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Teaching GuideTerm Faculty of Computer Science |
| Grao en Ciencia e Enxeñaría de Datos |
 Subjects |
| Statistical Analysis of Complex Data |
| Learning aims |
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| Identifying Data | 2022/23 | |||||||||||||
| Subject | Statistical Analysis of Complex Data | Code | 614G02031 | |||||||||||
| Study programme |
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| Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
| Graduate | 1st four-month period |
Fourth | Optional | 6 | ||||||||||
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| Learning outcomes | Study programme competences | ||
| Know and understand the basics of missing data | A3 A20 |
B6 |
C1 C4 |
| To know the main techniques to analyse problems with missing data | A3 A17 A20 |
B3 B4 B9 |
C1 |
| To know the main techniques to analyse functional data | A3 A17 A20 |
B3 B4 B9 |
C1 |
| To know the main techniques to analyse censored data | A3 A17 A20 |
B3 B4 B9 |
C1 |
| To know the main techniques to analyse problems with biased data | A3 A17 A20 |
B3 B4 B9 |
C1 |
| To be able to apply different techniques for missing data, functional data, censored data and biased data to a real or a simulated dataset | A20 |
B2 B3 B4 B9 |
C1 |
| To be able to interpret the results and to know the limitations of the different methods | A3 |
B6 B7 B8 B10 |
C1 C4 |
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