Answer:
(a) The joint PMF of W, L and T is:
![P(W,\ L,\ T)={5\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [0.60]^{n_{W}}\times [0.30]^{n_{L}}\times [0.10]^{n_{T}}](https://tex.z-dn.net/?f=P%28W%2C%5C%20L%2C%5C%20T%29%3D%7B5%5Cchoose%20%28n_%7BW%7D%21%5Ctimes%20n_%7BL%7D%21%5Ctimes%20n_%7BT%7D%21%29%7D%5Ctimes%20%5B0.60%5D%5E%7Bn_%7BW%7D%7D%5Ctimes%20%5B0.30%5D%5E%7Bn_%7BL%7D%7D%5Ctimes%20%5B0.10%5D%5E%7Bn_%7BT%7D%7D)
(b) The marginal PMF of W is:

Step-by-step explanation:
Let <em>X</em> = number of soccer games played.
The outcome of the random variable <em>X</em> are:
<em>W</em> = if a game won
<em>L</em> = if a game is lost
<em>T</em> = if there is a tie
The probability of winning a game is, P (<em>W</em>) = 0.60.
The probability of losing a game is, P (<em>L</em>) = 0.30.
The probability of a tie is, P (<em>T</em>) = 0.10.
The sum of the probabilities of the outcomes of <em>X</em> are:
P (W) + P (L) + P (T) = 0.60 + 0.30 + 0.10 = 1.00
Thus, the distribution of W, L and T is a appropriate probability distribution.
(a)
Now, the outcomes W, L and T are one experiment.
The distribution of <em>n</em> independent and repeated trials, each having a discrete number of outcomes, each outcome occurring with a distinct constant probability is known as a Multinomial distribution.
The outcomes of <em>X</em> follows a Multinomial distribution.
The joint probability mass function of <em>W</em>, <em>L</em> and <em>T</em> is:
![P(W,\ L,\ T)={n\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [P(W)]^{n_{W}}\times [P(L)]^{n_{L}}\times [P(T)]^{n_{T}}](https://tex.z-dn.net/?f=P%28W%2C%5C%20L%2C%5C%20T%29%3D%7Bn%5Cchoose%20%28n_%7BW%7D%21%5Ctimes%20n_%7BL%7D%21%5Ctimes%20n_%7BT%7D%21%29%7D%5Ctimes%20%5BP%28W%29%5D%5E%7Bn_%7BW%7D%7D%5Ctimes%20%5BP%28L%29%5D%5E%7Bn_%7BL%7D%7D%5Ctimes%20%5BP%28T%29%5D%5E%7Bn_%7BT%7D%7D)
The soccer tournament consists of <em>n</em> = 5 games.
Then the joint PMF of W, L and T is:
![P(W,\ L,\ T)={5\choose (n_{W}!\times n_{L}!\times n_{T}!)}\times [0.60]^{n_{W}}\times [0.30]^{n_{L}}\times [0.10]^{n_{T}}](https://tex.z-dn.net/?f=P%28W%2C%5C%20L%2C%5C%20T%29%3D%7B5%5Cchoose%20%28n_%7BW%7D%21%5Ctimes%20n_%7BL%7D%21%5Ctimes%20n_%7BT%7D%21%29%7D%5Ctimes%20%5B0.60%5D%5E%7Bn_%7BW%7D%7D%5Ctimes%20%5B0.30%5D%5E%7Bn_%7BL%7D%7D%5Ctimes%20%5B0.10%5D%5E%7Bn_%7BT%7D%7D)
(b)
The random variable <em>W</em> is defined as the number games won in the soccer tournament.
The probability of winning a game is, P (W) = <em>p</em> = 0.60.
Total number of games in the tournament is, <em>n</em> = 5.
A game is won independently of the others.
The random variable <em>W</em> follows a Binomial distribution.
The probability mass function of <em>W</em> is:

Thus, the marginal PMF of W is:
