The hospitalization time among mild covid-19 patients in Hubei province is normally distributed with mean of 21 days and a standard deviation of 9 days. What is the probability of a covid-19 patient with mild symptoms staying in the hospital? a. More than 32 days? b. Between 4 and 33 days? c. Top 10% of patients who stays the longest will be send to another location. How long a patient must be in the hospital in order to be send to the other location?
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!
The hospitalization time among mild covid-19 patients in Hubei province is
a. More than 32 days?
b. Between 4 and 33 days?
c. Top 10% of patients who stays the longest will be send to another location. How long a patient must be in the hospital in order to be send to the other location?
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