Course Topics
- Review of basic statistical concepts: descriptive statistics, key definitions, classification of variables, frequency distributions, graphical representations, measures of central tendency and variability, random variables, sample statistics, confidence intervals and hypothesis testing. - Data: types, sources, and quality. - Sample surveys: objectives, phases, and potential sources of bias. - Sampling techniques: probabilistic vs. non-probabilistic sampling, advantages and disadvantages of different schemes. - Survey design: formulation and types of questions, modes of administration, scaling techniques, assessment of internal consistency. - Experimental studies and randomized controlled trials. - Introduction to multivariate analysis: contingency tables, covariance and correlation. - Linear regression and extensions: simple and multiple regression, model estimation and evaluation, model assumptions, inferential tools, qualitative predictors, interaction effects.

Teaching format
In-person lectures and exercises. Whenever possible, lectures will be structured to prioritize in-class time for discussions, and practical applications.

Educational objectives
Knowledge and understanding The student acquires the competence to understand and quantitatively analyse tourism phenomena in order to support business decision-making processes. The student acquires the ability to interpret and use synthetic indicators of interest for the economic and market development policies of tourist destinations as well as of individual enterprises in the sector. The student understands and uses statistical-quantitative methodologies for the description, monitoring and evaluation of problems characterising the tourism system. Autonomy of judgement Acquire the ability to select data and use appropriate information to describe a problem concerning the management of tourism enterprises as well as tourism associations and destinations Communication skills The Master's degree graduate will be able to communicate effectively in oral and written form the specialised content of the individual disciplines, using different registers depending on the recipients and the communicative and didactic purposes, and to evaluate the formative effects of his/her communication. Written and oral communication skills are particularly developed in the training activities carried out for the preparation of the Master's thesis, in the discussion of business cases and in interactive lectures involving group discussions and the comparison of individual analyses. Learning skills to identify thematic connections and to establish relationships between different cases and contexts of analysis to frame a new problem systematically and generate appropriate taxonomies. to develop general models from the phenomena studied.

Assessment
Written exam with practical exercises, review questions and interpretation of output from statistical softwares. Assessment criteria are the same for both attending and non-attending students.

Evaluation criteria
Assessment of Written final exam is based on the following criteria: correctness and completeness of answers, ability to read and interpret the data analysis output correctly, clarity of explanations and comments.