Data Analysis with Minitab: Analyze & Apply

Overview

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.

Syllabus

Foundations of Predictive Analysis with Minitab

This module introduces learners to the core principles of predictive modeling, regression techniques, ANOVA analysis, and practical implementation using Minitab. Participants will explore how to interpret statistical outputs, compare variations across datasets, and document meaningful observations to support data-driven decisions.

Applied Statistics and Real-World Scenarios

This module focuses on applying descriptive statistics, hypothesis testing, and real-world case studies to develop practical insights. Learners will work with datasets on customer complaints, resting heart rates, and loan applicants to master statistical testing and decision-making using Minitab.