Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg offers a comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events,…

Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…

This study explores the use of generative AI, specifically ChatGPT, in statistical data analysis and its implications for statistics education at universities of applied sciences. This paper begins with first discussing the future division of labor between humans and machines in the context of statistical data analyses following the widespread…

In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…

We discuss our experience in teaching data analytics, and in particular prescriptive analytics, to students in business schools using an inter-coherent case study, where a managerial decision is decomposed into a series of research problems with interlocking analyses and the outcome of one analysis is the input of other analysis. Students who…

The design and analysis of experiments (DOE) has historically been an important part of an education in statistics, and with the increasing complexity of modern production processes and the advent of large-scale online experiments, it continues to be highly relevant. In this article, we provide an extensive review of the literature on DOE…

With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…

Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…

At the school level statistics begins with exploratory data analysis, or EDA. Statistical learning goes on to include statistical inference, which will be discussed in the second part of this article. In this article, the author will talk about EDA and CODAP. EDA can be thought of as looking for patterns in data using graphs and simple statistics…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…

The flipped classroom (FC) is a pedagogical model with an active learning concept and a hybrid course design that reverses the typical lecture process. Given the widespread use of online delivery methods, there is a need to explore the FC in delivering statistics courses. This study employs a prospective quasi-experimental study design to evaluate…

Data Analytics has emerged as an essential skill for business students, and several tools are available to support their learning in this area. Due to the students' lack of programming skills and the perceived complexity of R, many business analytics courses employ no-code analytical software like IBM SPSS Modeler. Nonetheless, generative…

Purpose: The purpose of this dissertation is to investigate the feasibility of using tests of robustness in peer review. This study involved selecting three high-impact papers which featured open data and utilized bioinformatic analyses but provided no source code and refactoring these to allow external survey participants to swap tools,…

The main goal of this study was to evaluate the impact of an animation and visualization of data structures (AVDS) tool on both perceptions and objective test performance. The study involved a rigorous experiment that assessed the usability, acceptability, and effectiveness of the AVDS tool in solving exercises. A total of 78 participants…