Data Analysis

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General Data Analysis

• This 1 h 23 min YouTube video by Ryan Alcantara and Garrick Bruening is a hands-on tutorial introducing GitHub and version control as a way researchers can collaborate, improve reproducibility, and maintain their code. Git/GitHub are free version control tools that allow collaborators to view line-by-line changes to code, add comments, or even revert a code base back to a previous version if something goes wrong. Researchers who develop custom scripts can benefit from this tutorial, regardless of research area or programming language. The resources for the tutorial are available here.

• This paper presents and explains twelve tips for data organization in spreadsheets:

• Please see the Data Visualisation and Statistics sections for resources relating to R.

• Or for Python, check out the ‘Data Science Handbook’

Biomechanical Data Analysis

• The GitHub repository by Luca Modenese contains an enormous amount of resources relating to biomechanical data collection and analysis.

• The YouTube channel by John Harry includes two series of video tutorials on ‘Matlab for Sport Science’: single trial and multiple trial analysis of countermovement jump and force plate data.

• My Sports Biomechanics Lecture Series includes lectures on motion capture hardware and software, a live motion capture demo, EMG, and inverse dynamics:

• The Visual3D Wiki contains lots of useful information for motion capture data analysis within Visual3D.

• I have also found free3d.com to be particularly useful for finding sporting equipment to integrate within 3D graphics generated in Visual3D. For a tutorial of how to add equipment, or scale segment colours to a calculated variable, check out the video below:

• This guide to analysing motion capture files with biomechanical toolkit (BTK) and Mokka is great - including example data to work through the tutorial with.