What is joint probability distribution
A joint probability distribution is a distribution of the probability of two or more events occurring simultaneously.
For example, the joint probability of two events X and Y is represented as P(X,Y) or P(X∩Y), and the joint probability of three events X, Y and Z is represented as P(X,Y,Z) or P(X∩Y∩Z).
When the random variables are discrete, the distribution is a discrete joint probability distribution; when they are continuous, the distribution is a continuous joint probability distribution.
Discrete joint probability distribution
Suppose that the blood types of a certain elementary school class have the following distribution:
X\Y |
Type A |
Type B |
Type O |
Type AB |
Boy |
0.25 |
0.10 |
0.10 |
0.05 |
Girl |
0.20 |
0.20 |
0.05 |
0.05 |
Considering event X as boy or girl and event Y as blood type, joint probability that event X is a girl and event Y is type O is 0.10.
Continuous joint probability distribution
The joint probability distribution of continuous random variables X and Y is expressed as follows:
P(a≤X≤b,c≤Y≤d)=∫ab∫cdf(x,y)dxdy
Since the sum of the probabilities is 1, the following equation holds
∫−∞∞∫−∞∞f(x,y)dxdy=1
As an example, consider the following probability density function:
f(x,y)={x+y0(0≤x≤1,0≤y≤1)(otherwise)
The probability P(0≤x≤21,0≤y≤21) with 0≤x≤21 and 0≤y≤21 can be obtained as follows.
P(0≤x≤21,0≤y≤21)=∫021∫021(x+y)dxdy=∫021[21x2+yx]021dy=∫021(81+21y)dy=[81y+41y2]021=81