Details of Award
NERC Reference : NE/M006344/1
Multivariate Statistics and Geostatistics for Geosciences using R
Training Grant Award
- Lead Supervisor:
- Dr M Cave, British Geological Survey, BGS Laboratories
- Grant held at:
- British Geological Survey, BGS Laboratories
- Science Area:
- Earth
- Terrestrial
- Overall Classification:
- Earth
- ENRIs:
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Properties Of Earth Materials
- Pollution
- Earth Surface Processes
- Soil science
- Abstract:
- This course has been designed to provide the opportunity for doctoral and early stage researchers to gain practical experience in some of the latest developments in multivariate statistics and geostatistics with the particular aim of providing ways to understand and interpret the increasing amounts of highly complex data that are routinely being studied by geoscientists. The platform for the training is the R programming language. It is a powerful and flexible and able to fit complicated models and handle large and complex data sets but also allows the user to follow all calculations. In addition, the R environment is able to achieve the goals of "reproducible research". The R open source programming language is rapidly becoming a de-facto standard programming language for statistics and data science applications. The overall aim is to introduce the R environment for data analysis along with the most important underlying principles of multivariate and geostatistical analysis with real world examples of their use. The attendees will learn the basic tools of multivariate statistics and geostatistics through R. This will provide a framework which can be built on by the attendees and allow them to go back to their working/research environments and apply and develop methods to interpret, model, visualise and predict in their own speciality subject. The course will specifically address the following Priority Training Areas: Modelling - multivariate and geostatistical modelling will be introduced along with model validation and prediction Data and information management - the course will illustrate a number of data processing techniques from data cleaning through to data modelling. The participants will be shown how the R programming language's powerful graphical capabilities can be used to visualise large multivariate data sets. The course will also reinforce the ideas behind reproducible research as implemented in the R environment Statistics - The course covers a number of important statistical concepts and methodologies through the R statistical programming environment Risk and Uncertainty - The course will highlight uncertainties in data modelling and predictions providing the course attendees with an appreciation of the limitations of their data The unique selling point of this course is to bringing together the three strands of multivariate statistics, geostatistics and the R programming language along with two very experienced course trainers who not only have considerable experience of delivering courses of this type but also have applied the data science methodologies being taught in a variety of both academic and commercial projects. Expected outcomes and impacts include: i) To develop R programming skills for use in their own research field and their future careers ii) To develop data visualisation skills using the R programming language iii) To develop skills in both multivariate statistics and geostatistics and know how to apply those appropriately to their own data sets iv) To know how to use large data resources to support research and inform results v) To understand the wider picture of how multivariate statistics and geostatistical approaches are used in geosciences and where to find resources to further their knowledge
- NERC Reference:
- NE/M006344/1
- Grant Stage:
- Completed
- Scheme:
- Doctoral Training
- Grant Status:
- Closed
- Programme:
- Advanced Training
This training grant award has a total value of £21,006
FDAB - Financial Details (Award breakdown by headings)
| Total - Other Costs |
|---|
| £21,006 |
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