ETC5523: Communicating with Data


Lecturer: Michael lydeamore

Department of Econometrics and Business Statistics

👩🏻‍🏫 ETC5523 Teaching Team

Dr. Michael Lydeamore

Lecturer & Chief Examiner

Cynthia Huang


Janith Wanniarachchi


Contacting the teaching team

  • For private matters, contact using your Monash student email and citing the unit name.
  • For non-private matters, you should post this in the Moodle discussion board.

👩🏻‍🏫 ETC5523 Teaching Team

Most material in this course was developed by

Emi is a guru of data communication, and I highly recommend checking out her website content and academic work.

🎯 ETC5523 Learning Objectives

Learning objectives

  1. Effectively communicate data analysis, using a blog, reports and presentation.
  2. Learn how to build a web app to provide an interactive data analysis.
  3. Learn to construct a data story.

Specific outcomes

After this unit, you should be able to:

  • understand and apply the elements of effective communication,
  • host R Markdown HTML outputs online for blogging, reports or other purposes,
  • be more confident with web technologies (HTML/CSS),
  • make a Shiny web app, and
  • build an R package.

🏛️ ETC5523 unit structure

  • 2 hour lectures are interactive sessions:
    • during the lecture we demonstrate, discuss and complete tasks in small groups
  • 1.5 hour tutorial → only go to the one you are assigned to!

🪵 Materials

Unit website

  • Lecture slides and tutorial materials are available on the unit website
  • Lecture videos and assessments will be available on Moodle


Materials are designed to develop your hard and soft skills.

✋ Consultation hours

  • A total of 2 hours of consultation each week

  • See Moodle announcement for the Zoom links for the consultations

  • Seek help early and often!

  • For coding issues, check out this guide1 to make it easier for others to help you

💯 Course assessments

  • Week 5: Assessment 1 (20%) develop and showcase a Shiny web app
  • Week 7: Blog entry (20%) write a data story on the web
  • Week 8: Video group discussion (10%) critique and reflection
  • Week 10: Assessment 2 (20%) develop and showcase an R-package
  • Oral exam (30%) on week starting 24 Oct on the technical aspects of HTML/CSS, Shiny apps and R-packages

🏁 Expectations Part 1

  • Attend lectures and assigned tutorials
  • Minimum total expected workload is 144 hours, that’s 12 hours each week or 8.5 hours of self study per week
  • Check the unit homepage and unit Moodle page often
  • ETC5513 (or equivalent) is a prerequisite → you need to catch up fast if you’re not confident
  • Install the latest R and RStudio IDE (or your chosen IDE that has the ability to run R code)
  • For the in-person tutorials, bring your own laptops

🏁 Expectations Part 2

Be an active learner!

An active learner asks questions, considers alternatives, questions assumptions, and even questions the trustworthiness of the author or speaker. An active learner tries to generalize specific examples, and devise specific examples for generalities.

An active learner doesn’t passively sponge up information — that doesn’t work! — but uses the readings and lecturer’s argument as a springboard for critical thought and deep understanding.

– Spencer (2022) Data in Wonderland