In statistical work there is often a demand for specific analyses that cannot be done using menu-based statistical software. In such situations, programming skills are good to have. The purpose of the course is to provide an introduction to such statistical programming.
The course is based on the statistical work and programming environment R, which is an implementation of the programming language S. This environment is well on its way to become a de facto standard for professional statisticians. The program is freely available under a GPL license and the student learns how to download and install the program. The first part of the course gives an introduction to R. The student learns how to import and export data, to handle different datatypes, create and use scripts, store data and results, create and save graphical illustrations, and also how data can be manipulated in R with logical operators.
Furthermore, the course provides an overview of the implemented analytical methods, such as methods for hypothesis testing, ANOVA and linear regression. The latter part of the course deals with functions, optimization of code, implementation of C code, and how to create your own R packages.
