The strength of a weld is determined by the formula X = 0 + 3N + 5C where X is the strength, and O, N, and C are the amounts of oxygen, nitrogen, and carbon, respectively in weight per cent in the weld. Suppose O, N and C are Independent normal random variables with respective means µ0 = 0.1665, µN = 0.0455, µC = .0346, and standard deviations o0 = 0.0340, oN = 0.0114, oC = .0131 a) Calculate the expected value of X. 0.476 b) Calculate the standard deviation of X. 0.0813 c) What is the probability that the strength(X) of a weld is more than 0.5? 0.384 d) What is the probability that the strength of a weld is between 0.4 and 0.6.? 0.761 e) If we pick a value k such that the probability that X > k equals .87 then calculate k? f) What is the median of the distribution of X? g )We look at 10 randomly selected welds. What is the probability that all 10 of the selected welds have strengths greater than .467? h) What is the probability that the strength of a weld is exactly .480? I) What is the probability that N > 0.05?
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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