Data-driven Bayesan network modelling to explore the relationship between SDGs and Italian regions' performance
Catacchio, Beatrice (A.A. 2021/2022) Data-driven Bayesan network modelling to explore the relationship between SDGs and Italian regions' performance. Tesi di Laurea in Data analysis for social sciences, Luiss Guido Carli, relatore Serena Arima, pp. 49. [Master's Degree Thesis]
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Abstract/Index
Methodology. Data selection and data pre-process. Descriptive analysis of the data. Statistical tools. Bayesian networks. Results. Bayesian network estimation. Discussion and implications.
References
Bibliografia: pp. 34-35.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree program in Global Management and Politics, English language (LM-77) |
| Chair: | Data analysis for social sciences |
| Thesis Supervisor: | Arima, Serena |
| Thesis Co-Supervisor: | Mingione, Marco |
| Academic Year: | 2021/2022 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 20 Feb 2023 11:55 |
| Last Modified: | 20 Feb 2023 11:55 |
| URI: | https://tesi.luiss.it/id/eprint/35150 |
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