Duration
Part : Operations Research : 15h Th
Part : Statistics : 15h Th
Number of credits
Lecturer
Part : Operations Research : Yasemin Arda
Part : Statistics : Cédric Heuchenne
Language(s) of instruction
English 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
Part : Operations Research
Operations research (OR) is a discipline that aims to solve complex real world decision problems using scientific approaches. Application areas of this discipline are various: transportation, production systems, telecommunication, administration, etc. The course gives an introduction to the most popular mathematical models and methods of operations research: linear programming, network models (minimal spanning tree problems and shortest path problems), project scheduling with PERT/CPM, decision making under risk and under uncertainty.
Part : Statistics
In this course, the methods studied in basic statistical courses are adapted to analyzing useful applied issues in Economics and Management (comprehension of a situation and its evolution, support for decision-making...).
Covered contents will be regression and/or classification analysis. Multivariate aspects and/or time dependencies (time series) will be developed.
Learning outcomes of the learning unit
Part : Operations Research
In relation with the Assurance of Learning process of HEC Liège, the learning objectives adressed in this course are:
- Strategy: This course will help students to demonstrate scientific precision and a critical mind.
- Implementation: This course will encourage students to adopt a holistic perspective when analyzing a complex management situation, and to take into account the different functions of the organization as well as the legal constraints and opportunities.
- Implementation: This course will exercise students in the ability to take advantage of data digitalization.
- Quality and Performance Control: This course will exercise students' ability to adopt a holistic perspective when analysing a complex management situation.
- Communication : This course will allow students to improve their proficiency in one foreign language.
- Adaptability: This course will encourage students to be curious and to show a scientific precision of academic level.
- To acquire a basic knowledge about the mathematical models of real world decision problems and the fundamental methods of OR.
- To be able to solve and interpret correctly the solutions of simple OR problems.
- To be able to recognize the situations where OR techniques can be used as decision making tools and to interpret correctly the conclusions which can be derived using these techniques.
Part : Statistics
C1. To acquire an overview of statistical problems met in the fields of Economics and Management.
P2. To be able to solve and interpret solutions of practical simple problems related to the theoretical part of the course.
P3. To be able to recognize situations where studied methods can be applied and what are their limitations in such particular situations.
More generally, on the program (master in management) point of view, the course addresses the following Key Intended Learning Outcomes:
- To understand, in management situations, the transversal tools of quantitative reasoning, information systems and project management.
- Developing a critical sense (arguing).
- Developing a transversal global vision.
Prerequisite knowledge and skills
Part : Operations Research
Basic notions of mathematics and statistics
Part : Statistics
Basic course in probability (cumulative distribution function, density, distribution, mean, variance, descriptive statistics, usual discrete and continuous univariate laws, multivariate normal) and statistical inference (sampling and estimation, confidence intervals, hypothesis testing). Equivalent to the content of the course: Probability and statistical inference STAT0067
Planned learning activities and teaching methods
Part : Operations Research
- Lectures
- Numerical exercises available on the virtual campus LOla
- Exercise session
Part : Statistics
/
Mode of delivery (face to face, distance learning, hybrid learning)
Part : Operations Research
Face-to-face course
Further information:
Lectures: The topics are covered in 5 * 3 lecture hours and are treated using numerical examples that are similar to the exercises of the final exam.
Self-study: Students are provided with some numerical exercises, their solutions, and multiple choice tests that they can use to practice their knowledge and to prepare themselves for the written exam as the chapters are treated during the semester.
Exercise session: At the end of the semester, an exercise session, before which students choose the exercises to be studied, is organized if possible.
Part : Statistics
Blended learning
Additional information:
Used methodology
A1. Classes: theoretical introduction and applications (quick overview of introductive videos and elementary notions, presentation of various methods, interpretation of their solutions, examples)
A1. Study and comprehension of the course material
A2. Supervised (possibly distance) software applications: the professor presents the software to the students and gives them exercises. Each student is expected to solve those exercises with the possible help from the professor.
Decomposition of the student workload
A1 Course (10h)
A2 Study (30h)
A2 Software applications (5h)
A2 Software training (12h)
Exam (2h)
Course materials and recommended or required readings
Part : Operations Research
Documents that can be found on the virtual campus Lol@:
1. Syllabus: The course notes and the PowerPoint presentations used during the lectures can be found on the virtual campus LOla. Students are wanted to be in possession of these notes during the lectures.
2. Exercises: Students are provided with some numerical exercises, their solutions, and multiple choice tests through the virtual campus LOla as the chapters are treated during the semester.
Recommended Reference:
Taha, H.A., 2007. Operations Research, An Introduction, eight edition, Pearson Prentice Hall.
Part : Statistics
The reference books allow for improving comprehension. The statements of exercises will be placed at the disposal of students (see the campus lola). Videos and exercises (on software or not) correspond to the material of the exam.
Advised books:
James G., Witten D., Hastie T. and Tibshirani R. (2013), An Introduction to Statistical Learning with Applications in R, Springer.
Wonnacott R.J. and Wonnacott T.H. (1990), Introductory Statistics for Business and Economics, New York, John Wiley & Sons (ISBN : 047161517X)
Simar, L. (2003), Statistique en Economie et Gestion, manuscript 248 pages, Institut de Statistique, Université Catholique de Louvain, Louvain-la-Neuve
Part : Operations Research
Exam(s) in session
Any session
- In-person
written exam ( multiple-choice questionnaire )
Further information:
1st session: A multiple-choice exam counts for 100% of the grade of the partim "Operations Research". Students obtain a grade over 10 for each partim and the final grade of the course is calculated as the sum of those grades. Students that fail the course "Quantitative Methods in Management" in the first session have to retake the second session exam of the partim "Operations Research" only if their first session grade for this partim is strictly less than 5 over 10.
2nd session: A multiple-choice exam counts for 100% of the grade of the partim "Operations Research".
Part : Statistics
E1/E2/E3. Final written and individual exam (during the weeks dedicated to the evaluations), covering the complete course material (30% dedicated to theory, 35% to applications and 35% to questions concerning softwares).
Work placement(s)
Organisational remarks and main changes to the course
Part : Operations Research
The course is given during the first semester.
The course is given in English.
Part : Statistics
Teaching language: English
Contacts
Part : Operations Research
Lecturer:
Yasemin ARDA (yasemin.arda@uliege.be)
Assistant:
Anisha MAHARANI (anisha.maharani@uliege.be)
Part : Statistics
Cédric HEUCHENNE, HEC-ULg Management School of the University of Liège, N1, local 309, email: C.Heuchenne@ulg.ac.be
Association of one or more MOOCs
Items online
Part : Operations Research
Campus LOl@
LOl@
Part : Statistics
course material
slides, videos, exercises