🗓️ Week 04 - Statistical Inference I

2023/24 Autumn Term

This week, we move away from the Computer Science side of Data Science and we start exploring the basic concepts of Statistics every data scientist should know. We will talk about population, samples, distributions and probability. We will also learn/review how to use Python to conduct an exploratory data analysis (mostly plots) on your data and will touch on concepts linked to the handling of missing data. Next week, we will explore the statistical inference side of Statistics more closely.

👨‍🏫 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 10%

• Each group within the class selects an article to present on the Week 05 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 February 7th.
• Every member of the group will have to take part in the presentation (15 minutes)
• A discussion will follow the presentation (10 minutes)
• For details on the content of the presentation and marking criteria, refer to this page

🏗️ Preparation for week 4 class

To allow for enough time for hands-on practice of Zotero and Quarto Markdown during the class this week, we ask that you install Anaconda (Python), Quarto, VSCode and Zotero before coming to class. Head this way to see how.

📚 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.