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Libera Università di Bolzano

Metodi di ricerca e disegno sperimentale

Semestre 2 · 31002 · Corso di laurea magistrale in Management del Turismo · 6CFU · EN


The course offers a comprehensive introduction to empirical research methods, covering both qualitative and quantitative approaches. It guides students through the entire research process, from designing studies and developing questionnaires to applying appropriate sampling techniques and collecting data. Key statistical topics include descriptive statistics, data visualization, statistical inference, bivariate analysis such as correlation and contingency tables, linear and logistic regression models and their extensions. Basic concepts of statistical programming are also introduced, with a focus on practical applications using R.

Docenti: Alessandro Casa, Dimitri Storai

Ore didattica frontale: 36 Prof. Alessandro Casa
Ore di laboratorio: 12 Dott. Dimitri Storai
Obbligo di frequenza: _

Argomenti dell'insegnamento
- 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.

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

Obiettivi formativi
INTENDED LEARNING OUTCOMES (ILO) ILO 1: KNOWLEDGE AND UNDERSTANDING ILO1.1 The student acquires the competence to understand and quantitatively analyse tourism phenomena in order to support business decision-making processes. ILO 1.2 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. ILO 1.3 The student understands and uses statistical-quantitative methodologies for the description, monitoring and evaluation of problems characterising the tourism system. ILO 2: AUTONOMY OF JUDGEMENT ILO 2.1 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 ILO 3: COMMUNICATION SKILLS ILO 3.1 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. ILO 4: LEARNING SKILLS ILO 4.1 To identify thematic connections and to establish relationships between different cases and contexts of analysis ILO 4.2 To frame a new problem systematically and generate appropriate taxonomies. ILO 4.3 To develop general models from the phenomena studied.

Modalità d'esame
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.

Criteri di valutazione
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.

Bibliografia obbligatoria

Agresti, A. Statistical Methods for the Social Sciences. Pearson, 2018.

For each topic, slides and exercise sheets will be provided by the professor.



Bibliografia facoltativa

James, G., Witten, D., Hastie, T., Tibshirani, R. An

Introduction to Statistical Learning with Applications in R.

Springer, 2013. Freely available at http://wwwbcf.

usc.edu/~gareth/ISL/

Watkins, J. C., (2023) An Introduction to the Science of Statistics: From Theory to Implementation. Preliminary Edition. https://www.math.arizona.edu/~jwatkins/statbook.pdf

Azzalini, A. and Scarpa, B. Data analysis and data mining: An introduction. OUP USA, 2012

Moore, D.S., McCabe G.P., Craig, B.A. Introduction to the Practice of Statistics., New York, WH Freeman, 2009. 




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Obiettivi di sviluppo sostenibile
Questa attività didattica contribuisce al raggiungimento dei seguenti Obiettivi di Sviluppo sostenibile.

3 8 10 13

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