5. For a construction project, a large mumber of bolts in one batch is purchased. It is known from the past experience that the tensile strength of each bolt can be modeled by a lognormal distribution with a mean value of µx = 350 kN and a coefficient of variation of 8g = 0.15. In a load test, a bolt is considered to be acceptable if it carries at least 270 KN. a) What is the probability that a bolt picked randomly will pass the test? b) It is impractical to test all the bolts for their strengths. Therefore, for quality control purposes, it is required that all of the 5 bolts selected at random from the batch must pass the test for the whole batch to be acceptable. In this case, what is the probability that the purchased batch is rejected (not suitable)? c) Apart from the inspection scheme applied in Part b, another inspection scheme is proposed in order to accept the purchased batch. In this new inspection scheme, at least 9 of the 10 bolts tested must pass the test for the whole batch to be acceptable. Is this new inspection scheme stricter than the one used in Part b?
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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