To make the most out of this book, you should recreate on your own the examples shown throughout, and make sure that you understand what each of them is doing in detail. If at some point you feel confused, it's not too difficult to do a couple of searches online to clarify things for yourself. However, I highly recommend that you look into the following books as well, which go into more detail on some of the concepts and ideas presented in this book, and are considered very good references for R programmers:
- R in a Nutshell, by Adler, O'Reilly, 2010
- The Art of R Programming, by Matloff, No Starch Press, 2011
- Advanced R, by Wickham, CRC Press, 2015
- R Programming for Data Science, by Peng, LeanPub, 2016
Sometimes all you need to do to clarify something is use R's help system. To get help on a function, you may use the question mark notation, like ?function_name, but in case you want to search for help on a topic, you may use the help.search() function, like help.search (regression). This can be helpful if you know what topic you're interested in but can't remember the actual name of the function you want to use. Another way of invoking such functionality is using the double question mark notation, like ?? regression.
Keep in mind that topics in this book are interconnected and not linearly ordered, which means that at times it will seem that we are jumping around. When that happens, it's because a topic can be seen through different points of view. That's why, to make the most out of this book, you should experiment as much as you can in the console and build code progressively using the write-execute loop mentioned earlier. If you simply replicate the code exactly as is shown, you may miss some of the learning that you could have gotten had you built the systems step by step.
Finally, you should know that this book is meant to show how to use R through somewhat real examples, and as such, does not provide too much technical depth or discussion on some of the topics presented. Furthermore, since my objective is to get you quickly working with the real examples, in this first chapter, I explain R fundamentals very briefly, just to introduce the minimum amount of knowledge you need to follow through the real examples presented in the following chapters. Therefore, you should not think that the explanations presented in this chapter are enough for you to understand R's basic constructs. If you're looking for a more in-depth introduction to R fundamentals, you may want to take a look at the references we mentioned previously.
