First success, sampling without replacement

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  • #1
alman9898
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Homework Statement


A box contains 5 keys, only one of which will open a lock. Keys are randomly selected and tried, one at a time, until the lock is opened (keys that do not work are discarded before another is tried). Let Y be the number of the trial on which the lock is opened. What is the prob function for Y?

Homework Equations


[tex]{{{m \choose k} {{N-m} \choose {n-k}}}\over {N \choose n}}[/tex]

The Attempt at a Solution



What I am trying to find...

P(Y = i) where i is the number of the trial where the "first" (and only) success occurs. This would be much easier if the trials were independent but since they are dependent, I'm having trouble translating the problem into a hypergeometric one. The explanations I"ve found provided online quickly jump to the math without explaining why they did what they did...

What I've tried is C(1,1) * C(4, i-1) / C(5, i) but I know this is wrong because I believe it should turn out that p(i) = 1/5 for all i (based off this http://docs.google.com/gview?a=v&q=cache:_nd2dQm5Me8J:https://www.cs.drexel.edu/classes/ProbStat/mcs311_Spring98/test2ans.pdf+%22a+box+contains+5+keys%22&hl=en&gl=us&sig=AFQjCNHgIMqwTOs-06Phz8C11i5iqKDTlA" I found online), but I can't determine how to proceed...I'm very confused...

Further update: it seems this formula probably describes the cdf rather than the pdf, but I don't know why...I would really appreciate a clear and concise explanation.
 
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  • #2
Its obvious P(Y=1) = 1/5. To get P(Y=2) two things must happen. You must fail on the first draw and succeed on the second. So you need a conditional probability:

[itex]P(Y=2) = P(Y\ne 1)P(Y=2|Y\ne 1)[/itex]

Can you figure that out and take it from there?
 
  • #3
So, what exactly did I find when I have

C(1,1)*C(4, i-1)/C(5,i) ... the conditional probability for Y = i ?
 
  • #4
just a quick question, did you get your answer, because I am dealing with similar problem atm and can't find any help online with it, cheers
 
  • #5
LCKurtz said:
Its obvious P(Y=1) = 1/5. To get P(Y=2) two things must happen. You must fail on the first draw and succeed on the second. So you need a conditional probability:

[itex]P(Y=2) = P(Y\ne 1)P(Y=2|Y\ne 1)[/itex]

Can you figure that out and take it from there?

alman9898 said:
So, what exactly did I find when I have

C(1,1)*C(4, i-1)/C(5,i) ... the conditional probability for Y = i ?

Somehow I didn't see your answer earlier. I don't know what your forumula represents, but you ignored my question. The answer to my question will lead you to the solution method.
 
  • #6
alman9898 said:

Homework Statement


A box contains 5 keys, only one of which will open a lock. Keys are randomly selected and tried, one at a time, until the lock is opened (keys that do not work are discarded before another is tried). Let Y be the number of the trial on which the lock is opened. What is the prob function for Y?

Homework Equations


[tex]{{{m \choose k} {{N-m} \choose {n-k}}}\over {N \choose n}}[/tex]

The Attempt at a Solution



What I am trying to find...

P(Y = i) where i is the number of the trial where the "first" (and only) success occurs. This would be much easier if the trials were independent but since they are dependent, I'm having trouble translating the problem into a hypergeometric one. The explanations I"ve found provided online quickly jump to the math without explaining why they did what they did...

What I've tried is C(1,1) * C(4, i-1) / C(5, i) but I know this is wrong because I believe it should turn out that p(i) = 1/5 for all i (based off this http://docs.google.com/gview?a=v&q=cache:_nd2dQm5Me8J:https://www.cs.drexel.edu/classes/ProbStat/mcs311_Spring98/test2ans.pdf+%22a+box+contains+5+keys%22&hl=en&gl=us&sig=AFQjCNHgIMqwTOs-06Phz8C11i5iqKDTlA" I found online), but I can't determine how to proceed...I'm very confused...

Further update: it seems this formula probably describes the cdf rather than the pdf, but I don't know why...I would really appreciate a clear and concise explanation.

Your formula above is the answer to a question completely from the one you are asking about. Rather than writing down random formulas (that may, or may not be relevant), just sit down and consider the situation one key at a time. What is the probability that the first key works? What is the probability that the first key does not work but the second one does? After answering these two questions you should start to see the needed pattern.

RGV
 
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FAQ: First success, sampling without replacement

What is meant by "First success" in sampling without replacement?

"First success" refers to the first time a specific outcome or event occurs in a sample without the possibility of that outcome occurring again in subsequent samples. This is a key concept in sampling without replacement, where each item or individual can only be selected once.

How is sampling without replacement different from sampling with replacement?

In sampling without replacement, once an item or individual is selected, it is removed from the sample and cannot be selected again. In contrast, sampling with replacement allows for the same item or individual to be selected multiple times in a single sample.

What are the advantages of using sampling without replacement in scientific research?

Sampling without replacement ensures that each item or individual in the sample has an equal chance of being selected and reduces the likelihood of biased results. It also allows for the use of statistical methods that assume independent samples.

Can sampling without replacement be used in all types of scientific research?

Sampling without replacement is commonly used in many types of scientific research, such as in surveys, experiments, and quality control. However, there may be situations where sampling with replacement may be more appropriate, such as in simulations or when the population is very large.

What are the potential limitations of using sampling without replacement?

One limitation of sampling without replacement is that it may not accurately represent the entire population if the sample size is too small. It also requires careful planning and consideration of the sampling method to ensure that all individuals or items have an equal chance of being selected.

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