Really awesome piece. Many technically minded people (including myself up until a few months ago) would really benefit from reading this and taking it to heart.
I only gained this insight through my own experience of empirical testing and data acquisition through to analysis and curve fitting. Fitting the data was extremely arduous, so I set out to “find” the model that fits the data. After a long period of development and deeper theoretical understanding of the physical system, it hit me that I would never “find” the perfect model. What I really needed to do was find the right modeling framework and for each new set of data, I had to *choose* which parts to hang onto in order for the fit to work well.
It was a huge eye-opener into just how human-made our models of the world are.
Thank you very much for your comment, Derek! Yeah, it is not immediate to internalise these ideas, I agree. My feeling is that it is not so easy to grasp that there is no such thing as a perfect model because, as undergrads, we go through a lot of equations and models that look perfect for the task at hand. However, we rarely study problems for which those models are not good enough.
Really awesome piece. Many technically minded people (including myself up until a few months ago) would really benefit from reading this and taking it to heart.
I only gained this insight through my own experience of empirical testing and data acquisition through to analysis and curve fitting. Fitting the data was extremely arduous, so I set out to “find” the model that fits the data. After a long period of development and deeper theoretical understanding of the physical system, it hit me that I would never “find” the perfect model. What I really needed to do was find the right modeling framework and for each new set of data, I had to *choose* which parts to hang onto in order for the fit to work well.
It was a huge eye-opener into just how human-made our models of the world are.
Thanks for your work!
Thank you very much for your comment, Derek! Yeah, it is not immediate to internalise these ideas, I agree. My feeling is that it is not so easy to grasp that there is no such thing as a perfect model because, as undergrads, we go through a lot of equations and models that look perfect for the task at hand. However, we rarely study problems for which those models are not good enough.
❤️