X and Y are discrete RVs
To find c:
We can tabulate the probabilities as follows:
f(x,y)= c(2x+y) ........ 0≤x≤2,0≤y≤3
=0
Since ∑$p_i$=1
∴42c=1
∴c=1/42
With this value the probability distribution is
∴The marginal probability distributions of X & Y are:
X |
P(X) |
0 |
6/42 |
1 |
14/42 |
2 |
22/42 |
Y |
P(Y) |
0 |
6/42 |
1 |
9/42 |
2 |
12/42 |
3 |
15/42 |
E(X)= $∑{p_i} {x_i}$
=0+1×14/42+2×22/42
E(X)=58/42=1.381
E(Y)=$∑{p_i}{ y_i}$
=0+1×9/42+2×12/42+3×15/42
E(Y)=78/42=1.857
E(XY)=$∑_{i=0}^2 $ $∑_{j=0}^3 {x_i} {y_j} . p(x=i,y=j)$
=0*0+1. $∑_{j=0}^3 {y_j} p(x=1,y=j)+2 . ∑_{j=0}^3 {y_j} p(x=2,y=j)$
=0+1(0×2/42+1×3/42+2×4/42+3×5/42)+2(0×4/42+1×5/42+2×6/42+3×7/42)
=26/42+76/42
E(XY)=102/42=2.429
E($X^2$ )=$∑{p_i} {x_i^2}$
=0+1×14/42+2^2×22/42
E($X^2$ )=102/42=2.429
E($Y^2$ )=$∑{p_i} {y_i^2}$
=0+1×9/42+$2^2$×12/42+$3^2$×15/42
E($Y^2$ )=192/42=4.571
Var(X)=E($X^2$ )-${E(X) }^2$
=2.429-${1.381}^2$
=2.429-1.9072
Var(X)=0.5218
Var(Y)=E($Y^2$ )-${E(Y) }^2$
=4.571-${1.857}^2$
=4.571-3.4484
Var(Y)=1.1226
cov(X,Y)=E(XY)-E(X)E(Y)
=2.429-1.381*1.857=2.429-2.565=-0.1355
Cov(XY)= -0.1355
$σ_x$=√(Var(X) )=√0.5218=0.7224
$σ_y$=√(Var(Y) )=√1.1226=1.06
$ρ_{xy}$=Cov(X,Y)/($σ_x$$ σ_y$ )=-0.1355/(0.7224*1.06)=0.177
$ρ_{xy}$=0.177