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 focuses 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.
Register to the course here
More information on the course
Time: 2024-05-20 - 2024-06-05
City: Umeå
Organiser: Department of Forest Economics
Last signup date: 26 March 2024
Additional info:
Prerequisites: Admitted to a postgraduate program, as well as a basic course in basic R programming (equivalent to the course Basic R programming (PFG0060). The course is suitable for all graduate students. Please get in touch with Camilla Widmark. if you are not sure that you meet the standards for the pre-requisite knowledge needed for this course.
Policies and procedures: 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 the SILVA research school have priority to the course. The student is expected to bring their own laptop for computer exercises.
Important: Please note that in view of the COVID-19-related restrictions, the obligatory meetings may be run either as virtual only (via e.g. zoom) or with a virtual option for participants who cannot attend physical meetings.
This course offers 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.
Preliminary time schedule:
Week 1: Lectures, self-study of literature, computer exercises
Week 2:Computer assignment
Week 3: Examination - turn in computer assignment.
Obligatory meetings: May 20-24
Pass grade requirement: Approved computer assignments
Literature:
R for Data Science: Available at: http://r4ds.had.co.nz/
ggplot2. Available at: http://ggplot2.tidyverse.org