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Edexcel S2 help

need help, part d, +1 if u can cheers!


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From your Part A, you know the probability of X being less than -4.2 for one pipe is 0.08. In d, you are now considering 60 lengths and also told to approximate.

Hence you can represent this as a binomial distribution Z~B(n,p) where n would be 60 in this case and p being the probability of P being less than -4.2.

You are told to approximate hence you can use the Poison Distribution to approximate this distribution where your mean would be n.p so 4.8 in this case. Hence now using the Poison Distribution, find the probability of it being less or equal to 2
Reply 2
Original post by TheTechnoGuy
From your Part A, you know the probability of X being less than -4.2 for one pipe is 0.08. In d, you are now considering 60 lengths and also told to approximate.

Hence you can represent this as a binomial distribution Z~B(n,p) where n would be 60 in this case and p being the probability of P being less than -4.2.

You are told to approximate hence you can use the Poison Distribution to approximate this distribution where your mean would be n.p so 4.8 in this case. Hence now using the Poison Distribution, find the probability of it being less or equal to 2


I did that bro and used the formula with lambda = 4.8 and x = 2 and got an incorrect answer :s-smilie:
What did you get? What is the correct answer?
Reply 4
Original post by old_engineer
What did you get? What is the correct answer?


i got 0.0948 the correct answer is 0.1425..
Original post by Virolite
need help, part d, +1 if u can cheers!


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What year is this?
Looks old as hell
Original post by Virolite
i got 0.0948 the correct answer is 0.1425..


Then I would say that you have probably used the Poisson probability density function rather than the Poisson cumulative distribution function. You could use the Poisson PDF, but then you would need to add P(0), P(1) and P(2).
Reply 7
Original post by old_engineer
Then I would say that you have probably used the Poisson probability density function rather than the Poisson cumulative distribution function. You could use the Poisson PDF, but then you would need to add P(0), P(1) and P(2).


oh right cheers!

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