Probability dice don't match and expected difference












1














The four musketeers decide to send a bouquet of roses to Snow White for
her Birthday. They toss a die each and contribute as many roses to the
bouquet as their die shows.



(i) What is the probability that at least two out of the four musketeers will
contribute different numbers of flowers?



For this part I assumed the probability of two number of flowers not matching is



$$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$



For the first roll some number will be rolled so probability
is 1. For the second roll theres a 1/6 chance the roll will match the first so a 5/6 chance is won't match. For the third there's a 4/6 chance it won't match the 1st or 2nd roll and then with the 4th roll there's a 3/6 chance it will match one of the others.
Similarly for the probability that 3 and 4 choose different numbers of flowers I get



$$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$
and



$$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$I think this isn't right. Do i instead need to work with 1 - probability of same number.



(ii) Let X be a random variable representing the maximal out of the four
contributions, and let Y stands for the minimal one. Calculate the value
of joint probability, PXY (3, 2), that X = 3 AND Y = 2.



For the number of possibilities that satisify this we are selecting 4 outcomes (4 dice rolls) and there are 2 possibilities for each outcome, either a 2 or a 3, so there would be 24 possibilities and a sample space of 64 so the probability is 24/64?



(iii) Calculate the expected difference between the maximal and the minimal contributions, E(X − Y ).



I'm not too sure about this one, but would it be, the probability of having a minimum of 2 would be 54/64 and the probability of the maximum being 3 is 34/64 so would he expected difference be



$$(2)(5^4/6^4)-(3)(3^4/6^4)$$










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    1














    The four musketeers decide to send a bouquet of roses to Snow White for
    her Birthday. They toss a die each and contribute as many roses to the
    bouquet as their die shows.



    (i) What is the probability that at least two out of the four musketeers will
    contribute different numbers of flowers?



    For this part I assumed the probability of two number of flowers not matching is



    $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$



    For the first roll some number will be rolled so probability
    is 1. For the second roll theres a 1/6 chance the roll will match the first so a 5/6 chance is won't match. For the third there's a 4/6 chance it won't match the 1st or 2nd roll and then with the 4th roll there's a 3/6 chance it will match one of the others.
    Similarly for the probability that 3 and 4 choose different numbers of flowers I get



    $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$
    and



    $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$I think this isn't right. Do i instead need to work with 1 - probability of same number.



    (ii) Let X be a random variable representing the maximal out of the four
    contributions, and let Y stands for the minimal one. Calculate the value
    of joint probability, PXY (3, 2), that X = 3 AND Y = 2.



    For the number of possibilities that satisify this we are selecting 4 outcomes (4 dice rolls) and there are 2 possibilities for each outcome, either a 2 or a 3, so there would be 24 possibilities and a sample space of 64 so the probability is 24/64?



    (iii) Calculate the expected difference between the maximal and the minimal contributions, E(X − Y ).



    I'm not too sure about this one, but would it be, the probability of having a minimum of 2 would be 54/64 and the probability of the maximum being 3 is 34/64 so would he expected difference be



    $$(2)(5^4/6^4)-(3)(3^4/6^4)$$










    share|cite|improve this question







    New contributor




    Richard Cameron is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.























      1












      1








      1







      The four musketeers decide to send a bouquet of roses to Snow White for
      her Birthday. They toss a die each and contribute as many roses to the
      bouquet as their die shows.



      (i) What is the probability that at least two out of the four musketeers will
      contribute different numbers of flowers?



      For this part I assumed the probability of two number of flowers not matching is



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$



      For the first roll some number will be rolled so probability
      is 1. For the second roll theres a 1/6 chance the roll will match the first so a 5/6 chance is won't match. For the third there's a 4/6 chance it won't match the 1st or 2nd roll and then with the 4th roll there's a 3/6 chance it will match one of the others.
      Similarly for the probability that 3 and 4 choose different numbers of flowers I get



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$
      and



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$I think this isn't right. Do i instead need to work with 1 - probability of same number.



      (ii) Let X be a random variable representing the maximal out of the four
      contributions, and let Y stands for the minimal one. Calculate the value
      of joint probability, PXY (3, 2), that X = 3 AND Y = 2.



      For the number of possibilities that satisify this we are selecting 4 outcomes (4 dice rolls) and there are 2 possibilities for each outcome, either a 2 or a 3, so there would be 24 possibilities and a sample space of 64 so the probability is 24/64?



      (iii) Calculate the expected difference between the maximal and the minimal contributions, E(X − Y ).



