Statistics in an MBA classroom can often feel like a “mathematical hurdle” rather than a strategic asset. To bridge this gap, I have moved away from traditional, formula-heavy lectures toward an experiential pedagogy titled “From Numbers to Narratives.” The goal? To transform Multiple Linear Regression (MLR) from a complex equation into a vital managerial decision-making tool.
The Shift to “Learning by Doing”
Most students can run a regression on software, but few can explain what the coefficients mean for a brand’s bottom line. My approach centres on three key stages:
Conceptual Foundation: We start with the “why” before the “how,” using Excel and SPSS to demystify R-squared and p-values through real business cases.
The Data Hunt: Instead of providing “clean” textbook data, students source their own datasets from platforms like Kaggle or the World Bank. This forces them to navigate the messy reality of data cleaning and variable selection.
The Pitch: Students do not just hand in a spreadsheet; they present a professional PowerPoint. They must translate statistical outputs into actionable strategic recommendations.
Why It Works
By grounding the curriculum in Kolb’s Experiential Learning Theory, students move up Bloom’s Taxonomy—from merely understanding a formula to creating business insights. They stop being “statistical operators” and start becoming “analytical storytellers.”
The result? Students leave the classroom not just with a grade, but with the confidence to use data to drive real-world impact.
About the author:
Professor, ABBS School of Management
