Degree in Electronic Engineering - Minor in Robotics

Become a qualified specialist focused in the field of robotics applied to sectors such as social, educational, therapeutic or care

Methods of Decision Analysis

Back to Syllabus

Description
Important decisions cannot be left to intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenges and make presentations that show we have done a thorough analysis and we have taken into account all the parameters that may affect our decision. We also need to make sense out of various sources of data, organize the inputs of experts and colleagues, and use state-of-the-art tools to provide analytical support to our reasoning. The objective of this course is to provide you with more effective tools for the decision making and discussing of our final decision. We will focus specially in the decision making under uncertainty and under risk. It is recommendable to brush up your Excel skills to solve large exercises with more confidence.
Type Subject
Optativa
Semester
Second
Credits
4.00

Titular Professors

Maria del Mar Roselló Canal
New Students service
Previous Knowledge

Basic knowledge about statistics and probability.
Basic knowledge about calculus.

Objectives

The learning outcome to be achieved by the students who attend this course is as follows:
- Be able to manage budgets for decision making, accounting for planning, budgeting, cost of products.

To achieve the above learning outcome, students should:

- Understand the different parts involved in a decision analysis process and the ideas in which they are based.
- Apply basic tools for solving decision analysis problems under certainty.
- Differentiate and solve decision analysis problems under uncertainty and under risk conditions.
- Introduce the student to the games theory.

Contents

-1. Introduction. How people make decisions involving multiple objectives.
-2. Aided decision maker with no uncertainty: SMARTER, EVEN SWAP and AHP.
-3. Introduction to probability.
-4. Decision making under uncertainty.
-5. Decision making under risk.
-6. Sequential decisions: probability trees.

Methodology

The training activities that are used in the course are:

- Presential lectures about basic concepts and procedures.
- lab work.
- Dedication to the lab work.
- Personal work and study.
- Evaluations

Evaluation

Evaluation activities which are used in the course are:

- Exams
- Continuous assessment controls and class exercises.
- Reports on exercises about cases.
- Participation in group dynamics.
- Reports and personal or group work.

Evaluation Criteria

The evaluation of the course consists of:

- Final exam (mandatory)
- Group work (mandatory)
- Individual work (mandatory)
- Midterm exam.
- Homework.
- Class attendance and participation.

Basic Bibliography

- Class slides and other materials (articles, papers...). Posted on 'eStudy'.
- 'Decision Analysis for management judgement'. Paul Goodwin and George Wright. John Wiley and Sons.

Additional Material