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 for you if:

• You need to apply statistical tests on large datasets in your current or future role
• You have a basic or higher level of programming using R and Rstudio
• You have a basic or higher understanding of statistics
• You work in health-related sector as either clinical, administrative or academic staff - for example as a nurse, health administrator, consultant, biomedical researcher, etc.
• You require flexible learning format

Course delivery mode

This course is entirely self-paced and all the materials are on the Learning Hub module. We recommend dedicating a total of approximately 10 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.

You will be going through 8 learning sessions, including theoretical refreshers and hands-on practicals. Each practical session:

• is carefully designed to be an immersive, hands-on learning experience of 30-60 minutes
• has video lectures in which you are following the instructor in writing simple code and applying it to health-related questions.
• has a link to learning materials the instructor is using if you prefer to read
• offers you stimulating questions to enhance your learning experience

! Note: each video will offer quiz-type questions and/or open reflection points. For quiz-type questions, you will be given the correct answer after you click 'Submit' at the end of the video. For open reflection points you are invited to contemplate at your own pace and will not be given a written-out correct answer.

Technology required:

• You will need to be able to download and use the free software RStudio on a computer or log into RStudio Cloud. This is to be able to take part in the parallel coding most lectures require.
• You will need to be able to download example data via the link the instructor provides.
• By the end of this course you will be able to:
• Describe the essential terms of hypothesis testing (e.g. null hypothesis, statistical power, etc)
• 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)

! Note: This course does not teach basic programming skills. If you are complete beginner to R, we recommend you start with 'Basic R with Data Carpentry' course which can be found on our website.