Preface

R can be challenging to the uninitiated. However, it is a versatile and powerful language and program for data analysis and more. This is an introductory book to learn how to use R for fundamental data analysis in market research.

Why Use this Book

I started using R for data analysis and data wrangling mainly because I needed something that was free and could handle different types of data, including social media data. Every time I faced a new problem to solve, I found that R had a solution. However, its large community of volunteer users who have created innumerable packages makes it hard to navigate for a novice. As I have used R more, I have developed an immense liking for its capabilities. However, it is not an easy program for a novice. My intention with this book is to provide a pathway for a beginner to learn R and use it for fundamental data analysis in market research.

Structure of the Book

The book is organized in a way that is useful to a beginner in R. Chapters 1 to 3 provide an introduction to R and R-Studio and a general direction on how to use the software itself. For someone who is already somewhat familiar with R, but would like to know more about using it for fundamental data analysis and manipulation, Chapter 4 is a place to start with the possibility of review in previous chapters. Chapter 4 takes the reader through data manipulation and creation in R. Chapter 5 takes the reader through steps required for fundamental data analysis and presentation of data that is typically encountered in market research using a sample data set. Chapter 6 is an in depth look at visualizing data in different ways and presenting findings in an aesthetically pleasing manner. Using this book will provide the reader with enough skills to appreciate the power of R for data analysis and to advance to the next level of using R, if so desired.

Acknowledgements

I am grateful to all the volunteers who have contributed to this immense open source project of R and R-Studio. Without these contributions and the packages that have helped me to create this book, this work would not exist. In particular, I am grateful to Wickham (2015) and Wickham and Grolemund (2017) who have done a lot of work in this area. Thanks are also due to Yuhui Xie (2020) who has done a lot of work in RMarkdown and Bookdown, which made the writing of this book possible.

About the Author

Dr. Sujata Ramnarayan is a faculty member at Notre Dame de Namur University. Her research, writing, and teaching interests are in the area of intersection between marketing, technology, and data. You may connect with her on her twitter handle at “mktgnugget.”

References

Wickham, Hadley. 2015. R Packages: Organize, Test, Document, and Share Your Code. 1st ed. Sebastopol, California: O’ Reilly Media Inc. http://r-pkgs.had.co.nz/intro.html.

Wickham, Hadley, and Garrett Grolemund. 2017. R for Data Science. 1st ed. Sebastopol, California: O’ Reilly Media Inc. https://r4ds.had.co.nz/.

Xie, Yihui. 2020. Bookdown: Authoring Books and Technical Documents with R Markdown. https://CRAN.R-project.org/package=bookdown.