THINK BAYES

DOWNEY

Published by Shroff
ISBN 10: 1449370780 / ISBN 13: 9781449370787
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International Edition, Cover & ISBN may be different from US edition, PAPERBACK. Book Condition: New. Brand New,Softcover,No Access code & No context dvd, But Contents are same as US Edition. Printed in English Language, Prompt shipping by USPS/,UPS/,DHL/,FedEx. Exceptional customer Service, Satisfaction Guaranteed. We may ship the books from Asian regions for inventory purpose. "Special Note" We do provide service on APO BOX & PO BOX addresses only in usa. Bookseller Inventory #

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If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you’ll begin to apply these techniques to real-world problems.

Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book’s computational approach helps you get a solid start.

  • Use your existing programming skills to learn and understand Bayesian statistics
  • Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing
  • Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey
  • Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.

Book Description: Bayesian Statistics in Python

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Title: THINK BAYES
Publisher: Shroff
Binding: PaperBack
Book Condition: Brand New
Edition: International Edition.

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Book Description O Reilly Media, Inc, USA, United States, 2015. Paperback. Book Condition: New. Language: English . Brand New Book. If you know how to program with Python and also know a little about probability, you re ready to tackle Bayesian statistics. With this book, you ll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book s computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing Get started with simple examples, using coins, MMs, Dungeons Dragons dice, paintball, and hockey Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome. Bookseller Inventory # AAH9781449370787

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Book Description O Reilly Media, Inc, USA, United States, 2015. Paperback. Book Condition: New. Language: English . Brand New Book. If you know how to program with Python and also know a little about probability, you re ready to tackle Bayesian statistics. With this book, you ll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book s computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing Get started with simple examples, using coins, MMs, Dungeons Dragons dice, paintball, and hockey Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome. Bookseller Inventory # AAH9781449370787

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