# Probability

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".

## Vocabulary

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 ## Formula

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.