Poisson Process: a problem of customer arrival.

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There is a question that I am not sure about the answer.



Customers arrive according to a Poisson process of rate 30 per hour. Each customer is served
and leaves immediately upon arrival. There are two kinds of service, and a customer pays $5
for Service A or $15 for Service B. Customers independently select Service A with probability
1/
3
and Service B with probability 2/
3



  • a. During the period 9:30–10:30am, there were 32 customers in total.
    What is the probability that none of them arrived during
    10:25–10:30am?

Attempt a:
$P(N(60)-N(55)=0|N(60)=30)=fracP(N(60)-N(55)=0,N(60)=32)P(N(60)=32)=fracP(N(55)=32)P(N(5)=0)P(N(60)=32)$.



At this point, simply plug in the poisson process with $P(N(t)=n)=frac(lambda t)^nexp(-lambda t)n!$



  • b. What is the probability that the first two customers after 9:00am
    request Service B?

Attempt b: Treat this as two indep poisson process each has rate of $1/3 lambda$ and $2/3 lambda$. This is simply $(frac 1/3 lambda1/3lambda +2/3 lambda)^2$



  • c. Determine the expected amount paid by all customers during a 10 minute period.

Attempt c: $E[N(t)]=E[N_1(t)]+E[N_2(t)]=5*1/3lambda t+15*2/3lambda t=35/3 lambda t$. @10 min, we have $35/3*30/60*10=350/6$










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  • 2




    You should ask those as three separate questions.
    – 355durch113
    Apr 9 '16 at 7:29














up vote
4
down vote

favorite
3












There is a question that I am not sure about the answer.



Customers arrive according to a Poisson process of rate 30 per hour. Each customer is served
and leaves immediately upon arrival. There are two kinds of service, and a customer pays $5
for Service A or $15 for Service B. Customers independently select Service A with probability
1/
3
and Service B with probability 2/
3



  • a. During the period 9:30–10:30am, there were 32 customers in total.
    What is the probability that none of them arrived during
    10:25–10:30am?

Attempt a:
$P(N(60)-N(55)=0|N(60)=30)=fracP(N(60)-N(55)=0,N(60)=32)P(N(60)=32)=fracP(N(55)=32)P(N(5)=0)P(N(60)=32)$.



At this point, simply plug in the poisson process with $P(N(t)=n)=frac(lambda t)^nexp(-lambda t)n!$



  • b. What is the probability that the first two customers after 9:00am
    request Service B?

Attempt b: Treat this as two indep poisson process each has rate of $1/3 lambda$ and $2/3 lambda$. This is simply $(frac 1/3 lambda1/3lambda +2/3 lambda)^2$



  • c. Determine the expected amount paid by all customers during a 10 minute period.

Attempt c: $E[N(t)]=E[N_1(t)]+E[N_2(t)]=5*1/3lambda t+15*2/3lambda t=35/3 lambda t$. @10 min, we have $35/3*30/60*10=350/6$










share|cite|improve this question



















  • 2




    You should ask those as three separate questions.
    – 355durch113
    Apr 9 '16 at 7:29












up vote
4
down vote

favorite
3









up vote
4
down vote

favorite
3






3





There is a question that I am not sure about the answer.



Customers arrive according to a Poisson process of rate 30 per hour. Each customer is served
and leaves immediately upon arrival. There are two kinds of service, and a customer pays $5
for Service A or $15 for Service B. Customers independently select Service A with probability
1/
3
and Service B with probability 2/
3



  • a. During the period 9:30–10:30am, there were 32 customers in total.
    What is the probability that none of them arrived during
    10:25–10:30am?

Attempt a:
$P(N(60)-N(55)=0|N(60)=30)=fracP(N(60)-N(55)=0,N(60)=32)P(N(60)=32)=fracP(N(55)=32)P(N(5)=0)P(N(60)=32)$.



At this point, simply plug in the poisson process with $P(N(t)=n)=frac(lambda t)^nexp(-lambda t)n!$



  • b. What is the probability that the first two customers after 9:00am
    request Service B?

Attempt b: Treat this as two indep poisson process each has rate of $1/3 lambda$ and $2/3 lambda$. This is simply $(frac 1/3 lambda1/3lambda +2/3 lambda)^2$



  • c. Determine the expected amount paid by all customers during a 10 minute period.

Attempt c: $E[N(t)]=E[N_1(t)]+E[N_2(t)]=5*1/3lambda t+15*2/3lambda t=35/3 lambda t$. @10 min, we have $35/3*30/60*10=350/6$










share|cite|improve this question















There is a question that I am not sure about the answer.



Customers arrive according to a Poisson process of rate 30 per hour. Each customer is served
and leaves immediately upon arrival. There are two kinds of service, and a customer pays $5
for Service A or $15 for Service B. Customers independently select Service A with probability
1/
3
and Service B with probability 2/
3



  • a. During the period 9:30–10:30am, there were 32 customers in total.
    What is the probability that none of them arrived during
    10:25–10:30am?

Attempt a:
$P(N(60)-N(55)=0|N(60)=30)=fracP(N(60)-N(55)=0,N(60)=32)P(N(60)=32)=fracP(N(55)=32)P(N(5)=0)P(N(60)=32)$.



At this point, simply plug in the poisson process with $P(N(t)=n)=frac(lambda t)^nexp(-lambda t)n!$



  • b. What is the probability that the first two customers after 9:00am
    request Service B?

Attempt b: Treat this as two indep poisson process each has rate of $1/3 lambda$ and $2/3 lambda$. This is simply $(frac 1/3 lambda1/3lambda +2/3 lambda)^2$



  • c. Determine the expected amount paid by all customers during a 10 minute period.

