Hazard quantification

This course is a natural continuation of the "Description of variability" course presented in S3. Its aim is to provide the concepts and methods underpinning modern biostatistics, i.e. the quantification of randomness, which is an omnipresent issue in the life sciences. This course provides an introduction to inferential statistics: parametric and non-parametric tests, linear regression, analysis of variance. Particular attention will be paid to the conditions of application of these methods, as well as to the notions of type I and II errors, power, replication and confidence intervals. Each notion will be illustrated by analysis of real, diversified biological data, contributing to the biostatistical culture useful for training critical thinking with regard to scientific results. In addition to training in this reference language and the statistical tools it implements, practical work in R will enable students to understand what they have learned in class and apply the methods presented.

2 maths courses S1, S2 + biostatistics course S3

Mobilize the concepts and tools of mathematics, physics, chemistry and computer science in the context of life science issues.

Choose and apply theoretical tools that can be used to appropriate the results of experimental studies (e.g. statistical approaches).

Validate a model by comparing its predictions with experimental results, and assess its limits of validity.