Statistical Parametric Mapping

Staistical Parametric Mapping (SPM) is an analysis technique that allows the statistical analysis of typical biomechanical data e.g. 1D curves and vectors. It ensures you avoid subjective analysis decisions. 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.

The intended learning goals of this workshop are:

1.        to understand the concepts and the basic principles that underpin SPM;

2.       to conduct basic SPM1d analyses in Matlab (or Python);

3.       to learn how to present these in scientific reports.

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

Workshop prerequisites

·         Prior knowledge: having undertaken at least basic undergraduate level courses on biomechanics and statistics

·         Suggest to refresh basic use of Matlab/Python if possible. No problem if no Matlab/Python experience.

·         Refresh theory on t-test, ANOVA and regression if possible.