We present an interactive spreadsheet that supports teaching essential concepts in classification using the logistic regression (LoR) model for binary classification. The interactive spreadsheet demonstrates the capabilities of LoR by integrating computation with visualization. Students will reinforce concepts like probabilities, maximum…

In response to research indicating a need for an increased emphasis on aspects of corporate accounting, including corporate taxation, in the accounting curriculum as well as employer expectations that entry-level accounting position applicants possess Excel skills, this classroom exercise uses Excel to compare the financial impacts of three…

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…

There is an increasing demand to introduce Introductory Business Analytics (IBA) courses into undergraduate business education. Many real-world business contexts require predictive analytics to understand the determinants of a dichotomous outcome; hence, IBA courses should include binary logistic regression analysis. This article provides our…

Data Analytics has grown dramatically in importance and in the level of business deployments in recent years. It is used across most functional areas and applications, some of the latter including market campaigns, detecting fraud, determining credit, identifying assembly line defects, health services and many others. Indeed, the realm of…

There are a variety of discrete facility location models that have practical relevance for operations management and management science courses. Integer linear programming (ILP) is the standard technique for solving such problems. An alternative approach that is often conceptually appealing to students is to pose the problem as one of finding the…

Chemistry is increasingly data centric and the undergraduate curriculum needs to adjust to keep up. To address this, we created the "Air Quality Activity," a new first-year undergraduate activity where students use Microsoft Excel to analyze a unique subset of atmospheric ozone (O[subscript 3]) and nitrogen dioxide (NO[subscript 2])…

The drive in computational methods and more intuitive software has seen a rise in the number of publications in this area in recent years. Computational simulations can be found in many areas of science from computational biology and chemistry to fundamental physics. These may help synthetic chemists in their drug discovery endeavors and…

Logistic regression is one of the most fundamental tools in predictive analytics. Graduate business analytics students are often familiarized with implementation of logistic regression using Python, R, SPSS, or other software packages. However, an understanding of the underlying maximum likelihood model and the mechanics of estimation are often…

Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the…

Addressing societal issues in civil and environmental engineering increasingly requires skills in data science and programming. To date, there is not much known about the extent students are learning these skills in current civil and environmental engineering curricula. We conducted a survey of accredited civil and environmental engineering…

Collecting data on learners' performance in different chemistry contents and analysing them to identify their knowledge and understanding in related content areas is a major task of Chemistry Education Research. The data collection process on the learners' content knowledge and understanding of content knowledge requires a standard measuring tool.…

A laboratory experiment characterized by a whole-class data-pooling approach to generate a data set that can be used to test a model of the influence of ionic strength on electrolyte solubility is described and discussed. The design of the experiment makes efficient use of the laboratory period and releases time for instructional and dialogic…

Powder diffraction is one of the most widely used analytical techniques for characterizing solid state materials. It can be used for phase or polymorph identification, quantitative analysis, cell parameter determination, or even full crystal structure analysis using the powerful Rietveld refinement method. As with much of modern crystallography,…

Scientific Data Analysis Toolkit (SDAT) is a rigorous, versatile, and user-friendly data analysis add-in application for Microsoft Excel for Windows (PC). SDAT uses the familiar Excel environment to carry out most of the analytical tasks used in data analysis. It has been designed for student use in manipulating and analyzing data encountered in…