Athlete Monitoring: Data Analysis and Visualization
Nominal Analysis
To remind ourselves, nominal analysis is the same as the continuous (i.e., ratio scale) analysis, but with dummy coding, where each level is represented as an additional variable with 0 or 1. Thus, (rolling) proportions and counts are the methods used to analyze and visualize the nominal variables.
In this video, I am explaining the implementation of the nominal analysis in the athletemonitoring package and prepare() function. Additional topics of daily aggregation (i.e., using mean or sum) on the results is discussed.
The video also explains the plotting functionalities explained in the Continuous Analysis video, but now applied to nominal variables.
Nominal analysis is not as fancy as continuous analysis, but sometimes you will have to analyze this type of data, and athletemonitoring will get you covered.
Ready to watch this course?
Take advantage of our promotional offerHurry Up! Spring Sale Expires In:
Related Articles
-
Create custom set and rep schemes with {STMr} – Module 7: Estimation and Individualization
-
Create custom set and rep schemes with {STMr} – Module 7: Estimation and Individualization Part 2
-
Create custom set and rep schemes with {STMr} – Module 7: Estimation and Individualization Part 3
-
Create custom set and rep schemes with {STMr} – Module 7: Estimation and Individualization Part 4
This topic contains 0 replies, has 1 voice, and was last updated by Mladen Jovanovic 2 years, 2 months ago.
You must be logged in to reply to this topic.
