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fixing a typo in chapter 01 #307

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Jun 14, 2022
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fixing a typo in chapter 01 #307

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2 changes: 1 addition & 1 deletion 01-introduction.Rmd
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Expand Up @@ -73,7 +73,7 @@ The issue flagged by Ada of having a 'great variety' of ways to solve a problem

R's notoriety for being able to solve a problem in multiple different ways has grown with the proliferation of community contributed packages. In this book we focus on the *best* way of solving problems, from an efficiency perspective. Often it is instructive to discover *why* a certain way of doing things is faster than others. However, if your aim is simply to *get stuff done*, you only need to know what is likely to be the most efficient way. In this way R's flexibility can be inefficient: although it is likely easier to find *a* way of solving any given problem in R than other languages, solving the problem with R may make it harder to find *the best* way to solve that problem, as there are so many. This book tackles this issue head-on by recommending what we believe are the most efficient approaches. We hope you trust our views, based on years of R using and teaching, but we also hope that you challenge them at times and test them, with benchmarks, if you suspect there's a better way of doing things (thanks to R's flexibility and ability to interface with other languages there may well be).

It is well known that R code can promote *algorithmic efficiency* compared with low level languages for certain tasks, especially if the code was written by someone who doesn't fully understand the language. But it is worth highlighting the numerous ways that R *encourages* and *guides* efficiency, especially programmer efficiency:
It is well known that R code can promote *algorithmic inefficiency* compared with low level languages for certain tasks, especially if the code was written by someone who doesn't fully understand the language. But it is worth highlighting the numerous ways that R *encourages* and *guides* efficiency, especially programmer efficiency:

- R is not compiled but it calls compiled code. This means that you get the best of both worlds: R thankfully removes the laborious stage of compiling your code before being able to run it, but provides impressive speed gains by calling compiled C, Fortran and other languages behind the scenes.
- R is a functional and object orientated language [@Wickham2014]. This means that it is possible to write complex and flexible functions in R that get a huge amount of work done with a single line of code.
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