Recently, Virzi (1992) presented data that support three claims regarding sample sizes for usability studies: (1) observing four or five participants will allow a usability practitioner to discover 80% of a product's usability problems, (2) observing additional participants will reveal fewer and fewer new usability problems, and (3) more severe usability problems are easier to detect with the first few participants. Results from an independent usability study clearly support the second claim, partially support the first, but fail to support the third. Problem discovery shows diminishing returns as a function of sample size. Observing four to five participants will uncover about 80% of a product's usability problems as long as the average likelihood of problem detection ranges between 0.32 and 0.42, as in Virzi. If the average likelihood of problem detection is lower, then a practitioner will need to observe more than five participants to discover 80% of the problems. Using behavioral categories for problem severity (or impact), these data showed no correlation between problem severity (impact) and rate of discovery. The data provided evidence that the binomial probability formula may provide a good model for predicting problem discovery curves, given an estimate of the average likelihood of problem detection. Finally, data from economic simulations that estimated return on investment (ROI) under a variety of settings showed that only the average likelihood of problem detection strongly influenced the range of sample sizes for maximum ROI.