The author discusses the importance of statistical significance to researchers and suggests that researchers should consider an additional statistic, the magnitude of effect index. (MK)

Problems inherent in relying solely on statistical significance testing as a means of data interpretation are reviewed. The biggest problem with statistical significance testing is that researchers have used the results of this testing to ascribe importance or meaning to their studies where such meaning often does not exist. Often researchers…

The disparity between methodology and empirical research literature is examined to suggest a cause for the casual acceptance of null hypotheses simply because obtained differences are not statistically significant. Analysis of training for psychological researchers suggests that programs have not emphasized the comprehensive evaluation of all…

Two articles discuss the controversy about the relationship between reliability and the power of significance tests in response to the discussion of Donald W. Zimmerman, Richard H. Williams, and Bruno D. Zumbo. Lloyd G. Humphreys emphasizes the differences between what statisticians can do and constraints on researchers. Zimmerman, Williams, and…