Think Bayes: bayesian statistics in python

By:

Downey, Allen B

Publication details: Mumbai: Shroff Publishers & Distributors, 2022.Edition: 2nd edDescription: xiv, 320p.: pbk.: 23 cmISBN:

9789391043445

Subject(s):

DDC classification:

519.542 DOW

Summary: If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than 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 there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey, this book's computational approach helps you get a solid start. Use your programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing Get started with simple examples, using coins, dice, and a bowl of cookies Learn computational methods for solving real-world problems https://www.shroffpublishers.com/books/9789391043445/?srsltid=AfmBOopLL-NvKv0siuheNQeft5CzApi780giwDFErfuXwMPkPwIahMgC&__cf_chl_tk=Tms2QKoxpoZEN.VT_XBN66r_RqmggVaglSY9XYYUdaQ-1736529130-1.0.1.1-KoXB0EidABwQu.Y7Qho3ziK2hy3dT3jgjlYu3kSfWEg

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	IIT Gandhinagar	General	519.542 DOW (Browse shelf(Opens below))	1	Available	034992

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Previous	519.542 CAL Introduction to Bayesian scientific computing: ten lectures on subjective computing	519.542 CAL Bayesian scientific computing	519.542 CHI Everything is predictable: how Bayes' remarkable theorem explains the world	519.542 DOW Think Bayes: bayesian statistics in python	519.542 SIL Signal and the noise: the art and science of prediction	519.542 TOR Comparison of statistical experiments, Vol. 36	519.5420285 KOL Probabilistic graphical models : principles and techniques	Next

Includes Index

If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than 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 there aren't many resources available to help beginners. Based on undergraduate classes taught by author Allen B. Downey, this book's computational approach helps you get a solid start.

Use your programming skills to learn and understand Bayesian statistics
Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing
Get started with simple examples, using coins, dice, and a bowl of cookies
Learn computational methods for solving real-world problems

https://www.shroffpublishers.com/books/9789391043445/?srsltid=AfmBOopLL-NvKv0siuheNQeft5CzApi780giwDFErfuXwMPkPwIahMgC&__cf_chl_tk=Tms2QKoxpoZEN.VT_XBN66r_RqmggVaglSY9XYYUdaQ-1736529130-1.0.1.1-KoXB0EidABwQu.Y7Qho3ziK2hy3dT3jgjlYu3kSfWEg

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