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A shipment of 250 smartphones contains 84 that are defecti
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22 Mar 2013, 00:07
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A shipment of 250 smartphones contains 84 that are defective. If a customer buys two smartphones at random from the shipment, what is the approximate probability that both phones are defective? A. 1/250 B. 1/84 C. 1/11 D. 1/9 E. 1/3
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Re: A shipment of 250 smartphones contains 84 that are defecti
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22 Mar 2013, 00:14
emmak wrote: A shipment of 250 smartphones contains 84 that are defective. If a customer buys two smartphones at random from the shipment, what is the approximate probability that both phones are defective? a)\(\frac{1}{250}\) b)\(\frac{1}{84}\) c)\(\frac{1}{11}\) d)\(\frac{1}{9}\) e)\(\frac{1}{3}\) Probability of chosing one defective phone from a lot of 250 which ontains 84 defective phones is = (84/250) Probability of chosing one defective phone from a lot of 249(we already picked one) which ontains 83(we already picked one) defective phones is = (83/249) Combined probability of series of events = product of the probabilities = (84/250)*(83/249) 84/250 is close to (1/3) and (83/249)= (1/3) so answer is (1/3)*(1/3) = (1/9) So, answer will be D Hope it helps!
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Re: A shipment of 250 smartphones contains 84 that are defecti
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08 Jul 2013, 13:43
Amm... this doesn't seem that difficult. The only problem is quickly identifying that 84 is one third. Chances of picking 1 defective phone = 84 / 250 = ~0.33 (25/8 is even faster) Chances of picking 2 phones then = 0.33 x 0.33 = 1/3 x 1/3 = 1/9 If we need to go further = 1/3 x 1/3 x 1/3 = 1/27 Lotto goes on ))



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Re: A shipment of 250 smartphones contains 84 that are defecti
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08 Jul 2013, 14:48
same as what the other two said.
Probability that the first phone is defective is (84/250) ~ (80*3 = 240). Therefore the approximation is (1/3) Assuming that the first is a favorable outcome, for the next phone there will only be (83/249). Again, the approximation is ~ (1/3)
Probability of both events happening = (1/3)*(1/3) = 1/9 = D



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Re: A shipment of 250 smartphones contains 84 that are defecti
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08 Jul 2013, 20:23
emmak wrote: A shipment of 250 smartphones contains 84 that are defective. If a customer buys two smartphones at random from the shipment, what is the approximate probability that both phones are defective?
A. 1/250 B. 1/84 C. 1/11 D. 1/9 E. 1/3 \(84C2/250C2 = (84*83)/(250*249)= 14/125 = 1/9\) Note: This is same as picking 2 red colored cards in random from a deck of 52 cards.....



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Re: A shipment of 250 smartphones contains 84 that are defecti
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26 May 2016, 08:06
emmak wrote: A shipment of 250 smartphones contains 84 that are defective. If a customer buys two smartphones at random from the shipment, what is the approximate probability that both phones are defective?
A. 1/250 B. 1/84 C. 1/11 D. 1/9 E. 1/3 probability of selecting two defective phones= 84/250*83/249= 1/9 D is the answer.
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Re: A shipment of 250 smartphones contains 84 that are defecti
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15 May 2018, 15:17
emmak wrote: A shipment of 250 smartphones contains 84 that are defective. If a customer buys two smartphones at random from the shipment, what is the approximate probability that both phones are defective?
A. 1/250 B. 1/84 C. 1/11 D. 1/9 E. 1/3 The probability of getting two defective smartphones is: 84/250 x 83/249 ≈ 1/3 x 1/3 = 1/9 Answer: D
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Re: A shipment of 250 smartphones contains 84 that are defecti
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22 Oct 2018, 08:16
Veritas Prep Official Solution: This is dependent probability, so start by setting up your conditions. The odds that the first phone is defective are 84/250. Assume the customer gets that first defective phone. Now one defective phone has been removed, so the odds that second phone is defective are 83/249, since only 83 defective phones and 249 total phones remain. Now we have 84/250 * 83/249, which looks awful. but remember that the GMAT doesn’t tend to give us random, unworkable numbers: there must be a shortcut. 83/249 simplifies perfectly to 1/3, while 84/250 can be simplified as 42/125. Multiplying these together gives us 42/375. 42 goes into 375 almost exactly nine times, so 42/375 is close to 1/9.



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Re: A shipment of 250 smartphones contains 84 that are defecti
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01 Dec 2019, 14:57
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