Exponential growth and epidemics

From the creator

A primer on exponential and logistic growth Help fund future projects: https://www.patreon.com/3blue1brown An equally valuable form of support is to simply share some of the videos. Special thanks to these supporters: http://3b1b.co/covid-thanks Home page: https://www.3blue1brown.com Excellent visualization of this kind of growth from Minutephysics and Aatish Bhatia: https://www.youtube.com/watch?v=54XLXg4fYsc Data source: https://www.worldometers.info/coronavirus/coronavirus-cases/#case-tot-outchina Some have (quite rightfully) commented on how you shouldn't look at the R^2 of linear regressions on cumulative data since even if the changes from one day to the next are completely random, the totals they add up to wouldn't be independent of each other. Since the derivative of an exponential should also be an exponential, we could instead run the same test on the logarithms of the differences from day to day, which in this case gives R^2 = 0.91. While this video uses COVID-19 as a motivating example, the main goal is simply a math lesson on exponentials and logistic curves. If you're looking for a video more focused on COVID-19 itself, I'd recommend taking a look at this one from Osmosis: https://youtu.be/cFB_C2ieW5I Extrapolation xkcd: https://xkcd.com/605/ Thanks to these viewers for their contributions to translations Hebrew: Omer Tuchfeld ------------------ These animations are largely made using manim, a scrappy open source python library: https://github.com/

Published 2020-03-08 · Watch on YouTube ↗
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