Think Bayes: (Record no. 98141)

MARC details
000 -LEADER
fixed length control field 01745cam a22002537i 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160709s2013 caua 001 0 eng d
015 ## - NATIONAL BIBLIOGRAPHY NUMBER
National bibliography number GBB397007
Source bnb
016 7# - NATIONAL BIBLIOGRAPHIC AGENCY CONTROL NUMBER
Record control number 016525585
Source Uk
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781449370787
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1449370780
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789391043445
042 ## - AUTHENTICATION CODE
Authentication code lccopycat
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.74015
Cutter DOW
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Downey, Allen,
245 10 - TITLE STATEMENT
Title Think Bayes:
Remainder of title Bayesian Statistics in Python
250 ## - EDITION STATEMENT
Edition statement Second edition.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Mumbai
Name of publisher, distributor, etc Shroff Publishers & Distributors Pvt. Ltd.
Date of publication, distribution, etc 2021
300 ## - PHYSICAL DESCRIPTION
Extent xv, 190 pages :
520 ## - Remark
Summary, etc 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.<br/><br/>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.<br/><br/>Use your programming skills to learn and understand Bayesian statistics<br/>Work with problems involving estimation, prediction, decision analysis, evidence, and Bayesian hypothesis testing<br/>Get started with simple examples, using coins, dice, and a bowl of cookies<br/>Learn computational methods for solving real-world problems
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Bayesian statistical decision theory
General subdivision Data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python (Computer program language)
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a Business Analytics
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Programme Full call number Barcode Date last seen Cost, replacement price Koha item type
    Dewey Decimal Classification     Main Library Main Library Analytics 29/11/2023 6038 960.00   005.74015 DOW 119088 29/11/2023 1200.00 Book

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