A machining operation produces bearings with diameters that are normally distributed with a mean of 3.0005 inches and a standard deviation of .0010 inches. Specifications require the bearing diameters to lie in the interval of 3.000 +/-.0020 inches. Those outside the interval are considered scrap and must be disposed of. With the existing machine setting, what fraction of total production will be scrap
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 machining operation produces bearings with diameters that are
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