      I'm not too sure about this one, but would it be, the probability of having a minimum of 2 would be 54/64 and the probability of the maximum being 3 is 34/64 so would he expected difference be



      $$(2)(5^4/6^4)-(3)(3^4/6^4)$$










      share|cite|improve this question







      New contributor




      Richard Cameron is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      The four musketeers decide to send a bouquet of roses to Snow White for
      her Birthday. They toss a die each and contribute as many roses to the
      bouquet as their die shows.



      (i) What is the probability that at least two out of the four musketeers will
      contribute different numbers of flowers?



      For this part I assumed the probability of two number of flowers not matching is



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$



      For the first roll some number will be rolled so probability
      is 1. For the second roll theres a 1/6 chance the roll will match the first so a 5/6 chance is won't match. For the third there's a 4/6 chance it won't match the 1st or 2nd roll and then with the 4th roll there's a 3/6 chance it will match one of the others.
      Similarly for the probability that 3 and 4 choose different numbers of flowers I get



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$
      and



      $$frac{6}{6}times frac{5}{6}timesfrac{4}{6}timesfrac{3}{6}$$I think this isn't right. Do i instead need to work with 1 - probability of same number.



      (ii) Let X be a random variable representing the maximal out of the four
      contributions, and let Y stands for the minimal one. Calculate the value
      of joint probability, PXY (3, 2), that X = 3 AND Y = 2.



      For the number of possibilities that satisify this we are selecting 4 outcomes (4 dice rolls) and there are 2 possibilities for each outcome, either a 2 or a 3, so there would be 24 possibilities and a sample space of 64 so the probability is 24/64?



      (iii) Calculate the expected difference between the maximal and the minimal contributions, E(X − Y ).



      I'm not too sure about this one, but would it be, the probability of having a minimum of 2 would be 54/64 and the probability of the maximum being 3 is 34/64 so would he expected difference be



      $$(2)(5^4/6^4)-(3)(3^4/6^4)$$







      probability






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      Richard Cameron is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      share|cite|improve this question







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      asked Jan 3 at 22:40









      Richard Cameron

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      11




      New contributor




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      New contributor





      Richard Cameron is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






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      Check out our Code of Conduct.






















          3 Answers
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          0














          In part (ii), you also need to be sure that not all the rolls are all $2$ or $3$. As such, your answer should be



          $$
          (2/6)^4 - (1/6)^4 - (1/6)^4
          $$



          Since there is a $(1/6)^4$ chance of getting all 2, which is equal to chance of getting all 3.



          This can also be done by multinational experiment.



          $$
          sum_{n=1}^3 frac{4!}{n!(4-n)!}(1/6)^4
          $$



          In part (iii), the dice rolls is uniform with a pmf of $1/6$ for $i = 1,2,...,6$. As such, the cdf is



          $$
          F(y) = y/6
          $$



          Notice that $P(Y_{max} < y)$ occurs only if all other rolls are less than $y$ also. Therefore



          $$
          P(Y_{max} leq y) = F(y)^4 = (y/6)^4
          $$



          As such, using $G(y)$ and $H(y)$ to simplify notation, we have



          $$
          G(y) = P(Y_{max} = y) = P(Y_{max} leq y) - P(Y_{max} leq (y-1)) = (y/6)^4 - ((y-1)/6)^4
          $$



          Similarly, since $P(Y_{min} geq y) = 1-(1-F(y))^4$, we have



          $$
          H(y) = P(Y_{min} = y) = P(Y_{min} leq y) - P(Y_{min} leq (y-1)) = ((7-y)/6)^4 - ((6-y)/6)^4
          $$



          Therefore, summing all possible values of y (1 through 6).



          $$E(X-Y) = E(X) - E(Y) = sum yG(y) - sum yH(y) \= 5.24459876543 - 1.75540123457 = 3.48919753086
          $$






          share|cite|improve this answer























          • $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
            – herb steinberg
            2 days ago



















          0














          Hint on (iii).



          By linearity of expectation: $mathbb E(X-Y)=mathbb EX-mathbb EY$.



          What follows makes it more easy to find $mathbb EX$ and $mathbb EY$.





          If $Z$ takes values in ${1,2,3,4,5,6}$ then: $$mathbb EZ=sum_{k=1}^6kP(Z=k)=sum_{k=1}^6sum_{r=1}^kP(Z=k)=sum_{r=1}^6sum_{k=r}^6P(Z=k)=sum_{r=1}^6P(Zgeq r)$$



          Applying this on $X$ we find:$$mathbb EX=sum_{r=1}^6P(Xgeq r)=sum_{r=1}^6left(1-P(X<r)right)=6-sum_{r=1}^6P(X<r)$$where $P(X<r)$ is quite easy to find.



