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The task:

The number of oil tankers, arriving at a certain refinery on one day, follow a Poisson distribution with the parameter $u = 2$. The present harbour facilities can serve 3 oil tankers a day. If more than 3 oil tankers arrive on a given day, the additional tankers (in excess of the 3) are sent to another refinery

Question 1: What is the probability that oil tankers are sent to another refinery?

Question 2: By how much should the capacity of the refinery harbour be extended, if it is desired that on a given day the probability of sending away arriving oil tankers does not exceed 0.05? 0.01?

Question 3: What is the expected number of oil tankers arriving on a given day?

Question 4: What is the most probable number of oil tankers arriving on a given day?

Question 5: What is the expected number of oil tankers served on a given day?

Question 6: What is the expected number of oil tankers sent on to other refineries on a given day?

I've tried to answer Question 1 and 3 and got stuck on question 4.

Q 1:

We let X be the value of oil tankers arriving each day.

Then we find the expected value of $P(X>3) = 0.35277$

(sorry don't know how to do the fancy equation stuff, but if the answer is correct I assume I've done that one right)

Q 3:

The expected number of a Poisson distribution with paramter $u = u$

therefor the expected number of oil tankers arriving on a given day is 2 right?

Q 4:

I belive it's something to do with the poisson formula right?

I've gotten so far:

$$\frac{2^k e^{-k}} k = P(k)$$

where i find P(0),P(1),P(2),P(3) etc? this is how far I've gotten. and I don't know what to do with these numbers as they don't make sense by themselves. Obviously there is no a 100% probability of 0 oil tankers arriving daily when the mean is 2

As for Question 2. I've tried using the same method I did for question 1. But replacing the maximum number of tankers it can serve to $y%, and replacing 3 with $y$ in the entire equation then solving for it gives 0.05.

but that didn't work out at all. :/

and I am completly blank on question 5 and 6 :(

hope you can help me out!

Thanks in advance geniuses!

Mikkel
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  • Any time I see something like "$u=u$", I tend to scratch my head. – dfeuer Oct 09 '13 at 22:31
  • well I guess in this scenario u is lamdba.

    What I mean is that u = The expected number of oil tankers arriving on a given day? right?

    and then the answer to question 3 would be u, which is 2.

    and thank you soo much for fixing the equations for me.

    Also think I got a bit further with question 4. let me just edit the post.

    – Mikkel Oct 09 '13 at 22:45

2 Answers2

1

Let $X$ be the number of tankers arriving on a randomly chosen day.

Q1: The probability that on a given day one or more oil tankers is sent to another refinery is $1$ minus the probability that $X\gt 3$. This is $$1-e^{-2}\left(1+\frac{2}{1!}+\frac{2^2}{2!}+\frac{2^3}{3!}\right).$$ I think that does not produce your number. Moreover, we want $\Pr(X\gt 3)$, not the "expected value $\dots$."

Q2: This one will require some experimentation. Suppose we extend capacity to $k$. We want to choose $k$ so that $\Pr(X\gt k)\le 0.05$. So we want $\Pr(X\le k)\gt 0.95$. Calculation shows that $k=4$ almost gets us there, and $k=5$ gets us there with plenty to spare.

Do a similar calculation for $0.01$.

For similar problems with different numbers, one might want to use more sophisticated techniques to estimate the "tail" of the Poisson.

Q3: Trivial. By the way, it is probably $\mu$, not $u$.

Q4: The probability the number is $k$ is $p_k$, where $p_k=e^{-2}\frac{\mu^{k}}{k!}$.

In our case, we can just compute the first few values, and observe that the maximum is reached at $2$ places, $k=1$ and $k=2$. But in addition we do this using more general tools. We have $$\frac{p_{k+1}}{p_k}=\frac{e^{-2}\frac{2^k}{k!}}{e^{-2}\frac{2^{k+1}}{(k+1)!}}=\frac{2}{k+1}$$ (there was a lot of cancellation). If $k+1\lt 2$, we have $p_{k+1}\gt p_k$. If $k+1=2$ we have equality, and if $k+1\gt 2$ then $p_{k+1}\lt p_k$. For "most probable" there is therefore a tie between $k=1$ and $k=2$.

Q5: Let $Y$ be the number of tankers served. The random variable $Y$ takes on the values $0$, $1$, $2$, or $3$.

The probabilities $\Pr(Y=0)$, $\Pr(Y=1)$, and $\Pr(Y=2)$ are just the Poisson probabilities. For $\Pr(Y=3)$, compute $1-\Pr(X\le 3)$. Now that you have $\Pr(Y=k)$ for the various values of $k$, you can compute $E(Y)$ in the usual way.

Q6: Let $Z$ be the number of tankers sent away. We want $E(Z)$. The easiest way to calculate this is to note that $Y+Z=X$ (here $Y$ is the random variable we used i Question 5). Thus $E(Y+Z)=E(X)=2$. By the linearity of expectation, we have $E(Y+Z)=E(Y)+E(Z)$. Thus $E(Z)=2-E(Y)$.

Added: On request, we do the detailed calculation for Question 5. The number $Y$ of tankers serviced is either $0$, $1$, $2$, or $3$.

