Probability is the measure of the likelihood that a particular event will occur. It is expressed as a number between 0 (impossible event) and 1 (certain event).
1. Experiment
An experiment is a process or activity that leads to one or more possible outcomes.
- Example:
Tossing a coin, rolling a die, or drawing a card from a deck.
2. Sample Space
The sample space is the set of all possible outcomes of an experiment.
- Example:
- For tossing a coin: S={Heads (H),Tails (T)}
- For rolling a die: S={1,2,3,4,5,6}
3. Event
An event is a subset of the sample space. It represents one or more outcomes of interest.
- Example:
- Rolling an even number on a die: E = {2,4,6}
- Getting a head in a coin toss: E = {H}
4. Mutually Exclusive Events
Two or more events are mutually exclusive if they cannot occur simultaneously.
- Example:
Rolling a die and getting a 2 or a 3. Both outcomes cannot happen at the same time.
5. Equally Likely Events
Events are equally likely if each has the same probability of occurring.
- Example:
In a fair coin toss, getting heads (P = 0.5) and getting tails (P = 0.5) are equally likely.
6. Exhaustive Events
A set of events is exhaustive if it includes all possible outcomes of the sample space.
- Example:
In rolling a die: {1,2,3,4,5,6} is an exhaustive set of events.
7. Sure Event
A sure event is an event that is certain to occur. The probability of a sure event is 1.
- Example:
Getting a number less than or equal to 6 when rolling a standard die: P(E)=1.
8. Null Event
A null event (or impossible event) is an event that cannot occur. Its probability is 0.
- Example:
Rolling a 7 on a standard die: P(E)=0.
9. Complementary Event
The complementary event of A, denoted as A^c, includes all outcomes in the sample space that are not in A.
- Example:
If is rolling an even number ({2,4,6}, then A^c is rolling an odd number ({1,3,5}.
10. Independent Events
Two events are independent if the occurrence of one event does not affect the occurrence of the other.
- Example:
Tossing two coins: The outcome of the first toss does not affect the outcome of the second toss.
One thought on “Probability: Definitions and examples, Experiment, Sample space, Event, mutually exclusive events, Equally likely events, Exhaustive events, Sure event, Null event, Complementary event and Independent events”