Why use median for subindices (zip code, property type, etc.) on the analytics site?
We chose to use the data median for the analytics site because without being able to control what property characteristics users select, we cannot guarantee that any combination that they put together will be appropriately captured by two or three power-law regions (Triple Power Law does fine with double-power law scenarios—it just folds down one of the regions). At the MSA level, or any region broad enough to encompass a full socioeconomic spectrum, Triple Power Law works well because it is a true representation of the data. If you just pick out isolated chunks of the spectrum, however, applying Triple Power Law may not be the best bet. Imagine the user who chooses Manhattan and the Bronx, which have very different price points. That psf distribution is essentially bimodal, and so the median is volatile. To conceptualize, imagine that between the two locations you have 100 transactions every day. One day 51 of them occurred in the Bronx and 49 in Manhattan, so the median is a Bronx pr
Related Questions
- Why do I keep getting the message that "No units were found for the provided Unit Type, Number, and Zip Code" when I try to create an account?
- What is the address of Laurel Hall on the University of tennessee property, Zip code 37916?
- How far from the property lines in zip code 33176 (residential) do you have build a shed?
