Toph Tucker

Bitemporal coronavirus cases

Sensitivity and Specificity (sketch)

Coronavirus orbits

Variance

Smoothing with simple moving average vs. binomial filter

Coronavirus logistic isopleths

Recreating John Burn-Murdoch’s Coronavirus tracker

Building up to John Burn-Murdoch’s Coronavirus tracker

Covid Tracking Project data

Coronavirus

Sketches

I would pay to get a one paragraph summary of Bayes’s Theorem from you.

Visnu Pitiyanuvath

Ha, hm!! Let's say A and B are two things that may be true or false, with some probability. If A and B are not independent, then the probability of A is changed by knowing B, and vice versa. The probability of A, if you know B, is not the same as the probability of B, if you know A; to get from one to the other, multiply it by the ratio of the probabilities of the thing given to the thing unknown. The ratio of the probability of A given B to that of B given A equals the ratio of the probability of A to that of B. When A and B are similarly probable, the probabilities of each given the other will be similar. But when A is much more probable than B, then the probability of A given B is much greater than the probability of B given A. So even if A and B are correlated, then knowing A is true shouldn't give you much confidence that B is also true.

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