SS510 Regression Analysis and Hypothesis Testing
This 2.5-day workshop will empower you to extract maximum meaning from your data. They allow you to answer the questions – has there been a change in my process or product. Is this process or product different from this one? Is there a correlation between these two or more factors and, if so, how can I predict future changes in my process or product? What do changes in these variables predict about changes in this variable?
Statistically designed experiments apply the same principle methods you will learn in this course. However, while statistically designed experiments (DOE) are the best way to confirm cause and effect, sometimes we haven’t had or it may be impractical to run designed experiments. These techniques give the next best option available to discover correlation and identity variables important to controlling and optimizing your processes and products and identifying root causes leading to effective corrective action.
- How to perform and interpret correlation and regression analysis and develop correlation models to predict changes in processes and products.
- How to relate one dependent variable to one or more independent variables
- How to confirm statistically significant differences in processes or products for continuous and discrete variables
- How to determine the minimum sample size you will need to confirm statistically significant differences
- How to assess the probability that you conclusions about correlations or differences are accurate
Who Should Attend
- 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
Discounts may apply, please refer to the registration page for details.
Principal Instructor: Steve Zagarola
Steve Zagarola is a founding member and managing partner of the Northwest Center for Performance Excellence (NWCPE). He is also founder of The ZDM Group, an organization dedicated to the advancement of statistically based approaches for competitive advantage. He graduated with a BS in mechanical engineering from Georgia Tech with post-graduate studies in Psychology and Statistics at Georgia Tech and Georgia State University. Mr. Zagarola is Six Sigma Master Black Belt with more than 30 years experience in the application of statistical and modern structured approaches to the optimization of manufacturing and transactional processes, quality systems, and R&D for industries ranging from food and beverage, plastics molding, wind energy, and advanced semiconductors. Prior to his current position with NWCPE, he served as the Director of Quality for Cascade Microtech, Six Sigma Program and Quality Manager for Vestas Wind Systems and Senior Manufacturing Manager for The Coca-Cola Company. He teaches Six Sigma, Statistical Process Control, Design of Experiments and other Statistical Quality methodologies and Process Excellence topics in four continents and in English and Spanish.
Co-Instructor: Aubrey Kendall
Aubrey Kendall is a supplier quality engineer at Vestas Wind Systems. He graduated with a BS in manufacturing engineering from Brigham Young University and an MBA from Clemson University. Mr. Kendall is a Six Sigma Black Belt with over 15 years of experience in manufacturing, quality, and engineering management in aerospace, energy, and other industries. His strong combination of technical skills and ease in communicating make him an effective trainer and facilitator.
Recommended: SS501- Intro to Continual Improvement and Structured Problem Solving, or equivalent knowledge about basic statistical methods. Equivalent knowledge includes understanding of basic statistical concepts such as distributions, sample statistics and the central limit theorem. The courses SS505- Intro to DOE and SS507- Intermediate DOE provide excellent backgrounds.