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Course Topics
- Descriptive statistics: basic definitions, classification of variables, overview of sampling techniques, frequency distributions, graphical representations, measures of central tendency and variability. - Probability: introduction to probability, basic axioms, conditional probability, independence, Bayes' theorem, introduction to discrete and continuous random variables, expected values and variance, introduction to known distributions for discrete and continuous random variables, central limit theorem. - Inference: Sample statistics and sample distributions, introduction to estimators and their properties, point estimation, interval estimation (mean, proportion, difference between means, paired samples), hypothesis testing (mean, proportion, difference between means, paired samples) - Additional topics: analysis of bivariate dependencies between variables using correlation and regression, introduction to R software for descriptive analysis, statistical inference and regression.

Teaching format
Lectures and exercises.

Educational objectives
ILO (Intended Learning Outcomes) ILO 1 - Knowledge and understanding ILO 1.1. of descriptive statistics and how to summarise data: variables, frequency distributions, measures of central tendency and variability. ILO 1.2. of the concept of uncertainty and the basic elements of probability theory. ILO 1.3. of the basic concepts of sampling theory. ILO 1.4. of the basic concepts of inferential statistics: point estimation; confidence intervals; hypothesis testing; linear regression. ILO 1.5. of the relationships between variables and the basic concepts in hypothesis testing. ILO 1.6. Statistical terminology ILO 1.7. Software available for data analysis in the social sciences. ILO 1.8. The basics of the concepts of uncertainty, ambiguity and robustness in the context of data analysis. ILO 1.9. Fundamental methods and algorithms for data analysis, as well as machine learning methods. ILO 2 - Ability to apply knowledge and understanding ILO 2.1. basic concepts useful for following courses in economics, business and administration ILO 2.2. economic problems with multiple variables in a formalised way; ability to identify (optimal) solutions and interpret the results based on existing theories. ILO 2.3. defining economic problems in a formalised manner; finding (optimal) solutions and interpreting results based on existing theories. ILO 2.4. using mathematical tools for the analysis of static and dynamic models. ILO 2.5. mathematical problems and models and ideas for solving them. ILO 2.6. Use mathematical tools to analyse static and dynamic models with multiple variables. ILO 2.7. Statistical methods as useful research tools in the social sciences. ILO 2.8. Descriptive and inferential statistics to synthesise information, analyse and interpret relationships between variables, and test hypotheses. ILO 2.9. At least one statistical application to develop a simple data analysis. ILO 2.10. Understanding the basic principles of modern data analysis concepts, e.g. machine learning. ILO 3 - Independent judgement ILO 3.1. Identifying the most relevant variables to use when making decisions in complex situations; ILO 3.2. Report analytically and critically on information, empirical evidence and data in order to make appropriate economic and managerial decisions. ILO 3.3. Evaluate the most appropriate quantitative and qualitative analysis tools to assist the decision-making process. ILO 3.4. Use logical arguments and relate information and analytical tools to find solutions. ILO 4 - Independent judgement (Communication skills) ILO 4.1. Graduates of the degree course in Tourism, Sport and Event Management will develop communication and presentation skills to explain, argue and summarise, in a professional context, the complex interdisciplinary issues of the tourism, sport and events sector. ILO 4.2. The achievement of this objective will be assessed through written exams, individual and group assignments, and the final degree thesis. ILO 5 - Learning skills ILO 5.1. ability to analyse, critically evaluate and integrate data, information and experiences; ILO 5.2. ability to develop possible solutions to economic and management problems in the operational contexts relevant to the employment opportunities of graduates.

Assessment
Assessment (for attending and non-attending students): - Mid-term written examination (optional): Covers approximately half of the course topics. Contributes 40-50% to the final mark, depending on the content (ILOs 1, 2, 3, 4, 5). - Final written exam: Covers the remaining topics if the midterm exam was taken (50-60% of the final mark), or the entire course if the midterm exam was not taken (100% of the final mark) (ILOs 1, 2, 3, 4, 5). Note: the midterm exam mark will remain valid for one year.

Evaluation criteria
Both the mid-term and final written examinations consist of theoretical questions and exercises. They will be assessed on the basis of clarity of presentation, knowledge and understanding of statistical methods, ability to apply appropriate statistical procedures, and correctness of results. The ability to read and interpret R results will be essential for solving some exercises.

Required readings

Moore, S. D., Basic Statistics, Apogeo 2nd Edition, ISBN-10 8850331975

Lecture notes and exercises will be provided.

Supplementary readings
Borra, S., Di Ciaccio, A. (2008). Statistics. Methodologies for economic and social sciences. McGraw-Hill. Statistical analysis of data with R. Apogeo. Pasetti, P. (2002). Tourism Statistics. Carocci.