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X-WR-CALNAME:Department of Statistics
X-ORIGINAL-URL:https://statistics.sciences.ncsu.edu
X-WR-CALDESC:Events for Department of Statistics
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BEGIN:VTIMEZONE
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BEGIN:DAYLIGHT
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DTSTART:20240310T070000
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DTSTART:20260308T070000
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260403T110000
DTEND;TZID=America/New_York:20260403T120000
DTSTAMP:20260415T122148
CREATED:20251215T145641Z
LAST-MODIFIED:20260328T015317Z
UID:29027-1775214000-1775217600@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Building faster and more expressive BART models \nPresenter: Sameer Deshpande \nAbstract: \nBayesian Additive Regression Trees (BART) is a highly effective nonparametric regression model that approximates unknown functions with a sum of binary regression trees. Most implementations of BART are based on trees that (i) recursively partition continuous inputs one variable at a time; (ii) one-hot encode categorical predictors; and (iii) represent piecewise constant functions. These implementations are fundamentally limited in their ability to learn complex decision boundaries that are not aligned with coordinate axes; to “borrow strength” across multiple groups; to leverage structural relationships between multiple categorical predictors (e.g.\, adjacency and nesting); and to estimate smooth functions.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-49/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260320
DTEND;VALUE=DATE:20260321
DTSTAMP:20260415T122148
CREATED:20251208T155920Z
LAST-MODIFIED:20251208T155920Z
UID:28977-1773964800-1774051199@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Spring Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-spring-break-5/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260318
DTEND;VALUE=DATE:20260319
DTSTAMP:20260415T122148
CREATED:20251208T155832Z
LAST-MODIFIED:20251208T155832Z
UID:28975-1773792000-1773878399@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Spring Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-spring-break-4/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260317
DTEND;VALUE=DATE:20260318
DTSTAMP:20260415T122148
CREATED:20251208T155750Z
LAST-MODIFIED:20251208T155750Z
UID:28973-1773705600-1773791999@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Spring Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-spring-break-3/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260316
DTEND;VALUE=DATE:20260317
DTSTAMP:20260415T122148
CREATED:20251208T155702Z
LAST-MODIFIED:20251208T155702Z
UID:28971-1773619200-1773705599@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Spring Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-spring-break-2/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260306T110000
DTEND;TZID=America/New_York:20260306T120000
DTSTAMP:20260415T122148
CREATED:20251215T145548Z
LAST-MODIFIED:20251215T150654Z
UID:29026-1772794800-1772798400@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle:  \nPresenter: Li Ma \nAbstract: \ndetails to come
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-48/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260227T110000
DTEND;TZID=America/New_York:20260227T120000
DTSTAMP:20260415T122148
CREATED:20251215T135131Z
LAST-MODIFIED:20260121T152017Z
UID:29011-1772190000-1772193600@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Vertex alignment and changepoint localization in network time series \nPresenter: Zachary Lubberts \nAbstract: \nExisting methodology for changepoint localization in an evolving time series of networks generally relies on accurately prescribed vertex correspondence between network realizations at different times. However\, such vertex alignments are often misspecified or even unknown. To understand the impact of vertex misalignment on inference for dynamic networks\, two illustrative models are constructed for network evolution\, each with a similar changepoint. Different techniques are compared for changepoint localization\, ranging from the simple network statistic of average degree to the more involved and recently developed procedure of Euclidean mirrors. In one model\, vertex misalignment causes comparatively little error\, and in the other\, it seriously impairs localization\, although the Euclidean mirror procedure can nevertheless extract a meaningful signal. It is shown how misalignment between network realizations at different times can effectively weaken their underlying correlation\, impeding inference procedures that rely on accurate inference of such correlation. Graph matching and optimal transport is discussed\, both of which are potential mechanisms for mitigating errors from misalignment\, but which may also fail to improve inference under certain models. Simulations are presented that illustrate these varying effects on approaches to localization.\n\n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-44/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Faculty,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260223T170000
DTEND;TZID=America/New_York:20260223T183000
DTSTAMP:20260415T122148
CREATED:20260205T141306Z
LAST-MODIFIED:20260205T141306Z
UID:29246-1771866000-1771871400@statistics.sciences.ncsu.edu
SUMMARY:February Professional Development Workshop
DESCRIPTION:Join us for the February Professional Development Workshop\, featuring a panel discussion with professionals from DLH Corporation. \n📅 Date: Monday\, February 23\, 2026⏰ Time: 5:00 – 6:30 PM📍 Location: 5104 SAS Hall Commons \nThis session will bring together a panel of industry professionals to discuss how statistics and data science are applied in industry settings\, particularly in areas related to health\, national security\, and applied research. Panelists will share insights into their career paths\, the types of roles available for students with quantitative backgrounds\, and what organizations like DLH look for when hiring new graduates. \nThe workshop will include a moderated panel discussion followed by time for student questions. \nWe hope you’ll join us for this opportunity to learn more about industry careers and engage directly with professionals working in the field.
URL:https://statistics.sciences.ncsu.edu/event/february-professional-development-workshop/
LOCATION:5104 SAS Hall (Solomon Commons)\, NC\, United States
CATEGORIES:College of Sciences Calendar,Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260217
DTEND;VALUE=DATE:20260218
DTSTAMP:20260415T122148
CREATED:20251208T155532Z
LAST-MODIFIED:20251208T155532Z
UID:28969-1771286400-1771372799@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Wellness Day
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-wellness-day-7/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260213T110000
DTEND;TZID=America/New_York:20260213T120000
DTSTAMP:20260415T122148
CREATED:20251215T135134Z
LAST-MODIFIED:20260120T203838Z
UID:29012-1770980400-1770984000@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Generalized Bayesian Inference for Dynamic Random Dot Product Graphs \nPresenter: Josh Loyal \nAbstract: The random dot product graph is a popular model for network data with extensions that accommodate dynamic (time-varying) networks. However\, two significant deficiencies exist in the dynamic random dot product graph literature:  (1) no coherent Bayesian way to update one’s prior beliefs about the latent positions in dynamic random dot product graphs due to their complicated constraints\, and (2) no approach to forecast future networks with meaningful uncertainty quantification. This work proposes a generalized Bayesian framework that addresses these needs using a Gibbs posterior that represents a coherent updating of Bayesian beliefs based on a least-squares loss function. We establish the consistency and contraction rate of this Gibbs posterior under commonly adopted Gaussian random walk priors. For estimation\, we develop a fast Gibbs sampler with a time complexity for sampling the latent positions that is linear in the observed edges in the dynamic network\, which is substantially faster than existing exact samplers. Simulations and an application to forecasting international conflicts show that the proposed method’s in-sample and forecasting performance outperforms competitors. \n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-45/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260206T110000
DTEND;TZID=America/New_York:20260206T120000
DTSTAMP:20260415T122148
CREATED:20251215T135146Z
LAST-MODIFIED:20260127T160935Z
UID:29010-1770375600-1770379200@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Rotated Mean-Field Variational Inference and Iterative Gaussianization \nPresenter: Sifan Liu \nAbstract: Mean-field variational inference (MFVI) approximates a target distribution with a product distribution in the standard coordinate system\, offering a scalable approach to Bayesian inference but often severely underestimating uncertainty due to neglected dependence. We show that MFVI can be greatly improved when performed along carefully chosen principal component axes rather than the standard coordinates. The principal components are obtained from a cross-covariance matrix of the target’s score function and identify orthogonal directions that capture the dominant discrepancies between the target distribution and a Gaussian reference. \nPerforming MFVI in a rotated system defines a rotation followed by a coordinatewise transformation that moves the target closer to Gaussian. Iterating this procedure yields a sequence of transformations that progressively Gaussianize the target. The resulting algorithm provides a computationally efficient construction of normalizing flows\, requiring only MFVI sub-problems and avoiding large-scale optimization. In posterior sampling tasks\, we demonstrate that the proposed method greatly outperforms standard MFVI while achieving accuracy comparable to normalizing flows at a much lower computational cost. \n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-46/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260206
DTEND;VALUE=DATE:20260207
DTSTAMP:20260415T122148
CREATED:20260113T161431Z
LAST-MODIFIED:20260113T161431Z
UID:29211-1770336000-1770422399@statistics.sciences.ncsu.edu
SUMMARY:Triangle Sports Analytics Competition 2026: Submissions Due
DESCRIPTION:Competition Website
URL:https://statistics.sciences.ncsu.edu/event/triangle-sports-analytics-competition-2026-submissions-due/
LOCATION:NC
CATEGORIES:Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260130T110000
DTEND;TZID=America/New_York:20260130T120000
DTSTAMP:20260415T122148
CREATED:20260121T141202Z
LAST-MODIFIED:20260121T204720Z
UID:29225-1769770800-1769774400@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Finding Anomalous Cliques in Inhomogeneous Networks using Egonets \nPresenter:  Srijan Sengupta \nAbstract: Cliques\, or fully connected subgraphs\, are among the most important and well-studied graph motifs in network science. We consider the problem of finding a statistically anomalous clique hidden in a large network. There are two parts to this problem: (1) detection\, i.e.\, determining whether an anomalous clique is present\, and (2) localization\, i.e.\, determining which vertices of the network constitute the detected clique. While this problem has been extensively studied under the homogeneous Erdos-Renyi model\, little progress has been made beyond this simple setting\, and no existing method can perform detection and localization in inhomogeneous networks within finite time. To address this gap\, we first show that in homogeneous networks\, the anomalousness of a clique depends solely on its size. This property does not carry over to inhomogeneous networks\, where the identity of the vertices forming the clique plays a critical role\, and a smaller clique can be more anomalous than a larger one. Building on this insight\, we propose a unified method for clique detection and localization based on a class of subgraphs called egonets. The proposed method generalizes to a wide variety of inhomogeneous network models and is naturally amenable to parallel computing. We establish the theoretical properties of the proposed method and demonstrate its empirical performance through simulation studies and application to two real world networks. \n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-51/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260126T170000
DTEND;TZID=America/New_York:20260126T183000
DTSTAMP:20260415T122148
CREATED:20260113T153332Z
LAST-MODIFIED:20260113T153332Z
UID:29210-1769446800-1769452200@statistics.sciences.ncsu.edu
SUMMARY:Professional Development Workshop
DESCRIPTION:Welcome back! We hope you’re off to a great start to the spring semester. Join us for the first Professional Development Workshop of the calendar year as we kick off the semester with a panel focused on careers in public service. \nCareers in State Government: Applying Statistics and Data Science \n📅 Date: Monday\, January 26\, 2026\n⏰ Time: 5:00 – 6:30 PM\n📍 Location: 5104 SAS Hall Commons \nIn this session\, students will hear from representatives from the North Carolina Office of the State Auditor (NC OSA) in a panel discussion on how statistics and data science are applied in state government. Panelists will also share information about the NC OSA Internship Program and pathways for students interested in government careers. \nWe hope you’ll join us for this informative and timely conversation as we begin the spring semester.
URL:https://statistics.sciences.ncsu.edu/event/professional-development-workshop-4/
LOCATION:5104 SAS Hall (Solomon Commons)\, NC\, United States
CATEGORIES:College of Sciences Calendar,Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260123T110000
DTEND;TZID=America/New_York:20260123T120000
DTSTAMP:20260415T122148
CREATED:20251215T135157Z
LAST-MODIFIED:20251215T144455Z
UID:29009-1769166000-1769169600@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Multivariate spatial models for high-dimensional ecological data \nPresenter: Jeffrey W. Doser\, Ph.D. \nAbstract: The proliferation of big spatial data from autonomous monitoring systems\, national monitoring programs\, and citizen science platforms offers never-before-seen opportunities to address pressing natural resource management and conservation questions. Yet\, such massive spatial data present a variety of computational and statistical challenges that limit their use by practitioners. In this seminar\, I will discuss recent methodological and software advances that enable efficient modeling of multivariate spatial data where both the number of locations and number of outcomes at each location is large. Case studies motivated by ecological and forestry data will highlight the framework’s utility for informing natural resource management and conservation.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-47/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260122T160000
DTEND;TZID=America/New_York:20260122T170000
DTSTAMP:20260415T122148
CREATED:20260113T161522Z
LAST-MODIFIED:20260113T161522Z
UID:29214-1769097600-1769101200@statistics.sciences.ncsu.edu
SUMMARY:Triangle Sports Analytics Competition 2026: Virtual Information Session
DESCRIPTION:Zoom Link\nCompetition Website
URL:https://statistics.sciences.ncsu.edu/event/triangle-sports-analytics-competition-2026-virtual-information-session/
LOCATION:NC
CATEGORIES:Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260119
DTEND;VALUE=DATE:20260120
DTSTAMP:20260415T122148
CREATED:20251208T155443Z
LAST-MODIFIED:20251208T155443Z
UID:28967-1768780800-1768867199@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Holiday
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-holiday-12/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260112
DTEND;VALUE=DATE:20260113
DTSTAMP:20260415T122148
CREATED:20251208T155253Z
LAST-MODIFIED:20251208T155346Z
UID:28965-1768176000-1768262399@statistics.sciences.ncsu.edu
SUMMARY:Classes Resume - Spring 2026
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/classes-resume-spring-2026/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260101
DTEND;VALUE=DATE:20260102
DTSTAMP:20260415T122148
CREATED:20251208T154746Z
LAST-MODIFIED:20251208T155105Z
UID:28963-1767225600-1767311999@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-7/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251231
DTEND;VALUE=DATE:20260101
DTSTAMP:20260415T122148
CREATED:20251208T154658Z
LAST-MODIFIED:20251208T154658Z
UID:28960-1767139200-1767225599@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-6/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251230
DTEND;VALUE=DATE:20251231
DTSTAMP:20260415T122148
CREATED:20251208T154605Z
LAST-MODIFIED:20251208T154952Z
UID:28958-1767052800-1767139199@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-5/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251229
DTEND;VALUE=DATE:20251230
DTSTAMP:20260415T122148
CREATED:20251208T154501Z
LAST-MODIFIED:20251208T154501Z
UID:28956-1766966400-1767052799@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-4/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251226
DTEND;VALUE=DATE:20251227
DTSTAMP:20260415T122148
CREATED:20251208T154305Z
LAST-MODIFIED:20251208T154820Z
UID:28954-1766707200-1766793599@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-3/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251225
DTEND;VALUE=DATE:20251226
DTSTAMP:20260415T122148
CREATED:20251208T153935Z
LAST-MODIFIED:20251208T154342Z
UID:28952-1766620800-1766707199@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-2/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251224
DTEND;VALUE=DATE:20251225
DTSTAMP:20260415T122148
CREATED:20251208T153727Z
LAST-MODIFIED:20251208T153827Z
UID:28948-1766534400-1766620799@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251213
DTEND;VALUE=DATE:20251214
DTSTAMP:20260415T122148
CREATED:20250203T180930Z
LAST-MODIFIED:20250203T180930Z
UID:27784-1765584000-1765670399@statistics.sciences.ncsu.edu
SUMMARY:University Graduation
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-graduation-3/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251212
DTEND;VALUE=DATE:20251213
DTSTAMP:20260415T122148
CREATED:20251208T161509Z
LAST-MODIFIED:20251208T161541Z
UID:29001-1765497600-1765583999@statistics.sciences.ncsu.edu
SUMMARY:Department Graduation
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/department-graduation/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251210
DTEND;VALUE=DATE:20251211
DTSTAMP:20260415T122148
CREATED:20251208T161351Z
LAST-MODIFIED:20251208T161351Z
UID:28998-1765324800-1765411199@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-71/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251209
DTEND;VALUE=DATE:20251210
DTSTAMP:20260415T122148
CREATED:20251208T161304Z
LAST-MODIFIED:20251208T161304Z
UID:28996-1765238400-1765324799@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-70/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251208
DTEND;VALUE=DATE:20251209
DTSTAMP:20260415T122148
CREATED:20251208T161218Z
LAST-MODIFIED:20251208T161218Z
UID:28994-1765152000-1765238399@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-69/
LOCATION:NC
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
END:VCALENDAR