Duration
Part I: Descriptive statistics : 5h Th, 8h Mon. WS
Part 2: Complements of descriptive statistics : 11h Th, 8h Pr
Number of credits
| Bachelor of Science (BSc) in Computer Science | 3 crédits |
Lecturer
Part I: Descriptive statistics : Gentiane Haesbroeck
Part 2: Complements of descriptive statistics : Gentiane Haesbroeck
Coordinator
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
Basic concepts of descriptive statistics are taught, interpreted and mathematically justified in this course. More precisely, here follows the content of the course: - Statistical tables and graphics - Summary statistics (central tendency, dispersion and shape) - Correlation analysis and linear regression
Learning outcomes of the learning unit
After the course, the student should be able to present and interpret data in an adequate manner, in particular using the taught statistical software.
Moreover, the student should be able to outline the advantages and disadvantages of the different techniques. He/she should alos be aware of their limitaiton in practice, using their mathematicial properties.
Prerequisite knowledge and skills
Basic concepts of analysis and algebra, taught in secondary school.
Planned learning activities and teaching methods
The learning activities are of three different types: theory lectures, practicals on exercises and data analyses on the statistical software R (with goupr discussions) and personal work via some MCQ on line.
Mode of delivery (face-to-face ; distance-learning)
The courses and the tutorials are given face-to-face over the second semester according to a timetable available on Celcat.
The theory lectures are recorded by means of the podcast equipment installed in the lecture room. The students may visualize these recordings when they want.
Recommended or required readings
Lecture notes and the slides used during the lectures are on line on e Campus.
Assessment methods and criteria
The final grade is obtained as follows:
- 5% for the mean result obtained by the student at the multiple choice questions on line during the semester
- 95% of the grade comes from the exam with the following parts: exercises and data analyses (50% of the global grade), theory and new MCQ (45%).
A minimal grade of 5/20 is required in the different parts of the exam in order to succeed in the course. Additional details on that constraint will be outlines during the course at the beginning and at the end of the semester.
Work placement(s)
Organizational remarks
The organisation of the course is a bit different with resepct to last year. The student who repeat the course should pay attention to that.
Contacts
Professor: G. Haesbroeck
Assistant: S. Klenkenberg
Adaptation of teaching commitments following the COVID-19 pandemic for the May-June 2020 session
Teaching methods implemented : distance-learning
Following the decision of ULiège to organise the teaching on-line, the organisation of the lectures and practicals has been adapted as follows:
- Lectures on theory (2 lectures): videos recorded by the professor have been put on line on eCampus. A forum has been activated on eCampus in order for the professor to answer the questions of the students, directly during the time slot of the lecture,
- As far as the practical are concerned, the exercise sheets were made available before the time slot of the practical and a forum has been activted in order to answer questions on the spot. A correction, either in a written form or in video, is then made available on eCampus.
Assessment subjects
The content remains unchanged but has been precised (eg it has been explained that the theory will be evaluated differently as there is no possibility to ask for a simple restitution in a distance exam)
Assessment methods
The examn is organised on-line on eCampus on the day fixed in the official schedule (the duration is 4 hours). More precisely, the exam consists in three parts:
1) Questionnaire (MCQ and open questions) on theory (30 points)
2) Questionnaire (MCQ and short-answer questions) for basic exercises for which no explanation on the resolution will be required (15 points)
3) Data analysis (including with R) on eCampus. This parts counts for 50 points and some explanation on the resolution/interpretation will have to be up-loaded on eCampus (possibly with a photograph if some mathematical developments are required).
The 5 remaining points come from the MCQ performed during the semester.
Look at the additional information on line on eCampus.
Contacts
Adaptation of teaching commitments following the COVID-19 pandemic for the Aug-Sept 2020 session
Assessment subjects
The content is the same as in May/June.
Assessment methods
The parts of the exam devoted to the theory and the exercises of descriptive statistics (either basic or "long") are kept unchanged with respect to the May/June session.
However, the part devoted to the data analysis with the software R (30 points) is trasnformed into a personnal project that has to be written down during the summer.
More pecise information are given on line (on eCampus).