Application profiling tools are the instruments used to measure software performance at the function and application levels. The most powerful measurement method available in application profiling tools today is sampling-based profiling, where a potentially unmodified application is interrupted based on some event to collect data on what it was doing when the interrupt occurred. It is well known that sampling introduces statistical uncertainty that must be taken into account when interpreting results; however, factors affecting the variability have not been well-studied. In attempting to validate two previously published analytical estimates, we obtained negative results. Furthermore, we found that the variability is strongly influenced by at least one factor, self-time fragmentation, that cannot be determined from the data yielded by sampling alone. We investigate this and other factors and conclude with recommendations for obtaining valid estimates of uncertainty under the conditions that exist.