Six Sigma Exploratory Data Analysis


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
This course introduces some key tools used for exploratory data analysis 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

Prerequisites
None

Expected Duration (hours)
0.9

Lesson Objectives

Six Sigma Exploratory Data Analysis

  • identify characteristics of a multi-vari analysis
  • identify guidelines for creating sampling plans
  • distinguish between types of variation
  • interpret variation results in a given scenario
  • identify uses of correlation analysis in Six Sigma
  • make inferences about data based on a given scatter diagram
  • recognize considerations for interpreting the correlation coefficient
  • identify characteristics of causation
  • identify purpose of determining the statistical significance of a correlation coefficient
  • recognize how linear regression is used during data analysis
  • recognize appropriate conditions for hypothesis testing
  • calculate an outcome using the simple least-squares linear regression formula
  • demonstrate your understanding of Six Sigma exploratory data analysis tools and techniques
  • Course Number:
    apr_04_a01_bs_enus

    Expertise Level
    Intermediate