UE Informatics and statistics

This course is devoted to a refresher course in statistics and computer science.

The objective of the first part is to train students to master the statistical methods used in the life and health sciences.

• Master the description of collected data
• Master the choice of a decision support tool (statistical test) in adequacy with the experimental context
• Master the concepts of modeling, regression, estimation of regression parameters, model validation and prediction
• Master the correct interpretation of the results obtained and know how to communicate them.

At the end of this part, the students will be able to carry out a work requiring the statistical tool or to carry out a critical study of an article, a survey or experiment using usual statistical methods.

The second part of the course will provide students with a basic knowledge of programming in order to make them autonomous and to provide a skill that is sought after and appreciated in the different fields of biotechnology and health.

Statistic (12h)

• Anova
• Chi-squared test
• Correlation
• Linear regression
• Logistic regression

Computer science (12h) :

Introduction to computer science and programming using Python :

• A notion of computation
• Python programming language
• Testing and debugging
• Data structure

The pre-requisites required to follow this UE are:

• Summary Statistics
• Confidence intervals
• Hypothesis testing
• Independence t-test and paired t-test