Advanced R programming
- R functions in depth: parameters, return values, variable scope
- Debugging
- Extract data from function output
- Advanced data manipulation
- Advanced R graphics: ggplot2
- A group of useful packages
The lectures are followed by computer exercises where the students either work on material provided by the lecturer, or work on their own statistical material.
Syllabus and other information
Syllabus
PFG0059 Advanced R programming, 3.5 Credits
Subjects
Other Social ScienceEducation cycle
Postgraduate levelGrading scale
Language
EnglishPrior knowledge
Admitted to a postgraduate program, as well as a basic course in basic R programming (equivalent to the course Basic R programming (course code). The course is suitable for all graduate students.Objectives
This advanced course in R programming aims at giving in-depth knowledge in advanced R programming and to develop the student’s skills in writing R functions and efficient scripts for solving complex applications. The course focus on writing R functions, efficient data manipulation, and advanced plot.
Upon completion of the course the student will be able to:
write advanced R functions,
advanced data manipulation like reshape data, merge data,
use advanced plot package, and
perform data analysis on different topics.
The course offered a combination of lectures, computer exercises and self-study.
Content
The lectures provide an overview of the following topics:
R functions in depth: parameters, return values, variable scope
Debugging
Extract data from function output
Advanced data manipulation
Advanced R graphics: ggplot2
A group of useful packages
The lectures are followed by computer exercises where the students either work on material provided by the lecturer, or work on their own statistical material.
Additional information
The student is expected to bring his/her own laptop for computer exercises.The Department reserves the right to cancel the course if there are not more than 5 students who have applied for the course. There is no tuition fee. The students should bring their own laptops for computer exercises. The student is responsible for any housing and travel costs. Students belonging to Statistics-related programs and the ECOS research school at the Forestry Faculty of SLU have priority to the course.
Responsible department
Department of Forest Economics