🗓️ Week 04 - Statistical Inference

2025/26 Autumn Term

This week, we move away from the Computer Science side of Data Science and we explore the basic concepts of Statistics every data scientist should know. We will talk about population, samples, distributions and probability. We will also briefly touch on exploratory data analysis (mostly plots) on your data. And take our first steps in the modeling world: we’ll see how to represent the world in the simplest possible way with a linear regression

👨‍🏫 Lecture Slides

🚧 This section will be updated before the lecture. Watch this space!

✍️ Summative: worth 30%

• Each group within the class selects an article to present on the Week 04 class (check your final group allocation, if you don’t know it already, on Slack or Moodle)- allocation for class group 2 currently pending
• The articles to be presented should be vetted by October 13th.
• Every member of the group will have to take part in the presentation (15 minutes)
• A discussion will follow the presentation (5-7 minutes)
• For details on the content of the presentation and marking criteria, refer to this page

📚 Recommended Reading

• Check the end of slides for the list of references cited in the lecture.
• Check the 📔 Syllabus for this week’s complete list of indicative and recommended readings.

📟 Communication

• Post your reflections, questions, and links on Slack.