A primer on the understanding, use, and calculation of confidence intervals that are based on central and noncentral distributions

Reform of statistical practice in the social and behavioral sciences requir es wider use of confidence intervals (CIs), effect size measures, and meta- analysis. The authors discuss four reasons for promoting use of CIs: They ( a) are readily interpretable, (b) are linked to familiar statistical signif icance tests, (c) can encourage meta-analytic thinking, and (d) give inform ation about precision. The authors discuss calculation of Cls for a basic s tandardized effect size measure, Cohen's delta (also known as Cohen's d), a nd contrast these with the familiar CIs for original score means. CIs for d elta require use of noncentral t distributions, which the authors apply als o to statistical power and simple meta-analysis of standardized effect size s. They provide the ESCI graphical software, which runs under Microsoft Exc el, to illustrate the discussion. Wider use of CIs for delta and other effe ct size measures should help promote highly desirable reform of statistical practice in the social sciences.