We analyze here the online and face-to-face teaching of mathematics and statistics at the university level and compare the results of students from two courses of applied mathematics. We examine the influence of online teaching on the performance of students with the help of grades from five consecutive years. A questionnaire on satisfaction with…

Publication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of…

Comparative Judgement (CJ) aims to improve the quality of performance-based assessments by letting multiple assessors judge pairs of performances. CJ is generally associated with high levels of reliability, but there is also a large variation in reliability between assessments. This study investigates which assessment characteristics influence the…

Heat maps have become ubiquitous in the media, yet students are rarely exposed to them and their inherent limitations and potential for misleading consumers. This article makes a case for exposing students to them in statistics instruction at the secondary and tertiary level.

Two approaches to causal inference in the presence of non-random assignment are presented: The Propensity Score approach which pseudo-randomizes by balancing groups on observed propensity to be in treatment, and the Endogenous Treatment Effects approach which utilizes systems of equations to explicitly model selection into treatment. The three…

In recent years, there have been calls for researchers to report and interpret confidence intervals (CIs) rather than relying solely on p-values. Such reforms, however, may be hindered by a general lack of understanding of CIs and how to interpret them. In this study, we assessed conceptual knowledge of CIs in undergraduate and graduate psychology…

When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allow efficient and accurate estimation of multilevel IRT models, we argue that a two-stage…

Random sampling and random allocation are essential processes in the practice of inferential statistics. These processes ensure that all members of a population are equally likely to be selected, and that all possible allocations in an experiment are equally likely. It is these characteristics that allow the validity of the subsequent calculations…

In recent years, there have been calls for researchers to report and interpret confidence intervals (CIs) rather than relying solely on p-values. Such reforms, however, may be hindered by a general lack of understanding of CIs and how to interpret them. In this study, we assessed conceptual knowledge of CIs in undergraduate and graduate psychology…

Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan), the likelihood is therefore specified as conditional on the latent variables. This can lead researchers to…

This study investigated factors that are associated with the creative motor skills of young children. We recruited through random sampling 233 typically developing children attending preschool or kindergarten in Afyonkarahisar, Turkey. We administered a "General Information Form" to gather the children's demographic characteristics and…

In this paper, we detail a convergent mixed-methods survey of faculty teaching applied social statistics courses, analyzed through a framework of learning theory. The survey explored faculty perceptions and use of recommended strategies for statistics education, perceived barriers to student success, and general recommendations for instruction in…

Large-scale language testing uses statistical information to account for the quality of an assessment system. In this reflection article, I explain how basic statistics can be used meaningfully in the context of classroom language assessment. The paper explores a series of statistical calculations that can be used to examine test scores and…

Teaching introductory statistics to postgraduate students from multidisciplinary background and with diverse mathematics ability is a huge challenge that many statistics lecturers do not deny. The large ability range can make it very difficult for lecturers to fine tune the right level for effective course delivery. Even though an introductory…

Accompanied by increasing demands on school administrator preparation and rapid development of computer technology, educational statistics courses are exposed to unprecedented pressures for changing both curriculum content and computing platforms. In this article, the intended curriculum is reviewed according to data analysis expectations from…