Charles Explorer logo
🇬🇧

R for life

Class at Faculty of Science |
MB162P13

Syllabus

An interactive lecture (with computers). We will introduce basics of work with data, graphics and programming in R (all the non-statistical tricks). This part roughly corresponds with chapters 1-5 in Crawley (2007). Topics of the theoretical part:

1. Introduction to R. Help and literature. R environment and specifics of R. R-editor, Tinn-R with highlighted syntax; data import and export, basics of syntax, operators, signs and brackets.

2. Basic structures in R. Variables, vectors, matrices, data frames, arrays, strings, characters vs. numbers. Indexes as a crucial concept.

3. Brief ?bestiary? of some useful functions. Random number generation. Operations with vectors and matrices (sample, order, sort, diff, max, min, unique, sums, which). Operations with strings. Basic mathematical functions.

4. Scripting and programming (code writing) ? most important, we will dedicate extra time to make sure anybody understand this. Functions, arguments of functions. Control flow & loops (if, else, for, while, repeat). Functions within/inside function.

5. Good programming practice.

6. Data visualisation and graphics in R. Good practice in data visualization. Plot, lines, points, abline, text, image, par etc. as tools to visualize nearly anything. Lattice (Trellis) graphics. Connection of graphics and programming ? drawing and animations in R.

Annotation

The main purpose of the course is to teach participants how to program (in R) and effectively use programming for solving common problems. We would like to show that programming is, in principle, easy and anybody can do it (R is very intuitive). Moreover, we would like to demonstrate that R is not just statistics but can be used to work with graphics, databases, simulations or GIS.

We intend to make the course comprehensible for all students, there are no restrictions concerning year, degree or programme. However, we assume that the attendants will be mostly biologists with elementary experience with biological data and with simple graphs. The course is especially suitable for all who spend more than ~3 hours a day working with computer.

If you are interested in the English version of the course, look at the MB120P147E - "R for life"