* General competences
- Description and data synthesis: Description of a set of data based on numeric and graphic measurements both at univariate and multivariate levels demonstrating possible relations between variables of interest.
- Modelling Ability to identify or create the appropriate model for a specific problem arising from each business activity (finance, marketing, production planning and control etc.).
- Model Analysis and Validation: Capacity to computationally manipulate established models, making the most of the power of statistical, optimisation methods etc. and analysing the results obtained.
- Drawing conclusions: Ability to perceive the nature of problems and interpret solutions provided by the corresponding models in a useful way, in order to improve performance in the various areas of a business (finance, production, quality, marketing, etc.).
- Presentation and communication of results: Ability to communicate results, conclusions of models and solutions proposed in a manner which is intelligible to the rest of the company, in order to ensure that they are accepted and implemented by decision makers.
* Specific competences
- Data description and synthesis.
- Modelling and statistical analysis of both static and dynamic data.
- Correct and rational use of software.
- Ability to devise and construct models and validate them.
- Graphic representation of data.
- Interpretation of results based on statistical models.
* Learning outcomes
Acquisition of knowledge on: 1) nonparametric estimation of the distribution function; 2) kernel density estimators and their applications; 3) nonparametric regression methods based on smoothing.