sampling distributions, Basu's theorem, Rao-Blackwellization and the Cramér-Rao inequality. Readers with a background in theoretical statistics willfind the text both accessible and absorbing.

Multivariate random variables -- 4. Statistical inference consists of statements concerning the unknown value s of the interest function s. The text also provides in-depth coverage of Lehmann-Scheffé theorems, focuses on tests of hypotheses, describes Bayesian methods and the Bayes' estimator, and develops large-sample inference. This site is like a library, Use search box in the widget to get ebook that you want. Drills and boxed summaries emphasize and reinforce important ideas and special techniques. The E-mail message field is required.