          Also you apply this on $Y$ where $P(Ygeq r)$ is quite easy to find.






          share|cite|improve this answer





























            0














            For (i) You started out with the right approach, but the wrong question, although your last remark is correct. The opposite possibility is that all four have the same number which is $P=(frac{1}{6})^3$, so the probability you want is $1-(frac{1}{6})^3=0.99537037037037$



            For (ii) You need to subtract the probabilities of all 3 or all 2 which $frac{2}{6^4}$.






            share|cite|improve this answer























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              3 Answers
              3






              active

              oldest

              votes








              3 Answers
              3






              active

              oldest

              votes









              active

              oldest

              votes






              active

              oldest

              votes









              0














              In part (ii), you also need to be sure that not all the rolls are all $2$ or $3$. As such, your answer should be



              $$
              (2/6)^4 - (1/6)^4 - (1/6)^4
              $$



              Since there is a $(1/6)^4$ chance of getting all 2, which is equal to chance of getting all 3.



              This can also be done by multinational experiment.



              $$
              sum_{n=1}^3 frac{4!}{n!(4-n)!}(1/6)^4
              $$



              In part (iii), the dice rolls is uniform with a pmf of $1/6$ for $i = 1,2,...,6$. As such, the cdf is



              $$
              F(y) = y/6
              $$



              Notice that $P(Y_{max} < y)$ occurs only if all other rolls are less than $y$ also. Therefore



              $$
              P(Y_{max} leq y) = F(y)^4 = (y/6)^4
              $$



              As such, using $G(y)$ and $H(y)$ to simplify notation, we have



              $$
              G(y) = P(Y_{max} = y) = P(Y_{max} leq y) - P(Y_{max} leq (y-1)) = (y/6)^4 - ((y-1)/6)^4
              $$



              Similarly, since $P(Y_{min} geq y) = 1-(1-F(y))^4$, we have



              $$
              H(y) = P(Y_{min} = y) = P(Y_{min} leq y) - P(Y_{min} leq (y-1)) = ((7-y)/6)^4 - ((6-y)/6)^4
              $$



              Therefore, summing all possible values of y (1 through 6).



              $$E(X-Y) = E(X) - E(Y) = sum yG(y) - sum yH(y) \= 5.24459876543 - 1.75540123457 = 3.48919753086
              $$






              share|cite|improve this answer























              • $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
                – herb steinberg
                2 days ago
















              0














              In part (ii), you also need to be sure that not all the rolls are all $2$ or $3$. As such, your answer should be



              $$
              (2/6)^4 - (1/6)^4 - (1/6)^4
              $$



              Since there is a $(1/6)^4$ chance of getting all 2, which is equal to chance of getting all 3.



              This can also be done by multinational experiment.



              $$
              sum_{n=1}^3 frac{4!}{n!(4-n)!}(1/6)^4
              $$



              In part (iii), the dice rolls is uniform with a pmf of $1/6$ for $i = 1,2,...,6$. As such, the cdf is



              $$
              F(y) = y/6
              $$



              Notice that $P(Y_{max} < y)$ occurs only if all other rolls are less than $y$ also. Therefore



              $$
              P(Y_{max} leq y) = F(y)^4 = (y/6)^4
              $$



              As such, using $G(y)$ and $H(y)$ to simplify notation, we have



              $$
              G(y) = P(Y_{max} = y) = P(Y_{max} leq y) - P(Y_{max} leq (y-1)) = (y/6)^4 - ((y-1)/6)^4
              $$



              Similarly, since $P(Y_{min} geq y) = 1-(1-F(y))^4$, we have



              $$
              H(y) = P(Y_{min} = y) = P(Y_{min} leq y) - P(Y_{min} leq (y-1)) = ((7-y)/6)^4 - ((6-y)/6)^4
              $$



              Therefore, summing all possible values of y (1 through 6).



              $$E(X-Y) = E(X) - E(Y) = sum yG(y) - sum yH(y) \= 5.24459876543 - 1.75540123457 = 3.48919753086
              $$






              share|cite|improve this answer























              • $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
                – herb steinberg
                2 days ago














              0












              0








              0






              In part (ii), you also need to be sure that not all the rolls are all $2$ or $3$. As such, your answer should be



              $$
              (2/6)^4 - (1/6)^4 - (1/6)^4
              $$



              Since there is a $(1/6)^4$ chance of getting all 2, which is equal to chance of getting all 3.



