Theory and Methods of Statistics

Nonfiction, Science & Nature, Mathematics, Statistics
Cover of the book Theory and Methods of Statistics by P.K. Bhattacharya, Prabir Burman, Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: P.K. Bhattacharya, Prabir Burman ISBN: 9780128041239
Publisher: Elsevier Science Publication: June 23, 2016
Imprint: Academic Press Language: English
Author: P.K. Bhattacharya, Prabir Burman
ISBN: 9780128041239
Publisher: Elsevier Science
Publication: June 23, 2016
Imprint: Academic Press
Language: English

Theory and Methods of Statistics covers 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
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Theory and Methods of Statistics covers 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.

More books from Elsevier Science

Cover of the book Thyroid Cancer and Nuclear Accidents by P.K. Bhattacharya, Prabir Burman
Cover of the book Wave Mechanics and Wave Loads on Marine Structures by P.K. Bhattacharya, Prabir Burman
Cover of the book Handbook of Endocrine Investigations in Children by P.K. Bhattacharya, Prabir Burman
Cover of the book Advances in Non-volatile Memory and Storage Technology by P.K. Bhattacharya, Prabir Burman
Cover of the book Developments in Surface Contamination and Cleaning - Vol 5 by P.K. Bhattacharya, Prabir Burman
Cover of the book Individual Case Formulation by P.K. Bhattacharya, Prabir Burman
Cover of the book Handbook of Sputter Deposition Technology by P.K. Bhattacharya, Prabir Burman
Cover of the book Nutritional Management of Renal Disease by P.K. Bhattacharya, Prabir Burman
Cover of the book Separation of Isotopes of Biogenic Elements in Two-phase Systems by P.K. Bhattacharya, Prabir Burman
Cover of the book Sectional Anatomy and Tomography of the Head by P.K. Bhattacharya, Prabir Burman
Cover of the book Signals and Systems using MATLAB by P.K. Bhattacharya, Prabir Burman
Cover of the book Carbon-based Polymer Nanocomposites for Environmental and Energy Applications by P.K. Bhattacharya, Prabir Burman
Cover of the book Advances in Research and Development by P.K. Bhattacharya, Prabir Burman
Cover of the book Osteoarchaeology by P.K. Bhattacharya, Prabir Burman
Cover of the book Deep Learning through Sparse and Low-Rank Modeling by P.K. Bhattacharya, Prabir Burman
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy