This is about Stevens’ typology of scales and most of the time it’s a red herring in our change measurement.
Ordinal scaling has order but no (implicit) mathematical relationships. For example, “rarely”, “sometimes” and “often” have a pretty clear sequence but you can’t say how much “sometimes” is more than “rarely” nor how much “often” is more than “sometimes” nor anything about how the differences relate to each other, is “often” more different from “sometimes” than “sometimes” is from “rarely”?
There’s an argument that this restricts the kind of statistical analyses that you can do with such scaling. However, this is a bit mad as what we can and cannot do with the numerical data is about the distributions of scores not their scaling. What we make of the data and of the statistical analyses is about applying our brains, not about maths!
Try also … #
Parametric versus non-parametric statistics
Bootstrap methods & bootstrapping
Mostly chapter 4 but also pertinent to chapter 10.