Quantification of risk

This course is a natural continuation of the course "Description of Variability" presented in S3. Its objective is to provide the concepts and methods on which modern biostatistics are based, namely the quantification of randomness, which is a ubiquitous issue in the life sciences. This course will serve as an introduction to inferential statistics: parametric and non-parametric tests, linear regression, and analysis of variance. Particular attention will be paid to the conditions for applying these methods, as well as to the concepts of type I and II errors, power, replication, and confidence intervals. Each concept will be illustrated with analyses of real and diverse biological data, contributing to the biostatistical culture that is useful for developing critical thinking with regard to scientific results. Practical work using R will provide training in this reference language and the statistical tools implemented in it, as well as an understanding of what has been seen in class through the application of the methods presented.

2 credits in mathematics S1, S2 + credits in biostatistics S3

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

Select and implement theoretical tools that enable the results of experimental studies to be understood (e.g., statistical approaches).

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