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Many companies vie a quaify control technique caled acceptance sampling to monitor incoming shipments of parts, raw materials, and so on. In the electronics industry, component parts are commanly shippes from supolers in large lots. Inspection of a sample of n components can be viewed as the n trials of a binamial esperiment. The outcome for each component tested (tria) witt oe that the component is classiled as good or defective. Reynolds Electronics accepts a lot from a particular supplier if the defoctive components in the lot do not exceed 0.5%. 54 ppose a random samp of seven items from a recent shioment is tested. (a) Assume that 0.5% of the shipment is defective. Compute the probability that no liems in the sample are defective. (Round your answer to four decimal places.) (b) Assume that 0.5% of the vilpment is defective. Compute the probablity tha exactiy one fiem in the sample is defective. (Round your answer to four decimal places.) (c) What is the probablity of observing one or more defective tems in the sample if 0.5% of the shipment is defective? (Round your answer to four decimal ptaces.) (d) Would you feel comfortabie accepting the shipment if ane item was found to be defective? Why or why not? B if 0.5% of the shipment is defective, it mould be that more then 0.5% of the shipment is defective. to see one or more defectives in a sample of swen tems. Therefore, observisg a defoctive