In praise of Table 1: The importance of making better use of descriptive statistics

As data analytic methods in the managerial sciences become more sophisticated, the gap between the descriptive data typically presented in Table I and the analyses used to test the principal hypotheses advanced has become increasingly large. This contributes to several problems including: (I) the increasing likelihood that analyses presented in published research will be performed and/or interpreted incorrectly, (2) an increasing reliance on statistical significance as the principal criterion for evaluating results, and (3) the increasing difficulty of describing our research and explaining our findings to non-specialists. A set of simple methods for assessing whether hypotheses about interventions, moderator relationships and mediation, are plausible that are based on the simplest possible examination of descriptive statistics are proposed.