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390 PART V: Analyzing and Reporting ResearchType II errors are likely when power is low, and low power has characterizedmany studies in the literature: The most common error in psychologicalresearch using NHST is a Type II error. Just because we did not obtain statisticalsignificance does not mean that an effect is not present (e.g., Schmidt, 1996).In fact, one important reason for obtaining a measure of effect size is that wecan compare the obtained effect with that found in other studies, whether ornot the effect was statistically significant. This is the goal of meta-analysis (seeChapter 6). Although a nonsignificant finding does not tell us that an effectis absent, assuming that our study was conducted with sufficient power, anonsignificant finding may indicate that an effect is so small that it isn’t worthworrying about.To determine the power of your study before it is conducted, you must firstestimate the effect size anticipated in your experiment. An examination of theeffect sizes obtained in previous studies for the independent variable of interestshould guide your estimate. Once an effect size is estimated, you must thenturn to “power tables” to obtain information about the sample size you shoulduse in order to “see” the effect. These steps for conducting a power analysisare described more fully in various statistics textbooks (e.g., Zechmeister &Posavac, 2003), and power tables can be found on the Web. When you have a goodestimate of the effect size you are testing, it is strongly recommended that you performa power analysis before doing a research study.Power tables are also used after the fact. When a study is completed and thefinding is not statistically significant, the APA Publication Manual (2010) recommendsthat the power of your study be reported. In this way you communicateto other researchers the likelihood of detecting an effect that was there. If thatlikelihood was low, then the research community may wish to suspend judgmentregarding the meaning of your findings until a more powerful replicationof your study is carried out. On the other hand, a statistically nonsignificantresult from a study with sufficient power may suggest to the research communitythat this is an effect not worth pursuing.NHST: COMPARING TWO MEANS• The appropriate inferential test when comparing two means obtained fromdifferent groups of subjects is a t-test for independent groups.• A measure of effect size should always be reported when NHST is used.• The appropriate inferential test when comparing two means obtained fromthe same subjects (or matched groups) is a repeated measures (withinsubjects)t-test.We now illustrate the use of NHST when comparing the difference betweentwo means. First, we consider a research study involving two independentmeans. The data for this study are from our example vocabularystudy, which we described in Chapter 11. Then we consider a situation wherethere are two dependent means, that is, when a repeated measures designwas used.