Academic year
2022/2023 Syllabus of previous years
Official course title
Course code
ET0060 (AF:359944 AR:188958)
On campus classes
ECTS credits
6 out of 12 of STATISTICS
Surnames A-La
Degree level
Bachelor's Degree Programme
Educational sector code
1st Term
Course year
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This course is part of the “core educational activities” of the degrees in “Economics and Business” and “Economics of Tourism”. It is a single 12 credit compulsory course taught in two terms (one semester). It aims at introducing the statistical inference principles and tools most commonly used in economic empirical analysis. Estimation and hypothesis testing are illustrated for both the main parametric models and some relevant nonparametric applications (goodness of fit, independence, homogeneity). A relevant part of the course concerns those probability theory topics that are propedeutical to inferential techniques.
The course aims at providing an adequate knowledge of the main probabilistic and inferential tools used in the empirically based analysis and interpretation of economic phenomena.
The exam of Mathematics (ET0045) is a prerequisite for the exam of Statistics. Therefore, the topics covered by both Mathematics (ET0045) and Mathematics: prerequisites (ET0101) courses are assumed to be as known.
The full 12 credit course programme is:

1. Elementary probability calculus: definitions, axioms and property of the probability measure; conditional probability and stochastic independence; Bayes theorem.
2. Random variables: discrete and continuous variables; expected value and moments; quantiles; transformations of random variables; some relevant models of univariate random variables; bivariate discrete random variables, covariance and correlation; some relevant properties of multivariate random variables; sequencies of random variables, laws of large numbers, the central limit theorem.
3. Descriptive statistics: data collection and classification; frequency distributions; the main statistica indeces; graphical tools.
4. Statistical inference: parametric statistical model and sampling; point and interval estimation; hypothesis testing; goodness of fit, independence and homogeneity testing.
Boella M., Probabilità e Statistica per ingegneria e scienze. Pearson, II ed. 2020. Chapter 1 (escluso paragrafo 1.8); Chapter 2 (sections 2.5.3 , 2.6.2, 2.6.6. and 2.8 can be omitted); Chapter. 3 (sections 3.1.3, 3.1.4, 3.5 can be omitted); Chapter 4 (sections 4.4, 4.6, 4.7.2 and 4.8 can be omitted); Chapter. 5 (section 5.3.3 can be omitted); Chapter 6 (sections 6.2, 6.3.3 and 6.4.2 can be omitted); Chapter 7 (sections 7.3.3, 7.4.4, 7.4.5 and 7.4.6 can be omitted); Appendix A, Appendix B (section B.4.2 can be omitted), Appendix C, Appendix D (sections from D.6 to D.13 can be omitted)

Further readings (exercises and applications):
Grigoletto M., Ventura L., Statistica per le Scienze Economiche: Esercizi con Richiami di Teoria, Giappichelli, 1998
Pauli F., Trevisani M., Torelli N., Statistica: esercizi ed esempi, Pearson, 2008
The final assessment consists of a written test, followed by an oral interview (provided the written test has been succesfully passed). The written test is composed by multiple choice questions and lasts one hour. Examples of multiple choice questions are available on Ca' Foscari Moodle elearning platform.
The course is taught through presentation style lectures and classroom practicals integrated by the individual student activities. Students are supported by the indicated textbook and by the resources made available on Moodle platform.
Students are invited to enrol to the course at
written and oral
Definitive programme.
Last update of the programme: 05/09/2022