independent Poisson processes probability












0












$begingroup$


I have been given this question to solve




The numbers of claims to an insurance company from smokers and nonsmokers follow independent Poisson processes. On average 4 claims from nonsmokers and 6 claims from smokers arrive every day independently of each
other.



Given that 8 claims arrived in a day, what is the probability that 5 of them
were from smokers?




so my attempt is:



$X_{t} :$ number of claims from non-smokers (with intensity $lambda = 4$)



$Y_{t} :$ number of claims from smokers (with intensity $alpha = 6$)



So from this I have



$Z_{t}:$ number of claims from smokers & non-smokers (with intensity $lambda+alpha = 10$)



So I have set the probability to be



$$frac{P(X_{1}=3)P(Y_{1}=5)}{P(Z_{1}= 8)}$$



I'm not sure if this is correct, I'm uncertain if I need to include $X_{t}$ in the equation.










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$endgroup$












  • $begingroup$
    This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
    $endgroup$
    – Tki Deneb
    Dec 18 '18 at 15:06


















0












$begingroup$


I have been given this question to solve




The numbers of claims to an insurance company from smokers and nonsmokers follow independent Poisson processes. On average 4 claims from nonsmokers and 6 claims from smokers arrive every day independently of each
other.



Given that 8 claims arrived in a day, what is the probability that 5 of them
were from smokers?




so my attempt is:



$X_{t} :$ number of claims from non-smokers (with intensity $lambda = 4$)



$Y_{t} :$ number of claims from smokers (with intensity $alpha = 6$)



So from this I have



$Z_{t}:$ number of claims from smokers & non-smokers (with intensity $lambda+alpha = 10$)



So I have set the probability to be



$$frac{P(X_{1}=3)P(Y_{1}=5)}{P(Z_{1}= 8)}$$



I'm not sure if this is correct, I'm uncertain if I need to include $X_{t}$ in the equation.










share|cite|improve this question











$endgroup$












  • $begingroup$
    This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
    $endgroup$
    – Tki Deneb
    Dec 18 '18 at 15:06
















0












0








0





$begingroup$


I have been given this question to solve




The numbers of claims to an insurance company from smokers and nonsmokers follow independent Poisson processes. On average 4 claims from nonsmokers and 6 claims from smokers arrive every day independently of each
other.



Given that 8 claims arrived in a day, what is the probability that 5 of them
were from smokers?




so my attempt is:



$X_{t} :$ number of claims from non-smokers (with intensity $lambda = 4$)



$Y_{t} :$ number of claims from smokers (with intensity $alpha = 6$)



So from this I have



$Z_{t}:$ number of claims from smokers & non-smokers (with intensity $lambda+alpha = 10$)



So I have set the probability to be



$$frac{P(X_{1}=3)P(Y_{1}=5)}{P(Z_{1}= 8)}$$



I'm not sure if this is correct, I'm uncertain if I need to include $X_{t}$ in the equation.










share|cite|improve this question











$endgroup$




I have been given this question to solve




The numbers of claims to an insurance company from smokers and nonsmokers follow independent Poisson processes. On average 4 claims from nonsmokers and 6 claims from smokers arrive every day independently of each
other.



Given that 8 claims arrived in a day, what is the probability that 5 of them
were from smokers?




so my attempt is:



$X_{t} :$ number of claims from non-smokers (with intensity $lambda = 4$)



$Y_{t} :$ number of claims from smokers (with intensity $alpha = 6$)



So from this I have



$Z_{t}:$ number of claims from smokers & non-smokers (with intensity $lambda+alpha = 10$)



So I have set the probability to be



$$frac{P(X_{1}=3)P(Y_{1}=5)}{P(Z_{1}= 8)}$$



I'm not sure if this is correct, I'm uncertain if I need to include $X_{t}$ in the equation.







probability stochastic-processes poisson-process






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edited Dec 18 '18 at 14:07







Rito Lowe

















asked Dec 18 '18 at 14:03









Rito LoweRito Lowe

465




465












  • $begingroup$
    This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
    $endgroup$
    – Tki Deneb
    Dec 18 '18 at 15:06




















