> The reason is simple and comprehensive.... > > Assume a population with ANY distribution of > elements. Then randomly select > a number of sample elements from the population to > characterize the > underlying population. That distribution of sample > elements ALWAYS tends > toward a normal [Gaussian] distribution. And the > mean and standard deviation > of the sample distribution are unbiased > representations of the mean and > standard deviation of the underlying population. Things have obviously changed since I was a lad. I was taught that the Central Limit Theorem was a theorem NOT a law. There are distributions which do not conform to this behaviour and (alas for us) the lognormal is one of them.
The Central Limit theorem also does not apply to mixed distributions or in cases of non-stationarity. Mind you, neither does geostatistics................ Isobel Clark http://geoecosse.bizland.com/news.html __________________________________________________ Do You Yahoo!? Everything you'll ever need on one web page from News and Sport to Email and Music Charts http://uk.my.yahoo.com -- * To post a message to the list, send it to [EMAIL PROTECTED] * As a general service to the users, please remember to post a summary of any useful responses to your questions. * To unsubscribe, send an email to [EMAIL PROTECTED] with no subject and "unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list * Support to the list is provided at http://www.ai-geostats.org
