Q methodology is a method to systematically study subjective matters such as thoughts and beliefs on any given topic. Q methodology can be used for both theory building and theory testing. The purpose of this paper was to give a brief overview of Q methodology to readers with various backgrounds. This paper discussed several advantages of Q…

In measurement theory, causal indicators are controversial and little understood. Methodological disagreement concerning causal indicators has centered on the question of whether causal indicators are inherently sensitive to interpretational confounding, which occurs when the empirical meaning of a latent construct departs from the meaning…

Data is critical, but data has not always lead to success. If data is not communicated clearly, the results can be disastrous. Design lets us communicate data so it can be understood. Dr. Rankin believes that "when we're fluent in visualizing our ideas, we can communicate them across global boundaries, across spoken language barriers, and…

Building on the work of Bollen (2007) and Bollen & Bauldry (2011), Bainter and Bollen (this issue) clarifies several points of confusion in the literature regarding causal indicator models. This author would certainly agree that the effect indicator (reflective) measurement model is inappropriate for some indicators (such as the social…

Purpose: The purpose of this paper is to examine current approaches to interpretation of student evaluation data and present an innovative approach to developing benchmark targets for the effective and efficient use of these data. Design/Methodology/Approach: This article discusses traditional approaches to gathering and using student feedback…

How do university students understand the graphs that they read in their textbooks? How does their knowledge regarding the content and their statistical training influence this understanding? Does the kind of task demand also influence this understanding? To answer these questions, we asked a group of psychology students and a group of economics…

In a series of 3 experiments, the authors investigated the influence of symmetry of variables on children's and adults' data interpretation. They hypothesized that symmetrical (i.e., present/present) variables would support correct interpretations more than asymmetrical (i.e., present/absent) variables. Participants were asked to judge covariation…

We present considerations for validity when a population outside of a normed sample is assessed and those data are interpreted. Using a career group counseling example exploring life satisfaction changes as evidenced by the Quality of Life Inventory (Frisch, 1994), we showcase qualitative and quantitative approaches to explore how normative data…

Autistic traits are widely thought to operate along a continuum. A taxometric analysis of Adult Autism Spectrum Quotient data was conducted to test this assumption, finding little support but identifying a high severity taxon. To understand this further, latent class and latent profile models were estimated that indicated the presence of six…

Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…

Data are becoming increasingly important in science and society, and thus data literacy is a vital asset to students as they prepare for careers in and outside science, technology, engineering, and mathematics and go on to lead productive lives. In this paper, we discuss why the strongest learning experiences surrounding data literacy may arise…

This case study presents an example of using a generalized linear model with a log-linear link to calculate an adjusted risk ratio to be able to assess the association between educational attainment and obesity in a cohort study of American adults. Both risk ratios and odds ratios can be calculated based on cohort study data, and risk ratios are…

Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps…

As literature has reported, it is usual that university students in statistics courses, and even statistics teachers, interpret the confidence level associated with a confidence interval as the probability that the parameter value will be between the lower and upper interval limits. To confront this misconception, class activities have been…

Lab activities are an important element of an undergraduate physics course. In these lab activities, students construct and interpret graphs in order to connect the procedures of the lab with an understanding of the related physics concepts. This study investigated undergraduate students' construction and interpretation of graphs with best-fit…