R programming with examples from health sciences

Target audience:

The course is aimed at those who work, or want to work, with data in health, healthcare, or similar fields. Being able to handle and understand parts or the entire process of data management and analysis yourself is becoming an increasingly important skill.

Content:

The course focuses on introducing the statistical programming language R as a tool for performing reproducible statistical analyses. Statistical programming is a necessary skill for working with data analysis, such as statistical analyses, machine learning, and artificial intelligence. In health sciences, R has become a key tool for managing and analyzing data.

A large part of the course deals with importing data, processing and cleaning data, transforming and creating new variables. This part of the process lays the foundation for being able to analyze and visualize data effectively. You will learn the basics of R programming such as data types and structures, control statements, and writing your own functions. You will also learn to write reproducible code that allows analyses to be repeated and reused.

After the course, you will be able to:

After the course, you will be able to manage data in R by importing data, processing and cleaning data, transforming and creating new variables, and performing statistical analyses and summarizing and visualizing the results.

Throughout the course, examples will mainly come from the health sciences. However, the skills are general and can be applied to data from many different sources. In the course, you will learn to perform statistical analyses, but the statistical methods will not be discussed in detail.

Study forms

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.