Correlation & Regression Analysis

Introduction to core methodologies central to Six Sigma strategy

This one-day Correlation and Regression Analysis workshop introduces participants to methods central to Six Sigma strategy by directly testing for the relationships between X (independent) and Y (dependent) variables. Sometimes those relationships directly reflect cause and effect (Y = f(X)). Sometimes they open a path to discover the real causal factors (Xs) by uncovering correlations due to common elements between two variables. Scatter diagrams, a Six Sigma Yellow Belt topic, is a visual representation of the correlation between one dependent and one independent variable. Regression analysis goes further by quantifying the relationship between a dependent variable and one or more independent variables. Regression models are invaluable to Six Sigma process and product design, control and DFSS, and Six Sigma DMAIC projects by helping us understand how things work and by enabling us to predict outputs (Ys) from their correlated variables (Xs).

Course Topics

  • Perform and interpret correlation and regression analysis and develop correlation models to predict changes in processes and products for linear and non-linear relationships
  • Determine correlation models for relating one dependent variable to one independent variable – simple regression
  • Determine correlation models for relating one dependent variable to one independent variable – simple regression
  • Assess the validity and accuracy of regression models with the correct interpretation of p-values, R2 values and confidence, prediction intervals and analysis of the differences from predicted and measured values (residuals analysis)
  • Apply correlation and regression analysis to DMAIC and DFSS Six Sigma projects
  • Review of basic statistical concepts – distributions, parameters, and statistics, central limit theorem
  • Intro to correlation and regression analysis
  • Scatter diagrams and multiple-variable analysis to spot possible relevant correlations efficiently
  • Regression least squares method
  • P value, R2, Confidence Intervals, Prediction Intervals, residuals analysis, model development
  • Linear, polynomial, simple and multiple regression, Logical Regression
  • Workshops for the analysis and interpretation of regression analysis
  • Application of correlation and regression analysis for Six Sigma DFSS and Six Sigma DMAIC projects

Course Objectives

Upon completion of this one-day course, participants will reinforce project planning methodologies through project development and feedback.

What Career Paths Benefit the Most From Six Sigma Correlation & Regression Analysis Workshop?

  • People working with manufacturing or non-manufacturing processes
  • Manufacturing, Process and Quality Engineers
  • R&D scientists and engineers
  • Product and process development and design engineers
  • Marketing and business analysts
  • Candidates for Six Sigma Black Belt certification

Additional Course Notes

Customized versions of this course on- or off-site are available for organizations desiring to target specific groups or objectives, e.g., overview for management including how to lead successful implementation of advanced analytical methods, quality and process engineers with emphasis on the analysis and interpretation, follow-up strategies and how to communicate the story that data tells us; marketing personnel and how to design studies to answer questions key to market understanding.

Prerequisites: Introduction to Statistical Methods to Manage & Improve Processes or equivalent knowledge about basic statistical methods is required. Equivalent knowledge includes awareness and understanding of basic statistical concepts such as distributions, sample statistics, and the central limit theorem. The courses Introduction to Statistically Designed Experiments and DOE-Intermediate Design of Experiments provide excellent backgrounds for this course but aren’t required.

Credit & Course Follow-Up

Participants who complete this course will earn credit toward certification toward Six Sigma Black Belt.

Credits: 0.75 CEUs