Business Statistics and Analytics

Ronald M. Miller, PhD Bonnie C. Allred Dalley Megan Costantino

A statistically polished answer is not yet a defensible decision. This resource teaches business students to tell the difference. Using the CARE framework, students learn to ask whether data is credible, the analysis appropriate, the interpretation responsible, and the action ethical and effective, then report findings in a decision-focused business write-up. The resource builds from descriptive statistics, probability, and inference through ANOVA, regression, forecasting, clustering, and machine learning, including decision trees, neural networks, and large language models. Students run analyses in both R and Python, finishing able to interpret data, challenge weak conclusions, and drive results in any organization.