This part of the book provides the foundations for subsequent parts. Assuming very little in terms of prior knowledge, this part covers core concepts and skills in data analysis, statistics, and causal inference.

  • 1  Introduction provides an introduction to the book, including a reading guide and instructions for setting up your computer.
  • Given the centrality of data skills to getting the full value out of this book, we provide a fast-paced tutorial-style introduction to R in 2  Describing data.
  • As we assume very little knowledge of statistics and regression analysis, we provide an introduction to the basics of regression analysis in 3  Regression fundamentals.
  • 4  Causal inference builds on 3  Regression fundamentals to provide an introduction to elements of causal inference.
  • 5  Statistical inference provides an introduction to statistical inference, which is a core part of empirical accounting research.

We then introduce key data sets frequently used in empirical accounting research.

This part of the book provides foundations for the remaining parts of the book. Depending on the preferences of readers and instructors, one could continue with Part II (Capital Markets Research), or skip ahead to Part III (Causal Inference). While some parts of Part III draw on skills and concepts covered in Part II, we flag such instances in each case.