Identifying the Impact Curved Factor Shapes have on Responses
Statistics, Predictive Modeling and Data Mining
Learn how to analyze sequential measurement data where measurements you want to analyze as factors are not single points, but a range of points presented as curves. Examples include chemical spectra, sensors, batch or streaming data. Learn how to efficiently use the full range of data rather than selected points in the curve to provide immediately interpretable results, including graphs typically used to understand these kinds of data. See a 30-minute demo and stay on if you want to join 15-30 minutes of Topic Discussion and Q&A.
This session covers: cleaning, aligning and handling outliers in streamed data; identifying underlying structures among batches in a process and the impact of shape changes on responses; building models; and maximizing desirability to get the best results.