TutorNext tutor is online

Mutually Exclusive Events

Events are said to be mutually exclusive (incompatible or disjoint) if the happening of any one of them precludes the happening of all the others, i.e., if no two or more of them can happen simultaneously in the same trial.

Illustrative Examples

  • In throwing a die all the $6$ faces numbered $1$ to $6$ are mutually exclusive since if any one of these faces comes, the possibility of others, in the same trial, is ruled out.
  • Similarly in tossing a coin the events head and tail are mutually exclusive.
  • In throwing a die, let $A$ be the event of getting an odd number and $B$ be the event of getting an even number. Then,

$A = \1, 3, 5\$ and $B = \2, 4, 6\$.

Mutually Exclusive Events

The events $A$ and $B$ are mutually exclusive, since when we throw a die either an even number or an odd number shows up but not both.

Now,

Exhaustive number of cases $n(\Omega) = 6,$

Number of cases favourable to $A$ is $n(A) = 3,$

Number of cases favourable to $B$ is $n(B) = 3.$

$\therefore \quad$Probability of getting an odd number is

$P(A) = \fracn(A)n(\Omega) = \frac36 = \frac12.$

Probaility of getting an even number is

$P(B) = \fracn(B)n(\Omega) = \frac36 = \frac12.$

It is clear that

$A \cup B = \1, 2, 3, 4, 5, 6\ = \Omega,$ and

$P(A) + P(B) = \frac12 + \frac12 = 1 = P(\Omega) = P(A \cup B).$

  • In the random experiment of throwing two dice, let $X$ be the event of getting a sum of $8$ and $Y$ be the event of getting a sum of $6$. Then,

$X = \(2, 6), (3, 5), (4, 4), (5, 3), (6, 2)\,$

$Y = \(1, 5), (2, 4), (3, 3), (4, 2), (5, 1)\.$

Mutually Exclusive Events

Here, the events $X$ and $Y$ are mutually exclusive.

Now,

Exhaustive number of cases $n(\Omega) = 36,$

Number of favourable cases to $X$ is $n(X) = 5,$

Number of favourable cases to $Y$ is $n(Y) = 5.$

$\therefore \quad$Probability that the total of numbers on the two dice to be $8$ is

$P(X) = \fracn(X)n(\Omega) = \frac536.$

Probability that the total of numbers on the two dice to be $6$ is

$P(Y) = \fracn(Y)n(\Omega) = \frac536.$

Now, let us consider an event $Z$ of getting either $6$ or $9$ as the total of numbers on the two dice. Then

$Z = \(1, 5), (2, 4), (2, 6), (3, 3), (3, 5), (4, 2), (4, 4), (5, 1), (5, 3), (6, 2)\.$

Number of cases favourable to $Z$ is $n(Z) = 10.$

$\therefore \quad$Probability that the total of numbers on the two dices is either $6$ or $8$ is

$P(Z) = \fracn(C)n(\Omega) = \frac1036 = \frac518.$

It is clear that

$X \cup Y = Z$, and

$P(X) + P(Y) = \frac536 + \frac536 = \frac1036 = \frac518 = P(Z) = P(X \cup Y).$

From the above discussion it is clear that

For any two mutually exclusive events $A$ and $B$,

$P(A \cup B) = P(A) + P(B).$

Similarly, if $E_1$, $E_2$, $\ldots$, $E_n$ are $n$ mutually exclusive events, then

$P(E_1 \cup E_2 \cup \ldots \cup E_n) = P(E_1) + P(E_2) + \ldots + P(E_n).$

Alternately, we can write it as

$P(\bigcup_i = 1^n E_i) = \sum_i = 1^n P(E_i).$

Related Tags

probability Mutually Exclusive Events , what are Mutually Exclusive Events in probability concept