During the start of the COVID 19 pandemic it is assumed that the rate of spread of the corona virus is 18 % daily following a simple logistic growth model by Verhulst. Ten persons are assumed to have acquired the virus in province X. Assuming province X with a population of 2 million does not follow any necessary protocol to prevent the spread of the virus, approximately how many are expected to have acquired the virus after 30 days?
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
During the start of the COVID 19 pandemic it is assumed that the rate of spread of the corona virus is 18 % daily following a simple logistic growth model by Verhulst. Ten persons are assumed to have acquired the virus in province X. Assuming province X with a population of 2 million does not follow any necessary protocol to prevent the spread of the virus, approximately how many are expected to have acquired the virus after 30 days?
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