Conditional Probability Formula

Conditional probability formula tells the formula for the probability of the event when an event has already occurred. If the probability of events A and B are P(A) and P(B) respectively then the conditional probability of B such that A has already occurred is denoted as P(A/B).

If P(A) > 0, then the P(A/B) is calculated by using the formula,

P(A/B) = P(A ∩ B)/P(A)

In the case of P(A) = 0 means A is an impossible event, in this case, P(A/B) does not exist.

Dependent and Independent Events

Dependent and Independent Events are the types of events that occur in probability. Suppose we have two events say Event A and Event B then if Event A and Event B are dependent events then the occurrence of one event is dependent on the occurrence of other events if they are independent events then the occurrence of one event does not affect the probability of other events.

We can learn about dependent and independent events with the help of examples such as the event of tossing two coins simultaneously the outcome of one coin does not affect the outcome of another coin then they are independent events. Suppose we take other experiments where we toss a coin only when we get a six in the throw of dice, where the outcome of one event is affected by other events then they are dependent events.

In this article, we will learn about dependent events, independent events, their formulas, examples, and others in detail.

Table of Content

  • Dependent and Independent Events in Probability
  • Dependent Events
    • Examples of Dependent Events
  • Independent Events
    • Examples of Independent Events
  • Difference Between Independent Events and Dependent Events
    • Mutually Exclusive Events
  • Conditional Probability Formula

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