This question is specifically aimed toward the practice of statistics and data science and toward statistics educators (particularly introductory level statistics).
In brief, ¿when do we really need to distinguish between interval and ratio measurement levels? More specifically, ¿have you ever encountered a situation where the analysis technique or statistical protocol used changed because you were using interval level data instead of ratio level data? (This is an extension of a recent conversation between colleagues.)
I personally have moved away from Stevens' 4-level typology to my own categorization:
In my teaching (from introductory level statistics to graduate level applied statistics), this has served me & my students very well. By reflecting on the type of variable on this new typology, students can make decisions about which analysis strategy to employ.
So, my question here is to see if the interval/ratio distinction has been useful to others...and more importantly, if so, is this something that is worth sharing with our introductory level statistics/data-science students.
(I recognize there may be some subjectivity to people's responses, but I am hoping there also will be some concrete examples people might be able to share.)