Minitab Applied Statistics & Hypothesis Testing Mastery

By the end of this course, learners will be able to analyze how multiple predictors influence a response variable, interpret regression outputs using Minitab, compare alternative regression models, and translate statistical findings into actionable business insights. Learners will develop the ability to evaluate predictor significance, visualize relationships, and select appropriate regression models to support data-driven decision-making. This course provides a practical, hands-on approach to regression analysis through a real-world Tech Mahindra case study. Rather than focusing on theory alone, learners work step-by-step through an end-to-end analytics project—starting from problem framing and exploratory analysis to model refinement and comparison. Using Minitab, learners gain experience interpreting regression coefficients, p-values, and visual diagnostics such as scatter plots to understand predictor–response relationships. What makes this course unique is its strong business orientation and project-based structure. Learners not only build and compare linear and quadratic regression models but also learn how to justify model choices based on both statistical performance and business relevance. This course is ideal for professionals and students seeking to strengthen applied regression skills and confidently use Minitab for real-world analytical challenges.

By the end of this course, learners will be able to analyze datasets, interpret statistical results, apply inferential methods, evaluate measurement systems, and monitor process performance using Minitab. Learners will develop the ability to select appropriate statistical tools, validate assumptions, and make data-driven decisions across quality, engineering, and business contexts. This course provides a structured, end-to-end journey through statistical analysis using Minitab, starting from foundational concepts such as data types, descriptive statistics, and data visualization, and progressing to probability distributions, sampling, hypothesis testing, regression, and process control. Through step-by-step demonstrations aligned with real-world scenarios, learners gain both conceptual clarity and practical proficiency. What makes this course unique is its progressive, practice-oriented design that bridges beginner concepts to advanced applications such as Measurement System Analysis (MSA), Process Capability Analysis, ANOVA, and Control Charts. Each topic is carefully sequenced to build confidence while reinforcing analytical thinking. Whether learners are new to statistics or seeking to strengthen their applied skills, this course equips them with industry-relevant statistical competence using Minitab.