Home page for accesible maths 8.1 Joint probability mass functions

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8.1.1 Properties of pX,Y⁢(x,y):

  1. 1.

    For all x and y, 0≤pX,Y⁢(x,y)≤1,

  2. 2.

    ∑all ⁢x,ypX,Y⁢(x,y)=1,

  3. 3.

    P((X,Y)∈A)=∑(x,y)∈ApX,Y(x,y).

Example 8.2.

The joint pmf of X and Y is

pX,Y⁢(x,y)=(x+y)/18

for x,y=0,1,2.

  1. a.

    Write out the joint probability table.

  2. b.

    Show this is a valid joint pmf.

  3. c.

    Evaluate (i) P(X=2), (ii) P(X=Y), (iii) P(X+Y≥2).

Solution.
  1. a.
    ypX,Y⁢(x,y)012001/182/18x11/182/183/1822/183/184/18
  2. b.

    pX,Y⁢(x,y)≥0 for all x,y, and ∑all ⁢(x,y)pX,Y⁢(x,y)=(0+1+2+1+2+3+2+3+4)/18=1.

  3. c.

    (i) P(X=2)=P((X,Y)∈{(2,0),(2,1),(2,2)})=2/18+3/18+4/18=9/18
    (ii) P(X=Y)=P((X,Y)∈{(0,0),(1,1),(2,2)})=0/18+2/18+4/18=6/18
    (iii) P(X+Y≥2)=P((X,Y)∈{(0,2),(1,1),(1,2),(2,0),(2,1),(2,2)})=(2+2+3+2+3+4)/18=16/18


Note that each of X and Y still have their own probability mass functions pX and pY. In the context of jointly distributed random variables, these are called the marginal probability mass functions.

pX(x)=P(X=x)=P((X,Y)∈{(x,0),(x,1),(x,2),…})=∑y=0∞pX,Y(x,y).

Similarly,

pY⁢(y)=∑x=0∞pX,Y⁢(x,y).

Exercise 8.3.

Bivariate random variables X and Y have joint pmf

y pX⁢(x)
0 1 2 3
x 1 5/60 8/60 2/60 1/60 16/60
2 12/60 7/60 3/60 2/60 24/60
3 4/60 8/60 6/60 2/60 20/60
pY⁢(y) 21/60 23/60 11/60 5/60 1

Fill in the marginal pmfs in the final row and column.