Data Analysis
A.Y. 2020/2021
Learning objectives
The main objective of the course is to promote the knowledge, understanding and use of basic and advanced classical statistical methods, and to show how these can face research problems in various fields, and in particular how these techniques can improve problem solving techniques. The course is dedicated both to the analysis of individual features and to the identification and evaluation of any existing relationships between them, always addressing both the descriptive and the inferential scope. The importance of formulating interpretative hypotheses as an essential starting point for any qualitative and quantitative analysis of the data will be emphasized. The various theoretical topics will also be addressed operationally, using real dataset and using IT tools, both generic as Microsoft Excel and for specific statistical analysis as IBM SPSS Statistics.
Expected learning outcomes
The course aims to provide a good knowledge of classical data analysis techniques. At the end of the course the student will be able to carry out an analysis of real data, starting from the choice of the data source and of the most appropriate analysis techniques, up to a conscious interpretation of the results obtained.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First trimester
SECS-S/01 - STATISTICS - University credits: 9
Lessons: 60 hours
Professor:
Siletti Elena