Refreshments: 3:30-4:00in 312 MDS building

 

Consider the problem of estimating the mean p of a {0,1} random variable.  This problem arises in many area, such as experiments with binary data, estimating exact p-values, and acceptance rejection methods for integration and summation.  Suppose it is desired to know p to a set number of significant figures.  Then it is necessary to bound the relative error of the estimate.  In this talk I will present a new estimate q such that the relative error (q/p - 1) of the estimate has a random distribution that does not depend on p at all!  This allows for a guaranteed quality of the relative error of the estimate using far fewer samples on average than previous methods.