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


This course is being held online via Zoom and run on Australian Eastern Daylight Time (UTC +11)

(Canberra, Sydney, Melbourne Daylight Savings time)


Level 2 - runs over 2 days

Dr Joanna Dipnall is an applied statistician with interests in the advanced statistical methods, including machine learning and deep learning techniques. She completed her Honours in Econometrics with Monash University and her PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate artificial intelligence within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Co-coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.

Course dates: Thursday 19 January 2023 - Friday 20 January 2023
Course status: Course completed (no new applicants)
Week 1
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.
Course fees
Non Member: 
Full time student Member: 
Participant feedback: 

This was an excellent course on a hard topic


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


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


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


I obtained basic understanding of R which is what I was looking for.


Summer Program 2023
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