Author: Istvan Szapudi
Title: Efficient sample pooling strategies for COVID-19 data gathering Document date: 2020_4_7
ID: nsxp3xwf_4
Snippet: where N = N + + N − by definition. This formula assumes the independence of each test from each, and neglects any correlations between each pool (e.g. when families are tested in one pool, there results are more likely to be positive or negative together). For intuitive picture, the formula is equivalent to coin tossing, assuming the probability of heads is q n . We wish to use Bayesian inference to extract the information the data has on q (an.....
Document: where N = N + + N − by definition. This formula assumes the independence of each test from each, and neglects any correlations between each pool (e.g. when families are tested in one pool, there results are more likely to be positive or negative together). For intuitive picture, the formula is equivalent to coin tossing, assuming the probability of heads is q n . We wish to use Bayesian inference to extract the information the data has on q (and therefore p = 1 − q). Using Bayes' theorem, the likelihood of q is
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