Introduction to R

Topics covered

• R basics and RStudio
• Data importing, organising and manipulating (with Tidyverse)
• Exploratory data analysis and simple regression models
• Graphics and data visualisation (with ggplot2)

Style of course

Computer lab – hands-on course combining taught overview, hints on programming practices, and practical exercises. Course attendance is limited to 18 participants.

Who should attend?

The course is intended for individuals who would like to become more comfortable with the R environment for research/study purposes. Basic knowledge of biostatistics is required for the course (e.g. confidence intervals, hypothesis testing) as the focus is on R rather than statistics. Some brief experience in R or another statistics package using programming commands (e.g. Stata, SAS) may be useful but is not presumed. The practicals will be completed using Windows but the material also applies to people running R on a Mac or Linux system.

Draft timetable

Teaching staff

• Dr James Stanley is a Research Professor and consulting biostatistician at the University of Otago, Wellington. He started using R in 2009 to draw nicer graphs than he could draw elsewhere, and now uses it for nicer everything-else-analysis.
• Ellie Johnson is a Research Fellow at the University of Otago, Wellington and has been using R for nearly a decade. She is passionate about the seemingly endless applications of R to research and making beautiful graphics.

Location

This course will be held in-person at the Wellington campus of University of Otago in Mein Street, Newtown (next to Wellington Regional Hospital). Specific directions to the course reception/room will be sent the week before the course start.

Course cost and registration

NZD$375 early bird, NZD$500 after Thursday 19 December 2024.

A 50% discount is available to full-time students, those unwaged and University of Otago staff.

Register now