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  • Sách/Book

  • Data envelopment analysis : a comprehensive text with models, applications, references, and DEA-Solver software

    • Authors: William W. Cooper (2000)

  • Each chapter accompanies its developments with simple numerical examples and discussions of actual applications. Emphasis is placed on the use as well as an understanding of DEA and the topics in this book have been selected and treated accordingly. The objective is to introduce students, researchers, and practitioners in business, economics, engineering, and the sciences to Data Envelopment Analysis.
  • Sách/Book

  • Statistical inference

    • Authors: George Casella (2002)

  • This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts
  • Sách/Book

  • Introduction to Mathematical Statistics and Its Applications

    • Authors: Richard J. Larsen (2013)

  • The authors demonstrate how and when to use statistical methods, while reinforcing the calculus that students have mastered in previous courses. Throughout theFifth Edition, the authors have added and updated examples and case studies, while also refining existing features that show a clear path from theory to practice.
  • Sách/Book

  • SilverComm : marketing practices and messages for the age of aging

    • Authors: Anne M. Cooper (2023)

  • The marketing world has long under-appreciated the buying power held by adults over 65 years of age. In the current age of longevity, it's essential that students engage with strategies that embrace all age groups. This text combines professional interviews, theory-based research, and practical exercises to supplement any strategic comm course
  • Sách/Book

  • Introduction to algorithms

    • Authors: Thomas H. Cormen (2022)

  • Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.
  • Sách/Book

  • Introduction to Mathematical Statistics

    • Authors: Robert Hogg (2020)

  • Substantial changes to the 8th Edition – many based on user feedback – help students appreciate the connection between statistical theory and statistical practice, while other changes enhance the development and discussion of the statistical theory presented
  • Sách/Book

  • Methods In Behavioral Research

    • Authors: Paul C. Cozby (2011)

  • Highlights of the new edition include a broader introduction of different research techniques in Chapter 4, extensive revision of the 'validity of measurements' section, and updated structural equations models.