Inferential statistics

Duration

20h Th, 20h Pr

Number of credits

Lecturer

Samuel Nicolay

Language(s) of instruction

French language

Organisation and examination

Teaching in the first semester, review in January

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course covers fundamental concepts of probability and statistical inference.
The main topics include:

• Introduction to probability theory and the concept of random variables.
  
  
• Statistical models and parametric estimation, with a particular focus on the mean parameter.
  
  
• Conducting and interpreting classical parametric tests.
  
  

Learning outcomes of the learning unit

At the end of the course, students will be able to understand the basic concepts of probability. The students will understand the notion of statistical models and they will master the basic principles of the estimation in a parametric model (principally inference on the mean). They will be able to perform and interpret basic parametric tests. 

 

Prerequisite knowledge and skills

A good understanding of logic and calculus is required. In particular the courses of general mathematics and descriptive statistics are prerequisites for comprehension of this course. The ability to reason abstractly is an asset.

Planned learning activities and teaching methods

The inferential statistics course is organized around two main components.

The first component is theoretical and delivered by the professor in a lecture hall to all students. Attendance at lectures is optional. Students who choose to attend are expected to respect basic rules of punctuality, silence, and courtesy, which includes avoiding unnecessary movement during the session. Some students may prefer to study the material independently at home, using lecture materials alongside reference texts; this choice is fully respected.

The second component consists of tutorial/problem-solving sessions led by teaching assistants. Attendance at these sessions is strongly recommended, as they provide essential preparation for the examinations. Students are also expected to respect basic rules of punctuality, silence, and courtesy during these sessions, avoiding unnecessary movement.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Further information:

Teaching in inferential statistics is primarily conducted in-person. A detailed schedule will be communicated to students on the first day of classes. This schedule may change during the year, so students are advised to check updates regularly.

Tutorial/problem-solving sessions aim to illustrate and complement the concepts presented in lectures. The goal is not to mechanically solve exercises, but to foster understanding and critical thinking. Students are expected to review the corresponding theoretical material before each session; this requires little time and greatly facilitates learning.

Course materials and recommended or required readings

Platform(s) used for course materials:
- eCampus
- MyULiège


Further information:

A PDF of the lecture slides will be available on eCampus. Students can supplement these notes during the lecture, which will be even more effective if the slides are briefly reviewed beforehand.

The exam material corresponds to the content of these slides, complemented by the professor's comments, additions, and demonstrations, which form a significant portion of the course material.

Tutorial exercises will also be posted on eCampus. Additional exercises are generally provided.

Exam(s) in session

Any session

- In-person

written exam ( multiple-choice questionnaire, open-ended questions )


Further information:

The assessment consists of two components:

• A part focused on theory and its immediate applications.

• A part focused on solving exercises.
  
  

• Students must bring their ULiège student card and a valid identity card.
  
  
• Students must bring writing materials: rough sheets and blank sheets.
  
  
• Students should bring any authorized tables and forms.
  
  
• Examinations are governed by university regulations, available on the Faculty of Science website.
  
  
• Students whose first language is not French are allowed to use a dictionary, subject to prior approval by the professor.
  
  
• Use of a basic calculator is permitted during assessments.
  
  

Work placement(s)

Organisational remarks and main changes to the course

Website of the Faculty of Science:
www.sciences.uliege.be

Contacts

S. Nicolay
Institut de Mathématique (B37), Grande Traverse, 12, Sart-Tilman, 4000 Liège.
E-mail: S.Nicolay@uliege.be

P. Hrebenar Pauline
E-mail : Pauline.Hrebenar@uliege.be

A. Kinable
E-mail : Antoine.Kinable@student.uliege.be

P. Stas
E-mail : Pierre.Stas@uliege.be

 

Attention:

* Please use only your ULiège email address (XXX@student.uliege.be) for all communication with the teaching staff.

* Use the title "Student Bio,..." and the course title in your emails.

* Be clear, concise and polite in your messages.

For questions related to the course material (clarifications on lectures or tutorials), discussion forums are available on the eCampus course platform. To help as many students as possible and encourage peer support, we will respond to these types of questions mainly via the forums. Feel free to use this space to ask questions and to respond to other students. The teaching staff will moderate the forum and provide additional information when necessary.

You may, of course, contact us for any questions.

Association of one or more MOOCs