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Statistical Parametric Mapping Workshop @UAntwerpen, Belgium, 3-4 May 2023

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  • Statistical Parametric Mapping Workshop @UAntwerpen, Belgium, 3-4 May 2023

    Statistical Parametric Mapping (SPM) is the analysis technique that allows the statistical analysis of typical biomechanical data e.g. 1D curves and vectors. It allows to avoid subjective analysis decisions. Actually, it works like the basic statistical analyses we all know, such as t-tests, ANOVA, and linear regression, but it extends these to one-dimensional profiles of forces or kinematics. Actually, pretty much anyone can use it with a little bit of training, which only requires one to learn the basic principles that underpin the technique, and then apply this through very basic tools.

    Workshop description
    In this in-person workshop you will learn to understand the principles underpinning SPM. You will conduct SPM analyses in Matlab (or Python) AND learn how to include SPM in your scientific reporting. A certificate can be earned at the end of the two-day workshop, based on successfully conducting hypothesis tests on experimental and simulated data.

    Topics covered during the workshop
    • Principles of probability and random field theory
    • Temporal data registration and smoothing
    • Running a t-test using SPM
    • ANOVA using SPM
    • Linear regression using SPM
    • Writing up SPM results

    So, on 3-4 May 2023 we are running an in-person workshop in Antwerp, Belgium. If this would not suit you, there is still also the opportunity to register for our online workshop. Both the in-person and online workshop cover pretty much the same materials, providing delegates with a thorough introduction to the use of SPM1D.

    For queries concerning workshop contents, feel free to contact Jos Vanrenterghem (jos.vanrenterghem@kuleuven.be)

    For practical queries concerning travel, accommodation or the venue, feel free to contact Ann Hallemans (ann.hallemans@uantwerpen.be)

    Registration and further info: http://www.spm1d.org/Workshops.html

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