Probability of Defective Components: Past Data Analysis & Quality Inspection

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On the basis of past data, suppose it is known that 0.5% of a components of a particular type manufactured by a firm are defective. The quality inspection procedure is such that 90% of the defective components will actually be found defective and 3% of the non-defective components will also be wrongly declared defective. A component is selected at random from the manufacturing process and inspected.

a) What is the probability that the components is declared defective?

b) If the component is declared defective, what is the conditional probability that the item is actually defective?
 
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There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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