Introduction to Structural Modelling for Statisticians
In statistics production, there is an interaction between several types of competences. The primary competences being ‘subject matter’, ‘statistical methodology’, and ‘information technology’.
This module is targeted at statisticians working in:
- subject matter,
- methodology, and
- statistics operations (production) areas.
This module aims to provide you with:
- the knowledge and skills to describe your statistical data using traditional statistical concepts and methods,
- provide knowledge of structural modelling concepts, and
- provide the ability to understand and be able to apply structural modelling concepts to statistical data.
The successful application of the concepts covered in this module will result in:
- statistically robust definitions of data in the statistical system,
- improved specifications of data in statistical tools, and
- the foundation upon which to map data descriptions to the SDMX standard.
The focus of this module is on macro statistics. Throughout the module, the term data will be used as a synonym for statistics, macrodata, and macro statistics.
What you’ll learn
At the end of this module, you’ll have a new understanding of and ability to create structural models of statistical data.
- Establish a shared understanding of statistical concepts and terms for structural modelling of macro statistics.
- Understand the three types of data models, their purpose, and their relevance to statisticians and IT experts.
- Know the two major components of the SDMX standard and their relationship to the data models.
- Learn how to create structural statistical models using well defined statistical concepts.
- Understand how to analyse a data table and identify and resolve information gaps in the structural model.
- Develop skills in structural modelling of statistical data.
You should already have experience working with statistical data and an understanding of the concepts for describing macro statistics.
Units in this module