Theory And Methods Of Statistics by P.K. BhattacharyaTheory And Methods Of Statistics by P.K. Bhattacharya

Theory And Methods Of Statistics

byP.K. Bhattacharya, Prabir BurmanEditorP.K. Bhattacharya

Paperback | May 27, 2016

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Theory and Methods of Statisticscovers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures.

  • Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource
  • Serves as an excellent text for select master's and PhD programs, as well as a professional reference
  • Integrates numerous examples to illustrate advanced concepts
  • Includes many probability inequalities useful for investigating convergence of statistical procedures
P.K. Bhattacharya has more than 30 years of experience teaching a broad spectrum of undergraduate and graduate courses in Statistics at Indian Statistical Institute, the University of Arizona, the University of California, Davis, and as a visiting professor at the University of Minnesota and MIT. He has supervised PhD students and has ...
Title:Theory And Methods Of StatisticsFormat:PaperbackDimensions:544 pages, 8.75 × 6.35 × 0.68 inPublished:May 27, 2016Publisher:Academic PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0128024402

ISBN - 13:9780128024409

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Table of Contents

Chapter 1: Probability Theory
Chapter 2: Some Common Probability Distributions
Chapter 3: Infinite Sequence of Random Variables and Their Convergence Properties
Chapter 4: Basic Concepts of Statistical Inference and a Decision Theoretic Approach
Chapter 5: Point Estimation in Parametric Models
Chapter 6: Hypotheses Testing in Parametric Models
Chapter 7: Asymptotic Properties of Likelihood Based Methods
Chapter 8: Ranks, Empirical Distribution Functions and Quantiles
Chapter 9: Nonparametric Curve Estimation
Chapter 10: Statistical Functionals
Chapter 11: Inference in Linear Models
Chapter 12: Multivariate Analysis
Chapter 13: Resampling: Jackknife and Bootstrap
Chapter 14: Time Series
Appendix A: Some Results from Advanced Calculus
Appendix B: Some Inequalities
Appendix C: Stieltjes Integration
Appendix D: Convergence in Law
Appendix E: Contiguity
Appendix F: Weak Convergence