Are you frustrated that addressing perceived root causes does not really solve a problem? If so, consider regression analysis—a powerful tool to verify relationships between variables. Regression goes beyond plotting relationships on a graph; it actually measures the strength of the relationship, so that you can verify to what extent a process variable X impacts the process output variable Y.

Learn about various regression procedures and see how they can potentially help you with root cause verification. Discover how regression analysis can be applied to your organization's processes to solve problems and achieve greater efficiency.

Course Objectives

• Understand how to measure the relationship between two or more process variables.
• Learn to distinguish between different available procedures in order to conduct regression analysis.
• Learn the assumptions related to regression analysis.
• Recognize ways to address situations in which the assumptions do not hold.
• Apply the concepts addressed to various data sets and interpret the results.
• Recognize how regression analysis can be applied to your own organization.

Main Topics

•  Introduction to linear regression 
• Basics of regression analysis
• General procedure for conducting regression analysis (one X)
• Regression analysis with transformed data
• Introduction to multiple linear regression
• Working with multiple regression
• General procedure for multiple regression
•  Introduction to curvilinear regression
•  Logistic regression
•  Using Minitab^TM in support of statistical tools

Who Should Attend

Managers and professionals who are engaged in process improvement activities, as well as associated quality, engineering, manufacturing, process, and industrial personnel. Also valuable for anyone involved in a Lean and/or Six Sigma deployment.

This course requires the use of Minitab^TM statistical software; attendees are responsible for bringing laptops with Minitab^TM  to the class.

CEUs:  1.5
Number of Days: 2