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    (Original post by abc123)
    did anyone manage the last part of No.7, where we had to prove that T(o) was between 22 and 23. Where we supposed to solve that fat arse equation? i dunno cause it was only worth 2 marks....
    That is a simple Pure question. Enter the values 22 and 23 into the quartic equation. Result: Func(22) < 0 and Func(23) > 0, therefore root (To) must lie between 22 and 23.
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    (Original post by pi is exactly 3)
    I Used the binomial that way too, cant remember the answer though, was it something like 0.2 or 0.3?
    x=2 was 0.195, x=1 was 0.371, and i think x=0 was 0.34~, so I got about...

    0.094. About. And yes, I did just use Windows calculator :P
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    (Original post by Urdegish)
    I personally approximated them to a binomial distribution, with N 50 and P 0.021. Then did 1 - p(x = 1,2,3).

    For a binomial np needs to be bigger than 5, which it wasn't, it was 1.05.

    So i think the only approximation is Po-(1.05)
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    I didnt think to try Poisson, on the strict rule of fact that the question stated it was a poisson distributed and part B) specified you had to use an approximation. And since I used Normal in part A), the rest followed...
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    (Original post by abc123)
    For a binomial np needs to be bigger than 5, which it wasn't, it was 1.05.

    So i think the only approximation is Po-(1.05)
    I thought that np had to be greater than 5 if you were using a normal approx to the binomial, not the other way round? Or am I completely wrong?
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    (Original post by Urdegish)
    I personally approximated them to a binomial distribution, with N 50 and P 0.021. Then did 1 - p(x = 1,2,3).
    Then model by a Poisson.
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    (Original post by Urdegish)
    I didnt think to try Poisson, on the strict rule of fact that the question stated it was a poisson distributed and part B) specified you had to use an approximation. And since I used Normal in part A), the rest followed...

    lol i'm confused now. In part a) we were given a poisson distribution, with a large lambda, so we could approximate using normal.

    then in part B) we were given a binomial distributon (with a (p) from part (a) ), and as N was large, and P small, we could approximate using poisson...

    I think thats how it was done
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    (Original post by pi is exactly 3)
    I thought that np had to be greater than 5 if you were using a normal approx to the binomial, not the other way round? Or am I completely wrong?
    Correct. That also. And np has to be less than 5 for Poisson to Normal. Looked at a question containing that before I entered exam.
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    (Original post by abc123)
    lol i'm confused now. In part a) we were given a poisson distribution, with a large lambda, so we could approximate using normal.

    then in part B) we were given a binomial distributon (with a (p) from part (a) ), and as N was large, and P small, we could approximate using poisson...

    I think thats how it was done
    I wish somebody would scan the paper, so we can remeber.
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    I think that part B was still in a Poisson distribution context. with lambda = 38x50 = 1900. Too big for Normal, and too big for Poisson, therefore have to use Binomial.

    38x50 comes from 38 uniform events a week, and since there are 50 weeks then lambda increases uniformly
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    I also apologise if I appear to be throwing my proverbial weight around here, being a new member n' all that.
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    But why approximate using a poisson when the original is a poisson? And do the poisson tables give enough accuracy and go high enough for when n is 50 and lamda is 1.05?
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    Ahh yes!! I remember now! Max n value was 30 in the formula book
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    u had a binomial with X~B(50,0.021) which can be approximated to X~Po(1.05)

    then the question asked for P(X>2) which is 1-P(X<=2) and u have to use the poisson formula. 1-(P(X=0)+P(X=1)+P(X=2))
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    (Original post by Urdegish)
    I think that part B was still in a Poisson distribution context. with lambda = 38x50 = 1900. Too big for Normal, and too big for Poisson, therefore have to use Binomial.

    38x50 comes from 38 uniform events a week, and since there are 50 weeks then lambda increases uniformly
    Although that makes sense, and i had that thought in the exam, the reason why i doubt it is because there was a previous question on the paper (ques 5 i think) were we had to use a muiltiple of a Lambda 2, i don't think they would have ask us to use the same theory twice...
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    (Original post by yan2004)
    u had a binomial with X~B(50,0.021) which can be approximated to X~Po(1.05)

    then the question asked for P(X>2) which is 1-P(X<=2) and u have to use the poisson formula. 1-(P(X=0)+P(X=1)+P(X=0))
    Yeah i see where you're coming from but i still dont get why theyd want u 2 approximate using poisson when the thing was a poisson to begin with. The binomial works fine the same way and gets rid of any extra weirdness from another approx
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    Unfortunately, its a maths paper, and they are out to get us and make us trip up!
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    (Original post by yan2004)
    u had a binomial with X~B(50,0.021) which can be approximated to X~Po(1.05)

    then the question asked for P(X>2) which is 1-P(X<=2) and u have to use the poisson formula. 1-(P(X=0)+P(X=1)+P(X=2))
    Agreed.
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    (Original post by pi is exactly 3)
    Yeah i see where you're coming from but i still dont get why theyd want u 2 approximate using poisson when the thing was a poisson to begin with. The binomial works fine the same way and gets rid of any extra weirdness from another approx
    well part a) was poisson in context, but part b) was binomial in context....so if you look at it that way, it may not seem so wierd
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    (Original post by pi is exactly 3)
    Yeah i see where you're coming from but i still dont get why theyd want u 2 approximate using poisson when the thing was a poisson to begin with. The binomial works fine the same way and gets rid of any extra weirdness from another approx
    Well if you think about it, its a completely different question. It concerned whether they would have to hire extra staff, or not. hence the binomial. Since N is too large to model, we had to use an approximation, and since np was less than 5, our only option was to use lambda.
 
 
 
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