13 May –
 30 May

Umeå

PhD course: Basic R programming

seminars, workshops |

The aim of the course is to provide basic knowledge of the R language and on the skills of writing R scripts for practical applications. The course will focus on the core of R programming language, and data manipulation with R.

Upon completion of the course the student should be able to:

- master the basic knowledge of R language,

- master functions commonly used for data manipulation,

- generate basic descriptive statistics, conduct a simple multiple linear regression analysis and specification test, and

- produce different types of data plot.

Register to the course here

More information on the course

Facts

Time: 2024-05-13 - 2024-05-30
City: Umeå
Organiser: Department of Forest Economics
Last signup date: 26 March 2024
Additional info:

Prerequisites: Admitted to a postgraduate program. The course is suitable for all graduate students. No programming experience is required, but students are recommended to possess knowledge in basic mathematical statistics.

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.


Programme

The course consists of lectures, computer exercises and self-study. The course begins with an orientation connected to the following concepts:

  • What is R and what can R do?
  • An IDE (Integrated Development Environment) for R

Further, the course covers programming of R, specifically:

  • Data types and data structures: vector, list, matrix, data frame, factor
  • Import data and write out data
  • Data manipulation
  • Control flow
  • Write simple function
  • Plot
  • Regression analysis

In a computer exercise, students will write R scripts to solve specific problems by using the knowledge from the lecturers. Exercise materials are provided by the lecturer.

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 13-17

Pass grade requirement: Approved computer assignment

Literature:

An introduction to R. Available at: https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf

Quick-R. Available at: https://www.statmethods.net/

 

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