科学研究设计与分析导论通过现代框架——鲁宾因果模型，让本科生和研究生了解经典实验设计和观察性研究的基础。因果推理框架在设计、数据收集和分析中很重要，因为它为研究人员提供了一个框架，便于评估研究局限性并得出适当的结论。R用于实施设计和分析收集的数据。
特征
经典的实验设计，重点是在R。
实验设计在临床试验、A/B测试和其他现代例子中的应用。
讨论经典实验设计和因果推理之间的联系。
大数据时代随机化在实验设计和抽样中的作用。
有解决方案的练习。
在RMarkdown中的讲师幻灯片中，将开发一个新的R软件包与本书一起使用，本书的bookdown版本将免费提供。这本书将强调伦理、沟通和决策，作为设计、数据分析和统计思维的一部分。
Design and Analysis of Experiments and Observational Studies Using R
Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework – The Rubin Causal Model. A causal inference framework is important in design, data collection and analysis since it provides a framework for investigators to readily evaluate study limitations and draw appropriate conclusions. R is used to implement designs and analyse the data collected.
Features
Classical experimental design with an emphasis on computation using tidyverse packages in R.
Applications of experimental design to clinical trials, A/B testing, and other modern examples.
Discussion of the link between classical experimental design and causal inference.
The role of randomization in experimental design and sampling in the big data era.
Exercises with solutions.
Instructor slides in RMarkdown, a new R package will be developed to be used with book, and a bookdown version of the book will be freely available. The proposed book will emphasize ethics, communication and decision making as part of design, data analysis, and statistical thinking.
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