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Data is Not Enough with Dr. Carlos Vega

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Manage episode 447419446 series 2832348
内容由Hanna Siemaszko提供。所有播客内容(包括剧集、图形和播客描述)均由 Hanna Siemaszko 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

It was refreshing to chat to Dr. Carlos Vega, Research Engineer at the Luxembourg Institute of Health and a teacher at the University of Luxembourg. Carlos, who recently distinguished himself in the science.lu Science Writing competition, is a very good communicator. In this episode we explore the practical challenges of data collection, processing, and visualisation, highlighting the pitfalls and ethical considerations that accompany the use of data in scientific research.

Carlos uses vivid analogies, such as the omelette analogy from his award-winning article, to illustrate complex concepts in a relatable manner. The conversation also touches on the role of inductive reasoning and the potential for errors in data interpretation.

This episode is a must-listen for anyone interested in the intersection of data science, ethics, and technology.

  continue reading

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Artwork
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Manage episode 447419446 series 2832348
内容由Hanna Siemaszko提供。所有播客内容(包括剧集、图形和播客描述)均由 Hanna Siemaszko 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

It was refreshing to chat to Dr. Carlos Vega, Research Engineer at the Luxembourg Institute of Health and a teacher at the University of Luxembourg. Carlos, who recently distinguished himself in the science.lu Science Writing competition, is a very good communicator. In this episode we explore the practical challenges of data collection, processing, and visualisation, highlighting the pitfalls and ethical considerations that accompany the use of data in scientific research.

Carlos uses vivid analogies, such as the omelette analogy from his award-winning article, to illustrate complex concepts in a relatable manner. The conversation also touches on the role of inductive reasoning and the potential for errors in data interpretation.

This episode is a must-listen for anyone interested in the intersection of data science, ethics, and technology.

  continue reading

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