              This can also be done by multinational experiment.



              $$
              sum_{n=1}^3 frac{4!}{n!(4-n)!}(1/6)^4
              $$



              In part (iii), the dice rolls is uniform with a pmf of $1/6$ for $i = 1,2,...,6$. As such, the cdf is



              $$
              F(y) = y/6
              $$



              Notice that $P(Y_{max} < y)$ occurs only if all other rolls are less than $y$ also. Therefore



              $$
              P(Y_{max} leq y) = F(y)^4 = (y/6)^4
              $$



              As such, using $G(y)$ and $H(y)$ to simplify notation, we have



              $$
              G(y) = P(Y_{max} = y) = P(Y_{max} leq y) - P(Y_{max} leq (y-1)) = (y/6)^4 - ((y-1)/6)^4
              $$



              Similarly, since $P(Y_{min} geq y) = 1-(1-F(y))^4$, we have



              $$
              H(y) = P(Y_{min} = y) = P(Y_{min} leq y) - P(Y_{min} leq (y-1)) = ((7-y)/6)^4 - ((6-y)/6)^4
              $$



              Therefore, summing all possible values of y (1 through 6).



              $$E(X-Y) = E(X) - E(Y) = sum yG(y) - sum yH(y) \= 5.24459876543 - 1.75540123457 = 3.48919753086
              $$






              share|cite|improve this answer














              In part (ii), you also need to be sure that not all the rolls are all $2$ or $3$. As such, your answer should be



              $$
              (2/6)^4 - (1/6)^4 - (1/6)^4
              $$



              Since there is a $(1/6)^4$ chance of getting all 2, which is equal to chance of getting all 3.



              This can also be done by multinational experiment.



              $$
              sum_{n=1}^3 frac{4!}{n!(4-n)!}(1/6)^4
              $$



              In part (iii), the dice rolls is uniform with a pmf of $1/6$ for $i = 1,2,...,6$. As such, the cdf is



              $$
              F(y) = y/6
              $$



              Notice that $P(Y_{max} < y)$ occurs only if all other rolls are less than $y$ also. Therefore



              $$
              P(Y_{max} leq y) = F(y)^4 = (y/6)^4
              $$



              As such, using $G(y)$ and $H(y)$ to simplify notation, we have



              $$
              G(y) = P(Y_{max} = y) = P(Y_{max} leq y) - P(Y_{max} leq (y-1)) = (y/6)^4 - ((y-1)/6)^4
              $$



              Similarly, since $P(Y_{min} geq y) = 1-(1-F(y))^4$, we have



              $$
              H(y) = P(Y_{min} = y) = P(Y_{min} leq y) - P(Y_{min} leq (y-1)) = ((7-y)/6)^4 - ((6-y)/6)^4
              $$



              Therefore, summing all possible values of y (1 through 6).



              $$E(X-Y) = E(X) - E(Y) = sum yG(y) - sum yH(y) \= 5.24459876543 - 1.75540123457 = 3.48919753086
              $$







              share|cite|improve this answer














              share|cite|improve this answer



              share|cite|improve this answer








              edited Jan 3 at 23:33

























              answered Jan 3 at 23:04









              Bryden C

              30418




              30418












              • $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
                – herb steinberg
                2 days ago


















              • $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
                – herb steinberg
                2 days ago
















              $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
              – herb steinberg
              2 days ago




              $G(y)$ and $H(y)$ are as defined independently. However don't you need to take into account min $le$ max?
              – herb steinberg
              2 days ago











              0














              Hint on (iii).



              By linearity of expectation: $mathbb E(X-Y)=mathbb EX-mathbb EY$.



              What follows makes it more easy to find $mathbb EX$ and $mathbb EY$.





              If $Z$ takes values in ${1,2,3,4,5,6}$ then: $$mathbb EZ=sum_{k=1}^6kP(Z=k)=sum_{k=1}^6sum_{r=1}^kP(Z=k)=sum_{r=1}^6sum_{k=r}^6P(Z=k)=sum_{r=1}^6P(Zgeq r)$$



              Applying this on $X$ we find:$$mathbb EX=sum_{r=1}^6P(Xgeq r)=sum_{r=1}^6left(1-P(X<r)right)=6-sum_{r=1}^6P(X<r)$$where $P(X<r)$ is quite easy to find.



              Also you apply this on $Y$ where $P(Ygeq r)$ is quite easy to find.






              share|cite|improve this answer


























                0














                Hint on (iii).



                By linearity of expectation: $mathbb E(X-Y)=mathbb EX-mathbb EY$.



