Probability I Probability II Técnicas de Inferencia Estadística I Técnicas de Inferencia Estadística II Métodos de Regresión

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.

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

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.