为了培养读者在面对数据时运用统计思维进行科学分析, 在数据分析的基础之上做出更加科学合理的判断, 作者M. D. Edge撰写了著作《统计思维: 科学家入门导引》, 其中包含了三个部分共十个章节的内容。主要涉及数据和概率等一些基础的概念, 概率、随机变量以及随机变量的性质等概率论方面的基本理论知识, 为后续更高级的统计学理论内容打下坚实的基础, 重点讲述了简单线性回归的统计方法。阐述了点估计量的性质和区级估计与推断, 分析了半参数估计与推断、参数估计与推断、贝叶斯估计与推断三种广泛使用的方法。

该著作的特点在于为统计学家和数据分析师的培养提供了概念框架, 系统地讲述统计思维的理论框架, 通过数据、随机变量和一些估计方法介绍几种重要的统计方法和思维, 为了解统计方法是如何设计的提供了思路和方向, 对读者已经知道如何应用技术, 则增加其深度, 激发读者的学习兴趣。

In order to train readers to make scientific analysis with statistical thinking in the face of data and to make more scientific and reasonable judgments based on data analysis, the author M. D. Edge has written the book Statistical Thinking from Scratch: A Primer for Scientists, which contains ten chapters in three parts. It mainly involves some basic concepts such as data and probability, basic theoretical knowledge of probability theory such as probability, random variables and the properties of random variables, which lays a solid foundation for the subsequent more advanced statistical theory content, with an emphasis on the statistical method of simple linear regression. The properties of point estimators and regional estimation and inference are described, and three widely used methods of semi-parameter estimation and inference, parameter estimation and inference, Bayes estimation and inference are analyzed. The feature of this work is that it provides a conceptual framework for the training of statisticians and data analysts, systematically describes the theoretical framework of statistical thinking, introduces several important statistical methods and thinking through data, random variables and some estimation methods, provides ideas and directions for understanding how statistical methods are designed, and adds depth to the techniques that readers already know how to apply, stimulate the reader's interest in learning.