Bayes’ Theorem became extremely relevant during the CoViD-19 pandemic. A study published in late 2021 calculated the probability of a false negative RT-PCR test during the early stages of the disease as approximately 58%. It has however a very high specificity of approximately 95%, meaning that the percentage of false positives is at 5%. Assuming that the positivity rate is an accurate measure of the true infected population, calculate the probability that a person selected at random has not contracted SARS-CoV-2, when their PCR test is negative, and the positivity rate is 4% and when it is 12%
Bayes’ Theorem became extremely relevant during the CoViD-19 pandemic. A study published in late 2021 calculated the probability of a false negative RT-PCR test during the early stages of the disease as approximately 58%. It has however a very high specificity of approximately 95%, meaning that the percentage of false positives is at 5%. Assuming that the positivity rate is an accurate measure of the true infected population, calculate the probability that a person selected at random has not contracted SARS-CoV-2, when their PCR test is negative, and the positivity rate is 4% and when it is 12%
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Bayes’ Theorem became extremely relevant during the CoViD-19 pandemic. A study published
in late 2021 calculated the
of the disease as approximately 58%. It has however a very high specificity of approximately
95%, meaning that the percentage of false positives is at 5%. Assuming that the positivity
rate is an accurate measure of the true infected population, calculate the probability that a
person selected at random has not contracted SARS-CoV-2, when their PCR test is negative,
and the positivity rate is 4% and when it is 12%
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