Università degli Studi di Napoli "Parthenope"

Teaching schedule

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Belonging course: 
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Year of study: 
Second semester
Hours of front activity: 



Course description

The teaching aims to provide the necessary skills to understand and apply the basic statistical tools needed to analyse the main elements of a statistical collective. The student should be able to use the main means of univariate and multivariate statistics to economic issues. The student will be introduced to Excel software.

Expected learning outcomes:
knowledge and understanding: The student must demonstrate that he/she understands the fundamental concepts of the discipline and that he/she is able to use the main tools to analyse problems in economics. The student needs to be able to recognise the typology of the statistical characters to be analysed, to be able to organise data into frequency distributions and to calculate the main statistical indices of synthesis, variability, and shape. The ability to deal with the study of the association between two statistical characters is required.

Applying knowledge and understanding: The student must construct data matrices from external sources (archives and surveys) and manage them using the software. The student should correctly interpret the outputs provided by statistical software. The student should be able to understand the interdependence between economic phenomena.

Making judgements: The student must demonstrate that he/she has developed the necessary skills to evaluate economic phenomena independently. In particular, the student will be able to describe the distribution of a statistical variable, make comparisons between several distributions and assess the association between economic phenomena.

Communication: The student must answer the questions in the oral test clearly and comprehensively. The student must also be able to use the technical language of the discipline to explain the topics covered in the course. The student must transmit to others the principles, contents, and applicative possibilities of the topics learnt in the course. The ability to contextualise the economic phenomenon analysed and highlight the purpose of the statistical tools is required.

Lifelong learning skills: The student must demonstrate an adequate capacity for learning and autonomy in exploring the topics covered in the course. During the course, in-depth study hints are provided through exercises to be carried out autonomously and checked by the professor.


No prerequisites


Part I (24 HOURS):
The detection of statistical phenomena. Classification of statistical characters. Distribution of a character and its representation. Graphical representation of univariate distributions. Synthesis of the distribution of a character. Summary and central tendency measures. Measures of variability. The shape of the distribution.

Part II (24 HOURS):
Bivariate distributions. Graphical representation of bivariate distributions. Analysis of the association between two characters. Measures for the study of dependence and interdependence. Measures of association between qualitative characters. Measures of association between quantitative and qualitative characters. Measures of association between quantitative traits. Linear regression.

Teaching Methods

Traditional lectures. Classroom exercises. Classroom applications using software (Excel).


Borra, S., Di Ciaccio, A., Statistica. Metodologie per le scienze economiche e sociali (quarta edizione). McGraw-Hill (cap. 1, 2, 3, 4, 6, 7, 16)
Quintano C., Castellano R. (2003), La Statistica in pratica: Esempi per l’Economia e le Aziende, Liguori.

Learning assessment

The written test lasts one and a half hours and consists of 4 exercises covering the entire course programme. Each question is awarded a mark of 7.5. A minimum of 18 is required to pass the written test. An oral examination supplements the written examination to discuss the written assignment and/or an in-depth evaluation of all the topics in the programme. The oral examination covers the topics discussed in the lectures and aims to verify the achievement of the training objectives. The final mark is obtained as the average of the written and oral examination marks. There is an optional project work based on the use of Excel software. The correct completion of the project work adds 1 point to the grade.

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