problem3.5.3

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Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers Roy D. Yates and David J. Goodman Problem Solution : Yates and Goodman,3.5.3 Problem 3.5.3 First we observe that for n 12 , the marginal PMF of N satisfies P N n n k 1 P NK nk 1 p n 1 p n k 1 1 n 1 p n 1 p Thus, the event B has probability PB n 10 P N n 1 p 9 p 1 1 p 1 p 2 1 p 9 From Theorem 3.11, P NKB nk P NK nk PB nk B 0 otherwise 1 p n 10 pn n 10 11 ; k 1 n 0 otherwise The conditional PMF P NB nb could be found directly from P N n using Theorem 2.19. However, we can also find it just by summing the conditional joint PMF. P NB n n k 1 P NKB nk 1 p n 10 p n 10 11 0 otherwise From the conditional PMF P NB n , we can calculate directly the conditional moments of N given B. Instead, however, we observe that given B, N N 9 has a geometric PMF with mean 1 p. That is, for n 12 , P NB n PN n 9 B P NB n 9 1 p n 1 p Hence, given B, N N 9 and we can calculate the conditional expectations ENB E N 9 B E NB 9 1 p 9 Var NB Var N 9 B Var NB 1 p p 2 Note that further along in the problem we will need E N 2 B which we now calculate. E N 2 B Var NB ENB 2 2 p 2 17 p 81 1

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  • Probability and Stochastic Processes:A Friendly Introduction for Electrical and Computer Engineers

    Roy D. Yates and David J. GoodmanProblem Solution : Yates and Goodman,3.5.3

    Problem 3.5.3First we observe that for n 1 2 , the marginal PMF of N satisfies

    PN

    n n

    k 1

    PN K

    n k

    1 p n 1 pn

    k 1

    1n

    1 p n 1 p

    Thus, the event B has probability

    P B

    n 10

    PN

    n

    1 p 9 p 1

    1 p

    1 p 2

    1 p 9

    From Theorem 3.11,

    PN K B

    n k PN K n k

    P B n k B0 otherwise

    1 p n 10 p n n 10 11 ;k 1 n0 otherwise

    The conditional PMF PN B

    n b could be found directly from PN

    n using Theorem 2.19. However,we can also find it just by summing the conditional joint PMF.

    PN B

    n n

    k 1

    PN K B

    n k

    1 p n 10 p n 10 11 0 otherwise

    From the conditional PMF PN B

    n , we can calculate directly the conditional moments of N given B.Instead, however, we observe that given B, N N 9 has a geometric PMF with mean 1 p. Thatis, for n 1 2 ,

    PN B

    n P N n 9 B PN B

    n 9

    1 p n 1 p

    Hence, given B, N N 9 and we can calculate the conditional expectations

    E N B E N 9 B E N B 9 1 p 9Var N B Var N 9 B Var N B

    1 p p2

    Note that further along in the problem we will need E N2 B which we now calculate.

    E N2 B Var N B

    E N B 2

    2p2

    17p

    81

    1

  • For the conditional moments of K, we work directly with the conditional PMF PN K B

    n k .

    E K B

    n 10

    n

    k 1

    k

    1 p n 10 pn

    n 10

    1 p n 10 pn

    n

    k 1

    k

    Since nk 1 k n

    n 1 2,

    E K B

    n 1

    n 12

    1 p n 1 p 12

    E N 1 B 1

    2p 5

    We now can calculate the conditional expectation of the sum.

    E N K B E N B! E K B 1 p 9 1

    2p " 5 32p 14

    The conditional second moment of K is

    E K2 B

    n 10

    n

    k 1

    k2

    1 p n 10 pn

    n 10

    1 p n 10 pn

    n

    k 1

    k2

    Using the identity nk 1 k2 n

    n 1

    2n 1 6, we obtain

    E K2 B

    n 10

    n 1

    2n 1 6

    1 p n 10 p 16E

    N 1

    2N 1 # B

    Applying the values of E N B and E N2 B found above, we find that

    E K2 B E N2 B

    3 E N B

    2

    16

    23p2

    376p 31

    23

    Thus, we can calculate the conditional variance of K.

    Var K B E K2 B

    E K B 2 5

    12p2

    76p 6

    23

    To find the conditional correlation of N and K,

    E NK B

    n 10

    n

    k 1

    nk

    1 p n 10 pn

    n 10

    1 p n 1 pn

    k 1

    k

    Since nk 1 k n

    n 1 2,

    E NK B

    n 10

    n

    n 1 2

    1 p n 10 p 12

    E N

    N 1 # B 1p2

    9p

    45

    2