Exploratory graph analysis (EGA) is a commonly applied technique intended to help social scientists discover latent variables. Yet, the results can be influenced by the methodological decisions the researcher makes along the way. In this article, we focus on the choice regarding the number of factors to retain: We compare the performance of the…

Avoiding statistical mistakes is important for educators at all levels. Basic concepts will help you to avoid making mistakes using statistics and to look at data with a critical eye. Statistical data is used at educational institutions for many purposes. It can be used to support budget requests, changes in educational philosophy, changes to…

Highlights effective graphical methods for screening and cleaning data, exploring and identifying models, and displaying data in counseling-psychology publications. Argues that graphs are not ancillary to scientific publications but are essential and, in some cases, sufficient expositions of results. (Author/GCP)

Although single-subject research techniques are valuable to counselors, analyzing change by graphs alone is open to major sources of error. Discusses these sources and explores the issues of serial dependency, unreliability of graphs, interjudge disagreement on graphed data, and the use of time-series statistics with relevance to the counselor in…

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…

Provides a brief overview of single-subject research designs. This method exercises its power by examining changes in single subjects' responses over time across experimental conditions. Describes a classroom project in which students collect repeated measures of their own behavior and graph the data. (MJP)