Department of Statistics

Introduction to R


This course assumes that participants will have no prior experience with R.

Day one: We will begin with the basics: using R as a calculator; reading in data from a file; and generating summary statistics and contingency tables. With the basics under our belts, we will begin unveiling some of the power of R in manipulating those very large data sets too unwieldy to deal with, in the introduction of in-built R functions that provide shortcuts for performing the same operation across many columns or rows of a data set simultaneously.

Day two: We will discuss optimal visual displays for presenting information from different variable types (e.g. continuous, count, categorical, etc.) as we take an in-depth tour of generating publication-quality graphics in R. This will include:

  • Boxplots, scatterplots, and bar charts, including legends
  • Plots presenting information from multiple variables simultaneously
  • The ggplot2 package for R, for even more sophisticated graphical displays

Finally, we will demonstrate how to use R to fit regression-type models to data. In addition, we will cover topics of special interest to participants (to be arranged with Kevin in advance; please email your interests to

The daily schedule may vary according to the pace of the workshop.



kevin chang

Kevin Chang (PhD, University of Auckland) has been working as a consultant with the Statistical Consulting Centre, Department of Statistics, University of Auckland since 2014. Prior to this Kevin was part of the Bioinformatics Institute, where he developed skills in designing and analysing the high-throughput biological experiments in the fields of genomics and proteomics. Kevin also has nine years’ experience in R programming, and has developed several R packages and web-deployed Shiny applications for MNCs and research groups.




Registration costs

  • $300 for internal University of Auckland 
  • $500 for participants from outside the University of Auckland

Payment methods:

  • University of Auckland - participants will be able to pay via UoA journaling from your PRESS, research or other account
  • External participants will be invoiced



  • City Campus, University of Auckland, Auckland CBD, Auckland, New Zealand