Join Richard Chua for an in-depth discussion in this video What you should know, part of Six Sigma: Green Belt.
- My design. This course builds upon what I've covered in Six Sigma Fundamentals and Introduction to Minitab. I strongly recommend that you thoroughly review those two courses before watching this green belt training. To have a complete understanding of Six Sigma at a green belt level, your learning journey must include Six Sigma Fundamentals and Intro to Minitab. To help you see how the materials build upon each other, I have developed a learning road map showing how the courses intertwine and support each other at the topic level.
Even if you've had some introductory Six Sigma training elsewhere or have not completed a Six Sigma fundamentals course, it's okay. You can still proceed with this course. Just follow the learning road map to guide you to the corresponding videos and the fundamentals course that you should watch first. Six Sigma is data driven. During green 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. If you're interested in learning how to use Minitab to carry out the exact analysis found in this course, please watch Introduction to Minitab. Lastly, this is not a course in statistics and mathematical formulas. So I will not cover the in depth calculations involved. Again for that, please watch Intro to Minitab. This course focuses on the why, what, and when to use statistics and other tools to carry out your green belt projects.
With these prerequisites out of the way, let's get started.
Dr. Richard Chua builds upon his Six Sigma Foundations and Learning Minitab courses, and covers an array of topics, including measurement system analysis, descriptive statistics, hypothesis testing, design of experiments, statistical process control, and more.
- Six Sigma and the organization
- Collecting the voice of the customer
- Project management basics
- Process maps
- Sampling in data collection
- Measurement system analysis
- Measuring performance using descriptive statistics
- Process performance measures
- Hypothesis testing
- Testing for means, variances, proportions, and independence
- Correlation and regression
- Using selection matrices
- Using failure modes and effects analysis
- Developing control plans
- Statistical process control