I am uncertain about the solution to the problem for which I am trying to solve. I am hoping that someone might help guide me to the correct solution. I have a discrete distribution (say 100) with a dichotomous population (either good or bad). There is no knowledge of the population split until after sampling. Since the testing of each sample cost time and money, only one sample set will be taken. I want to find the smallest sample size that has a 90% probability of being indicative of the entire population. The distribution seems like it would be a hypergeometric distribution (since I do not know the sample size, I do not know if a binomial distribution would be appropriate in this case). The information I have read on confidence intervals does no seem to be directly applicable to hypergeometric distributions. The method of maximum likelihood seems like a method to relate the sample population to the entire population, but it does not provide for determining the most efficient sample size and it does not indicate the accuracy of the sample distribution as compared to the entire population distribution. If you can help me solve this problem, I would greatly appreciate it. Thank you for your time. ================================================================= Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =================================================================