Statistics A
In this course, you will learn about conditional distributions, hierarchical/mixed-effects models, Bayesian analyses and computations and software for mixed-effects models and Bayesian computations.
Course description
Content
The course will give you the ability to identify relevant mixed-effects/hierarchical models (for concrete data examples), present and discuss results from statistical analyses based on mixed-effects/hierarchical models, and choose between principles for statistical analysis.
Recommended academic qualifications
Essential prerequisites: Probability distributions with densities, linear normal models, logistic and Poisson regression, R usage (all corresponding to courses “StatMet” and “MStat” (alternatively “MatStat” from previous years) and "Regression"). The course requires maturity at the level of MSc students in statistics; it is not an introductory statistics course.
Place
- The University of Copenhagen
- Department of Mathematical Sciences
Contact
University of Copenhagen
Continuing Education and Lifelong Learning
lifelonglearning@adm.ku.dk