Study-unit INTRODUCTION TO STATISTICS IN TOURISM
| Course name | Economics of tourism |
|---|---|
| Study-unit Code | 20099409 |
| Location | ASSISI |
| Curriculum | Comune a tutti i curricula |
| Lecturer | Silvia Pandolfi |
| Lecturers |
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| Hours |
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| CFU | 9 |
| Course Regulation | Coorte 2022 |
| Supplied | 2023/24 |
| Supplied other course regulation | |
| Learning activities | Caratterizzante |
| Area | Statistico-matematico |
| Sector | SECS-S/01 |
| Type of study-unit | Obbligatorio (Required) |
| Type of learning activities | Attività formativa monodisciplinare |
| Language of instruction | italian |
| Contents | The course aims at enabling students to critically understand quantitative reports and provides the first notions to correctly perform a statistical analysis of data with particular attention to touristic phenomena. The main knowledge acquired will be: a) the basic elements of descriptive statistics: population, types of characters, sample surveys, frequency distributions, mean, variance, dependence and association between two characters; b) the basic elements of time series analysis with particular reference to the components of the series and the estimation of the seasonality; c) the basic elements of inferential statistics: notions of probability, random sample, point or interval estimate, hypothesis tests. Students who successfully complete the module will be able to critically understand the statistical reports related to tourism as well as to perform some simple analysis and to construct appropriate syntheses of the data. |
| Reference texts | G. Cicchitelli, P. D’Urso, M. Minozzo. Statistica: Principi e metodi, Pearson, 2017. P. Pasetti, Statistica del turismo, Carocci editore, 2015. |
| Educational objectives | First notions of statistical data analysis with a particular view on tourism phenomena. The course is aimed at providing the main notions about Descriptive and Inferential Statistics. Descriptive statistics: Preliminary concepts; Comparisons between statistical quantities; Statistical distributions; Graphical tools; Means; Variability and concentration; An overview of the characteristic constants; Dependence analysis; Regression analysis; Correlation. Inferential Statistics: Probability; Random variables; Some specific probabilistic models; Sample distributions; Point estimation; Interval estimation; Hypothesis testing. |
| Prerequisites | Notions acquired in the first module of Principles of Mathematics. |
| Teaching methods | Six hours of lectures and practical exercises every week. |
| Other information | |
| Learning verification modality | Compulsory written exam; oral exam on an elective basis. |
| Extended program | Descriptive statistics Preliminary concepts: essential terminology; measurement of variables; data collection: sample surveys; data matrix. Comparison of quantities: differences and statistical ratios: the main statistical ratios; statistical ratios of particular interest for tourism studies. Statistical distributions: disaggregated statistical distributions; frequency distributions; relative frequencies; cumulative frequencies; frequency distributions with data grouped into classes with and without class totals; bivariate and multivariate distributions; time series; spatial series. Graphical tools: graphics for distributions of quantitative variables: bar chart; histogram; box-plot; graphical representation for nominal variables: pie charts; tri-dimensional graphics; graphical representation of time series and spatial series. Means: arithmetic mean; geometric mean; weighted mean; median; quartiles and quantiles; central value; mode. Variability: variability; standard deviation; range; interquartile range; percentage variability indices; concentration; G and R concentration indices; Lorenz curve. Asymmetry indices: symmetry and asymmetry; asymmetry indices; box plot. Index numbers: fixed-base and mobile-base index numbers. Mean percentage change. Index of Laspeyres. Bivariate distribution analysis: Dependence analysis; Regression analysis: least square method for the regression parameters; Correlation. Statistics for Tourism: The tourism phenomenon: who is the tourist; Sources of statistical data relating to tourism; indirect measures of tourism phenomena. Time series analysis: components of the time series; models for time series analysis; estimation of the seasonality; graphical representation of time series and spatial series. Inferential Statistics: Probability: random experiments; sample space and events; basic set theory operations; probability; interpretation of probability. Random variables: discrete random variables; mean and standard deviation; continuous random variables; mean and standard deviation; standardized random variables. Some specific probabilistic models: Bernoulli distribution; binomial distribution; Poisson distribution; normal distribution; standardized normal distribution; approximation of the binomial distribution through the normal distribution. Sample distributions: random sample; parameter; statistical inference: parameter estimation and hypothesis testing; sample statistics; sample distribution of the mean for normal populations and with large sample size (central limit theorem). Parameters estimation: estimator; properties o estimators; interval estimation. Hypothesis testing: statistical hypotheses; Testing hypotheses on the mean; errors of first and second type and their probabilities. |