This is a QCIF course and places are highly limited as Graduate School is paying the fee. If you are unable to attend, please de-register (or email if you are unable to do so). An unexplained absence could result in all your future QCIF registrations becoming Waitlisted.

Formerly known as Hypothesis testing using R.

Participants will learn how to compute, report, and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA.

Learning Objectives

  • Choose the right statistical test appropriate for the data and the research questions
  • Carry out inferential statistics in R
  • Generate plots, figures and tables of hypothesis tests using specific R packages
  • Interpret and report the results of a range of commonly-used statistical tests


  • An introduction to hypothesis testing terminology
  • Correlation analysis between two continuous variables
  • Statistical tests for both categorial and continuous variables
  • ANOVA – testing with more than two groups

Pre-workshop preparation

Attendees must have previous experience in R and the RStudio interface. Please come with R and RStudio installed.

While you are waiting, get started with R and RStudio:

NOTE: The examples used in this course will be from bioinformatics. You may also want to consider attending the R sessions in the Library. See the Library's training link for more information on the latest sessions.

About Statistics and modelling

If your research study employs quantitative or mixed methodologies, you would need to understand the nuts and bolts of statistics and modelling. The Graduate School works with different providers to provide a range of sessions covering descriptive and inferential statistics as well as modelling with esteemed providers such as ISSR and Student Services.

Useful links

Other upcoming sessions