This volume addresses the provocative issue of how to assess & interpret data in a way that will best serve theory and application. Both positive and negative stances are represented, as are alternatives. For all social scientists and statisticians.

Lisa L. Harlow, Stanley A. Mulaik, James H. Steiger

Contents: Preface. Part I: Overview.L.L. Harlow, Significance Testing Introduction and Overview. Part II: The Debate: Against and For Significance Testing.J.Cohen, The Earth Is Round. F.L. Schmidt, J. Hunter, Eight Objections to the Discontinuation of Significance Testing in the Analysis of Research Data. S.A. Mulaik, N.S. Raju, R. Harshman, There Is a Time and Place for Significance Testing. R.P. Abelson, A Retrospective on the Significance Test Ban of 1999 (If There Were No Significance Tests, They Would Be Invented). Part III: Suggested Alternatives to Significance Testing.R.J. Harris, Reforming Significance Testing via Three-Valued Logic. J.S. Rossi, Spontaneous Recovery of Verbal Learning: A Case Study in the Failure of Psychology as a Cumulative Science. J.H. Steiger, R.T. Fouladi, Noncentrality Interval Estimation and the Evaluation of Statistical Models. R.P. McDonald, Goodness of Approximation in the Linear Model. Part IV: A Bayesian Approach to Hypothesis Testing.R.M. Pruzek, An Introduction to Bayesian Inference and Its Application. D. Rindskopf, Testing 'Small,' Not Null, Hypotheses: Classical and Bayesian Approaches. C.S. Reichardt, H.F. Gollob, When Confidence Intervals Should Be Used Instead of Statistical Significance Tests, and Vice Versa. Part V: Philosophy of Science Issues.W.W. Rozeboom, Good Science Is Abductive, Not Hypothetico-Deductive. P.E. Meehl, The Problem Is Epistemology, Not Statistics: Replace Significance Tests by Confidence Intervals and Quantify Accuracy of Risky Numerical Predictions.