Academic year
2018/2019 Syllabus of previous years
Official course title
Course code
ET0060 (AF:253063 AR:147094)
On campus classes
ECTS credits
6 out of 12 of STATISTICS
Surnames Lb-Z
Degree level
Bachelor's Degree Programme
Educational sector code
1st Term
Course year
Go to Moodle page
This course is part of the “core educational activities” of the degree programs in “Economics and Business” and “Economics of Tourism”. It is a single 12 credit compulsory course taught in two terms (one semester). The course 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 Matematics (ET0045) and Mathematics: prerequisites (ET0101) courses are assumed to be known.
The program of the 12 credit course is the following:

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 - Prentice Hall. I ed. 2011. 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 in a two hour, open book written exam divided in two parts: multiple choice questions and exercises. The multiple choice questions aim at assessing the knowledge of the basic concepts and tools included in the program; the exercises require a higher level of abstraction and aim at assessing students’ ability of applying those concepts and tools to simple problems in the fields of economics and social sciences. Texts of several past exams, including synthetic solutions, are available on Moodle platform, in the area dedicated to this course (
The course is taught through presentation style lectures and classroom practicals integrated by the individual student activities. Students are supported by the indicated textbooks and by the resources made available on Moodle platform (slides, exercises, past exams).
Students are invited to enrol to the course at the e-learning platform ( ).
This programme is provisional and there could still be changes in its contents.
Last update of the programme: 10/04/2018