Probability - Binominal distribution

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SUMMARY

The discussion focuses on calculating the probability of a glass bottle being defective after it survives four drops. Given that 15% of the bottles are defective and that defective bottles break 60% of the time when dropped, the probability of a defective bottle surviving four drops is calculated as 2.56%. The correct approach involves using Bayes' Theorem to find the conditional probability P(D|S), where D is the event that the bottle is defective and S is the event that it survived the drops. The solution requires considering the total probabilities of surviving bottles, both defective and non-defective.

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MarcMTL
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Homework Statement


A factory makes glass bottles, and 15.0% of the bottles are considered defective. A defective bottle will break 60.0% of the time when dropped from a controlled height, whereas a non-defective bottle will only break 10.0% of the time in the same conditions.

You pick a single bottle at random and drop it four times in a row. It doesn't break. What is the probability that it is a defective bottle?

Homework Equations


The Attempt at a Solution



If a defective bottle breaks 60% of the time, I calculated the probability of it surviving four consecutive drops: (1-0.60)4 = 0.0256 (2.56%)

This is where I get doubtful, I'd tend to say that if 20% of the bottles are defective, and we picked a single bottle at random, that the probability that the bottle is defective would be:

0.0256 * 0.20 = 0.00512 (0.512%)

Not the right answer. Also, I feel that the last step was incorrect.

Any help would be greatly appreaciated!

Marc
 
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Try thinking about the whole population of bottles.

X% are not defective.
Y% are defective.

Now you pick a bottle at random and drop it four times.
What can happen?

It could be defective and survive. (a%)
It could be not-defective and survive (b%)
It could be defective and break (c%)
If could be not-defective and break (d%)

Now of course a+b+c+d = 100%. And we know that what actually happened was that our bottle didn't break, so we are actually only looking at (a+b)% of the population.

That should get you started..
 
Another way is...

S: the bottle survived 4 drops
D: the bottle is defective

Find these probabilities:
P(S:D), P(S:!D), P(D), P(S).

Then use Bayes Theorem to find P(D:S).
 

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