Tweet
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
For more information on one-dimensional SPM: www.spm1d.org
Registration and further info:
Any queries: jos.vanrenterghem@kuleuven.be
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
For more information on one-dimensional SPM: www.spm1d.org
Registration and further info:
Any queries: jos.vanrenterghem@kuleuven.be