Duration
35h Th, 25h Pr
Number of credits
Lecturer
Coordinator
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This course is subdivided in two parts. In the first part, we start by giving an introduction to descriptive statistical methods which permit to summarize a data set either graphically or numerically. Then we turn to inferential statistics, the basis of scientific reasoning, which consist in making conclusions on a population from a random sample drawn from it. The second part of the course tackles more advanced statistical methods, like linear regression, one-way analysis of variance, survival analysis, contingency tables and non-parametric techniques. During practical sessions, the student will be trained in the treatment of data applications encountered in practice.
The statistical software R, as well as various packages are viewed throughout the course. During the lectures, the statistical analysis methods presented in therotical courses will be applied on real databases. Special attention will be given to the interpretation of the results provided by the software.
This course also includes two 2-hour sessions devoted to critical reading of scientific articles.
Learning outcomes of the learning unit
The course is intended to get students familiar with statistical problems and data analysis. Emphasis is placed on the scientific reasoning rather than on the mathematical aspects of statistics or the formula to use. Students should have a sufficiently solid knowledge in statistics for the years ahead, and in particular for the thesis they have to write at the end of their curriculum.
In particular,
- to become familiar with the use of R
- understand and learn to criticize the statistical methodology of a scientific article
Prerequisite knowledge and skills
The mathematical training received in bachelor years is sufficient to take the course. As already mentioned, emphasis is placed the potential of statistical methods in experimental design and scientific research.
Corequis: STAT1001-1 and STAT0420-1 or equivalent.
Planned learning activities and teaching methods
Training exams will be available on eCampus.
Please take with you the lecture notes, a PC with R/Rcmdr installed.
Mode of delivery (face to face, distance learning, hybrid learning)
Face-to-face course
Further information:
Face-to-face course
Additional information:
The lectures take place in the first quadrimester.
Tutorals available before the courses. Exercices on eCampus. Scientific articles will also be available for critical reading.
Course materials and recommended or required readings
Platform(s) used for course materials:
- eCampus
- MyULiège
Further information:
Slides will be available to the students.
Textbook -Statistiques épidémiologie (4ème édition), Th. Ancelle - Introduction to Statistical Analysis. W.J. Dixon et F.J. Massey. McGraw Hill, 1983
Slides, tutorials, book of exercices and databases will be available to the students
Exam(s) in session
Any session
- In-person
written exam
Further information:
Exam(s) in session
Any session
- In-person
written exam ( multiple-choice questionnaire )
Additional information:
The final exam takes place on computer on eCampus during the January session. It consists of two parts:
- Theory and reflection questions and questions on the articles seen in the course (in the form of MCQs)
- Solving exercises using R/Rcmdr
The weighting of the overall mark is 50% for each of the two parts (MCQs and Exercises) BUT an insufficient mark in one of these two parts (< 8/20) will automatically result in this insufficient mark being taken as the overall mark.
Work placement(s)
Organisational remarks and main changes to the course
Contacts
* Anne-Françoise DONNEAU (Professor), Quartier Hôpital, Avenue Hippocrate, 13 - Bât 23, 4000 Liège - Belgique. Tél: 04-366.47.90 Email: afdonneau@uliege.be
* Bernard VRIJENS (Invited Professor) - CHU Sart Tilman (B23), 4000 Liège. Tél: 04-366.33.40 - Fax: 04-366.25.96 Email: ndardenne@uliege.be
* Assistant : Nadia DARDENNE, Quartier Hôpital, Avenue Hippocrate, 13 - Bât 23, 4000 Liège - Belgique - Tél: 04-366.33.40 - Email:ndardenne@uliege.be