document.write( "Question 495961: Please help me solve this problem: \"On a particular production line the probability that an item will be defective is 0.1. A quality controller selects, at random, three items from a batch and examines them for defects. If at least 2 of the items are defective then the whole batch is rejected. Determine the probability that a batch is rejected using the Binomial distribution.\"
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Algebra.Com's Answer #336274 by Theo(13342)\"\" \"About 
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probability of an item being defective is .1
\n" ); document.write( "probability of an item not being defective is 1 - .1 = .9
\n" ); document.write( "if p = defective and q = not defective, then the formula for x out of n would be:
\n" ); document.write( "p(x) = p^x * q^(n-x) * nCx
\n" ); document.write( "we are drawing 3 items from the batch, so n = 3
\n" ); document.write( "we want to find the probability that at least 2 are defective out of the 3.
\n" ); document.write( "this would be equal to 1 - p(0) - p(1) or it would be equal to p(2) + p(3).
\n" ); document.write( "we'll work it both ways so you can see how that happens.
\n" ); document.write( "nCx is the combination formula for x things out of n.
\n" ); document.write( "it is equal to n! / (x! * (n-x)!)
\n" ); document.write( "using the formula of p(x), we get:
\n" ); document.write( "p(0) = .1^0 * .9^3 * 3C0 = .729 * 1 = .729
\n" ); document.write( "p(1) = .1^1 * .9^2 * 3C1 = .081 * 3 = .243
\n" ); document.write( "p(2) = .1^2 * .9^1 * 3C2 = .009 * 3 = .027
\n" ); document.write( "p(3) = .1^3 * .9^0 * 3C3 = .001 * 1 = .001
\n" ); document.write( "sum up all the probabilities and you get p(all) = 1
\n" ); document.write( "this is what you should get when you add up all the probabilities of independent events like we have here.
\n" ); document.write( "p(>=2) = p(2) + p(3) = .027 + .001 = .028
\n" ); document.write( "p(>=2) = 1 - p(0) - p(1) = 1 - .729 - .243 = .028
\n" ); document.write( "we get the same answer either way, as we should.
\n" ); document.write( "your answer is that the probability of getting a sample with at least 2 defective units in it is .028 or 2.8%\r
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