This course is designed to help scientists and engineers understand the statistical methods used in process and product development. Variability is part of every process, design of experiments helps to separate systematic variability from special cause variability. You will get a chance to examine the different sources of variability how it relates to analytical method development, process improvement and sample size selection. The concept of experimental budget will be introduced to help you plan the total number of experiments needed. You will also learn to improve process output characteristics including quality, cost, and robustness through generating empirical models of your processes in the fewest experiments possible.
This highly interactive course will allow participants the opportunity to develop strategies for analysis of experimental data. The objective is to provide participants with key technical information along with perspectives to enable them to apply the technologies to their own projects and evolve their own statistical methods to support the various stages of product development.
- Learn the technical details and rationale for selecting and analyzing well designed statistically based experiments.
- Develop the confidence to design and execute experiments that maximizes information in your day-to-day activities.
- Participate in discussions with other course attendees to increase your confidence and proficiency in statistical hypothesis testing.
- Determine the most robust settings in your process to minimize the different sources of variability.
Who should Attend:
This course is developed to provide valuable assistance to all regulated companies that need to understand their processes including companies in the Medical Device, Diagnostic, Pharmaceutical, and Biologics fields. The employees who will benefit include:
- Development scientists
- Analytical method development, and QA/ QC personnel.