Teaching GuideTerm Faculty of Computer Science |
Mestrado Universitario en Técnicas Estadísticas (Plan 2019) |
Subjects |
Nonparametric Methods |
Methodologies |
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Identifying Data | 2022/23 | |||||||||||||
Subject | Nonparametric Methods | Code | 614493111 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 1st four-month period |
First | Obligatory | 5 | ||||||||||
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Methodologies | Description |
Guest lecture / keynote speech | The theoretical principles of the nonparametric tools and procedures for their application in practice will be introduced. Their interest in applications will be illustrated by using specific real examples from different disciplines, highlighting advantages and limitations. Students participation will be strongly encouraged. |
Seminar | Specific problems and suitable approaches to get them solved will be presented in seminars. The main objective is to show how the concepts and algorithms exposed in the keynote speechs are useful to face these problems. |
ICT practicals | Interactive sessions addressed to solve specific exercises by using scripts with free code from R software. The lecturer will support and supervise the right application of the knowledge and skills gathered by the students. |
Problem solving | Issues, exercises and examples that can be addressed by using nonparametric techniques of inference and modeling will be provided to be individually solved by students. |
Case study | Specific study cases will be proposed to be solved in group and/or individually. |
Supervised projects | Solutions for exercises and study case will be supervised by the lecturer. |
Workshop | Case study analyzed in detail by students will be presented and discussed. |
Objective test | Written examination to assess the the acquisition of knowledge. |
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