We discuss scientists’ tendency to turn hypotheses into innately true ‘essences’ passed down by tradition.

(See this notebook on GitHub) A year ago, I wrote about how to use R to solve a typical microeconomics problem: finding the optimal price and quantity of some product given its demand and cost. Doing this involves setting the first derivatives of two functions equal to each other and using algebra to find where they cross.

When it comes to job titles, data scientist is one of the biggest buzzwords in recent years. It is also one of the fastest growing fields of professional activity. Can an economist really be a data scientist? What skills are needed?

In today’s post, I want to start a discussion about the use of mathematics and statistics in economics, and with this shocking sentence: When a person studies economics for the first time, it is likely that they will not encounter “crazy” equations that go beyond basic mathematics.

I will present here some personal reflections on a concept that is considered very simple and perhaps common in economics, but which is labeled as the height of ignorance for making an assumption that cannot be observed in reality, but which in my view is a mistake. mistake.

This is the second in a series of posts (first one here) in which I am trying to process and collect ideas that came out of Scifoo. This post arises out of a discussion I had with Michael Eisen (UC Berkely) and Sean Eddy (HHMI Janelia Farm) at lunch on the Saturday. We had drifted from a discussion of the problem of attribution stacking and citing datasets (and datasets made up of datasets) into the problem of academic credit.

I’m in Barcelona at a satellite meeting of the EuroScience Open Forum organised by Science Commons and a number of their partners.Â

I am thinking about how to present the case for Open Science, Open Notebook Science, and Open Data at Science in the 21 ^st Century, the meeting being organised by Sabine Hossenfelder and Michael Nielsen at the Perimeter Institute for Theoretical Physics.