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Statistics history, interdisciplinarity, and data and society. Chris Wiggins talks with Jon Krohn about the power dynamics of data, the transformation of the field of biology through data-driven approaches to genetic sequencing, and the New York Times’ data science team’s cutting-edge approach to accommodating its tech stack.
This episode is brought to you by the AWS Insiders Podcast and by Modelbit, for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• The importance of the humanities in data science [09:18]
• How data science “rearranges” power [17:19]
• An overview of How Data Happened [20:36]
• The controversial nature of Bayes theorem [29:16]
• Why we need to consider data ethics [34:00]
• How biology came to adopt data science into its field [45:44]
• The data science tech stack at the New York Times [49:18]
Additional materials: www.superdatascience.com/703
By Jon Krohn4.6
295295 ratings
Statistics history, interdisciplinarity, and data and society. Chris Wiggins talks with Jon Krohn about the power dynamics of data, the transformation of the field of biology through data-driven approaches to genetic sequencing, and the New York Times’ data science team’s cutting-edge approach to accommodating its tech stack.
This episode is brought to you by the AWS Insiders Podcast and by Modelbit, for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• The importance of the humanities in data science [09:18]
• How data science “rearranges” power [17:19]
• An overview of How Data Happened [20:36]
• The controversial nature of Bayes theorem [29:16]
• Why we need to consider data ethics [34:00]
• How biology came to adopt data science into its field [45:44]
• The data science tech stack at the New York Times [49:18]
Additional materials: www.superdatascience.com/703

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