Masters of self-deception, rapid systematic reviews, and Gauss v. Legendre.

1. Human fallibility → Debiasing techniques → Better science Don’t miss Regina Nuzzo’s fantastic analysis in Nature: How scientists trick themselves, and how they can stop. @ReginaNuzzo explains why people are masters of self-deception, and how cognitive biases interfere with rigorous findings. Making things worse are a flawed science publishing process and “performance enhancing” statistical tools. Nuzzo describes promising ways to overcome these challenges, including blind data analysis.

2. Slow systematic reviews → New evidence methods → Controversy Systematic reviews are important for evidence-based medicine, but some say they’re unreliable and slow. Two groups attempting to improve this – not without controversy – are Trip (@TripDatabase) and Rapid Reviews.

3. Campus competitions → Real-world analytics → Attracting talent Tech firms are finding ways to attract students to the analytics field. David Weldon writes in Information Management about the Adobe Analytics Challenge, where thousands of US university students compete using data from companies such as Condé Nast and Comcast to solve real-world business problems.

4. Discover regression → Solve important problem → Rock the world Great read on how Gauss discovered statistical regression, but thinking his solution was trivial, didn’t share. Legendre published the method later, sparking one of the bigger disputes in the history of science. The Discovery of Statistical Regression – Gauss v. Legendre on Priceonomics.

5. Technical insights → Presentation skill → Advance your ideas Explaining insights to your audience is as crucial as getting the technical details right. Present! is a new book with speaking tips for technology types unfamiliar with the spotlight. By Poornima Vijayashanker (@poornima) and Karen Catlin.

Posted by Tracy Allison Altman on 24-Apr-2016.

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Museum musings.

Pondering the places where people interact with artificial intelligence: Collaboration on evidence-based decision-making, automation of data-driven processes, machine learning, things like that.

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