Six Sigma GREEN BELT (SSGB)
Green Belt training focuses on the principles of variation reduction and Lean Manufacturing.
The goal is to
Green Belts typically support Black Belts and are not always employed as full-time Green Belts. They often have an existing full-time role in the company and participate in Six Sigma projects as needed. However, Green Belts can lead teams and have a Black Belt serve as a mentor.
Study at your own pace with 1,000+ Green Belt program training slides in .pdf format. The slides include examples and a 180+ question practice exam. Working through this material will not only prepare you for a Green Belt project and certification but set the foundation as a Black Belt and beyond.
Green Belt Training and Certification usually requires knowledge or execution of the tools shown below. At this stage, similar to Yellow Belts, they generally are not taught to create and manage a DOE. They are introduced to the basic non-normal distributions and hypothesis testing.
All of these topics, and more, are covered within this website. Active subscribers will be provided login credentials to access all the content within the site.
Green Belt certifications programs are less rigorous than Black Belt program but more than Yellow Belt and usually consist of:
There are >180 example certification problems available for subscribers of this site. Many of the problems have further explanations along with additional developmental material that can be found within this site.
GB's should possess an understanding of basic statistics and hypothesis testing with normal and non-normal distributions.
GB's usually are not asked to perform hypothesis testing of non-parametric data. Typically, one will work together with a BB or MBB to go over the data, review assumptions, possibly transform the data, or apply non-parametric analysis together.
Link to new Six Sigma Material
Templates, Tables, and Calculators
Six Sigma
Templates, Tables & Calculators
Six Sigma Slides
Green Belt Program (1,000+ Slides)
Basic Statistics
Cost of Quality
SPC
Process Mapping
Capability Studies
MSA
SIPOC
Cause & Effect Matrix
FMEA
Multivariate Analysis
Central Limit Theorem
Confidence Intervals
Hypothesis Testing
T Tests
1-Way ANOVA
Chi-Square
Correlation
Regression
Control Plan
Kaizen
MTBF and MTTR
Project Pitfalls
Error Proofing
Z Scores
OEE
Takt Time
Line Balancing
Yield Metrics
Sampling Methods
Data Classification
Practice Exam
... and more