MINITAB
Specialization | 9 Course Series | 2 Mock Tests

This course delivers an in-depth learning experience in Minitab, one of the most trusted statistical tools used across industries such as business, engineering, quality management, and academic research. Through a well-structured series of modules, learners are guided from foundational concepts to advanced analytical practices, enabling them to confidently perform meaningful data exploration, statistical modeling, and predictive analysis.

Participants begin with the essentials navigating the Minitab interface, managing datasets, and applying basic statistical techniques. As they progress, they explore more complex tools including ANOVA, regression analysis, hypothesis testing, and a wide range of visualization and data-handling features. The program blends conceptual clarity with hands-on exercises, ensuring that learners not only understand key methods but can also apply them effectively in real decision-making scenarios.

Whether someone is just getting started with Minitab or looking to deepen their existing analytical skills, this course offers practical guidance and expert-driven insights to elevate their proficiency.

MODULE 1: Minitab Essentials Training

• Minitab for Beginners – 2023: Introduces new users to the software's interface, data import options, and fundamental statistical operations.
• Advanced Minitab Training – 2023: Expands on core knowledge with deeper coverage of hypothesis testing, ANOVA, and regression techniques.
• Advanced Minitab Training: Further strengthens analytical capabilities by exploring complex statistical tools, advanced data manipulation, and enhanced visualization features.

MODULE 2: Minitab Data Analytics & Statistics

• Minitab GUI and Descriptive Statistics: Focuses on effective GUI navigation, data entry, and descriptive analytics, including measures of spread, central tendency, and visual data summaries.
• Statistical Analysis using Minitab – Beginner: Teaches foundational statistical procedures, including hypothesis testing, confidence intervals, and interpreting Minitab-generated outputs.
• Minitab – Data Analytics: Covers sophisticated analytics methods such as factor analysis, clustering, and time series evaluation, along with guidance on data preparation and transformation.

MODULE 3: Minitab Regression & Predictive Modeling

• Predictive Analytics & Modeling with Minitab: Guides learners through building regression models, evaluating performance, and generating predictions using Minitab's predictive tools.
• Minitab Practical – Impact of Predictors on Outcomes: Provides hands-on practice in interpreting regression coefficients, assessing model accuracy, and extracting meaningful insights from predictor variables.
• Minitab Practical – Testing of Hypothesis: Focuses on conducting hypothesis tests, selecting appropriate methods, and interpreting statistical results through Minitab.

MODULE 4: Mock Tests and Quizzes

This module includes practice assessments and quizzes that help learners validate their understanding, pinpoint areas needing improvement, and prepare for real-world analytical tasks using Minitab.

• Learners should have a foundational understanding of key statistical concepts, including averages, variability measures, and basic hypothesis testing.
• A general awareness of common data analysis practices, including descriptive summaries, visualizations, and introductory inferential techniques, is helpful.
• Participants must be comfortable working on a computer and possess basic skills in using software applications.
• A motivated, open mindset and readiness to participate in practical exercises are important for developing strong Minitab skills.
• No previous experience with Minitab is needed, as the course begins with the basics and progresses to advanced analytical tools.

• Students pursuing undergraduate or postgraduate programs in statistics, data science, business analytics, or related disciplines who wish to strengthen their analytical and visualization skills using Minitab.
• Working professionals across sectors such as manufacturing, quality control, healthcare, finance, and market research who rely on Minitab for analysis, process enhancement, and informed decision-making.
• Researchers who require reliable statistical tools to examine data, run tests, and develop meaningful visual representations for their projects.
• Quality professionals and Six Sigma practitioners seeking to apply Minitab for process optimization, statistical evaluations, and continuous improvement initiatives.
• Individuals with an interest in data analysis who want to learn how to explore datasets, conduct statistical tests, and make sound, data-driven decisions using Minitab.