On Aug 3, 10:38 pm, [EMAIL PROTECTED] wrote: > I'm a Python newbie and certainly no expert on statistics, but my wife > was taking a statistics course this summer and to illustrate that > sampling random numbers from a distribution and taking an average of > the samples gives you a random number as the result (bigger sample -> > smaller variance in the calculated random number, converging in on the > mean of the original distribution), I threw together this program: > ... > > I added the lo and high stuff to my test program out of fear that I > was running into something funky in adding up 100 floating point > numbers. That would be more of a worry if the sample size was much > bigger, but lo and high showed apparent bias quite aside from the > calculation of the mean. > > Am I committing some other obvious statistical or Python blunder? > e.g. Am I mis-understanding what random.normalvariate is supposed to > do?
Doing some testing with mu=0, sigma=1, and n=1000000 gives me means of -0.00096407536711885962 -0.0015179019121429708 +6.9223244807378563e-05 +0.0017483897464631625 -0.0011148444018505548 +0.0015367250480148183 There appears to be no consistent bias. -- http://mail.python.org/mailman/listinfo/python-list
