Preface

After a few years in my undergraduate economics program, I grew interest in the field of programming. I felt that in the real world, the concepts and theories in the field of economics and finance are brought alive with data. Times are changing, and the ability to code and create elegant computer scripts will be very useful, especially when handling data sets and conducting analysis.

I realized that unless you were on your way towards a computer or data science degree, there wasn’t really a concrete way of getting used to working with data and programming on your own free time. Additionally, I wanted the content of this book to assist my fellow students in my program.


Data: the way you see it in movies
Data: the way you see it in movies


Therefore, I compiled this book. The purpose of this book is to storehouse all the foundations you need as a fresh beginner in statistical programming. Whether you are an undergraduate or postgraduate, this book will help you get started with R language programming and data analysis. This book will also dive deeper into the methodologies of causal inference, which will be particularly useful for final year research projects, postgraduate statistical studies, and research.

The content of this book is based on certain lectures and coursework that I have received throughout university, my personal study notes, as well as publicly available sources that I have encountered and used in my journey.

I believe anyone can code with R, but the question is how and where should one start?

Couscous (a pun of ‘cause-cause’) aims to be the solution for you.

By the end of reading this book, you will be able to use the R language effectively for causal inference.