Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or cross-validation procedures and the bootstrap method. Invariance procedures split the total sample into two subgroups and apply techniques to analyze each subgroup and compare results, often by using parameters obtained from one subgroup to evaluate the other subgroup. A simulated data set is presented and analyzed by invariance procedures for: (1) canonical correlation; (2) regression and discriminant analysis; (3) analysis of variance and covariance; and (4) bivariate correlation. Whereas invariance procedures split a sample into two parts, the bootstrap method creates multiple copies of the data set. The number of copies could exceed millions with current computer capability. The copies are shuffled and artificial samples of 20 cases each, called bootstrap samples, are randomly selected. The value of the Pearson product-moment correlation (or other statistics) is then calculated for each bootstrap sample to assess the generalizability of the results. (LPG)