Date(s) - 30/11/2022
2:00 pm - 3:30 pm
Category(ies) No Categories
IASS Webinar 23: Bridging Big Data and Sampling Methodology: What is “big” and where is the “bridge”
30 November 2022 at 2pm – 3:30pm (CET)
All are invited to the webinar, organised by the International Association for Survey Statisticians.
Please register for the IASS Webinar Here:
After registering, you will receive a confirmation email containing information about joining the webinar. There will be time for questions. The webinar will be recorded and made available on the IASS and ISI web site. See below for the abstract and biography of the speakers.
While the BigData-native statistical community is growing larger, sampling statisticians seem to grow divided between enthusiastic and worried. Is BigData also a big step ahead to extract trueful information and actual knowledge from data? Is BigData underplaying sampling theory? Supplanting it as a low-cost futuristic option? In this webinar I shall try and decipher the multifaceted relationship connecting BigData and Sampling methodology, starting with the blurry definition of BigData, discussing the non-probabilistic data generating mechanism, passing through different kind of data, of application contexts and goals, to end with some very personal considerations and views.
Fulvia Mecatti is PhD in Methodological Statistics at University of Trento and full professor of Statistics (since 2005) at University of Milano-Bicocca. She has been elected ISI member in 2004 and is more recent member of IASS. In her early academic career, she has been visiting student to Bradley Efron at Stanford University, visiting professor to Steve Thompson at Pennsylvania State University and to Jon K.N. Rao at Carleton University. As a professor she has been spending several research periods abroad, including Statistics Canada, NORC at University of Chicago, WHO in Geneva and University of Pernambuco, Brazil. She has been appointed Facilitator in the TB Monitoring and Evaluation Division of the WHO and Sampling Consultant with UN-Women and with the Inter-Secretariat Working Group on Household Surveys of UN Statistical Division. Her research work is mainly in Sampling Methods, Difficult-to-sample populations, and Re- sampling under complex sample designs, with also intersectional research in Gender Statistics and Causal Inference from observational biomedical data. She also has a committed interest in effective communication of Statistics to the general public. She is co- director of the Spring School in Data Journalism at San Raffaele Hospital University in Milano, and she has recently concluded her elective duty in the advisory board of the SIS- the Italian Statistical Society, which she represented in a Statistical Literacy project of the COVID-19 Working Group of FENStatS – the Federation of European Statistical Societies. She is former director of the PhD program in Statistics at University of Milano-Bicocca, and former president of S2G – the Survey Sampling Group of the Italian Statistical Society.