The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

The Journal of Agricultural Education (JAE) requires authors to follow the guidelines stated in the Publication Manual of the American Psychological Association [APA] (2009) in preparing research manuscripts, and to utilize accepted research and statistical methods in conducting quantitative research studies. The APA recommends the reporting of…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

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…

This paper examines the problems caused by relying solely on statistical significance tests to interpret results in contemporary social science. The place of significance testing in educational research has often been debated. Among the problems in reporting statistical significance are questions of definition and terminology. Problems are also…

This paper summarizes an experiment conducted to examine the counting performance of 7- and 8-year-olds. Analysis of variance was computed on counting errors produced when enumerating a set of squares on a computer screen. The factors included in the analysis were age, gender, array size, error type, proximity, and error form. The primary…

Problems with using stepwise analytic methods are discussed, and better alternatives are illustrated. To make the illustrations concrete, an actual data set, involving responses of 91 medical school admissions directors to 30 variables, was used. The 30 variables involved perceptions of barriers to medical school with respect to characteristics of…

Magnitude of effect measures (MEMs), when adequately understood and correctly used, are important aids for researchers who do not want to rely solely on tests of statistical significance in substantive result interpretation. The MEM tells how much of the dependent variable can be controlled, predicted, or explained by the independent variables.…

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,…

Discusses how to examine and evaluate claims of improved academic performance in advertisements for computer-assisted instruction. Highlights include the proper use of comparison groups; types of statistical analyses; the Hawthorne effect; the interpretation of scores; interpreting graphic presentations; tests of significance; and cost…