Think Bayes: Bayesian Statistics in Python 2nd
暫譯: 思考貝葉斯：Python中的貝葉斯統計（第二版）
Downey, Allen B.
- 出版商: O'Reilly
- 出版日期: 2021-06-22
- 定價: $1,980
- 售價: 9.5 折 $1,881
- 語言: 英文
- 頁數: 338
- 裝訂: Quality Paper - also called trade paper
- ISBN: 149208946X
- ISBN-13: 9781492089469
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相關分類:
Python、程式語言、機率統計學 Probability-and-statistics
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商品描述
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 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 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
商品描述(中文翻譯)
如果你知道如何編程，那麼你已經準備好迎接貝葉斯統計了。通過這本書，你將學會如何使用 Python 代碼來解決統計問題，而不是依賴數學公式，並使用離散概率分佈而非連續數學。一旦你將數學問題解決，貝葉斯的基本原理將變得更加清晰，你將開始將這些技術應用於現實世界的問題。
貝葉斯統計方法變得越來越普遍且重要，但可供初學者使用的資源並不多。這本書基於作者 Allen Downey 所教授的本科課程，採用計算方法幫助你打下堅實的基礎。
- 利用你的編程技能來學習和理解貝葉斯統計
- 處理涉及估計、預測、決策分析、證據和貝葉斯假設檢驗的問題
- 從簡單的例子開始，使用硬幣、骰子和一碗餅乾
- 學習解決現實世界問題的計算方法
作者簡介
Allen Downey is a Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT. He is author of Think Python, Think Bayes, Think DSP, and a blog, Probably Overthinking It.
作者簡介(中文翻譯)
艾倫·道尼（Allen Downey）是奧林工程學院（Olin College of Engineering）的計算機科學教授。他曾在威爾斯利學院（Wellesley College）、科爾比學院（Colby College）和加州大學伯克利分校（U.C. Berkeley）教授計算機科學。他擁有加州大學伯克利分校的計算機科學博士學位，以及麻省理工學院（MIT）的碩士和學士學位。他是《Think Python》、《Think Bayes》、《Think DSP》的作者，並經營一個名為《Probably Overthinking It》的部落格。
