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Introduction to R

He whakatakinga ki te R

Monday 7 February 2023

Introduction to R will cover the use of the open source programming language R (and RStudio) for data manipulation, simple data analysis, and graphing. This version of the course uses Tidyverse functions to illustrate data manipulation and graphing with dplyr and ggplot2. All practical exercises are illustrated using data from health sciences studies.

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 ggplotw)

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.

COVID-19 contingency plan

If COVID restrictions prevent in-person/face-to-face delivery of this course, the course will be cancelled and the course fee will be refunded in full.

Draft timetable

Time Content Presenter
8.30am Registration and Coffee
9:.00am R & RStudio orientation and getting started James Stanley
10:30am Morning break
11am Data management James Stanley
12:30pm Lunch break
1:15pm Statistical analyses and ouput James Stanley
3pm Afternoon break James Stanley
3:30pm Graphs with ggplot2 Ellie Johnson
4:50pm Summary of course and evaluation James Stanley
5pm Finish

Teaching staff

  • Dr James Stanley is a Research Associate 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 an Assistant 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.