Most Six Sigma projects follow the DMAIC protocol. As you would learn during online Six Sigma Green Belt courses on the topic, DMAIC stands for Define, Measure, Analyze, Improve, and Control. In this article, we will focus on the first element of the Six Sigma approach – The six Sigma Define Phase – and the most […]
Tag: Lean Six Sigma
Understanding Discrete Probability Distribution
In the data-driven Six Sigma approach, it is important to understand the concept of probability distributions. Probability distributions tell us how likely an event is bound to occur. Different types of data will have different types of distributions. Why do we need to know this? Well, in the Lean Six Sigma Course we learn that […]
Tollgate Checklist: 12 Questions to Complete Define Stage
Most Six Sigma projects follow the DMAIC model – Define, Measure, Analyze, Improve, Control as is often discussed in online Six Sigma training. These steps are followed in order. But how does a Six Sigma practitioner who has completed Lean Six Sigma training know when the team can move on from e.g. the Define phase […]
How to Calculate Probability Using the Poisson Distribution?
Lean Six Sigma Green Belt course graduates deal with two types of data during the Six Sigma Measure phase of their Six Sigma DMAIC projects: continuous data and discrete data. The Poisson distribution is a probability distribution for discrete data which takes on the values which are X = 0, 1, 2, 3 and so […]
Sigma Level : The Most Important Statistical Term in Six Sigma
The Six Sigma approach is a data-driven approach to problem-solving. Since we’re working with data, it is natural that we will work with statistics as you will learn in any reputable Six Sigma Green Belt training. There is one particular statistical term that is critical for Six Sigma and for understanding a process based on […]