Design of experiments is typically presented as a “one shot” approach. However, it may be more efficient to divide the experiment into smaller pieces, thus expending resources in a smarter, more adaptive manner. This sequential approach becomes especially suitable when experimenters begin with very little information about the process, for example, when scaling up a new product. It allows for better definition of the design space, adaption to unexpected results, estimation of variability, reduction in waste, and validation of the results.
The statistical literature primarily focuses on sequential experimentation in the context of screening, which in our experience is only the beginning of an overall strategy for experimentation. This tutorial begins with screening and then goes well beyond this first step for more complete coverage of this important topic:
Several real-world examples will be provided and demonstrated using software, thus providing attendees a solid briefing with very helpful aspects for practical application of sequential experimentation.
June 11 at 10:00am CT