Sign-up: PhD students should apply via the credit student application » at this link. The Course Code to enter is NFYK13011U.
MSc students sign up via kurser.ku.dk.
Please contact Aiga Voite if you have any questions or problems re. sign-up.
The course will give the student an introduction to - and a basic knowledge on - statistics. The focus will be on application and thus proofs are omitted, while examples and use of computers take their place.
The course will cover the following subjects:
• Introduction to statistics
• Distributions - Probability Density Functions
• Error propagation
• Correlations
• Monte Carlo - using simulation
• Statistical tests
• Parameter estimation - philosophy and methods of fitting data
• Chi-Square and Maximum Likelihood fits
• Simulation and planning of an experiment
• Multidimensional data and Fisher Discriminant
• Introduction to Machine Learning
• The power and limit of statistics.
SkillsThe student should in the course obtain the following skills:
KnowledgeThe student will obtain knowledge about statistical concepts and procedures, more specifically:
CompetencesThis course will provide the students with an understanding of statistical methods and knowledge of data analysis, which enables them to analyse data from essentially ALL fields of science. The students should be capable of handling uncertainties, fitting data, applying hypothesis tests and extracting conclusions from data, and thus produce statistically sound scientific work.
See Absalon for final course material. The following is an example of expected course literature.
Primary literature: Statistics - A Guide to the Use of Statistical Methods in the Physical Sciences, Roger Barlow.Additional literature: Statistical Data Analysis, Glen Cowan. Data Reduction and Error Analysis, Philip R. Bevington. Statistical Methods in Experimental Physics.
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Publication of new courses All planned PhD courses at the PhD School are visible in the course catalogue. Courses are published regularly.