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  • Understand the principles of modelling calibration results
  • Learn how to use calibration results to ensure compliance with the latest VIM definition
  • Learn how to use M-CARE modelling software

Employees tasked with interpreting calibration results. R&D personnel seeking to model measurement results and manage uncertainties in models more effectively.

  • Prior experience in performing calibrations would be useful
  • Basic skills in maths and statistics
  • Basic knowledge of metrology

By the end of the course, the participant will have a good understanding of the latest VIM definition and know how to apply it to real-life cases using the M-CARE tool.
They will know how to select the model that is best suited for using the data, validate it in relation to the data, and understand its limitations.


Reminder of basic statistics principles

  • Position
  • Dispersion
  • Laws of distribution
  • Statistics tests (Student, Khi Deux, Fisher, etc.
    Reminder of the basic principles of GUM
  • Type A and Type B evaluations
  • Sum of variances
  • Law of propagation of uncertainty
    Statistics model selection and validation
  • Modelling: Ordinary, weighted, generalised least squares, GGMR (generalized Gauss-Markov regression)
  • Calibration signature: significance of coefficients
  • Analysis of residues: significance test, normality test
  • Covariance - definition and impact on a measurement result
  • Expressing opportunity as related to the causes of uncertainty (variances “LO” and “HO”)
    The variances-covariances matrix
  • Theory
  • Sample applications
    Familiarization with the numerical simulation method: Statistics model selection and validation
  • Definition of a probabilistic model Modelling theory
  • Modelling: ordinary, weighted, generalised least squares, GGMR
  • Calibration signature: significance of coefficients
  • Analysis of residues: significance test, normality test
    Software training
  • Using course learning media
  • Using the participants’ own examples
From 2400 € Ex. Tax On site or at our premises For a group of up to 12 people CUSTOM - Pre and post-course support and mentoring
Remote Coaching
From 2100 € Ex. Tax Course available in full online format Pre and post-course support and follow-up - Remote Coaching Customized
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MT01 Introduction to metrology
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MT03 Learn how to meet MSA requirements
Metrology - Field of Excellence
EX01 Improving the metrology department: strategy and tools
EX02 Advanced course in evaluating measurement uncertainties
EX03 Latest calibration definition taken from VIM 3: Use of M-CARE modelling software
EX04 NF ISO/CEI Guide 98-4: Client and supplier risks
IN01 Introduction to evaluating uncertainties in measurements and tests
IN02 Practical introduction to evaluating and exploiting measurement uncertainties
IN03 Evaluating measurement uncertainties using indirect measurements
IN04 Evaluating measurement uncertainties using the Monte Carlo method
ST01 Basic statistical tools used in measurement
ST02 Using applied statistics to process experimental data, measurement uncertainties and tests
ST03 Inter-laboratory comparisons and proficiency testing procedures based on NF ISO 5725 et NF ISO 13528
FP02 Extra practical course component delivered via video-conference
FP03 Setting up the drift method with Optimu
FP04 Setting up the OPPERET method
FOP01 Measuring Instrument Management Module (MIM )
FOP02 Calibration module
FOP03 Movements module
FOP04 Uncertainty module
FOP05 Statistics module
FOP06 Administrative Management module
FOP07 Further Theory and Practice Module FD X07-014
FOP08 System settings
FOP09 Monitoring module
FOP10 module
  • Deltamu played a key role in drafting the CFM technical guide
  • The M-CARE modelling software was developed by Deltamu
  • Applied to real cases provided by the participants