1 Introduction to the Book

“The true path to wisdom can be identified … it has to have practical application in your life. Otherwise, wisdom becomes a useless thing and deteriorates, like a sword that is never used.” - Paulo Coelho, “The Pilgrimage”

This book is intended as a practical introduction to research methods in the social sciences. If you pursue research academically or professionally, it will probably not be the last book you need to read on the subject. This is intended as something of a gentle introduction with a focus on the applications of the information and examples.

There are a lot of terms that many such textbooks would include that are left out of this edition. I believe that learning is like pouring water into a cup. Once the cup is full, you can keep pouring but the cup wont hold more water. What you should do is drink the water before you refill it. The analogy gets a little bit stretched there, but “drinking the water” stands in for using the information. Once you actually understand the basics in this text, you’ll be ready to read a more advanced book that fills you back up.

So how did I decide what to leave out and what to include? I gave preference to the terms and information I need in my working life as someone who does research. Terms like inductive and deductive research are left out, not because they are unimportant, but because I rarely encounter them. Their definitions might be good material for a test on the terms in this book, but I don’t believe they are fundamentally important to your ability to engage with published research or conduct basic research yourself.

Research is best learned through practice. Like many classes, it is hard to really understand the difference between the different terms and ideas unless you’re actually using them for yourself. This book is written with the understanding that the subject is hard to internalize, and so real world examples are offered where they can be. But that’s not enough to make you an expert. And in fact, it’s hard for anyone to be an expert - there are always new methods and techniques to learn that can improve the ability of researchers to answer important questions. But this book is a good place to start, or at least I hope it is.

With that, I have to give a warning. If you take research methods from another teacher in the future, things might be described differently. That means I’ve sometimes ignored esoteric terms that you wont encounter outside a research methods class. And sometimes I define the terms I use slightly differently than others would. The goal is for this book to be approachable for students who have no background in the subject, aren’t interested in methods, and don’t like statistics.

My primary goal is to impart some of my excitement for research and statistics to you. If I fail in that, I hope I can at least make you better able to engage with the copious amounts of research that will shape policy and your behaviors during your life.

This book is copyrighted under Creative Commons Attribution-NonCommercial 4.0 International Public License, which means that it’s free for you and anyone to use. The Fall 2020 edition is a substantial expansion of another edition written in the Fall of 2019, and will continue to be updated in the future.

1.1 The Plan for this book

This book encompasses 1) the development of a research project and 2) the analysis of the resulting data you might collect.

The first half of the book concentrates on the development of a research project. That half of the book is written for a student that has to write a class research paper or thesis and doesn’t know where to start. It’ll walk the student through the development and identification of an idea through the collection of data.

But just collecting data isn’t enough if you’re going to do your own research. And with the growth of data that is available online, it isn’t even a necessary place to start (although understanding the first half is important), So the second half is written with the idea that the data is collected, and now it must be analyzed. In those chapters the book will walk the reader through basic steps of presenting and analyzing data that are common to many research projects. In those chapters we’ll also learn how to do all of that in R, a free software that is commonly used in data science. We’ll talk about that more later though.

1.2 Acknowledgements

I’d like to thank several students that helped with the updating of this book: Theresa Anderson, Maria Andrade, Derek Brumfield, Diane Buckley, Ashley Felan, Britain Forsyth, Omar Garcia, Marcus Gibson, Heather Glass, Ashley Hebert, Kirstie Jiles, Alisha Large, Liz Mexwell, Todd McConnell, Tokolongo Mokuena, Ashley Paratore, Chad Populis, Ben Quimby, Sabrina Richardson, Stephanie Riegel, Frank Robertson, Michelle Rosamond, and Tosha Shanableh. Of course, any errors or mistakes are the authors alone.

I’d also like to thank Jesse Lecy for pushing me to learn R and inspiring me to put together this book.