Credits: 7.5

Type: bridging

Objectives:

• To understand the fundamental concepts of statistics.
• To know how to apply statistical analysis effectively to a problem and some data.

Knowledge:

• Statistical models. Sufficiency. Verisimilitude. Selecting a model for a set of data.
• Bayesian paradigm.
• Hypothesis estimation and testing in different contexts.
• Linear models and generalisations. Nonparametric regression.
• Multivariate treatment of data.
• Statistical computations, graphics and analysis with R.

Subject-specific competences:

• To understand the various statistical methods and techniques and their mathematical foundation.
• To be able to implement algorithms appropriate to the analysis of different types of data.