Join Richard Chua for an in-depth discussion in this video What you should know/road map, part of Six Sigma: Black Belt.
- By design, this course builds upon what I've covered in Six Sigma Fundamentals, Six Sigma Green Belt, and Introduction to Minitab. These prerequisite courses should be completed as an integral part of the Black Belt training. To help you see how the materials build upon each other, I have developed a learning roadmap showing how the courses intertwine and support each other at the topic level. Follow the learning roadmap to guide you to the corresponding videos in the Six Sigma Fundamentals, Six Sigma Green Belt, and Introduction to Minitab courses that you should watch first.
Six Sigma is data-driven. During Black Belt training and project work, statistical software is used for plotting and analyzing data. This course is designed with that type of support in mind, regardless of whatever software you use. My personal preference is Minitab, and that's what you'll see in this course. Last, this is not a course in statistics or mathematical formulas, so I will not cover the in-depth calculations involved.
This course focuses on the why, what, when, and more importantly, how to use statistics and other advanced quality tools to carry out your Black Belt projects. With these prerequisites out of the way, let's dive in.
LinkedIn Learning (Lynda.com) is a PMI Registered Education Provider. This course qualifies for professional development units (PDUs). To view the activity and PDU details for this course, click here.
The PMI Registered Education Provider logo is a registered mark of the Project Management Institute, Inc. Dr. Richard Chua builds upon his Six Sigma: Green Belt, Six Sigma Foundations, and Learning Minitab courses—which are prerequisites to this course—and covers an array of topics, including measurement system analysis, hypothesis testing, response surface methods, displaying improved process capabilities, and more.
- Process flow metrics
- Measurement system analysis
- Calculating process capability
- Hypothesis testing
- Confidence intervals
- Testing for normality
- Designing, conducting, and analyzing full-factorial experiments
- Using fractional factorial experiments for screening
- Displaying improved process capability