Learners will analyze complex datasets, interpret advanced regression outputs, evaluate predictive models, and apply decision tree techniques using Minitab to solve real-world business problems.

This course provides in-depth, hands-on training in advanced statistical modeling using Minitab, moving beyond basic analytics to practical, decision-focused applications. Learners explore linear, logistic, multinomial, and CART regression models, supported by scatter plots, model diagnostics, and real industry case studies. Through guided examples and structured analysis, learners develop the ability to select appropriate models, interpret statistical outputs, and translate analytical results into actionable business insights. What makes this course unique is its strong emphasis on interpretation, visualization, and real-world applicability rather than formula-driven theory alone. Industry-inspired case studies, such as market segmentation and healthcare analytics, reinforce practical understanding, while step-by-step decision tree modeling builds confidence in explainable AI techniques. By completing this course, learners gain job-ready skills in advanced data analysis, improve their statistical decision-making capabilities, and become proficient in using Minitab to support data-driven strategies across business, quality, and analytics roles.