In the context of existing "quantitative"/"qualitative" schisms, this paper briefly reminds readers of the current practice of testing for statistical significance in social science research. This practice is based on a widespread confusion between two conditional probabilities. A worked example and other elements of logical argument demonstrate…

In elementary books on applied statistics (e.g., Siegel, 1988; Agresti, 1990) and books on research methodology in psychology and personality assessment (e.g., Aiken, 1999), it is often suggested that the choice of a statistical test and the choice of statistical operations should be determined by the level of measurement of the data. Although…

The present paper discusses criticisms of statistical significance testing from both historical and contemporary perspectives. Statistical significance testing is greatly influenced by sample size and often results in meaningless information being over-reported. Variance-accounted-for-effect sizes are presented as an alternative to statistical…

The purposes of the present paper are to address the historical development of statistical significance testing and to briefly examine contemporary practices regarding such testing in the light of these historical origins. Precursors leading to the advent of statistical significance testing are examined as are more recent controversies surrounding…

This paper examines some of the implications of testing for statistical significance. After considering methodological issues raised by two examples from the literature, the paper proceeds to look in detail at a variety of misunderstandings attached to the reporting of "significant" results. It is concluded that significance testing is of limited…

Despite its widespread use in evaluation data analysis, statistical testing has come under persistent criticism resulting in calls for its rethinking, and even possible elimination (Carver, 1978, 1993). Saxon and Boylan issue a call "to strengthen developmental education research and to make it more accessible" (2003, p. 2). Among the types of…

A general Computer program is described that will compute asymptotic standard errors and carry out significance tests for an endless variety of (standard and) nonstandard large-sample statistical problems, without requiring the statistician to derive asymptotic standard error formulas. The program assumes that the observations have a multinormal…

Because of criticisms leveled at statistical hypothesis testing, some researchers have argued that measures of effect size should replace the significance-testing practice. We contend that although effect-size measures have logical appeal, they are also associated with a number of limitations that may result in problematic interpretations of them…

Too few researchers understand what statistical significance testing does and does not do, and consequently their results are misinterpreted. This Digest explains the concept of statistical significance testing and discusses the meaning of probabilities, the concept of statistical significance, arguments against significance testing,…