DATA 202 (2024) - Labs

Every week, apart from the first week, there are drop-in computer lab sessions - these will be available as in person or online sessions.

  • Tutorial 1 (10am Thursday, KK216): In person drop in session
  • Tutorial 2 (10am Friday, KK216): In person drop in session
  • Tutorial 3 (11am Thu Weeks 2-7, 9am Thu Weeks 8-12): Zoom demonstration session (use the lecture zoom link) - the tutor will work through the solutions to the tutorial. You can ask questions. (PICK Note: this session will be videoed and posted in Nuku)

You do not need to sign up for a session, you can attend whichever one you like. You can also arrive and leave whenever you wish during the session.

This is an opportunity to practise programming with assistance from a teaching assistant.

At the in person session you can bring your own device (BYOD) if you'd rather work on that than the ITS (Windows) machines that are provided in the lab. If you do BYOD then it is your responsibility to ensure that the software (R and RStudio) is installed correctly. We may be able to help with that.

The course tutors will run the in person and zoom sessions. Material provided by: LM=Louise McMillan; BN=Binh Nguyen; RAd=Ryan Admiraal

The tutorial in the first week is self-guided: there will be no tutorial sessions that week, but you should work through the exercises yourself.

Week Tutorial Date Lab Notes
1 (No session) Self Guided: Introduction to R and Rstudio
2 Thu 7 Mar (LM) R objects and reading data
3 Thu 14 Mar (LM) Summary and display, Functions
4 Thu 21 Mar (LM) R Programming
5 Thu 28 Mar (LM) Output, strings and dates
6 Thu 18 Apr (BN) R and SQL
7 Thu 25 Apr (BN) R and SQL
8 Thu 2 May (BN) Data frames and summary data
9 Thu 9 May (BN) Wide vs. long format, "ggplot", and debugging
10 Thu 16 May (RAd) Introduction to Probability and Simulation
11 Thu 23 May (RAd) Probability Distributions and Application of Simulation
12 Thu 30 May (RAd) Network Data Storage Structures, Visual Displays, and Descriptive Statistics