Statistical software & data analysis

Statistical methods and software used for data analysis, decision support and modelling of complex systems, across environmental, biomedical and sport science applications. This covers exploratory data analysis and data mining, descriptive and decision statistics, linear and non-linear regression, and dimensionality reduction methods such as Principal Component Analysis - used for instance to identify the physiological, biomechanical and anthropometric factors that determine endurance running performance.

Matlab - numerical simulation, signal processing and biomechanical modelling (running kinematics, performance prediction models).

R - statistical modelling and data visualization.

SPSS / STATA - descriptive and inferential statistics for research studies.

Kinovea - free, open-source video analysis software used to extract kinematic parameters (angles, velocities, trajectories) from video, validated against classical physics models for sport biomechanics analysis.

Power BI - business intelligence tool for building interactive dashboards, data modelling (DAX) and reporting, used to monitor KPIs and turn operational/administrative data into decision-ready visualizations.

Data mining - classification, clustering (k-means), association rules and decision trees applied to extract patterns from environmental, biomedical, sport and business datasets.

Good statistics turn raw measurements into decision-useful information.