Principal Component Analysis (PCA) is a powerful statistical technique for reducing the complexity of data and making patterns and relationships within the data more easily understandable. By using PCA, students can learn to identify the most important features of a data set, visualize relationships between variables, and make informed decisions…

This short paper presents an educational approach to teaching three popular methods for encoding DNA sequences: one-hot encoding, binary encoding, and integer encoding. Aimed at bioinformatics and computational biology students, our learning intervention focuses on developing practical skills in implementing these essential techniques for…

This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…

Introduction: Interrupted Time Series (ITS) studies may be used to assess the impact of an interruption, such as an intervention or exposure. The data from such studies are particularly amenable to visual display and, when clearly depicted, can readily show the short- and long-term impact of an interruption. Further, well-constructed graphs allow…

Enzymes are nature's catalysts, mediating chemical processes in living systems. The study of enzyme function and mechanism includes defining the maximum catalytic rate and affinity for substrate/s (among other factors), referred to as enzyme kinetics. Enzyme kinetics is a staple of biochemistry curricula and other disciplines, from molecular and…

Development of graphical methods for representing data has not kept up with progress in statistical techniques. This article presents a brief history of graphical representations of research findings and makes the case for a revival of methods developed in the early and mid-twentieth century, notably ISOTYPE and Chernoff's faces. It resurrects and…

In this article we discuss the use of RapidMiner, a data science software platform, in a Database Management Systems course. For further understanding of the database and the skill learned, students are given an assignment to complete, to not only use another software beside SQL Server Management Studio but also translate their findings in a more…

The article presents an open educational resource (OER) to introduce humanities students to data analysis with Python. The article beings with positioning the OER within wider pedagogical debates in the digital humanities. The OER is built from our research encounters and committed to computational thinking rather than technicalities. Furthermore,…

With the emergence of COVID-19, public interest in data visualization has surged. Data visualizations also, importantly, raised questions related to the data and the social context in which it occurred. Extending beyond but remaining connected to COVID-19, this context involved the racial and social inequality and economic disparities brought to…

Best practices in statistics and data science courses include the use of real and relevant data as well as teaching the entire data science cycle starting with importing data. A rich source of real and current data is the web, where data are often presented and stored in a structure that needs some wrangling and transforming before they can be…

At the stage of designing an educational environment, one of the most significant problems is the creation of effective visualization tools for collecting, organizing and analysing educational information. Existing approaches to visual information analysis have a number of disadvantages, which include a significant resource intensity and high…

Over the last 20 years, statistics preparation has become vital for a broad range of scientific fields, and statistics coursework has been readily incorporated into undergraduate and graduate programs. However, a gap remains between the computational skills taught in statistics service courses and those required for the use of statistics in…

"Data science" is a discipline that provides principles, methodology, and guidelines for the analysis of data for tools, values, or insights. Driven by a huge workforce demand, many academic institutions have started to offer degrees in data science, with many at the graduate, and a few at the undergraduate level. Curricula may differ at…

We describe a "Day of Giving" university fundraising event that can be used to introduce data visualization to undergraduate students. The project involves integrating data sources, creating a Tableau data model, and designing a heat map that can be embedded into a front-end website. Our activity provides opportunities to discuss various…

In this project, students asked and attempted to answer questions about themselves by collecting and analyzing data. With the prevalence of big data and business analytics, managers have data and quantitative information available more immediately than ever. However, managers need to understand how to use this information. In this project,…