When you throw a dice, you don't know on which side it will fall. You've got "one chance in 6 to get a 2", "one chance in 6 to get a 1" or "3 chances in 6 to get an odd number".


Example for a random experiment is throwing a dice. We cannot foresee the result. Similarly , the weather forecast is a random experiment.   The different results of a random experiment are called elementary events. An event is a sum of elementary events. The universal set is the set of elementary events associated to a random experiment. We denote it by . Probability theory is very closely associated to set theory, then when you throw a dice, the results {1}, {2}, {3}, {4}, {5}, {6} are each one elementary events, is an event and the universal set is the set


If all results have the same chance to happen, the elementary events are equally likely outcomes. It's the case when you throw a dice. In that case, if A is an event, then the probability of the event A is a number between 0 and 1 which is:

For example if A is the event 'to get a number greater or equal to 3', then

The elementary events are not always equally likely. If today is a hot day, the probability that tomorrow will be hot is not same that the probability that it will rain tomorrow.