Duration
25h Th, 15h Pr, 10h Mon. WS
Number of credits
| Bachelor in mathematics | 5 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the second semester
Schedule
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
Look at the contents of the two parts.
1) Descriptive statistics
- Basic concepts: types of variables, percentages and rates
- Data representation and visualization (through tables and graphs)
- Summary statistics (through statistical parameters of location, scale and shape)
- Correlation analysis and linear regression
3) Data analysis
- Principal component analysis
- Clustering
Learning outcomes of the learning unit
Look at the learning outcomes of the two partims.
After the course, the student should be able to present, analyse and interpret data in an adequate manner, in particular using the statistical software package R.
Moreover, the student should be able to outline the advantages and disadvantages of the different techniques. He/she should also be aware of their limitations for practical use (based on their mathematicial properties).
Prerequisite knowledge and skills
look at the prerequisites for each part.
Basic concepts of calculus and linear algebra as well as matrix calculus.
Planned learning activities and teaching methods
Look at the information given for each part.
The learning activities are of three different types:
- theory lectures,
- practicals: written exercises and data analyses using the statistical software R.
Mode of delivery (face to face, distance learning, hybrid learning)
look at the information indicated in the partims.
Face-to-face course
Additional information:
Face to face
Recommended or required readings
Look at the informations given in the partims.
Platform(s) used for course materials:
- eCampus
Further information:
The lecture notes, the slides used during the theory sessions, and the exercices will be made available through eCampus.
Assessment methods and criteria
The final mark is a weighted mean computed on the two marks attributed to the assessments relative to the two parts of the course.
If the two separate marks are bigger than or equal to 5/20, then the weight of the result for part 1 is 20% and the weight for part 2 is 80%. However, if at least one of the two marks is below 5/20, the global mark will not exceed 9/20.
In case of absence at one part of the exam, the students will be given a mark of 0/20 for that part.
Exam(s) in session
Any session
- In-person
written exam ( multiple-choice questionnaire, open-ended questions )
Further information:
The final grade is obtained as follows:
- 60% corresponds to the result of a written examination (theory, MCQ, and exercises);
- 40% corresponds to the result of a practical examination (exercises and data analysis using the statistical software package R).
Work placement(s)
Organizational remarks
None
Contacts
See the information in the two parts of the course.
Arnout Van Messem
Assistant : Pauline Hrebenar