Probability distributions are an essential part of descriptive statistics that Six Sigma teams can use to assist in fitting collected data into various types of distributions. Probability distributions help to ascertain specific probability values in the distribution and lead the Six Sigma teams down the hypothesis testing roadmap to the next stage of the Six Sigma DMAIC process. Of course, all this is meaningless if the data you have gathered and used is not accurate or precise, which is where measurement systems analysis (MSA) comes into play. MSA is a task in the Measure stage of the Six Sigma DMAIC process and is used to identify the variability caused by the measurement system itself. This course will examine how to calculate normal, binomial, Poisson, chi-square, Student's t-distributions, and F distributions. It will also look at how to assess the precision and accuracy of an organization's current measurement system using Gauge Repeatability and Reproducibility (GR&R), bias, linearity, percent agreement, and Precision/tolerance (P/T) studies. This course is aligned to the ASQ Certified Six Sigma Green Belt certification exam and is designed to assist learners as part of their exam preparation.
Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level