Effect sizes have been increasingly emphasized in research as more researchers have recognized that: (1) all parametric analyses (t-tests, analyses of variance, etc.) are correlational; (2) effect sizes have played an important role in meta-analytic work; and (3) statistical significance testing is limited in its capacity to inform scientific inquiry. However, effect sizes tend to be biased by sampling and measurement error. The performance of the statistical corrections for sampling error bias of R. J. Wherry and P. A. Herzberg is illustrated and reviewed. The corrections are compared with empirical estimates of sampling error derived using "bootstrap" methods. A data set involving the responses of 31 college undergraduates (18 females and 13 males) on the Finding Embedded Figures Test (FEFT) and the Group Embedded Figures Test, is used for illusrative purposes to make the discussion concrete. It is suggested that bootstrap methods provide important insights for the researcher and are readily accessible to researchers due to the availability of user-friendly computer programs that automate the procedure (i.e., programs designed for use on microcomputers). Seven tables illustrate the example. An appendix provides an item analysis for heuristic FEFT data. A list of 65 references is included. (Author/SLD)