This workshop is for students who plan to use the free statistical software R for statistical analysis and graphical presentation. We will also provide an introduction to RStudio, a code environment that helps with the use of R. Participants should be familiar with basic statistical methods. R has become the software environment where most new statistical procedures first become available for general use: it now offers a wider range of statistical procedures than any commercial package. Moreover, it is a free and open-source, so if you can use R, then you will never be constrained by your future employer's choice of statistical software.
However, if your use of computers has always been ‘point-and-click’, R is likely to be a bit of a shock, since effective use of R requires you to type in commands for the software to execute. This means that you need to learn (at least some of) R's command language and syntax. This course will cover a general introduction to the R command language, and how to use it to import data, transform and manipulate data, calculate descriptive statistics, draw graphs, execute common (and some less common) statistical tests, and import specialist packages for more exotic analyses.
If you have had any experience with computer programming or with the use of programs like MatLab and S-Plus, your R experience will probably be quite a pleasant shock, since the R language is very much easier to learn and use than languages like C or Java (and is in fact virtually identical to the S-Plus command language). If this will be your first experience of programming, the learning curve will be a little steeper. However, six hours invested in this course, and another six hours spent practising, will certainly get you to the point where entering commands is no longer an impediment, and you can build your skills independently.
** Participants can bring their own laptop or use the lab computers
Presented by Professor Rhondda Jones
|Townsville||Tuesday 17 July 2018||10:00am to 5:00pm||142-020|
Registrations open 6 weeks prior to the workshop date via CareerHub.
Participation in this workshop may be counted in the Elective Component of RD7003 for PhD candidates.