A one day course on extracting quantitative information from data.

Aims & Objectives

To enable metrologists, scientists and engineers to:

• Build models of measurement systems
• Determine best estimates of model parameters from measurement data
• Evaluate uncertainties associated with fitted parameter estimates
• Validate models

Course Content

• Modelling overview: model parametrization, model predictions, measured responses
• Linear models: polynomials, splines, basis functions
• Statistical models associated with measurement data and maximum likelihood estimation
• Least squares estimates of model parameters, uncertainty associated with parameter values
• Numerical methods for linear models
• Nonlinear models, nonlinear least squares and uncertainty evaluation
• Numerical methods for nonlinear models
• Model validation

 

Prior Knowledge

The course is suited to attendees with a science or engineering background with some experience in measurement or testing, and some familiarity with matrix algebra.

Intended Audience

This course is aimed at scientists and engineers involved in analysing experimental data.

Documentation

Participants will receive a self-contained set of course notes, and the latest versions of the relevant Best Practice Guides, including No. 4: Discrete Modelling and Experimental Data Analysis.

Lecturing Team

Professor Alistair Forbes and Dr Peter Harris are both experienced researchers in the Mathematics and Scientific Computing Group, National Physical Laboratory, and are co-authors of Best Practice Guides on Discrete Modelling and Experimental Data Analysis and Uncertainty Evaluation.

Further Information

For enquiries or further information about the above course, please contact Course Manager: Professor Alistair Forbes
or
E-mail: mmm_events@npl.co.uk

Contact

For further technical information, please contact: Professor Alistair Forbes

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  This course has been endorsed by the Institute of Physics (IOP):

• If you are a member of the IOP, you will receive a 10% discount on the course fee
• CPD points will be awarded on this course at a rate of 3 per hour