23313a Vorlesung

SoSe 20: V Data science for biologists: generalized linear modelling with R

Alexandre Courtiol

Hinweise für Studierende

Zusätzl. Angaben / Voraussetzungen

Open for Master students who took part in the course Introduction to R for statistical applications / Einführung in R für statistische Anwendungen or equivalent courses and open for PhD students (as far as there are places left by masterstudents) Schließen


Research projects involve collecting data and analysing them. The goal of this course is to teach you how to analyse most datasets on your own, and derive biological meaning from them. The course specifically focuses on Generalised Linear Models (or GLMs for short) – a family of statistical models that aim at describing the effect of different variables on one outcome of interest. The GLM is the most useful statistical tool the for most natural scientists. It is also the foundation of more complex methods such as AI algorithms. During this course we will study GLMs in depth, favoring practical considerations over mathematics. By the end of the course, you should be able to use a wide range of GLMs (i.e. LM, GLM, LMM, GLMM) and understand how to solve several common practical problems that show up when analysing real datasets. You will also learn how to translate a concrete biological problem into a GLM. We will work with the open source software R, which is the most popular software for data science in the world. Schließen

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