Description: As a Lean or Lean Six Sigma project moves into the Analyze phase, team members identify possible sources of variation, underlying root causes, and areas for business process improvement. It is here where assumptions or the hypothesis about a process, product, or service are made. These are then validated using tests based on sample data. Once validated, they can drive process improvement, process control, and process design.
In this course, you'll learn about some common advanced hypothesis testing techniques used for testing variances and proportions. This course covers advanced hypothesis tests used in Six Sigma, and is aligned with ASQ’s 2015 Six Sigma Green Belt Body of Knowledge.
Target Audience: 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
Duration: 00:59
Description: During the Analyze phase of a Lean or Lean Six Sigma improvement project, the team conducts a number of statistical analyses to determine the nature of variables and their interrelationships in the process under study. This can in turn lead to business process improvement.
In this course, you'll learn about some of the basic concepts relating to hypothesis testing, and how it can drive process improvement, process control, and process design. You'll also explore how to carry out various types of hypothesis test design, to find and compare means. The course is aligned with ASQ’s 2015 Six Sigma Green Belt Body of Knowledge.
Target Audience: 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
Duration: 01:14
Description: In the Analyze stage of the Six Sigma DMAIC process, project teams carefully analyze process output and input variables. The goal of this data analysis is to narrow down the many possible inputs identified during the Measure stage, and lead to business process improvement. The analysis is carried out using tools that help identify a few probable issues and drive process improvement, process design, and process control.
In this course, you'll learn about some of the key tools used in exploratory data analysis in Lean and Lean Six Sigma, such as Multi-varied studies, Correlation analysis, and Regression models. The course is aligned with ASQ’s 2015 Six Sigma Green Belt Body of Knowledge.
Target Audience: 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
Duration: 00:54