Quantification of Risk

This course unit is a natural continuation of the course unit “Description of Variability” presented in S3. Its objective is to provide the concepts and methods underlying modern biostatistics—namely, the quantification of randomness—which is a pervasive issue in the life sciences. This course will serve as an introduction to inferential statistics: parametric and nonparametric tests, linear regression, and analysis of variance. Particular attention will be given to the conditions under which these methods are applicable, as well as to the concepts of Type I and Type II errors, power, replication, and confidence intervals. Each concept will be illustrated using analyses of real and diverse biological data, contributing to the biostatistical literacy necessary to develop critical thinking regarding scientific results. Practical exercises using R will provide training in this standard programming language and the statistical tools implemented within it, while also helping students understand the material covered in class through the application of the methods presented.

2 math courses (S1, S2) + biostatistics course (S3)

Apply concepts and tools from mathematics, physics, chemistry, and computer science to address issues in the life sciences.

Select and apply theoretical tools that enable students to understand the results of experimental studies (such as statistical methods).

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