Why Figures with Error Bars Should Replace p Values Some Conceptual Arguments and Empirical Demonstrations

Null-hypothesis significance testing (NHST) is the primary means by which data are analyzed and conclusions made, particularly in the social sciences, but in other sciences as well (notably ecology and economics). Despite this supremacy however, numerous problems exist with NHST as a means of interpreting and understanding data. These problems have been articulated by various observers over the years, but are being taken seriously by researchers only slowly, if at all, as evidenced by the continuing emphasis on NHST in statistics classes, statistics textbooks, editorial policies and, of course, the day-to-day practices reported in empirical articles themselves (Cumming et al., 2007). Over the past several decades, observers have suggested a simpler approach - plotting the data with appropriate confidence intervals (CIs) around relevant sample statistics - to supplement or take the place of hypothesis testing. This article addresses these issues.