Percentiles are far more useful than that linear approximation. That is just slope and intercept, basically two numbers.
With percentiles, I can answer the question “how fast is the search for 95% of my visitors?” With that linear interpolation, I don’t know anything about my customers. wunder Walter Underwood wun...@wunderwood.org http://observer.wunderwood.org/ (my blog) > On Dec 19, 2016, at 12:51 PM, John Blythe <j...@curvolabs.com> wrote: > > gotcha. yup, that was the back up plan so i think i'll go that route for > now. > > thanks for the info! > > best, > > -- > *John Blythe* > Product Manager & Lead Developer > > 251.605.3071 | j...@curvolabs.com > www.curvolabs.com > > 58 Adams Ave > Evansville, IN 47713 > > On Mon, Dec 19, 2016 at 3:41 PM, Toke Eskildsen <t...@statsbiblioteket.dk> > wrote: > >> John Blythe <j...@curvolabs.com> wrote: >>> if the range is 0 to 100 then, for my current purposes, i don't care if >> the >>> vast majority of the values are 92, i would want 25%=>25, 50%=>50, and >>> 75%=>75. so is there an out-of-the-box way to get the percentiles to >>> correspond to the range itself rather than the concentration of distinct >>> values? >> >> Then it is not percentiles. And I don't know of any build-in function that >> returns them directly. >> >> But as you have the min and max, you can just do >> 25%: (max-min)*0.25+min >> 50%: (max-min)*0.5+min >> 75%: (max-min)*0.75+min >> >> But of course, that won't guarantee that you match the distinct values. If >> you want that, you'll have to iterate the list of distinct values (hope >> it's not too large) and pick out the nearest ones. >> >> - Toke Eskildsen >>
