This module introduces learners to the core foundations of Six Sigma, highlighting its history, principles, and integration with Lean methodology. Learners will explore the prestige of Six Sigma certifications, understand the differences between Lean and Six Sigma, and identify key process improvement methods such as the Seven Wastes (Muda) and Just-In-Time (JIT). By mastering these essentials, participants build a strong knowledge base for applying Six Sigma to real-world quality improvement initiatives.

This module explores the practical application of Six Sigma in defining processes, assigning ownership, and aligning quality outcomes with organizational goals. Learners will gain insights into process components, project frameworks, and the importance of CTQ (Critical to Quality) and CTC (Critical to Customer) factors. Additionally, the module emphasizes structured project selection methods and the use of statistics to ensure that limited resources are directed toward the most impactful quality improvement initiatives.

This module equips learners with advanced statistical tools and data-driven techniques essential for Six Sigma mastery. Participants will explore graphical analysis, probability concepts, and normality testing to evaluate process performance. The module also covers correlation, regression, and handling of non-normal distributions, enabling practitioners to build predictive models and uncover relationships within data. Finally, learners will apply hypothesis testing, determine correct sample sizes, and set statistical guidelines to ensure reliable, evidence-based decision-making in quality improvement projects.