Expectations for Medical Statistics
- What can you expect?
- What do we expect?
- How to perform well for the exam and get most out of the course
Who’s teaching?
Lecturers and course responsibles
Course structure
Lectures
- Teacher presentations
- Literature
- Exercises in R
Workshops
- Teacher and student presentations
- Literature
- Assignments in R
Group project
- Data analysis with R
- Supervision
Code of Conduct
- Everyone should feel respected
- All questions are appreciated and will be addressed (if time allow)
- Be helpful to each other - you learn more this way
- Teachers try using appropriate tone - please call us out if we’re being boomers so we can be better!
- We dedicate a lot of time to this course but also teach other courses - please be patient with us if we do not answer email immediately
Responsibility
Student responsibility
- Read material in advance of lecture
- Collaborate on group exercises
- Use AI for (deeper) learning
Teacher responsibility
- Use student feedback ASAP
- Offer help during exercises
- If you actively follow the course, you will not only pass the course but also have advantage in job market.
How to study
Lectures
- Read literature before
- Read lecture notes before or after
- Teacher cover 50-75% of reading material (the most deficult part)
- you self-study the rest
- Exercises cover curriculum (aka exam-relevant)
Exercises
- Group work in class
- Teacher will help with everything we can (ask all you want)
Getting or asking for help 🙋♀️🙋♂️
- There are lots of helpers
- Table mates, try to help out too
- We’re all learning here!
- This is a supportive and safe environment
- Remember our Code of Conduct
- When you are IRL use humans
- When alone at home use chat models
Using chat models and AI
Do
- Prompt to explain concept differently (the teacher said “X” - can you reformulate?)
- Prompt to explain code (here is some R code - ELI5 what does it do?)
- Prompt to probe your own knowledge (give me more assignments on “X”)
- Use AI to challenge your understanding: “What assumptions am I making?”
- Ask for hints when you are stuck — before asking for the solution.
Don’t
- Relying on help will make you dependent (what happens when AI is not there?)
- Trust any answer. A fluent and confident answer is not necessarily a correct answer. you are responsible for using any code or information.
- Please use each other and the teachers - otherwise, your education might be ONLY chat model AI in the future…
- Don’t ask AI to simply solve every exercise. The solved exercise is not the goal. Learning is.
- Don’t try to teach an LLM medical statistics. It already has plenty of opinions — your job is to develop your own statistical reasoning.
The time to make mistakes, struggle, and learn is now — not when you are responsible for patients, colleagues, or decisions in the workplace.
More on chatmodels and AI
See the website chapter 5.2
Further resources on responsible use of AI
- AAU: Generative AI for students — guidance on academic practice, privacy, evaluating AI, useful scenarios, prompting, and avoiding over-reliance on AI.
- AAU: Rules for use of generative AI — know the rules that apply to your studies and exams.
- AAU: Scenarios for using generative AI — examples of appropriate uses of AI for studying, understanding difficult material, and exam preparation.
- UNESCO: Guidance for generative AI in education and research — a broader perspective on human-centred and responsible use of generative AI in education.
The exam
Stop-assignment
- Hand-in of course work
This will be developed in the workshops (important to show op)
Project
- Use skills from course to do a short 1 month applied data exploration and statistical analysis
- Draw question based on curriculum
see Appendix B on the website for an example
