Separate `interval` and `ratio` types

I’ve noticed there’s no way to tell the difference between interval and ratio scales ATM. They’re both Continuous right now, but they’re not quite the same; ratio scales have a true zero value (e.g. Kelvin), while interval scales don’t (e.g. Fahrenheit or Celsius). This makes a big difference in some stats analyses; for example, you can say something is “twice as much” with ratio scales, but not with interval scales. These scales are useful since they let us throw errors when users perform invalid operations on interval scales (like taking logarithms or using MAPE); in addition, we can warn users when they make questionable decisions (like trying to do a linear regression with a ratio outcome, without taking the logarithm first).

A good heuristic for ratio types is all-positive values.

What do you think about adding new types to make this distinction possible?

(cc @juliohm for the same issue in DataScienceTraits.jl)

No files or tests are named in the issue. Start by locating the existing Continuous type and its dispatch or validation uses; done means agreeing on how interval and ratio scales are distinguished and which statistical operations are affected.