All of Statistics: A Concise Course in Statistical Inference

All of Statistics: A Concise Course in Statistical Inference

Larry Wasserman / Jul 19, 2019

All of Statistics A Concise Course in Statistical Inference Taken literally the title All of Statistics is an exaggeration But in spirit the title is apt as the book does cover a much broader range of topics than a typical introductory book on mathematical

  • Title: All of Statistics: A Concise Course in Statistical Inference
  • Author: Larry Wasserman
  • ISBN: 9780387402727
  • Page: 307
  • Format: Hardcover
  • Taken literally, the title All of Statistics is an exaggeration But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics This book is for people who want to learn probability and statistics quickly It is suitable for graduate or advanced undergraduate students in computer scienceTaken literally, the title All of Statistics is an exaggeration But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics This book is for people who want to learn probability and statistics quickly It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas sification, topics that are usually relegated to follow up courses The reader is presumed to know calculus and a little linear algebra No previous knowledge of probability and statistics is required Statistics, data mining, and machine learning are all concerned with collecting and analyzing data For some time, statistics research was con ducted in statistics departments while data mining and machine learning re search was conducted in computer science departments Statisticians thought that computer scientists were reinventing the wheel Computer scientists thought that statistical theory didn t apply to their problems Things are changing Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology Clever data mining algo rithms are scalable than statisticians ever thought possible Formal sta tistical theory is pervasive than computer scientists had realized.

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    • ☆ All of Statistics: A Concise Course in Statistical Inference || ✓ PDF Read by à Larry Wasserman
      307 Larry Wasserman
    • thumbnail Title: ☆ All of Statistics: A Concise Course in Statistical Inference || ✓ PDF Read by à Larry Wasserman
      Posted by:Larry Wasserman
      Published :2018-010-04T11:53:48+00:00

    About "Larry Wasserman"

      • Larry Wasserman

        Larry Wasserman Is a well-known author, some of his books are a fascination for readers like in the All of Statistics: A Concise Course in Statistical Inference book, this is one of the most wanted Larry Wasserman author readers around the world.


    843 Comments

    1. Very good reference on notions on probability, statistics and machine learning. Not ideal to learn the matter from scratch, but ideal to refresh and supplement your knowledge when you do a PhD.


    2. 10/15/2015: So far, this is a really good book with comprehensive material, simple examples, rich problems, and most importantly easy to understand.12/8/2015: I like everything about this book, except the title. It may receive some complaints about not discussing in depth some topics, but one can always go look up and read more on their topics of interest. Nonetheless, this is a very well written book!


    3. The author states that he wrote the book to help get engineering students up to speed. The topics and depth are in line with what one would expect from a mathematical statistics book. It's a good book for finding out what is out there, but most discussions are too brief for most people to learn the material from this book.


    4. The material covered in this book is not covered in sufficient depth to understand it unless you have covered once already. That said this book is a great reference: collections of useful theorems and properties.






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