Descriptive statistics

Duration

35h Th, 15h Pr

Number of credits

Lecturer

Valérie Henry

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

The course presents the main theories in descriptive statistics and data analysis. It describes the main graphics of an univariate data set as well as the main measures of location, dispersion and skewness. We also talk about bivariate data sets.

Learning outcomes of the learning unit

Strategy : The course will allow students to analyse the financial and economic context of a complex situation. The course will allow students to demonstrate scientific precision and a critical mind in the analysis of a complex situation. Implementation : The course will train the student to capitalize on the characteristics of a more and more digitalized world when confronted with a complex situation. Communication : The course will allow students to communicate efficiently, internally and externally, about a company, organization or project Adaptability : The course will encourage students to be aware of the societal, economic, political and environmental issues in their studies as well as in their professional life. The course will encourage students to be curious and to show a scientific precision of academic level in their studies as well as in their professional life.
More specifically, the course wants to give to the students the important tools they need to critically analyse situations related to statistics. This is essential in order to understand the further main concepts of probability theory, estimation theory and tests theory

Prerequisite knowledge and skills

There is no prerequisities.

Planned learning activities and teaching methods

Many exercises will be done during the lessons. Some e-learning sessions will be devoted to the use of Excel and R in statistics.

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

Blended learning


Additional information:

The course takes place during the second part of the year. 50 hours will be devoted to lessons at the university, the other ones will be used by students to do works at home.

Lessons will be face-to-face if possible, completed by the contents of Lol@. If the system is available, lessons will be live broadcasted and recorded.

Recommended or required readings

The reference work is "Pratique de la statistique descriptive" G.Haesbroeck et V.Henry. It is available in the Edipac sold by Point de Vue. The slides showed during the classes and the exercises will be available on the Campus Lol@. These are essential to attend to the classes.

Exam(s) in session

Any session

- In-person

written exam

- Remote

written exam ( open-ended questions )


Additional information:

The evaluation will take place in June. The written exam will be about theory and exercises, the practical exam on the computer will be online and assess the use of Excel and R in statistics and the linked theory.

The written exam represents three quarters of the final note.

Work placement(s)

Organisational remarks and main changes to the course

If possible, courses are recorded with podcast system and put on the private website for students but it is not sure that every course will be recorded.

Contacts

Teacher : Valérie Henry V.Henry@ulg.ac.be

Bât B31, bureau 3.48 4000 Liège Sart-Tilman.
Assistant : Élodie Bebronne elodie.bebronne@uliege.be
Bât N1, room 334

Association of one or more MOOCs

Items online