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It’s also conceptually easier. Like convolutions are far simpler to comprehend in discrete form. Difference equations seem more intuitive than differential. Some things are harder imo like Laplace and Fourier transforms.
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Stochastic calculus is what you wanted I think. Brownian motion and jumps and so forth. This is where both math finance and physics have to go to explain most phenomena seen / experienced. It’s a weird thing to find reality is stochastic; things flashing in and out of existence.
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as a bonus we can teach people some type theory before they start hacking on python and improve the median code quality of the world quite a bit
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Apart from specific uses (not to be so easily dismissed), the differential and integral calculus is a great conceptual achievement. Then usually the continuous description is fundamental and discretization involves choices, e.g. generating a mesh for FEM.
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Calculus is such a beautiful methematical gem but you never use it in real life But before we drop it for discrete math could we at least concentrate our focus on teaching people the value of compound interest, it affects their financial livelihood so much and Is so important
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