Think Stats 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Allen B. Downey 作者

O'Reilly Media

译者

2011-7-22 出版日期

140 页数

USD 29.99 价格

Paperback

丛书系列

9781449307110 图书编码

Think Stats 在线电子书图书标签: 统计学数据分析 O'Reilly 统计 statistics Python 编程机器学习

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发表于2024-11-22

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Think Stats 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Think Stats 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Think Stats 在线电子书用户评价

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好书, 适合初学者

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作者把全书电子版放到网上让大家免费阅览实在让人非常感谢。从内容上来讲有些过于简略浅显，导致无论是关于我熟悉的内容的章节还是未学过的章节都没有学到太多

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关键词：python +程序员+概率统计基础

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从怎么用python写统计相关的知识的角度出发的。整本书围绕一个案例讲的，所以比较好懂

Think Stats 在线电子书著者简介

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.

Think Stats 在线电子书图书目录

Think Stats 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Think Stats 在线电子书图书描述

If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.

You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.

Develop your understanding of probability and statistics by writing and testing code

Run experiments to test statistical behavior, such as generating samples from several distributions

Use simulations to understand concepts that are hard to grasp mathematically

Learn topics not usually covered in an introductory course, such as Bayesian estimation

Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools

Use statistical inference to answer questions about real-world data

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