Multisite trials, which are being used with increasing frequency in education and evaluation research, provide an exciting opportunity for learning about how the effects of interventions or programs are distributed across sites. In particular, these studies can produce rigorous estimates of a cross-site mean effect of program assignment (intent-to-treat), a cross-site standard deviation of the effects of program assignment, and a difference between the cross-site mean effects of program assignment for two subpopulations of sites. However, to capitalize on this opportunity will require adequately powering future trials to estimate these parameters. To help researchers do so, we present a simple approach for computing the minimum detectable values of these parameters for different sample designs. The article then uses this approach to illustrate for each parameter, the precision trade-off between increasing the number of study sites and increasing site sample size. Findings are presented for multisite trials that randomize individual sample members and for multisite trials that randomize intact groups or clusters of sample members.