Mercè Roca

The course introduces the basic concepts of data analysis and statistics. It provides a review of the main tools used for data description and how to perform basic statistical analysis. The course is self-contained and requires only a minimal mathematical knowledge for data processing and data analysis, which is also reviewed.

It offers students the opportunity to perform a series of activities during the trip to and experience the implementation of an international business plan in a foreign country.

Visits to international companies and interviews with their managers will be organized so that students learn about the organizational structure and resources characteristic to international business operations.

The internship takes place in organizations that have a collaboration agreement with BSM and ESCI-UPF and has a duration of one trimester.  The assigned tasks of the internship are the result of a consensus between the organization that receives the student and the Master’s management team. The objective is that the tasks meet a real need of the firm. An internship coordinator supervises that the assigned tasks are relevant to the Master’s specific competences and objectives.

Application of statistical techniques to the market. Multivariate dependence methods. ANOVA, multiple progression, conjoint analysis, discrete choice models.

Students will be able to properly apply multivariate methods for dependent variables, analyse the results and present a suitable report of findings

• The marketing research process.
• Qualitative and quantitative information gathering techniques.
• Sources of information for the analysis of international markets.
• International marketing research: country, industry and motivational reports.

The Master's Thesis (hereinafter MT) constitutes a key output of the learning process of the Master of Science in Sustainability Management (MScSM), as the student delves into a topic of interest and further develops the skills and abilities acquired. The MT is an original project presented in the form of written work that integrates the knowledge, competences, and skills acquired along the MSc. The MT is a 9 ECTS course to be evaluated once the student has completed the master courses. The MT requires a total of 225 hours of individual student time workload. The work can be done in groups of up to 3 members.

Statistical inference. Point and interval estimates. Hypothesis testing, analysis of variance and contingency tables. Simple linear regression modelling. Sampling principles.

Learn how to infer population properties (estimating a parameter, deciding the truth of a statement, etc.) from the information gathered from a subset or sample.