110321 - QUANTITATIVE METHODS II

Subject type: Mandatory

Coordinator: Joan Triadó Aymerich

Trimester: Second term

Credits: 6

Academic year: 2025

Teaching course: 3

• English

English: for Theory and Laboratory sessions

Subject framed in the matter of operative investigation. The course aims to introduce students to the basic concepts, principles and foundations of simulation techniques, game theory, and Markov chains for analysis and decision making in all contexts. Finally, concepts related to business applications are introduced in the context of the digital transformation of the company, such as the big data and the Business intelligence.

The final grade is the weighted sum of the grades for the learning activities:

Q = 0.25 Pex1 + 0.35 Pex2 + 0.10 ExiPar + 0.30 Lab

Important: all activities are mandatory. To pass the course, the student must attend (or submit) all the activities!

Remarks on Recovery

The theory part of the subject (Pex1 and Pex2) is recoverable. The other parts are not recoverable. For students attending the resit exam their grade (Pex1 and Pex2) will be the one obtained in this test and their final grade (Q) will be calculated with the formulas detailed above and in no case will it exceed 7.

Rules for carrying out the activities

Remarks:

To pass the assessment activities, students must demonstrate the MECES Level - 2:

• (point c) have the ability to collect and interpret data and information on which to base their conclusions, including, where necessary and relevant, reflection on issues of a social, scientific or ethical nature in the field of their field of study

• (point e) know how to communicate to all types of audiences (specialized or not) in a clear and precise way, knowledge, methodologies, ideas, problems and solutions in the field of their field of study;

• (point f) be able to identify their own training needs in their field of study and work or professional environment and to organize their own learning with a high degree of autonomy in all types of contexts

For each activity, teachers will be informed of the particular rules and conditions that govern them

The one-to-one activities presuppose the student's commitment to carry them out individually and without any collaboration with other people. All activities in which the student does not comply with this commitment to individuality will be considered suspended (grade 0), regardless of their role (sender or receiver) and without this excluding the possible application of other sanctions in accordance. with the current Disciplinary Regime.

Likewise, the activities to be carried out in groups presuppose the commitment on the part of the students who make it up to carry them out within the group and without any kind of collaboration with other groups or people who are alien (group individuality). All activities in which the group has not respected this commitment regardless of its role (sender or receiver) and without this excluding the possible application of other sanctions in accordance with the current Disciplinary Regime will be considered suspended (rating 0).

In the case of activities that can be done in groups, when in any of them the commitment of group individuality is not respected and / or fraudulent means are used in its accomplishment, the qualification of the activity will be, for all members of the group, of 0 points (Activity Note = 0) and without this excluding the possible application of other sanctions in accordance with the current Disciplinary Regime.

Any activity not delivered will be considered a suspended subject.

It is up to the teachers to accept or not deliveries outside of the indicated deadlines. In the event that these late deliveries are accepted, it is up to the teacher to decide whether to apply any penalty and its amount.

Hillier, Frederick S .; Lieberman, Gerald J. (2010). Introduction to Operations Research. McGraw-Hill

Jared Dean (2014). Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners. Wiley, ISBN 978-1-118-92069-5.

Game Theory: An Introduction by Steven Tadelis Princeton University Press; 1st Edition edition January 6, 2013

Probability, Markov Chains, Queues, and Simulation: The Mathematical Basis of Performance Modeling by William J. Stewart; Princeton University Press (July 26, 2009)