On successful completion of the module, the successful student will be able to:

      - demonstrate a substantial knowledge and understanding of the theory, models and techniques    used for the analysis of data with complex structure and dependency, including repeated     measures, longitudinal and spatial data;

      - introduce the theory to the statistical modelling and analysis of practical problems involving      structured, dependent data, and to interpret results and draw conclusions in Environmetrics;

      - apply the use of advanced statistical software for the analysis of complex statistical data;

Skills

This module will call for the successful student to:

      - select and justify the use of proper descriptive statistical analysis tools for data sets with complex dependency structure; for example hierarchical, repeated measures, longitudinal and spatial data.

      - recognize when linear models, Generalized Regression Models for non-normally distributed variables, models with Instrumental Variables, environmetric models, longitudinal (panel) data, models for discrete choice, limited and categorical variable models appropriate to the stochastic processes and justify the model;

- apply and write the results of a technical analysis into a clearly written report form that may be understood by a non-specialist.