When computing limits for distribution categories given frequencies the following may be useful:
A number q is a p%-quantile of a data set If the percentage of data nums <= q is >= p% and the percentage of data nums >= q is >= (100-p)% For each percentage p there is an interval [lowerV,upperV] so that each number from that interval is p%-quantile of the data set. To make it unique some use in case lowerV < upperV the average of lowerV and upperV. -- d=data in lines, sorted ascending numeric -- p=percentage (num in range 0-100) function quantile p,d put the num of lines of d into N put N*p/100 into m0 put line ceil(N*p/100) of d into lowerV put line N+1 - ceil(N*(100-p)/100) of d into upperV -- return avg(lowerV,upperV) --> unique variant if lowerV=upperV then return lowerV else return lowerV,upperV end quantile For example quantile(50,d) returns the median of a data set, quantile(25,d), quantile(50,d), quantile(75,d) the quartiles. _______________________________________________ use-livecode mailing list use-livecode@lists.runrev.com Please visit this url to subscribe, unsubscribe and manage your subscription preferences: http://lists.runrev.com/mailman/listinfo/use-livecode
