⏭️ Week 02 Lab - Now What?

2025/26 Autumn Term

Author

Dr. Ghita Berrada

Okay, you finished the lab. Now what? The approach of this course is to learn by doing:

Have a look at the ✅ Week 02 Lab - Solutions (once you’ve tried out the lab questions on your own!) and see if you understand everything about them.
Freely explore the student performance dataset using dplyr functions and ggplot2 plots. Try to come up with your questions about the data and/or your ways to visualise the data. For example:

Based on travel time and study time, what were the average final grades?
What is the combination of both that leads to the highest average final grades?

If you are stuck, ask for help in the #help channel on Slack or book office hours.

Need more basic programming practice?

Reserve a couple of hours to practice the exercises from the R for Data Science book (Wickham, Çetinkaya-Rundel, and Grolemund 2023). The 📋 Getting Ready page features the chapters that are most relevant to you.
If you’re still not feeling confident about your R, maybe consider checking out the resources the Digital Skills Lab makes available to you, in particular the R pre-sessional workshops (still a few available this term).

You can also use the #help channel on Slack to ask for help with R.

References

Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 2nd edition. Sebastopol, CA: O’Reilly Media, Inc. https://r4ds.hadley.nz/.