Final Cover - For Printing

Eg. : In tossing a coin getting a head or getting a tail are mutually exclusive events,

because the occurance of head automatically prevents the occurance of tail.

10. Mutually independent events
    Two or more events are said to be mutually independent if the occurrence of one event
    does not prevent the occurrence of the other events in the same experiment.

Eg. : In tossing two coins, getting a head or tail in the first coin, and getting a head

or tail in the second coin are mutually independent events, because the occurance

of one event cannot prevent the occurance of the other.

The child must be facilitated to make a clear distinction between mutually exclusive

and mutually independent events.

11. Probability
    In a random experiment, the probability of occurrence of the event A, denoted by
    P(A) is defined as,

P (A) = n(S)^ mn^

n(A)

Number of exhaustive outcomes

Number of favourable outcomes for A = =

Note:

1. The probability of an event A lies between 0 and 1 i.e., 0 ≤ P(A) ≤ 1.


2. Number of outcomes which are not favorable to the event A = n-m. Probability of
   the non-occurrence of A denoted by A’ is given by

P(A’) = n−nm^ =^1 −^ mn

P(A’) = 1 - P(A)

Therefore, P(A) + P(A’) = 1

That is, the sum of the probability of the occurrence of an event and its non-occurrence

is equal to 1.