A ski lift states a maximum capacity is 12 people or 2004lb. A worst-case scenario would be 12 adult male passengers since they tend to be heavier verse women and children. Assume adult male weights are normally distributed with a mean of 188.6 lb and a standard deviation of 38.9 lb. A. If 12 men weighed exactly 2004 lb, what would be the average weight? B. Find the probability that a single man will have a weight greater than your result from A. C. Find the probability that a single man will have a weight greater than your result from A. Does the ski lift appear to have the correct weight limit from these results?
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!
A ski lift states a maximum capacity is 12 people or 2004lb. A worst-case scenario would be 12 adult male passengers since they tend to be heavier verse women and children. Assume adult male weights are
A. If 12 men weighed exactly 2004 lb, what would be the average weight?
B. Find the
C. Find the probability that a single man will have a weight greater than your result from A.
Does the ski lift appear to have the correct weight limit from these results?
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