Sometimes you have more information than simply total outcomes and favorable outcomes; hence, you are able to make more informed judgments regarding probabilities. For example, suppose you know the following information: In a particular village, there are 60 women and 40 men. Twenty of those women are 70 years of age or older; five of the men are 70 years of age or older (see Table 1).
|
70 or older |
69 or younger |
Totals | |
|---|---|---|---|
|
Women |
20 |
40 |
60 |
|
Men |
5 |
35 |
40 |
|
Total |
25 |
75 |
100 |
What is the probability that a person selected at random in that town will be a woman? Because women constitute 60 percent of the total population, the probability is 0.60.
What is the probability that a person 70 years of age or older, selected at random, will be a woman? This question is different because the probability of
A (being a woman) given
B (the person in question being 70 years of age or older) is now conditional upon
B (being 70 years of age or older). Because women number 20 out of the 25 people in the 70-or-older group, the probability of this latter question is
, or 0.80.
Conditional probability is found using this formula:

which is read: The probability of A given B equals the probability of A and B divided by the probability of B. The vertical bar in the expression A|B is read given that or given.

Introduction to Statistics
Probability
