Why we wrote R for Dummies

When you want to start using R, it’s hardly a problem to find information. Next to all the free guidance on the web, there exists a mountain of books that covers about everything you need to know about R. So you might wonder why we add yet another book to that stack of knowledge. The answer lies not in the topic of the book, but in the method.

However you look at it, R is firstly a programming language.  However, most authors of introductions to R leave that part to be discovered by the reader. Instead, they focus on how to use R as an analysis and plotting tool. This certainly has its merits, and many people would have been lost without that information. Yet, over and over again we noticed that novices in R keep asking questions on how to rearrange data or how to extract information. Most of those questions arise from not understanding some basic principles of the R language.

As more and more universities embrace R as a scientific tool, we noticed the urgent need for a textbook that could be used for introductory courses in scientific computing with R. So we sat down and thought about a logical sequence in which we could introduce topics like vectors, data structures, operations on these structures and writing functions. Obviously you can’t write an introductory book on R without at least briefly discussing graphics and data analysis, but we consciously decided to keep those topics for later in the book. After all, there is no use in trying to analyze and visualize your data without being able to put it in the right format.

The “for Dummies” format turned out to be very well suited for the kind of book we aimed at. The format forced us to separate the main issues from the details (without having to omit them completely). We had  to think carefully about how and in which order we introduced new concepts. Regardless of how complex some topics may be, the editors forced us to explain these topics in such a way that no prior knowledge about programming is needed to understand the topic at hand.

The end result is a book I am happy to use as a text book for introductory courses on scientific computing with R, but that can also serve the self-learner with no previous experience and introduce them to the wonder that is R.

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