Statistical inference 1100-1BF22
1. Probability: definitions and basic distributions
2. Central limit theorem
3. Statistics and estimators
4. Statistical hypothesis testing
5. Nonparametric tests
6. Maximum likelihood method
7. Resampling statistics
8. Permutation tests
Mode
Prerequisites (description)
Course coordinators
Learning outcomes
Lecture:
understanding basic statistical methods underlying widely used statistical hypothesis testing schemes.
Exercises:
Implementing basic statistical techniques for hypotheses testing, using freely available Python interpreters with proper libraries
Assessment criteria
If the session will be held remotely: written exam at kampus-egzaminy.ckc.uw.edu.pl (with parallel video connection via google meet) plus oral exam via google meet (or another platform, authorized by the University).
Otherwise: written exam in the lecture hall: open questions and single choice test.
Activity during lectures and attention to ev. homeworks will be also taken into account.
Positive marks from the lecture (as above) AND practical exercises are required to pass.
Practical placement
--
Bibliography
Lecture:
http://brain.fuw.edu.pl/edu/STAT:Wnioskowanie_statystyczne
Lab:
http://brain.fuw.edu.pl/edu/STATLAB:%C4%86wiczenia_ze_statystyki
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Applications of Physics in Biology and Medicine, first cycle programme
- Physics, second cycle programme
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: