Gibbs sampling was applied to obtain Bayes inferences in the case of unbalanced multilevel data when the homogeneity of variance assumption fails and when interest focuses on inferences for some or all of the groups' variances. This approach is compared to a more standard analysis based on restricted maximum-likelihood statistics. (SLD)

A solid understanding of "inferential statistics" is of major importance for designing and interpreting empirical results in any scientific discipline. However, students are prone to many misconceptions regarding this topic. This article structurally summarizes and describes these misconceptions by presenting a systematic review of publications…

Probability is an important idea with a remarkably wide range of applications. However, psychological and instructional studies conducted in the last two decades have consistently documented poor understanding of probability among different populations across different settings. The purpose of this study is to develop a theoretical framework for…

Using Microsoft® Excel, several interactive, computerized learning modules are developed to illustrate the Central Limit Theorem's appropriateness for comparing the difference between the means of any two populations. These modules are used in the classroom to enhance the comprehension of this theorem as well as the concepts that provide the…

This study examined the internal consistency and validity of a new rating scale to identify gifted students, the Gifted Rating Scales-School Form (GRS-S). The study explored the effect of gender, race/ethnicity, age, and rater familiarity on GRS-S ratings. One hundred twenty-two students in first to eighth grade from elementary and middle schools…

The increased use of effect sizes in single studies and meta-analyses raises new questions about statistical inference. Choice of an effect-size index can have a substantial impact on the interpretation of findings. The authors demonstrate the issue by focusing on two popular effect-size measures, the correlation coefficient and the…

Reports the results of a study that shows that the factors explaining experts' risk perception are similar to those of a comparable group of non-topical experts with a similar level of technological literacy and to the general public, and that the level of explained variance is quite comparable for experts and the general public. (Contains 32…

Considers objections to comparisonwise position, which holds that, when conducting simultaneous significance procedures, per-test Type I error rate should be controlled and that it is unnecessary to introduce adjustments designed to control familywise rate. Objections collected by Saville in an attempt to refute them are discussed along with…

There is a trend toward abandoning traditional parametric approaches to data analysis, with all their restrictive assumptions, in favor of computer-intensive nonparametric inferential statistical procedures, such as the jackknife and the bootstrap that are based on resampling of the sample data. These techniques are compared with the parametric…

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…

This study presents the results of a partial credit Rasch analysis of in-depth interview data exploring statistical understanding of 73 school students in 6 contextual settings. The use of Rasch analysis allowed the exploration of a single underlying variable across contexts, which included probability sampling, representation of temperature…

Developed a closed form expression for the asymptotic bias of the explained common variance, or the unexplained common variance under assumptions of multivariate normality in minimum rank factor analysis. Findings from existing data sets show that the presented asymptotic statistical inference is based on a recently developed perturbation theory…

Introduces a new inferential test for acyclic structural equation models (SEM) without latent variables or correlated errors. The test is based on the independence relations predicted by the directed acyclic graph of the SEMs, as given by the concept of d-separation. A wide range of distributional assumptions and structural functions can be…

Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…

Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and…