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Careful consideration of the tradeoff between Type I and Type II error rates when designing experiments is critical for maximizing statistical decision accuracy. Typically, Type I error rates (e.g., .05) are significantly lower than Type II error rates (e.g., .20 for .80 power) in psychological science. Further, positive findings (true effects and Type I errors) are more likely to be the focus of replication. This conventional approach leads to very high rates of Type II error. Analyses show that increasing the Type I error rate to .10, thereby increasing power and decreasing the Type II error rate for each test, leads to higher overall rates of correct statistical decisions. This increase of Type I error rate is consistent with, and most beneficial in the context of, the replication and "New Statistics" movements in psychology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).