Podcasts Technology Super Data Science: ML & AI Podcast with Jon Krohn SDS 581: Bayesian, Frequentist, and Fiducial Statistics in Data Science

SDS 581: Bayesian, Frequentist, and Fiducial Statistics in Data Science

Published: June 7, 2022, 11 a.m.

b"In this episode founding Editor-in-Chief of the Harvard Data Science Review and Professor of Statistics at Harvard University, Prof. Xiao-Li Meng, joins Jon Krohn to dive into data trade-offs that abound, and shares his view on the paradoxical downside of having lots of data.\\nIn this episode you will learn:\\u2022 What the Harvard Data Science Review is and why Xiao-Li founded it [5:31]\\u2022 The difference between data science and statistics [17:56]\\u2022 The concept of 'data minding' [22:27]\\u2022 The concept of 'data confession' [30:31]\\u2022 Why there\\u2019s no \\u201cfree lunch\\u201d with data, and the tricky trade-offs that abound [35:20]\\u2022 The surprising paradoxical downside of having lots of data [43:23]\\u2022 What the Bayesian, Frequentist, and Fiducial schools of statistics are, and when each of them is most useful in data science [55:47]\\nAdditional materials: www.superdatascience.com/581"