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X-WR-CALDESC:Events for Frost Institute for Data Science & Computing
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SUMMARY:Special Guest Lecture on Visual Inference with Claus Ekstrøm 12/1
DESCRIPTION:Join us for a special guest lecture (either in person or virtually) featuring Claus Ekstrøm\, professor and vice-chair at the Section of Biostatistics\, University of Copenhagen. His primary research interests are centered on developing methods for the analysis of high-dimensional data problems and causal discovery. He’s authored two books on statistics and is frequently used as an expert on statistics in Danish news media. Claus has been a grumpy old man from a young age. \nRegister Now  |  Wednesday 12/1/2021\, 4:00-5:00 PM\nThis is a hybrid event:  In person at Otto G. Richter Library\, CR 343  | or online via Zoom. \nTitle of the lecture:  “Validation of visual inference methods in statistics by use of deep learning” \nWhen does inspecting a certain graphical plot allow for an investigator to reach the right statistical conclusion? Visual inference is commonly used for various tasks in statistics—including model diagnostics and exploratory data analysis – and though attractive due to its intuitive nature\, the lack of available methods for validating plots is a major drawback. \nWe propose a new validation method for visual inference. Our method trains deep neural networks to distinguish between plots simulated under two different data-generating mechanisms (null or alternative)\, and we use the classification accuracy as a technical validation score (TVS). The TVS measures the information content in the plots\, and TVS values can be used to compare different plots or different choices of data-generating mechanisms\, thereby providing a meaningful scale that new visual inference procedures can be validated against. \nWe apply the method to three popular diagnostic plots for linear regression\, namely the scatter plot\, the quantile-quantile plot\, and the residual plot. We consider various types and degrees of misspecification\, as well as different within-plot sample sizes. Our method produces TVSs that increase with increasing sample size and decrease with increasing difficulty\, and hence the TVS is a meaningful measure of validity.
URL:https://idsc.miami.edu/idsc-event/claus-ekstrom/
LOCATION:Richter Library\, 1300 Memorial Drive\, Coral Gables\, Florida\, 33146\, United States
CATEGORIES:Creative Technologies,Lecture
ATTACH;FMTTYPE=image/jpeg:https://idsc.miami.edu/wp-content/uploads/2021/11/Claus-Ekstrom-730x350-1.jpg
ORGANIZER;CN="Frost Institute for Data Science and Computing":MAILTO:idsc@miami.edu
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