Understanding Smoothers through Interactive Examples by Xan Gregg

Talk begins at 6:00pm.

Abstract:
Smoothers provide a powerful way to cut through the noise and focus on trends in data. However, each smoothing technique brings underlying assumptions and can produce poor results when the assumptions are strained. I'll review the utility of smoothers from a data visualization perspective and explore their parameters and their weaknesses. Regression, moving average, spline and loess are covered.

Bio:
Xan Gregg is the R&D Director of Data Discovery for JMP at SAS Institute and develops the Graph Builder component of JMP. Find him online at https://packedbars.com/ and on Twitter at @xangregg.