91Ó°ÊÓ

The counts of subjects under four different categories are tabulated.

The probability for a simple event is:

$P\left(E\right)=\frac{\text{Number}\text{of}\text{favorable}\text{outcomes}}{\text{Total}\text{number}\text{of}\text{outcomes}}$

The conditional probability of an event relative to another event that occurred in the past is expressed as$P\left(E\left|F\right.\right)$, where F is the event that is known to have occurred.

The formula for conditional probability is:

$P\left(E\left|F\right.\right)=\frac{P\left(EandF\right)}{P\left(F\right)}$

Add the rows and columns of the counts as shown in the table.

Define event Aas choosing a subject who developed flu and B as the event of choosing a subject who received the vaccine treatment.

The number of subjects who developed flu is 109.

The number of subjects who received the vaccine treatment is 1070.

The number of subjects recorded is 1602.

The probability that the subject had developed flu is:

$P\left(A\right)=\frac{109}{1602}$

The probability that the subject had received the vaccine treatment is:

$P\left(B\right)=\frac{1070}{1602}$

The probability that the subject had developed flu and received the vaccine treatment is

$P\left(A\text{and}B\right)=\frac{14}{1602}$

The probability of the randomly selected subject to have developed flu, given that the subject was given the vaccine treatment, is expressed as:

$$\begin{gathered} P\left(A\left|B\right.\right)=\frac{P\left(A\text{and}B\right)}{P\left(B\right)} \\ =\frac{\frac{14}{1602}}{\frac{1070}{1602}} \\ =0.0131 \end{gathered}$$

Thus, the probability of the randomly selected subject to have developed flu, given that the subject was given the vaccine treatment, is 0.0131.