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 | 2023/24 | |||||||||||||
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 / results | ||
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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