Canonical correlation analysis is illustrated and three common fallacious interpretation practices are described. Simply, canonical correlation is an example of the bivariate case. Like all parametric methods, it involves the creation of synthetic scores for each person. It presumes at least two predictor variables and at least two criterion…

Responds to Biskin's comments (this issue) on the significance test controversy. Highlights areas of agreement (importance of replication evidence, importance of effect sizes) and disagreement (influence of sample size, evaluation of populations vs. samples, significance of Carver's article). Includes further recommendations for reporting research…

Introduces the three subsequent articles from this special section, which extend the discussion of future prospects for progress in the reporting and interpreting of effect sizes by researchers. The authors of these pieces represent diverse views. (SLD)

Web-based statistical instruction, like all statistical instruction, ought to focus on teaching the essence of the research endeavor: the exercise of reflective judgment. Using the framework of the recent report of the American Psychological Association (APA) Task Force on Statistical Inference (Wilkinson and the APA Task Force on Statistical…

The use of tests of statistical significance was explored, first by reviewing some criticisms of contemporary practice in the use of statistical tests as reflected in a series of articles in the "American Psychologist" and in the appointment of a "Task Force on Statistical Inference" by the American Psychological Association…

This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…