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Slideshow

Tags: General event

Encouraged by the success of the 2023 Data Science & Artificial Intelligence Summer Camp and due to popular demand, the Department of Statistics at the University of Georgia is once again partnering with Data Scientists at Wells Fargo to offer a Data Science & Artificial Intelligence Camp this summer. This camp will be held in person on the campus of University of Georgia. About 30 high school students will be selected to participate in…
Evaluating biomarkers for treatment selection from reproducibility studies Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and…
On estimation and order selection for multivariate extremes via clustering Abstract: We investigate the estimation of multivariate extreme models with a discrete spectral measure using clustering techniques. The primary innovation involves devising a method for selecting the appropriate order that not only consistently identifies the true order in theory but also has a straightforward and easy implementation in practice. Specifically, we…
Confidence ellipsoids of a multivariate normal mean vector based on noise perturbed and synthetic data with applications Abstract: We discuss at length the problem of constructing a confidence ellipsoid of a multivariate normal mean vector based on a random sample from it. The central issue at hand is the sensitivity of the original micro data and hence the data cannot be directly used/analyzed. We consider a few perturbations of the original…
The Impact Of Treatment Discontinuation Due Adverse Events On Efficacy In An Oncology Clinical Trial Abstract Randomized clinical trials persist as the gold standard for evaluating the efficacy and safety of new treatments. However, in clinical trials of reasonable size and duration, it is common for some patients to deviate from their assigned study treatment due to various reasons. One such deviation is treatment discontinuation resulting from…
Fully Functional Neural Networks for Functional Regression Abstract We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard…
AI and the formative Assesment: The Train Has Left the Station Abstract: Researchers have been questioning AI --whether we can and should use AI for formative assessment. AI is already being employed, for better or worse, to facilitate formative assessment in various educational contexts. In this talk, Dr. Zhai will demonstrate research on AI-based assessment in science education. He will respond to the many concerns raised in the field…
On Thursday, December 7, 2022, at 3:15 pm, Mr. David Lifsey will present the "Lifsey Graduate Fellowship in Statistics and Data Science" award to Mr. Ryan C. Smith who is pursuing a master's degree in Statistics as a Double Dawgs student. Dean Anna Stenport will also be attending the ceremony and saying a few words about Mr. Lifsey. Mr. Lifsey is takes very keen interest in the success of our program. When he…
The contribution of Joint Program in Survey Methodology (JPSM) to train graduate students in Survey and Data Science Abstract: The founding of JPSM in 1993 resulted from an initiative of the United States Federal Statistical Agency heads, the head of the Office of Management and Budget’s Statistical Policy Office, and the chair of the U.S. President’s Council of Economic Advisors. The founders of JPSM brought together a consortium of…
Sample Splitting for Assessing Goodness of Fit in Time Series Abstract: A fundamental and often final step in time series modeling is to assess the quality of fit of a proposed model to the data. Since the underlying distribution of the innovations that generate a model is often not prescribed, goodness-of-fit tests typically take the form of testing the fitted residuals for serial independence. However, these fitted residuals are inherently…

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