HIV/AIDS patients are regularly monitored for their CD4 counts in order to make sure that antiretroviral therapies are effective. Suppose the distribution of counts in a population is approximately normal with mu = 237 and sigma = 43 HIV patients are defined as moving into the AIDS stage of their disease course after their CD4 counts are less than 200. What proportion of patients in this population is suffering from aids
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!
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