Checking date: 30/05/2022


Course: 2022/2023

Resambling Techniques
(13726)
Study: Bachelor in Statistics and Business (203)


Coordinating teacher: MARIN DIAZARAQUE, JUAN MIGUEL

Department assigned to the subject: Department of Statistics

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
Probability I Probability II Técnicas de Inferencia Estadística I Técnicas de Inferencia Estadística II Métodos de Regresión
Objectives
General objectives: 1. Capacity for analysis and synthesis. 2. To model and solve problems. 3. Oral and written communication skills. Specific objectives: 1. To know the basic techniques of resampling methods 2. To know and use statistical software to work with resampling techniques.
Skills and learning outcomes
Description of contents: programme
1 Introduction to resampling methods: bootstrap and permutations 1.1 Examples of classical problems of estimation 1.2 Introduction to resampling methods 2 Aplications of bootstrap methods and permutations methods in data structures 2.1 Theoretical issues of bootstrap methods 2.2 Introduction to program bootstrap methods in R 3 Bootstrap based confidence intervals 3.1 Justification of alternatives of bootstrap confidence intervals 3.2 Application of bootstrap confidence intervals with R 4 Bootstrap based tests of hypotheses 4.1 Bootstrap hypothesis tests 4.2 Permutation hypothesis tests 5. Jackcnife methods 5.1 Properties of jacknife estimators 5.2 Application of jacknife methods with R 6 Resampling methods in linear models and time series analysis. 6.1 Regression models with bootstrap 6.2 Time series analysis with bootstrap
Learning activities and methodology
Theory (4 ECTS). Theoretical classes with support material available on the Web. Practice (2 ECTS) problem-solving classes. Computing practices in computer labs. Presentations and debates.
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70
Calendar of Continuous assessment
Basic Bibliography
  • A.C. Davison, D.V. Hinkley. Bootstrap Methods and their Applications. Cambridge University Press.. (1997)
  • B. Efron, R. Tibshirani . An Introduction to the bootstrap. Chapman and Hall.. (1993)
  • Phillip I. Good. Introduction to Statistics Through Resampling Methods and R. Wiley. (2013)
Additional Bibliography
  • Michael R. Chernick. Bootstrap Methods: A Guide for Practitioners and Researchers. Wiley. (2007)
  • Phillip I. Good. Resampling Methods A Practical Guide to Data Analysis. Birkhauser. (2006)

The course syllabus may change due academic events or other reasons.


More information: http://halweb.uc3m.es/esp/Personal/personas/jmmarin/esp/docencia.html