This is the first text in a generation to re-examine the purpose of the mathematical statistics course. The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.

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.

统计决策论及贝叶斯分析：第二版，ISBN：9787503725333，作者：（美）[J.O.伯杰]James O.Berger著；贾乃光译

多元统计分析是统计学中内容十分丰富、应用范围极为广泛的一个分支。在自然科学和社会科学的许多学科中，研究者都有可能需要分析处理有多个变量的数据的问题。能否从表面上看起来杂乱无章的数据中发现和提炼出规律性的结论，不仅需要对所研究的专业领域有很好的训练，而且要掌握必要的统计分析工具。 对研究者来说，本书是学习掌握多元统计分析的各种模型和方法的一本有价值的参考书：首先，它做到了“浅入深出”，既可供初学者入门，又能使有较深基础的人受益；其次，它既侧重于应用，又兼顾必要的推理论证，使学习者既能学到“如何”做，又能在一定程度上了解“为什么”这样做；最后，它内涵丰富、全面，不仅基本包括各种在实际中常用的多元统计分析方法，而且对现代统计学的最新思想和进展有所介绍。值得一提的是，本书中有大量来自实际问题的数据实例，通过对这些实例的分析，读者可以学到如何将一个实际问题转化为恰当的统计问题，进而选择恰当的方法来进行分析。

由茆诗松等编著的《概率论与数理统计教程》为普通高等教育“十一五”国家级规划教材。全书共八章，前四章为概率论部分，主要叙述各种概率分布及其性质，后四章为数理统计部分，主要叙述各种参数估计与假设检验。 《概率论与数理统计教程》的编写从实例出发；图文并茂，通俗易懂，注重讲清楚基本概念与统计思想，强调各种方法的应用，适合初次接触概率统计的读者阅读。全书插图100多幅，例题250多道，习题600余道。 本书可供高等学校数学类专业与统计学专业作为教材使用，亦可供其他专业类似课程参考，也适合自学使用。