Probability and Statistical Inference (Statistics: A Series of Textbooks and Monographs)

ISBN-13: 9780824703790
ISBN-10: 0824703790
Edition: 1
Author: Mukhopadhyay, Nitis
Publication date: 2000
Publisher: CRC Press
Format: Hardcover 665 pages
Category: Statistics
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Book details

ISBN-13: 9780824703790
ISBN-10: 0824703790
Edition: 1
Author: Mukhopadhyay, Nitis
Publication date: 2000
Publisher: CRC Press
Format: Hardcover 665 pages
Category: Statistics

Summary

Acknowledged authors Mukhopadhyay, Nitis wrote Probability and Statistical Inference (Statistics: A Series of Textbooks and Monographs) comprising 665 pages back in 2000. Textbook and eTextbook are published under ISBN 0824703790 and 9780824703790. Since then Probability and Statistical Inference (Statistics: A Series of Textbooks and Monographs) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Priced very competitively compared with other textbooks at this level!
This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts.

Beginning with an introduction to the basic ideas and techniques in probability theory and progressing to more rigorous topics, Probability and Statistical Inference

  • studies the Helmert transformation for normal distributions and the waiting time between failures for exponential distributions
  • develops notions of convergence in probability and distribution
  • spotlights the central limit theorem (CLT) for the sample variance
  • introduces sampling distributions and the Cornish-Fisher expansions
  • concentrates on the fundamentals of sufficiency, information, completeness, and ancillarity
  • explains Basu's Theorem as well as location, scale, and location-scale families of distributions
  • covers moment estimators, maximum likelihood estimators (MLE), Rao-Blackwellization, and the Cramér-Rao inequality
  • discusses uniformly minimum variance unbiased estimators (UMVUE) and Lehmann-Scheffé Theorems
  • focuses on the Neyman-Pearson theory of most powerful (MP) and uniformly most powerful (UMP) tests of hypotheses, as well as confidence intervals
  • includes the likelihood ratio (LR) tests for the mean, variance, and correlation coefficient
  • summarizes Bayesian methods
  • describes the monotone likelihood ratio (MLR) property
  • handles variance stabilizing transformations
  • provides a historical context for statistics and statistical discoveries
  • showcases great statisticians through biographical notes

    Employing over 1400 equations to reinforce its subject matter, Probability and Statistical Inference is a groundbreaking text for first-year graduate and upper-level undergraduate courses in probability and statistical inference who have completed a calculus prerequisite, as well as a supplemental text for classes in Advanced Statistical Inference or Decision Theory.
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