Revised by: Programme council for Master Programmes in Public Health, 2021-09-09
Contents
The course will focus on the use of R for the analysis of data. In addition to familiarization with standard R functions as well as functions for graphics and statistical analysis the students will learn how to program by creating their own functions. The use of script to facilitate reproducible results is central. The course will provide both demonstrations and practical exercises.
Expected learning outcomes
Knowledge and understanding: After completing the course, students shall be able to:
Comprehend and be familiar with standard functions in R.
Comprehend and be familiar with functions for graphical presentation in R
Have a basic understanding on how to formulate and undertake statistical computations in R
Have a basic knowledge on how to access documentation and find help for R.
Skills and abilities: After completing the course, students shall be able to:
Use R to clean and describe data
Use R to visualize data
Perform statistical analysis with R such as significance tests, ANOVA, generalized linear models and survival analysis
Undertake basic programming in R
Create reproducible R Markdown reports that integrate results, R code and text
Judgement and approach: After completing the course, students shall be able to:
Critically discuss and evaluate the application of R to improve code and create reproducible results
Required Knowledge
For non-programme students applying as single-course students, the requirements are 120 ECTS, and Proficiency in English equivalent to Swedish upper secondary course English B/6.
Form of instruction
The course is given daytime as a distance course at 25%. Teaching is performed through plenary lectures, web-lectures, group exercises and practical computer exercises. Teaching is given in English. Internet connection with access to Canvas and video conferencing software together with a functional computer for installation of R and RStudio is a requirement.
To be able to understand and assimilate the statistical methods a basic knowledge in statistics is recommended.
Earlier experience of R or programming is not a requirement
Examination modes
The following grades are used: Fail (U), Pass (G) or Pass with Distinction (VG). The examination encompasses a home exam and group exercises
Students who do not pass the regular examination have the right to a new examination (see Umeå university's rules for course examinations).
If there are special reasons, the examiner has the right to decide whether another form of examination can be used. It is only allowed to supplement a failing grade to a pass. Supplementation to achieve a higher grade is not allowed. A student who has failed two tests for a course, are entitled to have another examiner appointed, unless there are specific reasons against it. A written request is submitted to the director of studies.
Deviations from the course syllabus' examination may be made for a student who has been subject to a decision granting pedagogical support due to a disability. Individual adaption of the examination form shall be considered based on the student's needs. The form of examination is adapted within the framework of the expected study results of the course syllabus. At the student's request, the course coordinator shall promptly decide, in consultation with the examiner, on the appropriate form of examination. The decision shall then be communicated to the student.
