Università degli Studi di Napoli "Parthenope"

Teaching schedule

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Second semester
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Course description

Expected learning outcomes
Knowledge and ability to understand: The student must demonstrate that he/she knows and understands the typical problems of analysis applied to the market, with particular reference to segmentation and positioning techniques and, last but not least, the methods of analysis useful for identifying and explaining consumer preferences. They are learned through active participation in frontal activities and completed with individual study.
Ability to apply knowledge and understanding: the student must demonstrate that he/she is able to carry out a market survey in all its phases: from the definition of objectives to the analysis of data and the drafting of the reports necessary for the transfer of information to third parties. He/She must be able to carry out a complex investigation in all its phases and choose the methodology of statistical analysis most suitable to achieve the objectives.
Autonomy of judgement: the student must demonstrate that he/she has developed an ability to critically evaluate the statistical techniques and methodologies needed to solve the problem presented and the practical and operational skills needed to transform data into knowledge.
Communication skills: the student must be able to communicate clearly and comprehensively the techniques of investigation and the results obtained. This ability cannot be separated from the correctness of the vocabulary used and the ability to synthesize necessary to communicate the results achieved by the analysis conducted.
Learning ability: the student must demonstrate the ability to deepen his knowledge with relevant bibliographic references, succeeding in integrating the knowledge already acquired with further characterizing elements.


Market Analysis (I mod)


Text mining. Word cloud. Word association and clustering. Classification.

Some textual data analysis techniques will be presented, useful for the synthesis of reviews and opinions found on social media, e-commerce sites etc.
The methodologies presented will be applied on real datasets and aid of specific software (R and Python).

Teaching Methods

Traditional lectures, analysis of case studies. Use of software R and Python


Teacher-provided notes

Learning assessment

During the course the degree of learning has constantly assessed by asking students to perform exercises and develop case studies related to business context and economic dynamics. The exam is passed with a minimum score of 18/30. For the maximum score, in addition to an excellent knowledge of the proposed methodologies and a thorough interpretation of the results of the proposed analysis, a correct use of the specialist vocabulary must be demonstrated.
Oral assessments in english about all the topics covered in the program.

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