Answer :
Answer:
The joint probability distribution of X and Y is shown below.
Step-by-step explanation:
The distributions of X and of Y are described as follows:
X : 0 1
P (X) : 0.23 0.77
Y : 1 2 3
P (Y) : 0.40 0.22 0.38
It is provided that X and Y are independent.
That is:
P (X ∩ Y) = P (X) × P (Y)
Compute the joint probability distribution of X and Y as follows:
[tex]P(X=0,Y=1)=P(X=0)\times P(Y=1)=0.23\times 0.40=0.92\\\\P(X=0,Y=2)=P(X=0)\times P(Y=2)=0.23\times 0.22=0.0506\\\\P(X=0,Y=3)=P(X=0)\times P(Y=3)=0.23\times 0.38=0.0874\\\\P(X=1,Y=1)=P(X=1)\times P(Y=1)=0.77\times 0.40=0.308\\\\P(X=1,Y=2)=P(X=1)\times P(Y=2)=0.77\times 0.22=0.1694\\\\P(X=1,Y=3)=P(X=1)\times P(Y=3)=0.77\times 0.38=0.2926[/tex]
X 0 1
Y
1 0.9200 0.3080
2 0.0506 0.1694
3 0.0874 0.2926