Methods of Analysis
Name: Methods of Analysis
Code: GES13657M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Management
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Sustainable Development Goals
Learning Goals
With this course unit, students should:
-Be able to analyse real data from a statistical point of view;
-Understand theoretically what linear regression analysis is;
-Know and master the techniques of estimation and verification of assumptions, interpret results, and make inferences;
-Be able to model optimisation problems;
- Master quantitative approaches to solving economic and management problems;
- Know how to use different software in depth and interpret results.
-Be able to analyse real data from a statistical point of view;
-Understand theoretically what linear regression analysis is;
-Know and master the techniques of estimation and verification of assumptions, interpret results, and make inferences;
-Be able to model optimisation problems;
- Master quantitative approaches to solving economic and management problems;
- Know how to use different software in depth and interpret results.
Contents
1. Simple regression analysis
2. Multiple regression analysis
3. Other topics of linear regression analysis
4. Free and constrained optimization
5. Linear optimization
6. Empirical modelling
2. Multiple regression analysis
3. Other topics of linear regression analysis
4. Free and constrained optimization
5. Linear optimization
6. Empirical modelling
Teaching Methods
The topics of the program are taught in e-learning or in-person sessions, where, despite being theoretical sessions, it is privileged the application of concepts and principles to problems of economics and management, and in particular of agribusiness, as well as the use of computer resources. The Moodle platform is used in the communication between students and the teacher and is also available online, providing support documents for the course.
The use of Artificial Intelligence is encouraged in accordance with Order No. 34/2026 ? Guidelines for the Use of Artificial Intelligence (AI) in the Teaching, Assessment and Learning Process at the University of Évora.
The use of Artificial Intelligence is encouraged in accordance with Order No. 34/2026 ? Guidelines for the Use of Artificial Intelligence (AI) in the Teaching, Assessment and Learning Process at the University of Évora.
Assessment
In terms of assessment, students may choose the **Continuous Assessment** regime, which consists of four individual assignments, weighted at 15%, 20%, 20%, and 15%, respectively, and a final test, weighted at 30%.
Students may alternatively choose the Final Assessment regime, under the terms and access conditions established in the Academic Regulations of the University of Évora (RAUE) for each assessment period, in which the examination accounts for 100% of the final grade.
In cases where there are doubts regarding the assessment, students may be required to orally discuss and defend their assignments, in accordance with Order No. 216/2026, concerning the prevention of academic fraud, particularly in situations involving suspected improper use of Artificial Intelligence tools or other forms of academic misconduct.
Students may alternatively choose the Final Assessment regime, under the terms and access conditions established in the Academic Regulations of the University of Évora (RAUE) for each assessment period, in which the examination accounts for 100% of the final grade.
In cases where there are doubts regarding the assessment, students may be required to orally discuss and defend their assignments, in accordance with Order No. 216/2026, concerning the prevention of academic fraud, particularly in situations involving suspected improper use of Artificial Intelligence tools or other forms of academic misconduct.
Accreditations and Certifications
