Platform for starters in the geo sector
200 courses, 20 online supports, 60 moocs,
10 work to work trajectories,
Course R Programming
- Planning and Registration
This R programming course takes 3 days and costs € 1395.
Group discount: If you register several students for this course, a discount of 25% on the 2nd student, 50% on the 3rd student and 75% on the 4th, 5th, 6th, 7th and 8th student.
The R software package, designed by Ross Ihaka and Robert Gentleman, has been specially developed for statistics and data analysis. It is a ready-to-use version of the programming language S. The big advantage of R is the object-oriented character, which makes it quite easy to expand with packages. R is one of the most widely used scientific programming languages today. This course is a first introduction in which the student learns to apply this language when performing statistical analyzes. The R-Studio (freeware) development environment will be used in this course.
On the first day, an introduction is given to the basics of R Programming. After the first day, the student is able to read data, perform operations, and answer simple statistical questions using data selection, descriptive statistics, and plots.
On the second day, the student learns to make tables, interpret them and calculate margins. In addition, he / she will gain insight into S3 / S4 methods. They are also taught to deal with missing values and exceptional cases such as Inf. and NULL. Finally, the student learned to work with R Studio projects and was introduced to writing scripts and functions in R.
The third and last day of the course, the basic knowledge of R Programming is refined. At the end of this day, the student can perform independence tests on categorical data and perform and interpret advanced (linear) regression methods. In addition, the student is able to perform automatic model selection methods with R. Furthermore, extensive attention is also paid to a number of principles behind graphical analysis methods. The student can independently produce, adapt and interpret a number of commonly used plot types. Finally, attention is paid to the geographical component, it is explained how geographical data must be read and plotted on maps.
See also the course R spatial.