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PHYSTAT seminar: From COVID-19 Testing to Election Prediction: How Small Are Our Big Data? / Meng, Xiao-Li (speaker) (Harvard University)
The term “Big Data” emphasizes data quantity, not quality. What will be the effective sample size when we take into account the deterioration of data quality because of, for example, the selection bias in COVID-19 testing or the non-response bias in 2016 US Election polling results? This talk provides an answer to such questions, based on the concept of data defect index (ddi) developed in [1]. It will also discuss briefly the application of ddi for 2020 US Election, as reported in [2]. [1] Xiao-Li Meng (2018) “Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election”, Annals of Applied Statistics 12 685. [2] M [...]
2021 - 4531. EP-IT Data science seminars External link: Event details In : PHYSTAT seminar: From COVID-19 Testing to Election Prediction: How Small Are Our Big Data?

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