Predictive Analytics & Modeling with Minitab

Learners will be able to explain predictive modeling concepts, analyze group differences with ANOVA, interpret descriptive statistics, and conduct t-tests to evaluate relationships in real-world datasets. By completing this course, participants will strengthen their ability to summarize data, identify patterns, assess variability, and apply hypothesis testing using Minitab’s powerful statistical tools. This course provides a structured journey across two modules: Foundations of Predictive Analysis and Applied Statistics in Real-World Scenarios. Through practical lessons, learners will work with diverse case studies, including customer complaints, resting heart rate measurements, NAV price fluctuations, and loan applicant data. Each session emphasizes interpretation, ensuring participants can move beyond numbers to actionable insights. What makes this course unique is its balanced focus on statistical theory and hands-on implementation in Minitab, combined with real-life applications that mirror professional problem-solving. Designed for analysts, researchers, and professionals seeking to upskill, the course ensures learners gain both confidence and competence in making data-driven decisions that create measurable impact.

By completing this course, learners will be able to apply predictive modeling, perform hypothesis testing, analyze correlations, and build regression models to interpret complex datasets. They will gain skills in statistical tools such as ANOVA, chi-square, t-tests, and control charts while learning to implement and interpret outputs using Minitab and Excel. The course equips learners with the ability to identify patterns, evaluate case-based insights, and apply statistical reasoning to real-world data such as customer complaints, loan applicants, health indicators, and financial performance metrics. Through structured modules, learners will progress from foundational concepts in predictive analytics to advanced regression techniques for decision-making. What makes this course unique is its strong emphasis on practical application and interpretation. Each module combines theory with real-world examples, ensuring learners can translate statistical outputs into actionable insights. By the end, learners will not only understand statistical models but also apply them effectively in business, finance, and research settings.