Publication bias threatens meta-analysis validity. It is often assessed via the funnel plot; an asymmetric plot implies small-study effects, and publication bias is one cause of the asymmetry. Egger's regression test is a widely used tool to quantitatively assess such asymmetry. It examines the association between the observed effect sizes and…

This article promotes Bayesian intuition by introducing the concept of shrinkage with some motivational examples involving basketball statistics of Rudy Gobert and movie rankings from the Internet Movie Database. Supplementary and fully automated R code is provided to allow students to explore shrinkage in this dataset on their own. The content is…

Performance management in university-based scientific research institutions is essential for driving reform, advancing education quality, and fostering innovation. However, current performance evaluation models often focus solely on research indicators, neglecting the critical interdependence between the education and research systems. This…

This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

Students may find poetry a surprisingly rich, engaging, and accessible vehicle to motivate and synthesize statistical content. We share and discuss a project and activities used in workshops or a college statistical literacy course.

For decades, calculus has towered over the high-school math landscape, its mastery viewed as the surest marker of high academic achievement. Yet in New England as across the nation, changes are underway: Statistics and data science courses are multiplying, and state leaders are re-engineering graduation rules so students can choose the pathway…

Purpose: This study aimed at identifying the prevalence of statistic anxiety among students in social sciences programs and analyzing the relationship between statistics anxiety and four key variables: attitude toward statistics, statistics self-efficacy, achievement in statistics and academic procrastination. Design/methodology/approach: Method a…

Background/purpose: Statistics courses represent a fundamental component in social sciences programs; however, many students encounter challenges in mastering statistical concepts due to anxiety, negative attitudes, and low self-efficacy. Understanding the prevalence of these factors is crucial for improving learning outcomes. This study aimed to…

Children rely on their Approximate Number System to intuitively perceive number. Such adaptations often exhibit sensitivity to real-world statistics. This study investigates a potential manifestation of the ANS's sensitivity to real-world statistics: a negative power-law distribution of objects in natural scenes should be reflected in children's…

The purpose of this review is to present what we know about paternalistic leadership (PL) in education. Systematic content analysis was adopted to identify the manifest and latent information across 29 identified empirical studies obtained through the core educational leadership and management journals and the two databases, Education Resources…

In today's world, educated individuals are expected to understand basic statistical concepts and interpret statistical messages. For this reason, despite the undeniable importance of statistical literacy in the educational process, studies on undergraduate and postgraduate students in practice reveal that students have difficulties in determining…

Statistically skilled workers are highly demanded in today's world, which means we need high-quality statistics education. There has been a continuously increased enrollment of statistics students. At the college level, introductory statistics courses are typically taught by professors who often hold a strong qualification in mathematics but may…

A compelling demonstration of implicit learning is the human ability to unconsciously detect and internalize statistical patterns of complex environmental input. This ability, called statistical learning, has been investigated in people with dyslexia using various tasks in different orthographies. However, conclusions regarding impaired or intact…

Prior studies investigating the effects of non-normality in structural equation modeling typically induced non-normality in the indicator variables. This procedure neglects the factor analytic structure of the data, which is defined as the sum of latent variables and errors, so it is unclear whether previous results hold if the source of…

This note demonstrates that the widely used Bayesian Information Criterion (BIC) need not be generally viewed as a routinely dependable index for model selection when the bifactor and second-order factor models are examined as rival means for data description and explanation. To this end, we use an empirically relevant setting with…