Statistics with R

Move from statistical theory to practical application with R, using hands-on examples designed for health-related data.

4 hours

Basics of R

Intermediate

CPD accredited

Course information

This course will provide practical examples of how to perform statistical tests using the R software environment. We will explore the most widely used statistical tests and will explain the basic concept behind applying a stats test in R so that participants will be able to apply their knowledge to other tests not covered in this course. A basic knowledge of the statistical tests and a basic knowledge of R and Rstudio are essential.

This course is entirely self-paced and all the materials are on the Learning Hub module. We recommend dedicating a total of approximately 5 hours of learning time to get the most out of this course.

Live Q&A sessions with the instructors will be scheduled regularly so participants can receive support in whatever stage of the course they are. The dates will be emailed to you if you sign up to the course.

Learning objectives

Describe the essential terms of hypothesis testing

Compare qualitative and quantitative data and their subcategories

Choose statistical tests based on the type of data and the research questions at hand

Define steps of statistical analysis of qualitative data

Perform statistical analysis of qualitative data using Chi-squared and Fisher's tests

Define steps of statistical analysis of quantitative data

Test if data is parametric using Shapiro-Wilk test and Levene test

Perform statistical analysis of parametric quantitative data using t-test (independent and paired) and ANOVA (one-way and two-way)

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