Master-class October 2023: R Software for Data Science: Online

A 3-day a step-by-step, interactive introduction to R and RStudio for participants with no experience with these software packages.



This course will be run over 2 days in 1 week, and then the 3rd day will run in the following week.

Please check the syllabus below for details.

Fri - Sat 27-28 October - Days 1 & 2

Fri 3 November - Day 3



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

(Canberra, Sydney Melbourne, Daylight Savings time)



Friday, October 27, 2023 - Friday, November 3, 2023
Early bird cutoff date: 
Wednesday, September 20, 2023
Course details:

This masterclass offers a step-by-step, interactive introduction to R and RStudio for participants with no experience with these software packages.


This masterclass is part of the ACSPRI suite of courses in social data science is specially designed for those who want to learn how to use R for data manipulation and statistical analysis.



This course will  be run over 3 days, (2 days in week 1 & 1 day in Week 2), using the following timetable:


Day 1

  • 9.30 am - 10.00 am – Introductions and setup check
  • 10.00 am - 11.30 am - Instructional Zoom Session
  • 12.30 pm - 2.00 pm - Instructional Zoom Session
  • 3.00 pm - 5.00pm - Instructional Zoom Session and Exercises

Days 2 and 3

  • 10.00 am - 11.30 am - Instructional Zoom Session
  • 12.30 pm - 2.00 pm - Instructional Zoom Session
  • 3.00 pm - 5.00pm - Instructional Zoom Session and Exercises





Master Class - runs over 3 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: Friday 27 October 2023 - Friday 3 November 2023
Course status: Course completed (no new applicants)
Week 1
About this course: 

One of the key skills in data science is making effective use of software for manipulating data and generating results. R is an established software environment used in the world of data science. In this course, you will be introduced to basic data wrangling, descriptive statistics, visualisation and reporting of results. Key R data science libraries such as dplyr and ggplot will be introduced.

Upon completion of this master class, you will have the skills required to load different types of data files into R, manage and manipulate your data, build visualisations and produce a basic report. The workshop is relevant to researchers and data analysts in any area of research that want to use R for their research work. This workshop aims to introduce the foundations of R and build confidence in the use of R.


Course syllabus: 


Day 1

  • Introduction to R
  • Installing and loading libraries
  • Data structures in R (vectors, matrices, data frames)
  • Descriptive statistics
  • Tabulations
  • Exercises


Day 2

  • Introduction to data wrangling
  • Recoding variables
  • Generating new variables
  • Filtering data frames (rows and/or columns)
  • Merging and appending data
  • Exercises and homework


Day 3

  • Review of homework and Quiz
  • Basic graphs
  • Extending graphs with ggplot
  • Creating your first report of your analysis using Markdown files (tables, graphs)
  • Exercises



Course format: 

This course will be run online over 2 weeks with days 1 and 2 in the first week, and day 3 the following week. Homework will be provided to participants to complete over the following week, with a quiz to be completed prior to day 3.


Participants will require their own computers and to have loaded R and RStudio loaded onto their machines. They will also need to be able to access the internet to download R libraries. This course will be taught in the PC environment but MAC users are welcome.


Please note that due to the short 3-day structure, there will not be any time set aside for analysing participant’s own data.




Recommended Background: 

This course assumes that participants have:


  1. A basic understanding of statistical concepts including descriptive statistics (mean, median and interquartile range),
  2. Some familiarity with a PC/Mac environment including keyboard skills,
  3. An understanding of folder and file structures in the PC/Mac environment, and
  4. Some experience in using Microsoft Word and Excel or their equivalent.
Recommended Texts: 


Data Analysis and Graphics Using R by John Maindonald and W. John Braun.


Discovering Statistics Using R by Andy Field and Jeremy Miles.

Course fees
Non Member: 
Full time student Member: 
Supported by: 



Terms and Conditions: 

1. BOOKING - ACSPRI does not accept ‘expressions of interest’ for course places, i.e. all bookings, are considered firm, and a cancellation fee is charged if you cancel your booking after the early-bird date.


2. DISCOUNT RATE – The discounted rate for ACSPRI members is available to all staff and students of member organisations. To be eligible for this rate:

The course fee must be paid by either the member organisation or by you. Where fees are paid by a non-member organisation the non-member rate applies:and
You must either have a valid email address issued by the member organisation; or you must hold, or have a right to hold, a current staff or student identity card from the member organisation.

In addition, to be eligible for a full time student discount the participant must:

Hold, or have a right to hold, a current student identity card from the member organisation;
Be enrolled as a full-time student;
Make payment in full with your application, arrange electronic funds transfer (EFT), or contact ACSPRI to advise credit card details for payment, by the early-bird closing date;
Provide ACSPRI with contact details of your supervisor, so we can request them to confirm your eligibility for the full time student rate.

The early bird rate applies to all bookings paid in full by the early bird close date, otherwise you will be charged at the standard rate.



3. REFUNDS & CANCELLATIONS - Course fees are not refundable unless:

we cancel the course in which you have enrolled; or
you cancel your enrolment before the early-bird closing date.

A cancellation fee of $250 will be charged if you cancel within the period from the early-bird closing date of and one week prior to the commencement of the program. The full course fee will be charged if you cancel within 1 week of the beginning of your course.


4. PRE-REQUISITES - Course descriptions specify course pre-requisites. You must undertake to meet the pre-requisites of the course(s) in which you enrol. If in any doubt, you should contact ACSPRI prior to enrolling.


Delivery of this course is online - via Zoom.


Please ensure you have the following:

  • Reliable Internet connection with at least 5Gb per day of data available (i.e. a 5 day course will use about 25Gb of data just on the Zoom application)
  • A computer/laptop with the Zoom application installed (free)
  • A webcam (built in to most laptops)
  • A headset with a microphone (not required but ideal)
  • A second monitor/screen if possible


Please also check the course page for specific software requirements (if any).


Venue and Timetable: 

You will be attending from home, and each course may specify a slightly different timing schedule. Please expect around 4 "contact" hours per day, with the remainder of the usual working day for exercises, group work and self-directed activities.

All times specified are in Australian Eastern Time (Melbourne/Sydney/Canberra time)