110321 - QUANTITATIVE METHODS II

Subject type: Mandatory

Coordinator: Julián Horrillo Tello

Trimester: Second term

Credits: 6

Catalan/Spanish/English

Catalan: Theory sessions

English: 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.

At the end of the course the student must be able to:

• LO2: Apply the different simulation techniques: continuous and discreet and the tools for decision making (CE 22).
• LO3: Identify tools for optimizing models that have a single objective or several objectives (CE 22).
• LO4: Apply the basic knowledge of the techniques and models of operational research and be able to project them to applications of the industrial organization (CE 22).
• LO6: Design appropriate models for problems related to industrial organization (EC 22).
• LO7: Specify and estimate statistical and econometric models to support decision-making in the different functional areas of the company (EC 22).

All the theoretical concepts of the subject will be exposed in theory classes (large groups) and / or in laboratory sessions (small groups). In these classes, and at the discretion of the teachers, exercises and problems of a more practical nature will also be solved. Likewise and always at the discretion of the teachers, students may be asked to solve, individually or in groups, short problems and / or exercises. These activities, which due to their optional nature and brevity, will serve the student as an instrument of self-assessment of their achievement of the contents of the subject and can be used by the teacher to assess it.

 The more practical concepts and everything that can essentially be considered the practical application of the theoretical concepts will be worked on in small (laboratory) groups. In the sessions scheduled for this purpose, the appropriate tools will be given to solve the scheduled activities. Sometimes students will have to complete them during the time of autonomous learning. Whenever deemed appropriate, totally optional activities will be made available to students to help them prepare and prepare for the compulsory ones.

Students are provided with a series of highly practical activities (short exercises, problems...) that form the basis of the subject's learning activities. The students will have to solve these activities, often off-site, following the teachers' instructions and they will also be worked on in class, either as examples in the theory sessions or in the laboratory sessions. These activities will be compulsory, and will be essential to achieve the theoretical-practical knowledge of the subject.

In order to gather evidence of the achievement of the expected learning outcomes, the following evaluative activities are carried out:

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

Q = 0.35 Pex1 + 0.25 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 optional for teachers to accept or not deliveries outside the deadlines indicated. In the event that these late deliveries are accepted, it is up to the teacher to decide whether to apply a penalty and the amount of this.

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.

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

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