Quantifying Bivariate Plots in Sports Biomechanics
David Mullineaux ©2018
You must log in to watch this webinar recording.
Download the presentation slides
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.
Latest Webinars
- Enhancing Dance Performance and Reducing Injury Risk: Applying a True Holistic Model of Wellness
- Mindful Moves: Effective Attention and Focus Strategies to Elevate Dance Education Performance Indicators
- Youth Compendium of Physical Activities: An Investigation
- You might be fit now but you'll be fat by forty: the inevitability of human sloth
- Yoga for Runners: The Benefits and Practice Revealed
- Women, Weight, and Exercise