We have $\Pr(Y=0)=e^{-2}\frac{2^0}{0!}=e^{-2}$. Also, $\Pr(Y=1)=e^{-2}\frac{2^1}{1!}=2e^{-2}$. Similarly, $\Pr(Y=2)=2e^{-2}$. The probability that $Y=3$ is calculated a little differently. For $Y=3$ if $3$ or more tankers show up. (Then $3$ are serviced, and the rest sent away.) Thus $\Pr(Y=3)=1-(e^{-2}+2e^{-2}+2e^{-2})=1-5e^{-2}$. It follows that $$E(Y)=(0)(e^{-2})+(1)(2e^{-2})+(2)(2e^{-2})+(3)(1-5e^{-2}).$$ This simplifies to $3-9e^{-2}$. Numerically, it is about $1.782$.

André Nicolas
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  • Thank you so much for the answer André!

    I still have a few problems with it though :(

    when I try to calcuate: $$1-e^{-2}\left(1+\frac{2}{1!}+\frac{2^2}{2!}+\frac{2^3}{3!}\right).$$

    I get -32.251

    which doesn't really make sense?

    I think I got question 2 under control when I know how to answer question 1. thanks!

    #Q3, yes it μ, not u, just didn't know where to find the symbol. Thanks!

    any chance you could elaborate on Question 4. Still don't quite understand that method. How do I calculate wether k is equal smaller or larger than 2?

    – Mikkel Oct 09 '13 at 23:32
  • On evaluating the displayed expression, it is calculator work. The thing inside the brackets is about $6.33333333$. Multiply by $e^{-2}$, which is about $0.1353353$. On Q4, just calculate $\Pr(X=0)$, $\Pr(X=1)$, $\Pr(X=2)$, $\Pr(X=3)$. I will add a line for the general ratio argument. – André Nicolas Oct 09 '13 at 23:44
  • Thanks again André :)

    when I calculate the thing inside the brackets I get 6.33333 as well.

    However when I multiply that by e^-2 I get 0.8683 (0.14285 if I minus with 1)

    not 0.135?

    e in this case is the base of the natural logarithm right? or is that where I am going completly wrong? (~2.7183)

    – Mikkel Oct 09 '13 at 23:56
  • I get $0.85712346$ for the product, so $0.14287654$ for the answer. Yes, $e$ is the base of natural logarithms. You can do the whole computation on the calculator, never writing down and rekeying an intermediate result. – André Nicolas Oct 10 '13 at 00:04
  • Thank you soo Much André!!!

    You're a lifesaver :)

    what is the "E(Y)" in question 5 though?

    – Mikkel Oct 10 '13 at 00:38
  • You are welcome. It can take a while until Poisson distribution calculations become routine. The question was a good one, with several interconnected themes. – André Nicolas Oct 10 '13 at 00:41
  • oh wait. I think I misunderstood Question 4 too :/

    How can there be a tie between K=1 and k=2?

    in this scenario is k no longer the maximum of tankers that can be served in a day?

    if it is. k would be 3?

    and k+1=4 which is larger than 2. and both of them can't be most probable?

    – Mikkel Oct 10 '13 at 00:50
  • The question Q4 asks about tankers arriving. The probability it is $k$ is $e^{-2}\frac{2^k}{k!}$. Calculate, simplifying aa bit: $\Pr(X=0)=e^{-2}$; $\Pr(X=1)=2e^{-2}$; $\Pr(X=2)=2e^{-2}$; $\Pr(X=3)=\frac{4}{3}e^{-2}$; $\Pr(X=4)=\frac{2}{3}e^{-2}$. Then the numbers go down fairly rapidly. There is no most probable, $X=1$ and $X=2$ are equally likely, and all the other probabilities are smaller. – André Nicolas Oct 10 '13 at 00:59
  • ahh alright, I understand question 4 completely now.

    But in relation to question 5 and 6

    I have figured out. P(Y=1)=P(X=1)= the answer... But could you show me an example of one of those calculations please :)

    That would really help me out understanding what is it that I have to do. For my assignment I just need to write the answers, but I would REALLY like to know how to calculate this or I am going to have issues when I get a similar problem at my exam. :/

    – Mikkel Oct 10 '13 at 13:49
  • Sorry, I do not understand what your previous comment asks for. It is clear that you want me to show a detailed calculation of something. A detailed calculation of what? – André Nicolas Oct 10 '13 at 15:23
  • IF you could show me how to do one of the calculations in question 5?

    I take it you have to test Y for 1, 2 or 3? which one has the highest percentage? and therefor is the expected number?

    I am completly lost on that one :(

    – Mikkel Oct 10 '13 at 18:43
  • thank you SO much! I missed the last part. thats why it didn't make sense to me :) and the answer to question 6 is 0.2181 correct? – Mikkel Oct 10 '13 at 20:10
  • It is $2$ minus the answer to Q5. If my calculator work was correct (no guarantees!) it is about $0.218$. – André Nicolas Oct 10 '13 at 20:13
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Firstly, the expression of the Poisson distribution is $$ P(X,u) = \frac{u^{X}\exp^{-u}}{{X!}} $$ where $X$ represents the number of ships arriving. (This is different to the equation you outlined in your question above) As for the questions 1 assuming that you used the right form of the equation then yes P(X>3) is correct.

2) what value of X do we require to have a probability $p$ i.e. p=0.05 or 0.01 hint:re-arrange the above equation?

3) This requires taking a look on http://en.wikipedia.org/wiki/Poisson_distribution

4) The most likely number is related to the maximum value of the distribution i.e. the peak location. Try a few numbers.

5) The expected number of ships served is given by $$ \sum_{X=0}^{X=3}X P(X,u) $$

6) Similarly as question 5 except that the number served,$X$, at the other refinery is less the 3 that are served at the initial one.

Chinny84
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