 ### 4 Types of Relative Measures of Dispersion for Six Sigma

The Six Sigma approach is data-driven. Therefore, Six Sigma practitioners who have got the Lean Six Sigma training or another Lean Six Sigma Green Belt course will know that Six Sigma teams are confronted with many different types of data in different units of measure. Relative measures of dispersion are measures of the variance of […] ### How Do The Six Sigma Statistics Work?

The Six Sigma approach is data-driven, therefore Six Sigma statistics play a large role in the Six Sigma problem-solving process. Six Sigma Green Belt training stresses the importance of using Six Sigma statistics to visualize and analyze the data collected for each metric that is important to the customer and that must be tightly controlled. […] ### 4 Absolute Measures of Dispersion You Need to Know

In the Measure phase of the DMAIC process in Six Sigma, there are many types of statistical parameters that graduates of Lean Six Sigma Green Belt training or other Online Six Sigma courses should know. Measures of Central Tendency serve to locate the center of the distribution. However, they do not reveal how the items […] ### 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 […] ### 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 […]