R dummies

Chapter 15Testing Differences and RelationsIn This ChapterEvaluating distributionsComparing two samplesComparing more than two samplesTesting relations between categorical variablesWorking with modelsIt’s one thing to describe your data and plot a few graphs, but if you want todraw conclusions from these graphs, people expect a bit more proof. This is wherethe data analysts chime in and start pouring p-values generously over reports andpapers. These p-values summarize the conclusions of statistical tests, basicallyindicating how likely it is that the result you see is purely due to chance. The storyis a bit more complex — but for that you need to take a look at a statisticshandbook like Statistics For Dummies, 2nd Edition, by Deborah J. Rumsey, PhD(Wiley).R really shines when you need some serious statistical number crunching.Statistics is the alpha and omega of this language, but why have we waited untilChapter 15 to cover some of that? There are two very good reasons why we wait totalk about statistics until now:You can start with the statistics only after you’ve your data in the right format,so you need to get that down first.R contains an overwhelming amount of advanced statistical techniques, many ofwhich come with their own books and manuals.Luckily, many packages follow the same principles regarding the userinterface. So, instead of trying to cover all of what’s possible, in this chapter weintroduce you to some basic statistical tests and explain the interfaces in moredetail so you get familiar with that.