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## Conditional Probability – Definition, Formula, Probability of Events

## What is Conditional Probability?

Conditional probability is the probability of an event occurring given that another event has already occurred. The concept is one of the quintessential concepts in probability theoryTotal Probability RuleThe Total Probability Rule (also known as the law of total probability) is a fundamental rule in statistics relating to conditional and marginal. Note that conditional probability does not state that there is always a causal relationship between the two events, as well as it does not indicate that both events occur simultaneously.

The concept of conditional probability is primarily related to the Bayes’ theoremBayes’ TheoremIn statistics and probability theory, the Bayes theorem (also known as the Bayes’ rule) is a mathematical formula used to determine the conditional, which is one of the most influential theories in statistics.

Formula for Conditional Probability

Where:

P(A|B) – the conditional probability; the probability of event A occurring given that event B has already occurredP(A ∩ B) – the joint probability of events A and B; the probability that both events A and B occurP(B) – the probability of event B

The formula above is applied to the calculation of the conditional probability of events that are neither independentIndependent EventsIn statistics and probability theory, independent events are two events wherein the occurrence of one event does not affect the occurrence of another event nor mutually exclusive.

Another way of calculating conditional probability is by using the Bayes’ theorem. The theorem can be used to determine the conditional probability of event A, given that event B has occurred, by knowing the conditional probability of event B, given the event A has occurred, as well as the individual probabilities of events A and B. Mathematically, the Bayes’ theorem can be denoted in the following way:

Finally, conditional probabilities can be found using a tree diagram. In the tree diagram, the probabilities in each branch are conditional.

Conditional Probability for Independent Events

Two events are independent if the probability of the outcome of one event does not influence the probability of the outcome of another event. Due to this reason, the conditional probability of two independent events A and B is:

P(A|B) = P(A)P(B|A) = P(B)Conditional Probability for Mutually Exclusive Events

In probability theory, mutually exclusive eventsMutually Exclusive EventsIn statistics and probability theory, two events are mutually exclusive if they cannot occur at the same time. The simplest example of mutually exclusive are events that cannot occur simultaneously. In other words, if one event has already occurred, another can event cannot occur. Thus, the conditional probability of mutually exclusive events is always zero.

P(A|B) = 0P(B|A) = 0Additional Resources

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PDF Conditional Probability, Independence and Bayes' Theorem – Conditional Probability, Independence and Bayes' Theorem. Class 3, 18.05 Jeremy Orloﬀ and Jonathan Bloom. 1 Learning Goals. 1. Know the deﬁnitions of conditional probability and independence of events. 2. Be able to compute conditional probability directly from the deﬁnition. 3.Step 2: Determine the probability of event B which has already occurred by applying the probability formula, i.e., P(B)= Total chances of event B happening/ All possible chances Step 3: Next, Determine the joint probability of events A and B, P(A and B), which means chances that A and B can happen together / all possible chances of event B.The formula is the definition of conditional probability. What are you asking? $\endgroup$ – lulu Sep 14 '20 at 15:12 $\begingroup$ How they came up with it and such $\endgroup$ – Sergio Sep 14 '20 at 15:15

Conditional Probability (Definition, Formula) | How to – Click here 👆 to get an answer to your question ️ According to the general equation for conditional probability, if P(AuB')=5/9 and P(B)=1/3, what is P(A|B')? … susie098 susie098 07/20/2016The value of this probability is 12/2652. The probability of event B, that we draw an ace is 4/52. Thus we use the conditional probability formula and see that the probability of drawing a king given than an ace has been drawn is (16/2652) / (4/52) = 4/51.According to the general equation for conditional probability, if P(A and B )= 3/10 . and P(B)=3/5, what is P(A l B )?

What's the use of the conditional probability formula – If A and B are two events in a sample space S, then the conditional probability of A given B is defined as P (A | B) = P (A ∩ B) P (B), when P (B) > 0. Here is the intuition behind the formula. When we know that B has occurred, every outcome that is outside B should be discarded.Conditional probability formula gives the measure of the probability of an event given that another event has occurred. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B".According to the general equation for conditional probability, if? According to the general equation for conditional probability, if P(A^B) = 4/7 and P(B) = 7/8 , what is P(A|B)? Answer Save