🗓️ 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

Either click on the slide area below or click here to view it in fullscreen. Use your keypad to navigate the slides. You can also find a PDF version on Moodle.

🎥 Looking for lecture recordings? You can only find those on Moodle.

✍️ 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)
• 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.