  • $begingroup$
    This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
    $endgroup$
    – Tki Deneb
    Dec 18 '18 at 15:06


















$begingroup$
This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
$endgroup$
– Tki Deneb
Dec 18 '18 at 15:06






$begingroup$
This seems correct. You calculate $P(Y_1 = 5 | Z_1 = 8) = frac{P({Y_1 = 5}cap{X_1 + Y_1 = 8})}{P(Z_1 = 8)} = frac{P({Y_1 = 5}cap{X_1 = 3})}{P(Z_1 = 8)} = frac{P(Y_1 = 5)P(X_1= 3)}{P(Z_1 = 8)}$, so yes, you need to include $X_1$.
$endgroup$
– Tki Deneb
Dec 18 '18 at 15:06












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$begingroup$

$P(Y_1=5|Z_1=8)$



$ = frac{P(Y_1=5,; Z_1=8)}{P(Z_1=8)}$ (by Baye's rule)



$ = frac{P(Y_1=5, ; X_1=3)}{P(Z_1=8)}$ (since $Z_1=X_1+Y_1$)



$ = frac{P(Y_1=5)P(X_1=3)}{P(Z_1=8)}$ (since $X_1$ and $Y_1$ are independent)



Since $X_1,Y_1$, and $Z_1$ are all Poisson, you can easily plug in the standard formula in the above equation






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    $begingroup$

    $P(Y_1=5|Z_1=8)$



    $ = frac{P(Y_1=5,; Z_1=8)}{P(Z_1=8)}$ (by Baye's rule)



    $ = frac{P(Y_1=5, ; X_1=3)}{P(Z_1=8)}$ (since $Z_1=X_1+Y_1$)



    $ = frac{P(Y_1=5)P(X_1=3)}{P(Z_1=8)}$ (since $X_1$ and $Y_1$ are independent)



    Since $X_1,Y_1$, and $Z_1$ are all Poisson, you can easily plug in the standard formula in the above equation






    share|cite|improve this answer









    $endgroup$


















      0












      $begingroup$

      $P(Y_1=5|Z_1=8)$



      $ = frac{P(Y_1=5,; Z_1=8)}{P(Z_1=8)}$ (by Baye's rule)



      $ = frac{P(Y_1=5, ; X_1=3)}{P(Z_1=8)}$ (since $Z_1=X_1+Y_1$)



      $ = frac{P(Y_1=5)P(X_1=3)}{P(Z_1=8)}$ (since $X_1$ and $Y_1$ are independent)



      Since $X_1,Y_1$, and $Z_1$ are all Poisson, you can easily plug in the standard formula in the above equation






      share|cite|improve this answer









      $endgroup$
















        0












        0








        0





        $begingroup$

        $P(Y_1=5|Z_1=8)$



        $ = frac{P(Y_1=5,; Z_1=8)}{P(Z_1=8)}$ (by Baye's rule)



        $ = frac{P(Y_1=5, ; X_1=3)}{P(Z_1=8)}$ (since $Z_1=X_1+Y_1$)



        $ = frac{P(Y_1=5)P(X_1=3)}{P(Z_1=8)}$ (since $X_1$ and $Y_1$ are independent)



        Since $X_1,Y_1$, and $Z_1$ are all Poisson, you can easily plug in the standard formula in the above equation






        share|cite|improve this answer









        $endgroup$



        $P(Y_1=5|Z_1=8)$



        $ = frac{P(Y_1=5,; Z_1=8)}{P(Z_1=8)}$ (by Baye's rule)



        $ = frac{P(Y_1=5, ; X_1=3)}{P(Z_1=8)}$ (since $Z_1=X_1+Y_1$)



        $ = frac{P(Y_1=5)P(X_1=3)}{P(Z_1=8)}$ (since $X_1$ and $Y_1$ are independent)



        Since $X_1,Y_1$, and $Z_1$ are all Poisson, you can easily plug in the standard formula in the above equation







        share|cite|improve this answer












        share|cite|improve this answer



        share|cite|improve this answer










        answered Dec 18 '18 at 20:22









        Aditya DuaAditya Dua

        1,00418




        1,00418






























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