R programming with examples from health sciences

The course is offered as a freestanding course on advanced level, targeting students of health sciences, social science, science, economics, engineering, or similar, with an interest in learning analysis of data using the R programming language. Examples in the course are mainly from the health sciences.

The entry requirements are at least 120 credits and English B/English 6.

The course is focused on introducing the statistical programming language R as a tool to perform reproducible statistical analyses. Statistical programming is an essential skill in order to work with data analysis, including statistical analyses and machine learning, and AI. In the health sciences, R has evolved as a key tool for managing and analyzing data. The scope of the course ranges from importing data, processing and tidying data, transforming and manipulating data, performing statistical analyses, and summarizing and visualizing the results. You will learn the basic concepts of the R programming language such as data types and structures, control statements, and writing functions and reproducible code. Throughout the course, we will predominantly use examples from the health sciences. The course teaches how to perform statistical analyses; however, the statistical methods are not described in detail.

On successful completion of the course the student will be able to:

Knowledge and understanding

• Describe the most common data types and objects, as well as common file formats for R scrips and data
• Explain how to install and update packages
• Describe how to find and use documentation on R functions and packages
• Give examples of standard functions and common packages for statistics and visualizations

Competence and skills

• Write R scripts and user-defined functions
• Use R to import data from typical external data format
• Process and transform data in R by converting table formats and calculating new variables
• Perform statistical analyses using R
• Summarize and present results as informative tables and figures using R

Judgement and approach

• Critically discuss the use of open-source statistical software
• Choose approaches to develop scripts for comprehensible and reproducible analysis, including for example documentation, naming convention, code layout and use of functions

Teaching is online only and consists of a mixture of pre-recorded material and live online lectures, workshops, and computer exercises. The teaching takes place on digital platforms.

Language of instruction: English

Four mandatory computer assignments, presented in writing and orally

The grading scale comprises: Pass (G) and Fail (U)

The course evaluation is carried out in the form of an anonymous questionnaire. A compilation of the questionnaire is done by the course coordinator. The result and potential changes should be shared with both the students who carried out the evaluation and the students that are about to start the course.

A computer with internet, webcamera and a microphone, and with the possibility to install R and RStudio, is necessary to be able to follow the course.

If a student who has been failed twice for the same examination element wishes to change examiner before the next examination session, such a request is to be granted unless there are specific reasons to the contrary (Chapter 6 Section 22 HF).

If a student has received a certificate of disability study support from the University of Gothenburg with a recommendation of adapted examination and/or adapted forms of assessment, an examiner may decide, if this is consistent with the course’s intended learning outcomes and provided that no unreasonable resources would be needed, to grant the student adapted examination and/or adapted
forms of assessment.

If a course has been discontinued or undergone major changes, the student must be offered at least two examination sessions in addition to ordinary examination sessions. These sessions are to be spread over a period of at least one year but no more than two years after the course has been discontinued/changed. The same applies to placement and internship (VFU) except that this is restricted to only one further examination session.

If a student has been notified that they fulfil the requirements for being a student at Riksidrottsuniversitetet (RIU student), to combine elite sports activities with studies, the examiner is entitled to decide on adaptation of examinations if this is done in accordance with the Local Rules Regarding RIU Students at the University of Gothenburg.