Students
Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
On campus
Duration
Not Available
Details
Program Details
Degree
Masters
Major
Business Management | Data Analysis | Statistics
Area of study
Business and Administration | Mathematics and Statistics
Education type
On campus
Course Language
English
Intakes
Program start dateApplication deadline
2026-03-01-
About Program

Program Overview


Advanced Data Analysis in Tourism Program Details ## Description The Advanced Data Analysis in Tourism course covers a range of topics and tasks, including: - Developing a hypothesis, research problem, and related questions. - Selecting the appropriate research methodology to address the problem. - Collecting data accurately aligned with the research problem. - Utilizing data to make informed decisions. - Analyzing quantitative (and qualitative) data to measure program effectiveness. - Presenting data to stakeholders and decision-makers to support programs and initiatives. Upon completion of the course, students will possess the necessary knowledge and skills to conduct advanced data analysis in the tourism industry. Furthermore, they will be capable of presenting their research findings to stakeholders and decision-makers, effectively communicating the insights derived from quantitative (and qualitative) data analysis.

Objectives The main objective of the "Advanced Data Analysis in Tourism" course is to equip students with a comprehensive understanding of quantitative methods used in conducting meaningful research within the field of tourism. Throughout the course, students will gain valuable insights into research intent and design, becoming familiar with various methodologies and techniques employed in data analysis. By exploring commonly used statistical methods, students will develop proficiency in data management and analysis. The course aims to cultivate students' abilities to effectively frame research problems and generate relevant research questions within the context of tourism. Additionally, students will be empowered to critically evaluate and interpret research findings, thereby becoming knowledgeable consumers of others' research within the field. By acquiring these skills, students will be equipped to make data-driven decisions and effectively contribute as tourism experts.

Teaching Mode The course will be taught in presence, utilizing optimized and adaptive methodologies tailored to the skills and interests of individual participants.

Learning Methods The course involves students working on individual dossiers that will be gradually compiled and enriched alongside the progress of the lessons. In the initial stages, through these dossiers, the teachers will have the opportunity to interact with the students on an individual basis, with the aim of understanding their prior knowledge levels in various subjects and setting both short-term and long-term goals. After completing the foundational activities, students will have the option to decide how many and which topics to "unlock" the progressively more advanced and complex content for, effectively choosing whether they prefer a more interdisciplinary preparation or a more focused approach on specific elements. Learning resources are released according to the course timetable, week by week.

Examination Information The following provides a breakdown of how each part contributes to the overall performance: - Take-home assignments: 30% - Final Exam: 70% The exam is planned to be carried out in written form (90 minutes of time).

Bibliography Compulsory: - Veal, Anthony James. Research methods for leisure and tourism: a practical guide. 4th ed.. Harlow: Financial Times Prentice Hall, 2011. Deepening: - Candela, Guido, Figini, Paolo. The economics of tourism destinations. Berlin: Springer, 2012. - Mazzocchi, Mario. Statistics for marketing and consumer research. Los Angeles: SAGE Publications, 2008.

Education The course is part of the Master of Arts in Economics and Communication in International Tourism (COM), Lecture, 1st year.

Additional Information - Semester: Spring - Academic year: Not specified - ECTS: 3.0 - Language: English

See More