                What follows makes it more easy to find $mathbb EX$ and $mathbb EY$.





                If $Z$ takes values in ${1,2,3,4,5,6}$ then: $$mathbb EZ=sum_{k=1}^6kP(Z=k)=sum_{k=1}^6sum_{r=1}^kP(Z=k)=sum_{r=1}^6sum_{k=r}^6P(Z=k)=sum_{r=1}^6P(Zgeq r)$$



                Applying this on $X$ we find:$$mathbb EX=sum_{r=1}^6P(Xgeq r)=sum_{r=1}^6left(1-P(X<r)right)=6-sum_{r=1}^6P(X<r)$$where $P(X<r)$ is quite easy to find.



                Also you apply this on $Y$ where $P(Ygeq r)$ is quite easy to find.






                share|cite|improve this answer
























                  0












                  0








                  0






                  Hint on (iii).



                  By linearity of expectation: $mathbb E(X-Y)=mathbb EX-mathbb EY$.



                  What follows makes it more easy to find $mathbb EX$ and $mathbb EY$.





                  If $Z$ takes values in ${1,2,3,4,5,6}$ then: $$mathbb EZ=sum_{k=1}^6kP(Z=k)=sum_{k=1}^6sum_{r=1}^kP(Z=k)=sum_{r=1}^6sum_{k=r}^6P(Z=k)=sum_{r=1}^6P(Zgeq r)$$



                  Applying this on $X$ we find:$$mathbb EX=sum_{r=1}^6P(Xgeq r)=sum_{r=1}^6left(1-P(X<r)right)=6-sum_{r=1}^6P(X<r)$$where $P(X<r)$ is quite easy to find.



                  Also you apply this on $Y$ where $P(Ygeq r)$ is quite easy to find.






                  share|cite|improve this answer












                  Hint on (iii).



                  By linearity of expectation: $mathbb E(X-Y)=mathbb EX-mathbb EY$.



                  What follows makes it more easy to find $mathbb EX$ and $mathbb EY$.





                  If $Z$ takes values in ${1,2,3,4,5,6}$ then: $$mathbb EZ=sum_{k=1}^6kP(Z=k)=sum_{k=1}^6sum_{r=1}^kP(Z=k)=sum_{r=1}^6sum_{k=r}^6P(Z=k)=sum_{r=1}^6P(Zgeq r)$$



                  Applying this on $X$ we find:$$mathbb EX=sum_{r=1}^6P(Xgeq r)=sum_{r=1}^6left(1-P(X<r)right)=6-sum_{r=1}^6P(X<r)$$where $P(X<r)$ is quite easy to find.



                  Also you apply this on $Y$ where $P(Ygeq r)$ is quite easy to find.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered 2 days ago









                  drhab

                  98.3k544129




                  98.3k544129























                      0














                      For (i) You started out with the right approach, but the wrong question, although your last remark is correct. The opposite possibility is that all four have the same number which is $P=(frac{1}{6})^3$, so the probability you want is $1-(frac{1}{6})^3=0.99537037037037$



                      For (ii) You need to subtract the probabilities of all 3 or all 2 which $frac{2}{6^4}$.






                      share|cite|improve this answer




























                        0














                        For (i) You started out with the right approach, but the wrong question, although your last remark is correct. The opposite possibility is that all four have the same number which is $P=(frac{1}{6})^3$, so the probability you want is $1-(frac{1}{6})^3=0.99537037037037$



                        For (ii) You need to subtract the probabilities of all 3 or all 2 which $frac{2}{6^4}$.






                        share|cite|improve this answer


























                          0












                          0








                          0






                          For (i) You started out with the right approach, but the wrong question, although your last remark is correct. The opposite possibility is that all four have the same number which is $P=(frac{1}{6})^3$, so the probability you want is $1-(frac{1}{6})^3=0.99537037037037$



                          For (ii) You need to subtract the probabilities of all 3 or all 2 which $frac{2}{6^4}$.






                          share|cite|improve this answer














                          For (i) You started out with the right approach, but the wrong question, although your last remark is correct. The opposite possibility is that all four have the same number which is $P=(frac{1}{6})^3$, so the probability you want is $1-(frac{1}{6})^3=0.99537037037037$



                          For (ii) You need to subtract the probabilities of all 3 or all 2 which $frac{2}{6^4}$.







                          share|cite|improve this answer














                          share|cite|improve this answer



                          share|cite|improve this answer








                          edited 2 days ago

























                          answered Jan 3 at 23:02









                          herb steinberg

                          2,4932310




                          2,4932310






















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