Introduction Of Probability Theory

Match the items on the right to the items on the left.

Let S be the sample space associated with a random experiment and A be an event. Then P (A) =

If A and B are any two events and

\bar{B}

is the complementary events of B , then

P (A \cap \bar{B})

If A and B are any two events, then

P (A \cup B)

The conditional probability of an event B, assuming that the event A has already happened,

P (B / A)

Two events A and B are said to be independent if and only if

P (A \cap B)

\frac{n (A)}{n (S)}

P (A) - P (A \cap B)

P (A) + P (B) - P (A \cup B)

\frac{P (A \cap B)}{P (A)}

provided

P (A) \neq 0

P (A) . P (B)