__Introduction :__Probability is a branch of mathematics which mainly means 'the calculation of probable chances.' For example, if you flip a coin, chances of getting heads or tails is equally 1/2. It means that, as there are two options for the flip, the chances of getting one of the two options is always 1/2. Similarly you have 1/6 chances of getting 1 on a die (same for all other numbers) and 1/52 chances of getting an Ace of Spades out of the 52 playing cards.

Sr. No. | Random Experiments | Sample Space | No. of sample points |

1 | A coin is tossed | S = {H,T} | n(S) = 2 |

2 | Two coins are tossed | S = {HH, HT, TH, TT} | n(S) = 4 |

3 | Three coins are tossed | S = {HHH, HHT, HTH, THH, HTT, THT, TTH, TTT | n(S) = 8 |

4 | A die is thrown | S = {1,2,3,4,5,6} | n(S) = 6 |

5 | A card is drawn from a pack containing 25 cards | S = {1,2,3, ... ,25} | n(S) = 25 |

__Types of Events :__

__Certain Event :__An event which contains all sample points of a sample space is called a certain event. e.g. A die is thrown. Let M be the event of getting a score less than 10 and so M = {1,2,3,4,5,6} and hence n(M) = 6.

__Impossible Event :__An event which does not contain any sample points of a sample space is called an impossible event. e.g. A die is thrown. Let A be the event of getting a score divisible by 7 and so S = {1,2,3,4,5,6} and A = {} and hence n(A) = 0.

__Elementary Event :__An event containing only one sample point of a sample space is called an elementary event. e.g. A die is thrown. Let A be the event of getting a score divisible by 5 and so S = {1,2,3,4,5,6} and A = {5} and hence n(A) = 1.

__Complementary Event :__If A is an event of a sample space S the the set of all outcomes which are in S but not in A is called the complement of event A and denoted by A'. A and A' are complementary events.

__Mutually Exclusive Events :__If A and B are two events of a sample space S and if they do not have any sample point is common, then they are called mutually exclusive events.

__Exhaustive Events :__If the union of two or more events is a sample space then those events are exhaustive events.

__Probability of an Event :__Denoted as P(A), the probability of an event is P(A) = n(A) / n(S)

__Properties of Probability :__

- Probability of an impossible event is zero and that of a certain event is 1.
- If S is the finite sample space and A is an event of S then 0 <= P(A) <= 1.
- If S is a finite sample space and A is an event of S then P(A') = 1 - P(A) where A' is the complement of event A.