The notion of **conditional probability** It is used in the field of **statistics** . The expression refers to the **existing probability of an event A happening, knowing that another event B also occurs** .

It is important to keep in mind that there is no need for a **temporal or causal relationship** between **TO** and **B** . This means that **TO** may occur before **B** after or at the same **weather** , and that **TO** it can be the origin or the consequence of **B** or not have a causality link.

Conditional probability is calculated from two **events** or events (**TO** and **B** ) in a probabilistic space, indicating the probability of its occurrence **TO** since it has happened **B** . Is written **P (A / B)** , reading as **"Probability of A given B"** .

Let's see a **example** . In a group of **100 students** , **35** young boys **they play soccer and basketball** , while **80** of the members practice **soccer** . What is the probability that one of the students who plays at **soccer** , also play **basketball** or **basketball** ?

As you can see, in this case we know two facts: the students who play **soccer** and at **basketball** (**35** ) and the students who play **soccer** (**80** ).

*Event A:* For a student to play basketball (*x*)*Event B:* For a student to play football (*80*)*Event A and B:* For a student to play football and basketball (*35*)

*P (A / B) = P (A∩B) / P (B)P (A / B) = 35/80P (A / B) = 0.4375P (A / B) = 43.75%*

Therefore, this **conditional probability** indicates that the probability of a student playing at **basketball** since he also plays football is **43,75%** .