Statistical principles and biological data analysis

Teacher(s)

Schtickzelle Nicolas;

Language

French

Prerequisites

To follow this course, it is necessary to master the knowledge and skills developed in the course LBIO1282

Main themes

This course lays the foundations of the probabilities and statistics necessary for the analysis of biological data. The topics covered are: probability theory, principles of statistical inference and the main types of basic statistical analysis.
The practical work will allow practical application using the R software.

Learning outcomes

At the end of this learning unit, the student is able to :
1	Calculate and interpret the most common indicators of descriptive statistics, including graphs. Choose the appropriate theoretical distribution to model a random variable. Demonstrate an understanding of the principles of statistical inference. Formulate a hypothesis test in terms of null hypothesis and alternative hypothesis. Choose, perform and interpret a statistical analysis via a basic inference method (t test, analysis of variance, correlation and regression, Xhi²).

Content

With this course, students acquire the basic notions and principles of probability and statistical inference required for the scientific approach. By the end of the course, they are able to determine the important characteristics of an experimental design, to select and carry out the statistical analysis appropriate to the data, and to interpret the results and the possible limitations of the conclusions to be drawn.
The course begins with the basics of probability theory. It then details the principles of statistical inference (population vs sample; variables and distributions; sources of variation in the data; hypothesis testing, p-value and type I and type II errors; confidence interval…). The main types of basic statistical analysis are detailed and illustrated: t-test, one-, two- and three-way ANOVA, correlation and simple linear regression, count data (χ²).
The course is complemented by practical sessions on computer using the R software, which allow students to carry out in practice all the statistical analyses covered.

Teaching methods

Lectures and practical sessions in a computer room. The course is as interactive as possible: students are encouraged to take an active part and to ask their questions as they arise.

Evaluation methods

Open-book written exam consisting of multiple-choice questions, open questions and the practical solving of exercises with the R software. The exam is taken on Moodle, in a computer room on campus. Unless otherwise stated in the exam instructions on Moodle, only the UCLouvain computer in the computer room may be used to access the exam and the electronic documentation, and the use of artificial intelligence is prohibited.
As final marks must be rounded to a whole number, the mark is rounded up if the student has obtained at least 50% of the possible points for the "theoretical understanding" part and 50% of the possible points for the "practical solving of exercises" part, and rounded down otherwise.

Other information

A basic knowledge of the R software is required: students are expected to be able to create and modify R data sets independently. The course LBIO1282 is specifically designed to provide this knowledge; students who have not taken it beforehand must acquire these skills on their own, for example using the many resources freely available online.

Online resources

The course slides and the support material for the practical sessions are available on Moodle.
A full set of lectures recorded in a previous year is available on Moodle. The content of the course has nevertheless drifted over the years, so these recordings cannot be considered fully up-to-date material.
Introductory videos for the practical sessions are also available.

Teaching materials

• Les visuels du cours et le matériel en support aux travaux pratiques sont disponibles sur Moodle.

Faculty or entity

> BIOL