The distribution for the time a patient of a medical center spends waiting for an appointment is normal with mean of 35 minutes and standard deviation of 12 minutes. A random sample of 42 patients will be collected and the sample mean waiting time will be computed. c. If you wanted the standard deviation of the same mean to be 1.25, how big should your sample be
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!
2. The distribution for the time a patient of a medical center spends waiting for an appointment
is normal with
of 42 patients will be collected and the sample mean waiting time will be computed.
c. If you wanted the standard deviation of the same mean to be 1.25, how big should your sample be?
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