Teaching GuideTerm
Faculty of Computer Science
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Mestrado Universitario en Técnicas Estadísticas (Plan 2019)
 Subjects
  Nonparametric Methods
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Identifying Data 2020/21
Subject (*) Nonparametric Methods Code 614493111
Study programme
Mestrado Universitario en Técnicas Estadísticas (Plan 2019)
Descriptors Cycle Period Year Type Credits
Official Master's Degree 1st four-month period
First Obligatory 5
Language
Teaching method Hybrid
Prerequisites
Department Matemáticas
Coordinador
Vilar Fernandez, Jose Antonio
E-mail
jose.vilarf@udc.es
Lecturers
Vilar Fernandez, Jose Antonio
E-mail
jose.vilarf@udc.es
Web http://http://eio.usc.es/pub/mte/
General description Nonparametric methods to estimate the probability distribution, probability density and regression functions are introduced, paying sparticular attention to the kernel smoothing techniques. The main nonparametric goodness-of-fit test procedures, association tests in contingency tables and nonparametric rank-based location tests for one, two and more than two samples are also presented.
Contingency plan 1. Modifications to the contents The contents will not be modified. 2. Methodologies All teaching methodologies will be maintained. 3. Mechanisms for personalized attention to students. E-mail and telematic resources (Teams) will be employed. 4. Modifications in the evaluation Both continuous evaluation activities and exams can be developed by using telematic means. 5. Modifications to the bibliography or webgraphy No modifications.
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.
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