We strongly recommend to refer below post as a per-requisite for this.
Below is Bayes’s formula.
The formula provides relationship between P(A|B) and P(B|A). It is mainly derived form conditional probability formula discussed in the previous post.
Consider the below forrmulas for conditional probabilities P(A|B) and P(B|A)
Since P(B ∩ A) = P(A ∩ B), we can replace P(A ∩ B) in first formula with P(B|A)P(A)
After replacing, we get the given formula.
Product rule states that
So the joint probability that both X and Y will occur is equal to the product of two terms:
From the product rule :
implies P(X|Y) = P(X)/P(Y)
implies P(X|Y) = 1
When the above product rule is generalized we lead to chain rule . Let there are n events . Then , the joint probability is given by
From the product rule, and . As and are same .
Example : Box P has 2 red balls and 3 blue balls and box Q has 3 red balls and 1 blue ball. A ball is selected as follows:
(i) Select a box (ii) Choose a ball from the selected box such that each ball in the box is equally likely to be chosen. The probabilities of selecting boxes P and Q are (1/3) and (2/3), respectively.
Given that a ball selected in the above process is a red ball, the probability that it came from the box P is (GATE CS 2005)
R --> Event that red ball is selected B --> Event that blue ball is selected P --> Event that box P is selected Q --> Event that box Q is selected We need to calculate P(P|R)? P(R|P) = A red ball selected from box P = 2/5 P(P) = 1/3 P(R) = P(P)*P(R|P) + P(Q)*P(R|Q) = (1/3)*(2/5) + (2/3)*(3/4) = 2/15 + 1/2 = 19/30 Putting above values in the Bayes's Formula P(P|R) = (2/5)*(1/3) / (19/30) = 4/19
Exercise A company buys 70% of its computers from company X and 30% from company Y. Company X produces 1 faulty computer per 5 computers and company Y produces 1 faulty computer per 20 computers. A computer is found faulty what is the probability that it was bought from company X?
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above
- Mathematics | Conditional Probability
- Cauchy's Mean Value Theorem
- Mathematics | Lagrange's Mean Value Theorem
- Mathematics | Rolle's Mean Value Theorem
- Corollaries of Binomial Theorem
- Theory of Computation | Arden's Theorem
- Arden's Theorem and Challenging Applications | Set 2
- Digital Logic | Consensus theorem
- Advanced master theorem for divide and conquer recurrences
- Mathematics | Probability
- Mathematics | Law of total probability
- Mathematics | Renewal processes in probability
- Mathematics | Probability Distributions Set 4 (Binomial Distribution)
- Mathematics | Probability Distributions Set 3 (Normal Distribution)
- Mathematics | Probability Distributions Set 2 (Exponential Distribution)
Improved By : Surya Priy