Foundations of R for Research: Online - (2 days)

This 2-day workshop covers the foundations of using the free open-source R and RStudio programs to run their analysis. The course is a mix of lectures and hands-on exercises to introduce participants to the foundations for using R and RStudio.


This course will be offered online via Zoom And will run to the following timetable:

  • 9.30am - 11.00am: Instructional Zoom session
  • 11.00am - 11.30am: Break
  • 11.30am - 1.00pm: Instructional Zoom session
  • 1.00pm - 2.00pm: Lunch
  • 2.00pm - 3.30pm: Instructional Zoom session
  • 3.30pm - 4.00pm: Break
  • 4.00pm - 5.00pm:  Exercises


Exercises will be run interactively during sessions and end of each day


Please note: Courses will run on Australian Eastern Standard Time (GMT +10)


Workshop - runs over 2 days

Dr Joanna Dipnall is a biostatistician with the School of Public Health and Preventative Medicine (SPHPM) at Monash University and Honorary Research Fellow with School of Medicine at Deakin University. She holds a B.Ec(Honours) from Monash University, and a PhD from the School of Medicine at Deakin University. She also lectures and tutors with the Department of Statistics, Data Science and Epidemiology at Swinburne University. Joanna has developed a novel Risk Index for Depression (RID) utilising SEM and machine learning techniques that brought together five key determinants of depression. She has been a teacher of Stata software for over 15 years, training across Australia and overseas and was a member of the Scientific Committee for the Oceania Stata Users Group Meeting in 2017.

About this course: 

This course is a step by step interactive introduction for participants with no experience with R and RStudio. Notes will be provided and a set of exercises, covering a variety of data sets, will be run together during the lecture and also individually at the end of the day. The course content is particularly suited for those involved in research in the business, education, social and health sciences.


Participants will first be introduced to the foundations of R such as libraries, matrix manipulation, objects, and data frames. Participants will use R Markdown in RStudio to generate reports, tables and graphics to Word, PDF and HTML files. Once the foundations have been covered a variety of data management skills will introduced (e.g. filtering data, merging data). The production of descriptive statistics tables and graphs will be covered so that participants can easily use RStudio to explore data and produce reports.


The last session on each day will finish with a set of exercises for participants to run on their own and practice what they have learned that day. Please note that due to the short 2-day structure, there will not be any time set aside for analysing participant’s own data.


Course syllabus: 

Day 1

  • Lecture 1: Foundations of R
  • Lecture 2: Foundation data management skills
  • Lecture 3: Producing basic statistics and tables
  • Lecture 4: Producing your first simple report
  • Exercises in R


Day 2: 

  • Lecture 1: Review of day 1
  • Lecture 2: Extending data management skills
  • Lecture 3: Basic R Graphics
  • Exercises in R


Course format: 

This workshop will take place online using Zoom.

Please make sure you can share your screen as this is an interactive workshop.


Participants must download and install R and RStudio prior to the workshop.

You must be able to install R libraries on your computer during the course.




Recommended Background: 

This course assumes that participants have:

(1) A reasonable understanding of statistics to be able to comprehend the basic statistics such as mean, median and interquartile range.

(2) Some familiarity with a PC environment including keyboard skills and understanding of folder and file structures.

(3) Some experience in using Microsoft Word and Excel or their equivalent.

It does not assume prior experience with R, Stata, SAS, SPSS or any other specific statistical packages although any such experience would be helpful.

Recommended Texts: 

Course notes will be supplied.


No specific references are suggested but participants might find the following text useful:

  • “Discovering Statistics Using R” by Andy Field and Jeremy Miles.
  • “Data Analysis and Graphics Using R” by John Maindonald and W. John Braun.
Participant feedback: 

Course well developed, instructor kept to the schedule, very responsive to queries, and made me feel involved. (Nov 2021)


The workshop was focused heavily on applying the skills Jo taught us through R and R studio which made it a valuable course. (Nov 2019)


ˆ I had never used R prior to this course, so its set me off on the right foot. (Nov 2019)


I obtained basic understanding of R which is what I was looking for. (Nov 2019)


Supported by: