Friday, April 30,20211:00pm – 3:00pm EST Data Defect Correlation: A Unified Quality Metric for Probabilistic and Non-probabilistic Samples. Xiao-Li Meng, P.hD.Editor-in-ChiefWhipple V. N. Jones Professor of Statistics, and Founding Editor-in-Chief of Harvard Data Science Review Xiao-Li Meng, the Whipple V. N. Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, is well known…
Monday, March 22, 20211:00pm EST Talk 1: Offering Participant Control and Tailored Introductions in Smartphone-based Passive Data Collections to Avoid RefusalsPresented by doctoral student Alex Brown Breslin, JPSM Talk 2: Trends in Trust: Measuring Americans’ Expectations for Trustworthy Research Use of Social Media DataPresented by Sarah Gilbert, Postdoc, iSchool. Upcoming Roundtables April 26, 1 pm Youngho Kim,…
Event Date and Time : Friday, April 9, 2021 – 12:00 am to Sunday, April 11, 2021 – 11:59 pm Location : Washington DC About DataFest The 2021 DC Datafest is a 48-hour competition where teams of undergraduate students from the DC metro area compete virtually to analyze rich, complex data sets from a major organization. Students are…
MONDAY SYMPOSIUM IN MEASUREMENT AND STATISTICS (MSMS) UNIVERSITY OF MARYLAND together with OHIO STATE UNIVERSITY, UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL* UNIVERSITY OF NOTRE DAME (* Organizer of this talk) This presentation describes a benchmark method to validate statistical methods from the analysis of data on a known or established empirical effect. There are aspects to benchmark validation…
SoDa Associate and UMD Faculty Katie Shilton quoted in the New Yorker In computer science, the main outlets for peer-reviewed research are not journals but conferences, where accepted papers are presented in the form of talks or posters. In June, 2019, at a large artificial-intelligence conference in Long Beach, California, called Computer Vision and Pattern…
Mixed-mode contact and recruitment approaches have become increasingly critical in reaching people to participate in surveys and research panels and improving their likelihood of response and often, the representation of the sample, bringing groups more traditionally represented. Nielsen has designed a phased sequential multi-mode methodology to recruit homes through a combination of web, phone, and in-person/proximity methods for its core TV panels that have relied exclusively on in-person recruitment. This work has been accelerated due to the COVID-19 pandemic. Nielsen will present the results of a “push to web” recruitment test conducted in five markets from October 2020 to January 2021.
Information Risk is an important field that encompasses multiple existing disciplines and overcomes the boundaries among them that has impeded knowledge sharing and effective management of integrated business projects. These projects often span multiple organizational groups and use different structured frameworks of information, data, computing, and security management. The practical realities intrinsic to performing this work leads to gaps in complying with regulations, ensuring secure operations, satisfying auditors, and even meeting program objectives for data analysis and business uses. This talk describes how deeply embedded data disparities that remain hidden to typical data methods lead to high error rates in project results. Lessons learned from assessing and correcting these situations is presented with examples of the problems and methods to detect and fix them.
Distance is one of the most critical concepts in geography and has been widely used to quantify spatial separation between geographical entities. While measuring the distance between two points is straightforward, assessing the spatial separation between non-point objects can be challenging. This study investigates distance measurement between a location (point) and an area (polygon).
Responsive and adaptive survey designs can be used to reduce the risk of nonresponse bias through data collection. In responsive design, different protocols that appeal to prior nonrespondents can be introduced in phases. In adaptive survey design, particular nonrespondents can be targets in these subsequent phases, based on predefined criteria. In the case of nonresponse bias, the criteria can be propensity models. Key, however, it the specification of these models.
Gathering, managing, and using social data to address critical questions requires the development of large-scale data infrastructures. In this Social Data Science Center (SoDa) panel, the distinguished speakers will share their experiences with the challenges and opportunities presented by efforts to create social data science infrastructure at the state, national, and international level.
