Conditional Probability and Bayes' Formula Questions

In summary, conditional probability is the likelihood of an event happening given that another event has already occurred. Bayes' formula, also known as Bayes' rule or Bayes' theorem, is a mathematical formula used to calculate conditional probabilities. It is commonly used in various fields, including statistics, economics, and machine learning, to make predictions and decisions based on available data. The difference between conditional probability and joint probability is that joint probability considers the probability of two events happening simultaneously, while conditional probability considers the probability of one event happening after another has already occurred. Bayes' formula can also be extended to calculate the probability of multiple events, known as the extended version.
  • #1
sampahmel
21
0
Dear all,

Please clarify the following:

1.) The difference of conditional probability and Bayes' formula.

2.) Is Bayes' formula a "all weather condition" formula for all conditional probabilities problem?


Thank you,

S
 
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  • #2
Can anyone please answer to the above question?
 
  • #3
1) Conditional probability is [tex] \mathbb{P}(A|B):=\frac{\mathbb{P}(A \cap B)}{\mathbb{P}(B)}[/tex].

Bayes Theorem is used to swap the condition around,
[tex] \mathbb{P}(A|B):=\frac{\mathbb{P}(B|A) \mathbb{P}(A)}{\mathbb{P}(B)}[/tex]

2) You can use Bayes formula for any conditional probabilities such that [tex]\mathbb{P}(B)>0[/tex]
 

What is conditional probability?

Conditional probability is the probability of an event occurring given that another event has already occurred. It is denoted by P(A|B), where A and B are events. This means "the probability of event A happening, given that event B has happened."

What is Bayes' formula?

Bayes' formula, also known as Bayes' rule or Bayes' theorem, is a mathematical formula used to calculate conditional probabilities. It states that the probability of event A given event B is equal to the probability of event B given event A, multiplied by the probability of event A, divided by the probability of event B. In equation form, it is expressed as P(A|B) = P(B|A) * P(A) / P(B).

How is Bayes' formula used in real life?

Bayes' formula is used in various fields, including statistics, economics, and machine learning, to make predictions and decisions based on available data. It is commonly used in medical diagnosis, spam filtering, and stock market analysis.

What is the difference between conditional probability and joint probability?

Conditional probability is the probability of one event occurring given that another event has already occurred. Joint probability, on the other hand, is the probability of two events occurring together. It is denoted by P(A∩B), where A and B are events. In other words, joint probability considers the probability of two events happening simultaneously, while conditional probability considers the probability of one event happening after another has already occurred.

Can Bayes' formula be used for more than two events?

Yes, Bayes' formula can be extended to calculate the probability of multiple events. It is known as the extended version of Bayes' formula and is used when there are more than two events involved. The formula remains the same, but the equation becomes more complex as the number of events increases.

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