Attempt c: $E[N(t)]=E[N_1(t)]+E[N_2(t)]=5*1/3lambda t+15*2/3lambda t=35/3 lambda t$. @10 min, we have $35/3*30/60*10=350/6$







probability probability-theory poisson-distribution poisson-process






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edited Apr 9 '16 at 7:20

























asked Apr 9 '16 at 7:14









randy

411211




411211







  • 2




    You should ask those as three separate questions.
    – 355durch113
    Apr 9 '16 at 7:29












  • 2




    You should ask those as three separate questions.
    – 355durch113
    Apr 9 '16 at 7:29







2




2




You should ask those as three separate questions.
– 355durch113
Apr 9 '16 at 7:29




You should ask those as three separate questions.
– 355durch113
Apr 9 '16 at 7:29










2 Answers
2






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The (a) part could be simply solved by binomial. Although, Poisson is still an option, it just gets a little messy.



Binomial will simply be: Binomial(20,1/12). Try to check by solving. The answer will be (11/12)^32






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    up vote
    1
    down vote













    a) Conditional on the number of arrivals in a given period, the arrivals are independently uniformly distributed over the period, so the probability that all of them arrived in $frac1112$ of the hour is



    $$left(frac1112right)^32approx6.2%;.$$



    This is also what your more involved approach yields upon simplification.



    b) This has nothing to do with the arrival times and thus with the Poisson process; each customer independently decides with probability $frac23$ to choose service $B$, so the probability that the first two customers choose service $B$ is $left(frac23right)^2=frac49$. This is also what your more involved approach would have yielded upon simplification, except you seem to have accidentally applied it to service $A$ instead of $B$.



    c) Your answer is correct.






    share|cite|improve this answer




















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      2 Answers
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      2 Answers
      2






      active

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      active

      oldest

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      active

      oldest

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      up vote
      1
      down vote













      The (a) part could be simply solved by binomial. Although, Poisson is still an option, it just gets a little messy.



      Binomial will simply be: Binomial(20,1/12). Try to check by solving. The answer will be (11/12)^32






      share|cite|improve this answer
























        up vote
        1
        down vote













        The (a) part could be simply solved by binomial. Although, Poisson is still an option, it just gets a little messy.



        Binomial will simply be: Binomial(20,1/12). Try to check by solving. The answer will be (11/12)^32






        share|cite|improve this answer






















          up vote
          1
          down vote










          up vote
          1
          down vote









          The (a) part could be simply solved by binomial. Although, Poisson is still an option, it just gets a little messy.



          Binomial will simply be: Binomial(20,1/12). Try to check by solving. The answer will be (11/12)^32






          share|cite|improve this answer












          The (a) part could be simply solved by binomial. Although, Poisson is still an option, it just gets a little messy.



          Binomial will simply be: Binomial(20,1/12). Try to check by solving. The answer will be (11/12)^32







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Sep 8 at 11:16









          user585380

          556




          556




















              up vote
              1
              down vote













              a) Conditional on the number of arrivals in a given period, the arrivals are independently uniformly distributed over the period, so the probability that all of them arrived in $frac1112$ of the hour is



              $$left(frac1112right)^32approx6.2%;.$$



              This is also what your more involved approach yields upon simplification.



              b) This has nothing to do with the arrival times and thus with the Poisson process; each customer independently decides with probability $frac23$ to choose service $B$, so the probability that the first two customers choose service $B$ is $left(frac23right)^2=frac49$. This is also what your more involved approach would have yielded upon simplification, except you seem to have accidentally applied it to service $A$ instead of $B$.



              c) Your answer is correct.






              share|cite|improve this answer
























                up vote
                1
                down vote













                a) Conditional on the number of arrivals in a given period, the arrivals are independently uniformly distributed over the period, so the probability that all of them arrived in $frac1112$ of the hour is



                $$left(frac1112right)^32approx6.2%;.$$



                This is also what your more involved approach yields upon simplification.



                b) This has nothing to do with the arrival times and thus with the Poisson process; each customer independently decides with probability $frac23$ to choose service $B$, so the probability that the first two customers choose service $B$ is $left(frac23right)^2=frac49$. This is also what your more involved approach would have yielded upon simplification, except you seem to have accidentally applied it to service $A$ instead of $B$.



                c) Your answer is correct.






                share|cite|improve this answer






















                  up vote
                  1
                  down vote










                  up vote
                  1
                  down vote









                  a) Conditional on the number of arrivals in a given period, the arrivals are independently uniformly distributed over the period, so the probability that all of them arrived in $frac1112$ of the hour is



                  $$left(frac1112right)^32approx6.2%;.$$



                  This is also what your more involved approach yields upon simplification.



                  b) This has nothing to do with the arrival times and thus with the Poisson process; each customer independently decides with probability $frac23$ to choose service $B$, so the probability that the first two customers choose service $B$ is $left(frac23right)^2=frac49$. This is also what your more involved approach would have yielded upon simplification, except you seem to have accidentally applied it to service $A$ instead of $B$.



                  c) Your answer is correct.






                  share|cite|improve this answer












                  a) Conditional on the number of arrivals in a given period, the arrivals are independently uniformly distributed over the period, so the probability that all of them arrived in $frac1112$ of the hour is



                  $$left(frac1112right)^32approx6.2%;.$$



                  This is also what your more involved approach yields upon simplification.



                  b) This has nothing to do with the arrival times and thus with the Poisson process; each customer independently decides with probability $frac23$ to choose service $B$, so the probability that the first two customers choose service $B$ is $left(frac23right)^2=frac49$. This is also what your more involved approach would have yielded upon simplification, except you seem to have accidentally applied it to service $A$ instead of $B$.



                  c) Your answer is correct.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered Sep 8 at 11:52









                  joriki

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