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Quantifying Bivariate Plots in Sports Biomechanics

David Mullineaux ©2018

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Data is often presented as variable by variable graphs, or bivariate plots, and include angle-angle plots and phase-plane portraits. With data on both axes varying, analyses are more complex. This webinar explored different approaches to analyzing data in bivariate plots, including using RMSD, vector coding and CI2.

Learning Outcomes of the Webinar:

• Describe the background and uses of methods to explore bivariate plots.
• State assumptions, delimitations and limitations of approaches to exploring bivariate plots.
• Illustrate methods to quantifiably explore bivariate plots, including using CI2 (Mullineaux 2017; Gait and Posture).

Presenter overview

David Mullineaux is a Professor in Sports Science at the University of Lincoln, UK. He has made several transitions between academia and industry in the UK and USA. His research interests are in using real-time biofeedback to alter technique, and on applying analytical techniques in biomechanics. He has experience of applying this expertise to research in Sport and Exercise Science, Sports Medicine, Orthopedics, Biomedical Engineering, Athletic Training and Physical Therapy. He has co-authored the "Sample Size and Variability Effects on Statistical Power" chapter in the 2017 BASES book Biomechanical Evaluation of Movement in Sport and Exercise.