Terminology - Normalized, Indexed, or something else? What's the proper term to refer to data that's been transformed as a ratio of a baseline value?
I often work with datasets like
   Year Revenue
1: 2013     100
2: 2014      95
3: 2015     123

which I transform to be 
   Year Revenue.Transformed
1: 2013          1.00
2: 2014          0.95
3: 2015          1.23

and I'm not sure the "proper" way to refer to the transformed data.  I want to call it normalized but according to this answer I can't because values aren't necessarily restricted in [0-1].  Indexed maybe?  I know this stuff gets used all the time, especially with stocks, but it was difficult to google my question for an answer.
 A: I think "normalized to baseline" is a pretty reasonable term. I see biologists doing this all the time, and of all the names they give, this is the one that makes the most sense. 
I also want to point out that I think it's often used rather carelessly and is a great way to introduce more noise into your data and break standard assumptions required for most statistical tests. 
In help think about the more noise issue, consider that for most estimators, as the sample size increases, the influence of any single observation decreases. But if you scale by the first observation in your group, then no matter how large your sample size is, that first value will always have the same influence. 
In terms of the standard assumptions, many estimators assume independence of samples. However, if all your samples in a group have been scaled by the same single value, they are no longer independent, as they all have been scaled by the same value random value.
A: Them index numbers to me,  apart from the fact they are usually multiplied by 100.
