Healty people have body temperatures that are normally distributed with a mean of 98.20∘F98.20∘F and a standard deviation of 0.62∘F0.62∘F . (a) If a healthy person is randomly selected, what is the probability that he or she has a temperature above 99.2∘F99.2∘F? answer: (b) A hospital wants to select a minimum temperature for requiring further medical tests. What should that temperature be, if we want only 1 % of healty people to exceed it?
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!
Healty people have body temperatures that are
(a) If a healthy person is randomly selected, what is the
answer:
(b) A hospital wants to select a minimum temperature for requiring further medical tests. What should that temperature be, if we want only 1 % of healty people to exceed it?
answer:
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