Six Sigma Data Analysis and Root Cause Analysis

Candidates seeking Six Sigma Yellow Belt certification and any other individuals involved in quality and process improvement at the organizational or departmental level


Expected Duration
68 minutes

During the Analyze stage of a Six Sigma project, statistical data analysis is used to assess process performance and identify problem areas. The primary tool for presenting process data is the probability distribution graph, which is studied during data analysis. Another key type of analysis is root cause analysis, which uses tools such as 5 Whys, process mapping, relational matrix charts, and force-field analysis. In this course, you will learn about each area of analysis and the tools used. This course is aligned to the ASQ Body of Knowledge and is designed to assist Yellow Belt candidates toward their certification and also to become productive members on their Six Sigma project teams.


Analyzing Data for Six Sigma Projects

  • label examples of variables as continuous or discrete
  • identify characteristics of normal distribution
  • recognize situations for which you would use a binomial distribution
  • recognize how the shape of a distribution curve affects data interpretation
  • classify examples of causes of variations as either common or special causes
  • recognize how to use probability distributions and control charts in data analysis

Root Cause Analysis in Six Sigma

  • recognize the process for conducting a root cause analysis
  • recognize how the 5 Whys tool is used for root cause analysis
  • identify sources of information used when creating a process map
  • label process map symbols according to their meanings
  • recognize how relational matrix charts are used for root cause analysis
  • recognize activities involved in carrying out a force-field analysis
  • recognize methods for performing root cause analysis





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