Denise B. Dillon

Statistics Anxiety Update Refining the Construct and Recommendations for a New Research Agenda

Appreciation of the importance of statistics literacy for citizens of a democracy has resulted in an increasing number of degree programs making statistics courses mandatory for university students. Unfortunately, empirical evidence suggests that students in nonmathematical disciplines (e.g., social sciences) regard statistics courses as the most anxiety-inducing course in their degree programs. Although a literature review exists for statistics anxiety, it was done more than a decade ago, and newer studies have since added findings for consideration. In this article, we provide a current review of the statistics anxiety literature. Specifically, related variables, definitions, and measures of statistics anxiety are reviewed with the goal of refining the statistics anxiety construct. Antecedents, effects, and interventions of statistics anxiety are also reviewed to provide recommendations for statistics instructors and for a new research agenda.

A health social network recommender system

People with chronic health conditions require support beyond normal health care systems. Social networking has shown great potential to provide the needed support. Because of the privacy and security issues of health information systems, it is often difficult to find patients who can support each other in the community. We propose a social-networking framework for patient care, in particular for parents of children with Autism Spectrum Disorders (ASD). In the framework, health service providers facilitate social links between parents using similarities of assessment reports without revealing sensitive information. A machine learning approach was developed to generate explanations of ASD assessments in order to assist clinicians in their assessment. The generated explanations are then used to measure similarities between assessments in order to recommend a community of related parents. For the first time, we report on the accuracy of social linking using an explanation-based similarity measure.

An examination of the internal consistency and structure of the Statistical Anxiety Rating Scale (STARS)

The purpose of the current study was to examine the internal consistency and structure of the English version of the Statistical Anxiety Rating Scale (STARS). Participants were 202 (79% females) psychology undergraduates was recruited from James Cook University’s Singapore (71%) and Australia (29%) campuses. Acceptable internal consistency reliabilities, ranging from .81 to .94, were found in this sample. Approximate fit indices suggest that a correlated six first-order factor model best describes the data in contrast to theoretical considerations suggesting that a six factor model with two correlated superordinate factors (i.e., statistics anxiety and attitudes toward statistics) best describes the data. Researchers are recommended to use part one of the STARS to assess statistics anxiety and part two to assess attitudes toward statistics.

Deer who are distant: Response congruency to relative pronouns across human and nonhuman entities

The study explores the influence of relative pronouns WHO or THAT on attributions of humanness across four categories of entities (unnamed nonhuman animals, named animals, machines, and people). Eighty-three university students performed an attribution task where they saw a priming phrase containing one category item with either WHO or THAT (e.g., deer who are …) and then two trait attribute items (Uniquely Human UH /Human Nature HN word pairs; e.g., distant-nervous), from which they selected the trait attribute most meaningfully suited to the phrase. Data were analyzed with a repeated measures 2 (humanness: HN traits, UH traits) × 2 (pronoun: WHO , THAT ) × 4 (category: unnamed animals, named animals, machines, people) ANOVA . Participants responded relatively faster to HN trait attributes than to UH traits, and responded faster to named animals than to all other entities. Faster responses also ensued for people- WHO pairings than people- THAT pairings, and vice versa for named animals.

Deer Who Are Distant

The study explores the influence of relative pronouns WHO or THAT on attributions of humanness across four categories of entities (unnamed nonhuman animals, named animals, machines, and people). Eighty-three university students performed an attribution task where they saw a priming phrase containing one category item with either WHO or THAT (e.g., deer who are …) and then two trait attribute items (Uniquely Human UH /Human Nature HN word pairs; e.g., distant-nervous), from which they selected the trait attribute most meaningfully suited to the phrase. Data were analyzed with a repeated measures 2 (humanness: HN traits, UH traits) × 2 (pronoun: WHO , THAT ) × 4 (category: unnamed animals, named animals, machines, people) ANOVA . Participants responded relatively faster to HN trait attributes than to UH traits, and responded faster to named animals than to all other entities. Faster responses also ensued for people- WHO pairings than people- THAT pairings, and vice versa for named animals.

Psychometric properties of the Statistical Anxiety Scale among students in Singapore and Australia

The purpose of the current study was to examine the reliability and validity of the Statistical Anxiety Scale (SAS) among a sample of Singapore and Australia psychology undergraduates. Participants were 163 undergraduates (78.5% female) in the James Cook University Psychology programs at the Australia (33.1 %) and Singapore (66.9%) campuses. Acceptable internal consistency reliabilities, ranging from 0.89 to 0.95 for the factors and for the total scale of the SAS, were found in the current study. Exploratory factor analysis identified a three-factor structure, with the same eight items on each factor as identified by the authors of the scale. The results provided support for the use of the SAS among Singapore and Australia psychology undergraduates. Limitations include the exploratory nature of the study and non-generalizabilty of the results.

Individual Differences in Statistics Anxiety Among Students in Singapore

The purpose of the current study was to explore statistics anxiety among students in Singapore and the effect of individual differences on statistics anxiety. Participants were 65 psychology undergraduates (64 % female) enrolled in two statistics courses at James Cook University, Singapore campus. A series of t-tests revealed that the current sample reported significantly lower statistics anxiety than the UK sample but higher statistics anxiety than samples from China and Austria. MANOVA revealed a significant interaction effect between gender and prior statistics experience for the Computation Self-Concept Factor of statistics anxiety. Practical implications, limitations, and future research directions are discussed.