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  • Sách/Book

  • Fundamentals of linear algebra

    • Authors: James B. Carrell (2005)

  • This textbook is meant to be a mathematically complete and rigorous introduction to abstract linear algebra for undergraduates, possibly even first year students, specializing in mathematics. Linear algebra is one of the most applicable areas of athematics. It is used by the pure mathematician and by the mathematically trained scientists of all disciplines. This book is directed more at the former audience than the latter, but it is hoped that the writing is sufficiently clear with enough detail so that the anyone reading the text can understand it. While the book is written in an informal style and has many elementary examples, the propositions and theorems are generally carefully proved, and the interested student will certainly be able to experience the theorem-proof style of te...
  • Sách/Book

  • Bài tập đại số tuyến tính

    • Authors: Hoàng Xuân Sính (2000)

  • Lý thuyết và những bài tập căn bản phần đại số tuyến tính trong chương trình toán học cao cấp: Định thức, không gian vectơ, ánh xạ tuyến tính
  • Sách/Book

  • Introduction to probability and statistics for engineers and scientist

    • Authors: Sheldon M. Ross (2009)

  • As with the previous editions, Ross' text has remendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications apply probability theory to everyday statistical problems and situations
  • Sách/Book

  • Introduction to Mathematical Statistics

    • Authors: Robert V. Hogg (2006)

  • This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory—including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.
  • Sách/Book

  • All of nonparametric statistics

    • Authors: Larry Wasserman (2006)

  • This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation, nonparametric confidence sets, and wavelets. The book’s dual approach includes a mixture of methodology and theory